Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual Saliency Detection Algorithm in Compressed HEVC Domain

Saliency detection has been widely used to predict human fixation. In this paper, a Visual Saliency Detection Algorithm in Compressed HEVC Domain is proposed which consists of three parts: static saliency detection, dynamic saliency detection and competitive fusion. Firstly, the Gauss model is used to filter out the background of the static features which are extracted by down-sampling and DCT. Secondly, the motion vectors are used to represent the dynamic feature. Then the dynamic saliency is calculated by filtering out the background of dynamic feature. Finally, the competitive fusion model is used to adaptively combine the characteristic of static and dynamic saliency maps. Experimental results show that the proposed method is superior to classic state-of-the-art saliency detection methods with 0.05 AUC value increasing and 0.17 KL divergence decreasing on average. The average time of one frame detection is 2.3 seconds.
A Generalized Approach for Cancellable Template and Its Realization for Minutia Cylinder-Code

Hashing technology has gained much attention in protecting the biometric template lately. For instance, Index-of-Max (IoM), a recently reported hashing technique, is a ranking-based locality sensitive hashing technique, which illustrates the feasibility to protect the ordered and fixed-length biometric template. However, biometric templates are not always in the form of ordered and fixed-length. Rather, it may be an unordered and variable size point set, e.g., fingerprint minutiae, which restricts the usage of the traditional hashing technology. In this paper, we propose a generalized version of IoM hashing, namely gIoM, to enable the utilization of unordered and variable size biometric template. We demonstrate a realization by using a well-known variable size feature vector - fingerprint Minutia Cylinder-Code (MCC). The gIoM transforms MCC into index domain to form indexing-based feature representation. Consequently, the inversion of MCC from the transformed representation is computational infeasible, thus achieving non-invertibility while the performance is preserved. Public fingerprint databases FVC2002 and FVC2004 are employed for experiments. Furthermore, the security and privacy analysis suggest that gIoM meets the criteria of template protection, namely, non-invertibility, revocability, and non-linkability.
Online Speaker Adaptation for LVCSR Based on Attention Mechanism

Speaker adaptation is one of the most popular and important topics for speech recognition. In this paper, we propose a novel online speaker adaptation technique for deep neural networks based large vocabulary automatic speech recognition (LVCSR). In this approach, the i-vectors of the speakers in training set are extracted as a static memory. For each frame, attention mechanism is used to select the most relevant speaker i-vectors to the current speech segment from the memory. We also propose a new attention mechanism to improve the performance. The vectors obtained by the attention mechanism provide speaker information for improving the accuracy of speech recognition. Experiments on the Switchboard task show that the proposed approach achieves a relative 8.3% word error rate (WER) reduction over speaker independent model without any adaptation data. The result is comparable to that of the popular i-vector based offline speaker adaption method and is much better than that of the i-vector based online speaker adaption method.
55.1, a gene of unknown function of phage T4, impacts on Escherichia coli folate metabolism and blocks DNA repair by the NER

Phage T4, the archetype of lytic bacterial viruses, needs only 62 genes to propagate under standard laboratory conditions. Interestingly, the T4 genome contains more than 100 putative genes of unknown function, with few detectable homologues in cellular genomes. To characterize this uncharted territory of genetic information, we have identified several T4 genes that prevent bacterial growth when expressed from plasmids under inducible conditions. Here, we report on the various phenotypes and molecular characterization of 55.1, one of the genes of unknown function. High‐level expression from the arabinose‐inducible PBAD promoter is toxic to the bacteria and delays the intracellular accumulation of phage without affecting the final burst size. Low‐level expression from T4 promoter(s) renders bacteria highly sensitive to UV irradiation and hypersensitive to trimethoprim, an inhibitor of dihydrofolate reductase. The delay in intracellular phage accumulation requires UvsW, a T4 helicase that is also a suppressor of 55.1‐induced toxicity and UV sensitivity. Genetic and biochemical experiments demonstrate that gp55.1 binds to FolD, a key enzyme of the folate metabolism and suppressor of 55.1. Finally, we show that gp55.1 prevents the repair of UV‐induced DNA photoproducts by the nucleotide excision repair (NER) pathway through interaction with the UvrA and UvrB proteins.
Dual Beam Leaky Wave Antenna Using Dumbbell-Shaped Slots based on Substrate Integrated Waveguide

A dual beam leaky wave antenna (LWA) array is designed and investigated in this paper, which using the substrate integrated waveguide (SIW) technology based on TE20 mode at X-band. The dumbbell-shaped slots are etched out on the both sides of SIW. Using these types of slots has increased the bandwidth of the antenna, so that the proposed antenna bandwidth is between 9.4-14 GHz. Another advantages of this structure are the good gain, proper directivity, and radiation efficiency, so that at 12 GHz the antenna peak gain reaches to 12.6 dB. The beam scanning range changes from 5° to 78° in the first and fourth quadrants. The scanning range of this antenna is ~ about 73° degrees in each quadrant that makes it proper for radar applications. This antenna is analyzed and simulated by the CST Microwave Studio software.
5.6 A 400×400-Pixel 6μm-Pitch Vertical Avalanche Photodiodes CMOS Image Sensor Based on 150ps-Fast Capacitive Relaxation Quenching in Geiger Mode for Synthesis of Arbitrary Gain Images

The intensive development of Single-photon avalanche photodiode (SPAD) based CMOS image sensors (CIS) continues, with rapid progress [1–6]. Yet, due to unestablished quenching operation [5,6], realization of SPADs onto a CIS alongside conventional pixel circuitry has been a fundamental challenge.
Evaluation of Prototype Transmitter and Receiver with 64APSK Coded Modulation in Non-Linear Channel

We previously proposed a set-partitioning 64APSK coded modulation as a scheme of expanding transmission capacity for satellite broadcasting. Conducting transmission-performance evaluations with a nonlinear satellite transponder model, especially for the 12GHz-band, is very important for 64APSK because of the weakness of the multi-level amplitudes. We evaluated its transmission performance in a non-linear channel by computer simulation and showed it could achieve better transmission performance than other transmission schemes.For this study, we prototyped a transmitter and receiver with our 64APSK coded modulation and evaluated its transmission performance through the "satellite simulator" that has a nonlinear channel with 12GHz-band satellite transponder characteristics, and compared the performance of the prototype with that of computer simulation. The results indicated that the performance of the prototype in the non-linear channel was qualitatively equal to the computer simulation.
P-Edge NMOSFET for Improving TID Tolerance

This letter proposes a novel device structure named P-edge nMOS, in which high P+ doped belts are placed at the edges of the N+ source and drain. This structure is immune to the radiation-induced edge effects, thus, is able to improve total ionizing dose tolerance with much less area cost than enclosed layout transistors. Furthermore, P-edge nMOS is fully compatible with standard commercial technologies and can be used as a technique of radiation hardened by design. In order to evaluate the radiation tolerance of the new structure, sample transistors fabricated by the SMIC 350-nm commercial CMOS process with shallow trench isolation have been irradiated up to total doses of 2 Mrad(Si). The experimental results show that the leakage current of the P-edge nMOS is four orders of magnitude smaller than the normal nMOS device and the threshold voltage variation of the P-edge nMOS is reduced by about 90% when the dose is up to 2 Mrad(Si). The proposed P-edge nMOS can be a competitive alternative device to be used in CMOS integrated circuits for space applications.
A Widely Adaptive Time-Delayed Control and Its Application to Robot Manipulators

This paper presents a widely adaptive time-delayed control (WATDC) without imposing any restrictions on allowable control gains to make the most of the advantages of time-delayed control (TDC) and, then, applies the WATDC to robot manipulators. Since the proposed WATDC can provide arbitrarily high gains by using the time-varying bounds of time-delayed estimation errors, it has a room for improving the tracking performance and robustness of the existing stabilizing TDCs that have narrow range of control gains depending on system parameters comprising the inertia of a robot manipulator. Furthermore, the proposed WATDC employs a fast adaptive law to generate wide-ranging and well-timed control gains that depend on the magnitude of tracking errors. In other words, timely adaptation over a wide range of control gains makes the WATDC provide suitable control effort for desirable output responses. Additionally, to suppress unfavorable inherent time-delayed estimation errors arising from one sample delayed measurements, the proposed WATDC works together with a sliding-mode control that has switching gains based on the time-varying bounds of time-delayed estimation errors. In simulations and experiments with robot manipulators, the proposed WATDC has better tracking performance and robustness than the existing TDCs due to a wide range of adaptive control gains and the time-delayed-estimation-error-dependent switching gains.
A Novel Rat-Race Coupler With Widely Tunable Frequency

This paper presents a novel design method of rat-race couplers with tunable frequency. The port equivalent impedances of a reciprocity four-port network being matched and isolated are derived by employing the even–odd mode analyses. A frequency-reconfigurable matching network (MN) transforming the port equivalent impedances to normalized unit resistance is first designed, and then the frequency-reconfigurable couplers are constructed by attaching the MN to each port of the four-port network. Based on the proposed method, two frequency-tunable rat-race couplers with power-dividing ratios of 1:1 and 2:1 are designed and measured. The measurements agree well with simulations. The measured center frequencies of the couplers with power-dividing ratios of 1:1 and 2:1 are tuned from 840 to 2480 and 840 to 2410 MHz, respectively, with a return loss of better than 15 dB and isolation of better than 20 dB.
Split Ring Resonator-Based Microwave Fluidic Sensors for Electrolyte Concentration Measurements

A differential microwave sensor, based on a pair of uncoupled microstrip lines each one loaded with a split ring resonator (SRR), is applied to the measurement of electrolyte concentration in deionized (DI) water. For that purpose, fluidic channels are added on top of the SRR gaps, the most sensitive parts of the structure. The operating principle is based on the measurement of the cross-mode insertion loss, highly sensitive to small asymmetries caused by differences between the reference liquid and the liquid under test (LUT). In this paper, the reference liquid is pure DI water (the solvent), whereas the solution, DI water with electrolyte content, is injected to the LUT channel. The proposed sensor is able to detect electrolyte concentrations as small as 0.25 g/L, with maximum sensitivity of 0.033 (g/L)–1. The sensor is validated by measuring the concentration of three types of electrolytes, i.e., NaCl, KCl, and CaCl2. Finally, the sensor is applied to monitor variations of total electrolyte concentration in urine samples.
Coordinated Control of Spacecraft's Attitude and End-Effector for Space Robots

This letter addresses the coordinated control of the spacecraft's attitude and the end-effector pose of a manipulator-equipped space robot. A controller is proposed to simultaneously regulate the spacecraft's attitude, the global center-of-mass, and the end-effector pose. The control is based on a triangular actuation decomposition that decouples the end-effector task from the spacecraft's force actuator, increasing fuel efficiency. The strategy is validated in hardware using a robotic motion simulator composed of a seven degrees-of-freedom (DOF) arm mounted on a six DOF base. The tradeoff between control requirements and fuel consumption is discussed.
External Consensus Protocol of Networked Multiagent Systems With Communication Delays Under Event-Triggered Mechanisms

In this paper, the external consensus problem is discussed for networked multiagent systems with communication delays under an event-triggered mechanism. The communication topology among agents is characterized by an undirected and connected graph, and there exist network-induced delays during data transmissions. Based on recursive equations, a prediction strategy is proposed to actively compensate for the effects of network-induced delays. Then, an event-triggered mechanism is introduced to avoid continuous control updates and continuous communication among agents. According to the above prediction strategy and event-triggered mechanism, a distributed external consensus control protocol is proposed, by which system stability is ensured and the external consensus can be achieved. Finally, numerical simulation is made to illustrate the validity of the proposed protocol.
World Influence of Infectious Diseases from Wikipedia Network Analysis

We consider the network of 5 416 537 articles of English Wikipedia extracted in 2017. Using the recent reduced Google matrix (REGOMAX) method we construct the reduced network of 230 articles (nodes) of infectious diseases and 195 articles of world countries. This method generates the reduced directed network between all 425 nodes taking into account all direct and indirect links with pathways via the huge global network. PageRank and CheiRank algorithms are used to determine the most influential diseases with the top PageRank diseases being Tuberculosis, HIV/AIDS and Malaria. From the reduced Google matrix we determine the sensitivity of world countries to specific diseases integrating their influence over all their history including the times of ancient Egyptian mummies. The obtained results are compared with the World Health Organization (WHO) data demonstrating that the Wikipedia network analysis provides reliable results with up to about 80 percent overlap between WHO and REGOMAX analyses.
Latent Fingerprint Enhancement Using Generative Adversarial Networks

Latent fingerprints recognition is very useful in law enforcement and forensics applications. However, automated matching of latent fingerprints with a gallery of live scan images is very challenging due to several compounding factors such as noisy background, poor ridge structure, and overlapping unstructured noise. In order to efficiently match latent fingerprints, an effective enhancement module is a necessity so that it can facilitate correct minutiae extraction. In this research, we propose a Generative Adversarial Network based latent fingerprint enhancement algorithm to enhance the poor quality ridges and predict the ridge information. Experiments on two publicly available datasets, IIITD-MOLF and IIITD-MSLFD show that the proposed enhancement algorithm improves the fingerprints quality while preserving the ridge structure. It helps the standard feature extraction and matching algorithms to boost latent fingerprints matching performance.
Staphylococcus aureus leucocidin ED contributes to systemic infection by targeting neutrophils and promoting bacterial growth in vivo

Bloodstream infection with Staphylococcus aureus is common and can be fatal. However, virulence factors that contribute to lethality in S. aureus bloodstream infection are poorly defined. We discovered that LukED, a commonly overlooked leucotoxin, is critical for S. aureus bloodstream infection in mice. We also determined that LukED promotes S. aureus replication in vivo by directly killing phagocytes recruited to sites of haematogenously seeded tissue. Furthermore, we established that murine neutrophils are the primary target of LukED, as the greater virulence of wild‐type S. aureus compared with a lukED mutant was abrogated by depleting neutrophils. The in vivo toxicity of LukED towards murine phagocytes is unique among S. aureus leucotoxins, implying its crucial role in pathogenesis. Moreover, the tropism of LukED for murine phagocytes highlights the utility of murine models to study LukED pathobiology, including development and testing of strategies to inhibit toxin activity and control bacterial infection.
Stock Prediction Using Sentiment Analysis in Twitter for Day Trader

Capital market is a huge investment in today market because it has a great value in optimizing capital allocation, funding and also increasing the value of properties. Stock prediction is essential for day trader to determine what their next moves are for that day and tomorrow since they have to be one step further than the long term trader. With social media that rapidly increasing in popularity, one website stands out for the potential to use it for mining the database for the stock prediction which is twitter. This also combining with the sentiment analysis is used to predict the value of the stock. This are being done using with a sentiment analysis software that can give score to each individual tweets. The core of the prediction method is Artificial Neural Network that is present inside MATLAB to help us train the data and predict the price of the stock. The findings were that there is a very strong correlation between the sentiment and the value of the stock price and the artificial Neural Network has been successfully implemented with 99.95% success rate. Therefore, we can conclude that this method can be used to predict the price of the stock.
Cache Placement Phase Based on Graph Coloring

Data traffic is increasing in recent years and small cell densification is a promising solution for handling the consequences of this growth. However, it faces with backhual’ constraint which limits its efficiency. Caching the popular files near to the small base stations (SBSs) is an effective technique which decreases usage of backhual links. In this paper, we model the network by a graph and propose a new popular files’ placement based on graph coloring for which different powerful solutions and algorithms have been presented in the literature. In this respect, we propose an algorithm to fill the caches of SBSs with the popular files and show the efficiency of our proposed algorithm through simulations.
Online LSTM-based Iterative Mask Estimation for Multi-Channel Speech Enhancement and ASR

Accurate steering vector estimation is the key point for a beamformer which suppresses the background noise to improve the noisy speech quality and intelligibility. Recently, time-frequency masking approach, which estimates the steering vectors that are utilized for a beamformer, is popular in this field. In particular, we have proposed an iterative mask estimation (IME) approach to improve the complex Gaussian mixture model (CGMM) based beamforming and yield the best system for multi-channel ASR in CHiME-4 challenge [1]. And in [2], we also demonstrated that our algorithm could improve the speech quality (PESQ) and intelligibility (STOI) for multi-channel speech enhancement. In this study, we focus on the online processing of our IME algorithm for multi-channel speech enhancement and ASR, which achieves comparable performance to the offline version. In addition, a regression long short-term memory recurrent neural network (LSTM-RNN) for a multiple-target joint learning is utilized, denoted as LSTM-MT, to replace two separate models in [2]. Experiments on the CHiME-4 simulation data show that the online IME algorithm can improve the enhancement performance, e.g., PESQ from 2.18 to 2.58 and STOI from 86.85 to 94.51, which is comparable to those obtained by offline IME. Furthermore, the LSTM-MT based post-processing can achieve an additional PESQ improvement from 2.58 to 2.71. And experiments on the CHiME-4 real data show that the online IME approach outperforms the online CGMM-based approach, with a relative word error reduction (WER) of 14.49%.
Oxidative Modification of Peroxiredoxin Is Associated with Drug-induced Apoptotic Signaling in Experimental Models of Parkinson Disease*

The aim of this study was to investigate changes in protein profiles during the early phase of dopaminergic neuronal death using two-dimensional gel electrophoresis in conjunction with mass spectrometry. Several protein spots were identified whose expression was significantly altered following treatment of MN9D dopaminergic neuronal cells with 6-hydroxydopamine (6-OHDA). In particular, we detected oxidative modification of thioredoxin-dependent peroxidases (peroxiredoxins; PRX) in treated MN9D cells. Oxidative modification of PRX induced by 6-OHDA was blocked in the presence of N-acetylcysteine, suggesting that reactive oxygen species (ROS) generated by 6-OHDA induce oxidation of PRX. These findings were confirmed in primary cultures of mesencephalic neurons and in rat brain injected stereotaxically. Overexpression of PRX1 in MN9D cells (MN9D/PRX1) exerted neuroprotective effects against death induced by 6-OHDA through scavenging of ROS. Consequently, generation of both superoxide anion and hydrogen peroxide following 6-OHDA treatment was decreased in MN9D/PRX1. Furthermore, overexpression of PRX1 protected cells against 6-OHDA-induced activation of p38 MAPK and subsequent activation of caspase-3. In contrast, 6-OHDA-induced apoptotic death signals were enhanced by RNA interference-targeted reduction of PRX1 in MN9D cells. Taken together, our data suggest that the redox state of PRX may be intimately involved in 6-OHDA-induced dopaminergic neuronal cell death and also provide a molecular mechanism by which PRX1 exerts a protective role in experimental models of Parkinson disease.
16.7 A 30GHz Digital Sub-Sampling Fractional-N PLL with 198fsrms Jitter in 65nm LP CMOS

Digital phase-locked loops (DPLLs) have been demonstrated to achieve excellent performance as fractional-N frequency synthesizers in the sub-6GHz range, but, when used in the mm-wave range, at 30GHz and above, they typically feature poor jitter-power trade-off. This paper presents a 30GHz fractional-N DPLL in 65nm low-power (LP) CMOS achieving 198fs integrated jitter at 35mW power. The DPLL based on a digital-to-time converter (DTC) combines: (i) sub-sampling bang-bang phase detection to reduce power consumption, (ii) a digital error correction to reduce DTC noise contribution, and (iii) a low-power wide-lock-range divide-by-six circuit to allow operation up to 34GHz.