jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Luiz Felipe Martucci | Rosangela Aparecida dos Santos Eichler | Renée de Nazaré Oliveira da Silva | Tiago J. Costa | Rita C. Tostes | Geraldo F. Busatto | Marília Seelaender | Alberto J. S. Duarte | Heraldo Possolo de Souza | Emer S. Ferro
Source: iScience (article, 2023-08-06)
Field: Materials Science — Materials Chemistry

Intracellular peptides in SARS-CoV-2-infected patients Intracellular peptides (InPeps) generated by the orchestrated action of the proteasome and intracellular peptidases have biological and pharmacological significance. Here, human plasma relative concentration of specific InPeps was compared between 175 patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and 45 SARS-CoV-2 non-infected patients; 2,466 unique peptides were identified, of which 67% were InPeps. The results revealed differences of a specific group of peptides in human plasma comparing non-infected individuals to patients infected by SARS-CoV-2, following the results of the semi-quantitative analyses by isotope-labeled electrospray mass spectrometry. The protein-protein interactions networks enriched pathways, drawn by genes encoding the proteins from which the peptides originated, revealed the presence of the coronavirus disease/COVID-19 network solely in the group of patients fatally infected by SARS-CoV-2. Thus, modulation of the relative plasma levels of specific InPeps could be employed as a predictive tool for disease outcome. Intracellular ; Coronavirus ; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ; Coronavirus disease 2019 (COVID-19) ; Proteasome ; Biology ; Chemistry ; Disease ; Medicine ; Biochemistry ; Internal medicine ; Infectious disease (medical specialty) Advanced Nanomaterials in Catalysis ; Peptidase Inhibition and Analysis ; Ubiquitin and proteasome pathways
Authors: Lu Xie | Weigang Li | Lixia Fan | Mingxing Zhou
Source: steel research international (article, 2023-02-25)
Field: Materials Science — Materials Chemistry

Automatic Identification of the Multiphase Microstructures of Steels based on ASPP‐FCN The properties of steels are often closely related to the category and distribution of their microstructures. However, the classification and quantitative analysis of multiphase steel are mostly performed manually, which is time‐consuming and laborious. Moreover, due to the variant experience of experts, the classification results of one image will be different. In this article, an automatic classification model is proposed to identify the multiphase microstructures of steels by means of semantic segmentation, which realizes the automatic statistics of the relative content of each crystalline phase. Semantic segmentation can assign each pixel in an image to one of a set of predefined categories, which can accomplish two tasks concurrently: phase identification and segmentation. We propose an improved fully convolutional network ASPP‐FCN, and carry out comparative experiments with different networks, including FCN, DeepLab v3+, Unet, Enet and PSPnet. The final pixel accuracy of ASPP‐FCN in each category is more than 95%; and the mean intersection over union is over 80%, the results demonstrate that ASPP‐FCN has better segmentation effect in the automatic recognition of the multiphase microstructures of steels. Segmentation ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Identification (biology) ; Intersection (aeronautics) ; Set (abstract data type) ; Pixel ; Phase (matter) ; Image segmentation ; Image (mathematics) Machine Learning in Materials Science ; Hydrogen embrittlement and corrosion behaviors in metals ; Non-Destructive Testing Techniques
Authors: Arun S. Moorthy | Edward P. Erisman | Anthony J. Kearsley | Yuxue Liang | Edward Sisco | W.E. Wallace
Source: Journal of Forensic Sciences (article, 2023-07-11)
Field: Chemistry — Spectroscopy

On the challenge of unambiguous identification of fentanyl analogs: Exploring measurement diversity using standard reference mass spectral libraries Fentanyl analogs are a class of designer drugs that are particularly challenging to unambiguously identify due to the mass spectral and retention time similarities of unique compounds. In this paper, we use agglomerative hierarchical clustering to explore the measurement diversity of fentanyl analogs and better understand the challenge of unambiguous identifications using analytical techniques traditionally available to drug chemists. We consider four measurements in particular: gas chromatography retention indices, electron ionization mass spectra, electrospray ionization tandem mass spectra, and direct analysis in real time mass spectra. Our analysis demonstrates how simultaneously considering data from multiple measurement techniques increases the observable measurement diversity of fentanyl analogs, which can reduce identification ambiguity. This paper further supports the use of multiple analytical techniques to identify fentanyl analogs (among other substances), as is recommended by the Scientific Working Group for the Analysis of Seized Drugs (SWGDRUG). Fentanyl ; Identification (biology) ; Mass spectrum ; Hierarchical clustering ; Electrospray ionization ; Mass spectrometry ; Ionization ; Chemistry ; Tandem mass spectrometry ; Computer science ; Analytical Chemistry (journal) ; Cluster analysis ; Chromatography ; Artificial intelligence ; Medicine ; Pharmacology ; Biology ; Organic chemistry Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Forensic Toxicology and Drug Analysis
Authors: Xinxin Wang | Yamine Bouzembrak | Alfons Oude Lansink | H.J. van der Fels‐Klerx
Source: Risk Analysis (article, 2023-03-02)
Field: Chemistry — Analytical Chemistry

Weighted Bayesian network for the classification of unbalanced food safety data: Case study of risk‐based monitoring of heavy metals Historical data on food safety monitoring often serve as an information source in designing monitoring plans. However, such data are often unbalanced: a small fraction of the dataset refers to food safety hazards that are present in high concentrations (representing commodity batches with a high risk of being contaminated, the positives) and a high fraction of the dataset refers to food safety hazards that are present in low concentrations (representing commodity batches with a low risk of being contaminated, the negatives). Such unbalanced datasets complicate modeling to predict the probability of contamination of commodity batches. This study proposes a weighted Bayesian network (WBN) classifier to improve the model prediction accuracy for the presence of food and feed safety hazards using unbalanced monitoring data, specifically for the presence of heavy metals in feed. Applying different weight values resulted in different classification accuracies for each involved class; the optimal weight value was defined as the value that yielded the most effective monitoring plan, that is, identifying the highest percentage of contaminated feed batches. Results showed that the Bayesian network classifier resulted in a large difference between the classification accuracy of positive samples (20%) and negative samples (99%). With the WBN approach, the classification accuracy of positive samples and negative samples were both around 80%, and the monitoring effectiveness increased from 31% to 80% for pre-set sample size of 3000. Results of this study can be used to improve the effectiveness of monitoring various food safety hazards in food and feed. False positive paradox ; Food safety ; Statistics ; Bayesian probability ; Bayesian network ; Data mining ; Computer science ; Mathematics ; Medicine Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Food Safety and Hygiene
Authors: Mafalda Reis Pereira | Renan Tosin | Rui C. Martins | Filipe Neves dos Santos | Fernando Tavares | Mário Cunha
Source:  (article, 2023-10-05)
Field: Chemistry — Analytical Chemistry

Enhancing Kiwi Bacterial Canker Leaf Assessment: Integrating Hyperspectral-Based Vegetation Indexes in Predictive Modeling The potential of hyperspectral UV–VIS–NIR reflectance for the in-field, non-destructive discrimination of bacterial canker on kiwi leaves caused by Pseudomonas syringae pv. actinidiae (Psa) was analyzed. Spectral data (325–1075 nm) of twenty kiwi plants were obtained in vivo and in situ with a handheld spectroradiometer in two commercial kiwi orchards in northern Portugal over 15 weeks, resulting in 504 spectral measurements. The suitability of different vegetation indexes (VIs) and applied predictive models (based on supervised machine learning algorithms) for classifying non-symptomatic and symptomatic kiwi leaves was evaluated. Eight distinct types of VIs were identified as relevant for disease diagnosis, highlighting the relevance of the Green, Red, Red-Edge, and NIR spectral features. The class prediction was achieved with good model metrics, achieving an accuracy of 0.71, kappa of 0.42, sensitivity of 0.67, specificity of 0.75, and F1 of 0.67. Thus, the present findings demonstrated the potential of hyperspectral UV–VIS–NIR reflectance for the non-destructive discrimination of bacterial canker on kiwi leaves. Hyperspectral imaging ; Kiwi ; Spectroradiometer ; Reflectivity ; Vegetation (pathology) ; Pseudomonas syringae ; Artificial intelligence ; Remote sensing ; Botany ; Horticulture ; Environmental science ; Biology ; Computer science ; Microbiology ; Geology ; Optics ; Medicine ; Pathogen Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Plant Pathogens and Fungal Diseases
Authors: Marek Florkowski
Source: Energies (article, 2023-06-21)
Field: Materials Science — Materials Chemistry

Effect of Interplay between Parallel and Perpendicular Magnetic and Electric Fields on Partial Discharges This paper reports on the influence of a magnetic field on the dynamics of partial discharges (PDs) in two distinct configurations with respect to the mutual orientation of electric fields. The broad application areas include electrical insulation systems of both high-voltage grids and industrial network devices as well as emerging segments such as electric vehicles or more electric aircraft. Traditionally, PD measurements are only carried out in an electric field. In all current-carrying power equipment, magnetic fields are also superimposed onto electric ones, thus influencing partial discharge behavior. It has been observed that the interplay between electric and magnetic fields influences the dynamics of PDs; parallel and perpendicular mutual orientations were specifically investigated. The measurement technique allowed us to quantitively detect the effect of magnetic fields on PDs in a corona point–plane arrangement. The novel element presented in this article is a detection of PD intensity modulated by a magnetic field, with both perpendicular and parallel orientations with respect to electric one, and a quantitative visualization in the form of the time-sequence diagrams. The simulation of electron trajectories in the presence of electric and magnetic fields revealed the elongation of the pathways and differentiation of the charged particle propagation times. The perpendicularly oriented magnetic field led to a twisting effect, whereas the parallel alignment reflected the propagation along a helical trajectory. A slightly stronger PD intensity amplification effect was observed in the case of a parallel alignment of electric versus magnetic fields as compared with the perpendicular orientation. The presented results may contribute to PD measurement methodology in both electric and magnetic fields as well as a better understanding of the underlying physical mechanisms. The observed effect of the modulation of the magnetically based PD dynamics may be relevant for the insulation systems of power equipment. Electric field ; Perpendicular ; Magnetic field ; Physics ; Orientation (vector space) ; Voltage ; Computational physics ; Nuclear magnetic resonance ; Condensed matter physics ; Materials science ; Geometry High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Power Transformer Diagnostics and Insulation
Authors: Christopher D. Delhom | John D. Wanjura | Mathew G. Pelletier | Gregory Holt | Eric Héquet
Source: Journal of Cotton Research (article, 2023-01-26)
Field: Materials Science — Polymers and Plastics

Investigation into a practical approach and application of cotton fiber elongation Abstract Background The strength of cotton fiber has been extensively studied and significantly improved through selective breeding, but fiber elongation has largely been ignored, even though elongation contributes to determining the energy needed to break fibers. Recent developments to calibrate the high volume instrument (HVI) for elongation has renewed interest in elongation. However, it is not understood how best to utilize yet another fiber property which has the potential to add to the complexity of fiber selection. To explore a practical approach to applying elongation, cotton samples were tested using single fiber methods, the Stelometer, and the HVI. Comparison of strength, elongation, and combined properties such as modulus were explored. Results HVI testing was shown to be sensitive enough to characterize elongation differences but unlike single fiber testing it was unable to capture within-sample variation. Fiber bundle testing, like Stelometer and HVI was shown to reduce bias due to fiber selection. Conclusion The use of secant modulus, an intrinsic material property, allowed for one value to represent both strength and elongation. Secant modulus was shown to contain more useful information than either elongation or work-to-break. Work-to-break was shown to be more influenced by a specific value of breaking force or elongation rather than the intrinsic behavior of the sample being tested. Exploring the influence of genetics and environment on elongation, and its interaction with other fiber properties, requires additional work. Secant modulus, by combining strength and elongation into one value, shows the potential to incorporate elongation values into fiber characterization without increasing the complexity of current fiber selection processes. Elongation ; Fiber ; Modulus ; Composite material ; Materials science ; Bundle ; Biological system ; Ultimate tensile strength Textile materials and evaluations ; Research in Cotton Cultivation ; Natural Fiber Reinforced Composites
Authors: WU Zhe | Yunxing Shi | Yuwang Han
Source: Applied Sciences (article, 2023-03-01)
Field: Chemistry — Spectroscopy

Methane, Ethylene, and Ethane Detection by Differential Helmholtz Resonance Spectroscopy Using a 3345 nm Mid-Infrared Tunable Diode Laser Source Gas detection based on photoacoustic spectroscopy (PAS) has attracted extensive attention due to its high sensitivity and large range of linearity. Herein, to achieve the simultaneous detection of the light carbon gases (CH4, C2H4, and C2H6), a gas detection system was constructed using a single mid-infrared tunable diode laser (central wavelength 3345 nm) source based on differential Helmholtz resonance spectroscopy (DHRS). The detection parameters (driving current, modulation depth, phase angle, etc.) were optimized under ambient pressure using the 1f demodulation method. With an integration time of 2 s, the detection limit reached 98.8 ppb, 252 ppb, and 33 ppb for methane, ethylene, and ethane, respectively. The validation test of the three-component mixture shows that the cross-interference can be effectively reduced by multiwavelength linear regression, and single wavelength linear regression causes large errors in the quantification of methane and ethylene. Detection limit ; Materials science ; Methane ; Spectroscopy ; Analytical Chemistry (journal) ; Wavelength ; Photoacoustic spectroscopy ; Resonance (particle physics) ; Infrared ; Laser ; Optics ; Optoelectronics ; Chemistry ; Physics ; Atomic physics Spectroscopy and Laser Applications ; Atmospheric and Environmental Gas Dynamics ; Advanced Chemical Sensor Technologies
Authors: Dapeng Li | Jiang Long | Ziye Tang | Longbo Han | Zhongliang Gong | Liang Wen | Hailong Peng | Tao Wen
Source: Agriculture (article, 2023-08-21)
Field: Chemistry — Analytical Chemistry

Detection and Classification of Citrus Fruit Infestation by Bactrocera dorsalis (Hendel) Using a Multi-Path Vis/NIR Spectroscopy System In this study, a multi-path Vis/NIR spectroscopy system was developed to detect the presence of Bactrocera dorsalis (Hendel) infestations of citrus fruit. Spectra were acquired for 252 citrus fruit, 126 of which were infested. Two hundred and fifty-two spectra were acquired for modeling in their un-infested stage, slightly infested stage, and seriously infested stage. The location of the infestation is unclear, and considering the impact of the light path on the location of the infestation, each citrus fruit was tested in three orientations (i.e., fruit stalks facing upward (A), fruit stalks facing horizontally (B), and fruit stalks facing downward (C)). Classification models based on joint X-Y distance, multiple transmittance calibration, competitive adaptive reweighted sampling, and partial least squares discriminant analysis (SPXY-MSC-CARS-PLS-DA) were developed on the spectra of each light path, and the average spectra of the four light paths was calculated, to compare their performance in infestation classification. The results show the classification result changed with the light path and fruit orientation. The average spectra for each fruit orientation consistently gave better classification results, with overall accuracies of 92.9%, 89.3%, and 90.5% for orientations A, B, and C, respectively. Moreover, the best model had a Kappa value of 0.89, and gave 95.2%, 80.1%, and 100.0% accuracy for un-infested, slightly infested, and seriously infested citrus fruit. Furthermore, the classification results for infested citrus fruits were better when using the average spectra than using the spectrum of each single light path. Therefore, the multi-path Vis/NIR spectroscopy system is conducive to the detection of B. dorsalis infestation in citrus fruits. Infestation ; Bactrocera dorsalis ; Horticulture ; Biology ; Partial least squares regression ; Botany ; Mathematics ; PEST analysis ; Statistics ; Tephritidae Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Christelle Ange Waffo Tchounga | R.D. Marini | Emmanuel Nnanga Nga | Patient Ciza Hamuli | Rose Ngono Mballa | Philippe Hubert | Eric Ziémons | Pierre‐Yves Sacré
Source: Applied Spectroscopy (article, 2023-09-21)
Field: Chemistry — Analytical Chemistry

In-Field Implementation of Near-Infrared Quantitative Methods for Analysis of Medicines in Tropical Environments Near-infrared (NIR) spectroscopy is actually a well-established technique that demonstrates its performance in the frame of detection of poor-quality medicines. The use of low-cost handheld NIR spectrophotometers in low-resource contexts can allow an inexpensive and more rapid detection compared to laboratory methods. Considering these points, it was decided to develop, validate, and transfer methods for the quantification of ciprofloxacin and metronidazole tablet samples using a NIR handheld spectrophotometer in transmission mode (NIR-M-T1) coupled to chemometrics such as partial least squares regression (PLSR) algorithm. All of the models were validated with the total error approach using an accuracy profile as a decision tool, with ±10% specifications and a risk α set at 5%. Quantitative PLSR models were first validated in Belgium, which is a temperate oceanic climate zone. Second, they were transferred to Cameroon, a tropical climate zone, where issues regarding the prediction of new validation series with the initial models were highlighted. Two augmentation strategies were then envisaged to make the predictive models robust to environmental conditions, incorporating the potential variability linked to environmental effects in the initial calibration sets. The resulting models were then used for in-field analysis of ciprofloxacin and metronidazole tablet samples collected in three cities in Cameroon. The contents results obtained for each sample with the two strategies were close and not statistically different. Nevertheless, the first one is easier to implement and the second is the best regarding model diagnostic measures and accuracy profiles. Two samples were found to be noncompliant in terms of content, and these results were confirmed using high-performance liquid chromatography taken as the reference method. Chemometrics ; Partial least squares regression ; Calibration ; Near-infrared spectroscopy ; Computer science ; Field (mathematics) ; Environmental science ; Remote sensing ; Statistics ; Data mining ; Mathematics ; Machine learning ; Optics ; Geography Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Pesticide Residue Analysis and Safety
Authors: François Villamizar | Cédric Martel | Fabrice Boust | Shah Nawaz Burokur
Source: ACS Applied Electronic Materials (article, 2023-04-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Sparse Metasurfaces for Scattering Cross Section Reduction of Arbitrarily Shaped Metallic Bodies Reducing the scattering cross section (SCS) of metallic objects plays a key role in stealth technology. In this work, sparse metasurfaces are designed through numerical calculations of Green’s functions and are proposed to reduce the electromagnetic scattering of metallic cylinders. The metasurfaces are composed of relatively sparse meta-atoms, limited only by the impedance density without considering any resonance factor. The diameter of the metallic cylinders is of the order of one wavelength around the operating frequency of 5 GHz. By optimizing the load impedance distribution of the sparse metasurfaces coating the cylinders, the SCS of the cylinders can be considerably reduced. To experimentally demonstrate the concept, several prototypes are fabricated and tested in a microwave anechoic chamber. The experimental measurements are in good agreement with the numerical simulations and verify the consistent performance of the metasurfaces in SCS reduction. Scattering ; Anechoic chamber ; Materials science ; Reduction (mathematics) ; Cross section (physics) ; Electrical impedance ; Wavelength ; Microwave ; Coating ; Optics ; Radar cross-section ; Acoustics ; Physics ; Optoelectronics ; Composite material ; Geometry ; Mathematics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis