Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-View Subspace Clustering by Joint Measuring of Consistency and Diversity

In multi-view subspace clustering, it is significant to find a common latent space in which the multi-view datasets are located. A number of multi-view subspace clustering methods have been proposed to explore the common latent subspace and achieved promising performance. However, previous multi-view subspace clustering algorithms seldom consider the multi-view consistency and multi-view diversity, let alone take them into consideration simultaneously. In this paper, we propose a novel multi-view subspace clustering by joint measuring the consistency and diversity, which is able to exploit these two complementary criteria seamlessly into a holistic design of clustering algorithms. The proposed model first searches a pure graph for each view by detecting the intrinsic consistent and diverse parts. A consensus graph is then obtained by fusing the multiple pure graphs. Moreover, the consensus graph is structurized to contain exactly <inline-formula><tex-math notation="LaTeX">$c$</tex-math><alternatives> <mml:math> <mml:mi>c</mml:mi> </mml:math> <inline-graphic xlink:href="lv-ieq1-3199587.gif"/></alternatives></inline-formula> connected components where <inline-formula><tex-math notation="LaTeX">$c$</tex-math><alternatives> <mml:math> <mml:mi>c</mml:mi> </mml:math> <inline-graphic xlink:href="lv-ieq2-3199587.gif"/></alternatives></inline-formula> is the number of clusters. In this way, the final clustering result can be obtained directly since each connected component precisely corresponds to an individual cluster. Extensive experimental studies on various datasets manifest that our model achieves comparable performance than the other state-of-the-art methods.
Secure resource allocation in device-to-device communications underlaying cellular networks

With increasing the demand for transmitting secure information in wireless networks, device-to-device (D2D) communication has great potential to improve system performance. As a well-known security risk is eavesdropping in D2D communication, ensuring information security is quite challenging. In this paper, we first obtain the closed-forms of the secrecy outage probability (SOP) and the secrecy ergodic capacity (SEC) for direct and decode- and-forward (DF) relay modes. Numerical results are presented to verify the theoretical results, and these results show the cases that the DF relay mode improves security performance compared to the direct mode at long distances between the transmitter and receiver nodes. Further, we look into the optimization problems of secure resource allocation in D2D communication to maximize the SEC and to minimize the SOP by considering the strictly positive secrecy capacity constraint as a mixed-integer non-linear programming (MINLP) problem. In the continue, we convert the MINLP to convex optimization. Finally, we solve this program with a dual method and obtain an optimal solution in the direct and DF relay modes.
Offset-Free Model Predictive Control of Fuel Cell DC–DC Boost Converter With Low-Complexity and High-Robustness

This article proposes an easily implementable and computationally effective model predictive control (MPC) scheme for fuel cell dc–dc boost converter. The proposed control scheme contains an explicit MPC method just with a single-step predictive horizon. Thus, the computational burden can be greatly reduced. To further enhance its antidisturbance ability, the observer technique is adopted to, respectively, estimate the load impedance and input voltage for the predictive models. Since the estimated variables can be directly sent to the cost function, the satisfactory disturbance rejection performance can be guaranteed with optimal control. Besides, an additional reference current generation module based on the flatness theory is built to deal with the inevitable parameter uncertainties and the estimation errors. Thus, the nominal system model can be directly adopted to further reduce the design complexity. Some simulation and experimental tests based on a multiphase interleaved fuel cell dc–dc boost converter are conducted to verify the superiority of the proposed control scheme. Results show that, with the proposed control scheme, both the dynamic performance and robustness of the closed-loop system are satisfactory, which can help to contribute to the fuel cell applications in transportation electrification.
Grid Impedance Estimation Using Several Short-Term Low Power Signal Injections

In this paper, a signal processing method is proposed to estimate the low and highfrequency impedances of power systems using several short-term low power signal injections for a frequency range of 0-150 kHz. This frequency range is very important, and thusso it is considered in the analysis of power quality issues of smart grids. The impedance estimation is used in many power system applications such as power quality analysis of smart grids and grid connected renewable energy systems. The proposed impedance estimation technique is based on applying a wideband voltage signal at a Point of Common Coupling (PCC) and then a division of the voltage to a generated current signal in a frequency range of 0-150 kHz. In a noisy system, the energy of the injected signal must be sufficient for an accurate approximation. This is the main issue in proposing a new method for the impedance estimation. In this paper, our simulation error is additive white Gaussian noise which is considered as a generic measurement noise. The proposed algorithm consists of three main parts: 1) Determining several injection signals with sufficient energy using the Genetic algorithm. At least one of the determined signals should have sufficient energy in some frequencies so that the union of these ranges is can be the universal set of estimation. 2) Injecting individuals of the signals to the grid separately, and estimating the impedance following Ohm’s law. The width of injection signals is calculated by the best chromosome in GA. 3) The fusion of estimated impedances. The simulation results show that the proposed method can properly estimate grid impedance in a wide frequency range up to 150 kHz. Review History: Received: 6 February 2017 Revised: 23 August 2017 Accepted: 26 August 2017 Available Online:12 September 2018
Analysis of stakeholder roles and the challenges of solar energy utilization in Iran

Growing energy demand, rising greenhouse gas emissions and the depletion of fossil fuels necessitates the development of renewable energy sources. In order to improve renewable energy utilization, it is necessary to determine the most important factors influencing energy strategy. The energy system of Iran is highly dependent on fossil fuels; however, Iran has a high potential for solar energy development and several policies are being pursued by the government to develop power generation by renewable energy resources. This study presents and discusses several important parameters of energy policy and security which make the installation of photovoltaic (PV) systems crucial for the future. Installation of solar PV will improve energy security, foster job creation and reduce environmental problems. It also introduces and investigates those institutions and organizations involved in developing renewable energies, especially solar energy. These include the Ministry of Energy and universities, both of which play key roles in the development of solar energy.
Radiopharmaceutical Treatments for Cancer Therapy, Radionuclides Characteristics, Applications, and Challenges

Advances in the field of molecular biology have had an impact on biomedical applications, which provide greater hope for both imaging and therapeutics. Work has been intensified on the development of radionuclides and their application in radiopharmaceuticals (RPS) which will certainly influence and expand therapeutic approaches in the future treatment of patients. Alpha or beta particles and Auger electrons are used for therapy purposes, and each has advantages and disadvantages. The radionuclides labeled drug delivery system will deliver the particles to the specific targeting cell. Different radioligands can be chosen to uniquely target molecular receptors or intracellular components, making them suitable for personal patient-tailored therapy in modern cancer therapy management. Advances in nanotechnology have enabled nanoparticle drug delivery systems that can allow for specific multivalent attachment of targeted molecules of antibodies, peptides, or ligands to the surface of nanoparticles for therapy and imaging purposes. This review presents fundamental radionuclide properties with particular reference to tumor biology and receptor characteristic of radiopharmaceutical targeted therapy development.
Improvement of Bacterial Blight Resistance in Two Conventionally Cultivated Rice Varieties by Editing the Noncoding Region

xa13 is a recessive pleiotropic gene that positively regulates rice disease resistance and negatively regulates rice fertility; thus, seriously restricting its rice breeding application. In this study, CRISPR/Cas9 gene-editing technology was used to delete the Xa13 gene promoter partial sequence, including the pathogenic bacteria-inducible expression element. Rice with the edited promoter region lost the ability for pathogen-induced gene expression without affecting background gene expression in leaves and anthers, resulting in disease resistance and normal yield. The study also screened a family of disease-resistant and normal fertile plants in which the target sequence was deleted and the exogenous transgene fragment isolated in the T1 generation (transgene-free line). Important agronomic traits of the T2 generation rice were examined. T2 generation rice with/without exogenous DNA showed no statistical differences compared to the wild type in heading stage, plant height, panicles per plant, panicle length, or seed setting rate in the field. Two important conventional rice varieties, namely Kongyu131 (KY131, Geng/japonica) and Huanghuazhan (HHZ, Xian/indica), were successfully transformed, and disease-resistant and fertile materials were obtained. Currently, these are the two important conventional rice varieties in China that can be used directly for production after improvement. Expression of the Xa13 gene in the leaves of transgenic rice (KY-PD and HHZ-PD) was not induced after pathogen infection, indicating that this method can be used universally and effectively to promote the practical application of xa13, a recessive disease-resistant pleiotropic gene, for rice bacterial blight resistance. Our study on the regulation of gene expression by editing noncoding regions of the genes provides a new idea for the development of molecular design breeding in the future.
ANALYSIS OF AIRBORNE FACTORS OF IVANO-FRANKIVSK POPULATION MORBIDITY

The research was aimed at analysis of statistical data about children morbidity and cancer incidence to establish their dependence on the level of air pollutants concentration on the example of the city of Ivano-Frankivsk, which is located in close proximity to the Carpathian protected area, but has a range of pollution sources of industrial and transport type.
Deep Learning-Based Posture Recognition for Motion-Assisted Evaluation

With the development of computer vision technology, human action pose recognition has gradually become a popular research direction, but there are still some problems in the application research based on pose recognition in sports action assisted evaluation. In this paper, the human motion pose recognition technology based on deep learning is introduced into this field to realize the intelligence of sports-assisted training. Firstly, we analyze the advantages and limitations of the state-of-the-art human motion pose recognition algorithms in computer vision in specific fields. On this basis, a human motion space recognition method based on periscope neural network is proposed. Firstly, the classical radar signal processing method is used to preprocess the echo signal of human spatial position and generate the frequency image in the process of human spatial position. Then, the periscope neural network (CNN) is constructed, and the time-frequency image is used as the input data of CNN to train the network parameters. Finally, the method is tested by using the open dataset in the network. The experimental results show that the designed CNN can accurately identify four different types of physical motion, and the accuracy coefficient is at least 97%.
The complete mitochondrial genomes and phylogenetic analysis of two Nycteribiidae bat flies (Diptera: Hippoboscoidea)

Abstract We sequenced the complete mitochondrial genomes of two bat fly species within the Nycteribiidae (Diptera: Hippoboscoidea) – Dipseliopoda setosa (Cyclopodiinae) and Basilia ansifera (Nycteribiinae). Both mitogenomes were complete and contained 13 protein-coding genes, 22 tRNAs, and two rRNAs. Relative to the inferred ancestral gene order of dipteran mitochondrial genomes, no rearrangements were identified in either species. There were large differences in size between the two genomes, with D. setosa having a larger genome (19,164 bp) than B. ansifera (16,964 bp); both species had larger genomes than two previously published Streblidae bat fly species (e.g., Paradyschiria parvula and Paratrichobius longicrus). The increased genome sizes were due to expansions in the control region and the non-coding region downstream of the light-strand origin of replication. Additional differences between the two mitogenomes included a significantly longer cox3 gene in B. ansifera and a longer nad1 gene in D. setosa. Interestingly, both genomes also had the lowest GC content (D. setosa – 15.9%; B. ansifera – 17.0%) of any available Hippoboscoidea mitochondrial genome (18.8–23.9%). These mitogenomes represent the first sequences from species within the bat fly family Nycteribiidae. The sequence data here will provide a foundation for continued studies of genome evolution more generally within obligate blood-feeding ectoparasites, and specifically for the bat flies as vectors of significant ‘bat-associated’ viruses and microorganisms.
Flexible and Robust Real-Time Intrusion Detection Systems to Network Dynamics

Deep learning-based intrusion detection systems have advanced due to their technological innovations such as high accuracy, automation, and scalability to develop an effective network intrusion detection system (NIDS). However, most of the previous research has focused on model generation through intensive analysis of feature engineering instead of considering real environments. They have limitations to applying the previous methods for a real network environment to detect real-time network attacks. In this paper, we propose a new flexible and robust NIDS based on Recurrent Neural Network (RNN) with a multi-classifier to generate a detection model in real time. The proposed system adaptively and intelligently adjusts the generated model with given system parameters that can be used as security parameters to defend against the attacker’s obfuscation techniques in real time. In the experimental results, the proposed system detects network attacks with a high accuracy and high-speed model upgrade in real-time while showing robustness under an attack.
On the Return Stroke Initiated From the Attachment Point Considering Current Reflection From the Ground

In this article, we present an analysis of electric fields and derivative waveforms radiated from lightning return stroke in the presence of an attachment point above the ground. Return stroke initiated from the ground (RSG), return stroke initiated from an attachment point above the ground (RSAP), and return stroke initiated from the attachment point considering current reflection from the ground (RSAPR) were considered and compared. Both first and subsequent return strokes were included in the simulation. It is shown that the presence of the attachment point results in a noticeable initial sharp peak on the electric fields and the derivative waveform was characterized by larger positive peak and negative overshoot. Both the electric field and derivative waveforms in RSAPR were much similar and closer to the results from RSG due to the current reflection from the ground. The influences on the electric fields and derivative waveforms were also discussed, including velocity of upward and downward wave, the attachment point height, reflection coefficient from the ground, and wave velocity of the reflected wave. The simulated results were also compared to the measured fields.
Complete human mtDNA genome sequences revealed haplotype features of the Hmong-Mien language family in Vietnam

Vietnam is the homeland of 54 different ethnicities that belong to 5 major language families of the world, including Austroasiatic, Tai-Kadai, Hmong-Mien, Sino-Tibetan and Austronesian. Hmong-Mien, an ethnolinguistic family, presumably stemmed from Southern China and later spread to the Southeast Asia region. In this study, we analyzed the mitochondrial DNA sequences taken from 120 males belonging Hmong-Mien (HM) language family in Vietnam: Dao, Hmong, and Pathen, revealing 352 unique variants. Dao has the most number of polymorphisms (230 unique SNPs occurring 1469 times), followed by Hmong (181 unique SNPs occurring 1367 times) and Pathen (159 SNPs occurring 1243 times). Genetic variations within each population and among Hmong-Mien speakers were further measured by computations of haplotype diversity (H), nucleotide diversity (π) and fixation index (FST). There are nine major haplogroups (A, B, C, D, F, G, M, N9, and R) detected, with F and B making up over half of each population (Hmong: 56.09% (23/41), Pathen: 58.33% (21/36), Dao: 62.79% (27/43)). Haplotype classification was further divided into 30 haplogroups, of which 80% of them were specific to a single minority. Dao remained the most genetically diverse (H=0.957), while Pathen was the most homogeneous population (H=0.900). In terms of genetic distance, Dao and Hmong were more distinguished from each other, while Hmong and Pathen were more related. Complete mtDNA sequences of Viet HM speakers increased the mtDNA depository, improving the understanding of the genetic structure underlying this language family.
Theory of spherical and cylindrical Langmuir probes in a collisionless

A hydrodynamic torque converter for vehicles, particularly for passenger motor vehicles, with at least one pump wheel, one turbine wheel and one guide wheel supported on a free-wheeling device, in which the guide blades are automatically adjustable, when the guide wheel rotates, in dependence on the centrifugal force in the sense of a cascade opening with an increasing rotational speed.
Electrolyte Engineering for High-Voltage Lithium Metal Batteries

High-voltage lithium metal batteries (HVLMBs) have been arguably regarded as the most prospective solution to ultrahigh-density energy storage devices beyond the reach of current technologies. Electrolyte, the only component inside the HVLMBs in contact with both aggressive cathode and Li anode, is expected to maintain stable electrode/electrolyte interfaces (EEIs) and facilitate reversible Li+ transference. Unfortunately, traditional electrolytes with narrow electrochemical windows fail to compromise the catalysis of high-voltage cathodes and infamous reactivity of the Li metal anode, which serves as a major contributor to detrimental electrochemical performance fading and thus impedes their practical applications. Developing stable electrolytes is vital for the further development of HVLMBs. However, optimization principles, design strategies, and future perspectives for the electrolytes of the HVLMBs have not been summarized in detail. This review first gives a systematical overview of recent progress in the improvement of traditional electrolytes and the design of novel electrolytes for the HVLMBs. Different strategies of conventional electrolyte modification, including high concentration electrolytes and CEI and SEI formation with additives, are covered. Novel electrolytes including fluorinated, ionic-liquid, sulfone, nitrile, and solid-state electrolytes are also outlined. In addition, theoretical studies and advanced characterization methods based on the electrolytes of the HVLMBs are probed to study the internal mechanism for ultrahigh stability at an extreme potential. It also foresees future research directions and perspectives for further development of electrolytes in the HVLMBs.
Differences in High- and Low-Performing Students’ Fraction Learning in the Fourth Grade

Abstract The aim of this longitudinal study was to examine the differences between high- and low-performing students’ development of fraction proficiency over a school year and to investigate how those differences were related to instruction in fractions versus instruction in other mathematics topics. The data for this study were drawn from a group of (n = 398) students from 21 fourth-grade classes, from which we formed two subgroups: the 25% highest performing students (n = 99) and the 25% lowest performing students (n = 100), based on their Danish national test scores. The students’ fraction proficiency levels were studied over eight months at five measurement time points. A multiple linear regression analysis with random effects was used to model the test scores. The results showed that the high-performing students developed their fraction proficiency during most of the school year—both when instructed in fractions and, more surprisingly, when instructed in other mathematics topics. In contrast, low-performing students only developed their fraction proficiency while being instructed in fractions. Finally, the gap between high- and low-performing students’ fraction proficiency widened both when the students were taught lessons on fractions and when they were taught other topics in mathematics.
Investigation into the Effects of Subjective Test Interface Choice on the Validity of Results

Subjective experiments are a cornerstone of modern research, with a variety of tasks being undertaken by subjects. In the field of audio, subjective listening tests provide validation for research and aid fair comparison between techniques or devices such as coding performance, speakers, mixes and source separation systems. Several interfaces have been designed to mitigate biases and to standardise procedures, enabling indirect comparisons. The number of different combinations of interface and test design make it extremely difficult to conduct a truly unbiased listening test. This paper resolves the largest of these variables by identifying the impact the interface itself has on a purely auditory test. This information is used to make recommendations for specific categories of listening tests.
Activity and health monitoring systems

Abstract This paper presents an Open Platform Activity and health monitoring systems which are also called e-Health systems. These systems measure and store parameters that reflect changes in the human body. Due to continuous monitoring (e.g. in rest state and in physical effort state), a specialist can learn about the individual's physiological parameters. Because the human body is a complex system, the examiner can notice some changes within the body by looking at the physiological parameters. Six different sensors ensure us that the patient's individual parameters are monitored. The main components of the device are: A Raspberry Pi 3 small single-board computer, an e-Health Sensor Platform by Cooking-Hacks, a Raspberry Pi to Arduino Shields Connection Bridge and a 7-inch Raspberry Pi 3 touch screen. The processing unit is the Raspberry Pi 3 board. The Raspbian operating system runs on the Raspberry Pi 3, which provides a solid base for the software. Every examination can be controlled by the touch screen. The measurements can be started with the graphical interface by pressing a button and every measured result can be represented on the GUI’s label or on the graph. The results of every examination can be stored in a database. From that database the specialist can retrieve every personalized data.