jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ri Wu | Jonas B. Metternich | Anna S. Kamenik | Prince Tiwari | Julian A. Harrison | Dennis Kessen | Hasan Akay | Lukas R. Benzenberg | T.‐W. Dominic Chan | Sereina Riniker | Renato Zenobi
Source: Nature Communications (article, 2023-05-22)
Field: Chemistry — Spectroscopy

Determining the gas-phase structures of α-helical peptides from shape, microsolvation, and intramolecular distance data Mass spectrometry is a powerful technique for the structural and functional characterization of biomolecules. However, it remains challenging to accurately gauge the gas-phase structure of biomolecular ions and assess to what extent native-like structures are maintained. Here we propose a synergistic approach which utilizes Förster resonance energy transfer and two types of ion mobility spectrometry (i.e., traveling wave and differential) to provide multiple constraints (i.e., shape and intramolecular distance) for structure-refinement of gas-phase ions. We add microsolvation calculations to assess the interaction sites and energies between the biomolecular ions and gaseous additives. This combined strategy is employed to distinguish conformers and understand the gas-phase structures of two isomeric α-helical peptides that might differ in helicity. Our work allows more stringent structural characterization of biologically relevant molecules (e.g., peptide drugs) and large biomolecular ions than using only a single structural methodology in the gas phase. Intramolecular force ; Biomolecule ; Gas phase ; Ion ; Molecule ; Chemical physics ; Conformational isomerism ; Chemistry ; Characterization (materials science) ; Mass spectrometry ; Phase (matter) ; Ion-mobility spectrometry ; Computational chemistry ; Materials science ; Nanotechnology ; Physical chemistry ; Stereochemistry ; Organic chemistry ; Chromatography Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Advanced Proteomics Techniques and Applications
Authors: Jigang Xu | Shujun Liu | Ming Gao | Yonggang Zuo
Source: Lubricants (article, 2023-06-20)
Field: Chemistry — Analytical Chemistry

Classification of Lubricating Oil Types Using Mid-Infrared Spectroscopy Combined with Linear Discriminant Analysis–Support Vector Machine Algorithm To realize the classification of lubricating oil types using mid-infrared (MIR) spectroscopy, linear discriminant analysis (LDA) was used for the dimensionality reduction of spectrum data, and the classification model was established based on the support vector machine (SVM). The spectra of the samples were pre-processed by interval selection, Savitzky–Golay smoothing, multiple scattering correction, and normalization. The Kennard–Stone algorithm (K/S) was used to construct the calibration and validation sets. The percentage of correct classification (%CC) was used to evaluate the model. This study compared the results obtained with several chemometric methods: PLS-DA, LDA, principal component analysis (PCA)-SVM, and LDA-SVM in MIR spectroscopy applications. In both calibration and verification sets, the LDA-SVM model achieved 100% favorable results. The PLS-DA analysis performed poorly. The cyclic resistance ratio (CRR) of the calibration set was classified via the LDA and PCA-SVM analysis as 100%, but the CRR of the verification set was not as good. The LDA-SVM model was superior to the other three models; it exhibited good robustness and strong generalization ability, providing a new method for the classification of lubricating oil types by MIR spectroscopy. Linear discriminant analysis ; Support vector machine ; Principal component analysis ; Artificial intelligence ; Pattern recognition (psychology) ; Dimensionality reduction ; Normalization (sociology) ; Mathematics ; Smoothing ; Feature selection ; Calibration ; Algorithm ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Paul‐Albert Schneide | Rasmus Bro | Neal B. Gallagher
Source: Journal of Chemometrics (article, 2023-06-26)
Field: Chemistry — Spectroscopy

Shift‐invariant tri‐linearity—A new model for resolving untargeted gas chromatography coupled mass spectrometry data Abstract Multi‐way data analysis is popular in chemometrics for the decomposition of, for example, spectroscopic or chromatographic higher‐order tensor datasets. Parallel factor analysis (PARAFAC) and its extension, PARAFAC2, are extensively employed methods in chemometrics. Applications of PARAFAC2 for untargeted data analysis of hyphenated gas chromatography coupled with mass spectrometric detection (GC‐MS) have proven to be very successful. This is attributable to the ability of PARAFAC2 to account for retention time shifts and shape changes in chromatographic elution profiles. Despite its usefulness, the most common implementations of PARAFAC2 are considered quite slow. Furthermore, it is difficult to apply constraints (e.g., non‐negativity) to the shifted mode in PARAFAC2 models. Both aspects are addressed by a new shift‐invariant tri‐linearity (SIT) algorithm proposed in this paper. It is shown on simulated and real GC‐MS data that the SIT algorithm is 20–60 times faster than the latest PARAFAC2‐alternating least squares (ALS) implementation and the PARAFAC2‐flexible coupling algorithm. Further, the SIT method allows the implementation of constraints in all modes. Trials on real‐world data indicate that the SIT algorithm compares well with alternatives. The new SIT method achieves better factor resolution than the benchmark in some cases and tends to need fewer latent variables to extract the same chemical information. Although SIT is not capable of modeling shape changes in elution profiles, trials on real‐world data indicate the great robustness of the method even in those cases. Chromatography ; Mass spectrometry ; Chemistry ; Linearity ; Gas chromatography ; Gas chromatography–mass spectrometry ; Analytical Chemistry (journal) ; Physics Analytical Chemistry and Chromatography ; Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies
Authors: Puneet Mishra | Kristian Hovde Liland
Source: Journal of Chemometrics (article, 2023-04-04)
Field: Chemistry — Analytical Chemistry

An algorithm for robust multiblock partial least squares predictive modelling Abstract A new algorithm for robust multiblock (data fusion) modelling in the presence of outlying observations is presented. The method is a combination of a robust modelling technique called iterative reweighted partial least squares and the block order and scale‐independent component‐wise multiblock partial least squares modelling. The method is based on automatic down‐weighting of outlying observations such that their contribution is minimal during the estimation of block‐wise partial least squares models, thus leading to robust modelling minimally affected by outliers. The algorithm and test of the methods for modelling multiblock data sets (simulated and real) in the presence of outlying observation are demonstrated. Partial least squares regression ; Weighting ; Outlier ; Algorithm ; Least-squares function approximation ; Iteratively reweighted least squares ; Computer science ; Least trimmed squares ; Block (permutation group theory) ; Robust regression ; Non-linear least squares ; Mathematics ; Artificial intelligence ; Statistics ; Estimation theory Spectroscopy and Chemometric Analyses ; Advanced Statistical Methods and Models ; Statistical and numerical algorithms
Authors: Jing Han | Junxian Guo | Zhenzhen Zhang | Xiao Yang | Yong Shi | Jun Zhou
Source: Agriculture (article, 2023-10-01)
Field: Chemistry — Analytical Chemistry

The Rapid Detection of Trash Content in Seed Cotton Using Near-Infrared Spectroscopy Combined with Characteristic Wavelength Selection Herein, we propose a new method based on Fourier-transform near-infrared spectroscopy (FT-NIR) for detecting impurities in seed cotton. Based on the spectral data of 152 seed cotton samples, we screened the characteristic wavelengths in full-band spectral data with regard to potential correlation with the trash content of seed cotton. Then, we applied joint synergy interval partial least squares (siPLS) and combinatory algorithms with the competitive adaptive reweighted sampling method (CARS) and the successive projection algorithm (SPA). In addition, we used the sparrow search algorithm (SSA), gray wolf algorithm (GWO), and eagle algorithm (BES) to optimize parameters for support vector machine (SVM) analysis. Finally, the feature wavelengths optimized via the six feature wavelength extraction algorithms were modeled and analyzed via partial least squares (PLS), SSA-SVM, GWO-SVM, and BES-SVM, respectively. The correlation coefficients, Rc and Rp, of the calibration and prediction sets were subsequently used as model evaluation indices; comparative analysis highlighted that the preferred option was the inverse estimation model as this could accurately predict the trash content of seed cotton. Subsequently, we found that the accuracy of predicting the content of impurities in seed cotton when applying the optimized SVM model of SSA combined with the feature wavelengths screened via siPLS-SPA was optimal. Thus, the optimal modeling method for inverse impurity content was siPLS-SPA-SSA-SVM, with an Rc value of 0.9841 and an Rp value of 0.9765. The rapid application development (RPD) value was 6.7224; this is &gt;3, indicating excellent predictive ability. The spectral inversion model for determining the impurity rate of mechanized harvested seed cotton samples established herein can, therefore, determine the impurity rate in a highly accurate manner, thus providing a reference for the subsequent construction of a portable spectral detector of impurity rate. This will help objectively and quantitatively characterize the impurity rate of mechanized harvested seed cotton and provide a new tool for rapidly detecting impurities in mechanized harvested wheat. Our findings are limited by the small sample size and the fact that the model developed for estimating the impurity content of seed cotton was specific to a local experimental field and certain varieties of cotton. Support vector machine ; Feature selection ; Partial least squares regression ; Content (measure theory) ; Mathematics ; Sampling (signal processing) ; Inverse ; Fourier transform ; Biological system ; Algorithm ; Artificial intelligence ; Pattern recognition (psychology) ; Computer science ; Statistics ; Telecommunications Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Remote Sensing in Agriculture
Authors: Jvqiang Chang | Qixin He | Mengxin Li
Source: Sensors (article, 2023-04-25)
Field: Chemistry — Spectroscopy

Development of a Stable Oxygen Sensor Using a 761 nm DFB Laser and Multi-Pass Absorption Spectroscopy for Field Measurements An optical sensor system based on wavelength modulation spectroscopy (WMS) was developed for atmospheric oxygen (O<sub>2</sub>) detection. A distributed feedback (DFB) laser with butterfly packaging was used to target the O<sub>2</sub> absorption line at 760.89 nm. A compact multi-pass gas cell was employed to increase the effective absorption length to 3.3 m. To ensure the stability and anti-interference capability of the sensor in field measurements, the optical module was fabricated with isolation of ambient light and vibration design. A 1<i>f</i> normalized 2<i>f</i> WMS (WMS-2<i>f</i>/1<i>f</i>) technique was adopted to reduce the effect of laser power drift. In addition, a LabVIEW-based dual-channel lock-in amplifier was developed for harmonic detection, which significantly reduced the sensor volume and cost. The detailed detection principle was described, and a theoretical model was established to verify the effectiveness of the technique. Experiments were carried out to obtain the device's sensing performances. An Allan deviation analysis yielded a minimum detection limit of 0.054% for 1 s integration time that can be further improved to 0.009% at ~60 s. Finally, the reliability and anti-interference capability of the sensor system were verified by the atmospheric O<sub>2</sub> monitoring. Lock-in amplifier ; Laser ; Materials science ; Interference (communication) ; Absorption (acoustics) ; Distributed feedback laser ; Absorption spectroscopy ; Spectroscopy ; Optics ; Amplifier ; Optoelectronics ; Wavelength ; Computer science ; Channel (broadcasting) ; Physics ; Telecommunications Spectroscopy and Laser Applications ; Atmospheric Ozone and Climate ; Laser Design and Applications
Authors: Sebastian Dorl | Stephan Winkler | Karl Mechtler | Viktoria Dorfer
Source: Journal of Proteome Research (article, 2023-01-23)
Field: Chemistry — Spectroscopy

MS Ana: Improving Sensitivity in Peptide Identification with Spectral Library Search Spectral library search can enable more sensitive peptide identification in tandem mass spectrometry experiments. However, its drawbacks are the limited availability of high-quality libraries and the added difficulty of creating decoy spectra for result validation. We describe MS Ana, a new spectral library search engine that enables high sensitivity peptide identification using either curated or predicted spectral libraries as well as robust false discovery control through its own decoy library generation algorithm. MS Ana identifies on average 36% more spectrum matches and 4% more proteins than database search in a benchmark test on single-shot human cell-line data. Further, we demonstrate the quality of the result validation with tests on synthetic peptide pools and show the importance of library selection through a comparison of library search performance with different configurations of publicly available human spectral libraries. Benchmark (surveying) ; Identification (biology) ; Computer science ; False discovery rate ; Sensitivity (control systems) ; Mascot ; Decoy ; Database search engine ; Computational biology ; Search engine ; Information retrieval ; Chemistry ; Biology ; Engineering Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Jean Rochielle F. Mirandilla | M. Yamashita | Mitsunori Yoshimura | Enrico C. Paringit
Source: Remote Sensing (article, 2023-06-11)
Field: Chemistry — Analytical Chemistry

Leaf Spectral Analysis for Detection and Differentiation of Three Major Rice Diseases in the Philippines Monitoring the plant’s health and early detection of disease are essential to facilitate effective management, decrease disease spread, and minimize yield loss. Spectroscopic techniques in remote sensing offer less laborious methods and high spatiotemporal scale to monitor diseases in crops. Spectral measurements during the development of disease infection may reveal differences among diseases and determine the stage it can be effectively detected. In this study, spectral analysis was performed over the visible and near-infrared (400–850 nm) portions of the spectrum to detect and differentiate three major rice diseases in the Philippines, namely tungro, BLB, and blast disease. Reflectance of infected rice leaves was recorded repeatedly from inoculation to the late stage of each disease. Results show that spectral reflectance is characteristically affected by each disease, resulting in different spectral, signature sensitivity, and first-order derivatives. Red and red-edge wavelength ranges are the most sensitive to the three diseases. Near-infrared wavelengths decreased as tungro and blast diseases progressed. In addition, the spectral reflectance was resampled to common reflectance sensitivity bands of optical sensors and used in the cluster analysis. It showed that BLB and blast can be detected in the early disease stage on the IRRI Standard Evaluation System (SES) scale of 1 and 3, respectively. Alternatively, tungro was detected in its later stage, with an 11–30% height reduction and no distinct yellow to yellow-orange discoloration (5 SES scale). Three regression techniques, Partial Least Square, Random Forest, and Support Vector Regression were performed separately on each disease to develop models predicting its severity. The validation results of the PLSR and SVR models in tungro and blast show accuracy levels that are promising to be used in estimating the severity of the disease in leaves while RFR shows the best results for BLB. Early disease detection and regression models from spectral measurements and analysis for disease severity estimation can help in disease monitoring and proper disease management implementation. Remote sensing ; Orange (colour) ; Reflectivity ; Spectral signature ; Stage (stratigraphy) ; Environmental science ; Horticulture ; Veterinary medicine ; Biology ; Optics ; Medicine ; Geology ; Physics Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Smart Agriculture and AI
Authors: Rongfeng Yuan | Trevor D. Roberts | Rafaela M. Brinn | Alexander A. Choi | Ha H. Park | Chang Yan | Justin C. Ondry | Siamak Khorasani | David J. Masiello | Ke Xu | A. Paul Alivisatos | Naomi S. Ginsberg
Source: Science Advances (article, 2023-10-20)
Field: Materials Science — Materials Chemistry

A composite electrodynamic mechanism to reconcile spatiotemporally resolved exciton transport in quantum dot superlattices Quantum dot (QD) solids are promising optoelectronic materials; further advancing their device functionality requires understanding their energy transport mechanisms. The commonly invoked near-field Förster resonance energy transfer (FRET) theory often underestimates the exciton hopping rate in QD solids, yet no consensus exists on the underlying cause. In response, we use time-resolved ultrafast stimulated emission depletion (STED) microscopy, an ultrafast transformation of STED to spatiotemporally resolve exciton diffusion in tellurium-doped cadmium selenide-core/cadmium sulfide-shell QD superlattices. We measure the concomitant time-resolved exciton energy decay due to excitons sampling a heterogeneous energetic landscape within the superlattice. The heterogeneity is quantified by single-particle emission spectroscopy. This powerful multimodal set of observables provides sufficient constraints on a kinetic Monte Carlo simulation of exciton transport to elucidate a composite transport mechanism that includes both near-field FRET and previously neglected far-field emission/reabsorption contributions. Uncovering this mechanism offers a much-needed unified framework in which to characterize transport in QD solids and additional principles for device design. Quantum dot ; Exciton ; Biexciton ; Superlattice ; Förster resonance energy transfer ; Physics ; Cadmium selenide ; Chemical physics ; Materials science ; Condensed matter physics ; Optoelectronics ; Optics ; Fluorescence Quantum Dots Synthesis And Properties ; Semiconductor Quantum Structures and Devices ; Chalcogenide Semiconductor Thin Films
Authors: Konstantinos Rallis | Iosif-Angelos Fyrigos | Panagiotis Dimitrakis | Giorgos Dimitrakopoulos | Ioannis G. Karafyllidis | Antonio Rubio | Georgios Ch. Sirakoulis
Source: IEEE Transactions on Nanotechnology (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

A Reprogrammable Graphene Nanoribbon-Based Logic Gate In this paper, taking into consideration the exceptional technological properties of a unique 2-D material, namely Graphene, we are envisioning its usage as the structure material of a non-back-gated re-programmable switching device. The proposed topology is analyzed in depth, not only by verifying its operation and re-programmability as a 2-input XOR, 3-input XOR and 3-input Majority gate, but also by examining its computing performance in terms of area, delay and power dissipation. More specifically, we are utilizing L-shaped Graphene Nanoribbons (GNRs) to develop comb-shaped Graphene based switching devices. These devices are in position with effective programming through biasing to design any combinatorial circuit as resulting from the aforementioned universal set of Boolean gates. The resulting figures of merit regarding the area with a universal footprint of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{2.53}~nm^{2}$</tex-math></inline-formula> for every gate independently of the number of inputs, the propagation delay with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$2.05\times {10^{-2}}ps$</tex-math></inline-formula> and, last but not least, the power dissipation with only <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10.204nW$</tex-math></inline-formula> for the gates with greater number of inputs, are quite encouraging and promising. Moreover, the ability of the proposed topology to pave the way towards the implementation of basic circuits has been further investigated, by demonstrating an example of a 1-bit full adder cell and its sufficient operation arriving from the corresponding successful SPICE simulation results. XOR gate ; Logic gate ; Notation ; Graphene ; Topology (electrical circuits) ; Power (physics) ; Figure of merit ; Computer science ; Electrical engineering ; Mathematics ; Algorithm ; Arithmetic ; Physics ; Combinatorics ; Engineering ; Quantum mechanics Graphene research and applications ; Advanced Memory and Neural Computing ; Quantum-Dot Cellular Automata
Authors: Guangyin Zhang | Min Guo | Xinyu Zhao | Dongyu Cui | Lin Xu | Nan Wang | Rui Ni | Hongchao Qi | Jikuan Zhao | Ke Chen
Source: Microwave and Optical Technology Letters (article, 2023-01-13)
Field: Chemistry — Spectroscopy

Miniaturized nonresonant photoacoustic gas analyzer for CO<sub>2</sub> detection Abstract In this letter, a portable trace carbon dioxide (CO 2 ) measurement instrument based on photoacoustic spectroscopy (PAS) was proposed and designed. The nonresonance PA cell (PAC) including a cooper tube with 251.2 μl was designed. Two condenser microphones were used to measure the PA signal simultaneously. The center wavelength of the distributed feedback laser was chosen to 2004 nm. Within 1 s integral time, the detection limit for CO 2 reached 12.7 ppm. The normalized noise‐equivalent absorption coefficient was calculated to be 4.8468 × 10 −9 cm −1 W/Hz 1/2 . With Allan‐Werle deviation analysis, the measurement detection limit for CO 2 improved to 4 ppm with 30 s integration time. As a result, the trace CO 2 instrument based on PAS shows a good performance in long‐term detection. Detection limit ; Photoacoustic spectroscopy ; Allan variance ; Trace gas ; Analytical Chemistry (journal) ; Spectrum analyzer ; Time delay and integration ; Photoacoustic imaging in biomedicine ; Materials science ; Optics ; Condenser (optics) ; Wavelength ; Laser ; Optoelectronics ; Physics ; Chemistry ; Standard deviation ; Mathematics Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Atmospheric Ozone and Climate