jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Osamu Matsuda | Yoshinori Ohara
Source: PLoS ONE (article, 2023-09-20)
Field: Chemistry — Analytical Chemistry

Last-percent improvement in eligibility rates of crop seeds based on quality evaluation using near-infrared imaging spectrometry As the world population continues to grow, the need for high-quality crop seeds that promise stable food production is increasing. Conversely, excessive demand for high quality is causing “seed loss and waste” due to slight shortfalls in eligibility rates. In this study, we applied near-infrared imaging spectrometry combined with machine learning techniques to evaluate germinability and paternal haplotype in crop seeds from 6 species and 8 cultivars. Candidate discriminants for quality evaluation were derived by linear sparse modeling using the seed reflectance spectra as explanatory variables. To systematically proceed with model selection, we defined the sorting condition where the recovery rate of seeds matches the initial eligibility rate ( iP ) as “standard condition”. How much the eligibility rate after sorting ( P ) increases from iP under this condition offers a reasonable criterion for ranking candidate models. Moreover, the model performance under conditions with adjusted discrimination strength was verified using a metric “relative precision” ( rP ) defined as ( P–iP )/(1 –iP ). Because rP , compared to precision (= P ), is less dependent on iP in relation to recall ( R ), i.e., recovery rate of eligible seeds, the rP-R curve and area under the curve also offer useful criteria for spotting better discriminant models. We confirmed that the batches of seeds given higher discriminant scores by the models selected with reference to these criteria were more enriched with eligible seeds. The method presented can be readily implemented in developing a sorting device that enables “last-percent improvement” in eligibility rates of crop seeds. Ranking (information retrieval) ; Metric (unit) ; Sorting ; Statistics ; Crop ; Linear discriminant analysis ; Mathematics ; Population ; Computer science ; Biotechnology ; Artificial intelligence ; Biology ; Medicine ; Algorithm ; Agronomy ; Engineering ; Operations management Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Genetics and Plant Breeding
Authors: Noriaki Minami | Donghyun Hong | Céline Taglang | Georgios Batsios | Anne Marie Gillespie | Pavithra Viswanath | Nicholas Stevers | Carter J. Barger | J Costello | Sabrina M. Ronen
Source: Scientific Reports (article, 2023-03-30)
Field: Chemistry — Spectroscopy

Hyperpolarized δ-[1- 13C]gluconolactone imaging visualizes response to TERT or GABPB1 targeting therapy for glioblastoma TERT promoter mutations are a hallmark of glioblastoma (GBM). Accordingly, TERT and GABPB1, a subunit of the upstream mutant TERT promoter transcription factor GABP, are being considered as promising therapeutic targets in GBM. We recently reported that the expression of TERT or GABP1 modulates flux via the pentose phosphate pathway (PPP). Here, we investigated whether <sup>13</sup>C magnetic resonance spectroscopy (MRS) of hyperpolarized (HP) δ- [1-<sup>13</sup>C]gluconolactone can serve to image the reduction in PPP flux following TERT or GABPB1 silencing. We investigated two different human GBM cell lines stably expressing shRNAs targeting TERT or GABPB1, as well as doxycycline-inducible shTERT or shGABPB1cells. MRS studies were performed on live cells and in vivo tumors, and dynamic sets of <sup>13</sup>C MR spectra were acquired following injection of HP δ-[1-<sup>13</sup>C]gluconolactone. HP 6-phosphogluconolactone (6PG), the product of δ-[1-<sup>13</sup>C]gluconolactone via the PPP, was significantly reduced in TERT or GABPB1-silenced cells or tumors compared to controls in all our models. Furthermore, a positive correlation between TERT expression and 6PG levels was observed. Our data indicate that HP δ-[1-<sup>13</sup>C]gluconolactone, an imaging tool with translational potential, could serve to monitor TERT expression and its silencing with therapies that target either TERT or GABPB1 in mutant TERT promoter GBM patients. Gene silencing ; Cancer research ; Mutant ; Glioblastoma ; Chemistry ; In vivo ; Cell culture ; Molecular biology ; Biology ; Gene ; Biochemistry ; Genetics Advanced NMR Techniques and Applications ; Electron Spin Resonance Studies ; Solid-state spectroscopy and crystallography
Authors: Zhihao Gao | A. Solders | Ali Al-Adili | O. Beliuskina | T. Eronen | A. Kankainen | M. Lantz | I. D. Moore | D. A. Nesterenko | H. Penttilä | S. Pomp | Henrik Sjöstrand | the IGISOL team
Source: The European Physical Journal A (article, 2023-07-25)
Field: Chemistry — Spectroscopy

Applying machine learning methods for the analysis of two-dimensional mass spectra In a measurement of isomeric yield-ratios in fission, the Phase-Imaging Ion-Cyclotron-Resonance technique, which projects the radial motions of ions in the Penning trap (JYFLTRAP) onto a position-sensitive micro-channel plate detector, has been applied. To obtain the yield ratio, that is the relative population of two states of an isomer pair, a novel analysis procedure has been developed to determine the number of detected ions in each state, as well as corrections for the detector efficiency and decay losses. In order to determine the population of the states in cases where their mass difference is too small to reach full separation, a Bayesian Gaussian Mixture model was implemented. The position-dependent efficiency of the micro-channel plate detector was calibrated by mapping it with <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow></mml:mrow><mml:mn>133</mml:mn></mml:msup></mml:math>Cs<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msup><mml:mrow></mml:mrow><mml:mo>+</mml:mo></mml:msup></mml:math> ions, and a Gaussian Process was trained with the position data to construct an efficiency function that could be used to correct the recorded distributions. The obtained numbers of counts of excited and ground-state ions were used to derive the isomeric yield ratio, taking into account decay losses as well as feeding from precursors. Microchannel plate detector ; Detector ; Ion ; Position (finance) ; Population ; Yield (engineering) ; Excited state ; Atomic physics ; Gaussian ; Physics ; Analytical Chemistry (journal) ; Chemistry ; Computational physics ; Optics Mass Spectrometry Techniques and Applications ; Nuclear Physics and Applications ; Nuclear physics research studies
Authors: Yuesong Li
Source: Shock and Vibration (article, 2023-06-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Magnetic Circuit Optimization and Physical Modeling of Giant Magnetostrictive Actuator Due to the excellent performance, giant magnetostrictive actuator is used in the active vibration isolation control system. However, its hysteresis nonlinear dynamic model is too complex for engineering practical applications, so it is necessary to establish an accurate and easy-to-use model. Based on Simulink/Simcape, a magnetic circuit model and a nonlinear dynamic physical model of the giant magnetostrictive actuator are developed. In the optimization of the magnetic circuit, the uniform distribution and the magnetic energy utilization of the giant magnetostrictive actuator are taken as the optimization objective, and the design criteria of the magnetic circuit are given. The hysteresis performance between the current and the magnetization is analyzed by simulating the magnetic circuit model. From the perspective of energy conservation, a linear magnetostrictive model which can reflect the effects of the frequency doubling and preload is established. Finally, the accuracy of the nonlinear dynamic physical model for the giant magnetostrictive actuator is verified by an experiment. The results show that the physical model agrees well with the experiment results not only under the quasistatic operating conditions but also under dynamic operating conditions. The error of the output displacement of the GMA under step response is less than 0.6 μm. Magnetostriction ; Actuator ; Quasistatic process ; Magnetic circuit ; Nonlinear system ; Control theory (sociology) ; Inverse magnetostrictive effect ; Hysteresis ; Displacement (psychology) ; Engineering ; Magnetic field ; Computer science ; Magnet ; Mechanical engineering ; Physics ; Electrical engineering ; Condensed matter physics Magnetic Properties and Applications ; Piezoelectric Actuators and Control ; Electric Motor Design and Analysis
Authors: Narayan Vetrekar | Raghavendra Ramachandra | R. S. Gad
Source: IEEE Sensors Letters (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Multilevel Fusion of Multispectral Images to Detect the Artificially Ripened Banana Automatic detection of artificially ripened fruits based on a nondestructive approach has recently gained significant attention. This work explores the inherent properties of multispectral imaging to distinguish between natural and artificially ripened bananas. The proposed method combines the prediction scores computed from the support vector machine on the individual and fused spectral bands images to detect the artificially ripened banana. Extensive analyses are performed on 5760 banana images captured in eight different spectrum bands covering visible and near-infra-red ranges. Obtained results indicate the average detection accuracy of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$97.1\pm 3.6\%$</tex-math></inline-formula>, thereby illustrating our proposed work's applicability. Multispectral image ; Notation ; Pattern recognition (psychology) ; Artificial intelligence ; Support vector machine ; Computer science ; Mathematics ; Arithmetic Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Advanced Chemical Sensor Technologies
Authors: Florentin Coppey | C. Schelling | Jean‐Luc Veuthey | Pierre Esseiva
Source: Helvetica Chimica Acta (article, 2023-07-12)
Field: Chemistry — Analytical Chemistry

Cloud‐Enabled Handheld NIR Spectroscopy: A Transformative Approach for Real‐Time Forensic Analysis of Cannabis Specimens Abstract In the past few years, there has been significant interest within the forensic community regarding the deployment of portable solutions that provide real‐time results. This article introduces an innovative technology or technology architecture that enables the integration of a handheld device, specifically, Viavi MicroNIR , with a cloud‐based system. This cloud system encompasses a server responsible for data processing and a mobile application acting as a user interface. To demonstrate the transformative impact of this technology on field operators, the analysis of cannabis specimens has been utilized. System's capacity to distinguish between CBD‐type and THC‐type cannabis has been particularly highlighted, along with the remarkable congruence observed between the near‐infrared (NIR) spectra and the reference analytical method involving ultra‐high‐performance liquid chromatography (UHPLC) The article will present the advantages of this application primarily focusing on its potential to alleviate the burden on laboratories by expediting routine illicit drug analysis. Viavi MicroNIR technology provides laboratory personnel with additional time to handle more complex cases, thereby enhancing overall efficiency. Mobile device ; Cloud computing ; Transformative learning ; Software deployment ; Chemistry ; Computer science ; World Wide Web ; Operating system ; Psychology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Bing Wu | Keming Yang | Yanru Li | Jiale He
Source: Sustainability (article, 2023-12-12)
Field: Chemistry — Analytical Chemistry

Hyperspectral Inversion of Heavy Metal Copper Content in Corn Leaves Based on DRS–XGBoost This study proposes a method that is used for the nondestructive detection of copper content in corn leaves, which is achieved via visible–near infrared spectroscopy. In this paper, we collected the visible–near infrared spectral data of corn leaves that were planted in soils undergoing different gradients of heavy metal copper stress. Then, a preliminary pretreatment was carried out to obtain the original spectrum (OS), the continuous removal spectrum (CR), and the derivative of ratio spectroscopy (DRS). Singular value decomposition was used for spectral denoising. The characteristic bands corresponding to the OS, CR, and DRS were determined using correlation analysis, as well as mutual information. Based on training the extreme gradient boosting tree (XGBoost) predictive model using feature bands, the copper content in corn leaves was predicted, and a comparative analysis was conducted with the commonly used partial least squares regression (PLSR) model in regression analysis. The results showed that the accuracy of the PLSR and XGBoost models, which were established with CR and DRS, were higher than that of the OS, among which the DRS model had the highest accuracy. For the validation set in the PLSR model, the coefficient of determination (R2) was 0.72, the root mean square error (RMSE) was 1.21 mg/kg, and the residual predictive deviation (RPD) was 1.89. For the validation set in the XGBoost model, the R2 was 0.86, the RMSE was 0.86 mg/kg, and the RPD was 2.66. At the same time, the spectral data of the field-planted corn near a mining area were selected to test the robustness of the model. Among them, the DRS had a higher accuracy in the XGBoost model, where its R2 was 0.51, its RMSE was 0.86 mg/kg, and its RPD was 1.45, thus indicating that the model can better predict the copper content in corn leaves and that the model has a higher robustness, which could provide new ideas for the prediction of heavy metal content in crops. Mean squared error ; Partial least squares regression ; Mathematics ; Hyperspectral imaging ; Coefficient of determination ; Correlation coefficient ; Content (measure theory) ; Analytical Chemistry (journal) ; Statistics ; Chemistry ; Artificial intelligence ; Computer science ; Environmental chemistry Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Remote Sensing in Agriculture
Authors: Khadiga M. Kelani | Maha A. Hegazy | Amal M. Hassan | Mahmoud A. Tantawy
Source: Scientific Reports (article, 2023-11-11)
Field: Chemistry — Analytical Chemistry

Application of multivariate chemometrics tools for spectrophotometric determination of naphazoline HCl, pheniramine maleate and three official impurities in their eye drops This work is concerned with exploiting the power of chemometrics in the assay and purity determination of naphazoline HCl (NZ) and pheniramine maleate (PN) in their combined eye drops. Partial least squares (PLS) and artificial neural network (ANN) were the chosen models for that purpose where three selected official impurities, namely; NZ impurity B and PN impurities A and B, were successfully determined. The quantitative determinations of studied components were assessed by percentage recoveries, standard errors of prediction as well as root mean square errors of prediction. The developed models were constructed in the ranges of 5.0-13.0 μg mL<sup>-1</sup> for NZ, 10.0-60.0 μg mL<sup>-1</sup> for PN, 1.0-5.0 μg mL<sup>-1</sup> for NZ impurity B and 2.0-14.0 μg mL<sup>-1</sup> for two PN impurities. The proposed models could determine NZ and PN with respective detection limits of 0.447 and 1.750 μg mL<sup>-1</sup> for PLS, and 0.494 and 2.093 μg mL<sup>-1</sup> for ANN. The two established models were compared favorably with official methods where no significant difference observed. Chemometrics ; Multivariate statistics ; Chromatography ; Chemistry ; Computer science ; Machine learning Analytical Methods in Pharmaceuticals ; Pharmacological Effects and Assays ; Analytical Chemistry and Chromatography
Authors: Chende Xu | Zhengguang Wang | Shuai Tang | Xiangyu Chi | Xixi Zhu | Yaru Li | Naihua Wang
Source: Energies (review, 2023-05-09)
Field: Materials Science — Materials Chemistry

Research Progress on Thermal Hydraulic Characteristics of Spent Fuel Pools: A Review Nuclear power plants (NPPs) produce large amounts of spent fuel while generating electricity. After the spent fuel is taken out of the reactor core, it still has a high decay heat and needs to be cooled for years or even decades before it can be reprocessed or buried deeply. Due to the long storage period of spent fuel, storage safety evaluation is a concern. In this regard, cooling systems are critical for the safe storage of spent fuel. Here, the research progress of cooling methods for spent fuel pools (SFPs) is reviewed, and the structural characteristics, application limitations and heat transfer performance of active and passive cooling technologies under accident conditions are discussed in detail. Moreover, future developments of SFPs are discussed, and the results of this review confirm that there is a great deal of research scope to improve the cooling performance and safety of spent fuel. This paper aims to provide a reference guide for engineers and will be highly beneficial to researchers engaged in spent fuel storage. Spent nuclear fuel ; Spent fuel pool ; Nuclear power ; Scope (computer science) ; Waste management ; Electricity ; Environmental science ; Decay heat ; Engineering ; Nuclear engineering ; Computer science ; Electrical engineering Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Nuclear Engineering Thermal-Hydraulics
Authors: Changgeng Zhang | Haoran Li | Yakun Tian | Yongjian Li | Qingxin Yang
Source: Materials (article, 2023-06-14)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Harmonic and DC Bias Hysteresis Characteristics Simulation Based on an Improved Preisach Model Transformers, reactors and other electrical equipment often work under harmonics and DC-bias working conditions. It is necessary to quickly and accurately simulate the hysteresis characteristics of soft magnetic materials under various excitation conditions in order to achieve accurate calculations of core loss and the optimal design of electrical equipment. Based on Preisach hysteresis model, a parameter identification method for asymmetric hysteresis loop simulation is designed and applied to the simulation of hysteresis characteristics under bias conditions of oriented silicon steel sheets. In this paper, the limiting hysteresis loops of oriented silicon steel sheets are obtained through experiments under different working conditions. The first-order reversal curves(FORCs) with asymmetric characteristics is generated numerically, and then the Everett function is established under different DC bias conditions. The hysteresis characteristics of the oriented silicon steel sheets under harmonics and DC bias are simulated by improving FORCs identification method of the Preisach model. By comparing the results of simulation and experiment, the effectiveness of the proposed method is verified, so as to provide an important reference for material production and application. Electrical steel ; Harmonics ; Hysteresis ; DC bias ; Magnetic hysteresis ; Preisach model of hysteresis ; Materials science ; Transformer ; Control theory (sociology) ; Harmonic ; Mechanics ; Magnetization ; Computer science ; Voltage ; Magnetic field ; Condensed matter physics ; Physics ; Engineering ; Acoustics ; Electrical engineering ; Composite material Magnetic Properties and Applications ; Piezoelectric Actuators and Control ; Electric Motor Design and Analysis
Authors: Jordi Minnema | Rob J. Vandebriel | K.F. de Boer | Walther Klerx | Wim H. de Jong | Christiaan Delmaar
Source: Small (article, 2023-02-24)
Field: Materials Science — Biomaterials

Physiologically‐Based Kinetic Modeling of Intravenously Administered Gold (Au) Nanoparticles Physiologically-based kinetic (PBK) modeling is a valuable tool to understand the kinetics of nanoparticles (NPs) in vivo. However, estimating PBK parameters remains challenging and commonly requires animal studies. To develop predictive models to estimate PBK parameter values based on NP characteristics, a database containing PBK parameter values and corresponding NP characteristics is needed. As a first step toward this objective, this study estimates PBK parameters for gold NPs (AuNPs) and provides a comparison of two different NPs. Two animal experiments are conducted in which varying doses of AuNPs attached with polyethylene glycol (PEG) are administered intravenously to rats. The resulting Au concentrations are used to estimate PBK model parameters. The parameters are compared with PBK parameters previously estimated for poly(alkyl cyanoacrylate) NPs loaded with cabazitaxel and for LipImage 815. This study shows that a small initial database of PBK parameters collected for three NPs is already sufficient to formulate new hypotheses on NP characteristics that may be predictive of PBK parameter values. Further research should focus on developing a larger database and on developing quantitative models to predict PBK parameter values. Polyethylene glycol ; Colloidal gold ; Nanoparticle ; PEG ratio ; In vivo ; Kinetics ; Chemistry ; Materials science ; Nanotechnology ; Biology ; Organic chemistry ; Physics ; Biotechnology Nanoparticle-Based Drug Delivery ; Gold and Silver Nanoparticles Synthesis and Applications ; Nanoparticles: synthesis and applications
Authors: Fulvio Sarcinella | Szymon Śmiga | Fabio Della Sala | Eduardo Fabiano
Source: International Journal of Quantum Chemistry (article, 2023-06-29)
Field: Materials Science — Materials Chemistry

Gaussian expansion of Yukawa non‐local kinetic energy functionals: Application to metal clusters Abstract The development of kinetic energy (KE) functionals is one of the current challenges in density functional theory (DFT). The Yukawa non‐local KE functionals [Phys. Rev. B 103, 155127 (2021)] have been shown to describe accurately the Lindhard response of the homogeneous electron gas (HEG) directly in the real space, without any step in the reciprocal space. However, the Yukawa kernel employs an exponential function which cannot be efficiently represented in conventional Gaussian‐based quantum chemistry codes. Here, we present an expansion of the Yukawa kernel in Gaussian functions. We show that for the HEG this expansion is independent of the electronic density, and that for general finite systems the accuracy can be easily tuned. Finally, we present results for atomistic sodium clusters of different sizes, showing that simple Yukawa functionals can give superior accuracy as compared to semilocal functionals. Yukawa potential ; Gaussian ; Physics ; Kernel (algebra) ; Kinetic energy ; Gaussian function ; Space (punctuation) ; Density functional theory ; Simple (philosophy) ; Exponential function ; Hybrid functional ; Quantum mechanics ; Statistical physics ; Mathematical analysis ; Mathematics ; Pure mathematics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Catalysis and Oxidation Reactions