Miracle-dz/UniFAR-FTUs huggingface dataset:
An Ontology Like Model for gathering Personalized Web Information

: In recent days the amount of Information Available on the internet is huge when compared to past few decades. How to gather useful information from the web has become a challenging issue for users. Current web information gathering systems trying to satisfy user requirements by looking at their information needs. For this purpose, user profiles are created for user background knowledge description. User profiles represent the concept models possessed by users when gathering web information. A concept model is implicitly possessed by users and is generated from their background knowledge. While this concept model cannot be proven in laboratories, many web ontologists have observed it in user behaviour. When users read through a document, they can easily determine whether or not it is of their interest or relevance to them, a judgment that arises from their implicit concept models. If a user’s concept model can be simulated, then a superior representation of user profiles can be built. To simulate user concept models, ontology’s—a knowledge description and formalization model—are utilized in personalized web information gathering. Such ontology’s are called ontological user profiles or personalized ontology’s. To represent user profiles, many researchers have attempted to discover user background knowledge through global or local analysis.
Recent advances in bioethanol production from lignocelluloses: a comprehensive review with a focus on enzyme engineering and designer biocatalysts

Many countries have their biofuel policy programs in place as part of their overall strategy to achieve sustainable development. Among biofuels, bioethanol as a promising alternative to gasoline is of substantial interest. However, there is limited availability of a sufficient quantity of bioethanol to meet demands due to bottlenecks in the present technologies to convert non-edible feedstocks, including lignocelluloses. This review article presents and critically discusses the recent advances in the pretreatment of lignocellulosic biomass, with a focus on the use of green solvents, including ionic liquids and deep eutectic solvents, followed by enzymatic saccharification using auxiliary proteins for the efficient saccharification of pretreated biomass. Different techniques used in strain improvement strategies to develop hyper-producing deregulated lignocellulolytic strains are also compared and discussed. The advanced techniques employed for fermentation of mixed sugars contained in lignocellulosic hydrolysates for maximizing bioethanol production are summarized with an emphasis on pathway and transporters engineering for xylose assimilation. Further, the integration of different steps is suggested and discussed for efficient biomass utilization and improved ethanol yields and productivity.
A Study of Implementation of Multiuser Detection in Asynchronous Multi-Beam Communications

This paper deals with multi-user detection techniques in asynchronous multibeam satellite communications. The proposed solutions are based on successive interference cancellation architecture (SIC) and channel decoding algorithms. The aim of these detection methods is to reduce the effect of cochannel interference due to co-frequency access, and consequently, improves the capacity of the mulitbeam communications systems, by improving frequency reuse. Channel estimation allows the determination of interference coefficients, which helps their effects compensation. The developed multiuser detections techniques are iterative. Therefore, detection quality is improved from a stage to another. Moreover, a signals combining method, which is integrated into these detection solutions, enhances their capability. The proposed solutions are evaluated through computer simulations, where an asynchronous multibeam satellite link is considered over an AWGN channel. The obtained simulation results showed the robustness of these multi-user detection techniques.
CIMI: Classify and Itemize Medical Image System for PFT Big Data Based on Deep Learning

The value of pulmonary function test (PFT) data is increasing due to the advent of the Coronavirus Infectious Disease 19 (COVID-19) and increased respiratory disease. However, these PFT data cannot be directly used in clinical studies, because PFT results are stored in raw image files. In this study, the classification and itemization medical image (CIMI) system generates valuable data from raw PFT images by automatically classifying various PFT results, extracting texts, and storing them in the PFT database and Excel files. The deep-learning-based optical character recognition (OCR) technology was mainly used in CIMI to classify and itemize PFT images in St. Mary’s Hospital. CIMI classified seven types and itemized 913,059 texts from 14,720 PFT image sheets, which cannot be done by humans. The number, type, and location of texts that can be extracted by PFT type are all different, but CIMI solves this issue by classifying the PFT image sheets by type, allowing researchers to analyze the data. To demonstrate the superiority of CIMI, the validation results of CIMI were compared to the results of the other four algorithms. A total of 70 randomly selected sheets (ten sheets from each type) and 33,550 texts were used for the validation. The accuracy of CIMI was 95%, which was the highest accuracy among the other four algorithms.
Thermomechanical properties of polycarbonate under dynamic loading

In the present study, dynamic compression tests have been performed on polycarbonate (PC) specimen for strain rates in the range of 500 to 2000s -1 and on aluminum for a strain rate around 1300s -1 using a Split Hopkinson Pressure Bar (SHPB). Temperature measurement has been carried out using a fast response infrared optical pyrometer which is able to measure the surface temperature rise of a specimen during the tests. The temperature data shows that the mechanical work is not completely converted into heat It implies the existence of a stored energy within the material and possibly a subsequent delay for the conversion of mechanical work into heat.
IMPLEMENTATION OF IT AND ICT INTO EDUCATION: MULTIMEDIA TECHNOLOGIES IN CREATING AND USING ELECTRONIC BOOKS.

: The article deals with the planning, creation and use of multimedia books in the educational process. Radical changes in all areas of life, innovations in science and culture, transformations in the field of methodical science led to the need to modernize the education system. The authors of the article analyze the need to develop and test standards for the creation of electronic textbooks and textbooks that meet modern social and psychological requirements of the public education system of our republic. The authors argue that the use of electronic resources in the process of learning foreign languages greatly stimulates the development of speech, and most importantly - affects the initiative of learners and students, contributes to their active participation and increases interest in learning the language.
Agricultural soils: A sink or source of methane across the British Isles?

This study summarizes a large diverse dataset of methane (CH4) fluxes measured from agricultural sites across the British Isles. A total of 53,976 manual static chamber measurements from 27 different sites were investigated to determine the magnitude of CH4 fluxes from a variety of agricultural fields across the UK and Ireland. Our study shows that contrary to some studies, agricultural soils (both arable and grassland) are small net emitters of CH4 rather than sinks. Mean fluxes measured from arable and grassland sites (excluding fertiliser and tillage events) were 0.11 ± 0.06 and 0.19 ± 0.09 nmol m−2 s−1, respectively, and were not found to be significantly different (Welch t‐test, p = 0.17). Using the values reported in this study, we estimate that an annual emission of 0.16 and 0.09 Mt of CO2‐eq is expected from arable and grassland agricultural soils in the UK and Ireland (comparable to 0.3 and 0.7% of the current annual CH4 emission inventories, respectively). Where CH4 uptake occurs in soils, it is negligible compared to expected emissions of the application of animal manures and tillage events, which were both found to significantly increase CH4 emissions in the immediate few days to months after events. Our study highlights that there are significant differences in CH4 uptake and emissions between sites, and that these differences are partially the result of the moisture content of the soil (i.e., the aerobic status of the soil). We expect uptake of CH4 to be more prevalent in drier soils where volumetric water content does not exceed 35% and emissions to be exponentially greater where agricultural fields become waterlogged.
Ecological and hydrological applications of the fluorescence of the humic substances in the natural waters

The humic substances (HS) are always present in the natural waters to a greater or lesser extent. Their property to fluorescent while being excited optically can be applied to use humic substances as a water ecosystem natural indicator. To realize the possibility of using HS as an natural indicator it is necessary to ascertain the correlation between the fluorescence characteristics of HS, their fluorophore structure and the genesis of HS with the influence of the parameters of the environment. It is also important to analyze these rules in the water surface micro-layer which is very important in the mass exchange between the hydrosphere and atmosphere (and in the pollution transfer also). The results of the determination of the molecular photophysical parameters of the HS fluorophores of different genesis are presented in the paper. The non-linear and kinetical fluorimetry methods with variation and artificial neural net algorithms were applied. During the research were solved the inverse problems for which the kinetic fluorescence curves were taken as an initial data. The curves were obtained through the HS excitation with the third harmonic of Yag-Nd Laser. The differences in the meanings of these parameters are discovered. The precise analysis of the shape of HS fluorescence band is accomplished. The results of this analysis are used to determine the structure of the water masses using the fluorescence characteristics of HS. The differences of the HS fluorescence characteristics in the water surface micro-layer and in the water volume is discovered. The ability of determining the structure of water micro-layer by laser probe is shown. The significant investigation result is the possibility of distinguishing the small fluorescenting anthropogenic admixture from the intense HS fluorescence background.
Acute effects of single-bout exercise in adults with type 2 diabetes: a systematic review of randomised controlled trials and controlled crossover trials

Background: Exercise interventions improve type 2 diabetes (T2D). Published randomised control trials and crossover control trials were systematically examined to establish the differences in the effect of single-bout exercise on glucose control and insulin sensitivity in individuals with type 2 diabetes. Methods: Using PRISMA guidelines on three electronic databases, studies that tested the effects of a single bout of exercise on glucose control and insulin sensitivity in T2D were identified. To be included, studies had to meet the PRISMA criteria and contain data on the effects of a single bout of exercise on blood glucose and/or insulin resistance in individuals with T2D. Results: Three of the 205 articles met the inclusion criteria. All of the studies prescribed a single bout of continuous aerobic exercise at 40–60% heart rate reserve (HRR), 60% HRR, or 73% VO2 peak. Aerobic exercise was associated with improved glucose control when compared with resistance exercise. Continuous aerobic exercise significantly lowered average glucose during the first 24 hours post-exercise. Interval walking decreased mean and maximal blood glucose when compared with that in control. Conclusions: In conclusion, the findings of this review suggest high-intensity interval training to be the most effective form of exercise.
A Universal Low-Complexity Demapping Algorithm for Non-Uniform Constellations

A non-uniform constellation (NUC) can effectively reduce the gap between bit-interleaved coded modulation (BICM) capacity and Shannon capacity, which has been utilized in recent wireless broadcasting systems. However, the soft demapping algorithm needs a lot of Euclidean distance (ED) calculations and comparisons, which brings great demapping complexity to NUC. A universal low-complexity NUC demapping algorithm is proposed in this paper, which creates subsets based on the quadrant of the two-dimensional NUC (2D-NUC) received symbol or the sign of the in-phase (I)/quadrature (Q) component of the one-dimensional NUC (1D-NUC) received symbol. ED calculations and comparisons are only carried out on the constellation points contained in subsets. To further reduce the number of constellation points contained in subsets, the proposed algorithm takes advantage of the condensation property of NUC and regards a constellation cluster containing several constellation points as a virtual point. Analysis and simulation results show that, compared with the Max-Log-MAP algorithm, the proposed algorithm can greatly reduce the demapping complexity of NUC with negligible performance loss.
Nonpolar AlGaN-Cladding-Free Blue Laser Diodes with InGaN Waveguiding

We have demonstrated AlGaN-cladding-free m-plane InGaN-based blue laser diodes (LDs) using a novel structure that employs 50-nm-thick n- and p-type InxGa1-xN (x = 5–10%) as waveguiding layers. The thick, high In content InGaN waveguiding layers provided significant refractive index contrast to the GaN cladding layers, thereby eliminating the need for AlGaN cladding. Under pulsed operation, lasing was achieved at 442 nm with a threshold current density of 10 kA/cm2.
Solvent Extraction of Lanthanoid Elements by High Molecular Weight β-Diketones

The extraction behavior of lanthanoid elements has been investigated using such β diketone derivatives (HA) as dodecylbenzoyltrifluoroacetone (LIX 51), benzoylisooctanoylmethane (LIX 54) and dibenzoylmethane (DBM) in kerosene. Trivalent lanthanoid ions (M^3+) were extracted as tris- β -diketonate (MA_3); the extraction tendency followed the sequence LIX 51 ≫ LIX 54 >DBM. The extraction constants ( K _ex) for lanthanoid elements increased with an increase in their atomic number, and a “tetrad effect” was approximately observed for each extraction system, The mean separation factor between adjacent elements was evaluated to be 1.71 for LIX 51, 1.95 for LIX 54 and 2.23 for DBM.
Detecting Deformation on Pantograph Contact Strip of Railway Vehicle on Image Processing and Deep Learning

An electric railway vehicle is supplied with electricity by an OCL (Overhead Contact Line) through the contact strip of its pantograph. This transmitted electricity is then used to power the electrical equipment of the railway vehicle. This contact strip wears out due to contact with the OCL. In particular, deformations due to chipping and material loss occur because of friction with the fittings on the OCL. These deformations on the contact strip affect its power transmission quality because of contact loss with the OCL. However, it is difficult to monitor the contact strip during operation and judge its condition in order to implement accident prevention measures. Thus, in this study, we developed a contact strip monitoring method based on image processing for inspection. The proposed method measures the deformation in the contact strip based on an algorithm that determines the wear on the deformed contact strip using deep learning and image processing. The image of the contact strip is acquired by installing a camera and laser to capture the pantograph as it passes the setup. The proposed algorithm is able to determine the wear size by extracting the edges of the laser line using deep learning and estimating the fitted line of the deformations based on the least squares method.
Two-Layer-Graph Clustering for Real-Time 3D LiDAR Point Cloud Segmentation

The perception system has become a topic of great importance for autonomous vehicles, as high accuracy and real-time performance can ensure safety in complex urban scenarios. Clustering is a fundamental step for parsing point cloud due to the extensive input data (over 100,000 points) of a wide variety of complex objects. It is still challenging to achieve high precision real-time performance with limited vehicle-mounted computing resources, which need to balance the accuracy and processing time. We propose a method based on a Two-Layer-Graph (TLG) structure, which can be applied in a real autonomous vehicle under urban scenarios. TLG can describe the point clouds hierarchically, we use a range graph to represent point clouds and a set graph for point cloud sets, which reduce both processing time and memory consumption. In the range graph, Euclidean distance and the angle of the sensor position with two adjacent vectors (calculated from continuing points to different direction) are used as the segmentation standard, which use the local concave features to distinguish different objects close to each other. In the set graph, we use the start and end position to express the whole set of continuous points concisely, and an improved Breadth-First-Search (BFS) algorithm is designed to update categories of point cloud sets between different channels. This method is evaluated on real vehicles and major datasets. The results show that TLG succeeds in providing a real-time performance (less than 20 ms per frame), and a high segmentation accuracy rate (93.64%) for traffic objects in the road of urban scenarios.
Spontaneous motion of two droplets caused by mass transfer

Spontaneous motion of two droplets driven by surface tension gradients which result from mass transfer between the droplets and the continuous fluid phase is considered. It is shown that mass flux of a weak surfactant from the dispersed phase into the continuous one generates the droplet motion toward each other ; the oppositely directed mass transfer makes the droplets move apart from each other. In the approximation of a quasistationary Stokes flow and a low Peclet number in the outer fluid, the velocities of the droplets' spontaneous motion are calculated as functions of the separation distance between the drops and the Sherwood number characterizing the intensity of mass transfer. The mass transfer driven interaction of two drops significantly influences their motion and coalescence in the gravity field. The velocities of the droplets in this case are calculated as functions of the Marangoni and Archimedean numbers, as well as the ratios of the droplet radii. The results obtained account for a large number of experimental data on the influence of mass transfer direction on the rate of coalescence of drops and bubbles.
A machine learning framework for the prediction of chromatin folding in Drosophila using epigenetic features

Technological advances have lead to the creation of large epigenetic datasets, including information about DNA binding proteins and DNA spatial structure. Hi-C experiments have revealed that chromosomes are subdivided into sets of self-interacting domains called Topologically Associating Domains (TADs). TADs are involved in the regulation of gene expression activity, but the mechanisms of their formation are not yet fully understood. Here, we focus on machine learning methods to characterize DNA folding patterns in Drosophila based on chromatin marks across three cell lines. We present linear regression models with four types of regularization, gradient boosting, and recurrent neural networks (RNN) as tools to study chromatin folding characteristics associated with TADs given epigenetic chromatin immunoprecipitation data. The bidirectional long short-term memory RNN architecture produced the best prediction scores and identified biologically relevant features. Distribution of protein Chriz (Chromator) and histone modification H3K4me3 were selected as the most informative features for the prediction of TADs characteristics. This approach may be adapted to any similar biological dataset of chromatin features across various cell lines and species. The code for the implemented pipeline, Hi-ChiP-ML, is publicly available: https://github.com/MichalRozenwald/Hi-ChIP-ML
A Hybrid Soft Actuator Inspired by Grass-Spike: Design Approach, Dynamic Model, and Applications

This paper presents the bio-mimetic design approach, the dynamic model, and potential applications for a hybrid soft actuator. The proposed hybrid soft actuator consists of two main parts: a cylinder-shaped rigid core and soft silicone spikes wrapped around the core’s surface. The key idea of the proposed design approach is to mimic the movement of a grass-spike at a functional level by converting the vibration force generated by a small electric motor with a counterweight in the rigid core into a propulsion force produced by the elastic restoration of the spikes. One advantage of this design approach is that the hybrid soft actuator does not need to be tethered by a tube line from an air compressor and is more amenable to fine control. In addition, the hybrid soft actuator can be modularized with a wire and a tubular passage, which in turn work as a linear actuator. The dynamic model of the hybrid soft actuator can be derived by applying Lagrangian mechanics, and unknown system parameters can be identified by the optimization process based on the empirical data. Two applications—an elbow manipulator and a robotic hand grasper—demonstrate the feasibility of the proposed actuator to perform a muscle-tendon action successfully.
Abundances and breeding phenology of three sympatric grebes (little grebe Tachybaptus ruficollis, great crested grebe Podiceps cristatus and black-necked grebe Podiceps nigricollis) in Dayet El Ferd, Algeria

1 Laboratory of Water Conservation Management Soil and Forest, Faculty of Nature and Life Sciences, 13000, University of Tlemcen, Algeria. 2 Laboratoire Biologie, Eau et Environnement (LBEE), Faculté SNV-STU, Université 8 Mai 1945 Guelma. BP. 401 24000 Guelma, Algeria. * Corresponding author: mouslim.bara@gmail.com Abundancia y fenología reproductora de tres macaes simpátricos (zampullín chico, Tachybaptus ruficollis; zampullín de cresta grande, Podiceps cristatus; y zampullín de cuello negro, Podiceps nigricollis) en Dayet El Ferd, Argelia
Knowledge Discovering on Graphene Green Technology by Text Mining in National R&D Projects in South Korea

This paper reviews the development of South Korea’s national research and development (R&D) in graphene technology, focusing on projects that have been classified as “green” technology. A total of 826 projects (USD 210 billion) from 2010 to 2019 were collected from the National Science and Technology Information Service (NTIS), which is full-cycle national R&D project management system in South Korea. Then we analyzed its R&D trend by conducting diverse text mining methods including frequency analysis, association rule mining, and topic modeling. The analysis suggests that the number of graphene green technology (GT) R&D projects and the research expenses will show a rising curve again in the incumbent government along with the implementation of the Korean New Deal policy, which integrates the Green New Deal and the Digital New Deal.