Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliable Detection of Rotor Faults in IM Using Frequency Tracking and Zero Sequence Voltage

The AC Alternating Current Induction Motor (IM) is the most commonly used AC motor in industrial applications because of its simplicity, robust construction, and relatively low manufacturing costs. To avoid expensive repairs in IM, early faults detection is needed. In this context, this paper presents a novel approach used to detect rotor asymmetries in induction motors. The Zero Sequence Voltage (ZSV) defined as the potential difference between the null point of the supply voltage system and the neutral of the star connection of IM stator winding is measured and employed for tracking the amplitude of the most sensitive harmonics in the spectrum of ZSV. This detection leads to make a criterion to take a decision about the state of the machine without a Prior knowledge. Simulation and experimental results obtained from real tests are presented to validate the study.
National and School Specifics as a Prerequisite for the Successful Design of an e-Learning System: the UNITE approach

A part of comprehensive study related to the design and implementation of the Pedagogical Framework, which as an essential part of UNITE system development drives and guides the creation of e-/m-Learning scenarios, is presented. The paper elaborates on one of five components of the Pedagogical Framework related to national specifics and current pedagogical practices implemented in national curricula. Diverse aspects of national and school specifics regarding educational characteristics and existing practice were noted and analysed in order to formulate a common framework and make good use of the UNITE platform as well. Summary results of the undertaken analysis along with conclusion and recommendations are offered.
Simulation Study on Opinion Evolution of Collaborative Shopping

DW model is improved based on the unique characters of group consumption. At first, using social experiment, we determine the categories and attributes of agents, and then based on the DW model, participants’ interaction rules are established. Finally, a mass of numerical simulation experiments show that in the form of collaborative online shopping, merchants can reverse opinions, who could persuade consumers with negative attitudes, changing opinions, and supporting collaborative online shopping, and the level of characteristics is closely related to the number of consumers changing opinions; opinion leaders can differentiate group opinions, neither accelerating effect nor destructive effect; the characteristics level of individual consumers has close relation with positive group polarization effect; when an individual consumer has high conformity or trust propensity, the opinions of some customers with supporting collaborative online shopping will be strengthened, they accept collaborative online shopping more. In addition, for group interaction of collaborative online shopping context, there is no negative group polarization effect.
A Cost-Effective Tethered-UAV-Based Coherent Near-Field Antenna Measurement System

For antenna measurements, the device under test (DUT) is usually transported to an anechoic chamber equipped with a scanner system. To measure on-site, unmanned aerial vehicles (UAVs) are a flexible solution as they can precisely maneuver a probe antenna over a surface in the DUT’s near-field region. In this work, the designed multi-rotor UAV enables electromagnetically optimal placement of the probe antenna and effective gravity center re-balacing by payload position adjustment. The on-board software-defined radio (SDR) serves as a dual-channel receiver for the dual-polarized probe and as a signal source. For phase-coherent measurements, the source signal is transmitted to the DUT via an optical fiber tethering the UAV to the ground control station. Power supply cables allow unlimited flight times. A laser-based tracking system originating from virtual reality (VR) applications measures the probe position and orientation. The developed operator software guides the UAV along a trajectory and records the irregularly distributed near-field samples. An inverse equivalent sources solver (IESS) with full probe correction computes equivalent sources for antenna diagnostics and the DUT far field. The deployed components make the system very cost-effective. Still, verification measurements demonstrate its usability and the accuracy of the results for frequencies up to several GHz.
Elastic wavefield inversion by the alternating update method

Full-waveform inversion is a promising tool for a wide range of imaging scenario, in that it has the potential to harness the non-linear relationship between model parameters and data (as opposed to traditional methodologies), in order to produce truly quantitative results. Non-linearity represents an opportunity, in this sense, but it also begets local minimum issues when gradientbased optimization is employed. In this thesis, we are particularly interested in the quantitative estimation of the elastic parameters of the earth, such as compressibility, shear modulus, and density. If successful, this procedure brings geophysical imaging closer to the ultimate step of seismic exploration: the retrieval of pore pressure and rock properties. This would be of direct use for, say, the oil and gas industry. Other interesting applications are the description of the near surface/near ocean bottom, as a way to reduce drilling hazards, or non-destructive inspection of defects in oil and gas pipes, when ultrasounds are employed.
Genome‐wide prediction of activating regulatory elements in rice by combining STARR‐seq with FACS

Summary Self‐transcribing active regulatory region sequencing (STARR‐seq) is widely used to identify enhancers at the whole‐genome level. However, whether STARR‐seq works as efficiently in plants as in animal systems remains unclear. Here, we determined that the traditional STARR‐seq method can be directly applied to rice (Oryza sativa) protoplasts to identify enhancers, though with limited efficiency. Intriguingly, we identified not only enhancers but also constitutive promoters with this technique. To increase the performance of STARR‐seq in plants, we optimized two procedures. We coupled fluorescence activating cell sorting (FACS) with STARR‐seq to alleviate the effect of background noise, and we minimized PCR cycles and retained duplicates during prediction, which significantly increased the positive rate for activating regulatory elements (AREs). Using this method, we determined that AREs are associated with AT‐rich regions and are enriched for a motif that the AP2/ERF family can recognize. Based on GC content preferences, AREs are clustered into two groups corresponding to promoters and enhancers. Either AT‐ or GC‐rich regions within AREs could boost transcription. Additionally, disruption of AREs resulted in abnormal expression of both proximal and distal genes, which suggests that STARR‐seq‐revealed elements function as enhancers in vivo. In summary, our work provides a promising method to identify AREs in plants.
Off-Ramp Vehicle Mandatory Lane-Changing Duration in Small Spacing Section of Tunnel-Interchange Section Based on Survival Analysis

Due to topography, geology, and other factors, small spacing sections are common between tunnels and interchange exits. There is mandatory lane-changing behavior for vehicles that need to leave the main line and drive inside the road before leaving the tunnel. Affected by the “white hole” of a tunnel, the lane-changing behavior of off-ramp vehicles differs significantly from that of original roadbed sections. To study the mandatory lane-changing duration (MLCD) of off-ramp vehicles in small spacing sections of the tunnel to interchange in mountainous areas, their time and trajectory data were collected based on a driving simulator. According to the characteristics of the data, the survival analysis method was used to analyze the influence on the MLCD of off-ramp vehicles of the spacing section between the tunnel and interchange, vehicle types, tunnel types, ramp types, highway service level, and whether to set exit advance guide signs in the tunnel and the Cox proportional hazards model of the MLCD was established. The results showed that the spacing of the tunnel interchange, the road service level, and whether to set exit advance guide signs in the tunnel had significant effects on the MLCD of vehicles, while the vehicle, the tunnel, and the ramp types did not. When the spacing section of the tunnel interchange was less than 500 m, the off-ramp vehicle had continuous mandatory lane-changing behavior, and when the distance decreased from 400 m to 300 m, the risk rate of lane changing increased by 5.68 times. Survival function curve estimation provided the 75% quantile of MLCD of off-ramp vehicles under different conditions, which could provide a theoretical reference for setting the minimum distance between a tunnel and interchange exit.
Surgical mitral valve repair technique considerations based on the available evidence

Mitral valve regurgitation is the second most common valve disease in the western world. Surgery is currently the best tool for generating a long-lasting elimination of mitral valve regurgitation. However, the mitral valve apparatus is a complex anatomical and functional structure, and repair results and durability show substantial heterogeneity. This is not only due to differences in the underlying mitral valve regurgitation pathophysiology but also due to differences in repair techniques. Repair philosophies differ substantially from one surgeon to the other, and consensus for the technically best repair strategy has not been reached yet. We had previously addressed this topic by suggesting that ring sizing is "voodoo". We now review the available evidence regarding the various repair techniques described for structural and functional mitral valve regurgitation. Herein, we illustrate that for structural mitral valve regurgitation, resuspension of prolapsing valve segments or torn chordae with polytetrafluoroethylene sutures and annuloplasty can generate the most durable results paired with the best achievable hemodynamics. For functional mitral valve regurgitation, the evidence suggests that annuloplasty alone is insufficient in most cases to generate durable results, and additional subvalvular strategies are associated with improved durability and possibly improved clinical outcomes. This review addresses current strategies but also implausibilities in mitral valve repair and informs the mitral valve surgeon about the current evidence. We believe that this information may help improve outcomes in mitral valve repair as the heterogeneity of mitral valve regurgitation pathophysiology does not allow a one-size-fits-all concept.
IM-Shield: A Novel Defense System against DDoS Attacks under IP Spoofing in High-speed Networks

DDoS attacks are usually accompanied by IP spoofing, but the availability of existing DDoS defense systems for high-speed networks decreases when facing DDoS attacks with IP spoofing. Although IP traceback technologies are proposed to focus on IP spoofing in DDoS attacks, there are problems in practical application such as the need to change existing protocols and extensive infrastructure support. To defend against DDoS attacks under IP spoofing in high-speed networks, we propose a novel DDoS defense system, IM-Shield. IM-Shield uses the address pair consisting of the upper router interface MAC address and the destination IP address for DDoS attack detection. IM-Shield implements fine-grained defense against DDoS attacks under IP spoofing by filtering the address pairs of attack traffic without requiring protocol and infrastructure extensions to be applied on the Internet. Detection experiments using the public dataset show that in a 10Gbps high-speed network, the detection precision of IM-Shield for DDoS attacks under IP spoofing is higher than 99.9%; and defense experiments simulating real-time processing in a 10Gbps high-speed network show that IM-Shield can effectively defend against DDoS attacks under IP spoofing.
Desynchronosis: Types, Main Mechanisms, Role in the Pathogenesis of Epilepsy and Other Diseases: A Literature Review

Circadian information is stored in mammalian tissues by an autonomous network of transcriptional feedback loops that have evolved to optimally regulate tissue-specific functions. Currently, stable circadian rhythms of the expression of clock genes (Bmal1/Per2/Cry1, etc.), hormones, and metabolic genes (Glut4/leptin, etc.) have been demonstrated. Desynchronoses are disorders of the body’s biorhythms, where the direction and degree of shift of various indicators of the oscillatory process are disturbed. Desynchronosis can be caused by natural conditions or man-made causes. The disruption of circadian rhythms is a risk factor for the appearance of physiological and behavioral disorders and the development of diseases, including epilepsy, and metabolic and oncological diseases. Evidence suggests that seizure activity in the epilepsy phenotype is associated with circadian dysfunction. Interactions between epilepsy and circadian rhythms may be mediated through melatonin, sleep–wake cycles, and clock genes. The correction of circadian dysfunction can lead to a decrease in seizure activity and vice versa. Currently, attempts are being made to pharmacologically correct desynchronosis and related psycho-emotional disorders, as well as combined somatic pathology. On the other hand, the normalization of the light regimen, the regulation of sleep–wake times, and phototherapy as additions to standard treatment can speed up the recovery of patients with various diseases.
Deep Learning-Based Data Augmentation and Model Fusion for Automatic Arrhythmia Identification and Classification Algorithms

Automated ECG-based arrhythmia detection is critical for early cardiac disease prevention and diagnosis. Recently, deep learning algorithms have been widely applied for arrhythmia detection with great success. However, the lack of labeled ECG data and low classification accuracy can have a significant impact on the overall effectiveness of a classification algorithm. In order to better apply deep learning methods to arrhythmia classification, in this study, feature extraction and classification strategy based on generative adversarial network data augmentation and model fusion are proposed to address these problems. First, the arrhythmia sparse data is augmented by generative adversarial networks. Then, aiming at the identification of different types of arrhythmias in long-term ECG, a spatial information fusion model based on ResNet and a temporal information fusion model based on BiLSTM are proposed. The model effectively fuses the location information of the nearest neighbors through the local feature extraction part of the generated ECG feature map and obtains the correlation of the global features by autonomous learning in multiple spaces through the BiLSTM network in the part of the global feature extraction. In addition, an attention mechanism is introduced to enhance the features of arrhythmia-type signal segments, and this mechanism can effectively focus on the extraction of key information to form a feature vector for final classification. Finally, it is validated by the enhanced MIT-BIH arrhythmia database. The experimental results demonstrate that the proposed classification technique enhances arrhythmia diagnostic accuracy by 99.4%, and the algorithm has high recognition performance and clinical value.
Dynamic Air-Ground Collaboration for Multi-Access Edge Computing

Unmanned aerial vehicles (UAVs) are expected to improve the quality of services for the fifth-generation (5G) and beyond networks. Nevertheless, in the context of multi-access edge computing (MEC), a key pillar for meeting 5G key performance indicators, state-of-the-art design suffers from difficulty in matching time/spatial-varying communication/computation demands with distributed resources in highly dynamic air-ground integrated networks. To handle this issue, this paper proposes a joint online trajectory planning and offloading scheduling scheme based on reinforcement learning (RL), such that a UAV and base stations in a multi-cell network can dynamically and collaboratively offer edge computing services. We formulate the decision-making on trajectory planning/offloading scheduling as mutually embedded Markov decision processes, so as to avoid exponentially increasing joint state/action spaces and non-cooperative decision-making. In order to learn the policies for decision-making, novel RL algorithms are proposed based on deep Q-network and the kernel method, respectively. It is shown that the learned policy is able to make the joint trajectory planning and offloading scheduling adaptive to dynamic computation demands. Benefiting from this, the air-ground collaborative MEC can significantly outperform the terrestrial-only MEC in terms of the average backlog of newly produced computational task bits.
A review on antibiotics pervasiveness in the environment and their removal from wastewater

ABSTRACT The production and utilization of antibiotics is increasing every year. Overuse, inappropriate disposal, and leakage from production sites leads to the pervasiveness of their residues and toxic intermediates in wastewater and surface water. This paper summarizes the present state of antibiotics in the aquatic environment present around the world and the recent researches in the direction of their removal. Traditional wastewater treatment plants (WWTPs) cannot altogether remove many antibiotics due to inadequate treatment processes. As a result, an effective, cost-efficient, quick, operationally practical, and environmentally acceptable solution to remove antibiotics is required. Adsorption has been proved one of the most viable alternatives among other techniques. The adsorption behavior of some widely used antibiotics across different materials is critically discussed in this paper. In addition, the effects of several factors affecting the adsorption process are also analyzed. Future research directions for antibiotic elimination from aqueous medium are also highlighted. Toxicity studies of degraded hazardous antibiotic metabolites are essential, and their viable chemical conversion into economically attractive organic chemicals is the need of the day. GRAPHICAL ABSTRACT
Radius Domain-Based Importance Sampling Estimator for Linear Block Codes over the AWGN Channel

In this paper, the problem of efficiently evaluating the error performance of linear block codes over the AWGN channel is considered. Based on the geometric structure of the channel, we define the l2-norm of the noise vector as a random variable and refer to its sample space as the radius domain. A minimum-variance importance sampling (IS) estimator is proposed by deriving the optimal IS distribution on the radius domain. The IS gain of the proposed estimator compared to the Monte Carlo method is analyzed. The asymptotic IS gain for high SNR, which only depends on the minimum distance of the code, is derived. Finally, the effectiveness of the proposed estimator and the accuracy of the asymptotic IS gain are verified through simulation.
Energy efficient design of laser driver using field programming gate array

The laser drivers are extremely important to be used to provide safe interface for the optical components attached to the laser. In this paper, energy efficient laser driver circuit is design using field programming gate array (FPGA). The laser driver is first designed using current mode logic (CML) technique, which is widely used for designing the optical components. Then this design is implemented on FPGA using very large scale integration (VLSI). The laser driver produces the energy efficient output using voltage scaling technique in which the core voltage of FPGA virtex-7 board is reduced from 2.2 V (Peak core voltage of FPGA) to 0.5 V (base voltage of FPGA). By reducing core voltage of FPGA virtex-7 from peak to base voltage the power consume by laser drivers is reduced up to 90% for 15 THz frequency. Similarly, for less than 15 THz frequencies the power consumption is also reduced. The main advantage of designing this energy efficient laser driver is that it will control the output of any high frequency semiconductor laser up to 15 THz frequency. This energy efficient design of laser driver will be integrated with high frequency semiconductor laser to produce green optical output for communication systems.
Nanoparticles Loaded Mucoadhesive Buccal Patches - Review

Drug distribution for both local and systemic conditions is significantly facilitated by buccal methods of administration. When a rapid beginning of action is necessary, they have proven to be a potent substitute for the conventional oral route, the buccal route is regarded as patient-friendly. Although many procedures have been explored, drug permeability and regulated drug release via this route of delivery remain concerns for the effective therapy. They have shown to be an effective alternative to the traditional oral route, especially when fast onset of action is required. The buccal route is considered patient friendly due to its non-invasive nature and ease of administration. Nanotechnology has advanced to the point that clinical uses have been considered. The use of nanoparticles in buccal dosage forms not only provides efficient distribution but also lowers biological system side effects. Many methods for loading and delivering drug-loaded nanoparticles to the buccal mucosa have been proposed, both for topical and systemic administration. The primary objective of this review is to provide an overview of the nanotechnological methods that have been so far developed to enhance the buccal administration of medications.
HUBER 360 and PRIMUS-RS in the Advance Rehabilitation of a Patient with Right Anterior Cruciate Ligament Reconstruction: A Case Report

Background: HUBER 360 and PRIMUS-RS are technologically advance rehabilitation and assessment equipments. However, there is a dearth of literature, to the best of our knowledge, on the use of the above equipment’s in the objective assessment and effective rehabilitation. Case Report: The case discussed is of a 30 year old female who underwent Anterior Cruciate Ligament (ACL) Reconstruction three months prior to approaching our physiotherapy department and was looking for more advance rehabilitation. A thorough pre-assessment was done, a part of which included the PRIMUS-RS testing of isometric strength, power and endurance of knee muscles. A week wise rehabilitation protocol was designed for 5 weeks on HUBER 360 at the end of which again PRIMUS-RS testing was done. It was then found that the deficits in the muscle strength, power and endurance had reduced and patient perceived herself to be able to perform better in her daily activities. Conclusion: Thus, it proves that the PRIMUS-RS and HUBER 360 play an important role in objective assessment and rehabilitation of a musculoskeletal patient. KEY WORDS: Anterior Cruciate Ligament Reconstruction, HUBER 360, PRIMUS-RS, Rehabilitation.