jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Linsheng Huang | Taikun Li | Chuanlong Ding | Jinling Zhao | Dongyan Zhang | Guijun Yang
Source: Sensors (article, 2020-05-20)
Field: Chemistry — Analytical Chemistry

Diagnosis of the Severity of Fusarium Head Blight of Wheat Ears on the Basis of Image and Spectral Feature Fusion <i>Fusarium</i> head blight (FHB), one of the most prevalent and damaging infection diseases of wheat, affects quality and safety of associated food. In this study, to realize the early accurate monitoring of FHB, a diagnostic model of disease severity was proposed based on the fusion features of image and spectral features. First, the hyperspectral image of FHB infected in the range of the 400-1000 nm spectrum was collected, and the color parameters of wheat ear and spot region were segmented based on image features. Twelve sensitive bands were extracted using the successive projection algorithm, gray-scale co-occurrence matrix, and RGB color model. Four texture features were extracted from each feature band image as texture variables, and nine color feature variables were extracted from R, G, and B component images. Texture features with high correlation and color features were selected to participate in the final model building parameters via correlation analysis. Finally, the particle swarm optimization support vector machine (PSO-SVM) algorithm was used to build the model based on the diagnosis model of disease severity of FHB with different combinations of characteristic variables. The experimental results showed that the PSO-SVM model based on spectral and color feature fusion was optimal. Moreover, the accuracy of the training and prediction set was 95% and 92%, respectively. The method based on fusion features of image and spectral features can accurately and effectively diagnose the severity of FHB, thereby providing a technical basis for the timely and effective control of FHB and precise application of a pesticide. Artificial intelligence ; Pattern recognition (psychology) ; Support vector machine ; Particle swarm optimization ; Feature (linguistics) ; RGB color model ; Computer science ; Machine learning Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Mycotoxins in Agriculture and Food
Authors: Puneet Mishra | Jean‐Michel Roger | Douglas N. Rutledge | Ernst Woltering
Source: Postharvest Biology and Technology (article, 2020-09-09)
Field: Chemistry — Analytical Chemistry

Two standard-free approaches to correct for external influences on near-infrared spectra to make models widely applicable In near-infrared (NIR) spectroscopy of fresh fruit often the external influences due to differences in physical, chemical and environmental conditions lead to model failure. Correction methods are required where standard samples are measured covering all different conditions and then remodeling is performed. However, in the real-world, it is often difficult to measure standard samples. To deal with this, two different approaches to correct for external influences without standard sample measurements i.e., dynamic orthogonalization projection (DOP) and domain adaption (DA), are presented, and for the first time are applied to NIR spectroscopy of fresh fruit. Four different case studies, chosen based on their importance and their frequency of occurrences in the NIR spectroscopy domain, were used for the demonstration. The first case was an adaption to maintain the predictive performance of a model when used on a spectra from a second similar instrument. The second case was the correction of the temperature effects due to sensor heating. The third and fourth cases were about maintaining the model performance for multi-season fruit quality prediction models for mangos and for apples. In all of the cases, the aim was to solve the challenges without resorting to new measurement of standards. The results showed that for all the cases, both DOP and DA improved model performances. Up to 31% increase in R2p, and 98% and 66% reduction in prediction bias and root mean squared error (RMSE) of prediction were noted, respectively. The main benefit of the DOP and DA techniques in NIR spectroscopy is the limited need for standard measurements, providing general-purpose tools to complement the NIR spectroscopy and make the models scalable, transferable, and reusable. Near-infrared spectroscopy ; Mean squared error ; Orthogonalization ; Standard error ; Spectroscopy ; Measure (data warehouse) ; Biological system ; Projection (relational algebra) ; Statistics ; Mathematics ; Computer science ; Algorithm ; Optics ; Data mining ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Shizhuang Weng | S.K. Yu | Binqing Guo | Peipei Tang | Dong Liang
Source: Sensors (article, 2020-05-29)
Field: Chemistry — Analytical Chemistry

Non-Destructive Detection of Strawberry Quality Using Multi-Features of Hyperspectral Imaging and Multivariate Methods Soluble solid content (SSC), pH, and vitamin C (VC) are considered as key parameters for strawberry quality. Spectral, color, and textural features from hyperspectral reflectance imaging of 400–1000 nm was to develop the non-destructive detection approaches for SSC, pH, and VC of strawberries by integrating various multivariate methods as partial least-squares regression (PLSR), support vector regression, and locally weighted regression (LWR). SSC, pH, and VC of 120 strawberries were statistically analyzed to facilitate the partitioning of data sets, which helped optimize the model. PLSR, with spectral and color features, obtained the optimal prediction of SSC with determination coefficient of prediction (Rp2) of 0.9370 and the root mean square error of prediction (RMSEP) of 0.1145. Through spectral features, the best prediction for pH was obtained by LWR with Rp2 = 0.8493 and RMSEP = 0.0501. Combination of spectral and textural features with PLSR provided the best results of VC with Rp2 = 0.8769 and RMSEP = 0.0279. Competitive adaptive reweighted sampling and uninformative variable elimination (UVE) were used to select important variables from the above features. Based on the important variables, the accuracy of SSC, pH, and VC prediction both gain the promotion. Finally, the distribution maps of SSC, pH, and VC over time were generated, and the change trend of three quality parameters was observed. Thus, the proposed method can nondestructively and accurately determine SSC, pH, and VC of strawberries and is expected to design and construct the simple sensors for the above quality parameters of strawberries. Partial least squares regression ; Hyperspectral imaging ; Multivariate statistics ; Mean squared error ; Variable elimination ; Support vector machine ; Coefficient of determination ; Mathematics ; Artificial intelligence ; Pattern recognition (psychology) ; Regression ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Irini Psarrou | Antigoni Oreopoulou | Dimitrios Tsimogiannis | Vassiliki Oreopoulou
Source: Molecules (article, 2020-10-02)
Field: Chemistry — Organic Chemistry

Extraction Kinetics of Phenolic Antioxidants from the Hydro Distillation Residues of Rosemary and Effect of Pretreatment and Extraction Parameters Rosemary residue, remaining after the distillation of essential oil, is currently unexploited, while it is a source of phenolic antioxidant components. This raw material was used for the extraction of phenolic compounds by aqueous ethanol or acetone in a continuously stirred reactor. The experimental results were fitted with a two-stage diffusion model. The highest extraction rates, total phenolic content (TPC) recovery, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging capacity were obtained by acetone 60% and ethanol 60%. Grinding of the raw material enhanced the extraction rate and increased TPC yield and antioxidant capacity as the particle size decreased. Pre-treatment by maceration in water (4 h) dissolved a high amount of TPC and shortened the extraction time, while the combination with the pulsed electric field process did not provide further improvement. The use of ultrasound increased the efficiency of the extraction. Chemistry ; Acetone ; Extraction (chemistry) ; Chromatography ; Pomace ; Raw material ; DPPH ; Maceration (sewage) ; Distillation ; Sonication ; Solvent ; Steam distillation ; Antioxidant ; Organic chemistry ; Food science ; Materials science Free Radicals and Antioxidants ; Essential Oils and Antimicrobial Activity ; Chemical and Physical Properties in Aqueous Solutions
Authors: Rei Sonobe | Yuhei Hirono | Ayako Oi
Source: Plants (article, 2020-03-17)
Field: Chemistry — Analytical Chemistry

Non-Destructive Detection of Tea Leaf Chlorophyll Content Using Hyperspectral Reflectance and Machine Learning Algorithms Tea trees are kept in shaded locations to increase their chlorophyll content, which influences green tea quality. Therefore, monitoring change in chlorophyll content under low light conditions is important for managing tea trees and producing high-quality green tea. Hyperspectral remote sensing is one of the most frequently used methods for estimating chlorophyll content. Numerous studies based on data collected under relatively low-stress conditions and many hyperspectral indices and radiative transfer models show that shade-grown tea performs poorly. The performance of four machine learning algorithms-random forest, support vector machine, deep belief nets, and kernel-based extreme learning machine (KELM)-in evaluating data collected from tea leaves cultivated under different shade treatments was tested. KELM performed best with a root-mean-square error of 8.94 ± 3.05 μg cm<sup>-2</sup> and performance to deviation values from 1.70 to 8.04 for the test data. These results suggest that a combination of hyperspectral reflectance and KELM has the potential to trace changes in the chlorophyll content of shaded tea leaves. Hyperspectral imaging ; Chlorophyll ; Remote sensing ; Atmospheric radiative transfer codes ; Algorithm ; Random forest ; Artificial intelligence ; Mathematics ; Mean squared error ; Chlorophyll a ; Computer science ; Environmental science ; Horticulture ; Radiative transfer ; Botany ; Statistics ; Biology ; Geography Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Water Quality Monitoring and Analysis
Authors: Sofia Scataglini | Alex P. Moorhead | Francesco Feletti
Source: Muscles Ligaments and Tendons Journal (review, 2020-06-01)
Field: Materials Science — Polymers and Plastics

A Systematic Review of Smart Clothing in Sports: possible Applications to Extreme Sports Background. Traditional monitoring of athletes during sports has long been hampered by bulky, complicated and tethered systems. In the past decade, this has changed due to the miniaturization of sensors and improvement of systems to store and transmit data. These systems have been integrated into textiles to create 'smart clothing' which has been so ubiquitous that a review of the recent literature is crucial for understanding its full potential and potential use in extreme sports. Clothing ; sports equipment ; Architectural engineering ; Engineering ; Forensic engineering ; History ; Mechanical engineering Textile materials and evaluations ; Consumer Perception and Purchasing Behavior ; Color perception and design
Authors: Jaimyun Jung | Jae Ik Yoon | Hyung Keun Park | Hyeontae Jo | Hyoung Seop Kim
Source: Materialia (article, 2020-05-15)
Field: Materials Science — Materials Chemistry

Microstructure design using machine learning generated low dimensional and continuous design space Bayesian optimization ; Dimensionality reduction ; Curse of dimensionality ; Microstructure ; Autoencoder ; Mathematical optimization ; Bayesian probability ; Space (punctuation) ; Flexibility (engineering) ; Computer science ; Materials science ; Algorithm ; Artificial intelligence ; Mathematics ; Statistics ; Composite material ; Deep learning Machine Learning in Materials Science ; Injection Molding Process and Properties ; Additive Manufacturing and 3D Printing Technologies
Authors: Lude Wang | Duo Xu | Jie Gao | Xiang Chen | Yanhong Duo | Han Zhang
Source: Science China Materials (article, 2020-06-12)
Field: Materials Science — Materials Chemistry

Semiconducting quantum dots: Modification and applications in biomedical science Nanotechnology ; Materials science ; Quantum dot ; Drug delivery Quantum Dots Synthesis And Properties ; Advanced biosensing and bioanalysis techniques ; ZnO doping and properties
Authors: Utku Yolsal | Thomas A. R. Horton | Meng Wang | Michael P. Shaver
Source: Progress in Polymer Science (article, 2020-10-16)
Field: Chemistry — Organic Chemistry

Polymer-supported Lewis acids and bases: Synthesis and applications Lewis acids and bases ; Nanotechnology ; Polymer ; Supramolecular chemistry ; Frustrated Lewis pair ; Materials science ; Combinatorial chemistry ; Computer science ; Molecule ; Chemistry ; Organic chemistry ; Catalysis Organoboron and organosilicon chemistry ; Covalent Organic Framework Applications ; Carbon dioxide utilization in catalysis
Authors: Shi‐Yuan Zhang | David Fairen‐Jiménez | Michael J. Zaworotko
Source: Angewandte Chemie International Edition (article, 2020-06-27)
Field: Chemistry — Physical and Theoretical Chemistry

Structural Elucidation of the Mechanism of Molecular Recognition in Chiral Crystalline Sponges To gain insight into chiral recognition in porous materials we have prepared a family of fourth generation chiral metal-organic frameworks (MOFs) that have rigid frameworks and adaptable (flexible) pores. The previously reported parent material, [Co<sub>2</sub> (S-mandelate)<sub>2</sub> (4,4'-bipyridine)<sub>3</sub> ](NO<sub>3</sub> )<sub>2</sub> , CMOM-1S, is a modular MOF; five new variants in which counterions (BF<sub>4</sub><sup>-</sup> , CMOM-2S) or mandelate ligands are substituted (2-Cl, CMOM-11R; 3-Cl, CMOM-21R; 4-Cl, CMOM-31R; 4-CH<sub>3</sub> , CMOM-41R) and the existing CF<sub>3</sub> SO<sub>3</sub><sup>-</sup> variant CMOM-3S are studied herein. Fine-tuning of pore size, shape, and chemistry afforded a series of distinct host-guest binding sites with variable chiral separation properties with respect to three structural isomers of phenylpropanol. Structural analysis of the resulting crystalline sponge phases revealed that host-guest interactions, guest-guest interactions, and pore adaptability collectively determine chiral discrimination. Mechanism (biology) ; Stereochemistry ; Chemistry ; Philosophy ; Epistemology Crystallography and molecular interactions ; Crystallization and Solubility Studies ; Porphyrin and Phthalocyanine Chemistry
Authors: Ram Karan | Sam Mathew | Reyhan Muhammad | Didier Barradas‐Bautista | Malvina Vogler | Jörg Eppinger | Romina Oliva | Luigi Cavallo | Stefan T. Arold | Magnus Rueping
Source: Microorganisms (article, 2020-10-16)
Field: Materials Science — Materials Chemistry

Understanding High-Salt and Cold Adaptation of a Polyextremophilic Enzyme The haloarchaeon <i>Halorubrum lacusprofundi</i> is among the few polyextremophilic organisms capable of surviving in one of the most extreme aquatic environments on Earth, the Deep Lake of Antarctica (-18 °C to +11.5 °C and 21-28%, w/v salt content). Hence, <i>H. lacusprofundi</i> has been proposed as a model for biotechnology and astrobiology to investigate potential life beyond Earth. To understand the mechanisms that allow proteins to adapt to both salinity and cold, we structurally (including X-ray crystallography and molecular dynamics simulations) and functionally characterized the β-galactosidase from <i>H. lacusprofundi</i> (hla_bga). Recombinant hla_bga (produced in <i>Haloferax volcanii</i>) revealed exceptional stability, tolerating up to 4 M NaCl and up to 20% (v/v) of organic solvents. Despite being cold-adapted, hla_bga was also stable up to 60 °C. Structural analysis showed that hla_bga combined increased surface acidity (associated with halophily) with increased structural flexibility, fine-tuned on a residue level, for sustaining activity at low temperatures. The resulting blend enhanced structural flexibility at low temperatures but also limited protein movements at higher temperatures relative to mesophilic homologs. Collectively, these observations help in understanding the molecular basis of a dual psychrophilic and halophilic adaptation and suggest that such enzymes may be intrinsically stable and functional over an exceptionally large temperature range. Psychrophile ; Mesophile ; Extreme environment ; Extremophile ; Halophile ; Chemistry ; Adaptation (eye) ; Molecular dynamics ; Enzyme ; Haloferax volcanii ; Biology ; Thermophile ; Materials science ; Biochemistry ; Genetics ; Bacteria Enzyme Structure and Function ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications
Authors: Christy Maksoudian | Neshat Saffarzadeh | Evelien Hesemans | Nora Dekoning | Kiana Buttiens | Stefaan J. Soenen
Source: Nanoscale Advances (review, 2020-01-01)
Field: Materials Science — Materials Chemistry

Role of inorganic nanoparticle degradation in cancer therapy Nanomaterials are currently widely exploited for their potential in the development of novel cancer therapies, and so far, mainly nanoparticles (NPs) consisting of liposomes and polymers have made their way into the clinic. However, major bottlenecks for the clinical translation of other types of NPs (<i>i.e.</i> inorganic) are the lack of knowledge concerning their long-term distribution <i>in vivo</i> and their potential toxicity. To counter this, various research groups have worked on soluble NPs, such as zinc oxide (ZnO), copper oxide (CuO), and silver (Ag), which tend to dissolve spontaneously into their ionic form, releasing toxic metal ions and leading to reactive oxygen species (ROS) generation when exposed to cellular environments. By fine-tuning the dissolution kinetics of these NPs, it is possible to control the level of ROS production and thus cytotoxicity to selectively destroy tumor tissue. Specifically, cancer cells tend to exhibit a higher basal level of oxidative stress compared to normal cells due to their higher metabolic rates, and therefore, by engineering NPs that generate sufficient ROS that barely exceed toxic thresholds in cancer cells, normal cells will only experience reversible transient damage. This review focuses on the use of these soluble inorganic NPs for selective cancer therapy and on the various <i>in vitro</i> and <i>in vivo</i> studies that have aimed to control the dissolution kinetics of these NPs, either through particle doping or surface modifications. Degradation (telecommunications) ; Cancer therapy ; Nanoparticle ; Cancer ; Chemistry ; Medicine ; Chemical engineering ; Nanotechnology ; Materials science ; Internal medicine ; Computer science ; Engineering Nanoparticles: synthesis and applications ; Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications
Authors: Stefano Diodati | Richard I. Walton | Simone Mascotto | Silvia Gross
Source: Inorganic Chemistry Frontiers (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Low-temperature wet chemistry synthetic approaches towards ferrites Solution chemistry allows the crystallisation of range of iron oxides, including MFe<sub>2</sub>O<sub>4</sub>spinels, MFeO<sub>3</sub>perovskites and hexaferrites, such as BaFe<sub>12</sub>O<sub>19</sub>, with nanoscale crystallinity and properties suitable for fields such as catalysis and electronics. Crystallinity ; Nanoscopic scale ; Catalysis ; Crystallization ; Materials science ; Chemical engineering ; Inorganic chemistry ; Chemistry ; Nanotechnology ; Crystallography ; Organic chemistry Magnetic Properties and Synthesis of Ferrites ; Nanomaterials for catalytic reactions ; Advancements in Battery Materials
Authors: Kang‐Jia Lu | Dieling Zhao | Yuanmiaoliang Chen | Jian Chang | Tai‐Shung Chung
Source: npj Clean Water (article, 2020-06-25)
Field: Materials Science — Surfaces, Coatings and Films

Rheologically controlled design of nature-inspired superhydrophobic and self-cleaning membranes for clean water production Abstract Conventional fabrication technologies of superhydrophobic and self-cleaning membranes for wastewater treatment often involve complex surface modifications, and massive usage of nanomaterials or organic solvents. In this work, we developed a pure rheological spray-assisted nonsolvent induced phase separation (SANIPS) approach to fabricate self-cleaning polyvinylidene fluoride (PVDF) membranes with high porosity and hierarchical micro/nanostructures. The resultant membranes exhibit water contact angles and sliding angles in the range of 151.9–156.2° and 9.6–22.6°, respectively. We found that the spraying step caused local distortion of the membrane surface and induced a two-stage phase inversion, leading to the formation of multilevel polymeric crystal structures. Moreover, the morphological structures and other membrane properties (e.g., mechanical strength and liquid entry pressure) could be tuned by applying spraying materials with different physicochemical properties. The superior anti-wetting and self-cleaning properties of the resultant membranes have been demonstrated by treating hypersaline wastewater, comprising 10% sodium chloride and 2000 p.p.m. Rose Bengal dye via direct contact membrane distillation (DCMD) tests. The SANIPS membrane showed a remarkably stable vapor flux of 36.0 kg m −2 h at a feed temperature of 60 °C, and a salt rejection over 99.9% throughout the long-term test of 100 h. We envision this facile and green fabrication method will pave the way for large-scale production of superhydrophobic and self-cleaning membranes for diverse water treatment processes. Membrane ; Membrane distillation ; Contact angle ; Materials science ; Polyvinylidene fluoride ; Phase inversion ; Chemical engineering ; Wetting ; Porosity ; Fabrication ; Membrane emulsification ; Nanotechnology ; Desalination ; Composite material ; Polymer ; Chemistry Surface Modification and Superhydrophobicity ; Membrane Separation Technologies ; Advanced Sensor and Energy Harvesting Materials
Authors: Mohamed A. Abdelaziz | Fotouh R. Mansour | Neil D. Danielson
Source: Analytical and Bioanalytical Chemistry (article, 2020-10-23)
Field: Chemistry — Analytical Chemistry

A gadolinium-based magnetic ionic liquid for dispersive liquid–liquid microextraction Chemistry ; Chromatography ; Solvent ; High-performance liquid chromatography ; Extraction (chemistry) ; Detection limit ; Ionic liquid ; Disperser ; Aqueous solution ; Analytical Chemistry (journal) ; Materials science Analytical chemistry methods development ; Electrochemical Analysis and Applications ; Analytical Chemistry and Sensors