jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zhijie Yao | Haozhao Jiang | Huilin Wu | Xinyu Tang | Haitao Xu | Houcheng Liu | Haidong Deng | Yubin Lan | Xinlong Zhang | Yutao Liu | Jing Zhao | Yongbing Long
Source: Research Square (preprint, 2022-06-08)
Field: Chemistry — Analytical Chemistry

Quality Identification of Kale Cultivated under Different Light Treatments by Hyperspectral Imaging Technology Abstract The development of a new method to accurately and non-destructively identify the quality of vegetables cultivated under different light treatments is urgent because traditional methods of quality identification are time-consuming, costly and destructively. A method based on hyperspectral imaging technology combined with machine learning was developed in this paper to rapidly identify the quality of kale cultivated under different light treatments in a plant factory. UV-A supplementation in different photoperiods was used to regulate the quality of kale by improving the contents of moisture, photosynthetic pigments and the phytochemicals accumulation, and the quality grades were first established based on these indicators obtained by the traditional method. Then, a non-destructive quality identification method was presented by constructing an identification model based on the hyperspectral images of kale leaves and machine learning. It was revealed that the accuracy of the identification model based on linear discriminant analysis reached a high value of 95% by employing different feature selection methods to optimize the model. The differences of model accuracy were also investigated when the reflectance spectra extracted from different regions of interest (ROIs) such as whole leaf, mesophyll and leaf veins were used for modeling. It was shown that the quality identification models had higher accuracy when the mesophyll was used as ROI than others ROIs, indicating that the selection of ROI-mesophyll was an efficient way to improve the accuracy of the model. These results demonstrate that the proposed method combining hyperspectral imaging technology and machine learning can be used to rapidly and accurately identify the quality of vegetables cultivated under different light treatments. Hyperspectral imaging ; Identification (biology) ; Artificial intelligence ; Linear discriminant analysis ; Pattern recognition (psychology) ; Plant factory ; Quality (philosophy) ; Computer science ; Biological system ; Mathematics ; Botany ; Biology ; Physics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: J. C. Martı́nez | Robert E. Simpson
Source: Advances in Materials Science and Engineering (article, 2022-11-22)
Field: Materials Science — Materials Chemistry

Phase-Change Materials, 1/f Noise, and Phase Synchrony In this article, we study <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mn>1</a:mn> <a:mo>/</a:mo> <a:msup> <a:mrow> <a:mi>f</a:mi> </a:mrow> <a:mrow> <a:mi>γ</a:mi> </a:mrow> </a:msup> <a:mo>,</a:mo> <a:mi>γ</a:mi> <a:mo>≈</a:mo> <a:mn>1</a:mn> </a:math> electrical noise in amorphous phase-change materials. Given the relevance of noise in recent applications, it is necessary to gain a deeper perspective on its nature in phase-change semiconductors, a promising class of materials. Electron conduction is envisaged in terms of an envelope function and a field-dependent Bloch wave function; the electron transport across the structure is modeled as driven phase oscillators under a weak field and obeys a Kuramoto-type equation. Its solutions naturally divide into a phase-synchronized group and phase-desynchronized oscillators. The former is comprised by long-lived pairs or aggregates and are responsible for <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mn>1</c:mn> <c:mo>/</c:mo> <c:mi>f</c:mi> <c:mo>,</c:mo> <c:mi>γ</c:mi> <c:mo>=</c:mo> <c:mn>1</c:mn> </c:math> noise. We identify the dividing frequency between <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>γ</e:mi> <e:mo>=</e:mo> <e:mn>1</e:mn> </e:math> noise and <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>γ</g:mi> <g:mo>≠</g:mo> <g:mn>1</g:mn> </g:math> noise. The phase-desynchronized carriers generate <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:mi>γ</i:mi> <i:mo>≠</i:mo> <i:mn>1</i:mn> </i:math> noise and are single carriers, not aggregates, and are short-lived. We apply our analysis to recent experiments. Materials science ; Phase (matter) ; Noise (video) ; Acoustics ; Computer science ; Artificial intelligence ; Physics ; Quantum mechanics Phase-change materials and chalcogenides ; Transition Metal Oxide Nanomaterials ; Liquid Crystal Research Advancements
Authors: Xiaoming Ma | Tingting Feng | Peng Zhang | Hui Zhang | Xuan Hu | Yuying Yang | Zhen Wang | Huifang Zhang | Dong Peng | Xiaoqi Lai | Xun Li | Jianguo Xu
Source: Research Square (preprint, 2022-09-22)
Field: Materials Science — Materials Chemistry

Downregulation of peroxidase activity of platinum cube enables minute-time scale colorimetric signaling of hypoxanthine for fish freshness monitoring Abstract Due to the unique biological composition of aquatic products especially fish, it is extremely perishable than other muscle products. Herein, we proposed a polyvinylpyrrolidone-modified platinum cubic nanomaterials (PVP-PtNC) with peroxidase activity for colorimetric detection of hypoxanthine (Hx), the indicator of fish freshness, in a minute-time scale. The principle is based on the interaction of Hx with PVP-PtNC to occupy catalytic active sites on PVP-PtNC’s surface. This causes the downregulation of PVP-PtNC’s catalytic ability and weakened its ability to catalyze the oxidization of H2O2by TMB. Accordingly, the decrease of the UV-Vis absorption and the weakening of the colorimetric reaction color is proportional to the Hx concentration. On this basis, a target-triggered colorimetric method for detecting Hx is developed for fish freshness monitoring with a fast detection speed, low cost, high accuracy, and simplified operation. Experiments reveal that the correlation response of Hx is from 0.5 μM to 10 mM with a limit of detection of 0.16 μM. Especially, the Hx detected from real fish indicates the method possesses promising potentials for practical application. All these features are expected to promote the development of online detection tools for food safety monitoring. Fish <Actinopterygii> ; Hypoxanthine ; Chemistry ; Polyvinylpyrrolidone ; Detection limit ; Catalysis ; Peroxidase ; Nanomaterials ; Platinum ; Nanotechnology ; Combinatorial chemistry ; Chemical engineering ; Biochemistry ; Chromatography ; Materials science ; Enzyme ; Fishery ; Polymer chemistry ; Biology Advanced Nanomaterials in Catalysis ; Biosensors and Analytical Detection ; Advanced biosensing and bioanalysis techniques
Authors: Tianshu Hou | Ngai Wong | Quan Chen | Zhigang Ji | Hai-Bao Chen
Source: arXiv (Cornell University) (preprint, 2022-03-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Space-Time Neural Network for Analysis of Stress Evolution under DC Current Stressing The electromigration (EM)-induced reliability issues in very large scale integration (VLSI) circuits have attracted increased attention due to the continuous technology scaling. Traditional EM models often lead to overly pessimistic prediction incompatible with the shrinking design margin in future technology nodes. Motivated by the latest success of neural networks in solving differential equations in physical problems, we propose a novel mesh-free model to compute EM-induced stress evolution in VLSI circuits. The model utilizes a specifically crafted space-time physics-informed neural network (STPINN) as the solver for EM analysis. By coupling the physics-based EM analysis with dynamic temperature incorporating Joule heating and via effect, we can observe stress evolution along multi-segment interconnect trees under constant, time-dependent and space-time-dependent temperature during the void nucleation phase. The proposed STPINN method obviates the time discretization and meshing required in conventional numerical stress evolution analysis and offers significant computational savings. Numerical comparison with competing schemes demonstrates a 2x ~ 52x speedup with a satisfactory accuracy. Electromigration ; Speedup ; Computer science ; Joule heating ; Very-large-scale integration ; Artificial neural network ; Computational science ; Interconnection ; Algorithm ; Parallel computing ; Artificial intelligence ; Engineering ; Electrical engineering Copper Interconnects and Reliability ; Magnetic Properties and Applications ; Semiconductor materials and devices
Authors: Samuella Yosephine | Nur Intan | Sabrina Anjani | Shesa Rahma | Beti Pudyastuti | Triyadi Hendra Wijaya | Dhadhang Wahyu Kurniawan
Source: Acta Pharmaciae Indonesia Acta Pharm Indo (article, 2022-12-31)
Field: Materials Science — Materials Chemistry

The effect of particle size reduction on dissolution of ibuprofen The dissolution rate is an important characteristic to consider when designing a pharmaceutical dosage form, particularly for oral medications. Ibuprofen is an oral medication with a low dissolution rate. The common solution to this problem is to increase the dose to improve drug absorption and effectiveness in order to achieve therapeutic concentration. Some methods to increase dissolution rates have been explored, such as salt formation, prodrug formation, particle size reduction, crystal modification, micellar solubilization, complex formation, solid dispersion, and self-emulsifying. This review focuses on a strategy for increasing ibuprofen dissolution rate by reducing the particle size of the drug. Reduced particle size could improve ibuprofen solubility, allowing it to be absorbed more easily and achieve the desired therapeutic effect. Dissolution ; Reduction (mathematics) ; Ibuprofen ; Particle size ; Particle (ecology) ; Materials science ; Chemistry ; Chemical engineering ; Mathematics ; Medicine ; Geology ; Engineering ; Pharmacology ; Physical chemistry ; Geometry Crystallization and Solubility Studies ; Drug Solubulity and Delivery Systems ; Chemical Thermodynamics and Molecular Structure
Authors: F. Emil Thomasen | M.J. Cuneo | Tanja Mittag | Kresten Lindorff‐Larsen
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-10-08)
Field: Materials Science — Materials Chemistry

Conformational and oligomeric states of SPOP from small-angle X-ray scattering and molecular dynamics simulations Abstract Speckle-type POZ protein (SPOP) is a substrate adaptor in the ubiquitin proteasome system, and plays important roles in cell-cycle control, development, and cancer. SPOP forms linear higher-order oligomers following an isodesmic self-association model. Oligomerization is essential for SPOP’s multivalent interactions with substrates, which facilitate phase separation and localization to biomolecular condensates. Structural characterization of SPOP in its oligomeric state and in solution is, however, challenging due to the inherent conformational and compositional heterogeneity of the oligomeric species. Here, we develop an approach to simultaneously and self-consistently characterize the conformational ensemble and the distribution of oligomeric states of SPOP by combining small-angle X-ray scattering (SAXS) and molecular dynamics simulations. We build initial conformational ensembles of SPOP oligomers using coarse-grained molecular dynamics simulations, and use a Bayesian/maximum entropy approach to refine the ensembles, along with the distribution of oligomeric states, against a concentration series of SAXS experiments. Our results suggest that SPOP oligomers behave as rigid, helical structures in solution, and that a flexible linker region allows SPOP’s substrate binding domains to extend away from the core of the oligomers. Additionally, our results are in good agreement with previous characterization of the isodesmic self-association of SPOP. In the future, the approach presented here can be extended to other systems to simultaneously characterize structural heterogeneity and self-assembly. Molecular dynamics ; Small-angle X-ray scattering ; Isodesmic reaction ; Chemistry ; Crystallography ; Conformational entropy ; Linker ; Chemical physics ; Materials science ; Scattering ; Molecule ; Computational chemistry ; Physics ; Computer science Enzyme Structure and Function ; Glycosylation and Glycoproteins Research ; Endoplasmic Reticulum Stress and Disease
Authors: Abou Marak Dit Brome, Reem
Source: theses.fr (ABES) (article, 2022-12-08)
Field: Materials Science — Materials Chemistry

Caractérisation et Analyse des Signaux de Pression Cyclostationnaire Générés lors de la Marche : Prédiction des Chutes chez les Personnes Agées Il existe un intérêt croissant pour le développement de modèles de prédiction du risque de chute chez les personnes âgées qui peuvent être utilisés comme approches préventives pour prédire le risque de chute dans la communauté des personnes âgées.Les principaux objectifs de cette thèse sont d’étudier les aspects cyclostationnaires des signaux de pression de la semelle intérieure des personnes âgées et d’extraire les caractéristiques essentielles indicatives du risque de chutes futures. De plus, cette thèse vise à mettre en œuvre et à comparer différentes méthodes d’apprentissage automatique supervisé pour classer les sujets âgés en sujets avec ou sans risque de chute dans le futur. L’ensemble de données se compose de signaux de pression collectés à partir des semelles intérieures de 519 personnes âgées qui ont fait l’objet d’un questionnaire médical préalable incluant leur propension à la chute. Notre étude propose les caractéristiques indicatives des chutes futures, les modèles d’apprentissage automatique et les méthodes d’optimisation pour développer l’évaluation du risque de chute dans la communauté des personnes âgées.Enfin, notre étude propose une nouvelle méthode pour représenter les signauxde la semelle intérieure de pression cylcostationnaire et les utiliser dans un modèled’apprentissage en profondeur pour prédire les chutes potentielles dans la communautédes personnes âgées. Behavioral analysis ; Electrodiagnosis ; Medical screening Material Selection and Properties ; Engineering Education and Pedagogy ; Various Chemistry Research Topics
Authors: Elizabeth M. Diessner | Eric Wong | Vera Prytkova | J. Alfredo Freites | Douglas J. Tobias | Carter T. Butts
Source: Biophysical Journal (article, 2022-02-01)
Field: Materials Science — Materials Chemistry

Network Hamiltonian models for unstructured protein aggregates, with application to γD-crystallin Crystallin ; Chemistry ; Computational biology ; Computer science ; Biophysics ; Biological system ; Biochemistry ; Biology Enzyme Structure and Function ; Connexins and lens biology ; Protein Structure and Dynamics
Authors: Ayşe Dinçer | Yang Lu | Devin K. Schweppe | Sewoong Oh | William Stafford Noble
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-04-12)
Field: Chemistry — Spectroscopy

Reducing peptide sequence bias in quantitative mass spectrometry data with machine learning Abstract Quantitative mass spectrometry measurements of peptides necessarily incorporate sequence-specific biases that reflect the behavior of the peptide during enzymatic digestion, liquid chromatography, and in the mass spectrometer. These sequence-specific effects impair quantification accuracy, yielding peptide quantities that are systematically under- or over-estimated. We provide empirical evidence for the existence of such biases, and we use a deep neural network, called Pepper, to automatically identify and reduce these biases. The model generalizes to new proteins and new runs within a related set of MS/MS experiments, and the learned coefficients themselves reflect expected physicochemical properties of the corresponding peptide sequences. The resulting adjusted abundance measurements are more correlated with mRNA-based gene expression measurements than the unadjusted measurements. Pepper is suitable for data generated on a variety of mass spectrometry instruments, and can be used with labeled or label-free approaches, and with data-independent or data-dependent acquisition. Mass spectrometry ; Peptide ; Sequence (biology) ; Chemistry ; Chromatography ; Computational biology ; Biological system ; Computer science ; Biology ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Azad Sadraddin | Darya J. Raheem
Source: Mağallaẗ al-tarbiyaẗ wa-al-ʻilm (article, 2022-03-01)
Field: Materials Science — Polymers and Plastics

A Study of Some Changes in the Properties of Recycled PVC Plastic in Arbil Factories Abstract:<br /> This research was carried out in the laboratories of Erbil city on recycled PVC plastic for several times. The plasticizer DOP was extracted from the old plastic to study the extent to which the plasticizer remained in it after a period of time, as well as its exposure to heat of atmosphere. Several experiments were conducted to reach the optimum conditions to obtain the highest percentage of extracted plasticizer and then it was diagnosed by infrared spectrophotometer and thin layer chromatography. The results showed that the extracted plasticizer matches the standard plasticizer. We also performed viscosity measurements and bromine detection. The results showed that increasing the percentage of plasticizer works to increase the flexibility of plastic materials and reduce the degree of softening, knowing that adding the amount of plasticizer depends on the season of the year. This study can be used for the purpose of qualitative improvement of the production of recycled plastic as well as for the benefit of environmental issues. Plasticizer ; Materials science ; Softening point ; Bromine ; Composite material ; Environmental science ; Metallurgy Polymer Science and PVC
Authors: Taotao Chen
Source: Highlights in Science Engineering and Technology (article, 2022-12-04)
Field: Chemistry — Inorganic Chemistry

Metal-Organic Frameworks for Removing Radioactive Wastes in Water Humans only got a limited number of natural resources to survive and exploit. Water, as one of the limited natural resources, has been polluted because of human rapid development in many fields of industries. Nuclear wastes, as one of the pollutants, bring serious or in-reversible harm not only to the environment but also to human health. Metal-organic frameworks (MOFs) materials could be applied to various kinds of areas and also got a huge potential in the treatment of wastewater with radioactive wastes. This article mainly talks about the research progress of MOF material used in the field of radioactive wastewater treatment and introduces the preparation and characteristics of MOF-5, HKUST-1/KCoFC, and UiO66-COOH materials. Additionally, factors including solid-liquid ratio, initial concentration, reacting time, and pH value that affect the adsorption capacity on U(VI), Cs, and Sr are analyzed. Some research on MOFs materials used to remove different kinds of radioactive substances is also highlighted. Finally, some problems that still exist are raised, and expectations and directions for future development in this field are provided. Radioactive waste ; Waste management ; Environmental science ; Wastewater ; Pollutant ; Human health ; Harm ; Adsorption ; Environmental engineering ; Chemistry ; Engineering ; Law Radioactive element chemistry and processing ; Metal-Organic Frameworks: Synthesis and Applications ; Nuclear Materials and Properties
Authors: Riccardo Capelli | Francesco Muniz‐Miranda | Giovanni M. Pavan
Source: The Journal of Chemical Physics (article, 2022-05-16)
Field: Materials Science — Materials Chemistry

Ephemeral ice-like local environments in classical rigid models of liquid water Despite great efforts over the past 50 years, the simulation of water still presents significant challenges and open questions. At room temperature and pressure, the collective molecular interactions and dynamics of water molecules may form local structural arrangements that are non-trivial to classify. Here, we employ a data-driven approach built on Smooth Overlap of Atomic Position (SOAP) that allows us to compare and classify how widely used classical models represent liquid water. Macroscopically, the obtained results are rationalized based on water thermodynamic observables. Microscopically, we directly observe how transient ice-like ordered environments may dynamically/statistically form in liquid water, even above freezing temperature, by comparing the SOAP spectra for different ice structures with those of the simulated liquid systems. This confirms recent ab initio-based calculations but also reveals how the emergence of ephemeral local ice-like environments in liquid water at room conditions can be captured by classical water models. Liquid water ; Ephemeral key ; Water model ; Observable ; Molecular dynamics ; Position (finance) ; Open water ; Statistical physics ; Chemistry ; Physics ; Geology ; Thermodynamics ; Computer science ; Computational chemistry ; Oceanography Material Dynamics and Properties ; Quantum, superfluid, helium dynamics ; Spectroscopy and Quantum Chemical Studies
Authors: Emergency Rescue Service of Kharkiv | Victor P. Belogurov | S. V. Kosolapov
Source: Mathematical Modeling and Computing (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

In memory of V. F. Chekurin The purpose of the research article is to study the contribution of V. F. Chekurin to the development of science through a comprehensive and objective analysis of the publications of the author, his colleagues and co-authors. In the creative heritage of V. F. Chekurin, it is proposed to single out three areas of his works: semiconductors, pipeline gas dynamics, and an elasticity problem. It is shown that set of works by V. F. Chekurin can be called Chekurin's theory of pipeline gas dynamics. It is recommended to be used for pipelines condition monitoring. Verification of numerical modeling results according to the RR criterion showed that among the tested models, the model is suitable if $RR&lt;1$. This proves that the Chekurin–Khymko model can be registered in Data Base of Geospatial Objects. The variation method of homogeneous solutions is proposed for the evaluation of residual stresses formed in cylindrical bodies. Homogeneous ; Geospatial analysis ; Residual ; Pipeline (software) ; Set (abstract data type) ; Computer science ; Base (topology) ; Gas pipeline ; Applied mathematics ; Algorithm ; Mathematics ; Engineering ; Mechanical engineering ; Geography ; Mathematical analysis ; Cartography ; Combinatorics ; Programming language Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Industrial Engineering and Technologies