Miracle-dz/UniFAR-FTUs huggingface dataset:
One-dimensional modelling of a capacitively coupled rf plasma in silane/helium, including small concentrations of O2 and N2

Functional coating deposition using plasma is broadly used in industrial application working at a pressure ranging from low pressure discharges (a few Pascals) to atmospheric plasmas. The active gas (silane is selected for this study) is often diluted in a gas that helps in stabilizing the discharge like helium or argon. In addition, the discharge can be polluted by uncontrolled external gas source like air or oxygen coming from water adsorbed in reactor walls. In this paper, we study the interactions taking place within the bulk of a capacitively coupled plasma and study the impact of these reactions on the flux of species moving towards the substrate and so the impact on the composition of deposited film. A one-dimensional fluid model is presented for the modelling of radio frequency capacitively coupled plasmas in a mixture of silane/helium, including small concentrations of O2 and N2. In total, 48 different species (electrons, ions, neutrals, radicals and excited species) are considered in the model. After a sensitivity study, 27 electron–neutral and 76 chemical reactions (i.e. ion–neutral and neutral–neutral reactions) were maintained in the fluid model. The fluid model itself consists of a set of mass balance equations (i.e. one for every species), the electron energy equation and the Poisson equation. The reaction rate coefficients of the electron–neutral reactions, as a function of average electron energy, are obtained from a Boltzmann model. The reaction rate coefficients of the ion–neutral and neutral–neutral reactions are assumed to be constant. It is found that helium does not affect the silane plasma chemistry drastically. The incorporation of small amounts of air (containing about 82% N2 and 18% O2) in a silane/helium plasma, however, influences the plasma chemistry to a large extent. A large number of nitrogen species (i.e. N2, N, N2+), and species containing oxygen (i.e. SiH3O SiO, OH and others), are present in the discharge at relatively high densities (i.e. of the order of 1014–1017 m−3).
Ab initio energy‐adjusted pseudopotentials for the noble gases Ne through Xe: Calculation of atomic dipole and quadrupole polarizabilities

Nonrelativistic and one‐component relativistic energy‐adjusted ab initio pseudopotentials for the noble gases neon through xenon are presented together with corresponding optimized valence basis sets. To account for nonscalar relativistic effects the relativistic pseudopotentials are supplemented with effective spin–orbit potentials. The reliability of the presented pseudopotentials is demonstrated in atomic test calculations on ionization potentials and spin–orbit splittings in comparison with nonrelativistic and relativistic all‐electron calculations as well as experimental data. Together with extended valence basis sets the pseudopotentials are applied in calculations on the static dipole and quadrupole polarizabilities of the noble gas atoms. The best values, computed at the coupled‐cluster level of theory [CCSD(T)], for the dipole and quadrupole polarizabilities of the noble gases are 2.69a30 and 7.52a50 for Ne, 11.07a30 and 52.25a50 for Ar, 17.06a30 and 97.39a50 for Kr, and 27.66a30 and 209.85a50 fo.
Removal of Dyes, Sugars, and Amino Acids from NaCl Solutions Using Multilayer Polyelectrolyte Nanofiltration Membranes

Several recent studies demonstrated highly selective ion and neutral molecule transport through multilayer polyelectrolyte nanofiltration (NF) membranes. This work examines the potential of such membranes in the selective removal of dyes, sucrose, and amino acids from NaCl solutions. Remarkably, simple deposition of 4.5-bilayer poly(styrenesulfonate) (PSS)/poly(allylamine hydrochloride) (PAH) films on porous alumina supports yields membranes that exhibit NaCl/sucrose selectivities of ∼130 and NaCl/dye selectivities >2200. These high selectivities stem from rejections of 99.4% for sucrose and >99.9% for reactive dyes, along with small (∼20%) rejections of NaCl. Moreover, the solution flux (>1.7 m3/m2·day at 4.8 bar) through these membranes is comparable to or greater than that reported for commercial membranes. In contrast to results with sucrose and reactive dyes, the NaCl/glutamine selectivity of a [PSS/PAH]7 membrane is only 3.7 because of the relatively small size of glutamine. With increasing NaCl con.
Resonance conditions for multipole plasmon excitations in noble metal nanorods

A resonance condition has been obtained for the position of plasmon peaks of any multipole order in the extinction spectra of silver and gold nanorods, as a function of their material, size, shape, and dielectric environment. The expression has been derived combining electrodynamics simulations with the aid of a nanoantenna-standing wave model approach. Some scaling laws, emerging from the above expression, are also demonstrated, in very good agreement with recent experiments and theoretical studies.
Spectroscopy and dynamics of excited states in maleimide and N-methyl maleimide: Ionic projection and ab initio calculations

The state that is responsible for the strong one-photon absorption around 200 nm in the vapor absorption spectrum of maleimide and N-methyl maleimide has been investigated using excited-state photoelectron spectroscopy in combination with ab initio calculations. The projection of the wave function of the excited state on the ionic manifold done in this way reveals multiple, vibrationally resolved, ionization pathways to ground- and excited states of the radical cation, which provide direct evidence for electronic couplings with other, lower-lying states. From a comparison of the experimental intensity distribution over the ionic vibrational states with ab initio calculated Franck–Condon factors, we are able to elucidate the role of the various electronically excited states in the ionization process. The experiments also provide the first determination of adiabatic ionization energies in the two molecules. For maleimide values of 10.330 and 10.903 eV are found for D0 and D1, respectively; for N-methyl male.
Size and confinement effect on nanostructures

This report presents a systematic understanding of the nature behind the unusual behavior of a nanosolid, and a surface as well, in mechanics, thermodynamics, acoustics, optoelectronics, magnetism, dielectrics, atomic diffusivity and chemical reactivity towards predictable design and controllable growth of nanostructured materials. A bond order-length-strength (BOLS) correlation mechanism has been developed, which has enabled the tunability of a variety of properties of a nanosolid in connection with surface to be consistently predicted and experimentally verified. The BOLS correlation indicates that the coordination number (CN) imperfection of an atom at site surrounding a defect or in the surface skin causes the remaining bonds of the lower-coordinated atom to contract spontaneously. The spontaneous bond contraction is associated with bond-strength gain or atomic potential well deppression, which localize electrons and enhance the density of charge, mass, and energy in the relaxed region. The enhancement of energy density in the relaxed region perturbs the Hamiltonian and the associated properties such as the band-gap width, core-level energy, Stokes shift (electron-phonon interaction), and dielectric susceptibility. On the other hand, bond order loss lowers generally the cohesive energy of the lower-coordinated atom from the value of a fully-coordinated atom, which dictates the thermodynamic process such as self-assembly growth, atomic vibration, thermal stability, and activation energies for atomic dislocation and diffusion. Consistency between predictions and observations evidences the enormous impact of atomic CN imperfection and the validity and essentiality of the BOLS correlation.
Machine learning algorithm for activity‐aware demand response considering energy savings and comfort requirements

Due to the high cost of peak hour power generation and a push towards sustainability, the need for demand response (DR) is increasing. Compared to commercial-level DR, residential-level DR is more challenging. Residents are reluctant to participate, and DR controllers lack sufficient real-time activity information to balance energy savings with residents' need for comfort and convenience. To address the above challenges, we propose a sensor data-driven activity-based controller for heating, ventilation, and air conditioning devices. Using our proposed novel strategy, resident activities are recognized in real-time through a random forest machine learning approach. Integrating activity information and forecasted electricity pricing, the proposed controller can simultaneously reduce energy consumption for sustainability and maintain resident constraints for comfort based on recognized activities. Results demonstrate the superiority of the proposed approach.
Adaptive Lp-Norm Regularized Sparse Representation for Human Activity Recognition in Coal Mines

This paper aims to overcome the lack of in-depth exploration into the intrinsic geometry of human activities. For this purpose, a generalized adaptive Lp-norm regularized sparse representation (ARSR) approach was proposed for human activity recognition, which preserves the model adaptability through the adaptive Lp-norm regularization. In essence, the proposed method applies sparse representation to human activity recognition, turning it into a new optimization problem. In addition, the problem was solved by the iterative-shrinkage-thresholding algorithm. Specifically, the sparse representation learned by the ARSR algorithm was introduced into the support vector machine (SVM) classifier. Then, several experiments were conducted on coal-mining datasets for human activity identification. The experimental results revealed that the proposed algorithm is superior to the current sparse representation algorithms like the standard L1-norm regularized sparse representation algorithm. The research findings shed new light on the human activity recognition in coal mines.
Nutritional Evaluation, Glycemic Index and Sensory Property of Breakfast Cereals developed from Malted Amaranth and Roasted Sesame Blends

The aim of this study was to produce and assess breakfast meals produced from composite fl our samples of processed malted amaranth and roasted sesame blends. The various biomaterials were processed separately. The resulting fl our samples were blended at various ratios and processed to extruded breakfast meals. The extruded fl aked meals were assessed for selected quality parameters (total dietary fi bre, reducing/total sugar, sensory, amino acid and glycemic index/load) using standard methods. The results showed that there was increase in the amino acids, soluble, insoluble and total dietary fi bre of sesame substituted samples. There was decrease in the reducing sugar and total sugar, glycemic index and load, total and reducing sugar of the samples containing sesame. The sample containing 50% sesame and 50% amaranth was the most acceptable in all the sensory parameters except in colour. The study concluded that high nutritional quality breakfast meal, also of low glycemic index/load could be produced from malted amaranth substituted with roasted sesame.
Microbiome of the Uterus in Women With Unsuccessful in Vitro Fertilization Attempts

ObjectivesThis study aimed to investigate the peculiarities of the uterine microbiome in the case of infertility and repeated in vitro fertilization (IVF) failures. Accordingly, the microbiome of the uteri of 22 women with 2 or more IVF failures (first group) and 20 healthy women (second group) was analyzed in this study.Materials and MethodsThe samples of uterine microbiomes were collected 7 days after the luteinizing hormone elevation, which was determined by the urine test. All measures were taken to avoid sample contamination. Finally, the massively parallel sequencing of the 16S ribosomal RNA gene was done in every uterine sample.ResultsThe analysis of the mean relative abundance of various microorganisms in the uterine microbiome showed that women with infertility had higher microbiological diversity and variability compared to healthy women. Eventually, the mean relative abundance of the Lactobacillus genus comprised 34.4% and 63.0% in the first and second groups, respectively.ConclusionIn general, the presence of Lactobacillus in the uterine microbiome could be considered a favorable factor for good reproductive outcomes and successful IVF programs.
E-commerce Item Identification Based on Improved SqueezeNet

In order to improve the recognition rate of product images in e-commerce recommendation scenes, we proposed a high-performance improved SqueezeNet convolutional neural network, which uses a Fire Module structure containing two large convolution kernels to reduce the complexity of the model while fully extracting features, and adding a pooling layer behind each Fire Module to effectively filter key features of the classification. Experiments show that the algorithm in this paper has a better application in image recognition in e-commerce scenes, and the recognition accuracy is improved by 1%.
Introduction to the Luminescence of Solids

Edited by Parker D. Trask. A valuable new tool for geologists and engineers faced with the practical problems of sedimentation. The book contains 35 original articles, each a comprehensive subject summarized by a specialist. The articles are grouped under these seven topics: basic principles of sedimentation; engineering problems involving strength of sediments; applications of processes of sedimentation; applications involving nature of constituents; economic mineral deposits; petroleum geology problems; and military applications.
Machine Learning Model for a Dynamic Path Planning Problem

Due to an advancement in Industry 4.0 technology, various autonomous systems have been developed in order to increase the operational efficiency. This paper considers an application of Industry 4.0 technology to an autonomous transportation operation. The paper focuses on applying a machine learning technique to a dynamic path planning problem where real-time randomized obstacle locations are considered. The routes or the solutions from the dynamic path planning problem are determined by an A-star algorithm, which are then used to build machine learning models based on an artificial neural network. The models were developed to discover the relationship between the input and output of the dynamic path planning problem. The structure of the network which is defined by the number of intermediate layers and the number of nodes is provided, where the overall accuracy is used to evaluate the setting efficiency. The proposed methodology was tested with a problem that consists of 7 types of paths, and the number of randomized obstacles fluctuated from 1 to 8. The paths were generated based on a layout of a consumer product warehouse. The proposed model succeeded in predicting the robot paths with 98.5% prediction accuracy.
A novel Customer Service Recommendation Algorithm for Power Users

Aiming at the large amount of power user data and the fact that the collaborative filtering recommendation technology fails to consider the relationship between users and customer service staff, a k-means clustering and user portrait recommendation method is proposed. This method firstly uses clustering technology clustering the power users’ portrait label vectors to gather similar users together, and makes recommendations based on the cluster to which the users belong. Secondly, through calculating the user portrait label vector similarity between the attributes of the service feature vector to establish the connection between the user and the customer service, and improve the traditional grading forecast method, the user and the personnel of the service of similarity index is integrated into it. Finally, the personnel of the service will be recommended from the two aspects of service quality and service fits.
A Summary of Aspect-based Sentiment Analysis

Aspect-based sentiment analysis is a subclass of sentiment analysis tasks, focusing on judging the sentiment tendency of entities or attributes, and has received extensive attention due to fine-grained analysis results. The current research mostly summarizes the research from a single point of aspect extraction or sentiment classification, and lacks of research on the methods and problems in aspect-based sentiment analysis from the overall perspective. By using the method of literature investigation, an in-depth overview of the typical methods and solutions is given in the field of aspect-based sentiment analysis from three aspects: aspect information extraction, aspect information sentiment classification and aspect-based sentiment analysis joint modeling. Then, we discuss some of the most challenging problems existing in the field in terms of model adaptability, error transmission, knowledge and reasoning, and proposes future research opportunities in terms of strengthening knowledge representation, multi-task learning and integrating knowledge and reasoning from the overall perspective of practical application.
ResSCNN: A semantic segmentation method for fast processing of large-scale input

With the development of driver-assistance systems and driverless cars, vehicles are becoming more and more intelligent. However, today’s intelligent vehicles rely more on large sensors to sense the environment, so it is becoming more and more important for vehicles to be able to understand road information, and semantic segmentation has developed greatly. We find that the current mainstream semantic segmentation model is slow and inaccurate in the case of large scale input images. In this paper, we combine the large-scale input Fast-SCNN with the residual module to construct the residual semantic segmentation convolutional neural network (ResSCNN), after the experimental test, when the input scale is 1024 × 2048 px, yielding an accuracy of 68.4% mean intersection over union at 123.1 frames per second on Cityscapes dateset. Our network has achieved better results than the previous mainstream methods.
Connectivity detection in application to spike-wave discharge study

In our study, we compare three popular approaches to directed coupling analysis, in particular transfer entropy and two types of Granger causality, applied to real data from genetic absence epilepsy rats. We have chosen the channels for which the coupling architecture is already well known from previous studies. Recordings from 5 WAG/Rij rats of 8 hours duration with at least 28 spontaneous seizures of length not less than 6 s in each recording were studied. To test results for significance, surrogate signals based on series permutation technique were constructed. Connectivity development in time was investigated by considering six two-second intervals before, during and after the seizure. Our outcomes showed large differences between studied approaches, while all of them exploit the same general idea. Transfer entropy demonstrated the smallest number of significant couplings throughout all three considered measures, while the linear Granger causality showed the largest number of them. This indicates that transfer entropy is the most conservative measure and the least sensitive one. Its sensitivity is affected by insufficient series length. The linear Granger causality is likely to demonstrate insufficient specificity.
Experimental Study on Shear Behavior of Reinforced Autoclaved Aerated Concrete Slab

Process two-points concentrate force load shearing trial for 6 ALC plates (Autoclaved aerated concrete reinforced plate), the article introduced the trial specimen structure, trial device and load scheme. This trial obtained the influence of the shear capacity of ALC plate like failure mode, load-deflection curve, stress (varying) distribution, steel types and shear span ratio. The research shown that: ①The reinforced ALC plate easily form the strong bending and weak shearing members, happen shear pressure failure when designed shear span ratio X=2.5, happen diagonal-tension failure, when designed shear span ratio X>5; ②If the oblique crack position close to the anchoring gusset or pass through anchoring section then maybe weaken the anchoring force and reduce the shearing strength of plate. Because of its brittle nature, anchorage failure must be avoid. Sufficient anchorage can theoretically be provided either by bond or by cross bars welded to the longitudinal reinforcement. ③For the calculation method of the shear bearing capacity of ALC without shear reinforcement with high strength longitudinal steel reinforcement, the technical code for the application of autoclaved aerated concrete in building in China is no longer applicable, EU standards calculated result are all less than the measured values, the method of international RILEM materials association is more suitable and the calculated value more close to the measured value.
Hydrophilic properties of aged soot

The global presence of soot has significant effects on regional and global climate, as well as human health. Influence of soot on radiation budget, rain formation and heterogeneous chemistry, and its residence time in the atmosphere are largely dependent on its ability to interact with water. While freshly emitted soot is extremely hydrophobic, oxidation during aging causes soot to become more hydrophilic. Laboratory studies demonstrate that aged soot attracts and retains water, and can be efficiently removed from the troposphere by entrapment in existing liquid cloud droplets or by activation as cloud condensation nuclei.
Quantification of carbohydrates in fruit juices using FTIR spectroscopy and multivariate analysis

A combination of Fourier-transform infrared spectroscopy (FTIR) and multivariate statistics was applied as screening tool for the quantitative determination of carbohydrates, such as glucose, fructose and sucrose, in 28 processed commercial fruit juices and 5 genuine juices obtained from squeezed fruits. A number of 13 mixtures of glucose, fructose and sucrose standard solutions were prepared at different concentrations, scanned by attenuated total reflectance (ATR) FTIR spectroscopy and analyzed in the 900 and 1400 cm−1 spectral range. Principal component analysis (PCA) of the standard carbohydrate solutions enabled a better understanding of the main sources of variability affecting the FTIR spectra. Also, PCA enabled the grouping of apple, orange and peach juices. Calibration models for each carbohydrate, using partial least squares (PLS) regression were developed and used for prediction purposes. Cross-validation procedures indicated correlations of 0.88, 0.92 and 0.98 for glucose, fructose and sucrose, respectively, between HPLC measured values and FTIR first derivative spectra estimates. Carbohydrates in the expected concentration ranges were found for most of the pure fruit labelled juices. The samples with 4–50% pure fruit juice content showed discrepancies from average concentration values of authentic juices, mainly a high sucrose concentration can flag sucrose addition to maintain the juice sweetness intensity. The present results confirmed the efficiency of FTIR spectroscopy, in combination with multivariate statistics, as a rapid, reliable and cost-effective tool for routine monitoring of multiple constituents in fruit juices, as quality indicators.