Miracle-dz/UniFAR-FTUs huggingface dataset:
Design Space Exploration of a Sparse MobileNetV2 Using High-Level Synthesis and Sparse Matrix Techniques on FPGAs

Convolution Neural Networks (CNNs) are gaining ground in deep learning and Artificial Intelligence (AI) domains, and they can benefit from rapid prototyping in order to produce efficient and low-power hardware designs. The inference process of a Deep Neural Network (DNN) is considered a computationally intensive process that requires hardware accelerators to operate in real-world scenarios due to the low latency requirements of real-time applications. As a result, High-Level Synthesis (HLS) tools are gaining popularity since they provide attractive ways to reduce design time complexity directly in register transfer level (RTL). In this paper, we implement a MobileNetV2 model using a state-of-the-art HLS tool in order to conduct a design space exploration and to provide insights on complex hardware designs which are tailored for DNN inference. Our goal is to combine design methodologies with sparsification techniques to produce hardware accelerators that achieve comparable error metrics within the same order of magnitude with the corresponding state-of-the-art systems while also significantly reducing the inference latency and resource utilization. Toward this end, we apply sparse matrix techniques on a MobileNetV2 model for efficient data representation, and we evaluate our designs in two different weight pruning approaches. Experimental results are evaluated with respect to the CIFAR-10 data set using several different design methodologies in order to fully explore their effects on the performance of the model under examination.
Fundamental Structure of General Stochastic Dynamical Systems: High-Dimension Case

No one has proved that mathematically general stochastic dynamical systems have a special structure. Thus, we introduce a structure of a general stochastic dynamical system. According to scientific understanding, we assert that its deterministic part can be decomposed into three significant parts: the gradient of the potential function, friction matrix and Lorenz matrix. Our previous work proved this structure for the low-dimension case. In this paper, we prove this structure for the high-dimension case. Hence, this structure of general stochastic dynamical systems is fundamental.
Induction hardening of steel elements with complex shapes

As an example of induction hardening of steel elements with complex shapes the induction contour hardening of gear wheels was selected. The model of the process was proposed and simulation results elaborated by means of professional computer software for coupled physical fields were presented. Quite reasonable accordance between computations and measurements was obtained. Streszczenie. Jako przykład hartowania indukcyjnego elementów stalowych o złożonych kształtach wybrano proces hartowania konturowego kół zębatych. Zaproponowano model procesu oraz przedstawiono wyniki symulacji z wykorzystaniem programów do obliczania sprzężonych pól fizycznych. Uzyskano zadowalającą zbieżność wyników pomiarów i obliczeń. (Hartowanie indukcyjne elementów stalowych o złożonych kształtach).
Numerical simulation of solidification structures in continuous casting of a thin slab at high casting speed

ABSTRACT The solidification structure of a thin slab during the continuous casting process at high casting speed was simulated based on the cellular automaton-finite element (CAFE) model. The simulations were consistent with the solidification structures of actual steel samples, and the influence of the continuous casting process parameters and alloy elements were further studied in detail. The optimum process parameters obtained are as follows: the casting speed at 5.2–5.4 m min−1, the superheat at 20–25 °C, and the specific water flow at 1.62–1.64 L kg−1. Meanwhile, the Si content in the thin slab was appropriately increased to refine the grains and improve the production efficiency. This study provides important theoretical data for practical thin slab production, improvement of the continuous casting efficiency, thereby reducing accidents.
Polyaniline Functionalized Peptide Self-Assembled Conductive Hydrogel for 3D Cell Culture

The functionalization of self-assembled peptide hydrogel is of great importance to broaden its applications in the field of biomedicine. In this work, conductive hydrogel is fabricated by introducing conductive polymer polyaniline into peptide self-assembled hydrogel. Compared with pure peptide formed hydrogel, the conductive hydrogel exhibits enhanced conductivity, mechanical property and stability. In addition, the hydrogel is tested to be of great injectability and 3D bio-printability and could support the viability of encapsulated cells that are sensitive to electrical signals. It should have great application prospects in the preparation of tissue engineering scaffolds.
Conformational Changes in Ff Phage Protein gVp upon Complexation with Its Viral Single-Stranded DNA Revealed Using Magic-Angle Spinning Solid-State NMR

Gene V protein (gVp) of the bacteriophages of the Ff family is a non-specific single-stranded DNA (ssDNA) binding protein. gVp binds to viral DNA during phage replication inside host Escherichia coli cells, thereby blocking further replication and signaling the assembly of new phage particles. gVp is a dimer in solution and in crystal form. A structural model of the complex between gVp and ssDNA was obtained via docking the free gVp to structures of short ssDNA segments and via the detection of residues involved in DNA binding in solution. Using solid-state NMR, we characterized structural features of the gVp in complex with full-length viral ssDNA. We show that gVp binds ssDNA with an average distance of 5.5 Å between the amino acid residues of the protein and the phosphate backbone of the DNA. Torsion angle predictions and chemical shift perturbations indicate that there were considerable structural changes throughout the protein upon complexation with ssDNA, with the most significant variations occurring at the ssDNA binding loop and the C-terminus. Our data suggests that the structure of gVp in complex with ssDNA differs significantly from the structure of gVp in the free form, presumably to allow for cooperative binding of dimers to form the filamentous phage particle.
A New Six-Level Transformer-Less Grid-Connected Solar Photovoltaic Inverter With Less Leakage Current

This paper presents a novel structure of the transformer-less grid-connected inverters. The proposed inverter is combined with six power switches and two power diodes which can generate six voltage levels at the output. Furthermore, the proposed inverter can overcome the leakage current issue in the photovoltaic (PV) system, which is the major problem in grid-tied PV applications. Additional significant features include- reduced filter size, lower total harmonic distortion (THD) of the injected current to the grid, and voltage boosting ability. Moreover, the proposed topology provides full reactive power support to the grid. A control strategy is designed and implemented to provide a voltage boost ability without using any additional dc-dc boost converter. Finally, the performance of the proposed inverter is validated by the 770 $W$ laboratory prototype.
Modified downhill simplex method for fast adaption of optical filters in optical communication systems

The authors propose a control method based on the downhill simplex (Nelder–Mead) method for adaptive optical filters used for channel equalisation in optical communication systems. The performance of this method is compared to gradient methods in numerical simulations. The results show that the proposed method can adapt the filter to more rapid changes of the transmission channel than the gradient methods.
A Conical-Beam Electronically Scanning Antenna Array With Fixed-Frequency Using Edge Loading

This paper presents a conical-beam antenna array with fixed-frequency electronically scanning capability. Twelve half-width microstrip leaky-wave antennas with inclined beams are evenly distributed along a circle to realize conical beam. The fixed-frequency beam electronically scanning in the elevation plane can be realized by varying the capacitance of varactor diodes loaded on the radiation edge of the half-width leaky wave antenna. The simulated results show that the conical beam scans from 22° to 43° at 2.46 GHz in the elevation plane. The ripple is less than 1.5 dB and the gain is better than 4.8 dBi. This fixed-frequency beam electronically scanning capability makes the proposed antenna being potentially useful for wireless communication systems in the bio-medical applications.
Multitemporal Change Detection and Irregular Land Shape Area Measurement from Multispectral Sensor Images through BSO Algorithm

Pixel-based classification and area measurement play a vital role in satellite image processing. The accuracy in classification and area measurement is required for remote monitoring various regions such as water area, cultivation regions, reservoir water spread, and disease spread in cultivation area. Traditionally, Google Earth Pro-based area measurement has error in area measurement due to curvature nature and irregular land surface. Moreover, exact point identification on land surface on Earth pro is difficult due to frequent changes on the land surface. The problem in the land area measurement is mostly affected due to the man-made changes in that particular land area. In this paper, we solve land area measurement error problem through the automated single and multithresholding pixels of different iterations on the land surface by the BSO algorithm. The land cover region pixel intensity changes on the curvature region of land surface with respect to spatial and temporal variations which are identified through BSO optimization-based image segmentation for exact area measurement. For the experimentation of accurate measurement, land area images such as urban, semiurban, hill, and coastal region from LANDSAT and SENTINEL images for period 2016 to 2019 are taken for the land area measurement study. BSO enhances and segments the land regions such as road, building, water body, vegetation, bare land, hill, and coastal region of about 32% more than particle swarm optimization (PSO) algorithm. Furthermore, the urban land area measurement accuracy increases to about 97% than the irregular land surface area.
Microwave-Assisted Water Extraction of Aspen (Populus tremula) and Pine (Pinus sylvestris L.) Barks as a Tool for Their Valorization

The barks of aspen (Populus tremula) and pine (Pinus sylvestris) are byproducts of wood processing, characterized by their low economic value. In the present study, microwave-assisted one-cycle water extraction was explored as a tool for the valorization of this biomass as a source of biologically active compounds. The microwave extractor of the original construction equipped with a pressurized extraction chamber and a condenser section was used. The microwave-assisted extraction (MAE), specially including dynamic dielectric heating up to 70 °C followed by 30 min of isothermal heating, promoted the isolation of salicin from aspen bark, allowing for the obtention of a two-times-higher free salicin concentration in water extracts (−14% vs. 7%) reached by multi-cycle accelerated solvent extraction (ASE), which is an advanced technique used as a reference. The MAE of pine bark with dynamic heating up to 90–130 °C, avoiding the isothermal heating step, allowed for the obtention of a 1.7-times-higher concentration of proantocyanidin dimers-tetramers, a 1.3-times-higher concentration of catechin and a 1.2-times-higher concentration of quinic acid in water extracts in comparison to a more time- and solvent-consuming ASE performed at the same temperature. The biological activity of the obtained extracts was characterized in terms of their ability to inhibit xahntine oxidase enzyme, which is a validated target for the therapeutic treatment of hyperuricemia.
Development and evaluation of two posture-tracking user interfaces for occupational health care

The spinal column requires special care through exercises focused on muscle strengthening, flexibility, and mobility to minimize the risk of developing musculoskeletal disorders that may affect the quality of life. Guidelines for spinal column exercises are commonly presented through printed and multimedia guides accompanied with demonstrations performed by a physiotherapist, occupational health expert, or physical fitness trainer. However, existing guides lack interaction and oral explanations may not always be clear to the user, leading to decreased engagement and motivation to start, continue, or complete an exercise program. In this article, we present two interactive and engaging posture-tracking user interfaces intended to promote proper spinal column exercise form. One user interface employs a wooden manikin with an integrated inertial measurement unit to provide a tangible user interaction. The other user interface presents a mobile application that provides instructions and explanations about the exercises. Both user interfaces allow recording key postures during the exercise for reference and feedback. We compared the usability of the interfaces through a series of flexion and extension exercises, monitored with an inertial measuring unit worn around the torso, and a Microsoft Kinect V2 vision-based sensor. Although no significant differences between the manikin user interface and the mobile application were found in terms of usability, the inertial measurement unit provided more accurate and reliable data in comparison to the Microsoft Kinect V2 as a result of body occlusions in front of the sensor caused during the torso flexion. Although both user interfaces provide different experiences and performed well, we believe that a combination of both will improve user engagement and motivation, while providing a more accurate motion profile.
Iminophosphoranes: Synthesis, evolution of synthesis by 31P-NMR, DFT calculations and antioxidant activity

Abstract New mono-iminophosphoranes and new bis-iminophosphoranes 3 were prepared by reaction of triphenylphosphine or tri-alkyl phosphite and azides 1. In order to reduce the reaction time and detect the phosphazides intermediates 2, the reactions of synthesis of iminophosphoranes 3 were evaluated by 31P-NMR spectroscopy. Two phosphazides intermediates 2 in the Z/E form were detected. Density Functional Theory (DFT) calculations were performed at B3LYP/6-311++G** and M062X/def2TZVP to determine the relative stability of Z/E intermediates. Antioxidant activities of iminophosphoranes 3 were evaluated by a 1,1-diphenyl-2-picryl hydrazyl (DPPH) test. The compounds were characterized on the basis of IR, NMR spectroscopy (1H, 13C and 31P) and by HRMS. GRAPHICAL ABSTRACT
Sewer network design layout optimisation using ant colony algorithms

CITATION: De Villiers, N. B. , Van Rooyen, G. C. & Middendorf, M. 2018. Sewer network design layout optimisation using ant colony algorithms. Journal of the South African Institution of Civil Engineering, 60(3):2-15, doi:10.17159/2309-8775/2018/v60n3a1.
Prevalence and Predictors of Radiographically Apparent Upper Urinary Tract Urolithiasis in Eight Dog Breeds Predisposed to Calcium Oxalate Urolithiasis and Mixed Breed Dogs

Data on upper urinary tract (UUT) uroliths in dogs are important to understanding their etiology. The aim of this retrospective case-control study was to determine the prevalence and identify predictors of radiographically apparent UUT uroliths in dog breeds at increased risk for calcium oxalate uroliths (CaOx risk breeds) and mixed breed dogs. Radiologist reports of three-view abdominal radiographs were reviewed from 251 purebred dogs of 8 CaOx risk breeds and 68 mixed breed dogs. UUT uroliths were more common in CaOx risk breeds than mixed breed dogs (23% versus 6%, respectively; OR = 4.8, 95% confidence interval [CI] 1.7–18.9, p < 0.001). UUT uroliths were more common in dogs with lower urinary tract (LUT) uroliths (predominantly calcium-containing) than those without (41% versus 5%, respectively; OR = 13.6, 95% CI 6.3–33.1, p < 0.001), and LUT uroliths predicted the presence of UUT uroliths in the multivariable regression (OR = 6.5, 95% CI 2.8–16.7, p < 0.001). Increasing age (p < 0.001) and lower body weight (p = 0.0016) were also predictors of UUT urolith presence in the multivariable regression. The high prevalence of UUT uroliths in dogs with LUT uroliths supports a shared mechanism for their formation.
Determinants of willingness to help: Evidence from a survey experiment

We analysed determinants of willingness to help using a factorial survey approach (n=405 individuals, n=5937 vignettes). We tested the effect of situational characteristics and how characteristics of the bystander and the person in need influence willingness to help in hypothetical situations within the framework of a cost-reward model. We found that the situation itself has the strongest effect: willingness to help was strongest when the net gain of helping was positive, whereas it was weaker in situations when the cost of helping and cost of not receiving help were equal. These results provide support for the cost-reward model of helping and illustrate that the factorial survey approach could supplement or in some cases replace more widely used experimental methods (laboratory or field experiments).
A Multiphysical Model to Study Moisture Dynamics in Transformers

Moisture is one of the key variables that must be considered when determining the load profiles that can be safely applied to a transformer. The presence of high amount of water accelerates the aging rate of the transformer's solid insulation, shortening the life expectancy of the equipment. Moreover, the dynamic processes of moisture migration between paper and oil must be considered in order to avoid a potential cause of failure, such as the formation of bubbles in the paper–oil interface, or the moisture saturation and the subsequent formation of liquid water in oil. These processes are linked to the changes in temperature; however, within the transformer, both processes have very different time constants, which complicates the analysis. In this paper, a mathematical model is presented, which allows us to study the moisture dynamics in a transformer. The model considers a multi-physical approach incorporating a thermal module and a moisture dynamic module that makes it possible to analyze the behavior of the moisture for a certain load profile. Some application cases are included in this paper to illustrate the model operation.
Data-Driven Risk-Averse Two-Stage Optimal Stochastic Scheduling of Energy and Reserve With Correlated Wind Power

This paper proposes a data-driven optimization method to solve the integrated energy and reserve dispatch problem with variable and correlated renewable energy generation. The proposed method applies the kernel density estimation to establish an ambiguity set of continuous multivariate probability distributions and the optimization model for the integrated dispatch is formulated as a combination of stochastic and robust optimization problems. First, a risk-averse two-stage stochastic optimization model is formulated to hedge the distributional uncertainty. Next, the second-stage worst case expectation is evaluated, using the equivalent model reformulation, as a combination of conditional value-at-risk (CVaR) and the extreme cost in the worst case scenario. The CVaR is calculated using a scenario-based stochastic optimization problem. After describing the wind power correlation in ellipsoidal uncertainty sets, the robust optimization problem for finding the worst case cost is cast into a mixed-integer second-order cone programming problem. Finally, the column-and-constraint generation method is employed to solve the proposed risk-averse two-stage problem. The proposed method is tested on the 6-bus and IEEE 118-bus systems and validated by comparing the results with those of conventional stochastic and robust optimization methods.
Coupling Interference between Eddy Current Sensors for the Radial Displacement Measurement of a Cylindrical Target

In the radial displacement measurement of a small-sized cylindrical target, coupling interference between eddy current sensors reduces the accuracy of the measurement. In this study, finite element method (FEM) simulation based on ANSYS Maxwell was adopted to investigate the relationships between the coupling coefficient of the sensors and different parameters including the lift-off, cylinder diameter, axis angle, material, and excitation frequency. The experimental results were consistent with the simulation results. The coupling interference between the sensors increased with the decrease in the lift-off and cylinder diameter. The coupling effect decreased significantly when the probe axis angle increased to 120°, and the decrease in the sensor sensitivity was acceptable. A polynomial fitting function fitted the output signal well. A compensation method was given based on the compensation necessity evaluation. The results showed that the error of the rotor motion track was significantly decreased after compensation.
A Real-Time CNN-based Lightweight Mobile Masked Face Recognition System

Due to the global spread of the Covid-19 virus and its variants, new needs and problems have emerged during the pandemic that deeply affects our lives. Wearing masks as the most effective measure to prevent the spread and transmission of the virus has brought various security vulnerabilities. Today we are going through times when wearing a mask is part of our lives, thus it is very important to identify individuals who violate this rule. Besides, this pandemic makes the traditional biometric authentication systems less effective in many cases such as facial security checks, gated community access control, and facial attendance. So far, in the area of masked face recognition, a small number of contributions have been accomplished. It is definitely imperative to enhance the recognition performance of the traditional face recognition methods on masked faces. Existing masked face recognition approaches are mostly performed based on deep learning models that require plenty of samples. Nevertheless, currently, there are not enough image datasets that contain a masked face. As such, the main objective of this study is to identify individuals who do not use masks or use them incorrectly and to verify their identity by building a masked face dataset. On this basis, a novel real-time masked detection service and face recognition mobile application were developed based on an ensemble of fine-tuned lightweight deep Convolutional Neural Networks (CNN). The proposed model achieves 90.40% validation accuracy using 12 individuals’ 1849 face samples. Experiments on the five datasets built in this research demonstrate that the proposed system notably enhances the performance of masked face recognition compared to the other state-of-the-art approaches.
A Fully-Integrated Ambient RF Energy Harvesting System with 423-μW Output Power

This paper proposes a 2.4-GHz fully-integrated single-frequency multi-channel RF energy harvesting (RFEH) system with increased harvested power density. The RFEH can produce an output power of ~423-μW in harvesting ambient RF energy. The front-end consists of an on-chip impedance matching network with a stacked rectifier concurrently matched to a 50 Ω input source. The circuit mitigates the “dead-zone” by enhancing the pumping efficiency, achieved through the increase of Vgs drivability of the proposed internal gate boosting 6-stage low-input voltage charge pump and the 5-stage shared-auxiliary-biasing ring-voltage-controlled-oscillator (VCO) integrated to improve the start-up. The RFEH system, simulated in 180-nm complementary metal–oxide–semiconductor (CMOS), occupies an active area of 1.02 mm2. Post-layout simulations show a peak power conversion efficiency(PCE) of 21.15%, driving a 3.3-kΩ load at an input power of 0 dBm and sensitivity of −14.1 dBm corresponding to an output voltage, Vout,RFEH of 1.25 V.