Around the world, there is no population clear from urinary tract infection (UTI), particularly among women. UTI is considered the most predominant bacterial infection. This study aimed to detect the incidence of the most common major uropathogens in patients severe from urinary tract infection with antibiotic sensitivity tests that assist urologist doctors for appropriate antimicrobial empirical therapy.Methods: This study was carried in a private laboratory in Babil city, Iraq from May 2019 to May 2020. Totally 70 individuals suffering from clear symptoms of UTI, as well as, 20 healthy persons participated in this study as a control group. Then, the standard microbiological methods carried out to isolate and identify bacterial species. Antimicrobial susceptibility tests were performed using different antimicrobial discs by applying the Kirby–Bauer disc diffusion method.Results: Totally, 90 specimens were obtained from them 20 control group, 19 with no growth, and 51 patients with bacterial growth distributed as 43 (83%) females and 8 (17%) males. E. coli were the most common predominant organisms. All isolates were showed a high rate of resistance to evaluated cephalosporins 100% and 82% to cefotaxime and ceftriaxone respectively, while very low resistance recorded in Aminoglycosides 20% and 13% to Gentamicin and amikacin respectively. Most age group infected with UTI was 21-40 years old.Conclusion: The current study showed an increasing burden of urinary tract infection caused by various bacteria implicated in UTI that causes changeable sensitivity to various antimicrobial agents. Therefore, in clinical use appropriate medications should be selected based on the data obtained from antimicrobial susceptibility tests.

Background: The evolution of names, from “medical informatics” to “connected health”, implies that the evolvement of technology in health care has been shifted from technology-oriented to healthcare-oriented implementation. Connected healthcare, a healthcare platform of remote monitoring and self-management through technological measures, is suggested to contribute to the efficiency, cost effectiveness, and satisfaction of healthcare recipient enhancement. However, limited understanding of related connected health (CH) terminology may constrain its implementation. Whether CH is a Buzzword only or a practice that can contribute to an ageing society is controversial. Objective: This study aims to distinguish CH-related terminology and to identify the trend of CH through reviewing its definition, initiation, development, and evolvement, in order to offer management insights and implications. The objective is to understand what is connected and who is cared about in the connected health model, so that better applications can be addressed for the benefit of society. Method: This study reviews the evolution of names, from “medical informatics” in the 1970s to “connected health” after 2000, as well as relevant literature of CH, including e-health, telemedicine, telehealth, telecare, and m-health, to discover the trend of technology-related healthcare implementation. The current status and issues facing CH will be presented and its future trends will be explored through reviewing how changes in healthcare are managed, in addition to its operation and practice. Issues of accessibility, quality, and cost will be discussed, as well as its market status. Results: Preconditions and requirements for implementing CH are identified to select a typical case to study. Areas with a complete business ecosystem, including advanced technology and medical services, a payment system, an ageing population, geographic isolation, integrated health, and social care, are prevalent. These findings may be beneficial to designing and establishing comprehensive CH implantation and environments. Conclusion: The evidence and tendency of technological convergence create a demand for innovation and partnering with start-up companies that offer a competitive advantage in innovation. Specifically, it is necessary to innovate both the public and private operation model of the CH ecosystem. This focus will be further explored in future work.

Escherichia coli is the main pathogen responsible for extraintestinal infections. A total of 196 clinical E. coli consecutively isolated during 2016 in Spain (100 from Lucus Augusti hospital in Lugo) and France (96 from Beaujon hospital in Clichy) were characterized. Phylogroups, clonotypes, sequence types (STs), O:H serotypes, virulence factor (VF)-encoding genes and antibiotic resistance were determined. Approximately 10% of the infections were caused by ST131 isolates in both hospitals and approximately 60% of these infections were caused by isolates belonging to only 10 STs (ST10, ST12, ST58, ST69, ST73, ST88, ST95, ST127, ST131, ST141). ST88 isolates were frequent especially in Spain while ST141 isolates significantly predominated in France. The 23 ST131 isolates displayed four clonotypes: CH40-30, CH40-41, CH40-22 and CH40-298. Only 13 (6.6%) isolates were carriers of ESBL enzymes. However, 37.2% of the isolates were multidrug-resistant (MDR). Approximately 40% of the MDR isolates belonged to only four of the dominant clones (B2-CH40-30-ST131, B2-CH40-41-ST131, C-CH4-39-ST88 and D-CH35-27-ST69). Among the remaining MDR isolates two isolates belonged to B2-CH14-64-ST1193 i.e the new global emergent MDR clone. To our knowledge, it is the first identification of this emergent clone in Spain. Moreover, a hybrid ExPEC/enteroaggregative isolate belonging to A-CH11-54-ST10 clone was identified.

Whistler mode waves play a major role in regulating the lifetime of trapped electrons in the Earth's radiation belts. Specifically, whistler mode hiss waves are one of the mechanisms that maintains the slot region between the inner and outer radiation belts. The generation mechanism of hiss is a topic still under debate with at least three prominent theories present in the literature. Lightning generated whistlers in their ducted or non-ducted modes, are considered to be one of the possible sources of hiss. We present a study of new observations from the Radio Receiver Instrument (RRI) on the Enhanced Polar Outflow Probe (ePOP: currently known as SWARM-E). RRI consists of two orthogonal dipole antennas, which enables polarization measurements, when the satellite boresight is parallel to the geomagnetic field. Here we present 75 passes of ePOP - RRI from 2014 - 2018, in which lightning whistlers and hiss waves were observed. In more than 50% of those passes hiss is found to co-exist with the lightning whistlers. Moreover, the whistler observations are correlated with observations of wave power at the lower-hybrid resonance. The observations and a whistler mode ray-tracing study suggest that multiple-hop lightning induced whistlers can be a source of hiss and plasma instabilities in the magnetosphere.

Although the complexity of physically based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e. HBV. This has been rarely done for conceptual models as satellite data are often used in spatial calibration of the distributed models. Three different soil moisture products from ESA CCI SM v04.4, AMSR-E and SMAP, and total water storage anomalies from GRACE are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture are used to analyse the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis and then, these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal substantial contribution of remote sensing products to the lumped model calibration even if their spatially distributed information is lost during the spatial aggregation. Inclusion of new observations such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model’s physical behaviour while it keeps a reasonable water balance that is the key objective of every hydrologic model.

The protection of electronics against environmental influences and mechanical loads is important for integration of conventional electronics in textile conductive tapes. For this purpose, the sensors on the tapes are molded with plastic locally. This process step is recognized in the injection molding process. The molding compound is then later selected depending on: The field of application, the parameters of the manufacturing process and the textile tape properties. We have designed a mould for liquid silicone (LSR) as well as for the textile and electronic insertions. The cavities are sealed by a local compression of the textile and the two inserts are positioned with position pins representing the main aspect of the mould design. The sampling tool and the process parameter optimization are mainly based on the material properties of the silicone and the mechanical sensitivity of the inserts. To reduce the deformation of the circuit boards by the melt front and ensuring the functionality of the electronics a low-pressure process is used.

The Rybczynski theorem describes the trade effect within production analyses between factor endowments and outputs. The Stolper-Samuelson theorem focuses on cost analyses between factor reward and commodity price. This paper examines the trade effect of changes of factor endowments on prices, based on general equilibrium. The study shows that changes of factor endowments cause domestic output changes (the Rybczynski effect), which affect output prices and factor prices (the Stolper-Samuelson effect). It is like a chain of effects that the Rybczynski’s trade effect triggers the Stolper-Samuelson’s trade effect. The analysis of this paper shows that a small increase of a factor endowment of any country rewards another factor and the commodity using the latter factor intensively. It displays a tuneful circle. Trade brings a well-balanced development to the world.

Functional ZnO nanostructured surfaces are important in a wide range of applications. Here we report facile fabrication of ZnO surface structures at near room temperature with morphology resembling that of sea urchins, with densely packed, μm-long, tapered nanoneedles radiating from the urchin centre. The ZnO urchin structures were successfully formed on several different substrates with high surface density and coverage, including silicon (Si), glass, polydimethylsiloxane (PDMS), and copper (Cu) sheets, as well as Si seeded with ZnO nanocrystals. Time-resolved SEM revealed growth kinetics of the ZnO nanostructures on Si, capturing the emergence of “infant” urchins at the early growth stage and subsequent progressive increase in the urchin nanoneedle length and density, whilst the spiky nanoneedle morphology was retained throughout the growth. ε-Zn(OH)₂ orthorhombic crystals were also observed alongside the urchins. The crystal structures of the nanostructures at different growth time were confirmed by synchrotron X-ray diffraction measurements. On seeded Si substrates, a two-stage growth mechanism was identified, with a primary growth step of vertically aligned ZnO nanoneedle arrays preceding the secondary growth of the urchins atop the nanoneedle array. The antibacterial, anti-reflective, and wetting functionality of the ZnO urchins—with spiky nanoneedles and at high surface density—on Si substrates was demonstrated. First, bacteria colonisation was found to be suppressed on the surface after 24 h incubation in Gram-negative E. coli culture, in contrast to control substrates (bare Si and Si sputtered with 20 nm ZnO thin film). Secondly, the ZnO urchin surface, exhibiting superhydrophilic property with a water contact angle ~0°, could be rendered superhydrophobic with a simple silanization step, characterised by a water static contact angle θ of 159° ± 1.4° and contact angle hysteresis ∆θ < 7°. The dynamic superhydrophobicity of the surface was demonstrated by bouncing-off of a falling 10 μL water droplet, with a contact time of 15.3 milliseconds (ms), captured using a high-speed camera. Thirdly, it was shown that the presence of dense spiky ZnO nanoneedles and urchins on the seeded Si substrate exhibited a reflectance R < 1% over the wavelength range λ = 200–800 nm. The ZnO urchins with unique morphology via a facile fabrication route at room temperature, readily implementable on different substrates, may be further exploited for multifunctional surfaces and product formulations.

Abstract Introduction: Antimicrobial resistance (AMR) is a recognised public health threat today globally. Though many active and passive stewardship strategies are employed to counter AMR clinically, educating school going children on AMR could be a futuristic cost-effective measure to minimize AMR development. We hypothesised NICE’s e-bug module to class VII school students on AMR determinants. Methodology: A prospective non-randomized intervention study on 327 students belonging to 9 schools of class VII around Manipal town, Udupi district, Karnataka state, India were included for the study. 10 questions on AMR determinants extracted from NICE’s e-bug program were quizzed in written as pre-test followed by an education intervention on the same questions followed by a post-test to end the session. Descriptive statistics to estimate epidemiological characteristics, Wilcoxon Signed Ranks and Kruskal-Wallis tests were applied to analyse statistical significance of pre/post-test performance scores for the 10 questions and between schools respectively Results: Students had inadequate knowledge on 7 AMR determinants (antimicrobial indication, its course, hand hygiene, fermentation, spread of infection, microbial multiplication and characteristics of microbe) when analysed for post-test performance (p<0.05). Comparison of post-test performance of 9 participating schools revealed statistical significance (p<0.05) for 3 questions (definition on antimicrobial, cover while cough/sneezing and microbial characteristics) Conclusion: Although students exhibited sub-optimal knowledge on few AMR determinants, they showed keenness to learn exhibited by their performance. Our findings and previous similar studies from Europe are suggestive of early pedagogic interventions on AMR through inclusion of such education modules in the curriculum could be potential tool for AMR prevention for future generations.

Electronic Nose (eNose) systems are particularly appreciated for their portability, usability, relative low cost and real-time or near real-time response. Their application finds space in several domains, including environmental monitoring. Within this field, marine monitoring is of particular scientific relevance due to the fragility of this specific environment, daily threatened by human activities that can potentially bring to catastrophic and irreversible consequences on marine wildlife. Under such considerations, a systematic review, complying with the PRISMA guidelines, was conducted covering the period up to October 15, 2018, in PubMed, ScienceDirect and Google Scholar. Despite the relatively low number of articles published on this specific topic and the heterogeneity of the technological approaches employed, the results obtained by the various groups highlight the positive contribution eNose has given and can provide in near future for the monitoring and safeguarding of this delicate environment.

Although there are extensive literature reports on the use of gold nanoparticle (AuNP) based homogeneous assays for detection of biomolecules, very few experimental description and procedures involving their preparation are described. In this study, AuNPs conjugated to Bovine Serum Albumin or Envelope protein from Dengue II were developed as a homogeneous immunoassay for antibody detection. We report here optimization of key parameters to prepare an immunoassay like conjugation protein concentration, centrifugation time, electrolyte addition and assay temperature. We determined that saturating protein concentrations improved AuNPs surface coverage and uniformity of the assay and addition of sodium chloride improved sensitivity of the antibody detection method and assay stability. Furthermore, we showed that dynamic light scattering can be used to monitor changes in gold nanoparticles in the preparation and detection steps. Additionally, numerical simulations of the plasmonic optical response of AuNPs were carried out to scan for size-dependent response of the AuNPs. The AuNPs homogeneous immunoassay developed was further used in the detection of antibodies in vitro to detect Dengue virus infection.

Accurate estimates of daily rainfall are essential for understanding and modeling the physical processes involved in the interaction between the land surface and the atmosphere. In this study, daily satellite soil moisture observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) generated by implementing the standard NASA- algorithm are employed for estimating rainfall, firstly, through the use of recently developed approach, SM2RAIN (Brocca et al., 2013) and, secondly, the nonlinear autoregressive network with exogenous inputs (NARX) neural modelling at five climate stations in the Karkheh river basin (KRB), located in southwest Iran. In the SM2RAIN method, the period 1 January 2003 to 31 December 2005 is used for the calibration of algorithm and the remaining 9 months from 1 January 2006 to 30 September 2006 is used for the validation of the rainfall estimates. In the NARX model, the full study period is split into a training (1 January 2003 to 31 September 2005) and a testing (1 September 2005 to 30 September 2006) stage. For the prediction of the rainfall as the desired target (output), relative soil moisture changes from AMSR-E and measured air temperature time series are chosen as exogenous (external) inputs in NARX. The quality of the estimated rainfall data is evaluated by comparing it with observed rainfall data at the five rain gauges in terms of the correlation coefficient R, the RMSE and the statistical bias. For the SM2RAIN method, R ranges between 0.44 and 0.9 for all stations, whereas for the NARX- model the values are generally slightly lower. Moreover, the values of the bias for each station indicate that although SM2RAIN is likely to underestimate large rainfall intensities, due to the known effect of soil moisture saturation, its biases are somewhat lower than those of NARX. In conclusion, the results of the present study show that with the use of AMSR-E soil moisture products in the physically based SM2RAIN- algorithm as well as in the NARX neural network, rainfall for poorly gauged regions can be fairly predicted.

Apoptosis and cell cycle arrest induction are targeted in the strategy of cancer therapy. Furthermore, bacterial toxin such as shiga-like toxin producing Escherichia coli has been suggested to be used as novel therapeutic agent against tumor malignancies either as independent anti-neoplastic agents or in combination treatment with chemo or radiotherapy. The aim of study was to investigate the potency of shiga-like toxin originated from local strains of E. coli O157:H7 as a new cancer therapy. As many as 10 culture cells T47D cell line were subjected by crude extract Shiga like toxin originated from five local isolates of E. coli O157:H7 i.e. KL-48(2), SM-25(1), SM-7(1), DS-21(4), and one isolate ATCC 43894 as a control with IC50 doses, respectively. The treatment was observed for 24 h, with two replications. An FITC-Annexin V and PI assay was used to observe apoptosis and necrosis effect, and simultaneously with cell cycle analysis using propidium iodide (PI) staining. Results of study showed T47D cell treated with Shiga-like toxin from local strain KL-48 (2) show the lowest viable cell, followed by SM 7(1), ATCC 43894, SM-25(1), DS-21(4) and contrary with control with each percentages as 15.20, 16.36, 22.17, 22.64, 33.86, and 94.36%, respectively. The results were also confirmed by the induction of the cell cycle arrest in phase G0-G1 as inactive phase, i.e. 66.41, 63.37, 61.52, 55.36 and 47.28% for T47D cell treated with toxin of KL-48(2), ATCC 43894, SM 25(1), SM 7(1), and DS 21(4), respectively. These results show tendency deleterious effect of Shiga-like toxin from local isolates on T47D cell, so that concluded they have potency as a good anticancer drug in Gb3-expressing breast cancer.

Electronic-health applications rely on large computer networks to facilitate patients' information access and to communicate various types of medical data. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due to quantity of the information carrying packets, examining each packet's transmission parameters individually is not practical, especially when a real time operation is needed. Sampling allows a subset of packets that accurately represents the original traffic to be formed. In this study an adaptive sampling method based on regression and fuzzy inference system was developed. It dynamically updates the number of packets sampled by responding to the traffic variations. Its performance was found to be superior to the conventional non-adaptive sampling methods.

Tick-borne encephalitis virus is a pathogen endemic to northern Europe and Asia, transmitted through bites from infected ticks. It is a member of the Flaviviridae family, possesses a positive-sense, single-stranded RNA genome encoding a polypeptide that is processed into seven non-structural and three structural proteins, including the envelope (E) protein. The glycosylation of the E protein, a single N-linked glycan at position N154, plays a critical role in viral infectivity and pathogenesis. Here, we dissected the entire glycosylation profile of the E protein using liquid chromatography tandem mass spectrometry and identified three novel O-linked glycans which were found at relatively low frequency. One of the O-linked glycans was positioned close to the highly conserved N-linked glycan site and structural analysis indicated that it may be of relevance for viral maturation. The N154 site was found to be glycosylated with a high frequency, containing oligomannose or complex-type structures, some of which are fucosylated. An unusually high portion of oligomannose N-linked glycan structures exhibited compositions that are normally observed on proteins while they are translocated from the endoplasmic reticulum to the trans golgi network, suggesting disruption of the glycan processing pathway in the infected cells from which the E protein was obtained.

Bacterial vectors for biomolecule delivery to targeted organelles, facilitating temporary or continuous protein production, have emerged as a promising approach for treating acquired and inherited diseases. This method offers a selective cancer eradication and targeting strategy with minimal side effects. Bacterial vectors provide an alternative to viral gene delivery, given their capacity to deliver large genetic materials while inducing minimal immunogenicity and cytotoxicity. Bacteria such as Bifidobacterium, Salmonella, and Clostridium have demonstrated potential for tumor-targeted biomolecule delivery. These vectors have also been used to transfer and amplify genes encoding biomolecules such as prodrug-converting enzymes, toxins, angiogenesis inhibitors, and cytokines. The microenvironment of necrotic tumors offers a unique opportunity for targeted therapy with the non-pathogenic anaerobic bacterium. For example, Clostridium sporogenes can germinate selectively in the necrotic regions upon injection as endospores, which helps to enhance the specificity of Clostridium sporogenes, resulting in tumor-specific colonization. Further, some invasive bacteria vectors engineered with the invasin gene from Yersinia Pseudotuberculosis, which enables specific binding to integrin receptors abundantly expressed in cancer cells and escape the endosome with incorporation of the Listeriolysin O gene from Listeria monocytogenes, have shown potential for application in cancer therapy. This review provides an overview of the use of the bacteria vector in cancer therapy, highlighting strategies to maximize delivery efficiency and address potential challenges.

Cell membrane-derived liposomes, termed Memposomes, serve as promising carriers for drug delivery due to their ability to closely mimic cells and efficiently target specific cells. Liposomes derived from cancer cell membranes, in particular, exhibit homologous targeting capabilities, making them potential candidates for cancer-specific drug delivery. However, the underlying mechanisms and specific proteins responsible for this homologous targeting phenomenon remain debated. This study focuses on the role of E-cadherin, a cell adhesion molecule implicated in homophilic adhesion, in influencing the homologous targeting ability of Memposomes derived from cancer cell membranes. E-cadherin expression patterns were assessed in various cell lines, categorizing them into E-cadherin-positive and -negative groups. Memposomes were produced for each group, and their targeting tendencies were evaluated. The study confirmed that E-cadherin expression significantly influenced the homologous targeting ability of Memposomes. Cell lines with higher E-cadherin expression levels exhibited a more pronounced homologous targeting effect. This research demonstrates that cell adhesion molecules, particularly E-cadherin involved in homophilic adhesion, play a pivotal role in influencing the cell targeting ability of Memposomes. The study further validates the stability, safety, and purity of Memposomes, emphasizing their potential as effective drug delivery vehicles for the development of cell-specific therapies.

This qualitative study explores the pivotal roles of trust and communication in supplier relationship management (SRM) within the e-commerce sector. Drawing on interviews and thematic analysis, the study examines how trust, comprising dimensions of competence, benevolence, integrity, and reliability, underpins collaborative partnerships and operational resilience between e-commerce platforms and suppliers. Effective communication strategies, including proactive engagement, transparent feedback mechanisms, and real-time updates via digital platforms, are identified as critical enablers for enhancing information exchange and fostering mutual understanding in SRM. Challenges such as cultural differences, technological complexities, and regulatory compliance requirements are also discussed, highlighting the need for strategic management and investment to mitigate risks and maintain trust in supplier engagements. Relational competencies such as empathy, active listening, conflict resolution, and trust-building skills are recognized as essential for navigating interpersonal dynamics and fostering collaborative relationships in e-commerce SRM. Strategically, integrating these findings into comprehensive SRM frameworks is emphasized to cultivate a positive organizational culture characterized by openness, ethical integrity, collaboration, and adaptability. This approach aims to enhance supplier relationships, drive innovation, and achieve sustainable growth in a competitive marketplace.

Supplier diversity has emerged as a critical strategy for enhancing e-commerce operations by fostering inclusivity and innovation within supply chains. This qualitative research explores the role of supplier diversity in e-commerce, examining its impact on organizational strategies, competitive advantage, and stakeholder perceptions. Through semi-structured interviews with procurement managers, diversity officers, and supply chain executives from diverse e-commerce platforms, this study identifies key themes related to the benefits, challenges, and strategic implications of supplier diversity initiatives. Findings indicate that supplier diversity significantly enhances innovation and creativity within supply chains by integrating diverse perspectives and expertise. This diversity not only enriches product development and market responsiveness but also strengthens corporate reputation and brand equity, demonstrating organizational commitment to ethical business practices and community engagement. However, the study reveals persistent challenges, including financial barriers, systemic biases, and scalability issues, which hinder the effective implementation and scalability of supplier diversity programs. Effective supplier relationship management emerges as critical for maximizing the benefits of supplier diversity, fostering trust, collaboration, and long-term partnerships with diverse suppliers. Looking forward, the future of supplier diversity lies in digital transformation, globalization of supplier networks, and integration of sustainable sourcing practices to enhance transparency, efficiency, and resilience in supply chain operations. This study contributes to the growing literature on supplier diversity by providing empirical insights and practical implications for organizations aiming to leverage diversity as a strategic asset in e-commerce and global supply chain management.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

The graphene based highly conductive and flexible devices has received momentous attraction and growth in recent years for potential multifunctional uses. The development of flexible and washable textile sensors, actuators, energy storage and energy harvesting systems. Textile fabrics coated with graphene and conductive polymers have been used for wearable self-powered e-textiles, such as tribo-electric, piezoelectric, and Thermoelectric. Herein this research, 100% woven cotton fabric is Fictionalized with graphene oxide (GO) using industrial-scale cold pad batch dyeing technique for the development of low-grade body heat into self-powered wearable e-textiles. The conductive polymer PEDOT: PSS was coated using layer by layer approach. The study demonstrates that the resultant textile electrodes showed reduced electrical sheet resistance from 2.5 MΩ to 15KΩ, with a reduced graphene oxide and further reduced to (2.5 -12.5 Ω) for conductive polymer. The sheet resistance was decreased with the number of dyeing cycles (10-15) and increased with 20 washing cycles vice versa. The study demonstrates that the sensor response and performance were improved with increasing the content percent of rGO and PEDOT: PSS. The tensile strength of as coated fabric electrodes was improved from (25.0-85.5 mPa) and fabric thickness was increased to (26-38µm) without compromising or influencing the air permeability. The resultant textile electrodes may potentially be used in smart textiles for self-powered flexible wearable generators, sensors, and energy storage. The study demonstrates that the cold pad batch dyeing method is a suitable and effective method for the fabrication of graphene-based textiles.

Interoperable multilayer networks are pivotal and transformative in public digital health. They not only enhance the delivery of healthcare services but also contribute significantly to improving public health outcomes. Through better accessibility, efficiency, and data-driven decision-making, these networks are revolutionizing how we approach public health. The seamless data exchange and integration they facilitate across different healthcare systems and providers can lead to substantial cost savings for public healthcare systems. These networks pave the way for a more efficient and effective healthcare system by reducing redundancies, optimizing resource allocation, and minimizing unnecessary procedures. This study combines the pressing issues of public digital health with the innovative interpretation of multilayer network theory, proposing practical solutions that inspire academics and practitioners alike.Public digital health is not just about improving care access and patient engagement. It is also about ensuring the financial sustainability of our healthcare systems. Innovative multilayer network analysis is critical in this game, improving interoperability and reducing spatial and temporal constraints. These networks streamline processes and improve efficiency by easing complex interactions within healthcare systems. This process, in turn, allows healthcare providers to deliver high-quality care at a lower cost, transforming, whenever possible, in-patients and out-patients into home-patients. Networks are a cornerstone and a beacon of hope for transforming public digital health. They are increasing the Value for Money and enhancing a patient-centric approach, making us optimistic about the future of healthcare.This study shows that revolutionizing digital healthcare methodologies has a profound impact on crucial elements like resilience, interoperability, and patient well-being within public health. The enhancement of interoperability facilitates the smooth flow of data exchange across various platforms and healthcare providers, fostering improved collaboration and decision-making processes and elevating the safety of patients.

Background: A Morel–Lavallée lesion (MLL) is a traumatic, internal closed degloving injury that results from shearing of subcutaneous tissue away from underlying fascia, usually associated with high-velocity trauma. Case presentation: A 52-year-old man was transported to hospital for further follow-up of a superficial femoral artery injury. Examination on admission showed bruising seen around the left thigh. Contrast-enhanced computed tomography of the left thigh revealed hematoma with extravasation from a branch of the left superficial femoral artery, but no apparent aneurysms or femoral fractures. The patient was treated with compression bandages and discharged on hospital day 6. He left hospital able to walk unaided. He subsequently complained of left thigh pain with swelling and visited the hospital several times. He was treated at another outpatient clinic and was diagnosed with MLL. Single-use disposable portable negative pressure wound therapy (NPWT) was applied for about 2 months, achieving a stable wound site. Conclusion: We encountered a case of MLL successfully treated with single-use portable NPWT. This report presents the case of a patient with isolated MLL without fracture in the left thigh, in which the diagnosis was missed on initial admission. Finally, the patient received minor interventions including drainage along with tissue debridement and portable NPWT. We reviewed the relevant literature and summarize the pathogenesis, clinical manifestations, and treatment strategies for MLL. Emergency physicians require an increased understanding of MLL to avoid misdiagnosis and missed diagnosis.

Current VAT rules for cross-border e-commerce companies in the EU are not sustainable, because they are extremely complex and often opaque, due to the lack of tax harmonization. The aim of the research is to explore, using a qualitative method, what kind of harmonization would make the current legislation more uniform, simpler, more transparent, and easier to understand, without conflicting with the rules of any Member State. To this end, the aspects of the new platform regulation introduced on 1 July 2021 and its potential for expansion are assessed through information from possible sales models. The research suggests that the rules on platforms do not cover all possible sales models, which in our view imposes an unnecessary extra administrative burden on some businesses and makes their tax activities less transparent. In the light of the results of the research, we propose that the current EU platform regulation should be extended to cover B2B, B2C transactions and services. As a result of this suggested harmonization, a simpler, more transparent, uniform and sustainable tax system would contribute to the whitening of the economy, generating additional tax revenue for Member States.

Background and Objectives: In recent years Electronic scooters (E-Scooters) have gained popularity, whether for private use or as a publicly available transportation method. With introduction of these vehicles, reports of E-Scooter related accidents have surged, sparking a public debate and concern. Aim of this study was to analyse epidemiological data, characteristics and severity of traumatic brain injury (TBI) related to E-Scooter accidents. Materials and Methods: This retrospective case series evaluated 28 patients who were admitted to three largest neurosurgery clinics in Riga, Latvia between time period from April to October in two separate years – 2022 and 2023 after an E-Scooter related accident. Data were collected on patient demographics, time of the accident, alcohol consumption, helmet use, type of TBI, other related injuries, treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to E-Scooter use, with median age 30 years (Q1-Q3, 20.25-37.25), four individuals under age of 18, majority (64%) were male. In 23 cases the injury mechanism was fall, in 5 cases collision. None were wearing a helmet at time of injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (&gt;1.2ppm) in 75% cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma - 50% brain contusions, 43% traumatic subdural hematoma, almost 30% - epidural hematoma. Craniofacial fractures were evident in 71% of cases, fractures in other parts of body in 3 patients. 6 patients required emergency neurosurgical intervention. Neurological complications were noted in 2 patients, 1 patient died. Conclusions: E-Scooter related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and lack of helmet use. Prevention campaigns to raise awareness of potential risks and implementation of more strict regulations should be done.

We show that Universe inflation occurs when Einstein's gravity couples to nonlinear electromagnetic fields with cosmic stochastic magnetic fields background. Nonlinear electrodynamics with two parameters is used. The strength of magnetic fields to have the Universe inflation is obtained. It is shown that singularities of the energy density and pressure are absent for any scale factors. At large scale factors one arrives at equation of state for ultra-relativistic case. It is demonstrated that the curvature invariants do not have singularities. By computing the deceleration parameter we show that graceful exit takes place with reasonable e-folding number. The duration of Universe inflation as a function of model parameters is obtained. The classical stability and causality are analyzed by calculating the speed of the sound.

In recent years, e-commerce platforms have replaced conventional marketplaces. People are rapidly adopting internet shopping due to the convenience of making purchases from the comfort of their homes. Online review sites allow customers to share their thoughts on products and services. Customers and businesses are increasingly relying on online reviews to assess and improve the quality of products. Existing literature uses Natural language processing (NLP) to analyze customer reviews for different applications. Due to the growing importance of NLP for online customer reviews, this study attempts to provide a taxonomy of NLP applications based on existing literature. This study also examined emerging methods, data sources, and research challenges by reviewing 154 publications from 2013 to 2023 that explore state-of-the-art approaches for diverse applications. Based on existing research, the taxonomy of applications divides literature into five categories: sentiment analysis, review analysis, customer feedback and satisfaction, user profiling, and marketing and reputation management. It is interesting to note that the majority of existing research relies on Amazon user reviews. Additionally, recent research has encouraged the use of advanced techniques like Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM), and ensemble classifiers. The rising number of articles published each year indicates increasing interest of researchers and continued growth. This survey additionally addresses open issues, providing future directions in online customer review analysis.

Energy management systems (EMS) play a central role in improving the performance of microgrids by ensuring their efficient operation while minimizing operational costs and environmental impacts. This paper presents a comprehensive study of a MILP-based EMS developed and implemented in MATLAB using Yalmip software for the energy management of a new positive energy district in the city of Savona, Italy, as part of the Interreg Alpine Space Project ALPGRIDS. The main objective of this research is to optimize the functioning of the microgrid, focusing on cost efficiency and environmental sustainability. In pursuit of this objective, the EMS undergoes comprehensive testing and analysis, replicating actual conditions and addressing the diverse demands of end-users across typical days throughout the year considering real electricity selling and purchase price. The EMS also accounts for the reactive power capabilities of the various technologies integrated into the microgrid. The levelized cost of electricity (LCOE) serves as a metric for assessing curtailment costs, while penalties related to reactive power absorption from the distribution network are appraised in alignment with prevailing regulatory guidelines. The case study provides valuable insights into the practical implementation of EMS technology in microgrids and demonstrates its potential for sustainable energy management in complex urban energy districts. The insights and strategies developed through this research contribute to the overall goals of improving energy efficiency and reducing the environmental footprint of future energy districts.

In an era driven by technology and connectivity, where the sphere of learning goes beyond conventional classrooms, e-Service-Learning (e-SL) merges the possibilities of technology with the principles of experiential education in a powerful blend [1]. Service-learning (SL) is an educational proposal that has been cited by UNESCO [2] as an innovative educational tool through which to address the complex challenges of our society. The Sustainable Development Goals [3] provide a framework around which to structure the SL projects and thus develop the skills needed to act on the full range of goals. Embedding digital means open a debate on the intricate relationship between technology, education, and societal impact [4]. By analyzing two focus groups involving faculty, students and community partners, this contribution aims to explore the potential of combining SL and digital empowerment (DE). The focus group participants discussed the opportunities for innovation, the expected impact on them and the society at large, their needs and the pre-conditions needed to make SL and DE successful, and limitations. The results are presented according to the six principles of sustainability education in the university environment, highlighting the transformative potential of combining these principles within SL and DE.

The rapid advancement of technology has led to increased electronic consumption and a corresponding rise in e-waste generation. To address this issue, this study develops a low-carbon e-commerce closed-loop supply chain (LCE-CLSC) system with remanufacturer, platform, and the government as key stakeholders. An evolutionary game approach is employed to investigate the system's dynamics, analyzing the impact of stakeholder strategies on system equilibrium. Numerical simulations reveal important findings: Firstly, government initiatives promoting recycling, carbon taxes on traditional products, can incentivize remanufacturers to produce low-carbon items and encourage platform investment in recycling services. Secondly, higher sales revenues motivate remanufacturers to produce low-carbon products. Thirdly, consumer sensitivity to recycling services strengthens waste recovery when platforms increase investments in these services, leading to remanufacturers choosing low-carbon production. Lastly, government subsidies may become ineffective if the cost of remanufacturers' carbon reduction and platforms' recycling services exceeds their affordability. These findings offer insights for the sustainable development of obsolete electronic product recycling systems.

Sporadic Alzheimer’s disease (AD) derives from an interplay among environmental factors and genetic variants, while epigenetic modifications have been expected to affect the onset and progression of its complex etiopathology. Heterozygous carriers of the apolipoprotein E gene (APOE)4 allele have a 4-fold increased risk of developing AD, while APOE 4/4-carriers have a 12-fold increased risk in comparison with the APOE 3-carriers. The main longevity factor is the homozygous APOE ε3/ε3 genotype. In the present narrative review article, we summarized and described the role of APOE epigenetics in aging and AD pathophysiology. It is not fully understood how APOE variants may increase or decrease AD risk, but this gene is known to affect amyloid- and tau-mediated neurodegeneration directly or indirectly, also by affecting lipid metabolism and inflammation. For sporadic AD, epigenetic regulatory mechanisms may control and influence APOE expression in response to external insults. Diet, a major environmental factor, has been significant associated with physical exercise, cognitive function, and the methylation level of several cytosine-phosphate-guanine (CpG) dinucleotides sites of APOE.

Urinary tract infections (UTIs) caused by pathogens, particularly E. coli, have spontaneously become resistant to antimicrobial drugs in recent years. Therefore, regular monitoring and alternative strategies for the antimicrobial agent are crucial for combating antimicrobial resistance and bacterial biofilms. Here, we report a new cobalt iron oxide-conjugated tin oxide nanocomposite that can kill bacteria and treat multidrug-resistant E. coli posing UTIs. Following the isolation and identification of E. coli, we tested 57/134 samples against sixteen commonly used antibiotics phenotypically using the disk diffusion method to determine their sensitivity pattern. Of the 57 E. coli isolates, 66% (38/57) were multidrug-resistant. The E. coli isolates were resistant to cephradine (70.17%), ceftriaxone (59.64%), and azithromycin (59.64%), followed by cefixime (54.38%), cefuroxime sodium (52.63%), and co-trimoxazole (50.87%). X-ray diffraction results showed the crystallite sizes were about 5.68 and 8.84 nm in pure SnO2 nanoparticles and 95% SnO2-5% CoFe2O4 nanocomposite, respectively. Energy-dispersive X-ray spectroscopy and Fourier transform infrared determined the fundamental structure of the nanocomposite, encompassing Co, Fe, Sn, and O. Moreover, FTIR measurements implied that the distinct functional groups in both SnO2 and CoFe2O4 nanoparticles existed in a 95% SnO2-5% CoFe2O4 nanocomposite. Field emission scanning electron microscope analysis uncovered that the SnO2-CoFe2O4 nanocomposite had a size of roughly 24 nm and was spherical. In addition, the biosynthesized SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite were evaluated for their antibacterial activity. At a minimum 100 µg/mL concentration, SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite showed high antibacterial activity. The SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite demonstrated antibacterial activity on multidrug-resistant E. coli at 10 ± 0.7 and 16 ± 0.8 mm zone of inhibition, respectively. In conclusion, the new SnO2-CoFe2O4 nanocomposite might be a potential candidate for treating UTIs caused by drug-resistant E. coli in the foreseeable future.

A new power receiving unit (PRU) is proposed in this paper for the resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes and the capacitors, which needs no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. At a switching frequency of the resonant WPT in the experiment being 4MHz, the proposed PRU behaves itself as a negative impedance converter (NIC) in the subharmonics of 4MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrates a battery charging of 150W from 50cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to load (PDL) goes higher. The best power transfer efficiency (PTE) is 65% in the present findings. The simulation analysis shows that the circuit allows itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results.

Many studies have been conducted using pectin for modified drug delivery. In this regard, the goal of the work was to obtain interpolyelectrolyte complexes based on citrus or apple pectin and the Eudragit® EPO and study properties from the standpoint of using these carriers for oral drug delivery. Turbidity, gravimetry, viscosity, elementary analysis and FTIR spectroscopy, DSC analysis were used for physicochemical characterization. Diffusion-transport characteristics were studied to assess the swelling ability of the matrices and the release of diclofenac sodium. Mathematical modeling of the release parameters was carried out using the Krosmayer-Peppas equation. During the turbidity study, stoichiometry compositions were selected for the studied IPECs EPO/PeсA and EPO/PeсC at pH values = 4.0, 5.0, 6.0, 7.0. FTIR spectra of the complexes are characterized by an increase in the intensity of the bands at 1610 cm-1 and 1400 cm-1. According to the DSC analysis IPEC has a certain Tg = 57.3°C. The highest release rates are shown by IPEC EPO/PecC_1 and EPO/PecC_4. The mechanism of drug transport from the matrices IPEC EPO/PecC, IPEC EPO/PecA_3 and EPO/PecA_4 can be characterized as Super Case II. Anomalous (non-Fickian release) is typical for IPEC EPO/PecA_1 and EPO/PecA_2. Thus, the resulting systems are suitable for colon-specific drug delivery systems.

A 4×2 factorial experiment was conducted to evaluate the potential of feeding dietary gamma-oryzanol and vitamin E tocotrienols in hens reared in 840 (low cage density; LCD) or 420 cm2/hen (high cage density; HCD). A total of 120 hens were allocated into eight groups with five replicates. Diets were a control (CON) or the control diet supplemented with 200 ppm gamma-oryzanol (GO-200), 200 ppm vitamin E tocotrienols (VE-200) or 200 ppm gamma-oryzanol + 200 ppm vitamin E tocotrienols (GE-400). Results showed that HCD-housed hens decreased (P &lt; 0.01) egg performance and quality. Average egg weight (AEW), egg mass and FCR improved in all supplemented treatments. Results on the AEW, FCR, and eggshell qualities of birds kept at the HCD revealed the best responses in the GE-400 group (P &lt; 0.01). Among hens kept on an HCD, there was a noticeable decrease in HMGCR mRNA abundance in the VE-200 group, while the highest IFN-γ mRNA abundance was found in hens fed the GO-200 diet (P &lt; 0.05). Thus, this study suggested that dietary GO or VE at 200 ppm either individually or in combination could improve performance and egg quality as well as regulate the abundance of immune- and stress-related genes.

Taiwan’s Chi Mei Medical Center has a vision of becoming a sustainable organization. They found they violated the sustainable development goal (SDG) 13 (“Climate Action”) since its workflows consume excessive tangible resources and waste much operation time. To fulfill the vision, the Chi Mei Medical Center first introduced electronic invoicing. Implementing this electronic invoicing included adopting cloud E-invoice data and creating a software robot for auditing them. This study presents this software robot and its contributions. The software robot replaces an internal auditor to log into Taiwan’s E-invoice platform, download cloud E-invoice data, and detect the inconsistency between these cloud and on-premise data. Internal auditors of the Chi Mei Medical Center only needed to confirm the detection results. They welcome this software robot since it significantly reduces their work burdens. They approved more software robots for assisting other workflows. Besides, the Chi Mei Medical Center earned profits after eliminating paper invoices. This elimination helped release less carbon. This study concludes that chasing a sustainable organization is unnecessarily equivalent to the requirement of more costs. A software robot represents the last puzzle for constructing a paperless workflow since it can resolve the resistance of existing workers to a new workflow.

E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems’ accuracy can be improved if complex sequential patterns of user purchase behavior are learned by integrating sequential patterns of customer clicks and/or purchases into the user-item rating matrix input of collaborative filtering. This reviews focuses on algorithmic techniques of existing E-commerce recommendation systems that are sequential pattern based such as ChoRec05, ChenRec09, HuangRec09, LiuRec09, ChoiRec12, Hybrid Model RecSys16, Product RecSys16, SainiRec17, HPCRec18 and HSPCRec19. It provides a comprehensive and comparative performance analysis of these systems, exposing their methodologies, achievements, limitations, and potentials for solving more important problems in this domain. The review showed that integrating sequential pattern mining of historical purchase and/or click sequences into user-item matrix for collaborative filtering (i) improved recommendation accuracy (ii) reduced user-item rating data sparsity (iii) increased novelty rate of recommendations and (iv) improved scalability of the recommendation system.

The objective of the present study is to isolate phages targeting multidrug resistant (MDR), extended spectrum beta lactamase (ESBL) positive clinical isolate of E. coli ( U1007), sequence and analyze the phage genome and use machine learning tools to predict host cell surface receptor and finally evaluate the efficiency of monophage and phage cocktail in vitro and in vivo in a zebrafish model. Phage specific for E. coli U1007 was isolated from Ganges River (designated as U1G), Cuoom River (designated as CR) and Hospital waste water (designated as M phage). The obtained phages were triple purified and enriched. U1G phages had a greater burst size of 124 PFU/cell and a latent time of 25 min.M phage had a burst size of 150 PFU/cell with a shortlatent time of 20min. Similarly CR phage has a short latent 20 min and a burst size of 115 PFU/cell. Based on capsid architecture, U1G phage resembles Podoviridae, CR phage is structurally similar to Myoviridae and M phage has morphology that resembles Siphoviridae. Genome sequencing and analysis revealed that the size of the U1G phage genome is 73275 bp Whereas that of CR phage and M phage are 45236 bp and 45294 bp, respectively. All three genomes were marked by the absence of genes encoding tRNA sequence, antibiotic resistant or virulent genes. A machine learning (ML) based multi-class classification model using algorithms such as Random Forest, Logistic Regression, and Decision Tree were employed to predict the host receptor targeted by all 3 phages and the best performing algorithm Random Forest predicted LPS O antigen , LamB or OmpC for U1G FhuA, OmpC for CR phage and FhuA, LamB, TonB or OmpF for the M phage as the host receptor targeted by the receptor binding protein (RBP) of the phages. In vitro time kill assay showed that treatment with monophages alone and along with colistin resulted in regrowth whereas phage combinations significantly reduced the regrowth and by 24h the phage cocktail along with colistin produced a significant 3 log declinein cell counts relative to the untreated control. In vivo intramuscular infection study in zebrafish showed that phages were non toxic and a cocktail of dual (U1G +M) phage along with colsitin resulted in a significant 3.5 log decline in cell counts whereas triple phage combination along with colistin resulted in 3 log decline in cell counts probably due to host receptor competition. Our study highlights the potential of phage cocktail therapy in mitigating MDR clinical isolate of E. coli in vitro and in vivo.

Numerous goods and services are now offered through online platforms due to the recent growth of online transactions like e-commerce. Users have trouble locating the product that best suits them from the numerous products available in online shopping. Many studies in deep learning-based recommender systems (RSs) have focused on the intricate relationships between the attributes of users and items. Deep learning techniques have used consumer or item-related traits to improve the quality of personalized recommender systems in many areas, such as tourism, news, and e-commerce. Various companies, primarily e-commerce, utilize sentiment analysis to enhance product quality and effectively navigate today's business environment. Customer feedback regarding a product is gathered through sentiment analysis, which uses contextual data to split it into separate polarities. The explosive rise of the e-commerce industry has resulted in a large body of literature on e-commerce from different perspectives. Researchers have made an effort to categorize the recommended future possibilities for e-commerce study as the field has grown. There are several challenges in e-commerce, such as fake reviews, frequency of user reviews, advertisement click fraud, and code-mixing. In this review, we introduce an overview of the preliminary design for e-commerce. Second, the concept of deep learning, e-commerce, and sentiment analysis are discussed. Third, we represent different versions of the commercial dataset. Finally, we explain various difficulties facing RS and future research directions.

Background: Expansion of OKF6/TERT-2 oral epithelial cells in vitro is important for studying the molecular biology of disease and pathology affecting the oral cavity. Keratinocyte Serum-Free Medium (KSFM) is the medium of choice for this cell line. This study compares three media for OKF6/TERT-2 cultures: KSFM, Dulbecco’s Modified Eagle Medium/Nutrient Mixture of Hams F-12 (DMEM/F12) and a composite medium comprised of DMEM/F-12 and KSFM (1:1 v/v), referred as DFK. The toxicological effects of electronic cigarette liquids (E-liquids) on OKF6/TERT-2 cells cultured in these media were also compared. Methods: Cells were cultured in KSFM, DMEM/F12 or DFK and cellular morphology, growth, wound healing and gene expression of mucins and tight junctions were evaluated. Additionally, cytotoxicity was determined after E-liquid exposures. Results: Switching from KSFM to DMEM/F12 or DFK 24-hours post-seeding leads to typical cellular morphologies, and these cultures reach confluency faster than those in KSFM. Wound-healing recovery occurred fastest in DFK. Except for claudin-1, there is no difference in expression of the other genes tested. Additionally, E-liquid cytotoxicity appears to be amplified in DFK cultures. Conclusions: DMEM/F12 and DFK are alternative media for OKF6/TERT-2 cell culture to study molecular biology of disease and pathology, provided cells are initially seeded in KSFM.

This review paper delves into using micro-credentials in higher education ecosystems as a digital enablers. Micro-credentials, which are digital credentials that attest to a learner’s mastery of a specific skill or knowledge area, are becoming more popular in higher education. The paper examines the successful implementation of micro-credential frameworks in higher education, using case studies to demonstrate the advantages of micro-credentials. The review emphasizes the agility and flexibility of microcredentials, which enable learners to acquire new skills quickly and respond to changes in the job market. In addition, the paper discusses the digital nature of micro-credentials and how they allow institutionsto provide targeted, skills-based training that isrelevant to employers. It also explores how micro-credentials are delivered through online platforms, making them convenient and easily accessible for learners. The review underscores the significance of digital infrastructure, connectivity, and public utility for promoting micro-credentials. The paper argues that micro-credentials function as a digital enabler for higher edu- cation ecosystems, allowing learners to acquire targeted training and enabling institutions to expand their offerings and reach more students. The paper concludes by highlighting the potential for micro-credentials to help bridge the skills gap and equip learners with the skills necessary to succeed in today’s digital economy.

The use of Learning Management Systems (LMS) has had a rapid growth over the last decades. Great efforts have been recently made to assess the level of performance of the students online due to the COVID-19 pandemic. Faculty members with limited experience in the use of LMS such as Moodle, Edmodo, MOOC, Blackboard and Google Classroom can have some problems creat-ing online tests. In this work, a new plugin for Moodle is presented: FastTest PlugIn. This plugin is based on a Microsoft® Excel spreadsheet and it can be used to export questions to Moodle. Us-ers of FastTest PlugIn can create question pools in an easy and intuitive way. A literature review about plugins used to import/export questions in Moodle is carried out. Then, the characteristics of FastTest PlugIn are presented. At the end, the characteristics of the main plugins found in the literature are discussed and compared with the ones of FastTest PlugIn.

The global pandemic caused by the new coronavirus has largely changed established business practices. The aim of the study is to present the results of eighteen-month intensive research into the effects of the pandemic on e-consumer behavior. In one of the most active e-commerce markets in Europe, the Czech Republic, we analyzed a sample of more than one and a half million Facebook users in terms of their C2B interactions on the B2C activities of the five major e-commerce market players. The measurements were carried out in three periods, which corresponded to the onset of the first wave, peak, and fading of the second wave of the pandemic. This enabled us to monitor the effect of seasonality and the stabilization of patterns of consumer behavior during the coronavirus crisis. The results suggest that a specific panic pattern of e-consumer behavior was developed at the time of the onset of the pandemic. However, as the pandemic progressed, the market has adapted to a new normal, which, as evidenced by the change in trends, appears to be a combination of the pre-pandemic and pandemic behavioral patterns. Using a statistical analysis, it was possible to identify delta of changes within the patterns of consumer behavior, thus fulfilling the final condition for creating an empirical model of the COVID-19 pandemic impacts on e-consumer behavior presented in this study.

Background: Serious games are conceptualized as a broad topic and overlap segments of more modern forms of education: e-learning, edutainment, game-based learning, and digital game-based learning. Serious Games aligns with digitalization and the modern era and creates novel opportunities for learning and assessment in medical education. Escape rooms, a type of serious games, merge mental and physical aspects to reinforce critical skills useful in daily life. It challenges logic and reasoning and demands careful analysis of situations to correlate and solve different stages of the escape room under pressurized, timed conditions. Furthermore, it serves as an adequate environment to build problem-solving skills, communication skills, and leadership skills through the collaboration of people to achieve a common goal. The aim of this study was to investigate the applications of escape rooms in Medical Education. Method: This study investigated the applications of escape rooms in medical education. Serious games are expanding in education and have attained great relevance due to their intriguing and intrinsically motivating attributes. Within serious games, we focused on escape rooms in which participants are locked in a room, faced with puzzles that must be solved to ‘escape the room’. Compiling the data from the first 100 hits of medical application of escape rooms, we found 72 cases and categorized them by year, specialty, participants structure, simulation experience, and design. Results: We reported on escape rooms in medical education by the year in which they were reported, the medical specialty, the participant structure, grouped or individual, the experience design; real, hybrid, or digital, and the modality of the delivery. 72% of the escape rooms focused on four main areas: nursing education (25.0%), emergency medicine (22.2%), pharmacy (12.5%), and interprofessional education (12.5%). Most of the escape rooms had a group-based physical design and little attention was given to provide a detailed description of the design considerations, such as the pathway type (linear, semi-linear, open). Conclusion: Escape rooms are applied in a wide range of medical education areas. In Medical Education, group-based on-site escape rooms with a focus on nursing, emergency medicine, pharmacy and interprofessional education dominates the implementation landscape. To further advance the field, stronger emphasis on making explicit the design considerations will advance the research and inform implementations.

The adverse relationship between viral hepatitis and pregnancy in developing countries was seen as a reflection of retrospective biased hospital-based data collection by the West. However, the discovery of HEV from an epidemic of non-A, non-B hepatitis in Kashmir and documenting increased incidence and severity of hepatitis E in pregnancy from a house-to-house survey unmasked the unholy alliance. Among the family of HEV’s, genotype (gt)-1, with a unique ORF4-encoded protein enhancing viral polymerase activity and viral replication, is the sole HEV that shows this adverse relationship. The epidemics caused by HEV-gt1 and not by HEV-gt2 show adverse relationship with pregnancy. The pathogenesis of the unholy alliance is complex and at present not well understood. Possibly multiple factors play a role in causing severe liver disease in the mother including: infection, replication and damage to the maternal-foetal interface by HEV-gt1; vertical transmission of HEV to foetus causing severe foetal/neonatal hepatitis; and combined viral and hormone related immune dysfunction of diverse nature in the mother promoting viral replication. Management is multidisciplinary and needs a close watch for the development and management of ALF. Preliminary data suggest beneficial maternal outcomes by early termination of pregnancy in patients with lower grades of encephalopathy.

DDX3 is an ATP-dependent RNA helicase involved in multiple cellular activities, including RNA metabolism and innate immunity. DDX3 is known to assist the replication of some viruses while restricting some others through direct interaction with the viral proteins. However, the role of DDX3 in the replication of the hepatitis E virus (HEV) is unknown. In this study, DDX3 is shown to interact with the HEV capsid protein and provide an indispensable role in HEV replication. The DDX3 C-terminal domain was demonstrated to interact with the capsid protein, which was previously demonstrated to inhibit the production of type I interferons. Knockdown of DDX3 compromised the capsid protein-mediated blockage of interferon induction. Notably, DDX3 silencing led to a significant reduction in HEV replication. Also, the ATPase activity of DDX3 is required for the HEV replication as an ATPase-null mutant DDX3 failed to rescue the viral replication in the DDX3-silenced cells. These results demonstrate a pro-viral role of DDX3 in HEV replication, providing further insights into the virus-cell interactions.

Mast cells are long-lived, granular, myeloid-derived leukocytes that have significant protective and repair functions in tissues. Mast cells sense disruptions in the local microenvironment and are first responders to physical, chemical and biological insults. When activated, mast cells release growth factors, proteases, chemotactic proteins and cytokines thereby mobilizing and amplifying the innate and adaptive immune system. Mast cells are therefore significant regulators of homeostatic functions and may be essential in microenvironmental changes during pathogen invasion and disease. During infection by helminths, bacteria and viruses, mast cells release antimicrobial factors to facilitate pathogen expulsion and eradication. Mast cell-derived proteases and growth factors protect tissues from insect/snake bites and exposure to ultraviolet radiation. Finally, mast cells release mediators that promote wound healing in the inflammatory, proliferative and remodeling stages. Since mast cells have such a powerful repertoire of functions, targeting mast cells may be an effective new strategy for immunotherapy of disease and design of novel vaccine adjuvants. In this review, we will examine how certain strategies that specifically target and activate mast cells can be used to treat and resolve infections, augment vaccines and heal wounds. Although these strategies may be protective in certain circumstances, mast cells activation may be deleterious if not carefully controlled and any therapeutic strategy using mast cell activators must be carefully explored.

The implementation of teaching interventions in learning needs has received considerable attention, as the provision of the same educational conditions to all students, is pedagogically ineffective. In contrast, more effectively considered the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that support automatic modeling study and adjust the teaching content on educational needs and students' skills. Effective utilization of these educational approaches can be enhanced with Artificial Intelligence (AI) technologies in order to the substantive content of the web acquires structure and the published information is perceived by the search engines. This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is a novel hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a hybrid method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.

Biofilms enable the persistence of pathogens in food processing environments. In order to inactivate these microorganisms, sanitizing agents are needed that are effective against pathogens entrapped in biofilms which are more difficult to inactivate than planktonic cells that are displaced and found on equipment surfaces. We examined conditions to develop, analyze, and enumerate robust biofilms of 3 different foodborne pathogens assisted by fluorescence adherence assay and enzymatic detachment. We compared 3 different isomeric forms of fluorescent substrates that are readily taken up by bacterial cells based on carboxy-fluorescein diacetate (5-CFDA, 5,6-CFDA, 5,6-CFDA,SE). Biofilm-forming strains of L. monocytogenes, E.coli O157:H7, and Salmonella serovars were detected using the chosen substrate in a microplate fluorescence assay define previously for use with Listeria. Adherence levels were determined by differences in relative fluorescence units (RFU). Multiple hydrolytic enzymes were examined for each representative pathogen for the most suitable enzyme for detachment and enumeration to confirm data obtained by fluorescence assay. Cultures were grown overnight in microplates, incubated, washed and replenished with fresh sterile growth medium; this cycle was repeated 7 times before used as ‘biofilms’. All treatments were performed in triplicate and compared by one-way analysis of variance (ANOVA) to determine significant differences (p < 0.05). Analysis of 7-day biofilms by SEM indicated possible extracellular polysaccharide involvement with Salmonella and E. coli.

Here, we propose a novel scheme based on advanced techniques of digital modulation in optical communications to achieve a single-channel transmission rate above 100 Gb/s. We utilize a hybrid scheme amplitude/phase/frequency/dual polarization, combined with multidimensional dual lattice and a low-density parity-check-coded modulation. The Stokes parameters are applied to the proposed scheme to map the four-dimensional classical polarization \({I_X},{Q_X},{I_Y},{Q_Y}\) in a three-dimensional space. In addition, in the proposed system, the packing theory is applied to the bit interleaver process, three wavelengths are packaged before being transmitted over a wavelength-division multiplexing optical channel. This modulation process is carried out using symmetrical geometric shapes, such as a hypercube or a polyhedron, based on the molecular links theory using a grouping of 12 and 13/15 bits for the cubic and spherical lattices, respectively. The proposed technique is evaluated in the context of long distance communications over distances up to 100 km. The bit error rate results showed that the optical signal-to-noise ratio was approximately 4 dB over a distance of 50 km. In addition, the power spectral efficiency was found to be 3 lambda, which is considered good performance considering the effects of distance and the non-linear effects influencing the number of lambdas. Also, we use an optical time division multiplexing scheme (OTDM) in order to achieve a transmission rate beyond 1Tbit/s, where the speed effect is evaluated, taking into consideration that the power spectral efficiency is degraded. Furthermore, the average noise floor is -60dBm for all transmission distances. These findings are expected to contribute to the future implementation of robust long-distance optical communication infrastructure.

Traditionally understood in reference to distance education, cognitive presence may be defined as "the extent to which the participants in any particular configuration of a community of inquiry can construct meaning through sustained communication. The purpose of this paper was to create a blueprint for the reflective ePortfolio as the capstone project for my graduate degree. The blueprint was accomplished by adapting for use cognitive presence as a tool for both analysis and framing, which has never been done to the best of my knowledge. I considered myself to be a participant in a “community of inquiry” model and substituted the result of my interaction with each of the required instructor-course content pairings I took to serve as fellow participants in this community model. The result of my participation was understood to be the knowledge and experience that I have gained, which was reflected in eight of my academic research papers. These selected papers were the artifacts around which my ePortfolio was ultimately developed and demonstrated my participation as an active member in this community of inquiry constructing meaning through sustained communication.

The geometry of Poincare disk itself is interpreted without any mapping to dierent spaces. Our approach might be one of the shortest and is intended for educational contribution.

Hydrological models have been widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are nowadays available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, firstly soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall, SM2R-AMSRE, at different sites in the Karkheh river basin (KRB), southwest Iran. Secondly, the SWAT (Soil and Water Assessment Tool) hydrological model is applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall, due to soil moisture saturation, not accounted for in the SM2RAIN equation. The subsequent SM2R-AMSRE- SWAT- simulated monthly runoff reproduces well the observations at the 6 gauging stations (with coefficient of determination, R² > 0.72), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation than the SWAT model with ground-based rainfall input. Furthermore, rainfall estimations of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model. The monthly runoff obtained with 3B42- rainfall have 0.39< R2 < 0.70 and are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SM2R-AMSRE- SWAT- simulated runoff above. Therefore, in spite of the afore-mentioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT, appears to be a viable approach in basins with limited ground-based rainfall data.

The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using as input medical reference texts and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false and match), can have customizable length and difficulty and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.

Educational data-mining is an evolving discipline that focuses on the improvement of self-learning and adaptive methods. It is used for finding hidden patterns or intrinsic structures of educational data. In the arena of education, the heterogeneous data is involved and continuously growing in the paradigm of big-data. To extract meaningful information adaptively from big educational data, some specific data mining techniques are needed. This paper presents a clustering approach to partition students into different groups or clusters based on their learning behavior. Furthermore, personalized e-learning system architecture is also presented which detects and responds teaching contents according to the students’ learning capabilities. The primary objective includes the discovery of optimal settings, in which learners can improve their learning capabilities. Moreover, the administration can find essential hidden patterns to bring the effective reforms in the existing system. The clustering methods K-Means, K-Medoids, Density-based Spatial Clustering of Applications with Noise, Agglomerative Hierarchical Cluster Tree and Clustering by Fast Search and Finding of Density Peaks via Heat Diffusion (CFSFDP-HD) are analyzed using educational data mining. It is observed that more robust results can be achieved by the replacement of existing methods with CFSFDP-HD. The data mining techniques are equally effective to analyze the big data to make education systems vigorous.

A rapid, precise, accurate and low cost method for the determination of vitamin E (α-tocopherol) in cereal products and biscuits was developed. The uncertainty was calculated for the first time and the methods were performed in different cereal products and biscuits, characterized as “superfoods”. The limits of detection and quantification were calculated. Accuracy and precision were estimated using the certified reference material FAPAS T10112QC and the determined values were in good accordance with the certified values. The health claims according to the daily reference values for vitamin E were calculated and the results proved that the majority of the samples examined showed %daily value higher than 15%.

This study examines the key factors influencing E-bike adoption and explores how advancing E-bike usage in Henan Province, China, can foster sustainable urban transportation and contrib-ute to urban environmental preservation. Utilizing data from an online survey, binary logistic re-gression analyzes the impact of socio-demographic characteristics, perceived advantages, neigh-borhood environmental attributes, and vehicle ownership on E-bike usage. Findings indicate that socio-demographic factors, such as family size and occupation, significantly influence adoption, with workmen more likely than office workers to choose E-bikes. Cost savings emerged as the primary motivator for E-bike use, overshadowing environmental concerns, which unexpectedly negatively affected usage patterns. However, the presence of supportive infrastruc-ture—particularly charging stations and dedicated lanes—proves crucial for promoting E-bike usage, highlighting the importance of accessible, environmentally supportive urban design. Vehi-cle ownership characteristics further illuminate how access to E-bikes correlates with regular us-age. These findings suggest that, beyond cost-efficiency, targeted awareness campaigns and stra-tegic infrastructure improvements are essential for embedding E-bikes into sustainable urban transport systems. By fostering adoption and supporting E-bike infrastructure, cities can signifi-cantly reduce urban pollution, improve air quality, and advance toward sustainable mobility goals in Henan Province and beyond.

The recreational waters of hotels are widely used by locals and travelers all around the world and this impacts public health. In this regard, WHO frequently offers recommendations - especially in the COVID-19 era - so operators and managers of public pools, hot tubs or splash pads should continue to follow. This study aims to evaluate the microbiological results of COVID-19 sanitation protocols in recreational waters in hotels during the summer periods of post-COVID-19 (2020–2022) and compare them with those of pre-COVID-19 (2019). We found positive samples for different parameters in the period of 2019: 11.5 % for total coliforms (18/157), 12.2% for common aerobic bacteria (19/156), 2.9% for E. coli (5/170), and 18.2% for P. aeruginosa (27/148). For the pandemic years, the percentages of positive samples were: 8.1% for total coliforms (40/493), 1.3% for common aerobic bacteria (7/526), 1.3% for E. coli (7/526), and 18.4% for P. aeruginosa (83/450). The study found that the relative risk (RR) from the presence of P. aeruginosa in recreational waters with chlorination 25°C. Although non-compliance decreased at the beginning of the pandemic due to strict health protocols, this gradually stopped.

In the dynamic landscape of online shopping, predicting user behaviors such as clicks, cart additions, and orders is crucial for optimizing sales strategies. Traditional recommendation systems often focus on a single objective, limiting their effectiveness in a multifaceted e-commerce environment. This article proposes a multi-objective recommendation system that leverages previous events in user sessions to forecast these key metrics, addressing challenges such as imbalanced positive and negative samples, varying session lengths, and the need for effective sampling techniques. Our approach integrates LightGBM, XgBoost, and Recbole GRU4Rec through ensemble learning, combining the strengths of these models to enhance prediction performance. Extensive evaluations demonstrate that our model outperforms existing methods, offering significant improvements in accuracy and robustness. This work provides a comprehensive solution for online retailers to better predict user behaviors and optimize their sales strategies, ultimately enhancing customer satisfaction and business outcomes.

Objective: Fludeoxyglucose F18 positron emission tomography (FDG PET) can give early clues for diagnosing Alzheimer’s disease (AD). Our objective was to use the same scan to predict Apolipoprotein E4 (ApoE4), known to be a risk factor. A second objective was to determine the brain regions and imaging features associated with this gene allele that can potentially help elucidate the mechanisms of the disease and better comprehend the images. Method: We employed data from 112 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). PET and structural MRI data were co-registered with ANTx, and the Freesurfer tool delineated 95 whole brain, 19 hippocampal, and 9 amygdala regions. Using PyRadiomics we extracted 120 radiomic features from these segments. We employed a hybrid feature selection strategy. The HistGradientBoosting (HGB) classifier was evaluated using stratified five-fold cross-validation. Results: The proposed radiomics model predicted the homozygous ApoE4 genotype, with an AUC of 0.945 an accuracy of 0.875, a sensitivity of 0.914, and a specificity of 0.838. Reducing the feature set to seven key features resulted in a slightly decreased performance (AUC: 0.889). The mean values of the features showed statistically significant (p<0.05) incremental deterioration between different groups of homozygous ApoE4 carriers. Conclusion: Our findings underscore the critical role of specific brain regions and associated features in differentiating ApoE4 carriers. The hippocampus, entorhinal cortex, amygdala, thalamus, and pars orbitalis exhibited significant associations with the ApoE4 genotype. By employing SHAP analysis, we identified key features driving model predictions, enhancing interpretability, and providing insights into the underlying pathophysiology.

This qualitative study explores supplier collaboration in e-commerce product development, examining motivations, challenges, strategies, outcomes, and ethical considerations. Through in-depth interviews with stakeholders from diverse e-commerce sectors, the study identifies key themes shaping collaboration dynamics. Motivations include innovation, operational efficiency, and strategic partnerships, driving companies to integrate supplier expertise early in product development. Challenges such as global supply chain complexities, goal misalignment, and communication barriers underscore the need for robust governance and cultural sensitivity. Strategies for success include technology adoption, supplier development programs, and collaborative decision-making, enhancing supply chain visibility and mutual benefits. Effective collaboration yields improved product quality, cost efficiencies, and enhanced customer satisfaction, supporting competitive advantage. Ethical sourcing practices and sustainability initiatives are crucial for maintaining trust and regulatory compliance. Cultural and organizational factors, including leadership support and change management, significantly influence collaboration outcomes. The study concludes with implications for theory and practice, emphasizing the role of innovative strategies and continuous improvement in supplier relationships. Future research could explore digital transformation, sustainability trends, and technological impacts on supplier collaboration in e-commerce. Practical applications include optimizing supply chain strategies to navigate complexities and capitalize on market opportunities.

This qualitative research explores Supplier Relationship Management (SRM) as a pivotal driver of sustainable practices in the e-commerce sector. Through in-depth interviews with industry experts, practitioners, and scholars, the study investigates how SRM strategies integrate sustainability criteria into procurement processes, mitigate environmental and ethical risks, and enhance operational efficiencies. Key findings highlight the strategic importance of collaborative relationships with suppliers, technological innovations such as blockchain and data analytics in promoting transparency and accountability, and the influence of consumer preferences for sustainable products on market dynamics. Despite challenges such as regulatory complexities and global supply chain dynamics, businesses are increasingly adopting sustainable SRM practices to strengthen brand reputation, achieve cost savings, and align with evolving sustainability standards. The study underscores the interconnected nature of sustainability within e-commerce operations and calls for continued research to advance technological solutions, refine regulatory frameworks, and foster industry-wide collaboration. By embracing sustainability as a strategic imperative, businesses can navigate complexities, drive innovation, and contribute to a more resilient and sustainable future for the e-commerce industry.

This research investigates the pivotal role of Supplier Relationship Management (SRM) in enhancing e-commerce scalability. SRM practices are essential for optimizing supply chain operations and fostering strategic partnerships with suppliers, crucial in the dynamic and competitive e-commerce landscape. Through a comprehensive analysis of case studies, expert interviews, and secondary data, the study examines how leading e-commerce companies such as Amazon and Alibaba implement effective SRM strategies to achieve scalability. Key findings reveal that strategic supplier selection based on capabilities and alignment with business goals, coupled with continuous evaluation and development programs, ensures consistent supply chain performance and customer satisfaction. Technological advancements, including data analytics, artificial intelligence, and blockchain, play a transformative role in modern SRM by enhancing transparency, efficiency, and decision-making capabilities. These technologies enable real-time monitoring, automated processes, and risk mitigation strategies that bolster supply chain resilience and operational efficiency. Best practices in SRM, such as clear performance metrics, a culture of continuous improvement, and ethical sourcing policies, are critical for driving supplier accountability, innovation, and sustainability. Moreover, sustainability emerges as a growing priority in SRM, with businesses integrating environmental and social considerations into supplier management strategies to meet regulatory requirements and stakeholder expectations. Theoretical frameworks like the Resource-Based View and Transaction Cost Economics provide insights into the strategic implications of SRM, emphasizing its role in fostering competitive advantage and long-term business success. As e-commerce continues to evolve, businesses must adapt and innovate in their SRM approaches to navigate global supply chain complexities effectively. By prioritizing effective SRM practices, leveraging advanced technologies, and embracing sustainability, businesses can enhance their scalability, resilience, and competitiveness in the digital economy.

This study explores the dynamics of transparency and accountability in supplier relationship management (SRM) within the e-commerce sector. It investigates how e-commerce platforms and their suppliers navigate complexities to foster trust, enhance collaboration, and ensure ethical practices in global supply chains. The research employs a qualitative approach, utilizing semi-structured interviews with industry stakeholders to gather insights into current practices, challenges, and strategies in SRM. Findings highlight transparency as pivotal for sharing critical information such as sales forecasts, inventory levels, and pricing strategies, enabling suppliers to align operations with market demands effectively. However, achieving transparency faces hurdles including data privacy concerns and competitive sensitivities, necessitating robust data security measures and clear communication protocols. Accountability mechanisms, such as formal agreements and governance frameworks, emerge as essential for mitigating risks, resolving disputes, and ensuring compliance with ethical and regulatory standards across diverse contexts. Technological innovations like AI, blockchain, and big data analytics are transforming SRM by enhancing supply chain visibility, operational efficiency, and decision-making capabilities. Cultural factors and regulatory compliance also significantly influence SRM practices, shaping communication styles, relationship dynamics, and legal considerations. Emerging trends such as sustainable sourcing practices and collaborative partnerships are reshaping SRM, emphasizing sustainability and responsible business practices. This study contributes to the understanding of effective SRM strategies, offering insights and recommendations for stakeholders navigating the complexities of e-commerce supply chains.

This qualitative study explores collaborative supplier relationships within the context of e-commerce, aiming to uncover the dynamics, challenges, strategies, impacts, and future trends shaping these partnerships. Through thematic analysis of interviews with e-commerce platform managers, supplier representatives, and industry experts, the study identifies three primary types of relationships: transactional, relational, and strategic. Critical factors influencing these relationships include trust, effective communication, technological integration, and regulatory compliance. Challenges such as information asymmetry, cultural differences, logistical complexities, and competitive pressures are examined, alongside strategies for enhancing collaboration, including clear communication protocols, performance evaluations, and technological advancements. The findings highlight the significant impact of collaborative supplier relationships on business performance, including cost efficiencies, supply chain resilience, innovation capacity, customer satisfaction, and market competitiveness. Looking forward, trends in digital transformation, sustainability initiatives, global supply chain networks, resilience-building strategies, and industry collaboration are discussed as shaping the future landscape of e-commerce partnerships. Embracing these trends presents opportunities for organizations to innovate, adapt, and sustain growth in the competitive digital marketplace.

Background: Atopic dermatitis is a chronic condition that significantly affects the daily life of those who suffer from it, requiring complex and personalized management with active participation of the patient in the management of their disease. Objective: to describe the design and development process of a mobile application, using the Design Thinking method, for the follow-up of patients with atopic dermatitis. Methods: User-centered design and prototype creation method, differentiating the phases of the empathize, define, idea, prototype, and test. A purposive snowball sampling was used to recruit patients with atopic dermatitis, family members, and health professionals. Three two-hour workshops were held, attended by 25 people. Results: the parameters to be monitored will include objective data (physical, behavioral, treatments, environmental, integration of daily routines) and subjective data (user experience). On the other hand, it will figure out behavior patterns, set up rewards, foster a feeling of community, and use notifications and a chatbot. Conclusion: The active integration of all stakeholders at each stage of the design and development of the digital solution has improved its relevance and acceptance, resulting in a tool that is expected to significantly improve the management of atopic dermatitis.

This qualitative research investigates the impact of Supplier Relationship Management (SRM) on e-commerce innovation adoption. Through semi-structured interviews and document analysis, the study explores how SRM practices influence organizational capabilities to innovate in the context of digital commerce. Key themes emerged, emphasizing the critical role of trust, communication, collaboration, strategic alignment, technology integration, organizational culture, leadership, and external factors in shaping e-commerce innovation. Trust was found to be foundational, fostering transparent communication and collaborative relationships that facilitate innovation. Effective communication channels and collaborative initiatives enabled organizations and suppliers to leverage combined expertise, driving the development of innovative e-commerce solutions. Strategic alignment ensured that both parties worked towards shared goals, supported by technology integration that enhanced operational efficiency and decision-making. Organizational culture and leadership were identified as crucial in creating environments conducive to continuous innovation. External factors such as market dynamics, regulatory requirements, and technological advancements influenced innovation strategies, highlighting the need for adaptive and responsive SRM practices. The findings underscore the interconnectedness of these factors within the SRM framework, offering insights into how organizations can enhance their innovation capabilities and competitiveness in the digital economy. By strategically managing SRM practices and integrating sustainable initiatives, organizations can navigate challenges, seize opportunities, and achieve sustained success in e-commerce innovation.

In this study, a modular multi-step photometric microflow injection analysis (micro-FIA) system for the automatic determination of Cu(II) in a bioreactor has been developed. The system incorporates diverse 3D-printed modules, including a platform formed by a mixer module to mix Cu(II) with hydroxylamine which reduces Cu(II) to Cu(I) linked to a diluter module via a Tesla valve, a chelation mixer module, a disperser module, and a detector module provided by a LED light source at λ= 455 nm and a light dependence resistor (LDR) as a light intensity detector. The system measures the color intensity resulting from the chelation between Cu(I) and neocuproine. The micro-FIA system has demonstrated good capability for automatic and continuous Cu(II) determination, in a wide range of Cu concentrations from 34 to 2000 mg L-1. The device exhibits a good repeatability (coefficient of variation below 2% across the concentration range), good reproducibility, and has an accuracy of around 100% between 600 to 1900 mg·L-1. Real samples were analyzed using both the micro-FIA system and an atomic absorption spectroscopy method, revealing no statistically significant differences. Additionally, a Tesla valve located before the detector substituted a 3-way solenoid valve, eliminating the need for moving parts.

E-tourism is one of the most important modern services to achieve the development of the tourism sector while relying on sophisticated communication technologies. Certainly, these innovations in the field of tourism have disrupted this sector with new and different dimensions of tourism development. This has led various regions and countries to accelerate the search for the tools that are necessary to achieve excellence and sustainable development in tourism. This research aims to study the development factors of e-tourism to achieve excellence and sustainable development in the tourism of the Ha’il region. Therefore, we applied two analyses: in the first one, we used a statistical analysis based on the survey sent to employees from tourism companies. The objective of this analysis is to determine the main factors of e-tourism to achieve excellence in tourism in the Ha’il region. The results of the statistical analysis have given us the following elements: There are only four main factors that allow authorities to achieve excellence in tourism in the Ha’il region, namely ST, CP, HRS, and SC factors. Then we proceed with a second analysis, to determine the main factors of excellence in tourism that drive the achievement of sustainable development in tourism in the Ha’il region. For this reason, we applied an artificial intelligence method based on the unsupervised machine learning technique. The results obtained from the machine learning technique show that five factors determine the excellence in tourism and reveal the sustainable development of Ha’il’s tourism. These factors are ST, CP, FP, HRS, and GC. Consequently, we consider that all the factors found in both analyses are important to realise excellence in tourism and sustainable development in tourism. However, to achieve sustainable development in tourism in Ha’il, Saudi authorities must develop the three common factors found in the two analyses, namely ST, CP, and HRS.

E-waste management (EWM) refers to the operation-management of discarded or unproductive electronic devices and components, a challenge exacerbated due to overindulgent urbanization. This article presents a multidimensional cost-function-based analysis of the EWM framework structured on three modules - environmental, economic, and social uncertainties - which contemplate the 3 pillars of sustainability in an e-waste recycling plant, including the production-delivery-utilization process. The framework incorporates material recovery from a single e-waste facility provisioning for chemical and mechanical recycling. Each module is ranked using independent Machine Learning (ML) protocols: a) Analytical Hierarchical Process (AHP) and b) combined AHP and Principal Component Analysis (PCA). From a long list of possible contributors, the model identifies and ranks two key sustainability contributors to the EWM supply chain: overall energy consumption and volume of carbon dioxide generated. Another key finding is a precise time window for policy resurrection, which for the data considered, happens to be 400-600 days from the start of operation. Another interesting outcome is the quality of prediction using a combination of AHP and PCA, which consistently produced better results than any of these ML methods individually implemented. Model outcomes have been verified using a case study to outline a future E-waste sustained roadmap.

In the field of business environments, the integration of novel artificial intelligence (AI) techniques has been identified in the literature and theoretical discourse as an essential catalyst for enhancing the decision-making processes. In the contemporary landscape of digital transformation, the application of these techniques becomes essential, despite encountering various hurdles that impede their seamless integration into the rational decision-making process within e-government, which constitutes a critical component of digital government initiatives. This study explores whether similar advancements can be observed within the e-government sector and investigates the impact of using machine learning (ML) as a technique of artificial intelligence on rational decision-making (RDM). Employing an empirical research approach, the study utilized a quantitative methodology, relying on an electronically structured questionnaire survey administered to 163 employees in the e-government sector in Jordan through purposive random sampling. Data analysis was conducted using the SPSS v25 program, complemented by a media-tion analysis using AMOS v23 software. The research findings revealed a significant contribution of using machine learning to enhance rational decision-making and trust levels, with trust positively impacting RDM. Trust was identified as a beneficial mediator in the relationship between machine learning and rational decision-making. Despite certain limitations, this study's outcomes offer substantial insights for researchers and government policy-makers alike, contributing to the advancement of sustainable practices in the e-government domain.

Meals on Wheels (MoWs) are critical in enabling adults with care and support needs to live independently. However, many individuals are unaware that the service exists. The aim of this study was to review the websites of local authorities in the UK, and those of 3^rd-party providers they signpost to, to establish the quality of online information available on MoWs services, and the websites’ overall quality. Two data capture forms were used to extract information from local authority and 3^rd-party providers, consisting of 35 items across five domains, and 36 items across five domains, respectively. Items were awarded a score based on whether certain criteria were met or not, resulting in a maximum total score of 50 and 43 points for each local authority, and 3^rd-party provider, website, respectively. A total of 271 websites (223 local authority and 48 3^rd-party provider) were reviewed. The mean total score was 14.9 (SD 10.6, range: 1-40 points) for local authority websites, and 21.4 (SD 5.3, range: 10-35 points) for 3^rd-party provider websites. For all websites combined, online provision of MoWs information was generally poor, with the vast majority of websites (69.4%, n=188) assessed as requiring improvement, whereas only 4.4% of websites (n=12) were assessed as very good. These findings suggest that local authorities and 3^rd-party providers in the UK should seek to improve their online information provision on MoWs to enhance awareness of the service, and ensure that potential service users, and individuals who refer them to the service, can access high-quality information on MoWs.

This study employs molecular docking techniques to investigate a spectrum of targets within Escherichia coli (E. coli), with a specific focus on four key proteins: Beta-lactamase, MccE protein, Penicillin G acylase, and DNA polymerase II. The research explores the binding interactions of various natural compounds, emphasizing Hypericin. Through computational analyses, the study aims to unveil the potential interactions between these compounds and essential proteins in E. coli. Notably, Hypericin demonstrates remarkable binding energy scores of approximately -10.5 kcal/mol within the Ligand Binding Site of the specified proteins. This observation suggests Hypericin's potential as a potent modulator of E. coli targets, prompting further investigation into its antimicrobial properties and therapeutic applications.

The hepatitis E virus (HEV) is a zoonotic pathogen with a variety of hosts, including pigs, which act as reservoirs. In industrialized countries, sporadic cases caused by genotype 3, contracted by ingestion of contaminated uncooked or undercooked meat, have been reported. However, in developing countries, HEV infection is mainly dominated by genotype 2 and often associated with poor hygiene conditions and drinking water supplies. In West Africa, HEV infection and its circulation in domestic fauna are very poorly documented. The aim of this study was to assess the presence of HEV in pork sold in Saint-Louis. Meat products were collected between 20 and 25 August 2022 in three location of Saint-Louis region. After purchasing 250 g of sample, we minced 2 g of sample for extraction of total nucleic acids using the Purelink™ Viral DNA/RNA kit and then RT-PCR using the One-Taq™ One-Step RT-PCR kit targeting the HEV ORF2 genomic region. The products obtained were visualized on a 1% agarose gel. Of a total of 74 samples, divided into pork meat (n=65) and pork liver (n=9), 5.4% (n=4) were tested positive for HEV. In both cases, 2 samples were positive, representing a rate of 3.1% and 22.2% for meat and pork liver respectively. All new viral sequences obtained form a monophyletic group within HEV genotype 3. These preliminary results reveal a potential circulation of HEV in the pig population. The high proportion of contamination in the pork liver samples highlights a major risk associated with their consumption.

This investigation delves into the profound interplay between the e-commerce environment and the agricultural system, while scrutinizing the intricate human-land coupling dynamics engen-dered by transformations within the agricultural domain. Focusing on the expansion of orchards in Pinghe County, a pivotal epicenter for Chinese sweet pomelo production, this study eluci-dates the reverberations of Rural E-commerce Environment Development on Orchard Expansion through the lens of Tele-coupling. In doing so, it unveils the nuanced tapestry of the human-land coupling associations latent within the evolutionary trajectory of the agricultural system amidst the blossoming information society. The findings underscore a symbiotic relationship between the augmentation of orchard acreage and the burgeoning rural e-commerce landscape, effec-tively propelling the economic prosperity of the agricultural system. Moreover, a tele-coupling phenomenon has emerged, underscoring the intricate web of interconnections binding the mat-uration of the rural e-commerce ecosystem with the proliferation of orchards. The research illu-minates that the transformation of land utilization, imbricated within the agricultural system, manifests as a distinctive form of tele-coupling intricately woven into the fabric of urbanization and information technology advancements. Consequently, adopting a comprehensive theoreti-cal perspective, amalgamating disparate domains across distinct geographic realms, becomes imperative for discerning the intricate nuances of the human-land coupling nexus within these multifaceted, open systems.

The combination of e-commerce and the green economy allows enterprises to distribute their green products directly to consumers through Internet channels. This paper investigates the impact of service spillovers on emission reduction and channel decisions in a two-echelon supply chain,in which the supplier is a Stackelberg leader and the retailer is a follower.By comparing the equilibrium outcomes of the single-channel and dual-channel supply chain in a setting with and without retail services, we observe that the supplier prefers to encroach on the market when services that retail locations provide largely spillover to and benefit the direct sales channel. Contrary to popular belief, a higher degree of service spillovers is beneficial for the retailer to get more returns under the dual-channel structure, whereas supplier encroachment will lead to a decline in the service level if the spillover degree is relatively low. In addition, the emission reduction level of products under supplier encroachment is always higher than that employed in the single-channel structure if consumers have both low-carbon preference and high degree of service sensitivity. Furthermore, we extend the equilibrium decisions under a carbon cap-and-trade (CCT) mechanism; the results fully verify the above conclusions. Interestingly, the implementation of a carbon price not only motivates carbon emission abatement and supplier encroachment, but also helps achieve a win-win outcome for supply chain members when service spillovers happen.

Vitamin E, a potent antioxidant, is a necessary and complex micronutrient for cows. During the transition period, vitamin E deficiency (VED) is among the highest prevalent micronutrient deficits in dairy cows. It may eventually result in oxidative stress and immunological malfunction, and it increases the risk of peripartum disorders. At present, detailed data on blood metabolites in VED cows are limited. Consequently, the purpose of this research was to examine the alterations in the serum metabolic profile of VED cows throughout the early postpartum period. Using comprehensive 1H nuclear magnetic resonance (1H NMR), the alterations in serum metabolic activities of VED cows were analyzed. In total, 28 multiparous Holstein cows were assigned according to serum α-tocopherol (α-Toc) concentrations into a normal (α-Toc ≥ 4 μg/mL, n = 14) and VED (α-Toc &lt; 3 μg/mL, n = 14) groups at 21 days postpartum, and their blood samples were collected for biochemical and 1H NMR analyses. A t-test on independent samples as well as multivariate statistics were used to assess the findings. In comparison with normal cows, VED cows showed significantly worse body condition scores, milk yield, and dry matter intake (p &lt; 0.05). Significantly higher levels of serum non-esterified fatty acids, aspartate aminotransferase, low-density lipoprotein, and malonaldehyde were found in VED-affected cows, as well as lesser concentrations of serum albumin, high-density lipoprotein, and total antioxidant capacity in comparison with normal cows (p &lt; 0.01), while other vitamins and minerals concentrations showed no distinction between the groups (p &gt; 0.05). Furthermore, 24 upregulated serum metabolites were identified under VED conditions. The metabolomics pathway analysis of these metabolites demonstrated that a global metabolic response to VED in cows was represented by changes in 11 metabolic pathways, comprising energy, carbohydrate, and amino acid metabolism. These outcomes suggest that VED cows were more likely to experience a negative energy balance characterized by alterations of common systemic metabolic processes and develop oxidative stress, inflammation, and ultimately liver injury. This study provides the first evidence of metabolic changes in cows with VED.

High salinity in soil affects the normal growth and development of crop. MicroRNA171 (miR171) plays a momentous role in plant resistance to adversity stress. The functions of Sly-miR171d and Sly-miR171e on growth of tomato and fruit nutritional quality under salt stress were studied. The results showed that the seed germination and seedling growth of tomato that silencing of Sly-miR171d/e by short tandem target mimic (STTM) were better than those of wild-type (WT). Silencing of Sly-miR171d/e seeds maintained a high germination rate, while WT tomato seeds barely germinated under 50 mM NaCl stress. Under 100 mM NaCl stress, silencing of Sly-miR171d/e increased the expression of their target gene SlGRAS24 with increasing duration of salt stress, while they enhanced the antioxidant activity, reduced reactive oxygen species (ROS) accumulation, and enhanced the salt tolerance of tomato plant by regulating gibberellin (GA) level. Moreover, the preharvest and postharvest fruit nutritional quality under salt stress was also studied, and the results showed that silencing of Sly-miR171d/e increased soluble solids, lycopene, total carotenoids, Vitamin C, organic acids and phenolic substances in tomato fruit. The present study demonstrated that silencing of Sly-miR171d/e enhanced plant salt tolerance through the GA pathway, and improved fruit nutritional quality under salt stress.

Microbe bioengineering has the potential to improve the nutritional value and health benefits of food products. Modifying microbial cells to produce specific proteins or compounds that can improve human health is one approach. Penicillin and recombinant insulin are two examples of this. The production of recombinant insulin by genetically modified E. coli bacteria has transformed diabetes treatment by providing a consistent and cost-effective source of insulin. Previously, insulin was extracted from the pancreas of animals, which was an expensive process that frequently resulted in impurities that could cause adverse reactions. Bioengineered insulin is now the standard diabetes treatment, providing a safe and effective method of controlling blood glucose levels. Bacteria, for example, can be genetically modified to produce vitamins like B12, which are difficult to obtain from plant sources. Likewise, yeasts can be genetically modified to produce β-carotene, a precursor to vitamin A that is required for vision, immune function, and skin health. Overall, bioengineered microorganisms have the potential to provide significant health benefits by producing essential compounds and proteins. Because of ongoing advances in genetic engineering techniques and understanding microbial metabolism, the possibilities for improving human health through bioengineering are limitless.

Healthcare-associated infections (HAI) worldwide includes infections by ESKAPE-E pathogens. Environmental surfaces and fomites are important components in HAI transmission dynamics, and shoe soles are vectors of HAI. Ultraviolet (UV) disinfection is an effective method to inactivate pathogenic microorganisms. In this study, we investigated whether the SANITECH UVC shoe sole decontaminator equipment that provides germicidal UVC radiation could effectively reduce this risk of different pathogens. Six standard strains and four clinical MDR strains in liquid and solid medium were exposed to a UVC System at specific concentrations at other times. Bacterial inac-tivation (growth and cultivability) was investigated using colony counts and resazurin as meta-bolic indicators. SEM was performed to assess the membrane damage. Statistically significant reduction in cell viability for all ATCCs strains occurred after 10 sec of exposure to the UVC sys-tem, except for S enterica, which only occurred at 20 sec. The cell viability of P. aeruginosa (90.9%), E. faecalis and A. baumannii (85.3%), S. enterica (82.9%), E. coli (79.2%) and S. aureus (71.9%) was re-duced considerably at 20 sec. In colony count, after 12 sec of UVC exposure, all ATCC strains showed a 100% reduction in CFU counts, except for A. baumannii, which reduced 97.7%. A sub-stantial reduction of colonies above 3 log10 was observed at 12 and 20 sec in all bacterial strains tested, except for A. baumannii ATCC 19606 (12 sec). The exposure of ATCCs bacterial strains to the UVC system for only 2 sec was able to reduce 100% in the CFU count in all ATCCs strains, S. au-reus, P. aeruginosa, E. coli, A. baumannii, E. faecalis, except the S. enterica strain which had a statis-tically significant reduction of 99.7%. In ATCC strains, there was a substantial decrease in colonies after 4 sec (sec) of exposure to the UVC system, with a reduction ranging from 3.78-4.15 log10 CFU/mL. This reduction was observed in MDR/ESKAPE-E strains within 10 sec, showing that UVC could eliminate above 3.84 log10 CFU/mL. SEM showed a reduction of pili-like appendages after UVC treatment in all strains except for E. coli (ATCC 25922). The Sanitech UVC shoe sole decontaminator equipment from Astech Co. effectively killed in vitro a series of ATCCs and MDR/ESKAPE-E bacteria of sanitary interest, commonly found in the hospital environment.

Coaxial rotors can be found in multirotor vehicles for the added thrust compared to independent rotors while keeping similar area footprints but, performance losses should be considered. This experimental study analyzes the effects of varying motor throttle and propeller pitch values in motor-propeller systems with two to four coaxial rotors. The results show that in a two-rotor coaxial system, to lessen the adverse effects of a front rotor’s backwash and to operate at the maximum performance, only the back motor should be operated initially up to 75% duty cycle before using the front motor up to its 75% duty cycle. Additional thrust requirements should be generated from the back rotor and then from the front rotor up to their maximum duty cycles. In two, three, and four-rotor coaxial setups, total thrust output generated is 1.6, 2.1, and 2.5 times the thrust output at system thrust performance of 86%, 76%, and 66%, respectively of that of an isolated rotor. In a four-rotor coaxial setup, maximum system performance is achieved when the propeller pitch values are gradually increased from the first to the last rotor. The gradual increments in propeller pitch values also result in more uniform thrust sharing among rotors.

At present, there are no hardware or biochemical systems allow to assess the severity of post-COVID syndrome in vivo. The hardware of the proposed biotechnical system is based on routine transthoracic electrical impedance rheography, which makes it possible to register the frequency characteristics of the patient's bioimpedance response to controlled stress stimulation, thereby simultaneously fixing the characteristics of his productive heart, the state of the hemomicrocirculatory bed, the efficiency of the gas transport function of his blood, and also reliably assess personal reactivity and adaptive potential. Subsequent mathematical approximation of the obtained biometric data by an original neural network makes it possible to rank the results obtained and automatically generate a program of medical rehabilitation for a particular patient, depending on the severity of his post-COVID syndrome. The study results proved two reliable physiological signs confirming the presence of latent post-COVID complications: a decrease in the base impedance value for light exercise and an increase in the length of the systolic arc of the rheocardiogram.

A case study is presented which demonstrates the value and validity of a novel approach to the use of consolidated amateur (‘ham’) radio reception reports as indicators of the presence of intense ionospheric sporadic E (Es). It is shown that the use of amateur data can provide an important supplement to other techniques, allowing the detection and tracking of Es where no suitable ionosonde or other measurements are available. The effectiveness of the approach is demonstrated by reference to ionosonde data, and the advantages and limitations of the technique are discussed.

According to our previous investigation the total methanol extract from Graptopetalum paraguayense E. Walther demonstrates a significant inhibitory effect on HSV-1. To clarify what causes this inhibitory activity on HSV-1, a metabolic profile of the plant was performed. Three main fractions: non-polar substances, polar metabolites and phenolic compounds were obtained and GC-MS analysis was carried out. Since it is well known that phenolic compounds show a significant anti-herpes effect and that viral DNA polymerase (DNApol) appears to play a key role in HSV virus replication, we present a docking and quantum-chemical analysis of the binding of these compounds to viral DNApol amino acids. Fourteen different phenolic acids found by GS/MS analyses, were used in molecular docking simulations. According to the interaction energies of all fourteen ligands in the DNApol pockets based on docking results, DFT calculations were performed on the five optimally interacting with the receptor acids. It was found that hydroxybenzoic acids from phenolic fraction of Graptopetalum paraguayense E. Walther show a good binding affinity to the amino acids from the active site of the HSV DNApol, but significantly lower than that of acyclovir. The mode of action on virus replication of acyclovir (by DNApol) is different from that of the plant phenolic acids one, probably.

The experience gained over the last hundred years clearly indicates that two groups of viruses represent the main risk for the development of highly transmissible epidemics and pandemics in the human species: influenza viruses and coronaviruses (CoV). Although the search for viruses with pandemic potential in the environment may have an important predictive and monitoring role, it is still based on empirical methodologies, mostly translated from the clinic and not fully validated for environmental matrices.As far as the SARS-CoV-2 pandemic, currently underway, is concerned, environmental monitoring activities aiming at checking the presence of SARS-CoV-2 in wastewater can be extremely useful to predict and control the diffusion of the disease. For this reason, the present study aims to evaluate the SARS-CoV-2 diffusion by means of a wastewater-based environmental monitoring developed in Piedmont, N-W Italy, during the pandemic second and third waves. Sampling strategies, sampling points, sample pre-treatments and analytical methods have been developed and validated to give representative and reliable results. The outcomes highlighted by the present paper demonstrate a strong correlation between SARS-CoV-2 concentration in untreated wastewater and epidemic evolution in the considered areas as well as a predictive potential that could provide decision-makers with indications for establishing effective policies to mitigate the effects of the ongoing pandemic and to prepare response plans for future pandemics that could certainly arise in the decades to come.Moreover, the study highlights the potential of wastewater treatment plants to degrade the genetic material referable to SARS-CoV-2 as well.In conclusion, the preliminary data reported in the present paper, although they need to be complemented by further studies considering other geographical regions as well, are very promising.

In open, sustainable policymaking, we are expecting to develop the valuable results that will bring us closer to a fairer and more balanced society. One way to involve the public in these processes is to engage them in online e-participation projects. Despite the hopes, empirical analyses show that many e-participation initiatives have failed to deliver expected benefits. Revealing what actually works in examined projects and what requires improvement would allow for better policy planning in the future. In this article, I made an attempt to identify and assess the cognitive processes enabling emergence of collective intelligence (CI) in a singular e-participation project. For this reason, I worked out and tested an evaluation technique, combining the MILCS framework for group cognition and the results of empirical research on CI. A case study method based on semi-structured interviews was selected to evaluate a sample participatory budgeting initiative, Civic Budget of the City of Kraków. Results reveal that most cognitive processes are working satisfactorily, but the real problem is using collective memory, which works only to a very limited extent. A guideline for future policymakers should be to develop a shared memory system, to which all community members should have access.

Through the half-unit circle area computation using the integration of the corresponding curve power series representation, we deduce a slow converging positive infinite series to $\pi$. However, by studying the remainder of that series we establish sufficiently close inequalities with equivalent lower and upper bound terms allowing us to estimate, more precisely, how the series approaches $\pi$. We use the obtained inequalities to compute up to four-digit denominator, what are in this sense, the best rational numbers that can replace $\pi$. It turns out that the well-known convergents of the continued fraction of $\pi$, $22/7$ and $355/113$ called, respectively, Yuel\"{u} and Mil\"{u} in China are the only ones found. Thus we apply a similar process to find rational estimations to $\pi+e$ where $e$ is taken as the power series of the exponential function evaluated at $1$. For rational numbers with denominators less than $2000$, the convergent $920/157$ of the continued fraction of $\pi+e$ turns out to be the only rational number of this type.

Epithelial-mesenchymal transition (EMT) is a cellular biological process involved in migration of primary cancer cells to secondary sites facilitating metastasis. Besides, EMT also confers properties such as stemness, drug resistance and immune evasion which can aid a successful colonization at the distant site. EMT is not a binary process; recent evidence suggests that cells in partial EMT or hybrid E/M phenotype(s) can have enhanced stemness and drug resistance as compared to those undergoing a complete EMT. Moreover, partial EMT enables collective migration of cells as clusters of circulating tumor cells or emboli, further endorsing that cells in hybrid E/M phenotypes may be the ‘fittest’ for metastasis. Here, we review mechanisms and implications of hybrid E/M phenotypes, including their reported association with hypoxia. Hypoxia-driven activation of HIF-1α can drive EMT. In addition, cyclic hypoxia, as compared to acute or chronic hypoxia, shows the highest levels of active HIF-1α and can augment cancer aggressiveness to a greater extent, including enriching for a partial EMT phenotype. We also discuss how metastasis is influenced by hypoxia, partial EMT and collective cell migration, and call for a better understanding of interconnections among these mechanisms. We discuss the known regulators of hypoxia, hybrid EMT and collective cell migration and highlight the gaps which needs to be filled for connecting these three axes which will increase our understanding of dynamics of metastasis and help control it more effectively.

In this study, we first present a time-fractional L$\hat{e}$vy diffusion equation of the exponential option pricing models of European option pricing and the risk-neutral parameter. Then, we modify a particular L$\hat{e}$vy-time fractional diffusion equation of European-style options. Introduce a more general model from the models based on the L$\hat{e}$vy-time fractional diffusion equation and review some recent findings regarding of the Europe option pricing of risk-neutral free.

Escherichia coli or E. coli is a member of the fecal coliform group and is a more specific indicator of fecal contamination than other fecal coliform species, its presence indicate possibly presence of harmful bacteria which will cause diseases and it also suggests the extent as well as the nature of the contaminants. E. coli bacteria able to survive in water for 4 – 12 weeks and at present, it appears as an indicator to provide the accurate bacterial contamination of fecal matter in drinking water, because of the availability of simple, affordable, fast, sensitive and exact detection techniques. According to the laboratory experiment based techniques, 24 - 48 hours are required for the bacterial concentration to be reported. So, there is a necessity for continuous monitoring. Techniques for detection of many pathogenic bacterial strains are not yet available, sometimes days to weeks are required to get the results. To overcome the difficulties, expensive and time-consuming techniques are required to detect, count and identify the presence of specific bacterial strain. Public health relies on online monitoring of water quality that depends majorly on examination of fecal indicator bacteria, thus protection of health requires fecal pollution indicator so that it is not required to analyze drinking water to overcome the problems associated with waterborne diseases. This paper will brief the classification, sources, survival of E. coli bacteria and its correlation with basic water quality parameters in water sources.```

Hepatitis E virus (HEV) is responsible for large waterborne epidemics of hepatitis in endemic countries and is an emerging zoonotic pathogen worldwide. In endemic regions, HEV-1 or HEV-2 genotypes are frequently associated with fulminant hepatitis in pregnant women, while with zoonotic HEV (HEV-3 and HEV-4), chronic cases of hepatitis and severe neurological disorders are reported. Hence, it is important to characterize the interactions between HEV and its host. Here, we investigated the ability of the non-structural polyprotein encoded by the first open reading frame (ORF1) of HEV to modulate the host early antiviral response and in particular the type I interferon (IFN-I) system. We found that the amino-terminal region of HEV-3 ORF1 (MetPCP), containing a putative methyltransferase (Met) and a papain-like cysteine protease (PCP) functional domain, inhibited IFN-stimulated response element (ISRE) promoter activation and the expression of several IFN-stimulated genes (ISGs) in response to IFN-I. We showed that the MetPCP domain interfered with the Janus kinase (JAK)/signal transducer and activator of transcription protein (STAT) signalling pathway by inhibiting STAT1 nuclear translocation and phosphorylation after IFN-I treatment. By contrast, MetPCP had no effect on STAT2 phosphorylation and a limited impact on the activation of the JAK/STAT pathway after IFN-II stimulation. This inhibitory function seemed to be genotype-dependent as MetPCP from HEV-1 had no significant effect on the JAK/STAT pathway. Overall, this study provides evidence that the predicted MetPCP domain of HEV ORF1 antagonises STAT1 activation to modulate the IFN response.

Public participation is significant for the success of any urban planning project. However, most members of the general public are not planning professionals and may not understand the technical details of a 2D paper-based plan, which might hamper their participation. One way to expand the participation of citizens is to present plans in well-designed, user-friendly and interactive platforms that allow participation regardless of the technical skills of the participants. This paper investigates the impacts of the combined use of 3D visualization and E-participation on public participation in Kisumu, Kenya. A 3D City model, created with CityEngine2016, was exported into a web-based geo-portal and used as a Planning Support System in two stakeholder workshops in order to evaluate its usability. For e-participation, 300 questionnaires given out to planning practitioners. Five indicators were developed for evaluating the usability of the 3D model while the usability of e-participation was evaluated using communication, collaboration and learning as indicators. Results showed that effectiveness and efficiency varies within different professional groups while the questionnaires showed strong preference for e-participation methods, especially SMSs/USSDs and emails. The study concludes that the use of 3D visualization and E-participation has the potential for improving the quality and quantity of public participation and recommends further research on the subject.

Mungbean [Vigna radiata (L.) Wilczek] in Australia has been transformed from a niche opportunistic crop into a major summer cropping option for dryland growers in the summer-dominant rainfall regions of Queensland and New South Wales. This transformation followed stepwise genetic improvements in both grain yields and disease resistance. For example, more recent cultivars such as ‘Crystal’, ‘Satin II’ and ‘Jade-AU‘ have provided up to a 20% yield advantage over initial introductions. Improved agronomic management to enable mechanised management and cultivation in narrow (<50 cm) rows has further promised to increase yields. Nevertheless, average yields achieved by growers for their mungbean crops remain less than 1 t/ha, and are much more variable than other broad acre crops. Further increases in yield and crop resilience in mungbean are vital. In this review, opportunities to improve mungbean have been analysed at four key levels including phenology, leaf area development, dry matter accumulation and its partitioning into grain yield. Improving the prediction of phenology in mungbean may provide further scope for genetic improvements that better match crop duration to the characteristics of target environments. There is also scope to improve grain yields by increasing dry matter production through the development of more efficient leaf canopies. This may introduce additional production risks as dry matter production depends on the amount of available water, which varies considerably within and across growing regions in Australia. Improving crop yields by exploiting photo-thermal sensitivities to increase dry matter is likely a less risky strategy for these variable environments. Improved characterisation of growing environments using modelling approaches could also better define and identify the risks of major abiotic constraints. This would assist in optimising breeding and management strategies to increase grain yield and crop resilience in mungbean for the benefit of growers and industry.

The rapid growth of e-commerce has transformed customer behaviours, demanding deeper insights into how demographic factors shape online user preferences. To understand the impact of these changes, this study performs a threefold analysis. Firstly, the study investigates how demographic factors (e.g., age, gender, education, income) influence e-customer preferences in Serbia. From a sample of n = 906 respondents, we test conditional dependencies between demographics and user preferences – “purchase frequency”, “the most important property when buying for the first time”, “the most important property before repeating a purchase”, and “reasons for quitting an online purchase”. From a hypothetical framework of 24 tested hypotheses, the study successfully rejects 8/24 (with p < 0.05), suggesting a high association between demographics with purchase frequency (p < 0.01) and reasons for quitting the purchase (p < 0.01). However, although reported test statistics suggest an association, understanding how interactions between categories shape e-customer profiles is lacking. As a consequence, the second part considers an MCA-HCPC (Multiple Correspondence Analysis with Hierarchical Clustering on Principal Components) to identify user profiles. The analysis reveals three main clusters : (1) young female unemployed e-customers driven mainly by customer reviews; (2) retirees and older adults with infrequent purchases, hesitant to buy without experiencing the product in person; (3) employed, highly educated, male midlife adults who prioritise fast and accurate delivery over price. In the third stage, the study uses identified clusters as labels for Machine Learning (ML) classification through the following algorithms: Gradient Boosting Machine (GBM), Decision Tree (DT), k-Nearest Neighbors (kNN), Gaussian Naïve Bayes (GNB), Random Forest (RF) and Support Vector Machine (SVM). The results suggest high classification performance of GBM (AUROC = 0.994), RF (AUROC = 0.994) and SVM (AUROC = 0.902) in identifying user profiles. Lastly, after performing Permutation Feature Importance (PFI), the findings suggest that age, work status, education, and income are the main determinants of shaping e-customer profiles and developing marketing strategies.

Mono-crop plantation widely found in the world and dominated by few species such as Eucalyptus, Pinus and Tectona. While they lack diversified product, negative to environmental service and limited forest product for local use. The experiment was designed to evaluate the impact of mixed plantings on the early growth performance of the E. globulus tree species. The treatments included one monoculture of E. globulus and a combination of the plant with three other native and one foreign tree species. In four consecutive years after plantation, height, root collar diameter, DBH and leaf/branch count were measured. Following two years of out planting, the survival rates of seedlings were determined. Destructive sampling was applied to measure biomass of E. globulus. The growth performance of E. globulus in mixed plantations was compared to that of trees produced in pure plantations. The findings showed that there were no significant variations in growth parameters across the treatments. Following two years of out planting, the survival rates of seedlings were determined. The growth performance of E. globulus in mixed plantations was compared to that of trees produced in pure plantations. The findings showed that there were no significant variations in growth parameters across the treatments. The survival rate of E. globulus was good, ranging from 75 to 96.8%. Similarly, the growth performance of E. globulus's root collar diameter was larger even if the trial did not reveal a significant difference between the treatments for height. In comparison to other treatments, the one that included junipers and E. globulus had a higher mean height throughout the course of three years (1.28, 2.53, and 6.12 meters, respectively), as well as a lower RCD in the first and third years (1.3 and 5.34 cm). At year four, E. globulus attain higher in Height and DBH with high growth rate in mixed plantations compared to pure stands. The relative yield of E. globulus in pure stands compare to mixed stands greater than 1. Above and below ground biomass and carbon density of E, globulus is comparable in all treatment. Overall, the study's findings confirm that planting E. globulus improves its mingling with the examined tree species. Such studies ought to be conducted again over a longer time frame in order to examine the effects at a later stage and recommend technologies for broader implementation.

AI-driven tools can identify nursing students' strengths and weaknesses, thus enabling the development of customized learning plans that target specific areas for improvement. This targeted approach can enhance knowledge retention and skill development, resulting in better prepared healthcare professionals. Nursing students are required to overcome their own psychological stress during their internship in order to understand sick children’s emotional reactions, as well as to be able to interact and communicate with such children. The application of AI picture-based teaching e-books helps nursing students to understand how to use therapeutic games to improve communication with sick children. A comparison of the differences between nursing teachers’ self-efficacy scores and nursing students’ application of AI picture-based teaching e-books (experimental group) and narrative handouts (control group) was achieved via therapeutic games to deal with sick children’s fear of medical examinations and treatments. In addition, a comparison was also conducted on the differences between the impact of the self-efficacy of the experimental group and that of the control group in dealing with sick children’s behavioral responses with respect to fears of medical examinations and treatments. This study is a quasi-experimental study, in which the self-efficacy scores of 30 nursing students were collected and analyzed in both the experimental group and the control group before and after intervention in dealing with sick children’s behavioral responses to fears of medical examinations and treatments. It was found that the self-efficacy score of the experimental group was higher than that of the control group (β coefficient is 0.356) when assessing the self-efficacy scores and behavior of the experimental and control groups in dealing with sick children’s fears of medical examinations and treatments through one-way analysis of covariance (one-way ANCOVA), moreover, a statistically significant difference (p < 0.05) was observed. The experimental group’s score of behavioral responses to the fears of sick children to examinations and treatments was lower than that of the control group (β coefficient was -1.540), wherein a statistically significant difference (p < 0.05) was shown. The self-efficacy of the experimental group in dealing with sick children’s fears of medical examinations and treatments had a statistically significant impact on the sick children’s behavioral responses to the fear of medical examinations and treatments (p < 0.05). In addition, the higher the self-efficacy scores of the experimental group in dealing with sick children’s fear of medical examinations and treatments, the lower the sick children’s behavioral responses to fears of medical examinations and treatments (the β coefficient was -0.914), the control group’s self-efficacy scores in dealing with sick children’s fears of medical examinations and treatments did not have a statistically significant impact on the sick children’s behavioral responses to fears of medical examinations and treatments (p > 0.05). This study proves that the application of AI picture-based teaching e-books by nursing teachers is more effective than narrative handouts in improving nursing students’ self-efficacy when using therapeutic games to deal with, as well as reduce, sick children’s fears of medical examinations and treatments.

The integration of Augmented Reality (AR) in e-commerce has emerged as a transformative development, reshaping how consumers interact with online retail environments. This research explores the impact of AR on e-commerce by examining its effects on consumer behavior, purchase decisions, and overall shopping experience. Through a series of interviews with industry experts, the study uncovers key insights into how AR enhances product visualization, leading to improved consumer confidence and a reduction in return rates. The immersive and interactive nature of AR applications has been shown to significantly increase consumer engagement and conversion rates, as users are able to interact with products in a virtual setting that simulates real-world experiences. Despite these advantages, the research also highlights several challenges associated with AR implementation, including the high costs of development and maintenance, difficulties in integrating AR technology with existing e-commerce platforms, and concerns regarding privacy and data security. The study further explores the varying applications of AR across different sectors within e-commerce, such as fashion, furniture, and cosmetics, each benefiting from unique AR functionalities. Looking ahead, the potential for AR to be enhanced by emerging technologies like Artificial Intelligence and the Internet of Things is discussed, with implications for future advancements in the field. Overall, the research demonstrates that while AR offers significant benefits for enhancing online shopping experiences, addressing its associated challenges is crucial for its successful and widespread adoption.

This qualitative research explores Supplier Relationship Management (SRM) practices within the e-commerce fashion industry, aiming to uncover key strategies and their impacts. Through semi-structured interviews with supply chain managers, procurement officers, and supplier representatives, critical themes emerged: communication, trust, risk management, sustainability, and digital technologies. Effective communication, characterized by transparency and regular updates, emerged as pivotal for aligning expectations and resolving issues promptly. Trust-building practices, including fair dealings and formal agreements, were essential in fostering long-term partnerships, reducing transaction costs, and enhancing collaboration. Robust risk management strategies, such as supplier diversification and contingency planning, were identified as crucial for mitigating disruptions and ensuring supply chain resilience. Sustainability was highlighted as a strategic imperative, driven by ethical sourcing and environmental standards, supported by technologies like blockchain for transparency. The transformative role of digital technologies—supply chain management software, blockchain, IoT, and data analytics—was evident in enhancing visibility and decision-making across global supply chains. Viewing suppliers as strategic partners, rather than mere vendors, promoted collaborative innovation and mutual growth. Despite challenges like cultural differences and regulatory complexities, opportunities exist to enhance SRM through integrated best practices. By prioritizing effective communication, trust-building, risk management, sustainability, and digital innovation, companies can strengthen supplier relationships, optimize supply chain performance, and achieve competitive advantage in the e-commerce fashion sector.

This qualitative study explores the pivotal role of Supplier Relationship Management (SRM) in enhancing resilience within e-commerce supply chains. In an era marked by rapid digital transformation and global interconnectedness, the resilience of supply chains has become a strategic imperative for organizations striving to maintain operational efficiency and meet customer expectations. Through semi-structured interviews with supply chain managers, procurement officers, and strategic sourcing specialists across diverse industries, this research investigates the strategies, challenges, and outcomes associated with SRM practices. Findings reveal that effective communication and collaboration are fundamental to successful SRM, fostering trust, transparency, and responsiveness in supplier relationships. Strategic risk management through proactive identification and mitigation strategies enables organizations to navigate uncertainties such as economic fluctuations and geopolitical tensions. SRM implementation yields significant organizational benefits, including improved supply chain efficiencies, enhanced product quality, and increased customer satisfaction. However, challenges such as technological complexities, cultural differences among global suppliers, and regulatory compliance issues underscore the need for adaptive strategies and digital investments. The integration of digital technologies such as AI and blockchain enhances SRM effectiveness by enabling real-time data exchange, predictive insights, and decision-making capabilities. Ultimately, SRM emerges as a cornerstone of sustainable growth and competitive advantage in e-commerce, empowering organizations to optimize supply chain performance and resilience amidst dynamic market conditions.

This study explores the strategic importance of leveraging supplier relationships for competitive advantage in the e-commerce industry. Strong supplier relationships are crucial for enhancing operational efficiencies, cost management, quality assurance, innovation, sustainability, and overall supply chain resilience. Through collaborative partnerships, e-commerce companies can streamline logistics, reduce costs, ensure consistent product quality, and foster innovation through joint development initiatives. Ethical sourcing and sustainable practices play a pivotal role in supplier relationship management (SRM), aligning with consumer expectations and enhancing brand reputation. Advanced technologies such as AI, blockchain, and IoT further transform SRM practices by improving transparency, efficiency, and decision-making capabilities across the supply chain. The study also discusses challenges in managing global supplier relationships, emphasizing the importance of effective communication, cultural sensitivity, and strategic risk management. By addressing these challenges and nurturing trust-based relationships with suppliers, e-commerce firms can navigate market complexities and achieve sustainable growth. This research provides insights for e-commerce companies seeking to optimize their supplier relationships and maintain competitive advantage in a dynamic market environment.