Research has shown a protective association between social support and depression, depression among stroke patients, and health impacts of depression. Yet not much is known on the effect of social support on depression among stroke patients. This review aims to summarize the current research examining the association between social support and depression among stroke patients. A literature search was performed in PubMed to find original peer-reviewed journal articles from 2016 to Mar. 12, 2023 that examined the association between social support and depression among stroke patients. The search terms were depression and "social support" and stroke, which lead to 172 articles. After abstract review, seven observational studies that studied the target association among stroke patients were selected. One additional study was found using PsycINFO as a complementary source with the same search strategy and criteria. Overall, a negative association was found between social support and depression among stroke patients in seven studies, with more social support leading to lower rates of depression post-stroke. One study found that social support was positively related with depression, but the result was nonsignificant. Overall, the results of recent studies suggest that social support is negatively associated with depression among stroke patients. In most studies, this association was statistically significant. The findings suggest the importance of improving social support perceived by stroke patients in the prevention of depression after the occurrence of stroke.

The impact of the accurate estimated time of arrival (ETA) is often overlooked by bus operators. By providing accurate ETA to riders, it gives them the impression of bus services is efficient and reliable and this promotes higher ridership in the long run. This research project aims to predict bus arrival time by using the Support Vector Regression (SVR) model which is based on the same theory as the Support Vector Machine (SVM). Urban City Bus data covering part of the Petaling Jaya area (route name PJ03) is used in this research work. Features related to traffic such as travel duration, a distance of the road, weather and operation at peak or non-peak hour have been used as input in the training of the SVR model. By using kernel trick and specifying optimum parameters, all the features in higher dimensions are efficiently calculated and the SVR model achieves convergence. The model is evaluated with the test set of data split from the original dataset. The experimental result indicates the SVR model displays good prediction ability with its low average error on the prediction result. However, weather data has not been influential to the prediction model as the results of the model trained with and without weather data show a negligible difference.

Mechanical circulatory support has proven effective in managing postcardiotomy cardiogenic shock by stabilizing patients' hemodynamics and ensuring adequate organ perfusion. Among the available device modalities, the combination of extracorporeal life support and a microaxial flow pump for left ventricular unloading has emerged as a valuable tool in the surgical arma-mentarium. In this publication, we provide recommendations for the application and weaning of temporary mechanical circulatory support in cardiogenic shock patients, derived from a con-sensus among leading cardiac centers in German-speaking countrie

The Ranau Earthquake that struck on 5, June 2015 and follow by February 2018 and April 2021, were a new disaster in Sabah and caused many Sabahan to panic. The unpredicted disaster also caused a serious impact on all aspects of life in Sabah. The earthquake has caused severe damage to eight primary schools in the vicinity of the epicenter; although no casualties were reported. However, the disaster has passing deep psychological effects among students. In this study, we examine how the primary school teachers enabled the student to be resilient during and after the disaster. Based on the interviews of 16 primary school students it was revealed that most of the teachers used WhatsApp to support resilience during and after the earthquake. Interviews with 16 primary school teachers revealed there were two main reasons for them to communicate with students namely, delivering emotional aid and monitoring their stress. Based on student interviews, five content categories of emotional support were identified: caring, reassuring, emotion sharing, belonging, and distracting. The main contribution of this study is social media can be used as a spontaneously and proactive tool to support student's resilience during and after the earthquake trauma.

(1) Background: Adolescent well-being is a multifaceted construct embedded in family, school, and peer socialization contexts. By adopting a social-psychological perspective we test the association between three sources of support (parents, teachers, peers) and specific components of subjective well-being (cognitive, affective, global-and-domain-specific) to determine whether there is a functional specialization of the role that these crucial socialization agents play for adolescents to attain well-being in specific life domains. (2) Methods: Cross-sectional Albanian data from Wave 3 of the Children’s Worlds International Survey (www.isciweb.org) were used, including 2,339 adolescents (age range 9-13; girls = 49.3%). A structural equation model (SEM) was employed to explore associations between supportive relationships with parents, teachers, and peers and adolescent well-being. (3) Results: Findings support a functional specialization hypothesis as parental support was significantly related to global cognitive and affective well-being; teacher support was significantly related with school satisfaction; and significant relations were found between peer support and almost all well-being variables (context-free, domain-based life satisfaction and affective subjective well-being). (4) Conclusions: Findings contribute to a more nuanced understanding of the role of supportive relationships with adults and peers in adolescents’ proximal socialization contexts (family, school, peer groups) and specific components of subjective well-being.

One-step oxidative esterification of 2, 5-furandiformaldehyde (DFF) derived from biomass to prepare Dimethyl Furan-2, 5-dicarboxylate (FDMC) not only simplifies the catalytic process and increases purity of product, but also avoids the polymerization of 5-hydroxymethylfurfural (HMF) at high temperature condition. Gold supported on a series of acidic oxide, alkaline oxide and hydrotalcite were prepared by colloidal deposition to explore the effect of support on the catalytic activities. The Au/Mg3Al-HT catalyst exhibited the best catalytic activity in all catalysts, 97.8% selectivity of FDMC at 99.9% conversion of DFF. And this catalyst is suitable to oxidative esterification of benzaldehyde and furfural as well. X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and CO2 temperature programmed desorption (CO2-TPD) were performed to characterize the catalysts. The results indicated that the medium and strong basic sites in the heterogeneous catalysts benefited for the absorption of intermediate spices, further facilitated the oxidative esterification of aldehyde groups. While, neutral or acidic support tended to aldol condensation reaction. It was worth noting that basicity on the support surface reduce electronic state of the Au nanoparticle (Auδ-), thus enhance the catalytic selectivity of oxidative esterification. This finding demonstrated the support plays crucial role in oxidative esterification.

The study of the effect of corporate entrepreneurship(CE) which is a key indicator of success in corporate innovation performance(IP) is a central research topic. However, an empirical study on whether various types of government support(GS) have a moderating effect between these two variables is of new interest. This study empirically analyzed the effects of CE on IP and analyzed the indirect effects of GS on CE and IP based on 4000 Korean manufacturing firms. The results showed that all five factors of CE (innovativeness, risk-taking, proactiveness, autonomy, and competitive aggressiveness) had a positive effect on IP. In addition, the moderating effect of GS on the relationship between CE and IP was validated in seven categories: taxation, subsidies, financial support, human resources, technology, certification, and procurement. The results showed that five types of GS, other than financial support and technical support, strengthened the effect of CE on IP. This study provides a basis for establishing a strategy for strengthening organizational entrepreneurship and for selecting and focusing on various types of GS. It can be concluded that for more effective government support policies, direct government financial support or technical support should be more elaborately implemented.

The period of study in the online environment can be a very demanding trial for students and masters, especially for those who are not familiar with computer technology. This is largely due to a complex of factors that come from the changes to which they are subjected, such as: leaving the parental home and settling into another living environment (living in dormitories or other forms of accommodation) but also settling with an unfamiliar and very different educational environment from what they were familiar with. Along with all the changes occurring in the family and social plan, the students had to adapt to the educational system made exclusively online. Higher educa-tion institutions in Romania use, as a method of knowledge transmission, traditional learning methods, namely they use face-to-face lecture-type courses in a lecture hall or practical and ex-planatory activities in a seminar/laboratory room. The emergence of this pandemic forced higher education institutions to switch to an online teaching mode for all types of activities included in the educational process.

Background Tuberculosis is a type of infectious disease that can cause death if treatment is not completed. the duration of tuberculosis treatment can reach 6 to 8 months so it really requires discipline when doing treatment. This makes tuberculosis patients in dire need of health information and social support which is very helpful in providing motivation, health information, and monitoring treatment from nurses. Aim of this literature review is to provide an overview of the The Role Of Nurses In Providing Social Support In Tuberculosis Treatment: Literature Review. Method is a literature review research, this study uses electronic database searches using keywords according to research questions from the online library PubMed, Content Science, and Science Direct. Result it was found that the role of nurses in the aspect of social support, namely in providing motivation, supervision, comfort, empathy, and information. this is very necessary for patients with tuberculosis at the time of treatment. Conclution social support is needed by tuberculosis patients who are currently undergoing treatment to provide motivation, health information, and as a nurse's supervision of patient adherence to tuberculosis treatment.

The Burnout syndrome is a negative experience for the athlete development and it has been demonstrated that it gets worse when a sport is practiced in an obsessive way. The interventions about a positive vision through the sport could be a protective factor to boost the athlete’s wellbeing. The aim of the present study was to analyze the mediator effect from social support, the relationship between the burnout, positivity and passion in young Mexican athletes. The sample was composed by 452 Mexican athletes, males and females from 12 to 18 years of age (M = 16.29, SD = 1.66). Participants answered the Athlete Burnout Questionnaire, The Scale of the Social Support Perceived by Athletes, the Passion Scale and the Positivity Scale. The results of structural equation modeling showed the model presented a good adjustment (χ2 = 813.507; df = 229; χ2 /df = 3.552; p < 0.01; CFI = 0.93; TLI = 0.91; IFI = 0.93; NFI = 0.91; RMSEA = 0.07). The positivity and harmonious passion presented direct and indirect effects over the burnout, being the perceived social support the mediator variable of the indirect effects. However, the effect of the obsessive passion mediated by the perceived social support did not resulted significant.

Predicting copper price is essential for making decisions that can affect companies and governments dependent on the copper mining industry. Copper prices follow a time series that is non-linear, non-stationary, and which have periods that change as a result of potential growth, cyclical fluctuation and errors. Sometimes the trend and cyclical components together are referred to as a trend-cycle. In order to make predictions, it is necessary to consider the different characteristics of trend-cycle. In this paper, we study a copper price prediction method using Support Vector Regression. This work explores the potential of the Support Vector Regression with external recurrences to make predictions at 5, 10, 15, 20 and 30 days into the future in the copper closing price at the London Metal Exchanges. The best model for each forecast interval is performed using a grid search and balanced cross-validation. In experiments on real data-sets, our results obtained indicate that the parameters (C, ε, γ) of the model Support Vector Regression do not differ between the different prediction intervals. Additionally, the amount of preceding values used to make the estimates does not vary according to the predicted interval. Results show that the support vector regression model has a lower prediction error and is more robust. Our results show that the presented model is able to predict copper price volatilities near reality, being the RMSE equal or less than the 2.2% for prediction periods of 5 and 10 days.

Regional product labeling can help develop regional business activities, especially with traditional regional products. Their general popularity is a significant source of income for the less developed regions. The Gemer-Malohont region belongs to economically underdeveloped areas with high unemployment rate. The subject of the survey was regional food products, which are made by small farmer. The analysis was carried out on a questionnaire survey in the period April-July 2017 in each of the region's districts. The results obtained by questionnaire survey have been statistically processed using the statistical method (two-step cluster analysis, radar chart, box-plots, regression analysis) using Microsoft Excel and IBM SPSS Statistics 23 software. Through cluster analysis and based on the preference of regional food, we divided consumers into two groups - knowledgeable regional food purchasers and priced oriented consumers. We have shown that the more developed regions (Rimavská Sobota, Rožňava) show a higher rate of purchase of regional foods. Less developed regions (Poltár, Revúca) are represented by lower-income consumers for whose the food price is the decisive criterion. Local residents of backward regions should pay attention to domestic food and local small farmers, who are the way to create local capital and local development.

Energy system models have become indispensable to shape future energy systems by providing insights into different trajectories. However, sustainable systems with high shares of renewable energy are characterized by growing cross-sectoral interdependencies and decentralized structures. To capture important properties of increasingly complex energy systems, sophisticated and flexible modelling tools are needed. At the same time open science becomes increasingly important in energy system modelling. This paper presents the Open Energy Modelling Framework (oemof) as a novel approach in energy system modelling, representation and analysis. The framework forms a toolbox to construct comprehensive energy system models and has been published open source under a free license. With a collaborative development based on open processes the framework seeks for a maximum level of participation and transparency to facilitate open science principles in energy system modelling. Based on a generic graph based description of energy systems it is well suited to flexibly model complex cross-sectoral systems and incorporate various modelling approaches. This makes the framework a multi-purpose modelling environment for modelling and analyzing different systems ranging from an urban to a transnational scale.

This research mapped significant social networks of victims of childhood sexual abuse, identifying relationships between childhood trauma and social bonds in adult life. Ten adult women, aged between 20 and 40 years, in psychiatric care for the consequences of trauma suffered in childhood participated in the research. For data collection, the map of significant social networks was used and analyzed through the structure, functions and attributes of the bonds. The network is composed of people from the Friendship, Family, Community, Work/Study and Health Teams group. The networks of friendships, family, co-workers or studies play a predominant role of emotional support, while the Health Teams also offer emotional support, but primarily provide clinical support in overcoming trauma and its consequences. The network of relationships has specific functions that maintain psychosocial integrity and help women to overcome the abuse suffered.

The way in which a person walks, known as human gait, is a significant indicator of overall health and well-being. Abnormalities in gait can indicate the presence of metabolic disorders, such as diabetes or obesity. However, detecting these disorders can be challenging using traditional methods, which often involve subjective assessments or invasive procedures. In this study, a novel methodology known as Criticality Analysis (CA) was proposed for the detection and monitoring of human gait in people with metabolic disorders taking part in an intervention to increase activity and reduce weight. The CA approach utilised inertial measurement unit gait data, alongside clinical health measures. This allows for the control of nonlinear growth in the system, resulting in lower dimensional, nonlinear, free-scale, stable, controlled, and organised trajectories. These trajectories were then analysed using a Support Vector Machine (SVM) algorithm, which is well-suited for this task due to its ability to handle nonlinear and dynamic data. The combination of the CA approach and the SVM algorithm demonstrated high accuracy and non-invasiveness in detecting metabolic disorders, yielding an average accuracy within the range of 78.2% to 90%. Additionally, the classification technique accuracy, at a group level was observed to reduce during period of the intervention (e.g., from week 2 to week 3) alongside changes in fitness and health, which indicates the potential of using the approach to measure and monitor biological systems. As such, this novel methodology has the potential to be a valuable tool for healthcare professionals in detecting and monitoring metabolic disorders, as well as other unknown diseases associated with the human biological system.

Decision makers have to work on resolving multiple forms of problems within their organizations. The problems can be structured, semi-structured, or unstructured. Handling these issues requires intensive time dedication and resource allocation. Looking at the perspective of strategic decision making in Saudi Arabia, current operations are lacking in various sectors. This indulges an immediate need to introduce proper systems and highlight the loopholes that would allow the leaders make informed decisions aided by a support system. For this reason, the researchers set out to work on two research questions. The first question focused on how decision makers ensured accuracy of the decisions they are making. It would allow to identify why such system is important that should also guarantee consistency and accuracy. The second question asked about the proper process that would govern and control the outcome of decision. Considering the above questions, this research aimed at identifying the ideal framework, and whether the proposal developed would fit into the Saudi organizations. A case study in health sector has been reviewed containing various models across the world. Following this, interviews with five decision makers in their organization were conducted to perform the qualitative research. The researcher identified that most organizations lacked systems to ensure their decisions were accurate. The research also concluded that the tools and elements presented in the proposed informed decision framework would fit into most Saudi organizations to eliminate the identified problem, and especially due to the inclusion of the non-digital sources of information as part to the decision process. Furthermore, the analysis was conducted and discussion was determined stating validations of the study.

Background: Our study aimed to assess the differences between domestic and international students in terms of social support, vital exhaustion, and depression during the time of COVID-19. Methods: The online cross-sectional survey was conducted via Google Forms® at three time intervals during the pandemic. Results: Respectively 1320, 246, and 139 students completed our questionnaires in the different time intervals. International students reported significantly lower values of perceived social support. Women reached higher scores regarding vital exhaustion in both samples. Concerning depression, international female students had higher values than their male counterparts but the difference diminished with time. No differences could be found in the comparison of depression between domestic female and male students. Significant correlations were found between depression, perceived social support, and vital exhaustion. Discussion: International students perceive diminished social support just when they need more. Decreased levels of perceived social support may contribute to the development of their psychological problems.

The COVID-19 pandemic in Indonesia makes a significant impact both physically and psychologically. One month after the President of the Republic of Indonesia announced about the COVID-19 patient cases, the Indonesian Child Protection Commission data during April 2020, depicted that 76.7% of children were not happy to participate in distance learning because 81.8% were only given assignments by the teacher and 73.2% felt they had a heavy task and had a short period of time to complete. This reaction is an indicator of the children’s anxiety about distance learning. The anxiety that occurs in these students is assumed to depend on their social support and emotional maturity. When students get optimal family support and are able to control their emotions in the face of a pandemic, they can reduce anxiety in facing online learning. The subjects of this study were 202 junior high and high school students. The results showed that social support and emotional maturity simultaneously affect anxiety in online learning (Freg = 45.066, p = 0.00 <0.01). These results can be used as a basis for providing psycho-education to increase family support and emotional maturity to reduce anxiety in online learning.

The objectives were to identify conditions under which mothers may be willing to use telelactation and explore associations between participant characteristics, willingness, and beliefs regarding telelactation use. Mothers 2-8 weeks postpartum were recruited from two Florida maternal care sites and surveyed to assess demographics, breastfeeding initiation, and potential telelactation use. Analyses included descriptive statistics and logistic regression models. Of the 88 participants, most were white, married, earned less than $50,000 per year, had access to technology, and were willing to use telelactation if it was free (80.7%) or over a secure server (63.6%). Fifty-six percent were willing to use telelactation if it involved feeding the baby without a cover, but only 45.5% were willing if their nipples may be seen. Those with higher odds of willingness to use telelaction under these modesty conditions were experienced using videochat, white, married, and of higher income. Mothers with security concerns had six times the odds of being uncomfortable with telelactation compared to mothers without concerns. While telelactation can improve access to critical services, willingness to use telelactation may depend on conditions of use and sociodemographics. During the COVID-19 pandemic and beyond, these findings offer important insights for lactation professionals implementing virtual consultations.

Space missions have always assumed that the risk of spacecraft malfunction far outweighs the risk of human system failure. This assumption breaks down for longer duration exploration missions and exposes vulnerabilities in space medical system. Space agencies can no longer buy down the majority of human system risk through the crew member selection process and emergency re-supply or evacuation. No mature medical solutions exist to close the risk gap. With recent advances in biotechnology, there is promise in augmenting a space pharmacy with a biologically-based space foundry for on-demand manufacturing of high-value medical products. Here we review the challenges and opportunities of molecular pharming, the production of pharmaceuticals in plants, as the basis of a space medical foundry to close the risk gap in current space medical systems. Plants have long been considered an important life support object in space and can now also be viewed as programmable factories in space. Advances in molecular pharming-based space foundries will have widespread application in promoting simple and accessible pharmaceutical manufacturing on Earth.

Traditionally, overnight fasting before elective surgery has been the routine in medical practice for risk reduction of pulmonary aspiration of gastric contents. Several original study and international societies recommend a 2‐h preoperative fast for clear fluids and a 6‐h fast for solids in most elective patients. We conducted a narrative review of the literature, searching electronic databases (Medline and CINAHL). We used PICO approach. The results of our review suggest that nutrition support in the perioperative period is very important to reduce length of hospital stay and reduced postoperative complication.

In this review, we explore a broad-based view of technologies for supporting human activities on the Moon. Primarily, we assess the state of life support systems technology beginning with physicochemical processes, waste processing, bioregenerative methods, food production systems and the robotics and advanced biological technologies that support the latter. We observe that the Moon possesses in-situ resources but that these resources are of limited value in CELSS – indeed, CELSS technology is most mature in recycling water and oxygen, the two resources that are abundant on the Moon. This places a premium on developing CELSS that recycles other elements that are rarified on the Moon including C and N in particular but also other elements such as P, S and K which might be challenging to extract from local resources. Although we focus on closed loop ecological life support systems, we also consider related technologies that involve the application of biological organisms to bioregenerative medical technologies and bioregenerative approaches to industrial activity on the Moon as potential future developments.

This paper proposes a model that combines multi-criteria and multi-faceted risk assessment. Using two data sources, a fuzzy Technique for Order of Preference by Similarity to Ideal Solution FTOPSIS method combined with FMEA assessment. The FMEA method presented in this paper combines the technique of prioritising preferences according to FTOPSIS similarity to the ideal solution and conviction structure to overcome the defects of traditional FMEA indicators. The paper describes the exact process and tool selection, and the results obtained in the study verified accurate data. Finally, a numerical case study was presented on hospital reorganization services and case adaptation to prioritize surgical abandonment in Poland. The problem considered in the publication is the priority of patients’ operations in hospitals. The selection of relevant criteria, their importance and patient preferences are presented. The results obtained from the method provide a viable action plan for the proposed research problem. The proposed method is multi-faceted and can be part of an information system supporting reorganization, restructuring, and modification of the operational process.

The high demands of caring for and raising a child with autism spectrum disorder on a daily basis fatally lead parents to the appearance of physical and mental fatigue. This study aimed to assess the effect of social support and spirituality on the fatigue of parents with children with autistic spectrum disorder. A cross-sectional study with a convenience sample was conducted in Schools of Special Education in Attica (Greece). The sample consisted of 123 parents who completed The Fatigue Assessment Scale (FAS), the Multidimensional Scale of Perceived Social Support (MSPSS), and the Functional Assessment of Chronic Illness Therapy Spiritual Well-Being Scale (FACIT Sp-12) to measure the levels of fatigue, social support, and spirituality, respectively. Demographic data were, also, recorded. Data analysis was applied using IBM SPSS 21.0. The mean age was 47.3 years old, 81.3% were women, and 38.9% stated much / very much religious. The mean of total FAS was 28.4 (SD±7.5), of total FACIT Sp-12 was 31.5 (SD±8.7), and of total MSPSS 5.1 (SD±1.1). Higher levels of total MSPSS and FACIT Sp-12 were associated with lower total FAS (r= -0.50, p &lt;0.001 and r= -0.49, p&lt;0.001 respectively). Social support and spirituality are significant predictors of fatigue.

This research objective was to develop a promoting vegetable and fruit consumption behaviors program among preschool children based on 4 aspects of House’s social support framework to increase fruit and vegetable consumption in preschool the program. This study was quasi-experimental. The sample consisted of preschool children and their caregivers who were randomly selected based on the inclusion criteria. The experimental and control groups had 96 pairs of preschool-aged children and their caregivers. The experimental group was given the program, while the control group was to resume normal activities. The program development was based on the caring lifestyle of caregivers in Muang District, Nakhon Si Thammarat Province. The tools consisted of a preschool care eating behavior assessment and a caregiver knowledge test about the child's fruit and vegetable intake and how to modify the child's fruit and vegetable intake. In addition, fruit and vegetable eating behaviors in preschoolers and a handbook for nurses and primary caregivers were approved by five experts and deemed suitable for the caregiver support framework. The results of the development indicated that a 10-week program was appropriate and tended to increase preschoolers' consumption of fruits and vegetables. In especially experimental group both caregivers increasingly gained knowledge and behavior of caregivers to promote fruit and vegetable eating behavior and preschool increasing the fruit and vegetable consumption.

The continuous transformations that characterise cities have placed at the centre of the political debate the theme of urban regeneration, as urban, environmental, and social rehabilitation, especially about degraded urban areas that become fertile ground for new urban functions. Considering degraded areas as the result of economic, social, physical, and environmental transition processes, their regeneration must consider an inclusive and multi-actor process involving different stakeholders and users. Such an understanding examines multiple cultural and design approaches to urban regeneration and geographical transformation. This paper implements the Geodesign approach to investigate and develop a Collaborative Decision Support System oriented to the planning and assessing wasted roadscapes regeneration. The wasted roadscapes are conceived as degraded areas located close to roads, which need sustainable strategies with particular attention to local problems related to accessibility and the inclusion of degraded areas in the planning process. Bacoli’s city (South of Italy), has been selected as a best-fit case study for testing the decision-making process elaborated, involving a working group of professors, researchers, PhD candidates, students, local authorities, and citizens. The Geodesign approach facilitated the definition of sustainable planning strategies among people with diverse backgrounds and interests, aiming at recovering degraded landscapes and connecting them to urban accessibility strategies, facing conflicts and supporting the elaboration of a shared vision.

Assistance dogs provide significant benefits to older adult owners. However, despite protective legislation, aged care facilities continue to not allow owners to retain their dog on relocation. The purpose of the current study was to explore whether older adults should be allowed to retain their dog on relocation to an aged care facility, and what factors should impact this decision. Further, if allowed to retain their dog, what would be the best practice to allow for this. A deliberative democracy methodology was used, with a range of key stakeholders recruited. Focus groups were held, with follow up questionnaire to establish deliberation for all questions. Results indicated that with sufficient objective measurement, fair decisions can be made to ensure the welfare and wellbeing for owner and dog. Key policy and procedure changes would also be necessary to ensure ongoing support, such as training, care plans, and emergency directives. By ensuring sufficient policies and procedures are in place, training and support could lead to an ideal outcome where facilities could be at the forefront of a better future for aged care.

Soil working tools, implements, and machines are inevitable in mechanized agriculture. The soil-tool/machine interaction is a multivariate, dynamic, and intricate process. The accurate interpretation, description, and modeling of a soil-machine interaction is key to providing a solution to sustainable crop production by reducing energy input, excessive soil pulverization, and compaction. The traditional method provides insight into soil-machine interaction but often provides inadequate solutions and lacks broad applicability. Computational intelligence (CI) is a comprehensive class of approaches that rely on approximate information to solve complex problems. The CI method has been extensively studied and applied in soil tillage and traction domain in recent decades. The study critically reviews the CI techniques implemented in soil-machine interactions, especially in the context of tillage, traction, and compaction. The traditional methods and their limitation are discussed. The fundamental of CI methods and a detailed overview of the most popular methods are provided. The study reviews and summarizes the 50 selected articles on soil-machine interaction studies where CI methods were employed. It discusses the strength and limitations of employed CI methods. It also suggests the emergent CI methods and future applications are discussed. The outlined study would serve as a concise reference and a quick and systematic way to understand the applicable CI methods that allow crucial farm management decision-making.

The article explores the subject of information and accounting solutions for accounts receivable management that include appropriate accounting solutions and analytical techniques. The study focuses on the statutory framework for accounting for accounts receivable under the Russian Accounting Standards (RAP), International Financial Reporting Standards (IFRS), and the generally accepted accounting principles (GAAP). The analytical techniques are described in the context of the authors' view on the essence of accounts receivable management that implies analysis, the establishment of a credit policy and of a discount policy. The article places emphasis on the use of available information technology for accounts payable management, such as blockchain-based smart contracts.

The purpose of this study was to explore the role of moral distress on physician burnout during COVID-19. Physicians in the US were interviewed between February and March 2021; 479 responded to our survey. Results indicated that moral distress was a key mediator in explaining the relationship between perceived organizational support, medical specialization, emotional labor, and coping on burnout. There was no support for increased burnout among female physicians, and contracting COVID-19 likewise did not play a role in burnout. Our findings suggest that physician burnout can be mitigated by increasing perceived organizational support; likewise, physicians who engaged in deep emotional labor and problem-focused coping tended to fare better when it came to feelings of moral distress and subsequent burnout.

AbstractBackground: the development of nursing, especially related to the nursing intervention approach, is running so fast. This can be seen from the use of peer group support in nursing interventions in individual humans. The purpose of this literature is to find the impact of implementing nursing interventions using a peer group support approach.Method: this literature review method uses JBI and Prisma on 120 articles taken from journal databases, namely Scopus, PubMed and Sciendirect.Result: From the articles analyzed, it was found that the application of peer groups can improve individual abilities both in psychological and behavioral aspects.Conclusion: the application of the peer group approach is able to be one of the approaches in the world of nursing in carrying out nursing actions today.

Background: Malignant pleural mesothelioma (MPM) is an atypical, belligerent tumor that matures into cancer in the pleura, a stratum of tissue bordering the lungs. Pleural mesothelioma is a common type of mesothelioma that accounts for about 75 percent of all mesothelioma diagnosed yearly in the United States. Diagnosis of mesothelioma takes several months and is expensive. Given the difficulty of diagnosing MPM, early identification is crucial for patient survival. Our study implements artificial intelligence and recommends the best fit model for early diagnosis and prognosis of MPM. Method: We retrospectively retrieved patient’s medical reports generated by Dicle University, Turkey and implemented multi-layered perceptron (MLP), voted perceptron (VP), Clojure classifier (CC), kernel logistic regression (KLR), stochastic gradient decent SGD), adaptive boosting (AdaBoost), Hoeffding tree (VFDT), and primal estimated sub-gradient solver for support vector machine (s-Pegasos). We evaluated the models, compared and tested using paired T-test (corrected) at 0.05 significance based on their respective classification accuracy, f-measure, precision, recall, root mean squared error, receivers characteristic curve (ROC), and precision-recall curve (PRC). Results: In phase-1 SGD, AdaBoost.M1, KLR, MLP, VFDT generates optimal results with the highest possible performance measures. In phase-2, AdaBoost with a classification accuracy of 71.29% outperformed all other algorithms. C-reactive protein, platelet count, duration of symptoms, gender, and pleural protein were found to be the most relevant predictors that can prognosticate mesothelioma. Conclusion: This study confirms that data obtained from biopsy and imagining tests are strong predictors of mesothelioma but are associated with high cost, however, can identify mesothelioma with optimal accuracy. Predictive analytics without using biopsy results can diagnose mesothelioma with acceptable accuracy. Implementation of phase-2 followed by phase-1 can address diagnosis expenses and maximize disease prognosis. Additionally, results indicate improved MPM diagnosis using AI methods dependent upon the specific application.

Identifying human actions in complex scenes is widely considered as a challenging research problem due to the unpredictable behaviors and variation of appearances and postures. For extracting variations in motion and postures, trajectories provide meaningful way. However, simple trajectories are normally represented by vector of spatial coordinates. In order to identify human actions, we must exploit structural relationship between different trajectories. In this paper, we propose a method that divides the video into N number of segments and then for each segment we extract trajectories. We then compute trajectory descriptor for each segment which capture the structural relationship among different trajectories in the video segment. For trajectory descriptor, we project all extracted trajectories on the canvas. This will result in texture image which can store the relative motion and structural relationship among the trajectories. We then train Convolution Neural Network (CNN) to capture and learn the representation from dense trajectories. . Experimental results shows that our proposed method out performs state of the art methods by 90.01% on benchmark data set.

3D plotting is an additive manufacturing technology enabling biofabrication, thus the integration of cells or biologically sensitive proteins or growth factors into the manufacturing process. However, most (bio-)inks developed for 3D plotting were not shown to be processed into clinical relevant geometries comprising critical overhangs and cavities, which would collapse without a sufficient support material. Herein, we have developed a support hydrogel ink based on methylcellulose (mc), which is able to act as support as long as the co-plotted main structure is not stable. Therefore, 6 w/v %, 8 w/v % and 10 w/v % mc were allowed to swell in water, resulting in viscous inks, which were characterized for their rheological and extrusion properties. The successful usage of 10 w/v % mc as support ink was proven by multichannel plotting of the support together with a plottable calcium phosphate cement (CPC) acting as main structure. CPC scaffolds displaying critical overhangs or a large central cavity could be plotted accurately with the newly developed mc support ink. The dissolution properties of mc allowed complete removal of the gel without residuals, once CPC setting was finished. Finally, we fabricated a scaphoid bone model by computed tomography data acquisition and co-extrusion of CPC and the mc support hydrogel.

Aquaculture is growing ever more important due to the decrease in natural marine resources and increase inworldwide demand. To avoid losses due to aging and abnormalweather, it is important to predict seawater temperature in order to maintain a more stable supply, particularly for high value added products, such as pearls and scallops. The increase in species extinction is a prominent societal issue. Furthermore, in order to maintain a stable quality of farmed fishery, water temperature should be measured daily and farming methods altered according to seasonal stresses. In this paper, we propose an algorithm to estimate seawater temperature in marine aquaculture by combining seawater temperature data and actual weather data.

The research fills the policy research gap for the women entrepreneurship and sustainability performance for examining key successful factors. Previous women entrepreneurship research fails to offer policy recommendations. The research purpose is to investigate these factors affect women entrepreneurship capabilities and sustainability performance by using SEM analysis and making policy recommendation. This research employs online and mail survey and obtains 175 women entrepreneur sample. The study finds that family support and motivation have positive effect on women entrepreneurship capabilities and sustainability performance. Barriers have no effect on performance. Hopefully, the research can provide the guidance to contribute to women’s entrepreneurship opportunities for achieving SDGs. Policy recommendation and managerial implication are discussed in the article.

The complex and interconnected challenges of climate change, water stress, disasters, and health crises have far-reaching implications for sustainable development and global sustainability agendas, such as the Sustainable Development Goals (SDGs). However, one critical issue that has been overlooked is the nexus between climate change impacts and mental health (CCMH). Recognizing and addressing the negative emotions associated with this global phenomenon is essential to fostering a holistic approach to climate action planning and building long-term resilience. In this assessment, we present a set of narratives to argue that CCMH research requires a collaborative, transdisciplinary approach that integrates socio-economic and socio-cultural complexities. For this assessment, we used a case study approach to elucidate that the mental health impacts of climate change are unequally distributed, disproportionately affecting vulnerable groups based on age, gender, race, and socioeconomic status. The assessment presented in this study concluded that adequate mental health support programs are limited due to sociocultural stigmas and limited socioeconomic resources in some regions. Existing climate-related mental health services mechanisms lack coordination and specific action plans, leaving affected populations underserved. Unlike traditional understandings of the climate-health nexus, this research calls for experts from multiple fields to work together and for enhanced attention to and investment in CCMH research to bridge the gap between scientific knowledge and practical solutions. Such solutions will lead to scalable and lasting change as communities can implement research findings to support those in need and enhance disaster resilience. Furthermore, by collectively recognizing the climate and mental health nexus, global commitments such as the SDGs and the Paris Declaration can advance awareness and action in climate-related mental health, ultimately promoting a healthier relationship between humanity and nature.

Pregnant women have been considered a high-risk group for SARS-CoV-2 infection; the impact of the disease on the health of a mother and her child is still being studied. The emotional impact of the pandemic on pregnant women has been extensively studied. Emotional distress is proposed as a perspective to explain the emotional manifestations of women during this stage as something common rather than pathological. The objective of this study was to know the emotional experience of women who tested positive for SARS-CoV-2 towards the end of their pregnancy, during the first and second waves of COVID in Mexico. A qualitative study was carried out: 18 pregnant women with COVID were interviewed. A thematic analysis of the data was performed, resulting in three main themes and 14 subthemes. The COVID-infected mothers-to-be experienced mild to moderate emotional distress. It was more intense for those with comorbidities. This distress was aggravated during obstetrical complications and comorbidities, as well as during COVID and postpartum. The emotional distress was appeased by both the perception of medical care and social support. The emotional distress of pregnant women with COVID requires emotional accompaniment to reduce its impact.

Increasing the loading density of nanoparticles on carbon support is essential for making Pt-alloy/C catalysts practical in H2-air fuel cells. The challenge lies in increasing the load-ing while suppressing the sintering of Pt-alloy nanoparticles. This work presents a 40% Pt-weighted sub-3 nm PtCo/C alloy catalysts via a simple incipient wetness impregnation method. By carefully optimizing the synthetic conditions such as Pt/Co ratios, calcination temperature and time, the size of supported PtCo alloy nanoparticles is successfully con-trolled below 3 nm, and a high electrochemical surface area achieves of 94 m2/g is achieved, which is 2.8 times of commercial PtCo/C-TKK catalysts. Demonstrated by elec-trochemical oxygen reduction reaction, PtCo/C alloy catalysts present an enhanced mass activity of 0.45 A/mg at 0.9 V vs. RHE, which is 1.7 times that of PtCo/C-TKK catalyst. Therefore, the developed PtCo/C alloy catalyst can potentially be a highly practical cata-lyst for H2-air fuel cells.

Prosocial behavior is vital for positive social development among adolescents, contributing to improved peer relationships, emotional well-being, and social competence. Gratitude, a positive emotion arising from recognizing and appreciating benefits received from others, has been identified as a potential contributor to adolescent prosocial behavior. This study aimed to investigate the mediating roles of social support and basic psychological needs in the relationship between gratitude and prosocial behavior among adolescents. A total of 390 middle school students participated in a longitudinal study, completing questionnaires assessing gratitude, social support, basic psychological needs, and prosocial behavior at two time points with a six-month interval. The results indicated that gratitude positively correlated with social support, basic psychological needs, and prosocial behavior. Structural equation modeling revealed that social support and basic psychological needs partially mediated the relationship between gratitude and adolescent prosocial behavior. Moreover, a chain-like mediation effect was observed, wherein social support influenced basic psychological needs, which in turn predicted prosocial behavior. These findings emphasize the importance of gratitude in fostering prosocial behavior among adolescents and highlight the mediating roles of social support and basic psychological needs in this relationship.

Background: The diagnosis of phenylketonuria (PKU) in an infant is a devastating and overwhelming event for their parents. Providing appropriate information and support is paramount, especially at the beginning of a child’s life. Investigating if parents are receiving the right support is important for their continued care. Methodology: An online survey was distributed to explore parents’ perceptions of current support and information provided by their healthcare provider and to rate sources of other support (n=169 participants). Results: Dietitians received the highest (85%) rate of “very helpful” support. Overall, parents found Facebook to be helpful for support, but had mixed reactions when asked if healthcare professionals (HCPs) should provide advice as part of the groups. When rating the most effective learning methods, the top three were: 1:1 sessions (n=109, 70%), picture books (n=73, 50%) and written handouts (n=70, 46%). Conclusion: Most parents were happy with the support and information they received from their dietitian, but required more support from other HCPs. Facebook groups provide parents with the social support that HCPs and their family may be unable to offer, suggesting a place for social media in future PKU care.

Background Globally the average age of the worlds’ population of older persons continues to upsurge and social support becomes increasingly relevant. Overall, in Malaysia, social support and networking prevalence was found to be lower among older persons at 30.76%. In view of the scarce data on social support and its association with smoking status and its associated factors among the older Malaysian population this study was conducted. Methods Data from the National Health and Morbidity (NHMS) 2018 survey on health of older Malaysian adults was analyzed. This was a cross sectional population-based study using a two-stage stratified random sampling design. Elderly population aged 60 years and above was selected. Data were collected were sociodemographic characteristics, smoking status, and social support. A validated Malay language, interviewer-administered questionnaire of 11-item Duke Social Support Index was applied for assessing social support among the elderly. A complex sampling design analysis was used for the descriptive statistics. The associated risk factors for social support were identified using Multiple Logistic Regression analysis. Results A total of 3923 elderly respondents participated in the study. The prevalence of good social support was significantly higher among the 60-69 years old respondents compared to the > 80 years old (73.1%, 95% CI :69.3% -76.5% vs 50.1 %, 95% CI:41.7 %- 58.6%).Multivariate logistic regression analysis showed that the odds of poor social support were 1.7 times (aOR: 1.72 % ,95%CI: 1.19 -2.48) higher for the respondents aged > 80 years old, than those aged 60-69 years. Respondents with no formal education were 1.93 higher odds of poor social support than the respondents with tertiary education (aOR: 1.93%, 95%CI: 1.13,3.30). Respondents with income < RM 1000 were 1.94 times more likely to have poor social support compared to respondents with income > RM 3000 (aOR: 1.94, 95% CI : 1.21 -3.13). Former smokers have good social support compared to current smokers (73.6% ,95% CI: 67.7-78.7 vs 65.1 %, 95%CI:58.4 -71.2). For current smokers, the odds of poor social support were 42.0% higher than for non-smokers (aOR: 1.42, 95% CI: 1.05 -1.91. Conclusion There is poor social support among the older persons who are current smokers, advancing age, no formal education and low income However, further longitudinal studies are needed to determine the exact effects of the studied variables. These findings could assist the policymakers to develop strategies at the national level to enhance social support among the older smokers to ensure cessation of smoking.

Children under two years old are at risk for anemia because young children have an increased need for iron for their physical growth and brain development. The purpose of this study was designed to evaluate the effects of a caregiver potential support program on anemia prevention in children six months to two years old attending the subdistrict health-promoting hospital in Thasala District, Nakhon Si Thammarat Province. This study was quasi-experimental. The sample included children aged six months to two years old and their caregivers, who were selected by random sampling and allocated to either the experimental or control group, with 40 pairs per group. The experimental group received a potential support program, while the control group received regular care. Both groups were followed for 12 weeks. The instruments used were the potential caregiver assessment, children’s anemia assessment, and a program to support the potential of primary caregivers. Descriptive statistics, chi-square, and t-tests were used to analyze the data. The results revealed that 11.4% of the children had anemia, and a hematocrit count of less than 33% (range = 30-40, M = 34.89, SD = 1.97). The mean scores of knowledge about anemia and iron supplementation after using the program in the experimental group and control group were significantly different (p < 0.001). The mean scores of knowledge about anemia in the experimental and control group were 15.75, SD = 0.54, and 13.28, SD = 1.43 respectively. The mean scores of knowledge about iron supplementation in the experimental and control group were 10.75, SD = 0.49, and 8.15, SD = 1.54 respectively. It was found that the experimental group had a higher mean score on food care behaviors than the control group for 6-11 months and 1-2 years, with statistical significance. The experimental group also had a higher mean score of care behaviors concerning children’s consumption of medicine than the control group (M = 58.20, SD = 4.05; M = 45.78, SD = 9.66, respectively), (p < 0.001). The mean score of the hematocrit level for the experimental group was found to be higher than the control group after receiving the program (M = 35.80, SD = 1.55; M = 34.83, SD = 2.14, respectively), (p < 0.05). Therefore, healthcare providers should support caregivers' capacity to provide continued care for children to prevent anemia.

Intracranial hemorrhage is a serious medical problem that requires rapid and often intensive medical care. Identifying the location and type of any hemorrhage present is a critical step in the treatment of the patient. Diagnosis requires an urgent procedure, and the detection of hemorrhage is a difficult and time-consuming process for human experts. In this paper, we propose methods based on EfficientDet’s deep-learning technology that can be applied to the diagnosis of hemorrhages and thus become a decision-support system. Our proposal is two-fold. On the one hand, the proposed technique classifies slices of computed tomography scans for the presence hemorrhage or its lack, achieving 92.7% accuracy and 0.978 ROC-AUC. On the other hand, our methodology provides visual explanations of the classification chosen using the Grad-CAM methodology.

Catalyst with high catalytic activity and good stability are desirable in the electrocatalytic oxidation of glucose. Herein, Pt concave nanocubes with high-index facets (HIFs) supported by carbon black (Pt CNC/CB) are prepared through a hydrothermal method. The experimental results demonstrate that the peak current densities in different potential regions on the Pt CNC/CB anode are 0.22, 0.20, and 0.60 mA cm−2, respectively. The glucose oxidation reaction shows superior performances in basic and neutral conditions than in acid conditions. Better stability is achieved by Pt CNC/CB than Pt concave nanocubes (Pt CNCs). Abundant surface defects with low-coordinated atom numbers, such as the steps, kinks, and edges, are served as active sites in the electrocatalytic oxidation of glucose. With the addition of carbon black, the catalytic activity can be improved by facilitating the full exposure of the active surface defects on the HIFs of Pt CNCs. Moreover, to address the aggregation of Pt CNCs, caused by the high surface energy of HIFs, the introduction of carbon material is an effective way to preserve the HIFs, and thus enhance the stability of the catalyst. Hence, the prepared Pt CNC/CB electrocatalyst has great potential to be applied in the electrooxidation of glucose.

Background: Some developing countries, such as China, population is aging rapidly, meanwhile, the average years of schooling for residents is constantly increasing. However, the question of whether adult children’s education has an effect on the longevity of older parents, remains inadequately studied. Methods: This paper uses China Health and Retirement Longitudinal Survey (CHARLS) data to estimate the causal impact of adult children's education on their parents' longevity. Identification is achieved by using the truncated regression model and using historical education data as instrument variables for adult children’s education. Results: For every unit increase in adult children’s education, the father’s and mother’s longevity increased by 0.89 years and 0.75 years, respectively. Mechanism analysis shows that adult children's education has a significant positive impact on parents' emotional support, financial support and self-reported health. Further evidence shows that for every unit increase in adult children’s education, the father-in-law’s and mother-in-law’s longevity increased by 0.40 years and 0.46 years, respectively. Conclusions: It is conclusion that improving the level of adult children’s education can increase parents’ and parents-in-law’s longevity. Adult children’s education might contribute to the longevity of older parents by three channels that providing emotional, economic support and affecting parents’ health.

The introduction of social commerce ushered in a new era in business-consumer interaction. As a result, more power has passed from the vendor to the buyer, primarily fueling e-commerce acceptance. As a result, understanding consumer behaviour in the context of social commerce adoption has become essential for businesses looking to persuade customers by using the power of social ties and support.Furthermore, such social ties will facilitate trust as the most promising benefit while reducing perceived risk, which has always been a critical problem with online commerce. This study proposes a paradigm for understanding the impact of social commerce on the stages of the consumer decision-making process: need recognition, information search, alternative evaluation, purchase decision, and post-purchase behaviour, with a focus on social support. In this respect, relevant literature in the subject of social commerce either (1) lacks an adequate explanatory model, (2) has a solid theoretical base, or (3) contains practically complex theories with insufficient empirical data. The research model applies the Social Commerce Constructs (SCC): recommendations and referrals, forums and communities, and ratings and reviews to study the respective influence on the consumer decision-making process phases. This paper aims to understand the influence of social commerce on an integrative model that incorporates all customer choice phases while expecting new knowledge. Furthermore, it is advised that this conceptual model be empirically verified to evaluate the practical consequences.

During operation, the support bracket is the main part to withstand the axial loads of the pumped storage unit. Moreover, the effects of axial loads including the hydraulic thrust of runner flow and the weight of runner body may cause the support bracket deformation and fatigue damage. For the safe and stable operation, the simulation of the axial force and the structural analysis of the support bracket of a pumped storage unit was carried out in this paper. The CFD simulation result has revealed the variation rule of the axial force in different operating conditions. Using ANSYS Mechanical, the static stresses and deformation of support bracket with axial loads were calculated. The results release the location and variations of maximum stress and maximum deformation caused by the axial loads. By comparing the predicted maximum axial force with the admission force calculated by the structural analysis, it is found that the axial force of the researched machine is within the safe range. This study provides the reference for the safety and stable operation of the pumped storage unit.

Possible alterations of maternal immune function due to psychological stress may reflect immunoactive factor levels in breast milk. This study aimed to assess the association between maternal distress and breast milk levels of secretory IgA (SIgA), IgM, IgG, and lactoferrin (LF). We hypothesized this association is moderated by maternal social support achieved from others during lactation. The study group included 103 lactating mothers and their healthy 5-months-old infants. Maternal distress was determined based on the State Anxiety Inventory and the level of salivary cortisol. Social support was assessed using Berlin Social Support Scales. Breast milk samples were collected to test for SIgA, IgM, IgG, and LF using the ELISA method. Milk immunoactive factors were regressed against maternal anxiety, social support, salivary cortisol, and infant gestational age using the general regression model. Maternal anxiety was negatively associated with milk levels of LF (β=-0.22, p<0.05) and SIgA (β=-0.29, p<0.01), while social support was positively associated with milk IgG (β=0.25, p<0.05). Neither anxiety nor social support was related to milk IgM. No association was found between the level of maternal salivary cortisol and immunoactive factors in milk. Our results suggest that maternal psychological well-being and social support may affect milk immune properties.

Background: Breast cancer is the second type of cancer diagnosed in women and is the first cancer in women worldwide. Breast cancer also causes high morbidity and mortality in women and becomes a heavy burden due to the incidence of disability due to the disease. Purpose: This literature review aims to examine how social support affects anxiety, depression and quality of life in breast cancer sufferers. Method: The data were obtained by searching for reputable and trustworthy journals. have high quality criteria, namely Scopus, Proquest, Science Direct, Elsevier, Pubmed. Journals or articles used in this review literature are searched using keywords and Boolean operators (AND, OR NOT, or AND NOT). Keywords in this review literature are as follows: social support OR family support, quality of life OR Quality, anxiety OR depression, AND Cancer OR cancer treatment OR Chronic disease. Results: The results of this literature review show that there is a significant influence between the social support received by breast cancer patients on the improvement of their quality of life. The social support provided is also able to reduce anxiety and depression in breast cancer sufferersConclusion: Social support given to breast cancer patients is proven to have an effect on improving the quality of life, reducing anxiety and depression.

The systems ESTE are running in nuclear crisis centers at various levels of emergency preparedness and response in Slovakia, the Czech Republic, Austria, Bulgaria, and Iran (at NPP monitored by International Atomic Energy Agency, IAEA). ESTE is a decision support system, running 24/7, and serves the crisis staff to propose actions to protect inhabitants against radiation in case of a nuclear accident. ESTE is also applicable as decision support system in case of a malicious act with radioactive dispersal device in an urban or industrial environment. Dispersion models implemented in ESTE are Lagrangean particle model (LPM) and Puff trajectory model (PTM). Described are models approaches as implemented in ESTE. PTM is applied in ESTE for the dispersion calculation near the point of release, up to 100 km from the point of nuclear accident. LPM for general atmospheric transport is applied for short-range, meso-scale and large-scale dispersion, up to dispersion on the global scale. Additionally, a specific micro-scale implementation of LPM is applied for urban scale dispersion modelling too. Dispersion models of ESTE are joined with radiological consequences models to calculate a complete spectrum of radiological parameters - effective doses, committed doses and dose rates by various irradiation pathways and by various radionuclides. Finally, radiation protective measures, like sheltering, iodine prophylaxis, or evacuation, evaluated on the base of predicted radiological impacts are proposed. Dispersion and radiological models of the state-of-the-art ESTE systems are described. Results of specific analyses, like number of particles applied, initial spatial distribution of the source, height of the bottom reference layer, are presented and discussed.

The color and NIR spectrum are key to build an oil estimation model, thus it requires individual olives clustering before the Sohlext oil extraction method can be applied. The objective was to analyze an OC estimation model of individual olives, based on cluster of similar color and NIR spectrum in different combination of the first and/or the second season. This study was performed with Chilean Arbequina olives in 2016 and 2017. The descriptor of the cluster consisted of the 3 color channels of c1, c2, c3 color model plus 11 reflectance points between 1710 and 1735 nm of each olive, normalized with the Z-score index. Clusters of similar color and NIR spectrum were formed with the k-means++ algorithm, leaving a sufficient amount of olives to be able to perform the Sohlext analysis of OC, as reference value. The estimation models were based on the Support Vector Machine. The test was carried out with the Leave One-Out Cross Validation in different training-testing combinations. The best model predicted the OC with 6% and 13%deviation respect to the real value in one season by itself and when one season tested with another season, respectively. The use of clustering in estimation model is discussed.

(1) To analyse the potential association between school social support CECSCE and school social climate CASSS and experiences of dating violence among adolescents in Europe; (2) Cross-sectional design. We recruited 1,555 participants age 13-16 from secondary schools in Spain, Italy, Romania, Portugal, Poland and UK. The analysis in this text concerns student with dating experience (n=993) (57.2% of girls and 66.5% of boys). The association of the exposure to physical and/ or sexual dating violence, control dating violence and fear was measured by calculating the prevalence ratios (PR) and their 95% confidence intervals (CI), estimated by Poisson regression models with robust variance. All the models were adjusted by country and by sociodemografic variables; (3) The results show that the average values of all types of social support are significantly lower in young people who have suffered any type of dating violence or were scared of their partner. The likelihood of suffering physical and/or sexual dating violence decreased when CECSCE increased [PR (CI95%): 0.96 (0.92; 0.99)]. In the same way, the likelihood of fear decreased when CASSS classmates increased [PR (CI95%): 0.98 (0.96; 0.99)]; (4) There is an association between school social support and school social climate and experiences of dating violence among adolescents in Europe. Our results suggest that in the prevention of dating violence, building a supportive climate at schools and building / using the support of peers and teachers should be important.

Neuromuscular disorders cause progressive muscular weakness, which limits upper extremity mobility and performance during activities of daily life. A dynamic arm support can improve mobility and quality of life. However, their use is often discontinued over time for unclear reasons. This study aimed to evaluate whether users of dynamic arm supports demonstrate and perceive quantifiable mobility benefits over a period of two months. Nine users of dynamic arm supports were included in this observational study. They had different neuromuscular disorders and collectively used four different arm supports. They were observed for three consecutive weeks during which they were equipped with a multi-sensor network of accelerometers to assess the actual use of the arm support and they were asked to provide self-reports on the perceived benefits of the devices. Benefits were experienced mainly during anti-gravity activities and the measured use did not change over time. The self-reports provided contextual information in domains such as participation to social life, in addition to the sensor system. However self-reports overestimated the actual use by up to three-fold compared to the accelerometer measures. A combination of objective and subjective methods is recommended for meaningful and quantifiable mobility benefits during activities of daily life.

This current research follows up on Greenleaf’s oft-quoted best test of servant leadership that calls for employees to be better off financially, emotionally, physically, psychologically, etc. because of the time spent with the servant leader. While oft-quoted, little empirical work exists to see if this is true. In this study, 170 participants provided their perception of their supervisors’ level of servant leadership, their perception of the organization’s support, and their self-report of their general well-being. Gender and age bracket information described the participants, and there were no significant differences between gender or age brackets for participants’ perception of their supervisors’ servant leadership. The analysis showed that there was a moderate positive correlation between servant leadership, perceived organizational support, and general well-being. A modification of an existing general well-being instrument provided a new eight-item general well-being scale with a Cronbach’s alpha of 0.956.

Machine learning (ML) methodologies have been looked upon recently as a potential candidate for mitigating nonlinearity issues in optical communications. In this paper, we experimentally demonstrate a 40-Gb/s 256-quadrature amplitude modulation (QAM) signal-based Radio over Fiber (RoF) system for 50 km of standard single mode fiber length which utilizes support vector machine (SVM) decision method to indicate an effective nonlinearity mitigation. The influence of different impairments in the system is evaluated that includes the influences of Mach-Zehnder Modulator nonlinearities, in-phase and quadrature phase skew of the modulator. By utilizing SVM, the results demonstrated in terms of bit error rate and eye linearity suggest that impairments are significantly reduced and licit input signal power span of 5dBs is enlarged to 15 dBs.

Small business sector around the world is regarded as a catalyst of employment for the largest number of people. To reduce massive unemployment and inequality in the country, the Government of South Africa introduced various initiatives to stimulate and support small businesses, the Expanded Public Works Programme (EPWP) is one of such initiatives. The enterprise development approach, is one of the delivery mechanisms of the EPWP, which seeks to transfer income to poor households in the short to medium-term. This study critically assess the impact and effectiveness of training and support interventions provided to small businesses through the EPWP. The study employs a quantitative research method and due to the size, availability and ease of access to the participants, the entire population of twenty (20) small businesses supported by the EPWP in Pretoria Region was sampled. A questionnaire-based survey was conducted. The study demonstrates that the training intervention provided through the EPWP is making positive impact and achieving its intended goals of enhancing business management skills to participants. It also reveals an interesting outcome that the majority of the participants are women. The study also identified some weaknesses in the programme which leads to the recommendation that long-term support mechanisms are essential to ensure sustainability of emerging enterprises.

Manufacturing organizations shall recognize sustainability as a business occasion to capitalize on, rather than an undesirable pressing situation. Still, empirical evidence shows that this opportunity is hard to capture and communicate in global strategic decisions, through planning by tactical management, to daily operational activities. This paper systematically reviews the modeling challenges at the crossroad of value and sustainability decisions making, spotlighting methods and tools proposed in literature to link sustainability to customer value creation at strategic, tactical and operational level. While statistical results show that the topic of sustainability and value modeling is trending in literature, findings from content analysis reveal that recent attempts to promote a value-based view in the sustainability discussion remain at a strategic level, with most of the proposed indicators being suited for managerial decision-making. The lack of support at operational level points to the opportunity of cross-pollinating sustainability research with value-centered methodologies originating from the aerospace sector. The Value Driven Design framework is proposed as main hub from which to derive models supporting engineers and technology developers in the identification of win-win-win situations, where sustainable improvements are aligned with business advantages.

Government support plays an important role in Chinese economy. New energy industries, concerning innovation-driven source and environmental protection, are also supported by government. This paper aims to study the effects of the traditional government support at supply side on firms’ innovation and development. In this paper, we propose enterprise behavior model including characteristics of new energy industries, and study the innovation reaction of firms to government support in different situation. We further use propensity score matching to verify the results in theoretical model, and conduct robustness analysis. Our main conclusions include: (1) In the normal years government support can only promote the innovation output of firms which have innovated, however, can not promote the innovation probability of firms which have not innovated. That is to say, government support can only enhance the intensive margin of innovation, but can not enhance the extensive margin of innovation with less competition. (2) In the situation of bad economic environment and intense competition, firms’ innovation probability rises as the government support increase. Therefore, government should provide more R&D special subsidies and implement strict financial supervision to make the effectiveness of support policies especially in the normal years.

This study examines the potential of combining decision support approaches to identify optimal bundles of ecosystem services. A forested landscape, Zona de Intervenção Florestal of Paiva and Entre-Douro and Sousa (Portugal), is used to test and demonstrate this potential. The landscape extends over 14,000 ha, representing 1,976 stands. The property is fragmented into 376 holdings. The overall analysis was performed in three steps. First, we selected six alternative solutions (A to F) in a Pareto frontier generated by a multiple criteria method within a decision support system (SADfLOR) for subsequent analysis. Next, an aspatial strategic multi-criteria decision analysis (MCDA) analysis was performed with the Criterium DecisionPlus (CDP) component of another decision support system (EMDS) to assess the aggregate performance of solutions A to F for the entire forested landscape with respect to their utility for delivery of ecosystem services. For the CDP analysis, SADfLOR data inputs were grouped into two sets of primary criteria: Wood Harvested and Other Ecosystem Services. Finally, a spatial logic-based assessment of solutions A to F for individual stands of the study area was performed with the NetWeaver component of EMDS. The NetWeaver model was structurally and computationally equivalent to the CDP model, but the key NetWeaver metric is a measure of the strength of evidence that solutions for specific land stands were optimal for the unit. Solutions D and B performed best in the aspatial strategic MCDA analysis, and a composite of the maps generated by NetWeaver demonstrated the spatial basis for the performance of solutions D and B in individual land stands. We conclude with a discussion of how the combination of decision support approaches encapsulated in the two systems could be further automated.

The well-being in the people is a key aspect of the field of psychology. Hence, it is important to an-alyse the variables that are related to life satisfaction and happiness as perceived by individuals and that, therefore, increase their overall well-being. The main objective of this study was to ana-lyse the predictive capacity of emotional intelligence and perceived social support on both the level of life satisfaction and perceived happiness. A total of 380 psychology students completed the Trait Meta Mood Scale, the Multidimensional Scale of Perceived Social Support, the Satisfaction With Life Scale, and the Subjective Happiness Scale. The results show that both emotional intelligence and social support are related to and predictive of subjective happiness and life satisfaction. The importance of developing the components of emotional intelligence and promoting an adequate social network in young people is highlighted.

Cardiovascular diseases (CVD) are chronic diseases associated with a high risk of mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions, such as appro- priate counseling and medication, which can effectively manage the condition and improve patient outcomes. Preventive measures should be implemented at the general public level, promoting a healthy lifestyle, and at the individual level, that is, in people with moderate to high risk of CVD or patients already diagnosed with CVD by addressing an unhealthy lifestyle. Personalized early diagnostic systems based on artificial intelligence (AI), ontologies, and other medical information processing systems may prove to be a great preventive measure. In this paper, we focus on the use of ontology-inspired database models in the diagnosis of cardiovascular disease, as well as their potential for use in web application development.

While persons with schizophrenia find steady employment difficult to sustain, many of the women take on the most difficult task of all – motherhood. The aim of this paper is to review the challenges of motherhood in this population and the treatment strategies needed to keep mothers and children safe, protecting health and fostering growth. This is a narrative review reflecting the author’s life experience and a non-systematic search of the recent literature. Topics added are the stigma against motherhood in the context of schizophrenia, mothers’ painful choices, issues of contraception, abortion, and child custody, fostering and kin placement of children, the effects of antipsychotics, specific perinatal delusional syndromes, and parental supports. Recommendations are to work collaboratively with mothers who struggle with serious mental illness, take note of their strengths as well as their failings, offer a wide array of family services, monitor closely for safety, and appreciate the challenges these women daily face.

This study uses explainable artificial intelligence to analyze major predictors of poor self-rated health, dementia and their comorbidity, which include various aspects of social support. Data came from the Korean Longitudinal Study of Ageing (2016-2018), with 5527 participants aged 56 or more. The dependent variables were: (1) poor self-rated health (SRH) with 5 categories (very good, good, middle, poor, very poor); (2) dementia (no, yes); and (3) their comorbidity with 4 categories (SRH very good, good or middle, dementia no; SRH very good, good or middle, dementia yes; SRH poor or very poor, dementia no; SRH poor or very poor, dementia yes). The 49 demographic, socioeconomic and health-related predictors were included. The accuracy and area under the receiver operating characteristic curve (AUC) were compared for logistic regression and the random forest. Logistic regression and the random forest registered similar AUCs with the range of 0.80-0.87. Based on random forest variable importance, 18 out of top-20 predictors were identical for SRH, dementia and their comorbidity: previous SRH, life satisfaction - health, age, body mass index, income, chronic diseases, life satisfaction - economic, life satisfaction - overall, grandchildren alive, friendship meeting, brothers/sisters alive, class identity, children alive, social activity - friendship, education, children in weekly contact, religion and drinker. However, some variations were found among the three dependent variables, i.e., previous SRH for comorbidity (1st) and SRH (1st) compared to dementia (11th), grandchildren alive for SRH (6th) and dementia (4th) compared to comorbidity (9th), chronic diseases for comorbidity (6th) compared to SRH (10th) and dementia (10th). In terms of Shapley Additive Explanation (SHAP) values, the probability of dementia is expected to decrease by 5.57% in case a predictor grandchildren alive is included to the model. This study highlights the importance of social support for the prediction of poor self-rated health, dementia and their comorbidity. Specifically, the promotion of family support and friendship activity for elders would be vital for the prevention and management of their self-rated health and dementia.

Advanced heart failure (AHF) presents a complex landscape with challenges spanning diagnosis, management, and patient outcomes. In response, the integration of multimodality imaging techniques has emerged as a pivotal approach. This comprehensive review delves into the profound significance of these imaging strategies within AHF scenarios. Multimodality imaging, encompassing echocardiography, cardiac magnetic resonance imaging (CMR), and cardiac computed tomography (CCT), stands as a cornerstone in the care of patients with both short- and long-term mechanical support devices. These techniques facilitate precise device selection, placement, and vigilant monitoring, ensuring patient safety and optimal device functionality. In the context of orthotopic cardiac transplant (OTC), the role of multimodality imaging remains indispensable. Echocardiography offers invaluable insights into allograft function and potential complications. Advanced methods, like speckle tracking echocardiography (STE), empower the detection of acute cell rejection. CMR and CCT further enhance diagnostic precision, especially concerning allograft rejection and cardiac allograft vasculopathy. This comprehensive imaging approach goes beyond diagnosis, shaping treatment strategies and risk assessment. By harmonizing diverse imaging modalities, clinicians gain a panoramic understanding of each patient's unique condition, facilitating well-informed decisions. Thus, this review underscores the irreplaceable role of multimodality imaging in elevating patient outcomes, refining treatment precision, and propelling advancements in the evolving landscape of advanced heart failure management.

High-flow Nasal Cannula (HFNC) oxygen therapy is gaining traction globally as a treatment for respiratory failure. There are several physiological benefits and there may be a growing patient preference for HFNC. In this narrative review, we aim to outline the basic mechanisms of HFNC, who can use it and review the literature regarding its utility both in the critical care setting, as well as in the home setting for chronic hypercapnic respiratory failure with an emphasis on Chronic Obstructive Pulmonary Disease (COPD). The role of non-pharmacological interventions like non-invasive ventilation (NIV) and HFNC in the prevention of hospital readmissions following acute exacerbations of COPD (AECOPD) is an area of increasing importance because randomised controlled trials and systematic reviews have found measures like nurse-led predischarge bundles to be clinically ineffective and to have a high cost per quality adjusted life year. This review therefore considers the evidence of NIV vs HFNC in the context of AECOPD and the application of HFNC at home in the prevention of AECOPD. We also look at applications of HFNC in specific settings, such as in the peri-operative period, emergency department, acute (mainly Critical Care) setting including in immunocompromised patients and palliative care.

Body weight support (BWS) and incline running (IR) are commonly used either during rehabilitation or during training separately, with many positive effects on athletes’ performance and rehabilitation. The aim of this study is to investigate the effect of BWS and IR. In eighteen healthy men (age: 20.3 ± 1.2 yr, body weight: 70.2 ± 4.8 kg, body height: 179.6 ± 5.4 cm), the changes in electromyographic activity (EMGA) during a 10-min run with BWS (15% or 30% of body weight; in different occasions) and IR at 7%, as well as jumping performance and gait spatiotemporal parameters were evaluated. Lower Rating of Perceived Exertion and a significant decrease in VL (33,4%), SOL (17%), and GL EMGA (28.5%, p &lt; 0.05) but not in GM (10.5%, p &gt; 0.05), were observed during BWS30% at 7% slope compared to flat running. Also, low-frequency fatigue of the quadriceps was induced only after running without BWS at 7% slope (P = 0.011). No changes were found in jumping performance (p = 0.246) and gait spatiotemporal parameters (p &gt; 0.05) except for flight time (p &lt; 0.006). In conclusion, compared to normal flat running, BWS reduces electromyographic activity and fatigue during slope running.

This article considers the basic psychological needs theory and tries to determine how much autonomy support from a coach is required for basic psychological needs and how autonomy, competence, relatedness, and the psychological motivational climate can explain task and ego involvement in a group of young elite ice hockey players. Our three hypotheses were as follows: autonomy support from the coach will have an impact on motivational involvement, all three basic needs will have an impact on motivational involvement, and motivational involvement will be explained by the motivational climate. A total of 175 male elite ice hockey players from Norway, ranging in age from 15 to 18 years old, answered questionnaires about autonomy support, perceived motivational climate, achievement goal orientation, and basic psychological needs. A multiple regression analysis was run to predict ego–task involvement using autonomy support from the coach, the need for autonomy, the need for competence, the need for relatedness, the task climate, and the ego climate. The only two variables that statistically significantly predicted ego–task involvement were autonomy support from the coach and the ego climate. The analysis revealed that the athletes had a higher score on task than ego involvement, but when this was transformed into two variables (high and low) for task and ego involvement, we found that most players scored high for both task and ego involvement. We found that autonomy from the coach had a positive relationship with a high score for players on both task and ego involvement. We also found that the three basic psychological needs had no impact on the motivational involvement of the athletes. Lastly, we found that the ego climate had an impact on the motivational involvement. There was a positive relationship between a high score for the ego climate and a high score for both ego and task involvement.

Water pollution is a common problem for dams situated within an urban or agricultural catchment. This can negatively affect the hydro ecosystem, drinking, recreational and other uses of water. In this study, the drinking water quality class of the Roodeplaat Dam, South Africa which faces pollution problems was modeled using machine learning algorisms in Python Jupyter Notebook 6.0.0. Eleven monthly water quality parameters recorded at five sampling stations from January 1981 to September 2017 were used for training and testing the model. Five machine learning classifiers: Gaussian Naïve Bayes (GNB), K-nearest neighbors (KNN), Decision Tree (DT), Support Vector Machines (SVM), and Linear Regression (LR) at a test size of 20%, 25%, 30%, and 40% were used to classify water into five classes (Excellent to Very bad). It was investigated that the dam water has only three classes good, medium, and bad. The prediction accuracies of machine learning algorithms from the highest to the lowest were 96.39%, 96.17%, 92.25%, 90.20, and 54.19% for KNN, DT, SVM, GNB, and LR, respectively. Therefore, KNN at a test size of 30% was recommended to classify the water quality of Roodeplat Dam accurately. Hence, machine learning algorithms can be used to identify the class of water quality before the water is treated and distributed for drinking use.

Introduction: The "second victim" phenomenon, (SVP) refers to a health professional who was involved in an adverse event (AE) and continues to suffer from the event to the detriment of personal and professional functioning. The Second Victims Natural History of Recovery Model predicts stages of the phenomenon from AE occurrence until the ‘moving on’ stage and serves as a suitable structure for many organizational support programs worldwide. Purpose: Using the Second Victims Natural History of Recovery Model to examine the impact of SVP on Israeli nurses, with a specific focus on the organizational support they felt they required as compared to the support they felt that they had received from their organizations. Methods: Fifteen in-depth interviews were conducted, using a semi-structured questionnaire, among nurses who had experienced SVP. The interviews were recorded subject to the interviewee's consent, transcribed, and analyzed using thematic content analysis. Findings: Throughout all six stages of recovery, all interviewees reported physical and emotional manifestations following exposure to an AE, regardless of type of event or severity. They also reported difficulty in emotion regulation, as well as damage to functioning and overall quality of life. Most of the nurse interviewees reported a need to share the events with someone, but despite this desire to receive appropriate support, almost none of them proactively requested help from a professional source, nor did their organizational management initiate proactive support. This lack of referral for further assistance is possibly explained through limited awareness of SVP as a valid response to an AE, perceived lack of legitimacy to receive organizational support and personal barriers that accompany the phenomenon. Conclusions: Appropriate organizational support, offered proximal to an AE as well as over time, is essential for the nurse, the patient and the organization. Personal barriers, together with limited awareness, may challenge the identification and provision of appropriate assistance. Hence, it is important to address the phenomenon as part of general organizational policy to improve quality of care and patient safety.

Distributed Manufacturing (DM) is becoming increasingly important in operations management due to its potential to support sustainability goals, reduce risks in global supply chains, and boost local economies. However, previous analyses of the advantages and disadvantages of DM have mainly focused on operations, overlooking additional benefits across the supply chain. For example, DM can enable local sourcing, better serve end-users, and tackle reverse supply chain challenges. While economies of scale are essential for reducing costs and improving productivity, highly centralised manufacturing can increase transportation costs, vulnerability, and supply chain disruptions, particularly during pandemics or other times of restricted transportation. To address these challenges, this study introduces a Multi-attribute Decision Support System (MADSS) and assessment process that considers impacts across the supply chain and guides stakeholders, academics, and decision-makers. The MADSS handles quantitative and qualitative information, missing data, and uncertainty, and a team of experts from academia and industry in New Zealand has developed the evaluation. The MADSS was used to analyse DM and traditional construction alternatives from economic, social, environmental, and resilience perspectives in New Zealand. The research contributes to a better understanding of the impacts of DM across the entire supply chain. Also, it proposes a flexible decision-making framework to engage with stakeholders and support decision-making in other industries and regions.

The objective of this quantitative study was to examine the impact of selected factors on the level and state of public health in local self-government units in 2021, with the consideration of data from 2020 and 2019. This survey included 77 out of 145 local self-government units in the Republic of Serbia and examined six dimensions defined by the Law on Public Health: social care for the public health of the city/municipality in regard to the physical, mental, and social health of the population; health promotion and disease prevention; the environment and health; working environments and population health; the organization and functioning of the health system; and actions in emergency situations. The results of the Pearson correlation showed that there were statistically significant correlations between the effectiveness of the realized program budget and microbiologically defective drinking water samples from the so-called village water supply systems, defective samples of drinking water from public taps, unsatisfactory analyses of wastewater samples, the total number of air samples on an annual level for PM25s, and the number of mandated fines issued. The results of the logistic regression model showed that the local self-government units that received assistance from the Permanent Conference of Cities and Municipalities were 5.6 times more likely to perform analyses of their health status. Furthermore, we determined that the units of local self-governments that appointed a coordinator of the health council identified vulnerable groups in the analysis of the state of health four and a half times more often. In contrast, the units of local self-governments that prepared health status analyses could be used to identify vulnerable groups to a six times greater extent within the framework of the health status analysis. The results showed that in improving the state of public health at the local level, it is necessary to provide systematic institutional support to cities and municipalities in exercising their responsibilities. Based on these results, recommendations were made for the further development of support, i.e., the planning of further activities aimed at strengthening the capacity of the health councils and local self-government units in this area.

Postpartum depression (PPD) can predispose to physical and mental health problems in women. However, PPD is associated with health and perceived social support but their causal relationship is unclear. Therefore, this study intended to evaluate the association of PPD with insomnia, mental health, and physical health. Convenience sampling technique was used to collect data from 320 (52.8 %) young and middle aged postpartum women, in the outpatient departments of obstetrics and gynecology in Government Maula Bakhsh Hospital, District Head Quarter in Sargodha, Pakistan. The Edinburgh Postnatal depression scale, Pittsburg sleep quality index, Warwick-Edinburgh mental wellbeing scale, Patient health questionnaire, and Multidimensional scale of perceived social support were used to measure study variables. Results revealed a significant positive relationship of PPD with physical health (r= .45, p=.001), while a negative relationship with insomnia (r= -.24, p<.001), and perceived social support (r= -.38, p=.001). Results further confirmed that perceived social support played a moderating role (β = .97, p=.01) in the relationship between PPD and mental health among females. This study concluded that perceived social support has an important role in PPD and women’s health. The study also concluded that poor health is a risk indicator for identifying aid in the early stages of postpartum among women.

Tropical cyclones devastate large areas, take numerous lives and damage extensive property in Bangladesh. Research on landfalling tropical cyclones affecting Bangladesh has primarily focused on events occurring since AD1960 with limited work examining earlier historical records. We rectify this gap by developing a new tornado catalogue that include present and past records of tornados across Bangladesh maximizing use of available sources. Within this new tornado database, 119 records were captured starting from 1838 till 2020 causing 8,735 deaths and 97,868 injuries leaving more than 1,02,776 people affected in total. Moreover, using this new tornado data, we developed an end-to-end system that allows a user to explore and analyze the full range of tornado data on multiple scenarios. The user of this new system can select a date range or search a particular location, and then, all the tornado information along with Artificial Intelligence (AI) based insights within that selected scope would be dynamically presented in a range of devices including iOS, Android, and Windows. Using a set of interactive maps, charts, graphs, and visualizations the user would have a comprehensive understanding of the historical records of Tornados, Cyclones and associated landfalls with detailed data distributions and statistics.

Here we propose the concept of an electro–microbial route to uncouple food production from photosynthesis, thereby enabling production of nutritious food in space without the need to grow plant-based crops. In the proposed process, carbon dioxide is fixed into ethanol using either chemical catalysis or microbial carbon fixation, and the ethanol created is used as a carbon source for yeast to synthesize food for human or animal consumption. The process depends upon technologies that can utilize electrical energy to fix carbon into ethanol and uses an optimized strain of the yeast Saccharomyces cerevisiae to produce high quality, food grade single cell protein using only ethanol, urea, phosphate, and inorganic salts as inputs. Unlike crops using photosynthesis that require months to mature and are challenging to grow under the conditions found in space, the electro–microbial process could generate significant quantities of food on demand with potentially high yields and productivities. In this paper we explore the potential of the proposed process to provide food on demand in space, but it should be noted that this novel approach to food production has many valuable terrestrial applications too. For example, enabling food production in climatically challenged environments including turning deserts into food bowls, or utilizing surplus electricity generated from large-scale renewable power sources.

Objective: to analyze the relationships between sociodemographic variables, intolerance to uncertainty (INT), social support and psychological distress (i.e., indicators of Common Mental Disorders [CMDs] and perceived stress [PS]) in Brazilian men during the COVID-19 pandemic. Methods: a cross-sectional study with national coverage, of the web survey type, and conducted with 1,006 Brazilian men during the period of social circulation restriction imposed by the health authorities in Brazil, for suppression of the coronavirus and control of the pandemic. Structural equation modeling analysis was performed. Results: Statistically significant direct effects of race/skin color (λ=0.268; p-value<0.001), socioeconomic status (SES) (λ=0.306; p-value<0.001), household composition (λ=0.281; p-value<0.001), PS (λ=0.513; p-value<0.001) and INT (λ=0.421; p-value<0.001) were evidenced in the occurrence of CMDs. Black-skinned men, with higher SES, living alone and with higher PS and INT levels presented higher prevalence values of CMDs. Conclusions: high levels of PS and INT were the factors that presented the strongest associations with the occurrence of CMDs among the men. It is necessary to implement actions to reduce the stress-generating sources, as well as to promote an increase in resilience and the development of intrinsic reinforcements to deal with uncertain threats.

This paper presents the evaluation of a fungal disease forecast model in vineyards for qualitative parameter analysis using the data from off the shelf sensors, i.e. temperature and air relative humidity, rain precipitation, and leaf wetness. The rules for the fungal disease models are digitalized as a decision support tool that serve as an indicator to farmers for the need of spraying of the chemical substances to ensure the best growing condition and suppress the level of parasites. The temperature and humidity contexts are used interchangeably in practice to detect the risk of the disease occurrence. By taking into account a number of influences on these parameters collected from the shelf sensors, new topics for research in the multidimensional field of precision agriculture emerge. In this study, the impact of the humidity is evaluated by assessing how different humidity parameters correlate with the accuracy of the Botrytis cinerea fungi forecast. Each humidity parameter has it’s own threshold that triggers the second step of the disease modeling - risk index based on the temperature. The research showed that for humidity a low-cost relative humidity sensor can detect in average 14.61% risk values, a leaf wetness sensor an additional 3.99% risk cases, and finally, a precipitation sensor will detect only an additional 0.59% risk cases.

This paper aims to explore the effect of humble leadership on project success by integrating the mediating role of employee creativity. Top management support moderates the direct relationship (humble leadership and project management effectiveness) and indirect relationships through employee creativity. Time-lagged data were obtained from 332 persons working in the matrix organization across the information technology. The results showed that humble leadership enhance project management effectiveness by mediating and moderating processes. This study provides a solution to an underlying research question that has gone unanswered in prior studies. What are the strategies proposed for humble leadership in fostering the effectiveness of the project?

Objective: Studies in Sports Psychology and Sociology have validated causality in team-sport athletes by using emotional intelligence as a variable. This study aimed to examine the causal relationship between the types of autonomy support coaching, emotional intelligence, and interruption intention as psychosocial variables among current taekwondo athletes in Korea.Methods: In this study, 217 adult or university athletes registered in the Korea Taekwondo Association in 2020 were evaluated for the type of autonomy support coaching, emotional intelligence, and interruption intention. Results: Autonomy support coaching recognized by taekwondo athletes has a negative and positive effect on interruption intention and emotional intelligence, respectively. Moreover, emotional intelligence has a negative effect on interruption intention. which revealed that autonomy support coaching has a negative effect on interruption intention through emotional intelligence.Conclusions: Such outcomes can serve as a foundation for athletes to have the opportunity to participate in sports in a mature manner and promote positive changes in sports culture. In other words, the sensibility of the athletes can be harmoniously symmetry.

Objective: Studies in Sports Psychology and Sociology have validated causality in team-sport athletes by using emotional intelligence as a variable. This study aimed to examine the causal relationship between the types of autonomy support coaching, emotional intelligence, and interruption intention as psychosocial variables among current taekwondo athletes in Korea. Methods: In this study, 217 adult or university athletes registered in the Korea Taekwondo Association in 2020 were evaluated for the type of autonomy support coaching, emotional intelligence, and interruption intention. Results: Autonomy support coaching recognized by taekwondo athletes has a negative and positive effect on interruption intention and emotional intelligence, respectively. Moreover, emotional intelligence has a negative effect on interruption intention. which revealed that autonomy support coaching has a negative effect on interruption intention through emotional intelligence. Conclusions: Such outcomes can serve as a foundation for athletes to have the opportunity to participate in sports in a mature manner and promote positive changes in sports culture. In other words, the sensibility of the athletes can be harmoniously symmetry.

Institutional support and quality education are linked in a significant way. During Covid-19, institutional support is critical to closing the huge academic gap that has emerged as physical academic practices have been moved to a virtual education system using technology. This research aims to assess institutional support for online education in Bangladesh during the Covid-19 pandemic. This analysis is focused on the three main elements of the Adapted Model of Institutional Support (AMIS) of Bond et al, 2007, and the Institutional Support Model (ISM) of Valverde and Rodriguez, 2002, namely Financial Support (FS), Technical Support (TS), and Mentoring Support (MS). According to the findings, a few universities in Bangladesh have provided average support for continuing online education, while others have just started taking online classes. Several problems have been discovered, such as the lack of dedicated software for conducting online academic activities, lack of training and grooming, lack of mentoring, poor internet access, lack of smartphones, high internet package rates, and so on. This study concludes with some policy recommendations for a smooth online education system in Bangladesh.

Background: Few studies examined the contributions of childhood adversities, intimate partner violence and social support to antenatal depression (AD). This study aims to 1) evaluate association of these psychosocial factors with AD symptoms in early pregnancy; and 2) examine the mediating effect of social support on the relationship between psychosocial stressors and AD symptoms.Methods: Participants were 120 pregnant women aged from 18 to 49 in less than 16 gestational weeks and attending at Antenatal Care Center at Khon Kaen hospital, Thailand. AD symptoms were assessed by the Edinburgh Postnatal Depression Scale (EPDS). Childhood adversities, intimate partner violence and social support were measured using the Adverse Childhood Experiences Questionnaire (ACE questionnaire), Abuse Assessment Screen (AAS), and Multidimensional Scale of Perceived Social Support (MSPSS). Results: We found that the EPDS score was significantly and positively associated with adverse childhood experiences (ACEs) and negatively with social support. Partial Least Square analysis showed that 49.1% of the variance in the depressive subdomain of the EPDS score was predicted by ACEs, namely psychological and physical abuse and neglect, emotional or physical abuse by the partner, unplanned pregnancy, and no satisfaction with their relationship. The effects of adverse childhood experience due to neglect on the EDPS score was mediated by social support by friends. Limitations: ACEs were assessed retrospectively and, therefore, may be susceptible to recall bias.Conclusion: Prenatal depression scores are to a large extent predicted by psychological distress as indicated by early lifetime trauma, abuse by partner, relation satisfaction, and implications of unintended pregnancy.

This research investigated the effects of social isolation on frailty and health outcomes and tested whether these associations varied across different levels of frailty. We performed a multivariate analysis of data from the first wave of the FRéLE study among 1,643 Canadian older adults aged 65 years and over. We assessed social isolation using social participation, social networks, and support from various social ties, namely, friends, children, extended family, and partner. Frailty predicted disability, comorbidity, depression, and cognitive decline. Less social participation was associated with IADLs, depression, and cognitive decline. The absence of friends was associated with depression and cognitive impairment. Less social support from children and partner was related to comorbidity, depression, and cognitive decline. Overall, social isolation is linked to mental health, rather than physical health. The associations of having no siblings, receiving less support from friends, and participating less in social activities with ADL limitations, depression, and cognitive decline were higher among frail than pre-frail and robust older adults. This study corroborates the pivotal role of social connectedness, particularly the quality of relationships, on the mental health of older adults. Public health policies on social relationships are paramount to ameliorate the health status of frail older adults.

COVID-19 pandemic event requires a rapid response from various organizations at the international and national levels. One important response is the provision of information sharing facilities and monitoring of the spread of cases around the world, JHU CSSE developed the Dashboard in January 2020 and followed by WHO the same month for the WHO COVID-19 dashboard. Both dashboards have distributed information as expected by the user with their respective pros and cons. JHU CSSE Dashboard provides faster information with good access to mobile device users even though the display and color selection are less attractive. Information on the WHO COVID-19 Dashboard is often late but more data appearances and variations and comparisons between countries can be made. In the Indonesian context, ESSC for COVID-19 Geoportal as Esri Indonesia initiative has been developed with the support of data and information from various parties and developed with the principles of big data management which are fully supported by adequate spatial portal developer software from Esri. Particularly in Indonesia, there is not yet an adequate system to support spatial based decision making at the local level, therefore the development of a GIS dashboard to support provincial and district governments is highly recommended.

Identifying the determinants of human behavior is useful to adjust interventions and lead the civil society towards a stronger commitment with climate change mitigation and adaptation objectives, achieving greater support for successfully implementing environmental policies. Existing research has largely focused on case studies of pro-environmental behaviors (PEBs) in developed economies but there is yet very little evidence for developing countries. This study provides estimations of the effect of internal factors, such as sociodemographic variables, and four psychological dimensions (climate change knowledge, environmental attitudes, self-efficacy, trust in sources of environmental information) on PEBs. Data was obtained through a survey applied with future decision makers - university students - from Colombia (n = 4769) and Nicaragua (n = 2354). Indices were generated for PEBs and the psychological dimensions using z-scores and Principal Component Analysis. Partial correlations were evaluated through the Ordinary Least Squares method. Our results suggest that, in order to reach the planned emission reduction targets, policy approaches should more strongly focus on educating and motivating citizens and prepare them for contributing to the environmental cause, as well as provide individual solutions to combat climate change, rather than providing only information on its causes and consequences.

Recognition of the human interaction on the unconstrained videos taken from cameras and remote sensing platforms like a drone is a challenging problem. This study presents a method to resolve issues of motion blur, poor quality of videos, occlusions, the difference in body structure or size, and high computation or memory requirement. This study contributes to the improvement of recognition of human interaction during disasters such as an earthquake and flood utilizing drone videos for rescue and emergency management. We used Support Vector Machine (SVM) to classify the high-level and stationary features obtained from Convolutional Neural Network (CNN) in key-frames from videos. We extracted conceptual features by employing CNN to recognize objects from first and last images from a video. The proposed method demonstrated the context of a scene, which is significant in determining the behaviour of human in the videos. In this method, we do not require person detection, tracking, and many instances of images. The proposed method was tested for the University of Central Florida (UCF Sports Action), Olympic Sports videos. These videos were taken from the ground platform. Besides, camera drone video was captured from Southwest Jiaotong University (SWJTU) Sports Centre and incorporated to test the developed method in this study. This study accomplished an acceptable performance with an accuracy of 90.42%, which has indicated improvement of more than 4.92% as compared to the existing methods.

In this study, the decision-making process management of forest tending in the forestry business is decentralized, and forest tending decision-making activities at different points in time are integrated by decision makers at different geographical locations. The decision-making process was analyzed and optimized from a system perspective. Based on the optimized decision-making process, a forest tending business group decision support system (FTGDSS) was established. We first reviewed and discussed the characteristics and development of the forest tending business and forestry decision support system. Business Process Modeling Notation was used to draw a current state flow chart of the forest tending business, to identify and discover important decision points in the process of tending decision-making. We also analyzed the content and attributes of each decision point, and described the system structure, functional framework, knowledge base structure, and reasoning algorithm of FTGDSS in detail. Finally, FTGDSS was evaluated from the two dimensions of the technology adoption model. FTGDSS integrates different levels of time-space decision-making activities, historical tending data, business plans, decision-makers' management tendencies into the decision-making process and automatically extracts decision-making data from the forest business process management enterprise resource planning system (Smartforest) that improves the ease of use of the decision support system (DSS). It also improves the quality of forest tending decisions, and enables the DSS to better support multi-target management strategies.

NaoMaiTong (NMT: Radix et Rhi-zoma Rhei, Radix Ginseng, Radix Puerariae, and Rhizoma Ligustici Chuanxiong as 9: 9: 6: 6) is a traditional Chinese medicine prescription for treating ischemia cerebral apoplexy. In this work, four cell injury models of ischemic stroke were establish, namely hypoxic injury, glutamate damage, injury of potassium chloride and hydrogen peroxide damage model. The protective effects of NMT and its single herbs-containing sera of different time points on PC12 cell damage were evaluated respectively, and the corresponding efficacy-time curves were drawn. Cell viability was measured by MTT (3-(4,5)-Dimethylthiahiazo(-z-y1)-3,5-di-phenytetrazoliumromide) assay. Furthermore, an statistical methods of support vector machine (SVM) were used to establish the correlation between concentration-time-efficacy for the first time. These results revealed that NMT-containing serum has obvious protective effect on the four injury models and can significantly improve cell viability. The PK-PD correlation between fifteen ingredients in the NMT compound with four model efficacy indexes indicated that rhein, puerarin, and 3'-methoxy puerarin might be the most important constituents controlling the pharmacological effects of NMT. The study suggested that these fifteen components are likely to be the material basis of NMT and recommended to increase the amounts of Pueraria in the NMT compound. That provided the scientific basis and demonstration for the research of efficacy material base of Traditional Chinese Medicine (TCM).

The anti-money laundering (AML) process has failed both in identifying suspicious cases in due time as in assisting the AML analysts in decision making. Starting from a new generic anti-fraud approach, this article presents the main aspects related to the development of a multi-agent system that goes beyond the capture of suspicious transactions, seeking to assist the human expert in the analysis of suspicious behaviour. First, a transactional behavioural profile of clients is obtained in a data mining process. A set of rules, obtained through data mining over a real database, in conjunction with specific rules based on legal aspects and in the expertise of the AML analysts make up the agents' knowledge base. The cases for which the system was unable to suggest a decision are flagged as requiring more detailed analysis. The system analysed 6 months of real transactions and indicated several suspicious profiles, a set of these suspects was investigated by the AML analysts who proved the suspicion of several cases, including some that had not been identified by the systems in execution.

Dynamic measurement error correction is an effective method to improve the sensor precision. Dynamic measurement error prediction is an important part of error correction, support vector machine (SVM) is often used to predicting the dynamic measurement error of sensors. Traditionally, the parameters of SVM were always set by manual, which can not ensure the model’s performance. In this paper, a method of SVM based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement error of sensors. Natural selection and Simulated annealing are added in PSO to raise the ability to avoid local optimum. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters, they are the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absoluter percentage error are employed to evaluate the prediction models’ performances. The experiment results show that the NAPSO-SVM has a better prediction precision and a less prediction errors among the three algorithms, and it is an effective method in predicting dynamic measurement errors of sensors.

In this paper, a new approach to retrieve semantic images based on shape and geometric features of image in conjunction with multi-class support vector machine is proposed. Zernike moment as shape feature is to verify the invariance of objects for silhouette image. In addition, a set of geometrical features is to explore the objects shape using two features of rectangularity and circularity. Then the extracted features are normalized and employed for multi-class support vector machine either for learning or retrieving processes. The retrieving process relies on three main tasks which namely Query Engine, Matching Module and Ontology Manger, respectively. Query Engine is to build the input text or image query using SPARQL language. The matching module extracts the shape and geometric features of image’s objects and employ them to Ontology Manger which in turn inserts them in ontology knowledge base. Benchmark mammals have been conducted to empirically conclude the outcome of proposed approach. Our experiment on text and image retrieval yields efficient results to problematic phenomena than previously reported.

Keywords: Artificial Neural Network (ANN), Support Vector Machine (SVM), Support Vector Regression (SVR), Lightweight Gradient Boosting Machines (Light GBM), Machine Learning, Solar Irradiance (SI), Solar forecasting

Abstract Objective Variations of sex characteristics (VSC) are atypical genetic, hormonal, gonadal and anatomical sex traits that require holistic medical management. The Chicago Consensus statement 2006 introduced the requirement that multidisciplinary teams organise the transition of care from pediatric to adult services. Yet, the evidence that the transitional care is in place is scarce. The aim of this paper is to examine the implementation of transition of care for people with VSC. Method Seven focus groups were conducted with health care professionals and peer support groups in care teams in Central, Northern and Western Europe. The data from the focus groups were examined using reflexive thematic analysis. Results The participants in the study stated that the transition of care has been implemented in the last two decades. The quality of care depends on available resources and variation of sex characteristics. However, there are significant hurdles to adequate transition of care as there is lack of time and resources. Lack of adult care providers and psychosocial support leaves young adults and adults with VSC navigating the health care system often alone. Conclusion The outcome of the study shows that the transition of care is organized through the department of pediatric endocrinology. The quality of care varies due to resources and variation. Lack of adult specialists and psychosocial support represent the biggest obstacle for young adults and adults to navigate the healthcare system and for the improvement in provision of healthcare to adults, especially psychosocial support.

The increading emission of carbon dioxide to the atmosphere has urged the scientific community to investigate alternatives to alleviate such emissions being the principal contributor to the greenhouse gas effect. One major alternative is carbon capture and utilisation (CCU) towards the production of value-added chemicals using diverse technologies. This work aims at the study of the catalytic potential of different cobalt-derived nanoparticels for methanol syntheis from carbon dioxide hydrogenation. Thanks to its abundance and cost-efficacy, cobalt can serve as an economical catalyst compared to noble-metal-based catalysts. In this work, we present a systematic comparison among different cobalt and cobalt oxide nanocomposites in terms of their efficiency as catalysts for carbon dioxide hydrogenation to methanol as well as how different supports can enhance their catalytic capacity. The oxygen vacancies in the cerium oxide act as carbon dioxide adsorption and activation sites, which facilitates a higher methanol production yield.

Landslide is one of the most common geological disasters in China, which is characterized by suddenness and uncertainty, and it is difficult to realize accurate identification, early warning and forecasting of landslide disaster by conventional means. With the development of high-resolution remote sensing satellites and InSAR surface deformation monitoring technology, the traditional means of landslide monitoring data sources are limited, and there is a lack of effective methods to excavate the characteristics of the spatial distribution of landslide hazards and their triggering factors and other issues. In this paper, the area extending 10 km outside the VII isobar of the Gengma earthquake is taken as the study area, and 13 evaluation factors are screened out by integrating the factors of InSAR surface deformation, topography and geological environment, and the Bayesian Optimized Convolutional Neural Network (BO-CNN) is used for the evaluation of landslide susceptibility, and the BO-RF and PSO-SVM models are selected for the comparative analysis. The model accuracy evaluation was carried out by three indexes: ROC curve, AUC value and FR value, in which the ROC curves of PSO-SVM, BO-RF and BO-CNN were all close to the upper-left corner of the corner, and the AUC values were 0.9388, 0.9529, and 0.9535, respectively, and the FR value of landslide in the high susceptibility area of BO-CNN was as high as 14.9, and was higher than that of PSO-SVM and BO-RF, respectively. SVM and BO-RF model is 4.55 and 3.69 higher, the experimental results show that the BO-CNN model used in this paper has a better effect in landslide susceptibility evaluation, and the research results of the local government's disaster prevention and mitigation measures are of great significance.

3D metal nanostructures are often the basis of several applications such as in catalysis, plasmonics, medical diagnosis, therapy, drug screening, ophthalmologic, and biomedical applications. Porous gold nanoparticles (PGNs) are intensively investigated due to their outstanding morphological as well as advantageous optical properties. Unfortunately, the thermal stability of these open-porous structures is poor, i.e. even as a result of low-temperature annealing (150$^\circ$C in air), their porosity disappears and they lose their favorable optical properties. In order to preserve their beneficial properties, a thin metal oxide coating can be applied. Changing the coating's thickness and/or composition, the optical response of the PGNs can also be tuned in a wide wavelength region. Moreover, these nanoparticles can be synthesized also in support-free form, which makes them more attractive from an application point of view. This review article summarizes some of the preparation modes of these complex nanostructures (fixed and support-free), as well as their thermal stability and optical responses.

An out-of-hospital cardiac arrest (OHCA) is one of the leading causes of death in the world. The survival rate can be influenced by the Chain of Survival. The school is the institution that has the opportunity to promote the education of citizens in Basic Life Support (BLS), increasing the number of trained bystanders. This study aimed to identify the theoretical and practical knowledge and self-reported skills in BLS, in order to characterise the motivation to intervene in an emergency situation. A quantitative, descriptive, cross-sectional, and analytical study of the survey type was developed with a sample of 1215 students enrolled in 10th grade of secondary education in 2019-2020 in Portugal. The results point to a fragile appropriation of theoretical and practical knowledge in the field of BLS. Self-declared competences tend to rank below the theoretical knowledge manifested. Motivation to intervene is high: students are sensitive to the topic, willing to learn and highlight the importance and social relevance of the topic. We conclude that students do not feel nor are able to intervene in an OHCA episode. It seems necessary to develop didactic proposals that align the teaching of BLS with the Essential Learning at the end of compulsory education in Portugal.

Many spatial decision support systems suffer from user adoption issues in practice due to lack of trust, technical expertise, and resources. Automated machine learning has recently allowed non-experts to explore and apply machine learning models in the industry without requiring abundant expert knowledge and resources. This paper reviews recent literature from 136 papers, and proposes a general framework for integrating spatial decision support systems with automated machine learning to lower major user adoption barriers. Challenges of data quality, model interpretability, and practical usefulness were discussed as general considerations for system implementation. Research opportunities related to spatially explicit models in AutoML, and resource-aware, collaborative/connected, and human-centered systems were also discussed to address these challenges. This paper argues that integrating spatial decision support systems with automated machine learning can not only encourage user adoption, but also mutually benefit research in both fields — bridging human-related and technical advancements for fostering future developments in spatial decision support systems and automated machine learning.

Background. It is well established that human milk feeding contributes in limiting lung disease among vulnerable neonates. The primary aim of this research was to compare the need for mechanical ventilation of human milk-fed sick neonates with that of formula-fed sick neonates. Methods. All late preterm and full term infants from a single center with findings of sepsis, from 2002 to 2017, were identified. Data regarding infant feeding during hospital admission were recorded. Multivariate logistic regression analyses were performed to assess the impact of the type of milk on ventilation support and main neonatal morbidities. Results. The total number of participants was 322 (human milk group = 260, exclusive formula group = 62). On bivariate analysis, 72% of human milk-fed neonates did not need oxygen therapy nor respiratory support versus 55% of their formula-fed counterparts (P<0.0001). Accordingly, invasive mechanical ventilation was required by 9.2% of human milk-fed infants versus 32% of their formula-fed counterparts (P=0.0085). These results hold true in multivariate analysis, indeed human milk-fed neonates were more likely to require less respiratory support (OR=0.44; 95% CI: 0.22, 0.89) when compared to those who were exclusively formula-fed. Conclusion. Human milk feeding might minimize exposure to mechanical ventilation.

Research rarely explores LGBTQ+ youth bullying in the context of culture-specific outcomes (e.g., LGBTQ+ identity development) and what can mitigate the impact of peer stressors. This study used a concurrent mixed methods design to explore how experiences of peer victimization predicted LGBTQ+ youth’s identity development (i.e., stigma sensitivity, concealment motivation, and difficult process) and whether social support and outness served as protective, moderating factors. The mixed-methods approach provides a culture-specific context via qualitative inquiry to inform whether the quantitative findings align with how youth qualitatively discuss their experience of bullying, negative outcomes, and social support. Our sample consisted of 349 LGBTQ+ youth 14-17 years old who completed a survey (quantitative sample), and a subset of 39 LGBTQ+ youth who completed a semi-structured interview (qualitative sample). Our quantitative findings indicated that greater overall peer victimization was positively related to LGBIS-revised subscales of stigma sensitivity, concealment motivation, and difficult process, where both outness and social support moderated such relations. Qualitatively, victimized youth also reported stigma sensitivity and concealment motivation, while also endorsing how being out and having a support system played a role in their experience of being victimized. These qualitative findings align with our quantitative findings that classmate support mitigated the effects of peer victimization on difficulty of coming out. Implications for practitioners and researchers are provided.