jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tilman A. Grünewald | Stefano Checchia | Hamadou Dicko | Gilles Le Moullac | Manaarii Sham Koua | Jérémie Vidal‐Dupiol | Julien Duboisset | J. Nouet | Olivier Grauby | Marco Di Michiel | Virginie Chamard
Source: Proceedings of the National Academy of Sciences (article, 2022-11-02)
Field: Materials Science — Biomaterials

Structure of an amorphous calcium carbonate phase involved in the formation of <i>Pinctada margaritifera</i> shells Some mollusc shells are formed from an amorphous calcium carbonate (ACC) compound, which further transforms into a crystalline material. The transformation mechanism is not fully understood but is however crucial to develop bioinspired synthetic biomineralization strategies or accurate marine biomineral proxies for geoscience. The difficulty arises from the simultaneous presence of crystalline and amorphous compounds in the shell, which complicates the selective experimental characterization of the amorphous fraction. Here, we use nanobeam X-ray total scattering together with an approach to separate crystalline and amorphous scattering contributions to obtain the spatially resolved atomic pair distribution function (PDF). We resolve three distinct amorphous calcium carbonate compounds, present in the shell of <i>Pinctada margaritifera</i> and attributed to: interprismatic periostracum, young mineralizing units, and mature mineralizing units. From this, we extract accurate bond parameters by reverse Monte Carlo (RMC) modeling of the PDF. This shows that the three amorphous compounds differ mostly in their Ca-O nearest-neighbor atom pair distance. Further characterization with conventional spectroscopic techniques unveils the presence of Mg in the shell and shows Mg-calcite in the final, crystallized shell. In line with recent literature, we propose that the amorphous-to-crystal transition is mediated by the presence of Mg. The transition occurs through the decomposition of the initial Mg-rich precursor into a second Mg-poor ACC compound before forming a crystal. Amorphous calcium carbonate ; Amorphous solid ; Biomineralization ; Calcite ; Materials science ; Crystal (programming language) ; Carbonate ; Calcium carbonate ; Crystallography ; Chemical engineering ; Amorphous calcium phosphate ; Crystallization ; Chemical physics ; Atom (system on chip) ; Mineralogy ; Chemistry ; Calcium ; Metallurgy ; Composite material Calcium Carbonate Crystallization and Inhibition ; Paleontology and Stratigraphy of Fossils ; Bone Tissue Engineering Materials
Authors: Parham Kabirifar | Jonas Trojer | Miha Brojan | Jaka Tušek
Source: Journal of Physics Energy (article, 2022-09-16)
Field: Materials Science — Materials Chemistry

From the elastocaloric effect towards an efficient thermodynamic cycle Abstract In recent years, elastocaloric cooling technology has been considered as one of the most promising alternatives to vapor compression technology. Given that elastocaloric technology is only in the early stages of development, a uniform method for evaluating the elastocaloric effect has not yet been established, and the thermodynamics of different elastocaloric cooling cycles have not yet been studied in detail. Therefore, the main goal of this work is to investigate these two important areas. Here, multiple thermodynamic cycles were studied, focusing on the parameters of the holding period of the cycle, which is essential for heat transfer between the elastocaloric material and the heat sink/source. The cycles were applied to commercially available superelastic thin-walled NiTi tubes under compressive loading and a thin NiTi wire under tensile loading. Isostress cycles with constant stress throughout the holding period, isostrain cycles with constant strain throughout the holding period and no-hold cycles (without a holding period) were studied across multiple stress/strain ranges. Based on the experimental results, a previously developed phenomenological model was applied to better understand and further evaluate the different cycles. The results revealed that the applied thermodynamic cycle significantly affects the thermomechanical response and thus the cooling/heating efficiency of the elastocaloric material. We show that by using isostress cycles and partial transformations, a Carnot-like thermodynamic cycle with improved heating/cooling efficiency can be generated. By applying the isostress cycles, an adiabatic temperature change of 30.2 K was measured, which is among the largest directly measured reproducible adiabatic temperature changes reported for any caloric material to date. Ultimately, this study intends to serve as a basis for establishing a uniform method for evaluating the elastocaloric effect in different materials that would allow for reliable and accurate one-to-one comparison of the reported results in the rapidly growing field of elastocalorics. Adiabatic process ; Thermodynamic cycle ; Carnot cycle ; Materials science ; Thermodynamics ; Heat sink ; Vapor-compression refrigeration ; Work (physics) ; Mechanics ; Heat exchanger ; Refrigerant Shape Memory Alloy Transformations ; Titanium Alloys Microstructure and Properties ; High Entropy Alloys Studies
Authors: Emerson de Castro Barbosa | Tânia Maria de Almeida Alves | Markus Kohlhoff | Soraya Torres Gaze Jangola | Douglas E. V. Pires | Anna Carolina Cançado Figueiredo | Érica Alessandra Rocha Alves | Carlos Eduardo Calzavara-Silva | Marcos Sobral | Erna Geessien Kroon | Luiz Henrique Rosa | Carlos Leomar Zani | Jaquelline Germano de Oliveira
Source: Virology Journal (article, 2022-02-22)
Field: Chemistry — Organic Chemistry

Searching for plant-derived antivirals against dengue virus and Zika virus Our results showed that plant extracts, especially those from the Hippeastrum genus, can be a valuable source of antiviral compounds against ZIKV and DENV-2. The majority of compounds identified have never been previously described for their activity against ZIKV and other viruses. Dengue virus ; Zika virus ; Dengue fever ; Virology ; In silico ; Fractionation ; Biology ; Virus ; Cytopathic effect ; Bioassay ; Traditional medicine ; Pharmacology ; Chemistry ; Chromatography ; Medicine ; Biochemistry Chemical synthesis and alkaloids ; Alkaloids: synthesis and pharmacology ; Phytochemistry and Bioactivity Studies
Authors: Ruben F. Kranenburg | Yannick Weesepoel | Martin Alewijn | Sharon Sap | Peter W.F. Arisz | Annette van Esch | Peter H. J. Keizers | Arian van Asten
Source: Forensic Chemistry (article, 2022-07-11)
Field: Chemistry — Analytical Chemistry

The importance of wavelength selection in on-scene identification of drugs of abuse with portable near-infrared spectroscopy Both the increasing volume and diversity of drugs-of-abuse encountered by investigation services necessitates the need for fast on-scene detectors to detect and identify a broad range of substances. Near-Infrared (NIR) spectroscopy is suitable for presumptive drugs testing by miniaturized sensors implemented in portable devices. Currently, a myriad of different portable NIR spectrometers is available that utilize different wavelength ranges. This study presents a comparison of NIR spectra of frequently occuring drugs analyzed by five different devices. A 350 – 2500 nm range laboratory grade VIS-NIR spectrometer was used to gain insight in spectral ranges diagnostic for substances relevant in forensic science. Obtained spectra were compared to the output of portable spectrometers operating in the 740 – 1070 nm, 950 – 1650 nm, 1550 – 1950 nm and 1300 – 2600 nm range. The results yielded novel insights in the usability of individual spectrometers by visual inspection of NIR spectra as well as comparative statistics with reference substances. For MDMA detection, an instrument capable of detecting a highly abundant and specific peak at 2020 nm is beneficial whereas colored samples are more difficult to detect by lower wavelength range sensors. Relatively pure, lightly colored samples may be correctly characterized by all sensors. These findings may aid NIR spectrometer selection in forensic practice as well as future studies on instrument selectivity or cross-platform calibration transfer. Spectrometer ; Drugs of abuse ; Near-infrared spectroscopy ; Calibration ; Detector ; Spectroscopy ; Drug detection ; Materials science ; Analytical Chemistry (journal) ; Computer science ; Optics ; Chemistry ; Chromatography ; Physics ; Telecommunications ; Statistics ; Medicine ; Mathematics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Huaixiang Tian | Shuang Chen | Dan Li | Xinman Lou | Chen Chen | Haiyan Yu
Source: Journal of Dairy Science (article, 2022-07-19)
Field: Chemistry — Analytical Chemistry

Simultaneous detection for adulterations of maltodextrin, sodium carbonate, and whey in raw milk using Raman spectroscopy and chemometrics To achieve rapid on-site identification of raw milk adulteration and simultaneously quantify the levels of various adulterants, we combined Raman spectroscopy with chemometrics to detect 3 of the most common adulterants. Raw milk was artificially adulterated with maltodextrin (0.5-15.0%; wt/wt), sodium carbonate (10-100 mg/kg), or whey (1.0-20.0%; wt/wt). Partial least square discriminant analysis (PLS-DA) classification and a partial least square (PLS) regression model were established using Raman spectra of 144 samples, among which 108 samples were used for training and 36 were used for validation. A model with excellent performance was obtained by spectral preprocessing with first derivative, and variable selection optimization with variable importance in the projection. The classification accuracy of the PLS-DA model was 95.83% for maltodextrin, 100% for sodium carbonate, 95.84% for whey, and 92.25% for pure raw milk. The PLS model had a detection limit of 1.46% for maltodextrin, 4.38 mg/kg for sodium carbonate, and 2.64% for whey. These results suggested that Raman spectroscopy combined with PLS-DA and PLS model can rapidly and efficiently detect adulterants of maltodextrin, sodium carbonate, and whey in raw milk. Maltodextrin ; Chemometrics ; Sodium carbonate ; Chemistry ; Partial least squares regression ; Chromatography ; Raman spectroscopy ; Food science ; Sodium ; Mathematics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Identification and Quantification in Food
Authors: Mathias Walzer | David García‐Seisdedos | Ananth Prakash | Paul Brack | Peter Crowther | R. L. Graham | Nancy George | Suhaib Mohammed | Pablo Moreno | Irene Papatheodorou | Simon J. Hubbard | Juan Antonio Vizcaíno
Source: Scientific Data (article, 2022-06-14)
Field: Chemistry — Spectroscopy

Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas The number of mass spectrometry (MS)-based proteomics datasets in the public domain keeps increasing, particularly those generated by Data Independent Acquisition (DIA) approaches such as SWATH-MS. Unlike Data Dependent Acquisition datasets, the re-use of DIA datasets has been rather limited to date, despite its high potential, due to the technical challenges involved. We introduce a (re-)analysis pipeline for public SWATH-MS datasets which includes a combination of metadata annotation protocols, automated workflows for MS data analysis, statistical analysis, and the integration of the results into the Expression Atlas resource. Automation is orchestrated with Nextflow, using containerised open analysis software tools, rendering the pipeline readily available and reproducible. To demonstrate its utility, we reanalysed 10 public DIA datasets from the PRIDE database, comprising 1,278 SWATH-MS runs. The robustness of the analysis was evaluated, and the results compared to those obtained in the original publications. The final expression values were integrated into Expression Atlas, making SWATH-MS experiments more widely available and combining them with expression data originating from other proteomics and transcriptomics datasets. Computer science ; Metadata ; Workflow ; Pipeline (software) ; Annotation ; Human Protein Atlas ; Database ; Data mining ; Rendering (computer graphics) ; Information retrieval ; Data science ; Protein expression ; World Wide Web ; Artificial intelligence ; Biology Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Wan Si | Jie Xiong | Yuping Huang | Xuesong Jiang | Dong Hu
Source: Foods (review, 2022-04-20)
Field: Chemistry — Analytical Chemistry

Quality Assessment of Fruits and Vegetables Based on Spatially Resolved Spectroscopy: A Review Damage occurs easily and is difficult to find inside fruits and vegetables during transportation or storage, which not only brings losses to fruit and vegetable distributors, but also reduces the satisfaction of consumers. Spatially resolved spectroscopy (SRS) is able to detect the quality attributes of fruits and vegetables at different depths, which is of great significance to the quality classification and defect detection of horticultural products. This paper is aimed at reviewing the applications of spatially resolved spectroscopy for measuring the quality attributes of fruits and vegetables in detail. The principle of light transfer in biological tissues, diffusion approximation theory and methodologies are introduced, and different configuration designs for spatially resolved spectroscopy are compared and analyzed. Besides, spatially resolved spectroscopy applications based on two aspects for assessing the quality of fruits and vegetables are summarized. Finally, the problems encountered in previous studies are discussed, and future development trends are presented. It can be concluded that spatially resolved spectroscopy demonstrates great application potential in the field of fruit and vegetable quality attribute evaluation. However, due to the limitation of equipment configurations and data processing speed, the application of spatially resolved spectroscopy in real-time online detection is still a challenge. Spectroscopy ; Quality (philosophy) ; Environmental science ; Agricultural engineering ; Field (mathematics) ; Computer science ; Biochemical engineering ; Biological system ; Mathematics ; Engineering ; Biology ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Sai Xu | Jinchang Ren | Huazhong Lu | Xu Wang | Xiuxiu Sun | Xin Liang
Source: Postharvest Biology and Technology (article, 2022-07-14)
Field: Chemistry — Analytical Chemistry

Nondestructive detection and grading of flesh translucency in pineapples with visible and near-infrared spectroscopy Near-infrared spectroscopy ; Partial least squares regression ; Pattern recognition (psychology) ; Mathematics ; Principal component analysis ; Artificial intelligence ; Computer science ; Optics ; Statistics ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Smart Agriculture and AI
Authors: Ghulam Mustafa | Hengbiao Zheng | İmran Khan | Long Tian | Haiyan Jia | Guoqiang Li | Tao Cheng | Yongchao Tian | Weixing Cao | Yan Zhu | Xia Yao
Source: Remote Sensing (article, 2022-06-10)
Field: Chemistry — Analytical Chemistry

Hyperspectral Reflectance Proxies to Diagnose In-Field Fusarium Head Blight in Wheat with Machine Learning Hyperspectral reflectance (HR) technology as proxy approach to diagnose fusarium head blight (FHB) in wheat crop could be a real-time and non-invasive approach for its in-field management to reduce grain damage. In-field canopy’s non-imaging HR (400–2400 nm using ground-based spectrometer system), photosynthesis rate (Pn) and disease severity (DS) data were simultaneously acquired from artificially inoculated wheat plots over a period of two years (2020 and 2021) in the field. Subsequently, continuous wavelet transform (CWT) was employed to select the consistent spectral bands (CSBs) and to develop the canopy-based difference indices with criterion of variable importance score using random forest—recursive feature elimination. Thereby, different machine learning algorithms were employed for FHB classification and multivariate estimation, and linear regression models to evaluate the newly developed indices against conventional vegetation indices. The results showed that inoculation reduced the Pn rate of spikes, elevated reflectance in visible and short-wave infrared regions and decreased in near infrared region at different days after inoculation (DAI). CWT analysis selected five CSBs (401, 460, 570, 786 and 840 nm) employing datasets from 2020 and 2021. These spectral bands were employed to develop wheat fusarium canopy indices (WFCI1 and WFCI2). Considering the average classification accuracy (ACA) in both years of experiments, WFCI1 manifested a maximum ACA of 75% at 5 DAI with DS of 9.73% which raised to 100% at 10 DAI with a DS of 18%. ACA mentions the averaged results of all machine learning classifiers (MLC). While in the perspective of MLC, random forest (RF) outperformed the rest of the MLC, individually, it revealed 100% classification accuracy through WFCI1 at DS 10.78% on the eight DAI. The univariate estimation of disease based on WFCI1 and WFCI2 with independent data produced R2 and root mean square error (RMSE) values of 0.80 and 14.7, and 0.81 and13.50, respectively. However, Knn regression analysis with both canopy indices (WFCI1 and WFCI2) manifested the maximum accuracy for disease estimation with RMSE of 11.61 and R2 = 0.83. Conclusively, the newly proposed HR indices show great potential as proxy approach for detecting FHB at early stage and understanding the physical state of crops in field conditions for the better management and control of plant diseases. Hyperspectral imaging ; Fusarium ; Canopy ; Normalized Difference Vegetation Index ; Environmental science ; Remote sensing ; Multispectral image ; Artificial intelligence ; Mathematics ; Computer science ; Agronomy ; Horticulture ; Geology ; Biology ; Botany ; Leaf area index Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Leaf Properties and Growth Measurement
Authors: Lalit Mohan Kandpal | Muhammad Abdul Munnaf | Cristina Cruz | Abdul Mounem Mouazen
Source: Sensors (article, 2022-05-01)
Field: Chemistry — Analytical Chemistry

Spectra Fusion of Mid-Infrared (MIR) and X-ray Fluorescence (XRF) Spectroscopy for Estimation of Selected Soil Fertility Attributes Previous works indicate that data fusion, compared to single data modelling can improve the assessment of soil attributes using spectroscopy. In this work, two different kinds of proximal soil sensing techniques i.e., mid-infrared (MIR) and X-ray fluorescence (XRF) spectroscopy were evaluated, for assessment of seven fertility attributes. These soil attributes include pH, organic carbon (OC), phosphorous (P), potassium (K), magnesium (Mg), calcium (Ca) and moisture contents (MC). Three kinds of spectra fusion (SF) (spectra concatenation) approaches of MIR and XRF spectra were compared, namely, spectra fusion-Partial least square (SF-PLS), spectra fusion-Sequential Orthogonalized Partial least square (SF-SOPLS) and spectra fusion-Variable Importance Projection-Sequential Orthogonalized Partial least square (SF-VIP-SOPLS). Furthermore, the performance of SF models was compared with the developed single sensor model (based on individual spectra of MIR and XRF). Compared with the results obtained from single sensor model, SF models showed improvement in the prediction performance for all studied attributes, except for OC, Mg, and K prediction. More specifically, the highest improvement was observed with SF-SOPLS model for pH [<i>R</i><sup>2</sup><i>p</i> = 0.90, root mean square error prediction (RMSEP) = 0.15, residual prediction deviation (RPD) = 3.30, and ratio of performance inter-quantile (RPIQ) = 3.59], successively followed by P (<i>R</i><sup>2</sup><i>p</i> = 0.91, RMSEP = 4.45 mg/100 g, RPD = 3.53, and RPIQ = 4.90), Ca (<i>R</i><sup>2</sup><i>p</i> = 0.92, RMSEP = 177.11 mg/100 g, RPD = 3.66, and RPIQ = 3.22) and MC (<i>R</i><sup>2</sup><i>p</i> = 0.80, RMSEP = 1.91%, RPD = 2.31, RPIQ = 2.62). Overall the study concluded that SF approach with SOPLS attained better performance over the traditional model developed with the single sensor spectra, hence, SF is recommended as the best SF method for improving the prediction accuracy of studied soil attributes. Moreover, the multi-sensor spectra fusion approach is not limited for only MIR and XRF data but in general can be extended for complementary information fusion in order to improve the model performance in precision agriculture (PA) applications. Partial least squares regression ; Analytical Chemistry (journal) ; Spectroscopy ; Chemistry ; Fusion ; Mean squared error ; Coefficient of determination ; Spectral line ; Mathematics ; Statistics ; Environmental chemistry ; Physics Spectroscopy and Chemometric Analyses ; Soil Geostatistics and Mapping ; Smart Agriculture and AI
Authors: Andy Lin | Temana Short | William Stafford Noble | Uri Keich
Source: Journal of Proteome Research (article, 2022-09-27)
Field: Chemistry — Spectroscopy

Improving Peptide-Level Mass Spectrometry Analysis via Double Competition The analysis of shotgun proteomics data often involves generating lists of inferred peptide-spectrum matches (PSMs) and/or of peptides. The canonical approach for generating these discovery lists is by controlling the false discovery rate (FDR), most commonly through target-decoy competition (TDC). At the PSM level, TDC is implemented by competing each spectrum's best-scoring target (real) peptide match with its best match against a decoy database. This PSM-level procedure can be adapted to the peptide level by selecting the top-scoring PSM per peptide prior to FDR estimation. Here, we first highlight and empirically augment a little known previous work by He et al., which showed that TDC-based PSM-level FDR estimates can be liberally biased. We thus propose that researchers instead focus on peptide-level analysis. We then investigate three ways to carry out peptide-level TDC and show that the most common method ("PSM-only") offers the lowest statistical power in practice. An alternative approach that carries out a double competition, first at the PSM and then at the peptide level ("PSM-and-peptide"), is the most powerful method, yielding an average increase of 17% more discovered peptides at 1% FDR threshold relative to the PSM-only method. Peptide ; Decoy ; False discovery rate ; Shotgun proteomics ; Computer science ; Mascot ; Data mining ; Proteomics ; Chemistry ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications