jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anna Naumova | A. L. Ishevsky | P.I. Gunkova | Maria Danilyuk
Source:  (article, 2024-12-11)
Field: Materials Science — Biomaterials

THE USE OF POLYVINYL ALCOHOL AND MICROCRYSTALLINE CELLULOSE TO IMPROVE THE BARRIER PROPERTIES OF PROTECTIVE FILMS OF FOOD COATINGS The author's research is devoted to the proposal of the main directions for the development of the digital financial assets market in the Russian Federation.Through the definition of the category of digital financial assets and their economic essence, it is proposed to amend the national legislation on the market of digital financial assets by classifying them as non-documentary securities, which will make it possible to include digital financial assets in full-fledged civil law circulation.In addition to changing the legal aspects of the functioning of the digital financial assets market, the author formulates organizational, economic and institutional mechanisms for the formation and development of the digital financial assets market based on an integrated and systematic approach. Polyvinyl alcohol ; Microcrystalline cellulose ; Cellulose ; Microcrystalline ; Materials science ; Composite material ; Methyl cellulose ; Polymer science ; Chemical engineering ; Chemistry ; Engineering ; Crystallography Nanocomposite Films for Food Packaging ; Dye analysis and toxicity
Authors: Maylis Couton
Source: theses.fr (ABES) (article, 2024-12-17)
Field: Chemistry — Spectroscopy

15N site-specific analysis of arginine : fragmentation and analytical methods L’analyse isotopique site-spécifique est encore peu répandue et ne concerne majoritairement que les isotopes 2H et 13C. D’après les travaux antérieurs réalisés au laboratoire, la teneur isotopique en 15N de l’arginine expliquerait la déplétion en 15N observés dans des cellules cancéreuses. Afin de comprendre la filiation isotopique du 15N de l’arginine, il est nécessaire de développer des stratégies analytiques pour l’analyse 15N site-spécifique. Dans ce cadre, l’objectif de ce projet de thèse a consisté à développer une méthodologie permettant la fragmentation, la séparation et la purification de fragments en vue de leur analyse isotopique par irm-MS. Les résultats montrent qu’il est possible d’avoir accès spécifiquement à trois des quatre azotes de l’arginine, les deux autres concernant la partie guanidine étant indifférenciables. En parallèle, une nouvelle méthode utilisant la RMN 1H a été développée pour l’analyse isotopique 15N site-spécifique. Les résultats sur une série de composés plus simples que l’arginine ont montré que l’analyse 15N site-spécifique est envisageable. Cependant, un ensemble de paramètres sont encore à affiner pour permettre l’utilisation de cette technique en routine sur des molécules plus complexes. Ces premiers résultats sont prometteurs et pourront servir de référence pour le développement de l’analyse isotopique site-spécifique par une nouvelle technique performante : l’Orbitrap Alunite ; Fragmentation (computing) ; Oxygen-18 ; Isotopic signature Mass Spectrometry Techniques and Applications ; Nuclear Physics and Applications ; X-ray Spectroscopy and Fluorescence Analysis
Authors: Lellapalli Rithesh | N V Radhakrishnan | Susha S. Thara | G S Sreekala | T. Anuradha | Aswathi M. S | Soudamini Mohapatra
Source: Journal of Advances in Biology & Biotechnology (review, 2024-11-19)
Field: Chemistry — Inorganic Chemistry

A Centenary Review on Leaf Rot Disease of Coconut Coconut leaf rot disease (LRD) has posed a significant threat to coconut palms for over a century, causing widespread foliar damage, stunted growth, and reduced yield. The disease, often associated with the complex interaction of Root (wilt) disease (RWD), has been a persistent challenge since its first reports in the early 1900s. Despite extensive research, understanding the etiological agents and developing effective management strategies remain difficult due to evolving pathogenic profiles and climate variability. This centenary review consolidates over 100 years of research on LRD, offering a comprehensive analysis of the disease’s progression, and environmental influences, in coconut cultivation. It contrasts traditional management methods, such as cultural and chemical controls, with modern integrated disease management (IDM) approaches, including biological control agents and host resistance breeding. The review also explores the role of plant-microbe interactions, emphasizing the potential of microbial antagonists as biocontrol agents. Given the economic significance of coconuts in tropical regions, this review highlights the urgent need for region-specific disease management strategies and the development of climate-resilient coconut varieties. Additionally, it identifies research gaps and future directions to advance sustainable solutions for mitigating the impact of LRD. Disease ; Biology ; Disease management ; Biotechnology ; Agroforestry ; Medicine Coconut Research and Applications ; Plant Pathogens and Fungal Diseases ; Cocoa and Sweet Potato Agronomy
Authors: Juan J. Jiménez | Eduardo Pérez‐González | Mariana Y. Guerra-Montiel
Source: Journal of Food Processing and Preservation (article, 2024-01-01)
Field: Chemistry — Organic Chemistry

Optimising Resource Utilisation: A Case Study on Oleofinos’ Advanced Line 4 This study presents significant advancements in the refinement of vegetable oils, demonstrating a 40% increase in processing capacity and a 30% reduction in production time. Additionally, energy consumption was reduced by 25%, leading to a 20% decrease in greenhouse gas (GHG) emissions. These improvements are attributed to the implementation of renewable energy technologies and heat recovery systems. With these advancements, Oleofinos has enhanced its safety and quality standards, maintaining the FSSC 22000 Certification for Food Safety Risk Management and the Rainforest Alliance Certification, which is recognised as the world’s leading certifier under the Forest Stewardship Council® (FSC®) with over 25 years of experience in environmental certification. Currently, Oleofinos is the largest plant of its kind in Mexico, boasting an unprecedented processing capacity of 500,000 tonnes per year. The results of this study underscore the significance and transformative impact of research, establishing a benchmark for future initiatives aimed at process improvement in the sector and reinforcing the commitment to operational excellence and environmental responsibility. Resource (disambiguation) ; Line (geometry) ; Business ; Operations management ; Computer science ; Engineering ; Mathematics Edible Oils Quality and Analysis ; Catalysis for Biomass Conversion
Authors: Naufal Hilmi Fauzan | Adhimas Daffa Kurnia | Prayudi Efendi | Prasetyohadi | Daryadi
Source: Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI) (article, 2024-11-25)
Field: Materials Science — Materials Chemistry

Kinerja Isolator Kaca Bekas dan Berumur Terhadap Basic Insulation Level (BIL) Isolator tegangan tinggi memainkan peran penting dalam memastikan keamanan sistem listrik yang beroperasi pada tegangan tinggi. Isolator memiliki fungsi sebagai pemisah tegangan antara konduktor fase dan konduktor fase lainnya dan juga antara konduktor fase dengan ground. Dalam perancangan sistem tenaga listrik, basic insulation level (BIL) tidak dapat diabaikan. BIL merupakan batas operasional tegangan maksimum sebelum isolator mengalami flashover. Selain harus mampu menahan tegangan, isolator juga harus mampu menahan kondisi lingkungan, seperti suhu, kelembapan, dan polusi, yang dapat memengaruhi kinerja isolator. Pada penelitian ini, dilakukan pengujian untuk melihat kinerja isolator kaca bekas PLTU Adipala ketika dipengaruhi oleh kondisi lingkungan dan dibandingkan dengan nilai BIL. Pengujian dilakukan dengan empat skema, yaitu pengujian dalam kondisi baik, pengujian dengan kondisi basah, pengujian dengan kondisi diberikan polutan, dan pengujian dengan kondisi ketika isolator dengan polutan berada pada kondisi lembap. Berdasarkan pengujian, didapatkan hasil bahwa kondisi yang sangat memengaruhi kinerja isolator adalah kondisi basah dan juga kondisi berpolutan dan lembap. Pada kondisi isolator bersih yang terkena hujan, penurunan kinerja isolator sebesar 19% sampai 25%, sedangkan pada kondisi diberikan polutan dengan equivalent salt deposit density (ESDD) 0,113816 mg/cm2 dan non-soluble deposit density (NSDD) 1,309962 mg/cm2 serta berada pada kelembapan 90%, terjadi penurunan kinerja sebesar 41% hingga 53%. Penurunan yang sangat signifikan ini tentunya mengakibatkan kinerja isolator berada jauh di bawah standar BIL. Materials science High voltage insulation and dielectric phenomena ; Engineering and Technology Innovations ; IoT-based Control Systems
Authors: Celso Eduardo Olivier | Daiana Guedes Pinto | Ana Paula Monezzi Teixeira | Cibele Silva Miguel | Raquel Acácia Pereira Gonçalves Santos | Jhéssica Letícia Santos Santana | Regiane Patussi Santos Lima
Source:  (article, 2024-11-11)
Field: Chemistry — Analytical Chemistry

Endotyping Cellular and Humoral Immunoreactivity against Tartrazine in Allergic Patients: A Retrospective Study Background: Several publications report that tartrazine is responsible for IgE-mediated and non-IgE-mediated hypersensitivity reactions.There is no standardized lab exam to endotype non-IgEmediated immunoreactivity against tartrazine besides in vivo provocation tests.Aim: To evaluate the potential of the Tube Titration of Precipitins (TTP) and the Leukocyte Adherence Inhibition Test (LAIT) to endotype humoral and cellular immunoreactivity against tartrazine in patients clinically diagnosed with non-IgE-mediated allergic phenotypes associated with various non-IgE-mediated allergic conditions.Study Design: We retrospectively examined the medical charts of two cohorts of patients diagnosed with the aforementioned allergic phenotypes with clinical suspicion of tartrazine hypersensitivity, who were investigated with the help of TTP (first cohort) or ex vivo challenge tests monitored by LAIT (second cohort) against tartrazine.Methodology: The registered results of the semi-quantitative serum TTP against 1 mg/mL tartrazine solution were distributed in ranges through a cascade distribution chart to outline the variability of the results inside the first cohort.The registered results of the Leukocyte Adherence Inhibition (LAI) percentage promoted by the ex vivo challenges with 1 mg/mL tartrazine solution were distributed in ranges through a cascade distribution chart to outline the variability of results inside the second cohort.The statistical characteristics of these cohorts were calculated.Results: Most positive TTP results concentrated on the higher dilutions.The mean was estimated at 1:290; the standard deviation was estimated at 1:200.The LAI ranged from 0% to 88%.The mean was 35.4%; the standard deviation was 24,7%.The cascade distribution graph demonstrates that the LAIT distribution is mainly over the negative and weaker results.Conclusion: Our preliminary results support that the TTP and LAIT performed with 1 mg/mL tartrazine solution may discriminate diverse humoral and cellular immunoreactivity degrees in patients suffering from several non-IgE-mediated allergic conditions, encouraging further prospective studies and validation. Tartrazine ; Immunology ; Medicine ; Pathology Dye analysis and toxicity ; melanin and skin pigmentation ; Dyeing and Modifying Textile Fibers
Authors: Zekun Cui | Minglei Wei | Bing Gao | Kang Zhang
Source: Applied Mathematics and Nonlinear Sciences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Partial Discharge Type Identification of SF6 Gas Insulation Based on Crossover Features and Transformer Models Abstract In order to effectively identify the type of partial discharge of SF6 gas-insulated switchgear combinations and then to ensure the safe and stable operation of the equipment, a method for identifying the type of SF6 gas-insulated partial discharge based on crossover frequency features and the transformer model is proposed. First, four types of SF6 gas-insulated partial discharge signals are gathered. These are then broken down into their modal components using variational modal decomposition. The energy moments of each crossover signal are then calculated to find the crossover frequency characteristics. Finally, the Transformer model is used to identify the types of SF6 gas-insulated partial discharge signals. The experimental results show that the proposed method can effectively recognize different partial discharge types of SF6 gas insulation, and the recognition accuracy is as high as 99%, which verifies the validity and superiority of the proposed method of recognizing partial discharge types of SF6 gas insulation. Partial discharge ; Transformer ; Crossover ; Identification (biology) ; Materials science ; Computer science ; Engineering ; Electrical engineering ; Voltage ; Artificial intelligence ; Biology High voltage insulation and dielectric phenomena ; Aerosol Filtration and Electrostatic Precipitation ; Power Transformer Diagnostics and Insulation
Authors: Nugroho Adi Surya | N. S. Sonia | D. S. Nair | U. Krishnaja | Amit Kumar
Source: Journal of Advances in Biology & Biotechnology (article, 2024-11-15)
Field: Chemistry — Inorganic Chemistry

Protocol Refinement for the Development of Coconut Inflorescence Powder Aims: Coconut inflorescence holds significant potential as a nutraceutical due to its rich composition of bioactive compounds, including vitamins, minerals, and antioxidants. Its use in promoting health and preventing diseases has made it a valuable ingredient in both traditional medicine and modern functional foods. The aim of the study is the protocol refinement for the development of coconut inflorescence powder with acceptable moisture content and superior sensory quality. Study Design: Completely randomized design (CRD). Place and Duration of Study: Department of Plantation, Spices, Medicinal and Aromatic Crops, College of Agriculture, Vellayani, Kerala Agricultural University, between May 2024 and October 2024. Methodology: In the present study, coconut inflorescence was harvested at 5-6 months before inflorescence opening, size reduced (1 cm3 pieces), and precooked by adopting different methods, viz., steaming, boiling, dry roasting, and microwave cooking (non-precooked inflorescence was used as the control). The precooked inflorescence pieces were dried by different drying methods viz., hot-air oven drying at 600C (Control), cabinet drier at 600C, 700C, 800C and solar drying for developing coconut inflorescence powder (CIP). CIP was analyzed for moisture content and sensory quality. Results: CIP prepared by steaming the coconut inflorescence pieces for 30 minutes and drying in cabinet dryer at 600C (C1D1) recorded the least moisture content, 1.83±0.07 per cent. However, CIP prepared by boiling (95-1000C) the inflorescence pieces by submerging for 30 minutes and drying in cabinet dryer at 600C (C2D1) showed the highest mean rank value for all the sensory attributes viz., colour (735.50), consistency (730.63), flavour (730.68), mouthfeel (734.75) and taste (735.23) on a nine-point hedonic scale with a moisture content, 4.20±0.04 per cent. The lowest mean rank value for colour was recorded by C1D1 and C2D0 (211.06). The lowest values for consistency, mouthfeel, flavour and taste were observed for the treatments C4D1 (289.81), C4D1 (290.61), C4D0 (226.05) and C0D0 (216.50), respectively. Hence, C2D1 was identified as the best precooking and drying method for the preparation of coconut inflorescence powder. Inflorescence ; Protocol (science) ; Biology ; Biotechnology ; Mathematics ; Horticulture ; Medicine Coconut Research and Applications
Authors: Kacper Cybiński | James Enouen | Antoine Georges | Anna Dawid
Source: arXiv (Cornell University) (preprint, 2024-11-04)
Field: Materials Science — Materials Chemistry

Speak so a physicist can understand you! TetrisCNN for detecting phase transitions and order parameters Recently, neural networks (NNs) have become a powerful tool for detecting quantum phases of matter. Unfortunately, NNs are black boxes and only identify phases without elucidating their properties. Novel physics benefits most from insights about phases, traditionally extracted in spin systems using spin correlators. Here, we combine two approaches and design TetrisCNN, a convolutional NN with parallel branches using different kernels that detects the phases of spin systems and expresses their essential descriptors, called order parameters, in a symbolic form based on spin correlators. We demonstrate this on the example of snapshots of the one-dimensional transverse-field Ising model taken in various bases. We show also that TetrisCNN can detect more complex order parameters using the example of two-dimensional Ising gauge theory. This work can lead to the integration of NNs with quantum simulators to study new exotic phases of matter. Physicist ; Order (exchange) ; Phase (matter) ; Theoretical physics ; Computer science ; Physics ; Business ; Quantum mechanics Machine Learning in Materials Science
Authors: Dan Wang
Source: Applied Mathematics and Nonlinear Sciences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Current Transformer Condition Online Monitoring Platform Based on Big Data Abstract As an important power equipment indispensable to the normal operation of the power grid, the good or bad working condition of the current transformer directly affects the operational efficiency of the whole power grid. In this paper, an online monitoring platform based on big data technology has been developed to monitor the current status of transformers. First of all, for the temperature of the transformer, through the decoupling of the heat generation mode of the transformer, the state monitoring method based on fiber optic temperature measurement technology and optical multiplexing technology is proposed, and the overall scheme of transformer state monitoring is designed. The data signal of the transformer’s status is collected and processed, and a fault state diagnosis model is constructed based on the decision tree algorithm. Finally, according to the data requirements of the current transformer, an online monitoring platform for transformer status has been constructed using big data technology. Through the simulation test, the variation of ratio error of this paper’s monitoring method is less than 0.60%, and the variation of phase error is less than 0.75 percent, which is in line with international requirements. The average loading time of the monitoring platform is between 123.591s~143.911s, the average loading speed is less than 13s, the average throughput is between 241ops/sec ~257ops/sec, and the average latency of the read and upload operations is 24.225ms. The current transformer condition monitoring platform in this paper has good stability, the overall performance is excellent, and it provides a good solution for the research of the current transformer condition monitoring platform provides practical support for the research of current transformer condition monitoring platform. Big data ; Computer science ; Data science ; Data mining High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Power Systems Fault Detection
Authors: Erwin Cazares | Brian E. Schuster
Source: arXiv (Cornell University) (preprint, 2024-07-17)
Field: Materials Science — Materials Chemistry

Deep Learning for Quantitative Dynamic Fragmentation Analysis We have developed an image-based convolutional neural network (CNN) that is applicable for quantitative time-resolved measurements of the fragmentation behavior of opaque brittle materials using ultra-high speed optical imaging. This model extends previous work on the U-net model, where we trained binary, 3 and 5 class models using supervised learning on experimentally measured dynamic fracture experiments on various opaque structural ceramic materials that were adhered on transparent polymer (polycarbonate or acrylic) backing materials. Full details of the experimental investigations are outside the scope of this manuscript but briefly, several different ceramics were loaded using spatially and time-varying mechanical loads to induce inelastic deformation and fracture processes that were recorded at frequencies as high as 5 MHz using high speed optical imaging. These experiments provided a rich and diverse dataset that includes many of the common fracture modes found in static and dynamic fracture including cone cracking, median cracking, comminution, and combined complex failure modes that involve effectively simultaneous activation and propagation of multiple fragmentation modes. While the training data presented here was obtained from dynamic fragmentation experiments, this study is applicable to static loading of these materials as the crack speeds typically higher a kilometer per second in these materials are on the order of 1-10 km/s regardless of the loading rate. We believe the methodologies presented here will be useful in quantifying the failure processes in structural materials for protection applications and can be used for direct validation of engineering models used in design. Fragmentation (computing) ; Computer science High-Velocity Impact and Material Behavior
Authors: Alain Hertz | Sébastien Bonte | Gauvain Devillez | Valentin Dusollier | Hadrien Mélot | David Schindl
Source: PolyPublie (École Polytechnique de Montréal) (preprint, 2024-03-08)
Field: Chemistry — Physical and Theoretical Chemistry

Extremal Chemical Graphs for the Arithmetic-Geometric Index The arithmetic-geometric index is a newly proposed degree-based graph invariant in mathematical chemistry. We give a sharp upper bound on the value of this invariant for connected chemical graphs of given order and size and characterize the connected chemical graphs that reach the bound. We also prove that the removal of the constraint that extremal chemical graphs must be connected does not allow to increase the upper bound. Index (typography) ; Arithmetic ; Mathematics ; Combinatorics ; Discrete mathematics ; Statistics ; Computer science ; World Wide Web History and advancements in chemistry ; Graph theory and applications ; Computational Drug Discovery Methods