jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Colleen Partida | José Lucas Safanelli | Sadia Mannan Mitu | Mohammad Omar Faruk Murad | Yufeng Ge | Richard Ferguson | Keith Shepherd | Jonathan Sanderman
Source: Data in Brief (article, 2024-12-16)
Field: Chemistry — Analytical Chemistry

Building a near-infrared (NIR) soil spectral dataset and predictive machine learning models using a handheld NIR spectrophotometer This near-infrared spectral dataset consists of 2,106 diverse mineral soil samples scanned, on average, on six different units of the same low-cost commercially available handheld spectrophotometer. Most soil samples were selected from the USDA NRCS National Soil Survey Center-Kellogg Soil Survey Laboratory (NSSC-KSSL) soil archives to represent the diversity of mineral soils (0-30 cm) found in the United States, while 90 samples were selected from Ghana, Kenya, and Nigeria to represent available African soils in the same archive. All scanning was performed on dried and sieved (<2 mm) soil samples. Machine learning predictive models were developed for soil organic carbon (SOC), pH, bulk density (BD), carbonate (CaCO3), exchangeable potassium (Ex. K), sand, silt, and clay content from their spectra in the R programming language using most of this dataset (1,976 US soils) and are included in this data release. Two model types, Cubist and partial least squares regression (PLSR) were developed using two strategies: (1) using an average of the spectral scans across devices for each sample and, (2) using the replicate spectral scans across devices for each sample. We present the internal performance of these models here. The dry spectra and Cubist models for these soil properties are available for download from 10.5281/zenodo.7586621. An example of detailed code used to produce these models is hosted at the Open Soil Spectral Library, a free service of the Soil Spectroscopy for the Global Good Network (soilspectroscopy.org), enabling broad use of these data for multiple soil monitoring applications. Near-infrared spectroscopy ; Mobile device ; Computer science ; Research article ; Infrared ; Artificial intelligence ; Materials science ; Optics ; Physics ; World Wide Web Spectroscopy and Chemometric Analyses ; Soil Geostatistics and Mapping ; Mineral Processing and Grinding
Authors: Ning Li | Xuenan Liu | Hao Wang | Yingling Duan | Yu Zhang | Ping Zhou | Hao‐Fu Dai | Lan Tian
Source: Chinese Medicine (article, 2024-04-23)
Field: Chemistry — Organic Chemistry

“Qi Nan” agarwood restores podocyte autophagy in diabetic kidney disease by targeting EGFR signaling pathway The present study demonstrated that "QN" agarwood ameliorated renal injury in DKD by targeting EGFR and restoring podocyte autophagy. Podocyte ; Agarwood ; Albuminuria ; Medicine ; Kidney ; Glomerulosclerosis ; Cancer research ; Internal medicine ; Pharmacology ; Pathology ; Proteinuria Wood and Agarwood Research
Authors: Michael A. Klatt | Jaeuk Kim | Thomas E. Gartner | Salvatore Torquato
Source: The Journal of Chemical Physics (article, 2024-05-22)
Field: Materials Science — Materials Chemistry

Local number fluctuations in ordered and disordered phases of water across temperatures: Higher-order moments and degrees of tetrahedrality The isothermal compressibility (i.e., related to the asymptotic number variance) of equilibrium liquid water as a function of temperature is minimal under near-ambient conditions. This anomalous non-monotonic temperature dependence is due to a balance between thermal fluctuations and the formation of tetrahedral hydrogen-bond networks. Since tetrahedrality is a many-body property, it will also influence the higher-order moments of density fluctuations, including the skewness and kurtosis. To gain a more complete picture, we examine these higher-order moments that encapsulate many-body correlations using a recently developed, advanced platform for local density fluctuations. We study an extensive set of simulated phases of water across a range of temperatures (80-1600 K) with various degrees of tetrahedrality, including ice phases, equilibrium liquid water, supercritical water, and disordered nonequilibrium quenches. We find clear signatures of tetrahedrality in the higher-order moments, including the skewness and excess kurtosis, which scale for all cases with the degree of tetrahedrality. More importantly, this scaling behavior leads to non-monotonic temperature dependencies in the higher-order moments for both equilibrium and non-equilibrium phases. Specifically, under near-ambient conditions, the higher-order moments vanish most rapidly for large length scales, and the distribution quickly converges to a Gaussian in our metric. However, under non-ambient conditions, higher-order moments vanish more slowly and hence become more relevant, especially for improving information-theoretic approximations of hydrophobic solubility. The temperature non-monotonicity that we observe in the full distribution across length scales could shed light on water's nested anomalies, i.e., reveal new links between structural, dynamic, and thermodynamic anomalies. Order (exchange) ; Statistical physics ; Condensed matter physics ; Mathematics ; Physics ; Materials science ; Economics Material Dynamics and Properties ; Spectroscopy and Quantum Chemical Studies ; nanoparticles nucleation surface interactions
Authors: Bowen Xue | Yuanyuan KONG | Long Tian | Xue Wang | Xia Yao | Yan Zhu | Weixing Cao | Tao CHENG
Source: National Remote Sensing Bulletin (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Comparison between two types of fungal diseases in specific spectral responses and monitoring performance Biology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies
Authors: Nataporn Korprasertsak | Thananchai Leephakpreeda
Source: Heliyon (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Maximizing cooling/heating performance of thermoelectric modules across variable thermal loads via optimal control based on COP curves The thermoelectric module has high potential as a compact electrothermal actuator in the generation of cooling/heating effects without any moving part. However, one difficulty of the design is that the fundamental principles of optimal cooling/heating performance of thermoelectric modules are not yet fully understood and implemented. The purpose of this paper is to propose a mathematical optimization to gain insight and implement the most effective usages. In the proposed analysis, it is found that the coefficients of performance (COP) are dependent on the driving voltage and the ceramic-substrate temperatures of the thermoelectric module at both the cold and hot sides. The thermoelectric properties of a 91.2W thermoelectric module are used to simulate the proposed performance analysis to find the optimal driving voltage at desired operating temperatures at both sides on COP curves. The coefficient of determination R<sup>2</sup> of 0.9832 indicates strong agreement on the coefficients of performance between the analysis and the experiments under one hundred thirty-seven operating conditions. With the proposed methodology, the 91.2W thermoelectric module can be operated at the maximum coefficient of performance across variable thermal loads of airflow where the optimal driving voltage is determined from desired operating temperatures at both sides. Thermoelectric cooling ; Thermoelectric effect ; Coefficient of performance ; Thermoelectric generator ; Voltage ; Airflow ; Materials science ; Thermoelectric materials ; Thermal ; Mechanical engineering ; Control theory (sociology) ; Nuclear engineering ; Computer science ; Automotive engineering ; Electrical engineering ; Engineering ; Thermodynamics ; Control (management) ; Physics ; Heat pump Advanced Thermoelectric Materials and Devices ; Refrigeration and Air Conditioning Technologies ; Advanced Thermodynamics and Statistical Mechanics
Authors: In-Beom Jeong | Youngsub Lim
Source: Journal of Ocean Engineering and Technology (article, 2024-10-21)
Field: Materials Science — Materials Chemistry

Optimization of BOG Reliquefaction Process of Carbon Dioxide Considering Nitrogen Content As the importance of carbon capture and storage (CCS) technology increases for greenhouse gas reduction, CO2 transportation technology is also becoming crucial. Efficiently handling boil-off gas (BOG) generated during voyages is particularly important. This paper proposes a process incorporating two-stage separation and mixed refrigerants to reliquefy CO2 BOG containing nitrogen efficiently. This process was optimized based on specific power consumption (SPC) criteria and compared with the conventional single-stage separation using an ammonia refrigerant. The two-stage separation allows the removal of non-condensable gases, such as nitrogen, before expansion, and the use of mixed refrigerants enables more efficient heat exchange than ammonia refrigerants, improving the reliquefaction rate. As a result, the proposed process reduced SPC by up to 8.8 % with a nitrogen content of 5 mol% and up to 74.7 % with a nitrogen content of 15 mol%. In addition, the proposed process achieved a reliquefaction rate of over 74.2 % across all nitrogen content ranges of 5–15 mol%. Bog ; Carbon dioxide ; Nitrogen ; Environmental science ; Peat ; Process (computing) ; Environmental chemistry ; Chemistry ; Ecology ; Computer science ; Biology Catalytic Processes in Materials Science
Authors: Yiling Elaine Chen | Xinzhou Ge | Kyla Woyshner | MeiLu McDermott | Antigoni Manousopoulou | Scott B. Ficarro | Jarrod A. Marto | Kexin Li | Leo D. Wang | Jingyi Jessica Li
Source: Genomics Proteomics & Bioinformatics (article, 2024-04-01)
Field: Chemistry — Spectroscopy

APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate (FDR). To fill in this gap, we proposed a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR. Identification (biology) ; False discovery rate ; Computer science ; Database search engine ; Proteomics ; Computational biology ; Data mining ; Algorithm ; Information retrieval ; Search engine ; Biology ; Biochemistry Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Bioinformatics and Genomic Networks
Authors: J. Walkowiak | M. Hoppe | I. Ekmark | A. Jardin | J. Bielecki | K. Król | Y. Peysson | D. Mazon | D. Dworak | M. Scholz
Source: Nuclear Fusion (article, 2024-01-31)
Field: Materials Science — Materials Chemistry

First numerical analysis of runaway electron generation in tungsten-rich plasmas towards ITER Abstract The disruption and runaway electron analysis model code was extended to include tungsten impurities in disruption simulations with the aim of studying the runaway electron (RE) generation. This study investigates RE current sensitivity on the following plasma parameters and modelling choices: tungsten concentration, magnetic perturbation strength, electron modelling, thermal quench time and tokamak geometry—ITER-like or ASDEX-like. Our investigation shows that a tungsten concentration below 10 −3 does not cause significant RE generation on its own. However, at higher concentrations it is possible to reach a very high RE current. Out of the two tested models of electrons in plasma: fluid and isotropic (kinetic), results from the fluid model are more conservative, which is useful when it comes to safety analysis. However, these results are overly pessimistic when compared to the isotropic model, which is based on a more reliable approach. Our results also show that the hot-tail RE generation mechanism is dominant as a primary source of RE in tungsten induced disruptions, usually providing orders of magnitude higher RE seed than Dreicer generation. We discuss best practices for simulations with tungsten-rich plasma, present the dependence of the safety limits on modelling choices and highlight the biggest shortcoming of the current simulation techniques. The obtained results pave the way for a wider analysis of tungsten impact on the disruption dynamics, including the mitigation techniques for ITER in the case of strong contamination of the plasma with tungsten. Plasma ; Tungsten ; Tokamak ; Electron ; Nuclear engineering ; Materials science ; Atomic physics ; Nuclear physics ; Physics Fusion materials and technologies ; Magnetic confinement fusion research ; Laser-Plasma Interactions and Diagnostics
Authors: Julius Juhyun Chung | Hahnsung Kim | Yang Ji | Dongshuang Lu | Iris Y. Zhou | Phillip Zhe Sun
Source: Magnetic Resonance in Medicine (article, 2024-09-02)
Field: Materials Science — Materials Chemistry

Improving standardization and accuracy of in vivo omega plot exchange parameter determination using rotating‐frame model‐based fitting of quasi‐steady‐state Z‐spectra The model-based fitting of QUASS CEST Z-spectra enables consistent and accurate quantification of exchange parameters through Ω-plot construction by reducing error due to signal overlap and nonequilibrium CEST effects. In vivo ; Plot (graphics) ; Spectral line ; Nuclear magnetic resonance ; Steady state (chemistry) ; Chemistry ; Curve fitting ; Biological system ; Analytical Chemistry (journal) ; Physics ; Mathematics ; Statistics ; Chromatography ; Physical chemistry Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies
Authors: Daniele Carosi | Fabiana Zama | Alessandro Morri | Lorella Ceschini
Source: Mathematics and Computers in Simulation (article, 2024-03-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Linearising anhysteretic magnetisation curves: A novel algorithm for finding simulation parameters and magnetic moments This paper proposes a new method for determining the simulation parameters of the Jiles–Atherton Model used to simulate the first magnetisation curve and hysteresis loop in ferromagnetic materials. The Jiles–Atherton Model is an important tool in engineering applications due to its relatively simple differential formulation. However, determining the simulation parameters for the anhysteretic curve is challenging. Several methods have been proposed, primarily based on mathematical aspects of the anhysteretic and first magnetisation curves and hysteresis loops. This paper focuses on finding the magnetic moments of the material, which are used to define the simulation parameters for its anhysteretic curve. The proposed method involves using the susceptibility of the material and a linear approximation of a paramagnet to find the magnetic moments. The simulation parameters can then be found based on the magnetic moments. The method is validated theoretically and experimentally and offers a more physical approach to finding simulation parameters for the anhysteretic curve and a simplified way of determining the magnetic moments of the material. Magnetization ; Hysteresis ; Magnetic hysteresis ; Magnetic moment ; Ferromagnetism ; Paramagnetism ; Computer science ; Algorithm ; Physics ; Condensed matter physics ; Magnetic field Magnetic Properties and Applications ; Magnetic properties of thin films ; Electric Motor Design and Analysis
Authors: Saori Takeyama | Tomoaki Watanabe | Nanxin Gong | Masahiro Yamaguchi | Takumi Urata | Fumikazu Kimura | Keiko Ishii
Source: Journal of Medical Imaging (article, 2024-12-28)
Field: Chemistry — Analytical Chemistry

Dye amount quantification of Papanicolaou-stained cytological images by multispectral unmixing: spectral analysis of cytoplasmic mucin Multispectral imaging enables the quantitative analysis of dye amount maps of Papanicolaou-stained cytology specimens. The effectiveness is demonstrated in interpreting and classifying the cytoplasmic mucin of EC and LEGH cells in cervical cytology. Papanicolaou stain ; Multispectral image ; Medicine ; Staining ; Stain ; Pathology ; Cytology ; Papanicolaou Test ; Cervical cancer ; Remote sensing Spectroscopy and Chemometric Analyses ; AI in cancer detection ; Digital Imaging for Blood Diseases
Authors: Muhammad Bilal | Masad A. Alrasheedi | Muhammad Aamir | Saleem Abdullah | Siti Mariam Norrulashikin | Reza Rezaiy
Source: Scientific Reports (article, 2024-12-02)
Field: Chemistry — Analytical Chemistry

Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models A significant portion of the world's population relies on rice as a primary source of nutrition. In Malaysia, rice production began in the early 1960s, which led to the cultivation of the country's most significant food crop up till the present day. Research on various aspects of the price and production of rice has been done by various methods in the past. In this study, we have adopted novel multivariate fuzzy time series models (MFTS) i.e. fuzzy vector autoregressive models (FVAR) alongside conventional vector autoregressive model (VAR) for assessing rice price and production using a dataset from the Malaysian Agricultural Research and Development Institute (MERDI). The proposed method(s) especially with the usage of Trapezoidal Fuzzy Numbers (TrFNs) have commendable accuracy with great future forecasts over the VAR model. The model selection was made by the least MAPE with the corresponding highest Relative Efficiency as criteria. The study fills the gap in applying advanced fuzzy models for rice forecasting, aiming to improve accuracy using fuzzy vector autoregressive (FVAR) models with Triangular Fuzzy Numbers (TFNs) and Trapezoidal Fuzzy Numbers (TrFNs) over traditional VAR models. The study's findings imply that the enhanced forecasting accuracy of FVAR models with Trapezoidal Fuzzy Numbers (TrFNs) can significantly assist local farmers and stakeholders in making informed decisions about production and pricing. This improved forecasting capability is expected to promote business growth within the Malaysian market and facilitate increased rice exports, ultimately contributing to the country's economic prosperity. Autoregressive model ; Fuzzy logic ; Production (economics) ; Multivariate statistics ; Econometrics ; Computer science ; Time series ; Population ; Statistics ; Mathematics ; Operations research ; Economics ; Artificial intelligence ; Microeconomics Spectroscopy and Chemometric Analyses ; Stock Market Forecasting Methods
Authors: GuoZheng NIE | MingXin XIE | ZongLin LI | ZhiQuan CHEN | DeQiong LI | Hui XU | LinFeng LAN
Source: Zhongguo kexue. Wulixue Lixue Tianwenxue (article, 2024-08-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optical absorption modulation and image display capabilities of all-dielectric metasurface featuring integrated graphene <p indent="0mm">Perfect absorption in monolayer two-dimensional (2D) materials is critical for the next generation of on-chip devices. However, absorption mechanisms based on surface plasmon polaritons (SPPs) and Fabry-Perot cavities (FPCs) are limited by tuning capability, low stability, and complex fabrication processes. Bound states in the continuum (BICs) are considered ideal platforms for enhancing light-matter interactions. In this context, we propose an all-dielectric metasurface that supports symmetry-protected bound states in the continuum (SP-BIC) in the near-infrared spectral region. By breaking the symmetry of the metasurface, it is transformed into the quasi-bound state in the continuum (qBIC) with exceptional quality factors (<italic>Q</italic>-factor), while monolayer graphene is introduced into the system to form a critically coupled absorption system. Remarkably, we achieved a modulation efficiency of 93.8% for light absorption by solely controlling the polarization angle of the incident wave without altering the structural parameters. Based on this graphene-metasurface ideal absorber, optical digital “0-1” switching and metasurface image display functionalities have been successfully achieved, and they hold promise to provide theoretical guidance for next-generation integrated optical components on chips. Philosophy Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Thermal Radiation and Cooling Technologies
Authors: Yongxue Qiu | Liangui Deng | Yujie Zhan | Gongfa Li | Jianguo Guan
Source: Micromachines (article, 2024-04-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The Effect of Height Error on Performance of Propagation Phase-Based Metalens Metalenses, as a new type of planar optical device with flexible design, play an important role in miniaturized and integrated optical devices. Propagation phase-based metalenses, known for their low loss and extensive design flexibility, are widely utilized in optical imaging and optical communication. However, fabrication errors introduced by thin-film deposition and etching processes inevitably result in variations in the height of the metalens structure, leading to the fabricated devices not performing as expected. Here, we introduce a reflective TiO<sub>2</sub> metalens based on the propagation phase. Then, the relationship between the height variation and the performance of the metalens is explored by using the maximum phase error. Our results reveal that the height error of the unit structure affects the phase rather than the amplitude. The focusing efficiency of our metalens exhibits robustness to structural variations, with only a 5% decrease in focusing efficiency when the height varies within ±8% of the range. The contents discussed in this paper provide theoretical guidance for the unit design of the propagation phase-based metalens and the determination of its allowable fabrication error range, which is of great significance for low-cost and high-efficiency manufacturing. Fabrication ; Robustness (evolution) ; Materials science ; Phase (matter) ; Planar ; Optics ; Flexibility (engineering) ; Propagation of uncertainty ; Amplitude ; Optoelectronics ; Computer science ; Physics ; Chemistry ; Mathematics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Optical Coatings and Gratings