jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hsien-Chun Cho | Zih-Ching Chen | Ching-Yi Chen
Source: Sensors and Materials (article, 2025-08-28)
Field: Chemistry — Analytical Chemistry

Lightweight Vision-transformer-based Coffee Bean Quality Inspection with Class-aware Unsupervised Domain Adaptation With the rapid development of automated optical inspection (AOI) technology and imaging sensor systems, image-based coffee bean quality inspection has emerged as an effective alternative to manual sorting.High-resolution imaging sensors are capable of capturing critical surface features of coffee beans, including texture, color, and structural patterns, thereby providing rich input for downstream intelligent classification algorithms.However, most existing research has concentrated on green beans, while labeled datasets for roasted beans remain scarce.This imbalance severely restricts the generalization capability of trained models in realworld applications.To address this issue, a class-aware unsupervised domain adaptation (UDA) framework based on the vision transformer (ViT) architecture is proposed.The framework simultaneously aligns the feature distributions between the source domain (green beans) and the target domain (roasted beans), while enhancing class-level consistency during training.This design effectively mitigates domain shifts induced by variations in coffee processing stages, thereby improving model robustness in cross-domain scenarios.In addition, to enhance deployment efficiency and operational practicality in intelligent sensing environments, a model compression strategy is further introduced.By leveraging the modular dependency structure inherent in transformer-based architectures, we developed an approach that integrates structured pruning with knowledge distillation (KD) to significantly reduce model complexity while preserving classification performance.Experimental results confirm that the proposed method delivers high classification accuracy and generalization capability, demonstrating its potential for deployment in image-based coffee bean quality inspection systems. Domain adaptation ; Transformer ; Computer science ; Artificial intelligence ; Adaptation (eye) ; Computer vision ; Pattern recognition (psychology) ; Engineering ; Psychology ; Electrical engineering ; Neuroscience Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Advanced Chemical Sensor Technologies
Authors: Svetlana A. Korban | Oleg Mikhailovskii | Vladislav V. Gurzhiy | Ivan S. Podkorytov | Nikolai R. Skrynnikov
Source: IUCrJ (article, 2025-06-23)
Field: Materials Science — Materials Chemistry

Using multiple computer-predicted structures as molecular replacement models: application to the antiviral mini-protein LCB2 In this report, we describe a set of structures of the engineered protein LCB2 that has been solved starting from different computer-predicted molecular replacement (MR) models. We found that AlphaFold3, AlphaFold2, MultiFOLD, Rosetta, RoseTTAFold and trRosetta all produced successful MR models for this three-helix bundle 58-residue protein, while some of the older predictors failed. To assign B factors in the MR models we used the predictor-generated confidence scores or, as a convenient alternative, the accessible surface area (ASA) values. The process of multi-start structure determination using Coot and Phenix demonstrated good convergence, leading to six structures within 0.25 Å (all-atom RMSD) of each other. Of note, structural differences between the computer-predicted MR models and the final structures can be largely attributed to a single specific crystal contact. Comparing the six structural solutions, we observe that a number of surface side chains have been solved with different conformations. Interestingly, for each individual structure the electron density is consistent with a single rotameric state and offers no direct evidence of conformational heterogeneity. Strictly speaking, this behavior constitutes a case of model bias; we argue, however, that it represents a benign side of model bias. Specifically, when we use a model where the side-chain conformation corresponds to one of the actual (significantly populated) rotameric states, this leads to an enhancement of the electron density for this particular conformation. Conversely, when we use a model with an irrelevant (low-population) side-chain conformation, it fails to produce the matching electron density. We thus conclude that the six LCB2 structures obtained in this study can be grouped into a multiconformer ensemble, where structural variations are representative of protein's conformational dynamics. Indeed, using this six-member ensemble leads to a significant drop in R<sub>work</sub> and R<sub>free</sub> compared with the individual solutions. This interpretation was also supported by our MD simulations of the LCB2 crystal. Side chain ; Protein structure ; Chemistry ; Crystal structure ; Computer science ; Biological system ; Algorithm ; Crystallography ; Biology ; Biochemistry Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: Paolo Cavicchioli | Boštjan Gabrovšek | Matic Simonič
Source: ArXiv.org (preprint, 2025-07-06)
Field: Materials Science — Polymers and Plastics

Bonded braids and the Markov theorem Bonded knots arise naturally in topological protein modeling, where intramolecular interactions such as disulfide bridges stabilize folded configurations. These structures extend classical knot theory by incorporating embedded graphs, and have been formalized as bonded knots. In this paper, we develop the algebraic theory of bonded braids, introducing the bonded braid monoid in the topological and rigid settings, which encodes both classical braid crossings and (rigid) bonded connections. We prove bonded analogues of the Alexander and Markov theorems, establishing that every bonded knot arises as the closure of a bonded braid and that two bonded knots are equivalent if and only if their braid representatives are related by a finite sequence of algebraic (Markov-like) moves. In addition, we define the bonded Burau and reduced bonded Burau representations of the monoid, extending classical braid group representations to the bonded setting, and analyze their (non-)faithfulness in low dimensions. Braid ; Braid group ; Braid theory ; Knot (papermaking) ; Knot theory ; Algebraic number ; Monoid Synthesis and properties of polymers ; Structural Analysis and Optimization ; Model-Driven Software Engineering Techniques
Authors: Reetendra Singh | Abhishek Rakshit | Galit Atiya | Martin Kalina | Yaron Kauffmann | Yoav Kalcheim
Source: ArXiv.org (preprint, 2025-10-02)
Field: Materials Science — Polymers and Plastics

Reversal of strain state in a Mott insulator thin film by controlling substrate morphology The V2O3 phase diagram contains two insulating phases and one metallic phase with different lattice structures. The stability of these phases is very sensitive to pressure, offering a mechanism to tune phase transitions by inducing strain in thin films. The most studied source of strain is lattice mismatch between the film and the substrate. In this work, however, we find that the film/substrate thermal expansion mismatch can be made to play a dominant role by modifying the substrate morphology. When grown on sapphire, the lattice mismatch induces compressive strain in the V2O3 films, whereas thermal expansion mismatch induces tensile strain. We find that minute changes in substrate morphology may relax the compressive strain component, allowing the thermally-induced tensile component to overcome it. Thus, by simple annealing of the substrates to create either a flat or stepped morphology, strongly compressive or tensile strains may be induced in the films. This results in either full suppression of the metal-insulator transition or stabilization of insulating phases at all temperatures, exhibiting many orders of magnitude differences in film resistivity. To elucidate the strain relaxation mechanism, we use high-resolution scanning transmission electron microscopy (HRSTEM) to image the atomic steps in the substrate and the adjacent crystallographic defects in the V2O3. These findings offer a hitherto underexplored mechanism to tune strain in thin films, deepen our understanding of the effects of structural degrees of freedom on phase stability of a canonical Mott insulator and may allow for applications requiring insulator-metal switching above room temperature. Thin film ; Phase diagram ; Ultimate tensile strength ; Lattice (music) ; Annealing (glass) ; Transmission electron microscopy ; Thermal expansion ; Stress relaxation ; Phase transition Transition Metal Oxide Nanomaterials ; Advanced Memory and Neural Computing ; Physics of Superconductivity and Magnetism
Authors: Mauro Pazmiño Betancourth | Aleksandr Boldin | Victor Ochoa-Gutiérrez | R. A. Hogg | Francesco Baldini | Mario González‐Jiménez | Klaas Wynne | David Childs
Source: Spectroscopy Journal (article, 2025-03-07)
Field: Chemistry — Spectroscopy

Towards Fast Quantum Cascade Laser Spectrometers for High-Throughput and Cost-Effective Disease Surveillance Fourier transform infrared (FTIR) spectroscopy, coupled with machine learning (ML) analysis can be used for disease monitoring with high speed and accuracy, including the classification of mosquito samples by species, age and malaria detection. However, current FTIR instruments use low-brightness thermal light sources to generate infrared light, which limits their ability to measure complex biological samples, especially where high spatial resolution is necessary, such as for specific mosquito tissues. Moreover, these systems lack portability, which is essential for field applications. To overcome these issues, spectrometers using quantum cascade lasers (QCLs) have become an attractive alternative for building fast, and portable systems due to their high electrical-to-optical efficiency, small size, and potential for low-cost. Here, we present a QCL-based spectrometer prototype designed for large scale, low-cost, environmental field-based disease surveillance. Quantum cascade laser ; Throughput ; Cascade ; Spectrometer ; Laser ; Disease surveillance ; Quantum ; Computer science ; Disease ; Medicine ; Physics ; Chemistry ; Optics ; Telecommunications ; Internal medicine ; Chromatography ; Quantum mechanics Spectroscopy and Laser Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Spectroscopy and Chemometric Analyses
Authors: Bruno L. Menna | Ljubica Tasić | Marielton dos Passos Cunha | Marcelo Bispo de Jesus
Source: Journal of Health & Biological Sciences (article, 2025-08-01)
Field: Materials Science — Materials Chemistry

Perfil de citotoxicidade da prata coloidal em células de hepatocarcinoma humano (Huh-7) Objetivo: avaliar a citotoxicidade de uma formulação de prata coloidal em células de carcinoma hepatocelular Huh-7. Métodos: a formulação foi caracterizada por técnicas complementares, incluindo espalhamento dinâmico de luz (DLS), análise de nanopartículas por rastreamento (NTA) e microscopia eletrônica de transmissão (MET). A concentração inibitória média (IC50) foi determinada por uma abordagem ortogonal, utilizando o ensaio de MTT e a coloração dupla Hoechst 33342/propídio iodeto (PI). Além disso, foi realizada uma análise de alto conteúdo baseada em microscopia de fluorescência com o ensaio Live Cell Painting. Resultados: a caracterização indicou a presença de nanopartículas de prata (AgNPs) e íons de prata na formulação. A avaliação da citotoxicidade revelou valores de IC50 de 0,54 mg/L pelo ensaio de MTT e de 1,13 mg/L pela coloração dupla Hoechst 33342/PI. Observou-se, ainda, que o sobrenadante, enriquecido em íons de prata foi o principal responsável pela toxicidade observada (IC50 = 0,64 mg/L). A análise de alto conteúdo identificou alterações morfológicas no nucléolo como possíveis marcadores moleculares do dano induzido pela formulação. Conclusão: nossos dados indicam que a prata coloidal pode representar um risco potencial à saúde humana. Molecular biology ; Chemistry ; Biology Nanoparticles: synthesis and applications
Authors: Zain AbuShaeer | Essam M. Elsaid | Ahmed K. Abu‐Nab | Ahuod Alsheri | Mohamed R. Eid | Ali F. Abu‐Bakr
Source: Journal of Computational Design and Engineering (article, 2025-11-21)
Field: Materials Science — Materials Chemistry

Electrohydrodynamic behaviour of charged cavitation bubbles in hybrid nanofluids: A Mooney–Rivlin model approach Abstract To understand cavitation in complex fluids, especially hybrid nanofluids used in technology and medicine, it is important to grasp the electrostatic forces, viscoelastic effects, and flow behaviour of nanofluids. The main contribution of this work is how hybrid nanoparticles alter the charged cavitation mechanism when charging effects are present. This study introduces a combined cavitation model that features charging effects, hybrid nanofluid behaviour, and Mooney–Rivlin viscoelasticity. It offers new insights for biomedical and energy uses. The Mooney–Rivlin model is helpful for studying charged cavitation bubbles in fluids that conduct electricity. The study employs a modified Rayleigh–Plesset equation to examine these bubbles within an electric field. It looks at how the Mooney–Rivlin model changes the fluid’s stretchability and bending. The proposed model examines the behaviour of cavitation bubbles in the presence of either single-type or mixed nanoparticles. Research also explores how hybrid nanoparticles, charge density, and fluid stretch and flow affect cavitation bubble growth and collapse. Charged nanoparticles dramatically modify bubble formation, improving the mechanisms for cavitation bubble departure and energy dissipation. Nanoparticles (mostly TiO2–Ag/H2O) increase droplet radius reduction compared to pure water. The research also inaffectsated how the volume of nanoparticles, their electric charge, initial cavitation size, and initial temperature affect cavitation bubble formation in non-conductive liquids. The research also found that charged cavitation and varied hybrid nanoparticle quantities inhibit cavitation bubble formation. Finally, our conclusions, which are based on our study and the stability of the system, are more accurate and lead to a greater reduction in cavitation bubble development compared to prior models. Cavitation ; Bubble ; Nanofluid ; Work (physics) ; Flow (mathematics) ; Electrohydrodynamics ; RADIUS ; Sonoluminescence Ultrasound and Cavitation Phenomena ; Cavitation Phenomena in Pumps ; Electrohydrodynamics and Fluid Dynamics
Authors: Aswin V. Muthachikavil | Christoph Allolio | Thomas D. Kühne
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-10-21)
Field: Materials Science — Biomaterials

Molecular Grammar of Microtubule-Wetting Condensates Abstract Microtubule condensate interactions are fundamental for cell division, vesicle transport and cellular locomotion. Accordingly, they represent a large number of attractive drug targets. Due to the size of microtubuli and the slow timescale of condensate structural relaxation, there has not been a systematic investigation at the molecular level as to what binding patterns (molecular grammar) enable condensate binding to microtubuli. We provide a protocol that is able to predict whether any given disordered protein sequence will bind to microtubuli. This protocol is suitable for compound screening. Our pattern analysis allows us to establish two categories of strongly interacting subsequences that enable binding to microtubuli: positively charged hydrophobic clusters and alternating charge sequences. Their overall optimal balance is analyzed and preferential regions of interaction on microtubuli are identified and validated with known experimental results. Our results enable rapid prototyping of proteins that target the microtubule surface, i.e. they predict whether unstructured proteins will wet the microtubule interface. Sequence (biology) ; Microtubule ; Molecular dynamics ; Charge (physics) ; Protocol (science) ; Protein–protein interaction Diatoms and Algae Research ; Modular Robots and Swarm Intelligence ; Scientific Computing and Data Management
Authors: Raja Saharuddin Raja Daud | Muhammad Sharil Yahaya | Hidayat Zainuddin | Arfah Ahmad | Norhafiz Azis
Source: Journal of Power and Energy Engineering (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Condition Assessment of Medium Voltage Gas Insulated Ring Main Unit Using Health Index This paper presents a study on the formulation of a Health Index (HI) to assess the condition of gas-insulated Ring Main Units (RMUs). A total of 250 condition monitoring records for 11 kV distribution Ring Main Units (RMUs), aged between 1 and 27 years, were obtained from a Malaysian utility operator, with the sample randomly selected from a central region state that has the highest concentration of RMU assets in the country. The development of the HI algorithm was based on scoring, weighting, and ranking techniques. In addition to the HI, a risk factor was introduced to enhance the accuracy of the final HI estimation. Condition monitoring (CM) data were gathered using condition-based monitoring (CBM) techniques such as thermal scanning, ultrasonic testing, transient earth voltage measurement, SF6 gas level monitoring, and visual inspection. The ranking, weighting, and scoring for each parameter were determined based on expert assessments, utility practices, and relevant standards. The risk factor was established by considering environmental conditions, Original Equipment Manufacturer (OEM) data, and the risk of ageing mechanisms. Subsequently, the final HI for each CM data set was calculated. The findings showed that the HI approach can effectively be used to assess the condition of RMUs based on CM data. A statistical analysis of the 250 RMU records revealed that 44% of RMUs have a high HI, 51% have a medium HI, and 6% have a low HI. This indicates that the maintenance cycle for 44% of the RMUs can potentially be extended. The results are expected to support the development of optimized maintenance planning and cost management strategies. Index (typography) ; Unit (ring theory) ; Ring (chemistry) ; Materials science ; Voltage ; Nuclear engineering ; Composite material ; Electrical engineering ; Engineering ; Computer science ; Mathematics ; Chemistry High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Electrical Fault Detection and Protection
Authors: Kapil Nichani | Steffen Uhlig | Víctor Martín | Bertrand Colson | Karina Hettwer | Ulrike Steinacker | Heike Kaspar | Petra Gowik | Sabine Kemmlein
Source: Molecules (article, 2025-11-29)
Field: Chemistry — Spectroscopy

Towards Spectral Variation Analysis: A Data Quality Framework for Non-Targeted Methods Non-targeted methods (NTMs) require robust methods for comparing spectral data for reliable classification and identification. Traditional approaches using match factors reduce complex spectral relationships to single values, limiting their utility in quality assurance. This study presents an evaluation of spectral comparison methodologies, contrasting classical Mahalanobis distance (MD) with neural network approaches, namely, neural classification distance (NCD). Using matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry data from bacterial isolates, we systematically assessed these methods across varying levels of spectral variability. The MD approach exhibited consistent performance under controlled conditions but showed limitations with increasing spectral complexity. In contrast, the NCD demonstrated adaptability across all scenarios, revealing its capability in handling complex spectral relationships. Through this exemplary example, we present the mathematical framework for quantifying spectral variations and establish criteria for method selection in different analytical scenarios. This work provides a foundation for proposing data quality metrics in NTMs and offers practical implementations for routine quality assurance. The methodology developed here extends beyond mass spectrometry applications and contributes to the broader field of analytical quality control in complex spectral analysis. Mahalanobis distance ; Artificial neural network ; Data quality ; Quality (philosophy) ; Adaptability ; Metric (unit) ; Spectral signature ; Pattern recognition (psychology) Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Spectroscopy and Chemometric Analyses
Authors: lei kang | Huaping Luo | Xueting Ma | Jinlong Yu | Hongyang Liu | Huaiyu Liu | Yuesen Tong
Source: Research Square (preprint, 2025-12-10)
Field: Chemistry — Analytical Chemistry

Study on the Effect of Moisture Content on the Spectral Detection of Soluble Solids in Apricot (Prunus armeniaca ‘Diao Gan') Water content ; Hyperspectral imaging ; Moisture ; Partial least squares regression ; Sampling (signal processing) ; Residual ; Detection limit ; Spectral signature Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Water Quality Monitoring and Analysis
Authors: Gal-Erdene Battsengel | Noune Melkoumian | David Harvey | Rini Akmeliawati
Source: Biomimetics (review, 2025-11-07)
Field: Materials Science — Biomaterials

Bioinspired Drilling for Extraterrestrial Applications This review presents the novel synthesis of nature-inspired drilling strategies specifically tailored for extraterrestrial environments, where conventional technologies fail under the environmental conditions and power and mass constraints. Biomimetic drilling, inspired by insects, mollusks, reptiles, and other organisms, offers novel solutions for extraterrestrial subsurface exploration. Numerous organisms efficiently penetrate materials with low energy, using little force, and adapt to flexible substrates, which are essential capabilities for use off this planet. Traditional rotary and percussive drills do not function well under microgravity, at the end of the temperature spectrum, or in low energy and mass environments, such as landers which are typically under 300 kg and 200 W of power available. Nature-inspired approaches such as the reciprocating carpenter bee style have been shown to reduce overhead forces by as much as 50%; clam-like fluidization reduces drag by 90%; and sandfish-inspired methods improve mobility in granular media by 40%. These also improve the in situ resource utilization (ISRU) approaches for efficient sampling, water ice extraction, and planetary surface operations. This paper focuses on bio-drilling with other biological models, their engineering analogs, and exploration models for off-Earth use. Based on this synthesis, the paper recommends prioritizing dual-reciprocating and oscillatory mechanisms for near-term missions, while pursuing hybrid, AI-driven, and wear-resistant designs for long-term exploration. These approaches will help to improve penetration efficiency, reduce power demands, and extend the drilling system's lifespan in challenging extraterrestrial environments. Extraterrestrial life ; Drilling ; Propulsion ; Fluidization ; Measurement while drilling ; Icing Calcium Carbonate Crystallization and Inhibition ; Modular Robots and Swarm Intelligence ; Drilling and Well Engineering