Miracle-dz/UniFAR-FTUs huggingface dataset:
Scale‐oriented landslide monitoring and early warning system for uranium legacy complexes in Mailuu Suu, Kyrgyzstan

Radioactive waste and the legacies of uranium mining combined with massive landslides pose tremendous risks to vast areas of Kyrgyzstan and their inhabitants. These risks comprise the potential destruction of radioactive legacies and thus, the mobilisation of radioactive material through streams and rivers into intensively cultivated agricultural areas. To tackle these challenges, a scale‐oriented landslide monitoring and early warning system (LMEWS) was developed to increase the safety of Kyrgyz uranium legacy complexes in the Mailuu Suu region, southern Kyrgyzstan. The LMEWS utilizes cutting‐edge technologies like satellite‐ and ground‐based InSAR as well as Unmanned Aerial Systems (UAS) to ensure flexibility, transferability, and maximum protection against vandalism.
Utilizing Energy Efficiency and QoS awareness for Receiver-Arbitrated and Sender-Predicted MAC Protocol in Wireless Sensor Network

In this paper, we exploit energy-efficiency and QoS-awareness for receiver-arbitrated and sender-predicted MAC Protocol (EQAP-MAC) in wireless sensor network. EQAP-MAC improves the transmission concurrency by separating control stream from data stream; minimizes energy consumption by sender by predicting receiver’s wake-up time; supports priority-based QoS through priority-based data flow selected, arbitrated and interrupted mechanisms; reduces transmission interference between the nodes by interleaving neighbor nodes’ wake-up time; improves system throughput and reduces the data stream transmitting delay by pipelining mechanism and optimizing send sequence. We have implemented EQAP-MAC on TinyOS and evaluated its performance on testbed. The result shows EQAP-MAC achieves higher concurrent performance and priority-based QoS guarantee with lower energy consumption compared with RI-MAC and X-AMC.
Multitask Semantic Boundary Awareness Network for Remote Sensing Image Segmentation

In remote sensing images, boundary information plays a crucial role in land-cover segmentation. However, it is a challenging problem that sufficiently extracts complete and sharp boundaries from complex very-high-resolution (VHR) remote sensing images. To tackle this problem, we propose a semantic boundary awareness network (SBANet). The SBANet captures refined boundary information of land covers in feature extraction and then supervises its learning with a designed boundary loss. The key of SBANet includes boundary attention module (BA-module) and adaptive weights of multitask learning (AWML). The BA-module is proposed to capture land-cover boundary information from hierarchical features aggregation in a bottom-up manner. It emphasizes useful boundary information and relieves noise information in low-level features with the guidance of high-level features. To directly learn the boundary information, AWML adds a boundary loss to the original semantic loss by an adaptive fusion manner. This multitask learning enables the semantic information and the boundary information to work collaboratively and promote each other. Note that the BA-module and AWML are plug-and-play. Experimental results demonstrate the effectiveness of the proposed SBANet on the available ISPRS 2-D semantic labeling Potsdam and Vaihingen data sets. The SBANet also achieves the state-of-the-art performance in terms of overall accuracy (OA) and mean $F_{1}$ score (m- $F_{1}$ ).
Analysis of Demand Factor for High Speed Railway Power Transmission Line from Load Measurement Data

With the rapid construction of high-speed railway in China and other developing countries, as well as the continuous expansion of its distance and scale, the load of power transmission line along the railway is increased accordingly. However, the existing design standards for power transmission line of high speed railway cannot specify the demand factor for the electrical load supplied by power transmission line, and there is no unified calculation method for the demand factor, resulting in a large difference between the theoretical value and the actual value of transformer capacity and cable section selected for engineering project, which takes huge additional energy penalty from the utility companies. To address the problems and formulate a more accurate selection standard for the load demand factor of high-speed railway power transmission line (HSR-PTL), the demand factor is calculated from the data measured on several typical high-speed railway operating in China. Firstly, the load model of HSR-PTL is proposed. According to the function and characteristics of the several kinds of load in HSR-PTL, each load is classified for load demand modelling. By measuring the load of several typical operating HSR-PTL, based on the proposed model, the value of the required coefficient of each load type based on the measured data is proposed. The calculated demand factor can be applied as an applicable reference for the design of high-speed railway power system.
On the Lifetime Estimation of SiC Power MOSFETs for Motor Drive Applications

This work presents a step-by-step procedure to estimate the lifetime of discrete SiC power MOSFETs equipping three-phase inverters of electric drives. The stress of each power device when it is subjected to thermal jumps from a few degrees up to about 80 °C was analyzed, starting from the computation of the average power losses and the commitment of the electric drive. A customizable mission profile was considered where, by accounting the working conditions of the drive, the corresponding average power losses and junction temperatures of the SiC MOSFETs composing the inverter can be computed. The tool exploits the Coffin–Manson theory, rainflow counting, and Miner’s rule for the lifetime estimation of the semiconductor power devices. Different operating scenarios were investigated, underlying their impact on the lifetime of SiC MOSFETs devices. The lifetime estimation procedure was realized with the main goal of keeping limited computational efforts, while providing an effective evaluation of the thermal effects. The method enables us to set up any generic mission profile from the electric drive model. This gives us the possibility to compare several operating scenario of the drive and predict the worse operating conditions for power devices. Finally, although the lifetime estimation tool was applied to SiC power MOSFET devices for a general-purpose application, it can be extended to any type of power switch technology.
An Investigation of Aerodynamic Effects of Body Morphing for Passenger Cars in Close-Proximity

The potential energy-saving benefit for vehicles when travelling in a ‘platoon’ formation results from the reduction in total aerodynamic drag which may result from the interaction of bluff bodies in close-proximity. Early investigations of platooning, prompted by problems of congestion, had shown the potential for drag reduction but was not pursued. More recently, technologies developed for connected-autonomous vehicle control have provided a renewed interest in platooning particularly within the commercial vehicle industry. To date, most aerodynamics-based considerations of platooning have been conducted to assess the sensitivity of drag-saving to vehicle spacing and were based on formations of identically shaped constituents. In this study, the interest was the sensitivity of drag-saving to the shape of the individual platoon constituents. A new reference car, the Resnick model, was specially designed to include front and rear-end add-on sections to make distinct changes in profile form and simulate large-scale body morphing. The results of wind tunnel tests on small-scale models suggested that current trends in low-drag styling may not provide the ideal shape for platoon constituent members and that optimised forms are likely to be dependent upon position in the platoon.
Stochastic recruitment limited control of shape memory alloy based on Markov chain model

A new control method of Shape Memory Alloy (SMA) actuators based on stochastic recruitment is proposed. From the perspective of bionic control, the physiological basis of stochastic recruitment limited feedback control of artificial muscle is explained. The limited feedback control system of two-state cells and multi-state cells are established, and the limited feedback control law is deduced for these two kinds of systems. In the Simulink environment, two kinds of limited feedback control algorithms are simulated and compared, which verifies the feasibility of the algorithm. Aiming at the key problem of scaling coefficient in the system, the longitudinal and transverse comparative experiments are carried out to analyze the influence of the scaling coefficient on the system.
Determination of Cd, Cu, Pb and zn in biological tissues using zeeman graphite furnace AAS after microwave digestion in non-pressurized, semi-closed vessel

Heavy metals (Cd, Cu, Pb, and Zn) were determined in various fish organs (flesh, kidney, and liver), barnacles, mud clams, and crab muscles using Zeeman graphite furnace (Cd, Cu, Pb) and flame (Zn) atomic absorption spectroscopy after a simple, rapid dissolution step using a regular conventional (kitchen) microwave. A simple HNO 3 -H 2 O 2 digestion was used for the dissolution of tissue samples. Graphite furnace determination of Cd, Cu, and Pb was done using aqueous calibration standards. No chemical matrix modifiers were used during the analysis. Recovery results for spiked external certified reference materials (NRC Dorm-1 Dogfish Muscle, NRC Dolt-2 Dogfish Liver/Kidney, and CEC CRM278 Mussel Tissue) were 101, 115, 96% for Cd; 116, 103, 108% for Cu; 106, 102, 108% for Pb and 97, 106, 104% for Zn, respectively. The method is relatively quick and easy to use for routine analysis of environmental samples, processing up to 100 samples per day.
Early Leaf Removal Increases Berry and Wine Phenolics in Cabernet Sauvignon Grown in Eastern Serbia

Cluster zone leaf removal is a well-established viticulture practice for improving cluster microclimate and wine quality in cooler climates, while its efficacy in warmer conditions is less is known. Here we compared the effect of early (ELR, after fruit set; diameter of berries 3–5 mm) and late (LLR, beginning of veraison) leaf removal on berry composition and wine phenolic profile of grapevine (Vitis vinifera L.) variety Cabernet Sauvignon grown in a temperate, warmer region of Eastern Serbia. Compared to the control (no leaf removal), both leaf removal treatments increased the sugar content in fresh juice and alcohol concentration in wine. Over three consecutive years (2011–2013) markedly different in temperature and rainfall, ELR was clearly most effective in decreasing weights of cluster and of one berry, and in increasing of skin share in a berry. The content of total phenols, tartaric acid esters, anthocyanins, and flavanols in berry skin and wine was the highest in ELR treatment. ELR prominently modified the phenolic profile: Increasing flavanols, myricetin and quercetine in skin and wine, and anthocyanins, peonidin-3-glucoside in skin and delphinidin-3-glucoside in wine. This work demonstrated that early leaf removal positively influenced the chemical composition of berries and wine of Cabernet Sauvignon and might be recommended for practice in the temperate warm conditions.
The use of return on equity as a criterion for stock selection in the Indian equity markets

As per Dorsey, companies with a sustainable competitive advantage tend to outperform the market benchmarks over time. Companies which have a durable competitive advantage compared with their competitors manage to compound capital at attractive rates of return and such companies tend to grow sales and profits predictably and generate substantial free cash flows. This reflects in their share prices over time. In this paper we have used a measure of Return on Equity as an indicator that a company has a sustainable competitive advantage, and have studied the equity performance of such companies as compared with market performance. We find that companies which have attained Return on Equity greater than 15% each year for the past ten years tend to outperform the market benchmarks over the next five years.
Changes in participant behaviour and attitudes are associated with knowledge and skills gained by using a turtle conservation citizen science app

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2021 The Authors. People and Nature published by John Wiley & Sons Ltd on behalf of British Ecological Society 1School of Life and Environmental Sciences, The University of Sydney, Camperdown, NSW, Australia 2School of Science, Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW, Australia 3School of Molecular Sciences, La Trobe University, Wodonga, VIC, Australia
A New Skeletal Representation Based on Gait for Depression Detection

As the challenge of depression problems increases today, it is important to effective and timely detect for patients' treatments and depression prevention. Current methods of automated depression diagnosis depend almost entirely on audio, video, and Electroencephalogram (EEG) etc. In this paper, we propose a novel method to detect depression using gait data that is collected by Kinect camera. Its key components include a camera rectification method and a rigid-body representation of the human body. The camera rectification method achieves the purpose of improving data processing accuracy by changing the camera angle. The rigid-body representation can not only improve the robustness of detecting depression patients with noisy input, but also can reduce the classification time. We evaluate our method on the depression gait dataset in postgraduate students. The proposed method has an outstanding performance in classic machine learning algorithms, and the best accuracy can achieve 88.89%. Our solution provides a new method for automatic depression detection (ADD) that has exciting implications in clinical theory and practice, and has the advantages of high accuracy, inexpensive, low time cost, and no-contact.
Accuracy improvement method for dynamic substructuring models in vehicle systems

This study proposes an improved dynamic substructuring model using the estimated frequency response function information at coupling points between substructures. An assembled system generally consists of two or more substructures connected by a bolt. Individual substructure evaluation excluding the effects of other components is important in the development stage of a general mechanical system because the vibro-acoustic performance of the system depends on the specific combination of substructures. Therefore, this study predicted the final coupling system performance using information from the initial evaluation of the individual substructures. Accurate measurements of the joint properties are required to accurately estimate the dynamic assembled system characteristics; however, physical constraints typically limit such measurements at actual coupling points. Accordingly, a method that utilizes generalized coupling properties to estimate the dynamic characteristics of a new coupling system based on the characteristics of an original substructure is proposed. Virtual point transformation is then used to estimate accurate frequency response functions at the coupling points of the assembled system based on convenient measurements. The proposed method was validated using a vehicle suspension that was hard mounted in a test jig and onto an actual vehicle body to estimate the vibration characteristics of the assembled system. The findings of this study contribute to the accurate estimation of the dynamic properties of many real-world bolt-assembled systems.
Security Issues in Multi-hop Device-to-device Communication Networks - Secure Routing Protocols Solution

As one of the key technologies of fifth-generation mobile communication, device-to-device communication technology can not only realize direct communication between neighboring devices, but also reduce the delay of local services provided to users and increase the communication rate. Nevertheless, the special structure of the device-to-device communication network makes it more vulnerable to attacks from inside and outside the network. This paper summarizes the security issues faced by device-to-device communication networks, analysis the secure routing designed for different types of attacks, and discusses future research directions.
Molecular Investigation and Genotyping of Theileria equi and Babesia caballi in Horses in Mus Province, Turkey

Equine Piroplasmosis (EP) is a tick-borne disease caused by Theileria equi and Babesia caballi of the phylum Apicomplexa. In this study, 102 blood samples were randomly collected from the horses in Mus province of Turkey. PCR analysis, gene sequences, and phylogenetic analyses were carried out for detecting the presence and genotypic characteristics of species that cause piroplasmosis. 4 (3.9%) of the 102 horses that were examined were found to be positive for T. equi, while B. caballi was not detected. Theileria equi isolates that were detected in the sequence analyses were found to be 100% identical to the isolates that were isolated from the horses in Turkey, the United States, and South Africa as well. In the phylogenetic analysis, all of the isolates were found to cluster with T. equi sequences in the genotype A. This study, in which we revealed intraspecies sequence heterogeneity of the parasite using the 18S rRNA gene region, provides important epidemiological data for equine piroplasmosis. However, we think that determining the characterization of genotypes that are common in different parts of our country is extremely important in terms of developing new diagnostic tools and vaccines
The Influences of Internal Recycling Competencies and External Environmental Conditions on Urban Residents' Waste Classification and Recycling Behaviours: Based on the Mediating Effects of Classification and Recycling Intentions

Waste classification and recycling behaviours of urban residents are important for waste recovery, reduction, and decontamination. Because residents' waste classification and recycling behaviours are influenced by several factors, this study developed a new waste classification and recycling influencing factor model. Based on 424 questionnaires collected from Shanghai residents, the influences of internal recycling competencies (i.e., waste classification skills and habits) and external environmental conditions (i.e., classification facilities and systems, reward and penalty measures for classification, and failure to safeguard classification achievements) on residents' classification and recycling behaviours were empirically tested. It was found that residents' classification and recycling skills and habits as well as government reward and penalty measures for classification had a significant positive effect on the residents' classification and recycling behaviours(0.159,p
Solving Fractional Coupled EW and Coupled MEW Equations Using Bernstein Collocation Method

This paper deals with approximation solution for coupled of space-time-fractional of both the equal width wave equation(FCEWE) and the modified equal width wave equation (FCMEWE) using Bernstein polynomials with collocation method and employing the Caputo definition for fractional derivatives. The method reduces the coupled system to a system of algebraic equations which is simple in handling and gives the best results.
Modelling investigation on the thermal conductivity of pure liquid, vapour, and supercritical refrigerants and their mixtures by using Heyen EOS

ABSTRACT This work presents a literature survey of the available data regarding the thermal conductivity of refrigerants. About 31 pure refrigerants that contain 7127 data points are selected for the temperature range of 91.35–580.00 K, a pressure range of (0.000111-500) bar, and thermal conductivity range of (0.007–0.27) W m−1 K−1 containing liquid, vapour, and supercritical phases. Seven binary and three ternary mixtures are also collected both in liquid and vapour phases with an overall of 803 data points. Based on the similarity between the pressure-volume-temperature and Tλ (thermal conductivity) P diagrams, the thermal conductivity model based on Heyen equation of state has been developed for pure refrigerants and their mixtures. The genetic algorithm is used to determine the adjustable parameters of the model. The calculation results prove that this proposed model can reproduce and predict thermal conductivity of refrigerants with good accuracy (overall AAD = 6.85% for pure compounds, AAD = 6.14% for binary mixtures and AAD = 9.32% for ternary mixtures).
Hydraulics analysis of the U-tubing effect in a riserless drilling system

As a newly developed marine drilling technology, riserless drilling (RD) shows obvious advantages for use in deep-water and ultra-deepwater petroleum resources exploitation. However, the available published hydraulic analysis models for RD are rare or imperfect, especially regarding the lack of accounting for the out-of-hole time. To analyse the actual flow characteristics of drilling mud in an RD system after the surface mud pumping is complete, this paper presents a new hydraulic simulation model of the U-tubing effect. The specific calculation methods of pressure loss in the drilling string and the wellbore annulus at different flow regimes (turbulent flow, transition flow, and laminar flow) are provided based on the Herschel-Bulkley (HB) rheological model. A case study shows that a critical volumetric flow rate (CVFR) exists for a specific RD system to just cause the standpipe pressure to become zero. Only when the initial pump circulation rate is greater than the CVFR can it ensure the normal operation of the RD. Otherwise, the fluid mud level inside the drilling string will drop, resulting in the u-tubing effect. In the first few seconds after the surface pump is shut down, the wellbore transient flow rate is influenced strongly by the initial circulation rate. When the initial flow rate is less than the CVFR, the transient flow rate is accelerated during the first few seconds, which is not the expected behaviour. The influence of the drilling string size, fluid density and rheological parameters of the drilling fluid on the transient flow rate and the Bottom Hole Pressure (BHP) are also considered. The results proved that the smaller values of the rheological parameters are beneficial for reducing the fluctuation of the BHP during the U-tubing process.
Unsupervised Learning for MRI Brain Tumor Segmentation with Spatially Variant Finite Mixture Model in Reversible Jump MCMC Algorithm

MRI brain tumor segmentation is an important topic in medical image processing. Manual segmentation is risky and time-consuming when the MRI is in low quality. The automatic segmentation can be a solution to manage this problem. This paper proposed an improved modeling approach for unsupervised learning trough Spatially Variant Finite Mixture Model (SVFMM). The main contribution is the automation of the SVFMM algorithm to find the optimum number of clusters. This is achieved by employing the birth-death random process in Bayesian Reversible Jump MCMC. Validation of the proposed model is done by calculating the Correct Classification Ration (CCR) in comparison to the original SVFMM and Gaussian Mixture Model (GMM). The proposed model provides similar performance in image segmentation compared to the original SVFMM but is better than GMM. However, SVFMM-RJMCMC is faster and more efficient in finding the optimum number of clusters.