Miracle-dz/UniFAR-FTUs huggingface dataset:
SLIVER: A SLIPT-enabled IRS-assisted VLC System for Energy Optimization

This paper deals with a simultaneous lightwave power transfer (SLIPT) indoor visible light communication system, supported by intelligent reflective surfaces (IRS). The proposed system, namely SLIVER, aims to reduce the energy consumption, by means of an optimization problem formulated to minimize the average transmit power from luminaries under data rate and energy harvesting constraints at users, and exploiting mirror-based IRS. The complexity in this problem is due to the large combinations from IRS element rotations. To this end, the problem is transformed into an IRS assignment and spot-finding problem. To solve this, a blockwise efficient artificial neural network is proposed. The proposed architecture can predict the user positions and receiver orientations and accordingly find the optimal beamforming matrix, average transmit powers at luminaries, and IRS assignments. Results reveal that SLIVER system is helpful to achieve better performance under a wide range of user mobility, receiver orientations, and blockage conditions. Specifically, up to 60% of the transmit power can be reduced with the use of the IRS, as compared to traditional approaches (i.e., no IRS) and without complex algorithms.
Brain Tumor Classification using a Convolutional Neural Network and Different Optimizers

In this paper, we designed a brain tumor classifier using a convolutional neural network (CNN) which is a subfield of deep learning. The proposed framework aims to classify three different brain tumor classes which are meningioma, glioma, and pituitary from the publicly available Figshare brain tumor dataset. In this regard, VGG-16 CNN architecture is trained for three brain tumor classes and the results are very promising. This architecture is experimented with six different optimizers namely Adaptive Moment Estimation (Adam), Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMSprop), Adaptive Gradient (Adagrad), Adadelta, and Adamax. Simulation results demonstrate that the proposed VGG-16 architecture achieved 97.15% on the test dataset with respect to 70% training, 15% validation, and 15% testing data.
User Selection for MU-MIMO Based on Channel Estimation and Spatial Orthogonality

This paper addresses interference management in downlink (DL) transmission of a multi-user multiple-input multiple-output (MU-MIMO) system in time division duplex (TDD) mode. A novel method of user selection is proposed based on a relaxed definition of spatial orthogonality, where the base station (BS) obtains channel state information (CSI) using pilot symbols in uplink (UL) transmission. Due to channel reciprocity in TDD mode, the BS selects user groups based on obtained CSI and maximum pairwise channel orthogonality for the DL transmission. Then, the BS employs linear beamformers including maximum ratio transmission (MRT) and zero forcing (ZF) to transmit the payload symbols for the users. Analytical and simulated results indicate the accuracy of the proposed method in terms of the achievable rate. Also for the proposed user selection method, the optimal training sequence length in UL channel is found to maximize sum rate among the selected users.
IoT Educational Management and Consultancy System for Egyptian Public Schools

Educational systems in Egypt face a shortage in the number of teachers as there is an annual increment in the number of students who are enrolled in public schools. Therefore, voluntary teaching is proposed to assist the hierarchy of educational objectives and to compensate for this shortage. With the help of technologies such as QR code scanners, Blue-tooth, Wifi, RFID, and Computer Vision, a technological system guarantees a high quality and high performance of monitoring teaching activities. Nevertheless, an implementation of a mobile application guides the volunteer, the student, and the school administrators to monitor and access the course content easily along with a rewarding system that credits the volunteers for their effort.
Response of Spring Planted Cereals to Pyroxasulfone

Pyroxasulfone is a new herbicide being developed for weed control in corn, soybean and other crops prior to crop emergence. There is little information on the tolerance of spring planted cereals to pyroxasulfone under Ontario environmental conditions. Four field studies were conducted in Ontario over a three year period (2009 to 2011) to evaluate the tolerance of spring planted barley, durum wheat, oats, and wheat to pyroxasulfone applied preemergence (PRE) at 62.5, 125, 250, and 500 g ai ha-1. Regression equations were used to calculate the predicted pyroxasulfone doses (g ai ha-1) that resulted in 5, 10 or 20% injury, or a 5, 10 or 20% reduction in percent height and yield. The dose of pyroxasulfone that caused 5% injury in spring planted barley, durum wheat, oats, and wheat was as low as 23, 14, 7, and 164 g ai ha-1 at 1 WAE; 40, 13, 7, and 127 g ai ha-1 at 2 WAE; 33, 9, 5, and 142 g ai ha-1 at 4 WAE; and 38, 14, 8, and 119 g ai ha-1 at 8 WAE, respectively. The dose of pyroxasulfone that caused 5, 10, and 20% reduction in height was 80, 160, and 321 g ai ha-1 in barley; 30, 58, and 128 g ai ha-1 in durum wheat; 16, 30, and 59 g ai ha-1 in oats; and 149, 299, and >500 g ai ha-1 in wheat, respectively. The dose of pyroxasulfone that caused 5, 10, and 20% reduction in yield was as low as 31, 63, and 126 g ai ha-1 in barley; 25, 49, and 98 g ai ha-1 in durum wheat; 8, 16, and 34 g ai ha-1 in oats; and 122, 244, and 489 g ai ha-1 in wheat, respectively. Based on this study, among spring planted cereals evaluated, wheat is the most tolerant, followed by barley and then durum wheat while oats are the most sensitive.
Convolutional Neural Networks Using Scalograms for Stress Recognition in Drivers

In this paper we present a system which allows the detection of stress in drivers by analyzing a two-dimensional representation of their electrodermal activity Skin Potential Response (SPR) signal, and their electrocardiogram signal. Signals were logged during a simulated drive, in an experiment carried out in a company using a professional car driving simulator. Subjects had to overcome some stress-inducing events located at specific positions during the drive. The acquired SPR and heart rate signals are analyzed with scalogram plots, in order to obtain a time-frequency representation of the signals. The 2D scalogram representation is segmented into images, associated to short time segments, which are classified using a Convolutional Neural Network architecture. We show that the use of scalograms can allow the system to perform well in distinguishing among stress and non-stress situations, achieving a 91.78% accuracy. The same system was tested on real driving data available from a public dataset, achieving a 99.24% accuracy.
Social Learning with Non-Bayesian Local Updates

In non-Bayesian social learning, the agents of a network form their belief about a hypothesis of interest by performing individual Bayesian updates, which are then shared with their neighbors and aggregated according to a suitable pooling rule. This social learning scheme is called non-Bayesian because the pooling rule cannot be Bayesian owing to the limitations arising from the distributed learning setting. However, traditional non-Bayesian learning relies on using a local Bayesian update rule. In this work, we move away from this assumption and consider instead non-Bayesian learning with non-Bayesian updates. Taking as a benchmark the optimal centralized posterior, we show that this modified strategy can outperform traditional social learning and that, intriguingly, it can attain the same error exponent as the optimal scheme under two opposite scenarios: when the data are independent across the agents and when there are agents with highly dependent data.
Numerical models of thermally and mechanically coupled two-layer convection of highly viscous fluids

SUMMARY Numerical solutions for thermal convection of two superposed viscous fluid layers, with the same thicknesses as the Earth’s upper and lower mantles and separated by a fixed horizontal interface, are obtained at the onset of convection and in the nonlinear regime. Several heating configurations and thermal boundary conditions are considered, including an isothermal bottom boundary, a prescribed heat flux bottom boundary, and internal heating with an insulated lower boundary. At the onset of convection and with the same material properties in each layer, the lower layer is more unstable than the upper layer and long horizontal wavelengths (proportional to the lower layer thickness) predominate. For layers with sufficiently different material properties, the upper layer can be more unstable and short horizontal wavelengths (proportional to the upper layer thickness) can predominate at the onset of convection. When the material properties are chosen to make the two layers equally unstable, there are two stability curve (Rayleigh number Ra versus wavelength) minima with the lower minimum at long wavelength. Linear stability results typify weakly nonlinear convection except when both layers are equally unstable. When the layers have unequal stability, the stable layer has a conductive temperature field and its flow is viscously driven by the convective flow in the unstable layer. When the two layers are equally unstable, both layers are separately convecting even at Rayleigh numbers of only twice the critical value for convection onset. At large enough supercritical Ra the lower layer convects with a long wavelength cell even when linear stability theory predicts short wavelength cells. The upper layer always begins convecting with short wavelength cells. However, the upper layer cell over the lower layer downwelling plume increases in size with increasing Ra. Thus, horizontal wavelength (plate dimension, for example) cannot be used to discriminate between whole mantle and layered mantle convection. Mechanical coupling of the layers (downwelling plume over upwelling plume) occurs for all cases with the same material properties in each layer and for the case with the same Ra in each layer. When the material properties of the layers are sufficiently different to produce short wavelength cells at the onset of convection, the upper layer has two thermally coupled cells (downwelling plume over downwelling plume and a shear zone at the interface) over both lower layer plumes. A large (50 per cent of total) temperature difference across the interface occurs in all cases examined, implying that two-layer mantle convection should also have a large temperature change across the 670 km discontinuity. However, temperature dependent viscosity may reduce the magnitude of this temperature difference. Interpretations of geoid anomalies over subduction zones and seismic traveltime anomalies of slabs should account for possible thermal coupling of separate upper and lower mantle convective systems.
Interference-Induced False Detections in FMCW Radars: A Comprehensive Analysis

The increasing number of automotive radar systems operating within the 77 GHz band raises concerns about mutual interference between those systems. It is commonly understood that coherent interference (CI) leads to false detections, while incoherent interference (ICI) raises the noise floor at the victim radar. Some studies have shown that the effects of ICI depend on its periodicity. A periodic ICI creates lines in the range-Doppler map (RDM) for different values of Doppler. In this paper, we extend the common knowledge by demonstrating that even ICI can cause multiple false detections when it is periodic. We also show that these false detections can be spread across all range bins or localized in higher range bins depending on the parameters of the victim and the interfering sweeps.
Overview of the conservation status of cartilaginous fishes (Chondrichthyans) in the Mediterranean Sea

With the highest percentage of threatened sharks and rays in the world, the Mediterranean region is in need of regional planning and policy development for the conservation and sustainable management of chondrichthyan fishes. This third report in the series of Mediterranean Red List Assessments presents the findings of an expert workshop at which 71 Mediterranean species of sharks, rays and chimaeras (cartilaginous fishes) were assessed using the IUCN Red List categories and criteria. This assessment will be used for further development of priority research, conservation and management actions for the region.
Comparative study of two multipole-based numerical methods for 2D field-translation schemes

Two methods based on multipole expansions for the analysis of the field-translation between two distinct domains are comparatively investigated. Here, domain 1 contains the source of the incident field (a horn antenna) which is solved numerically using a commercial solver. Domain 2 contains the scatterer, here a lossless dielectric cylinder. In both methods, we aim at finding the multipole coefficients of the incident field with respect to domain 2. In the first method, the coefficients of a multipole expansion with respect to domain 1 are found from the computed values of the tangential magnetic field on a circular-cylindrical Huygens surface by exploiting orthogonality. Then, Graf’s addition theorem is applied to express the multipole expansion with respect to domain 2. The second method is based on the dyadic Green’s function directly referred to domain 2. Here both types of tangential fields (electric and magnetic) have to be considered on the Huygens surface of domain 1 which however can have an arbitrary shape in this case. Present work is limited to the 2D TE case. Numerical results show a perfect agreement between the two methods.
Effect of Various CSRR Meta-resonator Geometries on the Bandwidth of C-band Waveguide Filters

Recently, split ring resonator (SRR) or complementary split ring resonator (CSRR) meta-resonator structures have been widely used in waveguide filter designs. These waveguide filters with meta-resonator have some advantages over conventional waveguide filters using iris and post as follows: easy to make the equivalent circuit model, a wide range of applications, miniaturization, and low cost. In this work, the bandwidth impact of three widely used CSRR meta-resonator structures with different geometries (ring, rectangular, and crescent shapes) is investigated at C-band. The analyses are performed numerically in CST Microwave Studio (MWS) and Rogers 5SS0 is used as a substrate. According to the results, the narrowest band design is the rectangular-shaped filter while the widest band design is the crescent-shaped filter.
Selective Laser Sintering of Waveguide Devices for 5G and 6G Communication Systems

This article presents an overview of different waveguide devices implemented by additive manufacturing using the Selective Laser Sintering technique showing high performances for both terrestrial and space applications. Firstly, two types of mode two converters will be exposed. These broadband devices without resonant behaviour and without high electromagnetic field densities are especially well-suited to cope with the two main problems of additive manufacturing, i.e., the accuracy and the surface roughness. The first one is a T$E_{10}$ rectangular waveguide mode to T$E_{01}$ circular waveguide mode flared-type converter in Q-band and the second one is a T$E_{10}$ rectangular waveguide mode to T$M_{01}$ circular waveguide mode converter in Ku-band. Secondly, a compact ortho-mode transducer in Ku-band is presented with tested results similar to those obtained by milling or spark erosion suited for satellite applications. In all cases the experimental results of the prototypes are discussed in detail. In addition, the issues related to the orientation of the parts inside the building chamber and other undesirable effects such as spikes due to manufacturing asymmetries, are shared with the scientific community in other to contribute to the development of the additive manufacturing in microwave engineering.
Development of a Robotic Framework for Modeling and Simulation of an Upper Humanoid Robot

Robots can range from simple automated systems to advanced humanoid robots which have gained significant importance in various applications, ranging from customer service to social interaction and assistance for people with disabilities. To facilitate research and learning in this field, this paper presents the development of an open-source humanoid robot platform. The platform is built using the InMoov robot, an open-source 3D printed life-size robot. The paper focuses on kinematics modeling and simulating the humanoid robot, with a specific emphasis on forward kinematics using the Denavit-Hartenberg (DH) convention and inverse kinematics of the arm using a numerical approach and the hand using a geometrical approach. Also, joint and task space trajectories were developed to enable the robot to achieve tasks just as object manipulation. This robotic framework aims to serve as a foundation for other researchers, enabling heuristic analysis to address motion and control challenges in humanoid robots.
Bowtie-Shaped Plasmonic Nanoparticles-Enhanced Photovoltaic Anti-Reflective Coating

Light trapping is a promising technique that enhances sunlight absorption by solar cells. This paper presents a study of bow-tie-shaped nanoparticles embedded in the antireflection coating of photovoltaic solar cells, which enhances the optical transmission of the photovoltaic surface. Therefore, the optical path length for light penetration is increased through the semiconductor active layer. First, the fundamental electric field modes of a single nanoscaled bow-tie are examined under excitation of plane waves with different polarizations. Second, an array of bow-tie-shaped nanoparticles is embedded in an indium tin oxide layer of 80 nm thickness above an active layer of ultrathin hydrogenated amorphous silicon (a-Si:H). The proposed design demonstrates wideband enhancement in the visible and infrared spectrum, resulting in a total enhancement of 45 % over the a-Si:H without the anti-reflection coating.
Analysis of Cell Association in mmWave Networks based on Euclidean and Angular Distances

In millimeter wave (mmWave) networks, the communication link performance is heavily dependent on the directional characteristics of the transceiver beams. Under practical beam management considerations, the transmitter and receiver beams may not be perfectly aligned. We consider such a situation in the downlink of a mmWave cellular network. In this case, the received powers from the base stations (BSs) at the user equipment (UE) of interest will depend upon both the Euclidean and the angular distances (of the BSs to that UE). We develop a novel stochastic geometry framework to study maximum power-based association in this setting. To the best of our knowledge, this is the first work that rigorously explores the role of angular distances in the association policy and analysis of cellular networks. We derive exact expressions for the distributions of signal-to-interference-plus-noise ratio (SINR) and the link rate, as well as the average achievable rate. Among others, our analysis reveals that as the receiver beam becomes more directional (i) the instantaneous achievable rate improves at the expense of a significantly higher variance, and (ii) both the desired received power and the interference power decrease because of the reduced misalignment error and the reduction of the number of interfering BSs falling within in the 3 dB beamwidth of the receiver antenna pattern, respectively, and (iii) the probability of achieving a higher target rate than the average increases.
A Broadband Dual-Polarized Low-NEP SiGe HBT Terahertz Direct Detector for Polarization-Sensitive Imaging

A broadband silicon-integrated dual-polarized antenna-coupled THz direct detector with a minimum NEP of $2.7 \ \mathrm{pW}/\sqrt{{Hz}}$ at 450 GHz and $16 \ \mathrm{pW}/\sqrt{{Hz}}$ at 850 GHz is implemented in a 4-mirror focussed imaging setup, demonstrating polarization-sensitive imaging at 852 GHz. Polarization-sensitive images are computed through the Stokes vector formulation. Based on the degree of linear polarization, finer local physical fingerprints of an imprinted Teflon object are revealed.
Deep Symmetric Matrix Factorization

Deep matrix factorizations (deep MFs) are recent extensions of standard MFs to several layers. This allows one to extract hierarchical interleaved features in high-dimensional datasets. In this paper, we present a variant of deep MF where the input matrix is symmetric and nonnegative, dubbed deep symmetric nonnnegative matrix factorization (DSNMF). We compare several loss functions to tackle DSNMF and propose different possible initialization techniques. We apply successfully DSNMF to the extraction of several levels of communities, both on synthetic data and on a psychiatric network, a promising application in the medical field.
Detection of Nucleocapsid Proteins of COVID-19 using a Terahertz Chemical Microscope

Since the first person infected with COVID-19 was diagnosed in December 2019, the infection has spread rapidly all over the world. PCR and antigen testing are commonly used to detect infection, but detection sensitivity and sample size can be improved. In our group, a terahertz chemical microscope (TCM) has been developed. In this study, we successfully detected the SARS-CoV-2 nucleocapsid proteins (N protein) in solutions by immobilizing the aptamer and N protein on a sensing plate using avidin-biotin reaction.
Network Tomography and Reinforcement Learning for Efficient Routing

Network tomography is a powerful tool to infer the internal state of a network using end-to-end metrics observed by a few nodes at the edge of the network. However, previous research in network tomography has not focused on the objectives and challenges of specific network management applications, resulting in unsatisfactory performance. This paper proposes Subito (Shortest Path Routing with Multi-armed Bandits and Network Tomography) to address the needs and challenges of shortest path routing, a cornerstone of many network management tasks in wired and wireless networks. Subito combines network tomography with reinforcement learning to find an efficient routing strategy. Experiments on synthetic networks show that Subito provides performance improvements up to three times compared to two state-of-the-art approaches.
XHIBIT 1—C ONTAMINANTS ON THE F INAL CCL 4, R EGULATORY D ETERMINATION 3, UCMR 2, UCMR 3 AND P ROPOSED

: Owners and operators of affected facilities are required to comply with reporting and record keeping requirements for the General Provisions (40 CFR part 60, subpart A), as well as for the specific requirements at 40 CFR part 60, subpart SSS. This includes submitting initial notification reports, performance tests and periodic reports and results, and maintaining records of the occurrence and duration of any startup, shutdown, or malfunction in the operation of an affected facility, or any period during which the monitoring system is inoperative. These reports are used by EPA to determine compliance with these standards.