Study Directions For Future Research Research Articles

Effects of parenting styles on young children’s social skills

The family is the basic environment in which young children live and is the main vehicle for their socialization. Parenting styles, as the consistent style of parenting demonstrated by parents in the family, impact the child’s mental health and social skills development to some extent. Social skills are important skills that young children acquire and use appropriately through positive interactions with adults and peers and are widely used in their social interactions and adaptation to social life. This paper categorizes parenting styles, generalizes the social skills of young children, and examines the effects of parenting styles on young children’s social skills from both positive and negative perspectives. As a representative of positive parenting styles, the democratic parenting style was positively associated with and positively predicted the development of social skills; coddling, permissive, authoritarian, and inconsistent parenting styles were negatively associated with and negatively predicted the development of social skills. This paper proposes recommendations to promote the development of social skills in young children, such as popular science lectures in schools and parent meetings, parents improving their parenting knowledge, and fathers increasing their involvement in parenting, hoping to help parents learn more about scientific parenting and apply it in practice, and to provide research directions for future studies.

A bibliometric study on blockchain-based supply chain: a theme analysis, adopted methodologies, and future research agenda.

The emergence of the underlying blockchain technology of bitcoin has gained extensive attention from researchers and practitioners. As distributed ledger technology, blockchain widely finds its applications in the supply chain to mitigate issues related to transparency, information sharing, process efficiency, and traceability. This study employed a knowledge-based visualization technique to create a vision beyond other review studies on the blockchain-based supply chain. We used bibliometric and network analysis to synthesize the previous literature. In total, 431 articles in the timespan of 2017 to April 2022 from Scopus and Web of Science (WOS) databases were analyzed after applying search string, inclusion, and exclusion criteria. Basic information was extracted from initial data screening; then, data was analyzed on the grounds of co-occurrence, bibliographic coupling, citation, co-authorship, and co-citation analysis. In addition, thematic analysis was performed to analyze the content of the previous studies, adopted research methods, and dynamic industries in the literature. Besides all these, we identified various research gaps and proposed research directions for future study. We believe that this study provides adequate knowledge to academic scholars and supply chain practitioners to fast-track the current research in the supply chain domain using blockchain technology.

Advances in Materials, Sensors, and Integrated Systems for Monitoring Eye Movements.

Eye movements show primary responses that reflect humans' voluntary intention and conscious selection. Because visual perception is one of the fundamental sensory interactions in the brain, eye movements contain critical information regarding physical/psychological health, perception, intention, and preference. With the advancement of wearable device technologies, the performance of monitoring eye tracking has been significantly improved. It also has led to myriad applications for assisting and augmenting human activities. Among them, electrooculograms, measured by skin-mounted electrodes, have been widely used to track eye motions accurately. In addition, eye trackers that detect reflected optical signals offer alternative ways without using wearable sensors. This paper outlines a systematic summary of the latest research on various materials, sensors, and integrated systems for monitoring eye movements and enabling human-machine interfaces. Specifically, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, sensor functions, systems' performances, and their applications in eye tracking. Finally, we discuss the remaining challenges and suggest research directions for future studies.

Advances in Biosignal Sensing and Signal Processing Methods with Wearable Devices

AbstractWearable devices have received significant attention recently for their ability to monitor critical physiological signals noninvasively, such as electrocardiography, electroencephalography, electromyography, and photoplethysmography. These bio‐integrated wearable systems can potentially fill gaps in conventional clinical practice by providing highly cost‐effective health characterization and portable continuous health monitoring. Further, the physiological signals measured by wearables require post‐processing to derive meaningful values, such as heart rate or blood oxygen saturation. This requirement, in conjunction with the smaller form factor and limited sensor count of the miniaturized systems, often necessitates robust signal processing and data analysis to approach the stringent performance specifications of conventional medical devices, and machine learning techniques have found success in filling this analytical role for their ability to learn complex functional relationships. Thus, this review outlines a systematic summary of the latest research on various wearable devices and their biosignal sensing and signal processing methods, emphasizing machine learning. We also discuss the developmental challenges and advantages of current machine‐learning methods, while suggesting research directions for future studies.

Scarcity in today´s consumer markets: scoping the research landscape by author keywords

Scarcity refers to not having enough of what one needs. This phenomenon has shaped individuals´ life since ancient times, nowadays ranging from daily-life scarcity cues in shopping scenarios to the planet’s resources scarcity to meet the world´s consumer demand. Because of this ubiquity of scarcity, the topic has been attracting attention from scholars and practitioners in different areas. Studies regarding scarcity were conducted across disciplines, based on different assumptions, and focused on distinct study subjects. A lack of mainstream about this topic hindered the convergence of core ideas among different schools of thought. In this article, we take an integrative socio-economic perspective to join diverse findings on scarcity affecting consumer markets, identify topic-specific research questions still to be answered, and provide suggestions for future and integrative research opportunities. A systematic review based on author keywords from 855 publications analyzing scarcity affecting business-consumer interactions serves as a database. Exploratory factor analyses based on author keywords identify shared patterns within and linkages across discourses stemming from various disciplines and theories. Results differentiate distinct research foci in the consumer behavior, socio-political, and other disciplinary research realms. A mapping of these research themes identifies the scarcity-related interplay among consumers, producers, and other stakeholders. Findings point out research directions for future studies at both the research realm level and the interdisciplinary level.

Medical instrument detection in ultrasound: a review

Medical instrument detection is essential for computer-assisted interventions, since it facilitates clinicians to find instruments efficiently with a better interpretation, thereby improving clinical outcomes. This article reviews image-based medical instrument detection methods for ultrasound-guided (US-guided) operations. Literature is selected based on an exhaustive search in different sources, including Google Scholar, PubMed, and Scopus. We first discuss the key clinical applications of medical instrument detection in the US, including delivering regional anesthesia, biopsy taking, prostate brachytherapy, and catheterization. Then, we present a comprehensive review of instrument detection methodologies, including non-machine-learning and machine-learning methods. The conventional non-machine-learning methods were extensively studied before the era of machine learning methods. The principal issues and potential research directions for future studies are summarized for the computer-assisted intervention community. In conclusion, although promising results have been obtained by the current (non-) machine learning methods for different clinical applications, thorough clinical validations are still required.

Scientific Knowledge of Rheumatoid Arthritis: A Bibliometric Analysis from 2011 to 2020.

BackgroundRecently, research on rheumatoid arthritis (RA) has made rapid progress and grown rapidly. It is a challenge to comprehensively understand RA research and hotspots. The aim of this study was to explore the current status and research trends of RA through bibliometric analysis and to provide directions for future development.MethodsPublications on RA from 2011 to 2020 were retrieved from the Web of Science Core Collection database (WoSCC). VOSviewer, CiteSpace and online bibliometric platform were used to analyze publication characteristics, including countries, institutions, journals, authors, core references, and keywords.ResultsA total of 17,037 publications were included. The publications steadily increased over the 10 years. The United States (3648 publications), with the largest proportion of publications and citations, was the largest contributor. Karolinska Institutet (508) and Annals of the Rheumatoid Disease (763) were the most active institution and journal, respectively. Emery P (193) and Tanaka Y (193) were the most prolific authors, and Smolen JS ranked first among the cited authors. The most cited reference focused on recommendations for the management of RA with synthetic and biological disease-modifying antirheumatic drugs. A co-occurrence network analysis revealed four highly connected clusters of keywords in RA research, including etiology, pathology, prognosis, biomarkers and treatment of RA.ConclusionThe present study shows a systematic and comprehensive overview of the RA-related research in the past 10 years. Clinical trials on the long-term efficiency and safety of JAK inhibitors and other novel targeted drugs may be the potential research directions for future study in this field.

Circular economy practices in the waste electrical and electronic equipment (WEEE) industry: A systematic review and future research agendas

Circular economy is a sustainable economic development model. It replaces the traditional economic development model that relies heavily on resource consumption and waste generation. Circular economy is particularly important to the waste electrical and electronic equipment industry as e-waste contains toxic substances and precious metals. While previous review studies focused on specific aspects of the WEEE industry (e.g., “4R” circular economy strategies), these studies offer little details on how circular economy practices affect the development of the environment and economy in the waste electrical and electronic equipment industry. This study examines “10R” circular economy strategies to advance knowledge of the existing literature that focuses on “4R” circular economy strategies. To improve the methodology used in the previous review studies that apply subjective methods (e.g., content analysis), this paper conducts a systematic literature review on 208 studies and uses citation network analysis to examine specific circular economy practices in the waste electrical and electronic equipment industry. The citation network analysis identified five major research domains (i.e., “e-waste management systems and practices”, “e-waste legislation and its components”, “extended producer responsibility schemes”, “recycling critical materials from e-waste”, “circular economy strategies for the waste electrical and electronic equipment industry”). Based on these results, this study conducts a main path analysis to reveal ten major topics (i.e., e-waste recycling system; exploring untapped e-waste; compliance assurance of stakeholders; e-waste reverse logistics; reward and punishment mechanisms in extended producer responsibility system; verifying the rationality of product classification; recycling critical materials from urban mines; setting a specific target for preparation for reuse; “10R” strategies applied in the smart factory; consumer attitude toward remanufactured/refurbished/repurposed strategies and the resultant products) in the identified research domain. Finally, this paper proposes future research directions and provides managerial and policy implications for researchers and practitioners. • “10R” strategies for the waste electrical and electronic equipment industry. • Effect of circular economy practices on environmental and economic performance. • Related publications evolution characteristics in 2003–2020. • Five key research domains of circular economy practices and their major topics. • Research directions for future studies.

A Comprehensive Review on Multilevel Inverters for Grid-Tied System Applications

Multi-level inverters (MLIs) have been widely used in recent years due to their various advantages in industrial and grid-connected applications. Traditional MLI topologies are being hampered by the rapid surge of renewable energy systems (RES) as a result of performance difficulties such as poor power reliability, an economically unviable structure, and a lack of efficiency. These difficulties are due to the traditional MLI topologies’ inability to keep up with the increasing demand for RES. Because of concerns about performance and limitations posed by classic MLI topologies, researchers have found themselves driven to the idea of building innovative hybrid MLI topologies. This study provides a comprehensive analysis of multilevel inverter systems that are wired into the main power supply. Grid-connected inverter types and their configurations are discussed in depth in this review. Diverse multi-level inverter topologies, as well as the different approaches, are divided into various categories and discussed in depth. Additionally, a number of control reference frames for inverters were brought forward for discussion. Furthermore, different inverter control strategies were investigated, followed by a tabular summary of recent developments in the inverter-related literature for the convenience of the readers. Moreover, the recently proposed grid-connected multi-level inverter systems were discussed including their findings and innovations. In conclusion, a brief description of the study’s scope was offered and research directions for future studies were provided.

A review on the application of machine learning for combustion in power generation applications

Abstract Although the world is shifting toward using more renewable energy resources, combustion systems will still play an important role in the immediate future of global energy. To follow a sustainable path to the future and reduce global warming impacts, it is important to improve the efficiency and performance of combustion processes and minimize their emissions. Machine learning techniques are a cost-effective solution for improving the sustainability of combustion systems through modeling, prediction, forecasting, optimization, fault detection, and control of processes. The objective of this study is to provide a review and discussion regarding the current state of research on the applications of machine learning techniques in different combustion processes related to power generation. Depending on the type of combustion process, the applications of machine learning techniques are categorized into three main groups: (1) coal and natural gas power plants, (2) biomass combustion, and (3) carbon capture systems. This study discusses the potential benefits and challenges of machine learning in the combustion area and provides some research directions for future studies. Overall, the conducted review demonstrates that machine learning techniques can play a substantial role to shift combustion systems towards lower emission processes with improved operational flexibility and reduced operating cost.

A systemic review of Problem-Based Learning (PBL) and Computational Thinking (CT) in teaching and learning

Because of its educational benefits for both learners and teachers, Problem-Based Learning (PBL) and Computational Thinking (CT), teaching paradigms, and problem-solving methodologies have become widely used in teaching and learning. However, research on its integration into the teaching and learning process is still sparse, leaving educators with few guidelines for using constructive learning theory techniques. This study aims to thoroughly review and determine the country of application, learner level, PBL and CT dimensions, and learning methodologies that can lead to the successful implementation of PBL-CT. From 2017 to 2022, this study tracks relevant and published articles to identify gaps in the implementation of PBL-CT and maps their history into a taxonomy that can be used to guide future research. Limited study has yet been published that specifically describes the suitable PBL-CT framework or paradigm. Most articles deal with computing, followed by STEM (Science, Technology, Engineering, and Math) and non-STEM subjects. Some key implications can assist educators in developing effective PBL-CT lesson designs and provide some research directions for future studies. Effective PBL-CT integration improves learners' computational thinking skills while boosting teaching and learning. One of the 21st-century amplifications required for student success in CT

Advances in Soft and Dry Electrodes for Wearable Health Monitoring Devices.

Electrophysiology signals are crucial health status indicators as they are related to all human activities. Current demands for mobile healthcare have driven considerable interest in developing skin-mounted electrodes for health monitoring. Silver-Silver chloride-based (Ag-/AgCl) wet electrodes, commonly used in conventional clinical practice, provide excellent signal quality, but cannot monitor long-term signals due to gel evaporation and skin irritation. Therefore, the focus has shifted to developing dry electrodes that can operate without gels and extra adhesives. Compared to conventional wet electrodes, dry ones offer various advantages in terms of ease of use, long-term stability, and biocompatibility. This review outlines a systematic summary of the latest research on high-performance soft and dry electrodes. In addition, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, strategies to promote physical adhesion, methods for higher breathability, and their applications in wearable biomedical devices. Finally, we discuss the developmental challenges and advantages of various dry electrodes, while suggesting research directions for future studies.

Research on women in public administration: A systematic review of Chinese top journal publications (1987–2019)

The study of women has made significant progress in public administration research although little is known about its development in China. This article presents a systematic review of 222 studies on women published in the 15 representative journals in the Chinese public administration discipline since the 1980s. It addresses a set of key questions relevant to research on women by systematically examining the research paradigms, topics, methods, theories, and empirical research and clarify the shortcomings of existing research. Findings of the analysis and the international frontier progress then suggest the research directions for future studies on women. It proposes that Chinese scholars should critically examine international theories, propose diverse research topics, and use up-to-date methodologies.

A Review on Collaborative Robot Assembly Line Balancing Problems

Assembly line balancing problems have been the subject of numerous studies for decades. The recent advantages of technologies in the Industry 4.0 era and integrating collaborative robots into the assembly systems have created task allocation, workload balance, and scheduling challenges. This paper provides a brief literature review on the existing collaborative assembly line balancing problems comparing their main characteristics and suggests some research directions for future studies.

Recommendations for Reducing Heterogeneity in Handgrip Strength Protocols.

Handgrip dynamometers are widely used to measure handgrip strength (HGS). HGS is a safe and easy to obtain measure of strength capacity, and a reliable assessment of muscle function. Although HGS provides robust prognostic value and utility, several protocol variants exist for HGS in clinical settings and translational research. This lack of methodological consistency could threaten the precision of HGS measurements and limit comparisons between the growing number of studies measuring HGS. Providing awareness of the protocol variants for HGS and making suggestions to reduce the implications of these variants will help to improve methodological consistency. Moreover, leveraging recent advancements in HGS equipment may enable us to use more sophisticated HGS dynamometer technologies to better assess muscle function. This Special Article will 1) highlight differences in HGS protocols and instrumentation, 2) provide recommendations to better specify HGS procedures and equipment, and 3) present future research directions for studies that measure HGS. We also provided a minimum reporting criteria framework to help future research studies avoid underreporting of HGS procedures.

The Literature review of Influencing Factors of Chinese Youth with Character Disorders

As one of the frequent behavioral disorders among adolescents, the urgency of research on conduct disorder cannot be ignored. With the guide of ecological systems theory, this research summarizes and synthesizes four aspects: individual, family, school, and society, then points out the shortcomings and gaps of existing research, in order to provide references and new research directions for future studies.

Developments and Emerging Trends of Blended Learning: A Document Co-citation Analysis (2003–2020)

This study aims to analyze and visualize the research hotspots, evolution, and emerging trends of blended learning in a holistic way. In this study, 1657 biblio-metric records together with 48310 citations are collected from SCIE, SSCI and A&HCI databases. CiteSpace is adopted in the analysis and visualization. Results show: enhancing collaborative learning, pattern, and teacher training are the re-search hotspots in Period I, instructor perception, possible future direction, and research trend are the research hotspots in Period II, general science classroom, blended learning environment, and measuring student engagement are the re-search hotspots in Period III; the themes of covid-19 remain similar along the de-velopment, while the themes of digital health education change a lot; blended learning environment, online component, covid-19 pandemic, procrastinating be-havior, active blended learning, and observed learning orientation are the emerg-ing trends. These findings could provide research directions for future studies in blended learning.

Behavioral Decision Making in Normative and Descriptive Views: A Critical Review of Literature

Recent studies on decision analytics frequently refer to the topic of behavioral decision making (BDM), which focuses on behavioral components of decision analytics. This paper provides a critical review of literature for re-examining the relations between BDM and classical decision theories in both normative and descriptive reviews. We attempt to capture several milestones in theoretical models, elaborate on how the normative and descriptive theories blend into each other, thus motivating the mostly prescriptive models in decision analytics and eventually promoting the theoretical progress of BDM—an emerging and interdisciplinary field. We pay particular attention to the decision under uncertainty, including ambiguity aversion and models. Finally, we discuss the research directions for future studies by underpinning the theoretical linkages of BDM with fast-evolving research areas, including loss aversion, reference dependence, inequality aversion, and models of quasi-maximization mistakes. This paper helps to understand various behavioral biases and psychological factors when making decisions, for example, investment decisions. We expect that the results of this research can inspire studies on BDM and provide proposals for mechanisms for the development of D-TEA (decision—theory, experiments, and applications).

Understanding Complex Debris-Covered Glaciers: Concepts, Issues, and Research Directions

Understanding the climate-glacier dynamics of debris-covered glaciers is notoriously difficult given a multitude of controlling factors and feedback mechanisms involving climate forcing, debris-load properties, supraglacial water bodies, and multi-scale topographic effects. Recent studies have provided insights into controlling factors, and have reported the presence of anomalies that contradict the general consensus of the protective influence of debris loads on ablation dynamics. Nevertheless, numerous processes that regulate glacier dynamics at various spatial and temporal scales have not been adequately accounted for in statistical and numerical modeling studies. Furthermore, important feedbacks involving ablation, topography, irradiance, gravitational debris flux, and supraglacial ponding are often neglected or oversimplified in existing models, which poses a challenge to our understanding of conflicting field observations such as the accelerated mass loss of many Himalayan glaciers, and glacier-subsystem responses (ice-flow, debris flux, surface morphology, and supraglacial water bodies) to climate forcing. This paper provides insights into the complexity of debris-covered glacier systems by addressing concepts and issues associated with forcing factors and glacial processes, and highlights the importance of understanding system couplings and feedbacks. Specifically, we review recent studies on debris-covered glaciers and utilize simulation results based on the Baltoro Glacier in the central Karakoram to discuss important concepts and issues. Our results demonstrate that climate forcing, the properties and transport of debris, topography and supraglacial water bodies are the key controlling factors in a debris-covered glacier system, and that their coupled effects and positive feedbacks may increase the ice loss of a debris-covered glacier. We also recommend new research directions for future studies.

Blockchain-Enabled Applications in Next-Generation Wireless Systems: Challenges and Opportunities

Many emerging wireless applications are based on unique requirements such as edge data processing, distributed trust, and automation, which can be provided and enabled by blockchain technology through decentralization, transaction accountability, and smart contract-based automation. This article discusses opportunities and challenges of such blockchain-enabled wireless applications. First, blockchain technology and 5G system architecture are briefly reviewed. Then, an example wireless application use case is presented to illustrate the benefits that blockchain technology can bring to wireless applications. A set of pending research issues addressing some of the challenges faced by blockchain-enabled wireless applications is introduced. As a potential solution, a wireless blockchain middleware architecture (BlockWare) is proposed, based on a blockchain middleware layer connecting wireless applications and underlying blockchain infrastructure. The blockchain middleware layer interacts with various types of blockchain systems on behalf of different wireless applications. Thus, a wireless application does not need to implement complex blockchain functions, rather relying on the blockchain middleware layer and its services to leverage various underlying blockchain systems. This article also points out several research directions for future study, such as inter-blockchain interactions and interoperability, efficient blockchain transaction management, and blockchain-based messaging in future wireless systems such as 5G, beyond 5G, and 6G.