Future Research Directions Research Articles

Magnetic Ionic Liquids: Current Achievements and Future Perspectives with a Focus on Computational Approaches.

Magnetic ionic liquids (MILs) stand out as a remarkable subclass of ionic liquids (ILs), combining the desirable features of traditional ILs with the unique ability to respond to external magnetic fields. The incorporation of paramagnetic species into their structures endows them with additional attractive features, including thermochromic behavior and luminescence. These exceptional properties position MILs as highly promising materials for diverse applications, such as gas capture, DNA extractions, and sensing technologies. The present Review synthesizes key experimental findings, offering insights into the structural, thermal, magnetic, and optical properties across various MIL families. Special emphasis is placed on unraveling the influence of different paramagnetic species on MILs' behavior and functionality. Additionally, the Review highlights recent advancements in computational approaches applied to MIL research. By leveraging molecular dynamics (MD) simulations and density functional theory (DFT) calculations, these computational techniques have provided invaluable insights into the underlying mechanisms governing MILs' behavior, facilitating accurate property predictions. In conclusion, this Review provides a comprehensive overview of the current state of research on MILs, showcasing their special properties and potential applications while highlighting the indispensable role of computational methods in unraveling the complexities of these intriguing materials. The Review concludes with a forward-looking perspective on the future directions of research in the field of magnetic ionic liquids.

The Synergistic Effects of Preterm Birth and Parent Gender on the Linguistic and Interactive Features of Parent-Infant Conversations.

To investigate the language environments experienced by preterm-born infants, this study compared the linguistic and interactive features of parent-infant conversations involving 2-year-old preterm- and term-born infants. The study also explored how mother-infant and father-infant conversations may be differentially affected by preterm/term birth status. Twenty-two preterm-born (< 37 weeks' gestation) and 25 term-born (≥ 37 weeks' gestation) 2-year-old infants engaged in dyadic mother/father-infant free-play interactions that were transcribed to quantify the linguistic (parental volubility, speech rate, lexical diversity, and morphosyntactic complexity) and interactive (infant/parent responsiveness, turn-taking, and conversational balance) features of parent-infant conversations. Language, cognitive, socioemotional, and executive function skills were assessed via standardized tools. Compared to the term group, the preterm group was characterized by lower maternal speech rate, parental lexical diversity, and parent-infant turn-taking, as well as greater mother-infant conversational balance. The preterm group presented poorer language and executive function skills when compared to the term group. Both similarities and differences exist between the language environments of preterm and term groups. Similarities may be due to the partial developmental catch-up of preterm-born infants (cognitive and socioemotional skills) and parental scaffolding. Differences may partly reflect a parental adaptation to the language and executive function difficulties of preterm-born infants. These findings suggest that researchers/clinicians should appraise the language environment with respect to the unique developmental needs of preterm/term-born infants. Future research directions are provided to advance a more holistic characterization of the language environment and a deeper understanding of the developmental significance of preterm-term differences in such environments. https://doi.org/10.23641/asha.25021931.

Regulating Triplet Excitons of Organic Luminophores for Promoted Bioimaging.

Afterglow materials with organic room temperature phosphorescence (RTP) or thermally activated delayed fluorescence (TADF) exhibit significant potential in biological imaging due to their long lifetime. By utilizing time-resolved technology, interference from biological tissue fluorescence can be mitigated, enabling high signal-- to-background ratio imaging. Despite the continued emergence of individual reports on RTP or TADF in recent years, comprehensive reviews addressing these two materials are rare. Therefore, this review aims to provide a comprehensive overview of several typical molecular designs for organic RTP and TADF materials. It also explores the primary methods through which triplet excitons resist quenching by water and oxygen. Furthermore, we analyze the principal challenges faced by afterglow materials and discuss key directions for future research with the hope of inspiring developments in afterglow imaging.

Towards mmWave Altimetry for UAS: Exploring the Potential of 77 GHz Automotive Radars

Precise altitude data are indispensable for flight navigation, particularly during the autonomous landing of unmanned aerial systems (UASs). Conventional light and barometric sensors employed for altitude estimation are limited by poor visibility and temperature conditions, respectively, whilst global positioning system (GPS) receivers provide the altitude from the mean sea level (MSL) marred with a slow update rate. To cater to the landing safety requirements, UASs necessitate precise altitude information above ground level (AGL) impervious to environmental conditions. Radar altimeters, a mainstay in commercial aviation for at least half a century, realize these requirements through minimum operational performance standards (MOPSs). More recently, the proliferation of 5G technology and interference with the universally allocated band for radar altimeters from 4.2 to 4.4 GHz underscores the necessity to explore novel avenues. Notably, there is no dedicated MOPS tailored for radar altimeters of UASs. To gauge the performance of a radar altimeter offering for UASs, existing MOPSs are the de facto choice. Historically, frequency-modulated continuous wave (FMCW) radars have been extensively used in a broad spectrum of ranging applications including radar altimeters. Modern monolithic millimeter wave (mmWave) automotive radars, albeit designed for automotive applications, also employ FMCW for precise ranging with a cost-effective and compact footprint. Given the technology maturation with excellent size, weight, and power (SWaP) metrics, there is a growing trend in industry and academia to explore their efficacy beyond the realm of the automotive industry. To this end, their feasibility for UAS altimetry remains largely untapped. While the literature on theoretical discourse is prevalent, a specific focus on mmWave radar altimetry is lacking. Moreover, clutter estimation with hardware specifications of a pure look-down mmWave radar is unreported. This article argues the applicability of MOPSs for commercial aviation for adaptation to a UAS use case. The theme of the work is a tutorial based on a simplified mathematical and theoretical discussion on the understanding of performance metrics and inherent intricacies. A systems engineering approach for deriving waveform specifications from operational requirements of a UAS is offered. Lastly, proposed future research directions and insights are included.

Conflict Avoidance in Social Navigation—a Survey

A major goal in robotics is to enable intelligent mobile robots to operate smoothly in shared human-robot environments. One of the most fundamental capabilities in service of this goal is competent navigation in this “social” context. As a result, there has been a recent surge of research on social navigation; and especially as it relates to the handling of conflicts between agents during social navigation. These developments introduce a variety of models and algorithms, however as this research area is inherently interdisciplinary, many of the relevant papers are not comparable and there is no shared standard vocabulary. This survey aims at bridging this gap by introducing such a common language, using it to survey existing work, and highlighting open problems. It starts by defining the boundaries of this survey to a limited, yet highly common type of social navigation—conflict avoidance. Within this proposed scope, this survey introduces a detailed taxonomy of the conflict avoidance components. This survey then maps existing work into this taxonomy, while discussing papers using its framing. Finally, this article proposes some future research directions and open problems that are currently on the frontier of social navigation to aid ongoing and future research.

Opportunities and challenges for gas coproduction from coal measure gas reservoirs with coal‐shale‐tight sandstone layers: A review

AbstractThe extraction of coal measure gas has been shifted toward thin gas reservoirs due to the depletion of medium‐thick gas reservoirs. The coproduction of coalbed gas, shale gas, and tight sandstone gas (called a multisuperposed gas system) is a key low‐cost technology for the enhancement of natural gas production from thin gas reservoirs in coal measure. As an emerging engineering exploitation technology at its early stage of development, gas coproduction confronts various engineering challenges in hydraulic fracturing, bottom‐hole pressure regulation, well network arrangement, and extraction sequence. The current understanding of the opportunities and challenges in the gas coproduction from the multisuperposed gas system is not comprehensive enough. In this case, the previous achievements in the field of gas coproduction should be urgently reviewed to provide valuable guidance and recommendations for further development. This review first discusses the regional and spatial distribution characteristics and possible reservoir combinations of gas reservoirs in coal measure. Then, the basic properties of different reservoirs, engineering challenges, and interlayer interference are comparatively analyzed and discussed. The current simulation models for gas coproduction and potential future research directions are further explored. The results indicate that the coupling effects of reservoir heterogeneity, interwell interference, and geological structure for increasing coproduction prediction accuracy should be included in future simulation models for gas coproduction. Careful investigation is required to explore the mechanisms and their further quantifications on the effects of interlayer interference in gas coproduction. The fractal dimension as a scale can play an important role in the characterization of the gas and water transport in different reservoirs. The machine learning methods have tremendous potential to provide accurate and fast predictions for gas coproduction and interlayer interference.

Revealing the Potential and Challenges of High‐Entropy Layered Cathodes for Sodium‐Based Energy Storage

AbstractSodium‐ion batteries (SIBs) reflect a strategic move for scalable and sustainable energy storage. The focus on high‐entropy (HE) cathode materials, particularly layered oxides, has ignited scientific interest due to the unique characteristics and effects to tackle their shortcomings, such as inferior structural stability, sluggish reaction kinetics, severe Jahn‐Teller effects induced lattice distortion, and poor oxygen reversibility at high voltage. This review focuses on high‐entropy oxide materials, highlighting their fundamentals, design principles, and application in layered oxide cathodes for SIBs. It delves into the growth mechanism, composition‐properties correlations, and the functional roles of high‐entropy design in enhancing the performance of layered oxide cathodes. Furthermore, it furnishes a comprehensive survey of recent advancements and persisting challenges within the domain of layered high‐entropy cathode materials, as well as offers insights into potential future research directions in line with the current state of knowledge.

Progress of Polymer Electrolytes Worked in Solid-State Lithium Batteries for Wide-Temperature Application.

Solid-state Li-ion batteries have emerged as the most promising next-generation energy storage systems, offering theoretical advantages such as superior safety and higher energy density. However, polymer-based solid-state Li-ion batteries face challenges across wide temperature ranges. The primary issue lies in the fact that most polymer electrolytes exhibit relatively low ionic conductivity at or below room temperature. This sensitivity to temperature variations poses challenges in operating solid-state lithium batteries at sub-zero temperatures. Moreover, elevated working temperatures lead to polymer shrinkage and deformation, ultimately resulting in battery failure. To address this challenge of polymer-based solid-state batteries, this review presents an overview of various promising polymer electrolyte systems. The review provides insights into the temperature-dependent physical and electrochemical properties of polymers, aiming to expand the temperature range of operation. The review also further summarizes modification strategies for polymer electrolytes suited to diverse temperatures. The final section summarizes the performance of various polymer-based solid-state batteries at different temperatures. Valuable insights and potential future research directions for designing wide-temperature polymer electrolytes are presented based on the differences in battery performance. This information is intended to inspire practical applications of wide-temperature polymer-based solid-state batteries.

Detection of DoS Attacks for IoT in Information-Centric Networks Using Machine Learning: Opportunities, Challenges, and Future Research Directions

The Internet of Things (IoT) is a rapidly growing network that shares information over the Internet via interconnected devices. In addition, this network has led to new security challenges in recent years. One of the biggest challenges is the impact of denial-of-service (DoS) attacks on the IoT. The Information-Centric Network (ICN) infrastructure is a critical component of the IoT. The ICN has gained recognition as a promising networking solution for the IoT by supporting IoT devices to be able to communicate and exchange data with each other over the Internet. Moreover, the ICN provides easy access and straightforward security to IoT content. However, the integration of IoT devices into the ICN introduces new security challenges, particularly in the form of DoS attacks. These attacks aim to disrupt or disable the normal operation of the ICN, potentially leading to severe consequences for IoT applications. Machine learning (ML) is a powerful technology. This paper proposes a new approach for developing a robust and efficient solution for detecting DoS attacks in ICN-IoT networks using ML technology. ML is a subset of artificial intelligence (AI) that focuses on the development of algorithms. While several ML algorithms have been explored in the literature, including neural networks, decision trees (DTs), clustering algorithms, XGBoost, J48, multilayer perceptron (MLP) with backpropagation (BP), deep neural networks (DNNs), MLP-BP, RBF-PSO, RBF-JAYA, and RBF-TLBO, researchers compare these detection approaches using classification metrics such as accuracy. This classification metric indicates that SVM, RF, and KNN demonstrate superior performance compared to other alternatives. The proposed approach was carried out on the NDN architecture because, based on our findings, it is the most used one and has a high percentage of various types of cyberattacks. The proposed approach can be evaluated using an ndnSIM simulation and a synthetic dataset for detecting DoS attacks in ICN-IoT networks using ML algorithms.

Predicting Construction Company Insolvent Failure: A Scientometric Analysis and Qualitative Review of Research Trends

The construction industry is infamous for its high insolvent failure rate because construction projects require complex processes, heavy investment, and long durations. However, there is a lack of a comprehensive framework and a requirement for such a framework in predicting the financial distress of construction firms. This paper reviews relevant literature to summarize the existing knowledge, identify current problems, and point out future research directions needed in this area using a scientometric analysis approach. Based on a total of 93 journal articles relating to predicting construction company failure extracted from multiple databases, this study conducts a holistic review in terms of chronological trends, journal sources, active researchers, frequent keywords, and most cited documents. Qualitative analysis is also provided to explore the data collection and processing procedures, model selection and development process, and detailed performance evaluation metrics. Four research gaps and future directions for predicting construction company failure are presented: selecting a broader data sample, incorporating more heterogeneous variables, balancing model predictability and interpretability, and quantifying the causality and intercorrelation of variables. This study provides a big picture of existing research on predicting construction company insolvent failure and presents outcomes that can help researchers to comprehend relevant literature, directing research policy-makers and editorial boards to adopt the promising themes for further research and development.

When People Do Allyship: A Typology of Allyship Action.

Despite increased popular and academic interest, there is conceptual ambiguity about what allyship is and the forms it takes. Viewing allyship as a practice, we introduce the typology of allyship action which organizes the diversity of ways that advantaged individuals seek to support those who are disadvantaged. We characterize allyship actions as reactive (addressing bias when it occurs) and proactive (fostering positive outcomes such as feelings of inclusion, respect, and capacity), both of which can vary in level of analysis (i.e., targeting oneself, one or a few other individuals, or institutions). We use this framework to profile six productive yet largely independent bodies of social psychological literature on social action and directly compare relative benefits and constraints of different actions. We suggest several future directions for empirical research, using the typology of allyship to understand when, where, and how different forms of allyship might succeed. Despite increased popular and academic interest in the word, people differ in what they believe allyship is and the forms it takes. Viewing allyship as a practice, we introduce a new way (the typology of allyship action) to describe how advantaged individuals seek to support those who are disadvantaged. We characterize allyship actions as reactive (addressing bias when it occurs) and proactive (increasing positive outcomes such as feelings of inclusion, respect, and capacity), both of which can vary in level (i.e., targeting oneself, one or a few other individuals, or institutions). We use this framework to profile six large yet mostly separate areas of social psychological research on social action and directly compare the relative benefits and limitations of different actions. We suggest several future directions for how the typology of allyship action can help us understand when, where, and how different forms of allyship might succeed.

Mapping desistance research: a systematic quantitative literature review from 2011 to 2020

In the past decade, desistance research has attracted immense research attention, which has necessitated the clarification of the overall picture of desistance research in terms of methodology, definition, and theory. Using the systematic quantitative literature review method, we seek to provide an overview of English-written peer-reviewed journal articles on desistance from 2011 to 2020. Analysis of 196 studies reveals that despite an almost equal quantitative–qualitative divide in desistance research, there is skewness in terms of research location, sample size, and usage of operationalization and theory. Based on these findings, we suggest the future direction of desistance research.

Sleep and spatial memory: Mechanisms, relationships, applications, and potential

More and more attention is being paid to the study of sleep and memory because of the immense potential the field has to offer, with the majority of studies focusing on episodic and procedural memory. However, another type of declarative memory spatial memory is relatively lesser-known. This review discusses the scientific community's current understanding of spatial memory and its relationship with sleep using both animal and human studies as examples, exploring, in particular, existing knowledge on spatial memory, whether sleep can affect spatial memory, the nature of such a relationship, and cellular mechanisms. The discussion then moves onto some potential applications of recent findings, including actions that researchers have already taken to better incorporate the enhancing properties of sleep on spatial memory into solutions for clinical problems. The review also points out future directions for research, considering the uncertainties in sleep and memory research and the significance of investigating such topics.

The power of a pledge: Exploring the relationship between sense of calling and innovative work behaviour in healthcare

In the healthcare sector, sense of calling has raised increasing attention for its crucial role in fostering nurses' motivation and dedication to their work. Despite the fact that individuals with a sense of calling are more likely to go beyond their duties, the potential influence of this calling on their innovative behaviour remains largely unexplored. Drawing on work as a calling and self‐determination theories, this study aims to establish a link between a sense of calling and innovative work behaviour in the healthcare sector and investigate the underlying mechanisms and boundary conditions. Questionnaires were distributed through field and online surveys to collect the responses of 350 nurses in China. Structural equation modelling was adopted to test the research hypotheses. The results showed that sense of calling had a positive effect on nurses' innovative work behaviour and the relationship was mediated through meaning of work and employee resilience. Moreover, psychological safety was found to strengthen the positive impact of sense of calling on nurses' innovative work behaviour. Theoretical and practical implications were discussed along with the direction for future research.

Domain-Specific Service-Learning Student Reflections in Therapeutic Recreation Curriculum

The use of service learning has grown within all academic areas, its use within Therapeutic Recreation curriculum is no exception. Much of the educational value of service-learning experiences comes from the reflection that occurs after the service experience. Balancing reflection assignments with a need for professional preparation can be a struggle for Therapeutic Recreation educators. Acknowledging this issue, the current article introduces and analyzes insights learned from a pilot study using a discipline specific service-learning reflection format. This format focuses on the students’ abilities to identify both client and personal examples of the five functional domains (physical, social, emotional, cognitive, and spiritual) and describe it in their reflection. Student reflections then underwent a Thematic Analysis resulting in themes of personal influence, external influence, student insight, facilitation skills, and anticipations. A brief discussion of the accuracy of students’ categorization of the domains is presented as well as limitations, future directions for research, and implications.

Pharmacists as Patient Advocates: Enhancing Medication Adherence and Health Outcomes

This is a study of the pharmacists who are the advocates of patients' health. The study deals with enhancing medication adherence and improving the health outcomes of the patients. Using technology this can be done easily. Technologies such as Electronic Prescription Service (EPS) and Robotic Process Automation (RPA) provide efficiency to operations. The several benefits of automated dispensing have also been covered along with a drawback of using this technology. The benefits to the patients and pharmacists come with a reduction in dispensing errors and overall improved healthcare. Lastly, the study gives future research directions with fields to work towards.

RNAscope in situ hybridization reveals microvascular sequestration of Plasmodium relictum pSGS1 blood stages but absence of exo-erythrocytic dormant stages during latent infection of Serinus canaria

BackgroundBirds chronically infected with avian malaria parasites often show relapses of parasitaemia after latent stages marked by absence of parasites in the peripheral circulation. These relapses are assumed to result from the activation of dormant exo-erythrocytic stages produced during secondary (post-erythrocytic) merogony of avian Plasmodium spp. Yet, there is no morphological proof of persistent or dormant tissue stages in the avian host during latent infections. This study investigated persistence of Plasmodium relictum pSGS1 in birds with latent infections during winter, with the goal to detect presumed persisting tissue stages using a highly sensitive RNAscope® in situ hybridization technology.MethodsFourteen domestic canaries were infected with P. relictum pSGS1 by blood-inoculation in spring, and blood films examined during the first 4 months post infection, and during winter and spring of the following year. After parasitaemia was no longer detectable, half of the birds were dissected, and tissue samples investigated for persisting tissue stages using RNAscope ISH and histology. The remaining birds were blood-checked and dissected after re-appearance of parasitaemia, and their tissues equally examined.ResultsSystematic examination of tissues showed no exo-erythrocytic stages in birds exhibiting latent infections by blood-film microscopy, indicating absence of dormant tissue stages in P. relictum pSGS1-infected canaries. Instead, RNAscope ISH revealed rare P. relictum blood stages in capillaries of various tissues and organs, demonstrating persistence of the parasites in the microvasculature. Birds examined after re-appearance of parasitemia showed higher numbers of P. relictum blood stages in both capillaries and larger blood vessels, indicating replication during early spring and re-appearance in the peripheral circulation.ConclusionsThe findings suggest that persistence of P. relictum pSGS1 during latent infection is mediated by continuous low-level erythrocytic merogony and possibly tissue sequestration of infected blood cells. Re-appearance of parasitaemia in spring seems to result from increased erythrocytic merogony, therefore representing recrudescence and not relapse in blood-inoculated canaries. Further, the study highlights strengths and limitations of the RNAscope ISH technology for the detection of rare parasite stages in tissues, providing directions for future research on persistence and tissue sequestration of avian malaria and related haemosporidian parasites.

AI-Testimony, Conversational AIs and Our Anthropocentric Theory of Testimony

ABSTRACT The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact can give testimony. In section 3, I identify three assumptions underlying the view that rejects conversational AIs – AI-based technologies that converse, as testifiers: conversational AIs (1) lack intentions, (2) cannot be normatively assessed, and (3) cannot constitute an object in trust relations, while humans can. In section 4, I propose the concept ‘AI-testimony’ for analyzing outputs of conversational AIs, suggesting three conditions for technologies to deliver AI-testimony: (1) content is propositional, (2) generated and delivered with no other human directly involved, (3) the output is perceived as phenomenologically similar to that of a human. I conclude that this concept overcomes the limitations of the anthropocentric concept of testimony, opening future directions of research without associating conversational AIs with human-like agency.

Airborne Exposure to Pollutants and Mental Health: A Review with Implications for United States Veterans.

Inhalation of airborne pollutants in the natural and built environment is ubiquitous; yet, exposures are different across a lifespan and unique to individuals. Here, we reviewed the connections between mental health outcomes from airborne pollutant exposures, the biological inflammatory mechanisms, and provide future directions for researchers and policy makers. The current state of knowledge is discussed on associations between mental health outcomes and Clean Air Act criteria pollutants, traffic-related air pollutants, pesticides, heavy metals, jet fuel, and burn pits. Although associations between airborne pollutants and negative physical health outcomes have been a topic of previous investigations, work highlighting associations between exposures and psychological health is only starting to emerge. Research on criteria pollutants and mental health outcomes has the most robust results to date, followed by traffic-related air pollutants, and then pesticides. In contrast, scarce mental health research has been conducted on exposure to heavy metals, jet fuel, and burn pits. Specific cohorts of individuals, such as United States military members and in-turn, Veterans, often have unique histories of exposures, including service-related exposures to aircraft (e.g. jet fuels) and burn pits. Research focused on Veterans and other individuals with an increased likelihood of exposure and higher vulnerability to negative mental health outcomes is needed. Future research will facilitate knowledge aimed at both prevention and intervention to improve physical and mental health among military personnel, Veterans, and other at-risk individuals.

Bibliometric analysis of global performance and trends of research on combined sewer overflows (CSOs) from 1990 to 2022.

Combined sewer overflows (CSOs) are one of the main sources of pollution in urban water systems and significantly impede the restoration of water body functionalities within urban rivers and lakes. To understand the research and frontier trends of CSOs comprehensively and systematically, a visual statistical analysis of the literature related to CSOs in the Web of Science core database from 1990 to 2022 was conducted using the bibliometric method using HistCite Pro and VOSviewer. The results reveal a total of 1,209 pertinent publications related to CSOs from 1990 to 2022, and the quantity of CSOs-related publications indicated an increasing trend. Investigations of the distribution and fate of typical pollutants in CSOs and their ecological effects on receiving waters and studies on pollution control technologies (source reduction, process control, and end-of-pipe treatment) are the current focus of CSOs research. CSOs pollution control technologies based on source reduction and the monitoring and control of emerging contaminants are at the forefront of scientific investigations on CSOs. This study systematically and comprehensively summarized current research topics and future research directions of CSOs, thus providing a reference for CSOs control and water environment management research.