jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mehar Chand | Som Kumar | Santosh Kumar | Vishal Jagota | Subash Kumar | Kulwinder Kumar
Source: Journal of Materials and Engineering (article, 2024-10-01)
Field: Materials Science — Materials Chemistry

Effect of Machining Parameters on the Surface Roughness of Hot Die Steel H13 tool steel is frequently used in hot work dies, hot forging, hot extrusion, and mold materials for casting ferrous and nonferrous materials. Surface roughness is of key importance in case of dies and moulds, as it insures the finish of the final product. After studying the work done by the researchers in field of machining and its impact over surface roughness, it was found that machining behaviour of H13 steel at the annealed state is not being studied. The surface finish obtained during turning of H13 steel are not studied on a greater scale, so the present study includes the analysis of finish (surface roughness) generated. Turning operation is carried out on the CNC machine at dry condition with an aim to find systematically the effect on surface roughness by distinct machining variables like feed rate, depth of cut and speed. RSM model using Box Behnken design is used to predict the roughness developed during turning of annealed H13 steel using carbide tool. It was found that feed rate and the depth of cut have a direct relation with the surface finish and the value of surface roughness increases with increase in these parameters. On the other side, cutting speed has a less impact over the surface roughness &amp; is inversely related. Die (integrated circuit) ; Machining ; Surface roughness ; Materials science ; Surface finish ; Metallurgy ; Mechanical engineering ; Engineering ; Composite material Metal Alloys Wear and Properties ; Advanced Surface Polishing Techniques ; Advanced machining processes and optimization
Authors: Mariusz Święcicki
Source: JOIV International Journal on Informatics Visualization (article, 2024-03-14)
Field: Chemistry — Spectroscopy

A Classification Algorithm Inspired by the Chromatographic Separation Mechanism Dedicated to the Classification of Variable-length and Multi-class Vectors Nowadays, one of the critical problems related to data mining is the processing of large data sets. This article presents an algorithm that may apply to the issues associated with classifying large-volume data sets. The motivation behind defining this type of algorithm was that the methods used to process this data type are subject to several significant limitations. The first considerable limitation of using classical classification methods is ensuring a constant data size. The second type of constraint is related to the data dimension. The last limitation in using classic classification algorithms is associated with the situation in which a given input vector may contain data belonging to many classes simultaneously, in which case we are talking about so-called multi-class vectors. The presented algorithm is inspired by the method of chromatographic separation of chemical substances. This method is widely and successfully used in analytical chemistry. As we know, in the case of chromatographic separation, we are dealing with a similar class of problems that occur when processing large data sets, firstly: the molecules of a chemical substance have a different number of molecules - i.e., they have different lengths, which corresponds to the situation that occurs when processing large data sets. In this work, a classification algorithm inspired by the mechanism of resolution chromatography is presented. The article presents the results of calculations for sample data sets. It discusses issues related to the properties of the defined algorithm, which concern the algorithm training process and the classification of single-class and multi-class data. Algorithm ; Computer science ; Class (philosophy) ; Dimension (graph theory) ; Constraint (computer-aided design) ; Process (computing) ; Variable (mathematics) ; One-class classification ; Data mining ; Artificial intelligence ; Pattern recognition (psychology) ; Support vector machine ; Mathematics Analytical Chemistry and Chromatography
Authors: Ayşe Küçük Yılmaz | S. James O'Brien | Philipp R. Thies | Prodip K. Das | Erkan Oterkus
Source:  (article, 2024-06-09)
Field: Materials Science — Materials Chemistry

Leveraging Digital Twins for Hydrogen Loss Mitigation in Large Scale Salt Cavern Hydrogen Storage Abstract As hydrogen continues to emerge as a key solution to decarbonise the global energy sector, interest in efficient storage solutions increases to meet rising energy demands and to ensure energy security. Large scale hydrogen storage salt caverns look to be a promising solution for hydrogen storage due to their ability to store large volumes of gas safely, as proven when storing natural gas in underground salt caverns. Hydrogen stored in underground salt caverns exhibits losses due to reasons such as gas migration, and the active chemistry they possess in addition to leaks due to damage caused by the cyclic loading on the cavern. Understanding the hydrogen loss pathways could help reduce financial losses and mitigate any safety risks imposed. Using SSE’s Aldbrough Hydrogen Pathfinder project, based in the UK Humber region as a case study, this paper aims to demonstrate how a digital twin can be utilised to evaluate and forecast hydrogen leaks by incorporating real time and historical data from sensors, geological information, and environmental factors to provide a holistic view of the cavern’s dynamics. This research aims to facilitate early detection of failures and highlight possible intervention mechanisms and strategies for underground salt cavern storage used for green hydrogen. Hydrogen storage ; Hydrogen ; Salt (chemistry) ; Scale (ratio) ; Computer science ; Environmental science ; Chemistry ; Physics Advancements in Solid Oxide Fuel Cells
Authors: Florian Weissmann | Julia F. Greiwe | Thomas Pühringer | Thomas C. R. Miller | John F.X. Diffley | Alessandro Costa
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-04-10)
Field: Materials Science — Biomaterials

MCM Double Hexamer Loading Visualised with Human Proteins Abstract Eukaryotic DNA replication begins with the loading of the MCM replicative DNA helicase as a head-to-head double hexamer (DH) at origins of DNA replication 1–3 . Our current understanding of how DH is assembled by the Origin Recognition Complex (ORC), CDC6 and CDT1 comes mostly from budding yeast. Here we characterise human DH (hDH) loading using biochemical reconstitution and cryo-electron microscopy with purified proteins. We show that hDH engages DNA differently from yeast (yDH), and generates ∼5 base pairs of unwound DNA at the interface between hexamers, as seen in hDH isolated from cells 4 . We identify several differences from yeast in the order of factor recruitment and dependencies during hDH assembly. Unlike yeast 5–8 , the ORC6 subunit of ORC is not essential for initial MCM recruitment or hDH loading, but contributes to an alternative hDH assembly pathway requiring an intrinsically disordered region (IDR) in ORC1, which may work through a novel MCM-ORC (hMO*) intermediate. Our work presents a detailed view of how DHs are assembled in an organism utilising sequence-independent replication origins, it provides further evidence for diversity in eukaryotic DH assembly mechanisms 9 , and it represents the first step toward reconstitution of DNA replication initiation with purified human proteins. Random hexamer ; Computational biology ; Chemistry ; Computer science ; Biophysics ; Biology ; Crystallography Silk-based biomaterials and applications
Authors: Maryam Rashid | Neha Sajjad | Nusrat Shafiq | Shagufta Parveen | Rashid Ahmed Khan | Ariba Farooq | Muhammad Shahab | Turki M. Dawoud | Simone Brogi | Mohammed Bourhia
Source: ChemistrySelect (article, 2024-01-16)
Field: Materials Science — Biomaterials

Multi‐Technique Approach to Identify Potent Antimicrobial Agents from <i>Calotropis procera</i> : Insight into Pharmacophore Modeling, Molecular docking, MD simulation, and DFT Approaches Abstract In this research, natural compounds from Calotropisprocera were screened according to their antimicrobial activity against the pathogenic microbes selected as E. coli , S. aureus , Traypanosomabrucei , Moraxella catarrhalis , and Leishmaniaamazonensis . A 3D‐QSAR study was performed that evaluated the correlation of the structural parameters for the antimicrobial activity of the natural compounds which were selected based on their antimicrobial in‐vivo and in‐vitro studies previously. The screened active compounds were further studied by molecular docking to analyze the various interactions between the ligands and target proteins. Molecular docking was also performed with the three FDA‐approved antibiotics Cephalexin, Dicloxacillin, and Levofloxacin, having antimicrobial potential, and their results were compared with the docking results of the hit compounds. Results of ADME/T study of the compounds revealed that the two compounds stigmasterol and caryophyllene oxide are the hit compounds having no toxicity, best values of TPSA and average molecular weight. Validation of the docking results was also carried out by re‐docking as well as by molecular dynamic simulation. DFT study was also carried out to explore the stability and chemical properties of active compounds. Results showed that caryophyllene oxide is the hit compound because of the highest Moldock score with 3VOB protein, better than standard drugs and according to dynamic simulation analysis. Therefore, the derived results in these studies provide crucial information for designing antimicrobial drugs by using natural compounds that have better antimicrobial activity. Antimicrobial ; Docking (animal) ; ADME ; Pharmacophore ; Chemistry ; Quantitative structure–activity relationship ; Combinatorial chemistry ; Stereochemistry ; Computational biology ; Biochemistry ; In vitro ; Biology ; Organic chemistry ; Medicine Phytochemistry and Bioactive Compounds ; Bioactive Compounds and Antitumor Agents ; Phytochemistry and Bioactivity Studies
Authors: Tomislav Plesa
Source: arXiv (Cornell University) (preprint, 2024-06-05)
Field: Chemistry — Spectroscopy

Mapping dynamical systems into chemical reactions Polynomial dynamical systems (DSs) can model a wide range of physical processes. A special subset of these DSs that can model chemical reactions under mass-action kinetics is called chemical dynamical systems (CDSs). A fundamental problem, central to synthetic biology, is to map polynomial DSs into dynamically similar CDSs. In this paper, we introduce the quasi-chemical map (QCM) that can systematically solve this problem. The QCM introduces suitable state-dependent perturbations into any given polynomial DS which then becomes a CDS under sufficiently large translations of variables. This map preserves robust features, such as generic equilibria and limit cycles, and generic bifurcations, as well as some temporal properties, such as periods of oscillations. Furthermore, the resulting CDSs are at most one degree higher than the original DSs. We showcase the QCM by designing relatively simple CDSs with oscillations, chaos and bifurcations, and addressing Hilbert's 16th problem in chemistry. Computer science ; Dynamical systems theory ; Physics Molecular spectroscopy and chirality ; Gene Regulatory Network Analysis
Authors: Jared M. Ragland | Benjamin J. Place
Source: Journal of the American Society for Mass Spectrometry (article, 2024-05-05)
Field: Chemistry — Spectroscopy

A Portable and Reusable Database Infrastructure for Mass Spectrometry, and Its Associated Toolkit (The DIMSpec Project) Nontargeted analysis (NTA) is a rapidly growing field of techniques that includes the identification of unknown chemical analytes in complex mixtures such as environmental, biological, and food matrices. The use of reference mass spectral databases is a key component of most NTA workflows, providing a high level of confidence for chemical identification when analytical standards are not available, yet effective interlaboratory sharing of research grade spectra remains challenging. The Database Infrastructure for Mass Spectrometry (DIMSpec) project focused on the creation of an open-source toolkit supporting storage and sharing of high-resolution mass spectra with attached sample and methodological metadata. As a demonstration of its utility, the DIMSpec toolkit was used to create a database of curated mass spectra for per- and polyfluoroalkyl substances (PFAS) generated from various sources. While the underlying toolkit is agnostic to analytical targets, this initial release (along with the database schema, mass spectral data, and database tools) should enable PFAS researchers to use these data for their own studies, including the identification of novel PFAS in the environment. Workflow ; Metadata ; Database ; Chemistry ; Mass spectrometry ; Identification (biology) ; Computer science ; Data science ; World Wide Web ; Chromatography Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Per- and polyfluoroalkyl substances research
Authors: Christoph Gäntgen | Evan Berkowitz | Thomas Luu | Johann Ostmeyer | Marcel Rodekamp
Source:  (article, 2024-05-05)
Field: Chemistry — Organic Chemistry

Reducing the Sign Problem with simple Contour Deformation We apply constant imaginary offsets to the path integral for a reduction of the sign problem in the Hubbard model. These simple transformations enhance the quality of results from HMC calculations without compromising the speed of the algorithm. This method enables us to efficiently calculate systems that are otherwise inaccessible due to a severe sign problem. To support this claim, we present observables of the C20 and C60 fullerenes. Furthermore, we demonstrate that at a certain offset, the sign problem is completely lifted in the limit of large chemical potential. Sign (mathematics) ; Simple (philosophy) ; Offset (computer science) ; Observable ; Computer science ; Limit (mathematics) ; Path (computing) ; Algorithm ; Constant (computer programming) ; Reduction (mathematics) ; Mathematical optimization ; Mathematics ; Mathematical analysis ; Physics ; Geometry ; Quantum mechanics Fullerene Chemistry and Applications ; Advanced Chemical Physics Studies ; Advanced Physical and Chemical Molecular Interactions
Authors: Neha M Arolkar | C. Ortíz | Nikita Dapurkar | Carlos Blanes | Pablo Gonzalez-Planells
Source: Horticulturae (article, 2024-08-30)
Field: Chemistry — Analytical Chemistry

Automated Tenderness Assessment of Okra Using Robotic Non-Destructive Sensing The quality of okra is crucial in satisfying consumer expectations, and the tenderness of okra is an essential parameter in estimating its condition. However, the current methods for assessing okra tenderness are slow and prone to errors, necessitating the development of a better, non-destructive method. The objective of the present study is to develop and test a non-destructive robotic sensor for assessing okra freshness and tenderness. A total of 120 pods were divided into two sets and stored under different conditions: 60 pods were kept in a cold chamber for 24 h (considered tender), while the other 60 pods were stored at room temperature for two days. First, the samples were assessed non-destructively using the force sensor of a collaborative robot, where a jamming pad (with internal granular fill) was capable of adapting and copying the okra shapes while controlling its force deformation. Second, the okra pods were evaluated with the referenced destructive tests, as well as weight loss, compression, and puncture tests. In order to validate the differences in the tenderness of the two sets, a discriminant analysis was carried out to segregate the okra pods into the two categories according to the destructive variables, confirming the procedure which was followed to produce tender and non-tender okra pods. After the differences in the tenderness of the two sets were confirmed, the variables extracted from the robotic sensor (maximum force (Fmax), first slope (S1), second slope (S2), the first overshoot (Os), and the steady state (Ss)) were significant predictors for the separation in the two quality categories. Discriminant analysis and logistic regression methods were applied to classify the pods into the two tenderness categories. Promising results were obtained using neural network classification with 80% accuracy in predicting tenderness from the sensor data, and a 95.5% accuracy rate was achieved in distinguishing between tender and non-tender okra pods in the validation data set. The use of the robotic sensor could be an efficient tool in evaluating the quality of okra. This process may lead to substantial savings and waste reduction, particularly considering the elevated cost and challenges associated with transporting perishable vegetables. Tenderness ; Horticulture ; Environmental science ; Computer science ; Biology ; Food science Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Laura Palmieri | Maxime Ferrand | Ai Vu Hong | Isabelle Richard | Sonia Albini
Source: Preprints.org (preprint, 2024-09-05)
Field: Materials Science — Polymers and Plastics

In Silico Structural Prediction for the Generation of Novel Performant Midi-Dystrophins Based on Intein-Mediated Dual AAV Approach Duchenne Muscular Dystrophy (DMD) is a pediatric disorder characterized by progressive muscle degeneration and premature death, with no cure at the moment. The currently most promising therapeutic avenue is based on gene replacement mediated by adeno-associated viruses (AAVs) using a shortened, but still functional, version of Dystrophin, known as microdystrophin (µDys), to fit AAV capacity. The limited improvements observed in clinical trials suggest a sub-optimal performance of µDys in the human context, that could be due to the lack of key domains in the protein. Therefore, expressing larger dystrophin proteins may be necessary for a more complete correction of the disease phenotype. In this study, we developed three novel Midi-Dystrophin constructs using a dual-AAV approach, leveraging split intein-based protein trans-splicing. The midi-dystrophins include additional domains compared to µDys, such as the central cytoskeleton-binding domain, nNOS and Par1b interacting domains, and a complete C-terminal region. Given the limited capacity of each AAV vector, we strategically partially reduced hinge regions while ensuring that the structural stability of the protein remains intact. We predicted the interactions between the two halves of the split Midi-Dys proteins thanks to the deep-learning algorithm AphaFold3. We observed strong associations between the N- and C-termini in Midi-Dys 1 and 2, while a weaker interaction in Midi-Dys 3 was revealed. Our subsequent experiments confirmed the efficient protein trans-splicing both in vitro and in vivo in DBA2/mdx mice of the Midi-Dys 1 and 2 and not in Midi-Dy3 as expected from the structural prediction. Additionally, we demonstrated that Midi-Dys 1 and 2 exhibit significant therapeutic efficacy in DBA2/mdx mice, highlighting their potential as therapeutic agents for DMD. Overall, these findings highlight the potential of deep learning-based structural modeling for the generation of intein-based dystrophin versions and pose the basis for further investigation of these new midi-dystrophins versions for clinical studies. In silico ; Intein ; MIDI ; Dual (grammatical number) ; Computer science ; Computational biology ; Artificial intelligence ; Biology ; Genetics ; Operating system Polymer composites and self-healing ; Conducting polymers and applications
Authors: Alicia Sit | Francesco Di Colandrea | Alessio D’Errico | Ebrahim Karimi
Source: arXiv (Cornell University) (preprint, 2024-03-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A genetic algorithm for the response of twisted nematic liquid crystals to an applied field When an external field is applied across a liquid-crystal cell, the twist and tilt distributions cannot be calculated analytically and must be extracted numerically. In the standard approach, the Euler-Lagrange equations are derived from the minimization of the free energy of the system and then solved via finite-difference methods, often implemented in commercial software. These tools iterate from initial solutions that are compatible with the boundary conditions, providing limited to no flexibility for customization. Here, we present a genetic algorithm that outputs fast and accurate solutions to the integral form of the equations. In our approach, the evolutionary routine is sequentially applied at each position within the bulk of the cell, thus overcoming the necessity of assuming trial solutions. The predictions of our routine strongly support the experimental observations on different instances of spatially varying twisted nematic liquid-crystal cells, patterned with different topologies on the two alignment layers. Liquid crystal ; Field (mathematics) ; Genetic algorithm ; Algorithm ; Materials science ; Computer science ; Physics ; Condensed matter physics ; Optics ; Mathematics ; Pure mathematics Liquid Crystal Research Advancements ; Photonic Crystals and Applications ; Advanced Optical Imaging Technologies
Authors: Eduardo S. Kitano | Gareth Nisbet | Yana Demyanenko | Katarzyna M. Kowalczyk | Louisa Iselin | Stephen Cross | Alfredo Castelló | Shabaz Mohammed
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-04-03)
Field: Chemistry — Spectroscopy

Cheap, Robust and Versatile Two-Dimensional Chromatography system for Proteomics of Nanogram Scale Samples ABSTRACT In this work we describe a low loss fractionation system comprised of a reconfigured Evosep One LC system for the first dimension and a repurposed 3D-printer as a fraction collector. The setup operates as a high-pH fractionation system capable of effectively working with nanogram scales of lysate digests. The 2D RP-RP system demonstrated superior proteome coverage over single-shot data-dependent acquisition (DDA) analysis using only 5 ng of human cell lysate digest with performance increasing with increasing amounts of material. We found that the fractionation system allowed over 70% signal recovery at the peptide level and, more importantly, we observed over 30% increase on protein level intensity which indicates the complexity reduction afforded by the system outweighs the sample losses endured. The application of data-independent acquisition (DIA) and wide window acquisition (WWA) to fractionated samples allowed more than 8,000 proteins to be identified from 50 ng of material. The utility of the 2D system was further investigated for phosphoproteomics (&gt;21,000 phosphosites from 50 μg starting material) and pull-down type experiments and showed substantial improvements over single-shot experiments. We show that the 2D RP-RP system is highly versatile and powerful tool for many proteomics workflows. Fractionation ; Phosphoproteomics ; Proteome ; Proteomics ; Chromatography ; Lysis ; Chemistry ; Fraction (chemistry) ; Workflow ; Sample preparation ; Computer science ; Biological system ; Biology ; Database ; Biochemistry ; Enzyme Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications