Research Opportunities Research Articles

“Assessment Of Cardiac Autonomic Dysfunction In Children With Cerebral Palsy Using Heart Rate Variability”

Background: Cardiac autonomic imbalance in children with CP might be due to primary brain insult, vary with different levels of Gross Motor Functional Classification System or may alter with multimodal therapies in various types of cerebral palsy (1,2) . It is important to understand and to create awareness that autonomic impairment in children with CP is in part due to sedentary lifestyle (3).HRV(Heart Rate Variability) in cerebral palsy is recognized as an important tool for monitoring cardiovascular health, in which autonomic imbalance is characterized by reduced HRV (i.e. regarded as increased cardiac sympathetic activity and decreased vagal modulation) (4,5) . Of the research that does exist, each study discusses only very few parameters of the autonomic nervous system, thus providing opportunities for further research and hence the need for the study. Materials and Methods: This is a cross-sectional case control study of 51 children with Cerebral Palsy (CP) and 51 normal children, conducted at District Early Intervention Centre (DEIC) in the Department of Paediatrics, Vani Vilas hospital. These 51 cases were assessed and classified based on their demographic features, etiology, type of CP, GMFCS scale and with the objectives of assessing the heart rate variability (HRV) in children with cerebral palsy and compare it with controls in both supine position and after a stress test, and also to correlate the obtained parameters with GMFCS level, type of CP using a systematically designed proforma. Results: Results of the study showed that of the children with CP studied, 62% were male children, and majority of were between 6-8 years of age (58%), and it was found that the most common etiology for CP in our study was due to perinatal asphyxia (43%), and 80% of the children had history of NICU admission. Of the 51 cerebral palsy children studied 72% were in GMFCS levels 3 and 4, regarding the topographical classification majority had spastic quadriplegia (58.8%) followed by spastic diplegia (15.7%). Study revealed that cerebral palsy children had significantly lower HRV, higher sympathetic activity, autonomic response deficit to stress test, and higher autonomic dysfunction when compared to normal children. Among cases, HRV was lowest with spastic quadriplegia and triplegic CP, in functional classification HRV was lowest among GMFCS 4 and 3. Conclusion: Cerebral palsy children had significantly higher sympathetic activity and less cardiac vagal modulation compared to normal children in supine position and there was existence of autonomic response deficit in cerebral palsy children after stress test, higher the motor impairment, higher was the sympathetic activity

Modeling the significance of corporate social responsibility on green capabilities and sustainability performance

This study examines the complex interplay among corporate social responsibility (CSR), green dynamic capabilities, green innovation capabilities, and organizations' economic, environmental, and social performance in the current era of innovation and sustainability. The proposed framework was tested using data from 634 medium- and large-sized Chinese manufacturing firms. Partial least squares structural equation modeling was employed to analyze the data. The findings demonstrate that CSR to external and internal stakeholders positively influences green dynamic capabilities. Meanwhile, CSR to external stakeholders and green dynamic capabilities are positively associated with green innovation capabilities, subsequently influencing the economic, environmental, and social performance of manufacturing firms. Moreover, the results reveal the mediating effect of green dynamic capabilities on the association between CSR and green innovation capabilities. Green innovation capabilities also mediate the association between CSR to external stakeholders and green dynamic capabilities on manufacturing organizations’ economic, environmental, and social performance. This study offers a novel exploration of the intricate interplay among CSR, green dynamic capabilities, green innovation capabilities, and organizational performance within manufacturing organizations. These findings provide valuable insights for managers and offer opportunities for further research that will ultimately contribute to a deeper understanding of the roles of sustainability and innovation in modern corporations.

Application of simulation and machine learning in supply chain management: A synthesis of the literature using the Sim-ML literature classification framework

Stochastic modeling techniques, such as discrete-event and agent-based simulation, are widely used in supply chain management (SCM) for capturing real-world uncertainties. Over the last decade, data-driven approaches like machine learning (ML) have also gained prominence in SCM, employing methods such as supervised learning (SL), unsupervised learning (UL), and reinforcement learning (RL). As supply chains grow in complexity, hybrid models combining simulation (Sim) and ML are becoming increasingly common, and the field stands to gain from a structured review of this literature. Towards this, we developed the Sim-ML Literature Classification Framework, which includes a hierarchical taxonomy comprising five SC criteria, 22 Sim-ML classes and over 75 Sim-ML subclasses. We applied this framework to synthesize 99 papers, revealing significant diversity in how Sim-ML models are used to address supply chain challenges. Key findings include the recognition of the breadth of study objectives, identifying various forms of model hybridization achieved by combining discrete/continuous simulation techniques with SL, UL, and RL approaches, and the data flow mechanisms such as sequential and feedback methods employed by the simulation and ML elements of the hybrid model. Our findings also identify some gaps in the literature; for example, optimization is rarely incorporated into Sim-ML models. Also, most studies present Sim-ML models for addressing problems in general supply chains, likely due to the lack of access to industrial data. The review also highlights that Industry 4.0 technologies, such as digital twins and blockchain, are underrepresented in current research, as are topics like sustainability and transportation. These gaps suggest significant opportunities for future research. We provide guidelines for practitioners on applying Sim-ML models to manage supply chain drivers, mitigate the impact of disruptions, and integrate emerging technologies. Our review serves as a valuable resource for researchers, practitioners, and students interested in leveraging Sim-ML approaches in SCM.

A Canadian national study of provincial and territorial correctional workers' suicidal ideation, plans, and attempts.

Correctional workers (CWs) endure several operational stressors (e.g., exposures to potentially psychologically traumatic events) and organisational stressors (e.g., shift work, staff shortages), which are associated with positive screens for mental disorders and self-reports of suicidal behaviours and thus urgently warrant further inquiry. The Canadian Provincial and Territorial Correctional Worker Mental Health and Well-Being Study (CWMH) used an online survey to collect data from Canadian correctional service organisations across all 13 provinces and territories. This national Canadian study investigates suicidal behaviours among CWs across diverse occupational roles and provincial and territorial jurisdictions (n=3740, 50.1% female). The results estimated prevalence proportions for self-reported past-year and lifetime suicidal thoughts, planning, and attempts across the 13 Canadian provincial and territorial correctional systems, with the exceptions of past-year suicidal planning in Alberta, Newfoundland and Labrador, New Brunswick, and Yukon where jurisdictional considerations and requests precluded the inclusion of select questions. Substantial proportions of participants reported past-year or lifetime suicidal ideation (i.e., 9.1%, 29.2%, respectively), planning (i.e., 4.1%, 14.7%, respectively), or attempts (i.e., 0.8%, 7.2%, respectively). Sociodemographic variables (i.e., sex, age, marital status, total years of service, occupational category) were associated with past-year and lifetime suicidal behaviours. Findings provide opportunities for future research and can inform tailored efforts by clinicians, service providers, and organisational leaders to support proactive interventions and treatments, including supporting the partners and families of CWs, fostering social support networks, and improving access to timely mental health treatment.

Charged-particle transport in high energy density plasmas

This Special Topic Collection grew out of two gatherings of researchers active in the high energy density (HED) physics community: a mini-conference on charged-particle transport in HED plasma held during the 64th annual meeting of the American Physical Society's Division of Plasma Physics (Spokane, WA, November 2022) and a dedicated charged-particle transport coefficient code comparison workshop (Livermore, CA, July 2023). These gatherings provided opportunities for theoretical, computational, and experimental researchers to discuss the state of the field, including current capabilities and methods, needs of hydrodynamic simulations, and frontiers for future research. This special issue collects a total of 13 research and review articles on charged-particle transport in HED plasmas.

Individual preferences in multiple goal pursuit: Reconsidering the conceptualization and dimensionality of polychronicity

AbstractWith increasing demands in work and life, successful self‐regulation of multiple goals becomes critical to the well‐being and performance of individuals and organizations. When pursuing multiple goals, individuals may use different strategies and have divergent preferences toward these strategies. Polychronicity, or the preference for multitasking over sequential tasking, has long been considered a unidimensional construct with two opposing ends. To empirically test this assumption, we reconstructed existing polychronicity items to explore a new scale that measures preferences separately and synthesizes different operationalizations of multitasking (i.e., concurrent tasking and task switching) (study 1). We found that multitasking and sequential preferences, while related, have distinct components and can co‐occur within individuals, challenging the traditional bipolar assumption (study 2). Finally, we used a behavioral task‐switching paradigm to simulate a multitasking environment. We found that consistent with past research, the preferences were not associated with behavioral performance but were associated with subjective experience (study 3). Our findings suggest that assuming multitasking and sequential preferences are completely antithetical can be an oversimplification. This research opens opportunities for future research on multiple goals.

Should an acute palliative care unit be mandatory for cancer centers and tertiary care hospitals?

Acute palliative care units have been developing in the last years and their clinical activity and characteristics have been described, despite large differences in different countries. One controversial topic is whether such units should be mandatory as standard in comprehensive cancer centers or even in tertiary hospitals. In this "Controversies in Palliative Care" article, three expert clinicians independently answer this question. Specifically, each group provides a synopsis of the key studies that inform their thought processes, share practical advice on their clinical approach, and highlight the opportunities for future research. Interestingly, all three experts arrived at similar conclusions. They underscored the importance of an acute palliative care unit, which provides a different pattern of activities in comparison with typical inpatient hospices, generally caring for patients who have a limited expected survival.

Statistics in Phonetics

Phonetics is the scientific field concerned with the study of how speech is produced, heard, and perceived. It abounds with data, such as acoustic speech recordings, neuroimaging data, or articulatory data. In this article, we provide an introduction to different areas of phonetics (acoustic phonetics, sociophonetics, speech perception, articulatory phonetics, speech inversion, sound change, and speech technology), an overview of the statistical methods for analyzing their data, and an introduction to the signal processing methods commonly applied to speech recordings. A major transition in the statistical modeling of phonetic data has been the shift from fixed effects to random effects regression models, the modeling of curve data (for instance, via generalized additive mixed models or functional data analysis methods), and the use of Bayesian methods. This shift has been driven in part by the increased focus on large speech corpora in phonetics, which has arisen from machine learning methods such as forced alignment. We conclude by identifying opportunities for future research.

Role of Occupational Therapy Assessment and Office Ergonomics to Support Students with Accommodations in Higher Learning: A Narrative Review

Postsecondary students with disabilities (SWDs) face significant challenges to their academic and personal well-being. There is a demand for more supportive strategies to facilitate fulfilling and equitable academic experiences for SWDs. This review aimed to (1) determine the effectiveness of various interventions, programs, and accommodations for enhancing the overall well-being of postsecondary SWDs and (2) evaluate the implications of these support strategies for disability service providers at postsecondary institutions. A narrative review was conducted, examining 13 studies aimed at enhancing the well-being of postsecondary SWDs. Studies were classified using the International Classification of Functioning, Disability and Health (ICF) Model. Ergonomics, assistive technology, and counselling programs had positive improvements on the academic success of SWDs. In SWDs, health status was associated with higher community participation, and physical interventions were beneficial to reducing pain over time. Coaching and mentoring opportunities were beneficial for successful goal fulfilment. However, there remains a risk of digital eye strain when using technology to support postsecondary SWDs. The findings indicate that a range of support strategies can benefit several different components of SWDs experiences. This review identifies research gaps and opportunities to examine support strategies to improve the physical and mental well-being of SWDs.

Analysis of Computational Bibliometric Mapping in Multimedia for Art Learning Media Publications using VOSviewer

This research explores the development of fine arts learning media using interactive multimedia research. The goal can be a reference for researchers in conducting and defining research themes, especially around multimedia learning. The method is used through a bibliographic approach with computational mapping analysis using VOSviewer. Article data is retrieved from the Google Scholar database using a publish-or-perish reference management application. Article titles and abstracts serve as guidelines when searching for keywords like "art," "learning media," and "multimedia." We found 447 seemingly related articles. The study period used as learning material is a paper from the last five years (2018 to 2023) indexed by Google Scholar. The results of research on fine arts learning media using interactive multimedia can be classified into four terms. The first term "Training" belongs to cluster 2 with a total of 34 links, an overall link strength of 138, and 59 events. The second term, "Media", belongs to cluster 2, with a total of 30 links, an overall connection strength of 142, and 74 events. The third term, "Multimedia", belongs to cluster 2, with a total of 27 links, an overall connection strength of 110, and 55 events. The fourth term "art" belongs to cluster 1 with a total of 34 links, an overall link strength of 138 and 59 events. From 2018 to 2020, the survey found research fluctuations in several media-based art learning media studies (65, 110, and 124 publications per year, respectively). The number of studies decreased from 44 (2021) to 16 (2023) from 2021 to 2023. Thus, there are still many opportunities for researchers to discuss it.

Introduction

The challenges presented by the Covid-19 pandemic forced individuals to become more inward looking. To facilitate a process of reflection and stimulate and re-energize research within the research community, the guest editors of this special issue planned and implemented an online conference. This Conference served as a platform for researchers from various parts of the world can share initiatives that have enabled or challenged community transformation. It also provided an opportunity for researchers to connect with financial agencies, recognizing that funding is critical during both the research and implementation phases of any recommendations.

Orthopedic research productivity of KSA: First bibliometric analysis

PurposeMedical research is a crucial indicator of a nation's reputation and development. However, there are concerns about the limited orthopedic research in Kingdom of Saudi Arabia (KSA). Therefore, this study conducted bibliometric analysis to investigate orthopedic research output from KSA. MethodsPubMed database for orthopedic articles, with a minimum of one KSA-affiliated orthopedic author published from the year 2000 onwards, was searched. This excluded duplicate articles, corrections, letters, editorials, commentaries, and brief communications. The titles of the included articles, publication years, first and corresponding authors' primary affiliations and countries, countries and institutes of research, and total citations were noted. Thereafter, year-wise research contribution, top contributing and collaborating nations, top contributing affiliations, study types, levels of evidence, journal distribution, their impact factor, h-index and quartile-related information, and citation trends were analyzed. ResultsThe search strategy yielded 1047 eligible articles. An increasing trend in research contributions in recent years was observed, with the least number of articles (8) contributed in 2005 and the most (140) in 2023. The research was conducted in KSA for most articles (83.48%). Authors from Canada collaborated in 3.44% of the articles. King Saud University was the top contributing institution (17.38% of all articles). There were 66 (6.30%) basic science studies and 873 (83.3%) clinical studies. Among non-basic science studies, 84.51% had level IV evidence. Overall, 73.83% of articles had either first/corresponding or both authorships from KSA-affiliated orthopedic authors. The eligible articles were published in 303 journals, with a mean impact factor of 3.04 (range 0.4-51.1, 165 journals) and a mean h-index of 59.2 (range 1-367, 277 journals). Overall, 31.23% of articles with quartile information available were published in first-quartile journals. ConclusionsThe orthopedic research productivity in KSA is limited. However, there has been an increasing trend in orthopedic research in recent years. Nevertheless, the quality of clinical research, particularly the level of evidence, needs improvement. Therefore, further efforts should be made to strengthen research opportunities and encourage research participation among orthopedic and medical institutes.

Engineering implementation of permanent magnet uniform spreading system for 3 MeV electron beam accelerator

Electron radiation technology, a significant application of non-power civil nuclear technology, opens up various research opportunities for electron beam accelerators as radiation sources. This paper introduces the engineering implementation of a permanent magnet uniform spreading system for the 3 MeV electron beam accelerator. The system is designed to improve radiation homogeneity, which is a crucial performance parameter in the radiation processing. The paper firstly investigates the collimation of magnets and beam spot in electron beam accelerators and proposes a novel collimation method. In addition, we also address various engineering implementation challenges encountered during the practical application of the uniform spreading system's permanent magnet devices. As a prerequisite for the application of uniform spreading system, a long-term stability experiment is conducted on the permanent magnets in radiation environments. The engineering feasibility of the uniform spreading system is ultimately verified by assessing the radiation homogeneity at the target using radiation dose tablets.

Parental involvement in students’ mathematics activities: A bibliometric analysis

This study is focused on investigating parental involvement in students’ mathematical activities. It presents a comprehensive bibliometric analysis that examines new areas of research to discover current trends and future research opportunities related to parental involvement in their children’s mathematics activities. This study intends to provide a meaningful contribution toward enhancing educational interventions in the future. The metadata of the publications included in this analysis was extracted from the Scopus and ERIC databases using the search criteria “(parent OR parent) AND (involvement OR support) AND (math or math) AND student.” After the screening step, a comprehensive analysis was conducted on a total of 944 articles using the tools Harzing’s Publish or Perish 8, Biblioshiny, and VOSviewer 1.6.20. The findings indicated that studies on this topic covered 42 years and accumulated a total of 17,392 citations. The most prolific year in terms of publications was 2023, with a peak of 80 studies published. The leading contributors to this body of research were Jianzhong Xu and James Reed Campbell, each authoring six papers. The keyword mapping results revealed several interesting research avenues for future investigation, such as the incorporation of psychological interventions, longitudinal studies, multidisciplinary approaches, and the utilization of technology.

Applications of knowledge distillation in remote sensing: A survey

With the ever-growing complexity of models in the field of remote sensing (RS), there is an increasing demand for solutions that balance model accuracy with computational efficiency. Knowledge distillation (KD) has emerged as a powerful tool to meet this need, enabling the transfer of knowledge from large, complex models to smaller, more efficient ones without significant loss in performance. This review article provides an extensive examination of KD and its innovative applications in RS. KD, a technique developed to transfer knowledge from a complex, often cumbersome model (teacher) to a more compact and efficient model (student), has seen significant evolution and application across various domains. Initially, we introduce the fundamental concepts and historical progression of KD methods. The advantages of employing KD are highlighted, particularly in terms of model compression, enhanced computational efficiency, and improved performance, which are pivotal for practical deployments in RS scenarios. The article provides a comprehensive taxonomy of KD techniques, where each category is critically analyzed to demonstrate the breadth and depth of the alternative options, and illustrates specific case studies that showcase the practical implementation of KD methods in RS tasks, such as instance segmentation and object detection. Further, the review discusses the challenges and limitations of KD in RS, including practical constraints and prospective future directions, providing a comprehensive overview for researchers and practitioners in the field of RS. Through this organization, the paper not only elucidates the current state of research in KD but also sets the stage for future research opportunities, thereby contributing significantly to both academic research and real-world applications.

Immersive Technology in Education

ABSTRACTImmersive technologies like virtual reality (VR) and augmented reality (AR) are transforming higher education by providing engaging, experiential learning opportunities. However, their integration into educational practices presents challenges, including high costs, technological complexity, and the digital divide. This panel explores the application of immersive technologies in higher education, focusing on developing an immersive technology lab designed to support their adoption across the institution. The discussion will cover global perspectives on immersive learning, showcasing varied adoption rates and strategies across different regions. Additionally, the panel will highlight research opportunities in immersive education, emphasizing the need for studies on effective integration, impact on learning outcomes, and strategies to overcome barriers to adoption. The goal is to identify sustainable approaches to expose staff and students to immersive technologies, ensuring equitable opportunities for all stakeholders.

Understanding exercise (in)tolerance in sickle cell disease: impacts of hemolysis and exercise training on skeletal muscle oxygen delivery.

Sickle cell disease (SCD) is characterized by central (cardiac) and peripheral vascular dysfunctions, significantly diminishing exercise capacity and quality of life. Although central cardiopulmonary abnormalities in SCD are known to reduce exercise capacity and quality of life; the impact of hemolysis and subsequent cell-free hemoglobin (Hb)-mediated peripheral vascular abnormalities on those outcomes are not fully understood. Despite the recognized benefits of exercise training for cardiovascular health and clinical management in chronic diseases like heart failure, there remains substantial debate on the advisability of regular physical activity for patients with SCD. This is primarily due to concerns that prolonged and/or high-intensity exercise might trigger metabolic shifts leading to vaso-occlusive crises. As a result, exercise recommendations for patients with SCD are often vague or nonexistent, reflecting a gap in knowledge about the mechanisms of exercise intolerance and the impact of exercise training on SCD-related health issues. This mini-review sheds light on recent developments in understanding how SCD affects exercise tolerance, with a special focus on the roles of hemolysis and the release of cell-free hemoglobin in altering cardiovascular and skeletal muscle function. Also highlighted here is the emerging research on the therapeutic effects and safety of exercise training in patients with SCD. In addition, the review identifies future research opportunities to fill existing gaps in our understanding of exercise (in)tolerance in SCD.

Tunable valley states in two-dimensional ScBr2

Effective manipulation of valley degrees of freedom can offer significant opportunities for both fundamental research and practical applications. In this work, based on the first-principles calculations, we, respectively, studied the modulation of the valley states of the two-dimensional (2D) ferrovalley material ScBr2 in its bilayers and multiferroic heterostructures. The sliding ferroelectricity is found in ScBr2 bilayers, and the ferroelectric polarization is coupled with valley polarization, which can enable the switching of layer-polarization anomalous Hall effect. The switching of magnetic ground states can also be achieved through layer sliding. On the other hand, the reversal of the ferroelectric polarization of Ga2S3 in the ScBr2/Ga2S3 heterojunction can induce a semiconductor to half-metal phase transition, thereby enabling control of the anomalous valley Hall effect for “on” and “off” states. Our work provides two effective ways to manipulate the valley states in 2D materials.

Direct implementation of AI-Based Facial Recognition for ITSI students

The development of artificial intelligence (AI)-based facial recognition technology has become a significant research topic in the field of computing and security. At the Indonesian Palm Oil Institute (ITSI), AI-based facial recognition is introduced to students to improve their skills in developing AI-based applications. This study aims to implement and test a facial recognition system using a Python program by utilizing a dataset generated independently. This research method involves several stages, namely collecting ITSI students' facial data, data processing, creating a facial recognition model using a machine learning algorithm, and evaluating model performance. The dataset used was developed through a live shooting session involving active student participation. The facial recognition model was trained using a convolutional neural network (CNN) algorithm that was optimized to improve accuracy. The results of the study showed that the developed model was able to achieve high facial recognition accuracy, with an average accuracy rate of 92%. The discussion includes an analysis of factors that affect accuracy, such as variations in lighting and shooting angles, as well as the potential use of this technology in a campus environment, including for attendance and security purposes. The conclusion of this study shows that the implementation of AI-based facial recognition can be effectively applied in an academic environment, as well as providing students with practical experience in developing and testing AI applications. This study also opens up opportunities for further research on improving the performance of facial recognition systems and their application in various real-world scenarios.

Addressing Class Imbalance of Health Data: A Systematic Literature Review on Modified Synthetic Minority Oversampling Technique (SMOTE) Strategies

The Synthetic Minority Oversampling Technique (SMOTE) method is the baseline for solving unbalanced data problems. The working concept of the SMOTE method is to generate new synthetic data patterns by performing linear interpolation between minority class samples based on k-nearest neighbors. However, the SMOTE method has weaknesses, namely the problem of overgeneralization due to excessive sampling of sample noise and increased overlapping between classes in the decision boundary area, which has the potential for noise data. Based on the weaknesses of the Smote method, the purpose of this research is to conduct a systematic literature review on the Smote method modification approach in solving unbalanced data. This systematic literature review method comprises keyword identification, article search process, determination of selection criteria, and selection results based on criteria. The results of this study showed that the SMOTE modification approach was based on filtering, clustering, and distance modification to reduce the resulting noise data. The filtering approach removed the noise data before SMOTE, positively impacting resolving unbalanced data. Meanwhile, the use of a clustering approach in SMOTE can minimize the overlapping artificial minority data that has noise potential. The most used datasets are Pima 60% and Haberman 50%. The most used performance evaluation on unbalanced data is f1-measure 57%, accuracy 55%, recall 43%, and AUC 27%. The implication of the results of this literature review is to provide opportunities for further research in modifying SMOTE in addressing health data imbalances, especially handling noise and overlapping data. The thoroughness of our literature review should instill confidence in the research community.