Miracle-dz/UniFAR-FTUs huggingface dataset:
A Unified Information Diffusion Model for Social Networks

Modeling information diffusion for social networks enables analyzing and predicting the impact on a specific topic or event. Most existing information diffusion models only take information influence or diffusion among the network users independently into consideration, which can hardly depict the diffusion in a booming large-scale and complex social network. In this paper, we propose a unified information diffusion model which jointly combines information influence and the diffusion process. Based on the unified model, most existing diffusion models can be reconstructed and implemented easily by setting influence and diffusion functions. In this paper, we use this model reconstructed five traditional models and we evaluate the model with a real collected dataset of 2.2 million blogs and the results show that the unified model can be adopted easily to fulfill classic diffusion models. Furthermore, the model sheds light on designing novel explainable information model in the future.
High-Performance Perpendicularly-Enfolded-Textile Actuators for Soft Wearable Robots: Design and Realization

Textile materials have recently been used in wearable robotics to provide more compact, lightweight, and low-cost solutions. Designing the textile-based actuator remains challenging in terms of providing a spectrum of forces that support the human body motion. We propose a new design for a textile-based actuator, which is made of an inflatable tube folded inside a housing fabric. The direction of the folds is perpendicular to the actuation plane allowing the actuator to exhibit high performance in dealing with heavy weights; it also demonstrates coherent behaviors with a broad set of its geometric parameters. We built a wearable glove that exhibits high performance in holding <inline-formula> <tex-math notation="LaTeX">$9\;kg$ </tex-math></inline-formula> weights. We show that with a larger scale, the bending actuator can hold up to <inline-formula> <tex-math notation="LaTeX">$20\;kg$ </tex-math></inline-formula>. Furthermore, a physical assistive experiment shows a reduction of 50% in electromyography signals reflecting flexor digitorum sublimis muscle activity during <inline-formula> <tex-math notation="LaTeX">$9\;kg$ </tex-math></inline-formula> weight bar grasping and releasing stages. Finally, we propose a variable curvature design, which provides a new perspective for the human-centered design of wearable robots.
Modular Multilevel SOI-CMOS Active Gate Driver Architecture for SiC MOSFETs

High Voltage SiC power MOSFETs have specific driving challenges such as a reduced short circuit capability (compared to Si IGBTs) and a weak field oxide layer, a large gate to source driving voltage (compared to GaN FETs), a high electric field under negative gate bias in off-state and a high switching speed. The negative bias in off-state creates a high stress which reduces the reliability of the SiC MOSFET. The high positive gate bias can generate large drain saturation current in case of short circuit events. We propose a modular multilevel architecture, which takes benefits of SOI isolation and low voltage CMOS transistors to drive SiC MOSFETs and to improve their reliability using an active and dynamic multilevel-selection on the switching sequences and on/off states.
Linear-Quadratic Tracking Control of a Commercial Vehicle Air Brake System

This article proposes to utilize linear-quadratic tracking (LQT) control to reduce the air brake system response time and vehicle stopping distance, and hence, to significantly improve the system performance of a commercial vehicle air brake system equipped with electro-pneumatic proportional valve actuators. The nonlinear dynamic model of the air brake system, consisting of a control actuator (a proportional valve) and braking actuator (the brake chamber), is developed and linearized using the $q$ -Markov COVariance Equivalent Realization ( $q$ -Markov Cover) method in our early work. Based on the linearized dynamic model, an infinite horizon LQT controller is designed along with Kalman state estimation at each linearized operational condition. To apply the LQT control law over a wide operational range to track the target pressure, the designed controller was interpolated between the neighboring controllers to have a control law cover the entire operational range. To validate this control law, the control scheme is implemented into a dSPACE unit and validated through bench tests under different supply and reference pressures. The LQT control performance is also compared with the PID (proportional-integral-derivative) one. The bench test results confirm the effectiveness of the proposed control scheme.
Use of Geometric Water-Filling algorithm for Power Allocation in Cognitive Radio

In this paper, the power allocation strategy has been discussed for the OFDM-based Cognitive Radio systems. A power allocation scheme based on Geometric Water-Filling(GWF) Peak Power Algorithm is proposed. Power allocation is accomplished considering joint underlay and overlay spectrum access model for cognitive radio. Using the proposed algorithm CR users' transmission rate is enhanced. In the proposed algorithm, total power and individual peak power constraints are taken into account while the value of interference is maintained at certain threshold value. Significant improvement in CR users' transmission rate can be observed. Also, performance of GWF algorithm and suboptimal scheme has been compared.
Human Recognition using Ear based Deep Learning Features

Recognition of person on the basis of his/her ear features is an upcoming area of research in the biometric field. In compression to other biometric traits, datasets with large number of images is not available and as such performance gains due deep learning methodology is still unexplored. In this paper aggressive data augmentation is carried out to artificially increase the number of samples in the AMI ear database which has only seven images per class. The augmented dataset is subjected to feature extraction by deep learning and classification by a classical model to obtain a hybrid deep learning classical model. The deep learning architecture inceptionV3 is used as feature extraction mechanism in which input to avgpool layer is taken as feature vectors and the dimensions of the feature vectors are reduced using principal component analysis. The dimensionality reduced features are classified using linear and quadratic classifier and best accuracy rate of 98.1% is obtained on quadratic SVM classifier.
Modeling Trust-Aware Recommendations With Temporal Dynamics in Social Networks

In recent years, user’s trust has gained attention in recommender systems. Trust plays a vital role in the recommendation of online products. Trust is a dynamic feature which evolves with passage of time and varies from person to person. Trust-based cross domain recommender systems suggest items to the users usually by ratings, provided by similar users, often not available in the same domain. However, due to the sparse rating scores, recommender systems cannot generate up-to-the-mark recommendations. In this research, we solved a user cold start problem, mainly by modeling preference drift on a temporal basis. We tried to solve this problem by adopting one of the scenarios of cross domain of ‘No Overlap’ using cross domain information. In this work, we proposed a model called Trust Aware Cross Domain Temporal Recommendations (TrustCTR) that predict the rating of an item about an active user from the most recent time. We generated user features and item features by using latent factor model and trained the proposed model. We also introduced the concept of trust relevancy that shows the degree of trust, computed the trusted neighbors in target domain for an active user belonging to a source domain, and predicted the ratings of items for cold start users. We performed experiments on public datasets Ciao and Epinions and used these datasets in cross domain form such as the categories of Ciao as source domain and Epinions as the target domain. We selected five different domains, having a higher proportion of rating sparsity, for observing the performance of our approach using MAE, RMSE, and F-measure. Our approach is a viable solution of cold start problem and offers effective recommendations We also compared the model with state-of-the-art methods; the model generates satisfactory results.
1200-V 4H-SiC Merged p-i-n Schottky Diodes With High Avalanche Capability

In this article, the avalanche capability of the 1.2-kV 4H-SiC junction barrier Schottky (JBS) and merged p-i-n Schottky (MPS) diodes is investigated through simulation and experiments. For MPS diodes, the width of the wide P+ region (<inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>) is found to have great effects on the device avalanche capability. MPS diodes with varied <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-values (3–20 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula>) and JBS diode are designed and fabricated, and their avalanche energy/current capability is tested with unclamped inductive switching tests. The experimental results show that the MPS diode has an optimized avalanche capability at <inline-formula> <tex-math notation="LaTeX">${W} =8$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> design. Simulation study reveals that the avalanche current is mainly distributed at the edges of the P+ regions in the JBS/MPS diodes as a result of the curvature-effect-induced electric field crowding. The localized current crowding and unbalanced current distribution in the avalanche mode contribute to a reduced effective power dissipation area and a weaker avalanche capability. The current nonuniformity coefficient (<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula>) is used to characterize the severity of the current unbalance, and it is found that <inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> declines as <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula> increases when <inline-formula> <tex-math notation="LaTeX">${W} = {3}-8~\mu \text{m}$ </tex-math></inline-formula> and then gets increased when <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula> exceeds <inline-formula> <tex-math notation="LaTeX">${8}~\mu \text{m}$ </tex-math></inline-formula>. Both the experimental and simulation results indicate that the MPS diode is superior to the JBS diode in avalanche capability, and the width of the wide P+ region in the MPS diode has an optimal design (<inline-formula> <tex-math notation="LaTeX">$8~\mu \text{m}$ </tex-math></inline-formula> in this article) which corresponds to the alleviated current crowding issue and 9%–19% improvement of the avalanche capability.
Aerodrome Taxiway Line Detection and Cross-Track Error Estimation using Computer Vision Techniques

This paper describes a computer vision-based method to detect aerodrome taxiway lines and to estimate the deviation of a large passenger aircraft from the taxiway centerline using an onboard camera located on the vertical stabilizer of the aircraft. This method could be applied as part of a larger system to increase the situation awareness of pilots during taxiing and to alert them if the aircraft deviates from the centerline. The proposed method takes advantage of color and edge information in the camera images and proposes a Sliding Window (SW) method and clustering techniques to detect and process taxiways markings. First, the input image is transformed to a top-down view by applying the Homographic Transform. Then, color and edge detection techniques are applied to the top-down view to generate a binary map of pixels belonging to taxiway lines. Then, the region of the image directly in front of the aircraft is processed to determine whether the aircraft is turning or moving in a straight line. If it is determined that the aircraft is turning, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering technique is applied to the binary map; otherwise, a SW method is used to detect the taxiway centerline ahead of the aircraft and to detect any taxiway branches or junctions. Finally, the aircraft's lateral deviation from the taxiway centerline is estimated using a template matching approach. Tests on simulated video sequences show that the SW technique achieves a detection rate of 80% and a false positive rate of 3%. On the other hand, the clustering technique achieves a detection rate of 76% and a false positive rate of 4%. The aircraft's deviation from the taxiway centerline is estimated with a mean error of 0.8 pixels and a worst case error of ±3 pixels.
Cloning and Expression Analysis of a CBS Domain Containing Protein Gene TaCDCP1 from Wheat

To elucidate the defense response of wheat(Triticum aestivum L.) to Puccinia striiformis f.sp. tritici(Pst),we constructed the incompatible interaction SSH cDNA library of wheat(cv.Suwon 11) leaves infected by Pst CYR23.A total of 652 unigenes were identified and 424 genes were annotated. On the basis of previous study,according to cDNA sequence LWSRP2502(GenBank accession No.EV254338),a full-length sequence of the CBS domain containing protein gene,tentatively designated as TaCDCP1(Triticum aestivum CBS domain containing protein 1),was isolated and characterized from wheat leaves infected by Pst through in silico cloning and reverse transcription PCR(RT-PCR) approaches. The open reading frame of TaCDCP1 was 654 bp in length and predicted to encode 217 amino acids protein which contained two conserved cystathionine beta-synthase(CBS) domains and was without transmembrane domain or signal peptide sequence.The deduced protein was predicted existing in chloroplast stroma.The amino acid sequence of TaCDCP1 shares 92%,72%,and 63% identify with the homologs in barley(Hordeum vulgare),rice(Oryza sativa) and maize(Zea mays),respectively.The TaCDCP1 gene was highly expressed in leaves than in roots and stems.Challenged by Pst,TaCDCP1 was induced by this fungus in both incompatible and compatible interactions,with the maximal expression at 18 h post inoculation(hpi) and 96 hpi,respectively.Its transcript accumulation was much higher in the incompatible interaction than in the compatible interaction at the early stage of infection(18-48 hpi),but much lower at the late stage(96-120 hpi). The expression of TaCDCP1 was also up-regulated after treated by phytohormones such as abscisic acid(ABA),and down-regulated by benzyladenine,ethylene,gibberellins,methyl jasmonate and salicylic acid to a certain degree.And it was obviously up-regulated by various abiotic stresses,such as low temperature and drought. However,mechanical wound and high salinity stress could not induce the expression of TaCDCP1.These results suggest that TaCDCP1 is probably involved in the disease resistance and defense response in wheat to Pst through ABA,and also participate in the signal transmission pathways under low temperature,and drought conditions.
A RIVISION OF THE GENUS CRASPEDACUSTA IN CHINA(LIMNOMEDUSAE,OLINDIDAE)

The two subspecies and two variety of Craspedacusta sowerbyi, namely C. sowerbyi xinyangensis, C. sowerbyi hangzhouensis, C. sowerbyi var. kaitingi and C. sowerbyi var. kawaii are distinguished from 7 species of genus Craspedacusta by the shape and arrangement of nematocyst warts,shape and color of gonads, the author consider that the two subspecies and two variety should be promoted as species of the genus Craspedacusta.Up to now the genus Craspedacusta have contained 11 species in the world. The morphological characters of these 11 species are compared as follows.A key to these species is provided.
Towards a Modular RISC-V Based Many-Core Architecture for FPGA Accelerators

Multi-/Many-core architectures are emerging as scalable, high-performance and energy-efficient computing platforms suitable for a variety of application domains from edge to cloud computing. Recently, the appearance of RISC-V open-source ISA creates new possibilities to develop customized computing platforms with high savings in the non-recurring engineering costs. Moreover, the current trends toward open-source hardware frameworks are aimed to reduce design time and cost for complex system-on-chip architectures. Therefore, modularity and re-usability of hardware components are major challenges for flexible hardware architectures. The motivation behind this work is to introduce a modular cluster-based many-core architecture for FPGA accelerators that is re-usable and flexible tailored to implement different many-core taxonomies with less design time and costs by using regular and replicated sets of computing, memory, and interconnection blocks. The proposed many-core architecture is built using multiple processing clusters coupled with a NoC for communication which allows a high degree of design scalability. The processing cluster inside features a configurable multi-core architecture consisting of multiple RISC-V processing elements (PE) tightly coupled with a bus-based interconnection for intra-cluster communication using parameterized scratchpad shared memory. Each PE features a single RISC-V core with a tightly coupled parameterized scratchpad local memory and generic AXI interface. Evaluation results demonstrate that the proposed architecture features a scalable computing performance of 501 MOp/s for 4 clusters and 878 MOp/s for 8 clusters. Moreover, a scalable memory bandwidth up to 4.3 GB/s is achieved for 9 clusters with a power consumption of 1.4 W per cluster utilizing 7.7% of on-chip memory resources. The many-core architecture is implemented and evaluated on Xilinx Virtex Ultrascale+ with the feature of changing the architecture configurations during run-time using dynamic and partial reconfiguration which provides more flexibility and re-usability.
Inhibitory Effect of Trypsin Inhibitor from Cassia obtusifolia Seeds Against Pieris rapae Larvae

A native trypsin inhibitor(COTI)was isolated from seeds of Cassia obtusifolia.The weights of Pieris rapae L have decreased rapidly after being feeded on Brassica rape leaves contained purified COTI.Further analysis showed that the serine proteases activities of the distilled supernatant from midgut tissues of Pieris rapae L were inhibited by the purified COTI.The results suggest that COTI has inhibitory effect on Pieris rapae L and it is available for the transgenetic crops cultivation.
Effects of ocean acidification on larval development and early post-hatching traits in Concholepas concholepas (loco)

Larval stages represent a bottleneck influencing the persistence of marine populations with complex life cycles. Concholepas concholepas is a gastropod species that sustains the most important small-scale artisanal fisheries of the Chile-Peru Humboldt Coastal current system. In this study, newly-laid egg capsules of C. concholepas collected from 3 localities along the Chilean coast were used to evaluate the potential consequences of projected near-future ocean acidification (OA) on larval development and early post-hatching larval traits. We compared hatching time, hatching success and early survivorship of encapsulated larvae reared under contrasting average levels of pCO2: 382 (present-day), ca. 715 and ca. 1028 μatm CO2 (levels expected in near-future scenarios of OA). Moreover, we compared morphological larval traits such as protoconch size, thickness and statolith size at hatching. Some of the developmental traits were negatively affected by pCO2 levels, source locality, female identity, or the interaction between those factors. Meanwhile, the effect of pCO2 levels on morphological larval traits showed significant interactions depending on differences among egg capsules and females. Our results suggest that OA may decouple hatching time from oceanographic processes associated with larval transport and reduce larval survivorship during the dispersive phase, with a potential impact on the species’ population dynamics. However, the results also show geographic variability and developmental plasticity in the investigated traits. This variation may lead to an increased acclimatization ability, facilitate the persistence of natural populations and mitigate the negative effects that OA might have on landings and revenues derived from the fishery of this species.
Identification of Anomalous Phonocardiograms Based on Universal Probabilistic Modeling

Automatic analysis of phonocardiograms (PCGs) could be a useful tool assisting medical experts in diagnosing heart's functionality. This letter presents an algorithm processing PCGs for identifying existing abnormalities. It is based on a standardized feature set free of domain knowledge, the distribution of which is suitably approximated by a universal hidden Markov model capturing its temporal structure. At the same time, an integral part of the model is an adaptation module responsible for incorporating new data as soon as it is available without requiring complete model retraining. Extensive experiments following a standardized protocol show that the proposed algorithm reaches state of the art performance under noisy conditions in a subject/patient independent manner.
Facial Expression Recognition in Videos Using Dynamic Kernels

Recognition of facial expressions across various actors, contexts, and recording conditions in real-world videos involves identifying local facial movements. Hence, it is important to discover the formation of expressions from local representations captured from different parts of the face. So in this paper, we propose a dynamic kernel-based representation for facial expressions that assimilates facial movements captured using local spatio-temporal representations in a large universal Gaussian mixture model (uGMM). These dynamic kernels are used to preserve local similarities while handling global context changes for the same expression by utilizing the statistics of uGMM. We demonstrate the efficacy of dynamic kernel representation using three different dynamic kernels, namely, explicit mapping based, probability-based, and matching-based, on three standard facial expression datasets, namely, MMI, AFEW, and BP4D. Our evaluations show that probability-based kernels are the most discriminative among the dynamic kernels. However, in terms of computational complexity, intermediate matching kernels are more efficient as compared to the other two representations.
The Role of Ag/Al Electrodes in the Improvement of PEDOT:PSS/P3HT:PCBM Solar Cells Performance

In this work, polymer solar cells (PSCs) with the configuration of ITO/PEDOT:PSS/P3HT:PCBM/back electrode with different back electrodes of silver (Ag), aluminum (Al), and Ag/Al alloy with various weight percentages were investigated. Different electrodes were deposited at the same conditions using the thermal evaporation process on the P3HT:PCBM active layer. Moreover, the effect of different electrodes on the cell's performance was investigated. The electrical properties of components, such as ideality factor (<italic>n</italic>), inverse saturation current, turning-<sc>on</sc> voltage (<italic>V<sub>t</sub></italic>), and mobility (<italic>μ</italic>), were evaluated using the <italic>J–V</italic> curves of the cells in the dark and irradiated conditions. The results showed that the use of Ag/Al alloys with higher Ag percentages as the back electrode reduced both series resistance (<italic>R</italic><sub>ss</sub>) and the reverse saturation current, and increased both shunt resistance (<italic>R</italic><sub>sh</sub>) and the mobility (<italic>μ</italic>). Furthermore, it increased the fill factor (FF) and power conversion efficiency (PCE) by improving the metal/polymer junction in these types of cells.