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This paper aims to investigates a novel design of a modular moving magnet linear oscillating actuator (MMM-LOA) with the capability of coupling modules, based on their application and space requirements.

Proposed design comprised of modules, and modules are separated by using nonmagnetic materials. Movable part of the proposed design of LOA is composed of permanent magnets (PMs) having axial magnetization direction and tubular structure. Stator of the proposed design is composed of one coil individually in a module. Dimensions of the design parameters are optimized through parametric analysis using COMSOL Multi Physics software. This design is analyzed up to three modules and their response in term of electromagnetic (EM) force and stroke are presented. Influence of adding modules is analyzed for both directions of direct current (DC) and alternating input loadings.

Proposed LOA shows linear increase in magnitude of EM force by adding modules. Motor constant of the investigated LOA is 264 N/A and EM force per PM mass is 452.389 N/kg, that shows significant improvement. Moreover, proposed LOA operates in feasible region of stroke for compressor application. Furthermore, this design uses axially magnetized PMs which are low cost and available in compact tubular structure.

Proposed LOA shows the influence of adding modules and its effect in term of EM force is analyzed for DC and alternating current (AC). Moreover, overall performance and structural topology is compared with state-of-the-art designs of LOA. Improvement with regard of motor constant and EM force per PM mass shows originality and scope of this paper.

This study aims to explore the scientific research progress in the field of “Rural Livelihood” from 1991 to 2022.

A total of 2,122 documents were extracted from the Web of Science Core Collection using the key terms “Rural Livelihood” OR “Rural Livelihoods” in the “Title-Abstract-Keyword” field. The statistical analysis was performed through VOSviewer, Bibliometrix, Biblioshiney open-source package of R language environment, and MS Office software.

The results show that the first research article related to the field of rural livelihood was published in 1991, and the rapid growth in the publications of rural livelihood was observed since 2000, with a positive annual growth rate of 14.87%. Shackleton CM (n = 30 articles) and Belcher B (n = 1235 citations) are the most productive and highly cited authors in the field of rural livelihood, respectively. World Development is the most prolific and dominant journal, followed by Sustainability and Land Use Policy. The citation analysis disclosed that “Capitals and capabilities: a framework for analysing peasant viability, rural livelihoods and poverty” is the most cited research paper published in the field of rural livelihood by Anthony Bebbington. University of Copenhagen, Wageningen University and Rhodes University emerged as the topmost organizations engaged in rural livelihood research. The USA and the UK are the most productive and cited countries in rural livelihood. The keyword analysis revealed that most of the research published in the field of rural livelihood has focussed on rural livelihoods, management, conservation, poverty, strategies, climate change, etc.; however, the least emphasis is given on the subjects like food security, income diversification, biodiversity, deforestation, soil fertility management, bio-economy and environmental intervention. The thematic evolution reflects that the field of rural livelihood has been extensively researched and has undergone many dimensions, such as agriculture, management, conservation, climate change, households, policy and biodiversity.

The study’s findings provide an insight into global research trends, latest advances, hot issues, leading topics, and the thematic evolution of rural livelihood research over the last 31 years approximately. This study is quite useful to researchers and stakeholders to obtain rigorous bibliographic knowledge on literature related to the topic and work accordingly for R&D activities.

There have been numerous publications on human monkeypox since it was reported. With the help of bibliometric analysis, this study examined research hotspots and future trends related to human monkeypox. Science mapping was used in this study to identify influential monkeypox researchers, institutions, articles, keywords, thematic structures, and clusters of articles.

Based on a validated search query, bibliometric analysis of data collected from Web of Science from 1989 to September 2022 was conducted. Using the “Title-Keyword-Abstract” search option, the search query consisted of keywords “Monkeypox” OR “Monkeypox virus” OR “monkeypox” OR “monkey pox” OR “MPXV.” With the state-of-the-art tools Bibliometrix package of R Studio and VOSviewer, performance analysis and science mapping, as a part of standard bibliometric research of monkeypox research were conducted.

Researchers published 708 monkeypox papers from 1989 to September 2022, with American researchers publishing 460 papers. Further, USA had the highest international cooperation in terms of collaborative research output. Centers for Disease Control and Prevention (CDC) is a global leader in monkeypox research since it is the most prolific and collaborative organization. There have been the most published papers on monkeypox in the Journal of Virology. Damon Inger K is also the most prolific and influential researcher in monkeypox research, with the highest number of publications and citations. In total, 1,679 keywords were identified in the study. From the cluster analysis four themes were identified in monkeypox research. They are (1) clinical features, (2) monkeypox virus epidemiology, (3) monkeypox virus vaccine defense, and (4) monkeypox virus-related treatment measures.

Analysis of collaboration, findings, networks of research, and visualization separates this study from traditional metrics analysis. Currently, there are no similar studies with similar objectives based on the authors' knowledge.

The emotion regulation research has drawn considerable attention from academicians and scholars in the contemporary world. As a result, the publications that are specifically dedicated to emotion regulation research are rapidly escalating. Therefore, this study aims to conduct a bibliometric analysis of research articles that have been published in the field of “emotion regulation.” The study primarily examines the growth and development of scholarly publications, seminal studies, influential authors, productive journals, research production and collaboration among countries, emerging research themes, research hotspots and thematic evolution of emotion regulation research.

The Web of Science Core Collection database was used to gather the study’s data, which was then analysed using VOSviewer and Bibliometrix, Biblioshiney open-source package of the R language environment.

The study’s results reveal that the research on emotion regulation has grown significantly over the last three decades. Notably, Emotion and Frontiers in Psychology are the most dominant and productive journals in the field of emotion regulation research. The most prominent author in the area of emotion regulation is identified as James Gross, followed by Gratz, Wang and Tull. The USA is at the forefront of research on emotion regulation and has collaborated with most of the developed countries like Germany, England and Canada. The keyword analysis revealed that the most potential research areas in the field of emotion regulation are functional magnetic resonance imaging, amygdala, post-traumatic stress disorder, borderline personality disorder, alexithymia, emotion dysregulation, depression, anxiety, functional connectivity, neuroimaging, mindfulness, self-regulation, resilience and coping. The thematic evolution reflects that the research on emotion regulation has recently focused on issues including Covid-19, non-suicidal self-injury, psychological distress, intimate partner violence and mental health.

The results of this study highlighted the current knowledge gaps in emotion regulation research and suggested areas for further investigation. The present study could be useful for researchers, academicians, planners, publishers and universities engaged in emotion regulation research.

This study aims to investigate the research and citation impact of open access (OA) journals versus non-OA journals being published in the spectrum of library and information science (LIS) across the world and to further ascertain whether OA journals have greater citation counts than subscription-based journals in LIS discipline.

A total of 116 LIS journals (58 OA and 58 non-OA) were chosen from Scimago website. After selecting the journals, Publish or Perish software program was used to retrieve the publications and their corresponding academic citations by using International Standard Serial Number of journals from Google Scholar for the period of 2011–2018. The non-parametric Mann–Whitney U-test was applied on various research and citation indicators, namely, citation count, citations per author, citations per paper; g-index, h-index, hI norm and hI annual through SPSS.

Findings of the study demonstrate that non-OA journals in LIS have a significant citation advantage over OA journals. Moreover, Mann–Whitney U-test analysis rejected all the eight null hypotheses and reveals that non-OA journals in LIS discipline have greater citation counts, citations per author, citations per paper; g-index, h-index, hI norm and hI annual than OA journals.

To the best of the authors’ knowledge, this is the first study that embarks upon a whole-scale investigation of citation impact of OA and non-OA journals in LIS, which has implications for both research and practice. This study would serve as a reference guide to all involved in scholarly communication activities including academic communities, librarians, research funders, publishers and policymakers for publishing research work, grant funding, designing policies and subscriptions.

Tags are used to annotate resources on social media platforms. Most tag recommendation methods use popular tags, but in the case of new resources that are as yet untagged (the cold start problem), popularity-based tag recommendation methods fail to work. The purpose of this paper is to propose a novel model for tag recommendation called multi-feature space latent Dirichlet allocation (MFS-LDA) for cold start problem.

MFS-LDA is a novel latent Dirichlet allocation (LDA)-based model which exploits multiple feature spaces (title, contents, and tags) for recommending tags. Exploiting multiple feature spaces allows MFS-LDA to recommend tags even if data from a feature space is missing (the cold start problem).

Evaluation of a publicly available data set consisting of around 20,000 Wikipedia articles that are tagged on a social bookmarking website shows a significant improvement over existing LDA-based tag recommendation methods.

The originality of MFS-LDA lies in segregation of features for removing bias toward dominant features and in synchronization of multiple feature space for tag recommendation.

The purpose of this research study is to extract and identify named entities from Hadith literature. Named entity recognition (NER) refers to the identification of the named entities in a computer readable text having an annotation of categorization tags for information extraction. NER is an active research area in information management and information retrieval systems. NER serves as a baseline for machines to understand the context of a given content and helps in knowledge extraction. Although NER is considered as a solved task in major languages such as English, in languages such as Urdu, NER is still a challenging task. Moreover, NER depends on the language and domain of study; thus, it is gaining the attention of researchers in different domains.

This paper proposes a knowledge extraction framework using finite-state transducers (FSTs) – KEFST – to extract the named entities. KEFST consists of five steps: content extraction, tokenization, part of speech tagging, multi-word detection and NER. An extensive empirical analysis using the data corpus of Urdu translation of Sahih Al-Bukhari, a widely known hadith book, reveals that the proposed method effectively recognizes the entities to obtain better results.

The significant performance in terms of f-measure, precision and recall validates that the proposed model outperforms the existing methods for NER in the relevant literature.

This research is novel in this regard that no previous work is proposed in the Urdu language to extract named entities using FSTs and no previous work is proposed for Urdu hadith data NER.

This study aims to investigate the public deficit issue by contrasting conventional and Islamic views encompassing the paradigm, technical base, orientation and consequence detailed in nine discussions, which are rarely investigated in the research. There is a predisposition that contemporary Muslim scholars discuss the public deficit as well as the private sector perspective, which is used in the conventional conception, without riba as a primary feature.

The paper develops a comparative approach that derives two perspectives from the available literature using the qualitative method under the critical thinking method. It was drawn up in detail on how the paradigm and its related budgeting process contribute to public deficits, mainly in government institutions.

The paper reveals a prominent difference in public deficit in the Islamic view from a conventional perspective. From 9 points of comparison, the analysis covers 18 discussion that differentiates between private and public area criticism seems to overlap. The foundation giving a unique perspective in Islam toward public deficit is the concept of ownership that differs from capitalism, mainly the function of public spending is to distribute the wealth among people not for economic growth. The Islamic Government spent for public purposes based on cash-basis budgeting. The budgeting system in Islamic public spending is founded on treasure availability.

The paper uses a qualitative method that cannot empirically snapshot the actual or factual condition, in which subjectivity plays a plausible role. Furthermore, there is no actual sample (best practices) of the concept to be examined.

The research encompasses overlap between Islamic and conventional perspectives, including public and private issues regarding public deficits. The main beneficiary of the paper is a policymaker, including academicians or practitioners who are appropriate to use the concept in their circumstances.

The study is a pioneering study in public deficit comprehensively comparing conventional and Islamic perspectives and drawing up conceptual and technical aspects.

For over three decades, Afghanistan has been a battleground in which many of the states of the wider neighbourhood have been involved. The importance of fostering a concerted effort for Afghan peace and stability is widely agreed upon, yet such a process remains difficult to bring about. Some analysts emphasize states and their security relationships, seeing Afghanistan as an ‘insulator’ caught between different regional state systems, each with a strong dynamic of its own. Other analysts emphasize various transnational networks and see Afghanistan as the ‘core’ of a larger conflict formation. This chapter takes as its starting point the former perspective, which has been codified by Barry Buzan and Ole Wæver (2003) as the regional security complex (RSC) approach. The chapter examines the security dynamics of each of the regions surrounding Afghanistan – South Asia, the Persian Gulf and South Asia – adopting a comparative and historical perspective, with an emphasis on the period since the late 1970s. It concludes that each of Afghanistan's three surrounding regions is characterized by deep security concerns of its own. These concerns nonetheless inform the engagement of neighbouring countries in Afghanistan, which then comes to reflect conflicts and cleavages specific to the respective regions. One central implication is that a more promising strategy for Afghanistan might be to seek a unilateral non-offensive or neutral status, rather than full security integration with its neighbours. Although such a strategy would necessitate the creation of a forum for Afghanistan's neighbours to foster understanding for the Afghan position, it represents a dramatic departure from mainstream policy proposals with their emphasis on an integrated regional approach.

The purpose of this paper is to apply state-of-the-art machine learning techniques for assessing the quality of the restaurants using restaurant inspection data. The machine learning techniques are applied to solve the real-world problems in all sphere of life. Health and food departments pay regular visits to restaurants for inspection and mark the condition of the restaurant on the basis of the inspection. These inspections consider many factors that determine the condition of the restaurants and make it possible for the authorities to classify the restaurants.

In this paper, standard machine learning techniques, support vector machines, naïve Bayes and random forest classifiers are applied to classify the critical level of the restaurants on the basis of features identified during the inspection. The importance of different factors of inspection is determined by using feature selection through the help of the minimum-redundancy-maximum-relevance and linear vector quantization feature importance methods.

The experiments are accomplished on the real-world New York City restaurant inspection data set that contains diverse inspection features. The results show that the nonlinear support vector machine achieves better accuracy than other techniques. Moreover, this research study investigates the importance of different factors of restaurant inspection and finds that inspection score and grade are significant features. The performance of the classifiers is measured by using the standard performance evaluation measures of accuracy, sensitivity and specificity.

This research uses a real-world data set of restaurant inspection that has, to the best of the authors’ knowledge, never been used previously by researchers. The findings are helpful in identifying the best restaurants and help finding the factors that are considered important in restaurant inspection. The results are also important in identifying possible biases in restaurant inspections by the authorities.