Knowledge Of Processes Research Articles

Five guidelines to improve context-aware process selection: an Australian banking perspective

PurposeSelecting which processes to improve plays a critical role in the first phase of the business process management lifecycle, but it is a step with known pitfalls. Decision-makers rely on subjective criteria and their knowledge of the alternative processes put forward for selection is often inconsistent. This leads to poor quality decision-making and wastes resources. The purpose of this paper is to examine the proposition that decision-makers armed with context-enriched criteria make more logical, better-quality decisions. The context in question is qualitative, sensitive to decision-making bias and politically charged.Design/methodology/approachWe applied a design-science approach, engaging 70 industry decision-makers through a combination of research methods to assess how different contextual configurations, in a hypothetical scenario adapted from the Australian banking industry, influenced and ultimately improved the quality of the process selection step.FindingsThe study highlights the impact of framing effects on context, and the need to adapt framing to decision-maker behavior and provides five guidelines to improve process selection effectiveness.Originality/valueProcess selection research to date has largely focused on quantitative evaluation techniques, with little attention paid to the role of context and the behavioral interplay of decision-making styles in practice.

What do employers need when supporting stroke survivors to return to work?: a mixed-methods study

ABSTRACT Background Employers are key in supporting stroke survivors to return to work (RTW) but do not always have knowledge/skills or guidance to do so. Objectives To explore employers’ needs for provision of post-stroke RTW support. Methods Mixed-methods study. Participants recruited through voluntary response/purposive sampling. Survey of employers investigated stroke knowledge (maximum score: 7), RTW process knowledge (maximum score: 8), and perceived competency for actions supporting RTW (maximum score: 100%). Regression analyses explored relationships between employers’ demographic/contextual characteristics and knowledge and perceived competency scores. Interviews with employers explored factors influencing their post-stroke RTW support. Interview data were analyzed using a framework analysis. Survey/interview findings were synthesized with those from a qualitative systematic review. Results Across the survey (n = 50), interviews (n = 7), and review (25 studies), employers’ support was influenced by stroke survivors’ decisions to disclose stroke-related limitations, employers’ knowledge regarding roles/responsibilities, employers’ communication skills, and information provided by healthcare. Regression analyses: Human resources/occupational health support was positively associated with stroke knowledge (ß = 2.30, 95% CI 0.36–4.41, p = 0.013) and RTW process knowledge (ß = 5.12, 95% CI 1.80–6.87, p = 0.001). Post-stroke RTW experience was positively associated with stroke knowledge (ß = 1.36, 95% CI 0.46–2.26, p = 0.004) and perceived competency (ß = 31.13, 95% CI 18.40–44.76, p = 0.001). Organization size (i.e. working in a larger organization) was positively associated with RTW process knowledge (ß = 2.96, 95% CI 1.52–4.36, p = <.001). Conclusions Employers’ RTW support was influenced by personal and environmental factors; they may benefit from education and guidance on stroke and their roles/responsibilities during the RTW process.

Improving Bayesian Optimization via Hierarchical Variation Modeling for Combinatorial Experiments Given Limited Runs Guided by Process Knowledge

Active learning based on Bayesian optimization (BO) is a popular black-box combinatorial search method, particularly effective for autonomous experimentation. However, existing BO methods did not consider the joint variation caused by the process degradation over time and input-dependent variation. The challenge is more significant when the affordable experimental runs are very limited. State-of-the-art approaches did not address allocating limited experimental runs that can jointly cover (1) representative inputs over large search space for identifying the best combination, (2) replicates reflecting the true input-dependent testing variation, and (3) process variations that increase over time due to process degradation. This paper proposed Empirical Bayesian Hierarchical Variation Modeling in Bayesian Optimization (EHVBO) guided by the process knowledge to maximize the exploration of potential combinations in sequential experiments given limited experimental runs. The method first mitigates the process degradation effect through generalized linear modeling of grouped variations, guided by the knowledge of the re-calibration cycle of process conditions. Then, EHVBO introduces an empirical Bayesian hierarchical model to reduce the replicates for learning the input-dependent variation, leveraging the process knowledge of the common structure shared across different testing combinations. This way can reduce the necessary replicates for each input condition. Furthermore, the paper developed a heuristics-based strategy incorporated in EHVBO to improve search efficiency by selectively refining the search space over pivotal regions and excluding less-promising regions. A case study based on real experimental data demonstrates that the proposed method outperforms testing results from various optimization models.

Links between parental monitoring and parent-adolescent conflict: A multimodal test of bidirectional relations.

During adolescence, youth increase in both independence and conflict with parents. Parents vary in how much they know about their adolescents' whereabouts and activities and how they acquire this information (i.e., the sources of what parents know). We probed how parental knowledge of adolescents' whereabouts and activities-and their information sources-relates to (a) domains of parent-adolescent conflict (fighting about, or having different beliefs about, daily life topics) and (b) parent and adolescent attachment-related behavior during a conflict discussion task. Using the Actor-Partner Interdependence Model, we tested links between parental knowledge and its sources and conflict processes. Eighty-seven adolescents (Mage = 15.18; 55% female) and parents completed surveys about parental knowledge and its sources (i.e., parental solicitation of adolescents' activities, adolescent disclosure to parents about their activities) and separate interviews on conflict domains. A subset of parent-adolescent dyads (n = 65) interacted for 5 min about an adolescent-identified conflict topic. Different beliefs about daily life topics related to parental knowledge: parents' reports of greater different beliefs about daily life topics predicted less knowledge of adolescents' activities/whereabouts, solicitation, and disclosure, for both parent and adolescent reports of these domains. For adolescents, greater different beliefs related to less solicitation and disclosure. Only adolescent reports of parental knowledge, solicitation, and disclosure predicted attachment-related behaviors both dyad members displayed during the conflict discussion task. Findings reveal links between parental knowledge of adolescents' activities and conflict processes and demonstrate dyadic interdependence between parental knowledge of adolescents' activities and conflict processes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Green human resource management and organizational efficiency among local assemblies: role of process innovation and knowledge sharing

PurposeThe purpose of this study was to assess the mediating role of process innovation in the relationship between green human resource management (GHRM) and organizational efficiency among local governments. Further, the study assessed the moderating role of knowledge sharing in the relationship between process innovation and organizational efficiency.Design/methodology/approachThe study focused on metropolitan, municipal, and district assemblies (MMDAs) within the Ashanti region of Ghana. The sample size was 227 employees within the selected MMDAs. Structural equation modeling in Amos (v.23) was run to test the stated hypotheses.FindingsIt was concluded that GHRM had no direct effect on organizational efficiency within the MMDAs. The relationship was rather fully mediated by process innovation. Knowledge sharing further moderated the relationship between process innovation and organizational efficiency among the MMDAs.Practical implicationsLocal governments and other public institutions should adopt GHRM, as it could enhance process innovation, leading to organizational efficiency.Social implicationsThis paper contributes to the understanding of GHRM in the public sector, particularly in the context of local government organizations, and provides valuable insights for policymakers and practitioners seeking to enhance their organizational performance and sustainability.Originality/valueAlthough there is substantial evidence of GHRM within the private sector, less attention has been paid to the public sector, more specifically the local government. Furthermore, the interplay of process innovation and knowledge sharing adds to the knowledge of the relationship between GHRM and organizational efficiency.

Cell-free DNA end characteristics enable accurate and sensitive cancer diagnosis

The fragmentation patterns of cell-free DNA (cfDNA) in plasma can potentially be utilized as diagnostic biomarkers in liquid biopsy. However, our knowledge of this biological process and the information encoded in fragmentation patterns remains preliminary. Here, we investigated the cfDNA fragmentomic characteristics against nucleosome positioning patterns in hematopoietic cells. cfDNA molecules with ends located within nucleosomes were relatively shorter with altered end motif patterns, demonstrating the feasibility of enriching tumor-derived cfDNA in patients with cancer through the selection of molecules possessing such ends. We then developed three cfDNA fragmentomic metrics after end selection, which showed significant alterations in patients with cancer and enabled cancer diagnosis. By incorporating machine learning, we further built high-performance diagnostic models, which achieved an overall area under the curve of 0.95 and 85.1% sensitivity at 95% specificity. Hence, our investigations explored the end characteristics of cfDNA fragmentomics and their merits in building accurate and sensitive cancer diagnostic models.

A Cross-Sectional, Descriptive Web-Based Survey on Knowledge of the Organ Donation Process among Internal Medicine Residents

A Cross-Sectional, Descriptive Web-Based Survey on Knowledge of the Organ Donation Process among Internal Medicine Residents

Ship recycling process in Bangladesh and a survey-based risk assessment with mitigation proposal

Ship recycling industries play a significant role in the economic development of South Asian countries, including Bangladesh. In the wake of entering the Hong Kong Convention (HKC) in June 2025, the industry aims to improve its overall safety standards cost-effectively. However, due to the restrictive nature of the industry, solutions based on field surveys are limited. This study successfully articulates the indigenous industry knowledge of the recycling process in Bangladesh after carefully studying the practices followed by the existing ship recycling yards in the country. Based on field surveys conducted across 18 ship recycling yards in Bangladesh, the risk patterns inherent in the ship recycling industry are studied; for example, highly hazardous tasks in the ship recycling process are found to be (i) explosion hazards during primary cutting operations at the intertidal zone, (ii) falling hazards during inspections at the outer anchorage, (iii) falling and crushing hazards during block cutting and handling heavy objects. Industry experts and scholars consider the perception of the risk pattern regarding the current practices of ship recycling activities to cover a broader perspective of this issue. The correlation of survey outcomes with actual accident cases is comparable. Finally, practical recommendations for minimising risks have been recommended, especially in high-risk workplace areas. The study adds knowledge to the existing literature by giving a clear picture of evidence-based findings for this sector and helps improve the industry's overall safety standard.

Implementing Mental Health Screening for Adolescent Hematology and Oncology Patients: A Quality Improvement Initiative.

Purpose: Adolescents and young adults (AYA) with chronic illnesses experience an increase in mental health concerns. A mental health screening (MHS) process for hematology and oncology patients was implemented in a single institution. The quality improvement project was conducted to integrate a MHS process, educate providers about the importance of mental health in this patient population, and evaluate the process. Methods: The COM-B (capability, opportunity, motivation-behavior) model for behavior change was used to inform strategic planning and Plan-Do-Study-Act (PDSA) methodologies for process improvement. Retrospective chart reviews and surveys were conducted to determine missed screening rates and providers' perceptions, knowledge, attitudes, and skills of the MHS process. Results: Of 334 eligible patient encounters, the missed screening rate was 15.0%, the overall error rate of completing the screening was 3.8%, the error rate of completing the suicide or self-harm indicator was 2.6%, and the missed medical social worker touch point was 4.8%. Conclusion: The rising rates of mental health concerns in AYA hematology and oncology patients call for streamlined MHS processes to improve the identification of patients who may need intervention and services. Processes should be tailored to workflows and available resources. Future PDSA cycles will include providing dedicated nursing education and determining the cost needed to meet the rising mental health needs of the AYA hematology and oncology population.

Human-robot collaborative decision method of hexapod robot based on prior knowledge and negotiation strategy

Against the unstructured terrain environment, human drivers often rely on remote operating patterns to accomplish tasks with robots. With the gradual improvement in robot intelligence, a key problem that urgently requires attention is how to bridge cognitive and perceptual differences between human and robot in collaborative decision-making processes. Particularly effective resolution of differences in decision outcomes is crucial. Therefore, this paper utilizes the decision logic process and prior knowledge model of human drivers to form a robot's decision framework, narrowing the cognitive differences between human and robot. Besides, embedding the human-robot-environment features that affect the decision-making process as prior knowledge into the robot's decision-making system can effectively reduce perceptual gaps. Under the same decision framework, a negotiation strategy is proposed for forming a unified decision outcome between human and robot by finding an optimal concession rate. This study utilizes a hexapod robot simulated driving platform to gather experimental data and develop prior knowledge for robots. It also leverages virtual reality equipment and visual augmentation technologies to establish a remote human-robot collaborative decision-making experimental system. The experimental results conducted in complex obstacle terrain demonstrate the effectiveness of adopting the negotiation strategy for human-robot collaborative decision-making. Compared with the individual human or robot decision, the human-robot collaborative decision method significantly enhances robot stability, reduces energy consumption, and minimizes collisions.

Transferability of ecological forecasting models to novel biotic conditions in a long-term experimental study.

Ecological forecasting models play an increasingly important role for managing natural resources and assessing our fundamental knowledge of processes driving ecological dynamics. As global environmental change pushes ecosystems beyond their historical conditions, the utility of these models may depend on their transferability to novel conditions. Because species interactions can alter resource use, timing of reproduction, and other aspects of a species' realized niche, changes in biotic conditions, which can arise from community reorganization events in response to environmental change, have the potential to impact model transferability. Using a long-term experiment on desert rodents, we assessed model transferability under novel biotic conditions to better understand the limitations of ecological forecasting. We show that ecological forecasts can be less accurate when the models generating them are transferred to novel biotic conditions and that the extent of model transferability can depend on the species being forecast. We also demonstrate the importance of incorporating uncertainty into forecast evaluation with transferred models generating less accurate and more uncertain forecasts. These results suggest that how a species perceives its competitive landscape can influence model transferability and that when uncertainties are properly accounted for, transferred models may still be appropriate for decision making. Assessing the extent of the transferability of forecasting models is a crucial step to increase our understanding of the limitations of ecological forecasts.

TRIPLE: A blockchain-based digital twin framework for cyber-physical systems security

Cyber-physical systems (CPSs) are being increasingly adopted for industrial applications, yet they involve a dynamic threat landscape that requires CPSs to adapt to emerging threats during their operation. Recently, digital twin (DT) technology (which refers to a virtual representation of a device, process, or environment) has emerged as a suitable candidate to address the security challenges faced by dynamic CPSs. DT has the capability of strengthening the security of CPSs by continuously mapping the physical to twin counterparts to detect inconsistencies. The existing DT-based security solutions are constrained by untrustworthy data dissemination as well as limited data sharing among the involved stakeholders, which, in turn, limit the ability of DTs to run accurate simulations or make valid decisions. To address these challenges, this paper proposes a modular framework called TRusted and Intelligent cyber-PhysicaL systEm (TRIPLE), that leverages blockchain, DTs, and threat intelligence (TI) to secure CPSs. The blockchain-based DT components in the framework provide data integrity, traceability, and availability for trusted DTs. Furthermore, to accurately and comprehensively model system states, the framework envisions fusing process knowledge for modeling DTs from system specification-based and learning-based information and other sources, including infrastructure-as-code (IaC) and knowledge base (KB). The framework also integrates TI for future-proofing against emerging threats, such that threats can be detected either reactively by mapping the behavior of physical and virtual spaces or proactively by TI and threat hunting. We demonstrate the viability of the framework through a proof of concept. Finally, we formally verify the TRIPLE framework to demonstrate its correctness and effectiveness in enhancing CPS security.

A novel reuse method of machining process knowledge for similar ruled surface blades based on dual mapping

A novel reuse method of machining process knowledge for similar ruled surface blades based on dual mapping

Exploring Brain Activity in Different Mental Cognitive Workloads

Objective: Understanding neural mechanisms underlying cognitive workload is crucial for advancing our knowledge of human cognition and mental processes. In this study, we utilized electroencephalography (EEG) analysis to investigate brain activity associated with varying mental cognitive workloads from a psychological perspective. Method: We employed a publicly accessible EEG dataset consisting of a cohort of 36 healthy volunteers (75% female), aged 18 to 26 years, while the participants were at rest or engaged in an arithmetic task to explore mental cognitive workload. After preprocessing to reduce noise and various artifacts and to obtain a clean signal for every subject, functional connectivity and complexity features were calculated from EEGs through the coherence and permutation entropy algorithms, respectively. Then, repeated measures analysis of variance (ANOVA) was conducted to assess the differences in complexity and connectivity measures across various brain regions between the rest and task states. Results: Brain sites showed significant within-subject effects, and the interaction between states and channels was significant for connectivity values (F = 3.68, P = 0.034). Post hoc comparisons indicated that FP1-F7, FP1-F8 and FP1-Fz connectivity were significantly lower during the task state compared to the rest state (P &lt; 0.05). Moreover, F4-P3, F4-P4, FP1-O1, FP2-O2, F3-O1, F4-O1, F8-O1, C4-O1, F3-O2, F4-O2, F7-O2, F8-O2, Fz-O1, Fz-O2, Cz-O1 and Fz-P4 connectivity were significantly higher during the arithmetic task state (P &lt; 0.05). Furthermore, brain sites showed significant within-subject effects and the interaction between states and channels was significant for entropy values (F = 3.50, P = 0.041). Post hoc comparisons indicated that the permutation entropy was significantly higher in the FP1, T3, T4, P4 and Pz channels during the arithmetic task compared to the rest state (P &lt; 0.05). Conclusion: During arithmetic tasks, the increased connectivity in the frontoparietal and frontooccipital networks and heightened complexity in the prefrontal, temporal and parietal lobes reflect the collaborative engagement of brain areas specialized in numerical processing, attention, working memory, cognitive control, and visual-spatial cognition. These changes in connectivity and complexity facilitate the integration of multiple cognitive processes essential for effective arithmetic problem-solving.

New insights into the ovulatory process in the human ovary.

Successful ovulation is essential for natural conception and fertility. Defects in the ovulatory process are associated with various conditions of infertility or subfertility in women. However, our understanding of the intra-ovarian biochemical mechanisms underlying this process in women has lagged compared to our understanding of animal models. This has been largely due to the limited availability of human ovarian samples that can be used to examine changes across the ovulatory period and delineate the underlying cellular/molecular mechanisms in women. Despite this challenge, steady progress has been made to improve our knowledge of the ovulatory process in women by: (i) collecting granulosa cells across the IVF interval, (ii) creating a novel approach to collecting follicular cells and tissues across the periovulatory period from normally cycling women, and (iii) developing unique in vitro models to examine the LH surge or hCG administration-induced ovulatory changes in gene expression, the regulatory mechanisms underlying the ovulatory changes, and the specific functions of the ovulatory factors. The objective of this review is to summarize findings generated using in vivo and in vitro models of human ovulation, with the goal of providing new insights into the mechanisms underlying the ovulatory process in women. This review is based on the authors' own studies and a search of the relevant literature on human ovulation to date using PubMed search terms such as 'human ovulation EGF-signaling', 'human ovulation steroidogenesis', 'human ovulation transcription factor', 'human ovulation prostaglandin', 'human ovulation proteinase', 'human ovulation angiogenesis' 'human ovulation chemokine', 'human ovulatory disorder', 'human granulosa cell culture'. Our approach includes comparing the data from the authors' studies with the existing microarray or RNA-seq datasets generated using ovarian cells obtained throughout the ovulatory period from humans, monkeys, and mice. Current findings from studies using in vivo and in vitro models demonstrate that the LH surge or hCG administration increases the expression of ovulatory mediators, including EGF-like factors, steroids, transcription factors, prostaglandins, proteolytic systems, and other autocrine and paracrine factors, similar to those observed in other animal models such as rodents, ruminants, and monkeys. However, the specific ovulatory factors induced, their expression pattern, and their regulatory mechanisms vary among different species. These species-specific differences stress the necessity of utilizing human samples to delineate the mechanisms underlying the ovulatory process in women. The data from human ovulation in vivo and in vitro models have begun to fill the gaps in our understanding of the ovulatory process in women. Further efforts are needed to discover novel ovulatory factors. One approach to address these gaps is to improve existing in vitro models to more closely mimic in vivo ovulatory conditions in humans. This is critically important as the knowledge obtained from these human studies can be translated directly to aid in the diagnosis of ovulation-associated pathological conditions, for the development of more effective treatment to help women with anovulatory infertility or, conversely, to better manage ovulation for contraceptive purposes. N/A.

Особенности развития генеративных структур некоторых цветковых растений

The paper presents the results of a comparative study of the reproductive biology of a number of Crimean flora species and valuable plants introduced to the south of Russia belonging to various families (Magnoliaceae, Annonaceae, Ericaceae, Campanulaceae, Anacardiaceae, Lamiaceae, Ranunculaceae, Davidiaceae, Nyssaceae, Onagraceae, Papaveraceae), which made it possible to establish some features and regularities in the formation of the generative structures of the reproductive system, consisting in the conjugation of the development of male and female elements, the maturation of sexual gametes and the process of pollination in entomophilous plants. A conclusion was drawn concerning the high reproductive potential of the studied species, which is expressed in the formation of a sufficient number of full-fledged seeds to reproduce. The possibilities of using the knowledge of the reproductive processes of flowering plants in solving certain issues of taxonomy, determining the strategy of reproduction and conservation of phytodiversity, and showing the importance of antecological aspects in plant reproduction, breeding and nature protection were demonstrated. The material is of scientific interest to botanists, ecologists, breeders and other specialists.

Mediation effect of knowledge management on the impact of IT capability on firm performance: exploring the moderating role of organization culture management.

With the development of the digital economy, a multitude of firms have embarked on the path of digital transformation through information technology (IT). Scholars have called for attention to the mediating or moderating mechanisms of IT capability on firm performance. This study argues that further exploration is needed regarding the relationship between IT capability and firm performance. This study obtained questionnaire data from 152 IT senior managers of randomly selected manufacturing firms. The data was used to empirically test the proposed hypotheses using hierarchical regression analysis. The results showed that IT capability has a positive effect on firm performance directly and indirectly via knowledge stock and knowledge process. Moreover, organizational culture management moderates the relationship between knowledge stock/knowledge process, and firm performance. This study proposes the "resources-knowledge-performance" mechanism, which sheds light on the "black box" of how IT capability affects firm performance. This enriches the research on knowledge from different perspectives and the the research on organizational culture by discussing the moderating role of organizational culture management in the relationship between knowledge stock/process and firm performance. Our research also has important managerial implications to firm.

Physical activity in the creative learning of adolescents

In the educational context, the use of physical activity as a teaching resource to generate creative learning in adolescents is commonly ignored by teachers, wasting the opportunity that, through body movement, the student can acquire significant knowledge for his life. In this context, the objective of the research was to analyze the incidence of physical activity on the creative learning of adolescents. The quantitative approach was used by collecting quantitative data and its analysis was carried out with the help of computer and statistical tools that showed the reality of the management of physical activities. A population of 129 students was considered the General Baccalaureate of the Gonzalo Abad Grijalva Educational Unit in the city of Chone, province of Manabí – Ecuador. The Results demonstrate a relevant connection between physical activity and the development of thinking skills, obtaining that the strengthening of interpersonal relationships between students, the relaxation of the body, and the promotion of health care, constitute a path for the development of creativity in the acquisition of interdisciplinary knowledge in the educational process.

The Evolutionary Concordance Between Adolescent Self-Control and Academic Achievement: The Moderating Effect of Family Background

The connection between adolescent self-control and academic achievement in the setting of a familial environment focuses on familial relationships and upbringing which influence the relationship between self-control and learning success throughout adolescence. Due to family stress, students are unable to concentrate on their academic performance efficiently. This study examines the connections among adolescents’ academic achievement and self-control by employing the structure of developmental psychology. Focusing on the moderating impact of the familial environment in this connection. The research of 500 middle school students, the collection of pertinent data, and regression modeling revealed that self-control is considerably positively associated with academic achievement. Furthermore, family background has a considerable moderating influence on this connection. Specifically, the positive impacts of self-control on academic success were stronger in circumstances with high family support, whereas the impact was lower in conditions with inadequate family support. The study results offer a new view for instructors and parents, highlighting the role of the familial setting on adolescent's self-improvement and academic accomplishment.The study concludes with an improved knowledge of evolutionary processes that regulate adolescent development and educational achievements, enabling enhanced procedures focused on improving academic achievement in adolescents.

Механизмы электронного транспорта в низкоразмерных полупроводниковых структурах: обзор

Background: Low-dimensional semiconductor structures such as quantum wells, wires, and dots have sparked widespread attention due to their distinct electron transport properties that differ dramatically from bulk materials. These characteristics are critical for advances in nanoscale electrical and optoelectronic devices. Objective: The article aims to summarize current knowledge of electron transport processes in low-dimensional semiconductor devices, focusing on the impact of reduced dimensionality on electron behaviour. Methods: A thorough literature analysis was carried out, emphasizing experimental and theoretical investigations that shed light on electron transport dynamics in quantum wells, wires, and dots. The analysis looked into scattering mechanisms, quantum confinement effects, and the significance of material composition and structure. Results: The findings show that quantum confinement produces discrete energy states that drastically change electron mobility and conductivity. Furthermore, electron scattering by phonons, contaminants, and surfaces is shown to be heavily impacted by decreased dimensionality, which either enhances or suppresses electron transport depending on the precise configuration and size of the structures. Conclusion: Low-dimensional semiconductor structures have complex electron transport behaviours that differ significantly from their bulk counterparts. Understanding these mechanisms is critical for designing and developing future electronic devices, and this overview serves as a starting point for ongoing articles on this technologically significant topic.