jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hui Yan | Marina De Géa Neves | Barry M. Wise | Ingrid A. Moraes | Douglas Fernandes Barbin | Heinz W. Siesler
Source: Molecules (article, 2023-12-01)
Field: Chemistry — Analytical Chemistry

The Application of Handheld Near-Infrared Spectroscopy and Raman Spectroscopic Imaging for the Identification and Quality Control of Food Products The following investigations describe the potential of handheld NIR spectroscopy and Raman imaging measurements for the identification and authentication of food products. On the one hand, during the last decade, handheld NIR spectroscopy has made the greatest progress among vibrational spectroscopic methods in terms of miniaturization and price/performance ratio, and on the other hand, the Raman spectroscopic imaging method can achieve the best lateral resolution when examining the heterogeneous composition of samples. The utilization of both methods is further enhanced via the combination with chemometric evaluation methods with respect to the detection, identification, and discrimination of illegal counterfeiting of food products. To demonstrate the solution to practical problems with these two spectroscopic techniques, the results of our recent investigations obtained for various industrial processes and customer-relevant product examples have been discussed in this article. Specifically, the monitoring of food extraction processes (e.g., ethanol extraction of clove and water extraction of wolfberry) and the identification of food quality (e.g., differentiation of cocoa nibs and cocoa beans) via handheld NIR spectroscopy, and the detection and quantification of adulterations in powdered dairy products via Raman imaging were outlined in some detail. Although the present work only demonstrates exemplary product and process examples, the applications provide a balanced overview of materials with different physical properties and manufacturing processes in order to be able to derive modified applications for other products or production processes. Raman spectroscopy ; Near-infrared spectroscopy ; Mobile device ; Identification (biology) ; Process engineering ; Materials science ; Computer science ; Nanotechnology ; Optics Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Rachid Amrani | Elyes Garoudja | Fouaz Lekoui | Walid Filali | Hamid Neggaz | Yacine Adlane Djebeli | Laid Henni | Salim Hassani | Faouzi Kezzoula | Slimane Oussalah | Faisal Al mashary | M. Henini
Source: Bulletin of Materials Science (article, 2023-01-09)
Field: Materials Science — Materials Chemistry

Investigation of structural and electrical properties of ITO thin films and correlation to optical parameters extracted using novel method based on PSO algorithm Materials science ; Crystallinity ; Indium tin oxide ; Thin film ; Annealing (glass) ; Band gap ; Refractive index ; Analytical Chemistry (journal) ; Raman spectroscopy ; Absorption edge ; Transmittance ; Optoelectronics ; Optics ; Nanotechnology ; Composite material ZnO doping and properties ; Thin-Film Transistor Technologies ; Gas Sensing Nanomaterials and Sensors
Authors: Attila Kertész‐Farkas | Frank Lawrence Nii Adoquaye Acquaye | Kishankumar Bhimani | Jimmy K. Eng | William E. Fondrie | Charles E. Grant | Michael R. Hoopmann | Andy Lin | Yang Young Lu | Robert L. Moritz | Michael J. MacCoss | William Stafford Noble
Source: Journal of Proteome Research (article, 2023-01-04)
Field: Chemistry — Spectroscopy

The Crux Toolkit for Analysis of Bottom-Up Tandem Mass Spectrometry Proteomics Data The Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database. Computer science ; Mass spectrometry ; Tandem mass spectrometry ; Function (biology) ; Proteomics ; Tandem ; Data mining ; Information retrieval ; Chemistry ; Chromatography ; Engineering Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Andreas Halner | Luke Hankey | Zhu Liang | Francesco Pozzetti | Daniel Szulc | Ella Mi | Geoffrey Liu | Benedikt M. Kessler | Junetha Syed | Peter Liu
Source: iScience (article, 2023-04-11)
Field: Chemistry — Spectroscopy

DEcancer: Machine learning framework tailored to liquid biopsy based cancer detection and biomarker signature selection Cancer is a leading cause of mortality worldwide. Over 50% of cancers are diagnosed late, rendering many treatments ineffective. Existing liquid biopsy studies demonstrate a minimally invasive and inexpensive approach for disease detection but lack parsimonious biomarker selection, exhibit poor cancer detection performance and lack appropriate validation and testing. We established a tailored machine learning pipeline, DEcancer, for liquid biopsy analysis that addresses these limitations and improved performance. In a test set from a published cohort of 1,005 patients including 8 cancer types and 812 cancer-free individuals, DEcancer increased stage 1 cancer detection sensitivity across cancer types from 48 to 90%. In addition, with a test set cohort of patients from a high dimensional proteomics dataset of 61 lung cancer patients and 80 cancer-free individuals, DEcancer's performance using a 14-43 protein panel was comparable to 1,000 original proteins. DEcancer is a promising tool which may facilitate improved cancer detection and management. Liquid biopsy ; Biomarker ; Cancer ; Cancer biomarkers ; Biopsy ; Medicine ; Surgical oncology ; Lung cancer ; Biomarker discovery ; Feature selection ; Cohort ; Oncology ; Proteomics ; Internal medicine ; Machine learning ; Computer science ; Biology Advanced Proteomics Techniques and Applications ; Cancer Genomics and Diagnostics ; Gene expression and cancer classification
Authors: Michal Delkowski | José V. Anguita | Christopher T. G. Smith | S. Ravi P. Silva
Source: ACS Nano (article, 2023-01-09)
Field: Chemistry — Spectroscopy

Multifunctional Nanostructures with Controllable Band Gap Giving Highly Stable Infrared Emissivity for Smart Thermal Management Thermal control is essential to guarantee the optimal performance of most advanced electronic devices or systems. In space, orbital satellites face the issues of high thermal gradients, heating, and different thermal loads mediated by differential illumination from the Sun. Todaýs state-of-the-art thermal control systems provide protection; however, they are bulky and restrict the mass and power budgets for payloads. Here, we develop a lightweight optical superlattice nanobarrier structure to provide a smart thermal control solution. The structure consists of a moisture and outgassing physical barrier (MOB) coupled with atomic oxygen (AO)-UV protection functionality. The nanobarrier exhibits transmission and reflection of light by controlling the optical gap of individual layers to enable high infrared emissivity and variable solar absorptivity (minimum Δα<sub>S</sub> = 0.30) across other wavelengths. The multifunctional coating can be applied to heat-sensitive substrates by means of a bespoke room-temperature process. We demonstrate enhanced stability, energy-harvesting capability, and power savings by facilitating the radiation cooling and facility for active self-reconfiguration in orbit. In this way, the reduction of the operating temperature from ∼120 to ∼60 °C on space-qualified and nonmechanically controlled composite structures is also demonstrated. Emissivity ; Materials science ; Optoelectronics ; Infrared ; Passive cooling ; Low emissivity ; Thermal ; Nanotechnology ; Optics ; Coating ; Physics Aerogels and thermal insulation ; Transition Metal Oxide Nanomaterials ; Silicone and Siloxane Chemistry
Authors: Juxiang Qiao | Yun Liao | Chang‐Sheng Yin | Xiaohong Yang | Hoàng Minh Tú | Wei Wang | Yanfang Liu
Source: Frontiers in Plant Science (article, 2023-09-18)
Field: Chemistry — Analytical Chemistry

Vigour testing for the rice seed with computer vision-based techniques Rice is the staple food for approximately half of the world's population. Seed vigour has a crucial impact on the yield, which can be evaluated by germination rate, vigor index and <i>etc</i>. Existing seed vigour testing methods heavily rely on manual inspections that are destructive, time-consuming, and labor-intensive. To address the drawbacks of existing rice seed vigour testing, we proposed a multispectral image-based non-destructive seed germination testing approach. Specifically, we collected multispectral data in 19 wavebands for six rice varieties. Furthermore, we designed an end-to-end pipeline, denoted as MsiFormer (MisFormer cod3e will be available at https://github.com/LiaoYun0x0/MisFormer) by integrating a Yolo-based object detector (trained Yolo v5) and a vision transformer-based vigour testing model, which effectively improved the automation and efficiency of existing techniques. In order to objectively evaluate the performance of the proposed method in this paper, we conduct a comparison between MisFormer and other 3 deep learning methods. The results showed that, MisFormer performed much better with the accuracy of 94.17%, which was 2.5%-18.34% higher than the other 3 deep learning methods. Besides MsiFormer, possibilities of CIELab mediated image analysis of TTC (tetrazolium chloride) staining in rice seed viability and nCDA (normalized canonical discriminant analysis) in rice seed vigour were also discussed, where CIELab L<sup>*</sup> of TTC staining were negatively correlated with vigor index and germination rate, with Pearson's correlation coefficient of -0.9874, -0.9802 respectively, and CIELab A<sup>*</sup> of TTC staining were and positively correlated with vigor index and germination rate, with Pearson's correlation coefficient of 0.9624, 0.9544 respectively, and CIELab A<sup>*</sup> of nCDA had Pearson's correlation coefficient of -0.8866 and -0.9340 with vigor index and germination rate, respectively. Besides testing methods, vigour results within and among variety(ies) showed that, there were great variations among the 6 rice varieties, and mean coefficient of variation (CV) of vigor index of individual seed within a variety reached 64.87%, revealing the high risk of conventional methods in random sampling. Vigour variations had close relationship with wavelengths of 780 nm-970 nm, indicating their value in future research. Germination ; Artificial intelligence ; Multispectral image ; Mathematics ; Correlation coefficient ; Automation ; Statistics ; Computer science ; Pattern recognition (psychology) ; Agronomy ; Biology ; Engineering Spectroscopy and Chemometric Analyses ; GABA and Rice Research ; Smart Agriculture and AI
Authors: Federico Ghimenti | Ludovic Berthier | Grzegorz Szamel | Frédéric van Wijland
Source: Physical Review Letters (article, 2023-12-18)
Field: Materials Science — Materials Chemistry

Sampling Efficiency of Transverse Forces in Dense Liquids International audience Transverse plane ; Sampling (signal processing) ; Materials science ; Statistical physics ; Mechanics ; Physics ; Optics ; Structural engineering Material Dynamics and Properties ; Advanced Thermodynamics and Statistical Mechanics ; Phase Equilibria and Thermodynamics
Authors: Emre Brookes | Mattia Rocco | Patrice Vachette | Jill Trewhella
Source: Journal of Applied Crystallography (article, 2023-07-04)
Field: Materials Science — Materials Chemistry

AlphaFold-predicted protein structures and small-angle X-ray scattering: insights from an extended examination of selected data in the Small-Angle Scattering Biological Data Bank By providing predicted protein structures from nearly all known protein sequences, the artificial intelligence program AlphaFold (AF) is having a major impact on structural biology. While a stunning accuracy has been achieved for many folding units, predicted unstructured regions and the arrangement of potentially flexible linkers connecting structured domains present challenges. Focusing on single-chain structures without prosthetic groups, an earlier comparison of features derived from small-angle X-ray scattering (SAXS) data taken from the Small-Angle Scattering Biological Data Bank (SASBDB) is extended to those calculated using the corresponding AF-predicted structures. Selected SASBDB entries were carefully examined to ensure that they represented data from monodisperse protein solutions and had sufficient statistical precision and <i>q</i> resolution for reliable structural evaluation. Three examples were identified where there is clear evidence that the single AF-predicted structure cannot account for the experimental SAXS data. Instead, excellent agreement is found with ensemble models generated by allowing for flexible linkers between high-confidence predicted structured domains. A pool of representative structures was generated using a Monte Carlo method that adjusts backbone dihedral allowed angles along potentially flexible regions. A fast ensemble modelling method was employed that optimizes the fit of pair distance distribution functions [<i>P</i>(<i>r</i>) versus <i>r</i>] and intensity profiles [<i>I</i>(<i>q</i>) versus <i>q</i>] computed from the pool to their experimental counterparts. These results highlight the complementarity between AF prediction, solution SAXS and molecular dynamics/conformational sampling for structural modelling of proteins having both structured and flexible regions. Scattering ; Protein Data Bank ; Small-angle X-ray scattering ; Small-angle scattering ; Data bank ; Physics ; Crystallography ; Computational physics ; Optics ; Chemistry ; Protein structure ; Computer science ; Nuclear magnetic resonance Enzyme Structure and Function ; Protein Structure and Dynamics ; Bacterial Genetics and Biotechnology
Authors: Danfei Liu | Yunfei Zhong | Yumei Pu | Xiaoxuan Li | Siyuan Chen | Changfan Zhang
Source: Foods (article, 2023-06-08)
Field: Materials Science — Biomaterials

Preparation of pH-Responsive Films from Polyvinyl Alcohol/Agar Containing Cochineal for Monitoring the Freshness of Pork This study reported the production of pH-responsive films based on 8 wt% polyvinyl alcohol solution/0.2 wt% agar solution incorporated with cochineal-loaded starch particles (CSN) (2, 4, 6 and 8 wt% on agar basis) by a casting process. Results revealed that CSN presented obvious color changes over the pH range of 2-12. FTIR, XRD spectra and SEM micrographs presented that the incorporation of CSN formed new hydrogen bonds with a matrix and a tighter network structure. A certain improvement was observed in the color stability, swelling index and functional properties (antimicrobial and antioxidant activities) but water solubility, water vapor permeability and water contact angle of the pH-responsive films were decreased by the addition of CSN. The release of cochineal was a rate-limiting step following the Korsmeyer-Peppas model. The agar/polyvinyl alcohol film containing 6% CSN (PVA/GG-6) exhibited the best sensitivity for ammonia detection and its limit of detection was 35.4 ppm (part per million) for ammonia. The application trials showed that the PVA/GG-6 film presented different color changes for pork freshness. Hence, these pH-responsive films can be used as potential packaging materials for tracking the freshness of protein-rich fresh food in a non-destructive way. Polyvinyl alcohol ; Agar ; Chemistry ; Nuclear chemistry ; Fourier transform infrared spectroscopy ; Ammonia ; Alcohol ; Solubility ; Active packaging ; Starch ; Materials science ; Food science ; Chemical engineering ; Food packaging ; Organic chemistry ; Bacteria Nanocomposite Films for Food Packaging ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: Yu Zong | Yuxin Wang | Yi Yang | Dan Zhao | Xiaoqing Wang | Chengpin Shen | Liang Qiao
Source: Nature Communications (article, 2023-04-20)
Field: Chemistry — Spectroscopy

DeepFLR facilitates false localization rate control in phosphoproteomics Protein phosphorylation is a post-translational modification crucial for many cellular processes and protein functions. Accurate identification and quantification of protein phosphosites at the proteome-wide level are challenging, not least because efficient tools for protein phosphosite false localization rate (FLR) control are lacking. Here, we propose DeepFLR, a deep learning-based framework for controlling the FLR in phosphoproteomics. DeepFLR includes a phosphopeptide tandem mass spectrum (MS/MS) prediction module based on deep learning and an FLR assessment module based on a target-decoy approach. DeepFLR improves the accuracy of phosphopeptide MS/MS prediction compared to existing tools. Furthermore, DeepFLR estimates FLR accurately for both synthetic and biological datasets, and localizes more phosphosites than probability-based methods. DeepFLR is compatible with data from different organisms, instruments types, and both data-dependent and data-independent acquisition approaches, thus enabling FLR estimation for a broad range of phosphoproteomics experiments. Phosphoproteomics ; Computer science ; Phosphopeptide ; Proteome ; Computational biology ; Posttranslational modification ; Proteomics ; Phosphorylation ; Bioinformatics ; Biology ; Protein phosphorylation ; Cell biology ; Protein kinase A ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Ashmita Rawal | Alfred E. Hartemink | Yakun Zhang | Yi Wang | Richard A. Lankau | Matthew D. Ruark
Source: Precision Agriculture (article, 2023-11-15)
Field: Chemistry — Analytical Chemistry

Visible and near-infrared spectroscopy predicted leaf nitrogen contents of potato varieties under different growth and management conditions Abstract Visible-Near Infrared (vis-NIR) spectroscopy can provide a faster, cost-effective, and user-friendly solution to monitor leaf N status, potentially overcoming the limitations of current techniques. The objectives of the study were to develop and validate partial least square regression (PLSR) to estimate the total N contents of fresh and removed leaves of potatoes using the vis-NIR spectral range (350–2500 nm) generated from a handheld proximal sensor. The model was built using data collected from Hancock Agricultural Research Station, WI, USA in 2020 and was validated using samples collected in 2021 for four different conditions. The conditions included two sites (Coloma and Hancock), four potato varieties (Burbank, Norkotah, Goldrush, and Silverton), two N rates (unfertilized and 308 kg N ha −1 ), and four growth stages (vegetative, tuber initiation, tuber bulking, and tuber maturation). The calibration and validation models had high predictive performance for leaf total N with R 2 &gt; 0.8 and RPD &gt; 2. The model accuracy was affected by the total N contents in the leaf samples where the model underpredicted the samples with total leaf N contents greater than 6%. Horticulture ; Nitrogen ; Partial least squares regression ; Near-infrared spectroscopy ; Calibration ; Chemistry ; Mathematics ; Agronomy ; Environmental science ; Biology ; Statistics Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Water Quality Monitoring and Analysis
Authors: Kholood Alkhamis | Meshari M. Aljohani | Saham F. Ibarhiam | Yasmeen A. S. Hameed | Hana M. Abumelha | Turki M. Habeebullah | Nashwa M. El‐Metwaly
Source: ACS Omega (article, 2023-08-08)
Field: Chemistry — Inorganic Chemistry

Application of Metal–Organic Frameworks for Efficient Removal of Doxorubicin Hydrochloride: Removal Process Optimization and Biological Activity This study looked at the doxorubicin hydrochloride (DOX) anticancer drug's adsorption characteristics on a silver-based metal-organic framework (Ag-MOF). X-ray diffraction (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS) were used for the characterization of Ag-MOF. The pore volume and surface area of Ag-MOF were determined through Brunauer-Emmett-Teller (BET) testing at 77 K to be 0.509 cm<sup>3</sup>/g and 676.059 m<sup>2</sup>/g, respectively. Adsorption at pH 6 was established to be the best for DOX compared to alkaline solution. Ag-MOF has a good capacity for eliminating DOX (1.85 mmol/g), according to adsorption experiments. From the adsorption results, we can find that Langmuir is the most fitted adsorption isotherm model and the pseudo-second order model best fitted the adsorption kinetics. The energy of activation for adsorption, which was determined to be 15.23 kJ/mol, also supported a chemisorption process. The mechanism of adsorption was evaluated, and details of all possible interactions between DOX and Ag-MOF were illustrated. On the other hand, while examining the impact of temperature, we identified the thermodynamic constraints as Δ<i>G</i>°, Δ<i>H</i>°, and Δ<i>S</i>° and confirmed that the reaction was an endothermic one and spontaneous. Even after numerous reuse cycles, the efficiency remained constant. The synthetic adsorbent was remarkably recyclable at a rate of more than 91.6%. By using the MTT assay, the cytotoxicity of the tested Ag-MOF and DOX@Ag-MOF against human breast cancer cells (MCF-7) was evaluated <i>in vitro</i>. The <i>in vitro</i> antimicrobial activity of Ag-MOF and DOX@Ag-MOF was also tested. Doxorubicin Hydrochloride ; Process (computing) ; Hydrochloride ; Doxorubicin ; Chemistry ; Metal ; Combinatorial chemistry ; Computer science ; Organic chemistry ; Medicine ; Chemotherapy ; Surgery Metal-Organic Frameworks: Synthesis and Applications ; Chemical Synthesis and Characterization ; Adsorption and biosorption for pollutant removal
Authors: Peng Cheng | Zhiyang Wei | Yara Arbid | Tengfei Fu | Xiaowei Liu | Olivier Monfort
Source: Journal of environmental chemical engineering (article, 2023-12-17)
Field: Chemistry — Inorganic Chemistry

Insights into the performance and mechanism of Cr(VI) and U(VI) removal in water using innovative cross-linked chitosan adsorbent Chitosan ; Adsorption ; Mechanism (biology) ; Chemistry ; Chemical engineering ; Nuclear chemistry ; Engineering ; Physics ; Physical chemistry Radioactive element chemistry and processing ; Adsorption and biosorption for pollutant removal ; Extraction and Separation Processes