Hasil untuk "Science (General)"

C. Yang, Qunying Huang, Zhenlong Li et al.

ABSTRACT Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers – Big Data and cloud computing – and reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.

G. Gece

A. Ambrosi, M. Pumera

J. Shoven, J. Whalley

H. Helmholtz, A. Ellis

A. McCright

B. Hofer

James H. Stronge

K. Binder

Sandy Lim, Lilia M. Cortina, V. Magley

N. Allum, Patrick Sturgis, Dimitra Tabourazi et al.

M. Ainley, J. Ainley

Bin Liu, Ihtisham Bukhari, Fazhan Li et al.

Jonas Wilinski

Scholarly data are largely fragmented across siloed databases with divergent metadata and missing linkages among them. We present the Science Data Lake, a locally-deployable infrastructure built on DuckDB and simple Parquet files that unifies eight open sources - Semantic Scholar, OpenAlex, SciSciNet, Papers with Code, Retraction Watch, Reliance on Science, a preprint-to-published mapping, and Crossref - via DOI normalization while preserving source-level schemas. The resource comprises approximately 960GB of Parquet files spanning ~293 million uniquely identifiable papers across ~22 schemas and ~153 SQL views. An embedding-based ontology alignment using BGE-large sentence embeddings maps 4,516 OpenAlex topics to 13 scientific ontologies (~1.3 million terms), yielding 16,150 mappings covering 99.8% of topics ($\geq 0.65$ threshold) with $F1 = 0.77$ at the recommended $\geq 0.85$ operating point, outperforming TF-IDF, BM25, and Jaro-Winkler baselines on a 300-pair gold-standard evaluation. We validate through 10 automated checks, cross-source citation agreement analysis (pairwise Pearson $r = 0.76$ - $0.87$), and stratified manual annotation. Four vignettes demonstrate cross-source analyses infeasible with any single database. The resource is open source, deployable on a single drive or queryable remotely via HuggingFace, and includes structured documentation suitable for large language model (LLM) based research agents.

Marcos Gabriel Mendes Lauande, Geraldo Braz Júnior, João Dallyson Sousa de Almeida et al.

Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underdeveloped countries like Brazil, where it represents approximately 2% of cancers affecting men. This dataset was created to address the scarcity of publicly available resources for classifying histopathological images in penile cancer research. The images were collected in 2021 from tissue samples obtained through biopsies of patients undergoing treatment for penile cancer. After staining with Hematoxylin and Eosin (H&E), the tissue samples were photographed using a Leica ICC50 HD camera attached to a bright-field microscope (Leica DM500). The dataset comprises 194 high-resolution images (2048 × 1536 pixels), categorized by magnification (40X and 100X) and pathological classification (Tumor or Non-Tumor). Metadata includes additional information such as histological grade and, for some images, HPV status. Although previous works have focused primarily on binary classification tasks, the dataset includes additional labels, such as histological grade and HPV (Human Papilloma Virus) presence, which provide opportunities for multi-label classification or other types of predictive modelling. These extended labels enhance the dataset’s versatility for more complex tasks in medical image analysis. The dataset holds significant reuse potential for machine learning tasks beyond binary classification, allowing researchers to explore additional layers of analysis, such as HPV detection and histological grading. It can also be used for model benchmarking and comparative studies in cancer research, contributing to developing new diagnostic tools. The dataset and metadata are available for further research and model development.

Melissa Costan, Kasim Costan, Anna Weißbach et al.

The gap between theory and practice is well-documented in educational research. Physics teachers' willingness to apply research findings in practice may be influenced by a sceptical attitude towards science education research. This study explores physics teachers' perspectives on science education research, with a particular focus on potential scepticism towards the discipline. A two-step mixed-methods approach was employed: (1) Interviews with a purposeful sample of 13 experienced physics teachers for a first exploration of attitudes towards physics education research, and (2) a quantitative survey of 174 physics teachers to examine, among other aspects, the previously observed attitudes in a larger sample and to identify teacher profiles using latent profile analysis. The interview study revealed both sceptical and non-sceptical attitudes towards physics education research, including some that fundamentally questioned its practical value. Based on the survey data and latent profile analysis, four distinct teacher profiles differing in their level of scepticism towards science education research were identified. While one profile is highly sceptical, the other three exhibit a mix of sceptical and supportive attitudes. Thus, physics teachers are not generally sceptical. However, the cooperation between research and practice is perceived as unproductive by most teachers.

Thi Thanh Nga Le, Minh Thiet Vu, Hoang Dang Khoa Do

Abstract Dicliptera tinctoria is a member of Acanthaceae, which has a wide distribution and contains potentially medicinal species, and exhibited pharmaceutical potentials. This study sequenced and characterized the complete chloroplast genome of Dicliptera tinctoria. The newly sequenced cpDNA of D. tinctoria was 150,733 bp in length and had a typical quadripartite structure consisting of a large single copy (LSC, 82,895 bp), a small single copy (SSC, 17,249 bp), and two inverted repeat (IRs, 25,295 bp each) regions. This genome also contained 80 protein-coding genes, 30 transfer RNAs, and four ribosomal RNAs, which is identical to other chloroplast genomes in Acanthaceae family. Nucleotides diversity analysis among chloroplast genomes of Acanthaceae species revealed eight hypervariable regions, including trnK_UUU-matK, trnC_GCA-petN, accD, rps12-clpP, rps3-rps19, ycf1-ndhF, ccsA-ndhD, and ycf1. Phylogenetic analysis revealed the paraphyly of Dicliptera species and monophyly in four Acanthaceae subfamilies. These results provide an overview of genomic variations in Acanthaceae chloroplast genome, which is helpful for further genomic studies.

Ya-Wen Peng, Ri Tang, Qiao-Yi Xu et al.

Background: Fibrosis is a heavy burden on the global healthcare system. Recently, an increasing number of studies have demonstrated that Extracellular vesicles play an important role in intercellular communication under both physiological and pathological conditions. This study aimed to explore the role of extracellular vesicles’ in fibrosis using bibliometric methods. Methods: Original articles and reviews related to extracellular vesicles and fibrosis were obtained from the Web of Science Core Collection database on November 9, 2022. VOSviewer was used to obtain general information, including co-institution, co-authorship, and co-occurrence visualization maps. The CiteSpace software was used to analyze citation bursts of keywords and references, a timeline view of the top clusters of keywords and cited articles, and the dual map. R package ''bibliometrix'' was used to analyze annual production, citation per year, collaboration network between countries/regions, thematic evolution map, and historiography network. Results: In total, 3376 articles related to extracellular vesicles and fibrosis published from 2013 to 2022 were included in this study, with China and the United States being the top contributors. Shanghai Jiao Tong University has the highest number of publications. The main collaborators were Giovanni Camussi, Stefania Bruno, Marta Tepparo, and Cristina Grange. Journals related to molecular, biology, genetics, health, immunology, and medicine tended to publish literature on extracellular vesicles and fibrosis. “Recovery,” “heterogeneity,” “degradation,” “inflammation,” and “mesenchymal stem cells” are the keywords in this research field. Literature on extracellular vesicles and fibrosis associated with several diseases, including “kidney disease,” “rheumatoid arthritis,” and “skin regeneration” may be the latest hot research field. Conclusions: This study provides a comprehensive perspective on extracellular vesicles and fibrosis through a bibliometric analysis of articles published between 2013 and 2022. We identified the most influential countries, institutions, authors, and journals. We provide information on recent research frontiers and trends for scholars interested in the field of extracellular vesicles and fibrosis. Their role in biological processes has great potential to initiate a new upsurge in future research.

I. Cárdenas-León, R. Morales-Ortega, M. Koeva et al.

According to the KNMI Klimaatsignaal’21, the average surface temperature in The Netherlands has increased by 2.3°C between 1901 and 2020. Moreover, The Netherlands is also experiencing more frequent and intense heatwaves. Urban development significantly impacts the environmental conditions of a city, influencing thermal comfort and human well-being. To deal with these problems, municipalities across the country have been tasked to find ways to measure, understand, and find solutions to the increasing temperatures, specifically in urban areas. Because of this, several contrasting urban heat maps have been produced using different metrics and methods by different agencies. Koopman et al. presented a methodology for a standardized urban heat map at a 1-m spatial resolution to unify the stress tests by selecting the Physical Equivalent Temperature (PET) as a metric for heat stress. The PET is a key indicator in bio-meteorology, quantifying the combined effects of various environmental factors on human thermal perception. Despite its utility, widespread adoption of PET-based assessments by municipalities remains limited. To address this gap, this paper presents the development of a Digital Twin framework using PET analysis, enabling a collaborative, nondestructive, and cost-effective assessment of urban interventions’ impact on thermal conditions. Leveraging geoprocessing workflows and geospatial data, our framework allows for real-time PET calculations and scenario testing, facilitating informed decision-making by urban planners. The framework was tested and applied for Enschede, Netherlands, demonstrating its efficacy in visualizing current conditions, projecting future scenarios, and evaluating intervention strategies. Feedback from urban planners highlighted the tool’s usability and potential for enhancing community engagement in urban planning processes.

Noorhayati Idros, Lariyah Mohd Sidek, Nur Anis Aishah M. Rahim et al.

The aim of this study is to evaluate the current water quality status of one of the urban rivers in Malaysia, called Sungai Air Hitam. The river's water supply is not only unsuitable for the inhabitants but also hazardous to the aquatic species that depend on it. In order to simulate the water quality formulation of the river, the Model for Urban Stormwater Improvement Conceptualization (MUSIC) was used. The effects of various best management practices (BMPs) components have been examined to improve the river's water quality. This study also investigated different scenarios of the expected future changes in the land cover and the quality of the river. As the proportion of impervious surfaces increases, the urban hydrology cycle can be significantly altered, resulting in an increase in volumes and peak flows, and a decrease in storage, infiltration, and interception. The MUSIC results have shown significant reductions in biochemical oxygen demand (BOD), total suspended solids (TSS), total phosphorus (TP), and total nitrogen (TN) after introducing BMPs. It was also noticed that the prediction of pollutants falls within the acceptable range set by the Urban Stormwater Management Manual for Malaysia (MSMA) 2nd edition. For the land cover, it was found that the total reduction of BOD, TSS, TP, and TN for existing land use is 92.5 %, 94.5 %, 90.7 % and 91.9 %. Meanwhile, the total reduction in future land use is 81.6 % for BOD, 86.2 % for TSS, 80.9 % for TP and 80.8 % for TN. From the simulation results, it was observed that the application of BMPs has successfully reduced the observed mean BOD concentration from 92.38 mg/L (Class V) to 6.93 mg/L (Class IV) of the national water quality standards, NWQS, water quality index. As a result, the water quality index of the overall catchment has improved from Class IV to Class III (WQ1, WQ3, and WQ4) and from Class V to IV (WQ2) with the application of the BMPs. This assessment aims to raise awareness within the Sungai Air Hitam community regarding the importance of preserving river cleanliness and understanding the long-term environmental impact of water quality. These findings underscore the importance of an integrated system in managing urban water systems, which can offer valuable insight to the decision-makers.