Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Myocardial Extracellular Volume Fraction Measured with Magnetic Resonance Imaging in the Prediction of Left Ventricular Functional Outcome after Revascularization of Chronic Total Occlusion of Coronary Arteries

Objective The purpose of this study was to prospectively investigate the value of the myocardial extracellular volume fraction (ECV) in predicting myocardial functional outcome after revascularization of coronary chronic total occlusion (CTO). Materials and Methods Thirty patients with CTO underwent cardiovascular magnetic resonance (CMR) before and 6 months after revascularization. Three baseline markers of functional outcome were evaluated in the dysfunctional segments assigned to the CTO vessels: ECV, transmural extent of infarction (TEI), and unenhanced rim thickness (RIM). At the global level, the ECV values of the whole myocardium with and without a hyperenhanced region (global and remote ECV) were respectively measured. Results In per-segment analysis, ECV was superior to TEI and RIM in predicting functional recovery (area under receiver operating characteristic curve [AUC]: 0.86 vs. 0.75 and 0.73, all p values < 0.010), and it emerged as the only independent predictor of regional functional outcome (odds ratio [OR] = 0.83, 95% confidence interval [CI]: 0.77–0.89; p < 0.001) independent of collateral circulation. In per-patient analysis, global baseline ECV was indicative of ejection fraction (EF) at the follow-up examination (β = −0.61, p < 0.001) and changes in EF (β = −0.57, p = 0.001) in multivariate regression analysis. A patient with global baseline ECV less than 30.0% (AUC, 0.93; sensitivity 94%, specificity 80%) was more likely to demonstrate significant EF improvement (OR: 0.38; 95% CI: 0.17–0.85; p = 0.019). Conclusion Extracellular volume fraction obtained by CMR may provide incremental value for the prediction of functional recovery both at the segmental and global levels in CTO patients, and may facilitate the identification of patients who can benefit from revascularization.
Neural Evidence of Hierarchical Cognitive Control during Haptic Processing: An fMRI Study

Abstract Interacting with our immediate surroundings requires constant manipulation of objects. Dexterous manipulation depends on comparison between actual and predicted sensory input, with these predictions calculated by means of lower- and higher-order corollary discharge signals. However, there is still scarce knowledge about the hierarchy in the neural architecture supporting haptic monitoring during manipulation. The present study aimed to assess this issue focusing on the cross talk between lower-order sensory and higher-order associative regions. We used functional magnetic resonance imaging in humans during a haptic discrimination task in which participants had to judge whether a touched shape or texture corresponded to an expected stimulus whose name was previously presented. Specialized haptic regions identified with an independent localizer task did not differ between expected and unexpected conditions, suggesting their lack of involvement in tactile monitoring. When presented stimuli did not match previous expectations, the left supramarginal gyrus (SMG), middle temporal, and medial prefrontal cortices were activated regardless of the nature of the haptic mismatch (shape/texture). The left primary somatosensory area (SI) responded differently to unexpected shapes and textures in line with a specialized detection of haptic mismatch. Importantly, connectivity analyses revealed that the left SMG and SI were more functionally coupled during unexpected trials, emphasizing their interaction. The results point for the first time to a hierarchical organization in the neural substrates underlying haptic monitoring during manipulation with the SMG as a higher-order hub comparing actual and predicted somatosensory input, and SI as a lower-order site involved in the detection of more specialized haptic mismatch.
Predicting mutational routes to new adaptive phenotypes

Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive “wrinkly spreader” (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects. Impact statement A combination of genetics, experimental evolution and mathematical modelling defines information necessary to predict the outcome of short-term adaptive evolution.
An integrated review on new targets in the treatment of neuropathic pain

Neuropathic pain is a complex chronic pain state caused by the dysfunction of somatosensory nervous system, and it affects the millions of people worldwide. At present, there are very few medical treatments available for neuropathic pain management and the intolerable side effects of medications may further worsen the symptoms. Despite the presence of profound knowledge that delineates the pathophysiology and mechanisms leading to neuropathic pain, the unmet clinical needs demand more research in this field that would ultimately assist to ameliorate the pain conditions. Efforts are being made globally to explore and understand the basic molecular mechanisms responsible for somatosensory dysfunction in preclinical pain models. The present review highlights some of the novel molecular targets like D-amino acid oxidase, endoplasmic reticulum stress receptors, sigma receptors, hyperpolarization-activated cyclic nucleotide-gated cation channels, histone deacetylase, Wnt/β-catenin and Wnt/Ryk, ephrins and Eph receptor tyrosine kinase, Cdh-1 and mitochondrial ATPase that are implicated in the induction of neuropathic pain. Studies conducted on the different animal models and observed results have been summarized with an aim to facilitate the efforts made in the drug discovery. The diligent analysis and exploitation of these targets may help in the identification of some promising therapies that can better manage neuropathic pain and improve the health of patients.
Biological occupational allergy: Protein microarray for the study of laboratory animal allergy (LAA)

Background Laboratory Animal Allergy (LAA) has been considered a risk for the workers since 1989 by the NIOSH. About one third of the Laboratory Animal Workers (LAWs) can manifest symptoms to LAA as asthma, rhinitis, conjunctivitis and cutaneous reactions. The prevalence of LAA-induced clinical symptoms has been estimated with a great variability (4–44%) also due to the different methodologies applied. Objective Evaluate the prevalence of IgE positivity to mouse and rat allergens in LAWs and assess which factors are predisposing to sensitization among subjects exposed to laboratory animals in the workplace. Methods One hundred LAWs were invited to fill out a questionnaire regarding current allergic symptoms, atopic history, home environment, previous and current occupational history. IgE reactivity versus specific allergens was evaluated with ImmunoCAP ISAC. Results Out of one hundred LAWs, 18% had a serum susceptibility to mouse and/or rat allergens and 42% reported to have occupational allergy symptoms. Combining the results acquired by ImmunoCAP ISAC and questionnaire, 17% of LAWs have been defined as LAWs-LAA positive since they present a positive IgE response and allergy symptoms, 1% LAWs-LAA sensitized, 25% LAWs-LAA symptomatic and 57% LAWs-LAA negative. Presence of previous allergy symptoms in work and life environment were significantly related to LAWs-LAA positive/sensitized. Conclusions The study aimed to define the immunological profile of LAWs using the proteomic array as an innovative approach in the study of environmental and occupational exposure to allergens. We suggested a definition of LAWs-LAA considering serum IgE response and presence of allergy symptoms. The proposed approach has the advantage to provide a standard methodology for evaluating the specific IgE responsiveness to animal allergens in specific workplace also considering the immunological profile of workers referred to exposure in life and occupational environment.
40-nm 2×VDD Digital Output Buffer Design With DDR4-Compliant Slew Rate

A 2×VDD I/O buffer featured with PVT (process, voltage, temperature) corner detection and SR (slew rate) auto-compensation is proposed. Besides, a nonoverlap timing control is added to the gate drives of those large devices in the output stage such that the appearance of possible DC current spikes caused by simultaneous turn-on driving MOS transistors is prevented. Not only is the SR enhanced, the power dissipation is also reduced. The maximum data rate is 2.5/1.6 GHz given 0.9/1.8 V supply voltage with 20 pF load, respectively, by all-PVT-corner simulations. The ∆ SR improvement is 31.9%(rising)/48.9%(falling) and 26.0%(rising)/41.0%(falling) for 1×VDD and 2×VDD, respectively, when the proposed PVT auto-compensation design is activated.
Joint Optimization on Bandwidth Allocation and Route Selection in QoE-Aware Traffic Engineering

Wide area networks (WANs) are increasingly relying on software-defined networking to orchestrate data transmission. Google and Microsoft built B4 and SWAN, respectively, to interconnect their data centers in WANs, achieving higher network utilization and lower delay, where different priorities can be applied for bandwidth allocation and route selection in their centralized traffic engineering. However, simply relying on the priorities cannot accurately capture the complex properties of the quality of experience (QoE) function corresponding to the end users and always result in a suboptimal solution. We propose QTE, a novel traffic engineering in software-defined WANs, which proactively enforces forwarding policies by coordinating the traffic demand of each data center. The goal of QTE aims to maximize end-user QoE for client-trigger traffic and maximize network throughput for background traffic. We make several technical contributions in designing QTE. First, we formulate maximizing end-user QoE problem as two optimization programs and propose a heuristic algorithm to solve the problem. We further present a concrete design and implementation of the system based on the Floodlight controller. Extensive experiments use Openflow switches on Mininet and numerical simulations, which shows that QTE increases end-user experiences by 45.3% compared with prior work and can be readily implemented on the Floodlight controller.
Stability and Variability Emphasized STT-MRAM Sensing Circuit With Performance Enhancement

Spin transfer torque magnetic random access memory (STT-MRAM) is one of the most promising candidates for the next-generation nonvolatile memory (NVM). However, as the process dimension and supply voltage continue to decrease, the yield of the sensing amplifier is reduced. In this work, the proposed sensing block with high margin, speed and stability (HMSS) with performance enhancement can be applied to variability emphasized MRAM design. The sensing circuit is implemented with a 28-nm CMOS process and a perpendicular magnetic anisotropy (PMA) magnetic tunnel junctions (p-MTJ) based compact model. Working at low voltage with high speed and yield is the main goal of the designed HMSS sensing amplifier (HMSS-SA). For near-threshold operation, at the voltage of 700 mV, the yield of HMSS-SA is 2.06x by transistor sizing, reaching 4.1%. And the speed is increased by 33% by transistor sizing, reaching 0.09 ns with the power of 18.27 µW. The performance of HMSS drops by 0.85% yield and 0.05 ns speed at 0.7 V compared to the 1 V supply voltage which shows that the proposed HMSS-SA has excellent performance at low supply voltages.
Clone Detection Based on Physical Layer Reputation for Proximity Service

Proximity-based service (ProSe) provides direct communications among smart sensor nodes in proximity which aims at reserving resource consumption and alleviating the load in base stations, which is a promising solution for smart sensor systems that possess limited computing and energy resources. During the ProSe direct communications, most of the prior art security methods are usually provided by the ProSe function and are based on complex cryptography. However, despite the computing complexity, it is difficult for cryptographic methods to detect clone attack which is a common kind of attack in sensor systems. Clone nodes feature different physical positions but claim colliding IDs with captured nodes. Thus, clone nodes can be detected by spatial differences, in particular, by the surveillance of physical layer channel state information (CSI). However, CSI is not absolute static due to the random noise in wireless propagation environment. Accordingly, the detection accuracy varies with the stability of CSI. To address this challenge, we take the first attempt to introduce physical layer reputation and then elaborate the physical layer reputation based clone detection protocol to detect clone attack in multiple scenarios. The proposed protocol significantly improves the detection rate and false alarm rate and it is validated both by simulations and realizations.
Face Expression Recognition Based on Convolutional Neural Network*

In order to reduce the complexity for extracting artificial features from the face image in facial expression recognition (FER), a novel method is proposed based on convolutional neural network (CNN) in this paper. This method first preprocesses the facial expression images, then some trainable convolution kernels are used to extract facial expression features, and second, the largest pooling layer is used to fewer dimensions, finally seven types of facial expressions are recognized with the Softmax classifier. The proposed method is verified with Kaggle facial expression recognition challenge dataset (FER2013). The experimental results show that the method has good recognition performance and generalization ability.
Fully Digital Background Calibration Technique for Channel Mismatches in TIADCs

Time-interleaved analog-to-digital converter (TIADC) is a promising approach to meet the requirement of very high speed wireless communication systems. However, mismatches between the channels in a TIADC cause the spurious images in the output spectrum, thus decreasing its performance. Therefore, efficient correction techniques for these mismatches are highly required. In this paper, we present a fully digital background calibration technique for channel mismatches including offset, gain and timing mismatches in TIADCs using Hadamard transform and average offset mismatch errors. The proposed technique results in the removal of spurious images from the TIADC output spectrum, thus increases the signal-to-noise-and-distortion ratio (SNDR) and spurious-free dynamic range (SFDR). The performance improvement of TIADCs employing this technique is demonstrated through numerical simulations.
A Novel Digitally-Controlled DC Offset Calibration Circuit for the Chopper Instrumentation Amplifier

This paper presents a novel digitally-controlled DC offset calibration (DCOC) circuit for the chopper instrumentation amplifiers that offers better robustness, faster calibration speed, and lower average input noise than traditional integrator-based structures. Different from the traditional analog method, the proposed structure adopts digital circuit to cancel most of the offset introduced by the input-electrode, and the residual offset is eliminated by the second-stage capacitive-coupling amplifier. The difference of two reference voltages is used as the loop-output calibration voltage, so that the system has good temperature characteristic and process characteristic. The noise introduced by the digital offset calibration loop is proportional to the magnitude of the input offset, and no noise is introduced when the input offset is 0V. The circuit is designed in 0.18μm standard CMOS process with the supply voltage of 1.2V. The total power consumption is 36μW and the instrumentation amplifier consumes 7μW. The simulation results demonstrate the effectiveness of the amplifier functionality under different offset voltages, which can eliminate the offset up to ±300mV. Under different offset voltages, the input integrated noise range is 0.67~ 1. 49μVrms (0.1~150Hz).
A Virtual Reality based Training and Assessment System for Hand Rehabilitation

Virtual reality is widely applied in rehabilitation robot to help post-stoke patients complete rehabilitation training for the body function recovery. Most of virtual rehabilitation training systems lack scientific assessment standards and doctors don’t usually use quantitative examinations but qualitative observation and conversation with patients to evaluate the motor function of limb. Based on this situation, a virtual rehabilitation training and assessment system is designed, which contains two rehabilitation training games and one assessment system. The virtual system can attract patient attention and decrease the boredom of rehabilitation training and assessment. Compared with the existing rehabilitation assessment methods, the proposed virtual assessment system can give the assessment results similar to Fugl-Meyer Assessment, which is more quantitative, interesting and convenient. Five volunteers participate in the study of assessment system and the experimental results confirm the effectiveness of assessment system.
A Voltage Swing Robust Pseudo-Resistor Structure for Biomedical Front-end Amplifier

This paper proposes an improved pseudo-resistor structure with wide operation voltage. In bio-potential signal acquisition system, pseudo-resistors are always employed to realize very large RC time constant to suppress the input electrode DC offset voltage. With simple combination of two complementary back-to-back pseudo resistors, the resistance lifting across operating voltage is reduced. According to the simulation result with standard 0.18 µm CMOS process, the proposed pseudo-resistor provides robust resistance within 1.2 V voltage swing. A bandwidth tunable AC-coupled instrumentation amplifier which adopts a programmable resistor using the proposed pseudo-resistor is designed and simulated to verify the proposed structure.
Surface Charge Transport Characteristics of ZnO/Silicone Rubber Composites Under Impulse Superimposed on DC Voltage

Composites with nonlinear conductivity have been applied to modify the direct current (dc) electrical field distribution and accelerate the space charge dissipation in polymeric insulation. This paper focuses on the effect of nonlinear conductivity on the charge transport under an impulse superimposed on a dc voltage. The surface charge accumulation and dissipation properties of the zinc oxide (ZnO)/silicone rubber (SiR) composites under an impulse superimposed on a dc voltage are investigated by a 2-D surface potential decay test. The results prove that the homopolar impulse superimposed on the dc voltage intensifies the surface charge accumulation, leading to an increase in both the surface charge and area. Under a heteropolar impulse superimposed on a dc voltage, neutralization occurs first, and then, the heterocharges accumulate on the surface. The vertical charge transport to the ground and the horizontal movement on the surface are the two factors concerning the surface charge dissipation. The larger surface charge caused by a higher impulse voltage leads to an increase in the nonlinear conductivity, which accelerates the dissipation of the surface charge, and this effect becomes more obvious in composites with higher ZnO content. However, there is a special case, in which the positive surface charge dissipates slower in 15-wt% ZnO/SiR composites than in the undoped sample. It is deduced that the positive charges are more difficult to transport in the ZnO/SiR composites than the negative charges due to the charge transport mechanism of the n-type ZnO semiconductors with a back-to-back Schottky barrier of the grain boundary.
An Implantable Wideband Circularly Polarized Microstrip Patch Antenna via Two Pairs of Degenerate Modes

This paper presents a design approach for developing a wideband circularly polarized (CP) microstrip patch antenna (MPA) embedded in the human body. To achieve this goal, a pair of high-order degenerate modes (TM30 and TM03) in MPA have been excited and lowered for resonance in proximity to a pair of fundamental degenerate modes (TM10 and TM01). The proper disturbance of these two pairs of radiative resonant modes can contribute to the generation of two CP radiating waves at two near-by operating frequencies, aiming to realize CP radiation in a wide operating band covered by these two frequencies. A novel implantable wideband CP MPA is proposed and developed due to the emergence of two minima in the axial-ratio (AR) frequency response. The designed MPA is then demonstrated to tremendously achieve the wide 3-dB AR bandwidth which covers the 2.4 to 2.48 GHz ISM-band in the cubic human skin model. Moreover, the proposed CP MPA shows good tolerance to the variety of tissue according to our study on sensitivity and model integrity. Finally, the designed CP MPA is fabricated and tested, and a good agreement exists between measured and simulated results in a wide frequency region.
Antenna Modeling on Complex Platforms Through Constrained Equivalent Aperture Distributions

Accurate in situ antenna manifolds are desired for performance evaluation of radio frequency systems, including communication, navigation, and radar among others. In situ antenna measurements are the most accurate way to obtain antenna manifolds on the platform of interest, but are often impractical or impossible to obtain. Instead, combinations of simulations and measurements are used to estimate antenna manifolds on platforms. First, the gain and phase of the target antenna are measured on a simple ground plane, over the frequencies and field of view of interest. The measurements are then imported into computational electromagnetics codes to simulate platform scattering from the platform of interest. However, the representation of the measured data is not unique, which leads to inaccuracies and/or a large run time in computational electromaanetics codes. This paper presents a new method to represent measured antenna data in electromagnetics codes through aperture current distributions of simulated cross-slots and monopoles. A weighted sum of far-fields from the simulated equivalent elements approximates the measured antenna far-fields, with weights determined by the minimization of the L2-norm difference between measured far-fields and equivalent element far-fields. However, the least square solution may place large, unrealizable currents on the aperture. A constraint is introduced to limit the amount of current on the aperture, by minimizing the length of the solution vector. In this paper, the details of the suggested method will be presented. We will also illustrate the accuracy of the method through example simulations, where good agreement is achieved between truth data and equivalent antennas on complex platforms.