Miracle-dz/UniFAR-FTUs huggingface dataset:
Theory of a Strip Antenna Located at a Plane Interface of a Uniaxial Metamaterial and an Isotropic Magnetodielectric

Electrodynamic characteristics of a straight strip antenna located at a plane interface of a uniaxial metamaterial and an isotropic magnetodielectric are studied using the integral equation method. The antenna is perpendicular to the anisotropy axis of the metamaterial filling the half-space on one side of the interface and is excited by a given voltage. The cases of metamaterials with hyperbolic and nonhyperbolic dispersion are considered. A closed-form solution for the current distribution of an infinitely long strip is obtained and the input impedance of such an antenna is found. Based on this solution, the limits of applicability of the transmission line theory for determining the characteristics of the antenna are established and a generalization to the case of a finite-length strip antenna is discussed.
The Relationship between Self-Reported Adult Impact of Adverse Childhood Events and Health-Related Quality of Life

Childhood maltreatment has become a widespread public health problem that can have life-long impact, according to the National Center of Child Abuse and Neglect. The literature is replete with epidemiologic and co relational research about the relationship between adverse childhood events (ACE’s) and a wide range of negative health and mental health outcomes. Anecdotal evidence suggests that only some individuals who experience ACE’s follow a trajectory of poor outcomes, and not all individuals perceive the impact of ACE’s as necessarily negative. The purpose of this study was to investigate the relationship between individual’s current perceived impact of ACE in adulthood and health related quality of life (HRQL). Self-report data on ACE experiences, including number, severity, and ‘impact’ were collected from 154 community members recruited on the basis of having adverse childhood experiences that might affect adult health related quality of life. Results indicated that, regardless of the number of different types of adverse events experienced, high levels of perceived impact and the rating of this impact as negative or positive were strong predictors of current HRQL. Participants with high levels of perceived negative impact of ACE in adulthood had significantly lower levels of HRQL. Clinical implications and future directions are discussed.
Capacitor Multiplier with One Transconductor Cell

A new programmable capacitance multiplier implementation is presented in this paper. It is based on a fairly known architecture, but the proposed circuit employs only one linear transconductor (Gm cell). The mathematical analysis of the new capacitance multiplier is presented along with simulations performoed on a circuit implemented in standard 0.18-μm CMOS process. Two applications are also presented: a triangular waveform generator and afully differential lossy integrator, both with emulated capacitances programmable over three octaves.
High- ${k}$ HfO2-Based AlGaN/GaN MIS-HEMTs With Y2O3 Interfacial Layer for High Gate Controllability and Interface Quality

High-<inline-formula> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> HfO<sub>2</sub> has been widely adopted in Si based MOSFETs as gate dielectric for the superior control over gate leakage and channel electrostatics. However, in AlGaN/GaN HEMTs, the additional interface issue as well as high oxygen transparency of HfO<sub>2</sub> has hindered its practical applications. In this work, high-<inline-formula> <tex-math notation="LaTeX">${k}~\text{Y}_{2}\text{O}_{3}$ </tex-math></inline-formula> with ultra-low oxygen permeability and high thermodynamic robustness has been introduced as the interfacial layer between HfO<sub>2</sub>/GaN for the interface engineering. It has been demonstrated that, the HfO<sub>2</sub>/Y<sub>2</sub>O<sub>3</sub> gate dielectric stacks have obtained the GaN MIS-HEMT an ultra-small subthreshold swing of ~70 mV/decade, an extremely low gate leakage of ~10<sup>−12</sup> A/mm, and a desirable dielectric/semiconductor interface quality with interface state density in level of ~10<sup>12</sup> cm<sup>−2</sup>eV<sup>−1</sup>. Meanwhile, a maximum drain current of 600mA/mm has been achieved together with an on-state resistance (<inline-formula> <tex-math notation="LaTeX">${R} _{\mathrm{ on}}$ </tex-math></inline-formula>) of 10.7 <inline-formula> <tex-math notation="LaTeX">${\Omega }\cdot $ </tex-math></inline-formula>mm and a specific <inline-formula> <tex-math notation="LaTeX">${R} _{\mathrm{ on}}$ </tex-math></inline-formula> of 2.62 <inline-formula> <tex-math notation="LaTeX">$\text{m}{\Omega }\cdot $ </tex-math></inline-formula>cm<sup>2</sup>.
340 GHz Double-Sideband Mixer Based on Antenna-Coupled High-Temperature Superconducting Josephson Junction

Wireless communication and sensing are moving from microwave, millimeter-wave into the terahertz (THz) frequency regime to meet the fast growing demand of ultrahigh data-rate communications and super resolution imaging. Faced with severe atmospheric absorption attenuation and the lack of power efficient transmitting source at the higher band, ultrasensitive and cost-effective receiver frontend technology is required for advanced THz wireless systems. To date, the most sensitive heterodyne mixers, the key components of frontend receiver systems, are based on low-temperature superconducting materials that operate at liquid helium (4.2 K) temperature range, requiring expensive and bulky cryogenic cooling systems thus hindering them from commercial applications such as wireless communications and sensing. In this article, we present a 340 GHz double-sideband fundamental mixer based on thin-film antenna-coupled high-temperature superconducting (HTS) Josephson junction that operates at a much higher temperature range attainable with smaller and cheaper cryocoolers. Based on our innovative work in terms of advanced device circuit and on-chip antenna designs, accurate parametric simulation analyses, and Josephson junction parameter optimizations, the reported mixer exhibits a measured noise temperature of 470 and 780 K at operating temperatures of 20 and 40 K respectively at 340 GHz, a performance significantly higher than any HTS THz mixers reported to date.
Reducing Pulse Rate Variability Computational Error from a 30 Hz Photoplethysmography Recording

Smartphone based photoplethysmography (PPG) has been used as a way to provide a portable health monitoring system. One drawback of using smartphone to perform photo-plethysmography is its low sampling rate and the most common way to remedy this is via spline interpolation. In this paper, we evaluated the effect of different techniques such as interpolation on the computed pulse rate variability coefficients (PRV). The root mean square error of the computed pulse rate variability from a PPG recorded in 500 Hz and a corresponding signal down-sampled at 30 Hz was calculated to show the amount of deviations. The effects on the PRV of different techniques used to increase the resolution of a signal was evaluated as well. Results shows that fitting a curve can reduce the computational error. Furthermore, re-sampling and interpolation greatly reduced the error with the former generally outperforming the latter.
Monocular Depth Estimation Based on Multi-Scale Graph Convolution Networks

Monocular depth estimation is a foundation task of three-dimensional (3D) reconstruction which is used to improve the accuracy of environment perception. Because of the simpler hardware requirement, it is more suitable than other multi-view methods. In this study, a new monocular depth estimation algorithm based on graph convolution network (GCN) is proposed. The pixel-wise depth relationship is introduced into conventional convolution neural network (CNN) to make up the disadvantage of processing non-Euclidian data. And the remaining depth topological graph information on the spatial latent variables are extracted based on a multi-scale reconstruction strategy. The final results on NYU-v2 depth dataset and KITTI depth dataset demonstrate that our algorithm improves the quality of monocular depth estimation, especially there are several little objects coexisting in the scenes.
Performance Analysis of Hyperdimensional Computing for Character Recognition

The Internet of Things (IoT) is an increasingly expanding network of devices. The whole premise of IoT is to provide comfort and convenience, requiring functions such as recognition. This is done through data - first collected by nodes, and then processed to provide meaningful information, commonly using machine learning. However, conventional machine learning techniques such as deep-learning require complicated operations, which may be computationally heavy for small devices. This study explores the capabilities of hyperdimensional computing (HDC), as a less complex architecture for data classification. The effect of dimensionality (and therefore energy) in the performance of HDC, done through a character recognition application, was explored. Results show that a dimensionality of 4,000-bit one-shot learning system yields an average accuracy close to that of its 12,000-bit counterpart at 0% distortion, and an average accuracy of 89.94% with 14.29% distortion. This study provides insights towards optimizations of HDC applications.
The Method of Extracting Land Classification Information by HRI-RefineNET Model

Accurate land use classification results play an important role in scientific research and production practice. The existing neural network structure contains many pooling layers. Although the model incorporated spatial location information when extracting ground object information, many detailed features were also lost. At the same time, due to the great difference between remote sensing image and natural image, the model with good performance of natural image extraction cannot be transplanted directly into the extraction of high-resolution remote sensing image. Based on RefineNET model, this paper proposes an improved HRI-RefineNet (High Resolution Image) model. The model chooses farmland, residential areas, forest, roads and water area as extraction targets, and establishes a new method for extracting land classification information from high resolution remote sensing images. The proposed HRI-RefineNet model adjust the convolution layer number and convolution kernel size respectively according to the texture features of different five kinds of ground objects. An improved pooling layer is designed for the HRI-RefineNet for reducing the loss of location information in feature maps. A decoder group is added to the HRI-RefineNet model. 29 remote sensing images of Tai’an city, China, from 2015 to 2017 were selected for experiment. The experimental results showed that the accuracy of farmland, residential areas, forest, roads and water area obtained by HRI-RefineNET model was 93.9%, 92.3%, 91.7%, 90.1%, 88.7%, respectively, superior to the RefineNET model and some existing advanced models.
Process Capability Evaluation for Fabrication of ASIC IR-UWB Transceivers

This paper presents process capability evaluation for a lot of five ASIC prototypes of an impulse radio ultra-wideband transceiver (IR-UWB), fabricated in the white room facility of LAAS Toulouse, France, in ST Microelectronics CMOS 65 nm technology. The main purpose of our undertaken is, starting from the Voice of the Customer (VoC) -offered by an outstanding industrial aeronautic consortium - to provide an evaluation of manufacturing process capability, at different confidence levels, as usually required in industry.
Parallel SFC-based mesh partitioning and load balancing

Modern supercomputers allow the simulation of complex phenomena with increased accuracy. Eventually, this requires finer geometric discretizations with larger numbers of mesh elements. In this context, and extrapolating to the Exascale paradigm, meshing operations such as generation, adaptation or partition, become a critical issue within the simulation workflow. In this paper, we focus on mesh partitioning. In particular, we present some improvements carried out on an in-house parallel mesh partitioner based on the Hilbert Space-Filling Curve. Additionally, taking advantage of its performance, we present the application of the SFC-based partitioning for dynamic load balancing. This method is based on the direct monitoring of the imbalance at runtime and the subsequent re-partitioning of the mesh. The target weights for the optimized partitions are evaluated using a least-squares approximation considering all measurements from previous iterations. In this way, the final partition corresponds to the average performance of the computing devices engaged.
I-HMM-Based Multidimensional Network Security Risk Assessment

Cyber-physical systems (CPS) are vulnerable to network attacks because communication relies on the network that links the various components in the CPS. The importance of network security is self-evident. In this study, we conduct a network security risk assessment from the perspectives of the host and the network, and we propose a new framework for a multidimensional network security risk assessment that includes two stages, i.e., risk identification and risk calculation. For the risk identification stage, we propose a multidimensional hierarchical index system for assessing cybersecurity risk; the system’s security status is determined in three dimensions, i.e., basic operation, vulnerabilities, and threats, and these dimensions guide the data collection. In the risk calculation stage, we use a hidden Markov model (HMM) to assess the network security risk. We provide a new definition of the quality of alert and optimize the observation sequence of the HMM. The model uses a learning algorithm instead of setting the parameters manually. We introduce the concept of network node association to increase the reliability and accuracy of the risk assessment. The simulation results show that the proposed index system provides quantitative data that reflect the security status of the network. The proposed network security risk assessment method based on the improved HMM (I-HMM) reflects the security risk status in a timely and intuitive manner and detects the degree of risk that different hosts pose to the network.
Wave Propagation and Channel Modeling in Chip-Scale Wireless Communications: A Survey From Millimeter-Wave to Terahertz and Optics

The miniaturization of transceivers and antennas is enabling the development of Wireless Networks-on-Chip (WNoC), in which chip-scale communication is utilized to increase the computing performance of multi-core/multi-chip architectures. Although the potential benefits of the WNoC paradigm have been studied in depth, its practicality remains unclear due to the lack of a proper characterization of the wireless channel at the chip scale and across the spectrum, among others. In this paper, the state of the art in wave propagation and channel modeling for chip-scale communication is surveyed. First, the peculiarities of WNoC, including the design drivers, architecture, environment, and on-chip electromagnetics are reviewed. After a brief description of the different methods to characterize wave propagation at chip-scales, a comprehensive discussion covering the different works at millimeter-wave (mmWave), Terahertz (THz) and optical frequencies is provided. Finally, the major challenges in the characterization of the WNoC channel and potential solutions to address them are discussed, providing a roadmap for the foundations of practical WNoCs.
Impact of Vaccination on Hospitalized Adults With Influenza A, 2012–2013

BackgroundSeasonal influenza infection is a significant cause of morbidity and mortality in the United States. Annual influenza vaccine is the most effective method to prevent influenza infection; however, vaccine efficacy is known to be lower in the elderly or those with underlying medical conditions. Little is known about the impact of seasonal influenza vaccination on influenza-associated hospital outcomes. MethodsA retrospective chart review was performed of all hospitalized adult patients with confirmed influenza A infection admitted to a tertiary care medical center during the 2012–2013 influenza season. Demographic information, clinical data, and vaccination status were collected. Outcomes between the vaccinated and unvaccinated patients were compared. ResultsOf 126 influenza A patients hospitalized during the 2012–2013 influenza season, 71 (56%) were vaccinated against influenza and 117 (93%) had at least 1 high-risk medical condition. Serious outcomes were common; 31 patients (24.6%) required intensive care unit admission, and 7 (6%) died. Ten patients (8%) had evidence of rhabdomyolysis, and 26 (21%) met the criteria for health care–associated influenza. The vaccinated patients were significantly older than the unvaccinated patients (mean, 65.3 vs. 55.9 years, P = 0.03) and more likely to have high-risk medical conditions. Despite this, the vaccinated patients were significantly less likely to meet at least 2 of 4 criteria for SIRS or develop ARDS than the unvaccinated patients. ConclusionsWe describe the characteristics of adult patients hospitalized with influenza A infection. The findings suggest that influenza vaccination may be protective against development of SIRS and ARDS in patients hospitalized with influenza A infection.
Design of Servo Motor Controller Device for Antenna Stabilization Based on PID Controller

This paper discusses the design of servo Motor Controller Devices to be applied in Antenna Stabilization based on PID control systems. Antenna Stabilization is an antenna stabilizer that is often used in dynamic fields such as ships, vehicles, military vehicles, and others. Servo Motor Controller Device is needed to stabilize the antenna with PID as speed control. The first experiment analyzes the pulse signal at maximum frequency that the device can produce, the second experiment analyzes the response of servo motor to reference angle with angle variations of 45°, 90°, and 180°, the third experiment analyzes the response of servo motor to continuously changing reference angles, while the last experiment analyzes the response of servo motor to the IMU sensor. The experimental results show that the control system has a fairly good response, so it is worthy of being used as a control device on the antenna stabilization system.
A Terahertz Wireless Communication Link Using a Superheterodyne Approach

This article presents a wireless communication point-to-point link operated in the low terahertz (THz) range, at a center frequency of 300 GHz. The link is composed of all-electronic components based on monolithic millimeter wave integrated circuits fabricated in an InGaAs metamorphic high electron mobility transistor technology. Different configurations and architectures are compared and analyzed. The superheterodyne approach proves to be the most promising of all, being compliant with the new IEEE standard for 100 Gb/s wireless transmissions and showing compatibility to accessible, already available modems. The first option of realizing the superheterodyne configuration is by combining the 300-GHz transmitter and receiver with of-the-shelf up and down converters operating at a center frequency of 10 GHz. In this case, data rates of up to 24 Gb/s are achieved. The second option employs a fast arbitrary waveform generator that uses a carrier frequency to up-convert the baseband data. In this case, data rates of up to 60 Gb/s and transmission distances of up to 10 m are achieved with complex modulated signals like 16-QAM and 32-QAM. The baseband signal is composed of pseudo-random binary sequences and is analyzed offline using fast analog to digital converters. In superheterodyne configuration, multichannel transmission is demonstrated. Channel data rates of 10.2 Gb/s using 64-QAM are achieved. The successful transmission of aggregated channels in this configuration shows the potential of THz communication for future high data rate applications.
Mixed Pictures: Mental Models of Malware

Malware is a serious problem for users, who become affected as a result of the decisions they make online. This paper presents a study examining mental models related to malware and regular software, in hopes of finding clues to that will help us understand what users know about malware, and what we can do to help them make better decisions online. The study involved two drawing tasks, where participants were asked to draw their understanding of how a word processor and malware work, respectively. Several concerning patterns emerged. Participants seemed to regard malware as a fundamentally different kind of entity than regular software. They make black-and-white distinctions between malware and regular software in terms of whether the software is helpful or harmful, who the software serves, and who controls it. Finally, participants showed lesser knowledge of malware compared to regular software.
Combined Matching Approach of Road Networks Under Different Scales Considering Constraints of Cartographic Generalization

Identifying corresponding objects from geospatial databases at different levels of detail is crucial, especially in multi-scale road network matching, which is the prerequisite of data conflation, updating and quality assessment. ‘Stroke’ has a considerable effect on automatic road network generalization, and is essential in the road network matching process. In road network generalization, topological relationships may change, and some roads may be deleted. In this paper, we propose a combined stroke-based matching approach of road networks considering the constraints of cartographic generalization for road networks under different scales. In the entire stroke matching, we utilize the modified Hausdorff distance for geometric similarity. We consider the topological differences in the structural similarity calculation and propose a new weight calculation method. Partial stroke matching can further identify the corresponding roads with changes and updates in different scales. We also propose a method of roundabout detection and matching. The proposed approach could not only match road networks with a small scale difference, but also road networks with a large scale difference. And it can successfully identify the M:N, M:1, 1:1, 1/M:1/N, and 1/M:1 matching relationships. The effectiveness of the proposed approach is verified by experimental results.
Hand grip and pinch strength: Effects of workload, hand dominance, age, and Body Mass Index

Objective: Grip and pinch strength are considered important factors which reflect proper hand function, muscle function, general weakness, nutritional status, physical activities and muscle disability. Some of the factors affecting grip and pinch strength are hand dominance, posture , elbow joint angle, height, age and gender. Present study was designed to see the effects of Workload, Hand Dominance, Age, and Body Mass Index on grip and pinch strength among university students. Methodology: This study was conducted among 82 male student, with means and standard deviation of 24.25 (3.76) years and 24.75(2.44) kg/m2 for age and BMI, respectively. Grip and pinch strength for each participant were measured in time of rest and during light, moderate and heavy workload. Hand held dynamometer was used for measuring grip strength and pinch gauge to measure pinch strength. All Data analyses were performed using the statistical software package; SPSS-18 and analyzed with use of Pearson Correlation Statistical tests and paired sample t-test. Results: Pearson Correlation test showed that grip and pinch strength for the dominance hand was significantly higher than non-dominant hand for all workloads (p 0.05) but BMI considered as an effective parameter on grip and pinch strength for dominant and non-dominant hand in moderate and heavy activities (p < 0.05). Conclusion: these findings, unlike to age, workload and BMI are important factors on grip and pinch strength. This suggests that there is a need for more research to precisely evaluate the effects of these factors on grip and pinch strength.