jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Raissa José de França Carvalho | Maria Carolina Gonçalves Dias | Celso Ricardo Fernandes Carvalho | Marcelo Rodrigues Borba | Carlos Frederico Sparapan Marques | Carlos Walter Sobrado | Carolina Bortolozzo Graciolli Facanali
Source: Journal of Coloproctology (article, 2024-12-01)
Field: Chemistry — Physical and Theoretical Chemistry

IS THERE A BENEFIT TO USING INDIRECT CALORIMETRY IN OUTPATIENT PATIENTS WITH CROHN'S DISEASE? Medicine ; Crohn's disease ; Disease ; Internal medicine thermodynamics and calorimetric analyses ; Inflammatory Bowel Disease ; Viral gastroenteritis research and epidemiology
Authors: И.Л. Бухарина | Nadezhda Islamova | A.A. Isupova
Source:  (article, 2024-12-11)
Field: Chemistry — Analytical Chemistry

STUDY OF THE REACTION OF FUSARIUM EQUISETI AND CYLINDROCARPON MAGNUSIANUM TO DIFFERENT CONCENTRATIONS OF OIL AND HEAVY METALS IN THE MEDIUM Heavy metals ; Fusarium ; Chemistry ; Environmental science ; Environmental chemistry ; Horticulture ; Biology Spectroscopy and Chemometric Analyses
Authors: Chiara Gigante | Stefano Poli | Massimiliano Valle | Simone Tumiati | Fabio Giacometti | Lorenzo Cavalli | Maria Teresa Arnoldi | M. Boiocchi | Yasir Akram | Michela Cantù
Source: BIO Web of Conferences (article, 2024-01-01)
Field: Materials Science — Ceramics and Composites

Correlation between manufacturing parameters, properties and microstructure in 2D-C/SiC composites observed that prolonged oxidation at relatively low temperatures has a major impact on the mechanical properties of the composite in use. Microstructure ; Composite material ; Materials science ; Correlation ; Mathematics ; Geometry Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties ; Additive Manufacturing and 3D Printing Technologies
Authors: Elizabeth M. Diessner | Loring J. Thomas | Carter T. Butts
Source: Journal of Chemical Theory and Computation (article, 2024-09-11)
Field: Materials Science — Biomaterials

Production of Distinct Fibrillar, Oligomeric, and Other Aggregation States from Network Models of Multibody Interaction Protein aggregation can produce a wide range of states, ranging from fibrillar structures and oligomers to unstructured and semistructured gel phases. Recent work has shown that many of these states can be recapitulated by relatively simple, topological models specified in terms of multibody interaction energies, providing a direct connection between aggregate intermolecular forces and aggregation products. Here, we examine a low-dimensional network Hamiltonian model (NHM) based on four basic multibody interactions found in any aggregate system. We characterize the phase behavior of this NHM family, showing that fibrils arise from a balance between elongation-inducing and contact-inhibiting forces. Complex oligomers (including annular oligomers resembling those thought to be toxic species in Alzheimer's disease) also form distinct phases in this regime, controlled in part by closure-inducing forces. We show that phase structure is largely independent of system size, and provide evidence of a rich structure of minor oligomeric phases that can arise from appropriate conditions. We characterize the phase behavior of this NHM family, demonstrating the range of ordered and disordered aggregation states possible with this set of interactions. As we show, fibrils arise from a balance between elongation-inducing and contact-inhibiting forces, existing in a regime bounded by gel-like and disaggregated phases; complex oligomers (including annular oligomers resembling those thought to be toxic species in Alzheimer's disease) also form distinct phases in this regime, controlled in part by closure-inducing forces. We show that phase structure is largely independent of system size, allowing generalization to macroscopic systems, and provide evidence of a rich structure of minor oligomeric phases that can arise from appropriate conditions. Computer science ; Production (economics) ; Multibody system ; Chemistry ; Physics ; Classical mechanics ; Economics biodegradable polymer synthesis and properties ; Cellular Mechanics and Interactions ; Point processes and geometric inequalities
Authors: Rahul Rao
Source: MRS Bulletin (article, 2024-09-25)
Field: Materials Science — Materials Chemistry

Single-crystal WS2 ribbon arrays with controlled polarity synthesized Ribbon ; Materials science ; Polarity (international relations) ; Nanotechnology ; Optoelectronics ; Composite material ; Chemistry MXene and MAX Phase Materials ; 2D Materials and Applications ; Energy Harvesting in Wireless Networks
Authors: Khokha Mouhoubi | Fatiha Brahmi | Lila Boulekbache‐Makhlouf | Siham Ayouaz | Amina Abbou | Khodir Madani | Inmaculada Mateos‐Aparicio | Alejandra García‐Alonso
Source: Applied Sciences (article, 2024-10-05)
Field: Chemistry — Analytical Chemistry

Effect of Pre-Treatment, Treatment, and Extraction Technologies on the Bioactive Substances of Coriander Herbs and spices, with their wealth of bioactive compounds, are widely used in food, medicine, and cosmetics. Among them, coriander (Coriandrum sativum L.) is particularly valued for its medicinal and culinary properties. Growing consumer and industrial interest in natural products has led to the development of modern, environmentally friendly extraction techniques designed to improve the yield and quality of extracts while reducing time, energy, and solvent consumption. These processes make it possible to obtain optimal quantities of active compounds, thereby meeting the growing demand for plant-based products. After showing evidence of coriander’s health benefits, this review summarizes research findings on the impact of some treatments and pretreatments on its phytochemical composition. After that, it summarizes different aspects of the use of conventional and non-conventional extraction techniques for coriander’s bioactive constituents, mainly polyphenols and crude and essential oils (EO). Among these methods, microwave-assisted extraction (MAE/MAHD) emerges as one of the most efficient methods, offering higher yields, better-quality extracts, and a significant reduction in energy costs. Traditional medicine ; Extraction (chemistry) ; Chemistry ; Medicine ; Chromatography Spectroscopy and Chemometric Analyses
Authors: Bowen Shen | Leena R. Pade | Péter Nemes
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-02-16)
Field: Chemistry — Spectroscopy

The 15-min (Sub)Cellular Proteome P.N. and B.S. designed the study. L.R.P. collected the <i>X. laevis</i> cell aspirates. B.S. prepared and measured the samples. B.S. and P.N. analyzed the data and interpreted the results. P.N. and B.S. wrote the manuscript. All the authors commented on the manuscript. Proteome ; Xenopus ; Mass spectrometry ; Chemistry ; Tandem mass spectrometry ; Cell ; Proteomics ; Computational biology ; Biology ; Chromatography ; Biochemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Microfluidic and Capillary Electrophoresis Applications
Authors: Nozimjon Kabulov
Source: Himičeskaâ tehnologiâ. Kontrolʹ i upravlenie/Chemical Technology. Control and Management (article, 2024-02-29)
Field: Chemistry — Analytical Chemistry

A NEURAL NETWORK MODEL FOR MONITORING AND FORECASTING THE PROCESS OF STORING OILSEEDS The paper presents the results of research on the control, forecasting and management of the storage process of oilseeds. Vegetable oil production and energy consumption are two important factors of oilseed storage systems. The first ones should meet the needs of the population quantitatively and qualitatively. As a result, in order to properly control these two important aspects, it is necessary to maintain an appropriate microclimatic environment using a computational decision support system (DSS) that is able to adapt to changes in environmental characteristics. The multilayer perceptron neural network (MLP-NN) was developed to simulate the temperature and relative humidity profiles of the environment inside the storage. A specific NN uses Levenberg–Marquardt back propagation as a training algorithm; the input variables are external temperature and relative humidity, solar radiation, as well as internal temperature and relative humidity of the medium. The maximum errors in the calculations of temperature and relative humidity are 0.877 ℃ and 2.838%, respectively, while the determination coefficients are 0.999 for both parameters. A model with a low maximum error in forecasts will allow DSS to send appropriate control commands to the electrical drives of the storage to maintain internal conditions at the desired level for storage with the lowest possible energy consumption. Artificial neural network ; Process (computing) ; Computer science ; Artificial intelligence Spectroscopy and Chemometric Analyses
Authors: Ralph Reilly | Tahar Kechadi | Yu. А. Kuznetsov | É. G. Timoshenko | Kenneth A. Dawson
Source: arXiv (Cornell University) (preprint, 2024-07-16)
Field: Materials Science — Materials Chemistry

Using recurrent neural networks to predict aspects of 3-D structure of\n folded copolymer sequences The neural network techniques are developed for artificial sequences based on\napproximate models of proteins. We only encode the hydrophobicity of the amino\nacid side chains without attempting to model the secondary structure. We use\nour approach to obtain a large set of sequences with known 3-D structures for\ntraining the neural network. By employing recurrent neural networks we describe\na way to augment a neural network to deal with sequences of realistic length\nand long-distant interactions between the sequence regions.\n Copolymer ; Artificial neural network ; Computer science ; Recurrent neural network ; Artificial intelligence ; Materials science ; Polymer Machine Learning in Materials Science
Authors: Luiz Felipe Morillas Brunetto | Carise Elisane Schmidt | Alexandre Dalla'Rosa
Source: Revista Tecnia (article, 2024-03-01)
Field: Chemistry — Analytical Chemistry

Seleção de hiperparâmetros para uma rede Multi-Layer Perceptron aplicada na predição do preço da soja O agronegócio brasileiro representa uma parcela significativa do Produto Interno Bruto (PIB), além de ser um setor de produção essencial, por garantir o fornecimento de alimentos para a população. Contudo, o principal desafio enfrentado pelo setor é manter a rentabilidade, ante um cenário de alta dos custos de insumos. Diante disso, destaca-se a importância de avaliar ferramentas que possam auxiliar na tomada de decisão, com foco no aumento da rentabilidade. A proposta deste trabalho foi selecionar um conjunto de hiperparâmetros para uma rede neural Multi-Layer Perceptron (MLP), por meio da análise do Erro Médio Quadrático (EMQ), visando a sua utilização na predição do preço da soja. Para isso, um histórico de dados de preço do grão e da taxa de câmbio do dólar (2006 - 2022) foram utilizados como entrada do modelo matemático. Fazendo uso de simulações computacionais, o preço predito da soja foi avaliado, visando identificar o conjunto de hiperparâmetros que gera o menor EMQ. Entre as configurações avaliadas, o menor EMQ encontrado quando o modelo foi testado na série histórica teve valor igual a 1,2936. Esse resultado mostra que a configuração de hiperparâmetros selecionada é capaz de realizar a previsão do preço futuro da soja, acompanhando a tendência de preços do grão, no período em que ele foi avaliado. Molecular biology ; Biology Spectroscopy and Chemometric Analyses
Authors: Karolina Volodzkaitė
Source: Lithuanian University of Health Sciences (article, 2024-05-04)
Field: Chemistry — Physical and Theoretical Chemistry

The McKissock's method Scientific research supervisor: Dr.. Tautrimas Aštrauskas Identification (biology) ; Work (physics) ; Set (abstract data type) ; Process (computing) ; Point (geometry) History and advancements in chemistry ; Advanced Mathematical Theories and Applications ; Education, Leadership, and Health Research
Authors: Sergio Augusto de Almeida Christoforo | Jonathan dos Santos Cruz | Renato da Rocha Lopes | Mateus Giesbrecht
Source: Congresso Brasileiro de Automática (article, 2024-10-18)
Field: Materials Science — Materials Chemistry

Partial Discharge Waveform Denoising in High Voltage Current Transformers Using Convolutional Autoencoder This paper presents an analysis of partial discharge (PD) signals in high voltage current transformers (HVCTs). Our approach centers on using a convolutional neural network with an autoencoder architecture to filter out electrical noise, enabling assessment of the characteristic waveform shapes of PDs. The denoising convolutional autoencoder (DCAE) was trained using an extensive database composed of synthetic PD signals, with several characteristic waveforms, noise levels, quantities, and positions of occurrences. Furthermore, the DCAE was tested using real data collected from HVCTs during commissioning in electrical substations from various regions of Brazil. A comparative analysis between the DCAE and wavelet denoising methods is conducted. The results indicate that the proposed DCAE neural-network effectively denoises both synthetic and real signals, preserving the impulsive characteristics of PDs. Autoencoder ; Noise reduction ; Waveform ; Wavelet ; Pattern recognition (psychology) ; Transformer ; Convolutional neural network ; Partial discharge High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Aerosol Filtration and Electrostatic Precipitation
Authors: Kyle R. Dorman | Rishabh Kothari | Nathan Bianco | Matias Kalaswad | Catherine Sobczak | Saaketh Desai | Joyce Custer | Sadhvikas Addamane | Manish Jain | Alejandro Hinojos | Frank W. DelRio‬ | Brad Boyce | Rémi Dingreville | David P. Adams
Source:  (article, 2024-05-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Combinatorial synthesis and high-throughput characterization of Ni-Pt and Cu-Ag thin films fabricated by confocal magnetron sputter deposition Sputter deposition ; Materials science ; Characterization (materials science) ; Thin film ; Deposition (geology) ; Throughput ; Optoelectronics ; Sputtering ; Cavity magnetron ; Combinatorial synthesis ; Nanotechnology ; Computer science ; Chemistry ; Telecommunications ; Wireless Copper Interconnects and Reliability ; nanoparticles nucleation surface interactions ; Surface and Thin Film Phenomena
Authors: Thomas Van Laethem | Priyanka Kumari | Bruno Boulanger | Philippe Hubert | Marianne Fillet | Pierre‐Yves Sacré | Cédric Hubert
Source: Journal of Pharmaceutical and Biomedical Analysis (article, 2024-07-20)
Field: Chemistry — Spectroscopy

Uncertainty management for In Silico screening of reversed-phase liquid chromatography methods for small compounds Chemistry ; In silico ; Multiple-criteria decision analysis ; Process (computing) ; Bayesian probability ; Selection (genetic algorithm) ; Phase (matter) ; Chromatography ; Exploit ; Biochemical engineering ; Computer science ; Machine learning ; Artificial intelligence ; Operations research Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Spectroscopy and Chemometric Analyses
Authors: My Hanh Nguyen Thi | Nguyen Le Thai
Source: Indonesian Journal of Electrical Engineering and Informatics (IJEEI) (article, 2024-12-17)
Field: Materials Science — Materials Chemistry

The Use of Green-Phosphor LuAG:Ce-Al2O3 for HighLuminosity Light Emitting Diode Packages The LuAG:Ce-Al2O3 (LAGCA) green phosphor ceramic (GPC) is proposed for high-power white light emitting diodes (LEDs) in this paper. The luminescent properties of the GPC are examined with proper characterizing tools and under laser excitation. Then, LAGCA ceramic layer of 0.6 thickness is applied to fabricate the white LED. The results show LAGCA GPC is promising for high-power LED applications. The phosphor ceramic presents high thermostability and quantum efficacy and intense green emission peaking at nearly 550 nm. In the LED package, the amount of LAGCA in the composite layer is varied. The increasing dosage of LAGCA gives enhancement to the lumen output of the LED. However, the correlated color temperature stability and chromatic rendition declines. Thus, further improvements in LAGCA ceramic need to be carried out in the future works. Besdies, with the intense green emission, the LAGCA ceramics can be combined with red luminescent materials to increase the color performance of the LED lighting. Phosphor ; Materials science ; Green-light ; Light-emitting diode ; Optoelectronics ; Diode ; Blue light Luminescence Properties of Advanced Materials
Authors: Alaa Abdulhady Jaber
Source: Faculty of 1000 Research Ltd (article, 2024-01-01)
Field: Materials Science — General Materials Science

Referee report. For: Controlled seeding of contact cracks in test pieces for the evaluation and validation of non-destructive testing systems [version 1; peer review: 2 approved with reservations] Seeding ; Test (biology) ; System testing ; Reliability (semiconductor) ; Materials testing Engineering and Material Science Research ; Mechanical Failure Analysis and Simulation ; Adhesion, Friction, and Surface Interactions
Authors: Sambandh Bhusan Dhal
Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (article, 2024-11-25)
Field: Chemistry — Analytical Chemistry

Optimizing Biofuel Production: Integrating NIR Imaging and Machine Learning for Corn Stover Characterization This talk with deals with NIR imaging and Machine Learning methods for characterization of corn stover. Corn stover ; Biofuel ; Production (economics) ; Characterization (materials science) ; Stover ; Pulp and paper industry ; Agricultural engineering ; Environmental science ; Agronomy ; Biotechnology ; Materials science ; Engineering ; Nanotechnology ; Economics ; Biology ; Crop Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Shashank Galla
Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (article, 2024-08-02)
Field: Materials Science — Materials Chemistry

Scalable Anomaly Detection in Batch Polishing Processes for Inertial Confinement Fusion Shells Polishing ; Anomaly detection ; Inertial confinement fusion ; Scalability ; Fusion ; Anomaly (physics) ; Inertial frame of reference ; Computer science ; Artificial intelligence ; Physics ; Engineering ; Mechanical engineering ; Database ; Plasma ; Classical mechanics ; Nuclear physics Fusion materials and technologies ; Archaeological Research and Protection
Authors: Song Yie Park | Yeong Jae Ah | Eun Ji Suh | Eun Bin Choi | Mi‐Ja Lee | Han Gyeol Lee | Woo Duck Seo | Yuna Kim | Seung-Yeob Song
Source: Korean Journal of Breeding Science (article, 2024-09-01)
Field: Chemistry — Analytical Chemistry

Metabolic Discrimination of Mungbean (<i>Vigna radiata</i> L.) Sprout Depending on Growth Time from Multivariate Analysis of FT-IR Spectroscopy Data Song Yie Park, Yeong Jae Ah, Eun Ji Suh, Eun Bin Choi, Mi Ja Lee, Han Gyeol Lee, Woo Duck Seo, Yu-Na Kim, and Seung-Yeob Song. Korean J. Breed. Sci. 2024;56:269-79. https://doi.org/10.9787/KJBS.2024.56.3.269 Radiata ; Vigna ; Bin ; Multivariate statistics ; Multivariate analysis ; Horticulture ; Biology ; Mathematics ; Statistics ; Algorithm Spectroscopy and Chemometric Analyses ; Agriculture, Soil, Plant Science ; Metabolomics and Mass Spectrometry Studies
Authors: Naga VS Raviteja Chappa | Pha Nguyen | Page D. Dobbs | Khoa Luu
Source: Research Square (preprint, 2024-03-19)
Field: Chemistry — Physical and Theoretical Chemistry

REACT: Recognize Every Action Everywhere All At Once Action (physics) ; Almost everywhere ; Computer science ; Business ; Mathematics ; Discrete mathematics ; Physics History and advancements in chemistry
Source: Journal of Food Chemistry and Nanotechnology (article, 2024-09-06)
Field: Chemistry — Analytical Chemistry

Comparison of Sigmoid Logarithm and Hyperbolic Tangent Functions in Modeling the Oxidation Parameters of Soybean Oil Containing Extract of Black Plum Peels Natural Antioxidant Toktam Mohammadi-Moghaddam, Mohaddeseh Kariminejad, Hamid Bakhshabadi, Elham Taghavi and Afsaneh Morshedi To predict the oxidation parameters of soybean oil (SBO), we utilized five levels of black plum peel extraction (BPPE) antioxidant concentration (0, 400, 800, 1200, and 2000 ppm) and four levels of oil storage time (0, 8, 16, and 24 days) under accelerated oxidation conditions (temperature 60 °C). Hyperbolic function ; Logarithm ; Sigmoid function ; Antioxidant ; Mathematics ; Tangent ; Logarithmic decrement ; Natural logarithm ; Mathematical analysis ; Chemistry ; Organic chemistry ; Physics ; Computer science ; Artificial intelligence ; Geometry ; Acoustics Spectroscopy and Chemometric Analyses
Authors: Daniel Toth | Bálint Dudás | Erika Balog | Maria A. Miteva
Source: Biophysical Journal (article, 2024-02-01)
Field: Chemistry — Spectroscopy

Substrate specificity of SULT1A1 and SULT1A3 elucidated by conformational dynamics Gene isoform ; Chemistry ; Substrate (aquarium) ; Enzyme ; Docking (animal) ; Biochemistry ; Dopamine ; Stereochemistry ; Biophysics ; Biology ; Gene ; Neuroscience Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Chemical Synthesis and Analysis
Authors: Pablo S. Cornaglia | Leandro M. Chinellato | Cristian D. Batista
Source: arXiv (Cornell University) (preprint, 2024-04-22)
Field: Materials Science — Materials Chemistry

Quasicrystalline chiral soliton lattices in a Fibonacci helimagnet We investigate the ground state magnetic configurations of a Fibonacci chain of classical spins with nearest-neighbor ferromagnetic and monoaxial Dzyaloshinskii-Moriya exchange interactions. Our analysis reveals a diverse array of magnetic textures induced by an external magnetic field perpendicular to the Dzyaloshinskii-Moriya vector. These textures exhibit a spectrum ranging from a quasi-fully polarized non-collinear state under high magnetic fields, capable of maintaining metastable chiral soliton topological defects, to a variety of quasicrystalline chiral soliton lattices below a critical field $H_c$. For a range of magnetic fields below $H_c$, the ground state spin textures result from the interplay between an effective quasiperiodic potential influencing the solitons and their repulsive interactions. At lower magnetic fields, the system experiences a commensurate-incommensurate transition, signified by the appearance of discommensurations in the quasicrystalline soliton lattice. In the absence of an external magnetic field, the ground state assumes a helical configuration with a quasiperiodic pitch angle. Fibonacci number ; Quasicrystal ; Soliton ; Condensed matter physics ; Physics ; Materials science ; Quantum mechanics ; Mathematics ; Combinatorics ; Nonlinear system Quasicrystal Structures and Properties ; Algebraic structures and combinatorial models ; Nonlinear Waves and Solitons