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The significance of the ethical review process in human-based research undertakings cannot be overemphasized as it is necessary to uphold ethical standards and protect participants. However, the review process per se can act as a bottleneck, potentially hindering research progress and leading to academic dishonesty. The present work explores the benefits and challenges of ethical review, emphasizing issues like intellectual theft, forced authorship, and the stifling of independent researchers. Proposed solutions include leveraging previously approved designs, empowering experienced professors for clearance, establishing panels of researchers, creating voluntary ethical approval offices, utilizing private consultancy offices, and establishing a transnational ethical clearance authority. In conclusion, this work stresses the importance of finding mechanisms to streamline the ethical review process while maintaining ethical standards to foster integrity in research and combat academic dishonesty., Competing Interests: The author declares no competing interests., (Copyright: Subah Abderehim Yesuf et al.)

With the sharp increase in the volume of literature data, researchers must spend considerable time and energy locating desired papers. A paper recommendation is the means necessary to solve this problem. Unfortunately, the large amount of data combined with sparsity makes personalizing papers challenging. Traditional matrix decomposition models have cold-start issues. Most overlook the importance of information and fail to consider the introduction of noise when using side information, resulting in unsatisfactory recommendations. This study proposes a paper recommendation method (PR-SLSMF) using document-level representation learning with citation-informed transformers (SPECTER) and low-rank and sparse matrix factorization; it uses SPECTER to learn paper content representation. The model calculates the similarity between papers and constructs a weighted heterogeneous information network (HIN), including citation and content similarity information. This method combines the LSMF method with HIN, effectively alleviating data sparsity and cold-start issues and avoiding topic drift. We validated the effectiveness of this method on two real datasets and the necessity of adding side information. [ABSTRACT FROM AUTHOR]

Adopting a scoping review method, we examined peer‐reviewed academic papers published about human–lion conflict (HLC) (including coexistence) and identified knowledge gaps. We searched papers published between January 1981 and December 2023 using academic databases, with the key terms African lion, human–lion conflict, human–lion coexistence, and human–lion interaction. This produced 485 records, reduced to 137 after using additional criteria. Ninety‐eight papers were focused on lions in Kenya, Tanzania, Zimbabwe, and Botswana. Ten pan‐African studies were identified in our review. Our inductive analysis identified four themes related to HLC: attitudes and perceptions toward lions, causes of HLC, consequences of HLC, and mitigating HLC. Some limitations identified in systematic reviews of human–wildlife conflict have been addressed in recent years, such as broadening the geographical scale of research. However, some knowledge gaps remain, including a lack of assessment of mitigation strategies and studies on climate changes impact on human–lion conflict. Addressing the knowledge gaps highlighted in this review will require diversifying the disciplinary composition of the research teams and increasing researcher reflexivity. [ABSTRACT FROM AUTHOR]

The demand for eco-friendly packaging materials has urged researchers to look for alternatives to petroleum-based polymers. In this regard, paper-based products have turned out to be a promising choice; however, their weak resistance to water has limited their application. The use of various additives to enhance paper's moisture resistance is a common practice. However, considering the growing global agenda for sustainable development, the search for new bio-based paper additives has become increasingly important. This study investigated the potential synergistic impact of the addition of nanofibrillated cellulose (NFC) and chitosan additives (CHIT) to different fiber combinations to improve paper's properties, in particular, their wet strength. The efficacy of the additive application order was examined and was found to be crucial in achieving the desired outcomes. The results showed that incorporating CHIT after NFC enhanced the paper's tensile and burst indicators, as well as the paper stretch in the dry state, by 35–70%, 35–55%, and 20–35%, respectively. In addition, the tensile index and stretch in the wet state improved 9–13 times and 2.5–5.5 times over, respectively. The air permeability decreased 2.5–12 times over. These findings demonstrate that the sequential addition of the NFC and CHIT additives yield a greater enhancement of paper's properties than using each additive separately. [ABSTRACT FROM AUTHOR]

Image compression is a vital component for domains in which the computational resources are usually scarce such as automotive or telemedicine fields. Also, when discussing real-time systems, the large amount of data that must flow through the system can represent a bottleneck. Therefore, the storage of images, alongside the compression, transmission, and decompression procedures, becomes vital. In recent years, many compression techniques that only preserve the quality of the region of interest of an image have been developed, the other parts being either discarded or compressed with major quality loss. This paper proposes a study of relevant papers from the last decade which are focused on the selection of a region of interest of an image and on the compression techniques that can be applied to that area. To better highlight the novelty of the hybrid methods, classical state-of-the-art approaches are also analyzed. The current work will provide an overview of classical and hybrid compression methods alongside a categorization based on compression ratio and other quality factors such as mean-square error and peak signal-to-noise ratio, structural similarity index measure, and so on. This overview can help researchers to develop a better idea of what compression algorithms are used in certain domains and to find out if the presented performance parameters are of interest for the intended purpose. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of our study was to determine the order in which science and health researchers read scientific papers, their reasons for doing so and the perceived difficulty and perceived importance of each section. Study design and setting: An online survey open to science and health academics and researchers distributed via existing research networks, X (formerly Twitter), and LinkedIn. Results: Almost 90% of respondents self-declared to be experienced in reading research papers. 98.6% of the sample read the abstract first because it provides an overview of the paper and facilitates a decision on continuing to read on or not. Seventy-five percent perceived it to be the easiest to read and 62.4% perceived it to be very important (highest rank on a 5-point Likert scale). The majority of respondents did not read a paper in the IMRAD (Introduction, Methods, Results And Discussion) format. Perceived difficulty and perceived importance influenced reading order. Conclusion: Science and health researchers do not typically read scientific and health research papers in IMRAD format. The more important a respondent perceives a section to be, the more likely they are to read it. The easier a section is perceived, the more likely it will be read. We present recommendations to those teaching the skill of writing scientific papers and reports. [ABSTRACT FROM AUTHOR]

This article considers how undocumented youth in the UK survive and construct their everyday lives in precarious circumstances. Drawing on multiple in-depth narrative interviews with (n = 7) undocumented youth, I illustrate how these young people focus on the future and engage in purposeful activities as a way of enduring the everyday challenges of living with no papers. I reflect on the relationships, which young people draw on to enable them to endure adversity and rebuild their everyday lives. I conclude that the presence of love and community is critical for young people's survival, safety and wellbeing, and I suggest how practitioners and researchers might make use of these findings. [ABSTRACT FROM AUTHOR]

Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. Why are AI tools so attractive and what are the risks of implementing them across the research pipeline? Here we develop a taxonomy of scientists' visions for AI, observing that their appeal comes from promises to improve productivity and objectivity by overcoming human shortcomings. But proposed AI solutions can also exploit our cognitive limitations, making us vulnerable to illusions of understanding in which we believe we understand more about the world than we actually do. Such illusions obscure the scientific community's ability to see the formation of scientific monocultures, in which some types of methods, questions and viewpoints come to dominate alternative approaches, making science less innovative and more vulnerable to errors. The proliferation of AI tools in science risks introducing a phase of scientific enquiry in which we produce more but understand less. By analysing the appeal of these tools, we provide a framework for advancing discussions of responsible knowledge production in the age of AI., (© 2024. Springer Nature Limited.)

J‐aggregation and H‐aggregation are identified as two classical models of functionally oriented non‐covalent interactions, and significant attention has been drawn by researchers. However, due to the scarcity of single‐crystal examples of H‐aggregation, a comprehensive understanding of the relationship between its stacking mode and optical behaviour has been hindered. In recent studies, two polyaromatic Schiff base compounds, Cl‐Salmphen and H‐Salmphen, were successfully synthesized, and both were found to exhibit H‐aggregation. In the findings, H‐Salmphen was shown to display typical C─H···π interactions, characteristic of Aggregation‐Induced Emission (AIE) active molecules, whereas its halogenated counterpart was identified as behaving similar to Aggregation‐Caused Quenching (ACQ) active molecules. These types of results suggest that identical intermolecular interactions can produce differing optical behaviours. Light was shed, at least in part, on the formation mechanisms of H‐type aggregates and their luminescence properties from these observations. Additionally, the high optical signal‐to‐noise ratio inherent to H‐aggregates was utilized for the exploration of water content detection. As an outcome, a high‐performance fluorescent filter paper was developed, enabling easy real‐time detection using a smartphone. [ABSTRACT FROM AUTHOR]

Lecture Notes in Computer Science (LNCS) is a globally recognised publication outlet for the field of Computer Science, including in South Africa. In this study, spanning from 1973 to 2022, we investigated the research participation of South African based authors in LNCS. The publication output and citation impact of these authors were compared to the global Computer Science and LNCS output. The authorship patterns and collaborative behaviour of South African LNCS papers were explored, and a keyword or topic analysis also conducted. Of the total of 518 662 LNCS papers published globally between 1973 and 2022, South African based researchers contributed 1150 papers (0.22%). The LNCS papers from South Africa exhibit a strong collaborative publication culture, with 1043 (91%) co-authored and 107 (9%) singleauthored works. Local LNCS researchers prefer institutional collaboration (43%), followed by international (37%) and national collaboration (11%). Europe emerged as the most significant collaboration partner for LNCS researchers in South Africa. Of the 1150 papers, 836 (73%) had received citations, while 314 (27%) had not. On average, papers published by South African based authors received 6.05 citations, compared to the global LNCS average of 9.49 citations per paper. A keyword analysis revealed that the majority of papers by South African authors focus on artificial intelligence. The results indicate that, although LNCS serves as a reputable dissemination platform for Computer Science research output both globally and locally, South African authors should consider publishing more journal articles to build and improve their researcher profiles. Significance: * The study shows that LNCS is the most frequent publication outlet for Computer Science researchers, globally and in South Africa. * The study offers insight into the publication output, authorship patterns, collaborative behaviour and citation impact of South African based Computer Science researchers. [ABSTRACT FROM AUTHOR]

With the exponential growth in the number of academic researchers, it is crucial for editors of scientific journals to identify the highest-quality papers. While several measures exist to evaluate a paper's impact post-publication, the challenge of determining the potential impact of a manuscript during the review process remains an understudied issue. In this paper, we propose a reviewer-reputation ranking algorithm to identify high-quality papers based on paper citations, where a reviewer's reputation is computed from the correlation between their past ratings and the current number of citations received by the papers they have evaluated. During the review process, reviewers with high reputation scores are given more weight to determine the quality of papers. We test the algorithm on an artificial network with 200 reviewers and 600 papers, as well as on the American Physical Society (APS) data set, including in the analysis 308,243 papers and 274,154 mutual citations. We compare our approach with two existing methods, demonstrating that our algorithm significantly outperforms the others in identifying manuscripts with the highest quality. Our findings can help improve the impact of scientific journals, thereby contributing to academic and scientific progress. • We propose an algorithm to identify the papers with the highest quality from a large number of submissions. • We compare our new algorithm with other existing methods of aggregating user ratings in various online services. • We test our algorithm both with an artificial network and with the empirical data of the APS data set. • We show that our algorithm outperforms the other methods in identifying the papers with the highest quality. [ABSTRACT FROM AUTHOR]

A text generation based multidisciplinary problem identification method is proposed, which does not rely on a large amount of data annotation. The proposed method first identifies the research objective types and disciplinary labels of papers using a text classification technique; second, it generates abstractive titles for each paper based on abstract and research objective types using a generative pre-trained language model; third, it extracts problem phrases from generated titles according to regular expression rules; fourth, it creates problem relation networks and identifies the same problems by exploiting a weighted community detection algorithm; finally, it identifies multidisciplinary problems based on the disciplinary labels of papers. Experiments in the "Carbon Peaking and Carbon Neutrality" field show that the proposed method can effectively identify multidisciplinary research problems. The disciplinary distribution of the identified problems is consistent with our understanding of multidisciplinary collaboration in the field. It is necessary to use the proposed method in other multidisciplinary fields to validate its effectiveness. Multidisciplinary problem identification helps to gather multidisciplinary forces to solve complex real-world problems for the governments, fund valuable multidisciplinary problems for research management authorities, and borrow ideas from other disciplines for researchers. This approach proposes a novel multidisciplinary problem identification method based on text generation, which identifies multidisciplinary problems based on generative abstractive titles of papers without data annotation required by standard sequence labeling techniques. [ABSTRACT FROM AUTHOR]

The International Journal of Market Research (IJMR) is celebrating its sixty-fifth anniversary. Over the past decade, the journal has experienced significant growth in readership, impact factor, citations, and submissions. While the majority of accepted papers come from the United States, United Kingdom, Australia, and Germany, the journal aims to bridge the gap between academia and practice in the field of market research. In order to enhance its relevance and accessibility, IJMR will transition to an online-only format, adopt an interdisciplinary focus, provide guidelines for more user-friendly article formats, and publish a list of research priorities based on the perspectives of leading practitioners. [Extracted from the article]

Sustainable degrowth offers effective alternative strategies for tackling social and environmental problems such as climate crisis, resource depletion, biodiversity loss, and species hecatomb. However, it plays a marginal role in policy. Moreover, researchers need to operationalise many degrowth proposals in a more sufficient way for the policy. This mainly conceptual-methodological article conceptualises the problem of sustainable degrowth in policy as the problem of knowledge utilisation. How well research papers on the topic adapt to the needs of policy-makers is an important factor influencing this utilisation. This adaptation is under the control of researchers and may be seen as a necessary first step in the introduction of degrowth proposals into policy-making and further implementation. I argue that translating research papers into legislative drafts by researchers can be understood as adaptation of these papers to the policy-makers' needs. This is because the law can be understood as universal basis of public policies and fundamental language to express these policies. The legal system has a systematic, hierarchical, and logical structure while its language tends to be precise, clear, and unambiguous. Legal language may also be salient for many policy-makers. I labelled this way of adaptation as the Translational Legal Approach to Knowledge Utilisation (TLA). It can be applied beyond texts on sustainable degrowth as well. Based on the literature review, I theoretically and conceptually discuss the aforementioned hypotheses by looking at the corresponding criteria of research adaptation with characteristics of law and legal language. I provide the strongest support for the theses that translation of research papers into provisions of legislative drafts can increase readability, comprehensibility, precision, and operationalisation of degrowth research proposals, as well as helps to give them more systemic nature and incorporate policy-makers' context. Future research is needed to create a methodological framework for TLA as well as to empirically verify hypotheses made in this article. • Degrowth plays a marginal role in policies and needs better operationalisation. • The role of degrowth in policy can be seen as a problem of knowledge utilisation. • Law could be a common language between researchers and policy-makers. • Translating research papers into legislative drafts adapts them for policy-makers. • Translating degrowth proposals into legislative drafts supports their utilisation. [ABSTRACT FROM AUTHOR]

Scientific papers, as pivotal tools for academic communication, should be articulated with clarity and precision to ensure the effective conveyance of scholarly ideas and to prevent reader confusion. Yet, many such papers conspicuously lack in-depth research, and their core content is often ambiguously presented. This pattern poses a significant impediment to the progressive evolution of science and technology. While numerous researchers have recognized this widespread challenge, a holistic theoretical or methodological solution remains elusive in the academic realm. To bridge this gap, we introduce the INTEGrity vERification (INTEGER) task. This task aids researchers in assessing the integrity of their papers by verifying the clarity of each knowledge unit. To implement this task on text, we propose a multi-task learning model that utilizes the Tucker decomposition and span-level attention mechanism to identify terms and their integrity precisely. More specifically, to provide insights into the INTEGER task and validate the effectiveness of the proposed model, we collect 8076 sentences and construct three new datasets containing various types of terms and descriptions in different domains. Extensive experimental results show that our proposed model has an average performance improvement of 1.1% F1 over the three datasets compared to a series of state-of-the-art baseline methods. [ABSTRACT FROM AUTHOR]

Background: Cancer is a major public health challenge globally. However, little is known about the evolution patterns of cancer research communities and the influencing factors of their research capacity and impact, which is affected not only by the social networks established through research collaboration but also by the knowledge networks in which the research projects are embedded. Methods: The focus of this study was narrowed to a specific topic – 'synthetic lethality' – in cancer research. This field has seen vibrant growth and multidisciplinary collaboration in the past decade. Multi-level collaboration and knowledge networks were established and analysed on the basis of bibliometric data from 'synthetic lethality'-related cancer research papers. Negative binomial regression analysis was further applied to explore how node attributes within these networks, along with other potential factors, affected paper citations, which are widely accepted as proxies for assessing research capacity and impact. Results: Our study revealed that the synthetic lethality-based cancer research field is characterized by a knowledge network with high integration, alongside a collaboration network exhibiting some clustering. We found significant correlations between certain factors and citation counts. Specifically, a leading status within the nation-level international collaboration network and industry involvement were both found to be significantly related to higher citations. In the individual-level collaboration networks, lead authors' degree centrality has an inverted U-shaped relationship with citations, while their structural holes exhibit a positive and significant effect. Within the knowledge network, however, only measures of structural holes have a positive and significant effect on the number of citations. Conclusions: To enhance cancer research capacity and impact, non-leading countries should take measures to enhance their international collaboration status. For early career researchers, increasing the number of collaborators seems to be more effective. University–industry cooperation should also be encouraged, enhancing the integration of human resources, technology, funding, research platforms and medical resources. Insights gained through this study also provide recommendations to researchers or administrators in designing future research directions from a knowledge network perspective. Focusing on unique issues especially interdisciplinary fields will improve output and influence their research work. [ABSTRACT FROM AUTHOR]

Early detection of Toxoplasma gondii (T. gondii) is critical due to a lack of effective treatment for toxoplasmosis.This study established a simple, cost-effective, and rapid colorimetric detection method for T. gondii. The entire testing process, from sample collection to results, takes only 0.5 h. These characteristics fulfill the demands of researchers seeking rapid target detection with minimal equipment reliance. For genomic extraction, this study evaluated the ability of two filter papers to capture genomes. A rapid genomic extraction device combined with the two filter papers was designed to simplify the genomic extraction process, which was completed within 10 min and increased the detection sensitivity tenfold. The method utilized a simplified primer design for isothermal amplification, namely allosteric strand displacement (ASD), and employed an underutilized commercial color indicator, Bromothymol Blue (BTB), for signal output. Compared with other reported indicators, BTB exhibited a more pronounced color change, shifting from blue to yellow in positive samples, facilitating easier visual differentiation. The reaction was completed in 20 min with a limit of detection (LOD) as low as 0.014 T. gondii per microliter. [ABSTRACT FROM AUTHOR]

The more science advances, the more questions are asked. This compounding growth can make it difficult to keep up with current research directions. Furthermore, this difficulty is exacerbated for junior researchers who enter fields with already large bases of potentially fruitful research avenues. In this paper, we propose a novel task and a recommender system for research directions, RecSOI, that draws from statements of ignorance (SOIs) found in the research literature. By building researchers' profiles based on textual elements, RecSOI generates personalized recommendations of potential research directions tailored to their interests. In addition, RecSOI provides context for the recommended SOIs, so that users can quickly evaluate how relevant the research direction is for them. In this paper, we provide an overview of RecSOI's functioning, implementation, and evaluation, demonstrating its effectiveness in guiding researchers through the vast landscape of potential research directions. [ABSTRACT FROM AUTHOR]

This paper proposes diary studies as a methodological choice for addressing crucial questions in qualitative process research. Diary studies unearth within-individual relationships that capture individual experiences and sense-making of these experiences in a processual manner. Therefore, using diary studies not only addresses the need for more dynamic methodological designs in qualitative research, but is advantageous for providing a process view of how the individual engages with the constructs studied. While process-studies, studied longitudinally, are often fraught with challenges of attrition or disengagement, this paper discusses how a methodological choice which is perceived as being beneficial by the participant can sustain engagement and consequently, research rigour. On one hand, a comparison of interview and diary data from the same participants show evidence of memory decay in interviews and reinforce the rigour of diary studies in the study of processual phenomenon. On the other hand, this study also showcases how researcher know-how, unintentionally imparted through reflective and processual questions asked in the study positively impacts the participants, and when reflected on, enhanced learning. This paper therefore demonstrates the ability of a research method to benefit both the research and the researched, and suggests a step-by-step design to implement a rigorous and impactful diary study using user-friendly forms and reflective questioning. [ABSTRACT FROM AUTHOR]

In the growing halal industry, there are differences of opinion among researchers about the effect of Islamic attributes on consumer satisfaction. Therefore, this paper aims to evaluate the effect of Islamic attributes on consumer satisfaction. The Prisma flow diagram indicated 23 papers and consists of 59 studies to analyze with JASP Software. The study identifies significant authors, dominant publishers, methodology, and theories commonly employed in this topic. The result proves that catering to Muslim needs through Islamic attributes can significantly enhance consumer satisfaction and the presence of other variables as moderators will strengthen tourist satisfaction. [ABSTRACT FROM AUTHOR]

Conventional statistics methods in most psychological research, such as null-hypothesis significance tests (NHSTs), use aggregated values (i.e., the sample means) of group behaviours to make inferences about individuals. Such inferences are possibly erroneous because groups of humans rarely, if ever, constitute an ergodic system. To assume ergodicity without checking is to commit the 'ergodic fallacy'. The aim of the current study was to examine the prevalence of this error in contemporary psychological research. We analysed three highly cited 'Q1' journals in the fields of clinical, educational and cognitive psychology for statements that indicated this error. As hypothesized, the ergodic fallacy was found in the vast majority of the papers investigated here. We also hypothesised that the prevalence of this error would be highest in cognitive psychology papers because this field typically assesses theoretical claims about universal cognitive mechanisms, whereas clinical and educational psychology are more concerned with empirically supported interventions. This hypothesis was also supported by our results. Nonetheless, the prevalence of the ergodic fallacy was still high in all fields. Implications are discussed with respect to the reporting of research findings and the validity of theories in psychology. [ABSTRACT FROM AUTHOR]

Fake news is an explosive subject, being undoubtedly among the most controversial and difficult challenges facing society in the present-day environment of technology and information, which greatly affects the individuals who are vulnerable and easily influenced, shaping their decisions, actions, and even beliefs. In the course of discussing the gravity and dissemination of the fake news phenomenon, this article aims to clarify the distinctions between fake news, misinformation, and disinformation, along with conducting a thorough analysis of the most widely read academic papers that have tackled the topic of fake news research using various machine learning techniques. Utilizing specific keywords for dataset extraction from Clarivate Analytics' Web of Science Core Collection, the bibliometric analysis spans six years, offering valuable insights aimed at identifying key trends, methodologies, and notable strategies within this multidisciplinary field. The analysis encompasses the examination of prolific authors, prominent journals, collaborative efforts, prior publications, covered subjects, keywords, bigrams, trigrams, theme maps, co-occurrence networks, and various other relevant topics. One noteworthy aspect related to the extracted dataset is the remarkable growth rate observed in association with the analyzed subject, indicating an impressive increase of 179.31%. The growth rate value, coupled with the relatively short timeframe, further emphasizes the research community's keen interest in this subject. In light of these findings, the paper draws attention to key contributions and gaps in the existing literature, providing researchers and decision-makers innovative viewpoints and perspectives on the ongoing battle against the spread of fake news in the age of information. [ABSTRACT FROM AUTHOR]

Purpose: The primary purpose of this paper is to provide an analysis of the key perspectives that emerge in this Accounting, Auditing & Accountability Journal (AAAJ) Special Issue as a basis for determining the existence or otherwise of a Soccer Society, as well as reflecting on the challenges that evidence of corruption in soccer (the beautiful game) has had on the game to date. Reflections on these matters are then utilised to offer a prospective analysis of issues for further research. Design/methodology/approach: The paper is a reflective analysis that draws on existing societal work to provide key dimensions of accounting and accountability for significant organisations in the world of sport in general and soccer in particular. Findings: Much prior research on soccer has largely focussed on the internal workings of soccer organisations, with little discussion of the importance of context. This paper explores the influence of the game more broadly. Moreover, a number of the papers included illustrate an overwhelming sense of joy and pleasure from experiences of the beautiful game, as well as providing evidence of the general societal good that can flow from it. However, the study also highlights concerns emanating from weak, and seemingly pliable, governance, regulatory and accountability regimes that provide a fertile field for corruption and sportswashing. Research limitations/implications: This paper highlights a research agenda as an encouragement to interdisciplinary accounting researchers to investigate accountability and governance issues as a basis for evidence-based discussions of the impact of soccer and its regulation. Originality/value: This paper specifically, and the Special Issue more broadly, offers a set of original empirical and theoretical contributions with respect to an activity that has faced limited scrutiny and consideration by academic accountants. Together, they offer a substantive body of work to enable future research in this area. [ABSTRACT FROM AUTHOR]

Academic researchers publish their work in various formats, such as papers, patents, and research reports, on different academic sites. When searching for a particular researcher's work, it can be challenging to pinpoint the right individual, especially when there are multiple researchers with the same name. In order to handle this issue, we propose a name disambiguation scheme for researchers with the same name based on heterogeneous academic sites. The proposed scheme collects and integrates research results from these varied academic sites, focusing on attributes crucial for disambiguation. It then employs clustering techniques to identify individuals who share the same name. Additionally, we implement the proposed rule-based algorithm name disambiguation method and the existing deep learning-based identification method. This approach allows for the selection of the most accurate disambiguation scheme, taking into account the metadata available in the academic sites, using a multi-classifier approach. We consider various researchers' achievements and metadata of articles registered in various academic search sites. The proposed scheme showed an exceptionally high F1-measure value of 0.99. In this paper, we propose a multi-classifier that executes the most appropriate disambiguation scheme depending on the inputted metadata. The proposed multi-classifier shows the high F1-measure value of 0.67. [ABSTRACT FROM AUTHOR]

Early Childhood Education and Care (ECEC) places value and benefits on children's play in nature-based outdoor spaces. However, there is a lack of knowledge regarding teachers' support of play in environments with rugged terrains and natural materials. Therefore, this systematic review aims to locate, present, and discuss research literature on how teachers in ECEC settings can support children's play in nature-based outdoor spaces. According to the review, teachers' support of children's play was described in the literature as encouraging children's free and unstructured play through facilitating actions addressing the children's perspectives and the opportunities offered by the physical environment. Furthermore, teacher support was also described as teacher-led and teacher-guided interactions where teachers and children communicate or collaborate in playful situations. Differences and overlapping elements of types of teacher support are discussed, and implications for researchers, practitioners, and ECEC teacher education are provided. [ABSTRACT FROM AUTHOR]

With the rapid growth in urban construction in Malaysia, road breakage has challenged traditional manual inspection methods. In order to quickly and accurately detect the extent of road breakage, it is crucial to apply automated road crack detection techniques. Researchers have long studied image-based road crack detection techniques, especially the deep learning methods that have emerged in recent years, leading to breakthrough developments in the field. However, many issues remain in road crack detection methods using deep learning techniques. The field lacks state-of-the-art systematic reviews that can scientifically and effectively analyze existing works, document research trends, summarize outstanding research results, and identify remaining shortcomings. To conduct a systematic review of the relevant literature, a bibliometric analysis and a critical analysis of the papers published in the field were performed. VOSviewer and CiteSpace text mining tools were used to analyze and visualize the bibliometric analysis of some parameters derived from the articles. The history and current status of research in the field by authors from all over the world are elucidated and future trends are analyzed. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) technology has become an inevitable part of our daily lives. With the increase in usage of IoT Devices, manufacturers continuously develop IoT technology. However, the security of IoT devices is left behind in those developments due to cost, size, and computational power limitations. Since these IoT devices are connected to the Internet and have low security levels, one of the main risks of these devices is being compromised by malicious malware and becoming part of IoT botnets. IoT botnets are used for launching different types of large-scale attacks including Distributed Denial-of-Service (DDoS) attacks. These attacks are continuously evolving, and researchers have conducted numerous analyses and studies in this area to narrow security vulnerabilities. This paper systematically reviews the prominent literature on IoT botnet DDoS attacks and detection techniques. Architecture IoT botnet DDoS attacks, evaluations of those attacks, and systematically categorized detection techniques are discussed in detail. The paper presents current threats and detection techniques, and some open research questions are recommended for future studies in this field. [ABSTRACT FROM AUTHOR]

Purpose: This article introduces the AAAJ special issue's content and, in so doing, aims to reflect on the contribution that accounting as a discipline is placed to make within the more contemporary context of space exploration, the space economy and public space policy. Design/methodology/approach: The paper draws together, identifies, expands upon and advances opportunities available to researchers seeking to investigate the ways in which accounting research and practice might inform the modern space sector. Findings: Papers comprising the AAAJ special issue are informed by authors with diverse research backgrounds (including various accounting subfields and non-accounting business disciplines) and varying methodological approaches, including positivist, interpretivist as well as critical research paradigms. Interestingly, the call for papers also attracted several non-accounting academics or academics who have not traditionally undertaken or engaged appreciably with accounting research. This diverse approach to addressing initial space accounting questions should help establish a firm launching point for future research advances. Originality/value: The paper's originality lies in advancing a need to engage with the unique demands of "the New Space Age", requiring fundamentally innovative approaches to many aspects of accounting such as financial accounting, management accounting and sustainability accounting as well as contextualising or re-contextualising current accounting concepts, principles and thinking to apply to a new setting. [ABSTRACT FROM AUTHOR]

Online research methods have grown in popularity due in part to the globalised and far-reaching nature of the internet but also linked to the Covid-19 pandemic whereby restrictions to travel and face to face contact necessitated a shift in methods of research recruitment and data collection. Ethical guidance exists to support researchers in conducting online research, however this is lacking within health fields. This scoping review aims to synthesise formal ethical guidance for applying online methods within health research as well as provide examples of where guidance has been used. A systematic search of literature was conducted, restricted to English language records between 2013 and 2022. Eligibility focused on whether the records were providing ethical guidance or recommendations, were situated or relevant to health disciplines, and involved the use or discussion of online research methods. Following exclusion of ineligible records and duplicate removal, three organisational ethical guidance and 24 research papers were charted and thematically analysed. Four key themes were identified within the guidance documents, 1) consent, 2) confidentiality and privacy, 3) protecting participants from harm and 4) protecting researchers from harm with the research papers describing additional context and understanding around these issues. The review identified that there are currently no specific guidelines aimed at health researchers, with the most cited guidance coming from broader methodological perspectives and disciplines or auxiliary fields. All guidance discussed each of the four key themes within the wider context of sensitive topics and vulnerable populations, areas and issues which are often prominent within health research thus highlighting the need for unifying guidance specific for health researchers. Further research should aim to understand better how online health studies apply ethical principles, to support in informing gaps across both research and guidance. [ABSTRACT FROM AUTHOR]

Clinical named entity extraction (NER) based on deep learning gained much attention among researchers and data analysts. This paper proposes a NER approach to extract valuable Parkinson’s disease-related information. To develop an effective NER method and to handle problems in disease data analytics, a unique NER technique applies a “recognize-map-extract (RME)” mechanism and aims to deal with complex relationships present in the data. Due to the fast-growing medical data, there is a challenge in the development of suitable deep-learning methods for NER. Furthermore, the traditional machine learning approaches rely on the time-consuming process of creating corpora and cannot extract information for specific needs and locations in certain situations. This paper presents a clinical NER approach based on a convolutional neural network (CNN) for better use of specific features around medical entities and analyzes the performance of the proposed approach through fine-tuning NER with effective pre-training on the BC5CDR dataset. The proposed method uses annotation of entities for various medical concepts. The second stage develops a clinically NER method. This proposed method shows interesting results on the performance measures achieving a precision of 92.57%, recall of 92.22%, and F1- measure of 91.6% [ABSTRACT FROM AUTHOR]

Increasing research efforts are focused on studying the synthesis and mechanisms of nanomedicine in urologic cancer. We performed a bibliometric study of the literature on nanomedicine in urologic cancer over the last 23 years, focusing on aspects such as researchers, institutions, nations, and keywords. We searched for papers in the Web of Science Core Collection from January 1, 2001, to December 29, 2023. Only reviews and original articles written in English were considered. A total of 2386 papers satisfied the given criteria for inclusion. The publications included in the study originated from 90 nations. The United States had the largest number of published papers, accounting for more than 31.01% of the total. The leading institution in this field is the Chinese Academy of Sciences, with a publishing output of 2.35%. Farokhzad, Omid C., is the most prolific author, with 21 articles, and has garnered the most citations, totaling 6271. The latest phrase to enter the top ten most common lists was "gold nanoparticles." We searched for papers in the Web of Science Core Collection from January 1, 2000, to November 28, 2023. Only reviews and original articles written in English were considered. This is the first bibliometric study of nanomedicine in urologic cancer. This article provides a comprehensive analysis of the current state of research on nanomedicine in urologic cancer over the last 23 years. On the basis of this study, future researchers can identify noteworthy publications, journals, and potential collaborators and explore cutting-edge research directions. [ABSTRACT FROM AUTHOR]

Public engagement with research (PEwR) has become increasingly integral to research practices. This paper explores the process and outcomes of a collaborative effort to address the ethical implications of PEwR activities and develop tools to navigate them within the context of a University Medical School. The activities this paper reflects on aimed to establish boundaries between research data collection and PEwR activities, support colleagues in identifying the ethical considerations relevant to their planned activities, and build confidence and capacity among staff to conduct PEwR projects. The development process involved the creation of a taxonomy outlining key terms used in PEwR work, a self-assessment tool to evaluate the need for formal ethical review, and a code of conduct for ethical PEwR. These tools were refined through iterative discussions and feedback from stakeholders, resulting in practical guidance for researchers navigating the ethical complexities of PEwR. Additionally, reflective prompts were developed to guide researchers in planning and conducting engagement activities, addressing a crucial aspect often overlooked in formal ethical review processes. The paper reflects on the broader regulatory landscape and the limitations of existing approval and governance processes, and prompts critical reflection on the compatibility of formal approval processes with the ethos of PEwR. Overall, the paper offers insights and practical guidance for researchers and institutions grappling with ethical considerations in PEwR, contributing to the ongoing conversation surrounding responsible research practices. Plain English summary: This paper talks about making research fairer for everyone involved. Sometimes, researchers ask members of the public for advice, guidance or insight, or for help to design or do research, this is sometimes known as 'public engagement with research'. But figuring out how to do this in a fair and respectful way can be tricky. In this paper, we discuss how we tried to make some helpful tools. These tools help researchers decide if they need to get formal permission, known as ethical approval, for their work when they are engaging with members of the public or communities. They also give tips on how to do the work in a good and fair way. We produced three main tools. One helps people understand the important words used in this kind of work (known as a taxonomy). Another tool helps researchers decide if they need to ask for special permission (a self-assessment tool). And the last tool gives guidelines on how to do the work in a respectful way (a code of conduct). These tools are meant to help researchers do their work better and treat everyone involved fairly. The paper also talks about how more work is needed in the area, but these tools are a good start to making research fairer and more respectful for everyone. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to review the literature extensively by analysing recent work and providing a guide for models, data sets and research findings. Design/methodology/approach: This paper reviews the literature extensively by analysing recent work and providing a guide for models, data sets and research findings within the context of capital market imperfections. The authors further break down the literature into closer-in-nature categories for reader's convenience and comprehension. Finally, the authors address gaps in the existing literature and propose government policies that can tone down the potential effect of credit rationing on employment. Findings: This paper provides a map of the literature so as to help future researchers in the relevant literature and give a short insight of what has been explored so far. Originality/value: This paper is original and is the result of a thorough review of an extensive literature. [ABSTRACT FROM AUTHOR]

The biometrics system is mainly focuses on fingerprint recognition and how this system would be implemented. If it is implemented in research area, this system would authenticate or contradict the uniqueness of each individual endeavouring to gain access to the research region with a given sum of precision. The method of authenticating a person's identity through a comparison of their fingerprints with previously captured samples is known as fingerprint recognition. Human finger impressions in the form of ridges and grooves are called fingerprints. The minutiae points, or the places where scars start or end, are used to locate fingerprints stored in the system. To create a minutiae template, these are further mapped with lines connecting them. An additional key challenge of this will understand the methods used to analysed the information from the scan. There are several different methods has been implemented by different researchers for the fingerprint recognition system. In this paper the literature of the different approaches are discussed. [ABSTRACT FROM AUTHOR]