jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: T Touil | François Huot | S. Claveau | A. Bunel | Dennis Warner | D.E. Santschi | R. Gervais | É R Paquet
Source: Journal of Dairy Science (article, 2025-06-09)
Field: Chemistry — Analytical Chemistry

Predicting reticuloruminal pH and subacute ruminal acidosis of individual cows using machine learning and Fourier-transform infrared spectroscopy milk analysis Low reticuloruminal pH (rpH) for a prolonged period could lead to SARA. This disease negatively affects cow health and is associated with monetary losses for the dairy industry. The aim of this study was to predict rpH and SARA separately using different machine learning (ML) models applied to Fourier-transform infrared spectroscopy (FTIR) spectra obtained from routine DHI milk analysis of individual cows. A total of 107 primiparous and multiparous Holstein cows were selected from 12 commercial farms in Québec, Canada, and their rpH was continuously monitored for 150 d using wireless boluses. In parallel, 2,634 individual milk samples were collected in the morning and afternoon and analyzed to obtain FTIR spectra. After the cleaning process, 1,744 samples remained, evenly divided into 872 morning (a.m.) and 872 afternoon (p.m.) samples. The FTIR and rpH data were combined to create 3 equally balanced datasets for ML model development: one for a.m. samples, one for p.m. samples, and one composed of both a.m. and p.m. samples, with 872 samples in each dataset. Various spectra preprocessing methods were evaluated, including using the first derivative of the spectra and filtering with 3 different sets of spectra. Additionally, different ML algorithms, including partial least squares, random forest, and gradient boosting, were used to predict rpH and SARA. A total of 36 different models were developed and evaluated for both rpH and SARA prediction. All ML models were assessed using 3 different cross-validation (C-V) methods: nested 10-fold, nested leave-one-farm-out (LOFO), and nested leave-cows-out (LCO) C-V. For rpH prediction, the best performance was achieved using nested 10-fold C-V with median R<sup>2</sup> values of 0.26, 0.26, and 0.22 for the a.m., p.m., and a.m./p.m. datasets, respectively. However, these performances were likely overoptimistic as none of the models evaluated using nested LOFO or nested LCO C-V obtained R<sup>2</sup> higher than 0.12. Unlike rpH, SARA prediction accuracies evaluated using nested LOFO (a.m.: 59%, p.m.: 69%, a.m./p.m.: 64%), and nested LCO (a.m.: 67%, p.m.: 66%, a.m./p.m.: 64%) were closer to the nested 10-fold C-V. These results indicated that rpH was likely not predictable from FTIR, but SARA can be predicted separately and directly from FTIR with 69% accuracy from routine DHI milk samples of individual cows. Acidosis ; Fourier transform infrared spectroscopy ; Chemistry ; Fourier transform ; Animal science ; Food science ; Internal medicine ; Medicine ; Mathematics ; Biology ; Physics Spectroscopy and Chemometric Analyses ; Ruminant Nutrition and Digestive Physiology ; Effects of Environmental Stressors on Livestock
Authors: Nalber Miranda Leite Nalber | Cristina Ponte Lira | A.G. Rodríguez
Source: Brazilian Journal of Radiation Sciences (article, 2025-02-05)
Field: Chemistry — Analytical Chemistry

Computational analysis of wax deposition in deep-water pipelines using nuclear techniques Wax deposition in oil pipelines is a problem that affects flow assurance because it restricts production and, in more extreme cases, causes pipeline blockages. This problem occurs more frequently in offshore environments, where most of Brazil's reservoirs are located and where the ocean temperature at great depths is around 5°C. Detecting the wax layer on the inside walls of pipelines at an early stage avoids unscheduled stoppages and major economic losses. Among the various methods and techniques found in the literature for monitoring wax deposition, nuclear techniques are distinguished by the fact that their use does not interfere with the physical integrity of the pipeline, by the non-intrusive and indirect (non-contact) mode of operation and, therefore, does not affect the oil transportation process. This paper presents a computational model using the Monte Carlo N-Particle 6 (MCNP6) code and the gamma radiation transmission profiling technique to detect the presence of wax on the inner walls of pipelines used for deepwater oil transportation. The results of this study show that the model can detect the presence of up to 5% wax (in relation to the internal radius of the pipeline) with an accuracy of 7.4% in pipelines used in deep waters. Deposition (geology) ; Wax ; Pipeline transport ; Environmental science ; Materials science ; Geology ; Composite material ; Environmental engineering Petroleum Processing and Analysis ; Hydrocarbon exploration and reservoir analysis ; Heat transfer and supercritical fluids
Authors: Suchang Huang | Zhiyou Wu | Kuang Wang | Yiqun Liao | Jie Zeng | Rui Miao
Source: Botanical studies (article, 2025-09-29)
Field: Materials Science — Materials Chemistry

From biophysical interaction to structural modeling: bi-terminal G and TGS domains drive rice OsYchF1-OsGAP1 complex formation OsYchF1 belongs to the YchF subfamily in the Obg family of G proteins, and comprises a core G domain, an α-helical domain, and a TGS domain from the N-terminus to the C-terminus. The C2-domain Oryza sativa GTPase-activating protein (OsGAP1) binds to and accelerates the enzyme activity of OsYchF1. The OsYchF1–OsGAP1 module plays a pivotal role in the response of rice to environmental stress. Nonetheless, how OsYchF1 anchors OsGAP1 has remained elusive. Our results demonstrate that OsYchF1 interacts with OsGAP1 through its N-terminal G domain and C-terminal TGS domain, while the inserted helical domain imposes a steric hindrance, as shown by yeast two-hybrid and isothermal titration calorimetry assays. Also, we implemented the AlphaFold2 artificial intelligence system to predict the structure of the OsYchF1–OsGAP1 complex. However, AlphaFold2 could not capture these dynamic conformational changes, likely due to the weak (KD=102.6 ± 11.7 µM) and transient nature of the OsYchF1-OsGAP1 interaction, which is primarily driven by hydrophobic interactions. Unexpectedly, the protein-protein docking by a fully automated algorithm ClusPro accurately recapitulated both the experimental evidence for G/TGS domain-mediated binding and the known cluster regions on OsGAP1, whereas AlphaFold2 failed to align with these findings. Isothermal titration calorimetry ; Steric effects ; Docking (animal) ; Oryza sativa ; Subfamily ; Domain (mathematical analysis) ; Protein–protein interaction ; Protein structure ; Protein domain Enzyme Structure and Function ; Protein Structure and Dynamics ; Cellular transport and secretion
Authors: David A. Russo | Felix R Schneidmadel | Julie A. Z. Zedler
Source: PLANT PHYSIOLOGY (article, 2025-08-12)
Field: Chemistry — Spectroscopy

Library-free data-independent acquisition mass spectrometry enables comprehensive coverage of the cyanobacterial proteome Cyanobacteria have played a leading role in elucidating the fundamental mechanisms behind oxygenic photosynthesis, carbon fixation, the circadian clock, and phototaxis. Such molecular processes rely on proteins at their core. Thus, proteomics has become an indispensable tool in building our understanding of these processes. Amongst the proteomic approaches used, "shotgun proteomics", where complex protein mixtures are enzymatically digested into peptides and analyzed by liquid chromatography-mass spectrometry, has become the go-to technique for whole-proteome analysis. In this study, we introduce shotgun workflows that excel in speed, throughput, and sensitivity, and allow an in-depth description of the cyanobacterial proteome. The main features of these workflows are the improvement of sample cleanup and digestion through single-pot solid phase-enhanced sample preparation (SP3), the adoption of a previously validated trifluoroacetic acid lysis strategy, and the application of library-free data-independent acquisition. Using the established model organism Synechococcus elongatus PCC 7942, we show that these workflows exhibit high quantitative reproducibility and enable the detection of 83% to 85% of all open reading frames, the greatest single-shot coverage achieved so far for a cyanobacterium. These workflows require only a couple of hours of hands-on time and should be applicable to most, if not all, cyanobacterial species. Together with the rapid advancements in mass spectrometry technologies, this work has the potential to accelerate cyanobacterial proteomics. Proteome ; Mass spectrometry ; Computational biology ; Chemistry ; Proteomics ; Cyanobacteria ; Computer science ; Biology ; Chromatography ; Biochemistry ; Bacteria ; Genetics Advanced Proteomics Techniques and Applications ; Microbial Community Ecology and Physiology ; Mass Spectrometry Techniques and Applications
Source:  (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

APPLICABILITY OF WEAR MODELS FOR MATERIAL PARAMETER PREDICTION BASED ON PIN-ON-DISC WEAR DATA In the literature, several analytical models are put forth to forecast wear behavior under various assumptions [1].When analyzing wear data, the linear models (Archard, abrasive, etc.) and the non-linear power models (Evans and Wilshaw, Kato, etc.) are typically employed [1][2] Our prior research has demonstrated that, for pure or single-phase materials, linear models are better suited to forecast volume loss concerning load, but power models are more suited for composites or when the microstructure contains heterogeneities [1][3] .This study uses the inverse problem method of statistical analysis to try and predict material properties (pin material) based on pin-on-disc data.A comparison is made between the predicted parameter "hardness" and the standard known (or published in the literature) material hardness.Statistical analysis for optimization is done with MATLAB, which is free and open source. Materials science ; Computer science ; Composite material Metal Alloys Wear and Properties ; Lubricants and Their Additives ; Gear and Bearing Dynamics Analysis
Authors: Karen Ho | J Santos | Yen Luong | Douglas B. Clark
Source: The Canadian Journal for the Scholarship of Teaching and Learning (article, 2025-08-31)
Field: Chemistry — Physical and Theoretical Chemistry

Implementing Diverse Continuous Reflective Strategies in a Multi-Section General Chemistry II Lab Chemistry labs are often taught using a rote mechanical approach without much explicit scaffolding for academic reflection by the students. Reflection, however, can play an essential role in learning because it is an evidence-based learning process that generates, deepens, critiques, and documents learning. By moving away from traditional teaching approaches and emphasizing reflection, the first-year chemistry lab could support students in developing more diverse skills, a growth mindset, and greater engagement. The current study, which represents phase four of a multi-year project, explores first-year students’ attitudes toward reflective learning in a chemistry laboratory setting that focuses explicitly on supporting reflection. Two creative student-directed inquiry-based experiments were redesigned and implemented with diverse reflective strategies in order to support students’ sense-making skills and stimulate their understanding of scientific concepts. Data were collected using surveys and students’ reflective artifacts. The surveys are analyzed to better understand students’ attitudes and perspectives about the reflection exercises, and the artifacts are examined to explore students’ understanding of concepts and personal growth. A qualitative content analysis approach was used to analyze data. Findings show that many students welcome the inclusion of reflective exercises in the lab curriculum. Students appreciate the design of scaffolding different reflective exercises, which helped to enhance their learning from basic observation to critical thinking. Furthermore, the artifacts demonstrate positive outcomes in terms of deeper academic learning and personal growth as chemists. Reflection (computer programming) ; Reflective practice ; Inclusion (mineral) ; Process (computing) ; Reflective thinking ; Reflective writing ; Experiential learning ; Active learning (machine learning) ; Rote learning ; Qualitative property Various Chemistry Research Topics ; Reflective Practices in Education ; Science Education and Pedagogy
Authors: Z. Evrim Kanat
Source: Industria Textila (article, 2025-03-06)
Field: Materials Science — Polymers and Plastics

Modelling thermal resistance of woven fabrics in wet state In this study, a simple mathematical model based on conductive heat transfer is suggested for predicting the thermal resistance of wet woven fabric. For this purpose, cellulosic fabrics produced in two different weave types with different moisture content were investigated. Fabric is considered a system of a porous structure consisting of fibre, air and if present, water. The thermal resistance of fabric was calculated according to the proportion of these components. It was considered that the water’s location could have changed the resistance values. The assumption was the capillary water was arranged serially with fibres and air when it was located in the yarns, and it was arranged parallel with the air when it was located between the yarns. Calculated values were compared with the measurement values obtained from ALAMBETA. When the results were evaluated, the obtained values were quite good except for the absolute dry fabric. Serial arrangement of fibre and air was better fitted for dry fabric. So, it is thought that the air acts as a single block in absolute dry fabrics. Additionally, for comparison, Maxwell-Eucken2 (ME-2) was also used. The new model’s R2 value is a little higher than the other model as 0.9017. Furthermore, MSSD and MSAD values were 0.0000013 and 0.0007878 for this model, respectively. As a result of the study, it can be said that the suggested model is useful for predicting the thermal resistance of woven fabrics with different moisture content. Besides this, analyses of fabric porosity can be useful to manage the thermal resistance of wet fabrics. Resistance (ecology) ; Materials science ; Composite material ; Thermal ; State (computer science) ; Thermal resistance ; Computer science ; Thermodynamics ; Physics ; Ecology ; Biology Textile materials and evaluations
Authors: Zhe Xue | Weiran Sun | Zhennan Zhou | Min Tang
Source: arXiv (Cornell University) (preprint, 2025-01-04)
Field: Materials Science — Materials Chemistry

Crossover from ballistic transport to normal diffusion: a kinetic view The crossover between dispersion patterns has been frequently observed in various systems. Inspired by the pathway-based kinetic model for E. coli chemotaxis that accounts for the intracellular adaptation process and noise, we propose a kinetic model that can exhibit a crossover from ballistic transport to normal diffusion at the population level. At the particle level, this framework aligns with a stochastic individual-based model. Using numerical simulations and rigorous asymptotic analysis, we demonstrate this crossover both analytically and computationally. Notably, under suitable scaling, the model reveals two distinct limits in which the macroscopic densities exhibit either ballistic transport or normal diffusion. Crossover ; Kinetic energy ; Diffusion ; Statistical physics ; Physics ; Computer science ; Classical mechanics ; Quantum mechanics ; Artificial intelligence Nuclear Materials and Properties ; Atomic and Subatomic Physics Research ; Nuclear reactor physics and engineering
Authors: Da-Young Lee | Hye-Rin Ahn | Young-Min Han | Moon-Young Song | Seungwon Lee | You-Kyung Jang | Seok‐Ho Kim | Eun-Ji Go | Eun‐Hee Kim
Source: Frontiers in Nutrition (article, 2025-12-03)
Field: Materials Science — Biomaterials

Processed silkworm powder (Hongjam) ameliorates metabolic dysfunction-associated steatotic liver disease via GPR35/PKA and SIRT1/AMPK pathways These findings suggest that Hongjam and its fibroin-derived peptide exert protective metabolic effects by modulating lipid metabolism, inflammation, and glucose homeostasis. Together, they highlight the potential of Hongjam as a functional food ingredient for the prevention of MASLD. Ingredient ; Liver disease ; Fatty liver ; Nonalcoholic fatty liver disease ; Metabolic pathway ; Lipid metabolism ; Peptide ; Lipogenesis Silk-based biomaterials and applications ; Insect Utilization and Effects ; Protein Hydrolysis and Bioactive Peptides
Authors: Sheeba Fareed | Dalia Elmansy
Source: Preprints.org (preprint, 2025-09-26)
Field: Chemistry — Organic Chemistry

Pathway-Level Prediction and Gene Anchoring in PDAC Identify a TST-Linked Fatty-Acid/Glutathione Axis Background/Objectives: Metabolic rewiring and an immunosuppressive microenvironment are central to PDAC, yet transcriptome-based measures that are accurate, interpretable, and transferable remain limited. This study aimed to identify which immunometabolic pathways can be predicted consistently from routine tumor transcriptomes and to provide gene-level anchors that clarify the biology. Methods: A predefined panel of 10 metabolic and 5 immune pathways was analyzed in a primary PDAC cohort and validated externally. Pathway activities were summarized by gene-set methods, and immune composition was estimated by digital cytometry. For each pathway, supervised models (Elastic Net, Random Forest, XGBoost) predicted pathway activity from expression with or without microenvironment inputs. Robustness was assessed by permutation tests in single-feature and correlation-aware groupwise modes, and gene–pathway correlations supplied molecular anchors. Results: Metabolic pathways were predicted accurately from expression, and this pattern reproduced in external validation. Immune pathways showed more variable predictability, with improvement when microenvironment composition was included. Robustness was supported by sizable performance losses after permuting top features and by stable ranking under correlation-aware permutation. Among metabolic targets, fatty-acid and sterol biosynthesis and glutathione metabolism showed the highest predictability. TST (thiosulfate sulfurtransferase) emerged as the top shared gene anchor for fatty-acid biosynthesis and glutathione metabolism, linking lipid-anabolic demand to antioxidant capacity in PDAC. Conclusions: A compact, pathway-centered framework was established that pairs predictive modeling with gene-level interpretability and includes external validation. Key metabolic activities can be recovered reliably from routine transcriptomes, whereas immune activities benefit from microenvironment context. The TST-linked fatty-acid/glutathione axis provides a biologically interpretable entry point for mechanistic and translational follow-up. Interpretability ; Biological pathway ; Transcriptome ; Robustness (evolution) ; Metabolic pathway ; Immune system ; Gene ; Tumor microenvironment ; Pathway analysis Click Chemistry and Applications ; Peroxisome Proliferator-Activated Receptors ; Cancer-related gene regulation
Authors: Daniel Alves Heinze | Supreet S. Thale | Yimin Yao | John P. Reynolds | Mark Ballentine | Christopher Griggs | Christopher B. Williams | Michael J. Bortner
Source: ACS Applied Polymer Materials (article, 2025-09-08)
Field: Materials Science — Biomaterials

Rheology Indicators for Assessing Bead Spreading of Hydrogels with Functional Rheology Modifiers for Direct Ink Writing: A Case Study for Chitosan–Graphene–Titanium Dioxide The rheological behavior of a model system composed of chitosan (CS) hydrogels with graphene and titanium dioxide (TiO<sub>2</sub>) as functional fillers is studied to define a design space between rheology modification and bead spreading in direct ink writing (DIW) additive manufacturing (AM). Rheological results are combined with printed bead studies to determine how each formulation component affects extrudability and bead shape retention, identifying tan delta as the strongest indicator of good shape retention. Samples with tan delta >1 exhibited ink spreading postdeposition, while those with predominantly solid-like behavior (tan delta ≤ 1 at low angular frequencies) and low-to-intermediate TiO<sub>2</sub> concentrations extruded well and maintained their shape in the time scale of printing. Further increasing functional particle content (25 wt % TiO<sub>2</sub>) led to inconsistent extrusion that hindered adequate extrusion fidelity. Moreover, the time-dependent structural recovery of the formulations was strongly influenced by composition, with an increasing CS content being less detrimental to storage modulus recovery than the addition of fillers. Finally, the stress required for the inks to transition from a solid-like to a liquid-like state did not correlate with inconsistent extrusion, which were instead linked to high particle concentrations. This work provides insights into the effects of rheology modification using functional particles in DIW AM of hydrogel composites, ultimately helping to improve the efficiency of producing polymer-based hydrogel inks. Rheology ; Extrusion ; Self-healing hydrogels ; Dynamic mechanical analysis ; Bead ; Particle (ecology) ; Particle size ; 3D printing Electrospun Nanofibers in Biomedical Applications ; Additive Manufacturing and 3D Printing Technologies ; Innovations in Concrete and Construction Materials
Authors: Lyubomyr Mosiy | А. С. Сверстюк | АНДРІЙ РЕМЕЗ | ВОЛОДИМИР МАРКОВСЬКИЙ
Source: Herald of Khmelnytskyi National University Technical sciences (article, 2025-09-24)
Field: Materials Science — Polymers and Plastics

АНАЛІЗ ДОСЛІДЖЕНЬ ЖОРСТКОСТІ АРМОВАНИХ КОМПОЗИТІВ В РАДІОТЕХНІЦІ ТА МЕДИЦИНІ У статті представлено комплексне дослідження армованих композитних матеріалів для відбиваючих решіток та біомедичних застосувань, що поєднує бібліометричний аналіз наукових тенденцій та математичне моделювання напружено-деформованого стану антенних конструкцій. На основі аналізу 652 публікацій у базі Scopus за 10-річний період виявлено стабільне зростання дослідницької активності з піком у 2024 році (114 публікацій). Географічний розподіл демонструє лідерство Китаю (32,5%) та США (21,1%). Застосований бібліометричний підхід підтвердив універсальність статистичних методів для міждисциплінарних досліджень. Розроблено математичну модель температурного впливу на параболічну оболонку дзеркала антени з урахуванням анізотропних властивостей композитних матеріалів. Порівняльний аналіз матеріалів показав оптимальність міді для максимальної ефективності відбиття, алюмінію – для легких конструкцій, композитів з CNT та GPL – для структурно-оптимізованих рішень. Визначено високий потенціал композитних матеріалів з вуглецевими нанотрубками та графеновими пластинками для створення біомедичних електродів з підвищеним співвідношенням сигнал/шум (до 40 дБ) для електрокардіографічного моніторингу. Найперспективнішою технологією визначено електродугове напилення. Результати чисельного моделювання підтвердили критичний вплив температурних градієнтів на геометричну стабільність відбиваючих поверхонь. Дослідження виявило синергійний потенціал між технологіями виготовлення антенних решіток та біомедичних електродів, що відкриває перспективи для розробки багатофункціональних композитних систем. Дослідження створює науково-методологічну основу для розробки термостабільних антенних систем у аерокосмічній, енергетичній та медичній галузях. Identification (biology) ; Process (computing) ; Product (mathematics) Natural Fiber Reinforced Composites ; Heat Transfer and Mathematical Modeling ; Graphene and Nanomaterials Applications