jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Albert Jang | Hyungseok Jang | Nian Wang | Alexey Samsonov | Fang Liu
Source: ArXiv.org (article, 2025-10-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

MC BTS: simultaneously resolving magnetization transfer effect and relaxation for multiple components We propose a signal acquisition and modeling framework for multi-component tissue quantification that encompasses transmit field inhomogeneity, multi-component relaxation and magnetization transfer (MT) effects. By applying off-resonance irradiation between excitation and acquisition within an RF-spoiled gradient-echo scheme, in combination with multiple echo-time acquisitions, both Bloch-Siegert shift and magnetization transfer effects are simultaneously induced while relaxation and spin exchange processes occur concurrently. Simulation results showed excellent agreement with the derived analytical signal equation across a wide range of flip angles and echo times. Monte Carlo analyses further validated that the three-pool parameter estimation pipeline performed robustly over various signal-to-noise ratio conditions. Multi-parameter fitting results from in vivo brain and knee studies yielded values consistent with previously reported literature. Collectively, these findings confirm that the proposed method can reliably characterize multi-component tissue parameters in macromolecule-rich environments while effectively compensating for $B_1^+$ inhomogeneity. Magnetization ; Pipeline (software) ; Monte Carlo method ; Magnetization transfer ; Relaxation (psychology) ; SIGNAL (programming language) ; Excitation ; Flip angle Magnetic and transport properties of perovskites and related materials ; Magnetic properties of thin films ; Magnetic Properties of Alloys
Authors: Jonathan Muller | Angel Xia | Patrik R. Jones
Source: Journal of Biological Engineering (article, 2025-11-25)
Field: Materials Science — Materials Chemistry

A synthetic metabolic pathway for the de novo biosynthesis of medium chain length γ- and δ-lactones The synthetic pathways were shown to be functional and amenable to tailoring both the chain length and ring-structure of the resultant lactones. Metabolic pathway ; Biosynthesis ; Metabolic engineering ; Chain (unit) ; Synthetic biology ; Protein biosynthesis Enzyme Structure and Function ; Microbial Natural Products and Biosynthesis ; Carbohydrate Chemistry and Synthesis
Authors: Xiaoyu Xue | Haiqing Tian | Kai Zhao | Yang Yu | Chunxiang Zhuo | Ziqing Xiao | Daqian Wan
Source: Agronomy (article, 2025-01-23)
Field: Chemistry — Analytical Chemistry

Non-Destructive Detection of pH Value During Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging Technology The pH value of maize silage can accurately reflect its quality. In this study, a colorimetric sensor array (CSA) combined with hyperspectral imaging (HSI) was used to predict the pH value of maize silage during secondary fermentation. Seventeen color-sensitive dyes were used to construct the CSA, which was subsequently applied to capture the volatile odor profiles of maize silage samples. Hyperspectral images of the color-sensitive dyes on the CSA were acquired using the HSI technique. Different algorithms were used to preprocess the raw spectral data of each dye, and a partial least squares regression (PLSR) model was built for each dye separately. Subsequently, the adaptive bacterial foraging optimization (ABFO) algorithm was employed to identify three color-sensitive dyes that demonstrated heightened sensitivity to pH variations in maize silage. This study further compared the capabilities of individual dyes, as well as their combinations, in predicting the pH value of maize silage. Additionally, a novel feature wavelength extraction method based on the ABFO algorithm was proposed, which was then compared with two traditional feature extraction algorithms. These methods were combined with PLSR and backpropagation neural network (BPNN) algorithms to construct a quantitative prediction model for the pH value of maize silage. The results show that the quantitative prediction model constructed based on three dyes was more accurate than that constructed based on an individual dye. Among them, the ABFO-BPNN model constructed on the basis of combined dyes had the best prediction performance, with prediction correlation coefficient (RP2), root mean square error of the prediction set (RMSEP), and ratio of performance deviation (RPD) values of 0.9348, 0.3976, and 3.9695, respectively. The aim of this study was to develop a reliable evaluation model to achieve fast and accurate predictions of silage pH. Hyperspectral imaging ; Silage ; Fermentation ; Agronomy ; Environmental science ; Chemistry ; Food science ; Remote sensing ; Biology ; Geology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies
Authors: Anthony Dosseto | Florian Dux | Clément P. Bataille | Patrice de Caritat
Source:  (preprint, 2025-06-10)
Field: Chemistry — Inorganic Chemistry

A Bioavailable Strontium Isoscape of Australia Abstract. Strontium isotope ratios (⁸⁷Sr/⁸⁶Sr) at the Earth’s surface offer powerful tools for geological, environmental, and archaeological applications. In minerals and biological materials, ⁸⁷Sr/⁸⁶Sr reflects the isotopic composition of the local bedrock and derived soils. In Australia, however, large regional-scale surveys of bioavailable ⁸⁷Sr/⁸⁶Sr remain scarce. Here, we present a new dataset of bioavailable ⁸⁷Sr/⁸⁶Sr ratios from 278 catchment outlet (floodplain) sediment samples, spanning inland southeastern Australia (South Australia, New South Wales, Victoria), northern Western Australia, the Northern Territory, Queensland (north of 21.5° S), and the Yilgarn Craton in southern Western Australia. Combined with more than 20,000 global Sr isotope measurements, this dataset was used to generate a high-resolution isoscape of Australia using random forest regression (Bataille et al., 2020). Australian bioavailable ⁸⁷Sr/⁸⁶Sr values span a narrower range (0.70501–0.78121) compared to co-located bulk sediment values (0.70480–1.09089) (Caritat et al., 2022, 2023, 2025b), reflecting the influence of soluble and exchangeable mineral phases and atmospheric inputs such as rain and dust. The predicted isoscape reproduces major geological patterns, with higher values over ancient crustal provinces like the Yilgarn Craton and eastern Palaeozoic orogens, and lower values across younger sedimentary basins and coastal margins. Model uncertainty, assessed via prediction standard deviations, is lowest across well-sampled, geologically stable regions and highest in coastal and lithologically complex zones. Compared to existing global and regional isoscapes, our model offers significantly improved coverage and resolution for Australia. This isoscape provides a robust baseline for applications in provenance research, palaeoecology, and environmental geochemistry. Strontium ; Business ; Environmental science ; Chemistry Radioactive element chemistry and processing
Authors: Wenyan Zhang | Huayan Chen | Maobing Shuai | Xiangguo Zeng | Bin Huang
Source: Materials (article, 2025-06-16)
Field: Chemistry — Organic Chemistry

A Sintering–Resting Strategy of Microwave Heating for Lithium Hydride Ceramic Based on Numerical Analysis of Thermal Effects Lithium hydride (LiH) is one promising material for nuclear reactor shielding due to its high hydrogen content, but its poor mechanical strength and thermal conductivity pose challenges for fabricating large, crack-free ceramic components via conventional sintering. This study explores microwave sintering as a potential solution to enhance heating uniformity and reduce thermal stress during densification of bulk LiH ceramics. Using implicit function and level set methods, we numerically simulated the microwave field distribution and thermal response in both stationary and rotating samples. The results show that rotational heating improves temperature uniformity by up to 12.9% for specific samples, although uniform temperature control remains difficult through rotation alone. To mitigate stress accumulation from thermal gradients, we propose a cyclic sintering-resting strategy, which leverages LiH's tensile strength-temperature envelope to guide safe and efficient processing. This strategy successfully reduced total sintering time from several days to 1.63 h without inducing cracks. Our findings offer practical insights into optimizing microwave sintering parameters for large-scale LiH ceramic production and contribute to enabling its application in advanced nuclear shielding systems. Materials science ; Sintering ; Ceramic ; Hydride ; Lithium hydride ; Lithium (medication) ; Microwave ; Microwave heating ; Thermal ; Thermal analysis ; Composite material ; Titanium hydride ; Metallurgy ; Nuclear engineering ; Ion ; Thermodynamics ; Chemistry ; Metal ; Computer science ; Titanium ; Engineering Microwave-Assisted Synthesis and Applications ; Advanced ceramic materials synthesis ; Microwave Dielectric Ceramics Synthesis
Authors: Xiong Dun | Jian Zhang | Fansheng Chen | Zhanyi Zhang | Xuquan Wang | Yujie Xing | Siyu Dong | Zeying Fan | Yuzhi Shi | Gordon Wetzstein | Zhanshan Wang | Xinbin Cheng
Source: eLight (article, 2025-12-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Neural array meta-imaging Abstract Compact, high-quality imaging systems are highly desired for scientific, industrial, and consumer applications. Metalenses combined with computational imaging offer a promising solution for developing such systems, yet their performance is fundamentally limited by the commonly used point-to-point imaging model, which forces trade-offs between aperture size, F-number, field of view (FOV), waveband width, and image quality. Here, we experimentally demonstrate that a neural array imaging model can overcome these long-standing trade-offs, achieving a 25-Hz full-color imaging camera with a 2.76-mm aperture, 1.45 F-number, 50 $$^{\circ }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mmultiscripts> <mml:mrow/> <mml:mrow/> <mml:mo>∘</mml:mo> </mml:mmultiscripts> </mml:math> FOV, and a spectral range of 400–700 nm. The camera achieves image quality comparable to commercial compound lenses (e.g., Edmund 33-300) in both indoor and outdoor environments, while reducing the total track length by a factor of 13. We further demonstrate its suitability for object detection and depth estimation in real-world scenarios. This neural array imaging model is also applied to polarization imaging, showcasing its scalability and versatility for broadband applications. Image quality ; Broadband ; Computational photography ; High-dynamic-range imaging ; Scalability ; Spectral imaging ; Object detection ; Aperture (computer memory) ; Artificial neural network Metamaterials and Metasurfaces Applications ; Neural Networks and Reservoir Computing ; Advanced Optical Imaging Technologies
Authors: Han Lu | Lukas Frase | Claus Normann | Stefan Rotter
Source: Frontiers in Network Physiology (article, 2025-07-07)
Field: Materials Science — Polymers and Plastics

Resolving inconsistent effects of tDCS on learning using a homeostatic structural plasticity model Our model explained both Hebbian and homeostatic phenomena observed in human tDCS experiments by assuming memory strength positively correlates with engram connectivity. This includes applications with different polarity, intensity, electrode montage, and timing relative to motor learning. The HSP model provides a promising framework for unraveling the dynamic interaction between learning and transcranial DC stimulation. Homeostatic plasticity ; Neuroplasticity ; Neuroscience ; Plasticity ; Psychology ; Cognitive psychology ; Cognitive science ; Metaplasticity ; Synaptic plasticity ; Biology ; Materials science Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Transcranial Magnetic Stimulation Studies
Authors: Sofia Silva | João A. Rodrigues | Vítor Vale Cardoso | Rui Neves Carneiro | Cristina Almeida
Source: Molecules (article, 2025-04-03)
Field: Chemistry — Analytical Chemistry

Analysis of Pharmaceutical Active Compounds in Complex Water Samples: Sample Filtration as an Option Sample pretreatment is one of the most important steps in guaranteeing the success of a chromatographic analysis. The selected methodology must ensure simultaneously that a sample is "clean" enough for analysis and that the target analytes are not removed in the process. This can be especially difficult when working with complex matrices such as natural waters and wastewater. For pharmaceutical active compounds (PhACs) analysis by solid-phase extraction (SPE) followed by ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS), and due to the high level of organic matter in wastewater, the water samples are filtered consecutively through three filters, a paper filter, a glass microfiber filter of 1 µm, and a Nylon filter of 0.45 µm. This filtration allows the sample's passage through the SPE cartridge to be faster, and there is no cartridge clogging, allowing for greater efficiency in the adsorption process. The big question is whether the PhACs are eliminated during filtration, since they may be adsorbed to organic matter. This work aimed to determine if the best approach for quantifying PhACs in wastewater and surface waters would be to filter them prior or to perform SPE directly. Both approaches analyzed a total of 26 PhACs. Turbidity (TUR) and permanganate index (PI) were determined, and their values were high for samples with a high organic matter content. A statistical analysis was performed to determine the best approach to treat these water samples and whether any correlation existed between PhAC concentrations, PI, and TUR. The PhAC quantification shows a positive correlation with TUR and a negative correlation with PI for most of the target PhACs. However, there are not significantly different results for filtered and not-filtered wastewater samples. Cartridge ; Chromatography ; Solid phase extraction ; Wastewater ; Filtration (mathematics) ; Sample preparation ; Chemistry ; Analyte ; Organic matter ; Filter (signal processing) ; Adsorption ; Extraction (chemistry) ; Pulp and paper industry ; Environmental science ; Materials science ; Environmental engineering ; Mathematics ; Computer science ; Organic chemistry Analytical chemistry methods development ; Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Sensors
Authors: S. N. Deepa | A. D. Srinivasan | K. T. Veeramanju
Source: International Journal of Renewable Energy Research (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Performance Analysis of Dielectric Properties of Blended Neem and Olive Oils using TOPSIS and Fuzzy TOPSIS Methods for Power Transformer A power transformer is the power distribution system's essential component that must be contractually monitored. The electricity supply has to be uninterrupted to keep a harmonious balance between consumer demand and supply, which depends on the reliability of the transformer. Also, liquid insulation that offers efficient cooling and insulation is very much crucial to the lifespan of the transformer. Conventionally, mineral oil is being used as a coolant and insulation medium for power transformers, which is a derivative of petroleum. The objective of this proposed investigation is to reduce reliance on fossil fuels that are increasingly scarce and to upsurge the use of oils derived from renewable sources. Thereby, to overcome the limitations of mineral oil, such as its poor biodegradability and weak flash and fire point, recent research has concentrated on natural ester liquid, environmentally acceptable insulating oil with commendable dielectric properties. In this paper, investigations were conducted to examine the functionality of olive oil, neem oil, and its blended samples at different proportions to replace mineral oil employed as liquid insulation in power transformers. The characteristics investigated are breakdown voltage, viscosity, moisture content, and oxidation stability of blended samples per IEC and ASTM standards. The multi-objective optimization tools such as TOPSIS and fuzzy TOPSIS were employed to optimize and choose the suitable natural ester for power transformers. Among the samples, NM50+OL50 presents a higher breakdown voltage of 59.96 kV with an induction time of 1.26 hrs and a viscosity of 42.92 cSt at room temperature. It was found that TOPSIS and Fuzzy TOPSIS methods have computational robustness in selecting NM50+OL50 as a suitable alternative to power transformers among the blended samples. TOPSIS ; Fuzzy logic ; Olive oil ; Mathematics ; Computer science ; Chemistry ; Food science ; Artificial intelligence ; Operations research Spectroscopy and Chemometric Analyses
Authors: T Tabata | Akiyasu C. Yoshizawa | Kosuke Ogata | Chih‐Hsiang Chang | Norie Araki | Naoyuki Sugiyama | Yasushi Ishihama
Source: Molecular & Cellular Proteomics (article, 2025-06-02)
Field: Chemistry — Spectroscopy

UniScore, a Unified and Universal Measure for Peptide Identification by Multiple Search Engines We propose UniScore as a metric for integrating and standardizing the outputs of multiple search engines in the analysis of data-dependent acquisition (DDA) data from LC/MS/MS-based bottom-up proteomics. UniScore is calculated from the annotation information attached to the product ions alone by matching the amino acid sequences of candidate peptides suggested by the search engine with the product ion spectrum. The acceptance criteria are controlled independently of the score values by using the false discovery rate based on the target-decoy approach. Compared to other rescoring methods that use deep learning-based spectral prediction, larger amounts of data can be processed using minimal computing resources. When applied to large-scale global proteome data and phosphoproteome data, the UniScore approach outperformed each of the conventional single search engines examined (Comet, X! Tandem, Mascot, and MaxQuant). Furthermore, UniScore could also be directly applied to peptide matching in chimeric spectra without any additional filters. Measure (data warehouse) ; Identification (biology) ; Computational biology ; Computer science ; Information retrieval ; Biology ; Data mining Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Mass Spectrometry Techniques and Applications
Authors: Chunpeng Song | Xiaoliang Xu | Lehua Wang
Source: Buildings (article, 2025-05-23)
Field: Materials Science — Biomaterials

Development and Characterisation of Novel Fluid–Solid Coupled Similar Materials Under Dry–Wet Cycling Conditions This study aims to develop fluid–solid coupled similar materials to enhance the reliability of geotechnical model tests simulating reservoir slope stability under water-level fluctuations. Using an orthogonal experimental method, materials were prepared with quartz sand and barite as aggregates, cement and gypsum as binders, and water as the regulator. Tests on density, uniaxial and triaxial compressive strength, and flow properties determined the relationships between material properties and raw components. Uniaxial compressive strength tests under dry–wet cycles revealed that cement-to-binder ratio primarily influenced density, uniaxial compressive strength, cohesion, and hydraulic conductivity, while the binder-to-aggregate ratio affected elastic modulus and internal friction angle. Uniaxial compressive strength continuously degraded with cycles but at a decreasing rate. A water-damage resistance coefficient was defined to quantify degradation. Multiple linear regression analysis established a robust model for uniaxial compressive strength prediction, providing a theoretical basis for material proportioning. These findings improve the simulation accuracy in hydrologically active zones, with applications in designing stable reservoir slopes. Cycling ; Materials science ; Temperature cycling ; Composite material ; Thermodynamics ; Physics biodegradable polymer synthesis and properties
Authors: Junwan Lu | Mei Zhu | Jingzeng Ye | Leyao Xu | Chunhan Song | Kewei Li | Qiyu Bao | Xi Lin
Source: BMC Microbiology (article, 2025-08-23)
Field: Chemistry — Organic Chemistry

Identification of a novel aminoglycoside nucleotidyltransferase ANT(3″)-Ic from Citrobacter telavivum S24 Understanding the antibiotic resistance profile of the emerging pathogen Citrobacter telavivum S24 is important for clinical care, surveillance, and research. C. telavivum S24, a strain that exhibits resistance to both streptomycin and spectinomycin, was isolated from the soil at a broiler chicken farm. The strain was identified by whole-genome sequencing and average nucleotide identity analyses. Annotation of the resistance genes revealed that a novel aminoglycoside resistance gene, designated ant(3″)-Ic, is located on the chromosome of C. telavivum S24. This gene exhibits 52% similarity with the previously functionally characterized resistance gene aadA23. It distinguishes itself from ant(3″)-Ia and ant(3″)-Ib genes, and represents an independent branch. The ant(3″)-Ic gene is recognized as an inherent resistance gene of C. telavivum within a conserved genetic environment. The product of the ant(3″)-Ic gene is the aminoglycoside nucleotidyltransferase ANT(3″)-Ic, which has a theoretical pI of 5.05 and a molecular mass of 29 kDa. ANT(3")-Ic inactivates streptomycin and spectinomycin with the K<sub>m</sub> of 46.13 and 115.90 µM, respectively. The discovery of the novel antibiotic resistance gene ant(3″)-Ic and the functional characterization of ANT(3")-Ic will facilitate more targeted surveillance and treatment strategies for preventing and controlling zoonotic pathogens of zoonotic diseases. Biology ; Identification (biology) ; Computational biology ; ANT ; Aminoglycoside ; Bioinformatics ; Microbiology ; Antibiotics ; Ecology Carbohydrate Chemistry and Synthesis ; Biochemical and Molecular Research ; Glycosylation and Glycoproteins Research
Authors: Oanamari Daniela Orbuleţ | Liliana Bobirică | Mirela Enache | Ramona Cornelia Pațac | Magdalena Boșomoiu | Cristina Modrogan
Source: Environments (article, 2025-09-07)
Field: Materials Science — Materials Chemistry

Adsorption of Phosphates from Wastewater Using MgAlFe-Layered Double Hydroxides Phosphates pollution, primarily from agricultural runoff and wastewater discharge, is a major contributor to water eutrophication, adversely affecting aquatic ecosystems. This study reports the synthesis, characterization, and phosphates adsorption performance of a MgAlFe-layered double hydroxide (MgAlFe-LDH) with a 2:1:1 cationic ratio. The material was prepared via co-precipitation and characterized using digital microscopy, XRD, BET, XPS, and FTIR. Adsorption experiments were conducted at pH 3 and 9 to investigate equilibrium, kinetics, and reusability. The MgAlFe-LDH exhibited a high maximum adsorption capacity (q_max ≈ 215 mg/g) largely independent of pH, with adsorption well described by the Langmuir model. Kinetic studies revealed a pseudo-first-order mechanism, indicating that adsorption is dominated by surface diffusion and electrostatic interactions. Phosphate removal occurs through a dual mechanism involving rapid electrostatic attraction at protonated surface sites and slower ion exchange in the LDH interlayers. The material retained over 75% of its adsorption capacity after five consecutive adsorption–desorption cycles, highlighting its potential for sustainable phosphate recovery. Overall, the MgAlFe-LDH represents a promising, reusable adsorbent for phosphorus removal from wastewater, supporting circular economy strategies. Adsorption ; Layered double hydroxides ; Phosphate ; Hydroxide ; Wastewater ; Langmuir ; Ion exchange ; Cationic polymerization ; Phosphorus Layered Double Hydroxides Synthesis and Applications ; Phosphorus and nutrient management ; Adsorption and biosorption for pollutant removal