jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lin Wang | Haonan Zhang | Qi Jia | Wenyan Li | Chenguang Yang | Lijuan Ma | Ming Li | Ying Lü | Hongtao Zhu | Ping Zhu
Source: Proceedings of the National Academy of Sciences (article, 2025-03-18)
Field: Materials Science — Materials Chemistry

Cryo-EM structures reveal the acetylation process of piccolo NuA4 NuA4 is the only essential acetyltransferase in yeast that can catalyze the acetylation of the histones H2A, H2A.Z, and H4, thereby affecting gene transcription. However, the acetylation process of NuA4, such as how NuA4 acetylates H4 and H2A.Z differently, remains largely elusive. Here, using cryoelectron microscopy (cryo-EM) single particle analysis, we present seven cryo-EM structures of piccolo NuA4 (pNuA4) in complex with wild-type H2A.Z or H2A.Z-mutant-containing nucleosomes in the absence or presence of acetyl coenzyme A (Ac-CoA). We revealed that, in the absence of Ac-CoA, pNuA4 adopts multiple conformations to search for its substrates. After adding Ac-CoA, the single-molecule Förster resonance energy transfer (smFRET) and cryo-EM data indicated that pNuA4 prefers to bind H4 and undergoes a dynamic conformational change to complete the acetylation. We also obtained previously unseen structures in states associated with the acetylation of H2A.Z. These cryo-EM structures and smFRET results suggest a complex acetylation process on H4 and H2A.Z by pNuA4. The results provide a comprehensive picture of the mechanism by which pNuA4 acetylates its substrates within an H2A.Z-containing nucleosome. Acetylation ; Nucleosome ; Acetyltransferase ; Histone H4 ; Histone ; Biophysics ; Biology ; Histone acetyltransferase ; Biochemistry ; Gene Enzyme Structure and Function ; RNA modifications and cancer ; RNA and protein synthesis mechanisms
Authors: Yule Hao | Jiawen Qi | Xinggui Huang | Chenhao Liu | Yi Liu
Source: Frontiers in Pharmacology (review, 2025-01-29)
Field: Chemistry — Organic Chemistry

Euodiae Fructus: a review of botany, application, processing, phytochemistry, quality control, pharmacology, and toxicology Euodiae Fructus (EF) is the dried and nearly ripe fruit of <i>Euodia rutaecarpa</i>, first recorded in <i>Shen Nong's Herbal Classic</i>. EF is a versatile Traditional Chinese Medicine (TCM) known for the effects of dispelling colds and alleviating pain, suppressing adverse qi to relieve vomiting, and boosting yang to mitigate diarrhea. However, it should be noted that EF possesses mild toxicity. In TCM prescriptions, EF is employed to treat various ailments, including abdominal pain, diarrhea, chronic non-atrophic gastritis, irritable bowel syndrome, and primary dysmenorrhea. This review collected the literature published before September 2024 on EF. An exhaustive analysis of EF literature was conducted utilizing multiple sources, namely classic TCM books and various scientific databases like Web of Science, PubMed, Elsevier, ACS, ResearchGate, Google Scholar, and Chinese National Knowledge Infrastructure. So far, more than 300 metabolites have been extracted and identified from EF, exhibiting various pharmacological effects, such as cardiovascular protection, gastrointestinal protection, neuroprotection, anti-inflammation, analgesia, anti-tumor, glucose and lipid metabolism regulation, etc. It also exhibits diverse toxicological properties and poses specific toxic risks to the liver, heart, and kidney. Nonetheless, research is scarce regarding the toxicology of EF, especially on its cardiotoxicity and nephrotoxicity. Further in-depth research is necessary to explore the mechanisms underlying EF's pharmacological and toxicological mechanisms and to develop strategies for quality control and toxicity mitigation. The toxicity of EF can be reduced by processing, but this aspect is rarely discussed, and the quality control needs to be further standardized. Evodiamine, rutaecarpine, and limonin are the effective metabolites of EF and are also one of the causes of EF toxicity. The pharmacological effects of evodiamine and rutaecarpine have been intensely studied, but there are few studies on limonin and other metabolites of EF. Therefore, this paper focuses on the botanical characteristics, traditional applications, processing methods, phytochemistry, quality control, pharmacology, and toxicology of EF. We hope this paper provides a theoretical basis for the future high-value and high-connotation development of EF. Medicine ; Phytochemistry ; Pharmacology ; Rutaecarpine ; Traditional medicine ; Traditional Chinese medicine ; Diarrhea ; Ginseng ; Cardiotoxicity ; Toxicity ; Alternative medicine ; Internal medicine Quinazolinone synthesis and applications ; Synthesis and Biological Evaluation ; Plant-derived Lignans Synthesis and Bioactivity
Authors: Ranjit Singh | Sambit Satpathy | Dhirendra Kumar Shukla | Ravi Pratap Singh | Rajeev Trehan | J. P. Panda | Biplab Bhattacharjee
Source: Scientific Reports (article, 2025-08-02)
Field: Materials Science — Materials Chemistry

EDM-based analysis of Fe-based shape memory alloys using Cu-W electrodes with multiple output optimization and microstructural validation Shape Memory Alloys (SMAs) are pivotal in diverse industrial applications due to their exceptional properties, including actuation, biocompatibility, and adaptability in aerospace, biomedical, and military domains. However, their complex machinability often leads to high costs and suboptimal surface quality when processed using traditional methods. Using Response Surface Methodology (RSM) with a Central Composite Design (CCD), this study evaluated the effects of input parameters, including pulse on time (T<sub>on</sub>), pulse off time (T<sub>off</sub>), peak current (Ip), and gap voltage (GV), on material wear responses during Electrical Discharge Machining (EDM). Fe-based Shape Memory Alloys (SMAs) were machined using a Cu-tungsten electrode to investigate the wear characteristics of both workpieces and tool electrodes. Results revealed that Workpiece Material Removal Rate (WOW) ranged from 11.30 to 65.17 mm³/min, and Tool Wear Rate (WOTE) varied from 0.0062 to 0.01127 g/min. Scanning Electron Microscopy (SEM) of machined surfaces showcased craters, micro-cracks, and recast layers, elucidating the correlation between process parameters and surface integrity. Multi-objective optimization using the desirability approach identified optimal conditions for balancing machining efficiency and surface quality. This research provides a comprehensive understanding of the EDM process for Fe-based SMAs, paving the way for improved machinability and expanded industrial applications. Electrode ; Materials science ; Shape-memory alloy ; Computer science ; Biomedical engineering ; Metallurgy ; Chemistry ; Medicine Shape Memory Alloy Transformations ; Advanced Machining and Optimization Techniques ; Corrosion Behavior and Inhibition
Authors: Yufei Li | Qinghe Zhao | Zifang Zhang | Jinlong Liu | Junlong Fang
Source: Agriculture (article, 2025-05-07)
Field: Chemistry — Analytical Chemistry

Detection of Seed Potato Sprouts Based on Improved YOLOv8 Algorithm Seed potatoes without sprouts usually need to be manually selected in mechanized production, which has been the bottleneck of efficiency. A fast and efficient object recognition algorithm is required for the additional removal process to identify unqualified seed potatoes. In this paper, a lightweight deep learning algorithm, YOLOv8_EBG, is proposed to both improve the detection performance and reduce the model parameters. The ECA attention mechanism was introduced in the backbone and neck of the model to more accurately extract and fuse sprouting features. To further reduce the model parameters, Ghost convolution and C3ghost were introduced to replace the normal convolution and C2f blocks in vanilla YOLOv8n. In addition, a bi-directional feature pyramid network is integrated in the neck part for multi-scale feature fusion to enhance the detection accuracy. The experimental results from an isolated test dataset show that the proposed algorithm performs better in detecting sprouts under natural light conditions, achieving an mAP0.5 of 95.7% and 91.9% AP for bud recognition. Compared to the YOLOv8n model, the improved model showed a 6.5% increase in mAP0.5, a 12.9% increase in AP0.5 for bud recognition, and a 5.6% decrease in the number of parameters. Additionally, the improved algorithm was applied and tested on mechanized sorting equipment, and the accuracy of seed potato detection was as high as 92.5%, which was sufficient to identify and select sprouted potatoes, an indispensable step since only sprouted potatoes can be used as seed potatoes. The results of the study can provide technical support for subsequent potato planting intelligence. Algorithm ; Mathematics ; Horticulture ; Biology ; Computer science Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Kailu Liu | Wanying Qu | Haoyang Zeng
Source: Buildings (article, 2025-08-06)
Field: Chemistry — Spectroscopy

Multi-Objective Optimization Design of Foamed Cement Mix Proportion Based on Response Surface Methodology Foam cement, as a building insulation material, encounters a major problem in practical application, which is the difficulty in achieving a balance between its strength and insulation performance. To achieve multi-objective optimization of foamed cement mix design, this study first determined the optimal ranges of nano-silica aerogel (NSA), foaming agent, and polypropylene (PP) fiber dosage through single-factor experiments. Then, response surface methodology (RSM) was employed to construct a quadratic polynomial regression model, systematically investigating the influence of different NSA contents, foaming agent contents, and PP fibers contents on the thermal conductivity and compressive strength of foamed cement. Finally, the optimal mix ratio was further predicted and experimentally validated. The results demonstrate that the regression model developed using RSM exhibits high accuracy and reliability. The correlation coefficients R2 of the regression models established by the response surface method are 0.9756 and 0.9684, respectively, indicating good prediction accuracy. The optimized mix ratio was determined as follows: NSA content, 9.548%; foaming agent content, 0.533%; and PP fiber content, 0.1%. Under this mix, the model predicted a thermal conductivity of 0.123 W/(m·K) and a 28-day compressive strength of 1.081 MPa. Experimental verification confirmed that the errors between predicted and measured values for all performance indicators were within 5%, demonstrating the high reliability of the predictive model. This study provides support for the practical application of foam cement as a thermal insulation material in construction projects and offers guidance for optimizing its mixture composition. Response surface methodology ; Cement ; Materials science ; Structural engineering ; Composite material ; Engineering ; Computer science Aerogels and thermal insulation ; Infrastructure Maintenance and Monitoring
Authors: Jack D. Simpson | Lisa Thomson | Christopher M. Woodley | C Wallace | B. Dietrich | Alex S. Loch | Dave J. Adams | Neil G. Berry
Source: Advanced Materials (article, 2025-01-09)
Field: Materials Science — Biomaterials

Predicting the Mechanical Properties of Supramolecular Gels The prediction of gelation is an important target, yet current models do not predict any post-gel properties. Gels can be formed through the self-assembly of many molecules, but close analogs often do not form gels. There has been success using a number of computational approaches to understand and predict gelation from molecular structures. However, these approaches focus on whether or not a gel will form, not on the properties of the resulting gels. Critically, it is the properties of the gels that are important for a specific application, not simply whether a gel will be formed. Supramolecular gels are often kinetically trapped, meaning that predicting gel properties is inherently a difficult challenge. Here, the first successful a priori prediction of gel properties for such self-assembled, supramolecular systems is reported. Supramolecular chemistry ; Materials science ; Nanotechnology ; Molecule ; Organic chemistry ; Chemistry Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Bone and Dental Protein Studies
Authors: Batol Masruri | Ebrahim Taban | Ali Khavanin | Keith Attenborough
Source: Buildings (article, 2025-10-05)
Field: Materials Science — Polymers and Plastics

Sound Absorption and Thermal Insulation by Polyurethane Foams Reinforced with Bio-Based Lignocellulosic Fillers: Data and Modeling The acoustic, thermal, and mechanical performances of sawdust-reinforced polyurethane (PU) foam are investigated for different thicknesses and varying mesh sizes. Acoustic properties are explored using a combination of impedance tube testing and mathematical modeling with the Johnson–Champoux–Allard–Lafarge (JCAL) model, a simplified JCAL model and a model of non-uniform cylindrical pores with a log-normal radius distribution (NUPSD). Thermal Insulation and mechanical properties are determined by measuring the effective thermal conductivity (Keff) and by tensile strength tests, respectively. Compared with pure PU foam, the presence of sawdust matches noise reduction coefficients (NRC) and increases sound absorption averages (SAA) by nearly 10%. Increasing thickness and width of backing air gap have the usual effects of improving low- and mid-frequency absorption and shifting resonance peaks toward lower frequencies. As well as superior acoustic performance, samples with Mesh 16 sawdust reinforcement provide both useful insulation (Keff = 0.044 W/mK) and tensile strength (~0.06 MPa), confirming their multifunctionality. Although the JCAL model provides reasonable fits to the sound absorption data, some of the fitted parameter values are unphysical. Predictions of the NUPSD model are relatively poor but improve with sample thickness and after fiber addition. Noise reduction coefficient ; Thermal conductivity ; Ultimate tensile strength ; Sawdust ; Polyurethane ; RADIUS ; Fiber ; Soundproofing Natural Fiber Reinforced Composites ; Acoustic Wave Phenomena Research ; Polymer composites and self-healing
Authors: Sarah Mohammed Hailan | Zuzana Nógellová | Anton Popelka | Markéta Ilčíková | Miroslav Mrlík | Antonín Minařík | Filip Mikulka | Gordon McKay | Igor Krupa
Source: Emergent Materials (article, 2025-02-04)
Field: Materials Science — Surfaces, Coatings and Films

Utilization of polyethylene waste for designing foamy oil sorbents Abstract Recycling low-density polyethylene (LDPE) in its original form presents several challenges, including limited interest from converters, poor market demand for recycled products, higher sorting and cleaning costs, and reduced quality in the final products. It happens because recycled LDPE often exhibits lower mechanical strength and diminished aesthetic appeal than its virgin counterpart, making it rarely suitable for its original purpose, especially in packaging. Therefore, new applications for LDPE recyclates are needed to overcome these barriers and extend the material’s lifecycle. One such solution involves converting LDPE waste into foamy sorbents for water purification. The presented study investigated two strategies for recycling LDPE waste by exploring the potential of the modified waste to remove free oil spills. The first approach involves preparing and characterizing robust, mechanically stable foams using recycled waste from LDPE packaging. The process is based on parallel foaming and crosslinking of LDPE by peroxides. The final foamy structure (Foam 1) possesses around 75 vol% of pores (46 vol% open pores) and rapidly absorbs various organic liquids quickly (hexane, diesel oil, crude oil) in multiple cycles. The second target deals with the screening, testing, and characterizing of LDPE-based foams that were initially used for various packaging and deposited as waste to explore their potential free oil sorbents. The foam that was used in this study has a significantly porous structure, having 96 vol% of pores and more than 89 vol% open pores (Foam 2). Whereas the sorption capacity of Foam 1 was 4–5 g/g, depending on the type of oil, Foam 2 absorbed those oils in the range of 8–12 g/g. The Foam 1 showed significantly better stability over multiple cycles and better mechanical performance. Graphical abstract Waste management ; Polyethylene ; Environmental science ; Materials science ; Petroleum engineering ; Engineering ; Composite material Surface Modification and Superhydrophobicity ; Enhanced Oil Recovery Techniques ; Petroleum Processing and Analysis
Authors: Ziting Yuan | Kensuke Suzuki | Yota Yamamoto | Tomoyuki Yajima | Yoshiaki Kawajiri
Source: Processes (article, 2025-01-04)
Field: Chemistry — Spectroscopy

Estimation and Uncertainty Quantification of Solvent Strength Parameters in Gradient Elution of Chromatography Using Sequential Monte Carlo Method Gradient elution is a common method for the separation of complex components in chromatography. Strength-dependent models that describe the variation in chromatographic parameters, considering equilibrium and mass transfer under different solution strengths, are essential for the design and optimization of gradient elution. In this study, we proposed several hypothetical models based on experimental data obtained under varying mobile phase ratios in the water–methanol system. The uncertainties in the parameters were quantified using the sequential Monte Carlo (SMC) method with Bayesian inference. Finally, we performed model selection to determine the most appropriate model, utilizing multiple sources of information criteria. Monte Carlo method ; Elution ; Chromatography ; Bayesian inference ; Inference ; Markov chain Monte Carlo ; Chemistry ; Computer science ; Biological system ; Bayesian probability ; Mathematics ; Statistics ; Artificial intelligence Analytical Chemistry and Chromatography ; Crystallization and Solubility Studies ; Field-Flow Fractionation Techniques
Authors: Jiangtao Ji | Xinyi Lu | Hao Ma | Xin Jin | Shijie Jiang | Hongwei Cui | Xiaohong Lu | Ying Yang
Source: Frontiers in Plant Science (article, 2025-06-02)
Field: Chemistry — Analytical Chemistry

Estimation of plant leaf water content based on spectroscopy These results indicate that the model has some generalization ability and can accurately estimate the water content of leaves of woody plants in the same family, with some performance degradation across different growth forms. The study results achieved accurate estimation of leaf water content for three types of plants and also provided a reference for establishing plant leaf water content estimation models with generalization ability. Water content ; Estimation ; Content (measure theory) ; Environmental science ; Agronomy ; Mathematics ; Botany ; Statistics ; Biological system ; Biology ; Geology ; Engineering Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Water Quality Monitoring and Analysis
Authors: Tiandou Hu | Qingshen Sun
Source: Journal of Food Processing and Preservation (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Research Progress on Detection of Apple Watercore Based on Visible and Near‐Infrared Spectroscopy Apples are one of the most widely produced fruits globally, recognized for their crisp texture, juiciness, and nutritional value. Apples affected by watercore are particularly favored by consumers for their high sugar content and unique flavor. However, during prolonged storage, watercore apples often experience metabolic disorders, making it necessary to develop a rapid, high‐throughput, and effective nondestructive testing method to monitor this condition. Near‐infrared (NIR) spectroscopy has gained extensive application in apple quality assessment due to its speed, low cost, and ability to measure multiple indices simultaneously. This paper reviews physiological diseases affecting apples, particularly watercore, and discusses various nondestructive testing methods. It emphasizes the current application of visible/near‐infrared (Vis/NIR) spectroscopy in detecting watercore in apples. Additionally, this paper addresses the challenges and prospects of using Vis/NIR spectroscopy for watercore detection. This review is aimed at providing insights into more effective ways to manage physiological changes in apples, such as watercore. Infrared ; Infrared spectroscopy ; Spectroscopy ; Near-infrared spectroscopy ; Chemistry ; Optics ; Physics ; Organic chemistry ; Astronomy Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: David Dominguez-Santos | P. Muñoz | J. O. Morales-Ferreiro | Camila Sanhueza Acuña | D.E. Díaz-Droguett | Elvira Villaro
Source: International Journal of Concrete Structures and Materials (article, 2025-06-24)
Field: Materials Science — Materials Chemistry

Reinforced Concrete with Graphene Oxide: Techno-Economic Feasibility for Reduced Cement Usage and CO2 Emissions Concrete, a key material in modern infrastructure, significantly contributes to global CO2 emissions, urging innovative approaches for its environmental impact mitigation. This study evaluates the techno-economic feasibility of incorporating graphene oxide (GO) into concrete formulations to enhance mechanical properties and reduce cement usage, thereby mitigating CO2 emissions. The methodology involved synthesising GO using a modified Hummers’ method, ensuring uniform dispersion in concrete matrices. Concrete samples with varying GO contents underwent mechanical strength testing, as well as microstructural analysis including SEM, XPS, and Raman spectroscopy. Results led to simulations of the mechanical response of low- and medium-rise buildings subjected to seismic forces. Besides, economic assessments were performed by considering the overall cost of materials (GO and concrete) and the savings from CO2 emissions, based on different scenarios for both GO and CO2 prices. The optimal formulation uses 0.1% GO by weight of cement, improving compressive strength by up to 17.92% and flexural strength by up to 74.78%. Structural models indicate that GO can reduce the weight of structural elements by 8–24%, leading to lower seismic forces and easier compliance with seismic-resistant standards. Economic analysis reveals that low-rise buildings can benefit from GO-enhanced concrete if the GO price is between €50 and €80 per kg, depending on CO2 credit prices ranging from €60 to €200 per tonne. For taller buildings, the economic feasibility is more restrictive; GO prices must be between €50 and €70 per kg with CO2 credit prices starting at €100 per tonne to justify the use of 0.1% GO. Structural material ; Graphene ; Cement ; Oxide ; Materials science ; Waste management ; Metallurgy ; Nanotechnology ; Engineering Graphene research and applications ; Graphene and Nanomaterials Applications ; Nanotechnology research and applications