Miracle-dz/UniFAR-FTUs huggingface dataset:
Audio-visual aspect of the Lombard effect and comparison with recordings depicting emotional states

In this paper an analysis of audio-visual recordings of the Lombard effect is shown. First, audio signal is analyzed indicating the presence of this phenomenon in the recorded sessions. The principal aim, however, was to discuss problems related to extracting differences caused by the Lombard effect, present in the video, i.e. visible as tension and work of facial muscles aligned to an increase in the intensity of the articulated speech signal. Also the database of recordings, available on the internet, depicting emotional states was analyzed in order to compare and find a visual similarity between the Lombard effect and sentiment contained in speech. The results presented are discussed and further plans are depicted.
Real-time loop-mediated isothermal amplification for rapid detection of Enterocytozoon hepatopenaei

Background Enterocytozoon hepatopenaei (EHP) is a newly emerged microsporidian parasite that causes retarded shrimp growth in many countries. But there are no effective approaches to control this disease to date. The EHP could be an immune risk factor for increased dissemination of other diseases. Further, EHP infection involves the absence of obvious clinical signs and it is difficult to identify the pathogen through visual examination, increasing the risk of disease dissemination. It is urgent and necessary to develop a specific, rapid and sensitive EHP-infected shrimp diagnostic method to detect this parasite. In the present study, we developed and evaluated a rapid real-time loop-mediated isothermal amplification (real-time LAMP) for detection of EHP. Methods A rapid and efficient real-time LAMP method for the detection of EHP has been developed. Newly emerged EHP pathogens in China were collected and used as the sample, and three sets of specificity and sensitivity primers were designed. Three other aquatic pathogens were used as templates to test the specificity of the real-time LAMP assay. Also, we compared the real-time LAMP with the conventional LAMP by the serial dilutions of EHP DNA and their amplification curves. Application of real-time LAMP was carried out with clinical samples. Results Positive products were amplified only from EHP, but not from other tested species, EHP was detected from the clinical samples, suggesting a high specificity of this method. The final results of this assay were available within less than 45 min, and the initial amplification curve was observed at about 6 min. We found that the amplification with an exponential of sixfold dilutions of EHP DNA demonstrated a specific positive signal by the real-time LAMP, but not for the LAMP amplicons from the visual inspection. The real-time LAMP amplification curves demonstrated a higher slope than the conventional LAMP. Discussion In this study, pathogen virulence impacts have been increased in aquaculture and continuous observation was predominantly focused on EHP. The present study confirmed that the real-time LAMP assay is a promising and convenient method for the rapid identification of EHP in less time and cost. Its application greatly aids in the detection, surveillance, and prevention of EHP.
Analysis of fourth order manipulator kinematics using conic sections

A technique for analyzing robots with fourth-order inverse kinematic solutions is introduced. The solution of the inverse kinematics problem is restated as a pencil of conics. In this representation, the order of the solution reduces when one of the conics in the pencil becomes degenerate and noncentral. Properties of conics are exploited to define and develop special manipulator geometries. The method is illustrated by a detailed examination of all revolute (R) robots which have a three-axis wrist (i.e. 3R regional manipulators). All criteria for reduction of the inverse kinematics of this type of robot are determined, resulting in some new robot designs. These designs constitute all regional robots with kinematics that require the solution of only quadratic equations. <<ETX>>
Demodulated High-Order Synchrosqueezing Transform With Application to Machine Fault Diagnosis

Time–frequency analysis (TFA) is considered as a useful tool to extract the time-variant features of the nonstationary signal. In this paper, a new method called demodulated high-order synchrosqueezing transform (DHST) is proposed. The DHST introduces a two-step algorithm, namely, demodulated transform and high-order synchrosqueezing method to achieve a compact time–frequency representation (TFR) while enabling the reconstruction of the signal from TFR. The performance of the proposed DHST method in this paper is validated by both the simulated and experimental signals including bat echolocation and a vibration signal. The results show that the proposed TFA method is more effective in processing the nonstationary signals with fast varying instantaneous frequency.
An analysis of common foodborne parasitic zoonoses in slaughtered sheep and cattle in Tehran, Iran, during 2015-2018

Background and Aim: Cystic echinococcosis, Echinococcus granulosus, and liver flukes, such as Fasciola spp. and Dicrocoelium dendriticum, are important parasitic zoonoses, where they able to cause significant veterinary, medical, and economic problems. The present study was carried out to obtain the updated knowledge on the frequency of hydatidosis, fasciolosis, and dicrocoeliosis in the slaughtered sheep and cattle. Materials and Methods: Information were collected from meat inspection records using systematically visual inspection, palpation, and incision of the visceral organs in the industrial abattoir in Tehran, the capital of Iran, between February 1, 2015, and January 31, 2018. For an analysis of the data, SPSS version 16 was applied. Results: The hydatidosis infection in sheep and cattle was 2.48% and 2.25%, respectively. With respect to liver flukes, 0.62% and 0.25% sheep and cattle were infected by Fasciola spp. , respectively; furthermore, 2.86% sheep and 0.79% cattle were positive for D. dendriticum. Conclusion: The findings will provide considerable awareness for the future monitoring and control of these potentially important infections.
Generative Adversarial Network for Deblurring of Remote Sensing Image

Deblurring is a classical problem for remote sensing images, which is known to be difficult as an ill-posed problem. A feasible solution for the problem is incorporating various priors into restoration procedure as constrained conditions. However, the learning of priors usually assumes that the blurs in an image are produced by fixed types of reasons, and thus a possible decrease in model's description ability. In this paper, an end-to-end learned method based on generative adversarial networks (GANs) is proposed to tackle the deblurring problem for remote sensing images. The proposed deblurring model does not need any prior assumptions for the blurs. The proposed method was evaluated on a satellite map image data set and state-of-the-art performance was obtained.
Design Optimization of a Spoke-Type FSCW IPM Machine to Achieve Low Torque Ripple and High Torque Density Under a Wide Constant Power Speed Range

This paper optimally designs a fractional-slot concentrated-winding (FSCW) spoke-type interior permanent magnet (IPM) machine using a multi-objective optimization algorithm to achieve a high torque density, low torque ripple, wide constant power speed range (CPSR) with minimum material cost. Each of these objectives is in contradiction, which makes the design optimization a challenging process. This paper uses a well-defined finite element-based design optimization technique to find a global optimum design that can achieve the targeted objectives. 10-pole 12-slot combination has been selected as a well-known stator configuration. The optimization results demonstrate the capability of the optimized FSCW spoke-type IPM machine in the reduction of torque ripple without a reduction in torque density and CPSR. The selected optimized design has been prototyped to verify the results of optimization. Wide-ranging experimental tests are conducted to evaluate the performance characteristics of the prototype for the entire range of operation.
Arsenic sulfide amplifies JQ1 toxicity via mitochondrial pathway in gastric and colon cancer cells

Purpose Gastric and colon cancers have been the leading causes of cancer mortality in the world with limited therapy. Small molecules binding to bromodomains of bromodomain-containing protein 4 (BRD4) exert strong antitumor activities against hematological malignancies, while generally have limited efficacy in advanced solid tumors. Here, we found that the bromodomain and extra-terminal (BET)-bromodomain inhibitor JQ1, when combined with arsenic sulfide (As4S4, abbreviated as AS), synergistically decreased the expression of nuclear factor of activated T-cells (NFATs) as well as the downstream oncogene c-Myc and largely induced cell apoptosis via mitochondrial pathway in gastric and colon cancer cell lines. Methods The synergistic cytotoxicity of AS and JQ1 in gastric and colon cancer cells was determined by MTT assay and verified by FACS assay. Western blot analysis and quantitative real-time PCR (qPCR) assay were used to detect the expression of NFATs and downstream apoptotic proteins. The mitochondrial transmembrane potential was determined by FACS assay, and the metastasis of cancer cells was detected by the wound-healing assay. Results AS and JQ1 synergistically induced cell apoptosis in gastric and colon cancer cells by downregulating NFATs and upregulating apoptotic proteins. Combination of AS and JQ1 was associated with the decreased mitochondrial transmembrane potential, the cytochrome c release, and the subsequent caspase-3 activation. Conclusion Thus, our data indicate that AS can effectively enhance the cytotoxicity of BET inhibitors in gastric and colon cancer cells through mitochondrial-mediated apoptosis induction.
Combined Current Profiling and Biological Echosounding Results from a Single ADCP

The present work describes a newly-developed Acoustic Doppler Current Profiler (ADCP) that has a fully integrated single-beam wide-band biological echosounder, thus serving a dual purpose: current measurement and biomass assessment. The system comprises a traditional 4-beam Janus configuration head, which is responsible for profiling the currents, with a vertically oriented center beam for collecting high-resolution acoustic backscatter data for subsequent biomass analysis. The system belongs to the Signature Series family of ADCPs launched in 2013 by Norwegian scientific instrumentation company Nortek. Named Signature100, it is powered by the AD2CP electronics platform, described in United States Patent 7.911. 880. The four slanted beams (current profiling beams) operate at a center frequency of 100 kHz and have a range of up to 400 m with 4 m spatial resolution and sampling rate up to 1 Hz. The center vertical beam (echosounding beam) has a wider frequency band of approximately 70–120 kHz with a high dynamic range (∼130 dB), and presently operating in up to three discreet pulse characteristics from a single beam set: 1) 70 kHz monochromatic, 2) 120 kHz monochromatic, and 3) 91 kHz chirp with 50 percent bandwidth and pulse compression. Acoustic pulses from the echosounder beam are interweaved with pulses for the current profiling beam for synchronous data collection. In this work we describe the system's configuration, capabilities and results from initial trials.
Outlier Detection for Hydropower Generation Plant

A hydropower generation plant is a complex system and composed of numerous physical components. To monitor the health of different components it is necessary to detect anomalous behavior in time. Establishing a performance guideline along with identification of the critical variables causing anomalous behavior can help the maintenance personnel to detect any potential shift in the process timely. To establish any guideline for future control, at first a mechanism is needed to differentiate anomalous observations from the normal ones. In our work we have employed three different approaches to detect the anomalous observations and compared their performances using a historical data set received from a hydropower plant. The outliers detected are verified by the domain experts. Making use of a decision tree and feature selection process, we have identified some critical variables which are potentially linked to the presence of the outliers. We further developed a one-class classifier using the outlier cleaned dataset, which defines the normal working condition, and therefore, violation of the normal conditions could identify anomalous observations in future operations.
Clearing Algorithms and Network Centrality

I show that the solution of a standard clearing model commonly used in contagion analyses for financial systems can be expressed as a specific form of a generalized Katz centrality measure under conditions that correspond to a system-wide shock. This result provides a formal explanation for earlier empirical results which showed that Katz-type centrality measures are closely related to contagiousness. It also allows assessing the assumptions that one is making when using such centrality measures as systemic risk indicators. I conclude that these assumptions should be considered too strong and that, from a theoretical perspective, clearing models should be given preference over centrality measures in systemic risk analyses.
Morphological Analysis of 3D Skull Models for Ancestry Estimation

Skull analysis is the main tool used in anthropology to identify several characteristics such as ancestry, sex, and variations between populations. Yet, skull analysis methods used by anthropologists still rely heavily on direct manipulation and measurement of the skulls producing significant inter and intra observer errors. Direct manipulation also involves risks of damaging the specimens while handling. In recent years computer methods for skull analysis that rely on 3D models of skulls acquired with a 3D scanner have been proposed. This approach gives the possibility to perform analysis otherwise not possible, simultaneously easing the overall process of skull analysis and reducing variability. This paper describes the development of automatic and semi-automatic methods for morphological analysis of 3D skull models through the extraction and classification of structures aiming to support the estimation of ancestry. Results with fifty specimens are presented
Formal Analysis and Verification of DDS in ROS2

Robot Operating System(ROS) is widely used in the development of various service robots, which have high requirements in safety and reliability. Data distribution service(DDS) is deployed in ROS2 to implement the control of nodes and data distribution, which is very important for the operation of application on ROS2. In this paper, we focus on model abstraction, formal modeling and automatic verification for DDS in ROS2. A distributed model with interface parameters was established in PRISM. Properties such as security, liveness and priority of DDS in ROS2 were verified. The results show that the design satisfies these properties and high-priority messages can be sent and transmitted preferentially by the system. Due to the experiment result, we come up with a suggestion that the system will be better if its buffer can store six messages or more.
A 280GHz Super Regenerative Receiver with Differential Parallel Inductor in 65nm CMOS

Base on 65nm CMOS process, a super-regenerative receiver (SRR) is proposed in this paper. By using a novel differential parallel inductor (DPI), the SRR realizes high sensitivity. The simulated results show that the sensitivity of the SRR is -90dBm, the 3dB bandwidth is 2.3GHz, and the gain is larger than 13.5dB in its range of the 3dB bandwidth. The power consumption is 10.4 mW while applying 1.2-V power supply. The core area is 0.013 mm2.
Identification of key candidate genes and biological pathways in bladder cancer

Background Bladder cancer is a malignant tumor in the urinary system with high mortality and recurrence rates. However, the causes and recurrence mechanism of bladder cancer are not fully understood. In this study, we used integrated bioinformatics to screen for key genes associated with the development of bladder cancer and reveal their potential molecular mechanisms. Methods The GSE7476, GSE13507, GSE37815 and GSE65635 expression profiles were downloaded from the Gene Expression Omnibus database, and these datasets contain 304 tissue samples, including 81 normal bladder tissue samples and 223 bladder cancer samples. The RobustRankAggreg (RRA) method was utilized to integrate and analyze the four datasets to obtain integrated differentially expressed genes (DEGs), and the gene ontology (GO) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. Protein-protein interaction (PPI) network and module analyses were performed using Cytoscape software. The OncoLnc online tool was utilized to analyze the relationship between the expression of hub genes and the prognosis of bladder cancer. Results In total, 343 DEGs, including 111 upregulated and 232 downregulated genes, were identified from the four datasets. GO analysis showed that the upregulated genes were mainly involved in mitotic nuclear division, the spindle and protein binding. The downregulated genes were mainly involved in cell adhesion, extracellular exosomes and calcium ion binding. The top five enriched pathways obtained in the KEGG pathway analysis were focal adhesion (FA), PI3K-Akt signaling pathway, proteoglycans in cancer, extracellular matrix (ECM)-receptor interaction and vascular smooth muscle contraction. The top 10 hub genes identified from the PPI network were vascular endothelial growth factor A (VEGFA), TOP2A, CCNB1, Cell division cycle 20 (CDC20), aurora kinase B, ACTA2, Aurora kinase A, UBE2C, CEP55 and CCNB2. Survival analysis revealed that the expression levels of ACTA2, CCNB1, CDC20 and VEGFA were related to the prognosis of patients with bladder cancer. In addition, a KEGG pathway analysis of the top 2 modules identified from the PPI network revealed that Module 1 mainly involved the cell cycle and oocyte meiosis, while the analysis in Module 2 mainly involved the complement and coagulation cascades, vascular smooth muscle contraction and FA. Conclusions This study identified key genes and pathways in bladder cancer, which will improve our understanding of the molecular mechanisms underlying the development and progression of bladder cancer. These key genes might be potential therapeutic targets and biomarkers for the treatment of bladder cancer.
A High Speed SoftMax VLSI Architecture Based on Basic-Split

Due to simple to calculate and derivate, SoftMax is widely used in neural network computing as an activation function. But how to guarantee the accuracy and speed while minimizing the consumption of hardware resources is the most critical issue in the current SoftMax hardware design. The available Polynomial Fitting and CORDIC are contradictory in resource occupancy and accuracy. To meet the need of SoftMax, this paper proposes a new method named Basic-Split Calculation. Taking advantage of the math feature of exponential function, the Basic-Split Calculation method splits the exponentiation calculation of the SoftMax into several specific basics which is implemented by look-up table. Based on this strategy, the complex exponential calculation process is implemented by look-up table procedure and multiply operation. It simplify the hardware complexity and logic propagation delay remarkably. Experiment results show that the actual error rate is 10−8 magnitude. And, synthesis report based on SMIC65nm technology library show that, the operation frequency can be up to 1GHz. Compared with the existing design, Basis-Split Calculation method has a lot of advantages, such as faster calculation speed, higher accuracy, larger throughput.
Manipulator transition to and from contact tasks: a discontinuous control approach

The stability and control of robotic manipulators during the execution of tasks that require the manipulator to make a transition from noncontact motion to contact motion, or vice versa, are investigated. A dynamic model of the manipulator during noncontact and contact motion is developed. This model includes the effect of the inevitable collision that occurs between the manipulator end effector and the work environment during the transition from noncontact to contact motion. The work environment that the manipulator comes into contact with is modeled as a very still surface. The dynamic model of the robot during this transition is transformed through a nonlinear coordinate transformation into a new set of generalized coordinates in which the form of the dynamics is greatly simplified. A discontinuous control is proposed for the robotic manipulator system. It is shown that with this discontinuous control applied to the system, the closed-loop system can be treated as a generalized dynamical system. Using the theory associated with generalized dynamical systems, it is possible to extend Lyapunov stability analysis to systems with discontinuous controls. The system dynamics is written as a contingent equation to which a set valued control function is applied. Within this mathematical framework, the uniform asymptotic stability in the larger of the closed-loop systems is proved. The controller has several desirable properties, including the ability to return to contact motion if the manipulator end effector inadvertently leaves the surface due to some external disturbance acting on the system. <<ETX>>
Extraction of Cyanobacteria in Taihu Lake Based on Remote Sensing Image

In recent years, along with the rapid development of economy and the intensification of human activities, the eutrophication of inland lakes has become increasingly serious, leading to frequent occurrence of cyanobacteria. Cyanobacteria monitoring has become an important part of water quality control. Compared with traditional artificial water quality monitoring methods, remote sensing technology has more means to obtain information, which is faster and shorter in cycle time, and more conducive to monitor large-scale waters rapidly. In this study, Landsat-8 image of Taihu Lake in 2014 was taken as data foundation. The BP neural network algorithm was used as the extraction method of cyanobacteria in Taihu Lake. It provided a reliable technical support for the follow-up application field of cyanobacteria treatment and lake ecological protection.
Appearance of Achromatic Colors Under Optimized Light Source Spectrum

Light source spectrum can be optimized for object reflectance to reduce the energy consumption by reducing the amount of light absorbed by surfaces. While the feasibility of this approach to architectural lighting has been demonstrated, this concept has only been tested with objects of highly saturated colors. Here, the color appearance of 24 Macbeth ColorChecker test samples, which includes achromatic surfaces (i.e., gray, black, and white), illuminated by optimized theoretical test spectra and reference light sources (incandescent, equal-energy radiator, and phosphor-coated white LED) were calculated using a color space based on the International Commission on Illumination's (CIE) color appearance model, CIECAM02-UCS. Results show that energy consumption could be reduced to between 39% and 90%, with small shifts in color appearance, when considering all object colors. When lighting is optimized for achromatic test samples, energy consumption and light absorption were reduced more than when optimized for colorful surfaces, with imperceptible shifts in color appearance.