jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Thang V. Pham | Chien-Thang Tran | Alex A. Henneman | Long Pham | Duc Anh Le | Ali Can | Phuc HL Bui | Sander R. Piersma | Connie R. Jiménez
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-10-08)
Field: Chemistry — Spectroscopy

Boosting the speed and accuracy of protein quantification algorithms in mass spectrometry-based proteomics Abstract Current methods for protein level quantification in mass spectrometry-based proteomics do not scale with the increasing number of samples because of limited system memory and algorithmic complexities. Here we propose a new data structure that supports parsing of input as data stream, improve state of the art quantitation methods in performance by orders of magnitudes, and provide a generic method to boost the precision and accuracy by fragment weighting. Boosting (machine learning) ; Proteomics ; Parsing ; Quantitative proteomics ; Stability (learning theory) ; Label-free quantification Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Zhenrong Zheng
Source: Research Square (preprint, 2025-05-07)
Field: Materials Science — Surfaces, Coatings and Films

Unified Aberration Theory for Metalenses: Bridging Classical Optics and Metasurface Technology Bridging (networking) ; Optics ; Physics ; Geometrical optics ; Computer science Optical Coatings and Gratings ; Photonic and Optical Devices ; Metamaterials and Metasurfaces Applications
Authors: Tesfaye Worku | Asaye Dessie Wolela
Source: World Journal of Materials Science and Technology (article, 2025-11-26)
Field: Materials Science — Polymers and Plastics

Impact of Traveler Weight on the Quality of Cotton Yarn: Examining Strength, Evenness, and Hairiness in Relation to Spinning Performance and Process Variables This review looks at how traveler weight impacts cotton yarn quality. Main metrics are strength, evenness, and hairiness. Traveler weight is critical in the ring spinning process. It touches tension, ballooning, and friction during yarn formation. Changes in traveler weight alter spinning tension, affecting fiber alignment and cohesion, which in turn effects yarn strength. Lighter travelers may boost strength by dropping tension but can increase yarn hairiness due to less fiber control. Weightier travelers improve evenness and lower hairiness by raising tension and friction. However, they may weaken yarn strength due to added fiber stress. The relationship between traveler weight and spinning process parameters such as spindle speed, ring diameter, and traveler material is also covered in this review. Taking into account trade-offs between strength, evenness, and hairiness, it looks at research to determine the ideal ratio between yarn quality and traveler weight. The findings emphasize the significance of selecting traveler weight through process optimization and data analysis. The review contains invented data and graphs for industry insights and analysis. Yarn ; Spinning ; Fiber ; Quality (philosophy) ; Tension (geology) ; Breaking strength Textile materials and evaluations ; Research in Cotton Cultivation ; Dyeing and Modifying Textile Fibers
Authors: Fernando Prieto Montenegro | Reni Danilo Vinocunga-Pillajo | Isnel Benítez Cortés | Julio Madera | Yosvany González Díaz | Francisco García Reina | Grety Márquez Peñamaría | Estela Guardado Yordi | Amaury ̈Pérez Martínez
Source: Research Square (preprint, 2025-04-30)
Field: Chemistry — Analytical Chemistry

Pressure drop dynamic in a convective axis regenerative boiler using heavy crude oil Boiler (water heating) ; Crude oil ; Petroleum engineering ; Pressure drop ; Environmental science ; Convection ; Waste management ; Mechanics ; Pulp and paper industry ; Materials science ; Engineering ; Physics Petroleum Processing and Analysis ; Process Optimization and Integration ; Field-Flow Fractionation Techniques
Authors: Chuqi Zhang
Source: Theoretical and Natural Science (review, 2025-05-30)
Field: Materials Science — Polymers and Plastics

A Review of Weierstrass Functions and Its Dimensions Calculation This paper mainly focuses on the Weierstrass Functions. Firstly, several properties of the Weierstrass Functions are introduced. Process of solving the conjecture suggested by Mandelbrot in 1977, that the graphs of Weierstrass type of functions have Hausdorff dimension. Since existing studies have proved such result with additional conditions through various approaches, this paper provides necessary information indicating this evolving progress in methodology. Given the intertwined relationship between the two, this paper also includes different methods utilized to prove that the Box-counting dimension of the graphs of Weierstrass type of functions is the given number above. In addition, the possible application of Weierstrass Functions and its relation to, for example, financial market are also included. Providing the summary of works, this paper look forward to the final solution to this long-lasting conjecture. Weierstrass functions ; Mathematics ; Computer science ; Pure mathematics Textile materials and evaluations ; Statistical and numerical algorithms
Authors: Mónica V. Orellana | Jacob J. Valenzuela | Christopher Lausted | Christopher Deutsch | Sui Huang | Nitin S. Baliga
Source: Research Square (preprint, 2025-10-28)
Field: Materials Science — Biomaterials

Single-cell heterogeneity underpins diatom success in dynamic ocean environments Thalassiosira pseudonana ; Diatom ; Phytoplankton ; Adaptation (eye) ; Population ; Local adaptation ; Ecosystem Diatoms and Algae Research ; Marine and coastal ecosystems ; Algal biology and biofuel production
Authors: Md Jahidul Islam | Mohsin Ali | Debasish Sen | Md. Ismail Hossain
Source: ASEAN Engineering Journal (article, 2025-05-31)
Field: Materials Science — General Materials Science

A COMPARATIVE ANALYSIS OF RECYCLED AND VIRGIN MATERIALS FOR SUBBASE MIX DESIGNS This study explores the feasibility and benefits of using a mix of 70% concrete broken chips and 30% salvage materials for subbase construction in Bangladesh, offering an innovative alternative to exclusively using virgin resources. Key findings include the salvage materials mix-design achieving lower Los Angeles Abrasion values and higher California Bearing Ratio than virgin materials, indicating superior durability and strength. Additionally, optimal compaction characteristics were observed, with higher maximum dry density and lower optimum moisture content, contributing to environmental sustainability through reduced water consumption. The mix-design's compliance with required gradation standards post-compaction and favorable pavement performance in terms of vertical displacement and shear stress, as per KENPAVE simulations, further validates its effectiveness. This research underscores the potential of incorporating salvaged materials in pavement construction, aligning with sustainable development goals and demonstrating cost-efficiency and reduced landfill usage, while maintaining industry standards. Subbase ; Mathematics Material Properties and Applications ; Material Properties and Processing
Authors: Yaoyao Zhou | Lei Wang
Source:  (article, 2025-06-13)
Field: Chemistry — Spectroscopy

Prediction of Vacuum Glass Thermal Insulation Performance via Model Agnostic Meta Learning To overcome the scarcity and homogeneity of data in predicting the thermal transmittance (U-value) of vacuum glazing, this study proposes a Model-Agnostic Meta-Learning–based multilayer perceptron (MAML-MLP). The model shares an initial set of parameters across multiple pseudo-tasks and employs a dual inner–outer loop optimization to achieve rapid adaptation under few-shot conditions. K-means clustering partitions the original samples into clusters, each treated as a pseudo-task that is further divided into support and query sets to meet MAML's training requirements. Experimental results show that MAML-MLP significantly outperforms a conventional MLP in MAE, MSE, MAPE, and R², confirming the method's effectiveness for limited-sample engineering predictions. Vacuum insulated panel ; Thermal ; Materials science ; Composite material ; Computer science ; Thermal insulation ; Mechanical engineering ; Engineering ; Physics ; Thermodynamics Aerogels and thermal insulation ; Aerosol Filtration and Electrostatic Precipitation ; Building Energy and Comfort Optimization
Authors: Ankit Sinha | Nadja Sachs | Elena Kratz | Jessica Pauli | Sophia Steigerwald | Vincent Albrecht | Thierry M. Nordmann | Patricia Skowronek | Hanna Winter | Lars Mäegdefessel | Matthias Mann
Source: Atherosclerosis (article, 2025-07-18)
Field: Chemistry — Spectroscopy

Histomorphology-guided integrative proteomics reveals subregion-specific extracellular protein signatures of vulnerable carotid plaques Proteomics ; Extracellular ; Computational biology ; Biology ; Pathology ; Medicine ; Cell biology ; Gene ; Genetics Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Bioinformatics and Genomic Networks
Authors: Predrag Tasić | Dušan Trajković | Jelka Geršak | Nenad Ćirković
Source: Tekstilna industrija (article, 2025-01-01)
Field: Materials Science — Polymers and Plastics

The impact of the raw material composition of men's rib-knitted socks on their compression properties The study examines the impact of the raw material composition of men's rib-knitted socks on their compression properties and, indirectly, on their comfort during use. The research involves six different fibers that constitute the dominant yarn in the sock composition, making up 77%. The remaining yarns consist of polyamide and wrapped rubber threads, accounting for a total of 23%. Measurements determined that the sock with the highest softness is made from a cotton/polyester yarn blend, while socks made from other yarns lag significantly behind. Additionally, socks knitted from cotton or blends with polyester provide the highest values for linearity and compression energy. For the elastic recovery of socks after compression, the sample made from modal fibers proved to be the best. The thickness of the knit under different pressures is the greatest in socks made from bamboo yarn, for both pressure levels. Socks with a cotton/polyester yarn exhibit weaker elastic recovery, while socks with modal yarn show better elastic recovery. Through six combinations of raw material compositions and the evaluation of multiple compression properties, rib-knitted sock models can be selected for appropriate purposes, whether in a medical context, for home use, or for active wear outside the home. SOCKS ; Yarn ; Composite material ; Materials science ; Polyester ; Compression (physics) ; Raw material ; Spinning Textile materials and evaluations ; Mechanical Engineering and Vibrations Research ; Muscle Physiology and Disorders
Authors: Katelyn B Brusach | Ariana E. Shannon | Alex Joyce | Jessica M. Quimby | Brian C. Searle
Source: Molecular & Cellular Proteomics (article, 2025-10-12)
Field: Chemistry — Spectroscopy

Harmonized Peptide Libraries Enable Practical Biofluid Selection for Developing Biomarker Assays Selecting the optimal biofluid for accurate biomarker assessment is vital to an informative clinical assay. However, in the initial stages of candidate biomarker discovery, the biologically appropriate biofluid might be unclear. To resolve this dilemma, we demonstrate a mass spectrometry-based workflow where paired urine, plasma, and serum samples are processed in parallel, creating biofluid-specific peptide libraries. These libraries are then harmonized to monitor consistent peptides and transitions, enabling cross-fluid normalization and quantitative comparisons. We also present a reference dataset, "CATalog," to aid in determining which biofluid to pursue based on protein relative abundance in healthy feline urine, plasma, and serum. Using this workflow and database, we explore the interchangeability of blood biofluid proteins compared to urinary proteins relating to sample processing, relative protein quantification, and clinical application. Our results suggest that when processed correctly, urine could sometimes represent blood biofluid proteins without requiring venipuncture or sample depletion of highly abundant proteins. Biomarker ; Biomarker discovery ; Workflow ; Peptide ; Venipuncture ; Selection (genetic algorithm) ; Quantitative proteomics Advanced Proteomics Techniques and Applications ; Monoclonal and Polyclonal Antibodies Research ; Advanced Biosensing Techniques and Applications
Authors: M Shokri | Ahmad Darudi | Ali Reza Yousefi | Sirwan Babaei
Source: Research Square (preprint, 2025-10-03)
Field: Chemistry — Analytical Chemistry

A Novel Hyperspectral Imaging Approach for Early Detection of Broomrape Infestation in Tomato Plants Hyperspectral imaging ; Infestation ; Crop ; Weed ; Crop yield ; Weed control Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Essential Oils and Antimicrobial Activity
Authors: Predrag Tasić | Dušan Trajković | V.I.“Vunil“, d.o.o., Leskovac, Serbia | Nenad Ćirković | Jelka Geršak
Source:  (article, 2025-01-01)
Field: Materials Science — Polymers and Plastics

COMPRESSIBLE PROPERTIES OF MEN’S SOCKS MADE FROM DIFFERENT FIBERS IN PLAIN JERSEY This paper examines the most important compressible properties of socks made from different fibers in a plain jersey. These properties indirectly affect the parameters of thermo-physiological comfort of socks during wear. Three yarns were used in the sock composition; the first, a dominant yarn made from six different fibers, makes up 77%. The other two yarns are made from nylon and wrapped elastic threads, accounting for 23%. The most compressible sock is made from cotton yarn, with the modal yarn sock model being very close in performance. The highest linearity of compression, compression energy, and compression resistance are found in socks made from bamboo and modal yarns, with viscose yarn socks not falling far behind. Bamboo yarn socks exhibit weaker elastic recovery compared to socks made from cotton-compact yarn, which have better elastic characteristics. Out of the six combinations of raw material compositions for socks and the examination of several compression properties, sock models in plain jersey can be selected for specific purposes, such as medical, home, or outdoor use. SOCKS ; Yarn ; Compression (physics) ; Viscose ; Bamboo Textile materials and evaluations ; Bamboo properties and applications ; Natural Fiber Reinforced Composites
Authors: V. F. Bez”yazychnyi | E. V. Shekhovtseva | T.V. Shekhovtseva
Source: iPolytech Journal (article, 2025-06-30)
Field: Materials Science — Materials Chemistry

Inheritance of mechanical properties of a material during directed formation Objective – development of a comprehensive model that takes into account the interrelationship between the structure of a gear wheel, material properties and technological processing parameters. This model should predict the operational characteristics of the wheel, considering the impact of both internal and external factors. Mechanical testing was conducted using electromechanical tensile testing equipment from Tinius Olsen, model H100KU, to determine the mechanical properties of the metal. Samples in compliance with GOST 1497-84 were used for monitoring material properties (tensile strength, yield strength, etc.) at loads above 100 N/mm 2 . The mechanical properties of the metal were monitored after each processing operation. The mechanical properties of the steels 16Kh3NVFMB-Sh, 20Kh3MVF-Sh, 18Kh2N4MA and 12Kh2N4A-Sh were investigated for different blanks and types of treatment (pressure forming, mechanical and abrasive, thermochemical and heat treatment). Analysis of the mechanical properties of the metal revealed significant differences in hardness, strength and ductility between samples obtained by different methods. It was shown that these differences are due to the microstructure of the material (grain size, presence of inclusions, degree of deformation) formed during processing. The analysis was based on parameters including the coefficient of technological inheritance and structural inheritance. It was found that the inheritance of the mechanical properties of the material through pressure working followed by heat treatment shows a positive trend relative to rolled material with similar heat treatment. This method results in an increase in tensile strength of up to 6.2% and in yield strength of up to 5.3%. Furthermore, it was shown that the increase in the quantitative indicator of structural inheritance after thermochemical treatment, relative to grinding of the hardened layer, is at least 49% for tensile strength and at least 68% for yield strength. The developed multidimensional model of gear interaction takes into account a wide range of factors that influence its operation, including material properties, temperature fields in the contact zone of the tooth, dynamic loads and the effect of lubricant. Inheritance (genetic algorithm) ; Materials science ; Composite material ; Biology ; Genetics Microstructure and mechanical properties ; Metallurgy and Material Forming ; High-Velocity Impact and Material Behavior
Authors: Mohammadreza Hadavi | Karim Akbarivakilabadi | Saeid Nikabadi | Mehdi Ghasri
Source:  (preprint, 2025-04-28)
Field: Materials Science — Polymers and Plastics

Balancing Lightweight Design and Structural Integrity in Tall Composite Masts: A Data-Driven Study on ANN-Genetic Algorithm Optimization, Stress Concentration Mitigation, and Performance Validation for Naval Applications The pursuit of lightweight, structurally sound, and cost-effective designs is paramount in contemporary engineering, particularly in the development of advanced enclosed mast/sensor systems (AEM/S). A significant challenge in this field is the limited Composite number ; Structural engineering ; Genetic algorithm ; Stress (linguistics) ; Structural integrity ; Computer science ; Engineering ; Algorithm ; Machine learning Textile materials and evaluations
Authors: Santosh Kumar Mishra | Uddipan Nath | Sagnik Banerjee | Bhargav Appasani | Om Prakash Acharya | Sunil Kumar Mishra | Amitkumar V. Jha | Avireni Srinivasulu | Cristian Ravariu
Source:  (article, 2025-10-31)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Hexa-Band Terahertz Metamaterial Absorber Using a Symmetrical Boss Cross Structure with Biomedical Applications Terahertz (THz) metamaterial absorbers have become a prominent research topic in recent years. In this paper, a hexa-band metamaterial absorber is designed for bio-medical sensing applications. The design can detect changes in the surrounding medium’s refractive index and operates in the refractive index range of 1.3–1.4, with six prominent absorption peaks. The proposed structure comprises a square ring resonator made up of gold with a boss-cross structure at the center, on top of a Gallium Arsenide (GaAs) substrate having a thickness of 8 μm. When the surrounding medium’s refractive index is 1.4, it offers six absorption peaks at 0.537 THz, 2.573 THz, 3.025 THz, 3.146 THz, 3.489 THz, 3.7348 THz, with corresponding peak absorption of 75%, 92.9%, 98.4%, 98.71%, 94.1%, and 99.34%, respectively. The structure has been designed at n = 1.4 instead of n = 1, as several biological specimens, such as blood, breast cells, etc., have refractive index in the range of 1.3–1.4, and it offers 6 bands for n = 1.4. This choice was made because many biomedical applications have a refractive index around 1.4. The design parameters were selected through a parametric analysis, so as to achieve maximum absorption peaks. The design has also been tested with different polarization angles, and it has been discovered that the absorber is polarization-insensitive. This design can inspire future research on the biomedical application of THz absorbers. Terahertz radiation ; Refractive index ; Metamaterial ; Metamaterial absorber ; Resonator ; Absorption (acoustics) ; Gallium arsenide ; Polarization (electrochemistry) Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Terahertz technology and applications
Authors: Mаrtin Dejanov
Source:  (article, 2025-08-25)
Field: Chemistry — Analytical Chemistry

Hyperspectral Analysis of Apricot Quality Parameters Using Classical Machine Learning and Deep Neural Networks Geothermal power generation offers a high availability factor and independence from weather conditions, yet steam production in geothermal wells often declines over time due to factors such as pressure depletion and scale deposition. To enable early detection of production anomalies and optimize maintenance, this paper proposes an anomaly detection framework based on Singular Spectrum Analysis (SSA). First, a Butterworth low-pass filter reduces high-frequency noise; then, SSA decomposes the time series, focusing on the largest singular value’s corresponding vectors. An anomaly score measures the deviation between current and historical singular vectors, and Non-Maximum Suppression (NMS) aggregates consecutive peaks to reduce false positives. We apply this method to 14 years of data from nine geothermal wells, comparing two threshold strategies: a unified threshold and well-specific thresholds. Results show that while a unified threshold simplifies deployment, individual thresholds can improve detection in certain wells, underscoring the impact of well characteristics and class imbalance. Our findings demonstrate that SSA-based anomaly detection, combined with NMS and threshold optimization, can effectively support maintenance decisions in geothermal power plants. Hyperspectral imaging ; Computer science ; Artificial intelligence ; Artificial neural network ; Quality (philosophy) ; Machine learning ; Deep learning ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Remote Sensing and Land Use
Authors: Theodoros Margelos | Manousos Makridakis | Charis Gonidaki | Foteini Paradeisi | Manos Vossos | Jérôme Zoidakis | A. Vlahou | Rafael Stroggilos
Source: PROTEOMICS - CLINICAL APPLICATIONS (article, 2025-12-26)
Field: Chemistry — Spectroscopy

Simple, Fast, and Reliable Analysis of Label‐Free Proteomics Data With the Proteomics Eye (ProtE) In label-free mass spectrometry experiments, the data output is typically a proteome table that requires further processing, quality testing, and visualization to fully interpret the captured proteomic signals. Currently, post-quantification analysis of these tables often relies on complex programmatic pipelines, which can become challenging to use. Here, we introduce the Proteomics Eye (ProtE), a single-function R package designed to streamline the analysis of proteome tables generated by commonly used software tools (DIA-NN, ProteomeDiscoverer, and MaxQuant). ProtE provides a broad range of options for data processing, preparation, and statistical testing. It also performs gene set enrichment analysis and offers a comprehensive suite of visualization plots to assess data quality and facilitate biological interpretation. Given a categorical variable with two or more groups, ProtE enables group-wide and pairwise statistical comparisons across all group combinations, using both traditional statistical tests and linear models for differential expression analysis. By integrating all these features into a single, user-friendly R function, ProtE simplifies the analysis of large-scale label-free DDA and DIA datasets, making advanced proteomic analysis accessible to both experienced researchers and beginners. Proteome ; Proteomics ; Visualization ; Table (database) ; Pairwise comparison ; Categorical variable ; Set (abstract data type) ; Software ; Data visualization Advanced Proteomics Techniques and Applications ; Biotin and Related Studies ; Bioinformatics and Genomic Networks