jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: M. Reddy | Sarthak Nayak
Source: International Journal of Engineering Applied Sciences and Technology (article, 2024-06-01)
Field: Chemistry — Spectroscopy

A STUDY ON M100 (NGC 4321) This paper explores advanced imaging and analysis techniques in modern interferometry, emphasizing spectrometers, deconvolution methods, and the derivation of moment images and star formation rates (SFR). Spectrometers split the passband into narrow frequency ranges for simultaneous power measurements, enhancing sensitivity and uv coverage in continuum imaging through Multi-Frequency Synthesis (MFS). Spectral line observations yield three-dimensional data cubes, crucial for studying the gas content in astronomical objects. Deconvolution, particularly the CLEAN algorithm, iteratively refines images by removing sidelobes caused by incomplete uv sampling. The generation of moment 0 (intensity) and moment 1 (velocity) images facilitates the measurement of integrated flux densities and gas surface densities, with uncertainties derived from rms noise in line-free channels. Additionally, the paper examines the KennicuttSchmidt law, linking gas surface density to star formation rate surface density, providing insights into the processes driving star formation in galaxies. This comprehensive approach highlights the significance of precise imaging and robust analysis in understanding astronomical phenomena. Deconvolution ; Moment (physics) ; Physics ; Spectral density ; Passband ; Optics ; Star formation ; Astrophysics ; Scanner ; Spectrometer ; Imaging spectrometer ; Sampling (signal processing) ; Galaxy ; Computer science Spectroscopy and Laser Applications
Authors: О. А. Нуркенов | Anel Z. Mendibayeva | С. Д. Фазылов | Т. М. Сейлханов | С. К. Кабиева | E.M. Satbayeva | G.Zh. Karipova | Ardak K. Syzdykov
Source: Chemical Journal of Kazakhstan (article, 2024-03-15)
Field: Chemistry — Organic Chemistry

Synthesis of quaternary ammonium saltsisonicotinic and nicotinic hydrazones acids and their anti-inflammatory activity Currently, the number of infections caused by strains of bacteria that are not sensitive to antibiotics and antiseptics is growing worldwide. A similar increase in bacterial resistance is observed for both nosocomial infections and community-acquired human-to-human infections. An important task for chemists and pharmacologists is the synthesis of new compounds and the establishment of a structure-bioactivity relationship. The purpose of this work is to study the effect of the structure of quaternary ammonium derivatives of hydrazones of isonicotinic and nicotinic acids on the manifestation of their anti-inflammatory properties. Results and discussion. The alkylation of nicotinic acid hydrazones produced their new quaternary ammonium salts (43.7-70.7%). The methodology for the synthesis of quaternary ammonium compounds of hydrazones included obtaining a variety of structures by introducing one or two fluorine and bromine-containing fragments into their structure. The structure of compounds was confirmed by 1H, 13C NMR spectroscopy. Conclusion. New quaternary ammonium salts of nicotinic acid hydrazones have been obtained. The study of anti-inflammatory activity was carried out using the method of formalin paw edema in rats. The acute inflammatory reaction was reproduced by subplantar administration of 2% formalin solution. Compared with ibuprofen at a dosage of 100 mg/kg, these compounds were ineffective (p2&lt;0.05). According to the results of the analysis of possible pharmacological effects, it was also revealed that new compounds may have an effect on the regulation and production of ketone bodies, the enzymatic activity of transaminases. New alkylated hydrazones of isonicotinic and nicotinic acids may be of interest for studying their antituberculous and antiviral activities. Nicotinic agonist ; Ammonium ; Isonicotinic acid ; Chemistry ; Alkylation ; Nicotinic Acids ; Organic chemistry ; Biochemistry ; Catalysis ; Hydrazide Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and Biological Evaluation
Authors: Университет Аль-Нур | Али Ибрагим Ахмед | Салах Йехья Хусейн | Университетский колледж Аль-Мансура | Басим Галиб Меджбель | Университетский колледж Аль-Хикма | N. N. Bodnar | Университетский колледж Аль-Рафидаин | Мустафа Мохаммед Амин | Университет Аль-Турат
Source: Radioelectronics Nanosystems Information Technologies (article, 2024-09-17)
Field: Materials Science — Materials Chemistry

Improving Energy Conversion Devices' Thermoelectric Efficiency by the Use of Nanostructured Materials Приведен анализ эволюции термоэлектрических материалов, от их фундаментальных теоретических основ до их интеграции в устройства, подчеркивая достижения материаловедения, которые повышают их эффективность и применимость. Приведен обзор текущих исследований, посвященных новым материалам, усовершенствованным процедурам синтеза и инновационным стратегиям проектирования для улучшения термоэлектрической эффективности. Исследованы процедуры интеграции этих материалов в устройства, принимая во внимание как измерения производительности, так и масштабируемость. Показаны существенные успехи в производстве наноструктурированных термоэлектрических материалов, которые значительно повышают коэффициент Зеебека при сохранении электропроводности. Найдены важные решения для оптимизации архитектуры устройств, которые одновременно повышают управление теплом и эффективность. Прорывы в области материаловедения и инженерии способствуют быстрой интеграции улучшенных термоэлектрических материалов в практические системы. Будущие исследования должны сосредоточиться на масштабируемости этих технологий и их интеграции в более широкий спектр систем возобновляемой энергетики, тем самым улучшая их экономическую целесообразность и экологический эффект. Thermoelectric effect ; Materials science ; Thermoelectric materials ; Energy transformation ; Engineering physics ; Energy conversion efficiency ; Thermoelectric generator ; Nanotechnology ; Process engineering ; Optoelectronics ; Composite material ; Engineering ; Thermal conductivity ; Physics ; Thermodynamics Advanced Thermoelectric Materials and Devices
Authors: José A. Abadía
Source: Jornadas de jóvenes investigadores del I3A (article, 2024-07-17)
Field: Materials Science — Polymers and Plastics

José Antonio Abadía - Simulación computacional del fenómeno de relajación de tensiones en polímeros compuestos termoplásticos Physics ; Humanities ; Philosophy Polymer Nanocomposites and Properties
Authors: Quentin Drouhet | Fabienne Touchard | Laurence Chocinski‐Arnault
Source: International Journal of Damage Mechanics (article, 2024-09-14)
Field: Materials Science — Polymers and Plastics

Influence of hydrothermal fatigue on mechanical properties and damage mechanisms of hemp-reinforced biocomposites and comparison with glass-reinforced composites The aim of this work was to evaluate the tensile properties and the damage mechanisms of hemp and glass-reinforced composites when they were subjected to hydrothermal fatigue. Each wet/dry cycle consisted in immersing samples in water at 60°C during 12 days and drying them in an oven at 40°C during 2 days. Three different matrices (Epolam, Greenpoxy and Elium) were studied with two reinforcement orientations (±45° and 0°/90°). Gravimetric measurements were performed during 30 wet/dry cycles to determine the evolution of the parameters of the Fick diffusion model. Repeated progressive tensile loading tests instrumented with an acoustic emission setup were also carried out. Damage was investigated by means of SEM and micro-CT. Results showed that hydrothermal fatigue affects significantly the tensile properties of all the composites studied. Hemp/Greenpoxy appears to better resist to hydrothermal fatigue while the hemp/Elium behavior is more impacted. Moreover, contrary to what might be expected, glass/Epolam samples are not the least sensitive to hydrothermal fatigue. Hydrothermal circulation ; Materials science ; Composite material ; Ultimate tensile strength ; Reinforcement ; Gravimetric analysis ; Glass fiber ; Acoustic emission ; Diffusion Natural Fiber Reinforced Composites ; Innovations in Concrete and Construction Materials ; Geotechnical Engineering and Soil Stabilization
Authors: Jitendra Gautam | Pankaj Verma | Nitesh Kumar | Vineet Kumar | Naveen Kumar
Source: IOSR Journal of Mechanical and Civil Engineering (article, 2024-10-01)
Field: Materials Science — Polymers and Plastics

Drying Behaviour Investigation of Solar Dryer Using Polythene Air is heated and any food item can be dried using the solar drying method, which also uses biomass energy. Drying aids in the preservation of agricultural products while reducing wastage. A solar-biomass hybrid dryer was consequently created to address the drawbacks of natural sun drying, including exposure to direct sunlight, risk of pests and rodents, inadequate supervision, and higher costs associated with mechanical dryers. In this project, a portable hybrid dryer is designed and built. It consists of a biomass combustion chamber integrated with a sun drying chamber that holds a rack of three trays. Through the air inlet, air is supplied into the solar chamber, where it heats up and is used for drying (i.e., removing moisture content from the food ingredient or agricultural product loaded). It is a solar and biomassbased hybrid drier since drying is continued using biomass energy when solar energy is not available. Pune is the design's geographic location, and climatic data were gathered to ensure appropriate design specifications. Glass, mild steel metal bars, acrylic sheets, aluminum foil, and aluminum fabrication material for the trays were among the locally accessible materials utilized in the construction Environmental science ; Solar dryer ; Waste management ; Materials science ; Solar energy ; Engineering ; Electrical engineering Textile materials and evaluations
Authors: Russel E. Caflisch | Yunan Yang
Source: arXiv (Cornell University) (preprint, 2024-01-16)
Field: Materials Science — Materials Chemistry

Adjoint Monte Carlo Method This survey explores the development of adjoint Monte Carlo methods for solving optimization problems governed by kinetic equations, a common challenge in areas such as plasma control and device design. These optimization problems are particularly demanding due to the high dimensionality of the phase space and the randomness in evaluating the objective functional, a consequence of using a forward Monte Carlo solver. To overcome these difficulties, a range of ``adjoint Monte Carlo methods'' have been devised. These methods skillfully combine Monte Carlo gradient estimators with PDE-constrained optimization, introducing innovative solutions tailored for kinetic applications. In this review, we begin by examining three primary strategies for Monte Carlo gradient estimation: the score function approach, the reparameterization trick, and the coupling method. We also delve into the adjoint-state method, an essential element in PDE-constrained optimization. Focusing on applications in the radiative transfer equation and the nonlinear Boltzmann equation, we provide a comprehensive guide on how to integrate Monte Carlo gradient techniques within both the optimize-then-discretize and the discretize-then-optimize frameworks from PDE-constrained optimization. This approach leads to the formulation of effective adjoint Monte Carlo methods, enabling efficient gradient estimation in complex, high-dimensional optimization problems. Monte Carlo method ; Monte Carlo molecular modeling ; Adjoint equation ; Mathematical optimization ; Quantum Monte Carlo ; Hybrid Monte Carlo ; Dynamic Monte Carlo method ; Monte Carlo method in statistical physics ; Applied mathematics ; Computer science ; Kinetic Monte Carlo ; Monte Carlo integration ; Estimator ; Quasi-Monte Carlo method ; Discretization ; Statistical physics ; Markov chain Monte Carlo ; Mathematics ; Partial differential equation ; Physics ; Mathematical analysis Catalytic Processes in Materials Science ; Machine Learning in Materials Science ; Advanced Chemical Physics Studies
Authors: Haonan Peng | Daniel Grolimund | Enzo Curti | Nikolaos I. Prasianakis | Ashish Rajyaguru | Sergey V. Churakov
Source:  (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Towards Digital Twins of Capillary Mass Diffusion Experiments: A Physics-based Machine-Learning Framework for Inverse Modeling of Mass Transport Processes Mass transport ; Diffusion ; Capillary action ; Inverse ; Computer science ; Statistical physics ; Physics ; Engineering physics ; Thermodynamics ; Mathematics Machine Learning in Materials Science
Authors: О.В. Поркуян | Ж.Г. Самойлова
Source: ВІСНИК СХІДНОУКРАЇНСЬКОГО НАЦІОНАЛЬНОГО УНІВЕРСИТЕТУ імені Володимира Даля (article, 2024-02-14)
Field: Materials Science — Materials Chemistry

Вплив функції активації лінійної нейронної мережі на апроксимацію даних основних каналів керування реактру синтезу оцтової кислоти Штучні нейронні мережі будуються за принципами організації та функціонування їх біологічних аналогів. Вони можуть вирішувати широке коло завдань розпізнавання образів, ідентифікації, прогнозування, оптимізації керування складними об'єктами. Подальше підвищення продуктивності комп'ютерів дедалі більше пов'язують із штучними нейронними мережами, зокрема нейрокомп'ютерами. Нині з'являється більше інтелектуальних систем керування технологічними процесами у хімічної промисловості, у яких вирішуються завдання адаптації, самонавчання, самоналаштування. Для вирішення завдання керування технологічними процесами в хімічній промисловості використовуються багатошарові лінійні нейронні мережі зі зворотним розповсюдженням помилки. Для побудови багатошарової мережі для проміжного шару часто використовують функції активації типу логічної (logsig) або гіперболічного тангенсу (tansig), а для кінцевого шару використовується лінійна функція активації (purelin). У цій роботі для побудови та дослідження властивостей нейронної мережі використовувалися статистичні дані реального реактора синтезу оцтової кислоти, який працює у стаціонарному режимі в цеху оцтової кислоти,. Для моделювання використовувалося середовище програмного симулятора MATLAB 2021. Ця програма рекомендована для моделювання різних нейронних мереж із різною кількістю нейронів і різним типом функції активації. В даній роботи була побудована і досліджена лінійна нейронна мережа зі зворотним поширенням помилки з фіксованою кількістю нейронів першого шару за основними каналами керування реактором синтезу оцтової кислоти. В роботі досліджувався вплив функцій активації першого шару та кінцевого шару нейронної мережі на апроксимацію даних реактора синтезу оцтової кислоти. Архітектура нейронної мережі перший шар містить 23 нейрона. Функція активації нейронів змінюється. Спочатку це функція hardlim, потім функція tansig, потім функція logsig і purelin. Другий шар містить один нейрон також з різними функціями активації: hardlim, tansig, logsig і purelin. Діапазон зміни входу [8900-9800]. Моделювання нейромережі з використанням MATLAB 2021 показало успішність процесу побудови та навчання нейронної мережі та його задовільну якість, яка дозволить використовувати нейромережі для керування технологічними процесами синтезу оцтової кислоти та перспективність подальших досліджень цього напряму. Chemistry Machine Learning in Materials Science ; Statistical and Computational Modeling ; Process Optimization and Integration
Authors: Jose Antonio Abadi­a Durango | Jorge Grasa | Carmelo Pina
Source: Jornadas de jóvenes investigadores del I3A (article, 2024-07-17)
Field: Materials Science — Polymers and Plastics

Simulación computacional del fenómeno de relajación de tensiones en polímeros compuestos termoplásticos Se propone en este trabajo el desarrollo de una metodología que permita abordar el modelado del comportamiento de materiales de componentes de cocinas de inducción que trabajan bajo condiciones de deformación constante, tratando de optimizar la predicción del fenómeno de relajación de tensiones. Se presentan resultados de calibración del modelo inicial. Physics ; Humanities ; Philosophy Polymer Nanocomposites and Properties
Authors: Kalyani Kottilil | Maggie Nguyen | Megan E. Ramaker | Nicholas Cauwenberghs | Lydia Coulter Kwee | Sarah Short | R. Scooter Plowman | Robert J. Mentz | Pamela S. Douglas | Rury R. Holman | Adrian F. Hernandez | Kenneth W. Mahaffey | François Haddad | Svati H. Shah
Source: medRxiv (preprint, 2024-12-22)
Field: Chemistry — Spectroscopy

Proteomic Profiling of Early-Stage Heart Failure Identifies Candidate Biomarkers and Molecular Pathways of Cardiac Inflammation in the Project Baseline Health Study ABSTRACT Background Asymptomatic structural heart disease, or stage B heart failure (HF), is clinically relevant for early HF diagnosis and prevention; circulating biomarkers could have prognostic significance for this. Thus, we performed proteomics discovery in a well-phenotyped cohort, the Project Baseline Health Study (PBHS). Methods PBHS recruited participants with and without cardiovascular risk, collecting enrollment plasma biospecimens and cardiac imaging. Proteomic profiling (N=289) was performed using mass spectrometry on 503 individuals (185 stage B HF cases, 318 stage A HF controls). Logistic regression identified stage B-associated proteins, which were then eligible for inclusion in a joint protein score derived via elastic net. Scores were assessed for incident HF prediction in the UK Biobank (UKB) and the Exenatide Study of Cardiovascular Event Lowering (EXSCEL), examined for exenatide interactions in EXSCEL, and tested for imaging trait associations in PBHS and UKB. Mechanistic analyses of multivariate significant proteins included incident HF prediction in UKB and EXSCEL, Mendelian randomization (MR), and targeted methylation loci associations with stage B HF in PBHS. Results Sixty-five proteins were associated with cases, of which 32 (49%) were retained via elastic net modeling; the resulting protein score showed good discrimination for cases versus controls (AUC 0.71, 95% CI [0.60, 0.82]). The protein score was significantly associated with incident HF in UKB and EXSCEL and left ventricular mass index (LVMI) in PBHS, as well as beneficially modified by exenatide in EXSCEL. Multivariate analysis prioritized 11 proteins associated with cases for mechanistic study, of which 4 (B2M, EFEMP1, CST3, HBB) showed significant incident HF associations in UKB and EXSCEL; CST3 and HBB were significant in MR. Methylation of cg08099136 in PSMB8 was significantly associated with cases in PBHS. Conclusions Our findings highlight inflammatory biomarkers and mechanisms underpinning stage B HF. CpG hypomethylation at PSMB8 may be implicated in inflammation, resulting in increased LVMI (a known HF risk factor), with circulating B2M a byproduct of this process. ClinicalTrials.gov Identifier NCT03154346 Profiling (computer programming) ; Heart failure ; Inflammation ; Baseline (sea) ; Medicine ; Stage (stratigraphy) ; Bioinformatics ; Internal medicine ; Biology ; Computer science Advanced Proteomics Techniques and Applications ; Diabetes and associated disorders ; Metabolomics and Mass Spectrometry Studies
Authors: Péter Nemes‐Incze | András Pálinkás | Krisztián Márity | Konrád Kandrai | Zoltán Tajkov | Martin Gmitra | Péter Vancsó | Levente Tapasztó
Source: Research Square (preprint, 2024-04-18)
Field: Materials Science — Materials Chemistry

Identification of graphite with perfect rhombohedral stacking by electronic Raman scattering <title>Abstract</title> Rhombohedral graphite (RG) shows strong correlations in its topological flat band and is pivotal for exploring emergent, correlated electronic phenomena. One key advantage is the enhancement of electronic interactions with the increase in the number of rhombohedrally stacked graphene layers. Increasing thickness also leads to an exponential increase in the number of stacking faults, necessitating a precise method to identify flawless rhombohedral stacking. Overcoming this challenge is difficult because the established technique for stacking sequence identification, based on the Raman 2D peak, fails in thick RG samples. We demonstrate that the strong layer dependence of the band structure can be harnessed to identify RG without stacking faults, or alternatively, to detect their presence. For thicknesses ranging from 3 to 12 layers, we show that each perfect RG structure presents distinctive peak positions in electronic Raman scattering (ERS). This measurement can be carried out using a conventional confocal Raman spectrometer at room temperature, using visible excitation wavelengths. Consequently, this overcomes the identification challenge by providing a simple and fast optical measurement technique, thereby helping to establish RG as a platform for studying strong correlations in one of the simplest crystals possible. Stacking ; Raman spectroscopy ; Raman scattering ; Materials science ; Graphene ; Graphite ; Optics ; Molecular physics ; Optoelectronics ; Nanotechnology ; Physics ; Nuclear magnetic resonance Graphene research and applications ; Advancements in Battery Materials ; 2D Materials and Applications
Authors: Mong Hien Thi Nguyen | Minh Nguyen | Mau Tung Nguyen
Source: Technical Education Science/Giáo dục Kỹ thuật (article, 2024-12-28)
Field: Materials Science — Polymers and Plastics

Creating a Program to Predict the Clothing Size Using Fuzzy Logic This study presents a program to predict trousers’ size using a fuzzy logic technique. There are three variables to input into the program to give the output result of the fit size. The first variable is the waist measurement. The second variable is the hip measurement. The third variable is the trousers’ length measurement. The size determination is done by the Min-Max rule through the IF-THEN structure, effectively managing the commands in the model. The fuzzy rule matrix consists of 108 rows and 6 columns, in which each row represents a fuzzy rule. Each row is a fuzzy rule. The first column represents six groups of neck circumference. The second column represents six groups of hip circumference. The third column represents three groups of pants length. The fourth column represents six predicted output sizes. The fifth column is the weight coefficient. The last column represents the type of logical connection. This size prediction method only takes about five to six seconds to predict the fit size. This reduces the time to choose the size compared to the traditional method. In addition, it reduces the risk of damaging the sample. This method to predict sizes can apply to many other types of clothing as well as many other fields of the garment industry Column (typography) ; Fuzzy logic ; Circumference ; Mathematics ; Table (database) ; Row ; Row and column spaces ; Variable (mathematics) ; Statistics ; Sample size determination ; Computer science ; Data mining ; Artificial intelligence ; Connection (principal bundle) ; Geometry ; Mathematical analysis Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Color perception and design