jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fırat Akın | Oktay Arıkan
Source: Journal of Applied Polymer Science (article, 2025-05-28)
Field: Materials Science — Materials Chemistry

Investigation of Voltage Rise Rate Effect on the Breakdown Voltage of Solid Insulating Materials Considering Different Electrode Configurations ABSTRACT For reliable power equipment designs, it is critical to investigate the breakdown performances of insulating materials for a variety of scenarios, including various electrode geometries and voltage characteristics. In this study, the effect of voltage rise rate on the breakdown voltages of presspaper and styrene‐butadiene rubber/natural rubber (SBR/NR) is investigated through different electrode geometries. During the experiments, voltages were applied with rise rates of 500 and 3000 V/s, using three different electrode configurations: cylinder–cylinder, sphere–cylinder, and point–cylinder. In order to explain and support the experimental results, a simulation study was performed with COMSOL Multiphysics for electric field analysis. Materials science ; Electrode ; Multiphysics ; Voltage ; Breakdown voltage ; Composite material ; Cylinder ; Natural rubber ; Electric field ; High voltage ; Mechanics ; Electrical engineering ; Mechanical engineering ; Chemistry ; Engineering ; Structural engineering ; Finite element method ; Physics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Lightning and Electromagnetic Phenomena
Authors: A. Lagzdiņš | Ilze Beverte | Vilis Skruls | J. Andersons
Source: Polymers (article, 2025-09-08)
Field: Materials Science — Polymers and Plastics

Investigation of the Variants of Independent Elastic Constants of Rigid Polyurethane Foams with Symmetry Elements Rigid PU foams have wide practical applications, and their mathematical modelling would benefit from deeper knowledge about the variants of independent elastic constants of symmetric PU foams. Therefore, in this study, various symmetry elements of rigid PU foams were analysed in relation to the characteristics of production moulds and technologies. The generalised Hooke's law was considered together with additional relationships valid for certain types of symmetry. Variants of independent elastic constants were determined for orthotropic, orthotropic with a rotational symmetry, and isotropic PU foams. For transtropic PU foams, nine variants of independent elastic constants were identified and corresponding equations for the components of response strain tensor were derived. Then, in order to investigate the results provided by the 9 variants, 12 elastic constants were determined experimentally in compression and shear for free-rise, rigid, and quasi-transtropic PU foams with average densities of 34 kg/m<sup>3</sup>, 55 kg/m<sup>3</sup>, and 75 kg/m<sup>3</sup>. Based on the analysis of (a) measurement uncertainties and (b) satisfying of the transtropy equations, an assessment was made of the correspondence of the experimentally determined elastic constants to the constants of a perfectly transtropic material. This made it possible to identify variants of independent constants that ensure the best correspondence between the calculated strains and the set of average strains. Orthotropic material ; Isotropy ; Symmetry (geometry) ; Rotational symmetry ; Polyurethane ; Shear (geology) ; Tensor (intrinsic definition) Polymer composites and self-healing ; Environmental and Industrial Safety ; Structural mechanics and materials
Authors: Wang Zhiliang
Source: Edunity Kajian Ilmu Sosial dan Pendidikan (article, 2025-12-03)
Field: Materials Science — Materials Chemistry

Research and Application of Corrosion Prevention Technology for Underground Water Intake Pipelines Based on ICCP (Impressed Current Cathodic Protection) Underground water intake pipelines play a critical role in supporting the operational reliability of the IPP Sumsel-5 facility, including reuse water, service water, and fire protection systems. These pipelines supply essential resources such as boiler feedwater, steam support, and fire safety, making their integrity vital for continuous plant operations. However, prolonged underground service exposes them to severe corrosion risks that may lead to leaks, water loss, reduced system performance, and potential equipment damage. This study aims to analyze and implement an effective corrosion prevention strategy using Impressed Current Cathodic Protection (ICCP) technology to enhance pipeline lifespan and operational safety. A field-based engineering assessment was conducted involving soil resistivity measurement, pipeline potential testing, corrosion rate evaluation, and system modeling to identify the extent of corrosion threats. The ICCP design framework included anode bed configuration, current output determination, rectifier sizing, and protection potential optimization suited to site-specific soil characteristics. Data collection and analysis were performed through on-site inspection, electrochemical measurement, and simulation-based verification. The results show that the application of ICCP significantly improved the protection potential of the pipelines, maintaining the recommended - 850 mV (Cu/CuSO4) criterion and reducing corrosion progression to a negligible rate. The optimized ICCP system demonstrated stable current distribution, extended pipeline service life, and reduced maintenance risks. Overall, this study confirms that ICCP technology provides a reliable and effective solution for mitigating underground pipeline corrosion at IPP Sumsel-5 and can be adopted as a long-term corrosion management strategy. Cathodic protection ; Corrosion ; Pipeline transport ; Current (fluid) ; Anode ; Galvanic anode ; Corrosion monitoring ; Boiler (water heating) Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Structural Integrity and Reliability Analysis
Authors: U. A. Onwuzuruike | M. D. Uluocha | O. E. Agwo | I. N. Okwunodulu | C. F. Ezeanyagu
Source: ADAN Journal of Agriculture (article, 2025-12-31)
Field: Chemistry — Organic Chemistry

Antioxidant and Physicochemical Properties of African Oil Bean (Pentaclethra macrophylla) Seed Oil Blended with Roasted Sesame (Sesamum indicum L.) Seed Oil This study evaluated the antioxidant and physicochemical properties of African oil bean seed oil (AOBO) blended with roasted sesame seed oil (RSO). Oils were extracted from African oil bean seeds, unroasted sesame seeds, and roasted sesame seeds. AOBO was blended with unroasted and roasted sesame seed oil at two ratios: 90:10 and 85:15, respectively, using soybean oil as the reference. Following extraction, oil yields were calculated (AOBO: 47.95%; Unroasted Sesame: 46.88%; RSO: 53.70%). The unmixed and blended oils were assessed for their physicochemical properties (viscosity, refractive index, specific gravity, melting point, cloud, smoke, flash, and fire points) and antioxidant activity (DPPH, ABTS, and FRAP assays). Physicochemical properties varied, ranging from 36.66–42.06 cP for viscosity, 29.80–31.09°C melting point, 185.49–191.85°C smoke point and 319.05–337.94°C (flash point). Antioxidant activity assays showed values of 3.51–11.03% (FRAP), 54.74–96.28% (DPPH), and 46.27–91.47% (ABTS). The results indicate that blending African oil bean and roasted sesame oils achieved a product with better complementary benefits: enhanced thermal stability from higher smoke (185.49 – 191.85) and flash points (319.05 - 337.94), improved fluidity due to improved viscosity and melting point, and robust antioxidant activity than African oil bean seed oil blended with unroasted sesame seed oil. These findings suggest the potential of the blended oil as a versatile ingredient in culinary and nutraceutical applications. This study contributes to understanding how oil blending can optimize both the functional and health-promoting qualities of vegetable oils, particularly those derived from underutilized food material. Sesame oil ; Ingredient ; Antioxidant ; Soybean oil ; Sesame seed ; Vegetable oil ; Olive oil ; Linoleic acid Edible Oils Quality and Analysis ; Sesame and Sesamin Research ; Food Chemistry and Fat Analysis
Authors: Mehdi Mirzaei | Sadra Rafatnia | Mohammad Mohammadi Shahir | Somayeh Jamshidi | Maryam Farbodi
Source: Scientific Reports (article, 2025-11-11)
Field: Materials Science — Materials Chemistry

Observer-based fault tolerant control of shape memory alloy actuator This study aims to design and experimentally implement a nonlinear fault tolerant control scheme for shape memory alloy actuator employed for a robotic manipulator. In the proposed scheme, a super twisting sliding mode controller as a baseline controller is firstly developed based on a reduced order model of the overall system. This controller robustly controls the manipulator position in fault-free conditions of the shape memory alloy actuator. Simultaneously, a nonlinear observer is introduced to estimate perturbations and actuator faults. If the estimated perturbation exceeds a predefined threshold for unmodeled system dynamics, a potential actuator fault is detected. When actuator fault is detected, the decision mechanism activates and utilizes observer data to reconfigure the controller, thereby compensating for the fault. The stability of the controller has been demonstrated in the presence of input constraints using the Lyapunov method. Experimental results for healthy actuator demonstrate that the baseline controller maintains robustness against uncertainties and unmodeled dynamics without requiring perturbation estimates. Consequently, the perturbation information enables both fault detection and compensation within a simplified control architecture. Comparative results with a passive fault-tolerant controller indicate the superior performance of the suggested scheme in compensating for faults, uncertainties, and unmodeled dynamics. Control theory (sociology) ; Actuator ; Robustness (evolution) ; Nonlinear system ; Fault tolerance ; Perturbation (astronomy) ; Shape-memory alloy ; Controller (irrigation) ; Lyapunov stability Shape Memory Alloy Transformations ; Soft Robotics and Applications ; Piezoelectric Actuators and Control
Authors: Valentin Mikhailov | Serik Akhmediev | Gulzada Tazhenova | Murat Karacasu | Daniyar Tokanov | Madi Bakirov
Source: Istrazivanja i projektovanja za privredu (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Regression analysis algorithm for the results of reinforced concrete slabs technical inspection The paper presents an algorithm for calculating key statistical parameters, including correlation dependences, correlation coefficients, and a method of checking the presence of a linear dependence. A quadratic regression equation is obtained, regression curve graphs are constructed, distribution functions and probability densities with the procedure for their normalization are calculated. The main statistical parameters of random variables are also calculated: mathematical expectation, variance, standard deviation, and quantiles of various levels. The proposed regression analysis algorithm can be used to assess safety and reliability of building structures, which allows analyzing their operation in a probabilistic form. Based on the theoretical and applied results of the work, prospects are opened for further development of probabilistic analysis methods for safety of construction projects as a whole, taking into account their complex structure and interaction of various structural elements. Regression analysis ; Probabilistic logic ; Probabilistic analysis of algorithms ; Reliability (semiconductor) ; Proper linear model ; Linear regression ; Normalization (sociology) ; Quadratic equation ; Probability distribution Structural mechanics and materials ; Construction Management and Sustainability ; Environmental and Industrial Safety
Authors: Soné Kotze | Kai‐Uwe Goss | Andrea Ebert
Source: Preprints.org (preprint, 2025-10-09)
Field: Chemistry — Physical and Theoretical Chemistry

Classifying Transportable vs. Non-Transportable Compounds Through Fundamental Energy Constraints Predicting whether a compound is subject to active transport is crucial in drug development. We propose a simple threshold for passive membrane permeability Pm, derived from the cell’s energy limitation, to identify compounds unlikely to be actively effluxed. For MDCK cells, this threshold—normalized to the applied compound concentration (Cext)—was determined to be log(Pm*Cext / [cm/s*µM] ) = -1.7. To derive this threshold, we conducted an extensive analysis of literature-reported efflux ratios (ER) in MDCKII-MDR1, MDCK-BCRP, and MDCK-MRP2 cells (294 datapoints across 136 unique compounds). Concentration-dependent measurements for Amprenavir, Eletriptan, Loperamide, and Quinidine enabled the most accurate determination of the threshold. Literature ER values were re-evaluated through the experimental determination of reliable Pm values, as well as newly measured ER values with MDCK efflux assays. The results of these assays and the re-evaluation allowed us to reclassify all but three outliers (compounds with ER &amp;gt; 2.5 and log(Pm*Cext) &amp;gt; −1.7). In contrast, more than 60% of the compounds analyzed without significant ER values (123 compounds) fell above the threshold, in strong agreement with our theory of an energy limitation to active transport. This permeability threshold thus provides a simple and broadly applicable criterion to identify compounds for which active efflux is energetically not feasible, offering a practical tool for early drug discovery and optimization. Efflux ; Outlier ; Analyte ; Quinidine ; Permeability (electromagnetism) ; Membrane permeability ; Membrane History and advancements in chemistry
Authors: Hasan Basri Çelebi | Mikael Skoglund
Source: ArXiv.org (preprint, 2025-01-19)
Field: Chemistry — Electrochemistry

Reinforcement Learning Based Goodput Maximization with Quantized Feedback in URLLC This paper presents a comprehensive system model for goodput maximization with quantized feedback in Ultra-Reliable Low-Latency Communication (URLLC), focusing on dynamic channel conditions and feedback schemes. The study investigates a communication system, where the receiver provides quantized channel state information to the transmitter. The system adapts its feedback scheme based on reinforcement learning, aiming to maximize goodput while accommodating varying channel statistics. We introduce a novel Rician-$K$ factor estimation technique to enable the communication system to optimize the feedback scheme. This dynamic approach increases the overall performance, making it well-suited for practical URLLC applications where channel statistics vary over time. Goodput ; Reinforcement learning ; Reinforcement ; Maximization ; Computer science ; Error-driven learning ; Control theory (sociology) ; Artificial intelligence ; Mathematical optimization ; Mathematics ; Psychology ; Social psychology ; Control (management) Electrochemical Analysis and Applications ; Water Quality Monitoring and Analysis ; Electrochemical sensors and biosensors
Authors: Nur Indrianti | Muhammad Iqbal | Heru Cahya Rustamaji | Andrey Ferriyan | Panut Mulyono | Moh. Ais Ananta
Source: OPSI (article, 2025-12-30)
Field: Chemistry — Analytical Chemistry

Feature-based classification of sugarcane quality using the K-nearest neighbor algorithm The rapid advancement of artificial intelligence has enabled practical, data-driven approaches to agricultural quality assessment. However, many existing methods rely on complex sensor systems that are costly and difficult to deploy in the field. This study proposes a lightweight and interpretable K-Nearest Neighbor (KNN) model for non-destructive evaluation of sugarcane milling feasibility using five easily measurable physical attributes: relative distance ratio, internode length, mean diameter, circumference, and weight per centimeter. Samples with Brix less than 16 are categorized as not feasible for milling, while Brix equal to or greater than 16 are classified as possible. A dataset of 1,889 Bululawang samples collected in Malang, East Java, Indonesia, was evaluated across twenty-two scenarios that varied the train-test split, normalization method, distance metric, and neighborhood size. The optimal configuration, consisting of an 80:20 split, Standard normalization, the Minkowski distance metric, and k=75, achieved an accuracy of 78%. The findings confirm that physical measurements can serve as effective predictors of sugarcane quality and support data-driven inspection and sustainable resource utilization in line with SDGs 2, 9, and 12. Normalization (sociology) ; Minkowski distance ; Roundness (object) ; Quality (philosophy) ; Support vector machine ; k-nearest neighbors algorithm ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Soil Geostatistics and Mapping
Authors: Huaiyu Liu | Huaping Luo | Hongyang Liu | Jinlong Yu | Lei Kang | Tong Yang
Source: Agriculture (article, 2025-11-29)
Field: Chemistry — Analytical Chemistry

Quality Detection Model for Apricots (Diaoganxing) Based on Spectral Morphological Feature Fusion Across Different Moisture Intervals Moisture content is one of the key indicators for evaluating the quality of apricots. When moisture levels fluctuate over an excessively wide range, scattering effects and absorption characteristics interfere with each other, making it difficult for a single model to achieve accurate predictions across the entire range. This study investigates precision modeling methods applicable to different moisture intervals based on spectral morphological features. By extracting the spectral morphological features of the water-sensitive regions (peak and valley) and conducting Pearson correlation analysis, the spectral morphological feature parameters with relatively strong correlations were selected, and they were combined with the characteristic bands to construct a segmented model for water content intervals. The results indicate that spectral morphological features of apricots within the 25–40% and 40–55% moisture range exhibit a certain correlation with moisture content. A weak correlation is observed in the 55–70% moisture range. After preliminary fusion modeling of spectral morphological features and characteristic bands for apricots across different moisture ranges, further analysis revealed that moisture content models based on valley morphology features and characteristic bands outperformed those based on peak morphology features and characteristic bands, demonstrating superior representational capability. By establishing a fusion model based on the spectral morphological parameters selected through Pearson’s method and the characteristic bands, the detection accuracy and model stability in the 25–70% moisture content range have been effectively improved. Among all the models covering different moisture content ranges, the model for the 55–70% moisture content range has the best prediction effect. The correlation coefficient of its prediction set reaches 0.8723, and the Ratio of Performance to Interquartile Range (RPIQ) is 2.5220, indicating that this range is the most suitable for establishing a high-precision quantitative moisture content detection model. This research effectively solved the problem of spectral response distortion caused by wide variations in moisture content and improved the prediction accuracy of the moisture content detection model for apricots. Moisture ; Water content ; Fusion ; Correlation coefficient ; Range (aeronautics) ; Stability (learning theory) ; Feature (linguistics) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Plant Physiology and Cultivation Studies
Authors: Ziyu Zhou | Haozhe Luo | Mohammad Reza Hosseinzadeh Taher | Jiaxuan Pang | Xiaowei Ding | Michael B. Gotway | Jianming Liang
Source: ArXiv.org (preprint, 2025-01-17)
Field: Chemistry — Physical and Theoretical Chemistry

ACE: Anatomically Consistent Embeddings in Composition and Decomposition Medical images acquired from standardized protocols show consistent macroscopic or microscopic anatomical structures, and these structures consist of composable/decomposable organs and tissues, but existing self-supervised learning (SSL) methods do not appreciate such composable/decomposable structure attributes inherent to medical images. To overcome this limitation, this paper introduces a novel SSL approach called ACE to learn anatomically consistent embedding via composition and decomposition with two key branches: (1) global consistency, capturing discriminative macro-structures via extracting global features; (2) local consistency, learning fine-grained anatomical details from composable/decomposable patch features via corresponding matrix matching. Experimental results across 6 datasets 2 backbones, evaluated in few-shot learning, fine-tuning, and property analysis, show ACE's superior robustness, transferability, and clinical potential. The innovations of our ACE lie in grid-wise image cropping, leveraging the intrinsic properties of compositionality and decompositionality of medical images, bridging the semantic gap from high-level pathologies to low-level tissue anomalies, and providing a new SSL method for medical imaging. Decomposition ; Composition (language) ; Mathematics ; Chemistry ; Art History and advancements in chemistry
Authors: V. І. Havrysh | С. І. Яцишин | Viktoria Maikher | O. D. Hrytsai | F. Honchar
Source: Eastern-European Journal of Enterprise Technologies (article, 2025-10-31)
Field: Materials Science — Materials Chemistry

Construction of mathematical models of heat exchange for digital devices with local near-surface and internal heating This study investigates heat exchange processes for thermally sensitive media with local near-surface and internal heating. As a result of the thermal load, significant temperature gradients arise. To establish temperature regimes for effective operation of electronic devices, linear and nonlinear mathematical models for determining the temperature field have been constructed, which could allow further analysis of temperature regimes. Based on the stated linear and nonlinear boundary value problems of thermal conductivity, their analytical and numerical solutions have been derived. Using these solutions, numerical calculations of the temperature distribution in spatial coordinates for given geometric and thermophysical parameters have been performed. Reliability of the results has been confirmed by experimental findings and the determined numerical values of temperature distribution in the medium. For an effective description of local heating, the theory of generalized functions was used. A technique for linearizing nonlinear mathematical models has been introduced. As a result, linear second-order differential equations with partial derivatives and a singular right-hand side have been derived. The numerical results reflect the temperature distribution in the medium in spatial coordinates for the given geometric and thermophysical parameters. The number of divisions of the interval (0; x*) was chosen to be 9, which made it possible to derive numerical values of temperature with an accuracy of 10–6. The obtained numerical values of temperature for silicon under a linear temperature dependence of the thermal conductivity coefficient differ from the results obtained for its constant value by 2%. Nonlinear system ; Boundary value problem ; Field (mathematics) ; Mathematical model ; Thermal ; Thermal conductivity ; Numerical analysis ; Distribution (mathematics) ; Heat exchanger Advanced Materials and Semiconductor Technologies ; Heat Transfer and Numerical Methods ; Engineering and Agricultural Innovations