jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: César G. Pachón | Javier O. Pinzón-Arenas | Róbinson Jiménez Moreno
Source: International Journal on Advanced Science Engineering and Information Technology (article, 2020-10-30)
Field: Chemistry — Analytical Chemistry

Fruit Identification and Quality Detection by Means of DAG-CNN The design of quality control systems in food has become essential in research to guarantee an adequate state for its consumption. It is necessary to develop automatic and efficient systems that can verify its state before its distribution. This paper presents an algorithm based on deep learning for the identification of fruits and the state they are in, oriented to changes in camera focus, capture angles, lighting variations, and change of backgrounds. In this case, 8 types of fruit are chosen to identify what kind of fruit is being observed and if it is in good condition or not, establishing a total of 16 categories that the network must classify. A convolutional neural network with a DAG structure is proposed for the learning of fruits and their state. A graphic user interface is designed to allow the acquisition of the image of the fruit and its subsequent classification in some of the categories. A 94.43% accuracy was obtained in the 1600 test images classification, with approximate processing times of 45-55 milliseconds. Therefore, it can be concluded that the proposed system based on Deep learning can adequately perform a process of detection of types of fruits and their state. Convolutional neural network ; Computer science ; Identification (biology) ; Artificial intelligence ; Focus (optics) ; Process (computing) ; Deep learning ; State (computer science) ; Quality (philosophy) ; Pattern recognition (psychology) ; Artificial neural network ; Machine learning ; Data mining ; Algorithm Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Chinchinada V. S. L. Kalyani | Motepalli Sunil Kumar | Tella Nagaraju
Source: International Journal of Research in Engineering Science and Management (article, 2020-11-27)
Field: Materials Science — Materials Chemistry

TEG Cascaded Solar PV System with Enhanced Efficiency by Using the PSO MPPT Boost Converter Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a boost converter having a particle swarm optimization (PSO) MPPT algorithm was added to the TEG modeling. After the TEG output equations were determined, the TEG modeling was performed based on manufacturer data sheets. Thanks to the TEG model and the boost converter with PSO MPPT, the maximum power was tracked with a value of 98.64% and the power derived from the TEG was nearly unaffected by the load changes. The power outputs obtained from the system with and without MPPT were compared to emphasize the importance of MPPT. These simulation values were verified by using an experimental setup. Ultimately, the proposed modeling provides a system of TEGs and a boost converter having PSO MPPT. Maximum power point tracking ; Maximum power principle ; Thermoelectric generator ; Boost converter ; Photovoltaic system ; MATLAB ; Particle swarm optimization ; Computer science ; Power (physics) ; Control theory (sociology) ; Electrical engineering ; Inverter ; Thermoelectric effect ; Physics ; Engineering ; Algorithm ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Hybrid Renewable Energy Systems
Authors: Valentina Mărăscu | Cristian Stancu | Veronica Sătulu | Anca Bonciu | C. Grisolia | Gheorghe Dinescu
Source: Applied Sciences (article, 2020-09-30)
Field: Materials Science — Materials Chemistry

Material Erosion and Dust Formation during Tungsten Exposure to Hollow-Cathode and Microjet Discharges Tungsten erosion and dust occurrence are phenomena of great interest for fusion technology. Herein, we report results concerning the material damage and dust formation in the presence of high temperature and large area or concentrated discharges in helium and argon. In order to generate adequate plasmas, we used tungsten electrodes in two experimental discharge systems, namely a hollow discharge and a microjet discharge. In both exposure cases, we noticed surface modification, which was assigned to sputtering, melting, and vaporization processes, and a significant dust presence. We report the formation on electrode surfaces of tungsten fuzz, nano-cones, nanofibers, and cauliflower- and faced-like particles, depending on the discharge and gas type. Dust with various morphologies and sizes was collected and analyzed with respect to the morphology, size distribution, and chemical composition. We noticed, with respect to erosion and particle formation, common behaviors of W in both laboratory and fusion facilities experiments. Tungsten ; Vaporization ; Materials science ; Erosion ; Plasma ; Argon ; Sputtering ; Cathode ; Metallurgy ; Nanotechnology ; Atomic physics ; Chemistry ; Thin film Fusion materials and technologies ; Diamond and Carbon-based Materials Research ; Vacuum and Plasma Arcs
Authors: Minqiang Jiang
Source: Science China Physics Mechanics and Astronomy (article, 2020-08-07)
Field: Materials Science — Ceramics and Composites

Metallic glasses: A type of promising energetic materials Materials science ; Type (biology) ; Nanotechnology ; Engineering physics ; Physics ; Geology Glass properties and applications ; Metallic Glasses and Amorphous Alloys ; Material Science and Thermodynamics
Authors: Caroline Fátima Casanova | Marina Andreia De Souza | Bruno Fischer | Rosicler Colet | Cristiane Michele Marchesi | Jamile Zeni | Rogério Marcos Dallago | Natália Paroul | Rogério Luís Cansian | Geciane Toniazzo Backes | C Man | U Rahman | A Sahar | A Ishaq | R Aadil | T Zahoor | M Ahmad | J-Y Wu | H-I Hsiao | N Ndraha | H.-I Hsiao | J Vlajic | M.-F Yang | V Lin | -T | M Mataragas | V Bikouli | M Korre | A Sterioti | P Skandamis | S Jol | A Kassianenko | K Wszol | J Oggel | W Zeng | K Vorst | W Brown | B Marks | S Jeong | F Prez-Rodrguez | E Ryser | J Huang | Y Luo | B Zhou | J Zheng | X Nou | A Brizio | C Prentice | S Pourjavaher | H Almasi | S Meshkini | S Pirsa | E Parandi | N Maftoonazad | H Ramaswamy | G Kuntzler | A Costa | P Brizio | G Morais | M Hussain | A Asiri | M Arshad | M Rahman | J Kerry | M O'grady | S Hogan | J Riu | B Giussani | C Griesche | A Baeumner | D Liu | J Wang | L Wu | Y Huang | Y Zhang | M Zhu | Y Wang | Z Zhu | C Yang | A Brody | B Bugusu | J Han | C Sand | T Mchugh | N Mai | M Gudjnsdttir | H Lauzon | K Sveinsdttir | E Martinsdttir | H Audorff | W Reichstein | D Haarer | S Bogason | S Arason | C Yoshida | V Maciel | M Mendona | T Franco
Source: Biointerface Research in Applied Chemistry (article, 2020-09-11)
Field: Materials Science — Biomaterials

Development of Enzymatic – Colorimetric Time – Temperature Integrator for Smart Packaging A new enzymatic-colorimetric time-temperature integrator (ECTTI) to evaluate temperature abuse in refrigerated products was developed with Tributyrin, pH indicator, and lipase Calb. The kinetic behavior of the ECTTI (0.01 µL.L-1 enzyme) was assessed at 5, 10, 15, 20, and 25ºC, evaluating changes in pH (≤7.2) and color (ΔE ≥12). Storage at 5°C provided stability of the enzyme indicator for 16 days, and temperature abuses caused stability reduction to 15, 10, 0.5 0.3 days, with 10, 15, 20, and 25ºC of storage, respectively. The sequential abuse of temperature stability of ECTTI was assessed by exposure at 5.0ºC for 2 h and 25ºC for 1 or 5 min, returning to 5.0ºC for another 2 h, until the change in pH and color. The ECTTI subjected to temperature abuses for 5 and 1 min/25°C, remained stable for 5 and 9 cycles, respectively. The results of ECTTI stability before application, obtained with separate buffer/enzyme/water + substrate/indicator solutions, stored at 5 or 25ºC, before the reactive mixing of solutions, kept their stability, demonstrating the possibility of use as a tool against the temperature abuse conditions. Tributyrin ; Chemistry ; Substrate (aquarium) ; pH indicator ; Chromatography ; Lipase ; Enzyme ; Biochemistry ; Organic chemistry Nanocomposite Films for Food Packaging ; Advanced Chemical Sensor Technologies ; Biochemical Analysis and Sensing Techniques
Authors: Yufei Feng | Lin Teng | Yanli Wang | Yanyu Gao | Yuxuan Ma | Haichun Zhou | Guofeng Cai | Ji Li
Source: Journal of Chromatographic Science (article, 2020-11-02)
Field: Chemistry — Spectroscopy

Using Spectrum-Effect Relationships Coupled with LC–TOF–MS to Screen Anti-arrhythmic Components of the Total Flavonoids in <i>Hypericum attenuatum</i> Extracts This research explored the HPLC fingerprints of Hypericum attenuatum Choisy, which has anti-arrhythmic activity. HPLC was adopted to perform a determination of chemical fingerprints of H. attenuatum specimens acquired through seven distinct sources. The anti-arrhythmic activity of each H. attenuatum sample was obtained through pharmacodynamics experiments in animals. A regression analysis and correlation analysis were utilized to calculate the relationship of the peak and pharmacological effectiveness with the identified peak. Peaks numbered 5, 7, 13 and 14 in the fingerprint were regarded as the likely anti-arrhythmic agents. The fingerprint was compared with reference standards for identification of the correlative peaks. Liquid chromatography-time-of-flight-mass spectrometry was applied to identify its structure. As a consequence, a universal model was established for the utilization of HPLC to investigate anti-arrhythmic activity and the spectrum-effect relationship among H. attenuatum. This model is available for the discovery of the major bioactive constituents of Hypericum. Chemistry ; Chromatography ; Hypericum ; Fingerprint (computing) ; High-performance liquid chromatography ; Traditional medicine Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies ; Traditional Chinese Medicine Analysis
Authors: Tamás Langó | Zoltán Gergő Pataki | Lilla Turiák | András Ács | Julia K. Varga | György Várady | Nóra Kucsma | László Drahos | Gábor Tusnády
Source: Scientific Reports (article, 2020-06-01)
Field: Chemistry — Spectroscopy

Partial proteolysis improves the identification of the extracellular segments of transmembrane proteins by surface biotinylation Transmembrane proteins (TMP) play a crucial role in several physiological processes. Despite their importance and diversity, only a few TMP structures have been determined by high-resolution protein structure characterization methods so far. Due to the low number of determined TMP structures, the parallel development of various bioinformatics and experimental methods was necessary for their topological characterization. The combination of these methods is a powerful approach in the determination of TMP topology as in the Constrained Consensus TOPology prediction. To support the prediction, we previously developed a high-throughput topology characterization method based on primary amino group-labelling that is still limited in identifying all TMPs and their extracellular segments on the surface of a particular cell type. In order to generate more topology information, a new step, a partial proteolysis of the cell surface has been introduced to our method. This step results in new primary amino groups in the proteins that can be biotinylated with a membrane-impermeable agent while the cells still remain intact. Pre-digestion also promotes the emergence of modified peptides that are more suitable for MS/MS analysis. The modified sites can be utilized as extracellular constraints in topology predictions and may contribute to the refined topology of these proteins. Topology (electrical circuits) ; Biotinylation ; Proteolysis ; Transmembrane protein ; Membrane topology ; Extracellular ; Transmembrane domain ; Characterization (materials science) ; Computational biology ; Chemistry ; Biology ; Amino acid ; Biochemistry ; Materials science ; Nanotechnology ; Receptor ; Enzyme ; Mathematics Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; RNA and protein synthesis mechanisms
Authors: Qinyu Wang | Gennaro Senatore | K.M.B. Jansen | Arjan Habraken | Patrick Teuffel
Source: Frontiers in Built Environment (article, 2020-10-30)
Field: Materials Science — Polymers and Plastics

Vibration Suppression Through Variable Stiffness and Damping Structural Joints This paper introduces a new semi-active strategy for vibration control of reticular structures (i.e. trusses and frames) equipped with variable stiffness and damping joints which consist of a shape memory polymer (SMP) core reinforced by an SMP-aramid composite skin. When the joints are actuated to the transition temperature through thermal actuation, the SMP core transitions from a glassy to a rubbery state through a viscoelastic region, which causes a stiffness reduction and an increase of damping. The mechanic behavior of the joint can be thought of as transitioning from a moment to a pin connection. This way, it is possible to cause a shift of the structure natural frequencies and to increase damping, which is employed to obtain a significant reduction of the dynamic response. This paper comprises two parts: 1) characterization of a variable stiffness and damping material model through experimental testing; 2) numerical simulations of a truss bridge and a four-story frame, which are equipped with variable stiffness and damping joints. The truss bridge (case A) is subjected to a resonance and a moving load while the four-story frame (case B) is subjected to El Centro earthquake loading. For case A under resonance loading, the dynamic response can be reduced exclusively through a frequency shift and ignoring viscoelastic effects. For case A under moving load and case B under earthquake loading, vibration suppression is mostly caused by the increase of damping due to viscoelastic effects. Control time delays due to joint heating have been included in the analysis. When the joints are actuated to the transition range 55-65°C, which is specific to the SMP adopted in this study, the acceleration peak amplitude reduces by up to 95% and 47%, for case A and case B, respectively. For both cases, damping increases by up to 2.2% from undamped conditions (25ºC). This work has shown that the adoption of variable stiffness and damping structural joints has great potential to enable a new and effective semi-active control strategy to significantly reduce the structure response under a wide range of dynamic loading conditions. Structural engineering ; Viscoelasticity ; Stiffness ; Truss ; Vibration ; Materials science ; Reduction (mathematics) ; Natural frequency ; Joint (building) ; Engineering ; Composite material ; Physics ; Acoustics ; Mathematics Polymer composites and self-healing ; Structural Engineering and Vibration Analysis ; Vibration Control and Rheological Fluids
Authors: Miroslava Nedyalkova | Sergio Madurga | Davide Ballabio | Ralitsa Robeva | Julia Romanova | Ilia Kichev | Атанаска Еленкова | Vasil Simeonov
Source: Open Chemistry (article, 2020-08-11)
Field: Chemistry — Analytical Chemistry

Diabetes mellitus type 2: Exploratory data analysis based on clinical reading Abstract Diabetes mellitus type 2 (DMT2) is a severe and complex health problem. It is the most common type of diabetes. DMT2 is a chronic metabolic disorder that affects the way your body metabolizes sugar. With DMT2, your body either resists the effects of insulin or does not produce sufficient insulin to continue normal glucose levels. DMT2 is a disease that requires a multifactorial approach of controlling that includes lifestyle change and pharmacotherapy. Less than ideal management increases the risk of developing complications and comorbidities such as cardiovascular disease and numerous social and economic penalties. That is why the studies dedicated to the pathophysiological mechanisms and the treatment of DMT2 are extremely numerous and diverse. In this study, exploratory data analysis approaches are applied for the treatment of clinical and anthropometric readings of patients with DMT2. Since multivariate statistics is a well-known method for classification, modeling and interpretation of large collections of data, the major aim of the present study was to reveal latent relations between the objects of the investigation (group of patients and control group) and the variables describing the objects (clinical and anthropometric parameters). In the proposed method by the application of hierarchical cluster analysis and principal component analysis it is possible to identify reduced number of parameters which appear to be the most significant discriminant parameters to distinguish between four patterns of patients with DMT2. However, there is still lack of multivariate statistical studies using DMT2 data sets to assess different aspects of the problem like optimal rapid monitoring of the patients or specific separation of patients into patterns of similarity related to their health status which could be of help in preparation of data bases for DMT2 patients. The outcome from the study could be of custom for the selection of significant tests for rapid monitoring of patients and more detailed approach to the health status of DMT2 patients. Multivariate analysis ; Diabetes mellitus ; Anthropometry ; Medicine ; Type 2 Diabetes Mellitus ; Multivariate statistics ; Principal component analysis ; Disease ; Internal medicine ; Exploratory data analysis ; Computer science ; Endocrinology ; Statistics ; Data mining ; Mathematics Spectroscopy and Chemometric Analyses ; Advanced Statistical Methods and Models ; Statistical and Computational Modeling
Authors: Kyung Ju Jang | Tae‐Young Heo | Seon Hwa Jeong
Source: BioResources (article, 2020-10-15)
Field: Chemistry — Analytical Chemistry

Classification option for Korean traditional paper based on type of raw materials, using near-infrared spectroscopy and multivariate statistical methods Depending on the different types of raw materials used to produce hanji, a Korean traditional handmade paper, there can be significant differences in the durability and mechanical properties of the final product. In this study, near-infrared spectroscopy (NIR) combined with multivariate statistical methods were used to confirm the classification possibility of hanji based on the various type of raw materials. The hanji papers were prepared from paper mulberry trees, cooking agents, and mucilage. Altogether, a total of 60 hanji spectra were collected by NIR. Then, the 60 spectra were grouped into four categories: the control, paper mulberry, cooking agent, and mucilage type based on each of the types of raw materials contained in the hanji. Three different classification algorithms – partial least squares discriminant analysis (PLS-DA), support vector machines (SVM), and random forest (RF) – were used to classify the hanji types. The best hanji material classification performance was obtained when the hanji samples were classified according to paper mulberry type, wherein the prediction accuracies of PLS-DA, SVM, and RF were 100%, 100%, and 98%, respectively. These results suggested that NIR in combination with multivariate statistical methods can be used for hanji material classification. Linear discriminant analysis ; Raw material ; Pattern recognition (psychology) ; Mucilage ; Mathematics ; Partial least squares regression ; Artificial intelligence ; Multivariate statistics ; Near-infrared spectroscopy ; Support vector machine ; Materials science ; Statistics ; Computer science ; Chemistry ; Biology ; Botany Spectroscopy and Chemometric Analyses ; Cultural Heritage Materials Analysis ; Wood and Agarwood Research
Authors: Randy J. Read | Robert D. Oeffner | Airlie J. McCoy
Source: Acta Crystallographica Section D Structural Biology (article, 2020-02-25)
Field: Materials Science — Materials Chemistry

Measuring and using information gained by observing diffraction data The information gained by making a measurement, termed the Kullback-Leibler divergence, assesses how much more precisely the true quantity is known after the measurement was made (the posterior probability distribution) than before (the prior probability distribution). It provides an upper bound for the contribution that an observation can make to the total likelihood score in likelihood-based crystallographic algorithms. This makes information gain a natural criterion for deciding which data can legitimately be omitted from likelihood calculations. Many existing methods use an approximation for the effects of measurement error that breaks down for very weak and poorly measured data. For such methods a different (higher) information threshold is appropriate compared with methods that account well for even large measurement errors. Concerns are raised about a current trend to deposit data that have been corrected for anisotropy, sharpened and pruned without including the original unaltered measurements. If not checked, this trend will have serious consequences for the reuse of deposited data by those who hope to repeat calculations using improved new methods. Divergence (linguistics) ; Statistics ; Kullback–Leibler divergence ; Computer science ; Observational error ; Upper and lower bounds ; Probability distribution ; Algorithm ; Mathematics ; Data mining ; Econometrics X-ray Diffraction in Crystallography ; Enzyme Structure and Function ; Crystallization and Solubility Studies