jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Galina Smolikova | Daria Gorbach | Elena Lukasheva | Gregory Mavropolo-Stolyarenko | Tatiana Bilova | Alena Soboleva | Alexander Tsarev | E. V. Romanovskaya | Е. P. Podolskaya | Vladimir A. Zhukov | И. А. Тихонович | С.С. Медведев | Wolfgang Hoehenwarter | Andrej Frolov
Source: International Journal of Molecular Sciences (review, 2020-12-01)
Field: Chemistry — Spectroscopy

Bringing New Methods to the Seed Proteomics Platform: Challenges and Perspectives For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins, and carbohydrates in their seeds, distinctly dominate modern agriculture, thus play an essential role in food industry and fuel production. Therefore, seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, seed development and germination as well as age- and stress-related alterations in seed vigor, longevity, nutritional value, and safety can be addressed by a broad panel of analytical, biochemical, and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes accompanying plant development, senescence, and response to biotic or abiotic stress. Among individual post-genomic methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. During the recent decades, multiple methodological advances were introduced in different branches of life science, although only some of them were established in seed proteomics so far. Therefore, here we discuss main methodological approaches already employed in seed proteomics, as well as those still waiting for implementation in this field of plant research, with a special emphasis on sample preparation, data acquisition, processing, and post-processing. Thereby, the overall goal of this review is to bring new methodologies emerging in different areas of proteomics research (clinical, food, ecological, microbial, and plant proteomics) to the broad society of seed biologists. Proteomics ; Biotechnology ; Biology ; Agriculture ; Genomics ; Abiotic stress ; Data science ; Computer science ; Ecology ; Genome Advanced Proteomics Techniques and Applications ; Soybean genetics and cultivation ; Mass Spectrometry Techniques and Applications
Authors: Leon Sprave | Andreas Menzel
Source: Acta Mechanica (article, 2020-09-30)
Field: Materials Science — Materials Chemistry

A large strain gradient-enhanced ductile damage model: finite element formulation, experiment and parameter identification Abstract A gradient-enhanced ductile damage model at finite strains is presented, and its parameters are identified so as to match the behaviour of DP800. Within the micromorphic framework, a multi-surface model coupling isotropic Lemaitre-type damage to von Mises plasticity with nonlinear isotropic hardening is developed. In analogy to the effective stress entering the yield criterion, an effective damage driving force—increasing with increasing plastic strains—entering the damage dissipation potential is proposed. After an outline of the basic model properties, the setup of the (micro)tensile experiment is discussed and the importance of including unloading for a parameter identification with a material model including damage is emphasised. Optimal parameters, based on an objective function including measured forces and the displacement field obtained from digital image correlation, are identified. The response of the proposed model is compared to a tensile experiment of a specimen with a different geometry as a first approach to validate the identified parameters. Solid mechanics ; von Mises yield criterion ; Finite element method ; Isotropy ; Materials science ; Plasticity ; Digital image correlation ; Ultimate tensile strength ; Nonlinear system ; Mechanics ; Structural engineering ; Hardening (computing) ; Composite material ; Physics ; Engineering Microstructure and mechanical properties ; Metal Forming Simulation Techniques ; Advanced Surface Polishing Techniques
Authors: Kai-Kuang Wu | Yu‐Liang Chen | J.R. Yeh | Wei‐Lun Chen | Chia-Shih Lin
Source: Advances in Materials Science and Engineering (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Ballistic Impact Performance of SiC Ceramic‐Dyneema Fiber Composite Materials This study investigated the ballistic resistance of a composite target plate fabricated by combining SiC ceramic with the Dyneema fiber. To achieve a light‐weight target plate that conforms to the US National Institute of Justice level four (NIJ IV) standards, minimal areal density analysis was conducted to obtain the optimal SiC ceramic‐Dyneema fiber thickness combination. This study used energy absorption to analyze the ballistic resistance of the target plates. To drastically reduce experimental costs, most of this work employed ANSYS/LS‐DYNA software to conduct finite element numerical simulations. First, ballistic experiments that conformed to NIJ IV standards were conducted to verify the simulation parameter configurations. Subsequently, the correlation function of the relationship between the combined thickness of the composite material and its ballistic resistance was determined through the experimental design, which effectively reduced the simulation analysis time. According to simulation experiments and regression analysis, the equation for the relationship between the combined thickness of the composite material and its ballistic resistance was , though there were limitations to its application. From the numerical analysis results, 8.1940 mm SiC ceramic and 6.9637 mm Dyneema fiber were determined to constitute the optimal thickness combination for a composite that features a minimal areal density and which conforms to NIJ IV standards. The combination was verified to be consistent with the numerical simulation analysis results. Materials science ; Ceramic ; Composite material ; Composite number ; Fiber ; Ballistic impact ; Finite element method ; Computer simulation ; Area density ; Structural engineering ; Simulation ; Computer science ; Engineering High-Velocity Impact and Material Behavior ; Energetic Materials and Combustion ; Mechanical Behavior of Composites
Authors: Jian Wang | Chu Zhang | Ying Shi | Meijuan Long | Faisal Islam | Chong Yang | Su Yang | Yong He | Weijun Zhou
Source: Plant Methods (article, 2020-03-05)
Field: Chemistry — Analytical Chemistry

Evaluation of quinclorac toxicity and alleviation by salicylic acid in rice seedlings using ground-based visible/near-infrared hyperspectral imaging We develop a reliable and effective model using hyperspectral imaging technique which enables the evaluation and visualization of herbicide toxicity for rice. The reflectance spectra variations of rice could reveal the stress status of herbicide toxicity in rice along with the physiological parameters. The visualization of the herbicide toxicity in rice would help to provide the intuitive vision of herbicide toxicity in rice. A monitoring system for detecting herbicide toxicity and its alleviation by SA will benefit from the remarkable success of SVC models and distribution maps. Hyperspectral imaging ; Salicylic acid ; Toxicity ; Infrared ; Chemistry ; Remote sensing ; Optics ; Physics ; Geology ; Biochemistry Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Isotope Analysis in Ecology
Authors: Meng Zhang | Huaiqing Zhang | Xinyu Li | Yang Liu | Yaotong Cai | Hui Lin
Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

Classification of Paddy Rice Using a Stacked Generalization Approach and the Spectral Mixture Method Based on MODIS Time Series Paddy rice is a major stable food, accounting for about 20% world's food supply. And the rice paddy, an important artificial wetland type, plays an important role in the regional ecological environment. This study proposes a stacked generalization and spectral mixture approach to map paddy rice using coarse spatial resolution images [Moderate Resolution Imaging Spectralradiometer, (MODIS)]. By this method, the time series MODIS enhanced vegetation index images, phenological variables, land surface water index, elevation, and slope images are all employed to produce the optimal feature combination, which is then used to map paddy rice by the stacking algorithm. The validation experiment using the data of the Dongting Lake area showed that the proposed method can improve the overall accuracy of single classifiers, including the support vector machine, random forest, k-nearestneigbor (kNN), extreme gradient boosting (XGB), and decision tree. Stacking (XGB) achieves the highest overall accuracy (90.3%) and Kappa coefficient (0.86), which are 2.8% and 0.03 higher than that of using the single kNN classifier. Furthermore, its user accuracies for distinguishing double-cropping rice and single-season rice are 92.5% and 90.0%, respectively. In terms of the paddy rice classification accuracy, the stacking model is also superior to single classifiers. Moreover, the MODIS-derived rice map obtained by the stacked generalization approach and the spectral mixture method area has a large determination coefficient (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.9975) with the government statistic data. The results demonstrate the potential of the proposed method in using coarse spatial resolution images for large-scale paddy rice mapping. Generalization ; Time series ; Series (stratigraphy) ; Computer science ; Remote sensing ; Artificial intelligence ; Pattern recognition (psychology) ; Spectral analysis ; Algorithm ; Machine learning ; Mathematics ; Geology Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Remote Sensing in Agriculture
Authors: Zhiqi Hong | Yong He
Source: Applied Sciences (article, 2020-02-10)
Field: Chemistry — Analytical Chemistry

Rapid and Nondestructive Discrimination of Geographical Origins of Longjing Tea using Hyperspectral Imaging at Two Spectral Ranges Coupled with Machine Learning Methods Longjing tea is one of China’s protected geographical indication products with high commercial and nutritional value. The geographical origin of Longjing tea is an important factor influencing its commercial and nutritional value. Hyperspectral imaging systems covering the two spectral ranges of 380–1030 nm and 874–1734 nm were used to identify a single tea leaf of Longjing tea from six geographical origins. Principal component analysis (PCA) was conducted on hyperspectral images to form PCA score images. Differences among samples from different geographical origins were visually observed from the PCA score images. Support vector machine (SVM) and partial least squares discriminant analysis (PLS-DA) models were built using the full spectra at the two spectral ranges. Decent classification performances were obtained at the two spectral ranges, with the overall classification accuracy of the calibration and prediction sets over 84%. Furthermore, prediction maps for geographical origins identification of Longjing tea were obtained by applying the SVM models on the hyperspectral images. The overall results illustrate that hyperspectral imaging at both spectral ranges can be applied to identify the geographical origin of single tea leaves of Longjing tea. This study provides a new, rapid, and non-destructive alternative for Longjing tea geographical origins identification. Hyperspectral imaging ; Pattern recognition (psychology) ; Principal component analysis ; Support vector machine ; Artificial intelligence ; Spectral signature ; Computer science ; Mathematics ; Remote sensing ; Geography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Metabolomics and Mass Spectrometry Studies
Authors: Carlos Henrique Queiroz Rego | Fabiano França‐Silva | Francisco Guilhien Gomes | Maria Heloísa Duarte de Moraes | André Dantas de Medeiros | Clíssia Barboza da Silva
Source: Agriculture (article, 2020-08-17)
Field: Chemistry — Analytical Chemistry

Using Multispectral Imaging for Detecting Seed-Borne Fungi in Cowpea Recent advances in multispectral imaging-based technology have provided useful information on seed health in order to optimize the quality control process. In this study, we verified the efficiency of multispectral imaging (MSI) combined with statistical models to assess the cowpea seed health and differentiate seeds carrying different fungal species. Seeds were artificially inoculated with Fusarium pallidoroseum, Rhizoctonia solani and Aspergillus sp. Multispectral images were acquired at 19 wavelengths (365 to 970 nm) from inoculated seeds and freeze-killed ‘incubated’ seeds. Statistical models based on linear discriminant analysis (LDA) were developed using reflectance, color and texture features of the seed images. Results demonstrated that the LDA-based models were efficient in detecting and identifying different species of fungi in cowpea seeds. The model showed above 92% accuracy before incubation and 99% after incubation, indicating that the MSI technique in combination with statistical models can be a useful tool for evaluating the health status of cowpea seeds. Our findings can be a guide for the development of in-depth studies with more cultivars and fungal species, isolated and in association, for the successful application of MSI in the routine health inspection of cowpea seeds and other important legumes. Multispectral image ; Rhizoctonia solani ; Fusarium ; Biology ; Reflectivity ; Hyperspectral imaging ; Horticulture ; Artificial intelligence ; Computer science Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: Chaochao Yan | Sheng Wang | Jinyu Yang | Tingyang Xu | Junzhou Huang
Source:  (article, 2020-09-21)
Field: Materials Science — Materials Chemistry

Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation Molecule generation is to design new molecules with specific chemical properties and further to optimize the desired chemical properties. Following previous work, we encode molecules into continuous vectors in the latent space and then decode the embedding vectors into molecules under the variational autoencoder (VAE) framework. We investigate the posterior collapse problem of the current widely-used RNN-based VAEs for the molecule sequence generation. For the first time, we point out that the underestimated reconstruction loss of VAEs leads to the posterior collapse, and we also provide both analytical and experimental evidences to support our findings. To fix the problem and avoid the posterior collapse, we propose an effective and efficient solution in this work. Without bells and whistles, our method achieves the state-of-the-art reconstruction accuracy and competitive validity score on the ZINC 250K dataset. When generating 10,000 unique valid molecule sequences from the random prior sampling, it costs the JT-VAE 1450 seconds while our method only needs 9 seconds on a regular desktop machine. Autoencoder ; Embedding ; Computer science ; Sequence (biology) ; ENCODE ; Sampling (signal processing) ; Algorithm ; State (computer science) ; Artificial intelligence ; Deep learning ; Chemistry ; Computer vision Machine Learning in Materials Science ; Molecular Biology Techniques and Applications ; Image Processing Techniques and Applications
Authors: Zeynep Mine Şenol | Selçuk Şimşek | Ali Özer | Dilek Şenol Arslan
Source: Journal of Radioanalytical and Nuclear Chemistry (article, 2020-11-19)
Field: Chemistry — Inorganic Chemistry

Synthesis and characterization of chitosan–vermiculite composite beads for removal of uranyl ions: isotherm, kinetics and thermodynamics studies Uranyl ; Adsorption ; Epichlorohydrin ; Endothermic process ; Chemistry ; Point of zero charge ; Vermiculite ; Langmuir adsorption model ; Aqueous solution ; Chitosan ; Chemical engineering ; Composite number ; Fourier transform infrared spectroscopy ; Nuclear chemistry ; Materials science ; Ion ; Physical chemistry ; Polymer chemistry ; Organic chemistry ; Composite material Radioactive element chemistry and processing ; Adsorption and biosorption for pollutant removal ; Covalent Organic Framework Applications
Authors: Sawsan Zaghlol | Wael A. Amer | M. H. Shaaban | Mohamad M. Ayad | Patrycja Bober | Jaroslav Stejskal
Source: Chemical Papers (article, 2020-04-13)
Field: Materials Science — Polymers and Plastics

Conducting macroporous polyaniline/poly(vinyl alcohol) aerogels for the removal of chromium(VI) from aqueous media Aerogel ; Polyaniline ; Adsorption ; Freundlich equation ; Aqueous solution ; Hexavalent chromium ; Vinyl alcohol ; Desorption ; Chromium ; Chemical engineering ; Materials science ; Absorption (acoustics) ; Chemistry ; Nuclear chemistry ; Organic chemistry ; Polymer ; Composite material ; Polymerization Conducting polymers and applications ; Adsorption and biosorption for pollutant removal ; Covalent Organic Framework Applications
Authors: Benjamin Christiaen | Christophe Domain | Ludovic Thuinet | Antoine Ambard | Alexandre Legris
Source: Acta Materialia (article, 2020-06-10)
Field: Materials Science — Materials Chemistry

Influence of vacancy diffusional anisotropy: Understanding the growth of zirconium alloys under irradiation and their microstructure evolution Materials science ; Anisotropy ; Microstructure ; Zirconium ; Diffusion ; Vacancy defect ; Dislocation ; Anisotropic diffusion ; Kinetic Monte Carlo ; Work (physics) ; Irradiation ; Zirconium alloy ; Condensed matter physics ; Deformation (meteorology) ; Perpendicular ; Plane (geometry) ; Crystallography ; Monte Carlo method ; Chemical physics ; Metallurgy ; Thermodynamics ; Composite material ; Geometry ; Optics ; Nuclear physics ; Physics Nuclear Materials and Properties ; Fusion materials and technologies ; High Temperature Alloys and Creep
Authors: Justus F. Hoffmann | Andreas H. Roos | Franz‐Josef Schmitt | Dariush Hinderberger | Wolfgang H. Binder
Source: Angewandte Chemie International Edition (article, 2020-12-30)
Field: Chemistry — Organic Chemistry

Fluorescent and Water Dispersible Single‐Chain Nanoparticles: Core–Shell Structured Compartmentation Single-chain nanoparticles (SCNPs) are highly versatile structures resembling proteins, able to function as catalysts or biomedical delivery systems. Based on their synthesis by single-chain collapse into nanoparticular systems, their internal structure is complex, resulting in nanosized domains preformed during the crosslinking process. In this study we present proof of such nanocompartments within SCNPs via a combination of electron paramagnetic resonance (EPR) and fluorescence spectroscopy. A novel strategy to encapsulate labels within these water dispersible SCNPs with hydrodynamic radii of ≈5 nm is presented, based on amphiphilic polymers with additional covalently bound labels, attached via the copper catalyzed azide/alkyne "click" reaction (CuAAC). A detailed profile of the interior of the SCNPs and the labels' microenvironment was obtained via electron paramagnetic resonance (EPR) experiments, followed by an assessment of their photophysical properties. Electron paramagnetic resonance ; Amphiphile ; Nanoparticle ; Azide ; Fluorescence ; Electron paramagnetic resonance spectroscopy ; Polymer ; Materials science ; Covalent bond ; Chemical engineering ; Nanotechnology ; Copolymer ; Photochemistry ; Chemistry ; Polymer chemistry ; Organic chemistry ; Nuclear magnetic resonance ; Physics ; Composite material Click Chemistry and Applications ; Advanced Polymer Synthesis and Characterization ; Molecular Junctions and Nanostructures
Authors: Tanguy Jousselin‐Oba | Masashi Mamada | Atsushi Okazawa | Jérôme Marrot | Takayuki Ishida | Chihaya Adachi | Abderrahim Yassar | Michel Frigoli
Source: Chemical Science (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Modulating the ground state, stability and charge transport in OFETs of biradicaloid hexahydro-diindenopyrene derivatives and a proposed method to estimate the biradical character Biradicaloid compounds with an open-shell ground state have been the subject of intense research in the past decade. Although diindenoacenes are one of the most developed families, only a few examples have been reported as active layers in organic field-effect transistors (OFETs) with a charge mobility of around 10<sup>-3</sup> cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup> due to a steric disadvantage of the mesityl group to kinetically stabilize compounds. Herein, we disclose our efforts to improve the charge transport of the diindenoacene family based on hexahydro-diindenopyrene (HDIP) derivatives with different annelation modes for which the most reactive position has been functionalized with (triisopropylsilyl)ethynyl (TIPS) groups. All the HDIP derivatives show remarkably higher stability than that of TIPS-pentacene, enduring for 2 days to more than 30 days, which depends on the oxidation potential, the contribution of the singlet biradical form in the ground state and the annelation mode. The annelation mode affects not only the band gap and the biradical character (<i>y</i> <sub>0</sub>) but also the value of the singlet-triplet energy gap (Δ<i>E</i> <sub>S-T</sub>) that does not follow the reverse trend of <i>y</i> <sub>0</sub>. A method based on comparison between experimental and theoretical bond lengths has been disclosed to estimate <i>y</i> <sub>0</sub> and shows that <i>y</i> <sub>0</sub> computed at the projected unrestricted Hartree-Fock (PUHF) level is the most relevant among those reported by all other methods. Thanks to their high stability, thin-film OFETs were successfully fabricated. Well balanced ambipolar transport was obtained in the order of 10<sup>-3</sup> cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup> in the bottom-gate/top-contact configuration, and unipolar transport in the top-gate/bottom-contact configuration was obtained in the order of 10<sup>-1</sup> cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup> which is the highest value obtained for biradical compounds with a diindenoacene skeleton. Character (mathematics) ; Ground state ; Charge (physics) ; Chemistry ; Stability (learning theory) ; Computational chemistry ; State (computer science) ; Computer science ; Mathematics ; Physics ; Algorithm ; Atomic physics ; Quantum mechanics Synthesis and Properties of Aromatic Compounds ; Organic Electronics and Photovoltaics ; Conducting polymers and applications
Authors: Pravin Shende | Amar M. Patil | Bala Prabhakar
Source: Journal of Drug Delivery Science and Technology (article, 2020-01-14)
Field: Materials Science — Surfaces, Coatings and Films

Layer-by-layer technique for enhancing physicochemical properties of actives Nanocarriers ; Nanotechnology ; Polyelectrolyte ; Materials science ; Polymer ; Layer by layer ; Drug delivery ; Coating ; Chemistry ; Layer (electronics) Polymer Surface Interaction Studies ; 3D Printing in Biomedical Research ; Graphene and Nanomaterials Applications