Study Directions For Future Research Research Articles

Recent Progress in the Development of Flexible Wearable Electrodes for Electrocardiogram Monitoring During Exercise

Electrocardiogram (ECG) monitoring has recently been an important indicator of cardiac health diagnosis. In the past, ECG could be measured under limited conditions in hospitals with 12‐lead electrode systems. Recently, portable and wearable devices have offered continuous, real‐time monitoring of ECG signals in real life. However, developing wearable ECG sensors that provide low‐motion artifacts and high‐quality signals during exercise conditions is still challenging. Herein, this review reports a systematic summary of the key characteristics, properties, and requirements of flexible wearable ECG devices for the early diagnosis of heart dysfunction in dynamic motions, including exercise. In addition, the recent progress in controlling sensor adhesion and novel materials for designing dry electrodes are discussed to improve ECG signal quality in exercise. Finally, various aspects of electrode developmental challenges and limitations are reviewed, and research directions for future studies are discussed.

Impacts of wireless charging system for electric vehicles on power grid

Electric Vehicles (EVs) have become a viable choice for cutting carbon emissions in the field of road transportation. EVs will be incorporated into the electrical grid at an increasing rate in the near future. EVs themselves are becoming immense power consuming load on the power grid system as a result of the growing number of EVs, mostly light-duty EVs. In addition to posing major technical risks such power quality issues, voltage swings, harmonic injection, battery deterioration, and grid instability, the unplanned installation and rapid adoption of charging stations might impede the smooth functioning of the power distribution system. Therefore, this paper analyzes and summarizes the potential issues and solutions for Fast Wireless Charging (FWC) that allows for the wireless transmission of very high-power levels (>20 kW) from the power grid to explore the impact of EV charging on the power system network. This need can have far-reaching effects on the load profile, operation, and design of the distribution network. In order to avoid exceeding the grid's technical restrictions, it is crucial to find the maximum feasible deployment level before rolling out an FWC network. This study provides a method for assessing how FWC technologies influence distribution networks. Using a realistic model of an Indian MV distribution feeder, the proposed methodology is used, providing both quantitative and qualitative results that serve as potential directions for future research studies.

Lead‐Free Perovskites and Metal Halides for Resistive Switching Memory and Artificial Synapse

Memristive devices such as resistive switching memories and artificial synapses have emerged as promising technologies to overcome the technological challenges associated with the von Neumann bottleneck. Recently, lead halide perovskites have drawn substantial research attention as the candidate material for memristors and artificial synapses due to their unique optoelectronic properties, solution processability, and mechanical flexibility. However, the toxicity of lead‐containing species has raised major concerns for health and the environment, which makes it crucial to transition from lead‐based to lead‐free materials for practical applications. Herein, the recent progress of lead‐free metal halides including perovskites and perovskite analogs for resistive memory and artificial synapse is reviewed. Initially, the fundamentals of lead‐free materials and switching mechanisms are introduced. Next, the material design, fabrication technique, and device performance are summarized and critically evaluated for each metal halide species. Finally, the challenges of the lead‐free metal halides toward memristors and artificial synapses are outlined and discussed, and some potential research directions for future study are proposed.

Deep learning approaches for seizure video analysis: A review

Seizure events can manifest as transient disruptions in the control of movements which may be organized in distinct behavioral sequences, accompanied or not by other observable features such as altered facial expressions. The analysis of these clinical signs, referred to as semiology, is subject to observer variations when specialists evaluate video-recorded events in the clinical setting. To enhance the accuracy and consistency of evaluations, computer-aided video analysis of seizures has emerged as a natural avenue. In the field of medical applications, deep learning and computer vision approaches have driven substantial advancements. Historically, these approaches have been used for disease detection, classification, and prediction using diagnostic data; however, there has been limited exploration of their application in evaluating video-based motion detection in the clinical epileptology setting. While vision-based technologies do not aim to replace clinical expertise, they can significantly contribute to medical decision-making and patient care by providing quantitative evidence and decision support. Behavior monitoring tools offer several advantages such as providing objective information, detecting challenging-to-observe events, reducing documentation efforts, and extending assessment capabilities to areas with limited expertise. The main applications of these could be (1) improved seizure detection methods; (2) refined semiology analysis for predicting seizure type and cerebral localization. In this paper, we detail the foundation technologies used in vision-based systems in the analysis of seizure videos, highlighting their success in semiology detection and analysis, focusing on work published in the last 7 years. We systematically present these methods and indicate how the adoption of deep learning for the analysis of video recordings of seizures could be approached. Additionally, we illustrate how existing technologies can be interconnected through an integrated system for video-based semiology analysis. Each module can be customized and improved by adapting more accurate and robust deep learning approaches as these evolve. Finally, we discuss challenges and research directions for future studies.

Risk Factors for Cognitive Impairment in Multiple Sclerosis Patients

Cognitive impairment is one of the most significant burdens among the many neurological complaints in multiple sclerosis patients. Cognitive deficits negatively impact these patients’ quality of life, leading to partial or total loss of several mental functions, such as learning, memory, perception, or problem-solving. While the precise mechanisms involved in the onset and evolution of cognitive decline remain unknown, several risk factors have been associated with intellectual disability. With increasing data on this topic in recent years, the main aim of this review is to summarize the most relevant risk factors correlated with cognitive impairment in multiple sclerosis patients. Firstly, the authors demonstrate the importance of mental disability based on epidemiological data from multiple sclerosis patient cohorts. Subsequently, the intensely debated major risk factors for cognitive decline are discussed, with brief insights into the pathophysiology and possible underlying mechanisms. Finally, the authors describe the impact of medication on cognitive impairment in multiple sclerosis patients, highlighting the main research directions for future studies.

Applications of data envelopment analysis in acute care hospitals: a systematic literature review, 1984-2022.

This study reviews scholarly publications on data envelopment analysis (DEA) studies on acute care hospital (ACH) efficiency published between 1984 and 2022 in scholarly peer-reviewed journals.We employ systematic literature review (SLR) method to identify and analyze pertinent past research using predetermined steps. The SLR offers a comprehensive resource that meticulously analyzes DEA methodology for practitioners and researchers focusing on ACH efficiency measurement. The articles reviewed in the SLR are analyzed and synthesized based on the nature of the DEA modelling process and the key findings from the DEA models. The key findings from the DEA models are presented under the following sections: effects of different ownership structures; impacts of specific healthcare reforms or other policy interventions; international and multi-state comparisons; effects of changes in competitive environment; impacts of new technology implementations; effects of hospital location; impacts of quality management interventions; impact of COVID-19 on hospital performance; impact of teaching status, and impact of merger. Furthermore, the nature of DEA modelling process focuses on use of sensitivity analysis; choice of inputs and outputs; comparison with Stochastic Frontier Analysis; use of congestion analysis; use of bootstrapping; imposition of weight restrictions; use of DEA window analysis; and exogenous factors. The findings demonstrate that, despite several innovative DEA extensions and hospital applications, over half of the research used the conventional DEA models. The findings also show that the most often used inputs in the DEA models were labor-oriented inputs and hospital beds, whereas the most frequently used outputs were outpatient visits, followed by surgeries, admissions, and inpatient days. Further research on the impact of healthcare reforms and health information technology (HIT) on hospital performance is required, given the number of reforms being implemented in many countries and the role HIT plays in enhancing care quality and lowering costs. We conclude by offering several new research directions for future studies.

A Review of the Effects of Urban and Green Space Forms on the Carbon Budget Using a Landscape Sustainability Framework

Urban areas and green spaces are significant atmospheric carbon sources and sinks. Spatial planning is crucial for improving the urban carbon budget. However, there are many uncertainties due to the diversity and complexity of the effects of urban and green space forms on the carbon budget. As a result, the role of urban areas and green spaces in emission reduction and carbon sink increases remains ambiguous. We use a landscape sustainability framework and systematically review the literature from 2002 to 2022 to elucidate the interaction between urban and green space forms and the carbon budget. We focus on regional and landscape scales. Nine landscape planning indicators affecting urban area carbon emissions, four indicators affecting green space carbon sinks, and three indicators affecting the urban–green space ecotonal relationship and the carbon budget are derived. We analyze the causes of the differences between the studies and discuss the influences of the indicators on emission reduction, carbon sink increases, and sustainable development. We summarize the design and research of urban and green spaces and the urban–green space ecotone and provide suggestions for carbon emission reduction, carbon sink increases, and research directions for future studies.

Isothiocyanates: happy-go-lucky reagents in organic synthesis.

Owing to their unique structural features, isothiocyanates (ITCs) are a class of highly useful and inimitable reagents as the -NCS group serves both as electrophile and nucleophile in organic synthesis. ITCs share a rich legacy in organic, medicinal, and combinatorial chemistry. Compared to their oxygen equivalents, isocyanates, ITCs are easily available, less unpleasant, and somewhat less harmful to work with (mild conditions) which makes them happy-go-lucky reagents. Functionalized ITCs can finely tune the reactivity of the -NCS group and thus can be exploited in the late-stage functionalization processes. This review's primary aim is to outline ITC chemistry in the construction and derivatization of heterocycles through the lens of sustainability. For ease and brevity, the sections are divided based on reactive centers present in functionalized ITCs and modes of cyclisation. Scrutinizing their probable unexplored directions for future research studies is also addressed.

Importance of Particular Groups of Objects in the Identification of Victims of the Katyn Massacre in the Case of Finds from Kharkiv

The researchers have been focused increasingly on war crime archaeology in recent years, e.g. the most significant until now scientific and logistic achievements which were archaeological-exhumation works carried out 30 years ago, related to searching for mass hidden graves of Polish officers, policemen and other civil servants murdered in spring of 1940 by NKVD in Katyn, Kharkiv and Mednoye. These were the first survey researches performed abroad on such a huge scale by Polish archaeologists. Obtained information concerning exact burial locations, the number of victims, burial ground sizes and final identification of the method and murder weapon which contributed to confirmation, verification and completion of our knowledge included in documents concerning the truth of The Katyn Massacre. Experience gained and excavation methodology of those mass graves exploration was presented and reported in detail in numerous publications (Głosek 1995; 2001; 2011; 2021; Kola 1995; 1996; 1998; 2001; 2005; 2021; Młodziejowski 1995) outlining cognitive possibilities and research directions for future studies and challenges. One of the most important tasks was the victims identification which was possible thanks to objects found with the bodies. This article objective is to present new obtained knowledge, using particular types of objects (personal movable property) and their systematization. Moreover, the article authoress, also working on the restoration of these objects and deciphering inscriptions placed on them, wanted to indicate particular object groups significance in the victims identification.

What Aspects Explain the Relationship between Digital Transformation and Financial Performance of Firms?

The emergence of digital transformation and digitization has significantly influenced business growth, particularly in response to the COVID-19 pandemic. This study conducts a systematic bibliometric analysis to investigate the relationship between digital transformation and firms’ financial performance. The primary objectives are identifying research gaps and proposing future research directions and policy implications. Specifically, we examine the evolution of digital transformation in companies and its impact on their financial performance, while highlighting the major trends in digital transformation research. Employing text mining techniques, network analysis, and a systematic literature review (SLR), we evaluated 153 articles published between 2014 and 2023. Our analysis delves into academic publication journals, geographical locations, authors’, and academic institutions’ contributions, assessing their influence on the existing literature’s development. Our findings indicate a current absence of a consistent theoretical framework in the scientific literature pertaining to the study of digital transformation and its effects on firms’ financial performance. Furthermore, we have pinpointed specific areas that warrant further investigation, including SMEs, non-listed companies, and intermediary or mediating variables. Finally, this systematic bibliometric analysis contributes to the ongoing discourse on digital transformation and its influence on firms’ financial performance, summarizing the current scientific research and proposing new research directions for future studies, while also offering valuable insights for researchers, policymakers, and practitioners.

Neighbourhood physical environment influences on children’s outdoor play: a systematic review

Children’s access to outdoor activities is restricted due to the continuous spread of urbanisation in public spaces. Therefore, figuring out how to improve outdoor physical space within the existing environment is becoming increasingly important. This study conducted a systematic review of 55 studies using PRISMA method to examine the link between the physical settings in neighbourhoods and children’s outdoor play. Through Scopus databases to provide a complete list of journal articles based on stringent inclusion and exclusion standards. Identify the gaps by categorising the significant themes and aspects influencing children’s play area requirements. Studies show that the physical environment of a neighbourhood is affected by several social factors besides the needs and preferences of children’s games. It was also found that the most commonly used research methods in children’s play spaces were survey and interview, and the Affordance Theory was widely used as a research framework. This research provides new design possibilities for children’s play areas in residential neighbourhoods. These guidelines emphasise games with varied spatial qualities, the integration of spatial functions, the additional support requirements of parents for children’s play, and the flexibility of children to utilise outside space. Consequently, this analysis identifies knowledge gaps and suggests research directions for future studies.

Pleasure Reading and the Role of Libraries: A Review of the Literature

Pleasure reading soothes mental stress and dispels boredom from hectic pressure. A considerable number of studies have been conducted worldwide regarding pleasure reading. The purpose of this study is to conduct a state-of-art review of pleasure reading. This review also covers the role of libraries for promoting pleasure reading to set up the potential research directions for future studies. The analysis and findings suggest that pleasure reading possess positive effect on following aspects - academic achievement, meta-cognition, self-realization, achieving potential quality, career enhancement and so on. From the reviewed literature it is observed that libraries and library professionals with the help of researchers, practitioners, and policy makers can foster a shared culture to promote pleasure reading trend among the enthusiast readers community.

Supply Chain Management during a Public Health Emergency of International Concern: A Bibliometric and Content Analysis

A public health emergency of international concern, such as a pandemic, disrupts the normal operation of the global supply chain, which necessitates in-depth research on supply chain management. In this paper, we used bibliometric and content analysis to provide a systematic analysis of the supply chain industry from this background. The descriptive analysis provides insights into the publication growth trajectory, in terms of the contributing authors, countries, and subject categories, which presents an intuitive display of previous research. In addition, the existing research mainly covers three dimensions of supply chain disruption, strategies, and sustainability, which can be clustered into supply chain disruption, disruption recovery, reconfiguration, digital intelligence, optimization, and sustainability. By revisiting the supply chain industry, we explored the transformation of its characteristics in the pandemic, covering themes ranging from expansion to contraction, from traditional to digital intelligence, and from fragile to sustainability, which suggests potential research directions for future studies. This contributes to the further research of supply chain management during the pandemic and provides supply chain managers with a practical approach for dealing with supply chain disruption risks and improving supply chain sustainability in this context.

Leveraging digital capabilities toward a circular economy: Reinforcing sustainable supply chain management with Industry 4.0 technologies

Facing the challenges of globalisation and unpredictable shocks, manufacturers seek novel methods to maintain the sustainability of their supply chains. Adopting Industry 4.0 (I4.0) technologies facilitates sustainable supply chain management (SSCM) with the precise decision-making of supply chain activities and the realisation of circular development. However, according to the bibliometric analysis and systematic literature review of articles related to “SSCM”, few frameworks with I4.0 technologies are found to empower SSCM under circular economy (CE) logic. Thus, this article proposes a conceptual framework of I4.0 technologies-embedded SSCM, which takes advantage of five kinds of emerging digital technologies, including cloud services, artificial intelligence (AI), big data analytics (BDA), blockchain technology (BT), and internet of things (IoT). The CAB2IN framework is based on the technologies mentioned above alongside the design, manufacturing, delivering, using, and end-of-life stages of products and services to meet the requirements of reducing material usage, remanufacturing, reusing, and recycling. This paper's contribution lies in indicating the trends of SSCM in the era of Industry 4.0 and proposing CAB2IN to creatively establish the virtual side of circular SSCM, which leverages the data generated in each stage to assist sustainable decision-making. CAB2IN illuminates several research directions for future studies of digitalised SSCM under the perspective of CE. The case of Company S illustrates the application of CAB2IN in the healthcare supply chain. This paper also summarises insightful directions of digitalised SSCM under the proposed circular framework.

A critical analysis of the integration of blockchain and artificial intelligence for supply chain.

The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity. In particular, supply chain is one of the areas that have been shown to benefit tremendously from blockchain and AI, by enhancing information and process resilience, enabling faster and more cost-efficient delivery of products, and augmenting products' traceability, among others. This paper performs a state-of-the-art review of blockchain and AI in the field of supply chains. More specifically, we sought to answer the following three principal questions: Q1-What are the current studies on the integration of blockchain and AI in supply chain?, Q2-What are the current blockchain and AI use cases in supply chain?, and Q3-What are the potential research directions for future studies involving the integration of blockchain and AI? The analysis performed in this paper has identified relevant research studies that have contributed both conceptually and empirically to the expansion and accumulation of intellectual wealth in the supply chain discipline through the integration of blockchain and AI.

Seismic Hazard Assessment in Machine Foundation Design: A Review Study

This paper presents a comprehensive review of seismic hazard assessment in machine foundation design and highlights key research directions for future studies. The review includes a detailed analysis of existing literature, that covers a wide range of subjects associated with seismic analysis and design of machine foundations. It begins with an overview of the seismic hazard assessment evaluation procedure and the various factors that influence it, such as soil properties, machine stiffness, and earthquake excitation. Then it discusses the key challenges associated with the design and seismic analysis of machine foundations, including the impact of dynamic loads and soil-structure interaction. Following the analysis of the current research, the paper identifies several important research directions for future studies. These include the development of more accurate seismic hazard assessment methodologies, using sophisticated numerical modeling methods. The paper also emphasizes the need for more comprehensive experimental studies to validate the numerical models and better understand the behavior of machine foundations under seismic loads. In brief, the paper provides a comprehensive review of the current state of knowledge in seismic hazard assessment in machine foundation design and highlights the importance of future research to proceed in this field.

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.