Objective: The Covid-19 pandemic has raised significant concerns about public health, particularly in terms of mental well-being due to heightened fear and uncertainty. The findings of this study are based on a survey conducted to evaluate the mental health status of the general population in Croatia during the Covid-19 pandemic. Methods: A survey conducted randomly and cross-sectionally included 588 respondents from all 21 counties in Croatia. The survey gathered demographic data and assessed various factors related to pandemic response measures and mental health using the Mental Health Continuum-Short Form (MHC-SF) scale. Results: Despite feeling adequately informed about Covid-19 (76.0%), most respondents (60.8%) expressed concerns about their loved ones during the pandemic. There were significant numbers who felt there was no risk of infection (50.9%) or believed they would not get infected (40.2%), while 72.4% were content with government measures. Statistical analysis indicated that mental health was not significantly different between genders, but age-related differences were evident, with those under 21 experiencing the most distress. The lowest level of psychological and social well-being was observed in respondents who were unemployed. Conclusions: The study identifies vulnerable groups in the Croatian population during the pandemic, including younger individuals, those on parental leave, students, and the unemployed, who exhibited worse mental health. The importance of implementing targeted mental health interventions to support these vulnerable groups is highlighted by these findings.

The increasing focus on sustainability and the adoption of green practices across industries underscore the necessity of equipping future professionals with competencies in implementing sustainable solutions. This study explores the perceptions of former students from two departments within the technological sector towards sustainability practices. A cross-sectional online survey was carried out among alumni from two programs at the University of Thessaly, a university recognized for its commitment to sustainability and green initiatives as a member of the INVEST European University alliance. The survey questionnaire included background inquiries and 16 statements designed to gauge alumni perspectives towards sustainability practices. Specifically, it aims to assess their views through self-assessment and compare differences between the two alumni groups. Responses were collected on a 5-point Likert scale ranging from strongly disagree to strongly agree. A total of 300 graduates from the Computer Science and Telecommunications as well as Electrical Engineering undergraduate programs were encouraged to take part in the survey, achieving a response rate of 69%. Of those who responded, 61% (n = 126) represented the Computer Science and Telecommunications group, while 39% (n = 81) were from the Electrical Engineering program. Our findings indicate a generally positive attitude towards sustainability, with statistically significant differences in perspectives on the implementation of sustainable technologies and stakeholder engagement. These results underscore the necessity of integrating sustainability education deeply within the curricula of technological programs to cultivate a workforce capable of addressing future environmental challenges. This study illuminates the critical role of educational frameworks in shaping the sustainability competencies of technology professionals.

Due to growing environmental concerns and stringent emissions regulations, optimizing the fuel consumption of marine propulsion systems is crucial. This work deals with the potential in an LNG ship propulsion system to reduce fuel consumption through controlled load distribution between engines in Dual Fuel Diesel Electric (DFDE) plant. Based on cyclical data acquisitioning measured on board and using an optimization model, the study evaluates different load distribution strategies between set up according to the optimization model results and automatic (equal) operation to determine their effectiveness in improving fuel efficiency. The analysis includes scenarios with different fuel types, including LNG, MDO and HFO, at different engine loads. The results indicate that load distribution adjustment based on the optimization model results significantly improves fuel efficiency compared to conventional methods of uniform load distribution controlled by power management systems almost in all load intervals. This research contributes to the maritime industry by demonstrating that strategic load management can achieve significant fuel savings and reduce environmental impact, which is in line with global sustainability goals. This work not only provides a framework for the implementation of more efficient energy management systems on LNG vessels, but also sets a benchmark for future innovations in maritime energy optimization as well as in the view of exhaust emission reduction.

A review of literature, supporting the view on the psychophysical origins of some acceptance effects of cyber-physical systems (CPSs), is presented and discussed in the paper. Psychological effects like the reactance to a robot or the uncanny valley phenomenon suggest that CPSs are perceived as a special type of ‘being’, a phylogenetically emergent category, or a novel ontology in a philosophical sense, culturally developing as a function of the social brain. Justification of this view is provided by the psychophysically-relevant human responses to technologically and socially ambiguous stimuli on the one hand, and the probabilistic independence of the proposed ontology to similar ontologies, subjectively experienced by the human, on the other. The results of the presented in the paper analysis demonstrate the feasibility of the proposed hypothesis of ontological ‘near independence’ of the distribution of the probabilistic psychophysical processes in response to the cyber-physical stimulus as a socially evolving phenomenon.

Oleogels are of high interest as promising substitutes for trans fats in foods. An emulsion-templated method was used to trap olive oil in the chitosan crosslinked with vanillin matrix. Oil in water emulsions (50:50 w/w) with different chitosan content (0.7 and 0.8% w/w) with constant vanillin/chitosan ratio (1.3) were air-dried at different temperatures (50, 60, 70 and 80ºC) and freeze-dried (-26ºC and 0.1 mbar) to produce oleogels. Only falling-rate periods were determined during air-drying kinetics and were successfully modelled with empirical and diffusional models. At drying temperature of 70ºC the drying kinetics were the fastest. Viscoelasticity of oleogels showed that elastic modulus significantly increased after drying at 60 and 70ºC, and those dried at 50ºC and freeze-dried were weaker. All oleogels showed high oil binding capacity (> 91%), but the highest values (> 97%) were obtained in oleogels with a threshold elastic modulus (50,000 Pa). Oleogels color depended on drying temperature and chitosan content (independent of the drying method). Significant differences were observed between air-dried and freeze-dried oleogels with respect to oxidative stability. Oxidation increased with air drying time regardless of chitosan content. Found results indicated that drying conditions must be carefully selected to produce oleogels with specific features.

Background: Surgical parameters of phacoemulsification can have a significant impact on behavior of anterior hyaloid membrane (AHM). Methods: In a prospective study using anterior segment optical coherence tomograph the attachment or detachment of AHM of 82 eyes were examined after uneventful phacoemulsification preoperatively and postoperatively over a 1-year period. The impact of capsulorhexis size, number of hydrodissections, difficulty of nucleus rotation, nuclear sclerosis grade, cumulative dissipated energy (CDE), ultrasonic time, total surgical time, difficulty of irrigation/aspiration, intensity of capsular polish, weakness of zonular fibers, presence of lens materials in Berger's space (LM-BS), and fluid usage were investigated related to the behavior of AHM. Results: In presence of zonular weakness and high CDE, a significant linear trend was observed regarding anterior vitreous detachment (AVD) at all postoperative times. Similarly, AVD is observed at 1-month, 3-month, and 1-year follow-up in cases of high nuclear sclerosis grade and high fluid usage. A significant linear trend was observed in the case of zonular weakness, hard nucleus and extensive capsular polish with LM-BS, while CDE, total surgical time, and fluid usage were significantly higher in these cases. Conclusions: Zonular weakness, high CDE, hard nucleus and high fluid usage are risk factors of postoperative AVD.

Peritoneal fluid is an ovarian exudate from the growing follicle or corpus luteum. Therefore, the free concentrations of estrogens and progesterone are always much higher than in plasma, especially after ovulation. The peritoneum is not vascularised, and peritoneal implants and the superficial portion of deep endometriosis are likely influenced mainly by peritoneal fluid. Follicular phase progesterone concentrations are as high as during the luteal phase in plasma. This explains that most peritoneal implants are rarely proliferative and out of phase with the endometrium. From some 5 mm of depth onwards, endometriosis is rather influenced by plasma hormone concentra-tions, and the deeper parts can be proliferative as the endometrium. Because of these progesterone concentrations, progesterone resistance has to be postulated, permitting endometriosis lesions to initiate and develop. This opens the discussion of whether endometriosis is similar to the basal endometrium. These peritoneal fluid concentrations are important to understand the natural history and medical therapy of endometriosis. Most medical therapies decrease ovarian function and affect peritoneal fluid steroid hormone concentrations. It is suggested that the efficacy of medical therapy for endometriosis-associated pain is a consequence of the decreased estrogen concentrations in the peritoneal cavity and that the local effect of progestins may not be determinant for pain relief. If this is true, a history of endometriosis should not be considered a contraindication for hormone re-placement therapy.

This article examines the diagnosis of the Agricultural Innovation System (SIA) in the department of Tolima, Colombia, as part of a project led by the Colombian Ministry of Agriculture and Rural Development and the Technological University of Pereira (TUP), which also evaluated the National Agricultural Innovation System (NAIS) in regions such as Chocó, Bolívar, and Meta. A methodology was used that involved a survey with 58 questions on a Likert scale to 300 participants, evaluated with congruence and relevance indexes, identifying key variables in the operation of the Agricultural Innovation System (AIS). A survey was also applied to actors of the National Innovation System for Higher Education in Agriculture, A survey was also applied to map the participating actors in the regional agricultural innovation systems of Tolima to identify gaps in extension, innovation, development, sustainability, ICT, education and training. Among the conclusions, it stands out that the associativity subsystem presents the lowest lag and is close to a score of two on the scale of gaps, evaluation carried out among the five subsystems including extension, ICT, environmental aspects, and pub-lic policy. The department of Tolima shows low performance in innovation and ICT, while the extension is less lagging. In Chaparral there is a general lag, with innovation being the worst evaluated subsystem. Rovira obtains high scores in most subsystems, although innovation and ICT have lower scores. At the national and regional levels, innovation is low, and articulation among NARS actors is insufficient, which highlights the need to promote good practices, strategies, and projects.

Accurate crop diseases classification is crucial for ensuring food security and enhancing agricultural productivity. However, existing crop disease classification algorithms primarily focus on a single image modality and typically require a large number of samples. Our research counters these issues by using pre-trained Vision-Language Models (VLMs), which enhances multimodal synergy for better crop disease classification than traditional unimodal approaches. Firstly, we apply the multimodal model Qwen-VL to generate meticulous textual descriptions for representative disease images selected through clustering from the training set, which will serve as prompt text for generating classifier weights. Compared to using solely the language model for prompt text generation, this approach better captures and conveys fine-grained and image-specific information, thereby enhancing prompt quality. Secondly, we integrate the cross-attention and the SE (Squeeze-and-Excitation) attention into the training-free mode VLCD (Vision-Language model for Crop Diseases classification) and the training-required mode VLCD-T (VLCD-Training) respectively for prompt text processing, enhancing classifier weights by emphasizing key text features. Experimental outcomes conclusively prove our method’s heightened classification effectiveness in few-shot crop disease scenarios, tackling data limitations and intricate disease recognition issues. It offers a pragmatic tool for agricultural pathology and reinforces the smart farming surveillance infrastructure.

Alzheimer’s disease (AD), the most common cause of dementia, is characterized by disruptions in memory, cognition, and personality, significantly impacting morbidity and mortality rates among older adults. However, the exact pathophysiological mechanism of AD remains unknown, and effective treatment options for AD are still lacking. Human induced pluripotent stem cells (iPSC) are emerging as promising platforms for disease research, offering the ability to model genetic mutations associated with various conditions. Patient-derived iPSCs are useful for modeling neurodegenerative and neurodevelopmental disorders. In this study, we generated AD iPSCs from peripheral blood mononuclear cells obtained from a 65-year-old patient with AD carrying the E682K mutation in the amyloid precursor protein (APP) gene. Cerebral organoids derived from AD iPSCs recapitulated the AD phenotype, exhibiting significantly increased levels of tau protein. Our analysis revealed that an iPSC disease model of AD is a valuable assessment tool for pathophysiological research and drug screening.

Voltage-gated potassium (Kv) channels and hyperpolarization-activated cyclic nucleotide-gated (HCN) channels share similar structures but have opposite gating polarity. Kv channels have a strong coupling ( >109) between the voltage sensor (S4) and the activation gate: when S4s are activated the gate is open to >80%, but when S4s are deactivated, the gate is open < 10-9 of the time. Using noise analysis, we show that the coupling between S4 and the gate is < 200 in HCN channels. In addition, using voltage clamp fluorometry, locking the gate open in a Kv channel drastically altered the energetics of S4 movement. In contrast, locking the gate open or decreasing the coupling between S4 and the gate in HCN channels had only minor effects on the energetics of S4 movement, consistent with a weak coupling between S4 and the gate. We propose that this loose coupling is a prerequisite for the reversed voltage gating in HCN channels.

This study investigated changes in the average BMI of 5th and 6th grade elementary school students in Korea and provided foundational data to suggest the role of physical education for student health and set future directions. The 2019–2021 Physical Activity Promotion System (PAPS) of the Korean Ministry of Education was used. Data corresponding to 5th and 6th grade students (124,693 from 2019, 126,226 from 2020, and 117,809 from 2021) in 1,208 elementary schools in Korea were collected. The BMI was obtained by dividing weight by the square of height (㎏/m2). Repeated measures ANOVA was conducted for data analysis, and confidence intervals were modified through the Bonferroni correction for multiple comparisons. The Greenhouse-Geisser correction was used for effects test. The study findings are: First, the average BMI of 5th and 6th grade elementary school students in Korea increased significantly in 2021 compared to 2019 and 2020. Second, changes in the yearly average BMI showed a significant difference depending on gender and grade. Obesity among 5th and 6th grade elementary school students in Korea increased steadily in 2019–2021, which may be due to a decrease in students’ physical activity. Male students showed a steeper increase, regardless of grade.

This study examines if enterprises’ digital transformation enhances their sustainable development capabilities and reduces carbon emissions, thus enhancing carbon neutrality performance and implementing the "dual-carbon" strategy. It specifically explores the impact of Chinese firms’ digital transformation on carbon neutrality performance in 30 provinces and municipalities in China from 2011 to 2021. Based on the Difference-in-Difference method and spatial econometric modeling, this study finds a U-shaped relationship between enterprise digital transformation and carbon performance, with spatial spillover effects. It also finds that converting environmental charges into taxes can significantly improve carbon performance. In terms of the mechanism of action, digital transformation affects carbon performance by influencing energy use efficiency and adjusting the level of industrial structure advancement and rationalization. In terms of heterogeneity, this U-shaped relationship exists only in the eastern and central regions, and the significance is more substantial in the east; in addition, the impact of enterprise digital transformation on carbon performance is more evident in regions with higher R&D intensity and higher economic development levels. These findings imply that the government should further encourage and guide enterprise digital transformation, monitor the effects of environmental protection policies and select and implement carbon emission reduction strategies according to local conditions to improve carbon performance.

the intermittency and variability of these permeated Distributed Generators (DGs) could critically cause many security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. And then, four risk indices EENS, PLC, EFLC and SI were established to reflect the system risk level of distribution system. For the certain mathematical distribution of the DGs' output power, a developed PEM (point estimate method)-based method was proposed to calculate these four system risk indices. In this developed PEM-based method, enumeration method was used to list the states of distribution systems, an improved PEM was presented to deal with the uncertainties of DGs and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by the tests of a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments.

Corrugated board is a composite material characterized by strong orthotropy in both the elastic and plastic phases. Additionally, due to its layered structure, which consists of alternately arranged flat and wavy layers of paper, its mechanics becomes complicated. Therefore, a precisely selected set of laboratory tests is needed to correctly identify all the necessary material parameters of cardboard. The work attempts to define a full set of laboratory tests in order to determine material parameters describing the linear-elastic, orthotropic behavior of cardboard and the basic parameters defining popular plasticity criteria, such as the asymmetric orthotropic Hoffman criterion. For this purpose, sensitivity analysis and numerical models of several selected basic laboratory tests were used. Since the aim of the work is to choose appropriate laboratory tests necessary to correctly determine the material parameters of corrugated board (not its individual layers), the numerical models do not contain detailed cardboard geometry, but only its homogenized representation in the form of the flat shell models. All numerical models are based on the nonlinear finite element method and constitutive modelling in the form of UMAT subroutines implemented in the ABAQUS software. Based on the analyses, appropriate measurements and laboratory tests were indicated that are most sensitive to the material parameters sought.

This article focuses on obtaining the analytical solutions for parabolic Volterra integro- differential equations in d-dimensional with different types frictional memory kernel. Based on theories of Laplace transform, Fourier transform, the properties of Fox-H function and convolution theorem, analytical solutions of the equations in the infinite domain are derived under three frictional memory kernel functions respectively. The analytical solutions are expressed by infinite series, the generalized multi-parameter Mittag-Leffler function, Fox-H function and convolution form of Fourier transform. In addition, the graphical representations of the analytical solution under different parameters are given for one-dimensional parabolic Volterra integro-differential equation with power-law memory kernel. It can be seen that the solution curves subject to Gaussian decay at any given moment.

This study empirically analyzes the effectiveness of resource optimization utilizing artificial intelligence (AI) within cloud computing environments. It compares systems that have been transitioned from a Monolithic structure to Microservices Architecture (MSA) with those adopting a simple Rehost strategy, to validate the operational efficiency of two systems whose resource efficiency has been enhanced compared to traditional legacy systems. The research is based on systems that determined resource efficiency post-cloud migration using APM tools. It points out the limitations of traditional heuristic operation methods in resource optimization, which lead to issues such as application performance degradation, resource over-allocation, and increased operational costs. This study aims to overcome the conventional resource optimization standards that depended on the average peak usage of CPU and memory infrastructure, by introducing AI-based optimization tools, and applying on-premise standards to cloud and container environments to achieve resource optimization. The paper emphasizes the importance of resource optimization through AI-based automation tools, exploring the possibilities of resolving real-world application performance issues in cloud environments, reducing unnecessary resource usage costs, and cutting down on labor risks and operational expenses. Through this, it presents strategic directions on how AI technology can offer financial and operational advantages in managing cloud resources.

Autoimmune diseases of the liver and biliary tract require timely and accurate diagnosis. This study evaluates the D-tek panel (D-Tek, Mons, Belgium) of 10 immunodot antigens for its effectiveness in diagnosing autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC). We retrospectively analysed serum samples from 111 patients who had undergone routine testing, including indirect immunofluorescence (IIF) and enzyme-linked immunosorbent assays (ELISA), to confirm or exclude autoimmune liver or biliary tract disease. The panel tested for M2/nPDC, M2/OGDC-E2, M2/BCOADC-E2, M2/PDC-E2, gp210, sp100, LKM1, LC1, SLA, and F-actin antigens. Results showed that all positive IIF+ELISA results were confirmed by the immunodot panel, except for two samples from patients never diagnosed with AIH. The immunodot test identified over 20 additional autoantibodies in samples initially negative by IIF, corroborated by laboratory imaging and medical history. The immunodot technique proved to be a quick, sensitive, and specific method with high overall accuracy. This study suggests that the immunodot technique may be an effective screening and confirmatory method for autoimmune liver diseases, potentially improving diagnostic efficiency and accuracy in clinical practice.

With its unique properties and potential applications, nanoparticle-based delivery platforms for vac-cines have gained significant attention in recent years. Nanoparticles have the advantages of enhancing immunogenicity, targeting delivery and improving stability, providing a new solution for drug and vaccine delivery. And in some clinical studies, a variety of nanoparticle delivery platforms have been gradually applied to a wide range of vaccine applications. Current research priorities are exploring various types of nanoparticles as vaccine delivery system to enhance vaccine stability and immunogen-icity. Lipid nanoparticles have shown promising potential in preclinical and clinical studies to efficiently deliver antigens to immune cells. Moreover, lipid nanoparticles (LNPs) and other nanoparticles as nu-cleic acids especially mRNA delivery system, have shown vast potential for vaccine development. In this review, we present various vaccine platforms with an emphasis on nanoparticles for mRNA nano-vaccine delivery vehicles. We introduce several novel nanoparticles delivery platforms for mRNA vac-cine such as lipid, polymer, protein-based nanoparticle and so on. In addition, we overview the an-ti-tumor immunity of nanovaccine against different tumors in cancer immunotherapy. Finally, we give an outlook future perspectives and remaining challenges for this promising technolo-gy-nanoparticle-based delivery platforms for vaccines.

Non-toroidal shape primary pass through protection current transformers (CTs) are used to measure high currents. Their design provides them with a big airgap that allow passing several cables per phase though them, which is the main advantage versus toroidal types, as the number of CTs required to measure the whole phase current is drastically reduced. The cables pass through the transformer window can be in several positions. As the isolines of the magnetic field generated by the primary currents are centered in the cables, if these cables are not centered in the transformer window, the magnetic field will be non-uniform along the transformer core. Consequently, local saturations can appear if the cables are not properly disposed causing the malfunction of the CT. In this paper, the performance of a non-toroidal shape protection CT is studied. The research is focused on the cable position influence in possible partial saturations of the CT when it is operating near to its accuracy limit. Depending on the cable position, the ratio of the primary and secondary currents can depart from assigned ratio. The validation of this phenomenon has been carried out via Finite Element Analysis (FEA) showing that partial transformer core saturations appears in areas of the magnetic core close to the cable. Applying FEA, also the admissible accuracy region for cable positioning inside the CT is delimited. Finally, the simulation results are ratified with experimental tests performed in non-toroidal protection CTs varying the primary cables’ positions, which are subjected to currents up to 5 kA, achieving satisfactory results. From this analysis, installation recommendations are given.

Due to the growth of tourism, mining and manufacturing, economy of the Hainan Island, southern China has swiftly expanded, but also poses a risk of soil pollution by mercury (Hg) due to the traffic and mineral processing. In order to investigate the characteristics of soil Hg pollution in the Hainan Island and assess the health risk, a total of 239 samples were gathered from five representative regions across the island. A vehicle-mounted potable mercury analyzer was used to measure the atmospheric Hg and soil Hg concentrations in the collected samples. The results indicate that the soil Hg concentration of the five sub-study areas exhibits notable fluctuations, which was found to be influenced by various factors, including wind direction, mining activities, and economic development conditions. The degree of Hg pollution was assessed using both the Single Pollution Index Method and the Geoaccumulation Index Method. The results showed that although nearly half of the sampling points were contaminated, the current soil Hg level does not pose a non-carcinogenic risk to human health.

The Planetary Roller Screw Mechanisms (PRSMs), alongside Ball Screw Mechanisms (BSMs) and Electromechanical Actuators (EMAs), occupies a pivotal role in advancing the precision and efficiency of various industrial applications, including aerospace, automotive, and high-precision machining tools. Despite their critical advantages such as high load capacity, superior precision, and extended lifespan, the deployment of PRSMs in complex operational conditions reveals a landscape rife with challenges and opportunities for further research. This comprehensive review endeavors to dissect the multifaceted aspects of PRSMs, focusing on their mechanics and dynamics, tribology and thermal behavior, and the paramount importance of reliability and condition monitoring. By synthesizing current research findings, this paper highlights the significant advancements in understanding the static and dynamic characteristics of PRSMs, the intricate interplay between lubrication conditions and wear mechanisms, and the critical role of thermal effects on operational performance. Moreover, it delves into the dynamic models that address the impact of manufacturing imperfections, such as waviness and defects, on the reliability of these mechanisms. Despite the strides made, the review identifies critical gaps in the existing literature, particularly under conditions of extreme temperatures, large deformations, and multifaceted loads, advocating for a holistic approach to research. By proposing integrated thermo-mechanical models and emphasizing the need for empirical validations, this paper outlines a roadmap for future studies aimed at facilitating the development of more robust and reliable PRSMs, capable of meeting the demands of complex operational scenarios and advancing the field of high-precision applications in aerospace, robotics, and beyond.

Embryonic and larval Danio rerio is increasingly used as a toxicological model to conduct rapid in vivo tests and developmental toxicity assays; the zebrafish features as high genetic homology to mammals; robust phenotypes; and its value in high-throughput genetic and chemical screening have made it a powerful tool to evaluate in vivo toxicity. New methodologies of genome editing as CRISPR/Cas9; ZFN or Talen make it a suitable model to perform studies to pair human genetic diseases as well. This review surveys recent studies; employing zebrafish as experimental model; comparing it with other in vivo and in vitro models; presenting zebrafish as a potent vertebrate tool to evaluate drug toxicity to facilitate more extensive; easy and comprehensive knowledge of new generation drugs.

Recently, immunotherapy has arisen as a novel treatment approach for patients with colorectal cancer (CRC), but the effectiveness of immunotherapy varies in these patients. We hypothesized that immune checkpoint molecules (ICMs), which are the targets of immunotherapy, are often exhibit concomitantly. Our objective was to investigate the patterns of ICM expression in patients with CRC and the differences in ICM expression based on the microsatellite instability status. Immunohistochemical expression of programmed cell death protein 1 (PD-1), programmed cell death ligand 1 (PD-L1), T cell immunoglobulin and mucin-domain containing-3 (TIM-3), and lymphocyte-activation gene 3 (LAG-3) in the tumor center and periphery was assessed in patients with non-metastatic colorectal cancer. We enrolled 83 patients with CRC: 40 with microsatellite stable (MSS) and 43 with microsatellite instability-high (MSI-H). PD-L1 was more frequently expressed in the tumor center in patients with MSI-H than that in patients with MSS (18 [41.9 %] vs. 3 [7.5 %], respectively; P < 0.001), and the same trend was observed for TIM-3 expression (30 [69.8 %] vs. 19 [47.5 %], respectively; P = 0.047). Concomitant expression of two or more ICMs was more frequently observed than no expression or expression of a single molecule in both MSS and MSI-H groups; 34 (79.7 %) patients with MSI-H and 23 (57.5 %) with MSS showed ICM expression at the tumor center, whereas 34 (79.7 %) patients with MSI-H and 22 (55 %) with MSS showed expression at the tumor periphery. Patients with the genetic characteristics of MSI-H showed higher expression levels of ICMs than that in patients with MSS, and predominantly, two or more ICMs were concurrently expressed. Our findings highlight the potential efficacy of the dual-blockade approach in immunotherapy, particularly in patients with MSI-H CRC.

Glacier dynamics play an important role in the mass balance of many glaciers, ice caps and ice sheets. In this study we exploit Radarsat-2 (RS-2) Wide Fine (WF) data to determine the surface speed of Svalbard glaciers in the winters of 2012/2013 and 2013/2014 using Synthetic Aperture RADAR (SAR) offset and speckle tracking. The RS-2 WF mode combines the advantages of the large spatial coverage of the Wide mode (150 x 150 km) and the high pixel resolution (9m) of the Fine mode and thus has a major potential for glacier velocity monitoring from space through offset and speckle tracking. Faster flowing glaciers (1.95 m d^-1 - 2.55 m d^-1) which are studied in detail are Nathorstbreen, Kronebreen, Kongsbreen and Monacobreen. Using our Radarsat-2 WF dataset, we compare the performance of two SAR tracking algorithms, namely the GAMMA Remote Sensing Software and a custom written MATLAB script (GRAY method) that has primarily been used in the Canadian Arctic. Both algorithms provide comparable results, especially for the faster flowing glaciers and the termini of slower tidewater glaciers. A comparison of the WF data to RS-2 Ultrafine and Wide mode data reveals the superiority of RS-2 WF data over the Wide mode data.

As the digital transformation accelerates in our society, open data is being increasingly recognized as a key resource for digital innovation in the public sector. This study explores the following two research questions: 1) Can a machine learning approach be appropriately used for measuring and evaluating open data utilization? 2) Should different machine learning models be applied for measuring open data utilization depending on open data attributes (field and usage type)? This study used single-model (Random Forest, XGBoost, LightGBM, CatBoost) and multi-model (Stacking Ensemble) machine learning methods. A key finding is that the best-performing models differed depending on open data attributes (field and type of use). The applicability of the machine learning approach for measuring and evaluating open data utilization in advance was also confirmed. This study contributes to open data utilization and to the application of its intrinsic value to society.

As a precious natural resource, forests are being destroyed. In previous studies, there is a lack of interactive assessment of its distribution that comprehensively considers multiple external disturbances. This paper takes the Barcelona Metropolitan Region as an example. Based on remote sensing, it analyzes the development process of the forest from 2006 to 2018 through multiple landscape indicators, and OLS models were established to analyze variables that have direct and indirect effects on forest distribution. In addition, the ecological structure of the forest was analyzed based on NDVI. It was found that the forest area is the largest but has been decreasing, becoming more complex in distribution structure. Much of the forest was converted to agricultural land and grassland. The green quality of forests was increasing, and the broad-leaved forest, the second largest area, contributes the most. NDVI is the most important positively correlated variable, and daytime surface temperature is an important inverse factor related to NDVI. In addition, NDBI is also a negative condition that inhibits forest development. In conclusion: The BMR forest area is decreasing and becoming more fragmented. NDVI and daytime LST are the two most significant factors. Climate warming may lead to worse forest development.

The Food and Drug Administration’s 2011 Process Validation Guidance and International Council for Harmonization Quality Guidelines recommend continued process verification (CPV) as a mandatory requirement for pharmaceutical, biopharmaceutical, and other regulated industries. As a part of product life cycle management, after process characterization in stage 1 and process qualification and validation in stage-2, CPV is performed as stage-3 validation during commercial manufacturing. CPV ensures that the process continues to remain within a validated state. CPV requires the collection and analysis of data related to critical quality attributes, critical material attributes, and critical process parameters on a minimum basis. Data is then used to elucidate process control regarding the capability to meet predefined specifications and stability via statistical process control tools. In statistical process control, control charts and Nelson rules are commonly used throughout the industry to monitor and trend data to ensure that a process remains in control. In the control chart, the mean value is taken as the center line, and 3σ limits are placed on either side of the center line. In CPV, manufactured lots are summarized, trended, and discussed at a cross-functional level at pre-defined intervals (either weekly, bi-weekly, or even monthly) based on the batch run rate. A cross-functional team assesses details regarding 1) violation frequency, 2) statistical strength of the signal, 3) violation magnitude and its impact on process or quality, and 4) any potential root causes for out-of-expectation or out-of-trend signals. The cross-functional team must analyze whether any signal identified by the control chart is reliable and must determine whether corrective action should be taken and justify the decision in the CPV meeting minutes based on statistical strength and reliability of the signal. However, basic control charts are susceptible to false alarms and nuisance alarms. Therefore, it is imperative to understand the assumptions behind control charts and the inherent false alarm rates for different Nelson rules. In this article, the authors have detailed the assumptions behind the usage of control charts, the rate of false alarms for different Nelson rules, the impact of skewness and kurtosis of a data distribution on the false alarm rate, and methods for optimizing control chart design by reducing false alarm rates and nuisance signals.

The UN Sustainable Development Goal 7 Report 2022 is about ensuring access to clean and affordable energy, which is key to the development of agriculture, business, communications, education, healthcare, and transportation. The lack of access to energy hinders economic and human development. Nevertheless, the current pace of progress is insufficient to achieve Goal 7 by 2030. Huge disparities in access to modern sustainable energy persist. Rising commodity, energy and shipping prices have increased the cost of producing and transporting solar photovoltaics modules, wind turbines and biofuels worldwide, adding uncertainty to a development trajectory that is already far below Goal 7 ambitions. Achieving energy and climate goals will require continued policy support and a massive mobilization of public and private capital for clean and renewable energy such as methane from biomass. An important factor in improving methane yield from biomass waste is pre-treatment of the biomass prior to anaerobic digestion. Size reduction of lignocellulose biomass is important for changing and increasing digestibility thus increasing methane yield. A Hollander beater was used as the mechanical pre-treatment machine throughout this study. Results indicate that methane yield is directly proportional to feedstock/Inoculum (F/I) ratio as higher F/I ratio led to higher methane yield. It was observed at an F/I ratio of 0.5 that 5 minutes pre-treatment time produced highest methane yield, while the lowest methane yield was observed at an F/I ratio of 0.2 with 1 minute of pre-treatment time. Methane yield decreased by 30% from 140 mL gTS-1 at F/I ratio 0.5 with 5 minutes pre-treatment time to 98 mL gTS-1 at F/I 0.2 with 5 minutes pre-treatment time. The optimum methane yield was attained at high F/I ratio allowing sufficient nutrient essential for complete degradation of biomass. Overall, this research shows the Hollander beater is not efficient in optimizing methane yield for cardboard.

The article presents the results of the technical-economical study regarding the optimization of the FDM parameters (Lh – the height of the layer deposited in one pass and Id – the filling percentage) for the manufacture of PETG and ASA parts. To carry out the technical-economical study, we used the fundamental principle of value analysis, which consists in maximizing the ratio between Vi/Cp, where Vi - represents the mechanical characteristic, and Cp - represents the production cost. The results of the study show that for the tensile specimens made of PETG, the parameter that significantly influences the results of the Vi/Cp ratios is Lh, and in the case of the compression specimens made of PETG, the parameter that significantly influences the results of the Vi/Cp ratios is Id. In the case of specimens manufactured by FDM from ASA, the parameter that decisively influences the results of the Vi/Cp ratios of the tensile and compression specimens is Id – the filling percentage. By performing optimization of the process parameters with multiple responses, we identified the optimal parameters for FDM manufacturing of parts from PETG and ASA: Lh = 0.20 mm and Id = 100%.

The integration of deep learning models into financial risk prediction and analysis has significantly transformed traditional approaches. While conventional quantitative methods often rely on simplistic metrics like maximum drawdown, the advent of deep learning necessitates a more nuanced evaluation, emphasizing the model's generalization ability, especially during market crises such as stock market crashes. This paper explores the critical aspects of evaluating deep learning models' risk control capabilities in finance, underscoring the importance of understanding both statistical metrics and generalization abilities, particularly in adverse market conditions. By examining deep learning models' performance in scenarios like stock market crashes and highlighting the significance of cross-validation techniques, this study aims to offer practitioners insights into constructing robust risk management systems. It advocates for a comprehensive approach integrating quantitative analysis with macroeconomic factors to enhance financial risk prediction and analysis in volatile markets. The experimentation reveals that different deep generative models excel in various aspects of financial time series analysis, with generative adversarial networks (GANs) demonstrating superior performance in predicting Value at Risk (VaR) and variational autoencoders (VAEs) excelling in return rate prediction. Moreover, integrating multiple models further enhances predictive performance, leveraging the strengths of each model to compensate for individual weaknesses. Overall, this paper underscores the potential and significance of deep generative models in financial time series analysis, offering a roadmap for improved risk management and decision-making in financial markets.

Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenue, as well as to operate air pollution control devices at design conditions. Depending on plant type and design, these plants can adjust output within a fixed range in response to the plant operating or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation such as wind and solar is shifting the traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. Recent studies have shown that flexibility of a coal-fired power plant can be improved by energy storage. The objective of this work was to analyze a set of energy storage options and determine their impact on flexibility and economics of a representative coal-fired power plant. The effect of three energy storage systems integrated with a coal power plant on plant flexibility and economics was investigated. The results obtained in this project show that Energy Storage Systems integrated with a thermal power plant improves plant flexibility and participation in the Energy and Ancillary Services markets which improves plant financial performance. The study was funded by the U.S. Department Office of Fossil Energy FE-1 under Award Number DE-FE0031903.

This comprehensive review digs into the complex landscape of the Metaverse, focusing on user perceptions and the critical roles of usability, social influence, and interoperability. The paper integrates various scholarly insights, underscoring the Metaverse's evolving significance in the digital realm and its implications across diverse sectors. Central to the findings is the importance of usability. The influence of social factors is also prominent, shaping user behavior and decision-making within these virtual spaces. Interoperability becomes a big problem, showing how important it is to have standard protocols and technologies so that experiences on different Metaverse platforms are smooth and seamless. The review further reveals insights into user experience and accessibility, emphasizing the need for inclusive, ergonomic, and user-friendly design to enhance engagement and reduce barriers. Moreover, the paper discusses the ethical and societal implications of the Metaverse, including issues like digital harassment, aggressive marketing, and privacy concerns, which call for responsible development and robust regulatory frameworks. Additionally, the review identifies gaps in current research, particularly in user experience in healthcare applications, the impact of the Metaverse on educational outcomes, and the need for more empirical studies on the long-term effects of Metaverse interactions on user behavior and psychology. This synthesis offers a detailed overview of current user perceptions and challenges within the Metaverse and sets the stage for future research directions, aiming to foster a secure, inclusive, and interoperable Metaverse environment that aligns with ethical standards and societal needs.

Primary open-angle glaucoma (POAG) is a progressive optic neuropathy with a complex, multifactorial aetiology. Raised intraocular pressure (IOP) is the most important clinically modifiable risk factor for POAG. All current pharmacological agents target aqueous hu-mour dynamics to lower IOP. Newer therapeutic agents are required as some patients with POAG show a limited therapeutic response or develop ocular and systemic side ef-fects to topical medication. Elevated IOP in POAG results from cellular and molecular changes in the trabecular meshwork driven by increased levels of transforming growth factor β (TGFβ) in the anterior segment of the eye. Understanding how TGF affects both the structural and functional changes in the outflow pathway and IOP is required to de-velop new glaucoma therapies that target the molecular pathology in the trabecular meshwork. In this study we evaluated the effects of TGF-1 and -2 treatment on miRNA expression in cultured human primary trabecular meshwork cells. Our findings are pre-sented in terms of specific miRNAs (miRNA-centric), but given miRNAs work in net-works to control cellular pathways and processes, a pathway-centric view of miRNA ac-tion is also reported. Evaluating TGF-responsive miRNA expression in trabecular meshwork cells will further our understanding of the important pathways and changes involved in the pathogenesis of glaucoma and could lead to the development of miRNAs as new therapeutic modalities in glaucoma.

Epistaxis, particularly in Hereditary Hemorrhagic Telangiectasia (HHT) patients, is a common otolaryngological emergency, often requiring complex management. A hierarchy of increasingly invasive interventions, from external compression of the nasal pyramid to nostril closure, is typically proposed and applied. We conducted a retrospective study on HHT patients to assess the effectiveness and longevity of invasive procedures postoperatively. Data were collected using the Epistaxis Severity Score (ESS) questionnaire. The primary focus was on changes in the frequency and intensity of epistaxis, while the secondary focus was on the overall quality of life. The study found that invasive procedures initially improved the frequency and intensity of epistaxis in HHT patients. However, within one to 9 months postoperatively, these benefits often diminished, with hemorrhagic symptoms recurring at similar or worsened levels. Facial trauma further negated the advantages of these procedures. The findings suggest a need for a gradual and increasingly invasive approach to managing epistaxis in HHT patients. Highly invasive procedures should be reserved for cases where less invasive methods fail, due to their limited temporal effectiveness and the risk of causing anatomical-functional changes in the rhino-sinus area, complicating future management of severe epistaxis.

The present investigation highlights the synthesis of polyaniline (PANI) coated graphene oxide doped with SrTiO3 nanocube nanocomposites through facile in-situ oxidative polymerization method for the efficient removal of carcinogenic dyes, namely, the cationic dye methylene blue (MB) and the anionic dye methyl orange (MO). The synthesised nanocomposites were characterised by field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The adsorption efficiencies of graphene oxide (GO), PANI homopolymer and SrTiO3 nanocubes-doped nanocomposites were assessed by monitoring the adsorption of methylene blue and methyl orange dyes from aqueous solution. The adsorption efficiency of nanocomposites doped with SrTiO3 nanocubes were found to be of higher magnitude as compared with undoped nanocomposite. Moreover, the nanocomposite with 2 wt% SrTiO3 with respect to graphene oxide demonstrated excellent adsorption behaviour with 99% and 91% removal of MB and MO respectively, in a very short duration of time.

This study focuses on examining various approaches for Tensor Decompositions (TDs) and their potential applications in satellite imaging (SI) and deep learning (DL). The research highlights how these decompositions can contribute to the advancement of SI and DL, providing valuable insights for future utilization of TDs in research. It explores how these techniques contribute to the advancement of SI and DL methods, providing insights into their potential applications and suggesting future research directions. The study aims to enhance the use of TDs techniques to further advance research efforts in these fields. More importantly, the current investigation offers a thorough analysis of the potential advantages and reasons for employing TDs techniques in different domains, including satellite imaging and deep learning. The aim is to enhance research outcomes by utilizing TDs. The review also identifies unresolved issues and proposes future directions for further investigation in this field. Fundamentally, these proposed open problems will open new grounds to the research community to articulate, innovate, and provide more real-life applications to improve the current state of the art by delving into a wider vision for a higher-level performance of both satellite imaging (SI) and deep learning (DL). Looking at the bigger scenario, this also suggests that TDs could be potentially employed to revolutionize existing machine learning technologies as well as the current space AI industry.

In the present study. At first, some properties of r-fuzzy soft β-closed sets are introduced on fuzzy soft topological spaces based on the paper Aygunoglu et al. (Hacet. J. Math. Stat. 2014, 43, 193-208). Also, we define the closure and interior operators with respect to the classes of r-fuzzy soft β-closed and r-fuzzy soft β-open sets, and investigate some of their properties. In addition, the concept of r-fuzzy soft β-connected sets is introduced and characterized with help of fuzzy soft β-closure operators. Thereafter, some properties of a fuzzy soft β-continuity are studied. Furthermore, we introduce and study the concepts of fuzzy soft almost (weakly) β-continuous functions, which are weaker forms of a fuzzy soft β-continuity. Also, the relationships between these classes of functions are specified with the help of some illustrative examples. Finally, we explore new types of fuzzy soft functions called, fuzzy soft β-irresolute (strongly β-irresolute, β-irresolute open, β-irresolute closed and β-irresolute homeomorphism) functions, and discuss some properties of them. Also, we show that fuzzy soft strongly β-irresolute → fuzzy soft β-irresolute → fuzzy soft β-continuity, but the converse may not be true.

Despite copious research, the methods for assessing upper- and lower-limb motor coordination are limited. We devised a simplified evaluation method based on upper- and lower-limb motor coordination jumping and conducted a practical examination of the characteristics of the motion and applicability of the evaluation method. Overall, 88 high-school athletes with comparable competitive abilities were included in this study. The participants were divided into two groups based on their prior experience with motor coordination training (24 in the experienced group; 64 in the inexperienced group). First, a population proportion test was employed to assess the success rate of the four upper- and lower-limb motions in each task. This revealed significant difference between all tasks, except for the fourth motion, indicating that different motions have varying degrees of difficulty and that the combination of motions with differing difficulty coefficients can result in the creation of entirely new tasks with varying degrees of difficulty. Second, the experienced group demonstrated significantly superior performance compared to the inexperienced group by a t-test. These results confirmed that athletes (with the same level of competitive ability) trained in upper and lower limb motor coordination were able to excel in this evaluation method, confirming its validity.

In India, particularly within its North-Eastern territories, the occurrence of landslides triggered by post-dry period rainfall events is a significant concern, with the phenomena persistently causing extensive damage to both life and infrastructure. Despite the inevitability of such natural disasters, it is understood that the impact they exert can be substantially mitigated through the implementation of pre-emptive measures. Critical to the endeavour of landslide prevention is the application of a spectrum of mitigation strategies, predicated upon a foundational analysis of slope stability to ascertain critical surfaces for intervention. This investigation delves into the dynamics of partially saturated soils, a condition commonly resultant from the prolonged dry periods preceding the monsoonal rains. The study's focal point is an experimental examination conducted on soil samples to assess parameters such as soil matric suction and unconfined compressive strength across varying degrees of saturation and density, alongside performing analyses of slope failure incidents after dry period during the 2017 monsoon in the Lunglei district, Mizoram based on some established data. The Soil-Water Characteristic Curve (SWCC), derived from soil suction measurements employing the ASTM D5298-10 standard, utilizes a contact filter paper method and serves to delineate the moisture transition phases of the slope. To replicate the desiccation of the soil slope after monsoonal rains, a microwave drying technique based on the ASTM standard was employed to prepare unsaturated soil samples for Unconfined Compressive Strength (UCS) testing. The integrity of the slope was evaluated in a temporal context, before and after rainfall events of varied intensities throughout the calendar year, utilizing a blend of numerical modeling and empirical laboratory investigations. The persistence of real onsite slope failures underscores the necessity for a numerical analysis approach to unravel the underlying factors causing slope instability, especially given the absence of prior stability assessments for the landslide in question. An evaluation of SWCC curves, UCS tests on partially saturated soil at different densities and saturation and the utilization of the benchmark data collected in 2017 on the shallow transitional landslide in Lunglei, Mizoram caused by intense monsoonal precipitation, are central key data and information used to carry out this research. Rainfall data for Lunglei, sourced from the Mizoram Meteorological Department, facilitated a real-time monsoonal data-driven numerical analysis. This analysis elucidated the pivotal role of rainfall in inducing slope failure, indicating a marked destabilization of the slope after precipitation events. The implications of these findings are far-reaching, suggesting a foundational basis for the development of an advanced landslide early warning system, thereby enhancing disaster preparedness, and mitigating potential damages.

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

This qualitative study explores the intricacies of building sustainable supplier relationships in the e-commerce sector, focusing on best practices and strategic approaches. Through in-depth interviews with procurement managers, supply chain experts, and supplier representatives, the research identifies four critical themes: trust, technology integration, ethical practices, and performance measurement. Trust is found to be the foundation of effective supplier relationships, fostering open communication and collaboration, which are essential for addressing challenges and co-creating solutions. The integration of digital technologies such as supply chain management software, blockchain, and the Internet of Things significantly enhances transparency, decision-making, and operational efficiency, providing a competitive edge. Ethical practices, including adherence to fair labor standards and environmental sustainability, are increasingly crucial as consumer and regulatory expectations evolve, necessitating alignment between e-commerce companies and their suppliers. Performance measurement and continuous improvement are vital for maintaining quality and efficiency, with clear metrics and regular evaluations driving constructive feedback and optimization of supply chain processes. The study underscores the interdependence of these elements in fostering resilient and adaptable supplier relationships. The findings offer practical guidance for e-commerce businesses and suppliers, emphasizing the need for a holistic approach to supplier management that balances trust, technology, ethics, and performance. This approach not only enhances operational effectiveness but also ensures the long-term sustainability of supplier relationships in the dynamic e-commerce landscape. The research contributes to the theoretical understanding of supplier relationship management, providing a comprehensive framework for future studies and practical applications in the e-commerce industry.

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.

This study explores the role of stakeholder engagement in enhancing supply chain sustainability within the renewable energy sector. Through a qualitative research approach, including in-depth interviews with key stakeholders such as government agencies, industry associations, renewable energy companies, community groups, and environmental organizations, the research reveals the complexity and significance of effective stakeholder engagement. Stakeholders highlighted diverse motivations, including environmental, social, economic, and regulatory concerns, driving their participation. The study underscores the importance of tailored engagement strategies that recognize stakeholder heterogeneity and address specific needs and expectations. Collaborative approaches, such as public-private partnerships and multi-stakeholder initiatives, were identified as crucial for pooling resources, sharing knowledge, and addressing common challenges. However, challenges related to power imbalances, conflicting interests, and communication barriers were also noted. Government policies and regulatory frameworks were found to play a pivotal role in shaping stakeholder engagement practices and sustainability outcomes. Regulatory uncertainty and inconsistency were cited as significant concerns that could undermine sustainability initiatives. Community engagement emerged as a critical factor, with local communities often directly impacted by renewable energy projects. Meaningful engagement, including consultation and benefit-sharing mechanisms, is essential for building trust and securing social acceptance. Emotional intelligence and marketing strategies were recognized as important tools for effective stakeholder engagement, emphasizing the role of empathy, active listening, and clear communication. The findings of this study highlight the need for a holistic and integrated approach to stakeholder engagement and supply chain sustainability in the renewable energy sector. By addressing diverse stakeholder needs, fostering collaboration, and aligning policies with sustainability goals, stakeholders can work together to accelerate the transition towards a more sustainable energy future.

The space exploration landscape has transformed dramatically over the past several decades, with a significant rise in the number of annual launches. Key factors driving this increase include technological advancements, the miniaturization of satellites, and the surge in commercial satellite deployments for communication, Earth observation, and remote sensing. This paper examines the evolution of space activities from the launch of Sputnik 1 in 1957 to recent developments in commercial spaceflight and international collaborations. The paper discusses notable milestones in space exploration history, including early space missions, Apollo Moon landings, and the development of space stations like the International Space Station. It highlights the shift from state-led space programs to a more diverse landscape, characterized by private sector involvement and international partnerships. The "Space 4.0" phase, beginning around 2006, has seen the entry of commercial players like SpaceX, leading to a significant upsurge in orbital launches. Statistical data reveals an upward trend in launch activity, with over 200 launches in 2023 alone, driven by large satellite constellations like SpaceX's Starlink and the steady growth of China's space program. The increasing launch rate poses challenges such as space debris, emphasizing the need for mitigation strategies. Looking ahead, the paper projects a continued increase in launch activity, with over 150 launches expected annually by 2026 and 200-300 launches by 2040. Commercial space ventures, deep space exploration, lunar activities, and space tourism drive this growth. The paper concludes by emphasizing the importance of addressing space debris and promoting the long-term sustainability of space activities, which is crucial as humanity's presence in space continues to expand.

The number of XLPE cables being used near or beyond their designed lifespan is increasing. The importance of timely cable replacement is increasing. Therefore, research is actively being conducted using VLF Tan δ diagnostic technology to assess the insulation condition of cables. There is a lack of studies measuring and analyzing VLF Tan δ of service aged XLPE cables. Additionally, there is a lack of research considering the operating environment. Therefore, research is needed to diagnose and analyze the insulation condition of the same serviced aged cable when it is operated in a different environment. This paper evaluates and analyzes the insulation condition of cables installed in the BFP, cooling tower, and deaerator booster pump of a combined heat and power plant. Each cable was analyzed by measuring VLF Tan δ, dielectric breakdown test of the cable, and tensile strength, elongation at break, crystallinity, and dielectric strength of XLPE specimens. Additionally, the correlation between VLF Tan δ and other characteristics was also analyzed. It was found that degradation progressed in the order of BFP, cooling tower, and deaerator booster pump. Therefore, it was confirmed that even for the same cable, deterioration varies depending on the installation location.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

This systematic literature review meticulously explores the complexities of technological innovation and entrepreneurship, with a particular focus on the strategies and management practices involved in new product development from an interdisciplinary standpoint. By conducting an extensive analysis of 323 key articles from 11 top-tier journals published between 2020 and 2023, the review delineates the current research trajectories within these fields, underscoring significant scholarly interest and development. The study particularly emphasizes the emergence of artificial intelligence-generated content technology since 2022 and critically assesses its influence on innovation processes and product development practices among both nascent entrepreneurs and well-established corporations. This emergent technology's role in shaping the competitive landscape and its potential to drive significant shifts in market dynamics are thoroughly examined.

Because Canadian Nitrogen (N) fertilizer use has more than doubled since 1990 (1.2 to 2.9 MtN by 2021), a better understanding of this trend is needed. A comprehensive set of Recommended N Rates (RNR) that agreed with fertilizer sales data from 1996 and 2001 was compared with the Fertilizer Use Survey (FUS). The FUS was conducted from 2014 to 2021, with 2017 being the most representative year for these data. Using non-parametric statistics, confidence intervals were derived from the histograms used to present the FUS data. N application rates from the RNR for Canola, Spring and Duram wheat, and Oats in the west were all below their respective FUS confidence intervals, whereas N application rates for Grain corn showed almost no difference in N use between the RNR and FUS. Crop-specific N application rates interpolated from the RNR and FUS were integrated over their respective crop areas and plotted against national fertilizer sales records from 1990 to 2021. The rapid increase in N use between 2001 and 2017 (0.89 MtN), 90% of it (0.80 MtN) in Western Canada, was primarily due to increased application rates per crop, rather than crop area changes. The FUS-RNR interpolations were a good approximation of N sales records and could improve farm GHG emissions modelling. The economically important crops in Western Canada should be the main focus for N-related GHG reduction measures, but production losses need to be avoided.

In this review, we summarize recent progress in crystal growth and understanding the influence of crystal structure on the superconductivity in pure and Pb-doped Bi2Sr2CuOy (Bi-2201) materials belonging to the overdoped region of high temperature cuprate superconductors. The crystal growth of Bi-2201 superconductors faces challenges due to intricate materials chemistry and lack of knowledge of corresponding phase diagrams. Historically, a crucible-free floating zone method has emerged as the most promising growth approach for these materials, resulting in high-quality single crystals. This review outlines the described in the literature and the authors' synthesis endeavors, encompassing Pb-doped Bi-2201 crystals, detailed structural characterization of as-grown and post-growth annealed samples, and highlights optimal growth conditions that yield large-size, single-phase, and compositionally homogeneous Bi-2201 single crystals.

Mercury contamination in the Amazon is a significant public health concern arising from both natural sources and intensive mining activities in the region. This metal is used to separate Au from sediments, forming an amalgam that facilitates the extraction of precious metals. Accordingly, this study aimed to address the following question: What is the impact of mining on mercury contamination in the animal and human populations of the Amazon? The overall objective of this study was to conduct a systematic review of the existing literature to identify gaps in geographic coverage and assess the impact of Hg contamination on human and animal populations in the Amazon region. Our hypothesis was that higher mercury concentrations in tissue samples would be found closer to the mining areas. We employed the PECO and PRISMA-ScR protocols to collect articles published between 2017 and 2023, selected based on criteria representing projected points on a map within the biogeographic boundaries of the Amazon. Mercury concentrations increase with trophic levels, reaching high values of 3.7 µg/g in the muscles of predatory fish and 34.9 µg/g in human hair. The average level of mercury in humans exceeds 6 µg/g, surpassing tolerance levels. Although mining regions show high concentrations of Hg, the highest incidence was observed among populations with fish-based diets. Research on fish is crucial for assessing the risk to human health, given that fish are the main source of protein in the region.

Accurately predicting the distance an object will travel to its destination is very important in various sports. Acceleration sensors as a means of real-time monitoring are increasingly gaining increasing attention in sports. Due to the low energy output and power density of Triboelectric Nanogenerators (TENGs), recent efforts have focused on developing various acceleration sensors. However, these sensors suffer from significant drawbacks of large size, complexity, high power input requirements, and high cost. Here, we described a portable and cost-effective real-time refreshable strategy design comprising a series of individually addressable and controllable units based on TENGs embedded in a flexible substrate. This results in a highly sensitive, low-cost, and self-powered acceleration sensor. Putting, which accounts for nearly half of the strokes played, is obviously an important component of the golf game. The developed acceleration sensor has an accuracy controlled within 5 %. The initial velocity and acceleration of the forward movement of a rolling golf ball after it is hit by a putter can be displayed, and the stopping distance quickly calculated and predicted in about 7 seconds. This research demonstrates the application of the portable TENG-based acceleration sensor, while paving the way for designing portable, cost-effective, scalable, and harmless ubiquitous self-powered acceleration sensors.

Objective To investigate nailfold capillary parameters in community-dwelling individuals aged over 60 years who have hypertension and do not exercise regularly. Furthermore, the study examined the correlations between capillary function and other health-related indicators. Design A single- center pilot trial Setting Faculty of Health, Tsukuba University of Technology, Japan Participants hypertensive community-dwelling elderly people Intervention Microcirculation was observed before and 1 min after arm-curl exercise by means microscopy of capillary with non-exercised limb. Additionally, we examined other health-related indicators. Outcome measures: Acute effects of reperfusion on nailfold density, flow, and diameters. Secondary outcomes included the correlations between microvascular parameters and other health-related indicators. We hypothesized that brief exercise could enhance microcirculation reperfusion and correlate with other health-related parameters.　 Results: There were 20 participants with a mean (SD) age of 67.1 (5.8) years. The capillary flow rate changed from 2.3±6.7 to 2.7±0.2 log µm/s (P

One of the G protein-coupled receptors, C-C chemokine receptor 5 (CCR5), is an important regulator for the activation of T and B lymphocytes, dendritic cells, natural killer cells, and macrophages. Upon binding to the ligands, CCR5 activates downstream signaling, which plays critical roles in the innate and adaptive immune response through the promotion of lymphocyte migration and the secretion of pro-inflammatory cytokines. Anti-CCR5 monoclonal antibodies (mAbs) have been developed and evaluated in clinical trials for tumors and inflammatory diseases. In this study, we developed novel mAbs for mouse CCR5 (mCCR5) using the N-terminal peptide immunization. Among the established anti-mCCR5 mAbs, C₅Mab-4 (rat IgG_2a, kappa) and C₅Mab-8 (rat IgG₁, kappa), recognized mCCR5-overexpressed Chinese hamster ovary-K1 (CHO/mCCR5) and an endogenously mCCR5-expressing cell line (L1210) by flow cytometry. The dissociation constant (K_D) values of C₅Mab-4 and C₅Mab-8 for CHO/mCCR5 were determined as 3.5 × 10⁻⁸ M and 7.3 × 10⁻⁹ M, respectively. Furthermore, both C₅Mab-4 and C₅Mab-8 could detect mCCR5 by western blotting. These results indicated that C₅Mab-4 and C₅Mab-8 are useful for detecting mCCR5 by flow cytometry and western blotting and provide a possibility to obtain the proof of concept in preclinical studies.

Hiccups can significantly reduce the quality of life of patients and can occur as a drug side effect. Previous report using the Drug Adverse Event Database revealed sex-specific differences in the incidence of drug-induced hiccups. However, the pathogenesis of drug-induced hiccups remains unknown, and there is limited evidence on its treatment or prevention. This study examined molecular initiating events (MIEs), which are the starting point of adverse events, to investigate the drug-induced pathways of hiccups. We extracted drugs suspected to cause hiccups using FDA Adverse Event Reporting System, a large database on adverse drug reactions. Information on drugs suspected to be associated with hiccups were extracted from the overall population and sex-specific subgroups divided. In each data table, the predicted activity values of nuclear receptors (NRs) and stress response pathways (SPs) for each drug were calculated using the toxicity predictor, a machine-learning model. Univariate analysis extracted NRs and SPs associated with hiccups, and a multivariate analysis was performed to evaluate independent factors. Transforming growth factor-beta and antioxidant response element were considered an independent factor for hiccups in the male and female subgroups, respectively. This report first examined one of the mechanisms of drug-induced hiccups and identified MIEs associated with drug-induced hiccups.

The purpose of this study was to systematically review forest therapy programs designed to decrease the level of depression among adults and subsequently identify the gaps in the literature. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The authors independently screened full-text articles from various databases using the following criteria: 1) intervention studies assessing the effects of forest therapy on depression in adults aged 18 years and over; 2) studies including at least one control group or condition; 3) been peer-reviewed; and 4) been published either in English or Korean before July 2016. The Scottish Intercollegiate Guideline Network (SIGN) measurement tool was used to assess the risk of bias in each trial. In the final sample, a total of 28 articles (English: 13, Korean: 15) were included in the present systematic review. This review concluded that forest therapy is one of the emerging and effective interventions for decreasing the level of depression in adults. However, the studies included in this review lacked methodological rigor. Future studies assessing the long-term effect of forest therapy on depression using rigorous study designs are needed.

To achieve a narrow bandwidth optical filter with a wide swept range for new generation optical spectrum analysis (OSA), an optoelectronic equivalent narrowband filter (OENF) is investigated and a swept optical filter with bandwidth of several MHz and swept range of several ten nanometers is built using electric filters and a swept laser as local oscillator (LO). The principle of OENF is introduced and analysis of OENF system is presented. Two electric filters are optimized to be RBW filters for high and medium spectral resolution application. Both simulations and experiments are conducted to verify OENF principle and results show that power uncertainty is less than 1.2% and spectral resolution can reach 6 MHz. Then, a real-time wavelength calibration system consisting of HCN gas cell and FP etalon is proposed to guarantee a wavelength accuracy of ±0.4 pm at C-band and to reduce the influence of phase noise and nonlinear velocity of swept LO. Finally, experiments on OSA of actual spectra of various optical sensors using OENF system are conducted. Experimental results indicate that OENF system has an excellent capacity in analysis of fine spectrum structures.

Emerging data support associations between depletion of the healthy gut microbiome and aging-related physiological decline and disease. In humans, fecal microbiota transplantation (FMT) has been used successfully to restore gut microbiome structure and function to treat C. difficile infections, but application to healthy aging has been scarcely investigated. The marmoset is an excellent model for evaluating microbiome-mediated changes with age and interventional treatments due to their relatively shorter lifespan and many social, behavioral, and physiological functions that mimic human aging. This review 1) provides an overview of the rationale for FMT to support healthy aging using the marmoset as a translational geroscience model, 2) summarizes prior use of FMT in marmosets, 3) outlines a protocol for studying FMT in aging marmosets, and 4) describes knowledge gaps and future research needs in this field.

This manuscript employs a surface stress-driven nonlocal model to explore the combined effects of long-range interaction and surface energy on higher vibration modes of functionally graded nanobeams. The nanobeam theory, based on Bernoulli-Euler kinematics, incorporates surface effects such as surface elasticity, surface residual stresses, surface density, and rotary inertia. Hamilton's principle is applied to derive the governing equation with size-dependent considerations. The main outcomes of a parametric investigation, considering four different kinematic boundary conditions (Cantilever, Simply-Supported, Clamped-Pinned, and Doubly-Clamped) while varying the nonlocal parameter and material gradient index, are presented and discussed. Additionally, the normalized natural frequencies for the second, third, fourth and fifth modes of vibrations are provided and analyzed for each case under study. The results underscore the model's effectiveness in capturing surface energy effects on the overall dynamic behavior of functionally graded Bernoulli-Euler nanobeams, offering a cost-effective approach for designing and optimizing nano-scaled structures.

: Background: Since the consensus of ISAPP on the definition of the term “postbiotic” there has been an enthusiasm for publications, in review form - their number being disproportionate to the primary research. The aim of this bibliometry is to analyze the perspectives of the first and the last authors of such reviews; and, specifically, to note the connection of these authors with the broader subject of microbiome and probiotics. Methods: Search of the PubMed database for review articles on post-biotics, published between November 2021 and December 2023. Results: Analysis was performed on 76 review articles, the number corresponding to 2.9 reviews per month. Poland, China, Italy, Argentina and Iran had the maximum productivity among the 30 countries involved; 39 articles were published in 12 high-impact journals, while 31 were in journals with an IF between 5 and 5.9. The authors were mainly affiliated to universities with specialization in both basic research and technology, as well as food science. Eighteen first authors and six last authors had zero previous publications on the related topic of the microbiome and probiotics; and another 7 last authors had only one publication each. There were, however, 5 authors with 142, 92, 76, 71 and 41 related publications. Conclusions: It is clear that a part of this productivity is written by first authors with no previous engagement with related research and lacking colleagues or mentors involved with microbiome/probiotics research to support them as senior authors.

Landslides, resulting from disturbances in slope equilibrium, pose a significant threat to landscapes, infrastructure, and human life. Triggered by factors such as intense precipitation, seismic activities, or volcanic eruptions, these events can cause extensive damage and endanger nearby communities. A comprehensive understanding of landslide characteristics, including spatio-temporal patterns, dimensions, and morphology, is vital for effective landslide-disaster management. Existing Remote Sensing approaches mostly use either optical or Synthetic Aperture Radar (SAR) sensors. Integrating information from both these types of sensors promises greater accuracy for identifying and locating landslides. This study proposes a novel approach, the ML-LaDeCORsat (Machine Learning-based coseismic Landslide Detection using Combined Optical and Radar Satellite Imagery), that integrates freely available Sentinel-1, Palsar-2, and Sentinel-2 imagery data, along with relevant spectral indices and suitable bands using machine-learning-based classification for coseismic landslide detection implemented in Google Earth Engine (GEE). The approach includes a robust and reproducible training and validation strategy. Using landslides from four different earthquake case studies, we demonstrate the superiority of our approach over existing solutions in coseismic landslide iden-tification and localization, providing a detection accuracy of 87-92%. ML-LaDeCORsat can be adapted to other landslide events (GEE script is provided). Transfer learning experiments proofed that our model can be applied to other coseismic landslide events without the need for additional training data. Our novel approach therefore facilitates quick and reliable identification of co-seismic landslides, highlighting its potential to contribute towards more effective disaster management.

Fatigue is a recognized concern in air traffic management, prompting international bodies like ICAO and EASA to advocate for Fatigue Risk Management Systems (FRMS). EU Regulation 2017/373, effective since January 2020, imposes specific requirements on air traffic service providers regarding controllers' fatigue, stress, and rostering systems, as part of safety management protocols. Despite active campaigns promoting fatigue awareness in air traffic control (ATC), there remains a need for standardized operational requirements. Eurocontrol recently published "Guidelines on fatigue management in ATC rostering systems" (April 23), aiming to facilitate the adoption of common fatigue operational standards. However, neither EU Regulation 2017/373 nor existing documentation specifies exact rostering criteria. Air Navigation Service Providers (ANSPs) typically derive these criteria from scientific literature, best practices, historical data, and legal and operational necessities. Yet, assessing and monitoring fatigue in operational settings can be complex and require long-term studies due to its multifaceted nature, spanning factors such as sleep quality, circadian rhythms, psychosocial influences, individual traits, and environmental conditions. The case studies reported in this paper represent an attempt to create an evidence-based protocol for fatigue risk monitoring in ATC operations, utilizing a non-invasive approach and collecting multidimensional data. The two case studies involved en-route and tower controllers from different ATC Centers, and the results underscore the importance of fatigue assessment in ATC and elucidates challenges in implementing fatigue monitoring within operational contexts.

The assessment of Photovoltaic (PV) systems, a key component of sustainable energy solutions, is of paramount importance in the pursuit of a greener future. This abstract provides an overview of environmental assessments associated with PV systems, considering their life cycle, energy production, and ecological impact. The study explores various methodologies and tools employed in the evaluation of PV systems’ environmental performance, addressing issues such as material sourcing, manufacturing, installation, and end-of-life disposal. Additionally, it delves into the trade-offs and challenges in achieving sustainability objectives in the solar energy sector. By critically examining the environmental implications of PV systems, this research contributes to informed decision-making and the sustainable integration of solar power into our energy landscape.

In the extended malfatti problem, the numbers of circles in the triangle are triangle numbers, because the tangency properties among the internal circles and 3 sides of the triangle have special type of structure. That is, the corner circle tangent to two sides of the triangle and two boundary circles, the boundary circles tangent to one side of the triangle and 4 other circles, and the inner circles always tangent to 6 other circles. The circles we find in extended general Malfatti’s problem has the property that the smallest radius and the largest radius for the circle has big difference. In this paper, we proposed algorithms to solve the problem that the tangency properties among circles and sides of triangle is not fixed, so that the number of circles in the triangle is not necessary a triangle numbers. The purpose of this change is try to find the radii of the circles in the triangle is within a small range.

This paper investigates an Energy Neutral System using Micro Energy Harvesters for a Health Monitoring Wireless Sensor Node (HM-WSN). We have implemented HM-WSN consisting of a solar cell energy harvester, a Power Management Unit (PMU) and the ucontroller, sensor and transmitter acting as load. A battery extender and a switching logic circuit for sensor node is designed to evaluate the efficiency of the proposed system. The HM-WSN senses body temperature with improvement in lifetime of coincell. The HM-WSN is built using commercially available off the shelf (COTS components and consumes 47.2uW for data being updated every 134s. It can be operated for approximately 1.32 years only on a coincell. Furthermore, the HM-WSN can be operated with solar energy at 200lux, achieving 96.36 years with a combination of a coincell with an additional capacitor of 2.2mF. It attains 4.07 years to 16.87 years lifetime with the load capacitor varying from 1mF to 1.5mF at 350lux lighting condition. With the same ambient condition and a 2mF load capacitor, HM-WSN attains complete energy autonomy.

A decanter centrifuge has been employed to successfully separated phosphoric acid and rare-earth-element (REE)-containing particles from phosphoric acid sludge with concentrations ranging from 1,000 to 2,200 ppm REEs. Operating efficiently with up to 35 wt.% solids, the centrifuge was demonstrated to achieve approximately 95% phosphoric acid recovery and 90% REEs recovery in a single pass, eliminating the need for additional processing steps. This breakthrough supports a proposed REEs oxide recovery process integrating phosphoric acid (PA), elemental phosphorus (P4), and REEs into two potential pathways: PA-REO and PA-P4-REO. These processes aim to reintroduce recovered phosphoric acid into the main product to significantly increase output and revenue. Post-separation, phosphorus-rich particles can be converted to P4, while REEs-containing solids undergo further treatment including acid leaching, extraction/stripping, precipitation, and calcination to produce a marketable rare-earth oxide (REO) material. Techno-economic analysis indicates promising profitability, with the PA-REO process showing a delta net present value (∆NPV) of $441.8 million and an expected return within a year of construction, while the PA-P4-REO process yields a ∆NPV of $178.7 million over a 12-year return period. Both pathways offer robust financial prospects and demonstrate the feasibility of commercial-scale REEs recovery from phosphoric acid sludge.

In our previous papers, we demonstrated that inflammation and aging are the common roots of cancer and Alzheimer’s disease (AD). In both diseases, there is an inhibition of the mitochondria. In cancer, the alkaline intracellular pH (pHi) is associated with cell proliferation; acidic pHi causes apoptosis in AD. This difference is because cancer feeds on chemically neutral glucose, while neurons feed on acidic lactic acid. Increased uptake of lactic acid is responsible for acidic pH and cell death. Similarly, to AD, inflammation is responsible for metabolic shifts in age-related macular degeneration (AMD). In AD, there is hyperosmolarity responsible for increased lactic secretion by glial cells. Increased lactic secretion will cause neo-angiogenesis and neural cell death. Drugs increasing hyperosmolarity (Polyethylene Glycol) cause neo-angiogenesis and drusen-like structures in rodents. The link between AMD and inflammation is reinforced by the fact that treatments aiming at restoring mitochondrial activity, such as lipoic acid and/or methylene blue, have been experimentally shown to be effective in each set of diseases. The role of osmolarity has been demonstrated in the pathologies of the anterior segment of the eye, such as dry eye, corneal ulceration, cataracts, and glaucoma. The role of increased osmolarity in age-related macular degeneration (AMD) has been largely overlooked. We herein suggest that metabolic shift, inflammation, and hyperosmolarity are key players in the pathogenesis of AMD.

Staphylococcus aureus and coagulase-negative staphylococci account for about 80% of infections associated with medical devices and are associated with increased virulence due to their ability to form biofilm. In this study, we aimed to construct a comprehensive reference map followed by significant pathway analysis in the proteome of S. aureus biofilm grown for 3-days as compared with 24 h planktonic using a high-resolution TMT based MS. We identified proteins associated with secondary metabolites, ABC transporters, biosynthesis of amino acids, response to stress, and amino sugar and nucleotide sugar metabolism were significantly upregulated in the 3-day biofilm. In contrast, proteins associated with virulence factors, microbial metabolism in diverse environments, translation, and energy metabolism were significantly downregulated. GO functional annotation indicated that more proteins are involved in metabolic processes, catalytic activity, and binding in biofilm, respectively. Among the significantly dysregulated proteins, hyaluronidase (hysA) in conjunction with chitinase may play a significant role in the elimination and/or prevention of biofilm development. This study advances the current S. aureus subproteomes, identified potential pathways significant to biofilm biology and helped to understand their potential role in S. aureus which may shed light on developing new therapeutic regimes including antibiofilm agents in the treatment of biofilm-infections related with implantable medical devices.

Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer phylogenetic relationships exhibited similar protein and gene structures. Gene members of the TCP family showed developmental stage or tissue-specific expression profiles during the passion fruit life cycle. Transcriptome data also demonstrated that many PeTCPs showed induced expression in response to hormonal treatments and cold, heat, and salt stress. Based on transcriptomics data, eight candidate genes were chosen for preferential gene expression confirmation under cold stress conditions. Additionally, four TCP genes exhibited in silico binding with cold stress-related miRNA319s. This study will aid in the establishment of novel germplasm, as well as the further investigation of the roles of PeTCPs and their cold stress resistance characteristics.

Poikilodermatous plaque-like hemangioma (PPH) is a recently described clinical and pathological entity, with only 18 cases reported in the literature. Although uncommon, this benign condition presents consistent clinical and histological findings. We present a new case of PPH in an 81-year-old male and review the existing literature. The persistence over time and the need to distinguish PPH from more significant lesions underscore the importance of its clinical and pathological recognition.

Neural Fractional Differential Equations (Neural FDE) represent a neural network architecture specifically designed to fit the solution of a fractional differential equation to given data. This architecture combines an analytical component, represented by a fractional derivative, with a neural network component, forming an initial value problem. During the learning process, both the order of the derivative and the parameters of the neural network must be optimised. In this work, we investigate the non-uniqueness of the optimal order of the derivative and its interaction with the neural network component. Based on our findings, we perform a numerical analysis to examine how different initialisations and values of the order of the derivative (in the optimisation process) impact its final optimal value. Results show that the neural network on the right-hand side of the Neural FDE struggles to adjust its parameters to fit the FDE to the data dynamics for any given order of the fractional derivative. Consequently, Neural FDEs do not require a unique α value, instead, they can use a wide range of α values to fit data. This flexibility is beneficial when fitting to given data is required, and the underlying physics is not known.

Ever since the discovery of dendritic cells by Ralph Steinman and Zanvil Cohn in 1973, it is increasingly evident that dendritic cells are integral for adaptive immune responses, and there is an undeniable focus on them for vaccines development. Fungal infections, often thought in-nocuous, are becoming significant threats due to increased immunocompromised or im-mune-suppressed population and climate change. Further, the recent COVID-19 pandemic unraveled the wrath of fungal infections and devastating outcomes. Invasive fungal infections cause significant case fatality rates ranging from 20% to 90%. Regrettably, no licensed fungal vaccines exist, and there is an urgent need for preventive and therapeutic purposes. In this re-view, we discuss the ontogeny, subsets, tissue distribution, and functions of lung dendritic cells. In the latter part, we summarize and discuss the studies on the DC-based vaccines against pulmonary fungal infections. Finally, we highlight some emerging potential avenues that can be incorporated for DC-based vaccines against fungal infections.

Background DaVinci Single-Port (SP) robotic surgery offers several benefits compared to traditional multiport laparoscopic or robotic surgeries. One of the main advantages is that it allows for a minimally invasive approach, resulting in a single, smaller incision and reduced trauma to the patient’s body leading to less postoperative pain, faster recovery, and reduced risk of complications. The cosmesis of a single port with minimal visible scarring is also an attractive aspect to the patients; however, many surgeons use an additional port for energy device, stapler use, and drain insertion. Pure single port surgery with one incision is still rare. Here we share our experience of first 10 cases using SP robotic platform in colorectal surgery. Methods From May 2023 to December 2023, colorectal patients who underwent SP-robotic surgery were analyzed. Placement of the incision was umbilicus for 8 patients, and right lower quadrant for 2 patients through which ileostomy maturation was performed. Data including perioperative parameters and postoperative outcomes were analyzed with a median follow-up of 4.6months (range 0.6-7.4months). Results A total number of 10 colorectal patients underwent DaVinci Single-Port robotic colorectal surgery at our institution during this period. Demographics of the patients showed 4 males (40%) and 6 females (60%) with a median age of 63.5years (range 50-75years). Median body mass index (BMI) was 22.89kg/m2 (range 19.92-26.84kg/m2), and 9 patients were diagnosed with colorectal cancer and 1 patient was diagnosed with rectal gastrointestinal tumor. One patient underwent anterior resection and cholecystectomy simultaneously. Mean operation time was 222min (range 142-316min), and mean wound size was 3.25cm (range 2.5-4.5cm). Nine patients underwent surgery with single incision through which single port trocar was inserted, and one patient had one additional port for drain insertion. Mean hospital stay was 6 days (range 4-8 days) with 1 postoperative complication of bleeding requiring transfusion, but there was no re-admission within 30 days. Conclusion Overall, our experience with single-port robotic colorectal surgery has been promising. With only one patient with additional port for drain insertion, all nine patients underwent SP-robotic surgery with single incision for colon as well as rectal surgeries. Compared to an average postoperative length of stay of 6.5-8 days in laparoscopic colorectal surgeries reported in literature, SP-robotic surgery showed faster recovery of 6 days highlighting its benefits in patient recovery and satisfaction.

The paper delves into the critical issue of damage detection within the guy cable of a truss steel mast, a pivotal component in structural integrity. It introduces a model wherein damage manifests as a localized cross-section reduction in a single element of the cable. Employing Discrete Wavelet Transform (DWT), a pioneering methodology, the study scrutinizes the behavior of the affected elements through static structural analyses. Signal decomposition via the Mallat pyramid algorithm facilitates comprehensive examination. Static displacements at the connection point between the cable and the truss mast serve as the measured variables. Through systematic investigation, the paper evaluates the impact of damage size and location, external loading force, and cable tension force on the efficacy of the proposed approach. Utilizing data derived from Finite Element Method (FEM) computations for wavelet analysis the authors substantiate the findings with numerical examples, thus offering valuable insights into damage detection strategies for structural health monitoring and engineering applications.

Recently, there has been a growing interest in the production of electricity from renewable energy sources (RES). The RES investment is characterized by uncertainty, which is long-term, costly, depend on feed-in-tariff and support schemes. In this paper, we address the real option valuation (ROV) of a solar power plant investment. The real option framework is investigated. This framework considers the renewable certificate price, furthermore the cost of delay between establishing and operating the solar power plant. The optimal time of launching the project and assess the value of deferred option are discussed. The new three stage numerical methods are constructed, the Lobatto3C-Milstein (L3CM) methods. The numerical methods are integrated with concept of Black-Scholes option pricing theory, and applied in option valuation for solar energy investment with uncertainty. The numerical results of L3CM, finite difference and Monte Carlo methods are compared to show the efficiency of our methods. Our data set refers to the Arab Republic of Egypt.

A novel investigation into the structure-function relationship was undertaken to enhance understanding of the mechanism of action of the vasoactive peptide angiotensin II (AngII) using unconventional substitutions such as AIB (α-aminobutyric acid), CHA (cyclohexylalanine acid), IAP (isonipecotic acid), TOAC (2,2,6,6-tetramethylpiperidine-1-oxyl-4-amine-4-carboxylic acid) at position 3, and DMT (2,6-dimethyl-Tyrosine) at position 4. Biological potency assays were conducted on guinea pig ileum, and structural features were analyzed using circular dichroism (CD) and molecular dynamics (MD). CHA3-AngII and AIB3-AngII analogs retained some agonistic activity, whereas IAP3-AngII and TOAC3-AngII derivatives were inactive. CD results indicated low conformational flexibility for AIB3-AngII and CHA3-AngII, and greater conformational restrictions for IAP3-AngII and TOAC3-AngII, consistent with computational modeling analyses. DMT4-AngII exhibited significant agonistic activity compared to the inactive Phe4AngII. Molecular modeling suggested a potential interaction between the hydroxyl group of Tyr4 and the amide bond between positions 7 and 8. AngII showed greater conformational restriction compared to DMT4-AngII and Phe4-AngII, underscoring the importance of tyrosine at position 4.

Objective: This study aims to investigate the relationship between sports psychological capital, coach leadership behavior, and satisfaction among middle school students in the 2023 sports college entrance examination in Chongqing. Methods: Using the structural questionnaire design, this paper carries out a questionnaire survey on the candidates who come to participate in the volleyball specialty college entrance examination in Chongqing, the corresponding database was established and the data were statistically processed by spss21.0 and amos18.0. Results: 1) there was a significant positive correlation between sports psychological capital, coach leadership behavior and examinees satisfaction; 2) sports psychological capital and coach leadership behavior had a certain influence on five dimensions of examinees' personal treatment, personal performance, team integration, team interaction and support from relatives and friends; 3) The sense of self-efficacy in sports psychological capital and coach's leading behavior are the most important to examinees' satisfaction; 4) Both coaches' leadership behavior and sports psychological capital can directly affect examinees' satisfaction, but sports psychological capital is the most important. It can not only directly affect examinees' satisfaction, but also act as an intermediary between coaches' leadership behavior and examinees' satisfaction. Conclusion: Sports College Entrance Examination Students can improve training satisfaction and sports performance by strengthening sports psychological capital training and perceiving coach's leadership behavior; In the leadership behavior of coaches, we should emphasize training and appropriately weaken authoritative teaching, while the training of sense of hope and toughness should be highlighted in sports psychological capital.

Multilayered metallic sheets fabricated by hot metal forming processes are attractive structural components in the aerospace and automobile industry. The strength of the mechanical bond between the different layers is critical to the applicability of such components in load bearing applications. While it is well understood that the process conditions such as temperature, deformation and rate of deformation influence the bond strength, a clear functional relationship between these conditions and the bond strength has yet to be established. The objective of the current study is to investigate the joining of Aluminum-6061 alloy specimens by hot compression bonding. Hot compression tests of beam specimen pairs were conducted at different temperatures (300-500℃), with different strains and strain rates (10-2-10-1 [1sec]). Coupled thermo-mechanical finite element models were utilized to compute the time dependent thermo-mechanical fields that develop along the specimen interface. The computed values were used to map the spatial distribution of a scalar parameter J which is hypothesized to govern bond formation. Mechanical tensile tests were used to determine the bond strength and expose the bonded surfaces. It is demonstrated that the computed J distribution can be correlated well with SEM observations of the debonded surface. It is also shown that the actual bonded area can be predicted from the computations for a certain range of critical J values.

Background: Limited data exist on postoperative acute kidney injury (AKI) in patients underwent esophageal cancer surgery. The purpose of the study was to evaluate the incidence, risk factors and consequences of postoperative acute kidney after esophagectomy. Methods: This was a retrospective cohort study. The study was conducted in a tertiary specialized cancer center in Italy. All patients undergoing elective esophageal cancer surgery between 2016 and 2021 were included in the study. AKI was defined according to Kidney Disease: Improving Global Outcomes criteria (both serum creatinine and urine output), within 48 hours after surgery. Preoperative and intraoperative data were registered. We also collected data concerning progression of AKI, need for kidney replacement therapy, mortality, medical (pulmonary, cardiovascular, septic) and surgical complications within 30 days from surgery, as well as length of hospital stay. Results: Incidence of postoperative AKI was 32%. The independent risk factors were body mass index and the invasive surgical approach. Persistent AKI accounted for 15% of the cases and it was associated with increased risk of major cardiovascular events (odds ratio 4.14, 95% CI 1.05-15.8, p-value 0.036), pulmonary complications (OR 3.67, 95% CI 1.04-14.9, p-value 0.050) and increased length of hospital stay (AME 7.2, 0.5-13.9, p-value 0.035). Conclusions: Postoperative AKI is common after esophageal cancer surgery. BMI and totally invasive surgical approach are independent risk factors. Persistent AKI lasting more than 48 hours increased the risk for cardiovascular and pulmonary complications, with prolonged length of hospital stay.

Considerable research on intergroup relations emphasizes attitudes, motivations, and emotions that lead to reduction of prejudice. While factors that actively promote positive intergroup interactions have been emerging, a central theoretical framework has not been formally proposed. To address this gap, we engage a positive psychology lens to explore how and why people overcome their internalized biases to seek out successful and positive intergroup relations, looking to the positive counterparts of traditional prejudice-reduction models to begin building a framework of understanding. We reviewed the literature on values that guide intergroup behavior. After scanning 16,840 records that emerged in PsycInfo using keywords “egalitarian,” “non-prejudice,” and “intergroup,” we assessed 158 articles for eligibility. Among the relevant articles (N = 54), we analyzed authors’ definitions, methods of measurement, types of processes, and outcomes associated with egalitarian and non-prejudice values as they related to intergroup behavior. Overall, there was notable variability in how researchers conceptualized and observed egalitarianism. We discuss the five broad categories of egalitarianism (prejudice reduction, positive expression, concern for others, low social-dominance orientation, and universal orientation) and how they relate to positive or negative, and approach or avoidant outcomes. We propose a centralized model for studying positive values in intergroup contexts moving forward.

Burnout represents a concern for all healthcare providers, particularly those specializing in emergency medical care for whom burnout outcomes have been well-documented. What remains unknown is the effect of burnout on redeployed medical specialists during the COVID-19 pandemic from an appointment-centered practice to emergency care directed by public health considerations. This research aims to identify and assess the burnout responses of fourteen medical specialties noted in searched returns of the four most cited articles published since 2020 about non-emergency physicians regarding their burnout brought on by the unanticipated need for them to provide emergency care during the recent pandemic. The hypothesis is that medical specialists accustomed to planning for emergency possibilities in their appointment-centered practice would demonstrate the least burnout regarding COVID-19-related emergencies. Considering coping as a process based on Lazarus's research, comparing and ranking the COVID-19 emergency responses across the various normally appointment-centered medical specialties in their employed coping strategies determines the outcome. With the hypothesis supported, suggested interventions for future pandemics—when these specialists are, again, redeployed to emergency care directed by public health considerations—are those coping strategies identified as most effective in reducing burnout while maintaining the viability of the medical specialty and excellent patient care.

Anaerobic digestion of waste material to biogas, with the remaining digestate slurry used as agricultural biofertilizer, is already a route of sustainable fuel production and its uptake will grow further. However, the foam layer that forms on top of the reacting mixture impedes the process and leads to liquid and solid material contaminating the gas product. Ideally, any effective foam repression should be low-cost, and react fast. Therefore, methods of optimizing anaerobic digestion need foam repression as one of the parameters in increasing gas yield. Foam can be repressed by pre-treating substrate which destroys filamentous bacteria and adding trace elements. The drawback to this method is the high cost of pre-treatment, the trace elements not being biodegradable and being toxic at high concentration; this method does not completely repress foam and is only effective under moderate organic loading

The mechanical pre-treatment constitutes an unavoidable pre-step prior to biofuels conversion. As the cost of this step is often underestimated, recently researchers have striven to identify and characterize the mechanical pre-treatment effects in terms of post-treatment physical characterization, derived improvement of enzymatic digestibility, and output yields. The status of existing mechanical pre-treatment techniques is reviewed by substrate’s typology for lignocellulose biomass, focusing on comminution techniques. Emphasis has been dedicated to the particle size achieved after treatment, crystallinity breakage and eventual inhibitory phenomena deriving from the application of particle size reduction, which are analysed and discussed.

Weathering and erosion transport minerals and organics toward the sea or lake bottoms over geologic time. The finest solids are deposited in lower, less turbulent areas, such as lake bottoms and continental shelves. They sometimes stack up to thicknesses of kilometers, and begin compacting. These sediment sections are called shales, and as initially deposited in water, shales can have porosities up to 50-80{\%} water, As they are buried, many alteration products from oil to slate are produced due to overburden and temperature increasess, making them important to study. A preceeding paper \cite{1} showed that pressure solution is the primary mechanism for porosity reduction, with possible mechanical compaction at shallow depths. Without naming the mineral(s) involved, it postulated that the greater the product of the water and pore interfaces, the faster the reaction would proceed. This term is $ \varphi^{4m/3}(1-\varphi)^{4n/3}$ , where $\varphi$ is porosity and m and n are numbers close to unity. The large exponents, {\em 4/3}, recognize that the reaction occurs at the molecular scale at which the surfaces are rough. A second term, $\exp^{(-E/RT)}$ , indicates that the reaction is impeded by a quantum energy barrier, E, with diminished impeding power as increased available thermal energy, represented by the absolute temperature, T, becomes available at greater depths in the Earth. These two factors combine to allow porosity $\varphi$ to reduce with time, or equivalently for the fraction of solids, $(1-\varphi)$, to increase with time,$\left. \frac{\partial(ln(1-\varphi) ) }{\partial t } \right |_{\sigma} = (\varphi )^{4m/3}( 1-\varphi )^{4n/3}Ae^{-E/(RT)}$. { \em Here it is shown that this equation can cover quantitatively any actual deposition rates which may have been experienced by the six sections studied, the actual deposition rates being unknown for these cases. Hence a time-depth depositional history for any new shale section, known in detail, would allow determination of the parameters m, n, E and a lumped proportionality constant A. This was accomplished by showing that, for a wide range of depositional rates, r, the range of E for any of the studied sections is small compared to laboratory measurements of quartz solution\cite{2}, 24+-15kJ/mol. Results were obtained over this range of r's using the previously determined m and n, and porosity and temperature profiles. The presently existing porosity profiles necessarily incorporate any overpressure or underpressure conditions that may have existed in the past or currently, as the net difference between overburden and pore pressure is a primary driving force for pressure solution. $SiO_2$ usually comprises 20-50{\%} of shales. In conclusion, pressure solution of quartz can account for vertical compaction of shales quantitatively in the studied examples. Separately, a quasi-eqivalent method for discussing reduced porosities in Macron 2 versus Macron 1 as increased vertical stress, rather than additional horizontal stress, is illustrated. Experiments are suggested to clarify the pressure solution mechanism. The role of horizontal forces is discussed. From a global point of view, shale compaction by pressure solution is a quantified step in the cycling of continental rocks, beginning with rifting.

Vertical and horizontal bone augmentation is one of the most challenging techniques in bone engineering. The use of barrier membranes and scaffolds in guided bone regeneration (GBR) procedures is a common approach for the treatment of lost bone around teeth and dental implants. The aim of this study was to estimate the barrier effects of a synthetic poly (lactic acid/caprolactone) [P(PA/CL)] bilayer membrane for GBR, compared to a porcine collagen bilayer membrane, in the vertical augmentation model on 10–12-months old rat skull without periosteum. The HAp block (diameter: 4 mm, height: 3 mm, porosity:75%, average pore size:150 μm) was placed on the rat skull without a periosteum. The P(LA/CL) membrane (solid layer: 25 μm, porous layer: 175 μm) or the collagen membrane (solid layer, porous layer) was applied onto the HAp block. At 3, 6, and 12 weeks after the surgery, the incised tissues were fixed, decalcified, and stained with hematoxylin and eosin for histological evaluation. The P(LA/CL) membrane remained until 12 weeks and could achieve barrier effects to inhibit cellular invasion from the repositioned soft tissues. Local bone formation occurred in the interconnected pores of HAp at 6 weeks. On the other hand, the collagen membrane did not inhibit cellular invasion for its expansion until 3 weeks, and was absorbed until 6 weeks. The results indicated that the P(LA/CL) membrane might be effective in GBR as occlusive absorbable membrane.

TTF1-NP(5,2′,4′-trihydroxy-6,7,5′-trimethoxyflavone nanoparticles), derived from the traditional Changbai Mountain medicinal plant Sorbaria sorbifolia (SS), has been showedits anti-cancer effect in various liver cancer cell types and tissues. The present study was designed to evaluate the antitumor mechanism of the TTF1-NP against HepG2 hepatoma cells and HepG2 cells-induced hepatocarcinoma (HCC) in nude mouse model. Here we demonstrated that TTF1-NP inhibits tube formation of HUVECs and HepG2 cell migration and invasion, and inhibits tumor growth in nude mice implanted with HepG2 cells through the downregulation of STAT3 protein and activation, along with VEGF, KDR, bFGF, MMP2 and MMP9 levels. We further revealed that TTF1-NP decreased the DNA-binding capacity of STAT3. Together our results provide a mechanism by which TTF1-NP suppresses cancer cell migration, invasion and angiogenesis through the action of STAT3 and suggests TTF1-NP as a potential therapy for hepatocellular cancer treatment.

Hazelnut (Corylus avellana L.) is of great agroeconomic importance, prized for its nutritional value and antioxidant properties. Its yield and quality may differ due to factors such as season (S), locality (L) and cultivar (C). Our objective was to determine the dynamics of morphological features and antioxidant properties in nuts of Barcelona and Tonda di Giffoni (TDG) cultivars planted at two localities (Cunco and Perquenco) during three productive seasons (S1, S2 and S3). Barcelona grown in Perquenco in S1 and S3 (less precipitation, more solar radiation), performed better than in Cunco with respect to most morphological nut, kernel and shell features, and the same parameters generally had the same trends for TDG in S2 and S3. Among the seasons at the same localities, the differences between the predominant condition defects for both cultivars were in the decreasing order wrinkled/deformed kernels, double kernels, blank and mold ker-nels, with about 75% of hazelnuts without defect. In both cultivars, the shell had higher antioxi-dant properties that increased in S1 and S3 at both localities, and were consistently higher than in the kernels. Lipid peroxidation was higher in the kernel than shell in both cultivars and local-ities for S1 and S3. The results of this study suggest that the different hazelnut cultivar features including physical and chemical components depend on season and locality, which offers im-portant clues for all those interested in the hazelnut industry.

In this study, a comprehensive review on production scheduling based on reinforcement learning (RL) techniques using bibliometric analysis has been carried out. The aim of this work is, among other things, to point out the growing interest in this domain and to outline the influence of RL as a type of machine learning on production scheduling. To achieve this, the paper explores production scheduling using RL by investigating the descriptive metadata of all pertinent publications contained in the Web of Science database. The study focuses on a wide spectrum of publications spanning the years between 1998 and 2023. The findings and recommendations of this study can serve as new insights for future research endeavors in the realm of production scheduling using RL techniques.

Marine industries are dependent on the ocean and often have a direct impact on the marine environment. Although previous studies have talked about pollution from marine industries, it is not known to what extent and to what extent these behaviors affect the ocean. Therefore, this study examines the impacts of major marine industries on the marine environment, using China as an example. The Ministry of Ecology and Environment of the People's Republic of China categorizes the quality of seawater into Class I, Class II, Class III, Class IV, and Inferior Class IV in descending order according to the quality from good to poor. In this study, water quality of Class I and Class II are defined as good quality seawater, Class III as average quality, Class IV and Class IV as poor quality, and the proportion of the area of seawater with different water quality to the total area of the sea area symbolizes the overall quality of the marine environment. We use panel data from 11 provinces and cities along the coast of mainland China from 2006 to 2020, estimated by the full feasible generalized least squares (FGLS) method, to study the impacts of the development of coastal tourism, marine transportation, marine shipbuilding, marine salt, mariculture, and marine fishing on the marine environment. The empirical results show that, in descending order of the degree of influence, the marine industries that cause a decrease in the area of good quality seawater are coastal tourism, mariculture and shipbuilding, and the marine industries that cause an increase in the area of poor quality seawater are marine transportation and shipbuilding, while the marine salt industry has no obvious influence on the marine environment, and the development of the marine fishing industry indirectly contributes to the improvement of the marine environment.

This study aims to analyse the technical viability and economic feasibility of rainwater harvesting systems for single and multifamily residential buildings in the city of Florianópolis, Brazil. Simulations were conducted for representative buildings in the city under different water usage scenarios and system designs, in a total of 36 simulation scenarios. An economic analysis was performed for four scenarios over a twenty-year period. Both initial and operational costs were considered and net present value, internal rate of return and payback used as feasibility indicators. Almost all of the cases simulated were technically viable for the group of houses, and up to 78.9% for flats. As for the economic analysis, for houses, between 60.1% and 74.8% of the cases were economically feasible, achieving a discounted payback period ranging from 6.2 to 8.6 years. For flats, between 57.8% and 64.2% of the cases were economically feasible, achieving a discounted payback period ranging from 4.8 to 5.6 years. As the water tariff in the city underwent changes recently, the former and current tariff formats were compared. The current tariff format provides more economic benefits for saving potable water, and leads to a higher net present value and a shorter discounted payback period.

Wellbeing is a multifaceted concept that involves various facets of human condition and experience, including individual and communal spiritual, emotional, intellectual, physical, and social dimensions. To explore the complex facets of sustainable wellbeing, this study utilized an interpretive qualitative research approach, looking at round table (focus group) discussion data obtained from a diverse group of public and private sector representatives, including education, government, non-governmental organizations, and businesses in Qatar. The purpose of this study was to gain a contextualized understanding of how participants perceive and experience wellbeing. A purposive sampling technique was employed to recruit participants representing different sectors of society. To elicit participants’ perspectives on wellbeing, thematic analysis was used to identify recurring themes and patterns that emerged from the focus groups, viewed through the lens of Bronfenbrenner’ Ecological Systems Theory. Findings reveal that wellbeing is a very personal and subjective experience. Key themes extracted from the data include challenges to sustainable wellbeing in Qatar, including technological disruptions and socio-cultural influences. These challenges require proactive measures that reflect educational priorities, promote cultural preservation, and foster resilient communities while emphasizing individual and collective sustainable wellbeing. This research also identified opportunities for enhancing sustainable wellbeing in Qatar.

This research explores the application of Support Vector Machine (SVM) and Digital Surface Models (DSM) derived from Unmanned Aerial Vehicle (UAV) data for a vertical-horizontal classification of mangrove ecosystems in Tongke-tongke and Samataring Village. The study focuses on integrating high-resolution DSM subtracted from Digital Terrain Models (DTM) to classify mangrove vegetation into sixteen distinct vertical-horizontal classes based on vegetation type and elevation. The analysis revealed that older mangroves, particularly those within the 25-35 meters elevation range, dominate the landscape, accounting for 43.40% of the total classified area. This dominance suggests a mature and ecologically stable mangrove ecosystem, which is crucial for biodiversity conservation and carbon storage. The study demonstrates the effectiveness of SVM and UAV technologies in providing detailed and accurate ecological assessments of mangrove forests. The classification results contribute valuable insights into the structural diversity and health of mangrove ecosystems, facilitating targeted conservation and management strategies. Additionally, the research highlights the utility of advanced remote sensing and machine learning techniques in enhancing the precision of environmental monitoring and the assessment of carbon sequestration capabilities within mangrove ecosystems. The findings underscore the potential of UAV-based remote sensing for ecological studies, offering a replicable method for similar assessments in other regions, thereby supporting global environmental management and climate action initiatives.

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.

The increasing regulatory pressure to monitor and reduce GHG emissions and air pollutants requires cost-effective methods for their surveillance. The most common technique used for scientific investigations on gas concentration monitoring in barns are accurate but expensive and with a complex maintenance. This research study analysed the potential use of a low-cost portable measurement devices for the measurement of ammonia (NH3) and carbon dioxide (CO2) concentrations in an open dairy barn. A comparison between gas concentrations acquired at different heights from the floor by using portable devices and those acquired by a photoacoustic infrared multigas spectroscope (i.e., reference measurement) in the same sampling locations was carried out to determine the precision of the low-cost portable devices. The performance of low-cost portable devices was statistically analysed by the application of the one-way analysis of variance, correlation analysis and regression analysis. The results showed a significant difference between gas concentration values at various heights from the floor for both NH3 and CO2. The correlations between concentrations acquired by the low-cost portable device and the INNOVA were statistically significant (r=0.83; P<0.001) for gas concentrations monitored at 0.4 m from the floor. Compared with the reference measurement device, the low-cost devices were effective in the monitoring of NH3 concentrations at 0.40 m from the floor though it underestimated them in the barn at increasing of the height from the floor, whereas the device was not adequate for CO2 concentrations. In detail, the relative measurement error of the low-cost devices compared to INNOVA was reduced close to the floor during NH3 concentration measurements. Within these limitations, this device could be useful for monitoring NH3 concentration in the barn and to assess variation in NH3 concentrations mainly related to the animal occupied zone. Further efforts are needed in this field of research to identify low-cost device that could simplify emission estimation from open dairy barns.

Improving the capabilities of faculty members, including competencies of emotional intelligence in professors, can play a major role in various education levels of success and achievement, adjustment, and mental health in students, and is a fundamental solution to the promotion of higher education quality. For accurate examination of the issue, the present study aimed to determine the association between basic science professors' emotional intelligence and the ability to teach at the School of Medicine of Iran University of Medical Sciences. The present descriptive-analytical study was conducted at the School of Medicine of Iran University of Medical Sciences by census sampling of faculty members of the basic sciences. We included 98 faculty members in the study. The research tools included Dr. Haghani's "Emotional Intelligence in Teaching" questionnaire and Dr. Akbari's "Teaching Ability" questionnaire. We analyzed data through descriptive statistics and analytical tests, including Spearman's correlation test, Pearson test, t-test, and two-way analysis of variance. The mean score of faculty members' emotional intelligence was 111.51±9.3 equal to 89.93±7.5 percent, and the median score of total teaching ability of the questionnaire was 101.89±8.59 equal to 87.84±7.4 percent. There was a positive correlation between faculty members' emotional intelligence and teaching ability. (p= 0.0001, r= 0.71). The faculty members' emotional intelligence can be a determinant in their teaching ability. Their emotional intelligence was evaluated as good and there was a positive relationship between emotional intelligence and teaching ability.

C-C motif chemokine receptor-8 (CCR8) belongs to class A of G protein-coupled receptors (GPCRs). CCR8 interacts with the specific chemokine ligand CCL1/I-309 in humans, which is produced by various cells, including tumor-associated macrophages and regulatory T cells (Treg). CCR8 is highly expressed on Treg and T-helper 2 (T_H2) cells recruited to the inflammation site and is implicated in allergy, asthma, and cancer progression. The CCR8⁺Treg has been suggested to be an important regulator in the immunosuppressive tumor microenvironment (TME); therefore, it has been desired to develop sensitive monoclonal antibodies (mAbs) for CCR8. This study developed a specific mAb for human CCR8 (hCCR8), which is useful for flow cytometry by employing the Cell-Based Immunization and Screening (CBIS) method. The established anti-hCCR8 mAb, C₈Mab-21, (mouse IgM, kappa) reacted with hCCR8-overexpressed Chinese hamster ovary-K1 (CHO/hCCR8) cells, TALL-1 (acute T lymphoblastic leukemia), CCRF-HSB2 (human T-lymphoblastic leukemia), and natural killer cells, which express endogenous hCCR8 by flow cytometry. Furthermore, C₈Mab-21 demonstrated a moderate binding affinity for CHO/hCCR8 and TALL-1 with a dissociation constant of 6.5×10^-8 M and 2.0×10^-8 M, respectively. C₈Mab-21, which was established by the CBIS method, could be a useful tool for analyzing the hCCR8-related biological response using flow cytometry.

Generative artificial intelligence (GenAI) has been developing with many incredible achievements like ChatGPT and Bard. Deep generative model (DGM) is a branch of GenAI, which is preeminent in generating raster data such as image and sound due to strong points of deep neural network (DNN) in inference and recognition. The built-in inference mechanism of DNN, which simulates and aims to synaptic plasticity of human neuron network, fosters generation ability of DGM which produces surprised results with support of statistical flexibility. Two popular approaches in DGM are Variational Autoencoders (VAE) and Generative Adversarial Network (GAN). Both VAE and GAN have their own strong points although they share and imply underline theory of statistics as well as incredible complex via hidden layers of DNN when DNN becomes effective encoding/decoding functions without concrete specifications. In this research, VAE and GAN is unified into a consistent and consolidated model called Adversarial Variational Autoencoders (AVA) in which VAE and GAN complement each other, for instance, VAE is good at generator by encoding data via excellent ideology of Kullback-Leibler divergence and GAN is a significantly important method to assess reliability of data which is realistic or fake. In other words, AVA aims to improve accuracy of generative models, besides AVA extends function of simple generative models. In methodology this research focuses on combination of applied mathematical concepts and skillful techniques of computer programming in order to implement and solve complicated problems as simply as possible.

Headache is considered to be one of the most common causes of medical treatment and evaluation worldwide in both acute and outpatient settings. It is the most common neurological symptom seen worldwide affecting all genders, ages, ethnicities, and socioeconomic levels. It’s impact is noted in educational decline in school-aged children and decreased productivity through sick leave in adults. Its overall burden is well documented in well-resourced countries but limited data is seen low resourced countries. While many underlying causes bring about secondary headaches, primary headaches and more specifically migraines have been more widely explored. Migraines have a distinct criterion that is inclusive of one day duration (4 hours to 7 days, unilateral distribution, nausea and vomiting and disability as a few examples. However, migraines can vary and proper documentation through a migraine diary can help to guide treatment. Management of migraines can vary. Lifestyle modification is a key factor in the overall prevention and reduction of triggers in migraines. In addition to this, pharmacotherapy can be given in a tier-based approach based on overall severity and frequency of the migraine. Interventions have progressed from botox injection and have seen the advent of new medications such as nasal sprays to novel formulations of pre-existing drug formulations. Nonetheless, there is great room for further studies of headaches and migraines. Research specifically in low-resource countries can prove to beneficial.

This study describes KPC-204, a novel variant of Klebsiella Pneumoniae carbapenemase, characterized by a KDD amino acid insertion at Ambler position 269 deviates from KPC-2. This variant was identified in an ST11-type clinical isolate of carbapenem-resistant Klebsiella Pneumoniae from China. Notably, KPC-204 exhibits resistance to both ceftazidime-avibactam and carbapenems. Genetic analysis revealed that blaKPC-204 was located on a highly mobile IncFII/IncR plasmid within a complex genetic structure that facilitates its spread. Functional analysis, achieved through cloning into E. coli DH5α, validates KPC-204's contribution to increased resistance to ceftazidime-avibactam. The kinetic parameters showed that KPC-204 exhibited similar affinity to KPC-2 toward ceftazidime and reduced sensitivity to avibactam. Mating experiments demonstrated the resistance's transmissibility. This investigation underscores the evolving diversity of KPC variants affecting ceftazidime-avibactam resistance, highlighting the necessity for continuous monitoring.

Background: Surveys conducted in different regions of the world showed that the prevalence rates of health risk behaviors (HRBs) in university students are sometimes higher than those found in non-university populations. This study aims to identify the prevalence rates and demographic and academic environment correlates associated with HRBs among Brazilian university students. Methods: In a cross-sectional epidemiological study, a random sample of 5,310 university students answered an online questionnaire with demographic (sex, age, skin color, marital status, and paid work) and academic setting information (housing type, size of campus, year and shift of study), as well as items clustered in four HRB domains: personal safety and violence, sexual behavior and contraception, addictive substance use, and eating habits, physical activity, and sleep. The data were analyzed statistically using bivariate analysis and hierarchical multiple regression. Results: The highest prevalence rates occurred in HRBs clustered in the domain of eating habits, physical activity, and sleep (> 60%), while HRBs for personal security and violence were less prevalent (