jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Selene Lomoio | Giuseppina Tesco
Source: Methods in molecular biology (article, 2023-01-01)
Field: Materials Science — Biomaterials

A 3D Bioengineered Neural Tissue Model Generated from Human iPSC-Derived Neural Precursor Cells Neural cell ; Neural stem cell ; Neuroscience ; Scaffold ; Tissue engineering ; Neural tissue engineering ; Fibroin ; Cell biology ; Biology ; Cell ; Chemistry ; Materials science ; Biomedical engineering ; SILK ; Regeneration (biology) ; Stem cell ; Medicine ; Biochemistry Silk-based biomaterials and applications ; Nerve injury and regeneration ; Tissue Engineering and Regenerative Medicine
Authors: Mong Hien Thi Nguyen
Source: BOHR International Journal of Smart Computing and Information Technology (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

The simulation modeling to choose styles of torso dresses byfuzzy logic This study presents the use of the fuzzy logic technique in choosing Torso dresses for online shopping. Dressstyles are established based on analyzing three factors that prioritize clothing selection using the Pareto chart.These factors include the dress’s form, thickness, and color fabric of the dress. These are the three inputvariables of this model, and each of them has different membership functions. The first input variable is theform of the modeling, and has two membership functions. The second is the fabric type that can be used fordresses, and has five membership functions. The third input variable is the color of the fabric, and has threemembership functions. The output is a type of outfit looked for so the actual survey method is conducted inthe customers-interest-scale of clothing. The fuzzy If-Then rule and Sugeno controller are used in this modeling.There are 30 Torso dress styles coded for application to fuzzy logic modeling. Besides, the theoretical methodis applied in a 2D flat pattern designing a basic Torso pattern and a fuzzy logic model. Additionally, albumsof dress styles are created by the 3D simulation method as well as the model’s feasibility is evaluated by theexpert method. Torso ; Fuzzy logic ; Clothing ; Computer science ; Variable (mathematics) ; Artificial intelligence ; Engineering drawing ; Simulation ; Industrial engineering ; Engineering ; Mathematics ; Geography Textile materials and evaluations ; Color perception and design ; Consumer Retail Behavior Studies
Authors: Nina Demeulemeester | Marie Gébelin | Lucas Caldi Gomes | Paul Lingor | Christine Carapito | Lennart Martens | Lieven Clement
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-07-05)
Field: Chemistry — Spectroscopy

msqrob2PTM: differential abundance and differential usage analysis of MS-based proteomics data at the post-translational modification and peptidoform level Abstract In the era of open-modification search engines, more post-translational modifications than ever can be detected by LC-MS/MS-based proteomics. This development can switch proteomics research into a higher gear, as PTMs are key in many cellular pathways important in cell proliferation, migration, metastasis and ageing. However, despite these advances in modification identification, statistical methods for PTM-level quantification and differential analysis have yet to catch up. This absence can partly be explained by the inherently low abundance of many PTMs and the confounding of PTM intensities with its parent protein abundance. Therefore, we have developed msqrob2PTM, a new workflow in the msqrob2 universe capable of differential abundance analysis at the PTM, and at the peptidoform level. The latter is important for validating PTMs found as significantly differential. Indeed, as our method can deal with multiple PTMs per peptidoform, there is a possibility that significant PTMs stem from one significant peptidoform carrying another PTM, hinting that it might be the other PTM driving the perceived differential abundance. Our workflows can flag both Differential Peptidoform (PTM) Abundance (DPA) and Differential Peptidoform (PTM) Usage (DPU). This enables a distinction between direct assessment of differential abundance of peptidoforms (DPA) and differences in the relative usage of peptidoforms corrected for corresponding protein abundances (DPU). For DPA, we directly model the log2-transformed peptidoform (PTM) intensities, while for DPU, we correct for parent protein abundance by an intermediate normalisation step which calculates the log2-ratio of the peptidoform (PTM) intensities to their summarized parent protein intensities. We demonstrated the utility and performance of msqrob2PTM by applying it to datasets with known ground truth, as well as to biological PTM-rich datasets. Our results show that msqrob2PTM is on par with, or surpassing the performance of, the current state-of-the-art methods. Moreover, msqrob2PTM is currently unique in providing output at the peptidoform level. Abundance (ecology) ; Posttranslational modification ; Proteomics ; Differential (mechanical device) ; Computer science ; Confounding ; Computational biology ; Biology ; Chemistry ; Physics ; Mathematics ; Biochemistry ; Statistics ; Ecology ; Enzyme Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Metabolomics and Mass Spectrometry Studies
Authors: Franz Dietrich
Source: Materials research proceedings (article, 2023-04-13)
Field: Materials Science — Polymers and Plastics

Proposing a virtual simulation method to predict the shape-fidelity of 3D-knitted-textiles using knit-meshes and geometric invariants Abstract. Though the level of machine digitization in flatbed-knitting (FBK) today is high, the design and development of knittable data sets are still currently very time-consuming, digital simulations methods are calculation expensive and insufficient in terms of accuracy of fit and technical properties. Knitting process retrofitting activities are executed mostly manually by an operator on the basis of the operator´s experience. This circumstance makes it more difficult to use the diverse potential for flexibility and on-demand purposes in future-networked-production for lightweight constructions for Automotive, Aerospace and aviation or Medical-Products. New easy-to-learn, intuitive, calculation inexpensive digital augmented workflows for the planning of knitted objects with complex 3D-shapes are needed. With regard to the requirements of composite forming, the aspects of wrinkling, slip and permeability are of particular importance. However, flatbed-knitted fabrics are subject to different requirements in some cases, which implies different questions from those posed by research in the area woven textile composites. In order to address a few of the questions raised by previous research on textile composites, this paper covers some of the current research topics in the field of 3D-knitted flatbed-knitting fabrics and shows references as well as potentials to already researched problem fields of textile reinforced composites. In doing so, the author strongly refers to the topics of the summarizing publication "Advances in composite forming through 25 years of ESAFORM" by P. Boisse et al. [1]. Aerospace ; Workflow ; Textile ; Digitization ; Engineering drawing ; Computer science ; Automotive industry ; Mechanical engineering ; Polygon mesh ; Engineering ; Computer graphics (images) ; Computer vision ; Materials science ; Composite material Textile materials and evaluations ; Additive Manufacturing and 3D Printing Technologies ; Advanced Materials and Mechanics
Authors: Aswin Hendry Atmoko | Bagus Aradea | Annisa Nanda Oktavia
Source: JURNAL TRITON (article, 2023-12-22)
Field: Chemistry — Inorganic Chemistry

Analisis Keragaman Genetik Plasma Nutfah Tanaman Kayu Putih (Melaleuca cajuputi subsp. cajuputi) Berdasarkan Karakter Morfologi dan Anatomi Daun serta Oil Glands Tanaman kayu putih merupakan tanaman hutan asli Indonesia yang dimanfaatkan untuk produksi minyak atsiri. Keragaman genetik tanaman kayu putih yang tersebar di zona persebaran alami cukup beragam. Diperlukan adanya studi dan penelitian untuk mempelajari hubungan kekerabatan antar tanaman kayu putih dan keragaman genetik plasma nutfah tanaman kayu putih. Studi kekerabatan dan juga keragaman genetik plasma nutfah didasarkan pada kemiripan karakter fenetik (kuantitatif dan kualitatif) morfologi dan anatomi daun. Terdapat 36 klon unggul tanaman kayu putih yang dilakukan pengamatan morfologi dan anatomi daun untuk menentukan dendogram. Penelitian yang dilakukan merupakan penelitian deksriptif dan juga penelitian eksperimental yang disusun dalam Rancangan Acak Lengkap (RAL) non faktorial dengan faktor yaitu macam klon yang terdiri atas 36 taraf (macam klon) dan dilakukan analisis sidik ragam menggunakan ANOVA dan dilakukan uji lanjut menggunakan uji Duncan’s. Dendogram dibuat menggunakan aplikasi MVSP versi 3.22. Hasil penelitian menunjukkan bahwa keragaman genetik yang luas pada 36 klon unggul tanaman kayu putih. Pada dendogram terbentuk 4 klaster dengan 8 klon yang menunjukkan tingkat kemiripan yang tinggi berdasarkan nilai disimilaritas sebesar 0,0. klon 14 dan 36 merupakan klon dengan rerata jumlah kelenjar minyak tertinggi. Berdasarkan penelitian yang dilakukan dapat dipahami bahwa keragaman genetik pada 36 klon unggul tanaman kayu putih cukup tinggi, hal tersebut mendukung upaya pemuliaan tanaman karena database yang diperoleh memberikan informasi klon yang dapat digunakan sebagai indukan untuk meningkatkan kemampuan produksi minyak kayu putih karena memiliki potensi produksi minyak yang tinggi. Horticulture ; Mathematics ; Physics ; Biology Coconut Research and Applications ; Forest Ecology and Conservation ; Natural Products and Applications
Authors: Shuichi Kawano | Toshikazu Fukushima | Junichi Nakagawa | Mamoru Oshiki
Source: arXiv (Cornell University) (preprint, 2023-04-15)
Field: Chemistry — Analytical Chemistry

Multivariate regression modeling in integrative analysis via sparse regularization The multivariate regression model basically offers the analysis of a single dataset with multiple responses. However, such a single-dataset analysis often leads to unsatisfactory results. Integrative analysis is an effective method to pool useful information from multiple independent datasets and provides better performance than single-dataset analysis. In this study, we propose a multivariate regression modeling in integrative analysis. The integration is achieved by sparse estimation that performs variable and group selection. Based on the idea of alternating direction method of multipliers, we develop its computational algorithm that enjoys the convergence property. The performance of the proposed method is demonstrated through Monte Carlo simulation and analyzing wastewater treatment data with microbe measurements. Multivariate statistics ; Computer science ; Regularization (linguistics) ; Regression analysis ; Regression ; Multivariate analysis ; Data mining ; Property (philosophy) ; Monte Carlo method ; Feature selection ; Convergence (economics) ; Artificial intelligence ; Machine learning ; Statistics ; Mathematics Spectroscopy and Chemometric Analyses ; Statistical Methods and Inference ; Gene expression and cancer classification
Authors: Kristijan Bartol | Stefan Gumhold
Source:  (article, 2023-10-04)
Field: Materials Science — Polymers and Plastics

Protocols for High-Quality Indoor and Outdoor Scanning of Clothed People Protocols for High-Quality Indoor and Outdoor Scanning of Clothed People - 3DBODY.TECH 2023 - 14th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, 17-18 October 2023, Lugano, Switzerland - 3DBODY.TECH - The Premier Multidisciplinary International Conference and Expo on 3D/4D Human Body Scanning, Data and Processing Technologies Computer science ; Quality (philosophy) ; 3d scanning ; Computer vision ; Physics Textile materials and evaluations ; Consumer Perception and Purchasing Behavior ; Industrial Vision Systems and Defect Detection
Authors: Valerie Reinisch | Amrit Paudel | Joana T. Pinto
Source: Studies in health technology and informatics (article, 2023-05-02)
Field: Chemistry — Analytical Chemistry

Development of a Digital Interface for Personalized Dosing in Renal Impaired Patients: A Case-Study Using the ACE-Inhibitor Benazepril The use of the models via a practical user interface can help inform clinical decisions and design optimal dosing based on the individual anthropometric characteristics and stage of renal impairment. Dosing ; Medicine ; Pharmacokinetics ; Benazepril ; Population ; Physiologically based pharmacokinetic modelling ; Pharmacology ; Computer science ; Internal medicine Analytical Methods in Pharmaceuticals ; Pharmacogenetics and Drug Metabolism ; Statistical Methods in Clinical Trials
Authors: Tony Chernis | Niko Hauzenberger | Florian Huber | Gary Koop | James Mitchell
Source: SSRN Electronic Journal (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Predictive Density Combination Using a Tree-Based Synthesis Function Tree (set theory) ; Computer science ; Mathematics ; Combinatorics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Market Dynamics and Volatility
Authors: Marie Chion | Arthur Leroy
Source: arXiv (Cornell University) (preprint, 2023-07-18)
Field: Chemistry — Spectroscopy

A Bayesian Framework for Multivariate Differential Analysis Differential analysis is a routine procedure in the statistical analysis toolbox across many applied fields, including quantitative proteomics, the main illustration of the present paper. The state-of-the-art limma approach uses a hierarchical formulation with moderated-variance estimators for each analyte directly injected into the t-statistic. While standard hypothesis testing strategies are recognised for their low computational cost, allowing for quick extraction of the most differential among thousands of elements, they generally overlook key aspects such as handling missing values, inter-element correlations, and uncertainty quantification. The present paper proposes a fully Bayesian framework for differential analysis, leveraging a conjugate hierarchical formulation for both the mean and the variance. Inference is performed by computing the posterior distribution of compared experimental conditions and sampling from the distribution of differences. This approach provides well-calibrated uncertainty quantification at a similar computational cost as hypothesis testing by leveraging closed-form equations. Furthermore, a natural extension enables multivariate differential analysis that accounts for possible inter-element correlations. We also demonstrate that, in this Bayesian treatment, missing data should generally be ignored in univariate settings, and further derive a tailored approximation that handles multiple imputation for the multivariate setting. We argue that probabilistic statements in terms of effect size and associated uncertainty are better suited to practical decision-making. Therefore, we finally propose simple and intuitive inference criteria, such as the overlap coefficient, which express group similarity as a probability rather than traditional, and often misleading, p-values. Bayesian probability ; Estimator ; Prior probability ; Bayesian hierarchical modeling ; Computer science ; Posterior probability ; Hierarchical database model ; Missing data ; Statistical inference ; Bayesian average ; Inference ; Posterior predictive distribution ; Bayesian inference ; Statistics ; Mathematics ; Bayesian linear regression ; Data mining ; Artificial intelligence Advanced Proteomics Techniques and Applications ; Gene Regulatory Network Analysis ; Mass Spectrometry Techniques and Applications
Authors: Anurag Raj | Suruchi Aggarwal | Amit Kumar Yadav | Debasis Dash
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-06-03)
Field: Chemistry — Spectroscopy

Quality control of variant peptides identified through proteogenomics- catching the (un)usual suspects Abstract Variant peptides resulting from translation of single nucleotide polymorphisms (SNPs) can lead to aberrant or altered protein functions and thus hold translational potential for disease diagnosis, therapeutics and personalized medicine. Variant peptides detected by proteogenomics are fraught with high number of false positives. Class-specific FDR along with ad-hoc post-search filters have been employed to tackle this issue, but there is no uniform and comprehensive approach to assess variant quality. These protocols are mostly manual or tedious, and not accessible across labs. We present a software tool, PgxSAVy, for the quality control of variant peptides. PgxSAVy provides a rigorous framework for quality control and annotations of variant peptides on the basis of (i) variant quality, (ii) isobaric masses, and (iii) disease annotation. PgxSAVy was able to segregate true and false variants with 98.43% accuracy on simulated data. We then used ∼2.8 million spectra (PXD004010 and PXD001468) and identified 12,705 variant PSMs, of which PgxSAVy evaluated 3028 (23.8%), 1409 (11.1%) and 8268 (65.1%) as confident, semi-confident and doubtful respectively. PgxSAVy also annotates the variants based on their pathogenicity and provides support for assisted manual validation. In these datasets, it identified previously found variants as well some novel variants not seen in original studies. The confident variants identified the importance of mutations in glycolysis and gluconeogenesis pathways in Alzheimer’s disease. The analysis of proteins carrying variants can provide fine granularity in discovering important pathways. PgxSAVy will advance personalized medicine by providing a comprehensive framework for quality control and prioritization of proteogenomics variants. Availability PgxSAVy is freely available at https://github.com/anuragraj/PgxSAVy Key Points Variant peptide in proteogenomics have high rates of false positives class-specific FDR is not sufficiently effective, and tedious manual filtering is not scalable We developed PgxSAVy for automated quality control and disease annotation of variant peptides from proteogenomics search results PgxSAVy was validated using simulation data and manually annotated variant PSMs Independent application on large datasets on Alzheimer’s and HEK cell lines demonstrated that PgxSAVy discovered known and novel mutations with important biological roles. Graphical Abstract UniProt ; Proteogenomics ; Computational biology ; Computer science ; False positive paradox ; Quality (philosophy) ; Annotation ; Biology ; Genetics ; Artificial intelligence ; Genome ; Gene ; Genomics Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Genomics and Phylogenetic Studies
Authors: PAULO FILIPE T. LOPES | José Aurélio Medeiros da Luz | Tiago Martins Pereira | LEANDRO GERALDO C. SILVEIRA
Source: Anais da Academia Brasileira de Ciências (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Statistical analysis of blast-induced vibration near an open pit mine Blast-induced vibration may be harmful to facilities in the vicinity of operating mines, mainly causing structural damage and human discomfort. This study presents an application of multivariate statistics to predict vibration levels regarding their potential to cause structural damage and human discomfort. An extensive seismic monitoring campaign was executed in a large open-pit iron ore mine, near a small village, to gather a dataset for a predictive multivariate analysis. Ten blasting events have produced a dataset of 158 valid measurements. Three classes of vibration peak velocity were adopted from legal standards, which later supported a cluster analysis. Then, it was possible to compare how much these two classification modalities respond to discriminant analysis. The next step was to carry out a principal component analysis (PCA) from the original database, and, comparatively, to plot both the scores concerning the classes derived from the vibration standard and those from the groups obtained from cluster analysis. PCA has considerably explained the data variability, while the three classes from cluster analysis resulted very similar to the corresponding ones from the vibration standards. The results have demonstrated that multivariate statistics may be applied to manage blasting-induced vibration and its deleterious effects with few adjustments and automation. Chemistry ; Sapindaceae ; Orchard ; Prunus dulcis ; Gas chromatography ; Food science ; Botany ; Horticulture ; Biology ; Chromatography ; Cultivar Spectroscopy and Chemometric Analyses ; Essential Oils and Antimicrobial Activity
Authors: Ben Jordan | Michael G. Thomason | Jason D. Readle | J. R. Cooper | Jason P. Hayward | Howard L. Hall
Source: Journal of Analytical Atomic Spectrometry (article, 2023-01-01)
Field: Chemistry — Spectroscopy

Classification of gaseous UF<sub>6</sub> assay by femtosecond LIBS in the 424.4 nm spectral region using numerical HOGSVD-DTW features This technical note presents experimental results using numerical features of fs-LIBS data to classify the assay value of a gaseous UF 6 material. Femtosecond ; Analytical Chemistry (journal) ; Materials science ; Chemistry ; Laser ; Environmental chemistry ; Optics ; Physics Mass Spectrometry Techniques and Applications ; Laser-induced spectroscopy and plasma ; Spectroscopy and Chemometric Analyses
Authors: Yosuke Mitsuhashi | Nobuyuki Yoshioka
Source: arXiv (Cornell University) (preprint, 2023-06-30)
Field: Chemistry — Organic Chemistry

Clifford Group and Unitary Designs under Symmetry We have generalized the well-known statement that the Clifford group is a unitary 3-design into symmetric cases by extending the notion of unitary design. Concretely, we have proven that a symmetric Clifford group is a symmetric unitary 3-design if and only if the symmetry constraint is described by some Pauli subgroup. We have also found a complete and unique construction method of symmetric Clifford groups with simple quantum gates for Pauli symmetries. For the overall understanding, we have also considered physically relevant U(1) and SU(2) symmetry constraints, which cannot be described by a Pauli subgroup, and have proven that the symmetric Clifford group is a symmetric unitary 1-design but not a 2-design under those symmetries. Our findings are numerically verified by computing the frame potentials, which measure the difference in randomness between the uniform ensemble on the symmetric group of interest and the symmetric unitary group. This work will open a new perspective into quantum information processing such as randomized benchmarking, and give a deep understanding to many-body systems such as monitored random circuits. Unitary group ; Unitary state ; Mathematics ; Symmetry (geometry) ; Group (periodic table) ; Symmetry group ; Homogeneous space ; Special unitary group ; Pure mathematics ; Circular ensemble ; Theoretical physics ; Algebra over a field ; Quantum mechanics ; Physics ; Unitary matrix ; Mathematical physics ; Geometry Supramolecular Chemistry and Complexes ; Chemical Synthesis and Analysis ; DNA and Nucleic Acid Chemistry