Future Work Research Articles

From plate to profile: investigating the influence of dietary habits and inactive lifestyle on lipid profile in medical students at clerkship

BackgroundDietary habits have a strong association with body lipid levels and hyperlipidemia increases the risk of cardiovascular and metabolic diseases. Dietary habits have been a major concern among medical students due to busy schedules and demanding tasks. This study was designed to know the dietary habits and lifestyle of medical students and its association with their lipid profile.MethodsWe recruited 120 medical students at clerkship of the age of 18 and above. Weekly dietary habits were evaluated by an 18-item questionnaire. Five ml blood was drawn from the students and lipid profiles were measured at Dow Diagnostic Research and Reference Laboratory (DDRRL). Data was analyzed by SPSS V.22.ResultsWe found 70% of students were not involved in any physical activity throughout the week. Only 15.83% were following a regular diet plan. 65% of students were eating junk food for more than 3 days a week in their weekly diet. Moreover, 19.2%, 39.2%, 32.5%, and 25.84% of students were having their total cholesterol, triglycerides, HDL, and LDL levels above the optimum ranges respectively which were frequently found in students of final year (p < 0.05). There was high total cholesterol and LDL in males as compared to females (p value < 0.05). Total cholesterol and LDL were associated with skipped meal, use of junk food and carbonated drinks for more than 3 days a week (p < 0.05).ConclusionThere was a notable number of students with poor dietary habits, inactive lifestyle and lipid levels above the optimum ranges defined by American Heart Association (AHA) that have an association with dietary habits. This is alarming and can impact the health of future healthcare workers. There is a need to investigate the factors and remedies to help medical students to follow a healthy diet and a healthy lifestyle.

The nurse-led equitable learning framework for training programs: A framework to grow, bolster and diversify the nursing and public health workforce

BackgroundAddressing threats to the nursing and public health workforce, while also strengthening the skills of current and future workers, requires programmatic solutions. Training programs should be guided by frameworks, which leverage nursing expertise and leadership, partnerships, and integrate ongoing evaluation. Purpose statementThis article provides a replicable framework to grow, bolster, and diversify the nursing and public health workforces, known as the Nurse-led Equitable Learning (NEL) Framework for Training Programs. The framework has been applied by several multipronged, federally funded training programs led by investigators embedded in an academic nursing institution. MethodsThe NEL framework focuses on: (1) increasing equitable access to the knowledge, skills, and competencies needed to prepare a diverse workforce to deliver effective interventions; (2) fostering academic-practice linkages and community partnerships to facilitate the deployment of newly gained knowledge and skills to address ongoing and emerging challenges in care delivery; and (3) continuously evaluating and disseminating findings to inform expansion and replication of programs. ResultsTen programs using this framework have successfully leveraged $18.3 million in extramural funding to support over 1000 public health professionals and trainees. Longitudinal evaluation efforts indicate that public health workers, including nurses, are benefiting from the programs' workplace trainings, future clinicians are being rigorously trained to identify and address determinants of health to improve patient and community well-being, and educators are engaging in novel pedagogical opportunities to enhance their ability to deliver high quality public health education. ConclusionsTraining programs may apply the NEL framework to ensure that the nursing and public health workforces achieve equitable, sustainable growth and deliver high quality evidence-based care.

Penalizing the Hard Example But Not Too Much: A Strong Baseline for Fine-Grained Visual Classification.

Though significant progress has been achieved on fine-grained visual classification (FGVC), severe overfitting still hinders model generalization. A recent study shows that hard samples in the training set can be easily fit, but most existing FGVC methods fail to classify some hard examples in the test set. The reason is that the model overfits those hard examples in the training set, but does not learn to generalize to unseen examples in the test set. In this article, we propose a moderate hard example modulation (MHEM) strategy to properly modulate the hard examples. MHEM encourages the model to not overfit hard examples and offers better generalization and discrimination. First, we introduce three conditions and formulate a general form of a modulated loss function. Second, we instantiate the loss function and provide a strong baseline for FGVC, where the performance of a naive backbone can be boosted and be comparable with recent methods. Moreover, we demonstrate that our baseline can be readily incorporated into the existing methods and empower these methods to be more discriminative. Equipped with our strong baseline, we achieve consistent improvements on three typical FGVC datasets, i.e., CUB-200-2011, Stanford Cars, and FGVC-Aircraft. We hope the idea of moderate hard example modulation will inspire future research work toward more effective fine-grained visual recognition.

Project ChemicalBlooms: Collaborating with citizen scientists to survey the chemical diversity and phylogenetic distribution of plant epicuticular wax blooms.

Plants use chemistry to overcome diverse challenges. A particularly striking chemical trait that some plants possess is the ability to synthesize massive amounts of epicuticular wax that accumulates on the plant's surfaces as a white coating visible to the naked eye. The ability to synthesize basic wax molecules appears to be shared among virtually all land plants, and our knowledge of ubiquitous wax compound synthesis is reasonably advanced. However, the ability to synthesize thick layers of visible epicuticular crystals ("wax blooms") is restricted to specific lineages, and our knowledge of how wax blooms differ from ubiquitous wax layers is less developed. Here, we recruited the help of citizen scientists and middle school students to survey the wax bloom chemistry of 78 species spanning dicot, monocot, and gymnosperm lineages. Using gas chromatography-mass spectrometry, we found that the major wax classes reported from bulk wax mixtures can be present in wax bloom crystals, with fatty acids, fatty alcohols, and alkanes being present in many species' bloom crystals. In contrast, other compounds including aldehydes, ketones, secondary alcohols, and triterpenoids were present in only a few species' wax bloom crystals. By mapping the 78 wax bloom chemical profiles onto a phylogeny and using phylogenetic comparative analyses, we found that secondary alcohol and triterpenoid-rich wax blooms were present in lineage-specific patterns that would not be expected to arise by chance. That finding is consistent with reports that secondary alcohol biosynthesis enzymes are found only in certain lineages but was a surprise for triterpenoids, which are intracellular components in virtually all plant lineages. Thus, our data suggest that a lineage-specific mechanism other than biosynthesis exists that enables select species to generate triterpenoid-rich surface wax crystals. Overall, our study outlines a general mode in which research scientists can collaborate with citizen scientists as well as middle and high school classrooms not only to enhance data collection and generate testable hypotheses but also to directly involve classrooms in the scientific process and inspire future STEM workers.

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

Технология обучения иноязычной письменной коммуникации будущих работников водного транспорта

The research aims to develop and present an effective training technology that ensures high educational and professional results in foreign language written communication for future water transport workers. The paper considers the author’s technology for teaching future water transport workers written communication in a foreign (English) language. This technology consists of two components: an algorithm of educational activities for students to master foreign language written communication and a system of exercises aimed at developing various interrelated skills of written professional speech in a foreign language. The scientific novelty of the research lies in designing an original technological solution that implements the theoretical foundations of teaching foreign language professional written speech in the training of future water transport workers. As a result of the research, it has been found that the process of teaching foreign language written communication is based on the natural development of a person’s written speech skills in their native language, from imitating (copying) someone else’s text to independently producing a written foreign language message. At the same time, it has been proven that the effectiveness of the written communication process depends on students’ linguistic and speech skills, as well as their discursive, pragmatic, and sociocultural skills in professional written speech in a foreign language.

The Effect of Personality Traits of Healthcare Worker Candidates on their Attitudes Towards the Elderly

Background:: It is known that attitudes towards the elderly are an important variable affecting healthcare services. Considering the increasing trends of the population over 65 years in countries, it is important to determine the attitudes of future healthcare workers towards the elderly and to prepare them to serve in the health sector with activities that will lead to positive changes. In this direction, it is important to determine the effect of personality traits of prospective healthcare workers on their attitudes toward the elderly Methods:: The research was conducted using the “relational survey model”. The study was conducted with 581 prospective healthcare workers. Personal Information Form, Eysenck Personality Questionnaire, and Kogan's Scale of Attitudes towards the Elderly were used as data collection tools. Data were obtained and analyzed using the online data collection method. Results:: According to the results of the study, it was found that the attitudes of students who were healthcare candidates for older adults were generally positive ( = 63.46±13.42). While there was a positive yet moderate and statistically significant correlation between attitudes towards the elderly and scores on the Extraversion subscale (r= 0.634, p&lt;0.01) and a negative yet moderate and statistically significant correlation with scores on the Neuroticism (r= -0.568, p&lt;0.01) and Psychoticism (r= -0.602, p&lt;0.01) subscales. The personality traits extraversion, neuroticism, and psychoticism explained 58.6% of the attitude towards the elderly. According to the regression results, extraversion (β= 0.358; p&lt;0.001) positively affected attitudes towards the elderly, whereas neuroticism (β= -0.310; p&lt;0.001) and psychoticism (β= -0.307; p&lt;0.001) negatively affected attitudes towards the elderly. Conclusions:: Given the important role of healthcare professionals in improving the care and quality of life of the elderly, it is necessary to develop strategies to improve the attitudes of future healthcare professionals towards the elderly. Consideration of personality traits in determining these strategies may contribute to the development of effective and personalized approaches.

Do religious and cultural considerations militate against body donation? An overview and a Christian perspective.

The development of anatomy as a scientific undertaking appears to have left little room for religious and cultural input into the conduct of anatomical investigations. This has been brought to the fore by questionnaires regarding the willingness or otherwise of individuals to donate their bodies for dissection, with higher levels of willingness from those without religious affiliations. This has led to the assumption that there is inherent opposition to body donation by those with a religious stance, although there has been little exploration of this. This is increasingly important with growing awareness that anatomy is an international discipline, leading to increasing attention to the religious and cultural contexts within which it is practiced. There is a diversity of responses toward body donation within different countries, as well as by those influenced by Islam, Hinduism, and Buddhism. Additionally, there are diverse cultural attitudes within Confucianism in Asia, Zulu in Africa, and Māori in New Zealand. Even those within the Christian church are influenced by a variety of values, some of which are in tension, with emphasis on the sacredness of life and the significance of burial being negative toward body donation, with informed consent and altruism pointing in a positive direction. The challenge for anatomists is to understand those within their communities, seek to appreciate their perspectives, and also make known the potential of body donation and dissection for enhancing medical practice and improving the education of future health workers.

Exploring evidence selection with the inclusion network

Abstract Although systematic reviews are intended to provide trusted scientific knowledge to meet the needs of decision-makers, their reliability can be threatened by bias and irreproducibility. To help decision-makers assess the risks in systematic reviews that they intend to use as the foundation of their action, we designed and tested a new approach to analyzing the evidence selection of a review: its coverage of the primary literature and its comparison to other reviews. Our approach could also help anyone using or producing reviews understand diversity or convergence in evidence selection. The basis of our approach is a new network construct called the inclusion network, which has two types of nodes: primary study reports (PSRs, the evidence) and systematic review reports (SRRs). The approach assesses risks in a given systematic review (the target SRR) by first constructing an inclusion network of the target SRR and other systematic reviews studying similar research questions (the companion SRRs) and then applying a three-step assessment process that utilizes visualizations, quantitative network metrics, and time series analysis. This paper introduces our approach and demonstrates it in two case studies. We identified the following risks: missing potentially relevant evidence, epistemic division in the scientific community, and recent instability in evidence selection standards. We also compare our inclusion network approach to knowledge assessment approaches based on another influential network construct, the claim-specific citation network, discuss current limitations of the inclusion network approach, and present directions for future work.

Exploiting Blockchain to Make AI Trustworthy: A Software Development Lifecycle View

Artificial intelligence (AI) is a very powerful technology and can be a potential disrupter and essential enabler. As AI expands into almost every aspect of our lives, people raise serious concerns about AI misbehaving and misuse. To address this concern, international organizations have put forward ethics guidelines for constructing trustworthy AI (TAI), including privacy, transparency, fairness, robustness, accountability, and so on. However, because of the black-box characteristics and complex models of AI systems, it is challenging to translate these guiding principles and aspirations into AI systems. Blockchain, an important decentralized technology, can provide the capabilities of transparency, traceability, immutability, and secure sharing and hence can be used to make AI trustworthy. In this paper, we survey studies on blockchain-based TAI (BTAI) from a software development lifecycle view. We classify the lifecycle of BTAI into four stages: Planning, data collection, model development, and system deployment/use. Particularly, we investigate and summarize the trustworthy issues that blockchain can achieve in the latter three stages, including (1) data transparency, privacy, and accountability; (2) model transparency, privacy, robustness, and fairness; and (3) robustness, privacy, transparency, and fairness of system deployment/use. Finally, we present essential open research issues and future work on developing BTAI systems.

A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges

Graph Neural Networks (GNNs) perform well in community detection and molecule classification. Counterfactual Explanations (CE) provide counter-examples to overcome the transparency limitations of black-box models. Due to the growing attention in graph learning, we focus on the concepts of CE for GNNs. We analysed the SoA to provide a taxonomy, a uniform notation, and the benchmarking datasets and evaluation metrics. We discuss fourteen methods, their evaluation protocols, twenty-two datasets, and nineteen metrics. We integrated the majority of methods into the GRETEL library to conduct an empirical evaluation to understand their strengths and pitfalls. We highlight open challenges and future work.

Protocol for identifying and characterising critical physical tasks in the military: Development and validation.

When establishing Physical Employment Standards, validity is dependent on the correct identification and characterisation of critical job tasks. To develop and validate a standardised protocol for the identification, characterisation, and documentation of critical physical job tasks in military occupational specialities in the Swedish Armed Forces (SwAF), and propose a definition of critical physical job tasks for use in the SwAF. A protocol was drafted with three content domains, including a preliminary definition. Protocol content validity was iteratively assessed in two consecutive stages where ten subject experts rated relevance and simplicity. A consensus panel revised the protocol after each stage. Content validity index (CVI) was calculated as item-CVI (I-CVI) per each feature and as scale average (S-CVI/Ave) per content domain. Acceptable content validity thresholds were 0.78 and 0.90, respectively. The validated protocol consisted of 35 items with an I-CVI≥0.90 and≥0.80 for relevance and simplicity, respectively. The S-CVI/Ave was 0.97 for relevance and 0.98 for simplicity. The protocol was language reviewed, reorganised for easy use, and approved by the consensus panel. The final protocol includes: background and aim of the protocol, the accepted generic and critical physical job task definitions, protocol instructions, subject expert-qualifications, job task source and characteristics. A standardised protocol for identification and characterisation of critical job tasks in SwAF military occupational specialties was developed. The protocol content was rated relevant and simple by experts and will be of importance in future work establishing physical requirements in the SwAF.

Explainable Reinforcement Learning: A Survey and Comparative Review

Explainable reinforcement learning (XRL) is an emerging subfield of explainable machine learning that has attracted considerable attention in recent years. The goal of XRL is to elucidate the decision-making process of reinforcement learning (RL) agents in sequential decision-making settings. Equipped with this information, practitioners can better understand important questions about RL agents (especially those deployed in the real world), such as what the agents will do and why. Despite increased interest, there exists a gap in the literature for organizing the plethora of papers—especially in a way that centers the sequential decision-making nature of the problem. In this survey, we propose a novel taxonomy for organizing the XRL literature that prioritizes the RL setting. We propose three high-level categories: feature importance, learning process and Markov decision process, and policy-level. We overview techniques according to this taxonomy, highlighting challenges and opportunities for future work. We conclude by using these gaps to motivate and outline a roadmap for future work.

Pemutusan Hubungan Kerja bagi Pekerja

Workers or laborers have the right to obtain protection for safety and health, morals and decency, as well as treatment in accordance with human dignity and religious values. Termination of Employment is one of the problems in employment that often occurs. Termination of employment causes anxiety because it has a negative impact on the survival and future of workers and their families. As an effort to protect workers or laborers affected by Termination of Employment, in 2021 the Government issued a new policy, namely Government Regulation Number 37 of 2021 concerning the Implementation of the Job Loss Guarantee Program. This research aims to find out and analyze the Job Loss Guarantee program and its implementation in Karawang Regency. This research uses a normative legal research method by examining theories, concepts, legal principles and statutory regulations related to this research. The Job Loss Guarantee Program is provided to workers or laborers affected by Termination of Employment in the form of cash benefits, career counseling benefits, job training benefits, and job market information benefits. This guarantee program came into effect in Karawang Regency on February 11 2022 a year after the regulations were issued with the number of participants who have claimed benefits during 2022 amounting to 683 participants and the total funds disbursed amounting to IDR. 1,385,714,400.00. However, the implementation of this guarantee program in Karawang Regency is still not optimal because there are several technical problems in the benefit claim process

Exploring the role of hedonic emotions on attitudinal loyalty and EWOM: a contingency framework and propositions

ABSTRACT Hedonists actively pursue events that elicit emotional pleasure and enjoyment. This study investigates the complex role and importance of consumers’ hedonic emotions in post-purchase behaviors within the context of fine-dining experiences. Prior research has mainly neglected emotions in favor of cognitive responses. Given the high rate of customer turnover in the restaurant industry, further research is necessary to fully understand the topic. This study’s research methodology is based on a thorough analysis of scholarly existing literature, namely journal articles. It presents a review of methodological views, illustrates key trends and limitations in prior empirical research, and emphasizes the need to construct a research framework. To guide future empirical work, a conceptual framework for certain hedonic emotions, namely comfort, sentimentality, and stimulation, and their impact on attitudinal loyalty and the E-WOM relationship, is introduced. To the best of our knowledge, this is the first attempt to critically analyze and synthesize multiple dimensions of hedonic emotions in the context of fine-dining restaurant services. We also presented several research propositions concerning the moderating effects of experiential and psychological factors on domain linkages. This study can aid restaurant managers in choosing vital marketing and communication strategies to enhance the food service industry, particularly in fine dining establishments.

Proximal Policy Optimization With Time-Varying Muscle Synergy for the Control of an Upper Limb Musculoskeletal System

Because of their unique adaptability, flexibility, and robustness, musculoskeletal robotic systems are regarded potentially as next-generation robots. However, motion learning and generation of such a robotic system are still challenging. This paper presents a neuromuscular control method, namely, TMS-PPO, based on time-varying muscle synergy (TMS) and proximal policy optimization (PPO). The electromyogram (EMG) activation signals of actual human motions are decomposed to obtain TMSs based on the temporal properties of the TMS. The weights of networks are trained to generate the scale and phase coefficients through the PPO. The coefficients modulate the TMSs to generate appropriate activation patterns to optimize motion learning of the musculoskeletal system. To verify the effectiveness of the proposed method, the TMSs are extracted from human upper limb muscle activation signals, and we compare TMS-PPO with PPO in the motion learning and generation process of an upper limb musculoskeletal system. The results show that TMS-PPO can complete the control tasks because the average errors of the joints are less than 0.05 rad. In the meantime, TMSs are used as motion primitives of the musculoskeletal system to simulate the process of the human CNS controlling muscles. It shows that TMS-PPO reduces the energy consumption and improves the learning rate significantly compared with the PPO. The learning episodes reduce from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">\(10^4\)</tex-math> </inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">\(10^3\)</tex-math> </inline-formula> , which indicates that TMS-PPO has a stronger learning ability and better physiological explanation. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Due to the superiorities of the musculoskeletal system, humanoid robots that imitate human driven mechanisms are vigorously carried out worldwide. Taking advantages of human-like characteristics, the musculoskeletal robot provides new opportunities to understand and validate the human mechanisms of muscle control and motion learning, to compare the performance of the robot to that of humans as well as work in real world, e.g., human interactive robots, amusement robots and medical training robots in the future. However, strong redundancy, coupling, and nonlinearity of the system also raises many challenges for the investigation of the control problem. Inspired by how the human CNS controls a musculoskeletal system and realize motion generalization, a novel muscle-synergies-based neuromuscular control that combines time-varying muscle synergy (TMS) and Proximal Policy Optimization (PPO), namely, TMS-PPO is proposed in this paper. The learning efficiency of PPO and the physiological interpretation of the control process are improved during the motion learning and generation processes of the musculoskeletal system. Preliminary simulation experiments suggest that this method is feasible in terms of control accuracy and efficiency. Moreover, the performance of the TMS-PPO is comparable to the PPO without significant improvement. To solve this problem, in future work, we will introduce the cerebellar model into the control method which plays the role of adjusting and correcting the motions of the limbs to achieve accurate and stable control in the actions process of humans.

Surveillance for Selected Pathogens and Parasites of Northern Bobwhite (Colinus virginianus) from Western Oklahoma, USA, 2018-20.

The Northern Bobwhite (Colinus virginianus) has been undergoing a range-wide population decline. Potential causes for declines across its historic range have been investigated for decades and include habitat loss and fragmentation and a variety of parasitic and infectious diseases. Although there have been studies on bobwhite ecology in Oklahoma, USA, relatively little is known about parasites and pathogens in the region. We evaluated the health of free-ranging bobwhites from nine sites in western Oklahoma. From 2018 to 2020, 206 bobwhites were evaluated for gross and microscopic lesions and tested for selected pathogens. In general, bobwhites were in good nutritional condition with ample muscle mass and fat stores. No significant gross lesions were observed in any bobwhite and no significant histologic lesions were detected in a subset. There was no evidence of infection with or exposure to reticuloendotheliosis virus, West Nile virus, respiratory Mycoplasmataceae species, Pasteurella multocida, intestinal Eimeria spp., or oral Trichomonas spp. Several pathogens of potential concern were detected, including avian adenovirus (8.6%), Toxoplasma gondii (2.3%), and haemosporidians (a Haemoproteus sp. (1.5%), Leucocytozoon schoutedeni (1.5%), and Plasmodium homopolare haplotype 2 [lineage LAIRI01; 3.6%]). Physaloptera sp. (12%) and Sarcocystis sp. (1%) were detected in the breast muscle. Low intraspecific genetic diversity was noted for Physaloptera sp., and sequences were most similar to Physaloptera sequences from bobwhites and grasshoppers (Orthoptera) in Texas. Low intensities of chewing lice, chiggers, and ticks were observed. A subset of bobwhites had evidence of exposure to selected toxicants and heavy metals; a small number had low levels of iron, manganese, zinc, molybdenum, and copper, which were not considered diagnostically relevant. In general, bobwhites from western Oklahoma appeared to be in good health with a low diversity of pathogens detected, but future work is needed to understand potentially changing disease risks for this population.

Innovative learning methods of Islamic education subject in Indonesia: a meta-analysis

This study aimed to evaluate the effects of innovative learning methods in the Islamic education (ISE) subject on learning motivation, learning activity, and learning achievement of students in the elementary and secondary schools in Indonesia. This study employed the meta-analysis method which is among the quantitative research approach. There were 47 literatures that eligible to be included in the database. Results revealed that, for the learning motivation variable, effect size value in the form of odds ratio was significantly higher than 1.0 (average 3.008 [2.020-4.480]; P&amp;lt;0.001). For the learning activity variable, effect size value was significantly higher than 1.0 (average 2.905 [2.113-3.994]; P&amp;lt;0.001). For the learning achievement variable, effect size value was significantly higher than 1.0 (average 4.941 [4.136-5.903]; P&amp;lt;0.001). These indicated that innovative learning methods were able to elevate learning motivation, activity and achievement. There were no significant differences among the categories within most of the sub-groups, except for the sub-group of cycle, in which cycle 2 showed higher learning achievement than that of cycle 1 (P&amp;lt;0.05). It can be concluded that innovative learning methods are able to elevate learning motivation, learning activity, and learning achievement of students at elementary and secondary schools to study the Islamic education subject. Future work should address the interaction between each particular innovative learning method and the ISE specific topic.

Adaptive Set-Membership Filter Based Discrete Sliding Mode Control for Pneumatic Artificial Muscle Systems With Hardware Experiments

Pneumatic artificial muscle (PAM), featuring good flexibility and safety, has been widely used in rehabilitation and bionic robots. However, the complex hysteretic nonlinearities and uncertainties of the PAM cause great difficulties and challenges to the accurate modeling and controller design, especially when confronted with unknown external disturbances in applications. This paper proposes a robust control strategy with disturbance compensation for the hysteresis compensation and trajectory tracking of PAMs. Considering the high hysteretic nonlinearity of the PAM, a modified Prandtl-Ishlinskii model is used as a feedforward hysteresis compensator. For the linearized system, adaptive set-membership filtering (ASMF) is used to estimate the nonlinear terms and external disturbances of the overall system. A sliding mode controller (SMC) with disturbance compensation is designed and cascaded to the feedforward hysteresis compensator in series. The stability of the closed-loop system is theoretically proved. The proposed method guarantees that the tracking error of the PAM system is bounded. Finally, the effectiveness and robustness of the proposed controller are verified via a series of experiments on an in-house built testbench for PAMs. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —With the increasing demand on human-robot interaction, the safety and compliance of robots have become one key requirement. PAM is a compliant actuator, exhibiting good flexibility, safety, and clean energy. PAM is widely used in rehabilitation robots, whereas its strong hysteresis nonlinearity and sensitivity to external disturbances affect its motion accuracy. This paper proposes an ASMF-based discrete SMC, which uses an inverse hysteresis model to compensate for the strong hysteresis of the PAM and uses ASMF to estimate the lumped disturbance of the system. Compared with the other filters, ASMF is unique in that its estimation error is bounded, which is very useful in the stability proof of the overall system. The effectiveness of the proposed controller is experimentally verified. Experimental results show that PAM’s hysteresis can be efficiently compensated, and the influence of external disturbances can be attenuated by the proposed controller, resulting in improved motion accuracy and robustness. In future work, efforts will be directed towards the modeling and control of PAMs in multi-DOF robots.

Physical Activity Dependence on Relative Temperature and Humidity Characteristics in a Young, Insufficiently Active Population: A Weather Typing Analysis.

Physical activity (PA) is an important contributor to one's physical and mental health both acutely and across the lifespan. Much research has done on the ambient environment's impact on PA; however, these studies have used absolute values of atmospheric measures such as temperature and humidity, which vary spatiotemporally and make comparisons between studies which differ in location or time of year difficult to square with one another. Here, we employ the Global Weather Type Classification, Version 2, to determine the combined impact of temperature and humidity on PA in a sample of insufficiently active young adults. We conducted secondary analyses of data from a single-group behavioral intervention trial that varied the number of digital messages sent daily. Young adults (n = 81) wore Fitbit Versa smartwatches for a 6-month period sometime between April 2019 and July 2020, and location was tracked using a custom smartphone application. Mixed linear models indicated that, across 8179 person-days, PA was significantly lower on days with humid conditions and significantly higher on warm dry days, though the latter relationship was no longer significant when controlling for timing in relation to the COVID-19 pandemic declaration. Demographic factors did not affect the relationship between weather and PA. Results are a first step in providing additional guidance for encouraging PA in insufficiently active individuals given forecasted daily weather conditions. Future work should examine seasonal variability in the weather type-PA relationship without the influence of a world-altering event influencing results.