jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: peng hu | Pengfei Du | Yanxia Xing | Yiyi Li | Weimin Ma | Weizhen Xu | Weiting Wang
Source: Foods (article, 2026-02-14)
Field: Chemistry — Analytical Chemistry

A Rapid Grading Method for Beef Appearance Quality Based on Smartphone Imaging and ImageJ The grading of beef appearance quality is crucial for standardizing market circulation and promoting the upgrading of the beef cattle industry. China's current beef quality grading system, which relies primarily on human sensory-based visual assessment with marbling and meat color as core parameters, suffers from strong subjectivity, low efficiency, and large errors. This study proposes a rapid grading method for beef rib eye muscle using smartphone imaging combined with ImageJ software. Standardized images were acquired, and ImageJ was employed for grayscale conversion, threshold segmentation, and morphological processing to extract length, width, area, and marbling proportion. The R, G, B color channels were separated to calculate the R/(R + G + B) color ratio. Pearson correlation analysis showed that the ImageJ results were highly consistent with manual measurements (correlation coefficients > 0.97), indicating good reliability. A five-level grading standard (A1-A5) was established, characterized by low cost, simple operation, and objective results. It provides an economical technical solution for beef quality grading and facilitates the intelligent development of the industry. It should be noted that this experimental grading model has only been validated under the specific experimental conditions of this study, and further verification is required for broader application. Grading (engineering) ; Marbled meat ; Grayscale ; Pattern recognition (psychology) ; Image quality ; Quality assessment Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Food Supply Chain Traceability
Authors: Gabriel Antonio Pinilla Agudelo
Source: Revista de la Academia Colombiana de Ciencias Exactas Físicas y Naturales (article, 2026-01-21)
Field: Materials Science — Biomaterials

Main limnological patterns of the Andes and some Cis- and Trans-Andean areas of Colombia A comprehensive understanding of the structure and functioning of continental aquatic ecosystems is crucial for the effective conservation and sustainable use of water and hydrobiological resources in Colombia, a country renowned for its exceptional biodiversity and abundant water reserves. This study examines the biological arrangements and the environmental processes that structure freshwater bodies in various Colombian regions, analyzes the probable underlying causes, and suggests avenues for further research. Physicochemical variables were recorded in situ, and water samples were collected for nutrient analysis. Periphytic algae and aquatic macroinvertebrates were sampled from 26 lentic and 80 lotic ecosystems across different Andean, trans-Andean, and cis-Andean regions between 2005 and 2022. Data analysis involved classification (UPGMA) and ordination (PCA, UMAP, NMDS, LDA), which led to several significant findings: 1) The phycoperiphyton and macroinvertebrate assemblages showed a characteristic relationship with environmental factors, mirroring the environmental conditions of the aquatic ecosystems; 2) the physicochemical factors successfully classified different aquatic systems based on their specific geographical areas, emphasizing clear regional distinctions; 3) lentic systems exhibited more pronounced regional differences than lotic systems, implying that still-water environments may be more sensitive to local ecological effects, and 4) some physicochemical characteristics and biological composition correspondences were observed among aquatic systems in different regions, suggesting potential shared influences or similar environmental conditions affecting them. Based on these general limnological patterns, a comprehensive conceptual framework is proposed that clarifies the interactions among these factors. Potential future research topics have been identified to enhance the understanding of the structure and dynamics of these aquatic systems. Lake ecosystem ; Ordination ; Aquatic ecosystem ; River ecosystem ; Biodiversity ; Ecosystem ; Limnology ; Freshwater ecosystem Diatoms and Algae Research ; Freshwater macroinvertebrate diversity and ecology ; Chemical and Environmental Engineering Research
Authors: Arda Zaim | Haydar Aras
Source: Machines (article, 2026-02-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Software-Based Automation and Control Architecture for a Magnetic Refrigeration System In this study, software-based, measurement-driven automation and control architecture is developed for magnetic refrigeration systems. The proposed structure integrates real-time measurement data obtained from magnetic, hydraulic, and thermal sub-processes within a single decision layer. Control actions are generated based on cycle-level performance feedback. Instead of directly regulating absolute performance values, the control logic relies on performance trends between successive cycles as the primary decision variable. The method is experimentally implemented on a reciprocating magnetic refrigerator prototype. The system is first operated with fixed parameters, after which cycle-level adaptation is activated using measurement-based decisions. Experimental results show that adaptive control drives the system toward a stable and high-performance regime following a short transient phase. The average coefficient of performance (COP) increases from approximately 0.21 under manual operation to about 1.20 in adaptive operation, while cycle-to-cycle fluctuations are significantly reduced. The results indicate that operation based on fixed timing and preset parameters is insufficient for magnetic refrigeration systems. In contrast, software-based control using cyclic feedback shifts the system to a more stable and efficient regime. The proposed architecture provides a high-level control framework with low hardware dependency and can be adapted to different magnetic refrigeration configurations. Refrigeration ; Automation ; Control theory (sociology) ; Control system ; Coefficient of performance ; Temperature control ; Transient (computer programming) ; Reciprocating motion Magnetic and transport properties of perovskites and related materials ; Frequency Control in Power Systems ; Physics of Superconductivity and Magnetism
Authors: Yi-Pin Hsu
Source: Electronics (article, 2026-04-10)
Field: Materials Science — Materials Chemistry

Combining Interpolation Techniques and Lightweight Convolutional Neural Networks for Partial Discharge Image Signal Identification in Transformer Bushings Partial discharge detection is a key technology for maintaining the normal operation of industrial power equipment. Oil-impregnated paper bushings are crucial components connecting transformers to the power grid. Insulation degradation leads to partial discharge, posing a significant threat to power system operation. Developing on-line diagnostics for partial discharge in transformer bushings and automatic identification of insulation defects can effectively protect system and personnel safety. Due to limitations of small sample sizes and lightweight networks, this study combines interpolation techniques with a lightweight convolutional neural network to improve identification accuracy. This network uses interpolation to maintain the undistorted sample signal from the initial input and reduces training defects from a small sample size. The neural network extracts partial discharge features to determine the defect type and its cause. This study uses a publicly available dataset with discharge signals from generators. Although from a different source from the discharge signals generated by oil-impregnated paper bushings, the signal distribution is similar, allowing for a fair analysis and providing a reference for evaluating discharge signals obtained from oil-impregnated paper bushings or other discharge devices. The experimental results show that the accuracy of this network improved from 97% to over 99% while maintaining low computational complexity and excellent real-time performance. Furthermore, this network was implemented and validated on existing industrial equipment. Partial discharge ; Transformer ; Convolutional neural network ; Interpolation (computer graphics) ; Artificial neural network ; SIGNAL (programming language) High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Thermal Analysis in Power Transmission
Authors: Hao Xu | Nuno Bandeira
Source: bioRxiv (Cold Spring Harbor Laboratory) (article, 2026-01-09)
Field: Chemistry — Spectroscopy

Benchmarking Peptide Spectral Library Search Spectral library search (SLS) is a major approach for peptide identification from tandem mass spectrometry data, with performance depending substantially on the accuracy of the underlying Spectrum-Spectrum Matching (SSM) scoring functions. However, detailed comparative studies remain limited by the absence of comprehensive benchmark datasets. We propose new methods to build SSM scoring functions benchmarks and construct a benchmark dataset with (i) <i>eight</i> query spectrum sets with varying noise level for 476,063 precursors, and (ii) <i>three</i> spectral libraries with experimental, de-noised and predicted spectra for 3,065,819 precursors. We evaluate common spectrum preprocessing scenarios and SSM scoring functions, including SpectraST and EntropyScore. Results revealed this remains an important open problem, with the best recall for still assessed to be poor at just ∼70%, with SpectraST performing best for spectra with little-to-no noise, while JS-divergence showed superior noise resistance. Conversely, Cosine and Entropy score performed substantially worse, with Projected-Cosine performing especially poorly in most cases, with overall performance and relative ranking depending quite significantly on the minimum number of matching peaks. The benchmark dataset (MSV000095946/PXD056205) supports testing and development of new SSM scoring functions and the proposed benchmark construction approach provides an extensible foundation for additional types of SSM evaluation. Benchmarking ; Benchmark (surveying) ; Preprocessor ; Ranking (information retrieval) ; Matching (statistics) ; Pattern recognition (psychology) ; Identification (biology) ; Precision and recall Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Mass Spectrometry Techniques and Applications
Authors: Pınar Gümüş
Source: Food Analytical Methods (article, 2026-01-28)
Field: Chemistry — Organic Chemistry

Optimization of Process Parameters in Minimal Neutralization of Corn Oil by Response Surface Methodology Abstract Traditional refining is a crucial process used to remove undesired components such as free fatty acids, phospholipids, and oxidation products from crude oil. However, it also results in the loss of some beneficial minor components, including tocopherols and phenolic compounds. Nutritionally important minor components can be retained through alternative refining approaches like minimal refining that minimize processing intensity and reduce the number of refining stages. Calcium hydroxide has been used as an alternative to sodium hydroxide to reduce neutralization loss since it is cheaper and weaker than sodium hydroxide. The research focused on obtaining neutralized corn oil by calcium hydroxide Ca(OH) 2 instead of sodium hydroxide (NaOH), which is typically used in traditional neutralization. Response surface methodology was employed to optimize the process for producing corn oil via reduced FFA and retained α-tocopherol levels. The elucidated optimum values for the neutralization of corn oil by Ca(OH) 2 were at 0.44%, 47.4 °C, and 14.4 min. FFA values for crude, traditional, and minimal neutralized corn oils were 0.21%, 0.20%, and 0.13%, respectively. The α-tocopherol level of the crude, traditional, and minimal neutralized corn oils were 126.43, 100.56, and 125.04 mg/kg oil, respectively. Sodium hydroxide ; Refining (metallurgy) ; Response surface methodology ; Neutralization ; Calcium hydroxide ; Corn oil ; Process (computing) ; Sodium Edible Oils Quality and Analysis ; Nuts composition and effects ; Biodiesel Production and Applications
Authors: Shili Liu | Zhenhao Wei
Source: Energies (article, 2026-03-12)
Field: Materials Science — Materials Chemistry

Simulation Analysis of the Effects of Barrier Defects on the Electro–Thermal Fields of the XLPE Cable Buffer Layer With the increasing number of failures in high-voltage cross-linked polyethylene cables caused by buffer layer ablation, it is of great significance to investigate the electro–thermal coupling characteristics and ablation driving mechanisms under different defect conditions. Based on a multiphysics coupling model, an electro–thermal coupled simulation of the cable buffer layer and corrugated aluminum sheath was carried out, considering three typical defect types: air-gap barrier, moisture ingress, and white-powder barrier. The distributions of air-gap electric field, interfacial current density, temperature, and heat source were systematically analyzed. From the perspective of ablation mechanisms, the maximum air-gap electric field and its spatial location, as well as the maximum temperature of the buffer layer and its corresponding region, were investigated under different defect conditions. Meanwhile, the probabilities of electrical ablation and thermal ablation, together with their corresponding threshold parameters, were quantitatively evaluated. The results show that when an air-gap barrier exists between the buffer layer and the aluminum sheath, air breakdown may occur when the air-gap thickness is approximately 0.01–0.05 mm. When the buffer layer is moisture-contaminated and the defect length exceeds approximately 2 m, the buffer layer temperature may exceed 165 °C. When white-powder precipitates in the buffer layer, partial discharge may be initiated at the early stage. With the increase in powder barrier proportion, the buffer layer temperature may exceed approximately 220 °C. It should be noted that these critical characteristics are obtained under the simulation conditions of this study. The specific values depend on material parameters and operating conditions and can provide theoretical support for cable operation condition assessment. Buffer (optical fiber) ; Multiphysics ; Layer (electronics) ; Electric field ; Coupling (piping) ; Thermal ; Barrier layer High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Electrostatic Discharge in Electronics
Authors: Praveen Kumar A. | Krishnakumar S | Vivek S | Edeh Michael Onyema
Source: E3S Web of Conferences (article, 2026-01-01)
Field: Materials Science — Polymers and Plastics

Experimental Investigation on Paver Block with Waste Plastic Chips and Sugarcane Bagasse Ash India is the top producer of sugarcane in the world, making sugarcane bagasse 91 million tonnes annually from more than 500 sugar mills. Besides, the country is grappling with plastic waste management as it produces 3.4 million tonnes of plastic waste every year out of which only 30% is recycled. Therefore, solving these problems requires a new, eco-friendly approach that can efficiently use both agricultural and plastic wastes. This research is about the possibility of producing eco-friendly paver blocks by using sugarcane bagasse ash and waste plastic chips as partial substitutes for natural materials. We experimented with various percentages of bagasse ash and plastic chips to evaluate the main mechanical properties such as compressive strength and water absorption. The experimental results indicate that a mix containing 15% SBA and 5% waste plastic chips attained compressive strength values comparable to conventional paver blocks, with acceptable water absorption characteristics. Based on experimental outcomes, the developed paver blocks are suitable for footpaths and low-load paving applications, contributing to sustainable construction and effective waste utilization. Bagasse ; Compressive strength ; Absorption of water ; Plastic waste ; Raw material ; Block (permutation group theory) Natural Fiber Reinforced Composites ; Geotechnical Engineering and Soil Stabilization ; Geotechnical and construction materials studies
Authors: Praveen Kumar A. | Krishnakumar S | Vivek S | Edeh Michael Onyema
Source: Springer Link (Chiba Institute of Technology) (article, 2026-04-01)
Field: Materials Science — Polymers and Plastics

Experimental Investigation on Paver Block with Waste Plastic Chips and Sugarcane Bagasse Ash India is the top producer of sugarcane in the world, making sugarcane bagasse 91 million tonnes annually from more than 500 sugar mills. Besides, the country is grappling with plastic waste management as it produces 3.4 million tonnes of plastic waste every year out of which only 30% is recycled. Therefore, solving these problems requires a new, eco-friendly approach that can efficiently use both agricultural and plastic wastes. This research is about the possibility of producing eco-friendly paver blocks by using sugarcane bagasse ash and waste plastic chips as partial substitutes for natural materials. We experimented with various percentages of bagasse ash and plastic chips to evaluate the main mechanical properties such as compressive strength and water absorption. The experimental results indicate that a mix containing 15% SBA and 5% waste plastic chips attained compressive strength values comparable to conventional paver blocks, with acceptable water absorption characteristics. Based on experimental outcomes, the developed paver blocks are suitable for footpaths and low-load paving applications, contributing to sustainable construction and effective waste utilization. Bagasse ; Compressive strength ; Absorption of water ; Plastic waste ; Raw material ; Block (permutation group theory) Natural Fiber Reinforced Composites ; Geotechnical Engineering and Soil Stabilization ; Materials Engineering and Processing
Authors: Anna M. Piekarska | T. K. Kopeć
Source: ArXiv.org (article, 2026-03-21)
Field: Materials Science — Materials Chemistry

Physical manifestation of replica symmetry breaking in a quantum glass of bosons with off-diagonal disorder Glassiness occurs when disorder and frustration cause local degrees of freedom to freeze despite the lack of long-range order. In systems of interacting bosons, such glassiness may involve a purely quantum degree of freedom$\unicode{x2014}$local phases of particle wave functions$\unicode{x2014}$partly analogous to spins in spin glasses. However, experimental identification of such phases is difficult because it requires prohibitively long measurement times or recourse to the elusive Edwards-Anderson order parameter. Moreover, the off-diagonal character of the phase makes it seemingly even harder to capture via typical observables. To address this issue, we study a system of strongly interacting bosons with random hoppings that features off-diagonal glassiness exhibiting replica symmetry breaking (RSB). We find that the glass phase is compressible, which distinguishes it from the Mott insulator. Thus, we establish a direct correspondence between phase-based glassy order and a measurable density-based thermodynamic observable. We use a framework adopted from spin glasses, including the replica trick within the one-step RSB scheme, to obtain meaningful results in the glass phase and to characterize the order parameters, RSB structure, slow relaxation, and compressibility. Glassiness in particle systems could thus be experimentally identified via measurements of compressibility, such as probing density fluctuations or the particle-number response to a trapping potential. Symmetry breaking ; Replica ; Boson ; Spin glass ; Replica trick ; Phase (matter) ; Spins ; Frustration ; Quantum phases Material Dynamics and Properties ; Quantum many-body systems ; Theoretical and Computational Physics
Authors: Yongzhong Xu
Source: arXiv (Cornell University) (article, 2026-03-30)
Field: Materials Science — Materials Chemistry

The Spectral Edge Thesis: A Mathematical Framework for Intra-Signal Phase Transitions in Neural Network Training We develop the spectral edge thesis: phase transitions in neural network training -- grokking, capability gains, loss plateaus -- are controlled by the spectral gap of the rolling-window Gram matrix of parameter updates. In the extreme aspect ratio regime (parameters $P \sim 10^8$, window $W \sim 10$), the classical BBP detection threshold is vacuous; the operative structure is the intra-signal gap separating dominant from subdominant modes at position $k^* = \mathrm{argmax}\, σ_j/σ_{j+1}$. From three axioms we derive: (i) gap dynamics governed by a Dyson-type ODE with curvature asymmetry, damping, and gradient driving; (ii) a spectral loss decomposition linking each mode's learning contribution to its Davis--Kahan stability coefficient; (iii) the Gap Maximality Principle, showing that $k^*$ is the unique dynamically privileged position -- its collapse is the only one that disrupts learning, and it sustains itself through an $α$-feedback loop requiring no assumption on the optimizer. The adiabatic parameter $\mathcal{A} = \|ΔG\|_F / (η\, g^2)$ controls circuit stability: $\mathcal{A} \ll 1$ (plateau), $\mathcal{A} \sim 1$ (phase transition), $\mathcal{A} \gg 1$ (forgetting). Tested across six model families (150K--124M parameters): gap dynamics precede every grokking event (24/24 with weight decay, 1/24 without), the gap position is optimizer-dependent (Muon: $k^*=1$, AdamW: $k^*=2$ on the same model), and 19/20 quantitative predictions are confirmed. The framework is consistent with the edge of stability, Tensor Programs, Dyson Brownian motion, the Lottery Ticket Hypothesis, and neural scaling laws. Spectral gap ; Scaling ; Artificial neural network ; Position (finance) ; Smoothing ; Curvature ; Gradient descent ; Spectral shape analysis ; Adiabatic process Machine Learning in Materials Science ; Stochastic Gradient Optimization Techniques ; Quantum many-body systems
Authors: Bupesh Kumar K | B M Rajaprakash
Source: International Journal for Research in Applied Science and Engineering Technology (article, 2026-02-24)
Field: Materials Science — Polymers and Plastics

Optimization Studies of Kevlar/Epoxy Composites Strengthened with Hybrid SiC-ZnO Nanofillers using Taguchi L16 Technique Fibre Reinforced Polymer Composites (FRPCs) have been found to exhibit enhanced mechanical properties on addition of nanofillers. Recent research has also delved into the use of hybrid nanofillers to synergistically enhance their mechanical properties. In this present research, an attempt has been made to study the effect of hybrid Silicon Carbide (SiC) – Zinc Oxide (ZnO) nanofillers on the mechanical properties of Kevlar/Epoxy composite. Taguchi L16 technique has been employed in this current research for design and optimisation. The mechanical properties such as tensile strength, flexural strength, inter laminar shear strength and energy absorbed have been evaluated as output characteristics for optimising the input variables like weight percentage of SiC, weight percentage of ZnO, curing temperature and curing time. Confirmatory tests have also been performed for repeatability and validity. Taguchi methods ; Ultimate tensile strength ; Silicon carbide ; Curing (chemistry) ; Orthogonal array ; Flexural strength ; Ultra-high-molecular-weight polyethylene ; Composite number Natural Fiber Reinforced Composites ; Scientific and Engineering Research Topics ; Polymer Nanocomposites and Properties