jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rebecca D. Tarvin | Jeffrey L. Coleman | David A. Donoso | Mileidy Betancourth‐Cundar | Karem López-Hervas | Kimberly S Gleason | J Ryan Sanders | Jacqueline M Smith | Santiago R. Ron | Juan C. Santos | Brian E. Sedio | David C. Cannatella | Richard W. Fitch
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-05-15)
Field: Chemistry — Organic Chemistry

Passive accumulation of alkaloids in inconspicuously colored frogs refines the evolutionary paradigm of acquired chemical defenses Understanding the origins of novel, complex phenotypes is a major goal in evolutionary biology. Poison frogs of the family Dendrobatidae have evolved the novel ability to acquire alkaloids from their diet for chemical defense at least three times. However, taxon sampling for alkaloids has been biased towards colorful species, without similar attention paid to inconspicuous ones that are often assumed to be undefended. As a result, our understanding of how chemical defense evolved in this group is incomplete. Here we provide new data showing that, in contrast to previous studies, species from each undefended poison frog clade have measurable yet low amounts of alkaloids. We confirm that undefended dendrobatids regularly consume mites and ants, which are known sources of alkaloids. Thus, our data suggest that diet is insufficient to explain the defended phenotype. Our data support the existence of a phenotypic intermediate between toxin consumption and sequestration - passive accumulation - that differs from sequestration in that it involves no derived forms of transport and storage mechanisms yet results in low levels of toxin accumulation. We discuss the concept of passive accumulation and its potential role in the origin of chemical defenses in poison frogs and other toxin-sequestering organisms. In light of ideas from pharmacokinetics we incorporate new and old data from poison frogs into an evolutionary model that could help explain the origins of acquired chemical defenses in animals and provide insight into the molecular processes that govern the fate of ingested toxins. Biology ; Computational biology ; Evolutionary biology ; Communication ; Psychology Chemical synthesis and alkaloids ; Plant-based Medicinal Research ; Metabolomics and Mass Spectrometry Studies
Authors: Amir Hussairi Zaidi | Anis Hazirah ‘Izzati Hasnu Al-Hadi | Siti Mariatul Hazwa Mohd Huzir | Zakiah Mohd Yusoff | Nurlaila Ismail | Ali Abd Almisreb | Saıful Nizam Tajuddin | Mohd Nasir Taib
Source: International Journal of Advances in Applied Sciences (article, 2024-07-19)
Field: Chemistry — Organic Chemistry

Statistical analysis of agarwood oil chemical compound exists in four species of Aquilaria Aquilaria, renowned for its agarwood, and valued for its aromatic wood and rich resin, finds use in cosmetics, fragrances, incense, and medicine. Identifying the agarwood-producing species among 21 species of Aquilaria is challenging. This study analyzes chemical compounds in agarwood oil from 4 Aquilaria species: Aquilaria beccariana, Aquilaria crassna, Aquilaria malaccensis, and Aquilaria subintegra using gas chromatography-flame ionization detector (GC-FID). Statistical analysis explores compound abundance, employing methods like mean and Z-score tests. This analysis summarizes those 14 compounds that are consistently present based on zero and non-zero observations, and the Z-score test highlights five chemical compounds, with three compounds appearing in both analyses. These compounds can serve as a reference for future studies on Aquilaria species and agarwood oil, enhancing classification efforts. Agarwood ; Incense ; Chemical constituents ; Chemistry ; Traditional medicine ; Chromatography ; Geography ; Medicine ; Archaeology Wood and Agarwood Research ; Identification and Quantification in Food ; Advanced Image and Video Retrieval Techniques
Authors: Weiju Ren
Source: Journal of Pressure Vessel Technology (article, 2024-05-22)
Field: Materials Science — Materials Chemistry

Path Forward: Materials Data Modernization for ASME Codes and Standards in the Artificial Intelligence Era Abstract Development of the ASME Materials Properties Database was initiated in the early 2010s to support the ASME Codes and Standards. As information technologies advance at an accelerated pace with the artificial intelligence era on the horizon, the ASME Materials Properties Database must be further modernized from a database to a knowledgebase to ride the wave of digital information revolution and effectively support the ASME Codes and Standards in the new era. This paper is intended to provide an overview of the ASME Materials Properties Database and discuss a roadmap for its future development to facilitate understanding of and participation from different sectors of the Codes and Standards community. It first reviews the basic concepts of data, information, knowledge, database, and database system as well as the pros and cons in different types of data management and then discusses the path forward for a desired evolution of the database into a self-explanatory and machine-readable knowledgebase that is consistent with human cognitive processes for the Codes and Standards development and, furthermore, provides resources for data processing and analysis to reach an eventual goal of streamlining the Codes and Standards development from the initial inquiry, throughout data submission, analysis, …, to Codes and Standards rule establishment for final publication. Pace ; Database ; Modernization theory ; Path (computing) ; Engineering ; Computer science ; Data science ; Geography Machine Learning in Materials Science ; Manufacturing Process and Optimization ; Electron and X-Ray Spectroscopy Techniques
Authors: RAPEE SUKTHONGCHAIKOOL
Source: FARMACIA (article, 2024-10-28)
Field: Chemistry — Analytical Chemistry

NON-DESTRUCTIVE ANALYSIS OF BARIUM SULPHATE TABLETS BY NEAR-INFRARED SPECTROSCOPY A novel formulation of barium sulphate tablets was developed to replace the commercial radiopaque markers, since the commercial products are quite expensive and there is a restriction access for Thai patients.The quantitative determination of barium sulphate according to the United State Pharmacopoeia is performed using a gravimetric method which requires tedious sample preparation steps.In this study, fast and non-destructive analysis of barium sulphate tablets by benchtop and portable near infrared spectrometry (NIR) combined with chemometrics approach was developed and compared with reliable inductively coupled plasma-optical emission spectrometry (ICP-OES).Partial least square regression (PLSR) was the chemometrics tool selected in this study.The optimum PLSR model for benchtop NIR was obtained from standard normal variate (SNV) and orthogonal signal correction (OSC) pretreated NIR spectral data with 1 latent factor, R 2 Pearson for prediction was 0.9727, root mean square error of prediction (RMSEP) and bias were 3.7265 and 0.6614.While the best model for portable NIR was also obtained from SNV and OSC pretreated NIR spectral data with 2 latent factors, R 2 Pearson for prediction was 0.9371, RMSEP and bias were 5.6147 and -0.2604.The assay results of benchtop and portable NIR were not significantly different from ICP-OES. RezumatUlterior obinerii unei formulri cu sulfat de bariu sub form de comprimate, menit s nlocuiasc markerii comerciali actuali de radioopacitate, determinarea cantitativ a API a fost realizat conform printr-o metod rapid i nedistructiv de spectrometrie benchtop n infrarou apropiat (NIR), combinat cu abordarea chemometric i a fost comparat cu spectrometria de emisie optic cu plasm cuplat inductiv (ICP-OES).Regresia parial a celor mai mici ptrate (PLSR) a fost instrumentul chemometric selectat n acest studiu.Modelul PLSR optim pentru NIR de benchtop a fost obinut din date spectrale NIR cu variaii normale standard (SNV) i corecie a semnalului ortogonal (OSC) cu 1 factor latent, factorul R2 Pearson pentru predicie fiind regsit 0,9727, eroarea ptrat medie a prediciei (RMSEP) i bias au fost calculate 3,7265 i respective 0,6614.Cel mai bun model pentru NIR portabil a fost, de asemenea, obinut din datele spectrale NIR pretratate SNV i OSC, dar cu 2 factori lateni, factorul R2 Pearson pentru predicie a fost 0,9371, RMSEP i bias-ul au fost 5,6147 i respectiv -0,2604.Rezultatele testului NIR de benchtop portabil nu au fost semnificativ diferite de cele obinute prin intermediul ICP-OES. Barium sulphate ; Infrared spectroscopy ; Barium ; Infrared ; Spectroscopy ; Materials science ; Analytical Chemistry (journal) ; Chemistry ; Environmental chemistry ; Optics ; Radiochemistry ; Physics ; Metallurgy ; Organic chemistry Spectroscopy and Chemometric Analyses
Authors: Farias, Francisco Werley Cipriano | dos Santos, Telmo Jorge Gomes | Oliveira, João Pedro
Source: Universidade Nova de Lisboa's Repository (Universidade Nova de Lisboa) (review, 2024-03-01)
Field: Materials Science — Materials Chemistry

a state-of-the-art literature review Open access funding provided by FCT|FCCN (b-on). Funding by national funds from FCT-Fundação para a Ciência e a Tecnologia, I.P., in the scope of the projects LA/P/0037/2020, d. FWCF acknowledges Fundação para a Ciência e a Tecnologia (FCT-MCTES) for funding the Ph.D. Grant 2022.13870.BD. This activity has received funding from the European Institute of Innovation and Technology (EIT) Raw Materials through the project Smart WAAM: Microstructural Engineering and Integrated Non-Destructive Testing. Publisher Copyright: © The Author(s) 2024. Scope (computer science) ; Technology transfer ; Work (physics) ; Government (linguistics) ; White paper Machine Learning in Materials Science ; Composite Material Mechanics ; Thermography and Photoacoustic Techniques
Authors: Amit G. Nerkar | Yash Patil
Source: Current Trends in Pharmacy and Pharmaceutical Chemistry (review, 2024-09-07)
Field: Chemistry — Spectroscopy

A comprehensive review of analytical strategies for validating RP-HPLC methods of aceclofenac and thiocolchicoside in bulk drug and formulation This comprehensive review explores the analytical method development and validation of Aceclofenac and Thiocolchicoside bulk drugs and formulations using Reverse Phase High-Performance Liquid Chromatography (RP-HPLC). Aceclofenac, a nonsteroidal anti-inflammatory drug (NSAID), and Thiocolchicoside, a muscle relaxant, are commonly co-formulated for the treatment of pain and inflammation. The review discusses the principles and strategies involved in RP-HPLC method development, emphasizing factors such as stationary phase selection, mobile phase composition, and detection wavelength optimization. Furthermore, it highlights the importance of method validation in pharmaceutical analysis, covering parameters such as specificity, linearity, accuracy, precision, robustness, and system suitability. The literature review section examines previous studies on RP-HPLC methods developed for Aceclofenac and Thiocolchicoside, summarizing key findings and comparing different methodologies. Challenges and limitations encountered during method development and validation are discussed, along with recent advances in RP-HPLC methodology. Finally, the review outlines future research directions and potential applications of RP-HPLC in studying the pharmacokinetics and bioavailability of Aceclofenac and Thiocolchicoside formulations. Aceclofenac ; Drug ; Chromatography ; Traditional medicine ; Chemistry ; Pharmacology ; Medicine Analytical Chemistry and Chromatography ; Analytical Methods in Pharmaceuticals ; Microfluidic and Capillary Electrophoresis Applications
Authors: Leonhard M. Lohr | Richard Ciesielski | Vinh‐Binh Truong | Victor Soltwisch
Source: arXiv (Cornell University) (preprint, 2024-10-31)
Field: Materials Science — Surfaces, Coatings and Films

Hybrid approach to reconstruct nanoscale grating dimensions using scattering and fluorescence with soft X-rays Scatterometry is a tested method for measuring periodic semiconductor structures. Since the sizes of modern semiconductor structures have reached the nanoscale regime, the challenge is to determine the shape of periodic nanostructures with sub-nanometer accuracy. To increase the resolution of scatterometry, short-wavelength radiation like soft X-rays can be used. But, scatterometry with soft X-rays is an inverse problem whose solutions can be ambiguous and its sensitivity should be further increased to determine the shape of even more complicated periodic nanostructures made up of different materials. To achieve unique solutions with smaller uncertainties, scatterometry can leverage the excitation of low-Z materials with soft X-rays. Additional information from soft X-ray fluorescence analysis in a hybrid measurement approach can mitigate the problem of ambiguous solutions from soft X-ray scattering and could further decrease uncertainty. In this work, the hybrid approach is utilized to perform a comparison of solutions from the inverse problem and determine the actual solution over ambiguous solutions. Nanoscopic scale ; Optics ; Scattering ; Grating ; Fluorescence ; Physics ; Soft X-rays ; Materials science ; Nanotechnology Optical Coatings and Gratings ; Photonic and Optical Devices ; Near-Field Optical Microscopy
Authors: Aleksandra Milosavljević | Ana Kostov | Predrag Stolić
Source:  (article, 2024-01-01)
Field: Materials Science — General Materials Science

Liquid metal alloys based on gallium Liquid metal alloys based on gallium are materials of great interest due to their outstanding properties and wide range of applications. This paper provides an overview of the current state of research in the field of gallium-based liquid metal alloys, as well as applications in various industries. Examples of these materials with the lowest melting point are also given in this paper. Gallium ; Materials science ; Metal ; Metallurgy ; Liquid metal Material Properties and Applications ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry ; Advanced Energy Technologies and Civil Engineering Innovations
Authors: قبس محمود عباس | غسان فارس عطية
Source: Samarra Journal of Pure and Applied Science (article, 2024-12-30)
Field: Chemistry — Analytical Chemistry

فعالية بعض المنتجات النباتية كطلاء قابل للأكل في تثبيط الإصابة الفطرية وزيادة العمر الافتراضي لخزن الثمار التفاح المحلي Malus domestica L. لدراسة تأثير طلاء ثمار التفاح المحلي لمدة ثلاث أسابيع ببعض المنتجات الطبيعية لتثبيط الإصابة الفطرية وزيادة العمر الافتراضي للتخزين تحت ظروف 25 وبنسبة رطوبة طبيعية للغرفة لمدة 21 يوماً واشتملت عوامل التجربة على عاملين، العامل الأول أنواع مواد الطلاء الطبيعية اي: زيت الحبة السوداء، شمع العسل، البكتين، والعامل الثاني عامل التركيز بواقع (1%)، (2%)، (3%) على التوالي لكل مادة طلاء وصممت التجربة وفق تصميم تام التعشية completely Randomized Design وبتكرار ثلاث مرات لكل معاملة وتمت دراسة 7 صفات نوعية لمجاميع الثمار المحلية وهي Total Flavonoid Contents مستوى السكر، محتوى الفلافونويد الكلي، محتوى الفينولات الكلي. بالمقارنة مع مجموعة الثمار غير المطلية عند بدء التجربة ونهايتها، وأظهرت النتائج لصفة فقدان الوزن بان الطلاء بزيت الحبة السوداء عند جميع التراكيز المستخدمة سجلت اقل فقدان للوزن عند الأسبوع الأول الى الأسبوع الثالث وبنسب بلغت (4.85%)، (7.98%)، (8.12%)، (4.87%)، على التوالي مقارنة مع معاملة السيطرة بعد الخزن التي سجلت اعلى فقدان وزن وبنسب قد بلغت (6.94%)، (11.19%)، (16.24%)، و سجلت معاملة البكتين اعلى نسب فقدان للوزن بلغت عند الأسبوع الثالث (11.45%)، (10.24%)، (9.31%) بالتتابع كما أظهرت النتائج بأن نسبة الإصابة الفطرية سجلت اختلافاً في شدة الإصابة باختلاف نوع المادة وتركيزها فقد سجل التركيزات 2%، 3% لزيت الحبة السوداء أقل معدل للإصابة الفطرية عند الأسبوع الثالث مع قيم بلغت (10%) و( 11%). بينما سجلت المعاملة بشمع العسل نسب متوسطه لفقدان الوزن بلغت عند الاسبوع الثالث (‎%‎10.21‎) و (‎%‎9.02) و (‎%‎8.14) بالتتابع. Flavonoid ; Cultivar ; PEAR ; Malus Heavy Metals in Plants ; Garlic and Onion Studies ; Bioactive Compounds in Plants
Authors: Alvaro Ribot | Chandler Squires | Caroline Uhler
Source: arXiv (Cornell University) (preprint, 2024-02-22)
Field: Materials Science — Materials Chemistry

Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models We consider the task of causal imputation, where we aim to predict the outcomes of some set of actions across a wide range of possible contexts. As a running example, we consider predicting how different drugs affect cells from different cell types. We study the index-only setting, where the actions and contexts are categorical variables with a finite number of possible values. Even in this simple setting, a practical challenge arises, since often only a small subset of possible action-context pairs have been studied. Thus, models must extrapolate to novel action-context pairs, which can be framed as a form of matrix completion with rows indexed by actions, columns indexed by contexts, and matrix entries corresponding to outcomes. We introduce a novel SCM-based model class, where the outcome is expressed as a counterfactual, actions are expressed as interventions on an instrumental variable, and contexts are defined based on the initial state of the system. We show that, under a linearity assumption, this setup induces a latent factor model over the matrix of outcomes, with an additional fixed effect term. To perform causal prediction based on this model class, we introduce simple extension to the Synthetic Interventions estimator (Agarwal et al., 2020). We evaluate several matrix completion approaches on the PRISM drug repurposing dataset, showing that our method outperforms all other considered matrix completion approaches. Counterfactual thinking ; Bridging (networking) ; Imputation (statistics) ; Latent variable ; Econometrics ; Computer science ; Mathematics ; Artificial intelligence ; Missing data ; Psychology ; Statistics ; Social psychology ; Computer security Machine Learning in Materials Science ; Topic Modeling ; Bayesian Modeling and Causal Inference
Authors: N. I. Polushin | I. A. Bubnenkov | Mariya Stanislavovna Shitareva
Source:  (article, 2024-12-11)
Field: Materials Science — Materials Chemistry

THE INTERACTION OF SILICON WITH A GRAPHITE QUASI-SINGLE CRYSTAL The authors describe the current state of affairs in the global ICT industry and in the markets themselves, on the network, in digital ecosystems, on marketplaces, where big tech decides to launch new lines of gadgets for the next breakthroughs in AI and on the experience of Big Data, make forecasts for the mainstream and on potential leaders in Industry 4.0.The main tasks for the development of the cyber environment and the space of virtual and additional reality determine the tasks of the growing opposition between the collective West and the countries of the global South, the awakening East and Russia, which is fighting for its own self-purification. Silicon ; Graphite ; Materials science ; Crystal (programming language) ; Nanotechnology ; Optoelectronics ; Computer science ; Chemical physics ; Engineering physics ; Chemistry ; Physics ; Composite material Graphite, nuclear technology, radiation studies
Authors: Tristan Cardon | Diego Fernando Garcia-del Rio | Mehdi Derhourhi | Amélie Bonnefond | Sébastien Leblanc | Noé Guilloy | Xavier Roucou | Sven Eyckerman | Kris Gevaert | Michel Salzet
Source: Research Square (preprint, 2024-04-09)
Field: Chemistry — Spectroscopy

Deciphering the ghost proteome in ovarian cancer cells by deep proteogenomic characterization Proteogenomics ; Proteome ; Ovarian cancer ; Computational biology ; Biology ; Cancer research ; Cancer ; Bioinformatics ; Transcriptome ; Biochemistry ; Genetics ; Gene Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Genomics and Phylogenetic Studies
Authors: Kévin Colin | Håkan Hjalmarsson | Véronique Chotteau
Source: arXiv (Cornell University) (preprint, 2024-02-07)
Field: Materials Science — Materials Chemistry

Data-driven Bayesian estimation of Monod kinetics In this paper, we consider the well known problem of non-linear identification of the rates of the reactions involved in cells with Monod functions. In bioprocesses, generating data is very expensive and long and so it is important to incorporate prior knowledge on the Monod kinetic parameters. Bayesian estimation is an elegant estimation technique which deals with parameter estimation with prior knowledge modeled as probability density functions. However, we might not have an accurate knowledge of the kinetic parameters such as interval bounds, especially for newly developed cell lines. Hence, we consider the case when there is no accurate prior information on the kinetic parameters except qualitative knowledge such that their non-negativity. A log-Gaussian prior distribution is considered for the parameters and the mean and variances of these distribution are tuned using the Expectation Maximization algorithm. The algorithm requires to use Metropolis Hastings within Gibbs sampling which can be computationally expensive. We develop a novel variant of the Metropolis-Hastings within Gibbs sampling sampling scheme in order to accelerate and improve on the hyperparameter tuning. We show that it can give better modeling performances on a relatively large-scale simulation example compared to available methods in the literature. Bayesian probability ; Estimation ; Econometrics ; Bayes estimator ; Kinetics ; Economics ; Computer science ; Artificial intelligence ; Physics Machine Learning in Materials Science ; Gaussian Processes and Bayesian Inference ; Model Reduction and Neural Networks
Authors: Sanita Vucāne | Ingmārs Cinkmanis | Mārtiņš Šabovics
Source: Research Square (preprint, 2024-02-16)
Field: Chemistry — Analytical Chemistry

Python algorithm for Calculation of Total Phenolic Compounds in Vegetable Oils with Smartphone Image analysis Abstract In this research, a Python algorithm was developed that calculated one of the total concentrations of phenol in vegetable oils using the RGB colour system. The algorithm converts data obtained in the RGB colour system into absorbance values using NumPy, Pandas, Matplotlib and SciPy libraries. It allows for complex data calculations and analyses that are particularly accurate and more efficient than traditional methods such as MS Excel. Algorithm development is divided into six stages: library import, user data input and processing, absorbance calculations, linear regression and calibration curve drawing, data analysis and saving results in Excel format. The algorithm offers flexible use in both local Python development environments and online platforms such as Kaggle (https://www.kaggle.com/). It can also be used in the analyses of other plant extracts or chemical substances, where interpretations of RGB colour system data are used as a basis. This algorithm opens up new possibilities in scientific data analysis by taking advantage of modern technology and programming language. Python (programming language) ; Computer science ; Algorithm ; Computer graphics (images) ; Mathematics ; Programming language Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies