jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Bart Van Puyvelde | Simon Daled | Sander Willems | Ralf Gabriels | Anne Gonzalez de Peredo | Karima Chaoui | Emmanuelle Mouton‐Barbosa | David Bouyssié | Kurt Boonen | Christopher J. Hughes | Lee A. Gethings | Yasset Pérez‐Riverol | Nic Bloomfield | Stephen Tate | Odile Burlet‐Schiltz | Lennart Martens | Dieter Deforce | Maarten Dhaenens
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-11-25)
Field: Chemistry — Spectroscopy

A comprehensive LFQ benchmark dataset on modern day acquisition strategies in proteomics In the last decade, a revolution in liquid chromatography-mass spectrometry (LC-MS) based proteomics was unfolded with the introduction of dozens of novel instruments that incorporate additional data dimensions through innovative acquisition methodologies, in turn inspiring specialized data analysis pipelines. Simultaneously, a growing number of proteomics datasets have been made publicly available through data repositories such as ProteomeXchange, Zenodo and Skyline Panorama. However, developing algorithms to mine this data and assessing the performance on different platforms is currently hampered by the lack of a single benchmark experimental design. Therefore, we acquired a hybrid proteome mixture on different instrument platforms and in all currently available families of data acquisition. Here, we present a comprehensive Data-Dependent and Data-Independent Acquisition (DDA/DIA) dataset acquired using several of the most commonly used current day instrumental platforms. The dataset consists of over 700 LC-MS runs, including adequate replicates allowing robust statistics and covering over nearly 10 different data formats, including scanning quadrupole and ion mobility enabled acquisitions. Datasets are available via ProteomeXchange (PXD028735). Benchmark (surveying) ; Data acquisition ; Computer science ; Data mining ; Proteomics ; Proteome ; Data science ; Bioinformatics ; Biology ; Geography Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Sebastian Ströh | Eric W. Hammerschmith | David W. Tank | H. Sebastian Seung | Adrian Wanner
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-06-20)
Field: Materials Science — Surfaces, Coatings and Films

<i>In situ</i> X-ray assisted electron microscopy staining for large biological samples Abstract Electron microscopy of biological tissue has recently seen an unprecedented increase in imaging throughput moving the ultrastructural analysis of large tissue blocks such as whole brains into the realm of the feasible. However, homogeneous, high quality electron microscopy staining of large biological samples is still a major challenge. To date, assessing the staining quality in electron microscopy requires running a sample through the entire staining protocol end-to-end, which can take weeks or even months for large samples, rendering protocol optimization for such samples to be inefficient. Here we present an in situ time-lapsed X-ray assisted staining procedure that opens the “black box” of electron microscopy staining and allows observation of individual staining steps in real time. Using this novel method we measured the accumulation of heavy metals in large tissue samples immersed in different staining solutions. We show that the measured accumulation of osmium in fixed tissue obeys empirically a quadratic dependence between the incubation time and sample size. We found that potassium ferrocyanide, a classic reducing agent for osmium tetroxide, clears the tissue after osmium staining and that the tissue expands in osmium tetroxide solution, but shrinks in reduced osmium solution. X-ray assisted staining gave access to the in situ staining kinetics and allowed us to develop a diffusion-reaction-advection model that accurately simulates the measured accumulation of osmium in tissue. These are first steps towards in silico staining experiments and simulation-guided optimization of staining protocols for large samples. Hence, X-ray assisted staining will be a useful tool for the development of reliable staining procedures for large samples such as entire brains of mice, monkeys or humans. Staining ; Osmium tetroxide ; Osmium ; Microscopy ; Electron microscope ; Chemistry ; Negative stain ; Pathology ; Biochemistry ; Optics ; Ruthenium ; Physics ; Medicine Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Molecular Biology Techniques and Applications
Authors: Kiattisin Kanjanawanishkul
Source: International Journal of Automation and Smart Technology (article, 2021-01-01)
Field: Materials Science — Biomaterials

An Image-based Eri Silkworm Pupa Grading Method Using Shape, Color, and Size Eri silkworm pupae are well known as an alternative for a protein food source. At present, they are sold as canned food for long-term preservation. Therefore, good quality and size consistency are essential. To evaluate quality and size, an image-based grading method was proposed. The image of pupae was taken and then shape features (i.e., solidity, aspect ratio, and extent) and color features based on three color models (i.e., RGB, HSV, and L*a*b*) were extracted. Two neural networks with 10-fold cross validation were separately developed for shape evaluation and color evaluation. After misshapen and discolored pupae were identified by neural networks, remaining pupae were graded into five size numbers according to their length: very small, small, medium, large, very large. Experimental results showed that the average accuracies for shape evaluation and color evaluation were 99.64% and 99.58%, respectively. The accuracy for size evaluation was 94%. Therefore, the proposed grading method reduces sorting time and increases sorting accuracy. RGB color model ; Artificial intelligence ; Pattern recognition (psychology) ; Grading (engineering) ; Mathematics ; Computer science ; Sorting ; Algorithm ; Engineering Silk-based biomaterials and applications
Authors: Reza Amani | Charles D. Schwieters | Collin G. Borcik | Isaac R. Eason | Ruixian Han | Benjamin D. Harding | Benjamin J. Wylie
Source: Frontiers in Molecular Biosciences (article, 2021-11-30)
Field: Chemistry — Spectroscopy

Water Accessibility Refinement of the Extended Structure of KirBac1.1 in the Closed State NMR structures of membrane proteins are often hampered by poor chemical shift dispersion and internal dynamics which limit resolved distance restraints. However, the ordering and topology of these systems can be defined with site-specific water or lipid proximity. Membrane protein water accessibility surface area is often investigated as a topological function via solid-state NMR. Here we leverage water-edited solid-state NMR measurements in simulated annealing calculations to refine a membrane protein structure. This is demonstrated on the inward rectifier K + channel KirBac1.1 found in Burkholderia pseudomallei . KirBac1.1 is homologous to human Kir channels, sharing a nearly identical fold. Like many existing Kir channel crystal structures, the 1p7b crystal structure is incomplete, missing 85 out of 333 residues, including the N-terminus and C-terminus. We measure solid-state NMR water proximity information and use this for refinement of KirBac1.1 using the Xplor-NIH structure determination program. Along with predicted dihedral angles and sparse intra- and inter-subunit distances, we refined the residues 1–300 to atomic resolution. All structural quality metrics indicate these restraints are a powerful way forward to solve high quality structures of membrane proteins using NMR. Dihedral angle ; Crystallography ; Solid-state nuclear magnetic resonance ; Membrane protein ; Protein structure ; Chemistry ; Structural biology ; Topology (electrical circuits) ; Molecular dynamics ; Crystal structure ; Membrane ; Chemical physics ; Hydrogen bond ; Computational chemistry ; Molecule ; Physics ; Nuclear magnetic resonance ; Mathematics ; Biochemistry Advanced NMR Techniques and Applications ; Superconductivity in MgB2 and Alloys ; Physics of Superconductivity and Magnetism
Authors: Ali Momeni | Hamid Rajabalipanah | Mahdi Rahmanzadeh | Ali Abdolali | Karim Achouri | Viktar Asadchy | Romain Fleury
Source: IEEE Transactions on Antennas and Propagation (preprint, 2021-05-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Reciprocal Metasurfaces for On-Axis Reflective Optical Computing Analog computing has emerged as a promising candidate for real-time and parallel continuous data processing. This article presents a reciprocal way for realizing asymmetric optical transfer functions (OTFs) in the reflection side of the on-axis processing channels. It is rigorously demonstrated that the presence of cross-polarization exciting normal polarizabilities (CPENPs) of a reciprocal metasurface circumvents the famous challenge of Green’s function approach in implementation of on-axis reflective optical signal processing while providing dual computing channels under orthogonal polarizations. Following a comprehensive theoretical discussion and as a proof of concept, an all-dielectric optical metasurface is elaborately designed to exhibit the desired surface polarizabilities, thereby reflecting the first derivative and extracting the edges of images impinging from the normal direction. The proposed study offers a flexible design method for on-axis metasurface-based optical signal processing and also dramatically facilitates the experimental setup required for ultrafast analog computation and image processing. Reciprocal ; Computer science ; Signal processing ; Polarization (electrochemistry) ; Optics ; Computation ; Dielectric ; Reflection (computer programming) ; Digital signal processing ; Physics ; Optoelectronics ; Computer hardware ; Algorithm Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Advanced Optical Imaging Technologies
Authors: Guillaume L. Erny | Elsa Brito | Ana Bárbara Pereira | Andreia Bento‐Silva | María Carlota Vaz Patto | Maria Rosário Bronze
Source: RSC Advances (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Projection to latent correlative structures, a dimension reduction strategy for spectral-based classification Latent variables are used in chemometrics to reduce the dimension of the data. It is a crucial step with spectroscopic data where the number of explanatory variables can be very high. Principal component analysis (PCA) and partial least squares (PLS) are the most common. However, the resulting latent variables are mathematical constructs that do not always have a physicochemical interpretation. A new data reduction strategy, named projection to latent correlative structures (PLCS), is introduced in this manuscript. This approach requires a set of model spectra that will be used as references. Each latent variable is the relative similarity of a given spectrum to a pair of reference spectra. The latent structure is obtained using every possible combination of reference pairing. The approach has been validated using more than 500 FTIR-ATR spectra from cool-season culinary grain legumes assembled from germplasm banks and breeders' working collections. PLCS has been combined with soft discriminant analysis to detect outliers that could be particularly suitable for a deeper analysis. Correlative ; Dimensionality reduction ; Projection (relational algebra) ; Dimension (graph theory) ; Reduction (mathematics) ; Pattern recognition (psychology) ; Representation (politics) ; Latent variable ; Computer science ; Artificial intelligence ; Latent class model ; Mathematics ; Algorithm ; Machine learning ; Combinatorics ; Geometry Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Anna Bencsik | Philippe Lestaevel
Source: Frontiers in Toxicology (article, 2021-02-18)
Field: Materials Science — Materials Chemistry

The Challenges of 21st Century Neurotoxicology: The Case of Neurotoxicology Applied to Nanomaterials After a short background discussing engineered nanomaterials (ENMs) and their physicochemical properties and applications, the present perspective paper highlights the main specific points that need to be considered when examining the question of neurotoxicity of nanomaterials. It underlines the necessity to integrate parameters, specific tools, and tests from multiple sources that make neurotoxicology when applied to nanomaterials particularly complex. Bringing together the knowledge of multiple disciplines e.g., nanotoxicology to neurotoxicology, is necessary to build integrated neurotoxicology for the third decade of the 21st Century. This article focuses on the greatest challenges and opportunities offered by this specific field. It highlights the scientific, methodological, political, regulatory, and educational issues. Scientific and methodological challenges include the determination of ENMs physicochemical parameters, the lack of information about protein corona modes of action, target organs, and cells and dose- response functions of ENMs. The need of standardization of data collection and harmonization of dedicated neurotoxicological protocols are also addressed. This article highlights how to address those challenges through innovative methods and tools, and our work also ventures to sketch the first list of substances that should be urgently prioritized for human modern neurotoxicology. Finally, political support with dedicated funding at the national and international levels must also be used to engage the communities concerned to set up dedicated educational program on this novel field. Engineering ethics ; Standardization ; Harmonization ; Nanotechnology ; Computer science ; Management science ; Risk analysis (engineering) ; Data science ; Engineering ; Medicine ; Physics Nanoparticles: synthesis and applications ; Anesthesia and Neurotoxicity Research ; Graphene and Nanomaterials Applications
Authors: J.D. Jackson | Luca Laurenti | Eric W. Frew | Morteza Lahijanian
Source: arXiv (Cornell University) (preprint, 2021-12-31)
Field: Chemistry — Spectroscopy

Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression Leveraging autonomous systems in safety-critical scenarios requires verifying their behaviors in the presence of uncertainties and black-box components that influence the system dynamics. In this work, we develop a framework for verifying discrete-time dynamical systems with unmodelled dynamics and noisy measurements against temporal logic specifications from an input-output dataset. The verification framework employs Gaussian process (GP) regression to learn the unknown dynamics from the dataset and abstracts the continuous-space system as a finite-state, uncertain Markov decision process (MDP). This abstraction relies on space discretization and transition probability intervals that capture the uncertainty due to the error in GP regression by using reproducible kernel Hilbert space analysis as well as the uncertainty induced by discretization. The framework utilizes existing model checking tools for verification of the uncertain MDP abstraction against a given temporal logic specification. We establish the correctness of extending the verification results on the abstraction created from noisy measurements to the underlying system. We show that the computational complexity of the framework is polynomial in the size of the dataset and discrete abstraction. The complexity analysis illustrates a trade-off between the quality of the verification results and the computational burden to handle larger datasets and finer abstractions. Finally, we demonstrate the efficacy of our learning and verification framework on several case studies with linear, nonlinear, and switched dynamical systems. Computer science ; Correctness ; Abstraction ; State space ; Linear temporal logic ; Formal verification ; Model checking ; Observable ; Computation tree logic ; Kriging ; Discretization ; Kernel (algebra) ; Dynamical systems theory ; Gaussian process ; Theoretical computer science ; Computational complexity theory ; Algorithm ; Gaussian ; Mathematics ; Machine learning ; Discrete mathematics Mass Spectrometry Techniques and Applications ; Fault Detection and Control Systems ; Gene Regulatory Network Analysis
Authors: Kyongok Kang
Source: Scientific Reports (article, 2021-02-10)
Field: Chemistry — Physical and Theoretical Chemistry

Equilibrium phase diagram and thermal responses of charged DNA-virus rod-suspensions at low ionic strengths The collective behavior of DNA is important for exploring new types of bacteria in the means of detection, which is greatly interested in the understanding of interactions between DNAs in living systems. How they self-organize themselves is a physical common phenomenon for broad ranges of thermodynamic systems. In this work, the equilibrium phase diagrams of charged chiral rods (fd viruses) at low ionic strengths (below a few mM) are provided to demonstrate both replicas of (or self-organized) twist orders and replica symmetry breaking near high concentration glass-states. By varying the ionic strengths, it appears that a critical ionic strength is obtained below 1-2 mM salt, where the twist and freezing of nematic domains diverge. Also, the microscopic relaxation is revealed by the ionic strength-dependent effective Debye screening length. At a fixed low ionic strength, the local orientations of twist are shown by two different length scales of optical pitch, in the chiral-nematic N* phase and the helical domains [Formula: see text], for low and high concentration, respectively. RSB occurs in several cases of crossing phase boundary lines in the equilibrium phase diagram of DNA-rod concentration and ionic strength, including long-time kinetic arrests in the presence of twist orders. The different pathways of PATH I, II and III are due to many-body effects of randomized orientations for charged fd rods undergoing long-range electrostatic interactions in bulk elastic medium. In addition, the thermal stability are shown for chiral pitches of the N* phase and the abnormal cooling process of a specific heat in a structural glass. Here, the concentration-driven twist-effects of charged DNA rods are explored using various experimental methods involving image-time correlation, microscopic dynamics in small angle dynamic light scattering, optical activity in second harmonic generation, and differential scanning calorimetry for the glass state. Phase diagram ; Ionic bonding ; Chemical physics ; DNA ; Phase (matter) ; Thermal ; Ionic strength ; Materials science ; Chemistry ; Thermodynamics ; Ion ; Physics ; Physical chemistry ; Biochemistry Electrostatics and Colloid Interactions ; Material Dynamics and Properties ; Nanopore and Nanochannel Transport Studies
Authors: Fei Han | Han Yao | Entao Yao | Ping Wang | Yu Shi | Yuan Zhang
Source: Journal of Magnetism and Magnetic Materials (article, 2021-11-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Yield strength measurement of ferromagnetic materials based on the inverse magnetostrictive effect Materials science ; Electromagnetic acoustic transducer ; Ferromagnetism ; Magnetostriction ; Yield (engineering) ; Microstructure ; Transducer ; Composite material ; Ultrasonic sensor ; Inverse magnetostrictive effect ; Acoustics ; Magnetic field ; Condensed matter physics ; Ultrasonic testing ; Physics Magnetic Properties and Applications ; Non-Destructive Testing Techniques ; Microstructure and Mechanical Properties of Steels
Authors: А. А. Хлыбов | Yu. G. Kabaldin | M. S. Anosov | D. A. Ryabov
Source: Vestnik IzhGTU imeni M T Kalashnikova (article, 2021-04-06)
Field: Materials Science — Materials Chemistry

Influence of Long-Term Operation on Physical and Mechanical Properties and Cold Resistance Indicators of Pipe Steel 10G2 Проведено исследование влияния длительности эксплуатации магистрального газопровода на изменение физико-механических характеристик показателей хладостойкости трубной стали 10Г2.Установлено, что в процессе длительной эксплуатации стали 10Г2 в составе магистрального газопровода наблюдается изменение структуры металла, при этом происходит перераспределение перлитной составляющей и укрупнение зерен. Получены значения микротвердости исследуемой стали до и после эксплуатации (10, 25, 40 лет). Длительная эксплуатация (40 лет) материала труб приводит к росту значений микротвердости с 1518 до 2786 HV. Выявлено двукратное снижение значений ударной вязкости стали 10Г2 после старения и эксплуатации в течение 25 лет. Также наблюдается значительное повышение температуры вязко­хрупкого перехода, что снижает надежность магистральных трубопроводов. В результате испытаний стали 10Г2 в широком диапазоне температур после 25 лет эксплуатации наблюдается снижение пластичности металла (относительное удлинение уменьшается примерно в 1,6 раза), повышение предела прочности и снижение предела текучести (до 9 %).Предложена методика неразрушающего контроля деградации механических свойств стали 10Г2 в процессе эксплуатации изделий. Установлена зависимость акустического параметра D, рассчитанного на основе скорости распространения продольных и поперечных упругих волн в металле от срока эксплуатации газовых магистральных труб и температуры вязкохрупкого перехода для стали 10Г2. Показано, что предложенный акустический параметр может выступать в качестве характеристического параметра хладостойкости материала магистральных газопроводов и использоваться при технической диагностике для оценки их остаточного ресурса.Исследование выполнено по гранту РНФ № 19-19-00332 «Разработка научно обоснованных подходов и аппаратно-программных средств мониторинга поврежденности конструкционных материалов на основе подходов искусственного интеллекта для обеспечения безопасной эксплуатации технических объектов в арктических условиях». Term (time) ; Materials science ; Metallurgy ; Forensic engineering ; Environmental science ; Engineering ; Physics Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Engineering and Environmental Studies