jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Pawan Kumar Gupta | Akhilesh A. Waoo
Source: ShodhKosh Journal of Visual and Performing Arts (article, 2024-01-31)
Field: Chemistry — Analytical Chemistry

ANALYZING MACHINE LEARNING METHODS TO ENHANCE GRAIN QUALITY ASSESSMENT AND EVOLUTION Assessing grain quality is a crucial component of agricultural production, with significant implications for global food security and economic prosperity. With the increasing demand for top-tier grains, there arises a pressing need for sophisticated methodologies to aid in the ongoing assessment and monitoring of grain quality throughout its development. This paper offers a comprehensive examination of machine learning (ML) techniques utilized in grain quality evaluation. Through an analysis of recent research advancements, methodologies, and practical applications, this review sheds light on the effectiveness and potential obstacles associated with ML-driven approaches for enhancing grain quality assessment. Key areas of focus include the deployment of ML algorithms for predicting, classifying, and monitoring grain quality, as well as the incorporation of advanced sensing technologies and data analytics into grain quality assessment systems. Additionally, the review delves into emerging trends, future research avenues, and the broader implications of ML techniques in streamlining grain production processes and ensuring food safety and sustainability. By conducting a systematic review of existing literature, this paper contributes to a deeper comprehension of the role played by ML in addressing the multifaceted challenges of grain quality assessment and management within contemporary agriculture. Quality (philosophy) ; Computer science ; Quality assessment ; Artificial intelligence ; Machine learning ; Engineering ; Reliability engineering ; Evaluation methods ; Epistemology ; Philosophy Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Mineral Processing and Grinding
Authors: Samir F. Matar
Source: arXiv (Cornell University) (preprint, 2024-04-02)
Field: Materials Science — Materials Chemistry

Superhard lon C5 and derived carbon nitrides: C4N and C2N2. Crystal chemistry and first principles DFT studies Super-hard C5 with lon topology (lon: Lonsdaleite hexagonal diamond) and characterized by the presence of sp3 and sp2 -like carbon sites is devised from crystal chemistry and used as template matrix structure for identifying original carbonitrides C4N and C2N2 with lon topology except for the equiatomic belonging to a new topology (3,4L147). The steric effect of N(2s2) lone pair is highlighted in C2N2 in inducing an original structure of largely separated two-layered stacking of tetrahedra. The investigations based on crystal chemistry were backed by computations within the quantum density functional theory DFT. All systems were found cohesive and both mechanically (elastic constants) and dynamically (phonons band structures) stable. Super hardness characterizes the carbon allotrope C5 and the nitrides C4N and C2N2. Metallic-like conductivities and insulating characters were identified. Nitride ; Carbon fibers ; Chemistry ; Computational chemistry ; Nanotechnology ; Materials science Boron and Carbon Nanomaterials Research ; Fullerene Chemistry and Applications ; Diamond and Carbon-based Materials Research
Authors: Zhengguang Guo | Yonghong Yao | Jin Liu
Source: ChemistryOpen (article, 2024-10-17)
Field: Materials Science — Materials Chemistry

First Principles Study of Electronic and Optical Properties of Al‐P Co‐Doped ZnO in the Presence of Zn Vacancies The BP neural network optimized by the Adam algorithm was used to predict the defect formation energy of Al-P co-doped ZnO systems with different concentrations of P replacing O under the presence of different concentrations of V<sub>Zn</sub>. It was found that the easily formed Al<sub>Zn</sub>Po-1V<sub>Zn</sub>, Al<sub>Zn</sub>P<sub>O</sub>-2V<sub>Zn</sub>, and Al<sub>Zn</sub>2P<sub>O</sub>-1V<sub>Zn</sub> systems. The first principles of density function were used to study the geometric, electronic, and optical properties of each system. The simulation results show that the bandgap values of the three systems have decreased relative to the intrinsic ZnO, among which Al<sub>Zn</sub>P<sub>O</sub>-1V<sub>Zn</sub> and Al<sub>Zn</sub>P<sub>O</sub>-2V<sub>Zn</sub> is still a p-type conductive system, Al<sub>Zn</sub>P<sub>O</sub>-2V<sub>Zn</sub> has the highest conductivity. From the analysis of reflectivity, absorption rate, and light transmittance, Al<sub>Zn</sub>2P<sub>O</sub>-1V<sub>Zn</sub> has the most relatively excellent optical properties, followed by AlznPo-2V<sub>Zn</sub>. Doping ; Band gap ; Zinc ; Transmittance ; Conductivity ; Materials science ; Analytical Chemistry (journal) ; Optical conductivity ; Reflectivity ; Absorption (acoustics) ; Chemistry ; Physical chemistry ; Metallurgy ; Optics ; Optoelectronics ; Physics ZnO doping and properties ; Gas Sensing Nanomaterials and Sensors ; Ga2O3 and related materials
Authors: Alexey Rayevsky | Maxim O. Platonov | Elijah Bulgakov | Dmitriy M. Volochnyuk | Veklich To | S. О. Cherenok | R. V. Rodik | В. І. Кальченко | Kosterin Sa
Source: Molecular Informatics (article, 2024-12-05)
Field: Chemistry — Organic Chemistry

Structural Insight on the Selectivity of Calyx[4]Arene‐Based Inhibitors of Mg<sup>2+−</sup>Dependent Atp‐Hydrolases Located in plasma membranes, ATP hydrolases are involved in several dynamic transport processes, helping to control the movement of ions across cell membranes. ATP hydrolase acts as a transport protein, converting energy from ATP hydrolysis into transport molecules against their concentration gradients. In addition to energy metabolism and active transport, ATP hydrolase is essential for maintaining cellular homeostasis and cell function. This study focused on the domain architecture model of P-type ATPases, which participate in the reaction cycles of ATP hydrolysis carried out by membrane transport systems - Na+, K+-ATPase and Ca2+, Mg2+-ATPase. Targeted modulation of Na+, K+-ATPase and Ca2+, Mg2+-ATPase by unnatural drugs is of greatest interest due to the lack of known effectors. This new discovery presents a convenient model based on our recent experimental studies of the membrane structures and myocytes of the uterine smooth muscle, the myometrium. This current study strongly supports the fact that nanosized calix[4]arenes functionalised on the upper rings of the macrocycle with biologically active phosphonic acid fragments can serve as selective and potent inhibitors of cation-transporting electroenzymes. This is how we discovered that calix[4]arene of methylenebisphosphonic acid C-97 and calix[4]arene of bis-aminophosphonic acid C-107 selectively and effectively (I0.5 <100 nM) inhibit the activity of Mg2+, ATP-dependent electrogenic Na+ K+ plasma membrane pump. As drug discovery in the field of Mg2+-ATPase inhibitors is uncharted territory, basic research holds the key to explaining and predicting the mechanism of interaction and action of different classes of compounds. In light of the presented results, new calix[4]arene compounds can be used as potent inhibitors of Mg2+, ATP-dependent electrogenic ion pumps. ATP hydrolysis ; Chemistry ; ATPase ; Membrane ; Biophysics ; Stereochemistry ; Active transport ; Myometrium ; Ion transporter ; Enzyme ; Biochemistry ; Membrane transport ; Biology Chemical Reaction Mechanisms ; ATP Synthase and ATPases Research ; Supramolecular Chemistry and Complexes
Authors: Phan Thi-Thu-Hong | Vo Quoc-Trinh | Nguyen Huu-Du
Source: arXiv (Cornell University) (preprint, 2024-06-09)
Field: Chemistry — Analytical Chemistry

A novel method for identifying rice seed purity based on hybrid machine learning algorithms In the grain industry, the identification of seed purity is a crucial task as it is an important factor in evaluating the quality of seeds. For rice seeds, this property allows for the reduction of unexpected influences of other varieties on rice yield, nutrient composition, and price. However, in practice, they are often mixed with seeds from others. This study proposes a novel method for automatically identifying the rice seed purity of a certain rice variety based on hybrid machine learning algorithms. The main idea is to use deep learning architectures for extracting important features from the raw data and then use machine learning algorithms for classification. Several experiments are conducted following a practical implementation to evaluate the performance of the proposed model. The obtained results show that the novel method improves significantly the performance of existing methods. Thus, it can be applied to design effective identification systems for rice seed purity. Computer science ; Algorithm ; Machine learning ; Artificial intelligence Spectroscopy and Chemometric Analyses
Authors: Sunitha Palleti
Source: Journal of Chemistry & its Applications (article, 2024-10-08)
Field: Chemistry — Organic Chemistry

Reactive Extraction of Carboxylic Acids (Lactic, Propionic and Succinic Acids) using Tri-n-Butyl Amine Dissolved in Various Diluents The current study intends to look into the extraction of lactic acid, propionic acid and succinic acids from aqueous solutions of these substances utilizing various solvent-extractant combinations to ascertain the most effective composition for the reactive extraction. The commercial value of succinic, propionic, and lactic acids in industrial processes led to their selection as the carboxylic acids. The process of recovering carboxylic acids from their aqueous solutions is accomplished by the Process Intensification method of reactive Tri-n-Butyl Amine was employed in the experiments because it has better stability, a lower water solubility, and is more eco-friendly than other extractants of the amine type. The extractants were dissolved in various diluents with various chemical structures, including 1-octanol, chloroform, and dimethylene chloride. Each experiment was conducted at 298.15 K. The distribution coefficient (KD), loading factor (Z), and extraction yield (%E) were used to compare the results in the range of 0.1 to 0.4 N acid concentration at various concentrations of Tri-n-Butyl Amine (10% to 40%). It was observed that at 0.1N and 40% amine concentration succinic acid attains a maximum distribution coefficient KD is 8.01 and equilibrium complexion KE1 is 7.5 for Tri-n-Butyl Amine, followed by propionic acid and lactic acid and a (1:1) type of acid amine complex was observed. The kinetic studies that were carried out using stirred cells to figure out the kinetic parameters such as order of the reaction with respect to acid and amine, mass transfer coefficient, and rate constant are also reported. The reaction with the highest Hatta number, MH=14, occurs in an instantaneous regime in 1-octanol when succinic acid and Tri-n-Butyl Amine interact. Diluent ; Amine gas treating ; Chemistry ; Extraction (chemistry) ; Succinic acid ; Lactic acid ; Organic chemistry ; Chromatography ; Bacteria ; Biology Chemical Synthesis and Reactions
Authors: Daigo Mugita | Kazuyoshi Souno | Masaharu Isobe
Source: arXiv (Cornell University) (preprint, 2024-12-18)
Field: Materials Science — Materials Chemistry

Recursive Algorithm to the Centroid of Free Area for Inherent Structure and Hopping Motion in Deeply Supercooled Binary Hard Disk Systems Inherent structures, derived by eliminating thermal fluctuations from complex trajectories, illuminate fundamental mechanisms underlying structural relaxation and dynamic heterogeneity in dense glassy systems. However, determining these structures in hard disk/sphere systems presents unique challenges due to the discontinuous nature of inter-particle potentials and resultant flat potential energy landscapes. To address this limitation, we introduce the Recursive Centroid of Free Area algorithm (ReCFA), a novel approach inspired by a steepest descent method, which computes inherent structure configurations in hard disk systems. We conducted comparative analyses between ReCFA, similar methods, and a conventional time-coarse-graining technique, focusing on string-like hopping motions in supercompressed binary hard disks that emulate supercooled liquid behavior. ReCFA demonstrated notable advantages in capturing entropic contributions. The configurations derived through ReCFA exhibited physically reasonable particle displacements analogous to inherent structures in soft particle systems, effectively identifying hopping motions between metastable basins in jammed states. This ReCFA-based analysis enhances our understanding of relaxation dynamics in highly compressed glassy systems, offering a robust analytical tool for investigating both dynamic and structural characteristics across hard and soft particle systems. Centroid ; Supercooling ; Binary number ; Algorithm ; Motion (physics) ; Statistical physics ; Computer science ; Mathematics ; Physics ; Artificial intelligence ; Thermodynamics ; Arithmetic Material Dynamics and Properties ; Theoretical and Computational Physics ; Adhesion, Friction, and Surface Interactions
Source: Building Materials and Engineering Structures (article, 2024-12-30)
Field: Materials Science — Materials Chemistry

Analysis of Material selection for automotive fender using the weighted sum method Introduction: Material selection for automotive fenders involves the process of choosing the most suitable materials to be used in the construction of fenders based on various performance criteria, including mechanical properties, durability, weight, cost, safety, and environmental considerations. It involves assessing different materials and their characteristics to determine the optimal choice that meets the specific requirements of fenders. Research Significance: We will be able to choose a material with the right qualities thanks to research on the best materials for car fenders. Research on material choice for vehicle fenders was conducted for several reasons, including weight reduction and fuel efficiency, impact resistance including safety, resisting corrosion and durability, manufacturing procedure and cost optimisation, design flexibility and style, and environmental sustainability. It promotes innovation, aids in the creation of innovative materials, and aids automakers in meeting the changing demands of the market and customers. Method: This research employs the weighted sum approach to analyse the choice of material for an automobile fender. Alternate Parameters: High Strength Steels (Docol600DP and Docol1000DP), Aluminium alloys (AA2036T4 and AA6010T4), Thermoplastic polymers (PPE/PA/989Resin, PPO/PA66, NY66/40CF, PPS/40CF, AR/PC, PC/PBT resin) Evaluation Parameters: Ultimate Tensile Strength (UTS), Yield Strength (YS), Young's Modulus (YM), Linear Coefficient of Thermal Expansion (CTE), Material Cost (MC). Results: From the result it is seen that D1000DP is got the first rank where as is the PPE/PA/989 is having the lowest rank. Conclusion: the first ranking D1000DP is obtained with the lowest quality of PPE/PA/989. Fender ; Automotive industry ; Durability ; Material selection ; Ranking (information retrieval) ; Flexibility (engineering) ; Ultimate tensile strength ; Materials science ; Structural engineering ; Computer science ; Manufacturing engineering ; Composite material ; Engineering ; Mathematics Material Selection and Properties ; Natural Fiber Reinforced Composites ; Mechanical Engineering and Vibrations Research
Authors: Bedoya Rodriguez, Juan Esteban
Source: Univalle Digital Repository (University of Valle) (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Calculo teórico de diagramas de fase magnéticos mediante el método de los grupos de renormalización en campo medio (GRCM), realizando ajustes con redes neuronales e implementaciones numéricas El núcleo de este trabajo se centró en el estudio de los fenómenos magnéticos en los sistemas FepAl1−p y FepMn0.6−pAl0.4. En ambos casos, se analizó el diagrama de fase magnético, obteniendo un resultado teórico mediante el método de los grupos de renormalización en campo medio (GRCM). Además, se implementó un ajuste utilizando redes neuronales, marcando la primera aproximación de esta herramienta en este tipo de estudios, con resultados prometedores en cuanto a su similitud con los valores experimentales. Obteniendo en el mejor de los casos, funciones de costo del orden de 10^(-3), lo que representa el error entre los datos experimentales y el ajuste logrado. También se analizó el comportamiento de la energía de enlace, logrando reducir a la mitad los saltos energéticos en el segundo sistema estudiado, pasando de 60 meV a 30 meV con respecto a estudios previos, que concuerda con la realidad física de estos sistemas. Este análisis se complementó con simulaciones basadas en los resultados del ajuste de la energía de enlace mediante redes neuronales. Se obtuvieron temperaturas críticas con un error del 0.029 % en el mejor de los casos y del 25% en el peor de los mismo, lo cual puede atribuirse a fluctuaciones inherentes a la naturaleza experimental de los datos. Promediando los errores entre las temperaturas simuladas y experimentales, se obtuvo un error medio del 8.40%, lo cual respalda la validez del modelo propuesto. Para el primer sistema estudiado, se implementó un modelo con segundos vecinos que arrojó resultados alentadores tanto en el ajuste como en el comportamiento de la energía de enlace. Finalmente, en este mismo sistema, también se realizó una simulación tipo Monte Carlo basada en los datos obtenidos en este trabajo, lo que permitió corroborar los resultados de manera satisfactoria, ofreciendo una perspectiva prometedora para investigaciones futuras. Field (mathematics) ; Order (exchange) ; Closure (psychology) Magnetic Properties and Applications ; Metallic Glasses and Amorphous Alloys ; Metallurgical and Alloy Processes
Authors: Christianah Racheal
Source: Research Square (preprint, 2024-02-28)
Field: Materials Science — Polymers and Plastics

Comparison of Intradermal Irritation based on Poly(methyl methacrylate) Hydrogel Abstract To investigate the potential skin irritation response of domestically produced medical poly(methyl methacrylate) hydrogel, the intradermal injection method was used. Healthy white rabbits were selected for intradermal injection of 0.5% sodium chloride solution as a control, 0.5% sodium chloride extract, and olive oil extract for the test samples. The rabbits were observed for erythema and edema at 24 and 72 hours, and the primary irritation index was calculated. The primary irritation index of the domestically produced poly(methyl methacrylate) hydrogel was 0, indicating no skin irritation response. Irritation ; Methacrylate ; Skin irritation ; Methyl methacrylate ; Polymer science ; Polymer chemistry ; Materials science ; Dermatology ; Composite material ; Polymer ; Medicine ; Copolymer ; Immunology Synthesis and properties of polymers
Authors: Christina Schenk | Maciej Harańczyk
Source: arXiv (Cornell University) (preprint, 2024-07-23)
Field: Chemistry — Analytical Chemistry

A Novel Constrained Sampling Method for Efficient Exploration in Materials and Chemical Mixture Design Efficient exploration of multicomponent material composition spaces is often limited by time and financial constraints, particularly when mixture and synthesis constraints exist. Traditional methods like Latin hypercube sampling (LHS) struggle with constrained problems especially in high dimensions, while emerging approaches like Bayesian optimization (BO) face challenges in early-stage exploration. This article introduces ConstrAined Sequential laTin hypeRcube sampling methOd (CASTRO), an open-source tool designed to address these challenges. CASTRO is optimized for uniform sampling in constrained small- to moderate-dimensional spaces, with scalability to higher dimensions through future adaptations. CASTRO uses a divide-and-conquer strategy to decompose problems into parallel subproblems, improving efficiency and scalability. It effectively handles equality-mixture constraints, ensuring comprehensive design space coverage and leveraging LHS and LHS with multidimensional uniformity (LHSMDU). It also integrates prior experimental knowledge, making it well-suited for efficient exploration within limited budgets. Validation through two material design case studies, a four-dimensional problem with near-uniform distributions and a nine-dimensional problem with additional synthesis constraints, demonstrates CASTRO's effectiveness in exploring constrained design spaces for materials science, pharmaceuticals and chemicals. The software and case studies are available on GitHub. Sampling (signal processing) ; Computer science ; Mathematical optimization ; Biochemical engineering ; Industrial engineering ; Mathematics ; Engineering Spectroscopy and Chemometric Analyses ; Optimal Experimental Design Methods
Authors: Shiqing Dou | Yuan-Xiang Deng | Wenjie Zhang | Jichi Yan | Zhengmin Mei | Minglan Li
Source: Research Square (preprint, 2024-01-12)
Field: Chemistry — Analytical Chemistry

Prediction of the Soluble Solid Content of Citrus Based on the Fractional-Order Derivative and Optimal Band Combination Algorithm Abstract The soluble solid content (SSC) is a primary characteristic index for evaluating the internal quality of citrus fruits. The development of rapid and nondestructive SSC detection techniques can help address the current issues of postharvest quality grading in China's citrus industry. In this study, Three varieties of citrus were used as experimental materials. After obtaining the reflection spectra and SSCs,SNV-FOD (Standard Normal Variate - Fractional-Order Derivative) was used to process the spectra, and the optimal band combination algorithm (OBC) was introduced to select SSC-sensitive bands. Then, the obtained optimal dual-band combination was input into eight regression models for comparison, and the best-performing models stacked ensemble models was selected. Finally, the H-ELR (HyperOpt-optimized Ensemble Learning Regression) model, optimized using a Bayesian function, was applied for the effective prediction of citrus SSC. The results shows that (1) The SNV-FOD preprocessing method proposed in this paper improved the correlation coefficient with the SSC by 0.29 compared to that of the original spectrum; (2) The optimal dual-band combination (969 and 1069 nm) constructed by integrating the differential index (DI) and 1.2-order derivative yielded the most accurate results (RPD = 2.13); and (3) The H-ELR model, based on HyperOpt optimization, achieved good predictive performance (RPD = 2.46). This research contributes to the development of practical SSC prediction instruments with excellent universality and ease of application. Algorithm ; Mathematics ; Preprocessor ; Computer science ; Biological system ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Postharvest Quality and Shelf Life Management