Traditional Romanian food products are an integral part of local culture and spirituality. These food traditions have been formed over the centuries and represent a particularly important part for the development of a circular economy in rural areas. In order to contribute to the development of this sector of activity; we conducted a study on consumer perception of traditional Romanian food products. The purpose of this work was to identify the structure of the studies and the future directions of research related to the image of traditional food products through the bibliometric study as well as the identification of consumer trends of these products through a survey based on the questionnaire. The results obtained indicate that traditional Romanian food products are consumed by the majority of respondents participating in the survey and that this sector of activity has continuity in its development and presents a clear interest among citizens.

While digitization can make the health industry faster and more efficient, there are many financial, social and organizational obstacles and barriers to its implementation. This article offers a systematic review of the main troubles detected from the literature review. Also there is a proposal of new kind of restrictions to pay attention. Finally, its offer an heterodox reading about the problem analyzed.

L-gulonolactone oxidase enzyme (GULO) catalyzes the last step of L-ascorbic acid (vitamin C) biosynthesis. This enzymatic activity is lost in primates. The full-length rat GULO has been previously produced in plants and demonstrated to be active. In this study, we compare activity of two variants of GULO produced in Escheriachia coli cells, full-length rat GULO (fGULO) and its C-terminal catalytic domain (cGULO). The expression and purification of the recombinant proteins were optimised and their biological activity was confirmed by two methods, the GULO activity assay in the protein extracts and the ‘in-gel’ staining for GULO activity. Both variants of recombinant GULO were biologically active in both assays. However, cGULO is more promising than fGULO for ascorbic acid production because it is more efficiently produced by bacteria.

Long noncoding RNAs (lncRNAs) are known to play key roles in breast cancers; however, detailed mechanistic studies of lncRNA function have not been conducted in large cohorts of breast cancer tumors, nor have inter-donor and inter-subtype variabilities been taken into consideration. Here we provide the first identification and annotation of the human BORG lncRNA gene. Using multiple tumor cohorts of human breast cancers, we show that while BORG expression is strongly induced in breast tumors as compared to normal breast tissues, the extent of BORG induction varies widely between breast cancer subtypes and even between different tumors within the same subtype. Elevated levels of BORG in breast tumors are associated with the acquisition of core cancer aggression pathways, including those associated with basal tumor and pluripotency phenotypes, and with epithelial-mesenchymal transition (EMT) programs. While a subset of BORG-associated pathways was present in high BORG-expressing tumors across all breast cancer subtypes, many were specific to triple-negative breast cancer tumors. Finally, we show that genes induced by heterologous expression of BORG in murine models of TNBC both in vitro and in vivo strongly overlap with those associated with high BORG levels in human TNBC tumors, indicating that human BORG is a novel driver of the highly aggressive basal TNBC tumor phenotype.

The development of ballistic protection vests (BPVs) has become increasingly significant, particularly in the design of soft panels, which are critical to the overall size and configuration of these vests. Despite their importance, a standardized design process for soft panels is lacking in the literature. This research addresses this gap by creating soft panels tailored to the body types of regional soldiers while adhering to relevant standards. We propose a comprehensive design algorithm and evaluate the applicability of the National Institute of Justice (NIJ) standard 0101.06 test templates for configuring these panels. This study aims to design soft ballistic panels for BPVs that cater to the body type requirements of regional soldiers and comply with NIJ 0101.06 standards. We have developed an algorithm for designing soft panels and analyzed the feasibility of using NIJ test templates for their configuration. The research encompasses a detailed literature review, analysis of existing BPV soft panels, and comparison with NIJ test templates. The panels were designed and scaled using computer-aided design (CAD) systems and evaluated through by physical fitting on mannequins and virtual fitting using the Clo3D program. Our findings indicate that the NIJ standard test templates are only partially applicable to the design of soft panels. The developed methodology includes an algorithm and size specifications tailored to regional covers. A coefficient (K) was identified to calculate the soft panel surface area prior to design, thereby saving time and resources.

We report the detection of live Escherichia coli (E. coli) in liquid samples using a biosensor based on a field effect transistor (FET) biosensor with B/N co-coped graphene oxide (GO) gel (BN-GO) as the transducer material. The FET was functionalized with antibodies to detect E. coli K12 O-antigens in phosphate-buffered saline (PBS). The biosensor detected the presence of planktonic E. coli bacterial cells within a mere 2 minutes. The biosensor exhibited a limit of detection (LOD) of 10 cells per sample, which can be extrapolated to a limit of detection at the level of a single cell per sample and a detection range of at least 10– 108 CFU/mL. The selectivity of the biosensor for E. coli was demonstrated using Bacillus thuringiensis (B. thuringiensis) as a sample contaminant. We also present a comparison of our functionalized BN-GO FET biosensor with established detection methods of E. coli k12 bacteria, as well as with state-of-the-art detection mechanisms.

In the context of global warming and increasing scarcity of fresh water resources, it becomes significant to evaluate the contribution and evolution of non-rainfall waters such as dew. This study therefore aims to evaluate the relative dew and rain contributions in three sites of south-western of Madagascar (Ifaty, Toliara and Andremba), a semi-arid region which suffers from a strong water deficit. The studied period is 1/1991 – 7/2023, with extrapolation to 8/2033. Dew is calculated from meteo data by using a well-established energy model. The extrapolation of dew and rain follows an artificial neural network approach. It is found that dew forms regularly (2-3 days in average between events), in contrast to rain (10-15 days). The evolutions of dew and rain are similar, with an increase from 1991 to 2000, a decrease up to 2020 and a further increase until 2033. These oscillations follow the Indian Ocean dipole variations and should be influenced by the climate change. Dew contribution to the water balance remains modest on a yearly basis (3-4%) but is important during the dry season (Apr.-Oct.), up to 30%. Dew therefore appears to be a reliable and sustainable resource for plants, small animals and population, especially during droughts.

The study is based on information as the property of matter and its evolution from chemical to digital information. Consequences of these forms of information include molecular, modular, cel-lular, non-human, and human individual interactions, as well as human-machine interaction, and the formation of corresponding modules through self-organizing selective processes. The function of modular structures is decision-making and is analogous to the behavior of an intelligent agent. The evolutionary modular model is proposed based on the interaction of evolutionary factors (matter, energy, information, self-organization, natural selection, and heritability) among themselves and with the arrow of time. In conclusion, we realize that the essence of the evolution of living organ-isms is modular evolution. Modules through which the survival and reproduction of living organ-isms is ensured, are formed by two basic molecular processes, which are molecular recognition or information and modular self-organization.

The aim of the study was to assess the effects of an 8-week cognitive-motor training program on postural control and knee proprioception under single and dual-task conditions. Design: Randomized clinical trial. Methods: 20 healthy and physically active older adults (73.255.98 years) volunteered to participate and were randomly assigned into an experimental and a control group (EG and CG). Postural control was measured with the Romberg test, with open (RBOE), closed eyes (RBCE) and under unipodal dominant side (RUDL) conditions. Proprioception was assessed by measuring participants’ ability to reposition their dominant knee at 45º. Finally, performance on the cognitive task was measured through a subscale of the Barcelona Test called “categorical evocation in associations.” The EG and the CG completed 8-week training programme with two sessions the 30 minutes per week of postural control and proprioception exercises. The EG additionally included music in each session. Results: The results showed significant differences in both group at the postural control tests (RBOE and RBCE) and proprioceptive test post intervention. Conclusion: The 8-week training program had a positive impact on the post-intervention results for motor control and proprioception, but not on the results of the cognitive task. There were no significant differences between the groups that carried out sessions with or without music.

Money demand is the amount of real money balance with people and they can decide at any time what part of their assets to keep in cash. In this study, money was assumed to be a durable good that leads to the flow of some kind of service. Therefore, money became a function of utility. Using AIDS elasticity demand function, income, price and cross elasticities were evaluated. The statistics of this study are related to the years 2003-2022. The results showed that, based on the assumption of three goods, the demand includes bills and negotiable instruments, demand deposits, and time deposits. Based on the limitation of symmetry, collectability and homogeneity, the tensions can be calculated. The results showed that the price elasticity of demand for banknotes and muskox with term deposits is not significant. On the other hand, the cross tension between sight deposits and term deposits is negative and significant.

Abstract: (1) Background: to find out how COVID-19 infection during pregnancy affects the outcome of the pregnancy; (2) Methods: 166 SARS-CoV-2-positive pregnant women formed the study group. 128 SARS-CoV-2-negative pregnant women formed the control group. Anatomopathological study of the placenta was performed in all cases; (3) Results: Placental insufficiency appeared in 38 patients (22.9%) of the study group and in 17 patients (13.2%) in the control group (p=0.016). Villitis appeared in 50 patients (30.1%) of the study group and in 16 (12.6%) in the control group (p=0.000). 166 COVID-19 positive patients were further subdivided, into those with anatomopathological affection of the placenta, and those without. When gestational age between patients with placental insufficiency and those without it are compared, a difference of 4.38 days is obtained (p=0.0393). If we compare neonatal weight between patients with placental insufficiency and those without it, a difference of 406.4 grams is obtained (p=0.0000). When gestational age between patients with villitis and those with-out it are compared, a difference of 3.2 days is found (p=0.0919). When neonatal weight between patients with villitis and those without it are compared, a difference of 242.2 grams is obtained (p=0.0018). (4) Conclusions: COVID-19 infection during pregnancy may produce lower fetal weight and shorter gestational length.

This qualitative study explores the relationship between supply chain responsiveness (SCR) and customer loyalty within the e-commerce sector. E-commerce has revolutionized global commerce, driven by technological advancements and shifting consumer behaviors. Central to e-commerce success is the ability to meet customer expectations swiftly and reliably, necessitating agile supply chain management (SCM) practices. SCR in e-commerce encompasses the capacity to adapt to dynamic market demands, minimize disruptions, and enhance customer satisfaction through efficient logistics, inventory management, and last-mile delivery. Through in-depth interviews with customers, e-commerce platform managers, and supply chain practitioners, this study investigates key themes, challenges, strategies, and impacts associated with SCR and customer loyalty. Findings reveal that customers prioritize fast order fulfillment, reliable service quality, personalized experiences, and trustworthy interactions, all of which significantly influence their loyalty and advocacy behaviors. Challenges identified include inventory management complexities, logistical hurdles in last-mile delivery, and the need for effective supplier communication. Strategic approaches to enhance SCR include leveraging data analytics for demand forecasting, adopting agile SCM practices, integrating customer feedback into service improvements, and fostering collaborative relationships with suppliers. These strategies not only optimize operational efficiency but also cultivate enduring customer relationships based on satisfaction, trust, and loyalty. The study concludes that improved SCR practices lead to increased customer satisfaction, repeat purchases, and positive word-of-mouth, thereby strengthening competitive advantage and sustainability in the e-commerce marketplace.

Grayscale Lithography (GSL) is an alternative approach to the standard Binary Lithography in MEMSfabrication, enabling the fabrication of complicated arbitrary 3D structures on the wafer, without the need for multiple masks and exposure steps. Despite its advantages, GSL’s effectiveness is highly dependent on controlled lab conditions, equipment consistency, and finely-tuned photoresist exposure and etching processes. This works presents a thorough investigation of the challenges of GSL for Silicon (Si) wafers and presents a detailed approach on how to minimize the fabrication inaccuracies, aiming to replicate the intended design as closely as possible. Utilizing a maskless laser writer, all aspects of the GSL as analyzed, from photoresist (PR) exposure parameters to Si etching conditions. A practical application of GSL is demonstrated in the fabricationof 4 μm deep Silicon Fresnel Lenses for Long Wave Infrared imaging (8-12 μm). The surface topography of a Fresnel lens is a good case to apply GSL as it has varying shapes and size features that need to be preserved.. The final fabricated lens profiles show good match with the initial design and demonstrate successful etching of coarse and fine features and demonstrating images taken with an LWIR camera.

Interaction with social agents employing natural language have been discussed especially since Weizenbaum (1966) observed the social effects of his chatbot named 'Eliza', which imitated a cli-ent-centered conversation. With Nass and Reeves’ media equation theory and computers as social actors paradigm, a well-tested framework has been introduced to the study of human-computer interaction. In the 1990s, there was a renewed focus on natural language analysis, which has be-come a crucial area of research in machine learning. Recent advancements in data processing and storage capacities have led to the development of AI-generated utterances that closely resemble human utterances. As a result, AI-based systems can now mimic social relationships to a signifi-cant extent. In light of these technological developments, the article explores whether quasi-social relationships should be considered within the field of social psychology and examines the poten-tial advantages and challenges of this approach.

Ulcerative colitis (UC) is a chronic inflammatory disease, the incidence of which is increasing worldwide. However, the etiology and pathogenesis of UC remains unclear. The n-butanol extract of pulsatilla decoction (BEPD) of the traditional Chinese medicine herbal formula has been shown to be effective in treating UC. We aimed to explore the molecular mechanism underlying the effects of BEPD on UC, in particular its effects on neutrophil extracellular trap (NET) formation by neutrophils. High-performance liquid chromatography was used to determine the principal compounds of BEPD. UC was induced in mice using dextran sodium sulfate, and mice were treated with 20, 40, or 80 mg/kg BEPD daily for seven days. Colonic inflammation was determined by assessing the disease activity index, histopathology, colonic mucosal damage index, colonic mucosal permeability, and pro- and anti-inflammatory cytokine levels. The infiltration and activation status of neutrophils in the colon were determined by analyzing the levels of chemokine (C-X-C motif) ligand (CXCL)1 and CXCL2, reactive oxygen species, Ly6G, and numerous NET proteins. Our results showed that BEPD improved the disease activity index, histopathology, and colonic mucosal damage index scores of mice with UC, and restored colonic mucosal permeability compared with untreated mice. The expression levels of the pro-inflammatory cytokines interleukin-1β, interleukin-6, and tumor necrosis factor-α in colon tissues were significantly decreased, while the expression levels of anti-inflammatory cytokines in colon tissues were significantly increased, exceeding those of control mice. In addition, BEPD reduce the expression of the neutrophil chemokines CXCL1 and CXCL2 in the colon tissue of mice with UC, reduced neutrophil infiltration, reduced reactive oxygen species levels, and significantly reduced the expression of NET proteins. BEPD also significantly reduced NET formation. The results of this study suggest that BEPD exerts therapeutic effects in a murine model of UC by inhibiting neutrophil infiltration and activation in the colon, as well as by inhibiting the expression of key proteins involved in NET formation and reducing NET formation, thereby alleviating local tissue damage and disease manifestations.

Taiwan's bed and breakfast (B&B) development has been more than 25 years ago, from the first generation of retirement to the B&B industry, serving tourists from all over the world accom-modation, providing breakfast and accommodation mode to the present, after the change of employees from the second generation, more and more attention is paid to the cultivation and cultivation of business ability. With the advent of the era of AI technology networking, the ca-pabilities required for B&B operation are more focused on all aspects of service, and the good marketing ability of B&B can promote a green chimney-free tourism economy, which is also a favorite industry of various governments and the public. This study explores the basic vocational competency indicators required for running a B&B, with (1)EQ emotion management skills, (2)Financial management ability, (3)(SK) technical skills, and (4)Marketing and promotion management capabilities. Through the study method, the K-S Z test was determined by the con-sensus conclusion of expert reliability and validity p value

With advancements in digital technologies such as 5G communications, big data, and cloud computing, the components of network operation systems have become increasingly complex, significantly complicating system monitoring and maintenance. Correspondingly, automated log anomaly detection has become a crucial means to ensure stable network operation and protect them from malicious attacks or failures. Conventional machine learning and deep learning methods assume consistent distributions between the training and testing data, adhering to a closed-set recognition paradigm. Nevertheless, in realistic scenarios, systems may encounter new anomalies that were not present in the training data, especially in log anomaly detection. Inspired by evidential learning, we propose a novel anomaly detector called LogEDL, which supervises training of the model through an evidential loss function. Unlike traditional loss functions, the evidential loss function not only focuses on correct classification, but also quantifies the uncertainty of predictions. This enhances the robustness and accuracy of the model in handling anomaly detection tasks, while achieving functionality similar to open-set recognition. To evaluate the proposed LogEDL method, we conduct extensive experiments on three datasets, i.e., HDFS, BGL, and Thunderbird, to detect anomalous log sequences. Experimental results demonstrate that our proposed LogEDL achieves state-of-the-art performance in anomaly detection.

The practice of stormwater management has evolved from a singular focus on drainage to a multifaceted approach to support integrated urban development. By contributing to healthy, livable, ecological, and water sensitive cities, it is a key tool to promote Sustainable Development Goal 11 from neighborhood to metropolitan scales. A review of the knowledge base for stormwater management shows several attributes that favor an integrative approach to achieve co-benefits across several sectors. Functional areas of its contributions include drainage, flood control, flood plain management, water quality control, urban ecology, recreation, and city beautification. Legacy path dependance affects the potential to reform land use practices, while stormwater management practice is being affected by climate change, sea level rise, urbanization, inequality, and poor governance. Technical methods for stormwater management are well advanced, but integrative frameworks to address social, ecological and infrastructure needs are more challenging. The sensitivity of ecological issues is most evident in cities in coastal zones. Organizational initiatives are needed to counter neglect of essential maintenance and sustain flood risk reduction in cities. Stormwater management is related to other integrative tools, including IWRM, One Water, One Health, and integrated flood management, as well as the broader concept of urban planning. Stormwater capture and rainfall harvesting offer major opportunities to augment scarce water supplies. Nature-based solutions like low-impact development and the Sponge City concept show promise to transform cities. Major cities face challenges to sustain conveyance corridors for major flows and to store and treat combined sewer runoff. The neighborhood focus of stormwater management elevates the importance of participation and inclusion to advance environmental justice and strengthen social capital. Integrating organizational initiatives from local to city scale and funding improvements to stormwater systems are major challenges that require leadership from higher governance levels, although governments face resistance to change toward integration, especially in countries with poor land use and public works management systems. Finding solutions to neighborhood issues and the connectivity of water systems at larger scales requires complex approaches to urban planning and represent an important agenda for urban and water governance going forward.

The effort to expand the U.S. study abroad programs to have a global impact has never been fully expressed by Higher Education Institutions (HEIs) and study abroad administrators. Study Abroad since its inception has not been a truly global platform. This article constructively points out the existing potential of Minority Serving Institutions (MSIs) to make the U.S. study abroad a truly global program capable of defending U.S. national interest in this era of inter-dependence among nations, especially as the global knowledge economy and cultural competence advantage take center stage. Study abroad is at a crossroads at the moment, new ideas must be developed for study abroad to justify the true potential of education abroad. Over two decades, four countries in Western Europe have been hosting the highest number of U.S. students in study abroad. There is no evidence that this trend will reach the entire globe as a reciprocity of international students in U.S. colleges and universities.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

Water is essential for all life on earth. It is a major component that makes up living organisms and plays a vital role in multiple biological processes. It provides a medium for chemical and enzymatic reactions in the cell and is a major player for osmoregulation and maintenance of cell turgidity. Despite this, many organisms, called anhydrobiotes, are capable of surviving under extremely dehydrated conditions. Less is known about how anhydrobiotes adapt and survive under the desiccation stress. Studies have shown that morphological and physiological changes occur in anhydrobiotes in response to desiccation stress. Certain disaccharides and proteins, including heat shock proteins, intrinsically disordered proteins, and hydrophilins, play important roles in the desiccation tolerance of the anhydrobiotes. In this review, we summarize the recent findings of the desiccation tolerance in the budding yeasts Saccharomyces cerevisiae. We also propose that the yeast under desiccation could be used as a model to study neurodegenerative disorders.

The objective of this paper was to study the expression pattern of the GLOD4 gene in the testis and its regulatory effect on testicular cells. Currently, the regulated mechanism through are unclear. Here, we explored how GLOD4 functions in goat leydig cells to enhance our understanding of spermatogenesis and improve reproduction in breeding rams. In this study, we demonstrated that the localization of GLOD4 in testicular cells using immunohistochemistry and subcellular localization analyses. Subsequently, we analyzed the GLOD4 expression pattern in 4 age-based groups (0, 6, 12, and 18 months old) using real-time quantitative polymerase chain reaction (qRT‒PCR) and protein blotting. Finally, we performed GLOD4 gene silencing and overexpression studies in testicular cells from goats and explored the effects of GLOD4 on cell proliferation, the cell cycle, steroid hormone secretion and the expression of candidate testosterone hormone-regulated genes. GLOD4 was mainly expressed in testicular leydig cells, and the subcellular localization results showed that the GLOD4 protein was mainly localized in the cytoplasm and nucleus. Silencing of GLOD4 significantly suppressed the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD and CYP17A1 and the mRNA expression levels of cell-cycle related genes CDK6, PCNA, and Cyclin E. Moreover, the cell cycle was blocked at the G2/M phase after GLOD4 silencing, which significantly suppressed testosterone secretion. In contrast, GLOD4 overexpression significantly increased the mRNA expression levels of the testosterone secretion-related genes CYP11A1, 3β-HSD, and CYP17A1 and increased the expression of the cell-cycle related genes CDK6, PCNA, and Cyclin E. Moreover, GLOD4 overexpression promoted the cell cycle from G0/G1 phases to enter the S phase and G2/M phases,promoted the secretion of testosterone. Taken together, our experimental results indicate that GLOD4 may affect the development of cells in Qianbei Ma goats of different ages by influencing the cell cycle, Proliferation and testosterone hormone synthesis. These findings enhance our understanding of the functions of GLOD4 in the cells of goats.

Millimeter wave antennas have significance for high-speed, high-capacity wireless communication, delivering substantial advantages and an array of applications. This literature review analyzes the historical development, assessment of performance, difficulties with design, and contemporary applications in telecommunications, radar systems, and imaging. It covers the development of technology, especially within the context of 5G and beyond, and focuses at several antenna designs that deal with technical issues including reduction and impedance matching. The review also studies the effect of design on efficiency and bandwidth, identifying research gaps and potential futures, notably in terms of 5G technology. The commitment to develop millimeter wave antenna technology for next-generation wireless networks is evident, underlining the need of continued research and development.

This literature review investigates the importance of simulation and measurement techniques in the development of transmission lines and antennas, which are crucial to the reliability and efficiency of communication system. It emphasizes the necessity of exact measurement and computational approaches for simulating complicated electromagnetic process, which help to optimize designs before physical prototypes are built. The review examines a variety of research articles that offer innovative solutions to improving accuracy in antenna design, scalability and cost challenges in antenna measurements, and crosstalk measurement methods. It also explores how these methodologies affect antenna design parameters such as gain, bandwidth, and radiation patterns, emphasizing the importance of correct modeling to ensure the performance of transmission lines and antennas in modern communication system. The review serves as a valuable reference for guiding future research and technological advancements in these fields.

Robotic-assisted hip and knee arthroplasty represents significant advancements in orthopedic surgery. Artificial intelligence (AI) - driven chatbots, such ChatGP, plays a significant role in healthcare education. This study aims to evaluate the quality of responses provided by ChatGPT to the top 20 questions concerning robotic-assisted hip and knee arthroplasty.We have asked ChatGPT to select the top 20 questions on Google concerning robotic hip and knee arthroplasty and to provide a detailed answer to each of them. The accuracy of the information provided were examined by three orthopedic surgeons with scientific and clinical experience in hip and knee replacement surgery. The accuracy was assessed through a 5-point Likert scale (from 1 – completely incorrect to 5 – correct); the completeness through a 4-point Likert scale (from 0 – comprehensiveness not assessable for completely incorrect answers to 3 – exhaustive information) on two different occasions to ensure the consistency of the assessment. Our analysis reveals that ChatGPT provides a relatively high degree of accuracy, moreover the explanations can be considered satisfy, especially for factual questions. The findings suggest that ChatGPT can serve as a valuable initial resource for general information on robotic hip and knee arthroplasty but the integration with human expertise remains essential.

This paper presents the five-parameter Exponentiated Weibull Weibull (EWW) distribution with Weibull base failure rate parameterization, developed to model the dropout times of students in an online class module. Parameters of the model were estimated using both Maximum Likelihood and Bayesian estimation procedures to determine the most effective estimation method. Simulation results indicate that, across various hazard types and censoring levels, Bayesian estimates are more accurate and precise than Maximum Likelihood estimates. Real-life data analysis of online students module presentation supports these findings, showing significantly lower standard deviations for Bayesian estimates compared to Maximum Likelihood estimates, highlighting the efficiency of Bayesian estimation for the EWW distribution. Additionally, a comparative goodness-of-fit analysis demonstrated that the EWW distribution better fits the student dropout times dataset than Weibull Weibull (WW), Weibull Exponential (WE), and Exponential Weibull (EW) distributions. The median dropout time estimated using the EWW distribution is 24 days, suggesting that instructors should closely monitor student attendance around this period.

Neural or mental simulation of actions is a powerful tool for allowing cognitive agents to develop Prospection Capabilities that are crucial for learning and memorizing key aspects for challenging skills. In previous studies we developed an approach based on the animation of the redundant human Body Schema based on the Passive Motion Paradigm (PMP). In this paper we show that this approach can be easily extended to hyper-redundant serpentine robots as well as to hybrid configurations where the serpentine robot is functionally integrated with a traditional skeletal infrastructure. A simulation model is analyzed in detail showing that it incorporates spatio-temporal features discovered in the biomechanical studies of biological hydrostats like the elephant trunk or the octopus tentacles. It is proposed that such generative internal model can be the basis for a cognitive architecture appropriate for serpentine robots, independent of the underlying design and control technologies. Although robotic hydrostats have received a lot of attention in the last decades, the great majority of research activities have been focused on the actuation/sensorial/material technologies that can support the design of hyperredundant soft robots as well as the related control methodologies. The cognitive level of analysis has been limited to motion planning, without addressing synergy formation and metal time travel. This is where the contribution of the paper is focused on.

The article presents the author’s works in the field of modifications and modeling of the PQC CSIDH algorithm on non-cyclic supersingular Edwards curves and its predecessor CRS scheme on ordinary non-cyclic Edwards curves are reviewed. Lower estimates of the computational speed gains of the modified algorithms over the original ones are obtained. The most significant results were obtained by choosing classes of non-cyclic Edwards curves connected as quadratic twist pairs instead of cyclic complete Edwards curves, as well as the method of algorithm randomization as an alternative to “constant time CSIDH.” It is shown that in the CSIDH and CSIKE algorithms, there are two independent cryptosystems with the possibility of parallel computation, eliminating the threat of side-channel attacks. For the CRS scheme, there are four such cryptosystems. Integral lower bound estimates of the performance gain of the modified CSIDH algorithm are obtained at 1.5 ∙ 29, and for the CRS scheme are 3 ∙ 29.

Recently, polyacetylene (PA) is receiving a renewed scientific attention due to its electrical properties potentially useful for energy applications (e.g., fabrication of electrodes for batteries and supercapacitors) and unique functional characteristics (e.g., flame retardant, oxygen scavenger, EMI-shielding, etc.). This chemical compound can be obtained in form of a polyacetylene-PVOH copolymers simply by chemical dehydration of poly(vinyl alcohol) (PVOH), which is a very common type of polymer, widely used in packaging and other technological areas. This very inexpensive chemical reaction for the large-scale synthesis of PA/polyvinylenes has been investigated by reacting PVOH with fuming sulfuric acid at room temperature. In this process, PVOH, shaped in form of film, is dipped in fuming sulfuric acid (i.e., H₂SO₄ at 95-97%) and, after complete chemical-dehydration, it has been mechanically removed from the liquid phase by using a nylon sieve. The reduction process leads to a substantial PVOH film conversion to PA as it has been proved by infrared spectroscopy (ATR-mode). Indeed, the ATR spectrum of the reaction product included all characteristic absorption bands of PA. The reaction product has been also characterized by UV-Vis spectroscopy in order to evidence the presence in the structure of conjugated carbon-carbon double bonds of various lengths. Differential scanning calorimetry (DSC) and thermogravimetric analysis have been used respectively to investigate the PA solid-state cis-trans isomerization and thermal stability in air and nitrogen, respectively.

This article introduces the Theory of Inverse Discrete Dynamical Systems (TIDDS), a novel methodology for modeling and analyzing discrete dynamical systems via inverse algebraic models. Key concepts such as inverse modeling, structural analysis of inverse algebraic trees, and the establishment of topological equivalences for property transfer between a system and its inverse are elucidated. Central theorems on homeomorphic invariance and topological transport validate the transfer of cardinal attributes between dynamic representations, offering a fresh perspective on complex system analysis. A significant application presented is an alternative proof of the Collatz Conjecture, achieved by constructing an associated inverse model and leveraging analytical property transfers within the inverted tree structure. This work not only demonstrates the theory's capability to address and solve open problems in discrete dynamics but also suggests vast implications for expanding our understanding of such systems.

This study explores the impact of supply chain visibility (SCV) on marketing strategies within the fast-moving consumer goods (FMCG) industry. In a rapidly evolving market characterized by complex supply chains and dynamic consumer demands, SCV offers a transformative capability by providing real-time data and insights into supply chain operations. Through semi-structured interviews with industry practitioners, the research identifies several key themes: enhanced demand forecasting, increased consumer trust through transparency, improved marketing agility, and the integration of advanced technologies. Findings suggest that SCV significantly improves the accuracy of demand forecasts by providing timely insights into inventory levels, production schedules, and market conditions. This enhanced forecasting aligns supply chain capabilities with marketing efforts, reducing stockouts and optimizing promotional activities. Moreover, SCV fosters consumer trust by enabling transparency regarding product sourcing and ethical practices, which can be effectively communicated in marketing campaigns to build brand loyalty. The agility provided by SCV allows companies to quickly adjust their marketing strategies in response to market disruptions and shifts in consumer preferences, making their campaigns more resilient and responsive. Advanced technologies such as IoT, blockchain, and analytics further enhance the benefits of SCV, providing deeper insights and more sophisticated capabilities for marketing. The study also highlights the importance of cross-functional collaboration between supply chain and marketing teams in leveraging SCV data effectively. Despite challenges such as the need for significant investment and organizational change, the advantages of SCV in enhancing marketing strategies and overall organizational performance are substantial. The research underscores SCV's critical role in shaping effective marketing strategies, offering FMCG companies a path to greater efficiency, agility, and consumer engagement in a competitive landscape.

COVID-19 was a terrible worldwide pandemic that caused a global public health crisis, with numerous deaths and a severe economic depression. To suppress the spread of COVID-19 and initiate patient isolation and contact tracing to reduce its effect, early diagnosis was required, with real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test being the most widely used. However, the RT-PCR test was sometimes found to be lengthy and inaccurate and; for that reason, in many cases of severe complications of COVID-19 pneumonia, chest screening with radiography imaging was preferred. In this paper, we carried out a study for COVID-19 detection from computed tomography images, and compared the obtained results using deep learning (DL) and support vector machine (SVM). The findings showed that, despite the excellent results shown by deep learning, the accuracy in predicting COVID-19 using SVM, in the presence of small databases, was slightly higher than DL. The execution time using SVM was also shorter

The utilization of optical antennas for active control of far-field radiation at the subwavelength scale is crucial in various scientific and technological applications. We propose a thermally tunable disk design of indium tin oxide (ITO) and aluminum gallium nitride (Al0.18Ga0.82As), enabling a switch between absorption and scattering. Furthermore, the control of far-field radiation pattern can be easily realized by combining ITO and Al0.18Ga0.82As to enhance or suppress emission. Our results demonstrate that hybrid structure can be dynamically tuned with temperature variations. In the proposed design, a frequency is achieved at the epsilon-near-zero wavelength of 1240 nm. The thermal tunability of hybrid structure introduces new multifunctional possibilities for light manipulation, thereby enhancing the potential applications of new devices in the near-infrared range.

Chronic lymphocytic leukemia (CLL) is the most common form of leukemia in adults, characterized by abnormal growth of mature B cells in the blood, bone marrow, and lymphoid tissues. Although CLL primarily affects the hematopoietic system and lymph nodes, renal involvement is exceptionally rare and presents diagnostic and treatment challenges. Potential causes of renal failure in CLL patients include sepsis, dehydration, tumor lysis syndrome (TLS), compression of the ureter by enlarged lymph nodes, and side effects of cancer therapy. This report presents a case of CLL with renal infiltration leading to severe renal failure, discussing the clinical presentation, diagnostic workup, and management of this condition.

In this paper, a low-grade copper oxide ore with highly alkaline was treated. The thermodynamic model of CuO-(NH4)2SO4-NH3-H2O was established in the leaching system of tenorite (CuO) under the condition of double conservation of mass and charge. The fitting function of MATLAB and the diff and solve functions were used to calculate the optimal ammonia concentration and total copper ion concentration of tenorite under different ammonium sulfate concentrations. The effects of different ammonia-ammonium salt (ammonium sulphate, ammonium carbonate, ammonium chloride) solution on copper leaching rate were investigated. Results show that under the conditions of ammonia concentration of 1.2 mol/L, ammonia-ammonium ratio of 2:1 and liquid-solid ratio of 3:1, the copper leaching rate from the ammonium sulphate and ammonium chloride solution reaches 70%, slightly higher than that of ammonium carbonate. Therefore, ammonia ammonium sulfate system is selected to leach low-grade copper oxide due to its lower corrosion to the equipment than the chlorination system.

This research aims to enhance scholarly understanding Analysis of potential Value Creation research on managing transit oriented that may arise from Mass Rapid Transit resources through an extensive literature review, analyzing 235 papers from the Scopus database spanning 2011-2024, with a specific focus on value creation managing transit-oriented area. Data collection was conducted on January 1, 2024, using Harzing's Publish or Perish tool. The selected studies are associated with keywords such as 'managing transit orientation (154 papers), Value creation MRT (45 papers), Innovation MRT (36 papers)/ In the filtering process, 235 papers were assessed, excluding those unrelated to the research focus on the cash flow statement. The inclusion of 31 carefully selected articles reflects a targeted approach, ensuring alignment with the research focus on value creation in managing transit orientation a relevant dataset for analysis. This article was created by accessing several scientific articles regarding the application of identification in managing transit orientation using Vos viewer. Value creation research in managing transit oriented is needed to explore the following areas: Long-term sustainability of identified core competencies, Competitive Imitation, Organizational Adaptability, Industry Specific Applications, Performance Measurement, Dynamic Capability Development, Cross-Cultural Perspective. Potential areas for further research include Incorporate additional contingent factors into the model, such as environmental dynamism and competitiveness, to test the validity of the Resource-Based View (RBV) model. Extend the analysis to small and medium-sized businesses to examine how organizational structure and competitive strategy impact performance in this context.

This study used 10 replicate pens per treatment in a randomized complete block design and each pen contained 8 steers (initial BW = 305 ± 30.4 kg; n=80 steers/treatment) to determine if a phytogenic feed additive (PFA) with essential oils and plant extracts (PHYTOsolvan 200; DOSTOFARM, Westerstede, Germany) influences measures of growth or growth efficiency during the feedlot receiving phase in auction-derived beef steers. No steers were removed from the study; one steer from the control treatment was treated for respiratory disease. No mortality was noted in the present experiment. No appreciable differences were noted for BW, ADG, DMI, or feed conversion efficiency from d 1 to 29, 29 to 53, or during the cumulative receiving period (P ≥ 0.12). Performance based NEm and NEg were not influenced by dietary treatment (P ≥ 0.79). The ratio of observed-to-expected dietary net energy was not impacted by dietary treatment (P ≥ 0.71). These were healthy, high-growth potential Northern Plains steers. There was minimal morbidity (0.63%) and no mortality noted during the 53 d receiving study. Steers performed well and met growth performance expectations (the ratio of observed-to-expected NEm = 1.00), hence, it was not anticipated that the phytogenic compound would appreciably influence growth or health outcomes under the conditions of this experiment.

Isolation, quarantine, and contact tracing were some of the most critical and commonly employed non-pharmaceutical interventions to control the COVID-19 pandemic. However, the effectiveness of these strategies after their implementation depends upon many factors such as the country's population, availability of sufficient resources to diagnose and effectively isolate the infected individuals, and feasibility, and acceptability of isolation and quarantine policy by the public. This narrative review aims to appraise the current evidence on the correct implementation strategies and shortcomings made in the isolation and quarantine strategies during the COVID-19 pandemic. PubMed, SCOPUS, EMBASE, and Web of Science citation index with the following keywords were searched: Pandemic, COVID-19, Coronavirus, Quarantine, and Isolation. The results showed that quarantine and isolation of COVID-19 patients were more effective than late adoption (5-fold versus 2.6-fold)’. Around 90% of outbreaks could have been managed if 80% of contacts were monitored, traced, and isolated within 4 days. For each new case of COVID-19, around thirty-six individuals should have been traced. When the percentage of individuals without symptoms is greater than 30%, isolation and contact tracing alone cannot contain the infection. The delay between the onset of symptoms and isolation is the most important factor determining whether an outbreak is controllable. The ideal day for testing should start on the 6th of the quarantine. However, this evidence is mostly based on mathematical modeling studies, and evidence for its effectiveness in real scenarios is required. Symptom-based isolation strategy should not be considered the sole criterion for considering isolation.

Energy poverty in the Global South generally focuses on the lack of basic access to modern fuels and energy carriers. Impoverished people rely primarily on traditional biomass as a source of energy. This situation of basic resource deprivation, in which almost one third of the world's population lives, masks other relevant features of the problem. Current assessments of energy poverty in impoverished areas and the mitigation strategies being implemented derive from the development agenda and, with variations in detail and scope, highlight electricity connections and access to clean cooking fuels as guarantors of progress. However, a comprehensive understanding of energy poverty requires going beyond basic access, building on the interactions between the supply of energy sources and carriers, the provision of energy services and its impact on decent living conditions. Several studies in the last decade have attempted to construct an assessment framework centered on energy services to deal with these interactions. This work discusses the relevant dimensions in the framework (supply, services and impact in wellbeing), reviews the multidisciplinary work available in each aspect, presents a range of proposed taxonomies, and discusses the different issues. A detailed framework is proposed for the integrated assessment of the supply of energy carriers and energy equipment, the provision of relevant energy services, and the improvements obtained in living conditions.

Introduction: The disease caused by Coronavirus-2019 (COVID-19) was initially described in December 2019. Severe acute respiratory syndrome type 2 (Sars-Cov-2) is responsible for an important multisystem inflammatory spectrum. Cardiovascular conditions have been reported with an estimated frequency of 8-28%. In this context, transthoracic echocardiography associated with the analysis of the two-dimensional Global Longitudinal Strain (GLS) of the left ventricle derived from Speckle Tracking emerges as a promising modality. Objective: This study aims to evaluate the applicability of GLS and segmental deformity assessment in detecting subclinical myocardial dysfunction in patients that recovered from COVID-19 infection. Methods: The observational study involved 18 patients (mean age 52 years) with recent evidence of COVID-19 infection that underwent detailed echocardiographic evaluation with GLS, and cardiac magnetic resonance (CMR) according to segmental assessment results. The degree of correlation between the methods was analyzed and a systematic literature review was also conducted. Results: The mean left ventricular ejection fraction (LVEF) was 57.50 ± 9.98%. Only 16.6% of patients had reduced LVEF. The average GLS was – 18.70 ± 3.54% and in 44% of cases only one myocardial segment was affected, particularly the inferolateral basal. CMR revealed inflammatory cardiomyopathy. Discussion: Subclinical myocardial involvement is associated with major adverse cardiac events. Literature review supports the use of GLS for detecting early cardiac involvement. Conclusion: Speckle-tracking echocardiography has been shown to have clinical utility in a variety of settings and to offer superior prognostic value with a potential to enhance subclinical detection of myocardial changes in patients after COVID-19 infection.

Lahpet-ye-hsain, known as a “tea shop” or teahouse, is where the people of Myanmar conduct their daily social activities besides its economic orientation. They are private establishments and informal gathering places serving tea and food at different times of the day for various clients. They can be small snacks, large open-aired, or covered restaurants with extensive menus. Patrons sit around small square tables on footstools. A diverse range of characters goes to tea shops. They have a reputation for welcoming people from all backgrounds and walks of life, but the role of women is hardly seen and unclear. They provide a space for men to share a cup of tea and food and exchange ideas, opinions, problems, hopes, and aspirations. They provide not only space but also to get ‘good taste and cheap food.’ A cup of tea at a tea shop is an opportunity to share knowledge amongst old and new friends. Such shops are abundant over the country. This paper examines the social, political, and economic role of these ubiquitous features of Myanmar society. The barriers to women's participation and inroads in some locales are discussed.

Long intergenic noncoding (LINC)01270 is a 2278 bp transcript belonging to the intergenic subset of long noncoding (lnc)RNAs. Despite increased reports of LINC01270’s involvement in different diseases, evident research on its effects on inflammation is yet to be achieved. In the present study, we investigated the potential role of LINC01270 in modulating the inflammatory response in the human monocytic leukemia cell line THP-1. Lipopolysaccharide treatment upregulated LINC01270 expression, and siRNA-mediated suppression of LINC01270 enhanced NF-kB activity and the subsequent production of cytokines IL-6, IL-8, and MCP-1. Interestingly, the knockdown of LINC01270 downregulated expression of leucine zipper downregulated in cancer 1 (LDOC1), a novel NF-kB suppressor. An analysis of the LINC01270/micro-RNA (miRNA)/protein interactome profile identified miR-326 as a possible mediator. Synthetic RNA agents that perturb the interaction among LINC01270, miR-326, and LDOC1 mRNA mitigated the changes caused by LINC01270 knockdown in THP-1 cells. Additionally, a luciferase re-porter assay in HEK293 cells further confirmed that LINC01270 knockdown enhances NF-kB activation, while its overexpression has the opposite effect. This study provides insight into LINC01270’s role in modulating inflammatory responses to lipopolysaccharide stimulation in THP-1 cells via miR-326/LDOC1 axis which negatively regulates NF-kB activation.

During our digital transition, Docker containers have become essential for adaptable application deployment, although posing inherent security threats. This study utilizes Trivy for static analysis and Falco for dynamic analysis to identify and address vulnerabilities in Docker environments before deployment and in real-time. The IoT sector is now dealing with security issues that are made more severe by extensive connectivity and the prevalence of WiFi. This research promotes the use of AWS cloud security technologies such as IoT Core, CloudWatch, and GuardDuty to protect IoT devices from threats, with the goal of maintaining user privacy and ensuring safety in our interconnected digital world. This comprehensive strategy aims to enhance security measures in both Docker and IoT sectors, strengthening the security framework in our interconnected world.

This qualitative study explores the influence of ethical supply chain practices on brand equity from the perspective of consumers. In-depth interviews were conducted with 30 participants to examine their attitudes, perceptions, and behaviors towards brands that emphasize ethical considerations in their supply chain operations. Thematic analysis revealed several key findings. Transparency and authenticity emerged as critical factors influencing consumer trust and perceptions of brand integrity. Participants valued brands that communicated clearly and honestly about their ethical sourcing practices, viewing transparency as indicative of reliability and ethical commitment. Ethical considerations significantly influenced consumer purchase decisions, with participants emphasizing the importance of factors such as fair labor practices, environmental sustainability, and responsible sourcing in shaping their perceptions of product quality and brand value. Brands that integrated these ethical principles into their supply chain management were perceived as offering higher-quality products, which enhanced consumer willingness to pay a premium and bolstered brand reputation. The study also highlighted varying levels of consumer awareness and engagement with ethical supply chain practices, underscoring the importance of effective communication and consumer education. Ethical supply chain practices were found to foster brand loyalty and trust, with brands perceived as ethical and socially responsible enjoying stronger consumer relationships and loyalty. Overall, the findings suggest that ethical supply chain practices play a crucial role in enhancing brand equity by aligning business operations with consumer values and expectations. The study contributes to existing literature by providing empirical insights into the mechanisms through which ethical considerations influence consumer perceptions and behaviors towards brands.

Emerging data processing techniques brought back into attention the HF range communication as an interesting alternative to third-party solutions for IoT applications, such as data transmission in distributed energy production facilities. The physical size of HF antennas, often comparable to the surrounding objects, require in-situ radiation measurements. Drone-borne measuring systems are already known as a flexible solution, but mostly restricted to higher frequency ranges. In this work, we propose to use an electrically small, folded dipole as a probe for drone-borne measurements on HF antennas. We also propose a calibration approach for the effects related to the near-field zone, and to the drone body proximity. The impact of ground reflection is also investigated. We show that despite its low, realized gain figure such a probe can provide stable results for near-field measurements, even at low input power levels.

The integration of supply chain data analytics with marketing strategies has become increasingly critical for organizations seeking to enhance customer insights and competitive advantage in today's dynamic business environment. This qualitative research explores the intersection of these two disciplines, focusing on implementation strategies, benefits, challenges, and future directions. Through semi-structured interviews with industry experts and stakeholders, key themes emerged, highlighting the importance of cross-functional collaboration, technological integration, and robust data governance in achieving effective integration. The study identifies significant benefits, including enhanced customer insights, improved operational efficiencies, and competitive advantage through personalized marketing strategies and optimized supply chain management. However, challenges such as data silos, technological complexities, and regulatory compliance issues pose barriers that require strategic solutions and organizational commitment. Future directions point towards the continued evolution of predictive analytics, AI-driven solutions, and sustainability integration, shaping the future landscape of supply chain management and marketing. Proactive engagement with regulatory frameworks and ethical considerations will be crucial in navigating these challenges and building trust with consumers. Ultimately, this research contributes to a deeper understanding of how organizations can leverage data analytics to drive strategic decision-making, enhance customer relationships, and achieve sustainable growth in an increasingly data-driven economy.

This qualitative research explores the profound implications of integrating real-time supply chain information on marketing decisions within service industries. Through semi-structured interviews with professionals from logistics, retail, hospitality, healthcare, and telecommunications sectors, the study examines how real-time data enhances demand forecasting, inventory management, personalized marketing approaches, agility in marketing responses, and supplier relationship management. Findings reveal that real-time supply chain information significantly improves accuracy in predicting customer demand and optimizing inventory levels, thereby reducing costs and enhancing service delivery efficiency. Moreover, real-time data enables more targeted marketing strategies through granular customer segmentation and dynamic pricing adjustments based on real-time market dynamics. The agility afforded by real-time information allows companies to swiftly adapt marketing strategies to emerging trends and consumer behaviors, maintaining competitiveness in dynamic service markets. Enhanced supplier collaboration and risk management further underscore the strategic value of real-time supply chain integration, fostering stronger partnerships and supply chain resilience. This study contributes to a deeper understanding of how real-time supply chain information transforms marketing practices in service industries, highlighting its role in improving operational efficiency, customer satisfaction, and overall competitiveness. Future research could explore implementation challenges and long-term impacts across diverse service sectors, providing insights into optimizing the strategic use of real-time data for sustained business success.

Epithelial ovarian cancer significantly contributes to cancer-related mortality in women, often recurring post-treatment with chemotherapy resistance. Dietary interventions have demonstrated influence on cancer progression; for instance, caloric restriction has exhibited tumor growth reduction and enhanced survival in animal cancer models. This study aims to calculate a transcriptomic signature based on caloric-restriction for ovarian cancer patients and explore its correlation with disease progression. We identified proteins modulated by fasting, intermittent fasting or caloric restriction in human females. Based on their gene expression, we calculated a Non-Fasting Genomic Signature score for ovarian cancer samples from the TCGA database. We examined the association between this genomic profile and clinical characteristics. The non-fasting signature, comprising eight genes, demonstrated higher prevalence in primary ovarian tumors compared to normal tissue. Patients with elevated signature expression exhibited reduced overall survival and increased lymphatic invasion. The mesenchymal subtype, associated with chemotherapy resistance, displayed the highest signature expression. Multivariate analysis suggested the non-fasting genomic signature as a potential independent prognostic factor. Ovarian cancer tumors expressing a “non-fasting” transcriptional profile correlate with poorer outcomes, emphasizing the potential impact of caloric restriction on improving patient survival and treatment response. Further investigations, including clinical trials, are warranted to validate these findings.

Epilepsy is known to cause alterations in neural networks. However, many details of these changes remain poorly understood. The objective of this study was to investigate changes in the properties of hippocampal CA1 pyramidal neurons and their synaptic inputs in a rat lithium-pilocarpine model of epilepsy. In the chronic phase of the model, we found a marked loss of pyramidal neurons in the CA1 area. However, the membrane properties of the neurons remained essentially unal-tered. The results of the electrophysiological and morphological studies indicate that the direct pathway from the entorhinal cortex to CA1 neurons is reinforced in epileptic animals, whereas the inputs to them from CA3 are either unaltered or even diminished. In particular, the dendritic spine density in the str. lacunosum moleculare, where the direct pathway from the entorhinal cortex ter-minates, was found to be 2.5 times higher in epileptic rats than in control rats. Furthermore, the summation of responses upon stimulation of the temporoammonic pathway was enhanced by approximately twofold in epileptic rats. This enhancement is believed to be a significant con-tributing factor to the heightened epileptic activity observed in the entorhinal cortex of epileptic rats using an ex vivo 4-aminopyridine model.

The injury causes resistance in human gastric cancer (GC). This Adverse Outcome Pathway (AOP) entitled “Increases in cellular reactive oxygen species (ROS) and chronic ROS leading to human treatment-resistant gastric cancer (GC)” consists of molecular initiating event (MIE) as “Increases in cellular ROS” and “Chronic ROS”, followed by series of key events (KEs); “porcupine-induced Wnt secretion and Wnt signaling activation”, “beta-catenin activation”, “epithelial-mesenchymal transition (EMT), and adverse outcome (AO) as “human treatment-resistant GC” in the sequence. ROS has multiple roles in disease such as development and progression of cancer, or apoptotic induction causing anti-tumor effects. In this AOP, we focus on the role of sustained levels of chronic ROS to induce the therapy-resistance in human GC. EMT, which is cellular phenotypic change from epithelial to mesenchymal-like features, demonstrates cancer stem cell (CSC)-like characteristics in human GC. EMT is induced by Wnt/beta-catenin signaling, providing the rationale to have Wnt secretion and beta-catenin activation as KEs in the AOP.

Graphene was synthesized through a two-step pyrolysis method using waste candlenut (Aleurites moluccanus) shells as the precursor. Cerium (Ce)/graphene composites were prepared via an impregnation technique. The resulting graphene and Ce/graphene were characterized using various analytical methods, including Scanning Electron Microscopy with Energy-Dispersive Spectroscopy (SEM-EDS), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), Thermo Gravimetric Analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, Cyclic Voltammetry (CV), and Linear Sweep Voltammetry (LSV). The bio-carbon produced predominantly exhibited a graphene structure with flat carbon morphology and an interlayer distance of 0.33 nm. This structural information is supported by XRD data, which shows a broad and weak peak at 2θ = 26° corresponding to the C (002) plane, indicative of graphene presence. FTIR, XPS, and Raman spectroscopy further confirmed the presence of graphene through the detection of Csp2 aromatic bonds and the characteristic D, G, and 2D peaks. Notably, the performance of cerium can be enhanced by the incorporation of graphene, attributed to the large surface area and chemical interactions between Ce and graphene. Consequently, candlenut-derived graphene shows potential as a supportive material for modifying the properties of cerium, thereby opening avenues for various advanced applications, such as sustainable and high-performance energy storage systems.

The automotive industry is increasingly adopting laminated glass in side and rear windows to comply with safety standards aimed at reducing ejection injuries. However, this trend may have unintended consequences for occupant rescue and escape in submerged vehicle incidents. As more vehicles incorporate laminated glass, concerns arise that they could become "glass coffins" in water, making it more difficult for occupants to exit or be rescued. The use of laminated glass is driven by Federal Motor Vehicle Safety Standard 226 (FMVSS 226) for ejection mitigation, but it does not address the risk of vehicle submersion and occupant drowning. Drowning accounts for a substantial portion of vehicle-related fatalities. As the adoption of laminated glass grows, there is a need for drowning prevention measures, such as automatic window opening systems, to mitigate the risk of vehicles becoming "glass coffins" in water. A comprehensive approach addressing both ejection and submersion dangers is necessary to maximize occupant protection and save lives.

The high penetration of distributed energy resources poses significant challenges to the dispatch and operation of power systems. Improving the accuracy of short-term load forecasting (STLF) can optimize grid management, leading to increased economic and social benefits. Currently, some simple AI and hybrid models has issues to deal with and struggle with multivariate dependencies, long-term dependencies, and non-linear relationships. This paper proposes a novel hybrid model for short-term load forecasting (STLF) that integrates multiple AI models with Lasso regression using the stacking technique. The base learners include ANN, XgBoost, LSTM, Stacked LSTM, and Bi-LSTM, while Lasso regression serves as the meta-learner. By considering factors such as temperature, rainfall, and daily electricity prices, the model aims to more accurately reflect real-world conditions and enhance predictive accuracy. Empirical analyses on real-world datasets from Australia and Spain show significant improvements in forecasting accuracy, with a substantial reduction in Mean Absolute Percentage Error (MAPE) compared to existing hybrid models and individual AI models. This research highlights the efficiency of the stacking technique in improving STLF accuracy, suggesting potential operational efficiency benefits for the power industry.

The theory says that number interacts with spaces based on the meaning of mathematics, in this way it is possible to obtain numerical knowledge. The theory shows the possibility of using spaces related to each other to explain the reasons why two even numbers form a pair, two odd numbers form a pair, an even number and an odd number form an odd number, three odd numbers form an odd number . three even numbers make an odd number. an even, an odd and two evens make an odd, two odd and an even make a pair. Furthermore, it is possible to extend the logic to larger numbers, but applying rules to make it work.

PARK7, also known as DJ-1, plays a critical role in protecting cells by functioning as a sensitive oxidation sensor and modulator of antioxidants. DJ-1 acts to maintain mitochondrial function and regulate transcription in response to different stressors. In this study, we showed that cell lines vary based on their antioxidation potential at basal conditions. The transcriptome of HEK293 cells was tested following knockdown (KD) of DJ-1 using siRNAs which reduced the DJ-1 transcripts to only 12% of the original level. We compared the expression levels of 14k protein-coding transcripts, and 4.2k non-coding RNAs relative to control cells treated with non-specific siRNAs. Among the coding genes, ~200 upregulated differentially expressed genes (DEGs) signified a coordinated antiviral innate immune response. Most genes were associated with regulation of type 1 interferons (IFN) and induction of inflammatory cytokines. About a quarter of these genes were also induced in cells treated by non-specific siRNAs that were used as a negative control. Beyond the antiviral response, 114 genes were specific to KD of DJ-1 with enrichment in RNA metabolism and mitochondrial functions. A smaller set of downregulated genes (58 genes) were associated with dysregulation in membrane structure, cell viability, and mitophagy. We propose that KD of DJ-1 diminish its protective potency against oxidative stress, rendering the cells labile and responsive to dsRNA signal by activation of a large number of genes, many of which drive apoptosis, cell death, and inflammatory signatures. The KD of DJ-1 highlights its crucial role in regulating genes associated with antiviral responses, RNA metabolism, and mitochondrial functions, apparently through alteration in STAT activity and downstream signaling. Given that DJ-1 is highly expressed in metastatic cancers, targeting DJ-1 could be a promising therapeutic strategy where manipulation of DJ-1 levels may reduce cancer cell viability and enhance the efficacy of cancer treatments.

In this work, we study the equation of the catenary curve in the context of the Caputo derivative. We solve this equation and compare the solution with real physical models. From the experiments, we find that the best approximation is achieved in the classical case. Therefore, introducing a fractional parameter arbitrarily can be detrimental. However, we observe that when adding a certain weight to the chain, fractional calculus produces better results than classical calculus for modeling the minimum height.

Background/Objectives: To evaluate incidental findings in the mandible after the placement of dental implants using a new cone-beam computed tomography (CBCT) software. Methods: The initial sample consisted of 2,872 CBCT scans of patients of both sexes. The parameters evaluated in this study were the location of the implants in the mandible, implant length, anatomical relationship of the implant with the mandibular canal, presence or absence of damage to the adjacent teeth, presence or absence of implant fractures, and presence or absence of bone support. Fisher's exact test was performed to compare the variables. The significance level was set at p = 0.05. Results: Out of 2,872 CBCT scans, 214 images of patients with an average age of 44.5 years were included. The most frequent location of the implants was the posterior region (93.5%), with 54% of the implants having a length between 9 and 14 mm. It was found that 92% of the implants were positioned above the mandibular canal. Three damage to adjacent teeth was observed, with no correlation with the implant positioning (p = 0.999). In 100% of cases of implants in the anterior region, there was bone support. Fracture was observed in 1.7% of implants with a length between 9- and 14-mm. Conclusions: The installation of implants in the mandible occurs more frequently in the posterior region, with a high presence of bone support and a low incidence of damage to adjacent teeth, anatomical structures, and fractures.

Cytomegalovirus infection contributes to 10-30% congenital hearing loss in children. Vertebrate peripheral auditory organs include the outer, middle and inner ear. Their development is regulated by multiple signaling pathways. However, most ear diseases due to viral infections are due to congenital infections and reactivation, and affect healthy adults to a lesser extent. This may be due to the fact that viral infections affect signaling pathways that are important for the development of peripheral hearing organs. Therefore, an in-depth understanding of the relationship between viral infections and the signaling pathways involved in the development of peripheral hearing organs is important for the prevention and treatment of ear diseases. In this review, we summaries the effects of viruses on signaling pathways and signaling molecules in development of peripheral auditory organ, with a focus on Human cytomegalovirus as an example.

The present work consisted of an exploratory study aiming to evaluate in vitro the potential of AuNPs during Radiation Therapy (RT) in human pancreatic adenocarcinoma cells. AuNPs coated with hyaluronic and oleic acids (HAOA-AuNPs) or with bombesin peptides (BBN-AuNPs) were used. AuNPs were characterized by Atomic Force Microscopy (AFM) and Dynamic Light Scattering. BxPC-3 tumour cells were irradiated with a 6 MV X-rays beam, in the absence or presence of AuNPs. AFM showed that HAOA-AuNPs and BBN-AuNPs are spherical with a mean size of 83+-20 nm and 49+-12 nm, respectively. For RT alone, a reduction in cell viability of up to 33+-12% was obtained compared to the control (p ≤ 0.0001). HAOA-AuNPs alone at 200 and 400 μM showed a reduction in cell viability of 20+-4% and 35+-4%, respectively, while for BBN-AuNPs, at 50 and 200 μM, a reduction in cell viability of 25+-3% and 37+-3% was obtained, respectively, compared to the control (p < 0.0001). At 72 h post-irradiation, a decrease in cell viability of 26+-3% and 22+-2% between RT+HAOA-AuNPs at 400 μM and RT+BBN-AuNPs at 50 μM, compared to RT alone, was obtained (p < 0.004). The combination of RT with AuNPs led to a significant decrease in cell viability compared to the control, or RT alone, thus representing an improved effect.

Natural and sustainable plant-based antioxidants and antimicrobials are highly desirable for improving food quality and safety. The present investigation assessed the antimicrobial and antioxidant properties of active components from Alkanna tinctoria (herb) roots, also known as Ratanjot root. Two methods were used to extract active components: microwave-assisted hot water (MAHW) and ethanol and air-dried. MAHW extract yielded 6.29% while the ethanol yielded 18.27%, suggesting superior Ratanjot root extract powder (RRP) solubility in ethanol over water. The ethanol extract showed significantly higher antioxidant activity than the MAHW extract. Gas chromatography and mass-spec analysis revealed three major phenolic compounds: Butanoic acid, 3-hydroxy-3-methyl-; Arnebin 7, and Diisooctylpthalate. The color attributes (L*, a*, b*, hab, C*ab) for the ethanolic and MAHW extracts revealed significant differences (P < 0.05) in all the above parameters for both types of extracts, except for yellowness (b*) and chroma (C*ab) values. The ethanol extract exhibited antimicrobial activity against 14 bacterial species, with a signifi-cantly higher inhibitory effect against Gram-positive bacteria (Listeria monocytogenes and Staphylococcus aureus) than the Gram-negative bacteria (Salmonella enterica serovar Typhimurium and Escherichia coli). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were both 25 mg/ml for the Gram-negative bacteria, while the MIC and MBC concentrations varied for Gram-positive bacteria (0.049 - 0.098 mg/ml and 0.098 - 0.195 mg/ml) and the antimicrobial effect was bactericidal. The antimicrobial activities of RRP extract remained stable under broad temperature (37-100°C) and pH (2-6) conditions, as well as during refrigerated storage for 30 days. Application of RRP at 1% (10 mg/g) and 2.5% (25 mg/g) levels in a cooked chicken meatball model system prevented lipid oxidation and improved sensory attributes and retarded microbial growth during refrigerated (4°C) storage for 20 days. Furthermore, the RRP extract was non-toxic when tested with sheep erythrocytes and did not inhibit the growth of probiotics, Lacticaseibacillus casei, and Lactiplantibacillus plantarum. In conclusion, the study suggests that RRP possesses excellent antimicrobial and antioxidant activities, thus making it suitable for food preservation.

This research introduces a hybrid feature extraction approach that combines Linear Discriminant Analysis (LDA) and Multilayer Perceptron (MLP) methods to address the challenges of reducing feature vector dimensionality and accurately classifying smartphone-based human activities. Moreover, to refine activity classification accuracy, Support Vector Machine (SVM) optimization with Stochastic Gradient Descent (SGD) is employed. LDA, a statistical tool, is leveraged to derive a new feature space for data projection, enhancing class separation and test feature label prediction. The proposed approach, named LMSS, was evaluated using the UCI-HAR dataset and compared with state-of-the-art models. The results demonstrate that the proposed approach outperformed the best-performing method over this dataset. It achieved an accuracy rate of 99.52%, precision of 99.55%, recall of 99.53%, and an F1-score of 99.54%, highlighting the effectiveness of the proposed method in accurately classifying the data.

This qualitative research explores the influence of supply chain disruption management on brand resilience and consumer perception. Amidst increasingly complex global dynamics, effective strategies are crucial for organizations to mitigate risks, maintain operational continuity, and preserve consumer trust. The study employs semi-structured interviews with stakeholders across diverse industries, focusing on strategies employed, outcomes observed, and challenges faced in managing disruptions. Key findings underscore the significance of proactive measures such as risk assessment, contingency planning, diversification, technology integration, and collaboration in enhancing organizational resilience. These strategies not only enable businesses to navigate disruptions effectively but also contribute to sustaining competitive advantage and stakeholder confidence. Consumer perception during disruptions emerges as pivotal, shaped by brands' transparency, responsiveness, and ethical considerations in managing supply chain challenges. Transparent communication and reliable service delivery during disruptions enhance brand reputation and foster consumer loyalty. However, challenges including information gaps, resource constraints, coordination issues, and regulatory compliance complexities highlight the need for adaptive strategies and robust partnerships across the supply chain. Overall, the study provides insights into the interconnectedness of disruption management, brand resilience, and consumer perception, offering practical implications for organizations seeking to strengthen their resilience strategies and consumer relationships in dynamic market environments.

This research provides an in-depth analysis of drought impacts in West Pokot, Kenya, utilizing both remote sensing surveys and focus group discussions. The study commenced by assessing the impact of drought on vegetation health via spatial sensors. It then utilized surveys and focus group discussions (FGDs) to engage farmers from the most drought-affected areas in Kacheliba and Sigor sub-counties. The analysis of remote sensing data from 1990 to 2022 highlighted that Sigor and Kacheliba experienced significant drought events during the years 1995, 2000, 2002, 2005, and 2009, and 1991, 1995, 2000, 2005, and 2019, respectively. This study delves into both the meteorological and socio-economic effects on local communities. Using the Multinomial Logistic Regression (MLR) model with the glm function, the research uncovered the impacts of so-cio-economic factors and agricultural practices on household livestock production. Additionally, the study employed Multiple Correspondence Analysis (MCA) to explore the dynamics between livestock production, community resilience, and crop production. The findings underscore the urgent need for tailored interventions to enhance community resilience in the face of increasing climatic extremes, serving as a blueprint for similar arid and semi-arid regions worldwide.

Lipid-lowering therapy (LLT) is a cornerstone of atherosclerotic cardiovascular disease prevention. Although LLT might lead to different reductions in low-density lipoprotein cholesterol (LDL-C) levels in women and men, LLT diminishes cardiovascular risk equally effectively in both sexes. Despite similar LLT efficacy, the use of high-intensity statin, ezetimibe, and proprotein convertase subtilisin/kexin type 9 inhibitors is lower in women compared to men. Women achieve the guideline-recommended LDL-C levels less often than men. Greater cholesterol burden is particularly prominent in women with familial hypercholesterolemia. In clinical practice, women and men with dyslipidemia present with different cardiovascular risk profiles and disease manifestations. The concentrations of LDL-C, lipoprotein(a) and other blood lipids differ between women and men over a lifetime. Dissimilar levels of LLT’s target molecules partially result from sex-specific hormonal and genetic determinants of lipoprotein metabolism. Hence, to evaluate a potential need for sex-specific LLT, this comprehensive review (i) describes the impact of sex on lipoprotein metabolism and lipid profile, (ii) highlights sex differences in cardiovascular risk among patients with dyslipidemia, (iii) presents recent, up-to-date clinical trial and real-world data on LLT efficacy and safety in women, and (iv) discusses diverse medical needs of women and men with dyslipidemia and increased cardiovascular risk.

The rational design of magnetic carbon composites, encompassing both composition and microstructure, holds significant potential for achieving exceptional electromagnetic wave absorbing materials (EAMs). In this study, FeCo@CM composites was efficiently fabricated through an advanced microwave plasma assisted reduction chemical vapor deposition (MPARCVD) technique, offering high efficiency, low cost, and energy-saving benefits. By depositing graphitized carbon microspheres, the dielectric properties were significantly enhanced, resulting in improved electromagnetic wave absorption performances through optimized impedance matching and a synergistic effect with magnetic loss. A systematic investigation revealed that the laminar-stacked structure of FeCo exhibited superior properties compared to its spherical counterpart, supplying a higher number of exposed edges and enhanced catalytic activity, which facilitated the deposition of uniform and low-defect graphitized carbon microspheres. Consequently, the dielectric loss performance of the FeCo@CM composites was dramatically improved due to increased electrical conductivity and the formation of abundant heterogeneous interfaces. At a 40 wt% filling amount and a frequency of 7.84 GHz, the FeCo@CM composites achieved a minimum reflection loss value of -58.2 dB with an effective absorption bandwidth (fE) of 5.13 GHz. This study presents an effective strategy for developing high-performance EAMs.

Climate change has altered the frequency and severity of extreme weather, which can affect vegetation condition and habitat quality for wildlife. Declines in vegetation productivity during droughts and heatwaves can negatively impact animals that depend on vegetation for water and nutrition. The ability to detect such effects on habitat suitability can reveal refugia, which can be prioritised for protection to improve threatened species conservation. We used the normalised difference vegetation index (NDVI) to look at relationships between vegetation productivity and the presence of koalas (Phascolarctos cinereus) in potential habitat throughout much of their range. Using a large, long-term koala presence dataset, we tested the hypothesis that locations where koalas had been observed would exhibit higher NDVI values than a random, representative sample from the same vegetation group (i.e. woodlands, open forests or tall open forests). We also identified the minimum NDVI threshold at which koalas occurred across time for each vegetation group and compared these to the minimum NDVI values observed across potential koala habitat before and during the millennium drought; one of the worst recorded in Australia. Additionally, we investigated whether vegetation above the minimum NDVI thresholds was significantly closer to perennial water than unsuitable vegetation. We found that koalas tend to occur at locations exhibiting higher NDVI than average for all vegetation groups. We also found that 49% of all vegetation groups maintained a minimum NDVI above the koalas’ NDVI threshold before drought, equating to 190,227 km2, which declined to 166,746 km2 during drought (a 12% reduction). We also found that unsuitable vegetation tended to occur farther from perennial water than suitable vegetation for some vegetation groups. Areas that remained above the NDVI thresholds during the drought should be considered potential refugia for populations during an event of similar magnitude and could indicate future core habitat extent.

Short-term energy consumption forecasting crucial for the operation of new electrical en-ergy grids, not only due to their own characteristics, but also due to the new elements pre-sent in the energy matrix. Many existing models are limited by their methodologies or by considering only a narrow set of factors influencing energy consumption. This study in-troduces a pipeline for developing an energy forecasting model and evaluates the signifi-cance of factors affecting energy consumption and, consequently, forecast accuracy. The study utilizes a dataset from ISO NE (Independent System Operator New England), span-ning the total electric load of various cities in New England from January 2017 to December 2019. This dataset comprises 23 independent variables, including weather data, economic indicators, and market information. The results outline the steps involved in constructing energy forecast models using time series analysis. By carefully selecting variables and rep-resenting external factors, the study demonstrates the feasibility of generating more accu-rate predictions with reduced computational resources.

Despite advances in our knowledge of systemic lupus erythematosus (SLE) has increased over time, there are still many challenges in deciphering the precise mechanisms involved in the development and progression of the disease. Recent evidence has raised questions about the effectiveness of the programmed cell death protein 1 (PD-1) in suppressing autoreactive CD4+ T cells during the autoimmune response. Research has ventured into investigate the potential impact of PD-1 on various CD4+ T cell subpopulations, including T follicular helper (Tfh) cells, circulating Tfh (cTfh) cells, and T peripheral helper (Tph) cells, all of which exhibit substantial PD-1 expression and have been closely related with several autoimmune disorders including SLE. This review aims to highlight the complex role of PD-1 in autoimmunity and emphasizes the imperative for further research to elucidate its functions during autoreactive T-cell response. Additionally, we address the potential of PD-1 or its ligands as a possible therapeutic target in SLE.

Serum biochemical indicators serve as vital proxies that reflect the physiological state and functions of different organs. The genetic parameters and molecular mechanisms underlying serum biochemical indicators of sheep (Ovis aries) have not been well understood. Therefore, the aim of the present study was to identify genetic architecture and genomic loci underlying ten serum biochemical indicators in sheep, including alanine transaminase, aspartate transferase, lactate dehydrogenase, cholesterol, glucose, phosphorus, calcium, creatinine, urea concentrations and total protein levels. We implemented genetic parameter estimations and GWAS for each trait in 422 Akkaraman lambs. Overall, low to moderate heritability estimates were found, in the range 0.14–0.55. Additionally, low to high genetic correlations were observed among traits. In total, 23 SNP loci were associated with serum biochemical indicators leading to 19 genes . These are SPTA1, MGST2, CACUL1, IGFBP7, PARD3, PHB1, SLC15A5, TRIM35, RGS6, NUP93, CNTNAP2, SLC7A11, B3GALT5, DPP10, HST2ST1, NRP1, LRP1B, MAP3K9, ENSOARG00020040484.1 as well as LOC101103187, LOC101117162, LOC105611309 and LOC101118029. To our knowledge, these data provide the first association between SPTA1 and serum cholesterol and between ENSOARG00020040484.1 and serum glucose. The current findings provide a comprehensive inventory of the relationships between serum biochemical parameters, genetic variants, and disease-relevant characteristics. This information may facilitate the identification of therapeutic targets and fluid biomarkers and establish a strong framework for comprehending the pathobiology of complex diseases as well as providing targets for sheep genetic improvement programmes.

Decompression sickness (DCS) with neurological disorders is the leading cause of diving accidents. Exposure to high levels of CO2 during diving is a safety concern for occupational , groups at risk of DCS. However, the effects of prior exposure to CO2 have never been evaluated. The purpose of this study was to evaluate the effect of CO2 breathing prior to a provocative dive on the occurrence of DCS in mice. 50 mice were exposed to a maximum CO2 concentration of 70 hPa for one hour at atmospheric pressure. Another 50 mice breathing air under similar conditions served as controls. In the AIR group (controls), 22 out of 50 mice showed post-dive symptoms compared to 44 out of 50 in the CO2 group. We found that CO2 breathing is associated with a decrease in body temperature in mice and that CO2 exposure dramatically increases the incidence of DCS. More unexpectedly, it appears that a lower temperature of the animals even before exposure to the accident-prone protocol leads to an unfavorable prognosis. This study also suggests that the composition of the microbiota may influence thermogenesis and thus accidentology. Depending on prior exposure, some bacteria identified in this work could be perceived as protective or pathogenic.

Approximately more than 120 transthyretin mutations are known whose variation in clinical presentation is heterogeneous, as the course of disease onset depends on genetic variation and level of penetrance. It is little known in Ecuador, and some of the reported cases; suggest to the family tree analysis that they come from a province that is possibly considered endemic. The main objective is to carry out a descriptive cross-sectional analysis on the presentation of transthyretin amyloidosis in families carrying the p.Ser43Asn gene from the index case identified.

We propose a novel approach for time series forecasting with many predictors, referred to as the GO-sdPCA, in this paper. The approach employs a variable selection method known as the group orthogonal greedy algorithm and the high-dimensional Akaike information criterion to mitigate the impact of irrelevant predictors. Moreover, a novel technique, called peeling, is used to boost the variable selection procedure so that many factor-relevant predictors can be included in prediction. Finally, the supervised dynamic principal component analysis (sdPCA) method is adopted to account for the dynamic information in factor recovery. In simulation studies, we found that the proposed method adapts well to unknown degrees of sparsity and factor strength, which results in good performance even when the number of relevant predictors is large compared to the sample size. Applying to economic and environmental studies, the proposed method consistently performs well compared to some commonly used benchmarks in one-step-ahead out-sample forecasts.

A change in the wettability of liquid sodium due to sodium implantation was evaluated theoretically. Interface models between sodium and a sodium-implanted substrate metal were created, and their electronic states were calculated. The discrete variational Xα cluster method was used in the calculations. The calculations show that the bond order, indicating the strength of the covalent bonds between atoms, decreases within the substrate metal and increases at the interface between sodium and the substrate metal due to sodium implantation. Their ratio, the bond order ratio, increased with the increasing sodium implantation. Previous studies have shown that wettability is better as the bond order ratio increases. Therefore, from the calculations results, wettability improves with increasing sodium implantation. The wettability of sodium-implanted metals was experimentally evaluated using the contact angle of the sodium droplets. The contact angle decreased, and the wettability improved due to sodium implantation. The change rate in the contact angle increased with the bond order ratio. The experimental and calculation results correlate well, without contradiction. In conclusion, sodium implantation changes the electronic state of the interface, affecting the wettability of liquid sodium.

Background & Objective: Acne Vulgaris is a common skin disease, with 5 % prevalence in Pakistan and has a significant physiological, psychological, emotional and social impact on the population, our study aims to estimate its annual economic burden per person in Pakistan.Methodology: Economic burden was estimated by using Cost of Illness analysis. All types of costs, including direct medication costs, direct non-medical costs and indirect costs due to loss of work. Data were collected from online databases and literature reviews. Results: Cost of illness analysis estimated that the cost of Acne Vulgaris treatment varies for mild, Moderate and severe acne. Acne is causing an annual economic burden of PKR 1,92,366 PKR per person (direct cost is PKR 1,86,366 and indirect cost 6,000) for an expensive treatment and PKR 53,550 (direct cost is PKR 47550 and indirect cost 6,000) for a cheap treatment. Limitation: Being an LMIC, Pakistan needs extensive study on the pharmacoeconomic analysis of Acne for proper and rational allocation of resources. Conclusion: Acne has a significant economic burden in Pakistan. Even with significant impact of Acne, there is very minute work done about Acne in Pakistan.

Whole body electromyostimulation (WB-EMS) is frequently presented as a safe and attractive training technology, however evidence for this description is vague. Thus, the present study aimed to provide an overview of different aspects related to safety and attractiveness of WB-EMS in non-athletic cohorts. A systematic review of the literature according to PRISMA searched five electronic databases, two study registers and google scholar without language restrictions. Briefly, WB-EMS studies that reported adverse effects, loss to follow, withdrawal or attendance rates in non-athletic cohorts were included. Finally, 58 eligible studies were eligible. All studies applied low-frequency WB-EMS predominately 1-2x 20-25 min/week. Seventeen studies provided a superimposed protocol. While no study (n=56) reported serious adverse effects, four studies observed abnormal laboratory findings, albeit without clinical relevance. Loss to follow-up (10±11%) and withdrawal rate (5±6%) of WB-EMS trials were low, but did not differ from data for the non-training (10±12% and 4±6%) or exercise control groups (12±11% and 7±8%). In parallel, we observed high attendance rates (94±7%) in the WB-EMS groups that again did not relevantly vary from findings for the exercising control groups (n=20; 91±7%). WB-EMS can indeed be considered as a safe and attractive training technology for non-athletic cohorts, be it with or without health problems.

Our world is increasingly challenged by managing the impacts of natural disasters, particularly floods, which are frequent, dangerous, and costly. Traditional flood mapping methods, reliant on Optical satellites (MSI), struggle under cloud cover which is typical during such events. Synthetic Aperture Radar (SAR) offers a promising alternative with its cloud-penetrating capability, though its use has been limited due to complexity and data labeling challenges. This project aims to develop a SAR-based flood segmentation model that can rapidly and accurately map floods globally, with high adaptability to different flood types and regions. By utilizing deep learning and a novel transfer-learning technique that combines the strengths of Optical/MSI and SAR data, the model seeks to bypass the challenges of manual labeling and improve mapping accuracy. Initial results show the model's effective generalization across various flood events, with superior performance indicated by an Intersection over Union (IoU) of 0.72, outperforming existing methods and demonstrating promising capabilities in precise flood mapping.

Alpha-methyl-p-tyrosine (AMPT; also referred as metyrosine) is an approved medication for the treatment of pheochromocytoma. As a tyrosine hydroxylase inhibitor AMPT may be a potential candidate for the treatment of diseases involving catecholamine alterations. However, only small-scale clinical trials have tested AMPT repurposing in few other illnesses. Chronic fatigue syndrome (CFS) is an heterogenous disorder with genetically associated vulnerability of catecholamine metabolism (e.g. catechol O-methyltransferase polymorphisms) holding an important impact of environmental factors. The current case report compiles genetic and longitudinal biochemical data for over a year follow-up of one patient sequentially diagnosed with sustained overstress, neurasthenia, CFS, and POTS (postural orthostatic tachycardia syndrome) over a 10-year period, and reports patient’s symptom improvement in response to low-medium doses of AMPT.

Visible-light photocatalysis, particularly in its application to organic synthesis, has experienced a big renaissance in the past decade. The rational design of new photocatalysts with designed and improved photocatalytic properties, that at the same time circumvents the necessity of using scarce and toxic transition metals, will predictably play a key role in photocatalysis in the next few years. Although free-base porphyrins were identified some years ago as a promising, easily accessible and easily tunable class of organic photoredox catalysts, a systematic study on the effect of the electronic nature and of the position of the substituents on both the ground-state and the excited-state redox potentials of these compounds is still lacking. We have prepared a set of known functionalized derivatives of meso-tetraphenyl porphyrin containing different substituents either in one of the meso-positions or at a beta-pyrrole carbon and we have determined their ground- and (singlet) excited-state redox potentials. This survey has led us to conclude that the introduction of a carbonyl group at the beta-pyrrolic position strongly increases the facility of the monoelectronic reduction of the porphyrin both in the ground state and in the singlet excited state. We have also prepared a second set of four previously unknown benzoyl derivatives of meso-tetraphenylporphyrin, and we have confirmed the validity of our conclusions.

This qualitative study explores the transformative role of digital technologies in enhancing supply chain efficiency and marketing effectiveness across diverse industries. The integration of Internet of Things (IoT), artificial intelligence (AI), blockchain, and advanced analytics has reshaped organizational practices, enabling real-time data collection, analysis, and decision-making in supply chain management (SCM) and marketing. Through semi-structured interviews with 25 professionals, including supply chain managers, marketing executives, and IT specialists, insights were gathered into the adoption, integration, and impact of digital technologies within organizational contexts. Key findings highlight IoT's contribution to enhancing supply chain visibility, predictive maintenance, and operational efficiency through continuous monitoring and data-driven insights. AI technologies support demand forecasting, inventory optimization, and personalized marketing strategies, improving customer engagement and satisfaction. Blockchain enhances supply chain transparency, traceability, and security, reducing risks associated with fraud and ensuring compliance with regulatory standards. Advanced analytics provide organizations with actionable insights into consumer behavior and market trends, guiding strategic decision-making and optimizing marketing campaigns. Despite these benefits, organizations face challenges such as technological complexity, integration issues, data privacy concerns, and organizational resistance to change. Strategic planning, leadership support, and investment in digital infrastructure are essential for overcoming these challenges and maximizing the potential of digital technologies. Future research directions include exploring sustainability initiatives in digital SCM, advancing AI-driven analytics, and understanding digital transformation in emerging markets.

Hirschsprung disease (HSCR, incidence 1/5000 live births) is caused by failure of neural crest-derived precursors to migrate, survive, proliferate or differentiate during the embryonic development of the Enteric Nervous System (ENS), which could be disrupted by many factors, in-cluding inflammatory processes. The NF-κB family controls several biological processes includ-ing inflammation, neurogenesis and cell migration. With the aim of studying the potential role of NF-κB in HSCR, we have analyzed the expression of the NF-κB main subunits and other NF-κB-related genes by RT-qPCR in HSCR tissue samples (sub-divided in ganglionic and agan-glionic segments). We found a decreased gene expression of the NF-κB main subunit RelA/p65, but also of IkBα, TNF-α, TFGBR2 and ERBB3 in the pathologic distal aganglionic segments com-pared to the proximal ganglionic segments. Moreover, we could also confirm the lower protein expression of RelA/p65 in the aganglionic distal segments by immunofluorescence staining. Fur-ther, we show that the expression of RelA/p65 in the proximal segments concurs with lymphocyte infiltration in the bowel tissue, indicating a pro-inflammatory activation of p65 in the proximal ganglionic HSCR tissue in the patients analyzed. In all, our findings suggest that the modulation of NF-κB signaling in the neuro-enteric system does obviously contribute to the pathological ef-fects in HSCR.

Non-conventional resonances, both acoustic and photonic, are found in metallic particles with a toroidal nanopropeller geometry that is generated by sweeping a three-lobed 2D-shape along a spiral with twisting angle, α. For both optical and acoustic cases, the spectral location of resonances experiences a red-shift as a function of α. We demonstrate that the optical case can be understood as a natural evolution of resonances as the spiral length of the toroidal nanopropeller increases with α, implying a huge helicity dependent absorption cross section. In the case of acoustic response, two red-shifting breathing modes are identified. Additionally, even a small α allows the appearance of new low-frequency resonances, whose spectral dispersion depends on a competition between length of the generative spiral and the pitch of the toroidal nanopropeller.

Online food delivery services are rapidly growing in popularity, making customer satisfaction critical for company success in a competitive market. Accurate delivery time predictions are key to ensuring high customer satisfaction. While various methods for travel time estimation exist, effective data analysis and processing are often overlooked. This paper addresses this gap by leveraging spatial data analysis and preprocessing techniques to enhance the data quality used in Bayesian models for predicting food delivery times. We utilized the OSRM API to generate routes that accurately reflect real-world conditions. Next, we visualized these routes using various techniques to identify and examine suspicious results. Our analysis of route distribution identified two groups of outliers, leading us to establish an appropriate boundary for maximum route distance to be used in future Bayesian modelling. The spatial analysis revealed that these outliers were primarily deliveries to the outskirts or beyond the city limits. By refining the data quality through these methods, we aim to improve the accuracy of delivery time predictions, ultimately enhancing customer satisfaction.

This article provides exact analytical formulae for various kinds of rainbow step barrier options. These are highly flexible and sophisticated multi-asset barrier options based on the following principle : the option life is divided into several time intervals on which different barriers are monitored w.r.t. different underlying assets. From a mathematical point of view, new formulae are provided for the first passage time of a multidimensional geometric Brownian motion to a boundary defined as a step function. The article shows how to implement the obtained valuation formulae in a simple and very efficient manner. Numerical results highlight a strong sensitivity of rainbow step barrier options to the correlations between the underlying assets.

Artificial intelligence methods, especially artificial neural networks (ANNs), have increasingly been utilized for the mathematical description of physical phenomena in (metallic) material processing. Traditional methods often fall short in explaining the complex, real-world data ob-served in production. While ANN models, typically functioning as "black boxes," improve pro-duction efficiency, a deeper understanding of the phenomena, akin to that provided by explicit mathematical formulas, could enhance this efficiency further. This article proposes a general framework that leverages (CAE) ANNs to explain predicted results alongside their graphical presentation, marking a significant improvement over previous approaches and those relied on expert assessments. Unlike existing Explainable AI (XAI) methods, the proposed framework mimics the standard scientific methodology, utilizing minimal parameters for the mathematical representation of physical phenomena and their derivatives. Additionally, it analyzes the relia-bility and accuracy of the predictions using well-known statistical metrics, transitioning from deterministic to probabilistic descriptions for better handling of real-world phenomena. The proposed approach addresses both aleatory and epistemic uncertainties inherent in the data. The concept is demonstrated through the hot extrusion of aluminum alloy 6082, where CAE ANN models and predicts key parameters, and ChatGPT explains the results, enabling researchers and/or engineers to better understand the phenomena and outcomes obtained by ANNs.

The convective hot air drying technology can cause physicochemical, nutritional, and organoleptic losses in mango (Mangifera indica). Therefore, mango dehydration technologies were compared through a Systematic Literature Review to identify the effects on mango’s physicochemical, nutritional, and organoleptic properties. The bibliographic and theoretical results were analyzed. Of the 76 resulting articles, it was found that the countries with authors who participated most in the scientific production were those related to mango production or importation. Furthermore, the freeze-drying technology allows operating at lower temperatures than convective hot air drying, contributing to the preservation of ascorbic acid, among other compounds. The refractance window has the shortest operation time to obtain moisture values between 10 and 20%. The dehydrated samples using the refractance window are smooth, homogeneous, non-porous, and comparable to the color obtained with freeze-drying, which is acceptable for industrial applications.

Various symptoms have been reported to persist beyond acute phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which is referred as long coronavirus disease 19 (long COVID-19). Over 65 million individuals suffer from long COVID-19. However, the causes of long COVID-19 have been largely unknown. Since long COVID-19 symptoms are observed throughout the body, vascular endothelial dysfunction may be a strong candidate to induce long COVID-19. The angioten-sin-converting enzyme 2 (ACE2), the entry receptor of SARS-CoV-2, is ubiquitously expressed in endothelial cells. We previously found that the risk factors for athero-sclerotic cardiovascular disease (ASCVD) and the history of ASCVD can be the risk for severe COVID-19, suggesting a contribution of pre-existing endothelial dysfunction to severe COVID-19. Here, we show a significant association of endothelial dysfunction with development of long COVID-19 and show that biomarkers for endothelial dysfunction in patients with long COVID-19 are also crucial players in development of ASCVD. We consider the influence of long COVID-19 on development of chronic kidney disease (CKD) and ASCVD. Furthermore, we suggest the therapeutic interventions for long COVID-19 by considering endothelial dysfunction as the treatment tar-gets for long COVID-19. Such interventions may prevent pandemic of CKD and ASCVD in post COVID-19 era.

Currently, there is a high interest in smart sensors and integrated composite materials in various industries such as construction, aviation, automobile, medical, information technology, communication, and manufacturing. Here, a new conceptual design for a force and temperature sensor system is developed by integrating fiber optic Bragg grating sensors embedded within composite materials, and a mathematical model is proposed that allows one to estimate strain and temperature based on signals obtained from optical Bragg gratings. This is important for understanding the behaviors of sensors under different conditions and for creating effective monitoring systems. Describing the strain gradient distribution, especially considering different materials with different values of Young's modulus, provides insight into how different materials respond to applied forces and temperature changes. The shape of the strain gradient distribution was obtained, which is a quadratic function with a maximum value of 1500 µ, with a maximum value at the center of the lattice and a symmetrically decreasing strain value with distance from the central part of the fiber Bragg grating. With axial strain at the installation site of the Bragg grating sensor under applied force values ranging from 10 to 11 N, the change in strain was linear. As a result of theoretical research, it was found that the developed system with fiber-optic sensors based on Bragg gratings embedded in composite materials is resistant to external influences and temperature changes.

Objective: To explore the functions that physical activity (PA), life satisfaction, and self-efficacy have in the process of coping with anxiety among Chinese college students, and to explore the mediating role of life satisfaction and self-efficacy in this process. Methods: Participants were 358 college students (186 males, 172 females, mean age 20.88, SD=±1.80). Psychosocial tests including the Physical Activity Rating Scale (PARS-3), College Student Life Satisfaction Scale (CSLSS), General Self-Efficacy Scale (GSES), and Generalized Anxiety Disorder Scale (GAD-7) were completed. Correlations between variables were calculated using Pearson's test. The mediation model was tested using the SPSS 26.0 PROCESS macro and regression bootstrap. Results: Physical activity showed a negative correlation with anxiety (β= -0.1617, p < 0.001), life satisfaction and self-efficacy played a role in the relationship between physical activity and anxiety, and, more importantly, physical activity affected anxiety through the parallel mediating effects of life satisfaction and self-efficacy, with a total mediating effect of 55.34%. Conclusion: By increasing college students' participation in physical activity, it helps to promote the growth of their life satisfaction and self-efficacy, which is the key to reducing anxiety and promoting college students' mental health.

The text examines the assessment of learning in science and the use of technologies like Scratch to enhance this process. Assessment is crucial for measuring progress and guiding teaching, especially in science where it fosters scientific skills and understanding. The study focuses on third-year secondary education students, evaluating the impact of Scratch on their learning compared to a gamification approach. Scratch, developed by MIT, is effective in interactive teaching and improves academic performance and student motivation. The research used an experimental design with a control group (gamification) and an experimental group (Scratch), measuring acquired knowledge through pretests and posttests. Results show that both groups significantly improved their knowledge, although the control group had a higher baseline initially. Students valued collaboration and playful learning. However, they faced technical challenges and highlighted the importance of teamwork. The study concludes that Scratch has great educational potential, suggesting improvements such as redesigning activities and increasing work sessions to maximize its effectiveness in learning and student motivation.

The estuarine exchange flow increases longitudinal dispersion of passive tracers and traps sinking particles, potentially creating an estuarine turbidity maximum (ETM): a localized maximum of suspended particulate matter concentration in an estuary. The ETM can have many implications - dead zones due to increased turbidity or hypoxia from organic matter decomposition, naval navigation challenges, and other water quality problems. Using timescales, we investigate how the interaction between exchange flow and particle sinking leads to ETMs by modeling a sinking tracer in an idealized box model of the Total Exchange Flow (TEF) first developed by Parker MacCready. Results indicate that the balance of particle sinking and vertical mixing is critical to determining ETM size and location. We then focus on the role of ecology in ETM formation through the use of The Peter-Parker Model: a new biophysical model which combines the TEF box model with a Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD) model, the likes of which were first developed by Peter J.S. Franks. Detritus sinking rates similarly influence detritus peak concentration and location (an ETM), but detritus ETMs occur in a different location than the sinking tracer due to the influence of the biological factors which create a time lag of about 1 day. Lastly, we characterize the flow of the models with a dimensionless parameter that compares timescales and summarizes the dynamics of the sinking tracer in ETM formation and can be used across systems.

A two scalar field model that incorporates non Riemannian Measures of integration or usually called Two Measures Theory (TMT) is introduced, in order to unify the early and present universe. In the Einstein frame, a K-essence is generated and as a consequence for the early universe, we can have an Inflation for the very early universe and then, after inflation, an early dark energy period and a late dark energy period for the present universe dark, both dark energy epochs have a consistent generation of dark energy (DE), dark matter (DM) and stiff matter. This is obtained when the scale invariance is introduced and then is spontaneously broken from the integration of the degrees of freedom associated with the modified measures. The resulting effective potentials and K-essence in the Einstein frame produce the three flat regions corresponding to the different epochs mentioned before. For the first flat region, we can associate an inflationary universe. Also assuming this first plateau, we study the inflation in the framework of the slow-roll approximation. In this scenario under the slow roll approximation, we obtain a linear combination that is a constant. The corresponding cosmological perturbations in our model are determined and we also obtain the different constraints on the parameter-space from the Planck data. The slow roll approximation can be arranged so that the transition from inflation to the next flat region can be achieved without problems. In the following two flat regions, in addition to the inflation phase, representing the Early Dark Energy and Late Dark Energy Periods, with DE and also the DM, do not need to be introduced separately, they are instead a result of a K-essence induced by the multi measures, multi field theory. Therefore the scalars generate both the DE and the DM . Also a stiff matter component is automatically generated from the K-essence theory from two scalar fields. From the perturbative analysis associated to the perturbation solution of background, we find a correlation between the two scalars. Besides, we obtain that our model during the dark epoch has a behaviour of tracking freezing mode

This qualitative research explores consumer perceptions of supply chain responsiveness and its impact on brand loyalty within the apparel industry. The study investigates how consumers perceive supply chain practices such as reliability, agility, and sustainability, and examines their influence on brand loyalty decisions. Thirty participants, representing diverse demographics and purchasing behaviors, were interviewed to gather insights into their awareness, expectations, and experiences related to supply chain responsiveness. Findings reveal that consumers prioritize supply chain reliability, expecting brands to consistently deliver high-quality products, accurate sizing, and timely responses to market trends. Sustainability practices also emerged as a significant factor, with consumers favoring brands that demonstrate ethical sourcing and environmental responsibility. Technology plays a crucial role in enhancing supply chain responsiveness, as consumers value real-time updates, personalized experiences, and seamless transactions. Moreover, the study underscores the impact of supply chain disruptions on brand trust and loyalty, highlighting the importance of resilience and contingency planning in supply chain management. Brands that effectively navigate disruptions through agile strategies can enhance consumer trust and loyalty, even in challenging circumstances. Overall, this research contributes to understanding the intricate relationship between supply chain dynamics, consumer perceptions, and brand loyalty in the apparel industry. It offers practical implications for apparel brands seeking to enhance consumer satisfaction, differentiate themselves in a competitive market, and foster sustainable growth through strategic supply chain management.

Molecular-scale density fluctuations at equilibrium produce cavities in a liquid and can be analyzed to shed light on the statistics of the number of molecules occupying observation volumes of increasing radius. An information theory approach led to the conclusion that these probabilities should follow a Gaussian distribution function. This prediction has been confirmed by computer simulations in different liquid models if the size of the observation volume is not large. The reversible work of cavity creation is exactly linked to the probability of finding zero molecules in a given observation volume. The Gaussian formula for the latter probability is scrutinized to arrive at the enthalpy and entropy changes associated with cavity creation. The reversible work of cavity creation has a purely entropic origin due to the solvent-excluded volume effect produced by the inaccessibility of a given region of the configurational space. The consequent structural reorganization of liquid molecules leads to exactly compensating enthalpy and entropy changes. These results are in line with those obtained in a direct statistical mechanical study by Lee.

In the Lemongrass (Cymbopogon citratus), the investigations showed a wide range of active molecules their biological properties. However, most of these studies were conducted on the wid varieties, while cultivated plan addressed. This study aimed to characterize the biomolecules and biological activities of Lemongrass growing us African conditions sons in in Marocco. Marocco. Phenolic compound profiles of aqueous (AE) E) ethanol ethanol (EE), (EE), and methanol (ME) extract: fractions were obtained with steric exclusion chromatography on Sephadex 050 gel and identified by LC-MS/MS polyphenols (TPC), flavonoids (TFC), and antioxidant activities (FRAP: scavenging value and TAC: Total Antioxidant C the fraction were evaluated as well as the antimicrobial activity Obtained results showed that the ME contained e compounds (ie. Apigenine-7-0-rutinoside and myricitine-3-0-rutinoside). The AE showed the presence of five mole kaemiferol-3-0-glucuronide), while EE showed the presence of three molecules (Le. Quercetine-3-0-rutinoside). Reg chemical characterization, the rization, e highest value of Total phenolic content (TPC) was obtained in conten btained in AE ΑΕ (25) (4.60-0.29 mg highest value of Total flavonoids content (TFC) was obtained Ined in ME (29) (0.7±0.08 mg/g). Concerning the antioxide the highest FRAP was obtained in ME (29) (97.89%) and the highest total antioxidant capacity (TAC) was obtained (89.89%) Correlation between FRAP, TPC, and TFC was noted poly in fractions of AE and ME. All tested extracts of and their fractions showed a significant antimicrobial effect. The lowest minimum inhibitory concentration (MIC) wa for ME against E. col. Extracts biological activities and their fractions were governed by their active molecules. Ther new and clarify a novel aspect of bioactive molecules in the extracts of cultivated C. citratus Equaly, throughout this we clarified the relationship between identified molecules and their biological properties including antioxidant and comparative studies new activities, which is new for the study area. This study is suggested to be a reference. assays of other biological activities for the study plant

Cerebral aneurysms come in a wide range of shapes and sizes, they can evolve over time and present significant changes. It is generally accepted that large aneurysms are more prone to rupture, but the rupture of small aneurysms has also been observed, indicating the presence of additional risks factors. The aim of this study is to assess the effects of the aneurysm size and wall thickness on its rupture risk by using fluid-structure interaction simulations. Six patient-specific geometries were chosen, four were used for studying the size effect and two for studying the thickness effect. Additional cases where the aneurysm was removed were included. It was found that thinner walls suffer from significantly greater stresses, whereas an increment in size means, in general, lower wall shear stress and greater equivalent stress. By removing the aneurysm, it could be noted that at the rupture point, the reduction in the time-averaged wall shear stress was 75%. Although the size of an aneurysm has a great impact in its rupture risk, its wall thickness needs to be considered, since even maintaining its size, the aneurysm could suffer from a thin-ning of its walls that can lead to structural failure.

This qualitative study investigates how supply chain disruptions affect brand loyalty by analyzing consumer experiences during crises. Through in-depth interviews with diverse participants, the research explores the nuanced factors shaping consumer perceptions and behaviors when supply chains face challenges. Findings reveal that trust is pivotal, with transparent communication and consistent updates fostering consumer confidence and loyalty. Brand reputation emerges as crucial, influencing perceptions of reliability and ethical conduct during disruptions. Effective crisis management strategies, including agility and proactive communication, mitigate negative impacts on brand loyalty. Consumer decision-making is influenced by the availability of substitutes and perceptions of disruption severity, highlighting the importance of brand resilience and continuity. Emotional responses, such as frustration and anxiety, significantly influence consumer loyalty, underscoring the role of empathetic engagement and support from brands. Aligning with consumer expectations and delivering on promises are essential for sustaining loyalty and reducing the risk of consumer defection. The study concludes that navigating supply chain disruptions requires brands to prioritize trust, reputation, crisis management, consumer-centric strategies, emotional intelligence, and alignment with consumer expectations. These insights contribute to a deeper understanding of consumer behavior in crisis contexts and provide strategic implications for brands seeking to enhance resilience and maintain loyalty in dynamic market environments.

This study presents a fit-for-purpose evaluation of commercially available portable sensor systems, measuring PM, NO2 and/or BC, through extensive lab- and field benchmarking. The main aim of the study is to identify sensor systems that can be used for mobile monitoring by citizens to assess dynamic exposure in ambient air. After an initial literature study and market search resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked in laboratory and real-word conditions. We evaluated comparability to reference analyzers, sensor precision and sensitivity to temperature, humidity and O3. Moreover, we evaluated if accuracy can be improved by the lab and field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM and BC, but maturity of the tested NO2 sensors is still low and additional efforts are needed in terms of signal noise and calibration. The horizontal accuracy of the build-in GPS was generally good achieving a &lt;10m horizontal accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and exposome impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.

Good Boussinesq equations will be considered in this work. First we apply three combined compact schemes to approximate spatial derivatives of good Boussinesq equations. Then three fully discrete schemes are developed based on symplectic scheme in time direction, which are sympletic-structure preserving.Meanwhile, the convergence and conservation of the fully discrete schemes are analyzed. Finally, we present numerical experiments to confirm our theoretical analysis. Both our analysis and numerical test indicate that the fully discrete schemes are efficient in solving the spatial derivative mixed equation.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and communication, anxiety, hyperactivity, and restricted interest for specific subjects. In addition to the genetic factors, multiple environmental factors have been related to the development of ASD. Animal models can serve as crucial tools for understanding the complexity of ASD and identifying potential therapeutic strategies. In this study, a chemical model of ASD has been developed in zebrafish by exposing embryos to valproic acid (VPA) from 4 to 48 hours post-fertilization. After the exposure, embryos were transferred to fish water and the effects on behavior and neurotransmitters profile were analyzed at both larval and adult stages. Larvae from VPA-treated embryos showed hyperactivity and decreased visual and vibrational escape responses, as well as an altered neurotransmitters profile, with increased glutamate and decreased acetylcholine and norepinephrine levels. Adults from VPA-treated embryos exhibited impaired social behavior characterized by larger shoal sizes and a decreased interest for their conspecifics. Neurotransmitter analysis revealed a significant decrease in dopamine and GABA levels in the brain. These results support the interest of this model in the study of ASD.

Objective: Evaluation of patients with prosthetic valves who developed infective endocarditis by comparing treatment outcomes in both early- and late-onset IE episodes following prosthetic valve replacement surgery. This study sought to conduct a comprehensive assessment of the efficacy of these methodologies. The insights derived from this assessment will be utilized to enhance the quality of care for individuals with infective endocarditis who have received prosthetic valve replacement surgery. Results: During the period of investigation (January 2018 - December 2022), 78 patients diagnosed with infective endocarditis (IE) on prosthetic valve were admitted to the Infectious Diseases Department of the "Dr. Carol Davila" Central Military Emergency University Hospital in Bucharest. In 28 cases (35.8%), the onset of PVE occurred within 12 months of surgery (early onset), whereas in 50 patients (64.2%), the onset occurred more than 12 months after surgery (late onset). The mortality rate was 35.9% (53.6% among the early onset patients and 26% among the late-onset patients). Among patients who received surgical and medical therapy, the mortality rate was 29.6%, whereas among those who underwent only medical therapy, a 39.2% mortality rate was reported. According to the extracted data, antibiotic therapy was successful in 72.6% of patients. In contrast, a combination of surgical and drug-based approaches resulted in a cure in 76.1% of the patients. The most common etiological agent was Staphylococcus aureus (38.5%), followed by Enterococcus faecalis (26.9%), and Streptococcus mitis (10.3%). The mortality rate of patients with S. aureus was 29.2%, indicating the severity of this infectious agent. Conclusions: Prosthetic valve endocarditis (PVE) is a serious condition associated with a high mortality rate both in the short and long term. Regardless of the therapy used, the risk of death remains high. All patients with PVE who survived received effective early treatment, highlighting the need for prophylactic measures.