jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: V Viswanatha | A C Ramachandra | Rayyan Mohammed | Sai Kiran | Parth Sheetal Kumthekar
Source: Saudi Journal of Engineering and Technology (article, 2023-01-26)
Field: Chemistry — Analytical Chemistry

Support Vector Machine Implementation to Separate Linear and Non-Linear Dataset This paper presents the implementation of separating the linear and non-linear data using support vector machine (SVM) algorithm. First let us understand what linear and non-linear datasets are. Linear datasets are the data that can be easily separable using a straight line. Such data are usually easy to implement in Artificial Neural Networks as they require a smaller number of hidden layers for its computation. Less layers implies a smaller number of weights assigned to the nodes present between the layers and less amount of time needed is needed to compute and update the weights for the current neural network. Hence linear datasets are easy to train and model. Whereas non-linear datasets are those datasets which cannot be separated by a straight line. For such datasets more hidden layers and weights are required and also more time and computational power is needed for a system to update the weights and train the model to give a better and sophisticated output data. As a result, training and modeling such neural network is tedious due to its complexity. To solve this problem SVM comes into picture. SVM stands for Support Vector Machine which is a machine or an algorithm that helps in classification and diversifying the data given to it. The data provided to the Support Vector Machine (SVM) should be a labeled one. Then these datasets are given to a training model where the training process of the neural network is being undergone. Once the training is completed, the next step is to predict the output. For this process we have to provide a new data that may or may not belong to the dataset, so that the neural network can predict the output of it. If the prediction is wrong, again the training is done until we get the actual output matching with the desired output given by the designer for verification purposes. This is the basic working process under the SVM algorithm. The linear data that is used for this separation is an Iris dataset that contains various information about the different plant-life growing from 2002-2004. Support vector machine ; Artificial neural network ; Computer science ; Process (computing) ; Linear model ; Artificial intelligence ; Data mining ; Machine learning ; Line (geometry) ; Computation ; Algorithm ; Pattern recognition (psychology) ; Mathematics Spectroscopy and Chemometric Analyses ; Neural Networks and Applications ; Smart Agriculture and AI
Authors: О. Shorinov | S. Polyvianyi
Source: New Materials and Technologies in Metallurgy and Mechanical Engineering (article, 2023-01-09)
Field: Materials Science — General Materials Science

DETERMINATION OF ENERGY PARAMETERS OF Ni+Al2O3 POWDER PARTICLES IN A SUPERSONIC NOZZLE DURING COLD GAS-DYNAMIC SPRAYING USING THE ANALYTICAL METHOD Purpose. To calculate the temperature and velocity of nickel and aluminum oxide particles in the supersonic flow in the low-pressure cold gas-dynamic spraying nozzle. To investigate the effect of gas parameters at the nozzle inlet, in particular temperature and pressure, on the velocity and temperature of particles at the nozzle outlet.&#x0D; Research methods. The calculation of the temperature-velocity characteristics of the powder particles is performed after determining the parameters of the gas flow in the supersonic nozzle channel using well known gas-dynamic dependencies. The initial data for the calculation are the following: the geometry of the nozzle, the temperature and pressure of the gas (air) at the nozzle inlet. The density of the material from which particles are obtained, as well as their diameter, were taken into account in the calculation of the energy parameters. Nickel particles with a diameter of 25 µm and aluminum oxide particles with a diameter of 22 µm were used.&#x0D; Results. Based on the calculations results, graphs of changes in the velocities and temperatures of the particles of the investigated powders, as well as working gas, in the channel of the low-pressure cold gas-dynamic spraying supersonic nozzle were developed. The dependences of the temperature-velocity parameters of the particles at the nozzle exit in the range of initial values of temperature at the nozzle inlet from 300 to 600 C° and pressure from 0.6 to 1.0 MPa were also developed.&#x0D; Scientific novelty. The influence of the initial parameters of the gas at the nozzle inlet in a wide range of values on the temperature and velocity of nickel and aluminum oxide particles during the low-pressure cold gas-dynamic spraying is shown.&#x0D; Practical value. The obtained results can be used to determine rational spraying parameters in the development of technological processes of deposition of protective and restorative coatings from Ni+Al2O3 powder mixture. Nozzle ; Supersonic speed ; Materials science ; Inlet ; Discharge coefficient ; Mechanics ; Range (aeronautics) ; Particle velocity ; Particle (ecology) ; Thermodynamics ; Composite material ; Mechanical engineering ; Physics Material Properties and Applications ; Surface Treatment and Coatings ; Coal Combustion and Slurry Processing
Authors: Dapeng Jiang | Yizhuo Zhang | Yilin Ge | Keqi Wang
Source: Chemosensors (article, 2023-08-23)
Field: Chemistry — Analytical Chemistry

Fusion Recalibration Method for Addressing Multiplicative and Additive Effects and Peak Shifts in Analytical Chemistry Analytical chemistry relies on the qualitative and quantitative analysis of multivariate data obtained from various measurement techniques. However, artifacts such as missing data, noise, multiplicative and additive effects, and peak shifts can adversely affect the accuracy of chemical measurements. To ensure the validity and accuracy of results, it is crucial to preprocess the data and correct for these artifacts. This paper proposes a fusion recalibration algorithm, called Spectral Offset Recalibration (SOR), that combines the Extended Multiplicative Signal Correction (EMSC) and Correlation-Optimized Warping (COW) algorithms to address both multiplicative and additive effects and peak shifts. The algorithm incorporates prior spectroscopic knowledge to down-weight or disregard spectral regions with strong absorption or significant distortion caused by peak alignment algorithms. Experimental validation on wood NIR datasets and simulated datasets demonstrates the effectiveness of the proposed method. The fusion recalibration approach offers a comprehensive solution for accurate analyses and predictions in analytical chemistry by mitigating the impact of artifacts. Multiplicative function ; Algorithm ; Offset (computer science) ; Distortion (music) ; Fusion ; Computer science ; Image warping ; Biological system ; Mathematics ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Monika Vargová | Łukasz Bołoz | Miroslava Ťavodová | Richard Hnilica
Source: AgriEngineering (article, 2023-03-07)
Field: Materials Science — Materials Chemistry

Increasing the Durability of Tools for Forest Road Maintenance To ensure the care of forests, it is necessary to make them sufficiently accessible by forest roads. The basic working tool are hammers, or round shanks of various shapes, composed of a body and a tip. They are subject to a strong abrasive environment, which often leads to damage up to the complete destruction of the functional part of the tool. For these reasons, it is necessary to deal with the possibilities for increasing their lifetime. One of the possibilities of increasing the service life of these tools is hardfacing by welding. The article deals with the abrasive resistance of the original material of the tool and the hardfacing materials. Based on the chemical analysis of the base material of the tool, we found that the tool is made of manganese steel 38Mn6. This material was used as a standard and was compared with the hardfacing materials Abradur 58, E DUR 600, UTP DUR 600 and OK 84.58. Electron microscopy was used to evaluate the microstructure. Next, the Rockwell hardness measurement was performed on the samples. The original tool material 38Mn6 reached the lowest hardness value, namely, 21 HRC. The highest value was reached by the hardfacing material E DUR 600, namely, 59 HRC. Subsequently, a test of resistance to abrasive wear was performed according to GOST 23.208-79. Based on this test, we can conclude that the highest value of resistance to abrasive wear was achieved by Abradur 58. Even though the hardness of this coating was slightly lower than the hardfacing material E DUR 600, specifically 56 HRC, we can state that this hardfacing material (Abradur 58) achieved the best results among the investigated materials. Hardfacing ; Abrasive ; Welding ; Metallurgy ; Materials science ; Microstructure ; Cast iron ; Service life ; Durability ; Coating ; Composite material Metal Alloys Wear and Properties ; Advanced materials and composites ; Tunneling and Rock Mechanics
Authors: Juan Ramírez | Esteban Yépez | Fernando Pantoja-Suárez | Eliana Acurio | Fabián Pérez | Leonardo Basile
Source:  (article, 2023-12-06)
Field: Materials Science — Materials Chemistry

Design and Construction of a High-Current Capacitor Bank for Flash Graphene Synthesis This paper introduces the design and fabrication of a versatile capacitor bank developed specifically for its integration within the innovative flash joule heating (FJH) technique, aimed at synthesizing graphene. The capacitor bank offers two adaptable configurations, providing options for capacitance at 180,000 µF and 68,000 µF, combined with a maximum charging capability of 400 V. This equipment facilitates the swift conversion of carbon-containing materials into graphene by harnessing transient current discharges. The proposed capacitor bank facilitates the execution of comprehensive research pertaining to graphene production from diverse carbon sources, opening an opportunity for advancing exploration within this rapidly evolving field of study in Ecuador. Graphene ; Capacitor ; Flash (photography) ; Capacitance ; Materials science ; Joule heating ; Supercapacitor ; Current (fluid) ; Fabrication ; Joule (programming language) ; Nanotechnology ; Electrical engineering ; Computer science ; Engineering physics ; Engineering ; Voltage ; Electrode ; Physics ; Efficient energy use Graphene research and applications ; Radiation Effects in Electronics ; Graphene and Nanomaterials Applications
Authors: Ximei Li | Guang Jin | Mingcong Deng
Source: Dynamics (article, 2023-04-17)
Field: Materials Science — Materials Chemistry

Nonlinear Fault-Tolerant Vibration Control for Partial Actuator Fault of a Flexible Arm This paper presents a nonlinear fault-tolerant vibration control system for a flexible arm, considering partial actuator fault. A lightweight flexible arm with lower stiffness will inevitably cause vibration which will impair the performance of the high-precision control system. Therefore, an operator-based robust nonlinear vibration control system is integrated by a double-sided interactive controller actuated by the Shape Memory Alloy (SMA) actuators for the flexible arm. Furthermore, to improve the safety and reliability of the safety-critical application, fault-tolerant dynamics for partial actuator fault are considered as an essential part of the proposed control system. The experimental cases are set to the partial actuator as faulty conditions, and the proposed vibration control scheme has fault-tolerant dynamics which can still effectively stabilize the vibration displacement. The reconfigurable controller improves the fault-tolerant performance by shortening the vibration time and reducing the vibration displacement of the flexible arm. In addition, compared with a PD controller, the proposed nonlinear vibration control has better performance than the traditional controller. The experimental results show that the effectiveness of the proposed method is confirmed. That is, the safety and reliability of the proposed fault-tolerant vibration control are verified even if in the presence of an actuator fault. Control theory (sociology) ; Actuator ; Fault tolerance ; Vibration ; Controller (irrigation) ; Nonlinear system ; Fault (geology) ; Vibration control ; Engineering ; Displacement (psychology) ; Control engineering ; Computer science ; Control (management) Shape Memory Alloy Transformations ; Vibration Control and Rheological Fluids ; Structural Engineering and Vibration Analysis
Authors: A.I. Voronina | A.V. Rybina
Source: Biomedical Chemistry Research and Methods (article, 2023-01-01)
Field: Chemistry — Spectroscopy

A Program for Predicting the Retention Time of Peptides with Post-Translational Modifications This paper describes the Retention Time Predictor (RTP) program and web service for predicting the retention time of peptides on a chromatographic column in mass spectrometry experiments. Taking into account post-translational modifications of peptides the program represents a modification of the well-known SSRCalc version 3 (Krokhin, Anal. Chem. 2006, 78(22), 7785-7795). The values of retention coefficients for modified amino acid residues and the algorithm for calculating the isoelectric point value were from the pIPredict program (Skvortsov et al., Biomed. Chem. Res. Meth. 2021, 4(4), e00161). Modifications described in the program include (i) Tandem Mass Tag (TMT) and Isobaric Tags for Relative and Absolute Quantification (iTRAQ) labels; (ii) acetylation, formylation, and methylation of the N-terminal residue and/or lysine side chain; (iii) carbamidomethylation of cysteine, asparagine, and glutamic acid residues; (iv) oxidation and double oxidation of methionine and proline residues; (v) phosphorylation of serine, threonine, and tyrosine residues; (vi) C-terminal amidation of lysine and arginine residues; (vii) formation of propionamide with a cysteine residue. Retention coefficient estimation was based on data from 25 mass spectrometry experiments for which identification was performed from the raw data deposited in the ProteomeXchange database. The RTP program and web service are freely available at http://lpcit.ibmc.msk.ru/RTP. Chemistry ; Tandem mass spectrometry ; Threonine ; Chromatography ; Lysine ; Serine ; Retention time ; Cysteine ; Isobaric labeling ; Mass spectrometry ; Histidine ; Residue (chemistry) ; Methionine ; Peptide ; Amino acid ; Biochemistry ; Phosphorylation ; Protein mass spectrometry ; Enzyme Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Yiran Li | Jiaquan Wu | Fei Ye | Xinyu Zhang
Source: AIP Advances (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Abnormal thermal conduction and stochastic resonance phenomenon in a finite lattice system This paper studies the thermal conduction of Frenkel–Kontorva (FK)-ϕ4 lattices with the finite number of atoms under a periodic force. Through numerical simulations, we find that in the thermal conduction of non-linear lattices, external periodic signals can act in conjunction with noise to create stochastic resonance behaviors and that some adjustable dynamical parameters, such as the onsite potential of the FK and ϕ4 lattices, the amplitude and frequency of external periodic signals, can regulate heat flux. Our study results can provide a sufficient theoretical basis for the fabrication of thermal devices and the control and utilization of thermal energy. Thermal conduction ; Thermal ; Condensed matter physics ; Stochastic resonance ; Amplitude ; Lattice (music) ; Resonance (particle physics) ; Physics ; Heat flux ; Noise (video) ; Statistical physics ; Materials science ; Mechanics ; Quantum mechanics ; Heat transfer ; Thermodynamics ; Computer science ; Acoustics Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Advanced Thermodynamics and Statistical Mechanics
Authors: Kazi Md. Elias | Mohammad Obaidur Rahman | H. M. Zakir Hossain
Source: Journal of Textile Science and Technology (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

Studying the Effect of Polyester Fiber Blend Ratio and Pilling Cycle on Blended Knit Fabrics Pilling is a severe concern for blended fabrics. The aesthetic look and smoothness are the buyers’ prime requirements. The main focus of the study was to see the pilling behavior from various percentages of polyester fiber blend ratio as well as the different pilling cycles on blended fabrics. The cotton, polyester, and elastane prepared the study fabrics. These fabrics are (90% Cotton/5% Polyester/5% Elastane, 90% Cotton/6% Polyester/4% Elastane, 90% Cotton/7% Polyester/3% Elastane, 90% Cotton/8% Polyester/2% Elastane, and 90% Cotton/9% Polyester/1% Elastane, 85% Cotton/10% Polyester/5% Elastane, 85% Cotton/11% Polyester/4% Elastane, 85% Cotton/12% Polyester/3% Elastane, 85% Cotton/13% Polyester/2% Elastane, and 85% Cotton/ 14% Polyester/1% Elastane, 80% Cotton/15% Polyester/5% Elastane, 80% Cotton/16% Polyester/4% Elastane, 80% Cotton/17% Polyester/3% Elastane, 80% Cotton/18% Polyester/2% Elastane, and 80% Cotton/19% Polyester/1% Elastane). The selected polyester blend ratios were 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18% and 19% respectively. The study used the Martindale pilling tester with 2000, 5000, and 7000 cycles, respectively. The evaluation followed the ISO 12945-2:2000. The study findings are that the polyester fiber blend ratio did not influence the pilling grade on blended fabrics for pilling cycles 2000, and the pilling grade remained constant at 4 - 5. The pilling grade started to deteriorate in pilling cycle 5000 for the fabrics 85%C/10%P/5%E, 85%C/11%P/4%E, 85%C/12%P/3%E, 85%C/ 13%P/2%E, 85%C/14%P/1%E showed the pilling grade 4, and the fabrics made from 80%C/15%P/5%E, 80%C/16%P/4%E, 80%C/17%P/3%E, 80%C/ 18%P/2%E, 80%C/19%P/1%E showed the pilling grade 4, 3, 3, 3, and 3 respectively. For the pilling cycles 7000, the pilling grade further deteriorated for the fabrics 80%C/15%P/5%E, 80%C/16%P/4%E, 80%C/17%P/3%E, 80%C/ 18%P/2%E, 80%C/19%P/1%E showed the pilling grade 3, 3, 2, 2, and 2 respectively. The study finds the dominance of polyester fiber throughout the experiment. The author hopes this study’s outcome will help new researchers, advanced researchers, and the textile industry’s sustainable development research and development team. Polyester ; Materials science ; Composite material Textile materials and evaluations ; Color perception and design ; Color Science and Applications
Authors: Anuradha M. Vibhakar | D. D. Khalyavin | P. Manuel | N. J. Steinke | Lei Zhang | Kazunari Yamaura | Alexei А. Belik | R. D. Johnson
Source: Physical review. B./Physical review. B (article, 2023-08-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Magnetic inhomogeneities in the quadruple perovskite manganite <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mrow><mml:mo>[</mml:mo><mml:msub><mml:mi mathvariant="normal">Y</mml:mi><mml:mrow><mml:mn>2</mml:mn><mml:mo>−</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msub><mml:msub><mml:mi>Mn</mml:mi><mml:mi>x</mml:mi></mml:msub><mml:mo>]</mml:mo></mml:mrow><mml:msub><mml:mi>Mn</mml:mi><mml:mn>6</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>12</mml:mn></mml:msub></mml:mrow></mml:math> The authors show here that the introduction of substitutional disorder in the presence of competing exchange interactions causes the [Y${}_{2\ensuremath{-}x}$Mn${}_{x}$]Mn${}_{6}$O${}_{12}$ quadruple perovskite manganites to develop short-range antiferromagnetic clusters contained in a paramagnetic matrix, before transitioning to a phase characterized by well correlated long-range ferrimagnetic order that coexists with the short-range antiferromagnetic clusters. It is spin doping through the substitution of magnetic Mn ions for nonmagnetic Y ions that gives rise to a spin texture that is inhomogeneous on the nanoscale. Antiferromagnetism ; Ferrimagnetism ; Manganite ; Paramagnetism ; Condensed matter physics ; Perovskite (structure) ; Phase (matter) ; Physics ; Materials science ; Crystallography ; Ferromagnetism ; Chemistry ; Magnetization ; Magnetic field ; Quantum mechanics Magnetic and transport properties of perovskites and related materials ; Advanced Condensed Matter Physics ; Multiferroics and related materials
Authors: Luciana Dias Rocha | Gizele Ingrid Gadotti | Ruan Bernardy | Romário de Mesquita Pinheiro | Rita de Cássia Mota Monteiro
Source: Revista Caatinga (article, 2023-05-22)
Field: Chemistry — Analytical Chemistry

Data mining for ranking sorghum seed lots ABSTRACT The ranking of seed lots is a fundamental process for all companies in the seed industry. This work aims to demonstrate data mining methods for ranking sorghum seed lots during the seed processing through analysis of quality control data. Germination and cold tests were performed to verify the physiological quality of the lots. Seed samples from each lot were evaluated in two moments: post-cleaning and finished product (ready for marketing). The results after pre-processing totaled 188 rows of data with six attributes, encompassing 150 lots accepted for marketing, 6 rejected, and 32 intermediate lots. The classifiers used were J48, Random Forest, Classification Via Regression, Naive Bayes, Multilayer Perceptron, and IBk. The Resample filter was used for adjustment of the data. The k-fold technique was used for training, with ten folds. The metrics of Accuracy, Precision, Recall, F-measure, and ROC Area were used to verify the accuracy of the algorithms. The results obtained were used to determine the best machine-learning algorithm. IBk and J48 presented the highest accuracy of data; the IBk technique presented the best results. The Resample filter was essential for solving the data imbalance problem. Sorghum seed lots can be classified with great accuracy and precision through artificial intelligence and machine learning technique. C4.5 algorithm ; Machine learning ; Artificial intelligence ; Naive Bayes classifier ; Data mining ; Computer science ; Random forest ; Multilayer perceptron ; Ranking (information retrieval) ; Mathematics ; Artificial neural network ; Support vector machine Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Sumaiya Islam | Md Nasim Reza | Shahriar Ahmed | Md Shaha Nur Kabir | Sun‐Ok Chung | Heetae Kim
Source: Korean Journal of Agricultural Science (review, 2023-12-01)
Field: Chemistry — Analytical Chemistry

Short-range sensing for fruit tree water stress detection and monitoring in orchards: a review Water stress ; Remote sensing ; Environmental science ; Tree (set theory) ; Range (aeronautics) ; Geography ; Horticulture ; Biology ; Engineering ; Mathematics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Smart Agriculture and AI