jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mauritz Kop
Source: Digital Society (article, 2023-05-26)
Field: Materials Science — Surfaces, Coatings and Films

Quantum-ELSPI: A Novel Field of Research Field (mathematics) ; Quantum ; Computer science ; Physics ; Quantum mechanics ; Mathematics ; Pure mathematics Electron and X-Ray Spectroscopy Techniques ; Electrochemical Analysis and Applications ; Quantum Information and Cryptography
Authors: Vincenzo Barone | Silvia Di Grande | Cristina Puzzarini
Source: Molecules (article, 2023-01-16)
Field: Chemistry — Spectroscopy

Toward Accurate yet Effective Computations of Rotational Spectroscopy Parameters for Biomolecule Building Blocks The interplay of high-resolution rotational spectroscopy and quantum-chemical computations plays an invaluable role in the investigation of biomolecule building blocks in the gas phase. However, quantum-chemical methods suffer from unfavorable scaling with the dimension of the system under consideration. While a complete characterization of flexible systems requires an elaborate multi-step strategy, in this work, we demonstrate that the accuracy obtained by quantum-chemical composite approaches in the prediction of rotational spectroscopy parameters can be approached by a model based on density functional theory. Glycine and serine are employed to demonstrate that, despite its limited cost, such a model is able to predict rotational constants with an accuracy of 0.3% or better, thus paving the way toward the accurate characterization of larger flexible building blocks of biomolecules. Biomolecule ; Characterization (materials science) ; Computation ; Quantum chemical ; Quantum ; Spectroscopy ; Scaling ; Density functional theory ; Rotational spectroscopy ; Computer science ; Biological system ; Nanotechnology ; Statistical physics ; Chemistry ; Materials science ; Computational chemistry ; Physics ; Molecule ; Algorithm ; Mathematics ; Quantum mechanics Molecular Spectroscopy and Structure ; Advanced Chemical Physics Studies ; Spectroscopy and Laser Applications
Authors: Jinji Sun | Jianyi Ren | Jin Li | Yuejing Huang
Source: Materials (article, 2023-04-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Measurement and Analysis of Magnetic Properties of Permalloy for Magnetic Shielding Devices under Different Temperature Environments The relative permeability, coercivity, and remanence of permalloy are closely related to the performance of magnetic shielding devices. In this paper, the relationship between the magnetic properties of permalloy and the working temperature of magnetic shielding devices is measured. Firstly, the measurement method of permalloy properties based on the simulated impact method is analyzed. What is more, a magnetic property test system consisting of a soft magnetic material tester and a high-low temperature chamber for permalloy ring samples at different temperatures was established to measure DC and AC (0.01 Hz to 1 kHz) magnetic properties at different temperatures (-60 °C to 140 °C). Finally, the results show that compared with room temperature (25 °C), the initial permeability (μi) decreases by 69.64% at -60 °C and increases by 38.23% at 140 °C, and the coercivity (hc) decreases by 34.81% at -60 °C and increases by 8.93% at 140 °C, which are the key parameters in the magnetic shielding device. It can be concluded that the relative permeability and remanence of permalloy are positively correlated with temperature, while the saturation magnetic flux density and coercivity are negatively correlated with temperature. This paper is of great significance to the magnetic analysis and design of magnetic shielding devices. Permalloy ; Electromagnetic shielding ; Materials science ; Composite material ; Condensed matter physics ; Magnetic field ; Magnetization ; Physics Magnetic Properties of Alloys ; Nuclear Physics and Applications ; Magnetic Field Sensors Techniques
Authors: Chuin Wei Tan | Chris J. Pickard | William C. Witt
Source: The Journal of Chemical Physics (article, 2023-03-23)
Field: Materials Science — Materials Chemistry

Automatic differentiation for orbital-free density functional theory Differentiable programming has facilitated numerous methodological advances in scientific computing. Physics engines supporting automatic differentiation have simpler code, accelerating the development process and reducing the maintenance burden. Furthermore, fully differentiable simulation tools enable direct evaluation of challenging derivatives-including those directly related to properties measurable by experiment-that are conventionally computed with finite difference methods. Here, we investigate automatic differentiation in the context of orbital-free density functional theory (OFDFT) simulations of materials, introducing PROFESS-AD. Its automatic evaluation of properties derived from first derivatives, including functional potentials, forces, and stresses, facilitates the development and testing of new density functionals, while its direct evaluation of properties requiring higher-order derivatives, such as bulk moduli, elastic constants, and force constants, offers more concise implementations than conventional finite difference methods. For these reasons, PROFESS-AD serves as an excellent prototyping tool and provides new opportunities for OFDFT. Density functional theory ; Computer science ; Physics ; Quantum mechanics Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; X-ray Diffraction in Crystallography
Authors: Maud Formanek | Salvatore Torquato | Roberto Car | Fausto Martelli
Source: The Journal of Physical Chemistry B (article, 2023-04-11)
Field: Materials Science — Materials Chemistry

Molecular Rotations, Multiscale Order, Hyperuniformity, and Signatures of Metastability during the Compression/Decompression Cycles of Amorphous Ices We model, via large-scale molecular dynamics simulations, the isothermal compression of low-density amorphous ice (LDA) to generate high-density amorphous ice (HDA) and the corresponding decompression extending to negative pressures to recover the low-density amorphous phase (LDA<sub><i>HDA</i></sub>). Both LDA and HDA are nearly hyperuniform and are characterized by a dynamical HBN, showing that amorphous ices are nonstatic materials and implying that nearly hyperuniformity can be accommodated in dynamical networks. In correspondence with both the LDA-to-HDA and the HDA-to-LDA<sub><i>HDA</i></sub> phase transitions, the (partial) activation of rotational degrees of freedom activates a cascade effect that induces a drastic change in the connectivity and a pervasive reorganization of the HBN topology which, ultimately, break the samples' hyperuniform character. Key to this effect is the rapid rate at which changes occur, and not their magnitude. The inspection of structural properties from the short- to the long-range shows that signatures of metastability are present at all length-scales, hence providing further solid evidence in support of the liquid-liquid critical point scenario. LDA and LDA<sub><i>HDA</i></sub> differ in terms of HBN and structural properties, implying that they are distinct low-density glasses. Our work unveils the role of molecular rotations in the phase transitions between amorphous ices and shows how the unfreezing of rotational degrees of freedom generates a cascade effect that propagates over multiple length-scales. Our findings greatly improve our basic understanding of water and amorphous ices and can potentially impact the field of molecular network-forming materials at large. Metastability ; Amorphous solid ; Molecular dynamics ; Amorphous ice ; Chemical physics ; Cascade ; Phase (matter) ; Phase transition ; Materials science ; Isothermal process ; Physics ; Chemistry ; Crystallography ; Thermodynamics ; Quantum mechanics Material Dynamics and Properties ; Theoretical and Computational Physics ; High-pressure geophysics and materials
Authors: Xiaofeng Wu | Yi‐Kai Liu | Anton Iliuk | W. Andy Tao
Source: TrAC Trends in Analytical Chemistry (article, 2023-04-24)
Field: Chemistry — Spectroscopy

Mass spectrometry-based phosphoproteomics in clinical applications Phosphoproteomics ; Extracellular vesicles ; Phosphorylation ; Computational biology ; Proteomics ; Identification (biology) ; Protein phosphorylation ; Mass spectrometry ; Chemistry ; Bioinformatics ; Biology ; Cell biology ; Biochemistry ; Chromatography Advanced Proteomics Techniques and Applications ; Extracellular vesicles in disease ; Mass Spectrometry Techniques and Applications
Authors: Zhangzhi Xue | Tiansheng Zhu | Fangfei Zhang | Cheng Zhang | Nan Xiang | Liujia Qian | Xiao Yi | Yaoting Sun | Wei Liu | Xue Cai | Linyan Wang | Xizhe Dai | Yue Liang | Lu Li | Thang V. Pham | Sander R. Piersma | Qi Xiao | Meng Luo | Cong Lu | J. Zhu | Yongfu Zhao | Guangzhi Wang | Junhong Xiao | Tong Liu | Zhiyu Liu | Yi He | Qi‐Jun Wu | Ting‐Ting Gong | Jianqin Zhu | Zhiguo Zheng | Juan Ye | Yan Li | Connie R. Jiménez | Jun Arita | Tiannan Guo
Source: Patterns (article, 2023-07-01)
Field: Chemistry — Spectroscopy

DPHL v.2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v.1, a previous pan-human library built from 1,096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying of 10,943 proteins. Here, we generated DPHL v.2 from 1,608 DDA-MS data. The data included 586 DDA-MS data acquired from 18 tissue types, while 1,022 files were derived from DPHL v.1. DPHL v.2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v.2 to include semi-tryptic peptides and protein isoforms. DPHL v.2 was then applied to two colorectal cancer cohorts. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v.1. Our findings show that the increased human proteome coverage of DPHL v.2 provides larger pools of potential protein biomarkers. Human proteome project ; Proteomics ; Proteome ; Biomarker ; Biomarker discovery ; Human breast ; Computational biology ; Prostate cancer ; Cancer ; Bioinformatics ; Biology ; Oncology ; Breast cancer ; Medicine ; Internal medicine ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Qiang Liu | Zhongliang Gong | Dapeng Li | Tao Wen | Jinwei Guan | Wenfeng Zheng
Source: Molecules (article, 2023-08-08)
Field: Chemistry — Analytical Chemistry

Rapid and Low-Cost Quantification of Adulteration Content in Camellia Oil Utilizing UV-Vis-NIR Spectroscopy Combined with Feature Selection Methods This study aims to explore the potential use of low-cost ultraviolet-visible-near infrared (UV-Vis-NIR) spectroscopy to quantify adulteration content of soybean, rapeseed, corn and peanut oils in <i>Camellia</i> oil. To attain this aim, test oil samples were firstly prepared with different adulterant ratios ranging from 1% to 90% at varying intervals, and their spectra were collected by an in-house built experimental platform. Next, the spectra were preprocessed using Savitzky-Golay (SG)-Continuous Wavelet Transform (CWT) and the feature wavelengths were extracted using four different algorithms. Finally, Support Vector Regression (SVR) and Random Forest (RF) models were developed to rapidly predict adulteration content. The results indicated that SG-CWT with decomposition scale of 2<sup>5</sup> and the Iterative Variable Subset Optimization (IVSO) algorithm can effectively improve the accuracy of the models. Furthermore, the SVR model performed best for predicting adulteration of camellia oil with soybean oil, while the RF models were optimal for camellia oil adulterated with rapeseed, corn, or peanut oil. Additionally, we verified the models' robustness by examining the correlation between the absorbance and adulteration content at certain feature wavelengths screened by IVSO. This study demonstrates the feasibility of using low-cost UV-Vis-NIR spectroscopy for the authentication of <i>Camellia</i> oil. Camellia ; Adulterant ; Rapeseed ; Camellia oleifera ; Feature selection ; Near-infrared spectroscopy ; Correlation coefficient ; Mathematics ; Biological system ; Pattern recognition (psychology) ; Artificial intelligence ; Chemistry ; Computer science ; Food science ; Chromatography ; Statistics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Said Nawar | Elsayed Said Mohamed | Safa Essam-Eldeen Sayed | Wagih S. Mohamed | Nazih Y. Rebouh | A. Hammam
Source: Frontiers in Environmental Science (article, 2023-07-17)
Field: Chemistry — Analytical Chemistry

Estimation of key potentially toxic elements in arid agricultural soils using Vis-NIR spectroscopy with variable selection and PLSR algorithms Potentially toxic elements (PTEs) pose a significant threat to soil and the environment. Therefore, the fast quantification of PTEs is crucial for better management of contaminated sites. Versatile technique such as Visible near-infrared spectroscopy (Vis–NIRS) (350–2,500 nm) has attracted tremendous attention for assessing PTEs and has achieved promising results combined with successful multivariate analysis. This research investigated the potential of Vis–NIRS combined with partial least squares regression (PLSR) and variable selection methods to assess key PTEs (Cd, Co, Cu, Cr, Pb, and Zn) in agricultural soils under arid conditions. The soil samples (80) were collected from a polluted area around Al-Moheet drainage, Minya Governorate–upper Egypt. The samples were scanned using an ASD FieldSpec-4 spectroradiometer. Simulated annealing (SA) and uninformative variable elimination (UVE) were used to select the effective wavelengths in predicting PTEs. PLSR was used to develop the spectral models using the full range (FR-PLS) and feature-selected spectra techniques SA (SA-PLS) and UVE (UVE-PLS). The results indicated that UVE-PLS models performed better than FR-PLS and SA-PLS models in predicting the key PTEs. The obtained coefficient of determination (R 2 ) and the ratio of performance to deviation (RPD) were 0.74 and 2.48 (Cr), 0.72 and 2.03 (Pb), 0.62 and 1.86 (Cd), 0.59 and 1.78 (Cu), 0.52 and 1.68 (Co), and 0.46 and 1.41 (Zn), respectively. The results suggested that the UVE-PLS spectral model is promising for predicting Cr, Pb, and Cd, and can be improved for predicting Cu, Co, and Zn elements in agricultural soils. Partial least squares regression ; Variable elimination ; Feature selection ; Spectroradiometer ; Soil water ; Soil test ; Coefficient of determination ; Environmental science ; Environmental chemistry ; Chemistry ; Soil science ; Mathematics ; Statistics ; Computer science ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Geochemistry and Geologic Mapping ; Mineral Processing and Grinding
Authors: Ghulam Mustafa | Hengbiao Zheng | Wei Li | Yuming Yin | Yongqing Wang | Meng Zhou | Peng Liu | Muhammad Bilal | Haiyan Jia | Guoqiang Li | Tao Cheng | Yongchao Tian | Weixing Cao | Yan Zhu | Xia Yao
Source: Frontiers in Plant Science (article, 2023-01-16)
Field: Chemistry — Analytical Chemistry

Fusarium head blight monitoring in wheat ears using machine learning and multimodal data from asymptomatic to symptomatic periods The growth of the fusarium head blight (FHB) pathogen at the grain formation stage is a deadly threat to wheat production through disruption of the photosynthetic processes of wheat spikes. Real-time nondestructive and frequent proxy detection approaches are necessary to control pathogen propagation and targeted fungicide application. Therefore, this study examined the ch\lorophyll-related phenotypes or features from spectral and chlorophyll fluorescence for FHB monitoring. A methodology is developed using features extracted from hyperspectral reflectance (HR), chlorophyll fluorescence imaging (CFI), and high-throughput phenotyping (HTP) for asymptomatic to symptomatic disease detection from two consecutive years of experiments. The disease-sensitive features were selected using the Boruta feature-selection algorithm, and subjected to machine learning-sequential floating forward selection (ML-SFFS) for optimum feature combination. The results demonstrated that the biochemical parameters, HR, CFI, and HTP showed consistent alterations during the spike-pathogen interaction. Among the selected disease sensitive features, reciprocal reflectance (RR=1/700) demonstrated the highest coefficient of determination (<i>R</i> <sup>2</sup>) of 0.81, with root mean square error (RMSE) of 11.1. The multivariate k-nearest neighbor model outperformed the competing multivariate and univariate models with an overall accuracy of <i>R</i> <sup>2</sup> = 0.92 and RMSE = 10.21. A combination of two to three kinds of features was found optimum for asymptomatic disease detection using ML-SFFS with an average classification accuracy of 87.04% that gradually improved to 95% for a disease severity level of 20%. The study demonstrated the fusion of chlorophyll-related phenotypes with the ML-SFFS might be a good choice for crop disease detection. Univariate ; Hyperspectral imaging ; Pattern recognition (psychology) ; Mean squared error ; Artificial intelligence ; Feature selection ; Biology ; Feature (linguistics) ; Multivariate statistics ; Computer science ; Statistics ; Mathematics Spectroscopy and Chemometric Analyses ; Mycotoxins in Agriculture and Food ; Plant Pathogens and Fungal Diseases
Authors: Fenghua Yu | Juchi Bai | Zhongyu Jin | Honggang Zhang | Jiaxin Yang | Tongyu Xu
Source: Frontiers in Plant Science (article, 2023-03-22)
Field: Chemistry — Analytical Chemistry

Estimating the rice nitrogen nutrition index based on hyperspectral transform technology The logarithmic difference transformation of the spectrum can effectively improve the estimation accuracy of the NNI estimation model, providing a new approach for improving NNI estimation methods based on hyperspectral technology. Hyperspectral imaging ; Mean squared error ; Mathematics ; Spectral index ; Canopy ; Logarithm ; Autoencoder ; Remote sensing ; Transformation (genetics) ; Artificial intelligence ; Statistics ; Computer science ; Spectral line ; Botany ; Chemistry ; Artificial neural network ; Biology ; Physics ; Geography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Water Quality Monitoring and Analysis
Authors: Haneen A. Basheer | Maram A. Alhusban | Ahlam Zaid Alkilani | Anas Alshishani | Lina Elsalem | Kamyar Afarinkia
Source: Cancers (article, 2023-10-16)
Field: Materials Science — Biomaterials

Niosomal Delivery of Celecoxib and Metformin for Targeted Breast Cancer Treatment Breast cancer continues to be a prominent worldwide health concern and requires continued investigation into innovative therapeutic approaches. Here, we report the first investigation into the therapeutic efficacy of combining Metformin (MET) and Celecoxib (CXB), both in free and niosomal form, for the treatment of breast cancer. Our investigation encompassed the characterization of these niosomal drug carriers, their stability assessment, and their effect on breast cancer cell models. The thin-film hydration technique was employed to prepare niosomes with spherical, uniform-size distributions and high encapsulation efficiencies. The niosomes were characterized by TEM, particle size analyzer, and ATR-FTIR. The niosomes with an average size of 110.6 ± 0.6 and 96.7 ± 0.7, respectively, for MET and CXB were stable when stored at 4 °C for three months with minimal drug leakage, minor changes in encapsulation efficiency and size, and unchanged physicochemical parameters. Evaluation in two-dimensional (2D) and three-dimensional (3D) viability assays demonstrated an increased cytotoxicity of encapsulated drugs when compared to their free-drug counterparts. Additionally, the combination of Metformin Niosomal Particles (MET NPs) and Celecoxib Niosomal Particles (CXB NPs) led to decreased cell viability in both 2D and 3D models compared to each drug administered individually. When comparing the effect of the niosomal versus the free combination of the drugs on cell migration, we found that both interventions effectively prevented cell migration. However, the efficacy of the niosomes' combination was not superior to that of the free drug combination (<i>p</i> < 0.05). In conclusion, the results of this study provide valuable insights into the potential application of combining MET and CXB nanoparticle delivery systems to breast cancer treatment. Exploring the in vivo application of this drug delivery system could open new avenues for more effective and targeted therapeutic approaches for breast cancer patients. Celecoxib ; Metformin ; Medicine ; Breast cancer ; Oncology ; Cancer ; Internal medicine ; Pharmacology ; Insulin Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery ; Click Chemistry and Applications
Authors: Jing Cui | Yu Zhao | Casey Sun | Junzhong Xu | Zhongliang Zu
Source: Magnetic Resonance in Medicine (article, 2023-04-24)
Field: Materials Science — Materials Chemistry

Evaluation of contributors to amide proton transfer<scp>–</scp>weighted imaging and nuclear Overhauser enhancement<scp>–</scp>weighted imaging contrast in tumors at a high magnetic field CESTR reflects a combined effect of T<sub>1</sub> weighting and CEST/NOE. Both factors depend on f<sub>s</sub> , which contributes positively to the dependence of CESTR on f<sub>s</sub> in APT imaging and enhances its correlation with f<sub>s</sub> . In contrast, these factors have opposite contributions to its dependence on f<sub>s</sub> in NOE (-3.5) imaging, thereby weakening the correlation. Magnetization transfer ; Chemistry ; Nuclear magnetic resonance ; Nuclear Overhauser effect ; Contrast (vision) ; Weighting ; Correlation ; Flip angle ; Nuclear magnetic resonance spectroscopy ; Magnetic resonance imaging ; Physics ; Medicine ; Mathematics Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies
Authors: Vanessa Rück | Mikkel Baldtzer Liisberg | Christian Brinch Mollerup | Yan‐Mei He | Junsheng Chen | Cecilia Cerretani | Tom Vosch
Source: Angewandte Chemie International Edition (article, 2023-08-14)
Field: Materials Science — Materials Chemistry

A DNA‐Stabilized Ag<sub>18</sub><sup>12+</sup> Cluster with Excitation‐Intensity‐Dependent Dual Emission Abstract DNA‐stabilized silver nanoclusters (DNA‐AgNCs) are easily tunable emitters with intriguing photophysical properties. Here, a DNA‐AgNC with dual emission in the red and near‐infrared (NIR) regions is presented. Mass spectrometry data showed that two DNA strands stabilize 18 silver atoms with a nanocluster charge of 12+. Besides determining the composition and charge of DNA 2 [Ag 18 ] 12+ , steady‐state and time‐resolved methods were applied to characterize the picosecond red fluorescence and the relatively intense microsecond‐lived NIR luminescence. During this process, the luminescence‐to‐fluorescence ratio was found to be excitation‐intensity‐dependent. This peculiar feature is very rare for molecular emitters and allows the use of DNA 2 [Ag 18 ] 12+ as a nanoscale excitation intensity probe. For this purpose, calibration curves were constructed using three different approaches based either on steady‐state or time‐resolved emission measurements. The results showed that processes like thermally activated delayed fluorescence (TADF) or photon upconversion through triplet‐triplet annihilation (TTA) could be excluded for DNA 2 [Ag 18 ] 12+ . We, therefore, speculate that the ratiometric excitation intensity response could be the result of optically activated delayed fluorescence. Excitation ; Emission intensity ; Intensity (physics) ; Cluster (spacecraft) ; Atomic physics ; Materials science ; Chemistry ; Physics ; Optics Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques