jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ahmed Rady | Daniel E. Guyer | Irwin R. Donis-González | W. W. Kirk | Nicholas J. Watson
Source: Journal of Food Measurement & Characterization (article, 2020-08-12)
Field: Chemistry — Analytical Chemistry

A comparison of different optical instruments and machine learning techniques to identify sprouting activity in potatoes during storage Abstract The quality of potato tubers is dependent on several attributes been maintained at appropriate levels during storage. One of these attributes is sprouting activity that is initiated from meristematic regions of the tubers (eyes). Sprouting activity is a major problem that contributes to reduced shelf life and elevated sugar content, which affects the marketability of seed tubers as well as fried products. This study compared the capabilities of three different optical systems (1: visible/near-infrared (Vis/NIR) interactance spectroscopy, 2: Vis/NIR hyperspectral imaging, 3: NIR transmittance) and machine learning methods to detect sprouting activity in potatoes based on the primordial leaf count (LC). The study was conducted on Frito Lay 1879 and Russet Norkotah cultivars stored at different temperatures and classification models were developed that considered both cultivars combined and classified the tubers as having either high or low sprouting activity. Measurements were performed on whole tubers and sliced samples to see the effect this would have on identifying sprouting activity. Sequential forward selection was applied for wavelength selection and the classification was carried out using K-nearest neighbor, partial least squares discriminant analysis, and soft independent modeling class analogy. The highest classification accuracy values obtained by the hyperspectral imaging system and was 87.5% and 90% for sliced and whole samples, respectively. Data fusion did not show classification improvement for whole tubers, whereas a 7.5% classification accuracy increase was illustrated for sliced samples. By investigating different optical techniques and machine learning methods, this study provides a first step toward developing a handheld optical device for early detection of sprouting activity, enabling advanced aid potato storage management. Sprouting ; Hyperspectral imaging ; Mathematics ; Linear discriminant analysis ; Artificial intelligence ; Horticulture ; Food science ; Pattern recognition (psychology) ; Chemistry ; Computer science ; Biology Spectroscopy and Chemometric Analyses ; Potato Plant Research ; Water Quality Monitoring and Analysis
Authors: Ilaria Lanza | Daniele Conficoni | Stefania Balzan | Marco Cullere | Luca Fasolato | Lorenzo Serva | Barbara Contiero | A. Trocino | Giorgio Marchesini | Gerolamo Xiccato | Enrico Novelli | Severino Segato
Source: Food Quality and Safety (article, 2020-11-21)
Field: Chemistry — Analytical Chemistry

Assessment of chicken breast shelf life based on bench-top and portable near-infrared spectroscopy tools coupled with chemometrics Abstract Objectives Near-infrared (NIR) spectroscopy is a rapid technique able to assess meat quality even if its capability to determine the shelf life of chicken fresh cuts is still debated, especially for portable devices. The aim of the study was to compare bench-top and portable NIR instruments in discriminating between four chicken breast refrigeration times (RT), coupled with multivariate classifier models. Materials and Methods Ninety-six samples were analysed by both NIR tools at 2, 6, 10 and 14 days post mortem. NIR data were subsequently submitted to partial least squares discriminant analysis (PLS-DA) and canonical discriminant analysis (CDA). The latter was preceded by double feature selection based on Boruta and Stepwise procedures. Results PLS-DA sorted moderate separation of RT theses, while shelf life assessment was more accurate on application of Stepwise-CDA. Bench-top tool had better performance than portable one, probably because it captured more informative spectral data as shown by the variable importance in projection (VIP) and restricted pool of Stepwise-CDA predictive scores (SPS). Conclusions NIR tools coupled with a multivariate model provide deep insight into the physicochemical processes occurring during storage. Spectroscopy showed reliable effectiveness to recognise a 7-day shelf life threshold of breasts, suitable for routine at-line application for screening of meat quality. Partial least squares regression ; Chemometrics ; Linear discriminant analysis ; Near-infrared spectroscopy ; Shelf life ; Multivariate statistics ; Artificial intelligence ; Computer science ; Classifier (UML) ; Mathematics ; Pattern recognition (psychology) ; Chemistry ; Food science ; Machine learning ; Biology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Xue Zhang | Tapani Viitala | Riina Harjumäki | Alma Kartal-Hodzic | Juan José Valle‐Delgado | Monika Österberg
Source: Journal of Colloid and Interface Science (article, 2020-09-25)
Field: Materials Science — Biomaterials

Effect of laminin, polylysine and cell medium components on the attachment of human hepatocellular carcinoma cells to cellulose nanofibrils analyzed by surface plasmon resonance The development of in vitro cell models that mimic cell behavior in organs and tissues is an approach that may have remarkable impact on drug testing and tissue engineering applications in the future. Plant-based, chemically unmodified cellulose nanofibrils (CNF) hydrogel is a natural, abundant, and biocompatible material that has attracted great attention for biomedical applications, in particular for three-dimensional cell cultures. However, the mechanisms of cell-CNF interactions and factors that affect these interactions are not yet fully understood. In this work, multi-parametric surface plasmon resonance (SPR) was used to study how the adsorption of human hepatocellular carcinoma (HepG2) cells on CNF films is affected by the different proteins and components of the cell medium. Both human recombinant laminin-521 (LN-521, a natural protein of the extracellular matrix) and poly-l-lysine (PLL) adsorbed on CNF films and enhanced the attachment of HepG2 cells. Cell medium components (glucose and amino acids) and serum proteins (fetal bovine serum, FBS) also adsorbed on both bare CNF and on protein-coated CNF substrates. However, the adsorption of FBS hindered the attachment of HepG2 cells to LN-521- and PLL-coated CNF substrates, suggesting that serum proteins blocked the formation of laminin-integrin bonds and decreased favorable PLL-cell electrostatic interactions. This work sheds light on the effect of different factors on cell attachment to CNF, paving the way for the utilization and optimization of CNF-based materials for different tissue engineering applications. Polylysine ; Laminin ; Biophysics ; Extracellular matrix ; Surface plasmon resonance ; Fetal bovine serum ; Chemistry ; Cell adhesion ; Protein adsorption ; Cell culture ; Cell ; Cancer cell ; Materials science ; Biochemistry ; Adsorption ; Nanotechnology ; Organic chemistry ; Biology ; Cancer ; Nanoparticle Advanced Cellulose Research Studies ; Electrospun Nanofibers in Biomedical Applications ; Nanoparticle-Based Drug Delivery
Authors: Shanoob Balachandran | Abhishek Dutt Tripathi | Arunima Banerjee | Manaswini Chinara | Ravi Teja | S.J. Suresha | Deep Choudhuri | Rajarshi Banerjee | D. Banerjee
Source: MATEC Web of Conferences (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Transformations, Recrystallization, Microtexture and Plasticity in Titanium Alloys The objective of this contribution is to summarise the range of α crystallography and distribution that arises from the β to α transformation and the hot working of α/β alloys and their recrystallisation and relate these features to the slip character of these alloys. α morphology and distribution have been mapped as a function of β stabilizer content and aging temperature. A dominant transgranular grouping of α variants with a common close packed direction characterizes transformation patterns across the entire range of β stabilizer content. Recrystallization during thermomechanical processing in the α/β regime has been studied with the help of fine scale, orientation image mapping techniques. Two distinct recrystallization processes have been identified. The first is associated with the well-known α globularisation process. An alternative recrystallization process has also been described in which newly recrystallized α and β grains form with the Burgers orientation relationship with each other. This process has been called epitaxial recrystallization. The role of transformation and recrystallisation texture on the plasticity of titanium alloys is assessed through quantitative EBSD /TEM based analysis of slip systems in the α phase and slip transfer between the α and β phases. Recrystallization (geology) ; Materials science ; Electron backscatter diffraction ; Plasticity ; Metallurgy ; Slip (aerodynamics) ; Dynamic recrystallization ; Titanium alloy ; Titanium ; Hot working ; Microstructure ; Composite material ; Alloy ; Thermodynamics ; Geology Titanium Alloys Microstructure and Properties ; Metallurgy and Material Forming ; Metal and Thin Film Mechanics
Authors: Rafael R. Sola‐Guirado | Sergio Bayano-Tejero | Fernando Aragón-Rodríguez | Bruno Bernardi | Souraya Benalia | Sergio Castro‐García
Source: Computers and Electronics in Agriculture (article, 2020-11-01)
Field: Chemistry — Analytical Chemistry

A smart system for the automatic evaluation of green olives visual quality in the field Ripeness ; RGB color model ; Bruise ; Mean squared error ; Artificial intelligence ; Computer science ; Computer vision ; Image processing ; Segmentation ; Mathematics ; Statistics ; Horticulture ; Image (mathematics) Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Smart Agriculture and AI
Authors: Astrid Maléchaux | Yveline Le Dréau | Jacques Artaud | Nathalie Dupuy
Source: Foods (article, 2020-05-01)
Field: Chemistry — Organic Chemistry

Exploring the Scientific Interest for Olive Oil Origin: A Bibliometric Study from 1991 to 2018 The authenticity and traceability of olive oils have been a growing concern over the past decades, generating numerous scientific studies. This article applies the tools of bibliometric analyses to explore the evolution and strategic orientation of the research focused on olive oil geographical and varietal origins. A corpus of 732 papers published in 178 different journals between 1991 and 2018 was considered. The most productive journals, authors and countries are highlighted, as well as the most cited articles associated with specific analytical techniques. A cluster analysis on the keywords generates 8 main themes of research, each focused on different analytical techniques or compounds of interest. A network between these thematic clusters and the main authors indicates their area of expertise. The metabolomics methods are drawing increasing interest and studies focused on the relationships between the origin and the sensory or nutritional properties provided by minor compounds of olive oils appear to be future lines of research. Olive oil ; Traceability ; Bibliometrics ; Thematic map ; Data science ; Geography ; Computer science ; Biology ; Library science ; Food science ; Cartography Edible Oils Quality and Analysis ; Advanced Chemical Sensor Technologies ; Spectroscopy and Chemometric Analyses
Authors: Jie Ou | Xiao‐Qing Luo | You-Lin Luo | Weihua Zhu | Zhiyong Chen | Wu-Ming Liu | Xinlin Wang
Source: Nanophotonics (article, 2020-11-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Near‐infrared dual‐wavelength plasmonic switching and digital metasurface unveiled by plasmonic Fano resonance Abstract Plasmonic Fano resonance (FR) that contributes to multitudinous potential applications in subwavelength nanostructures can facilitate the realization of tunable wavelength selectivity for controlling light–matter interactions in metasurfaces. However, the plasmonic FR can be generated in metasurfaces with simple or complex geometries, and few of them can support flexible amplitude modulation and multiwavelength information transfer and processing. Here, we study the near‐infrared plasmonic FR in a hybrid metasurface composed of concentrically hybridized parabolic‐hole and circular‐ring‐aperture unit cells, which can induce polarization‐dependent dual‐wavelength passive plasmonic switching (PPS) and digital metasurface (DM). It is shown that the designable plasmonic FR can be realized by changing the geometric configurations of the unit cells. In particular, owing to the polarization‐dependent characteristic of FR, it is possible to fulfill a compact dual‐wavelength PPS with high ON/OFF ratios in the related optical communication bands. Moreover, such PPS that manipulates the amplitude response of the transmitted spectrum is an efficient way to reveal a 1‐bit DM, which can also be rationally extended to a 2‐bit DM or more. Our results suggest a pathway for studying polarization‐dependent PPS and programmable metasurface devices, yielding possibilities for subwavelength nanostructures in optical communication and information processing. Plasmon ; Fano resonance ; Optoelectronics ; Polarization (electrochemistry) ; Wavelength ; Materials science ; Optics ; Optical switch ; Physics ; Chemistry Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Optical Wireless Communication Technologies
Authors: Raoni Batista dos Anjos | Larissa Sobral Hilário | Henrique Borges de Moraes Juviniano | Djalma Ribeiro da Silva
Source: BioResources (article, 2020-05-19)
Field: Materials Science — Surfaces, Coatings and Films

Crude oil removal using Calotropis procera Calotropis procera (CP) fiber is a natural and renewable material with great lumen and hydrophobic-oleophilic characteristics, providing it with a good oil absorption capacity. In order to increase the absorption efficiency of organic oils and solvents, CP fiber was treated with either 0.1 M NaOH (CPNaOH), 1% NaClO2 (CPNaClO2), or hydrothermal conditions (CPHT) in an effort to improve its ability to remove crude oil from leaks or spills. The fibers were characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy with field emission (SEM-FEG), and wettability for water and diesel. The fibers CPHT, CPNaOH, and CPNaClO2 showed excellent hydrophobic-oleophilic properties and good crude oil absorption capacity in water 99.2 g/g, 103.9 g/g, and 92.0 g/g. The absorption after 60 min for most fibers in dry systems or with a layer of oil floating on water exceeded 90% of its absorption capacity for the time of 1440 min. The CPNaOH after 6 runs absorbed 445.8 g of crude oil per gram of fiber. Based on the results, the treated fibers can be considered an alternative for the removal of oil from leaks and spills due to the high availability and excellent absorption property for various oils. Materials science ; Fourier transform infrared spectroscopy ; Absorption (acoustics) ; Fiber ; Calotropis procera ; Absorption of water ; Diesel fuel ; Chemical engineering ; Nuclear chemistry ; Composite material ; Chemistry ; Organic chemistry Surface Modification and Superhydrophobicity ; Polymer composites and self-healing ; Polymer Nanocomposites and Properties
Authors: Shuangyin Zhang | Jun Li | Siying Wang | Yingjing Huang | Yizhuo Li | Yiyun Chen | Teng Fei
Source: Remote Sensing (article, 2020-02-02)
Field: Chemistry — Analytical Chemistry

Rapid Identification and Prediction of Cadmium-Lead Cross-Stress of Different Stress Levels in Rice Canopy Based on Visible and Near-Infrared Spectroscopy Accurate detection of cadmium (Cd) and lead (Pb)-induced cross-stress on crops is essential for agricultural, ecological environment, and food security. The feasibility to diagnose and predict Cd–Pb cross-stress in agricultural soil was explored by measuring the visible and near-infrared reflectance of rice leaves. In this study, two models were developed—namely a diagnostic model and a prediction model. The diagnostic model was established based on visible and near-infrared reflectance spectroscopy (VNIRS) datasets with Support Vector Machine (SVM), followed by leave-one-out cross-validation (LOOCV). A partial least-squares (PLS) regression, as the prediction model was employed to predict the foliar concentration of Cd and Pb contents. To accurately calibrate the two models, a rigorous greenhouse experiment was designed and implemented, with 4 levels of treatments on each of the Cd and Pb stress on rice. Results show that with the appropriate pre-processing, the diagnostic model can identify 79% of Cd and 85% of Pb stress of any levels. The significant bands that have been used mainly distributed between 681–776 nm and 1224–1349 nm for Cd stress and 712–784 nm for Pb stress. The prediction model can estimate Cd with coefficient of determination of 0.7, but failed to predict Pb accurately. The results illustrated the feasibility to diagnose Cd stress accurately by measuring the visible and near-infrared reflectance of rice canopy in a cross-contamination soil environment. This study serves as one step forward to heavy metal pollutant detection in a farmland environment. Environmental science ; Cadmium ; Support vector machine ; Partial least squares regression ; Cross-validation ; Remote sensing ; Canopy ; Stress (linguistics) ; Materials science ; Computer science ; Artificial intelligence ; Machine learning ; Geology ; Botany Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Soil Geostatistics and Mapping
Authors: Najeeb Ur Rehman | Ahmed Al‐Harrasi | Ricard Boqué | Fazal Mabood | Mohammed Al‐Broumi | Javid Hussain | Saif Alameri
Source: Foods (article, 2020-06-24)
Field: Chemistry — Analytical Chemistry

FT-NIRS Coupled with PLS Regression as a Complement to HPLC Routine Analysis of Caffeine in Tea Samples Daily consumption of caffeine in coffee, tea, chocolate, cocoa, and soft drinks has gained wide and plentiful public and scientific attention over the past few decades. The concentration of caffeine in vivo is a crucial indicator of some disorders-for example, kidney malfunction, heart disease, increase of blood pressure and alertness-and can cause some severe diseases including type 2 diabetes mellitus (DM), stroke risk, liver disease, and some cancers. In the present study, near-infrared spectroscopy (NIRS) coupled with partial least-squares regression (PLSR) was proposed as an alternative method for the quantification of caffeine in 25 commercially available tea samples consumed in Oman. This method is a fast, complementary technique to wet chemistry procedures as well as to high-performance liquid chromatography (HPLC) methods for the quantitative analysis of caffeine in tea samples because it is reagent-less and needs little or no pre-treatment of samples. In the current study, the partial least-squares (PLS) algorithm was built by using the near-infrared NIR spectra of caffeine standards prepared in tea samples scanned by a Frontier NIR spectrophotometer (L1280034) by PerkinElmer. Spectra were collected in the absorption mode in the wavenumber range of 10,000-4000 cm<sup>-1</sup>, using a 0.2 mm path length and CaF<sub>2</sub> sealed cells with a resolution of 2 cm<sup>-1</sup>. The NIR results for the contents of caffeine in tea samples were also compared with results obtained by HPLC analysis. Both techniques provided good results for predicting the caffeine contents in commercially available tea samples. The results of the proposed study show that the suggested FT-NIRS coupled with PLS regression algorithun has a high potential to be routinely used for the quick and reproducible analysis of caffeine contents in tea samples. For the NIR method, the limit of quantification (LOQ) was estimated as 10 times the error of calibration (root mean square error of calibration (RMSECV)) of the model; thus, RMSEC was calculated as 0.03 ppm and the LOQ as 0.3 ppm. Caffeine ; High-performance liquid chromatography ; Complement (music) ; Chromatography ; Chemistry ; Regression analysis ; Medicine ; Mathematics ; Biochemistry ; Internal medicine ; Statistics Spectroscopy and Chemometric Analyses ; Tea Polyphenols and Effects ; Coffee research and impacts
Authors: Mark Kasperczyk | Josh A. Zuber | Arne Barfuss | Johannes Kölbl | Viktoria Yurgens | Sigurd Flågan | Tomasz Jakubczyk | Brendan Shields | Richard J. Warburton | Patrick Maletinsky
Source: Physical review. B./Physical review. B (article, 2020-08-27)
Field: Materials Science — Materials Chemistry

Statistically modeling optical linewidths of nitrogen vacancy centers in microstructures We investigate the relationship between ion implantation and the optical linewidth of the nitrogen vacancy (NV) zero-phonon line (ZPL) in bulk and structured samples. We also propose a novel approach to ion implantation that we name postimplantation, in which nitrogen is implanted after all fabrication processes have been completed. We examine three post-implanted samples, one implanted with $^{14}\mathrm{N}$ and two with $^{15}\mathrm{N}$ isotopes. We perform photoluminescence excitation (PLE) spectroscopy to assess optical linewidths and optically detected magnetic resonance (ODMR) measurements to isotopically classify the NV centers. From this, we find that NV centers formed from nitrogen naturally occurring in the diamond lattice are characterized by a linewidth distribution peaked at an optical linewidth nearly two orders of magnitude smaller than the distribution characterizing most of the NV centers formed from implanted nitrogen. Surprisingly, we also observe a number of $^{15}\mathrm{NV}$ centers with narrow ($&lt;500\phantom{\rule{4pt}{0ex}}\mathrm{MHz}$) linewidths, implying that implanted nitrogen can yield NV centers with narrow optical linewidths. We further use a Bayesian approach to statistically model the linewidth distributions, to accurately quantify the uncertainty of fit parameters in our model, and to predict future linewidths within a particular sample. Our model is designed to aid comparisons between samples and research groups, in order to determine the best methods of achieving narrow NV linewidths in structured samples. Laser linewidth ; Ion implantation ; Vacancy defect ; Spectroscopy ; Materials science ; Nitrogen ; Ion ; Photoluminescence ; Diamond ; Atomic physics ; Analytical Chemistry (journal) ; Molecular physics ; Optoelectronics ; Physics ; Chemistry ; Condensed matter physics ; Optics ; Laser Diamond and Carbon-based Materials Research ; High-pressure geophysics and materials ; Electronic and Structural Properties of Oxides