Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Study of Data and Power Wireless Transfer System for UAV

Unmanned aerial vehicle (UAV) has been widely used in a variety of occasions in recent decades. Due to the lack of battery capacity, its endurance has been limited. To tackle this problem, wireless power transfer (WPT) technology is a great solution to UAV from the charging perspective. In this paper, a data and power wireless transfer system of UAV based on inductive power transfer (IPT) technology is proposed. The key constraint of wireless charging with regards to the inherent magnetic coupling coefficient is investigated. In this paper, ferrite and metglas amorphous alloy are used as a case study of the magnetic coupling problem. The magnetic material is placed next to the secondary coil side to investigate the effects of horizontal displacement and air gap distance on the coupling coefficient and magnetic field distribution. An experimental system platform is implemented, and the commercial finite element software tool Comsol is used to evaluate the performance of the magnetic material. The simulation results showed that amorphous alloy magnetic material is superior to ferrite material, and it is in a good agreement to the experimental results. Furthermore, the attention of using metglass material in the practical application has been discussed.
Gene Mutation Classification Using CNN and BiGRU Network

Designing medical solutions based on genomic information can help achieve precision medicine. Currently, clinical pathologists have to manually review and classify each gene mutation according to the evidence in the clinical literature, which is a time-consuming work. In this paper, we propose a novel machine learning algorithm that can classify gene mutations based on clinical evidence (text). The algorithm model combines convolutional neural network (CNN) with Bidirectional Gated Recurrent Unit (BiGRU) sequence neural network, in which CNN is used as feature extractor of semantic information and BiGRU is used as mapping device of context semantic structure. This model can analyze text from two aspects—semantic information features and context semantic structure. We train and evaluate the model using a real-world dataset. Experimental results show that our model outperforms traditional single neural network model and some mixed neural network models.
The impact of social networks on technology entrepreneurs’ opportunity recognition process

The purpose of this study is to examine the relationships of the weak ties network and entrepreneurial opportunity recognition of small technology firms in Malaysia. The study seeks to explore the gaps between the practice of networking among new start-up firms and industry. This paper employs quantitative research design involving self-reporting questionnaires. Founders and co-founders of technology companies (n=255) are surveyed as respondents and data collected are analysed using Partial Least Squares – Structural Equation Modeling (PLS-SEM) technique to examine the reliability, goodness-of-fit, predictive strength, and strength of relationship of independent and mediating variables with the dependent variable. Findings show that weak ties affect the entrepreneur’s ability to recognise opportunity. Entrepreneurs who possesses wider social contacts benefits from a wide array of information which plays a key role to opportunity previously not recognised either due to lack of information or resources to exploit. To identify opportunities, a weak tie network is best suited to spark the imagination of entrepreneurs in novel ideas. In practice, the use of networking programs in entrepreneurial and incubation initiatives needs to focus on networking heterogenous groups. The clear delineation of the opportunity construct within the entrepreneurship studies enables progress to be made in building a clearer opportunity recognition framework. Empirical results also support the presence of entrepreneurial alertness as the mediator in the model.
Exploring Relationship between Headline News Sentiment and Stock Return

Information from news is an integral part of investment activity. Such information is widely available from online media platforms, in which we can obtain relatively easy thanks to the development of technology. Despite predicting future stock prices being a hard challenge, the availability of big data is able to support investment decisions. Any relevant news is deemed as a determinant factor for influencing the public decision making. The Efficient Market Hypothesis states that financial markets depend on the availability of information. Sentiment analysis act as assisting tool to support the sentiment classification process, which falls into positive or negative categories. The process uses Naïve Bayes and Support Vector Machine method. We conduct the research to see the relationship of headlines news from 20 companies listed in the Indonesia LQ45 index (February 2013 - August 2018) and stock returns. This study is carried out by Spearman rank correlation in looking at the relationship between stock returns and headline news. The findings of the study indicates that there is a correlation between headline news and stock return.
A common mechanism modulates saccade timing during pursuit and fixation.

Smooth pursuit is punctuated by catch-up saccades, which are thought to automatically correct sensory errors in retinal position and velocity. Recent studies have shown that the timing of catch-up saccades is susceptible to cognitive modulation, as is the timing of fixational microsaccades. Are the timing of catch-up and microsaccades thus modulated by the same mechanism? Here we test directly whether pursuit catch-up saccades and fixational microsaccades exhibit the same temporal pattern of task-related bursts and subsidence. Observers pursued a linear array of 15 alphanumeric characters that translated across the screen, and simultaneously performed a character identification task on it. At a fixed time, a cue briefly surrounded the central element to specify it as the pursuit target. After a random delay, a probe (E or 3) appeared briefly at a randomly selected character location and observers identified it. For comparison, a fixation condition was also tested with trial parameters identical to the pursuit condition, except that the array remained stationary. We found that during both pursuit and fixation tasks, saccades paused after the cue and then rebounded as expected, but also subsided in anticipation of the task. The time courses of the reactive pause, rebound and anticipatory subsidence were similar, and idiosyncratic subject behavior was consistent across pursuit and fixation. The results provide evidence for a common mechanism of saccade control during pursuit and fixation, which is predictive as well as reactive and has an identifiable temporal signature in individual observers.
Evaluate Accessibility and Usability Issues of Particular China and Pakistan Government Websites

Today the Web has become an essential part of people’s life. Everyone has the right to access websites, including seniors and disabled people. Government websites contain public information for the whole society, but affect mostly disabled people. In this paper, we have analyzed the accessibility and usability issues of selected top 60 government websites of Pakistan and China. We analyzed all websites’ loading time, page size, mobile friendliness, broken links, HTML5 and ARIA, Web Content Accessibility Guidelines (WCAG) 2.0 (Level A, Level AA, Level AAA) conformance, and contrast errors through online accessible testing tools and human inspections. We designed an interactive evaluation framework for Web accessibility and usability, which is used to evaluate both countries’ government websites. According to the evaluation 22 out of 30 Chinese government websites have less than about 50% of the accessibility issues, while Pakistan in contrast only 12 out of 30 government websites have less than about 50% of accessibility issues. The Chinese government websites are much better than Pakistani government websites with respect to accessibility and usability features. The all-inclusive results indicate that Pakistan government websites have poor conformance levels to meet WCAG standards. We gave some valuable recommendations, which will be helpful for web designers, developers and also web users particularly disabled people performance in the newest Artificial Intelligence (AI) area in a decent way.
Slow Moving Target Detection for Airborne Radar Systems by Dynamic Programming on SAR Images

A dynamic programming based approach is proposed to detect slow moving, low reflectivity targets for airborne radar systems. The suggested method utilizes the reflectivity amplitudes of the SAR image, possibly containing multiple slow moving targets, and poses the target detection problem as a maximum likelihood sequence detection problem. Dynamic programming is applied to capture the target related features such as along track smeared target signatures in the SAR image to this aim. Typical clutter and target models are estimated from SAR images. The performance of the algorithm is illustrated on a real SAR image acquired with SARPER™ radar developed by ASELSAN.
Predictive Functional Controller with Reduced-Order Observer Design for Pneumatic Positioning System

The pneumatic system is a type of actuator system widely used in industries that involve a movement of control in their applications. However, the usage of the pneumatic system in industries was limited to only certain applications since it always has problems associated with its accuracy. Due to nonlinearities and uncertainties in the system itself, accurate positioning control for the pneumatic system is very difficult to achieve. Thus, a suitable controller must be designed to deal with these issues. This paper proposes designing a reduced order observer for predictive functional control (PFC) as a new method for controlling the pneumatic positioning system. In this study, the pneumatic system was represented by a third-order auto-regressive with exogenous input (ARX) model structure, which is based on a system identification technique. The simulation results obtained from MATLAB/Simulink proved that this new control method can be used to control the pneumatic positioning system used in this study. Comparison with full-order observer system also demonstrated that this new control method can provide a good transient response as performed by full-order observer system, which clearly shows the potential of this new method to control the pneumatic positioning system in the real-time experiment.
A Fast Dynamic Response Regulation Method for Undersea Wireless Power Transfer System

As widely used mobile devices and the electric vehicles, the wireless charging system has been developed quickly. However, when it comes to the underwater wireless charging system, there are few research papers and the industrial applications. For the Autonomous Underwater Vehicles, they always use the battery swapping and physical power cable (conductive charging). These methods are not convenient. Another method is the AUVs docking station. This system should adapt the accurate navigation system with the expensive price. In order to deal with these challenges, the underwater wireless power transfer system (UWPT) is provided. For the marine environments, the key challenge of the UWPT is the regulation for the load battery in the dynamical operation. This article describes a new design method to deal with the misalignment and the changeable distance between the transmitter side and receiver side of the UWPT system to get the stable load regulation. In this paper, the authors adapt the switched capacitor (SC) converter acting as the boost DC-DC converter. The SC converter is controlled by the nonlinear verified one-cycle control (VOCC) method to reject the disturbance occurred when the misalignment happens and the distance changes between the transmitter side and receiver side. The load voltage of the UWPT could be regulated robustly with the fast-dynamical response speed to reject the external disturbance.
Flower Recognition Based on Convolutional Neural Network

In view of the problem that flowers still need to rely on experience to manually select features and low recognition rate in complex background at present, an 8-layer convolutional neural network is designed and compare the influence of various parameter selection on network performance during network construction, and a recognition method of deep convolutional neural network is proposed. Through the convolutional neural network learning feature, the features of the last layer in the network are integrated and connected as the output feature vector, then the characterization data was trained and tested using a Random Forest classifier. The Oxford 17 Flowers dataset is augmented, then classified, and compared with other classifiers. The experiment showed that the recognition rate of Random Forest classifier reached 81.37%, which is significantly better than Softmax classifier and Support Vector Machine.
Micro-motion Parameters Estimation Using Randomized Stepped Frequency Radar

This paper deals with the micro-motion parameter estimation of ballistic targets. In the proposed method, the Randomized Stepped Frequency (RSF) radar waveform is applied to provide high resolution of both range and velocity at the same time, which makes the separation of multiple micro-motion components easier. Then following the least squares criterion, a new estimation algorithm is introduced to achieve accurate target precession angle and period. Numerical experiments using data from commercial electromagnetic simulation software show that the proposed method can accurately estimate the micro-motion parameters of a conical warhead with a significantly shorter observing time.
Is Radar Cardiography (RCG) Possible?

In this paper, we propose a novel concept of Radar Cardiography (RCG). We demonstrate the ability to achieve precise heartbeat measurement wirelessly using advanced radar signal processing technique. We show that the reconstructed heartbeat waveform matches the reference electrocardiography (ECG) signal. We propose a new heartbeat monitoring method, in which we isolate cardiovascular activity from strong respiratory-inference in the 3-Dimensional (3-D) spaces: azimuth, elevation, and depth. With significant pulse signal-to-noise-ratio (SNR) improvement compared to the conventional radar approach, heart-rate variability (HRV) analysis using radar is therefore possible.
Deep Convolutional Neural Network with Segmentation Techniques for Chest X-Ray Analysis

The deep ConvNets is suitable for learning the mapping between CXR gradients. This paper proposes an example segmentation algorithm based on deep learning applied to xray medical image automatic segmentation annotation. The basic convolutional neural network is used to extract the feature map of the image, and the corresponding branch structure: classification, regression, and mask that can complete the automatic analysis of the image's infrastructure. Our method is evaluated on a dataset that consisted of 180 cases of real two-exposure dual-energy subtraction chest radiographs. Meanwhile, we design histogram averaging and data augmentation to enhance the low contrast image. Finally, we visualize the image and the good results have been achieved in the segmentation and labeling of clavicle and rib. We hope that our research will provide a good prospect for the application of deep learning in automatic segmentation and labeling of medical images.
Exposure to heavy metals from point pollution sources and risk of incident type 2 diabetes among women: a prospective cohort analysis

ABSTRACT Heavy metal exposures may contribute to diabetes risk but prospective studies are uncommon. We analyzed the Australian Longitudinal Study on Women’s Health (three cohorts aged 18–23, 45–50, or 70–75 at baseline in 1996, N = 34,191) merged with emissions data for 10 heavy metals (As, Be, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn) from the National Pollutant Inventory. Over 20-year follow-up, 2,584 women (7.6%) reported incident diabetes. Cox proportional hazards regression models showed that women aged 45–50 at baseline had higher diabetes risk in association with exposure to total air emissions, total water emissions, all individual metals air emissions, and six individual water emissions. After correction for false discovery rate, nine of 11 air emissions and five water emissions remained significant. Associations were not observed for land-based emissions, or for younger or older cohorts. Emissions were dominated by mining, electricity generation and other metals-related industrial processes.
Phase of sensorimotor μ‐oscillation modulates cortical responses to transcranial magnetic stimulation of the human motor cortex

Oscillatory brain activity coordinates the response of cortical neurons to synaptic inputs in a phase‐dependent manner. Larger motor‐evoked responses are obtained in a hand muscle when transcranial magnetic stimulation (TMS) is synchronized to the phase of the sensorimotor μ‐rhythm. In this study we further showed that TMS applied at the negative vs. positive peak of the μ‐rhythm is associated with higher absolute amplitude of the evoked EEG potential at 100 ms after stimulation. This demonstrates that cortical responses are sensitive to excitability fluctuation with brain oscillations Our results indicate that brain state‐dependent stimulation is a new useful technique for the investigation of stimulus‐related cortical dynamics.
Encapsulated Carbenoxolone Reduces Lung Metastases

Carbenoxolone is an anti-inflammatory compound and a derivate of a natural substance from the licorice plant. We previously showed that carbenoxolone reduces the metastatic burden in the lungs of mice through its antagonistic effect on high mobility group box 1 (HMGB1). To further enhance carbenoxolone’s activity and localization in the lungs, thereby reducing the potential adverse side effects resulting from systemic exposure, we developed a poly(lactic-co-glycolic acid) (PLGA) slow-release system for pulmonary delivery which maintains drug activity in-vitro, as demonstrated in the anoikis assay. Both systemic and intranasal administrations of carbenoxolone effectively minimize metastatic formation in a lung colonization model in mice. Our results show a decrease in the metastatic burden in the lung tissue. Notably, the therapeutic effect of a single intranasal administration of 25 mg/kg carbenoxolone, in the form of drug-loaded particles, had a similar effect in reducing metastatic lesions in the lungs to that of a 10-fold dose of the free drug via intraperitoneal injections, three times per week over the course of four weeks. These data offer new means to potentiate the anti-cancer activity of carbenoxolone and simultaneously reduce the requirement for high dosage administration; the upshot substantially improves therapeutic effect and avoidance of side effects.
Multivariate Regression Transform for Hybrid Optical OFDM in Visible Light Communications

In this paper, a multivariate regression transform (MRT) is proposed for pulse-amplitude-modulated-based hybrid optical orthogonal frequency division multiplexing (PHO-OFDM) visible light communications (VLC). PHO-OFDM is a hybrid modulation scheme that combines pulse amplitude modulated discrete multitone (PAM-DMT) and DC-biased optical orthogonal frequency division multiplexing (DCO-OFDM) for simultaneous transmission. The proposed method reduces the peak-to-average power ratio of PHO-OFDM to improve its system performance. Complementary cumulative distribution function simulation results show that the proposed method can effectively mitigate the PAPR of PHO-OFDM under different constellation combinations.
Cutting Edge: USP27X Deubiquitinates and Stabilizes the DNA Sensor cGAS to Regulate Cytosolic DNA–Mediated Signaling

Key Points USP27X promotes deubiquitination and stabilization of cGAS. USP27X deficiency impairs cGAS-mediated innate signaling. USP27X positively regulates innate antiviral immunity to DNA viruses. Cyclic GMP-AMP synthase (cGAS), a cytosolic DNA sensor, catalyzes the formation of the second messenger 2′3′-cGAMP that binds to STING and triggers the type I IFN signaling. Activation of cGAS can be modulated by several protein posttranslational modifications, including ubiquitination. However, the cGAS activation regulated by protein deubiquitination remains poorly understood. In this study, we identified that deubiquitinase USP27X could interact with cGAS and cleave K48-linked polyubiquitination chains from cGAS, leading to cGAS stabilization. Consistently, knockout of Usp27x in mice macrophages resulted in an accelerated turnover of cGAS, decreased cGAMP production, phosphorylation of TBK1 and IRF3, and IFN-β production. Furthermore, Usp27x knockout mice macrophages showed impaired innate antiviral responses against HSV type 1 infection. Our data suggest that USP27X is a novel regulator of the cGAS–STING cytosolic DNA sensing pathway.
Compact Balanced Substrate Integrated Waveguide Filter With Low Insertion Loss

A balanced substrate integrated waveguide (SIW) filter is proposed by etching transverse slots on the top surface. The SIW structures between each two adjacent slots are resonators operating at TE<inline-formula> <tex-math notation="LaTeX">$_{20\delta }$ </tex-math></inline-formula> mode for differential-mode (DM) operation and at TE<inline-formula> <tex-math notation="LaTeX">$_{10\delta }$ </tex-math></inline-formula> and TE<inline-formula> <tex-math notation="LaTeX">$_{30\delta }$ </tex-math></inline-formula> modes for common-mode (CM) operation. The proposed TE<inline-formula> <tex-math notation="LaTeX">$_{20\delta }$ </tex-math></inline-formula>-mode resonator is much shorter than the traditional TE<sub>201</sub>-mode resonator, which causes the whole design to be compact and low loss. Furthermore, the strong electric coupling formed by slots make it have wider bandwidth when compared with the state-of-the-arts. A prototype is designed at 3.5 GHz with the size of <inline-formula> <tex-math notation="LaTeX">$1.2\lambda _{\mathrm {d}} \times 0.83\lambda _{\mathrm {d}}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\lambda _{\mathrm {d}}$ </tex-math></inline-formula> is the wavelength in dielectric at the center frequency), the minimum insertion loss of 0.91 dB, the 3-dB fractional bandwidth (FBW) of 16%, and the FBW for 20 dB CM suppression of 79%.
Phytotherapy in endometriosis: an up-to-date review

Abstract Endometriosis is a benign gynecological disease which symptoms can provide a severe impact on patient’s quality of life with subsequent impact on psychological well-being. Different therapeutic strategies are available to treat this disease, such as surgery, hormonal therapies, and nonsteroidal anti-inflammatory drugs. Nevertheless, the efficacy of conventional medical treatments is limited or intermittent in most of the patients due to the associated side effects. Therefore, a woman with endometriosis often search for additional and alternative options, and phytotherapy might be a promising alternative and complementary strategy. Different medicinal plants, multicomponent herbal preparations, and phytochemicals were investigated for pharmacological proprieties in endometriosis therapy. In most of the cases, the effect on endometriosis was related to phenolic compounds, such as flavonoids and phenolic acids reporting anti-inflammatory, proapoptotic, antioxidant, and immunomodulatory functions. Moreover, some phytochemicals have been related to a strong phytoestrogenic effect modulating the estrogen activity. Although promising, available evidence is based on in vitro and animal models of endometriosis with a limited number of well-performed clinical studies. There are almost none randomized control trials in this area. Therefore, properly constructed clinical trials are mandatory to achieve more conclusive results about the promising role of phytotherapy in the management of endometriosis.