Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Multidirectional Myocardial Deformation Result From Pressure and Volume Overload in Compensatory Stage

Aortic stenosis (AS) and aortic regurgitation (AR) were two types of aortic valve defects which had different hemodynamic characteristics. Ultimately, chronic pressure and volume overloads result in different geometrical and functional patterns. The expectation of our study was to compare the impacts of two different types of loading conditions on myocardial deformation in asymptomatic patients with normal ejection fraction in compensatory stage using three-dimensional speckle tracking echocardiography (3D-STE). Among severe aortic valve disease, 36 patients with AR, and 32 patients with AS were enrolled. All subjects underwent conventional two-dimensional echocardiography and 3D-STE. Clinical and echocardiography characteristics were compared between the groups. Compared with control group, left ventricular twist was increased, along with decreased longitudinal, radial, and circumferential strain in the AS group. And AR patients were characterized by a spherical expansion of ventricle, and reduced myocardial longitudinal and radial strain, along with a preserved rotational motion. In univariate linear regression analysis, age, diastolic blood pressure, e’, sphericity index, end-diastolic volume index, stoke volume index, ejection fraction, and left ventricular mass index were independently associated with global longitudinal strain (GLS) in the AR group and relative wall thickness, stroke volume index (SVI), LV mass index, and peak velocity were independently associated with GLS in the AS group. In addition, multiple stepwise regression analysis showed that sphericity index, SVI, and left ventricular ejection fraction (LVEF) were independently associated with GLS in the AR group. And LVEF, peak velocity, and left atrial dimension were independently associated with GLS in the AS group. The affected myocardial layers of AS patients were worse than AR patients, but increased twist was the compensatory mechanism to maintain the effective stroke volume. Multidirectional myocardial damages alert clinicians to be aware that these patients need closer attention.
Towards the Design of Wireless Communicating Reinforced Concrete

This paper addresses the concept of a smart-node wireless network designed for structural health monitoring applications. The network architecture is based on a smart mesh composed of sensing nodes and communicating nodes. The sensing nodes are used to implement the so named communicating material/communicating concrete and collect physical data for structural health monitoring purposes. These data are sent to the communicating nodes that interface the smart-node network with the digital world through the Internet. The sensing nodes are batteryless and wirelessly powered by the communicating nodes via a wireless power transmission interface. Experimental results have been obtained for a simplified sensing node using a LoRaWAN uplink wireless communication (from the sensing node to the communicating node) proving that the functionality of the sensing nodes can be controlled wirelessly by using only the wireless power transmission downlink.
Compact Deep Descriptors for Keyword Spotting

In this work, we present a novel approach for the extraction of deep features from a Convolutional Neural Network (CNN), designed for the task of Keyword Spotting (KWS). The main novelty of our work concerns the generation of a compact descriptor able to simulate the existence/absence of unigrams or bigrams. This is accomplished using a binary, attribute-based representation of a word string together with an appropriate training procedure. Deep features are extracted from the output of the last convolutional layer and are organized into zones in order to incorporate spatial information of the detected attributes. In addition, a novel optimization scheme is proposed which relies on a very effective initialization of the network generating the compact descriptors. Experiments conducted on the IAM dataset prove the efficiency of the novel compact descriptor since the proposed system's performance in on par with the state-of-the-art.
A P-Matrix Model for Third Order Electric and Acoustic Nonlinearities in TC-SAW Devices

A nonlinear P-Matrix model is implemented to describe the generation of third harmonic (H3)and third order intermodulation (IMD3)products in temperature compensated surface acoustic wave (TC-SAW)devices on LiNbO3-rot 128°YX substrate. The constitutive equations are extended by considering the source terms of mixed acoustic and electric origin, where the nonlinear sources are written as sum of mixed third order terms in strain and electric field. Two nonlinear sources are introduced, one is the directly induced nonlinear current at the electrode finger and another is due to acoustic sources distributed in the device, which indirectly lead to a nonlinear current at the electrodes. In total eight source terms and therefore, eight nonlinear coefficients are introduced to extend the P-Matrix approach. The third order nonlinear model shows a good fit to different H3 and IMD3 measurements for duplexers operating in frequency range of LTE band. The nonlinear constants extracted provide a broad dataset for predicting the nonlinear performance. Finally, the role of electric and acoustic contributions to the nonlinear responses of TC-SAW devices is discussed.
Controlling TCP ACK Transmission: Suitable Value of Discard Ratio in LTE-Advanced Pro

The first release of standards for 5th generation (5G) mobile communication has been approved in the 3rd Generation Partnership Project (3GPP). During the 5G standardization, performance of Transmission Control Protocol (TCP) in the 5G mobile networks was studied. It has been observed that the TCP performance is improved when protocols in the Radio Access Network (RAN) take the TCP behavior into consideration. The authors have been studying TCP ACK filtering that can work well with the link layer protocols in RAN, where the TCP ACKs can be intentionally discarded. It has been shown that proposed methods accomplish good TCP throughput while the number of TCP ACKs is largely reduced. In this paper, the authors tackle a remaining issue: finding the suitable value of “discard ratio”. It is proposed that the suitable value is obtained based on the average number of TCP ACKs transmitted in one transmission time interval. Simulation results demonstrate that the suitable value for the TCP ACK filtering can further improve the TCP performance when the number of mobile stations is small. In addition, it improves both throughput and fairness of the TCP when the number of mobile stations becomes large.
Étude électrophysiologique de la mémoire visuelle à court terme

The N2pc is an event-related potential (ERP) component observed typically about 180-270 ms after the target onset. This component is used as a tool to study the deployment of visual spatial attention. In several studies, a slow and late ERP is observed following the N2pc. This activity appears about 300 ms after target onset. In 2006, Jolicoeur, Ses sa, Dell' Acqua and Robitaille, called this component the "Sustained Posterior Contralateral Negativity" (SPCN) and they hypothesized that this ERP reflects the presence of items in visual shortterm memory (VSTM). The goal of this research was to provide additional evidence to support the hypothesis that the SPCN reflects the maintenance of items in VSTM. This was done with experimental manipulations designed to demonstrate dissociations between the N2pc and the SPCN. The position of stimuli (upper vs. lower visual field), the number of items maintained in VSTM, and the length of the retention interval were manipulated. The results suggest that the SPCN reflects maintenance of items in VSTM and that it is separable from the N2pc.
Bag of Features vs Deep Neural Networks for Face Recognition

This paper proposes a comparative study of Bag of Features (BoF) and Deep Neural Networks (DNN) approaches for the problem of face recognition. For the latter approach we consider three pre-trained models, namely AlexNet, ResNet50 and GoogleNet provided through Caffe Model Zoo and use them as feature extractors. Although these models were trained on different datasets, e.g., ImageNet, bottom-most layers act like universal feature extractors thus it is possible to be employed for different classification tasks. In order to adapt the models to various face datasets requirements we performed modifications to the input data as well as to the output layer of the pre-trained models by replacing it with a multiclass SVM classifier.
Forgery detection based on reverberation time estimation in multiple bands

In this paper we propose a system that detects an audio intrusion by analyzing the temporal evolution of an important acoustic parameter, i.e. the reverberation time (RT). Considering the forensic context of our application, we chose a blind method for estimating the reverberation time, and we propose a multiband approach for the RT’s estimation. Furthermore, we introduce a succession of post-processing operations of the RT estimates in order to facilitate the detection of intrusions.
Flexible Carbon-based Urea Sensor by Laser Induced Carbonisation of Polyimide

Pyrolysis of patterned polymers is a widespread technique for obtaining miniaturised carbon structures and devices. This process is performed at ≥ 900°C, which limits the device fabrication to rigid, high-temperature resistant substrates such as silicon. We obtain carbon patterns on commercially available polyimide films by a controlled laser writing, which induces a pyrolysis-like effect and causes the partial conversion of the polyimide into an electrically conductive, high-surface area carbon material. These flexible carbon patterns are characterised using microscopic and spectroscopic techniques, and are used as electrodes for the electrodeposition of chitosan. Subsequently, urease enzyme is immobilised on the chitosan film, and this composite electrode assembly is used for pH-based urea detection. This lithography-free, low-cost, and rapid fabrication process is capable of polyimide surface patterning with any desired shape in the micro- to millimeter range. Electrodeposited chitosan films can be used for the immobilisation of a variety of enzymes and chemical moieties for biosensing applications.
Large Scale Crowd Density Estimation Using a sub-GHz Wireless Sensor Network

Automatic crowd density estimation can be very useful for a multitude of applications such as traffic control or crowd control systems during large-scale events. Classic camera-based setups have several shortcomings, the most notorious of which is the privacy issue. The use of a crowd estimator which makes use of a wireless sensor network (WSN) can provide a potential solution to this problem. We deployed a sub-GHz (433 MHz & 868 MHz) wireless sensor network in an indoor stage at a music festival. Visual validation was established by a team of volunteers who manually analyzed a large set of low-quality camera images which were taken during the event. Next, RSS measurements obtained by the network were classified into different density-based categories by a simple probabilistic neural network. Results indicate that the system is capable of estimating the crowd density with a high accuracy, proving the feasibility of using a WSN for such a task.
Fully Integrated Voltage Doubler With Dual-Mode Three-Dimensional Load Regulation for On-Chip Photovoltaic-Powered Applications

This paper presents a compact and fully integrated switched-capacitor voltage doubler for voltage boosting in photovoltaic-powered implantable devices. Gate-voltage boosting, nonoverlapping, and interleaving techniques are adopted to enhance the driving capability of the voltage doubler at low supply voltage with high efficiency. A dual-mode three-dimensional (3-D) digital control circuit is proposed to regulate the output voltage under the load current variation. The 3-D control on the number of active converter cells, operation frequency, and on-resistance enable fine output voltage regulation over a wide load current range without extensive device segmentation, thereby reducing the routing complexity and the associated parasitic losses. Other advantages are that the switching loss can be proportionally scaled with the load current for high power efficiency and the periodic charge transfer to the output can keep small for small voltage ripple. Pulse-skipping modulation is employed to allow the converter to operate under ultra-light load. The proposed voltage doubler is designed and implemented using 0.18 μm-CMOS process. The measurement results demonstrate that the proposed converter can generate a voltage of 0.9 V from an input of 0.6 V, with a power efficiency of more than 60% within the output current range of 30–440 μA. The peak efficiency is 73% and the active area is 0.33 mm2. These measurement results suggest that the proposed voltage doubler is suitable for voltage boosting at low voltage under the limited availability of power and area.
Constellation design with deep learning for downlink non-orthogonal multiple access

The non-orthogonal multiple access (NOMA) technique is considered as a key component for the next generation cellular system. In downlink NOMA, the constellation of several users are superposed for transmission. The resulting super-constellation needs to be carefully designed for allowing recovering of the data at the receiver side. A deep learning method for constellation optimization is proposed here in the context of downlink NOMA communications. The method is based on an analogy between auto-encoders, a powerful tool in neural networks, and communication systems. Simulation results have verified the effectiveness of this method for both constellation design and optimization of the individual receivers of the users. The optimized encoder/decoder can be successfully combined with iterative error-correction devices such as turbo-codes or LDPC and can be integrated in current communication systems. This technique is quite general and can be used for point-to-point communication as well as for multi-user access under various channel conditions.
Multiscale FEM for the Linear 2-D/1-D Problem of Eddy Currents in Thin Iron Sheets

A novel 2-D/1-D approach to simulate the eddy currents in a single thin iron sheet is presented. The introduced method utilizes ideas of the multiscale finite-element method by reducing the 3-D problem to a 2-D one. This is achieved via a decomposition of the solution with respect to its dependence on the coordinate directions. The decomposition is approximated using an expansion into polynomial shape functions. Integration over the respective coordinate gives an explicit 2-D problem. This eliminates the need to iteratively solve two coupled problems, as it is done in conventional 2-D/1-D methods. As another important advantage, the presented method allows for the incorporation of air gaps between the steel sheets. This can be done “for free,” i.e., without the introduction of additional unknowns and without changing the complexity of the resulting problem. The derivation is shown in detail for both the magnetic vector potential and the current vector potential formulation, giving explicit formulas for low polynomial orders of the used shape functions and illustrating how to proceed for shape functions of arbitrary degree. Finally, the developed method is tested in two numerical examples utilizing different geometries for the iron sheet and the computational efficiency is studied via comparison with a suitable standard finite-element model.
Application of the Parabolic Equation Method for Analyzing the Influence of Forest Massifs on the Radio Wave Propagation

The report gives examples of modeling the propagation of radio waves over an uneven terrestrial surface under difficult conditions with allowance for forest massifs using the parabolic equation method with fast Fourier transform. The proposed methodology can be used for educational, methodological and research purposes, for the operational prediction of propagation of radio waves in a specific locality.
A Minimum Phase Modeling Approach to Disturbance Observer Design for Balancing Control of a Single-wheel Robot

Stabilization of the inverse model of the target system is a critical problem in a current disturbance observer (DOB) based control scheme. When the system is identified as a second order system by the recursive least square (RLS) algorithm, the minimum phase (MP) of the model is not guaranteed. This paper addresses a guaranteed minimum phase method of the identified second order model. Jury's test is conducted to check the stability. All-Pass-Filtering (APF) process are conducted for updating prior parameters of RLS to satisfy the minimum phase criteria. To verify the proposal, a single-wheel robot is identified as a second order model by the RLS method with guaranteed stability. Disturbance observer is designed based on the model. Balancing control experiments of a single-wheel robot are conducted.
Localizing and Recognizing Text in Lecture Videos

Lecture videos are rich with textual information and to be able to understand the text is quite useful for larger video understanding/analysis applications. Though text recognition from images have been an active research area in computer vision, text in lecture videos has mostly been overlooked. In this work, we investigate the efficacy of state-of-the art handwritten and scene text recognition methods on text in lecture videos. To this end, a new dataset - LectureVideoDB compiled from frames from multiple lecture videos is introduced. Our experiments show that the existing methods do not fare well on the new dataset. The results necessitate the need to improvise the existing methods for robust performance on lecture videos.
A Two-Terminal Active Inductor With Minimum Apparent Power for the Auxiliary Circuit

This letter proposes a two-terminal active inductor concept with minimum apparent power processed by the auxiliary circuits, which are implemented by power semiconductor switches and passive elements. It has the same level of convenience as a passive inductor with two power terminals only. Compared with a conventional inductor with the same equivalent inductance and current rating, the energy storage requirement of the inductor can be reduced significantly, as well as the weight and volume. The auxiliary circuit in the active inductor processes both partial voltage and partial current, with the lowest apparent power rating compared to existing solutions. A case study for the dc-link filter inductor in a three-phase diode-bridge rectifier is discussed. Proof-of-concept experimental results are given to verify the functionality and effectiveness of the proposed active inductor.
Cryptanalysis of a Lightweight Certificateless Signature Scheme for IIOT Environments

As an extremely significant cryptographic primitive, certificateless signature (CLS) schemes can provide message authentication with no use of traditional digital certificates. High efficiency and provable security without random oracle are challensges in designing a CLS scheme. Recently, Karati et al. proposed an efficient pairing-based CLS scheme with no use of map-to-point hash function and random oracle model to provide data authenticity in Industrial Internet of Things (IIoT) systems. The security proof was given under several hardness assumptions. However, we notice that both public key replacement attack and known message attack are existing in Karati et al.’s scheme. Any adversary without knowledge of signer’s private key is capable of forging valid signatures. This leads to several serious consequences. For example, anybody can sign IIoT data on behalf of IIoT data owner without being detected.
Avaliação preliminar do tratamento cirúrgico de fraturas intra-articulares do calcâneo *

SUMMARY Preliminary evaluation of the surgical treatment of calcaneal joint fractures The authors performed a retrospective study on 21 patients with 22 calcaneal joint fractures surgically treated with an elliptical posterolateral approach or right angle lateral approach, sometimes associated with a medial approach and internal fixation without bone grafting. The authors obtained 72.72% of good results, 18.18% of fair and 9.09% of poor results. Main complications were skin necrosis, superficial infections, increased heel width, and decreased subtalar motion. Compared to previously published reports, the preliminary evaluation demonstrated low morbidity and satisfactory results.
A New Aprroach for the Assesment of Coronary Artery Disease Risk

Coronary artery disease (CAD) represents a major cause of death worldwide and atherosclerosis is considered as the main cause of the disease. The whole spectrum of coronary artery disease evolves through various events leading to the formation and progression of atherosclerotic plaque and finally its complications. Atherosclerosis is a multifactorial, multistep disease that involves chronic inflammation at every step. Adiponectin is an adipocytokine that appears to have significant antiatherogenic and antiinflammatory properties in the process of atherosclerosis. Objective: to investigate whether circulating concentrations of adiponectin may constitute a significant coronary risk factor and the relation between plasma concentrations of adiponectin and various groups of CAD patients including stable angina pectoris (SAP) and acute coronary syndrome (ACS) patients. Subjects and methods: This study included 80 subjects; 20 apparently healthy subjects as a control group and 60 patients diagnosed as CAD (20 patients with SAP and 40 patients with ACS (27 patients with UA/NSTEMI and 13 patients with STEMI). All subjects (patients and controls) were subjected to clinical evaluation, ECG examination, laboratory tests namely; Troponin I, CK, CK-MB, LDH, Specific laboratory tests included Lipid profile, Fasting blood glucose, and adiponectin and Coronary angiography when indicated Results: Serum concentrations of adiponectin differed significantly among patients with CAD versus control group, STEMI versus SAP and control groups, UA/NSTEMI versus SAP and control groups, ACS (AMI and UA/NSTEMI) versus SAP and control groups. While no statistical difference was observed in adiponectin concentration when comparing SAP versus control group, or UA/NSTEMI versus STEMI. There was negative correlation between adiponectin versus fasting glucose, triglyceride, and LDH. Serum adiponectin levels differed significantly between diabetic and non- diabetic patients with CAD. Angiographic data of number of vessels involved with atherosclerosis did not correlate significantly with serum concentrations of adiponectin. Conclusion: Adiponectin as a marker of atherosclerosis can be used to assess patients at risk of development of CAD and it can be used for risk stratification of patients with myocardial ischemia.