Hasil untuk "data science"

Meixiang Gao, Xiujuan Yan, Xin Li et al.

ABSTRACT The field of soil science has seen significant advancements in recent years, largely due to the integration of computational tools and statistical methods. Among these resources, the programming language R has emerged as a powerful and versatile platform for soil scientists, aiding in a spectrum of tasks from data analysis and modeling to visualization. Nonetheless, the broader trends and specific patterns of R usage in soil research have not been thoroughly documented. Our study investigated the prevalence of R and its package usage in 25,888 research articles published in 10 leading soil science journals over a decade, from 2014 to 2023. A considerable number of these articles, 7899 (or 30.5%), named R as their primary data analysis tool. The use of R has followed a steady linear growth pattern, rising from 13.9% in 2014 to 46.5% in 2023. The most commonly used R packages were “vegan,” “ggplot2,” “lme4,” “nlme,” and “randomForest,” with each journal showcasing unique research focuses, resulting in varying frequencies of R package applications across different publications. Furthermore, there was a notable increase in the average number of R packages used per article throughout the study period. This research highlights the pivotal role of R, armed with its robust statistical and visualization capabilities, in enabling soil scientists to conduct comprehensive analyses and gain in‐depth insights into the complex dimensions of soil science.

Silingene Joyce Ngcobo, Tracy Zhandire, Zamasomi Meyiwa Luvuno et al.

<h4>Background</h4>South Africa's higher education institutions (HEIs) continue to face challenges in implementing inclusive language policies that integrate indigenous African languages into academic settings, even three decades after apartheid. Higher Education Institutions (HEIs) face significant challenges in integrating indigenous African languages into academic settings. Despite progressive reforms, higher education institutions face significant challenges in integrating indigenous African languages into academic settings.<h4>Objectives</h4>This scoping review aims to evaluate the current state of language policy implementation in South African public HEis. Specifically, it seeks to: (1) map the integration of multilingual policies into teaching, research, and administrative practices; (2) identify persistent barriers to effective policy implementation; (3) explore successful strategies for promoting multilingualism (4) assess the extent of African language usage in academic contexts; and (5) identify research gaps to guide future investigations.<h4>Methods</h4>The review will adhere to the PRISMA-ScR guidelines and follow the framework outlined by Arksey and O'Malley, ensuring a systematic and transparent approach. A comprehensive search will be conducted in databases including Google Scholar, Scopus, Web of Science, ERIC, and African Journals Online (AJOL), covering studies published from 1994 to the present. This will be supplemented by grey literature from government and institutional sources. Three independent reviewers will screen studies using predefined eligibility criteria, managing and screening articles through Rayyan. Data will be extracted using a standardized form, and thematic analysis will synthesize the findings, with stakeholder consultation to validate results.<h4>Expected outcomes</h4>This review will provide a comprehensive assessment of language policy implementation, highlighting successful strategies and persistent challenges across institutions. The findings will inform policy refinement, identify effective practices, and guide future research directions for achieving linguistically inclusive higher education in South Africa, while contributing to a broader understanding of implementing multilingual policies in post-colonial educational contexts. This protocol is preregistered on OSF, available at https://doi.org/10.17605/OSF.IO/AU2SD.

Aron Bell, Liam Anthony Mannion, Mark Kelly et al.

The life cycle carbon dioxide equivalent (CO2e) intensity of Power-to-Liquid (PtL) sustainable aviation fuel (SAF) scenarios in Spain are evaluated using a specific, granular, and transparent modelling approach. Post combustion CO2 capture and direct air CO2 capture are considered, in addition to grid and renewable electricity sources. The mass and energy requirements of the PtL system are determined from a mass and energy conserved reaction mechanism and a comprehensive literature review. The SAF yield is constrained by its molecular composition, formulated to meet the physical property specifications for Fischer-Tropsch synthetic paraffinic kerosene (FT-SPK) in ASTM D7566 Annex 1. The results of the life cycle assessment (LCA) show large ranges in CO2e intensity of PtL SAF scenarios, from 11 to 101 gCO2e/MJ. The electricity emission factors at which the CO2e intensity of PtL SAFs meet the 70% reduction required under the ReFuelEU Aviation legislation are 112 – 168 gCO2e/kWh for direct air capture and post combustion capture of biogenic CO2. As the average EU grid is approximately 300 gCO2e/kWh, the use of renewable electricity (onsite or power purchase agreement) is therefore essential to achieve the 70% reduction. The carbon intensity of the Madrid to Dublin commercial flight route is analysed, per revenue-passenger-kilometre (RPK), as a specific use case with actual data of Ryanair Boeing 737-800 and 737 MAX 8 aircraft. Compared to the Science Based Targets 1.5°C limit of 3.3 gCO2/RPK, it is shown that sustainable aviation is challenging using PtL SAF, with a best case of 9 gCO2/RPK.

Michael Petrides, Aliki Peletidi, Evangelia Nena et al.

Background Approximately 50 million individuals across the globe are impacted by epilepsy, leading to fear, discrimination, psychiatric issues, high costs, and social stigma. Proper diagnosis and treatment could allow up to 70% of those affected to live seizure-free. Community pharmacists have significant potential to actively participate in epilepsy patient care, beyond merely dispensing medications. The objective of this study was to systematically review and assess the roles of pharmacists in epilepsy care, focusing on pharmacist-led interventions and services for patients with epilepsy.Methods Following PRISMA 2020 guidelines, the review included cross-sectional, retrospective cohort, and qualitative/quantitative studies on pharmacist-led epilepsy interventions in community and outpatient settings. Searches were conducted in Scopus, PubMed Central, and Science Direct for studies published through the end of 2023. Two evaluators independently reviewed and chose studies, and the data was analysed using Microsoft Excel®. Quality assessment was performed using the MMAT tool.Results Five eligible studies were included, covering 457 participants. Studies originated from the USA (n = 3), Netherlands (n = 1), and Palestine (n = 1). They evaluated pharmacist-led interventions in epilepsy, including medication adherence, quality of life, and pharmacist’s integration in epilepsy care.Conclusion This review underscores the possible contributions of pharmacists in epilepsy care, stressing the importance of pharmacist-led interventions to enhance medication adherence and the quality of life for individuals with epilepsy. Future research should evaluate the effectiveness and cost-effectiveness of these services, including disease management and patient education. Increasing awareness among pharmacists and patients about pharmacists’ contributions is crucial for improving epilepsy care.

Andre Massahiro Shimaoka, Renato Cordeiro Ferreira, Alfredo Goldman

This study explores the integration of eXtreme Programming (XP) and the Cross-Industry Standard Process for Data Mining (CRISP-DM) in agile Data Science projects. We conducted a case study at the e-commerce company Elo7 to answer the research question: How can the agility of the XP method be integrated with CRISP-DM in Data Science projects? Data was collected through interviews and questionnaires with a Data Science team consisting of data scientists, ML engineers, and data product managers. The results show that 86% of the team frequently or always applies CRISP-DM, while 71% adopt XP practices in their projects. Furthermore, the study demonstrates that it is possible to combine CRISP-DM with XP in Data Science projects, providing a structured and collaborative approach. Finally, the study generated improvement recommendations for the company.

Guoqiang Liang, Jingqian Gong, Mengxuan Li et al.

Large language models (LLMs) have exhibited exceptional capabilities in natural language understanding and generation, image recognition, and multimodal tasks, charting a course towards AGI and emerging as a central issue in the global technological race. This manuscript conducts a comprehensive review of the core technologies that support LLMs from a user standpoint, including prompt engineering, knowledge-enhanced retrieval augmented generation, fine tuning, pretraining, and tool learning. Additionally, it traces the historical development of Science of Science (SciSci) and presents a forward looking perspective on the potential applications of LLMs within the scientometric domain. Furthermore, it discusses the prospect of an AI agent based model for scientific evaluation, and presents new research fronts detection and knowledge graph building methods with LLMs.

Badar Almarri, Gaurav Gupta, Ravinder Kumar et al.

Nektaria-Ioanna Karma, Fotini Mellou, Panagoula Pavlou et al.

It is well established that marine organisms consist of a great variety of active compounds that appear exclusively in the marine environment while having the ability to be vastly reproduced, irrespective of the existing conditions. As a result, marine organisms can be used in many scientific fields, including the ones of pharmaceutics, nutrition, and cosmetic science. As for the latter, marine ingredients have been successfully included in cosmetic formulations for many decades, providing numerous benefits for the skin. In the present review, the contribution of marine compounds in wound healing is thoroughly discussed, focusing on their role both as active ingredients in suitable formulations, designed to contribute to different stages of skin regeneration and restoration and also, indirectly, as a tool for facilitating wound closure as part of a wound dressing. Additionally, the advantages of these marine ingredients are presented, as well as ways of incorporating them effectively in formulations, so as to enhance their performance. Numerous studies have been referenced, showcasing their efficacy in wound healing. Finally, important data in regard to their stability, limitations, and challenges to their use, safety issues, and the existing legislative framework are extensively reviewed.

Florian Guitton, Axel Oehmichen, Étienne Bossé et al.

Data is the foundation of any scientific, industrial or commercial process. Its journey typically flows from collection to transport, storage, management and processing. While best practices and regulations guide data management and protection, recent events have underscored its vulnerability. Academic research and commercial data handling have been marred by scandals, revealing the brittleness of data management. Data, despite its importance, is susceptible to undue disclosures, leaks, losses, manipulation, or fabrication. These incidents often occur without visibility or accountability, necessitating a systematic structure for safe, honest, and auditable data management. In this paper, we introduce the concept of Honest Computing as the practice and approach that emphasizes transparency, integrity, and ethical behaviour within the realm of computing and technology. It ensures that computer systems and software operate honestly and reliably without hidden agendas, biases, or unethical practices. It enables privacy and confidentiality of data and code by design and by default. We also introduce a reference framework to achieve demonstrable data lineage and provenance, contrasting it with Secure Computing, a related but differently-orientated form of computing. At its core, Honest Computing leverages Trustless Computing, Confidential Computing, Distributed Computing, Cryptography and AAA security concepts. Honest Computing opens new ways of creating technology-based processes and workflows which permit the migration of regulatory frameworks for data protection from principle-based approaches to rule-based ones. Addressing use cases in many fields, from AI model protection and ethical layering to digital currency formation for finance and banking, trading, and healthcare, this foundational layer approach can help define new standards for appropriate data custody and processing.

Xiaoting Li, Gang Liu, Jinghong Chen et al.

We present the design and test results of two optical data transmission ASICs for the High-Luminosity LHC (HL-LHC) experiments. These ASICs include a two-channel serializer (LOCs2) and a single-channel Vertical Cavity Surface Emitting Laser (VCSEL) driver (LOCld1V2). Both ASICs are fabricated in a commercial 0.25-um Silicon-on-Sapphire (SoS) CMOS technology and operate at a data rate up to 8 Gbps per channel. The power consumption of LOCs2 and LOCld1V2 are 1.25 W and 0.27 W at 8-Gbps data rate, respectively. LOCld1V2 has been verified meeting the radiation-tolerance requirements for HL-LHC experiments.

P. A. Nechaeva, G. R. Yusupova

In the modern economy, digitalization has become one of the key components of the Russian Federation regions socio-economic development. Enterprises of various industries are faced with the need to process large amounts of data, which greatly complicates data management, and therefore the relevance of the analysis of artificial intelligence technologies increases. Training employees for industrial processes is a major challenge in any industry. Effective human resource management requires an accurate assessment and presentation of available competencies, as well as an effective mapping of the required competencies for specific positions. Competences enable the company to achieve high production and economic results.   The aim of the study is to develop a structural model of a predictive expert system for managing data on the competencies of a modern manager by combining artificial and human intelligence, which can serve as a decision support tool for managers in real conditions to improve the efficiency of a particular enterprise.   The study of the demand for managers and requirements for candidates in the Russian Federation and the Republic of Tatarstan was conducted on the data of the largest Russian Internet recruitment company HeadHunter. To develop a structural model of the proposed expert system, information from specialized scientific publications published in the Russian and foreign scientific literature of the Web of science and Scopus databases was used. The expert system will allow the manager to find the best options for using employees, predict the development of the enterprise as a whole and its individual divisions, which will significantly increase the key performance indicators of any company.

Genevieve Dammery, Louise A. Ellis, Kate Churruca et al.

Abstract Background Healthcare systems may be resilient and adaptive, but they are not fit for purpose in their current state. Increasing threats to health system sustainability have underscored the need to move towards a learning health system in which research and data are used routinely in clinical practice to facilitate system improvement. This study aimed to establish which elements of the learning health system were being realised within a university-based general practice and determine acceptability from staff to embrace further the transition towards a learning health system. Methods Semi-structured interviews were conducted with practice staff, including clinical and administrative staff, to determine the current state of the learning health system in the practice. An embedded researcher was placed within the general practice on a part-time basis to investigate the learning health system model. Interviews were transcribed and thematically analysed based on the National Academy of Medicine’s framework of learning health systems. Results In total, 32 (91%) practice staff were interviewed, comprising general practitioners (n = 15), nurses (n = 3), administrative staff (n = 13), and a psychologist (n = 1). Participants indicated that the practice was operating with several characteristics of a learning health system (e.g., emphasising science and informatics; focusing on patient-clinician partnerships; applying incentives; supporting a continuous learning culture; and establishing structures and governance for learning). These measures were supported by the university-based setting, and resultant culture of learning. Nevertheless, there were areas of the practice where the learning health system could be strengthened, specifically relating to the use of patient data and informatics. Staff generally expressed willingness to engage with the process of strengthening the learning health system within their practice. Conclusion Although the idea of a learning health system has been gaining traction in recent years, there are comparatively few empirical studies presented in the literature. This research presents a case study of a general practice that is operating as a learning health system and highlights the utility of using the learning health system framework.

Amar Taksande, Patel Zeeshan Jameel, Rupesh Rao et al.

Objectives: The exact prevalence of cardiac anomalies in diagnosed cases of echogenic foci is still unknown, as various studies have been carried out across multiple populations with different methodologies.  Objectives: The primary objective of this study was to determine the precise prevalence of cardiac anomalies found in cases with intracardiac echogenic foci.  Methods: The authors manually searched the electronic databases (Cochrane Library, PubMed, EMBASE, Scopus, Web of Science). Two reviewers independently did data extraction and quality control; a third reviewer resolved any raised conflicts. The data were analyzed by comprehensive meta-analysis software version 2. Risk of bias assessment and strobe checklist were used for quality assessment.  Results: Out of 531 articles identified, 32 studies met the inclusion criteria and were included in the meta-analysis with a total sample size of 7568. The pooled prevalence of cardiac anomalies in the fetuses with intracardiac echogenic foci was 4.8% (95% CI, 3.6%-6.4%). Subgroup analysis was done according to the geographical distribution of cases, maternal age, gestational age, year of publication, risk of bias, and ultrasonography operator.  Conclusions: The current study represents the first and only meta-analysis concerning the prevalence of cardiac anomaly in fetuses diagnosed with intracardiac echogenic focus (ICEF). This study supports a definitive relationship between ICEF and underlying congenital heart disease. We recommend increased training of individuals performing this ultrasonography to improve early detection, ultimately enhancing the care given to infants immediately post-birth.

Zahid Mehmood, Zubair Ahmad, Asad Ullah et al.

Background: Understanding students' perception of the educational environment and their cognitive load in this context is crucial for optimizing the effectiveness of e-learning platforms. Objective: To compare educational environment perception and cognitive load in under-graduates Doctor of Physical Therapy (DPT) and post-graduate Master in Science of Physical Therapy (MSPT) students having online learning experiences. Methodology: In this comparative cross-sectional study, data was collected through non-probability convenient sampling from n=274 under-graduates DPT (n=225) and post-graduates MSPT(n=49) students of either gender having one-semester experience of online learning, Dundee Ready Education Environment Measure (DREEM) for measuring educational environmental perception and Rating Scale of Mental Effort (RSME) for measurement of cognitive load. Online self-structured was developed questionnaire and shared through communication media platform and data analysis was made through SPSS version 28. Results: There were n=225 under-graduates (DPT) and n=49 post-graduates (MSPT) students in which, there were n=208 females and n=66 males. The overall DREEM score showed that MSPT students are more significantly positive (p<0.001, Cohen’s d=1.01) than DPT students regarding the perception of the educational environment with a large effect size. While there was no significant difference (p=0.114) between MSP and DPT students regarding cognitive load. Conclusion: Post-graduates (MSPT) students have better educational environmental perception than undergraduate (DPT) students but there was no significant difference in cognitive load in undergraduate (DPT) and post-graduates (MSPT) students. Keywords: cognition; cognitive load; mental effort; e-learning; physiotherapist.

The AXIS Time-Domain, Multi-Messenger Science Working Group, : et al.

The Advanced X-ray Imaging Satellite (AXIS) promises revolutionary science in the X-ray and multi-messenger time domain. AXIS will leverage excellent spatial resolution (<1.5 arcsec), sensitivity (80x that of Swift), and a large collecting area (5-10x that of Chandra) across a 24-arcmin diameter field of view to discover and characterize a wide range of X-ray transients from supernova-shock breakouts to tidal disruption events to highly variable supermassive black holes. The observatory's ability to localize and monitor faint X-ray sources opens up new opportunities to hunt for counterparts to distant binary neutron star mergers, fast radio bursts, and exotic phenomena like fast X-ray transients. AXIS will offer a response time of <2 hours to community alerts, enabling studies of gravitational wave sources, high-energy neutrino emitters, X-ray binaries, magnetars, and other targets of opportunity. This white paper highlights some of the discovery science that will be driven by AXIS in this burgeoning field of time domain and multi-messenger astrophysics.

Badzlin Nabilah, Adi Setyo Purnomo, Hamdan Dwi Rizqi et al.

Methylene blue (MB) is one of synthetic dyes that is used in the textile industry which is difficult to degrade in nature. Previously, the brown-rot fungus (BRF) Daedalea dickinsii had shown a good ability to degrade MB, however, the decolorization ability was relatively still low and had a long period of incubation. Therefore, improvement of process is needed to increase the ability of D. dickinsii to decolorize MB. In this study, the effect of Ralstonia pickettii bacterium addition on MB biodecolorization by the BRF D. dickinsii in potato dextrose broth (PDB) medium was investigated. The amount of R. picketti that was added to the culture of D. dickinsii were 2, 4, 6, 8, and 10 mL (1 mL ≈ 1.39 × 108 CFU). The cultures had ability to decolorize MB (100 mg/L) at 30 °C after 7 days incubation. The highest percentage of MB biodecolorization was obtained at addition of 10 mL of R. pickettii approximately 89%, while biodecolorization process by particularly D. dickinsii was approximately 17%. The MB degradation metabolites by mixed cultures of D. dickinsii and 10 mL of R. pickettii were Azure A, thionine, glucose-MB, C12H11N3SO6 and C12H13N3O6. This study indicated that the addition of R. pickettii could enhance MB biodecolorization by fungus D. dickinsii. Besides that, this study also indicated that mixed cultures of D. dickinsii and R. pickettii has great potential for high efficiency, fast and cheap dye wastewater treatment.

Anastasios I. Manettas, Panagiotis Tsaklis, Dario Kohlbrenner et al.

Rationale: Allogeneic hematopoietic stem cell transplantation (HSCT) is associated with increased treatment-related mortality, loss of physical vitality, and impaired quality of life. Future research will investigate the effects of multidisciplinary rehabilitative interventions in alleviating these problems. Nevertheless, published studies in this field show considerable heterogeneity in selected outcomes and the outcome measurement instruments used. The purpose of this scoping review is to provide an overview of the outcomes and outcome measurement instruments used in studies examining the effects of rehabilitative interventions for patients treated with allogeneic HSCT. Methods: We conducted a scoping review that included randomized controlled trials, pilot studies, and feasibility studies published up to 28 February 2022. Results: We included <i>n</i> = 39 studies, in which <i>n</i> = 84 different outcomes were used 227 times and <i>n</i> = 125 different instruments were used for the measurements. Conclusions: Research in the field of rehabilitation for patients with haematological malignancies treated with allogeneic HSCT is hampered by the excess outcomes used, the inconsistent outcome terminology, and the inconsistent use of measurement instruments in terms of setting and timing. Researchers in this field should reach a consensus with regard to the use of a common terminology for the outcomes of interest and a homogeneity when selecting measurement instruments and measurement timing methods.

Jennifer J. Sun, Megan Tjandrasuwita, Atharva Sehgal et al.

Neurosymbolic Programming (NP) techniques have the potential to accelerate scientific discovery. These models combine neural and symbolic components to learn complex patterns and representations from data, using high-level concepts or known constraints. NP techniques can interface with symbolic domain knowledge from scientists, such as prior knowledge and experimental context, to produce interpretable outputs. We identify opportunities and challenges between current NP models and scientific workflows, with real-world examples from behavior analysis in science: to enable the use of NP broadly for workflows across the natural and social sciences.

Xiaolong Ya, Chaoqi Zhang, Shuo Zhang et al.

Background: Delayed cerebral ischemia (DCI) is the main cause of death and disability after intracranial aneurysm rupture. Previous studies have shown that smoking can lead to DCI after intracranial aneurysm rupture. However, some recent studies have shown that nicotine, as the main ingredient of tobacco, can cause cerebral vasodilation. This view has led to a debate about the relationship between smoking and DCI. This study aims to determine the relationship between smoking and DCI.Methods: A systematic literature search was performed according to PRISMA guidelines. The Cochrane Library, Web of Science, PubMed, and Embase online databases were searched for studies published up to September 2020. All studies related to smoking and DCI were included in the analysis. The R and RevMan software were used for data analysis, and random or fixed model analysis was selected depending on the degree of heterogeneity. Publication bias was examined by using the Begg–Mazumdar test and using contour-enhanced funnel plots with trim method.Results: A total of eight original articles (12 cohorts) with 10,722 patients were included in this meta-analysis. There were statistically significant higher rates of DCI in the smoking group than in the non-smoking group (RRtotal = 1.16, 95%CI: 1.05–1.27). After heterogeneity among cohorts was removed by sensitivity analysis, there was still a statistically significant difference in the incidence of DCI between the smoking and non-smoking groups (RRtotal = 1.13, 95%CI: 1.07–1.20).Conclusions: Although the effects of nicotine as the main component of tobacco are unclear in terms of cerebral vessels, the present study suggests that smoking is a risk factor for DCI in patients with ruptured aneurysm.

Babatope O. Adebiyi, Ferdinand C. Mukumbang

Abstract Background Fetal Alcohol Spectrum Disorder (FASD) remains a global public health problem. South Africa is estimated to have the highest recorded prevalence of FASD. However, no study has systematically evaluated the available prevalence studies to provide estimates that may facilitate effective planning and delivery of prevention and management services. Therefore, we propose to conduct a systematic review and meta-analysis to report a pooled estimate of the FASD prevalence among children, youth and adults in South Africa. Methods We will include quantitative (cohort and cross-sectional) studies that reported on the prevalence of FASD in South Africa. We will search databases such as Academic Search Complete, Education Resource Information Center (ERIC), SocINDEX, Health Source: Nursing/Academic Edition, Cumulative Index of Nursing and Allied Health and PsycARTICLES), Scopus, Science Direct, Springer Link, JSTOR, SAGE journals, PubMed, Web of Science and Sabinet. The references of included studies will be searched for additional studies on the prevalence of FASD. The search will be from inception to October 2021. Screening of (titles, abstracts and full text of the potentially relevant articles) will be done by two independent authors using software. All disagreements will be resolved by discussion. A standardised data extraction form will be designed for the extraction. Two authors will independently extract the data from the selected articles and all disagreements will be resolved by discussion. We will use a tool developed by Munn and colleagues to critically appraise all the included studies. The primary outcome will be the proportion of individuals with FASD in South Africa. We will use the Freeman–Tukey double arcsine transformation to transform the raw prevalence estimates so that the data can follow an approximately normal distribution. We will use random-effects models to calculate 95% confidence intervals and prediction intervals based on multiple meta-analyses with transformed proportions. We will test heterogeneity using Cochran’s Q and describe using the I2 statistic. Discussion The pooled prevalence estimate will assist the government and other stakeholders (such as non-profit organisations and researchers) to plan and prioritise prevention and management interventions. Systematic review registration The protocol has been registered with PROSPERO (registration number: CRD42020197979 ).