jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Pan Huang | Jianxia Du | Mingjie Yuan | M. Zhu
Source: Journal of Fiber Bioengineering and Informatics (article, 2025-12-10)
Field: Materials Science — Polymers and Plastics

An Intelligent Framework for Multi-Scenario Fabric Selection in Cycling Apparel: A User-Expert Dual-Driven Approach Traditional evaluation of cycling trouser fabrics employs fixed-weight methods, failing to address the diverse performance demands of dynamic cycling scenarios. To overcome this limitation, this study developed and validated an intelligent scoring system using a “user-expert” dual-driven dynamic weight optimisation strategy. A dynamic weighting scheme was first constructed by integrating the Analytic Hierarchy Process (AHP) with user survey data. To mitigate data scarcity, a Generative Adversarial Network (GAN) was utilised to augment the dataset. Subsequently, a random forest regression model, integrated with a fuzzy logic engine, was employed to dynamically adjust performance weights (abrasion resistance, moisture permeability, air permeability) based on scenario inputs. The model achieved a coefficient of determination ($R^2$) of 0.924 on the training set and an average $R^2$ of 0.893 on the test set. Further validation demonstrated a prediction error of $\le 5.2\%$ for new fabrics and maintained $R^2$ values above 0.85 under hyperparameter sensitivity analysis, indicating strong generalisation and robustness. This research provides a validated, data-driven framework for fabric selection in customised clothing and introduces a novel paradigm for the performance-based design of advanced technical textiles. Weighting ; Fuzzy logic ; Process (computing) ; Set (abstract data type) ; Hyperparameter ; Selection (genetic algorithm) ; Sensitivity (control systems) ; Analytic hierarchy process Textile materials and evaluations ; Advanced Sensor and Energy Harvesting Materials ; Epoxy Resin Curing Processes
Authors: Clínicos IPS. Bogotá, Colombia. Universidad Industrial de Santander. Bucaramanga, Colombia | Camilo Rojas | Alexánder Rojas | Universidad Industrial de Santander. Bucaramanga, Colombia | Álvaro J. Idrovo
Source: Salud UIS (article, 2025-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Sobre la introducción de quelantes para tratar intoxicaciones por metales en Colombia: una historia olvidada Este trabajo resume las primeras experiencias con quelantes para manejar intoxicaciones con metales en Colombia. El primer uso conocido fue consecuencia de la intoxicación con metil-paratión de más de 500 individuos en Chiquinquirá en 1967; el dimercaprol o BAL (British Anti-Lewisite) fue usado erróneamente entre algunos afectados. A comienzos de los años 70 del siglo XX, el médico de la mina “La Esperanza”, en Aranzazu, Caldas, empezó a usar BAL y penicilamina para tratar los numerosos casos de hidrargirismo. Esto dos casos son hitos de la historia de la farmacología, la toxicología y la salud ambiental y ocupacional colombiana y latinoamericana que han sido olvidados. Linea ; Dimercaprol ; Context (archaeology) History and advancements in chemistry ; Thallium and Germanium Studies ; Carcinogens and Genotoxicity Assessment
Authors: Hu Li | Zhu Shiyang | Wen Xu | ZHONGYONG YANG | X. Liu | WEIQI ZHANG
Source: TURKISH JOURNAL OF AGRICULTURE AND FORESTRY (article, 2025-04-21)
Field: Chemistry — Analytical Chemistry

Assessment of chlorophyll levels in navel oranges based on remote sensing images of unmanned aerial vehicles The swift, effective, and noninvasive assessment of citrus chlorophyll levels is important for the timely diagnosis of citrus growth status, and the decision-making of orchard management. In this study, unmanned aerial vehicles (UAVs) with multispectral remote sensing imagery were applied to the mandarin orange, through which five vegetation indices [Medium Resolution Imaging Spectrometer Terrestrial Chlorophyll Index (MTCI), Red-edge Chlorophyll Index (CIre), Nitrogen Reflectance Index (NRI), Red, and Normalized Difference Vegetation Index (NDVI)], which better reflect citrus photosynthetic activity and productivity, were screened. The stepwise linear regression (SLR) method, support vector machine (SVM) regression method, and radial basis function neural network (RBFNN) technique were employed to develop the chlorophyll inversion model for navel oranges, and the precision and relevance of the inversion model were evaluated using the coefficient of determination (R2), root mean square error (RMSE), mean relative error (MRE), and estimation accuracy (EA). The results revealed that the MTCI and CIre exhibited highly significant correlations with the citrus chlorophyll content, with correlation coefficients of 0.830 and 0.829, respectively. Additionally, the NRI, Red, and NDVI also showed certain correlations with the citrus chlorophyll content, with correlation coefficients of –0.547, –0.481, and 0.470, respectively. Moreover, the four metrics used to evaluate the SLR method fell short, with an R² value trailing behind that of both the SVM method and the RBFNN by 9.6% and 15.0%, respectively. The training concentration effect of the SVM method was the best, with an R2 = 0.738. In the actual test, the effect decreased, with an R2 = 0.714, and the RBFNN method had the best effect in the test concentration, with an R2 = 0.759. Additionally, the citrus chlorophyll content during the coloration period could be simulated based on the RBFNN model, with R2, RMS, RMRE, and EA values of 0.759, 0.053, 0.188, and 0.975, respectively. The results indicated good applicability of the RBFNN model in determining the citrus chlorophyll content, which could provide accurate guidance for the management of citrus orchards. Navel orange ; Navel ; Remote sensing ; Environmental science ; Chlorophyll ; Chlorophyll a ; Botany ; Horticulture ; Biology ; Geography Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Remote Sensing in Agriculture
Authors: 余可 | 胡琴 | 曾婷玉 | 彭汉平 | 韩明静 | 张金团
Source: 中国科学与技术学报 (article, 2025-06-12)
Field: Materials Science — Polymers and Plastics

基于专利挖掘的中国智能纺织/服装技术主题发展研究 我国作为传统纺织大国，纺织/服装技术与国民生活息息相关。随着大数据、人工智能等技术的快速发展，智能纺织/服装技术正逐步从单一功能向多功能集成方向发展，本研究聚焦于智能纺织/服装技术这一融合了纺织科学、材料工程与信息技术的交叉领域，旨在通过专利挖掘方法，深入分析智能纺织/服装技术，以揭示其技术主题及发展情况。本研究以IncoPat专利数据库为数据来源，检索智能纺织/服装技术相关专利并分析其发展情况，运用LDA主题模型提取专利数据中隐含的技术主题。研究表明中国智能纺织/服装专利以发明专利为主，正处于成熟初期，专利申请主要集中在江苏、浙江、广东等东部沿海地区，并识别出纺织机械与设备、功能性纤维与智能材料、服装模块化与AI检测技术、智能衣物温控调节技术四大技术主题。 Chemistry Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Additive Manufacturing and 3D Printing Technologies
Source: International Journal of Open-access Interdisciplinary and New Educational Discoveries of ETCOR Educational Research Center (iJOINED ETCOR) (article, 2025-08-05)
Field: Chemistry — Organic Chemistry

Habitat Suitability of Lapnisan (Aquilaria spp.) Under Various Climatic Projections for Reforestation in Negros Oriental, Philippines Aim: This study aimed to assess the habitat suitability of Aquilaria species in Negros Oriental, Philippines, in response to projected climate change scenarios Representative Concentration Pathway (RCP) 2.6 and RCP 8.5 in 2050.Specifically, it sought to determine the area (km 2 ) and location for suitable Aquilaria reforestation sites. Methodology:The study employed purposive sampling and data mining to determine the actual location of Aquilaria species.The coordinates of Aquilaria were used to evaluate the model's performance through the Area Under the Curve (AUC), assessing its ability to distinguish between suitable and unsuitable habitats.Key input layers-including climatic variables (temperature and rainfall), environmental factors (land cover, soil type, elevation, and slope), and a Digital Elevation Model (DEM)-were reclassified and weighted based on their relevance to Aquilaria growth.These layers were integrated in ArcGIS to generate habitat suitability maps under climate scenarios RCP 2.6 and RCP 8.5, projecting potential suitable areas for Aquilaria by the year 2050.Results: Under the extreme RCP 8.5 scenario, no areas remained classified as highly suitable.However, moderately suitable habitats expanded significantly from 6.79% to 4,559.329km 2 (93.44%), while marginally suitable areas increased from 3.20 km 2 (0.06%) to 319.90 km 2 (6.56%).Despite a reasonably strong model performance (AUC = 0.79), ecological compatibility for Aquilaria declined-likely due to its dependence on stable moisture conditions and limited thermal tolerance.Additionally, habitat fragmentation and reduced connectivity, particularly in climate-impacted barangays, exacerbate risks to the species' survival.Conclusion: Highly suitable areas may vanish entirely, with the species being forced into less favorable, moderately to marginally suitable zones.The RCP 8.5 climate scenario marks a critical ecological turning point for Aquilaria spp., with suitable habitats in Negros Oriental projected to shift from low elevations (<300-400 m) to mid elevations (600-900 m), particularly under this high-emissions pathway. Reforestation ; Habitat ; Agroforestry ; Geography ; Afforestation ; Forestry ; Environmental science ; Ecology ; Biology Wood and Agarwood Research
Authors: Peter Fallows | Gavin J. Wright
Source: PubMed (article, 2025-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Convolution-based Gamma Knife planning from ICON CBCT: Three-level stepwise electron density assignment versus Hounsfield Unit curve. Using ICON CBCT images for dose calculation can result in an underestimation of the dose compared to convolution using CT images. However, using CBCT images along with a three-level stepwise electron density curve with fixed electron densities can provide good agreement with doses calculated using convolution with CT images. Hounsfield scale ; Convolution (computer science) ; Icon ; Mathematics ; Computer science ; Nuclear medicine ; Computed tomography ; Artificial intelligence ; Medicine ; Radiology Electron and X-Ray Spectroscopy Techniques
Authors: Aezeden Mohamed
Source: SHS Web of Conferences (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Design and Fabrication of a Novel Automatic Coconut De-husking and Deshelling Machine Such an innovative machine integrating dehusking and desshelling operations has been developed in response to the challenges of small scale coconut processors that are necessary to meet the market demands for fast, efficient, and economical coconut processing technologies. The process in general with traditional methods normally becomes very inefficient, with high labor costs and low throughput. The proposed machine is composed of a dehusking unit with the adaptation of the applied force to maximize the dehusking rate and a deshelling unit for breaking the shell in a controlled manner in order to protect the kernel from damage. The machine is equipped with energy efficient components, modular attachments for flexibility and a user friendly control panel to ease its operate and maintenance. The design elements in these two parts of the machine are intended to make the machine both accessible and practical for small scale use. Performance tests prove splendidly more efficient and faster than traditional methods. As this machine successfully reduced labor requirement by X % and energy consumption by Y %, it presents an incredible opportunity to completely revolutionize coconut processing outting a processing rate of up to X coconuts per hour. The end result of such an innovative solution is that it is expected to benefit small scale processors by enhancing productivity, minimizing operational costs and offering a sustainable option as opposed to labor consuming traditional methods, and in line with the ongoing call for technologically modernized agriculture. Fabrication ; Computer science ; Engineering ; Materials science ; Medicine Coconut Research and Applications ; Embedded Systems and FPGA Applications ; Industrial Automation and Control Systems
Authors: Bahtiar Rahmat | Agung Ari Purwanto | Muhammad Fahrudin | Wahyu Wijaya Widiyanto
Source: Infotekmesin (article, 2025-01-30)
Field: Materials Science — Materials Chemistry

Pengaruh Metode Penyayatan dan Kedalaman Penyayatan terhadap Dimensi dan Kekasaran Permukaan Kayu Olahan The application of CNC technology in the furniture industry has already become familiar, in addition to its use in the metal and plastic industries. HMR (High Moisture Resistant) panels, which had better moisture resistance than MDF (Medium Density Fiberboard), had also started to develop. However, few studies have investigated the effects of variations in machining parameters on the cutting quality of HMR boards. This study aimed to test the effects of machining parameters (cutting method and cutting depth) on the dimensions and surface roughness of the workpiece. Four schemes of machining parameter settings, namely conventional and climb methods with cutting depths of 2 mm and 4 mm, respectively, were performed with three repetitions each. After testing, it was found that the cutting method, cutting depth, and the interaction between the cutting method and cutting depth had not significantly affected the length and width dimensions of the specimen. However, the cutting method significantly influenced the final surface roughness of the specimen. The conventional cutting method with a cutting depth of 2 mm produced the best surface roughness, measuring 26.47 µm. Physics Material Selection and Properties ; Occupational Health and Safety Management ; Geotechnical and construction materials studies
Authors: Mario Gobrial | Lukas Domenig | Michael Reichelt | Manfred Kaltenbacher | Olaf Steinbach
Source: ArXiv.org (preprint, 2025-04-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inclusion of an Inverse Magnetic Hysteresis Model into the Space-Time Finite Element Method for Magnetoquasistatics In this note we discuss the numerical solution of the eddy current approximation of the Maxwell equations using the simple Pragmatic Algebraic Model to include hysteresis effects. In addition to the more standard time-stepping approach we propose a space-time finite element method which allows both for parallelization and adaptivity simultaneously in space and time. Numerical experiments confirm both approaches yield the same numerical results. Finite element method ; Hysteresis ; Eddy current ; Simple (philosophy) ; Maxwell's equations ; Algebraic equation ; Space (punctuation) ; Inverse Magnetic Properties and Applications ; Electromagnetic Simulation and Numerical Methods ; Advanced Numerical Methods in Computational Mathematics
Authors: Doddy Kastanya | Dumitru Serghiuta
Source: Nuclear Science and Engineering (article, 2025-03-19)
Field: Materials Science — Materials Chemistry

Special issue featuring papers from the 2023 International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&amp;C 2023) <i>Guest Editors</i> Nuclear science ; Science and engineering ; Engineering ethics ; Computer science ; Nuclear engineering ; Engineering physics ; Physics ; Engineering Graphite, nuclear technology, radiation studies
Authors: Olivier Nadeau
Source: theses.fr (ABES) (article, 2025-12-12)
Field: Materials Science — Materials Chemistry

Simulation of hydrogen absorption in intermetallic compounds L’hydrogène est un vecteur énergétique prometteur en raison de sa densité énergétique gravimétrique élevée, de son abondance et de la possibilité de l’utiliser sans émettre de carbone. Parmi les matériaux de stockage, les alliages de type A₂B₇ suscitent un intérêt scientifique considérable, puisqu’ils combinent une capacité d’absorption élevée et réversible avec une cinétique favorable et une stabilité sur de nombreux cycles d’absorptiondésorption. Ce travail vise à prédire, à partir des premiers principes et sans paramètres empiriques, les propriétés d’absorption de l’hydrogène de ces alliages. Une approche Monte Carlo Grand canonique basée sur des potentiels harmoniques est d’abord développée pour prédire l’isotherme d’absorption complète du Nd₃MgNi₁₄, conduisant à la création du logiciel GAMMON. À notre connaissance, il s’agit du premier travail produisant une isotherme d’absorption complète exclusivement à partir de calculs ab initio. Il met aussi en évidence l’importance cruciale des fonctionnelles d’échange-corrélation hybrides ainsi que des effets nucléaires quantiques pour reproduire fidèlement les résultats expérimentaux. La méthodologie est générale et robuste, fournissant un outil pour étudier l’impact des substitutions atomiques sur la thermodynamique d’hydrures complexes. Par la suite, une méthode d’échantillonnage Grand canonique a été implémentée dans le logiciel Machine Learning Assisted Sampling (MLAS), établissant une boucle auto-cohérente dans laquelle un potentiel d’apprentissage machine (MLIP) est entraîné activement. Le MLIP est ajusté pour reproduire les énergies, forces et contraintes issues de calculs DFT pour les configurations échantillonnées dans l’ensemble Grand canonique. Il est important de noter que le MLIP est uniquement utilisé pour générer de nouvelles configurations décorrélées, alors que les propriétés thermodynamiques sont obtenues directement à partir des calculs DFT, ce qui assure la précision des résultats. Après une étude approfondie, la famille de MLIP GrACE a été sélectionnée pour sa stabilité et sa transférabilité exceptionnelles. Cette approche a été validée sur le MgH₂, où elle a permis d’effectuer une simulation Monte Carlo Grand canonique avec une précision proche de la DFT, ce qui était jusqu’alors inaccessible. La méthodologie est désormais prête à être appliquée aux alliages de type A₂B₇, ouvrant la voie à des simulations précises et efficaces de l’absorption d’hydrogène dans les hydrures. Linear response theory ; Monte Carlo method ; Neutron scattering ; Hydrogen Hydrogen Storage and Materials ; Rare-earth and actinide compounds ; Machine Learning in Materials Science
Authors: Guillaume Deflandre | Sebastian Gibb | Laurent Gatto
Source:  (preprint, 2025-07-22)
Field: Chemistry — Spectroscopy

PSMatch: an R/Bioconductor package to explore proteomics identification data We present the R/Bioconductor PSMatch package, that helps proteomics practitioners to load, manage and handle peptide spectrum matches. It provides functions to model peptide-protein relations,visualise these as graphs and make informed decisions about shared peptide filtering. The package also provides functions to calculate fragments and, in conjunction with the Spectra package,annotate and visualise MS2 scans. Bioconductor ; Identification (biology) ; R package ; Computer science ; Data science ; Biology ; Programming language Advanced Proteomics Techniques and Applications ; Gene expression and cancer classification ; Genetics, Bioinformatics, and Biomedical Research
Authors: S. F. Diakov | S. A. Agafonov
Source: Vestnik MGSU (article, 2025-12-30)
Field: Materials Science — Materials Chemistry

Method of analysis and interpretation of SCAD++ calculation results using external postprocessor Introduction. One of the crucial aspects of solving various mechanical problems using numerical methods is the interpretation of the obtained results for their further use. Modern computational complexes implementing the finite element method have a so-called postprocessor — a module designed to ease visualization and interpretation of the results of performed calculations. However, no matter how advanced the postprocessor built into the CAE programme is, its functionality may be insufficient for solving a particular engineering task. One of the ways to optimize the relevant stages of work is to use third-party software products and develop custom extensions. Materials and methods. Determination of the required parameters of reinforcement of monolithic reinforced concrete structures of complex geometric shape is performed in the SCAD++ computer complex, but their further processing by built-in tools is challenging. Within the framework of the proposed methodology, interpretation, and analysis of the results of reinforcement of a monolithic reinforced concrete slab with wide beams obtained in SCAD++ were performed using the freeware software product Gmsh and a user script in the Python programming language. Results. The implementation of the proposed algorithm of data processing obtained from SCAD++ allowed to overcome the limitations of standard means of CAE system in terms of visualization of the results of the performed calculations. As well as to create initial data for their further use in engineering and construction design. Conclusions. The proposed methodology is convenient for application in engineering practice and provides wide opportunities for effective analysis of the results of calculations performed by the finite element method and their further processing. Its use will increase the efficiency of decisions taken, improve the design process of geometrically complex structures and their elements, as well as optimize the financial costs of software acquisition. Python (programming language) ; Visualization ; Software ; Finite element method ; Interpretation (philosophy) ; Slab ; Processing Structural mechanics and materials ; Construction Management and Sustainability ; Advanced Energy Technologies and Civil Engineering Innovations
Authors: Maristella | Marlina Setia Sinaga
Source: Jurnal Absis Jurnal Pendidikan Matematika dan Matematika (article, 2025-04-30)
Field: Chemistry — Analytical Chemistry

Application of sugeno's fuzzy inference system (FIS) in determining palm oil production Palm oil is an important export commodity in Indonesia, and factors such as palm oil prices, production, and palm oil prices influence palm oil production. In this research, the fuzzy logic method is used to overcome uncertainty in predicting palm oil production. Various fuzzy methods, including Mamdani, Tsukamoto, and Sugeno, are used to model production based on certain factors. The type of research carried out in this research is a literature study and this research uses secondary data or data obtained by other parties. Secondary data taken is CPO price data, palm oil prices and palm oil production data. The prediction results for palm oil production using the Sugeno fuzzy method for several months are based on factors such as CPO prices and palm oil prices in the fuzzy system. The final results of MAPE provide information about the level of accuracy of the model in predicting palm oil production, which is 7.09%. FIS Sugeno connects input-output with fuzzy rules. The steps include variable selection, membership functions, rules, inference, defuzzification, evaluation, optimization, and implementation. The predicted MAPE is 7.09%, indicating the accuracy of the model in estimating palm oil production compared to the actual value. Palm oil ; Fuzzy inference system ; Fuzzy inference ; Palm ; Production (economics) ; Inference ; Fuzzy logic ; Agricultural engineering ; Computer science ; Artificial intelligence ; Fuzzy control system ; Environmental science ; Adaptive neuro fuzzy inference system ; Agricultural science ; Engineering ; Economics Spectroscopy and Chemometric Analyses