jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fia B. Larsen | Matteo Cagiada | Jonas Dideriksen | Amelie Stein | Kresten Lindorff‐Larsen | Rasmus Hartmann‐Petersen
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-01-03)
Field: Chemistry — Spectroscopy

Rare catechol-O-methyltransferase (COMT) missense variants are structurally unstable proteasome targets Abstract Catechol- O -methyltransferase (COMT) is a key enzyme in the metabolism of catecholamines. Substrates of the enzyme include neurotransmitters such as dopamine and epinephrine, and therefore, COMT plays a central role in neurobiology. Since COMT also metabolises catecholamine drugs such as L-DOPA, variation in COMT activity could affect pharmacokinetics and drug availability. Certain COMT missense variants have been shown to display decreased enzymatic activity. Additionally, studies have shown that such missense variants may lead to loss-of-function induced by impaired structural stability, which results in activation of the protein quality control system and degradation by the ubiquitin-proteasome system. Here, we demonstrate that two rare missense variants of COMT are ubiquitylated and targeted for proteasomal degradation as a result of structural destabilisation and misfolding. This results in strongly reduced intracellular steady-state levels of the enzyme, which for the L135P variant is rescued upon binding to the COMT inhibitors entacapone and tolcapone. Our results reveal that the degradation is independent of the COMT isoform, as both soluble (S-COMT) and ER membrane-bound (MB-COMT) variants are degraded. In silico structural stability predictions identify regions within the protein that are critical for stability overlapping with evolutionarily conserved residues, pointing towards other variants that are likely destabilised and degraded. Catechol-O-methyl transferase ; Missense mutation ; Chemistry ; Enzyme ; Deamidation ; Dopamine ; In silico ; Biochemistry ; Mutation ; Biology ; Cell biology ; Endocrinology ; Gene ; Genotype Advanced Proteomics Techniques and Applications ; Mitochondrial Function and Pathology ; Ubiquitin and proteasome pathways
Authors: Takanori Sugimoto
Source: arXiv (Cornell University) (preprint, 2023-04-26)
Field: Materials Science — Materials Chemistry

Quantum-circuit algorithms for many-body topological invariant and Majorana zero mode Topological states of matter are promising resources for composing fault-tolerant quantum computers, advancing beyond the limitations of current noisy intermediate-scale quantum devices. To enable this progress, a deep understanding of topological phenomena within actual quantum computing platforms is essential. However, existing quantum-circuit algorithms to examine topological properties remain limited. Here we introduce three quantum-circuit algorithms designed to (i) determine the ground state within a specified parity subspace, (ii) identify the many-body topological invariant, and (iii) visualize zero-energy edge modes. We illustrate these algorithms with the interacting Kitaev chain, a typical model of one-dimensional topological superconductors. These approaches are versatile, extending beyond one-dimensional systems to various topological states, including those in higher dimensions. Topological degeneracy ; Topology (electrical circuits) ; Topological order ; Quantum computer ; MAJORANA ; Physics ; Symmetry protected topological order ; Zero mode ; Zero-point energy ; Topological entropy in physics ; Topological quantum number ; Algorithm ; Subspace topology ; Quantum algorithm ; Realization (probability) ; Invariant (physics) ; Qubit ; Quantum ; Computer science ; Quantum mechanics ; Mathematics ; Fermion Electronic and Structural Properties of Oxides ; Advanced Condensed Matter Physics ; Topological Materials and Phenomena
Authors: Zahra Hemmati Dezaki | Kazem Parivar | Vahabodin Goodarzi | Mohammad Reza Nourani
Source: Advanced Pharmaceutical Bulletin (article, 2023-07-22)
Field: Materials Science — Biomaterials

Cobalt/Bioglass Nanoparticles Enhanced Dermal Regeneration in a 3-Layered Electrospun Scaffold The 3-layered scaffold which is loaded with cobalt ions-bonded bioglass nanoparticles, is a better substrate for the culture of the fibroblasts. Scaffold ; Nanoparticle ; Polycaprolactone ; Materials science ; Composite number ; Electrospinning ; Contact angle ; Fourier transform infrared spectroscopy ; Biomedical engineering ; Regeneration (biology) ; Chemical engineering ; Chemistry ; Biophysics ; Composite material ; Nanotechnology Electrospun Nanofibers in Biomedical Applications ; Wound Healing and Treatments ; Silk-based biomaterials and applications
Authors: Jiarui Li | Jinglin Qi | Mei Yue
Source: Highlights in Science Engineering and Technology (article, 2023-02-21)
Field: Chemistry — Inorganic Chemistry

Research on Composition Analysis of Glass Products Based on Clustering and Random Forest Model Glass cultural relics are important material and cultural heritage of human beings and play an important role in the history of human civilization. This study aims to investigate the relationship between the chemical composition of glass artefacts and the glass type of the artefacts. The chemical composition of glass was analyzed and identified by using K-means clustering, multiple correspondence analysis, SOM model and random forest algorithm. In this paper, based on the given data, the physical properties and chemical composition of the high-potassium glass relics and the lead-barium glass relics were studied respectively, and the classification basis of the two was obtained. It is found that the content of silica and lead oxide can be used as an important basis for distinguishing the two types of glass cultural relics and based on this, a prediction model for further classification of cultural relics and inference of glass cultural relics is designed. This study answered the relationship between the chemical composition of glass relics and the glass type of relics, and further research is needed to obtain more relevant data to train the model to improve its applicability. Chemical composition ; Composition (language) ; Cluster analysis ; Mineralogy ; Materials science ; Computer science ; Chemistry ; Artificial intelligence ; Physics ; Art ; Thermodynamics ; Literature Pigment Synthesis and Properties
Authors: Edison Zhamungui Sánchez | Hassan Hijazi | Jana Haidar | Enrica Mecarelli | Elda Bauda | Isabelle Petit-Härtlein | Jean‐Marie Teulon | Jean‐Luc Pellequer | Elisabetta Boeri Erba
Source: Frontiers in Analytical Science (article, 2023-07-13)
Field: Chemistry — Spectroscopy

Sequencing intact membrane proteins using MALDI mass spectrometry Membrane proteins are key players in many cellular events and represent crucial drug targets. Matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) is a valuable approach to investigate them. To our knowledge, there are only a few reports of sequencing small membrane proteins using MALDI in-source decay (ISD). We report the successful fragmentation and sequencing of membrane proteins up to 46 kDa by MALDI-ISD. We have 1) investigated key MALDI parameters that influence the sequencing of a soluble protein; 2) used atomic force microscopy to observe our samples and correlate their topological features with MALDI data, which allowed us to optimize fragmentation conditions; 3) sequenced N- and C-termini of three membrane proteins (SpoIIIAF, TIM23, and NOX), solubilized in three different ways. Our results indicate that detergent and buffer type are of key importance for successful MALDI-ISD sequencing. Our findings are significant because sequencing membrane proteins enables the unique characterization of challenging biomolecules. The resulting fragmentation patterns provide key insights into the identity of proteins, their sequences, modifications, and other crucial information, such as the position of unexpected truncation. Chemistry ; Mass spectrometry ; Matrix-assisted laser desorption/ionization ; Membrane protein ; Computational biology ; Fragmentation (computing) ; DNA sequencing ; Proteomics ; Protein mass spectrometry ; MALDI imaging ; Membrane ; Tandem mass spectrometry ; Chromatography ; Biology ; Biochemistry ; DNA ; Desorption ; Gene Mass Spectrometry Techniques and Applications ; Ion-surface interactions and analysis ; Advanced Proteomics Techniques and Applications
Authors: J. C. Neto | T. M. Souza
Source: Revista SODEBRAS (article, 2023-07-01)
Field: Materials Science — Biomaterials

PROJETO DE PRODUÇÃO DA CARROCERIA DE VEÍCULO ELÉTRICO POR MANUFATURA ADITIVA Gardening is an activity that requires time and dedication, requirements that have become increasingly scarce in the face of the accelerated routine of today. That said, this article presents the development of an smart plant pot prototype that aims to irrigate a plant through the use of a pump, automatically, through the use of microcontrollers, responsible for controlling the water pump, moisture sensor and OLED display, which acts by presenting information about whether the earth is moist or not. As a way to execute this development we share the areas that will be focused on this article: Mechanical Modeling, 3D Printing, Electronics and Programming. Humanities ; Art Electrospun Nanofibers in Biomedical Applications
Authors: Róbinson Jiménez Moreno | Javier Eduardo Martínez Baquero
Source: International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (article, 2023-01-31)
Field: Chemistry — Analytical Chemistry

Automatic food bio-hazard detection system This paper presents the design of a convolutional neural network architecture oriented to the detection of food waste, to generate a low, medium, or critical-level alarm. An architecture based on four convolution layers is used, for which a database of 100 samples is prepared. The database is used with the different hyperparameters that make up the final architecture, after the training process. By means of confusion matrix analysis, a 100% performance of the network is obtained, which delivers its output to a fuzzy system that, depending on the duration of the detection time, generates the different alarm levels associated with the risk. Computer science ; Convolutional neural network ; Hazard ; Architecture ; Artificial intelligence ; Process (computing) ; ALARM ; Data mining ; Pattern recognition (psychology) ; Real-time computing ; Operating system ; Engineering Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies
Authors: Dennis Kim | Michael Xu | James M. LeBeau
Source: arXiv (Cornell University) (preprint, 2023-03-04)
Field: Materials Science — Materials Chemistry

Validation of machine-learned interatomic potentials via temperature-dependent electron thermal diffuse scattering Machine-learned interatomic potentials (MLIPs) show promise in accurately describing the physical properties of materials, but there is a need for a higher throughput method of validation. Here, we demonstrate using that MLIPs and molecular dynamics can accurately capture the potential energy landscape and lattice dynamics that are needed to describe electron thermal diffuse scattering. Using SrTiO$_3$ as a test-bed at cryogenic and room temperatures, we compare electron thermal diffuse scattering simulations using different approximations to incorporate thermal motion. Only when the simulations are based on quantum mechanically accurate MLIPs in combination with path-integral molecular dynamics that include nuclear quantum effects, there is excellent agreement with experiment\end{abstract} Thermal ; Electron ; Molecular dynamics ; Scattering ; Interatomic potential ; Quantum ; Lattice (music) ; Physics ; Materials science ; Computational physics ; Statistical physics ; Molecular physics ; Nuclear physics ; Quantum mechanics ; Thermodynamics Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Electronic and Structural Properties of Oxides
Authors: Jan Wolf | Romy Peters | Jonathan Mädler | Daniel Sebastian Jens Wolz | Thomas Behnisch | Mohsen Sadeghi Bogar | Leon Urbas | Μaik Gude
Source:  (preprint, 2023-07-03)
Field: Materials Science — General Materials Science

Thermomechanical modeling of the stabilization process for carbon fiber production Within carbon fiber manufacturing, the stabilization process is the most time- and energy-intensive process due to the complexity of chemical structure transformation. Therefore, optimization is strictly required to enable cost-efficient stabilization processes. For the first time, a hybrid semi-parametric model for continuous stabilization is developed to prognose stabilization progress and density of the stabilized fiber. The proposed model takes the process parameters like dwell time, stabilization temperature, and fiber stretching as well as precursor properties, such as fiber density, into account. Finally, the proposed hybrid semi-parametric model offers a novel plant-transferable optimization solution for model-based energy optimization in the stabilization process. Production (economics) ; Process (computing) ; Fiber ; Pulp and paper industry ; Business ; Process engineering ; Materials science ; Computer science ; Economics ; Composite material ; Engineering ; Microeconomics Material Properties and Applications ; Fiber-reinforced polymer composites ; Additive Manufacturing and 3D Printing Technologies
Authors: Mykhailo Zgurovsky | Vitalii Tatarchuk | Sergii Khlamov | Vadym Savanevych | Tetiana Trunova | Olexander Briukhovetskyi | Oleksandr Kuznetsov | Yelyzaveta Kuznetsova | Yuriy Gorbenko | Emanuele Frontoni | Oleksandr Lemeshko | Batoul Sleiman | Oleksandra Yeremenko | Valentyn Lemeshko | Maryna Yevdokymenko | Mykhailo Persikov | V Glushkov | Serhii Predictions | Leonid Kravchuk | Uryvsky | Danylo Parkhomenko | Serhii Osievsky | Vadym Fustii | Oleksii Nesmiian | Vladimir Krizhanovski | Yulia Rassokhina | Volodymyr Kryzhanovskyi | Andrei Grebennikov | Radiophysical Relativistic | Gravimetr Serhii | A Matviienko | Serhii Matviienko | Oleksandr Pryshchenko | Oleksandr Dumin | Vadym Plakhtii
Source:  (article, 2023-11-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

UkrMiCo 2023 TOC Computer science ; Environmental science Magnetic Properties of Alloys
Authors: В. М. Иевлев | К. А. Солнцев | С. В. Горбунов | Н. Р. Рошан | В. С. Касьянов | Н. Б. Морозова | А. И. Донцов
Source: Неорганические материалы (article, 2023-11-01)
Field: Materials Science — Materials Chemistry

Эффект ультразвуковой обработки мембранной фольги сплава Pd–4 ат. % In–1 ат. % Ru: сорбция и водородопроницаемость Методами циклической вольтамперометрии, оже-электронной спектроскопии и атомно-силовой микроскопии исследовано влияние ультразвуковой обработки поверхности мембранной фольги твердого раствора системы Pd–In–Ru на сорбцию водорода и водородопроницаемость. Показано, что такая обработка приводит к увеличению сорбции водорода в приповерхностный слой фольги при сохранении величины ее водородопроницаемости. Установлено, что ультразвуковая обработка позволяет сохранить без изменений морфологию, состав и структуру фольги. Chemistry ; Computer science Thermal Expansion and Ionic Conductivity ; High Entropy Alloys Studies ; MXene and MAX Phase Materials
Authors: Zhaojian Liang | Shanlin Chen | Meng Ni | Jingyi Wang | Mengying Li
Source: arXiv (Cornell University) (preprint, 2023-12-08)
Field: Materials Science — Materials Chemistry

A novel control strategy to neutralize heat source within solid oxide electrolysis cell (SOEC) under variable solar power conditions The integration of a solid oxide electrolysis cell (SOEC) with a photovoltaic (PV) system presents a viable method for storing variable solar energy through the production of green hydrogen. To ensure the SOEC's safety and longevity amidst dramatic fluctuations in solar power, control strategies are needed to limit the temperature gradients and rates of temperature change within the SOEC. Recognizing that the reactant supply influences the current, a novel control strategy is developed to modulate heat generation in the SOEC by adjusting the fuel flow rate. The effectiveness of this strategy is assessed through numerical simulations conducted on a coupled PV-SOEC system using actual solar irradiance data, recorded at two-second intervals, to account for rapid changes in solar exposure. The results indicate that conventional control strategies, which increase airflow rates, are inadequate in effectively suppressing the rate of temperature variation in scenarios of drastic solar power changes. In contrast, our proposed strategy demonstrates successful management of the SOEC's heat generation, thereby reducing the temperature gradient and rate of variation within the SOEC to below 5 K/cm and 1 K/min, respectively. Photovoltaic system ; Environmental science ; Power (physics) ; Thermodynamics ; Physics ; Electrical engineering ; Engineering Advancements in Solid Oxide Fuel Cells ; Chemical Looping and Thermochemical Processes ; Advanced battery technologies research
Authors: Amra Bratovčić
Source:  (article, 2023-10-01)
Field: Chemistry — Analytical Chemistry

Sophisticated Transformation of Chemical, Pharmaceutical and Food Industry by Implementation of Digitalization and Automatization This paper will discuss the solutions and advantages of Industry 4.0 in the chemical, pharmaceutical and food industries.Industry 4.0 implies automation and process control, which enables greater process reliability and repeatability, better work control, efficient error diagnosis, maintenance support and higher product quality. In order to achieve this, it is necessary to use industrial equipment to achieve high functionality and reliability, i.e., the use of the latest developed smart technologies.it enables collection and storage of data from multiple sources in one central data warehouse in a contextualized manner, providing integrity of the underlying data and instant access from a single point.A central monitoring system provides operators with a detailed overview of equipment performance, helps maintenance personnel to eliminate errors and provides aggregation of all relevant data. The application of Industry 4.0 will improve the monitoring of process parameters, the management of production recipes, and accelerate the change of products.In addition, it enables efficient development, management and remote download of recipes to production equipment without affecting the production process on the machine/line itself.The implementation of Industry 4.0 leads to the improvement of product quality, better management of material flow, lower energy consumption, and better utilization of machines and higher productivity, which reduces operating costs and positively affects business results. Computer science ; Reliability (semiconductor) ; Automation ; Quality (philosophy) ; Manufacturing engineering ; Process (computing) ; Food industry ; Production (economics) ; Process control ; Productivity ; Production line ; Risk analysis (engineering) ; Product (mathematics) ; Reliability engineering ; Engineering Spectroscopy and Chemometric Analyses ; Digital Transformation in Industry ; Economic and Technological Innovation
Authors: Yueming Guo | Hu Miao | Qiang Zou | Mingming Fu | Athena S. Sefat | Andrew R. Lupini | Sergei V. Kalinin | Zheng Gai
Source: arXiv (Cornell University) (preprint, 2023-02-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Revealing intrinsic vortex-core states in Fe-based superconductors through machine-learning-driven discovery Electronic states within superconducting vortices hold crucial information about paring mechanisms and topology. While scanning tunneling microscopy/spectroscopy(STM/S) can image the vortices, it is difficult to isolate the intrinsic electronic states from extrinsic effects like subsurface defects and disorders. We combine STM/S with unsupervised machine learning to develop a method for screening out the vortices pinned by embedded disorder in Fe-based superconductors. The approach provides an unbiased way to reveal intrinsic vortex-core states and may address puzzles on Majorana zero modes. Superconductivity ; Vortex ; Scanning tunneling microscope ; Condensed matter physics ; MAJORANA ; Scanning tunneling spectroscopy ; Physics ; Core (optical fiber) ; Spectroscopy ; Topology (electrical circuits) ; Local density of states ; Nanotechnology ; Quantum mechanics ; Materials science ; Engineering ; Optics ; Electrical engineering Iron-based superconductors research ; Physics of Superconductivity and Magnetism ; Rare-earth and actinide compounds
Authors: Shuai Wang | Yuanmu Yang
Source: Light Science & Applications (article, 2023-05-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metasurface designed with quantitative field distributions A new method for designing metasurfaces has been proposed and demonstrated, which allows for the generation of precise quantitative field distributions. This unique approach involves combining a tandem neural network with an iterative algorithm to optimize the metasurface design, enabling accurate control over the intensity and polarization of the resulting field. This strategy is both efficient and robust and has the potential to accelerate the development of metasurface devices with complex functionalities. Computer science ; Tandem ; Polarization (electrochemistry) ; Field (mathematics) ; Artificial neural network ; Electronic engineering ; Algorithm ; Artificial intelligence ; Materials science ; Engineering ; Mathematics ; Chemistry Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Energy Harvesting in Wireless Networks
Authors: Alejandro Blanco | José Sánchez Sánchez | Christian del Carpio | Erwin Dianderas | Guillermo Kemper
Source: International Journal of Applied Science and Engineering (article, 2023-01-01)
Field: Chemistry — Organic Chemistry

Identification of Peruvian timber species based on image processing and convolutional neural networks The identification of timber species is highly important worldwide due to their global trade and the arising requirement of controlling, regulating and monitoring illegal logging. Peru has an important timber trade due to extensive forest resources in the Peruvian Amazon. This context makes it necessary to have technological tools for timber species identification using tree leaves, in an attempt to control deforestation in the Amazon forests. Current identification methods require manual labor, are subjective and inefficient regarding time, cost and precision. Moreover, the scientific literature does not include electronic devices nor algorithms which exclusively identify Peruvian timber species. With this in mind, this work proposes a portable electronic equipment that detects 11 timber species from the Peruvian jungle, based on image processing techniques and convolutional neural networks (CNN). The device consists of a carbon fiber structure, a keyboard, a 7-inch display, internal lighting and a tray for the leaf sample. The algorithm uses color filters, thresholding and other operations to segment the leaf and then input it to a neural network. After comparing the AlexNet, VGG-16 and MobileNet architectures, the last one shows the best performance, with an average precision of 98.64% when identifying the 11 timber species. Convolutional neural network ; Identification (biology) ; Context (archaeology) ; Computer science ; Amazon rainforest ; Logging ; Artificial intelligence ; Thresholding ; Deforestation (computer science) ; Geography ; Forestry ; Ecology ; Image (mathematics) ; Archaeology Wood and Agarwood Research