jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Luca Telesca | Braddock K. Linsley | Lukasz Witek | Bärbel Hönisch
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-11-29)
Field: Materials Science — Biomaterials

Biomineralization and biomechanical trade-offs under heterogeneous environments in the eastern oyster <i>Crassostrea virginica</i> ABSTRACT Accurate biological models are critical to reliably predict vulnerability of marine organisms and ecosystems to rapid environmental changes. Current predictions on the biological impacts of climate change and human-caused disturbances primarily stem from controlled experiments but lack assessments of the mechanisms underlying biotic variations in natural systems. Such information is key to translating experimental models to natural populations, especially for habitat-forming, climate sensitive species with key ecological roles. This study aimed to characterize and quantify spatial patterns of shell biomineralization and biomechanical properties in a key reef-building oyster, Crassostrea virginica , collected from restored reefs along natural estuarine gradients in the Hudson River Estuary (NY, U.S.). We characterized patterns of oyster shell production (i.e., shape and thickness), structure (i.e., abundance of foliated and chalky calcite), mineralogy (i.e., crystal size and density), composition (i.e., organic matrix and Mg/Ca ratios), and mechanical performance (i.e., elastic modulus and hardness) at the macro and micro scale. Our results demonstrate a strong protective capacity of C. virginica for compensatory adjustments in shell biomineralization and biomechanics to maintain shell production and protective functions as a response to biotic and abiotic stressors. We reveal salinity as a key predictor of oyster shell structure, mechanical integrity, and resistance to dissolution, and describe the functional role of chalky calcite in shaping shell mechanical performance. Compensatory adjustments along salinity gradients indicate that oysters produce shells with i ) high mechanical resistance but increased vulnerability to dissolution under marine conditions, and ii ) lower structural integrity but higher protection from dissolution under brackish conditions. Our work illustrates that biomineralization and biomechanical adjustments may act as compensatory mechanisms in eastern oysters to maintain overall performance under heterogeneous estuarine environments, and could represent a cornerstone for calcifying organisms to acclimate and maintain their ecological functions in a rapidly changing climate. Crassostrea ; Biomineralization ; Abiotic component ; Oyster ; Ecosystem engineer ; Ecology ; Eastern oyster ; Environmental science ; Ecosystem ; Calcite ; Habitat ; Geology ; Biology ; Paleontology Calcium Carbonate Crystallization and Inhibition ; Marine Bivalve and Aquaculture Studies ; Ocean Acidification Effects and Responses
Authors: V Nirenjana | Mini Safaya B | K S Nikitha | P Nivedya | R Sharmeela
Source: International Journal for Research in Applied Science and Engineering Technology (review, 2023-04-30)
Field: Chemistry — Analytical Chemistry

A Review on Quality Scanner Device for Radish and Carrot using Image Processing Technique Abstract: Agriculture is the backbone of the Indian economy and productivity. The market value obtained from them is immense and effect both the export and quality valuation . Although grading and quality can be analysed by humans it is still inaccurate, time intensive, unreliable, subjective, and also hard which can be easily influenced by surrounding. Hence, there is an ultimate need for intelligent classification for vegetables. This paper focuses on Developing an analysis device for Radish (Raphanus raphanistrum ) and Carrot (Daucus carota subsp. sativus) which is an edible root vegetable grown in most parts of India. Radish and carrots are good sources of natural nitrates, minerals, calcium, and potassium. Thus, vegetables must be used as soon as possible to get a superior fresh character from them. External parameters such as size, shape, and quality factors of radish are important for finding out the total quality that is acceptable to the people. Various methods and algorithms are been put forwarded for the quality evaluation for the external defects present in it. Convolutional Neural Networks is the method used in image processing as this is more advantageous since it can learn special characteristics from images and by establish CNN for image classification where analyst have to gather the dataset. The requirement for doing this project is to have a computer and a python program for use the driver code. Image processing method is used for estimating quality of the particular food product efficiently in these days. This review paper examines current developments in methods for assessing food quality through image processing. The use of CNN (Convolutional Neural Networks) to identify characteristics of vegetables and its diseases through several built-in python libraries Daucus carota ; Raphanus ; Agricultural engineering ; Quality (philosophy) ; Computer science ; Python (programming language) ; Image processing ; Artificial intelligence ; Horticulture ; Engineering ; Image (mathematics) ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Marina Ņikitina
Source:  (article, 2023-04-17)
Field: Chemistry — Analytical Chemistry

Evaluation of Neural Network for Automated Classification of Plant Component on Histological Section Classification of plant component on image histological sections is critical for determining non-compliance type of undeclared additiveand further action for technologist, or other responsible person. However, this task is often challenging due to the absence of professional histologists or non-compliance with the conditions of microstructural analysis and also the subjective criteria for evaluation. In this study, we propose a machine learning model that automatically classifies the plant component on images histological sections. Our model uses a convolutional neural network to identify regions of plant components, then aggregates those classifications to infer predominant and minor plant components on histological sections image. We evaluated our model on an independent set of 95 images histological sections. It achieved a kappa score of 0.525 and an agreement of 66.6% with three histologists for classifying the predominant plant component, slightly higher than the inter-histologists kappa score of 0.485 and agreement of 62.7% on this test set. All evaluation metrics for our model and the three histologists were within 95% confidence intervals of agreement. Convolutional neural network ; Kappa ; Artificial intelligence ; Pattern recognition (psychology) ; Artificial neural network ; Component (thermodynamics) ; Set (abstract data type) ; Computer science ; Task (project management) ; Component analysis ; Data set ; Support vector machine ; Contextual image classification ; Image (mathematics) ; Mathematics ; Engineering Spectroscopy and Chemometric Analyses ; Digital Imaging for Blood Diseases ; Image Retrieval and Classification Techniques
Authors: S. Spezzano
Source: Nachrichten aus der Chemie (article, 2023-04-28)
Field: Chemistry — Spectroscopy

Trendbericht Physikalische Chemie 2023 (1/3): Astrochemistry of star and planet formation Abstract Stickstoff‐ und Kohlenstoffverbindungen im interstellaren Staub verraten, wie Sterne entstehen. Diese Moleküle haben Weltraumforscher:innen mit hochauflösender Rotationsspektroskopie detektiert und dazu die Verhältnisse im All im Labor nachgestellt. Wie organische Reaktionen wie nukleophile Substitution auf Molekülebene ablaufen, lässt sich mit Molekularstrahlmethoden herausfinden. Streumethoden dienen dazu, Reaktionen auf Oberflächen auf atomarer Ebene zu erfassen. Zeitaufgelöste Beugungsmethoden mit ultrakurzen Elektronen oder Röntgenphotonen werden zunehmend auf chemische Fragen angewandt, um Strukturen transienter Zustände zu beobachten. Astrobiology ; Planet ; Physics ; Chemistry ; Humanities ; Philosophy ; Astrophysics Molecular Spectroscopy and Structure ; Astrophysics and Star Formation Studies ; Atmospheric Ozone and Climate
Authors: Lukas Lampe | Johannes Neugebauer
Source: ChemRxiv (preprint, 2023-12-20)
Field: Materials Science — Materials Chemistry

Automatic orbital pair selection for multi-level local coupled-cluster based on orbital maps We present an automatic, orbital-map based orbital pair selection scheme for multi-level local coupled-cluster approaches that exploits the locality of chemical reactions and concentrates on the part of the molecule directly involved in the reaction. The previously introduced pair-selected multi-level extension to domain-based local pair natural orbital coupled-cluster with singles, doubles, and semi-canonical perturbative triples [DLPNO-CCSD(T0)] partitions the orbital pairs according to relative changes in pair correlation energies [J. Chem. Phys. 157, 064102 (2022)]. To this end, maps between localized orbitals are required which in turn require maps between the atoms of structures along reaction paths. So far, these atom maps have been manually determined, which can be a (human) time-consuming procedure. In order to automatize this procedure, we present an atom mapping algorithm based on the principle of minimum chemical distance that incorporates the orientation through dihedral angles. Within the methodology of this algorithm, linear assignment problems are addressed and explicitly solved, giving rise to the idea of considering the orbital mapping problem as such. This led to a new strategy to obtain orbital maps that proves advantageous over the previously used direct orbital selection. Along with a modified orbital pair prescreening, this results in an improved variant of the pair-selected multi-level DLPNO-CCSD(T0) method. For given combinations of pair selection thresholds, the performance of this approach is demonstrated for various reaction types showing a significant efficiency gain and accurate results due to beneficial, systematic error cancellation. The presented method operates in a black-box manner due to its fully-automatized algorithms with only the need to specify a single target-accuracy parameter. Core orbitals can be included in the correlation treatment in a computationally cheap way such that there is no need for the frozen-core approximation. Additionally, we demonstrate that basis set extrapolation techniques can be applied. Atomic orbital ; Coupled cluster ; Physics ; Cluster (spacecraft) ; Atom (system on chip) ; Orbital overlap ; Molecular orbital ; Computer science ; Algorithm ; Topology (electrical circuits) ; Mathematics ; Molecule ; Quantum mechanics ; Combinatorics Machine Learning in Materials Science ; Nonlinear Optical Materials Research ; Advanced Chemical Physics Studies
Authors: Fan Chen | Liu Tianbo | Guihua Hu | Ming-Lei Yang | Jian Long
Source: Нефтехимия (article, 2023-12-15)
Field: Chemistry — Analytical Chemistry

Online Determination on the Properties of Naphtha as the Ethylene Feedstock Using Near-Infrared Spectroscopy Providing real-time information on the properties of naphtha as the ethylene feedstock within the minimal time is significant for improvement of the process simulation, control, and real-time optimization. To develop models predicting naphtha properties for different pre-processing methods, an online full transmittance near-infrared (NIR) spectrum measurement system has been used along with the principal component regression and partial least squares (PLS) methods. The results show that the Savitzky-Golay smoothing combined with the first-derivative pre-processing provides the best denoising effect compared to other methods. The predicted relative errors of the NIR models developed by PLS, especially for the cutting temperature points of the test set, basically make 1‒5% indicating it can be used to create good NIR prediction models for the on-line determination of naphtha properties. Naphtha ; Raw material ; Ethylene ; Infrared spectroscopy ; Infrared ; Spectroscopy ; Materials science ; Chemistry ; Chemical engineering ; Organic chemistry ; Catalysis ; Engineering ; Optics Spectroscopy and Chemometric Analyses ; Thermodynamic properties of mixtures ; Chemical Thermodynamics and Molecular Structure
Authors: Aurore Finco | V. Jacques
Source: arXiv (Cornell University) (preprint, 2023-07-13)
Field: Materials Science — Materials Chemistry

Single spin magnetometry and relaxometry applied to antiferromagnetic materials Despite the considerable interest for antiferromagnets which appeared with the perspective of using them for spintronics, their experimental study, including the imaging of antiferromagnetic textures, remains a challenge. To address this issue, quantum sensors, and in particular the nitrogen-vacancy (NV) defects in diamond have become a widespread technical solution. We review here the recent applications of single NV centers to study a large variety of antiferromagnetic materials, from quantitative imaging of antiferromagnetic domains and non-collinear states, to the detection of spin waves confined in antiferromagnetic textures and the non-perturbative measurement of spin transport properties. We conclude with recent developments improving further the magnetic sensitivity of scanning NV microscopy, opening the way to detailed investigations of the internal texture of antiferromagnetic objects. Antiferromagnetism ; Spintronics ; Condensed matter physics ; Magnetometer ; Diamond ; Spin (aerodynamics) ; Materials science ; Relaxometry ; Texture (cosmology) ; Physics ; Ferromagnetism ; Magnetic field ; Spin echo ; Magnetic resonance imaging ; Computer science ; Medicine Diamond and Carbon-based Materials Research ; Electronic and Structural Properties of Oxides ; Force Microscopy Techniques and Applications
Authors: Mostafa Mohamed | Ali Shamaa | Saher Mohammed | A. M. Abdeen
Source: Egyptian Dental Journal /Egyptian Dental Journal (article, 2023-07-01)
Field: Materials Science — Materials Chemistry

COMPARISON BETWEEN SILVER DIAMINE FLUORIDE AND THEOBROMINE SOLUTIONS IN REMINERALIZATION OF DEMINERALIZED HUMAN ENAMEL [ SCANNING ELECTRON MICROSCOPE AND EDEX STUDY] Introduction: Dental caries in its initial phase formation can be remineralized by using fluoride, Although fluoride could be considered the first choice in caries prevention, overexposure to fluoride especially in children can cause side effects, so we need alternatives materials such as Theobromine and silver diamine fluoride that the most promising materials in the remineralization of demineralized enamel due to their advantages.Purpose: To compare between the solution forms of both theobromine and silver diamine fluoride in the remineralization potential of the demineralized human enamel. Materials & Methods: twenty sounds mandibular first premolar were divided into 4 equal groups (5 samples each):Control group (C) , demineralization group (D) subjected to demineralizing solution then 5 days PH cycle. The remaining two groups were similar to demineralization group with addition of treatment material “theobromine solution (T) and silver diamine fluoride solution (S) ,The samples were investigated by scanning electron microscope (SEM) and energy dispersive x-ray analysis (EDXA).Results: The enamel of demineralization group was porous exposing the subsurface enamel rods with severe rod core defects. Theobromine solution group showed improvement of the enamel surface, silver diamine Fluoride solution also showed improvement in the enamel surface but less than theobromine. EDXA revealed that the calcium phosphorus ratio displayed a descending order: (C > T > S > D). Conclusion: Theobromine solution and silver diamine fluoride are more effective remineralizing agents. But silver diamine Fluoride solution less than theobromine Remineralisation ; Enamel paint ; Scanning electron microscope ; Theobromine ; Materials science ; Fluoride ; Dental enamel ; Dentistry ; Chemistry ; Nuclear chemistry ; Inorganic chemistry ; Medicine ; Composite material ; Internal medicine Corrosion Behavior and Inhibition ; Aerogels and thermal insulation ; Silicone and Siloxane Chemistry
Authors: Barkha Shrivastava | Poonam Hariyani | Rekha Vijay
Source: Journal of Analysis and Computations (article, 2023-12-01)
Field: Chemistry — Organic Chemistry

Spiro-Heterocycle: Synthesis and Computational Study Heterocycles have achieved a prominent place among various classes of organic compounds for their diverse biological and medicinal activity. In the present paper a facile synthesis of spiroazabicycloadducts has been accomplished by [3+2] cycloaddition reaction of azomethine ylides, generated from 3-methyl-cyclopentane-1,2-dione and different secondary cyclic amino acids, with electron-deficient dipolarophiles in 62-70% yield. DFT calculations have been performed to understand the stereochemical course of the cycloaddition reactions. The products have been characterized by physical and spectroscopic techniques. Computer science Inorganic and Organometallic Chemistry ; Synthesis and biological activity
Authors: Kwai-Kong Ng | Min-Fong Yang
Source: arXiv (Cornell University) (preprint, 2023-10-20)
Field: Materials Science — Materials Chemistry

Unsupervised learning of phase transitions via modified anomaly detection with autoencoders In this paper, a modified method of anomaly detection using convolutional autoencoders is employed to predict phase transitions in several statistical mechanical models on a square lattice. We show that, when the autoencoder is trained with input data of various phases, the mean-square-error loss function can serve as a measure of disorder, and its standard deviation becomes an excellent indicator of critical points. We find that various types of phase transition points, including first-order, second-order, and topological ones, can be faithfully detected by the peaks in the standard deviation of the loss function. Besides, the values of transition points can be accurately determined under the analysis of finite-size scaling. Our results demonstrate that the present approach has general application in identification/classification of phase transitions even without a priori knowledge of the systems in question. Autoencoder ; Anomaly detection ; Standard deviation ; Mean squared error ; Scaling ; Pattern recognition (psychology) ; Computer science ; Artificial intelligence ; A priori and a posteriori ; Data point ; Phase transition ; Anomaly (physics) ; Square lattice ; Algorithm ; Unsupervised learning ; Mathematics ; Statistical physics ; Physics ; Deep learning ; Statistics ; Condensed matter physics Machine Learning in Materials Science ; Protein Structure and Dynamics
Authors: Hang Wong | Baiyang Liu | Jinyu Wu | Qingfeng Zhang
Source: Research Square (preprint, 2023-07-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multi-diverse metasurfaces for fast wide-angle sensing and through-wall imaging Abstract Multi-diverse metasurfaces play a crucial role in enhancing the capacity of sensing, radar, imaging, and communication systems through electromagnetic wave manipulation across different diversity controls. Currently, the primary approach for achieving multidimensional manipulation is through the use of dynamic metasurfaces. However, this method has drawbacks when it comes to fast sensing and imaging because of limitations in pattern switching speed. To address this issue, we propose a novel microwave-to-millimeter-wave meta-atom that provides polarization and frequency diversities. The meta-atoms formed in an array with a disordered permutation enable a wide-angle near-field fast sensing for tracking the moving trajectory of an object. Moreover, employing a dispersion-engineered strategy to arrange the meta-atoms in an array allows for high-gain through-wall imaging, enabling the detection of a sparse object with varying shapes and positions. The achieved result confirms that the proposed technology paves the way for developing multi-diverse metasurfaces that possess fast detecting and through-wall imaging capabilities. This breakthrough creates opportunities for identifying previously unseen modalities, and opens up new possibilities in various applications such as autonomous vehicles, all-weather sensing in surveillance, and radar integrated communication systems in 6G and beyond. Remote sensing ; Computer science ; Optics ; Materials science ; Physics ; Geology Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: Weizheng Cao | Juefei Wu | Yongkai Li | Cuiying Pei | Qi Wang | Yi Zhao | Changhua Li | Shihao Zhu | Mingxin Zhang | Lili Zhang | Yulin Chen | Zhiwei Wang | Yugui Yao | Yanpeng Qi
Source: arXiv (Cornell University) (preprint, 2023-10-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Pressure-induced Superconductivity and Structure Phase Transition in SnAs-based Zintl Compound SrSn2As2 Layered SnAs-based Zintl compounds exhibit a distinctive electronic structure, igniting extensive research efforts in areas of superconductivity, topological insulators and quantum magnetism. In this paper, we systematically investigate the crystal structures and electronic properties of the Zintl compound SrSn2As2 under high-pressure. At approximately 20.8 GPa, pressure-induced superconductivity is observed in SrSn2As2 with a characteristic dome-like evolution of Tc. Theoretical calculations together with high pressure synchrotron X-ray diffraction and Raman spectroscopy have identified that SrSn2As2 undergoes a structural transformation from a trigonal to a monoclinic structure. Beyond 28.3 GPa, the superconducting transition temperature is suppressed due to a reduction of the density of state at the Fermi level. The discovery of pressure-induced superconductivity, accompanied by structural transitions in SrSn2As2, greatly expands the physical properties of layered SnAs-based compounds and provides a new ground states upon compression. Superconductivity ; Condensed matter physics ; Raman spectroscopy ; Monoclinic crystal system ; Electronic structure ; Materials science ; Synchrotron ; Fermi level ; Crystal structure ; Phase (matter) ; Ground state ; Phase transition ; Crystallography ; Chemistry ; Physics ; Atomic physics ; Electron Iron-based superconductors research ; Electronic and Structural Properties of Oxides ; Physics of Superconductivity and Magnetism