jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nuno Rodrigues | António M. Peres | Paula Baptista | José Alberto Pereira
Source: Plants (article, 2022-01-19)
Field: Chemistry — Organic Chemistry

Olive Oil Sensory Analysis as a Tool to Preserve and Valorize the Heritage of Centenarian Olive Trees In inland areas of Portugal and some regions of the Mediterranean basin, olive production is based on traditional olive groves, with low intensification, local cultivars, aged plants, and centenarian trees. These plants play a key role in the ecosystem, contributing to carbon sequestration and possessing a high genetic diversity, particularly important for selecting cultivars more resistant to climatic changes. Appreciation of the value of this genetic diversity implies genetic, morphological, and physicochemical characterization of centenarian trees, which is expensive and time-consuming. Sensory evaluation is also of utmost importance. Thus, in this study, centenarian olive trees were selected in the Côa Valley region, a UNESCO World Heritage site. The descriptive sensory profile of their extracted olive oils was established and used to cluster the oils, using hierarchical clustering analysis, and consequently the olive trees, into five groups with similar intensities of perceived olfactory-gustatory attributes. Each cluster revealed olive oils with unique sensory patterns, presumably due to similarities of the olive trees, confirming the potential of the proposed screening approach. The identification of sensorially homogeneous oil-tree groups would reduce the number of specimens needed for subsequent morphological, genetic, and chemical characterization, allowing a cost-effective and robust future evaluation procedure. Centenarian ; Olive trees ; Olive oil ; Biology ; Genetic diversity ; Homogeneous ; Ecology ; Botany ; Longevity ; Food science ; Mathematics Edible Oils Quality and Analysis ; Essential Oils and Antimicrobial Activity ; Antioxidant Activity and Oxidative Stress
Authors: Pengfei Zhao | Jianfei Xing | Can Hu | Wensong Guo | Long Wang | Xiaowei He | Zhengxin Xu | Xufeng Wang
Source: Agriculture (article, 2022-03-15)
Field: Chemistry — Analytical Chemistry

Feasibility of Near-Infrared Spectroscopy for Rapid Detection of Available Nitrogen in Vermiculite Substrates in Desert Facility Agriculture Fast and precise estimation of the available nitrogen content in vermiculite substrates promotes prescription fertilization in desert facility agriculture. This study explored near-infrared spectroscopy for rapid detection of the available nitrogen content in vermiculite substrates in desert facility agriculture. The spectra of vermiculite matrices with different available nitrogen contents were collected through a self-assembled near-infrared spectrometer. Partial least squares expression (PLSR) established the available nitrogen spectrum prediction model optimized using different pretreatments. After pretreatment, the prediction model of the available nitrogen spectrum was simplified by adopting three feature extraction methods. A comprehensive comparison of the results of each prediction model showed that the prediction model combining the first derivative with SG smoothing pretreatment was the best. The correlation coefficients of the corresponding calibration and prediction sets were 0.9972 and 0.9968, respectively. The root mean square errors of the calibration and prediction sets were 149.98 and 159.65 mg/kg, respectively, with 12.57 RPD. These results provide a feasible method for rapidly detecting the available nitrogen content of vermiculite substrates in desert facility agriculture. Vermiculite ; Nitrogen ; Calibration ; Partial least squares regression ; Environmental science ; Chemistry ; Materials science ; Mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Soil Geostatistics and Mapping ; Water Quality Monitoring and Analysis
Authors: Huanhuan Qi | Feng Yu | Jiao Deng | Pingfang Yang
Source: International Journal of Molecular Sciences (review, 2022-06-30)
Field: Chemistry — Analytical Chemistry

Studies on Lotus Genomics and the Contribution to Its Breeding Lotus (<i>Nelumbo nucifera</i>), under the Nelumbonaceae family, is one of the relict plants possessing important scientific research and economic values. Because of this, much attention has been paid to this species on both its biology and breeding among the scientific community. In the last decade, the genome of lotus has been sequenced, and several high-quality genome assemblies are available, which have significantly facilitated functional genomics studies in lotus. Meanwhile, re-sequencing of the natural and genetic populations along with different levels of omics studies have not only helped to classify the germplasm resources but also to identify the domestication of selected regions and genes controlling different horticultural traits. This review summarizes the latest progress of all these studies on lotus and discusses their potential application in lotus breeding. Lotus ; Germplasm ; Domestication ; Genomics ; Biology ; Genome ; Biotechnology ; Genetics ; Gene ; Ecology ; Botany Chromatography in Natural Products ; Ginseng Biological Effects and Applications ; Genetic Mapping and Diversity in Plants and Animals
Authors: Marvin Masche | Jierong Liang | Kurt Engelbrecht | C.R.H. Bahl
Source: Applied Thermal Engineering (article, 2022-07-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Improving magnetic cooling efficiency and pulldown by varying flow profiles Magnetic refrigeration systems are promising cooling solutions that employ the active magnetic regenerator refrigeration cycle to achieve practical temperature spans and environmental benefits. The hydraulic system that ensures a continuous flow of the heat transfer fluid through the system with a reciprocating flow in each regenerator bed is critical to the performance of the refrigeration cycle. Hence, we investigate the characteristics of the parallel flow circuit of a rotary active magnetic regenerator system, which consists of thirteen trapezoid-shaped regenerators, each filled with 295 g of gadolinium spheres. Fluid flow is controlled via electrically actuated solenoid valves (both piloted and direct-acting) connected to the regenerator hot side. By varying the percentage of opening of the control valves, different blow fractions (or fluid flow waveforms) could be investigated. The objective of the study is twofold: (i) assess whether flow imbalances of the heat transfer fluid exist in the cold-to-hot blow (cold blow) and hot-to-cold blow (hot blow) directions, and (ii) determine whether there is an optimal value of the blow fraction both to maximize the cooling performance and realize a rapid temperature pulldown. Flow resistance measurements demonstrate a symmetric flow circuit design and resistances that are similar in the cold and hot blow directions. Moreover, for the studied temperature spans of 6 K and 16 K, the best blow fraction was found to be about 41.6 %. For instance, at a 16 K span, a utilization of 0.32, and at 1.4 Hz, increasing the fluid blow fraction from 25.0 to 41.6 % enhanced the cooling capacity and second-law efficiency from 70 to 330 W and from 2.6 to 17.4 %, respectively. In turn, lower blow fractions favored a more rapid temperature pulldown. The magnetocaloric system was about 30 % faster in establishing approximately 14 K temperature span when the blow fraction was reduced from 41.6 to 30.6 %. Hence, magnetic refrigeration systems can benefit greatly from solenoid valves, which allow the system to operate either in a time-saving mode or an energy-saving mode. Regenerative heat exchanger ; Cooling capacity ; Refrigeration ; Mechanics ; Solenoid ; Heat transfer ; Materials science ; Flow (mathematics) ; Reciprocating motion ; Heat exchanger ; Thermodynamics ; Working fluid ; Mechanical engineering ; Engineering ; Control theory (sociology) ; Nuclear engineering ; Physics ; Computer science ; Gas compressor Magnetic and transport properties of perovskites and related materials ; Physics of Superconductivity and Magnetism ; ZnO doping and properties
Authors: Andrés Cruz-Conesa | Joan Ferré | Itziar Ruisánchez | A.M. Pérez-Vendrell
Source: Chemometrics and Intelligent Laboratory Systems (article, 2022-12-30)
Field: Chemistry — Analytical Chemistry

Selection of reference samples for updating multivariate calibration models used in the analysis of pig faeces Monitoring and updating calibration models are common tasks when analytical methods are based on near-infrared spectroscopy. This work describes a situation in which a PLS calibration model that is used routinely for the determination of phosphorus content in pig faeces in digestibility studies had to be updated in order to be used with the faeces collected in a new trial with phytases. An approach based on D-optimality is presented that selects a reduced number of the new samples to be analyzed with the reference analytical method so that the small set is used to confirm the need to update the model and validate it. The rest of the new samples that had not been selected by the algorithm were accurately predicted with the updated model. The updated model maintained its previous performance for the samples in the validation set (an RMSEP of 1.58 g kg−1 compared with an RMSEP of 1.54 g kg−1 before the update) and the prediction error for the new samples was RMSECV = 1.95 g kg−1, much lower than the RMSEP = 11.38 g kg−1 obtained before the model update. In addition, the predictive ability of the updated PLS model was significantly better than updated models selecting the reduced dataset using other sample selection methods such as Kennard-Stone, a leverage-based selection method and random selection. Leverage (statistics) ; Calibration ; Selection (genetic algorithm) ; Multivariate statistics ; Statistics ; Model selection ; Mathematics ; Set (abstract data type) ; Computer science ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Pesticide Residue Analysis and Safety ; Meat and Animal Product Quality
Authors: J. R. Capers | S. J. Boyes | Alastair P. Hibbins | S. A. R. Horsley
Source: New Journal of Physics (article, 2022-11-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Designing disordered multi-functional metamaterials using the discrete dipole approximation Abstract The ability to design passive structures that perform different operations on different electromagnetic fields is key to many technologies, from beam-steering to optical computing. While many techniques have been developed to optimise structures to achieve specific functionality through inverse design, designing multi-function materials remains challenging. We present a semi-analytic method, based on the discrete dipole approximation, to design multi-functional metamaterials. To demonstrate the generality of our method, we present two key examples. Firstly, we work at optical wavelengths to design a disordered 2D arrangement of silicon spheres that beams light into different directions depending on the source polarisation. Secondly, we design a 3D device that works at microwave wavelengths and sorts plane waves by their angle of incidence. In this case, the scatterers are more complicated meta-atoms, with a strong dipole resonance at microwave frequencies. Physics ; Discrete dipole approximation ; Metamaterial ; Dipole ; Wavelength ; Microwave ; Optics ; Topology (electrical circuits) ; Computational physics ; Quantum mechanics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Orbital Angular Momentum in Optics
Authors: Wenlong Li | Yu Luo | Xi Wang | Xingchu Gong | Wenhua Huang | Guoxiang Wang | Haibin Qu
Source: Separations (article, 2022-10-14)
Field: Chemistry — Analytical Chemistry

Development and Validation of a Near-Infrared Spectroscopy Method for Multicomponent Quantification during the Second Alcohol Precipitation Process of Astragali radix The objective of this study was to develop and validate a near-infrared (NIR) spectroscopy based method for in-line quantification during the second alcohol precipitation process of Astragali radix. In total, 22 calibration experiments were carefully arranged using a Box–Behnken design. Variations in the raw materials, critical process parameters, and environmental temperature were all included in the experimental design. Two independent validation sets were built for method evaluation. Validation set 1 was used for optimization. Different spectral pretreatments were compared using a “trial-and-error” approach. To reduce the calculation times, the full-factorial design was applied to determine the potential optimal combinations. Then, the best parameters for the pretreatment algorithms were compared and selected. Partial least squares (PLS) regression models were obtained with low complexity and good predictive performance. Validation set 2 was used for a thorough validation of the NIR spectroscopy method. Based on the same validation set, traditional chemometric validation and validation using accuracy profiles were conducted and compared. Conventional chemometric parameters were used to obtain the overall predictive capability of the established models; however, these parameters were insufficient for pharmaceutical regulatory requirements. Then, the method was fully validated according to the ICH Q2(R1) guideline and using the accuracy profile approach, which enabled visual and reliable representation of the future performances of the analytical method. The developed method was able to determine content ranges of 8.44–39.8% at 0.541–2.26 mg/mL, 0.118–0.502 mg/mL, 0.220–0.940 mg/mL, 0.106–0.167 mg/mL, 0.484–0.879 mg/mL, and 0.137–0.320 mg/mL for total solid, calycosin glucoside, formononetin glucoside, 9, 10-dimethoxypterocarpan glucopyranoside, 2′-dihydroxy -3′, 4′-dimethoxyisoflavan glucopyranoside, astragloside II, and astragloside IV, respectively. These ranges were specific to the early and middle stages of the second alcohol precipitation process. The method was confirmed to be capable of achieving an in-line prediction with a very acceptable accuracy. The present study demonstrates that accuracy profiles offer a potential approach for the standardization of NIR spectroscopy method validation for traditional Chinese medicines (TCMs). Partial least squares regression ; Calibration ; Chemometrics ; Process analytical technology ; Cross-validation ; Factorial experiment ; Process (computing) ; Near-infrared spectroscopy ; Computer science ; Biological system ; Mathematics ; Statistics ; Artificial intelligence ; Machine learning ; Engineering ; Work in process Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Traditional Chinese Medicine Analysis
Authors: Minhui An | Chengmao Cao | Zhengmin Wu | Kun Luo
Source: Sensors (article, 2022-10-29)
Field: Chemistry — Analytical Chemistry

Detection Method for Walnut Shell-Kernel Separation Accuracy Based on Near-Infrared Spectroscopy In this study, Near-infrared (NIR) spectroscopy was adopted for the collection of 1200 spectra of three types of walnut materials after breaking the shells. A detection model of the walnut shell-kernel separation accuracy was established. The preprocessing method of de-trending (DT) was adopted. A classification model based on a support vector machine (SVM) and an extreme learning machine (ELM) was established with the principal component factor as the input variable. The effect of the penalty value (C) and kernel width (g) on the SVM model was discussed. The selection criteria of the number of hidden layer nodes (L) in the ELM model were studied, and a genetic algorithm (GA) was used to optimize the input layer weight (W) and the hidden layer threshold value (B) of the ELM. The results revealed that the classification accuracy of SVM and ELM models for the shell, kernel, and chimera was 97.78% and 97.11%. The proposed method can serve as a reference for the detection of walnut shell-kernel separation accuracy. Kernel (algebra) ; Support vector machine ; Artificial intelligence ; Preprocessor ; Extreme learning machine ; Pattern recognition (psychology) ; Principal component analysis ; Computer science ; Biological system ; Algorithm ; Mathematics ; Artificial neural network ; Biology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Christoph Berg | Nina Ihling | Maurice Finger | Olivier Paquet‐Durand | Bernd Hitzmann | Jochen Büchs
Source: Bioengineering (article, 2022-09-04)
Field: Chemistry — Analytical Chemistry

Online 2D Fluorescence Monitoring in Microtiter Plates Allows Prediction of Cultivation Parameters and Considerable Reduction in Sampling Efforts for Parallel Cultivations of Hansenula polymorpha Multi-wavelength (2D) fluorescence spectroscopy represents an important step towards exploiting the monitoring potential of microtiter plates (MTPs) during early-stage bioprocess development. In combination with multivariate data analysis (MVDA), important process information can be obtained, while repetitive, cost-intensive sample analytics can be reduced. This study provides a comprehensive experimental dataset of online and offline measurements for batch cultures of <i>Hansenula polymorpha</i>. In the first step, principal component analysis (PCA) was used to assess spectral data quality. Secondly, partial least-squares (PLS) regression models were generated, based on spectral data of two cultivation conditions and offline samples for glycerol, cell dry weight, and pH value. Thereby, the time-wise resolution increased 12-fold compared to the offline sampling interval of 6 h. The PLS models were validated using offline samples of a shorter sampling interval. Very good model transferability was shown during the PLS model application to the spectral data of cultures with six varying initial cultivation conditions. For all the predicted variables, a relative root-mean-square error (RMSE) below 6% was obtained. Based on the findings, the initial experimental strategy was re-evaluated and a more practical approach with minimised sampling effort and elevated experimental throughput was proposed. In conclusion, the study underlines the high potential of multi-wavelength (2D) fluorescence spectroscopy and provides an evaluation workflow for PLS modelling in microtiter plates. Partial least squares regression ; Bioprocess ; Principal component analysis ; Biological system ; Sampling (signal processing) ; Chemometrics ; Multivariate statistics ; Mean squared error ; Computer science ; Pattern recognition (psychology) ; Process engineering ; Statistics ; Artificial intelligence ; Mathematics ; Filter (signal processing) ; Machine learning ; Engineering ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Viral Infectious Diseases and Gene Expression in Insects
Authors: Vitalii Kovalchuk | Maksym Koval | Artur Onyshchenko | Ivan Kravets | Olena Bal | Ruslan Markul | Svitlana Vikhot | Oleksiy Petrenko | Roman Rybak | Andriy Мilyanych
Source: Eastern-European Journal of Enterprise Technologies (article, 2022-06-30)
Field: Materials Science — Materials Chemistry

Determining the strained state of prefabricated metal corrugated structures of a tunnel overpass exposed to the dynamic loading from railroad rolling stock This paper reports the analysis of prospects for the use of prefabricated metal corrugated structures in the body of the embankment of a railroad track in the form of a tunnel overpass in order to pass road vehicles and railroad rolling stock. A technique of inertial dynamic tests of the deformed state of a tunnel overpass from prefabricated metal corrugated structures during the passage of railroad rolling stock is given, by measuring accelerations at the top and on the sides of overpass structures. An algorithm is proposed for processing the acceleration signal for assessing the strained state of metal corrugated structures of a tunnel overpass under the action of dynamic load from railroad transport. Experimental dynamic measurements of accelerations arising at the top and on the sides of a tunnel overpass during the passage of passenger and freight railroad rolling stock were carried out. The maximum value of accelerations arising at the top of a tunnel overpass during the passage of a freight train was 7.99 m/s2, and when passing a passenger train – 6.21 m/s2; the maximum accelerations that occur on the sides were 2.63 m/s2 and 1.77 m/s2. It is established that the maximum deformations of metal corrugated structures of the top of a tunnel overpass, when passing freight and passenger trains are, respectively, 1.63 mm and 1.11 mm. The maximum strains of metal corrugated structures on the sides of an overpass are 1.07 mm and 0.48 mm. The value of relative deformations in the vertical and horizontal dimensions of the structures of a tunnel overpass under the action of dynamic loads from the railroad rolling stock has been found. The relative vertical strains of an overpass amounted to 0.020 %; horizontal – 0.012 %. The practical significance of this work is that with the help of the devised procedure for measuring accelerations, it is possible to assess the strained state of metal corrugated structures under the influence of dynamic loads from the railroad rolling stock Structural engineering ; Train ; Track (disk drive) ; Engineering ; Mechanical engineering Material Properties and Failure Mechanisms ; Geodetic Measurements and Engineering Structures ; Industrial Engineering and Technologies
Authors: Jungmi Oh | Kyung‐Ja Ha | Young‐Heon Jo
Source: Asia-Pacific Journal of Atmospheric Sciences (review, 2022-04-25)
Field: Materials Science — Polymers and Plastics

Use of Weather Factors in Clothing Studies in Korea and its Implications: a Review Clothing ; Business ; Climate change ; Extreme weather ; Empirical research ; Environmental science ; Geography Textile materials and evaluations ; Skin Protection and Aging ; Urban Heat Island Mitigation
Authors: Linge Li | Zhonghuai Hou
Source: Biophysics Reports (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Theoretical modelling of liquid–liquid phase separation: from particle-based to field-based simulation Liquid-liquid phase separation (LLPS) has proved to be ubiquitous in living cells, forming membraneless organelles (MLOs) and dynamic condensations essential in physiological processes. However, some underlying mechanisms remain challenging to unravel experimentally, making theoretical modeling an indispensable aspect. Here we present a protocol for understanding LLPS from fundamental physics to detailed modeling procedures. The protocol involves a comprehensive physical picture on selecting suitable theoretical approaches, as well as how and what to interpret and resolve from the results. On the particle-based level, we elaborate on coarse-grained simulation procedures from building up models, identifying crucial interactions to running simulations to obtain phase diagrams and other concerned properties. We also outline field-based theories which give the system's density profile to determine phase diagrams and provide dynamic properties by studying the time evolution of density field, enabling us to characterize LLPS systems with larger time and length scales and to further include other nonequilibrium factors such as chemical reactions. Statistical physics ; Field (mathematics) ; Phase diagram ; Computer science ; Non-equilibrium thermodynamics ; Protocol (science) ; Particle (ecology) ; Phase (matter) ; Biological system ; Physics ; Mathematics ; Ecology ; Thermodynamics ; Biology Block Copolymer Self-Assembly ; Nanopore and Nanochannel Transport Studies ; RNA Research and Splicing