jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Swati Chandna | Benjamin E. Bagozzi | Snigdhansu Chatterjee
Source: BIROn (Birkbeck, University of London) (preprint, 2024-12-20)
Field: Chemistry — Analytical Chemistry

Profile least squares estimation in networks with covariates Many real world networks exhibit edge heterogeneity with different pairs of nodes interacting with different intensities. Further, nodes with similar attributes tend to interact more with each other. Thus, in the presence of observed node attributes (covariates), it is of interest to understand the extent to which these covariates explain interactions between pairs of nodes and to suitably estimate the remaining structure due to unobserved factors. For example, in the study of international relations, the extent to which country-pair specific attributes such as the number of material/verbal conflicts and volume of trade explain military alliances between different countries can lead to valuable insights. We study the model where pairwise edge probabilities are given by the sum of a linear edge covariate term and a residual term to model the remaining heterogeneity from unobserved factors. We approach estimation of the model via profile least squares and show how it leads to a simple algorithm to estimate the linear covariate term and the residual structure that is truly latent in the presence of observed covariates. Our framework lends itself naturally to a bootstrap procedure which is used to draw inference on model parameters, such as to determine significance of the homophily parameter or covariates in explaining the underlying network structure. Application to four real network datasets and comparisons using simulated data illustrate the usefulness of our approach. Covariate ; Estimation ; Statistics ; Least-squares function approximation ; Econometrics ; Computer science ; Mathematics ; Economics ; Estimator Spectroscopy and Chemometric Analyses ; Face and Expression Recognition
Authors: Cruz | Gergov | Tarapoulouzi | Kirilova | Kostadinova | Nikolova
Source: Bulgarian Chemical Communications (article, 2024-04-15)
Field: Chemistry — Analytical Chemistry

Classification of apple varieties by VIS-NIR diffuse reflectance spectroscopy and chemometrics The new promising VIS NIR-ES (visible near infrared extra sensitive) spectrometer was used to identify a variety of apples.The aim of this study was to investigate the applicability of VIS-NIR spectroscopy combined with chemometric methods for the classification of different varieties of apples.The study was performed by analyzing the diffuse reflectance spectra of three different types of Chinese apples: the Fuji apple, the Red Star apple, and the Gala apple.To achieve this, after suitable preprocessing, a variable selection algorithm called interval partial least squares discriminant analysis (iPLS-DA) was used to identify the most significant spectral range.This range was then compared with the results obtained by PLS-DA (using the entire NIR spectrum) to discriminate apples of different species.The obtained results have shown that the iPLS-DA model outperforms the PLS-DA application in the entire spectral range when it comes to apple cultivar identification.The best model achieved an impressive 97.77% accuracy in the calibration set and 100% accuracy in the prediction set.These results show that the use of NIR spectroscopy is a capable method for identifying the apple variety and even the growing region. Chemometrics ; Diffuse reflectance infrared fourier transform ; Reflectivity ; Near infrared reflectance spectroscopy ; Analytical Chemistry (journal) ; Diffuse reflection Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Water Quality Monitoring and Analysis
Authors: Tomoya Maruyama | KyoungOk Kim | Masayuki Takatera
Source: Autex Research Journal (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Price estimation and visual evaluation of actual white fabrics used for dress shirts and their photographic images Abstract Consumers recognize the appearance and texture of fabric through viewing photographic images on E-commerce. However, the relationship between evaluations of the actual fabric and its image remains unclear. To understand the evaluation difference between actual fabric and its image, we investigated the relationship of visual evaluations including the price evaluation between actual white fabrics used for dress shirts and their photographic images concerning the online purchase of items presented by their photos. Participants evaluated the impressions of 24 white fabrics (actual fabrics and their images), comparing them with a standard white fabric. Participants also estimated the prices of shirts hypothetically made from different fabrics. We compared the difference between the results for actual fabrics and images. We also carried out a principal component analysis of those impressions and examined the relationship among principal component analysis results, weave structure, and fabric materials and price estimation. In a comparison of actual fabric and image evaluations, the impression of glossiness and brightness differed, with the actual fabrics being rated significantly higher in terms of glossiness and brightness. These differences are due to the difference in media (i.e., direct viewing versus screen display), although the visual environment of the lighting and displays may have had an effect. In principal component analysis, the first principal components were Delicateness and Glossiness for both actual fabrics and their images. The second principal components were Lightness and Coolness for the images of fabrics and Lightness, Coolness, and Softness for the actual fabrics. Fabrics evaluated highly in the first principal component had high price estimations. Thus, it is clear that Delicateness and Glossiness affected the price evaluation for both actual white fabrics and their images. Fabrics with a high value of Delicateness and Glossiness were a poplin made of at least 95% cotton. In contrast, fabrics containing linen and having a small repeating dobby pattern with roughness were evaluated as having low Delicateness and Glossiness and were assessed at a lower price. Additionally, even in the case of blended fabrics such as a cotton–polyester fabric, the expected price was high for diagonal patterns such as stripes and checks. These results will be helpful in the procurement of fabrics with which to make clothing and in the marketing of clothing for E-commerce. White (mutation) ; Art ; Visual arts ; Artificial intelligence ; Computer vision ; Computer science ; Computer graphics (images) Textile materials and evaluations ; Color Science and Applications ; Industrial Vision Systems and Defect Detection
Authors: José E. Chacón | Carlos Tenreiro
Source: Statistica Neerlandica (article, 2024-07-31)
Field: Chemistry — Spectroscopy

Estimation of density functionals via cross‐validation Abstract In density estimation, the mean integrated squared error (MISE) is commonly used as a measure of performance. In that setting, the cross‐validation criterion provides an unbiased estimator of the MISE minus the integral of the squared density. Since the minimum MISE is known to converge to zero, this suggests that the minimum value of the cross‐validation criterion could be regarded as an estimator of minus the integrated squared density. This novel proposal presents the outstanding feature that, unlike all other existing estimators, it does not need the choice of any tuning parameter. Indeed, it is proved here that this approach results in a consistent and efficient estimator, with remarkable performance in practice. Moreover, apart from this base case, it is shown how several other problems on density functional estimation can be similarly handled using this new principle, thus demonstrating full potential for further applications. Cross-validation ; Mathematics ; Density estimation ; Estimation ; Statistics ; Applied mathematics ; Computer science ; Estimator Analytical Chemistry and Chromatography ; Chemical Thermodynamics and Molecular Structure ; Computational Drug Discovery Methods
Authors: Muhittin Mungan | Dheeraj Kumar | Sylvain Patinet | Damien Vandembroucq
Source: arXiv (Cornell University) (preprint, 2024-09-25)
Field: Materials Science — Materials Chemistry

Self-organization and memory in an disordered solid subject to random loading We consider self-organization and memory formation in a mesoscopic model of an amorphous solid subject to a random shear strain protocol confined to a strain range $\pm \varepsilon_{\rm max}$. We develop proper read-out protocols to show that the response of the driven system retains a memory of the strain range, which can be subsequently retrieved. Our findings generalize previous results obtained upon oscillatory driving and suggest that self-organization and memory formation of disordered materials can emerge under more general conditions, such as a disordered system interacting with its fluctuating environment. The self-organization results in a correlation between the dynamics of the system and its environment. We conclude by discussing our results within the context of environmental sensing, highlighting their generalizability to adaptation strategies of simple organisms under changing conditions. Subject (documents) ; Amorphous solid ; Materials science ; Computer science ; Crystallography ; Chemistry ; World Wide Web Material Dynamics and Properties ; 3D Shape Modeling and Analysis ; Textile materials and evaluations
Authors: Anda Skeja | Sofia C. Olhede
Source: arXiv (Cornell University) (preprint, 2024-05-23)
Field: Chemistry — Physical and Theoretical Chemistry

Quantifying Multivariate Graph Dependencies: Theory and Estimation for Multiplex Graphs Multiplex graphs, characterised by their layered structure, exhibit informative interdependencies within layers that are crucial for understanding complex network dynamics. Quantifying the interaction and shared information among these layers is challenging due to the non-Euclidean structure of graphs. Our paper introduces a comprehensive theory of multivariate information measures for multiplex graphs. We introduce graphon mutual information for pairs of graphs and expand this to graphon interaction information for three or more graphs, including their conditional variants. We then define graphon total correlation and graphon dual total correlation, along with their conditional forms, and introduce graphon $O-$information. We discuss and quantify the concepts of synergy and redundancy in graphs for the first time, introduce consistent nonparametric estimators for these multivariate graphon information--theoretic measures, and provide their convergence rates. We also conduct a simulation study to illustrate our theoretical findings and demonstrate the relationship between the introduced measures, multiplex graph structure, and higher--order interdependecies. Real-world applications further show the utility of our estimators in revealing shared information and dependence structures in real-world multiplex graphs. This work not only answers fundamental questions about information sharing across multiple graphs but also sets the stage for advanced pattern analysis in complex networks. Multivariate statistics ; Multiplex ; Computer science ; Graph ; Mathematics ; Theoretical computer science ; Statistics ; Bioinformatics ; Biology History and advancements in chemistry ; Bayesian Modeling and Causal Inference
Authors: Ирина Геннадиевна Булан
Source: THE TIDINGS of the Baltic State Fishing Fleet Academy Psychological and pedagogical sciences (Theory and methods of professional education) (article, 2024-04-03)
Field: Chemistry — Organic Chemistry

Цифровые возможности повышения эффективности обучения математикеЦифровые возможности повышения эффективности обучения математике Освящается проблема применения в процессе обучения математике цифровых технологий. С одной стороны, включение таких технологий направлено на оптимизацию учебной деятельно-сти, способствующей оперативному достижению результатов. С другой стороны, технические возможности технологий, обеспечивающие быстроту выполнения математических операций и конечный результат, остаются скрытыми для студентов, не дают представления о способах ре-шения. Рассматривается понятие «цифровые возможности»; проводится анализ. Business Synthesis and Properties of Aromatic Compounds ; Geometric and Algebraic Topology ; Coordination Chemistry and Organometallics
Authors: Márton Rátkai | Richárd Kicsiny | Łászló A. Székely
Source: Journal of Central European Green Innovation (article, 2024-11-28)
Field: Materials Science — Materials Chemistry

Megújuló energiával történő melegítés matematikai modellezése szoláris főzőedényben A kutatás tárgya, a szoláris főzőedény, egy új találmány, amely a Szellemi Tulajdon Nemzeti Hivatalában, 2021-ben kapott használatiminta-oltalmat, 5489-es lajstromszám alatt. Az edény ételek, italok (vagy egyéb folyadékok) melegítésére vagy főzésére használható. Felépítését tekintve, egy cső a csőben hőcserélőhöz hasonlóan, rendelkezik egy külső köpennyel és egy belső főzőtérrel. A főzőedény fizikálisan már legyártásra került, a rajta végzett vizsgálatok folyamatosan zajlanak. A jelen munka a berendezés matematikai úton történő vizsgálatát tűzi ki célul matematikai modellek és számítógépes szimulációk segítségével. Célunk a szoláris főzőedény modellezése, amely lehetővé teszi a főzőedény hőmérsékletének előrejelzését. Bemutatásra kerül a főzőedény matematikai modellezése, valamint a modellezéshez kapcsolódó első szimulációs eredmények, amelyek alapján következtetések vonhatók le a főzőedény működésének hatékonyságára és gyakorlati alkalmazhatóságára vonatkozóan. A környezetbarát főzőedény az eredmények alapján képes főzési feladatok ellátására. Használata egy főzés alkalmával 247 grammal csökkenti a széndioxid-kibocsátást. A jövőbeni kutatási tervek között szerepel a főzőedényből és a napkollektorból álló kísérleti rendszer megépítése, a rendszer és a rendszerelemek további modellezése és a rendszeren mérések elvégzése különböző időjárási körülmények között. A tervezett kísérleti vizsgálatok majd lehetővé teszik a matematikai modellek validálását és a főzőedény működőképességének felmérését. Humanities ; Physics ; Philosophy Graphite, nuclear technology, radiation studies
Authors: Nur Mohammad | Mohammad Amirul Islam | Mohammad Mukhlesur Rahman | Istiak Ahmed | Golam Mahboob
Source: Qeios (preprint, 2024-02-11)
Field: Chemistry — Analytical Chemistry

Yield Forecasting Model for Maize Using Satellite Multispectral Imagery Driven Vegetation Indices In recent decades, the cultivation of maize (_Zea mays_ L.) has witnessed remarkable growth in Bangladesh, particularly in the northern regions. Maize, as a high-yielding grain crop with diverse applications, plays a pivotal role in the country's agricultural landscape. Traditional methods of yield prediction involve time-consuming and subjective on-site field visits, resulting in significant errors and delayed information dissemination to government authorities and decision-makers. This study explores the potential of remote sensing technology to predict maize yields before harvest, thereby enhancing agricultural decision-making processes. The research utilizes 16-day (~30 m) Landsat 8 and 10-day (~10 m) Sentinel 2A imagery from two years, November 2018 to February 2019 and November 2019 to February 2020, to forecast maize yields in the Kaharole upazila of the Dinajpur district, Bangladesh. Four cloud-free images, representing the maximum normalized difference vegetation index (NDVI) for each maize growing season, are selected from the Landsat 8 and Sentinel 2A data. Regression models are established to relate NDVI values to the maize yields across 20 individual farmers' fields. The results reveal that the prediction models based on mean NDVI values for the combined growing seasons outperform those based on single growing seasons, and the finer spatial resolution of Sentinel 2A contributes to its superior performance in comparison to Landsat 8, offering valuable insights for improved agricultural management and food security. Multispectral image ; Vegetation Index ; Satellite imagery ; Yield (engineering) ; Vegetation (pathology) ; Satellite ; Remote sensing ; Satellite image ; Environmental science ; Normalized Difference Vegetation Index ; Leaf area index ; Geography ; Agronomy ; Engineering ; Materials science Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Remote Sensing and Land Use
Authors: Gastón A. Rodríguez-Granillo | Bibiana Rubilar | Lucía Fontana | Nahir Luna | Sara Garrón Arias | Pedro Lylyk | Rosana Poggio
Source:  (article, 2024-02-01)
Field: Materials Science — Materials Chemistry

Myocardial Tissue Characterization Using Electron Density Imaging: Relationship with Sex and Cardiovascular Risk Factors Characterization (materials science) ; Internal medicine ; Cardiology ; Medicine ; Materials science ; Nanotechnology Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Cardiac Imaging and Diagnostics
Authors: Kathryn A. McGurk | Lara Curran | Arunashis Sau | Fu Siong Ng | Brian Halliday | James S. Ware | Declan P. O’Regan
Source: medRxiv (preprint, 2024-10-19)
Field: Chemistry — Spectroscopy

Circulating cardiovascular proteomic associations with genetics and disease Abstract Background The analysis of the circulating proteome can identify translational modifiers and biomarkers of disease expressivity and severity at a given time point. Here we explore the relationships between protein measures implicated in cardiovascular disease and whether they mediate causal relationships between cardiovascular risk factors and disease development. Methods To understand the relationships between circulating biomarkers and genetic variants, medications, anthropometric traits, lifestyle factors, imaging-derived measures, and diagnoses of cardiovascular disease, we analysed measures of nine plasma proteins with a priori roles in genetic and structural cardiovascular disease or treatment pathways (ACE2, ACTA2, ACTN4, BAG3, BNP, CDKN1A, NOTCH1, NT-proBNP, and TNNI3) from the Pharma Proteomics Project of the UK Biobank cohort (over 45,000 participants sampled at recruitment). Results We identified significant variability in circulating proteins with age, sex, ancestry, alcohol intake, smoking, and medication intake. Phenome-wide association studies highlighted the range of cardiovascular clinical features with relationships to protein levels. Genome-wide genetic association studies identified variants near GCKR , APOE , and SERPINA1 , that modified multiple circulating protein levels (BAG3, CDKN1A, and/or NOTCH1). NT-proBNP and BNP levels associated with variants in BAG3 . ACE2 levels were increased with a diagnosis of hypertension or diabetes and were influenced by variants in genes associated with diabetes ( HNF1A, HNF4A ). Two-sample Mendelian randomisation identified ACE2 as protective for systolic blood pressure and Type-2 diabetes. Conclusions From a panel of circulating proteins, the results from this observational study provide evidence that ACE2 is causally associated with hypertension and diabetes. This suggests that ACE2 stimulation may provide additional protection from these cardiovascular diseases. This study provides an improved understanding of the circulating pathways depicting cardiovascular disease dynamics. Graphical abstract Disease ; Genetics ; Biology ; Computational biology ; Medicine ; Evolutionary biology ; Internal medicine Advanced Proteomics Techniques and Applications
Authors: Д. В. Куркин | N. V. Atapina | S.I. Diachkov | A.S. Rzayeva | A.A. Fetisova
Source:  (article, 2024-12-19)
Field: Chemistry — Spectroscopy

THE PERSPECTIVES OF FURTHER MODIFICATIONS OF ACETYLSALICYLIC ACID MOLECULE The collection includes scientific articles of participants of the International University Science Forum, the purpose of which is to present significant results of scientific research in the field of humanities, natural and technical sciences; the formation of a modern level of scientific knowledge, experience in transformation of theoretical science into the sphere of practical application of innovations; generalization of research and practical experience.The forum is a tool for establishing sustainable ties, as well as the exchange of experience between teachers and researchers of universities and research organizations.Le recueil comprend des articles scientifiques des participants du Forum Scientifique International des Universits, dont l'objectif est la prsentation des rsultats significatifs de la recherche dans le domaine des sciences humaines, de la nature et de l'ingnieur; la formation du niveau contemporain des connaissances scientifiques, de l'exprience de la transformation de la science thorique au champ de l'application pratique des innovations; la synthse de l'exprience des recherches scientifiques et pratiques.Le forum est un instrument permettant d'tablir des liens durables et d'changer des donnes d'exprience entre les enseignants et les chercheurs des universits et les organisations scientifiques. Molecule ; Chemistry ; Computer science ; Organic chemistry Analytical Chemistry and Chromatography ; Chemical Thermodynamics and Molecular Structure
Authors: John D Stempien
Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (article, 2024-12-02)
Field: Materials Science — Materials Chemistry

Post-irradiation Heating Tests of As-Irradiated AGR-3/4 TRISO Fuel Compacts Four post-irradiation heating tests of fuel compacts from the U.S. Advanced Gas Reactor (AGR)-3/4 irradiation experiment were completed. In addition to tristructural isotropic (TRISO)-coated driver fuel, each compact contained designed-to-fail (DTF) particles with fuel kernels coated only in pyrocarbon so as to simulate exposed kernels. Tests at 1600/1700°C, 1400°C, and 1200°C were performed to measure fission product release as a function of time and temperature. Silver release was highest in the 1200°C test, supporting the observation that silver release rates are highest in the 1100–1300°C range. Compared to tests of AGR-1 compacts with no exposed kernels, the Cs-134 and Kr-85 releases were noticeably higher in AGR-3/4. The exposed kernels’ contributions to Eu and Sr release are inconclusive, due to the difficulty in distinguishing among the combined effects of higher irradiation temperatures in these particular AGR-3/4 compacts, the presence of the DTF particles, and the Fuel Accident Condition Simulator (FACS) test temperatures. These data can be used to make inferences about fission product retention in exposed kernels as a function of time and temperature. Irradiation ; Materials science ; Radiochemistry ; Nuclear engineering ; Gamma irradiation ; Environmental science ; Chemistry ; Engineering ; Nuclear physics ; Physics Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Nuclear and radioactivity studies