jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Russell J. Stewart | Paul B. Frandsen | Steffen U. Pauls | Jacqueline Heckenhauer
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-07-09)
Field: Materials Science — Biomaterials

Conservation of three-dimensional structure in Lepidoptera and Trichoptera L-fibroins for 290 million years ABSTRACT The divergence of sister orders, Trichoptera (caddisflies) and Lepidoptera (moths and butterflies), from a silk-spinning ancestor occurred around 290 million years ago. Trichoptera larvae are mainly aquatic and Lepidoptera larvae are almost entirely terrestrial, distinct habitats that required molecular adaptation of their silk for deployment in water versus air. The major protein components of their silks are Heavy chain and Light chain fibroins. In an effort to identify molecular changes in L-fibroins that may have contributed to the divergent use of silk in water versus air, we used the ColabFold implementation of AlphaFold2 to predict three-dimensional structures of L-fibroins from both orders. Comparison of the structures revealed that despite the ancient divergence, profoundly different habitats, and low sequence conservation, a 10-helix core structure was strongly conserved in L-fibroins from both orders. Previously known intra- and intermolecular disulfide linkages were accurately predicted. Structure variations observed outside of the core may represent molecular changes that contributed to the evolution of silks adapted to water or air. The distributions of electrostatic potential, for example, are not conserved and present distinct order-specific surfaces for potential interactions with or modulation by external factors. Also, the interactions of L-fibroins with the H-fibroin C-termini are different between the orders; lepidopteran L-fibroins have N-terminal insertions, not present in trichopteran L-fibroins, which form an unstructured ribbon in isolation but become part of an intermolecular β-sheet when folded with their corresponding H-fibroin C-termini. The results may serve as another example of protein structure prediction from deep sequence data of understudied proteins made possible by AlphaFold2. SILK ; Fibroin ; Lepidoptera genitalia ; Saturniidae ; Midgut ; Bombyx mori ; Biology ; Larva ; Botany ; Materials science ; Biochemistry ; Gene Silk-based biomaterials and applications ; Biochemical and Structural Characterization ; Neurobiology and Insect Physiology Research
Authors: Domingo Olivares-Postigo | Federico Gorrini | Valeria Bitonto | Johannes Ackermann | Rakshyakar Giri | Anke Krueger | Angelo Bifone
Source: Research Square (preprint, 2022-02-15)
Field: Materials Science — Materials Chemistry

Divergent Effects of Laser Irradiation on Ensembles of Nitrogen-vacancy Centers in Bulk and Nano-diamonds: Implications for Biosensing Abstract Ensembles of negatively charged nitrogen vacancy centers (NV - ) in diamond have been proposed for sensing of magnetic fields and paramagnetic agents, and as a source of spin-order for the hyperpolarization of nuclei in magnetic resonance applications. To this end, strongly fluorescent nanodiamonds represent promising materials, with large surface areas and dense ensembles of NV - . However, surface effects tend to favor the less useful neutral form, the NV 0 centers, and strategies to increase the density of shallow NV - centers have been proposed, including irradiation with strong laser power [1]. Here, we study the fluorescence properties and optically detected magnetic resonance (ODMR) of NV - centers as a function of laser power in strongly fluorescent bulk diamond and in nanodiamonds obtained by nanomilling of the native material. In bulk diamond, we find that increasing laser power increases ODMR contrast, consistent with a power-dependent increase in spin-polarization. Conversely, in nanodiamonds we observe a non-monotonic behavior, with a decrease in ODMR contrast at higher laser power. We hypothesize that this phenomenon may be ascribed to more efficient NV - → NV 0 photoconversion in nanodiamonds compared to bulk diamond, resulting in depletion of the NV - pool. A similar behavior is shown for NDs internalized in macrophage cells under the typical experimental conditions of imaging bioassays. Our results suggest strong laser irradiation is not an effective strategy in NDs, where the interplay between surface effects and local microenvironment determine the optimal experimental conditions. Diamond ; Laser ; Vacancy defect ; Materials science ; Irradiation ; Electron paramagnetic resonance ; Fluorescence ; Chemical physics ; Paramagnetism ; Laser power scaling ; Condensed matter physics ; Optoelectronics ; Chemistry ; Nanotechnology ; Nuclear magnetic resonance ; Optics ; Physics Diamond and Carbon-based Materials Research ; High-pressure geophysics and materials ; Metal and Thin Film Mechanics
Authors: Gayatri S. Kamble Monika V. Jagtap
Source: Mathematical Statistician and Engineering Applications (article, 2022-04-15)
Field: Materials Science — Materials Chemistry

Synthesis of Nanoparticles of Aluminium–Boron complex for Radiation Sensor Radiation sensors based on thermo luminescence from nanoparticles of aluminium-boron complex for gamma radiation have been reported. Crystal chemistry of aluminium boride is quite complicated and is derived from complex tetragonal modification of boron. The crystal structure varies with the method of preparation and energy band gap contains defect states governed by the temperature during synthesis. There are various methods of preparing nanoparticles like boll milling, sol-gel and RF-thermal plasma. In the present studies Aluminum boron complex nanoparticles were synthesized by DC- transferred arc thermal plasma method. The DC-transferred arc thermal plasma has been received great attention as a useful method to synthesize nanoparticles. Since a substance is easily evaporated in large volume of thermal plasma. A pure aluminium and boron powders were mixed together and made to evaporate from water cooled graphite after impinging thermal plasma plume. Argon with flow rate of 3L/min was used as a plasma forming gas for the evaporation of raw powder mixture in Ar ambient in the plasma reactor. The obtained nanoparticles of aluminum –boron complex were characterized using X-ray diffraction technique for structural analysis, Transmission electron microscopy (TEM) for morphological analysis and energy dispersive analysis by X-ray (EDAX) for elemental analysis. The aluminum boron complex so obtained was investigated for thermoluminscence properties. Materials science ; Nanoparticle ; Boron ; Aluminium ; Electric arc ; Transmission electron microscopy ; Analytical Chemistry (journal) ; Evaporation ; Plasma torch ; Plasma ; Graphite ; Chemical engineering ; Nanotechnology ; Metallurgy ; Chemistry ; Organic chemistry ; Physical chemistry Boron and Carbon Nanomaterials Research ; Polymer Nanocomposite Synthesis and Irradiation ; Diamond and Carbon-based Materials Research
Authors: Yuqi Bi | Dawei Xu | Lihui Yang | Lin Chu | Bo Zhang | Yanting Li
Source: Wireless Communications and Mobile Computing (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Nutritional Components of Beverage Granules by Near‐Infrared Spectroscopy Based on PLS Model The nutritional content of instant beverages sold in the market is uneven. The existing standards and regulatory system are not sound enough, and the phenomenon of the unknown nutritional content of ingredients frequently occurs, which makes the beverage lose its nutritional characteristics, and long‐term drinking may cause harm to consumers’ health. Therefore, it is necessary to strengthen the quality and safety supervision of beverage granules and carry out quality and authenticity inspections and evaluations. The purpose of this study is to collect samples of milk tea powder and to detect its protein, total sugar, ash, fat, and moisture content. By analyzing its near‐infrared spectral characteristics, the paper establishes the NIR (near‐infrared spectrum) rapid detection model and the PLS (partial least square) model of protein and fat in milk powder. The study uses external inspection and cross‐validation to judge the reliability of the model. The results showed that the relative error of protein was less than 1.9%, and the relative error of fat was less than 1.5%, which indicated that the model had good predictability. It provides a new strategy for the quality evaluation and formula process identification of milk tea powder. It also provides a strong reference for the improvement of local standards and the formulation of national standards for milk tea powder. The study provides strong data support for illegal businesses to take effective actions to abuse consumer sentiment and take advantage of the regulatory vacuum period. Quality (philosophy) ; Harm ; Computer science ; Food science ; Predictability ; Reliability (semiconductor) ; Business ; Environmental science ; Mathematics ; Statistics ; Chemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: Utkarsh Pangle | Bhide | R Upton | B David | S Gafner | Madan Mohan | Rastogi | & Subha | Ajay Rawat | A Gopal | S Reddy | V Gayatri | Umme Habiba | Md Rasel | Md Howlader | Rahat Islam | Md Hossain Faisal | Rahman | R Janani | Dr Vijayashree | Venkataraman | N Mangayarkarasi | Shitala Prasad | P Pankaj | Singh | M Dileep | P Pournami | C Amuthalingeswaran | Mr Sivakumar | Dr Renuga | Amala Sabu | K Sreekumar | R Rahul | Nair
Source: International Research Journal of Modernization in Engineering Technology and Science (article, 2022-10-02)
Field: Chemistry — Analytical Chemistry

IDENTIFICATION OF MEDICAL PLANTS USING HAAR CASCADE CLASSIFIER The accurate study and management of biodiversity depend on being able to identify plant species. Different plant traits are evaluated as identification keys in a manual identification method, and these identification keys are then sequentially and adaptively analyzed to identify plant species. The manual method, however, is timeand labor-intensive. Recently, technological advancement has demanded more effective ways to satisfy species identification needs, such as developing digital image processing and pattern recognition tools. There are still difficulties in correctly automating the identification of plant species, despite the existence of several research. A real-time automated approach for identifying therapeutic plant species was suggested in this study. Four distinct species of medicinal plants had their leaves harvested. It has been demonstrated how to automatically recognize medicinal plants using computer vision and the Haar cascade classifier. The suggested approach has a 60% overall accuracy rate. Cascade ; Artificial intelligence ; Haar-like features ; Haar ; Classifier (UML) ; Identification (biology) ; Computer science ; Pattern recognition (psychology) ; Engineering ; Biology ; Botany ; Face detection Spectroscopy and Chemometric Analyses
Authors: Hannah Kniesel | Timo Ropinski | Tim Bergner | Kavitha Shaga Devan | Clarissa Read | Paul Walther | Tobias Ritschel | Pedro Hermosilla
Source: arXiv (Cornell University) (preprint, 2022-03-29)
Field: Materials Science — Surfaces, Coatings and Films

Clean Implicit 3D Structure from Noisy 2D STEM Images Scanning Transmission Electron Microscopes (STEMs) acquire 2D images of a 3D sample on the scale of individual cell components. Unfortunately, these 2D images can be too noisy to be fused into a useful 3D structure and facilitating good denoisers is challenging due to the lack of clean-noisy pairs. Additionally, representing a detailed 3D structure can be difficult even for clean data when using regular 3D grids. Addressing these two limitations, we suggest a differentiable image formation model for STEM, allowing to learn a joint model of 2D sensor noise in STEM together with an implicit 3D model. We show, that the combination of these models are able to successfully disentangle 3D signal and noise without supervision and outperform at the same time several baselines on synthetic and real data. Computer science ; Noise (video) ; Artificial intelligence ; Differentiable function ; Sample (material) ; SIGNAL (programming language) ; Image (mathematics) ; Scale (ratio) ; 3d model ; Computer vision ; Pattern recognition (psychology) ; Algorithm ; Mathematics Electron and X-Ray Spectroscopy Techniques ; Image Processing Techniques and Applications ; Advanced Electron Microscopy Techniques and Applications
Authors: Nguyen Minh Quang | Tran Nguyen Minh An | Phạm Văn Tất
Source: Vietnam Journal of Catalysis and Adsorption (article, 2022-01-30)
Field: Materials Science — Materials Chemistry

Development of new metal-thiosemicarbazone complexes using visual screening methods and in silico models The stability constants (logb11) of forty-two new metal-thiosemicarbazone complexes were predicted based on the results of the quantitative structure-property relationship (QSPR). The QSPR models were developed from 88 logb11 values of experimental complexes by using the multivariate linear regression (QSPRMLR) and artificial neural network (QSPRANN). Four descriptors such as xch9, xv0, core-core repulsion and cosmo area were found out in the best of the linear model QSPRMLR which was harshly evaluated by the statistical values: R2train = 0.864, Q2LOO = 0.840, SE = 0.711, Fstat = 131,355 and PRESS = 49.31. Furthermore, the artificial neural network model QSPRANN with architecture I(4)-HL(5)-O(1) was discovered with the same variables of the QSPRMLR model that the statistical results were extremely impressive as R2train = 0.970, Q2CV = 0.984 and Q2test = 0.974. Also, both of the QSPR models were externally validated on the data set of 18 logb11 values of independently experimental complexes. As a consequence, the results from the QSPR models could be used to calculate the stability constants of other new metal-thiosemicarbazones. Stabilizer (aeronautics) ; Particle size ; Nanoparticle ; Chemical engineering ; Materials science ; Nanotechnology ; Chemistry Copper-based nanomaterials and applications ; Nanomaterials for catalytic reactions ; Ionic liquids properties and applications
Authors: Ion Matei | Johan de Kleer | Maksym Zhenirovskyy
Source: arXiv (Cornell University) (preprint, 2022-09-08)
Field: Chemistry — Physical and Theoretical Chemistry

2D Density Control of Micro-Particles using Kernel Density Estimation We address the problem of 2D particle density control. The particles are immersed in dielectric fluid and acted upon by manipulating an electric field. The electric field is controlled by an array of electrodes and used to bring the particle density to a desired pattern using dielectrophoretic forces. We use a lumped, 2D, capacitive-based, nonlinear model describing the motion of a particle. The spatial dependency of the capacitances is estimated using electrostatic COMSOL simulations. We formulate an optimal control problem, where the loss function is defined in terms of the error between the particle density at some final time and a target density. We use a kernel density estimator (KDE) as a proxy for the true particle density. The KDE is computed using the particle positions that are changed by varying the electrode potentials. We showcase our approach through numerical simulations, where we demonstrate how the particle positions and the electrode potentials vary when shaping the particle positions from a uniform to a Gaussian distribution. Kernel density estimation ; Probability density function ; Estimator ; Electric field ; Particle density ; Particle (ecology) ; Capacitive sensing ; Density estimation ; Kernel (algebra) ; Statistical physics ; Mechanics ; Physics ; Classical mechanics ; Computer science ; Mathematics ; Plasma ; Statistics Electrostatics and Colloid Interactions ; Microfluidic and Bio-sensing Technologies ; Modular Robots and Swarm Intelligence
Authors: Ilian T. Todorov
Source: Open Research Europe (article, 2022-08-01)
Field: Materials Science — Ceramics and Composites

Evolving requirements for materials modelling software and underlying method developments: an inventory and future outlook This European Materials Modelling Council (EMMC) study provides an outline of the survey intent and ambitions, followed by an analysis of the results and a follow up discussion, focused on the future perspectives of the EMMC. The survey covers materials modelling and characterisation communities in both academia and industry. It provides a profile of the surveyed players in these communities and a scaled measure on their usage of computational methodologies. The survey outcomes include: (i) summary views of the recent as well as perceived future trends of materials modelling and its associated fields, with respect to two focus areas surveyed, Model Development and Software, (ii) the main adoption factors and associated bottlenecks for computational methods and software, (iii) the most targeted materials properties and digital twins approaches, and (iv) the wider communities expectations of how EMMC can help facilitate, fulfil and drive further the European Materials Modelling Roadmap to the benefit of the European Commission's (ECs') research and innovation. European commission ; Software ; Management science ; Computer science ; Focus (optics) ; Data science ; Engineering management ; Systems engineering ; Engineering ; Business ; European union Advanced ceramic materials synthesis ; Additive Manufacturing and 3D Printing Technologies ; Material Selection and Properties
Authors: Edgar Acosta
Source: ChemRxiv (preprint, 2022-08-08)
Field: Chemistry — Spectroscopy

Hildebrand-Assessed Margules (HAM) interaction parameter: applications to surfactant and polar oil partition The Hildebrand-Assessed Margules (HAM) method uses Henry's law constant and vapor pressure for pure components from free cheminformatic software to obtain the interaction parameter of a component "i" with water (Aiw) and its molar volume (Vmi). Inspired by the concept of the solubility parameter of Hildebrand (δi), where (Aiw/Vmi)^0.5 = (δi-δw), HAM makes a simple assessment of the binary interaction parameter Aij: (δi-δj) =(Aij/Vmi)^0.5 = (δi-δw)-(δi-δw)= (Aiw/Vmi)^0.5- (Ajw/Vmi)^0.5. The Aij predictions from this relatively simple expression were compared to literature Aij data obtained from activity coefficients of "i" at infinite dilution in a solvent "j". The performance of the HAM framework was compared to other predictive models, UNIFAC, MOSCED, COSMO-RS, HSP and the original Hildebrand model. The HAM method overpredicted Aij (>1Aij unit) in systems where the solvent was an acid or a base that could dissociate in the presence of water. However, for most systems (small polar molecules, short chain alcohols, medium chain alcohols, aromatics and alkanes), the Aij values were predicted within 1 Aij unit and commonly within 0.5 Aij units. A systemic underprediction of Aij was observed when the HAM-predicted log P was compared to predictions from the ACD/Labs software, which required the introduction of a correction term. The corrected HAM method reproduced the partition coefficient of surfactant and polar molecules with an RMSE of 1.05 and an NRMSE of 15%, comparable to other models that require more inputs and resources. Chemistry ; UNIFAC ; Thermodynamics ; Activity coefficient ; Flory–Huggins solution theory ; Solubility ; Hildebrand solubility parameter ; Partition coefficient ; Solvent ; Vapor pressure ; Chromatography ; Physical chemistry ; Organic chemistry ; Aqueous solution ; Polymer ; Physics Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Crystallization and Solubility Studies
Authors: Xiang Xu | Yiyun Cao | Wentao Xiao | Zhengyong Zhang
Source: Research Square (preprint, 2022-10-13)
Field: Chemistry — Analytical Chemistry

Fused Lasso Logistic Matrix Regression Method for Multi- Source Data Fusion of Raman Spectroscopy Computer science ; Sensor fusion ; Iterative and incremental development ; Lasso (programming language) ; Spectrometer ; Iterative method ; Algorithm ; Fuse (electrical) ; Matrix (chemical analysis) ; Process (computing) ; Data mining ; Pattern recognition (psychology) ; Artificial intelligence ; Chemistry ; Engineering ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Lizhuo Ai | Aleksandra Binek | Simion Kreimer | Matthew Ayres | Aleksandr Stotland | Jennifer E. Van Eyk
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-12-29)
Field: Chemistry — Spectroscopy

High Field Asymmetric Waveform Ion Mobility Spectrometry-Mass Spectrometry to Enhance Cardiac Muscle Proteome Coverage Abstract Heart tissue sample preparation for mass spectrometry (MS) analysis that includes pre-fractionation reduces the cellular protein dynamic range and increases the relative abundance of non-sarcomeric proteins. We previously described “IN-Sequence” (IN-Seq) where heart tissue lysate is sequentially partitioned into three subcellular fractions to increase the proteome coverage than a single direct tissue analysis by mass spectrometry. Here, we report an adaptation of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled to mass spectrometry, and the establishment of a simple one step sample preparation coupled with gas-phase fractionation. FAIMS approach substantially reduces manual sample handling, significantly shortens MS instrument processing time, and produces unique protein identification and quantification approximating the commonly used IN-Seq method in for less time requirement. Ion-mobility spectrometry ; Mass spectrometry ; Proteome ; Chemistry ; Fractionation ; Chromatography ; Proteomics ; Analytical Chemistry (journal) ; Biochemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Nan Hu | Qinggong Mao | Xibin Sun | Qianhao Xu | Meimei Li | Hao Chen
Source: Research Square (preprint, 2022-07-13)
Field: Materials Science — Biomaterials

Aren't aluminum and iron resorbed from old leaves? Abstract Purpose Leaf resorption is an important mechanism for plant nutrient conservation, but not all elements are resorbed by plants. It is believed that aluminum (Al) and iron (Fe) are accumulated in old leaves rather than be resorbed due to their toxic effects, but this view never be systematically evaluated. Methods Here, a data synthesis was conducted to explore the patterns and controls on leaf resorption efficiency of Al and Fe, based on 34 published studies with 272 data points. Results The resorption efficiency of Al was positive in conifer plants (11.3%), but was negative in deciduous and evergreen plants (-94.2% and − 111.2%, respectively). The resorption efficiency of Fe was positive in nitrogen-fixing plants (39.2%), but was negative in non-nitrogen-fixing plants (-37.0%). Lower soil pH favored the leaf Al resorption, but limited the leaf Fe resorption. Higher precipitation inhibited the leaf Fe resorption. Conclusions In contrast to the general belief, our study highlights that Al and Fe can be resorbed from old leaves, depending mainly on plant species and soil environment. This knowledge is an important supplement for understanding leaf nutrient resorption process, and is helpful for modeling global biogeochemical cycle. Resorption ; Evergreen ; Nutrient ; Deciduous ; Biogeochemical cycle ; Botany ; Nitrogen ; Chemistry ; Soil nutrients ; Agronomy ; Horticulture ; Biology ; Environmental chemistry ; Organic chemistry Clay minerals and soil interactions ; Plant Micronutrient Interactions and Effects ; Aluminum toxicity and tolerance in plants and animals