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This study explores the social media engagement of human service nonprofits during the early phase of the COVID-19 pandemic. We analyzed 2,726 tweets from 15 food banks in Texas to understand their communication and audience engagement on social media. During the early outbreak, food banks were more active on social media, and these organizations primarily shared community-building and informational content. Before the pandemic, community-building content led to the highest engagement level. However, action and informational content saw greater engagement during the crisis. Our findings reveal that online audiences perceive the importance of each content type differently in varying circumstances. By understanding preferences and needs of online audiences, human service nonprofits can harness the power of social media to amplify their impact while operating during times of crisis.

This paper introduces an enhanced version of the Capuchin Search Algorithm (CapSA) called ECapSA. CapSA draws inspiration from the collective intelligence of Capuchin monkeys and has shown success in solving real-world problems. However, it may encounter challenges handling complex optimization tasks, such as premature convergence or being trapped in local optima. ECapSA employs a local escaping mechanism operating the abandonment limit concept to exploit potential solutions and introduce diversification trends. Additionally, the ECapSA algorithm is improved by integrating the principles of the cooperative island model, resulting in the iECapSA. This modification enables better management of population diversity and a more optimal balance between exploration and exploitation. The efficiency of iECapSA is validated through a series of experiments, including the IEEE-CEC2014 benchmark functions and training the feedforward neural network (FNN) on seven biomedical datasets. The performance of iECapSA is compared to other metaheuristic techniques, namely differential evolution (DE), sine cosine algorithm (SCA), and whale optimization algorithm (WOA). The results of the comparative study demonstrate that iECapSA is a strong contender and surpasses other training algorithms in most datasets, particularly in terms of its ability to avoid local optima and its improved convergence speed.

The K-12 health and physical education professions are largely guided and supported by three entities. They include state departments of education, national and state professional associations, and teacher education programs (i.e., health education teacher education [HETE] and physical education teacher education [PETE]). From the outside looking in, it may seem that HETE and PETE programs are not dissimilar, yet both disciplines continue to operate largely within individual vacuums, each being historically undermined and marginalized. Therefore, questions regarding the purpose and relevance of K-12 health and physical education programs are continually raised. These common challenges may have a negative impact on recruitment of health and physical education teachers, retention of HETE and PETE programs, and ultimately the learning outcomes of youth in schools. In this article, we review critical challenges faced by both HETE and PETE programs with the hope that this can lead to collaboration, advocacy, and meaningful change.

In this study, we conducted experiments to model the temperature of two manufacturing processes using various metaheuristic search algorithms. The two processes adopted were the P05 horny steel tool and the AISI304 stainless steel castings machines. Our approach involves building a data-driven model, as traditional search methods for modeling manufac-turing problems often need help finding the global optimum when faced with a complex objective function and numerous decision variables. Bio-inspired metaheuristic search algorithms have shown promising performance in handling multi-model optimization functions, and efficiently exploring the search space to attain more global results. We applied several metaheuristic search algorithms to find the optimal tuning parameters of a temperature-based model. The results from the case studies demonstrate that Particle Swarm Optimization (PSO) provided the best performance in tuning model parameters, resulting in minimum modeling error.

Sleep apnea is a sleeping disorder affecting more than 20 % of all American adults, associated with intermittent air passageway obstruction during sleep. This results in intermittent hypoxia, sympathetic activation, and an interruption of sleep with various health consequences. The diagnosis of sleep apnea traditionally involves the performance of overnight polysomnography, where oxygen, heart rate, and breathing, among other physiologic variables, are continuously monitored during sleep at a sleep center. However, these sleep studies are expensive and impose access issues, given the number of patients who need to be diagnosed. There is hence utility in having an effective triage system to screen for OSA to utilize polysomnography better. In this study, we plan to explore using several machine learning algorithms to utilize pre-screening symptoms to diagnose obstructive sleep apnea (OSA). Per our experimental results, it was found that Decision Tree Classifier (DTC) and Random Forest (RF) provided the highest classification accuracies compared to other algorithms such as Logistic Regression (LR), Support Vector Machines (SVM), Gradient Boosting Classifier (GBC), Gaussian Naive Bayes (GNB), K Neighbors Classifier (KNC), and Artificial Neural Networks (ANN).

The growing diversity of students in schools has raised important questions regarding how students learning English and discipline-content simultaneously succeed academically. This challenge has been exacerbated by disparities in resources among multilingual communities throughout the COVID-19 pande...

We describe the rationale and study design for “TRUsted rEsidents and Housing Assistance to decrease Violence Exposure in New Haven (TRUE HAVEN),” a prospective type 1 hybrid effectiveness/implementation study of a multi-level intervention using a stepped wedge design. TRUE HAVEN aims to lower rates of community gun violence by fostering the stability, wealth, and well-being of individuals and families directly impacted by incarceration through the provision of stable housing and by breaking the cycle of trauma.

Parental and family involvement in schools has been a concern for educators and administrators. The authors set out to assess the path directions and significance of the interrelationships between Performance Feedback (PF), Academic Performance (AP) on Parent–Family Involvement (PFI), and Parent Satisfaction (PS) in schools. This study utilizes data from the PFI in Education Survey 2019 under the National Household Education Surveys program done by the US Department of Education. The sample for this research is 954 parents. Structural equation modeling was employed using AMOS. Results establish the three research propositions: influence of PFI on PS with the mediation of AP and PF, influence of AP on PS is moderated by PF, influence of AP on PFI is moderated by PF. The findings are important for school administrators and all stakeholders for ensuring greater PFI, improved PF and AP of students, and higher PS. This study is unique in assessing the interactional effects of the variables considered. The study also establishes mediating and moderating influences and offers new insights in understanding the influences on PFI and PS and some bidirectional effects. © 2023 Wiley Periodicals LLC.

The following research examines the acculturation processes of migrants, working in Switzerland, particularly in the hospitality industry. Due to rapid globalisation and lack of investigation on worker’s adaptation, there remains a gap in the research based on the employees’ cultural clash occurrence. The study explores potential tools which might simplify cultural adaptation and provide a better understanding of international communication for any future employees coming to live and work in Switzerland. Semi-structured interviews with participants from different nationalities were conducted to identify the importance of effective acculturation, the adaptation issues, and the influence of those on work and life in Switzerland. The results demonstrate that the most efficient way to acculturate in Switzerland is integration to the culture and traditions of the country and its history through understanding their values, norms, practices. Moreover, Switzerland was viewed as a very conservative and strict country where one must work hard to be accepted. Those participants who tried to separate, assimilate, or marginalise tend to experience tougher acculturation. Language, namely Swiss German or German, was highlighted as the most essential to learn or to be provided by the workplace. Lastly, current research identified a link between successful acculturation with job opportunities and development. Since salaries and job opportunities are not the same for the foreign workers in comparison to Swiss employees on the same position there might be a potential recommendation for improvement. Little to no link has been found between acculturation and psychological well-being, financial status, and health conditions. © 2023 AJHTL /Author(s)

Winning football matches is the major goal of all football clubs in the world. Football being the most popular game in the world, many studies have been conducted to analyze and predict match winners based on players’ physical and technical performance. In this study, we analyzed the matches from the professional football league of Qatar Stars League (QSL) covering the matches held in the last ten seasons. We incorporated the highest number of professional matches from the last ten seasons covering from 2011 up to 2022 and proposed SoccerNet, a Gated Recurrent Unit (GRU)-based deep learning-based model to predict match winners with over 80% accuracy. We considered match- and player-related information captured by STATS platform in a time slot of 15 minutes. Then we analyzed players’ performance at different positions on the field at different stages of the match. Our results indicated that in QSL, the defenders’ role in matches is more dominant than midfielders and forwarders. Moreover, our analysis suggests that the last 15–30 minutes of match segments of the matches from QSL have a more significant impact on the match result than other match segments. To the best of our knowledge, the proposed model is the first DL-based model in predicting match winners from any professional football leagues in the Middle East and North Africa (MENA) region. We believe the results will support the coaching staff and team management for QSL in designing game strategies and improve the overall quality of performance of the players.

Audiovisual speech perception includes the simultaneous processing of auditory and visual speech. Deficits in audiovisual speech perception are reported in autistic individuals; however, less is known regarding audiovisual speech perception within the broader autism phenotype (BAP), which includes individuals with elevated, yet subclinical, levels of autistic traits. We investigate the neural indices of audiovisual speech perception in adults exhibiting a range of autism-like traits using event-related potentials (ERPs) in a phonemic restoration paradigm. In this paradigm, we consider conditions where speech articulators (mouth and jaw) are present (AV condition) and obscured by a pixelated mask (PX condition). These two face conditions were included in both passive (simply viewing a speaking face) and active (participants were required to press a button for a specific consonant–vowel stimulus) experiments. The results revealed an N100 ERP component which was present for all listening contexts and conditions; however, it was attenuated in the active AV condition where participants were able to view the speaker’s face, including the mouth and jaw. The P300 ERP component was present within the active experiment only, and significantly greater within the AV condition compared to the PX condition. This suggests increased neural effort for detecting deviant stimuli when visible articulation was present and visual influence on perception. Finally, the P300 response was negatively correlated with autism-like traits, suggesting that higher autistic traits were associated with generally smaller P300 responses in the active AV and PX conditions. The conclusions support the finding that atypical audiovisual processing may be characteristic of the BAP in adults.

The aim of this study is to describe a measured return to instrumental dysphagia assessments for our vulnerable surgical patient population, such that best practice patterns could be resumed and our staff kept safe from transmission of COVID-19. A retrospective medical record review provided data on clinical practice patterns of swallowing assessment in an at-risk surgical patient population. Outcomes of this study support protocols that allow clinicians to safely resume the use of instrumental assessment and return to best practice in dysphagia assessment for our surgical patient population.

Psychoeducation, where clinicians teach problem-solving skills in a supportive environment, can help address families’ social vulnerabilities and promote well-being. Group well-child care (GWCC) may provide unique opportunities for pediatric residents to improve their skills in psychoeducation. Our aim was to characterize pediatric residents’ perspectives and experiences of communication while conducting both individual well-child care and GWCC. We used a longitudinal qualitative study design to conduct 15 semistructured interviews with five pediatric residents who facilitated GWCC. Using the constant comparative method, we characterized pediatric residents’ perspectives and experiences of communication while conducting both individual well-child care and GWCC. Four themes emerged. Residents perceived that GWCC (i) enabled families to honestly share their knowledge and parenting practices, (ii) allowed time and a space for families to share personal stories and scenarios, (iii) facilitated discussions of maternal health and psychosocial matters, toward which residents felt ambivalence, and (iv) fostered skills in psychoeducation that transferred to the rest of their clinical practice. When pediatric residents lead GWCC, they perceive that they can facilitate key aspects of psychoeducation, enabling them to assist families in meeting complex social needs. Residents describe that they transfer psychoeducation skills learned in GWCC to the rest of their practice.

In modern-day computing, cloud services are widely used in every aspect of life. So, user satisfaction depends on the effectiveness and efficiency of cloud services. Service broker policy of the cloud maintains the effectiveness and efficiency of cloud services. Service broker policy provides the rules and norms based on which a data center is selected for a userbase request. This paper proposes a genetic algorithm-based service broker policy that provides the optimal sequence of data centers for different userbases based on their requirements. This research aims to find an optimal data center for userbases that can achieve user satisfaction by minimizing the cloud service's response time and data processing time. We have experimented with our proposed genetic algorithm-based service broker policy in the CloudAnalyst platform based on different real-world scenarios. Simulation results indicate that our proposed genetic algorithm outperforms existing traditional algorithms. © 2023 IEEE.

Impaired autonomic modulation and baroreflex sensitivity (BRS) have been reported during and after COVID-19. Both impairments are associated with negative cardiovascular outcomes. If these impairments were to exist undetected in young men after COVID-19, they could lead to negative cardiovascular outcomes. Fatigue is associated with autonomic dysfunction during and after COVID-19. It is unclear if fatigue can be used as an indicator of impaired autonomic modulation and BRS after COVID-19. This study aims to compare parasympathetic modulation, sympathetic modulation, and BRS between young men who had COVID-19 versus controls and to determine if fatigue is associated with impaired autonomic modulation and BRS. Parasympathetic modulation as the high-frequency power of R-R intervals (lnHFR-R), sympathetic modulation as the low-frequency power of systolic blood pressure variability (LFSBP), and BRS as the -index were measured by power spectral density analysis. These variables were compared between 20 young men who had COVID-19 and 24 controls. Independent t-tests and Mann-Whitney U tests indicated no significant difference between the COVID-19 and the control group in: lnHFR-R, P=0.20; LFSBP, P=0.11, and -index, P=0.20. Fatigue was not associated with impaired autonomic modulation or BRS. There is no difference in autonomic modulations or BRS between young men who had COVID-19 compared to controls. Fatigue did not seem to be associated with impaired autonomic modulation or impaired BRS in young men after COVID-19. Findings suggest that young men might not be at increased cardiovascular risk from COVID-19-related dysautonomia and impaired BRS.

COVID-19 has extensively reshaped lifestyle practices, supply chain dynamics, and climate mitigation efforts. The resulting crises from the pandemic in relation to local and community sustainability practices have not yet been investigated in depth. There is a need to explore the individual characteristics and responses from rapid transitions of lifestyles at various scales. Analysing how the COVID-19 pandemic has shaped and altered sustainable living practices, and the motivations supporting them, has yet to be determined but is crucial to gain further insight to improve management responses to large-scale disruptive change. Presenting empirical findings from semi-structured interviews in New Haven County, Connecticut, this study elucidates the ways in which the lifestyles have been altered and how they responded while specifically highlighting the consequences for behavioural routines and sustainable lifestyle practices. As a result of lockdowns and pandemic mitigation responses, individual sustainability engagement fluctuated with participants shifting dietary, mobility, and energy and food consumption patterns. Specifically, participants emphasised substantial decrease in daily travel during initial phases of the pandemic alongside increased online shopping and energy use at home. Though changes to consumption practices were replaced former habits with unsustainable ones, individuals also noted how they co-opted the pandemic over time to pursue sustainable actions at home. As a macro-level ‘window of opportunity’ and disruptive change, this study illustrates how sustainable lifestyle practices were reshaped; some by choice, some by force, and some reflecting a forced choice. These findings have clear implications for the stability of maintaining sustainable practices influenced by landscape-level shocks.

The HF method uses single determinant to solve Schrödinger equation and obtain molecular orbitals. A variety of post-HF methods such as MP2 and CCSD are needed to treat molecular systems in ground states accurately, while the CIS and EOM-CCSD methods are developed to study excited states. All these methods can write out wavefunction files in single determinant so that the unique electron density distributions of the system at all these calculation levels are available. The quantum theory of atoms in a molecule (QT-AIM) performs density topological analyses and rigorously obtain properties such as net atomic charges and delocalization and localization indices for ground states at HF/CIS and post-HF levels and for excited states at CIS, EOM-CCSD levels. The density functional theory (DFT) develops a larger number of functionals to account for the electron–electron correlation via exchange-correlation potentials, and TD-DFT methods study properties of electronically excited states. The DFT and TD-DFT methods rely on electron density to solve Schrödinger equations and write out final wavefunctions in single determinant format. Therefore, density-based analyses can be also done for a variety of DFT and TD-DFT methods. Along with molecular orbitals, density-based analyses are applied to explain ambident reactivity, to identify bonding characteristics in organic transition metal compounds, and to evaluate the performance of current DFT and TD-DFT methods. © 2023 Elsevier Inc. All rights reserved.

This chapter explores the case of President Bill Clinton and the Lewinsky scandal as a pivotal moment in the convergence of political, technological, and cultural changes that elevated the presence of gossip and rumor in mainstream news sources, with major, lasting consequences. Throughout the unfolding of the scandal, unconfirmed and often salacious information about what had happened was transmitted among individuals and amplified through the media. The chapter takes a close look at some key elements contributing to such trends, including use of anonymous sourcing, heightened competition between media outlets, and the emergence of new media actors covering American politics and the presidency. An analysis of two specific incidents, involving coverage of allegations there were eyewitnesses to the president’s affair with Monica Lewinsky and that Lewinsky had a dress stained with the president’s DNA in her possession, demonstrates how prominent national news outlets publicized information reflecting weaker reporting standards and conveyed unsubstantiated rumors as news. As the news media devalued itself in cases such as this one, abandoning professional conventions and prioritizing sensational, entertaining content, the public began to no longer trust or rely on such sources to help it interpret events. We continue to see the ramifications of those developments in the present, with widespread belief in fake news, little consensus on what constitute facts or reality, and stark partisan divides about who can be relied upon to transmit the truth of political events. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.