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The current study examined the psychometric properties and correlates of three measures assessing individual differences in mattering among people from Palestine assessed in January, 2024. This study uniquely considers mattering as a resource and feelings of not mattering as a risk factor among people experiencing traumatizing life circumstances. Our sample consisted of 950 Palestinian adults (305 men and 645 women). They completed the General Mattering Scale, the Anti-Mattering Scale, the Fear of Not Mattering Inventory, and the Depression Anxiety Stress Scales-21 (DASS-21). Extensive psychometric tests supported these measures as each having one factor with adequate reliability and validity. Examination of means indicated significantly elevated levels of fear of not mattering, anxiety, depression, and stress. Regression analyses further established that each measure predicted significant unique variance in anxiety, depression, and stress. The findings attest to the further use of these measures and how feelings of mattering can be vital resource as the need for resilience and adaptability escalates due to traumatizing events.

The study delves into the relationship between sustainability, consumer behavior, and leadership styles among students at C3S Business School in Barcelona. It focuses on the impact of ecological consciousness, which refers to environmental awareness and concern, on purchasing decisions and leadership practices. In the current context, with sustainability increasingly crucial in decision-making, individuals and organizations are reassessing their actions considering ecological concerns. The literature suggests a growing demand for sustainable products driven by heightened environmental awareness among consumers, especially millennials. Despite this trend, there is a noticeable gap between attitudes and behaviors, with many environmentally conscious individuals needing help translating their values into consumer choices. The research uses a qualitative approach, combining semi-structured interviews and online questionnaires. Semi-structured interviews allow in-depth exploration of students' environmental attitudes and behaviors, while online questionnaires provide a broader perspective. This approach was chosen to ensure a comprehensive understanding of how students identify with environmentalism and its impact on consumer behavior. The study categorizes participants into environmentalist and non-environmentalist groups, analyzing their motivations, purchasing behaviors, and the influence of leadership styles on their decisions. Key findings reveal that transformational leadership styles significantly enhance pro-environmental behaviors among students, aligning personal values with sustainable practices. These findings have practical implications for businesses and educational institutions, highlighting the role of leadership in promoting sustainable behaviors.

The objective of the current study was to develop a model for predicting hope in university students that takes into account the time perspective and attachment patterns, with psychological resilience serving as a mediator. The research method was descriptive-correlational and pathway analysis. The study’s statistical population comprised all undergraduate students at non-state universities in Tehran during the academic year 2019-2020. 480 students (312 females and 168 males) were selected through the clustered random sampling method to comprise the statistical sample. Adult Attachment Styles (AAS), Zimbardo Time Perspective Inventory (ZTPI), Connor-Davidson Resilience Scale (CD-RISC), and Adult Domain-Specific Hope Scale (DSHS) comprised the questionnaires that were implemented. The data analysis was conducted through pathway analysis via SPSS and AMOS version 23. The findings indicated that students' hope is significantly correlated with their psychological resilience, time perspective, and secure, avoidant, and ambivalent attachment styles (p

Introduction To successfully provide and distribute agricultural services throughout the supply chain and enhance efficiency in this sector, selecting the right locations for service centers is a crucial and complex challenge. One of the ways to develop rice mechanization infrastructure is to establish rice seedling banks. A rice seedling bank is a specialized facility dedicated to the large-scale industrial production of rice seedlings, utilizing seedling trays to optimiz space, resources, and labor. The primary aim of this research is to identify the most suitable location for establishing a rice seed bank by employing multiple-criteria decision-making (MCDM) methods.Materials and MethodsThe present research was conducted in Fuman County, Guilan Province, Iran. The main objective of identifying a location for the seedling bank in the studied area is to minimize transportation costs for the seedling trays while selecting a site with the greatest potential for successfully establishing the seedling bank. To achieve this, we analyzed the location criteria for the seedling bank at the district level during the early stages of the research. The selection criteria for identifying a suitable district include several factors, such as the number of farmers, land leveling, area under cultivation, the number of agricultural machines, the level of mechanized transplanting and harvesting, and the number of seed banks in each district. Subsequently, the best village in the district, chosen in the prior step, was evaluated using several key criteria: total cultivated area, number of farmers, cultivated area per farmer, and total distance from other villages within the district. Shannon's entropy method was employed to estimate the weight and rank for the location criteria in both stages. The districts were ranked using the Fuzzy VIKOR method, while the TOPSIS method was used to prioritize villages within the selected district.Results and DiscussionAccording to the results of the Fuzzy VIKOR method, among the five studied districts in Fuman County, Lulaman rural district stands out as the best location for establishing a seedling bank. Furthermore, based on the results obtained from the TOPSIS method, Khoshknudhan-e Bala village is identified as the most favorable site for establishing a seedling bank within the Lulaman district, among the fifteen alternatives considered. The VIKOR model excels in ranking alternatives due to its ability to generate ideal positive and negative maps, making it particularly well-suited for location and spatial analysis. By utilizing this model, we can assess not only the locations themselves but also evaluate how each alternative measures up against both positive and negative ideals. In contrast, other models lack this capability, as they merely identify the optimal location without providing a comprehensive understanding of each alternative's standing.ConclusionThe purpose of this research is to provide a suitable algorithm for locating a seedling bank in Fuman County. Given the numerous influencing factors and available options, the integration of the VIKOR MCDM model with fuzzy numbers to identify the most suitable district, followed by the TOPSIS MCDM model to determine the best village, yielded promising results. The findings indicate that several factors play a crucial role in identifying the optimal location for the seedling bank. However, integrating all these elements through traditional methods—such as manual map analysis—proves impractical due to the sheer volume of data involved. Furthermore, neglecting these factors in site selection leads to substantial waste of material resources, energy, and environmental resources. Overall, the results of the Fuzzy VIKOR analysis revealed that Khoshknudhan-e Bala village in the Lulaman district is the best option for establishing a seedling bank in Fuman County.

IntroductionAgricultural mechanization plays a crucial role in driving agricultural development and is considered one of the most capital-intensive inputs in the agricultural sector. Effective supply chain management is a crucial necessity for improving the quality of agricultural machinery and reducing operational expenses in agricultural mechanization. This is imperative for the advancement of agricultural mechanization. The present research aims to identify the primary structures of the supply chain for rice agricultural machinery in the provinces of Gilan and Mazandaran in Iran. The study also examined the important functional aspects of the chain members, including manufacturers, importers, retailers, and farmers who serve as the ultimate consumers of the chain's products. Furthermore, the research delved into the processes that govern the supply chain.Materials and MethodsMeasuring supply chain performance involves utilizing the Supply Chain Operations Reference model (SCOR) with five distinct dimensions: cost (12 questions), responsiveness (22 questions), flexibility (16 questions), assets (13 questions), and reliability (30 questions). The study data were analyzed using SPSS software. Additionally, latent variables were generated at each level of the hierarchy by using the variables from the aforementioned model. The normality of the variables was assessed using the Kolmogorov-Smirnov test. The evaluation of normal variables was conducted through a one-sample t-test, while abnormal variables were evaluated with a one-sample Wilcoxon test. Furthermore, descriptive analysis of the expectations and constraints of manufacturers and importers regarding rice machines was carried out.Results and DiscussionThe Wilcoxon test results indicate the impact of commitment, cost management, and communication on the average test value. The variables of normal distribution such as human resource management, quality management, strategic organization, flexibility, responsiveness, performance, and reliability in stores, exhibit significant deviation from the mean value. The majority of store managers and agricultural rice machinery dealers lack formal education in the field of agricultural machinery. Including individuals with educational backgrounds in agricultural machinery at various stages of the supply chain will likely improve the dissemination of information throughout the chain. Employing dependable techniques for transmitting accurate information regarding consumers' quality requirements can assist suppliers in manufacturing or importing superior-quality machinery. This approach not only minimizes uncertainty in the supply chain and streamlines inventory management but also reduces the lead time for meeting consumer demands.ConclusionThe continuous demand for rice agricultural machinery in Iran has resulted in the bullwhip effect phenomenon being perceived as a less significant challenge in the supply chain. Currently, local manufacturing enterprises have relatively limited knowledge regarding the market and technical needs of rice farmers compared to their foreign counterparts. It is advisable for manufacturing companies to broaden their comprehension of consumer behavior and needs by diversifying their market evaluation techniques.

ABSTRACT COVID‐19 had a significant impact on public health, including respiratory and cardiovascular complications. Because of COVID‐19 hypercoaglupathy effect, it can lead to cardiovascular complications. A 68‐year‐old Iranian male admitted to the infectious diseases department with the diagnosis of COVID‐19 infection. Despite initially stable vital signs and mild symptoms, the patient's condition rapidly deteriorated over the course of several days, with severe respiratory distress and other concerning symptoms. Further investigations revealed evidence of aortic aneurysm or dissection, which was confirmed to be a Stanford type A aortic dissection extending from the aortic root to the abdominal aorta. The available evidence points to a potential association between COVID‐19 infection and aortic dissection, and the need for continue investigations about the pathophysiological mechanisms underlying this relationship.

The present study examined and analyzed risks in oil and gas industries according to API RP 580 and 581 standards and the theory of Intuitionistic fuzzy sets (IFSs) for stakeholders' decisions and implementation in the risk-based inspection program. In this study, time risk analysis is performed concerning the significance of time risk in a risk-based inspection (RBI) program, as well as risk calculations. This approach is critical for calculating inspection time intervals and lowering relevant expenditures. The studied case examples were three steel tanks under the pressure of sour gas and gas condensate exposed to hydrogen cracking (HIC) damage. After examining the mechanism of damage and obtaining information from the test results and Fitness for Service (FFS), risks were ranked and prioritized. The obtained risk information forms the basis of RBI. The results indicated the high financial risk of all three tanks. The risk of environmental damage was medium to Tanks 1 (V1000) and 2 (T2020), and high to Tank 3 (T2320). The highest time risk was assigned to T2320 and the lowest time risk was assigned to V1000. The findings indicate that is in critical condition of Tank 3 compared to the other tanks. Additionally, the data was evaluated using the RBI qualitative method to compare the proposed approach's outcomes. An analysis of the outcomes from both methods indicates that the proposed method demonstrated superior accuracy and clarity. The findings can be used in the RBI program.

Environmentally friendly soil improvement approaches are recently a global interest due to their lower environmental impact compared to traditional stabilizers. The traditional stabilizers, such as cement, contribute significantly to greenhouse gas emissions and soil degradation. Tragacanth Gum (TG), a carbohydrate polymer, is an eco-friendly additive, which offers a more sustainable and less polluting alternative. Only a few studies on the strength behavior of TG stabilized soils have been conducted. This study investigates the effect of TG addition in improving low-strength sandy soil. Unconfined compressive strength (UCS), direct shear, and scanning electron microscopy (SEM) tests were carried out on stabilized sandy soil with TG at 0.5 %, 1 %, and 2 % by weight after curing times of 1, 3, and 7 days to evaluate their short-term performance. UCS values increased from 20 kPa to 72 kPa, depending on the dry unit weight of sandy soil. The TG stabilization improved cohesion value from 8 kPa to 53 kPa and internal friction angle from 30.88° to 46.64°, for dry unit weights of 16 and 17 kN/m3, respectively. This study shows the prospect of using TG as a greener additive in geotechnical and pavement applications.

In the present study, the polyethersulfone (PES)/graphene oxide (GO)/polyethylene glycol 200 (PEG-200) adsorptive mixed matrix membranes (AMMMs) were fabricated using a non-solvent induced phase inversion method. According to the design of experiments using response surface methodology (RSM), PES concentration (15, 17.5, and 20%), PEG-200 concentration as a pore former additive (0.5, 2.5, and 4.5%), and GO nanosheet loading percent (0, 0.5, and 1%) were varied during fabrication. A green solvent, dimethyl sulfoxide, was used as an alternative to conventional solvents, while it exhibited better membrane performance. Methylene blue (MB) removal was optimized in PES AMMM synthesis using RSM. Attenuated total reflectance Fourier transform infrared spectroscope confirmed the presence of GO functional groups in the optimum membrane. Scanning electron microscopy analysis revealed the optimum membrane was thicker than the neat membrane and atomic force microscopy analysis demonstrated higher surface roughness. The membranes hydrophilicity increased, with a decrease in water contact angle from 61.1 [+ or -] 0.2[degrees] (neat PES) to 54.4 [+ or -] 0.9[degrees] (optimal membrane). Pure water flux of 524.8 L [m.sup.-2] [h.sup.-1] and MB rejection of 97.46% were obtained for the optimum membrane. Furthermore, the optimum PES AMMM demonstrated a greater dynamic adsorption capacity in comparison to the unmodified PES membrane. Highlights * The optimization of the polyethersulfone (PES) adsorptive mixed matrix membranes (AMMM) for methylene blue removal was performed utilizing the response surface methodology. * The calculation of the dynamic adsorption capacity (DAC) was performed through the breakthrough curves. * The integration of graphene oxide into the AMMM resulted in an enhanced DAC of the AMMM. * The PES AMMM performance is based on Donnan electrostatic exclusion. KEYWORDS breakthrough curves, dye adsorption, membrane, nontoxic solvent, optimization, polyethersulfone, 1 | INTRODUCTION In modern times, alteration in lifestyles, population growth, and urbanization have contributed to an increase in wastewater production from various industries, highlighting the necessity for development of [...]

Introduction: In this era of progress, interest has developed regarding advancing deep learning (DL) in medicine. However, there has been reluctance to use deep learning, particularly among medical educators. The limitations of previous research were examined in this study, along with the extent to which DL can be used in medical education and its potential impact on educational quality. We were interested in discussing DL’s prospects, and determining whether we could benefit from it in medical education.Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was used to manage this review procedure. Six databases were searched carefully to obtain relevant studies. Our search identified 981 articles from the database based on our standards. After filtering the duplicated articles, 11 studies were included in the systematic review. Results: The results showed that DL applications attracted researchers’ attention in the medical and education technology owing to their effectiveness to provide the personalized assistanceand feedback. Furthermore, the majority of research concentrated on teaching medical students how to utilize DL applications in the classroom, and all of them tried to improve medical students’proficiency with DL instruments in practical applications. Deep learning components in medical learning environments have two segments—in the educational settings like speech recognitionor Video content analysis for affecting students’ learning, and in the medical settings, applying deep learning from diagnosis to prevention. An integration of them can work better in medicaleducation.Conclusion: Medical education uses DL to improve the students’ education. DL is a powerful instrument which has become more famous in terms of superb outcomes. Besides, using DL in medical education is likely to continue as a hotly debated area of research and a well-known classroom strategy.

Earthquakes are usually associated with damage. Therefore, any action to predict it is necessary. In data monitoring systems, being real-time and accuracy of data play a key role. In this article, a monitoring system based on the Internet of Things was proposed for the messaging of seismic data. In the first solution, the lightweight protocol Message Queuing Telemetry Transfer (MQTT) was chosen for messaging. In the second solution, redundancy was applied in the sensor layer using the gray wolf algorithm, and in the third solution، redundancy was applied in the controller layer. The simulation results showed that the redundancy in the sensor and controller layer saved energy consumption by more than thirty percent. Also, the average end-to-end delay was significantly reduced in the second and third solutions. Finally، in the first solution, the rate of successful package delivery for different numbers of packages was a constant value of 78.98%. But by applying redundancy in the sensor and controller, the package delivery rate increased to over 92%, which can be the result of increasing the number of sensors and controllers and their proper placement.

BackgroundPresenting ongoing outbreaks and the potential for their spread to nearby neighborhoods and social classes may offer a deeper understanding, enable a more efficient reaction to outbreaks, and enable a comprehensive understanding of intricate details for strategic response planning. Hence, this study explored the spatiotemporal spread of COVID-19 outbreaks and prioritization of the risk areas among social classes in the Kermanshah metropolis.MethodsIn this cross-sectional study, the data of 58.951 COVID-19-infected patients were analyzed. In 2020, out of 24.849 infected patients, 10.423 were females, 14,426 were males, and in 2021, 15.714 were females, and 18,388 were males. To categorize social classes (working, middle, and upper), we utilized economic, social, cultural, and physical indicators. Our analysis utilized Arc/GIS 10.6 software along with statistical tests, including standard distance (SD), mean center (MC), standard deviational ellipse (SDE), and Moran’s I.ResultsThe results revealed that the average epicenter of the disease shifted from the city center in 2020–2021 to the eastern part of the city in 2021. The results related to the SD of the disease showed that more than 70% of the patients were concentrated in this area of the city. The SD of COVID-19 in 2020 compared to 2021 also indicated an increased spread throughout the city. Moran’s I test and the hotspot test results showed the emergence of a clustered pattern of the disease. In the Kermanshah metropolis, 58,951 COVID-19 cases were recorded, with 55.76% males and 44.24% females. Social class distribution showed 28.86% upper class, 55.95% middle class, and 15.19% working class. A higher disease prevalence among both males and females in the upper class compared to others.DiscussionOur study designed a spatiotemporal disease spread model, specifically tailored for a densely populated urban area. This model allows for the observation of how COVID-19 propagates both spatially and temporally, offering a deeper understanding of outbreak dynamics in different neighborhoods and social classes of the city.

Background: Colon carcinoma poses a significant health challenge globally, particularly in developed nations where sedentary lifestyles, poor dietary choices, and genetic factors play a crucial role in its prevalence. Chemotherapy, the primary treatment method, carries severe side effects that can jeopardize patients' lives. Herbal extracts such as Ocimum Basillicum extract have shown effectiveness against cancer cells. Additionally, nanoparticles can significantly enhance drug delivery efficacy in these scenarios. Aim: This article aims to investigate the impact of copper nanoparticles coated with Ocimum Bassilicum at chemoradiotherapy of Colon Carcinoma to hopefully create new treatment options with fewer side effects for patients. Methodology: CuO bio-NPs were produced by the addition of 15 mL of extract dropwise to 80 mL of a 5 mM Cu (OAc)2 aqueous solution, which was then refluxed for 2 h at 100 °C. The mixture gradually became darker brown in color as a result of the heating procedure. The production of CuO NPs and the hydrogen-donating activity of antioxidant phenols within the plant are signaled by surface plasmon resonance excitation, which is the cause of this. In the cell culture, LS174t colon cancer cells were treated with OB extract, CuNPs, and OB-coated CuNPs with and without different radiation levels in order to assess cell viability, through the MTT assay, and the pro-apoptotic BAX and anti-apoptotic BCL2 expressions, through qPCR assay. Results: The results demonstrate a decrease in cell viability and the expression of BCL2 and an increase in the expression of BAX especially when treated with OB-coated CuNPs and even furthermore when paired with radiation therapy. Conclusions: After doing the clinical trial studies, the recent nanoparticles can be used for the treatment of Colorectal carcinoma.

During January-August 2021, the Community Prevalence of SARS-CoV-2 Study used time/location sampling to recruit a cross-sectional, population-based cohort to estimate SARS-CoV-2 seroprevalence and nasal swab sample PCR positivity across 15 [...]

Objective(s): With the spread of COVID-19 pandemic, different countries have implemented various intervention to control the disease. Providing information on how the disease spreads and local risk factors can help policymakers and managers to control the disease. The aim of this study was to analyze the spatial factors of Covid-19 disease in Hamadan province, Iran. Methods: All cases of Covid-19 in Hamadan province from the beginning of the epidemic (Jan 2020) to the end of March 2021 with a confirmed diagnosis of Covid-19 disease based on PCR test were included in the study. The required information was collected through the Covid-19 case registration system in Hamadan University of medical science, other provincial institutions and the Statistics Center of Iran. Statistical analyzes were performed in two parts: descriptive and analytical. Zoning maps were used to show the distribution of disease cases. Getis-Ord G statistic was used in the analytical analysis to analyze the hot spots. Results: A total of 25197 patients suspected of Covid-19 were studied. Of these 10366 were positive based on PCR test. There were 1510 confirmed positive cases of the disease who died during the period of investigation. Population density, employment rate, development index, illiteracy rate, distance from the provincial center, air temperature, number of frosty days, average air humidity showed a significant relationship with the incidence of positive cases of Covid-19 in Hamadan province. Conclusion: Based on the findings, the most important variables related to the increase in the death of covid-19 included the increase in population density and the level of development. The preparation of risk maps using GIS can help to plan a rapid response to the COVID-19 epidemic, focus on prevention programs in high-risk areas, and plan the necessary strategies appropriate to the epidemic trend to control COVID-19 and similar epidemics in the future.

Abstract A type‐2 fuzzy logic‐based adaptive backstepping control (T2FABSC) approach is designed for an H‐bridge inverter. This inverter has an LC filter to decrease the level of total harmonic distortion (THD) that can affect the efficiency of the system. Reduction of THD and stability insurance of the filter are challenging trade‐offs, tackled here by a controller design. The performance, however, is not suitable for actual applications under a wider range of disturbances, and the parameters need to be adjusted once more for more dependable operations. Backstepping control is given a Lyapunov definition‐based adaptive mechanism that can improve this scheme's stability and robustness in the face of numerous disturbances. Additionally, the system is viewed as a “Black box” without the need for a precise mathematical model, which might lead to a lighter computing burden and simpler implementation. Moreover, a fuzzy type‐2 structure is adopted that can optimize the gains of the adaptive Backstepping controller (ABSC) in challenging conditions. The antlion optimization algorithm is employed to optimize the parameters of the membership functions in the fuzzy system, hence improving the performance of the controller. In addition, compared with different optimization algorithms, it can more quickly and accurately locate the best solutions. Finally, the findings of both the simulations and the experimental outputs are examined, proving the T2FABSC's significant robustness and faster dynamics in a variety of challenging circumstances.

The aim of this study was to investigate the effect of academic buoyancy and academic self- handicapping on life satisfaction of second high school students through the mediation of adolescent perception of parenting educational methods by path analysis. The statistical population included students of Arak city who were studying mathematics, experimental and humanities in the Second Period public high schools and were selected by multi-stage cluster sampling method. The number of sample people was considered as 719 students, considering the probability of failure in completing the questionnaires. Data collection tools included Academic Boyancy Questionnaire (Dehghanizadeh & Hossein Chari), Academic Self- handicapping (ASHS) ( Schwinger & Stiensmeier-Pelster), Multidimensional Students’ Life Satisfaction (MSLSS) (Huebner) and Adolescent Perception of Parenting Educational Methods (POPS)( Robbins). The obtained data were analyzed by the structural equation model of latent variable type. In order to verify the model's fit, the values of the ratio of chi-square to degree of freedom, (RMSEA), (CFI), (NFI), (TLI), (IFI) and Cronbach's alpha were reported that indicate appropriate model reliability. Findings showed that buoyancy and academic self- handicapping have a direct and significant effect on life satisfaction and adolescent perception of parenting educational methods. The direct effect of the mediating variable on life satisfaction was also confirmed. By doing this research, by observing educational problems or lack of mental health and identifying the factors affecting it in students, appropriate programs can be implemented to increase life satisfaction in students.