Syamsul Aripin, Nana Meily Nurdiansyah, Armai Arief
et al.
Purpose – This study aims to gain an in-depth understanding of the effectiveness and reformulation of Islamic Religious Education (IRE) in the modern era.
Design/methods/approach – The research method used is a literature study with a descriptive qualitative approach. The data sources and data collection techniques used were obtained from books, journals, or scientific articles, and the analysis technique used was content analysis.
Findings – The results of the study show that, first, changes to Islamic Religious Education in the modern era are very complex, because the elements of modernity continue to undergo changes in terms of teaching, material, methods, and approaches. The effectiveness of Islamic Religious Education (IRE) in the modern era requires a reformulation of learning that is contextual and adaptive. Therefore, the differences that arise due to the development of science and technology need to be seen as a gift that enriches comprehensive and holistic understanding; second, learning is directed at solving the problems of modernity faced by Muslims through scientific, social, and religious approaches; third, the delivery of Islamic knowledge is not dogmatic, but emphasizes historical analysis so that students are able to understand the dynamics of the development of Islamic teachings; fourth, text-based learning methods must be balanced with critical analysis of social realities to make them more applicable; fifth, strengthening the spiritual dimension through Sufism is a fundamental requirement in shaping religious character; sixth, the effectiveness of Islamic Education is not only measured by individual piety, but also by its contribution to building social piety.
Research implications/limitations – Data sources are limited to online and offline scientific literature based on literature reviews as the primary source. Future researchers can use more in-depth techniques and methods such as research and development or case studies.
Originality/value – The results of this study provide knowledge and implications for IRE teaching models and their reformulation to contribute to the challenges and progress of the times, so that synergy between various transformations can be achieved.
Sharifah Altalhi, Júnia Schultz, Tahira Jamil
et al.
Abstract Background Hydrothermal vents along mid-ocean ridges host diverse microbial communities and are crucial to global elemental cycling. The Red Sea, known for its unique environmental conditions—including low nutrient levels, high year-round temperatures, bottom-water temperatures of 21 °C, and elevated salinity—hosts recently discovered active low-temperature hydrothermal vent fields at the axial Hatiba Mons volcano. These vents, characterized by large iron oxide mounds and abundant microbial mats, offer an extreme environment for studying the diversity and functions of prokaryotes involved in elemental cycling in this system. In this study, we used 16S rRNA sequencing and shotgun metagenomics to examine the microbial diversity and metabolic capabilities of precipitates and microbial mats from five vent sites. Results We recovered 314 non-redundant metagenome-assembled genomes (MAGs), including 250 bacterial and 64 archaeal MAGs, representing 34 bacterial and 11 archaeal phyla. Functional annotations revealed diverse nutrient and metal cycling potentials, with notable enrichment in iron redox genes. Key players include Bathyarchaeia and Chloroflexi in the precipitates (contributing to carbon, nitrogen, sulfur, and metal cycling potentials) and Pseudomonadota members in the microbial mats and upper precipitates (involved in iron and sulfur metabolism and carbon fixation through the CBB cycle). Carbon fixation in precipitate potentials primarily occurs through the Wood–Ljungdahl pathway. Sulfur and nitrogen cycling genes are distributed across various genomes, indicating collaborative cycling. Conclusion Our genome-resolved analysis positions the Hatiba Mons vents as an iron-rich system that provides new insights into oligotrophic hydrothermal environments, with potential relevance for understanding novel metabolic pathways, extremophilic adaptations, and their roles in element cycling and biotechnological applications.
ObjectivesThis study conducted a meta-analysis comparing vancomycin and linezolid for treating central nervous system (CNS) infections, addressing the lack of comprehensive evaluations in existing research on antibiotic therapy for CNS infections.MethodsWe systematically searched databases, including the PubMed, Embase, Web of Science, Cochrane Library and Chinese databases, up to April 22, 2025. All eligible randomized controlled trials and cohort studies of vancomycin or linezolid were included. The clinical success rate was the primary outcome of interest. The secondary outcomes of interest were cerebrospinal fluid (CSF) parameters, systemic inflammatory markers and the occurrence of adverse drug reactions (ADRs). Two reviewers independently extracted the data and assessed the study quality (NOS/ROB 2.0). The meta-analysis employed random/fixed-effects models to calculate pooled dichotomous outcomes (ORs) and continuous outcomes (SMDs) with 95% CIs via RevMan 5.4.ResultsThis meta-analysis included 17 studies (6 head-to-head). Clinical cure rates were not significantly different between vancomycin (84.7%, 222/262) and linezolid (79.7%, 200/251), with a pooled OR of 1.29 (95% CI: 0.55–2.99; p =0.56), while substantial heterogeneity existed (I2 = 58%). The secondary outcomes showed no differences but suffered extreme heterogeneity (I² >90%). Safety analysis revealed a significantly greater ADR with vancomycin (21.0% vs. 15.1%; OR 1.63, 95% CI: 1.01–2.65; p = 0.05) with low heterogeneity (I² = 15%).ConclusionVancomycin and linezolid have similar effectiveness in CNS infection from current available evidences, but vancomycin is associated with a greater risk of ADR. Treatment selection should be based on patients’ individual characteristics, such as risk of thrombocytopenia, renal function, and availability of therapeutic drug monitoring.
This paper addresses the fundamental problem of seed selection in semi-supervised clustering, where the quality of initial seeds has a significant impact on clustering performance and stability. Existing methods often rely on randomly or heuristically selected seeds, which can propagate errors and increase dependence on expert labeling. To overcome these limitations, we propose FA-Seed, a flexible and adaptive model that integrates active querying with self-guided adaptation within the framework of fuzzy hyperboxes. FA-Seed partitions the data into hyperboxes, evaluates seed reliability through measures of membership and association density, and propagates labels with an emphasis on label purity. The model demonstrates strong adaptability to complex and ambiguous data distributions in which cluster boundaries are vague or overlapping. The main contributions of FA-Seed include: (1) automatic estimation and selection of candidate seeds that provide auxiliary supervision, (2) dynamic cluster expansion without retraining, (3) automatic detection and identification of structurally complex regions based on cluster characteristics, and (4) the ability to capture intrinsic cluster structures even when clusters vary in density and shape. Empirical evaluations on benchmark datasets, specifically the UCI and Computer Science collections, show that our approach consistently outperforms several state-of-the-art semi-supervised clustering methods.
Hércules Lázaro Morais Campos, Elisa De Leon, Ingred Merllin de Souza
et al.
Introduction: Aging in rural areas is challenging and has very specific characteristics in the way these elderly people live their old age, from the perspectives of cognition, functionality and life purpose. There is a lack of information and data in the literature on how people age in rural areas around the world. The aim of this study was to identify and describe how people age in rural areas, focusing on the following domains: cognition, physical function/functionality and life purpose.
Methods: We included cross-sectional studies published up to April 2023 found in six databases: PubMed, LILACS, PsycINFO, Scopus, SciELO and Web of Science. The Rayyan software was used for the first selection of studies and the Observational Study Quality Evaluation was used to assess methodological quality and risk of bias. For the primary analysis, the titles and abstracts available in the search engine were analyzed using the following MeSH descriptors: "physical functioning"; "cognition"; "cognitive function"; "life purpose"; 'personal satisfaction'; 'subjective well-being'; "aged"; "elderly"; "old"; "rural aging"; "rural population"; "communities, rural"; "distribution, rural spatial"; "medium communities"; "rural settlement"; "small community". In the secondary selection, the selected articles were fully read by two independent reviewers and confirmed by a third reviewer when necessary.
Results: From 22 studies methodologically evaluated it was seen that rural aging in the world is female and mostly in elderly women farmers; mental evaluation together with activities of daily living and instrumental activities were the most evaluated; the studies did not mention the evaluation of life purpose.
Conclusion: The world ages very differently in rural areas, and the way we age is directly linked to where this process takes place. Cognition, followed by functionality, are the most researched outcomes in cross-sectional studies with this population and the assessment of life purpose has not been investigated to date.
Special situations and conditions, Public aspects of medicine
Over the last decade there has been an increasing focus on utilising government-held data for large-scale data linkage research projects, with an emphasis on public benefit.
Most, if not all, administrative data research initiatives will recognise public involvement and engagement (PI&E) as a cornerstone of research and emphasise that administrative data is essentially public data, and, therefore, that publics must have a say in how it is used. Much of this focuses on engaging with communities and their representative organisations.
What is less explicitly discussed is the role that data-driven research plays within a broader public realm that is increasingly driven by data, or datafied.
This paper will examine the ways in which PI&E both challenges and contributes to the datafication of society, through the work of the Administrative Data Research Centre Northern Ireland (ADRC NI), part of ADR UK. It will explore if – and how – PI&E in administrative data research can play a role in democratising this datafied society.
The paper will use the Northern Ireland Public Data Panel (NIPDP) and the Voices of Young People in Care (VOYPIC) initiative as case studies to explore the ways in which ADRC NI successfully or unsuccessfully create sites of democratisation within the data ecosystem.
Finally, the paper will consider how to amplify the democratic benefits of PI&E in data-driven research while minimising any potential harms, in the form of a potential framework for data justice within PI&E in data-driven research.
Abstract: The Book of Enoch presents an explanation of Moon in a different way when compared to many ancient manuscripts. The periods of the Moon associated with the Moon phases are illustrated in a unique way that, in first glance, requires a deep understanding. This explanation is different with what science has explained nowadays. To begin with, the previous research of this subject on the Book of Enoch is out to dated. Therefore, this research conducts a new approach to examine the Book of Enoch using Islamic perspective where this study is rare to conduct. This study utilizes qualitative research with content analysis to gain the answer in depth. This research also uses triangulation method to investigate the data and obtain the validity of the results. Overall, the Moon phase in the Book of Enoch has the same understanding as the modern science. The Book of Enoch describes implicitly the appearance of Moon in the northern hemisphere. The explanation of Enoch lunar-day in each month is followed by the Urfi Islamic calendar. Then the statement about “once the month is 28-day†is based on the using of Callippic cycle in Charles opinion while in the author’s opinion that the Book of Enoch shows the sidereal month cycle. In addition, the theory which has been adopted by Islamic astronomy has a strong relationship with this manuscript since it is believed that this manuscript is attributed to Prophet Enoch or Idris.
Abstrak: Kitab Henokh menyajikan penjelasan tentang Bulan dengan cara yang berbeda jika dibandingkan dengan banyak naskah kuno. Periode Bulan yang terkait dengan fase Bulan diilustrasikan dengan cara yang unik sehingga sekilas memerlukan pemahaman yang mendalam. Penjelasan ini berbeda dengan penjelasan ilmu pengetahuan saat ini. Pertama-tama, penelitian sebelumnya mengenai subjek Kitab Henokh ini sudah ketinggalan zaman. Oleh karena itu, penelitian ini melakukan pendekatan baru untuk mengkaji Kitab Henokh dengan menggunakan perspektif Islam dimana penelitian ini jarang dilakukan. Penelitian ini menggunakan penelitian kualitatif dengan analisis isi untuk memperoleh jawaban secara mendalam. Penelitian ini juga menggunakan metode triangulasi untuk menyelidiki data dan memperoleh keabsahan hasil. Secara keseluruhan, fase Bulan dalam Kitab Henokh mempunyai pemahaman yang sama dengan ilmu pengetahuan modern. Kitab Henokh menggambarkan secara implisit penampakan Bulan di belahan bumi utara. Penjelasan hari lunar Henokh di setiap bulannya diikuti dengan penanggalan Islam Urfi. Kemudian pernyataan “satu bulan ada 28 hari†didasarkan pada penggunaan siklus Callippic menurut pendapat Charles sedangkan menurut pendapat penulis Kitab Henokh menunjukkan siklus bulan sidereal. Selain itu, teori yang dianut oleh ilmu astronomi Islam mempunyai kaitan erat dengan naskah ini karena diyakini naskah ini milik Nabi Henokh atau Idris.
Mohammad Parvaresh-Masoud, Mahsa Rahimkhanli, Hamid Torabian
et al.
Background: Prehospital emergency care plays a vital role in the healthcare system and can significantly affect the outcomes of patients. Integrating medical science education into Emergency Medical Technicians (EMTs) training programs could improve prehospital emergency care and patient outcomes.Objectives: The present study was conducted to explore the perspectives of Iranian EMTs on integrating medical science education in prehospital emergency care.Methods: This study was a qualitative descriptive design in Iran. Using the purposive sampling method, data were collected through in-depth individual interviews with 13 EMTs who had completed EMT training programs in Iran. Thematic analysis, a form of qualitative content analysis, was used to identify key challenges and barriers to integrating medical science education, as well as potential benefits and opportunities.Results: After multiple rounds of analyzing and summarizing the data and considering similarities and differences, 2 main categories and 6 subcategories were created based on the results of the data analysis, including: "inadequate training" and "lack of ongoing training and professional development opportunities".Conclusion: The study highlights the importance of stakeholder collaboration and communication to develop effective EMT training programs. Integrating medical science education in EMT training programs could improve the quality of prehospital emergency care and, ultimately, the health outcomes of patients.
There has been a significant surge in the number of scientific papers published in recent years,which makes it challen-ging for researchers to keep up with the latest advancements in their fields.To stay updated,researchers often rely on reading the contributions section of papers,which serves as a concise summary of the key research findings.However,it is not uncommon for authors to inadequately present the innovative content of their articles,making it difficult for readers to quickly grasp the essence of the research.To address this issue,we propose a novel task of contribution summarization to automatically generate contribution summaries of scientific papers.One of the challenges of this task is the lack of relevant datasets.Therefore,we construct a scientific contribution summarization corpus(SCSC).Another issue lies in the fact that currently available abstractive or extractive models tend to suffer from either excessive redundancy or a lack of coherence between sentences.To meet the demand of ge-nerating concise and high-quality contribution sentences,we present MSSRsum,a multi-step sentence selecting-and-rewriting model.Experiments show that the proposed model outperforms baselines on SCSC and arXiv datasets.
We present the first James Webb Space Telescope/NIRCam-led determination of 7 < z < 9 galaxy properties based on broadband imaging from 0.8 to 5 μ m as part of the GLASS-JWST Early Release Science program. This is the deepest data set acquired at these wavelengths to date, with an angular resolution ≲0.″14. We robustly identify 13 galaxies with signal-to-noise ratio ≳ 8 in F444W from 8 arcmin ^2 of data at m _AB ≤ 28 from a combination of dropout and photometric redshift selection. From simulated data modeling, we estimate the dropout sample purity to be ≳90%. We find that the number density of these F444W-selected sources is broadly consistent with expectations from the UV luminosity function determined from Hubble Space Telescope data. We characterize galaxy physical properties using a Bayesian spectral energy distribution fitting method, finding a median stellar mass of 10 ^8.5 M _⊙ and age 140 Myr, indicating they started ionizing their surroundings at redshift z > 9.5. Their star formation main sequence is consistent with predictions from simulations. Lastly, we introduce an analytical framework to constrain main-sequence evolution at z > 7 based on galaxy ages and basic assumptions, through which we find results consistent with expectations from cosmological simulations. While this work only gives a glimpse of the properties of typical galaxies that are thought to drive the reionization of the universe, it clearly shows the potential of JWST to unveil unprecedented details of galaxy formation in the first billion years.
Objectives To evaluate through a systematic review the effectiveness of electronic methods in monitoring adherence to regular inhaled corticosteroids (ICS) alone or in combination with long-acting β2-agonists (LABAs) and their effect on clinical outcomes.Design A narrative systematic review.Data sources MEDLINE, EMBASE, Cochrane Database of Systematic Reviews and Web of Science were searched through up to 10 July 2022.Eligibility criteria We included peer-reviewed studies of qualitative and quantitative outcomes that compared the effect of electronic methods to routine non-electronic monitoring intervention or placebo among children and adults with asthma on medication adherence rates to regular ICS alone or in combination with LABA, asthma control and asthma exacerbations.Data extraction and synthesis Data extraction was performed according to a predetermined sheet specific to the review objectives. The risk of bias was assessed using the Cochrane Risk of Bias Tool for randomised controlled trials and the Risk of Bias in Systematic Reviews tool for systematic reviews. Meta-analysis was not possible based on the findings of the scoping search; however, a narrative review was performed to allow for the grouping of results based on asthma inhaler adherence rates, asthma control and exacerbations.Results Six articles comprising 98 studies published from 1998 to 2022 in the USA, Canada and the UK were included. Compared with the control, electronic monitoring devices (EMDs) showed a 23% adherence improvement, mean difference (MD) of 23%, 95% CI 10.84 to 34.16, p=0.0002. Asthmatic children were 1.5 times more likely to be adherent using EMDs compared with non-EMD users (RR=1.5, 95% CI 1.19 to 1.9) (p<0.001). Mobile devices and text message reminders (MHealth) showed a 12% adherence improvement (MD 12%, 95% CI 6.22 to 18.03) (p<0.0001), alongside a small to medium improvement in asthma control (standardised mean difference (SMD) 0.31, 95% CI 0.17 to 0.44), small improvement in asthma-related quality of life (SMD 0.26) (p=0.007) and variable risk reduction in asthma exacerbations for digital health (risk ratio 0.53, 95% CI 0.32 to 0.91) (p=0.02) compared with EMDs, which showed insignificant differences (risk ratio 0.89, 95% CI 0.45 to 1.75) (p=0.72). Technologies combined yielded variable adherence effects, with an SMD for eHealth of 0.41, 95% CI 0.02 to 0.79, and MD for digital health was 14.66% higher than the control, 95% CI 7.74 to 21.57. Heterogeneity between studies was significant (eHealth I2=98%, digital I2=94%).Conclusion Electronic methods improved adherence to inhaled medications in asthma. EMDs appear to be the most effective technology, followed by mHealth. The adherence improvement was associated with a small clinical improvement. There was inconsistent overlapping of terminology describing electronic methods that require standardisation. Data on the cost-effectiveness of electronic devices and their utilisation in severe asthma are lacking and require further research.PROSPERO registration number CRD42022303069.
Natasha Shaukat, Javeria Amin, Muhammad Imran Sharif
et al.
Diabetic retinopathy (DR) is a major reason of blindness around the world. The ophthalmologist manually analyzes the morphological alterations in veins of retina, and lesions in fundus images that is a time-taking, costly, and challenging procedure. It can be made easier with the assistance of computer aided diagnostic system (CADs) that are utilized for the diagnosis of DR lesions. Artificial intelligence (AI) based machine/deep learning methods performs vital role to increase the performance of the detection process, especially in the context of analyzing medical fundus images. In this paper, several current approaches of preprocessing, segmentation, feature extraction/selection, and classification are discussed for the detection of DR lesions. This survey paper also includes a detailed description of DR datasets that are accessible by the researcher for the identification of DR lesions. The existing methods limitations and challenges are also addressed, which will assist invoice researchers to start their work in this domain.
With the rapid development of science and technology, biomedicine has entered a new era of big data. Massive biomedical data has speeded up the rise of medical informatics, systems biology, computational biology and the interdisciplinary disciplines, which brought unprecedented opportunities for traditional Chinese medicine. The resources of Chinese medicine are abundant, and a large amount of data has been accumulated in various aspects such as Chinese medicine resources and clinical applications. The application of informatics technology in the field of Chinese medicine expands continuously. This paper specifically reviews commonly used traditional Chinese medicine databases and describes research progresses of Chinese medicine informatics.
Furthermore, the opportunities and prospects of traditional Chinese medicine are discussed.
The translation process includes transferring the source language into the target language with the intention of knowing the meaning. When meaning is expressed to the reader, then all information, insight, and knowledge can also be understood. As in textbooks, knowledge conveyed through texts in it of course have references from foreign languages, including Arabic. Therefore, in this article there are several objectives; (1) becoming one of the references for writers and translators in understanding the importance of the translation process to find out the meaning of writing textbooks, (2) helping students and students learn to understand science through printed books. In particular, the discussion in this article is focused on understanding, strategies and the urgency of meaning in Arabic translation which is applied to writing lesson texts. This article uses a qualitative descriptive method. The data obtained are sourced from observations, findings, and literature reviews from various sources. The results of the analysis of this article are in the form of emphasizing the importance of the translation process as language transfer and messages from the source text which includes the source language into the target text which includes the target language. The translation process must refer to the understanding of both languages, and involve the sensitivity and feelings of the translator. This translation strengthens the position of language and cultural differences that are no longer a barrier in the development of science. Thus, by using a good and correct translation process, the meaning of textbooks can be fully grasped
Clustering is one of the most important unsupervised machine learning tasks. It is widely used to solve problems of intrusion detection, text analysis, image segmentation etc. Subspace clustering is the most important method for high-dimensional data clustering. In order to solve the problem of parallel subspace clustering for high-dimensional big data, this paper proposes a parallel subspace clustering algorithm based on spark named PSubCLUS which is inspired by SubCLU, a classical subspace clustering algorithm. While Spark is the most popular big data parallel processing platform currently, PSubCLUS uses the Resilient Distributed Datasets (RDD) provided by Spark to store data points in a distributed way. The two main performing stages of this algorithm, one-dimensional subspace clustering and iterative clustering, can be executed in parallel on each worker node of cluster. PSubCLUS also uses a repartition method based on the number of data points to achieve load balancing. Experimental results show that PSubCLUS has good parallel speedup and ideal load balancing effect, which is suitable for solving the parallel subspace clustering of high-dimensional big data.