Miracle-dz/UniFAR-FTUs huggingface dataset:
A Deep Reinforcement Learning-based Trust Management Scheme for Software-defined Vehicular Networks

Vehicular ad hoc networks (VANETs) have become a promising technology in intelligent transportation systems (ITS) with rising interest of expedient, safe, and high-efficient transportation. VANETs are vulnerable to malicious nodes and result in performance degradation because of dynamicity and infrastructure-less. In this paper, we propose a trust based dueling deep reinforcement learning approach (T-DDRL) for communication of connected vehicles, we deploy a dueling network architecture into a logically centralized controller of software-defined networking (SDN). Specifically, the SDN controller is used as an agent to learn the most trusted routing path by deep neural network (DNN) in VANETs, where the trust model is designed to evaluate neighbors' behaviour of forwarding routing information. Simulation results are presented to show the effectiveness of the proposed T-DDRL framework.
mully: An R Package to Create, Modify and Visualize Multilayered Graphs

The modelling of complex biological networks such as pathways has been a necessity for scientists over the last decades. The study of these networks also imposes a need to investigate different aspects of nodes or edges within the networks, or other biomedical knowledge related to it. Our aim is to provide a generic modelling framework to integrate multiple pathway types and further knowledge sources influencing these networks. This framework is defined by a multi-layered model allowing automatic network transformations and documentation. By providing a tool that generates this model, we aim to facilitate the data integration, boost the reproducibility and increase the interoperability between different sources and databases in the field of pathways. We present mully R package that allows the user to create, modify and visualize graphs with multi-layers. The package is implemented with features to specifically handle multilayered graphs.
Hospitalization Trends and Health Resource Use for Adult Congenital Heart Disease–Related Heart Failure

Background This study assessed trends in heart failure (HF) hospitalizations and health resource use in patients with adult congenital heart disease (ACHD). Methods and Results The Nationwide Inpatient Sample was used to compare ACHD with non‐ACHD HF hospitalization and health resource trends. Health resource use was assessed using total hospital charges, hospital length of stay, and procedural burden. A total of 87 175±2676 ACHD‐related HF hospitalizations occurred between 1998 and 2011. During this time, ACHD HF hospitalizations increased 91% (4620±438–8809±740, P<0.0001) versus a 21% increase in non‐ACHD HF hospitalizations (P=0.003). ACHD HF hospitalization was associated with longer length of stay (ACHD HF versus non‐ACHD HF, 7.2±0.09 versus 6.8±0.02 days; P<0.0001), greater procedural burden, and higher charges ($81 332±$1650 versus $52 050±$379; P<0.0001). ACHD HF hospitalization charges increased 258% during the study period ($26 533±$1816 in 1998 versus $94 887±$8310 in 2011; P=0.0002), more than double that for non‐ACHD HF (P=0.04). Patients with ACHD HF hospitalized in high‐volume ACHD centers versus others were more likely to undergo invasive hemodynamic testing (30.2±0.6% versus 20.7±0.5%; P<0.0001) and to receive cardiac resynchronization/defibrillator devices (4.7±0.3% versus 1.8±0.2%; P<0.0001) and mechanical circulatory support (3.9±0.2% versus 2.4±0.2%; P<0.0001). Conclusions ACHD‐related HF hospitalizations have increased dramatically in recent years and are associated with disproportionately higher costs, procedural burden, and health resource use.
An ADPLL-Based PSK Receiver for VHBR 13.56-MHz Contactless Smartcards and NFC Applications

This brief proposes an all-digital phase-locked loop (ADPLL) used as the phase-shift keying (PSK) receiver for a very high bit rate of 13.56-MHz smartcards. A detailed implementation from system to circuit level is presented. This ADPLL-based PSK demodulator mainly consists of a high dynamic range time to digital converter (TDC) without pulse shrinking effect, a dual-path digital loop filter, and a fine resolution digital controlled oscillator based on capacitor division without dithering. This design is fabricated by GF CMOS 40-nm technology with a core area of only 0.035 mm2. The measurement results show low current consumption of 40 mA for phase locking and 70 mA for PSK demodulation with 1.2-V supply. Both integral non-linearity and differential non-linearity of our TDC are smaller than 0.6 LSB. This prototype can demodulate 8-PSK at a symbol rate of 6.78 MHz, corresponding to a data rate of 20.34 Mb/s, with an energy efficiency of 4.1 pJ/bit.
A Novel Flexible Sensor for Muscle Shape Change Monitoring in Limb Motion Recognition

Human limb movement intent recognition fundamentally provides the control mechanism for assistive devices such as exoskeleton and limb prosthesis. While different biopotential signals have been utilized for limb movement intent decoding, they seldom could account for spatial information associated with changes in muscle shape that could also be used to characterize the limb motor intent. Therefore, this study developed a novel nano gold stretchable-flexible sensor that captures spatial information associated with the muscle shape change signal (MSCS) during different muscle activation patterns. The novel sensor consists of 2-channels to acquire MSCS at a sampling rate of 125 Hz, corresponding to multiple classes of upper limb movements acquired across six able-bodied subjects. By utilizing the linear discriminant analysis algorithm on the acquired data with a single extracted feature, an overall average motion decoding accuracy of 90.9% was achieved. In addition, the waveform analysis results show that the novel sensor’s recordings were less affected by external interferences, thus yielding high quality signals. This study is the first to utilize nano gold stretchable-flexible material for sensor fabrication in pattern recognition of upper limb movement intent, which may facilitate the development of effective assistive devices.
Acromion morphology and prevalence of rotator cuff tear: A systematic review and meta‐analysis

The causes of degenerative rotator cuff (RTC) tears are unclear but certain acromion morphology may contribute. This study's objective was to determine using a systematic review and meta‐analysis the association of acromion type and acromial index with the prevalence of RTC tears. Six databases were searched electronically. Seventeen relevant studies between 1993 and 2017 were included in the meta‐analyses determining the association of RTC tears with acromion type (n = 11) or acromial index (n = 10). Effect sizes were calculated as an odds ratio (OR) for the studies reporting acromion type and as raw mean difference (RMD) for the studies reporting acromial index. Meta‐analysis was performed using a random‐effects model. There was a significant small‐to‐medium effect found in the meta‐analysis for acromion type (overall OR = 2.82, P = 0.000003), indicating an almost three times greater odds for a RTC tear in individuals with a type‐III acromion as compared with those with a type‐I or ‐II. A significant effect was also found for acromial index (RMD = 0.071, P < 0.0000001), indicating that a larger acromial index is associated with a greater likelihood of a RTC tear. Because of substantial heterogeneity in RMD for acromial index (Q‐df = 92, P < 0.00001; I2 = 89%), subgroup analyses and meta‐regressions were performed. Interestingly, the continent where the study was conducted (i.e., Europe vs. Asia) was the only moderator variable that could explain some of the acromial index heterogeneity. Overall, the findings from our analyses indicate that individuals with either a type‐III acromion and/or a larger acromial index have a greater likelihood for non‐traumatic RTC tears. Clin. Anat. 32:122–130, 2019. © 2018 Wiley Periodicals, Inc.
Unloaded shape identification of human cornea by variational shape optimization

Abstract The present study proposes a computational method to identify the unloaded corneal shape based on the prescribed surface profile of the cornea acquired from in vivo measurements. Variational shape optimization of the unloaded corneal shape was formulated to satisfy that the corneal shape at the mechanical equilibrium state in the physiological situation corresponded to the prescribed surface profile. The shape variation was calculated using the Lagrange multiplier method with a finite element solution. Numerical solution showed that the optimized corneal shape was in excellent agreement with the prescribed surface profile of the cornea without μm-scale surface irregularities.
A 10-Gb/s Reference-Less Baud-Rate CDR for Low Power Consumption With the Direct Feedback Method

This brief presents a reference-less baud-rate digital clock and data recovery (CDR) with a data decision feedback (DDF) with a direct feedback method (DFM). The DDF with DFM has been used for the equalization of the channel loss for the serial link with a decision feedback equalizer. However, we apply DDF with DFM to the baud-rate CDR to reduce the number of data samplers, which is dropped to 2/3 compared to conventional baud-rate CDR. As a result, the power consumption and mismatch problem of the data samplers can be reduced. The test chip fabricated in 65-nm CMOS technology operates at a 10-Gb/s data rate with 13.84-mW power consumption.
WiP: Floating XY-YX: An Efficient Thermal Management Routing Algorithm for 3D NoCs

3D Network-on-Chips (3D NoCs) have higher scalability, higher throughput, and lower power consumption over 2D NoCs. However, the reliability of data transfer in 3D NoCs is seriously threatened by thermal problems. This is due to poor heat dissipation, inappropriate traffic distribution, and cooling restriction for layers away of the chip heat-sink in 3D NoCs. To solve this problem, this paper proposes an efficient deadlock-free and traffic-and thermal-aware routing algorithm, called Floating XY-YX. The main idea behind Floating XY-YX routing algorithm is twofold: 1) to use XY and YX routing algorithms in consecutive layers in dessicate form, and 2) to evenly load the traffic, which is realized by switching the type of XY and YX routing algorithms to YX and XY routing algorithms, respectively. Based on the experimental results, the proposed routing algorithm reduces the temperature variance by 30.74% and traffic variance by 23.77% with respect to the state-of-the-art routing mechanisms.
Improving Item Ranking by Leveraging Dual Roles Influence

Ranking items to users is a typical recommendation task, which evaluates users’ preferences for certain items over others. Easy access to social networks has motivated researchers to incorporating trust information for recommendation. In this paper, aiming at offering fundamental support to the trust-based research for item recommendation, we conduct an in-depth analysis on Epinions, Ciao, and FilmTrust data sets. We find that a user’s selection of an item is influenced not only by her trustees but also by her trusters. We leverage this “dual roles influence” to derive two more accurate matrix factorization (MF)-based ranking models, namely, <italic>BPRDR</italic> and <italic>FSDR</italic>, respectively. In more detail, the first <italic>BPRDR</italic> model performs three pairwise preferences comparisons under the Bayesian personal ranking framework, considering the dual roles influence in its ranking assumptions. The second <italic>FSDR</italic> is an improved factored similarity model as it incorporates dual roles influence to contribute its ranking scores. Extensive experiments on three data sets show that it is essential to consider the dual roles influence when generating top-<inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> item recommendation.
Lentiviral-mediated inducible silencing of TLR4 attenuates neuropathic pain in a rat model of chronic constriction injury

An increasing body of evidence has indicated that spinal microglial Toll-like receptor 4 (TLR4) may serve a significant role in the development and maintenance of neuropathic pain (NP). In the present study, experiments were conducted to evaluate the contribution of a tetracycline inducible lentiviral-mediated delivery system for the expression of TLR4 small interfering (si)RNA to NP in rats with chronic constriction injury (CCI). Behavioral tests, including paw withdrawal latency and paw withdrawal threshold, and biochemical analysis of the spinal cord, including western blotting, reverse transcription-quantitative polymerase chain reaction and ELISA, were conducted following CCI to the sciatic nerve. Intrathecal administration of LvOn-si-TLR4 with doxycycline (Dox) attenuated allodynia and hyperalgesia. Biochemical analysis revealed that the mRNA and proteins levels of TLR4 were unregulated following CCI to the sciatic nerve, which was then blocked by intrathecal administration of LvOn-siTLR4 with Dox. The LvOn-siTLR4 was also demonstrated to have no effect on TLR4 or the pain response without Dox, which indicated that the expression of siRNA was Dox-inducible in the lentivirus delivery system. In conclusion, TLR4 may serve a significant role in neuropathy and the results of the present study provide an inducible lentivirus-mediated siRNA against TLR4 that may serve as a potential novel strategy to be applied in gene therapy for NP in the future.
Effects of bifocals on visual acuity in children with Down syndrome: a randomized controlled trial

Children with Down syndrome (DS) typically have reduced visual acuity (VA) and accommodation lag, but it is unclear whether prescribed glasses should correct both distance VA (DVA) and near VA (NVA) due to the lack of RCTs. We therefore conducted a multicentre RCT to compare the effects of bifocals designed to correct both DVA and NVA with distance‐correcting unifocal glasses in children with DS.
PartsNet: A Unified Deep Network for Automotive Engine Precision Parts Defect Detection

Defect detection is a basic and essential task in automatic parts production, especially for automotive engine precision parts. In this paper, we propose a new idea to construct a deep convolutional network combining related knowledge of feature processing and the representation ability of deep learning. Our algorithm consists of a pixel-wise segmentation Deep Neural Network (DNN) and a feature refining network. The fully convolutional DNN is presented to learn basic features of parts defects. After that, several typical traditional methods which are used to refine the segmentation results are transformed into convolutional manners and integrated. We assemble these methods as a shallow network with fixed weights and empirical thresholds. These thresholds are then released to enhance its adaptation ability and realize end-to-end training. Testing results on different datasets show that the proposed method has good portability and outperforms the state-of-the-art algorithms.
Compressive Sensing for Breast Microwave Imaging

This work proposes a novel microwave imaging (MWI) multi-frequency technique, which combines compressive sensing (CS) with the well-known distorted Born iterative method (DBIM) to enhance the accuracy in the imaging procedure. CS strategies are emerging as a promising tool in MWI applications, which can also reduce the number of data samples. The proposed approach is based on an iterative shrinkage thresholding algorithm (ISTA), which has been modified to include an automatic and adaptive selection of multi-threshold values. The proposed implementation is applied in reconstruction of two-dimensional numerical heterogeneous breast phantoms, where it outer-performs the standard thresholding implementation and proves to be an interesting tool for medical imaging applications.
Toward a highly sensitive polymer waveguide fiber Fabry–Pérot ultrasound detector

Abstract. In recent times, there has been extensive research on fiber-optic imaging devices in order to enable imaging/sensing at a size scale inaccessible to other modalities. The design for fabrication of a highly sensitive fiber-optic ultrasound detector is proposed. The transducer employs a polymer Fabry–Pérot resonator for ultrasound detection. To enhance acoustic sensitivity, a method is proposed for fabricating a self-aligned polymer waveguide within the cavity to improve the resonator quality factor (Q-factor). Simulation studies were conducted to evaluate feasibility and quantify the improvement in Q-factor for different transducer configurations. Results show that with dielectric mirrors and a waveguide, Q-factor can approach the order of 10,000. Additional simulation studies are presented to analyze the effect of cavity shape on the device performance, drawing out the importance of a flat mirror for waveguided devices. Subsequently, results from optical testing of the first iteration of fabricated devices are presented, highlighting the main drawback of this method—the nonideal shape of the waveguiding pillar. Finally, initial results from the second iteration of devices that overcome this drawback are presented, demonstrating the feasibility of creating straight self-aligned polymer waveguides on gold-coated fibers, followed by a discussion on the implications of this work and future steps.
Factors influencing mental health improvements in school teachers

Objective To identify changes in work-related psychological attitudes that influence mental health improvement in school teachers after participation in a psychological group program. Methods In an exploratory study with N = 544 matched cases we combined a screening instrument for general mental health (GHQ) with measures of work-related behavioral and experiential patterns (AVEM). We compared four GHQ change types pre and post intervention with regard to their performance on eleven sub-scales that figure as professional resources. Factors that showed significant relative changes and thus (likely) contributed to improved health status were identified by means of pairwise t-tests and corresponding effect sizes. Results Decreases in willingness to work to exhaustion (VB), in striving for perfection (PS), and in the tendency for resignation in the face of failure (RT), as well as an increase of distancing ability (DF) and of inner calm and balance (IR) appear to be the main factors influencing health improvement in the intervention. Simultaneously, an increase of satisfaction with life (LZ) is observed. Conclusions The balanced use of professional resources is a critical ingredient in maintaining teachers' health. Adjusting the balance between commitment and resistance through factors found in this analysis help teachers in maintaining and strengthening resilience. The coaching program addresses these factors by focusing on personal attitudes and good interpersonal relationships in the school environment.
Quantitative variations in texture analysis features dependent on MRI scanning parameters: A phantom model

Abstract Objectives To evaluate the influence of MRI scanning parameters on texture analysis features. Methods Publicly available data from the Reference Image Database to Evaluate Therapy Response (RIDER) project sponsored by The Cancer Imaging Archive included MRIs on a phantom comprised of 18 25‐mm doped, gel‐filled tubes, and 1 20‐mm tube containing 0.25 mM Gd‐DTPA (EuroSpinII Test Object5, Diagnostic Sonar, Ltd, West Lothian, Scotland). MRIs performed on a 1.5 T GE HD, 1.5 T Siemens Espree (VB13), or 3.0 T GE HD with TwinSpeed gradients with an eight‐channel head coil included T1WIs with multiple flip angles (flip‐angle = 2,5,10,15,20,25,30), TR/TE = 4.09–5.47/0.90–1.35 ms, NEX = 1 and DCE with 30° flip‐angle, TR/TE=4.09–5.47/0.90–1.35, and NEX = 1,4. DICOM data were imported into an in‐house developed texture analysis program which extracted 41‐texture features including histogram, gray‐level co‐occurrence matrix (GLCM), and gray‐level run‐length (GLRL). Two‐tailed t tests, corrected for multiple comparisons (Q values) were calculated to compare changes in texture features with variations in MRI scanning parameters (magnet strength, flip‐angle, number of excitations (NEX), scanner platform). Results Significant differences were seen in histogram features (mean, median, standard deviation, range) with variations in NEX (Q = 0.003–0.045) and scanner platform (Q < 0.0001), GLCM features (entropy, contrast, energy, and homogeneity) with NEX (Q = 0.001–0.018) and scanner platform (Q < 0.0001), GLRL features (long‐run emphasis, high gray‐level run emphasis, high gray‐level emphasis) with magnet strength (Q = 0.0003), NEX (Q = 0.003–0.022) and scanner platform (Q < 0.0001). Conclusion Significant differences were seen in many texture features with variations in MRI acquisition emphasizing the need for standardized MRI technique.
Comparative Study of Optimal Power Flow Solution using DC and Generalized Generation Distribution Factor Formulations

This paper proposes the use of Generalized Generation Distribution Factors (GGDF) to model network constraints in the optimal power flow (OPF). In this formulation, the nodal balance equality constraints are modeled using one equality constraint, and the transmission network constraints have been modeled using the GGDF. This formulation is compared vs classical DC formulation. Several popular commercial software are used to evaluate the computational efficiency of the OPF formulations. Both formulations are validated and tested on the PJM 5-bus and IEEE 14-bus systems
HMDD v3.0: a database for experimentally supported human microRNA–disease associations

Abstract Comprehensive databases of microRNA–disease associations are continuously demanded in biomedical researches. The recently launched version 3.0 of Human MicroRNA Disease Database (HMDD v3.0) manually collects a significant number of miRNA–disease association entries from literature. Comparing to HMDD v2.0, this new version contains 2-fold more entries. Besides, the associations have been more accurately classified based on literature-derived evidence code, which results in six generalized categories (genetics, epigenetics, target, circulation, tissue and other) covering 20 types of detailed evidence code. Furthermore, we added new functionalities like network visualization on the web interface. To exemplify the utility of the database, we compared the disease spectrum width of miRNAs (DSW) and the miRNA spectrum width of human diseases (MSW) between version 3.0 and 2.0 of HMDD. HMDD is freely accessible at http://www.cuilab. cn/hmdd. With accumulating evidence of miRNA–disease associations, HMDD database will keep on growing in the future.
Adaptive Algorithm based on Renyi's Entropy for Task Mapping in a Hierarchical Wireless Network-on-Chip Architecture

This paper describes the use of Renyi’s entropy as a way to improve the convergence time of the Population-Based Incremental Learning (PBIL) optimization algorithm. As a case study, the algorithm was used in a hierarchical wireless network-on-chip (WiNoC) for the sake of performing the optimal task mapping of applications. Two versions of Renyi’s entropy are used and compared to the more traditional Shannon formulation. The obtained results are promising and suggest that Renyi’s entropy may help to reduce the PBIL convergence time, without degrading the quality of the found solutions.