Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Analysis of Conformal Antenna Array for Millimeter-Wave MIMO Communications: Array Modelling and Error Rate Analysis

In this paper we propose three novel ideas for Spatial Modualtion(SM) based Millimeter-Wave(mmWave) Multiple-Input Multiple-Output(MIMO) systems. Firstly, we propose an Hemispherical-Conformal Antenna Array(H-CAA) and Cylindrical Conformal Array Antenna(C-CAA), for which we develop the framework for SM scheme known as Conformal Antenna Array-Spatial Modulation(CAA-SM). The proposed system comprises of a single RF-chain like Conventional SM system. With the aid of this single RF chain we activate multiple antenna elements and make all the receive antenna aim at the transmitter. Whilst maintaining the advantages of the Conventional SM scheme it has been proved that the system under study has much better performance when compared with traditional SM systems.
Complete Genome Sequence of Klebsiella pneumoniae Podophage Pylas

Carbapenemase-producing Klebsiella pneumoniae is an important opportunistic pathogen due to its drug resistance. This study reports on the isolation and characterization of a podophage, named Pylas, infecting this bacterium. The complete genome of phage Pylas is described, and it is distantly related to the well-studied phage N4. ABSTRACT Carbapenemase-producing Klebsiella pneumoniae is an important opportunistic pathogen due to its drug resistance. This study reports on the isolation and characterization of a podophage, named Pylas, infecting this bacterium. The complete genome of phage Pylas is described, and it is distantly related to the well-studied phage N4.
Impact of Particle Swarm Optimization Parameters on its Convergence

Particle swarm optimization algorithm is an intelligent optimization technique applied to solve optimization problem in the field of Engineering, optimization design of electrical networks, aircraft, control systems, optimum design of chemical processing equipment, design of civil engineering structure, economic load dispatch, load flow, management system, medical etc. Various parameters of PSO are: population size(P), inertia weight, acceleration constants random number, Maximum number of iteration. In this paper an attempt is made to understand the PSO algorithm by solving Rosenbrock benchmark function manually. The impact of variations of parameters on PSO convergence has been studied. Each parameters is varied systematically keeping all other parameters fixed to some value. Rosenbrock benchmark function has been used to study the impact of parameters variations. It was found that PSO is sensitive to the values of these parameters, combination of various parameters for best accuracy and faster convergence has been determined.
Non-Convex Relaxation Low-Rank Tensor Completion for Hyperspectral Image Recovery

As a low-rank tensor modeling, tensor tubal rank has been received more attention in hyperspectral image (HSI) recovery. However, the tubal rank is often approximated by tensor nuclear norm, which leads to modeling bias. To achieve an unbiased approximation and improve the model robustness, in this paper, a non-convex relaxation based HSI low-rank recovery model is proposed. And the model is solved efficiently by alternating direction method of multipliers (ADMM) optimization method. Two HSI datasets are employed to exhibit the superiority of the proposed model over the nuclear norm penalization method in terms of the accuracy and robustness.
Landslide Susceptibility Mapping Using Logistic Regression Model Based On Information Value for the Region Along China-Thailand Railway from Saraburi To Sikhio, Thailand

The main purpose of this study is to map landslide susceptibility using the logistic regression model based on information value, for the region along China-Thailand Railway from Saraburi to Sikhio, Thailand. In this study, a total of 60 landslides identified from remotely sensed images were divided into two groups: a group of 80% for training and the left 20% for validation. Landslide hazardous areas were mapped using six landslide controlling factors by logistic regression model based on information value. The performance of the model was evaluated by Receiver Operating Characteristic (ROC) curve. The results showed the model could provide 81.8% and 79.4% success and prediction rates respectively, meaning the map behaved good performance. Furthermore, the two factors of river networks and geotechnical types had a higher impact on the occurrence of landslides compared with other factors. This landslide susceptibility map can be used for preliminary railway construction and landslide mitigation.
Measurement properties of performance-based instruments to assess mental function during activity and participation in traumatic brain injury: A systematic review

Abstract Background: Performance-based measures that focus primarily on the ability to engage in ADL are routinely used by occupational therapists to assess a client’s cognitive abilities. Objective: To perform a systematic review to investigate measurement properties of performance-based instruments to assess mental function during activity and participation in individuals with traumatic brain injury. Material and methods: Pubmed, EMBASE, CINAHL, PsycINFO and OTseeker were searched. The Consensus-based Standards for the selection of health measurement instruments checklist was used to evaluate methodological quality of each included study. The quality criteria adapted by Terwee were applied to extract the results of each measurement property followed by a best evidence synthesis. Results: Twenty-eight articles, including 40 ratings of measurement properties, were included. The combination of the Functional Independence Measure and the Functional Assessment Measure showed moderate evidence of good internal consistency (Cronbach’s alpha 0.99), but conflicting evidence of reliability (ICC 0.83) and poor evidence of construct validity. All other instruments showed limited or unknown evidence. Conclusions: This review provides an overview of measurement properties of performance-based instruments and contributes to such methodological considerations before choosing an instrument. Though, the results reveal a lack of high-quality evidence for any of the measurement properties, it is recommended to use tools with the highest possible evidence for positive ratings. Significance: This review contributes with psychometric evidence on instruments to use in occupational therapy practice and research.
A Fine-Grained Fully Convolutional Network For Extraction of Building Along High-Speed Rail Lines from VHR Remote Sensing Image

Very high resolution (VHR) remote sensing offers the potential for efficient identification of building areas along the high-speed rail (HSR) lines. However, high intra-class and low inter-class variances in this type of images and pose serious challenges. Fully convolutional network (FCN) has shown impressive performance and great potential for image classification and object detection. Nevertheless, only classification results with coarse resolutions can be obtained from traditional FCN-based methods. To address this issue, this paper presents a fine-grained fully convolutional network to conduct the building extraction task along the HSR lines. The proposed method introduce a fine-grained upsampling module in the encoder-decoder paradigm to upsample the low-resolution feature maps to higher resolution ones instead of the traditional interpolation processing, thus can reserve and recover more fine-detailed information. Furthermore, an enhanced loss function is designed to impose smoothness prior for building extraction. Experiments on the remote sensing image with 0.5 m spatial resolution from Google Earth covering the part area of Zhengzhou-Xi’an high-speed rail line indicates the proposed method achieve competitive results compared with other state-of-the-art FCN based methods. The study demonstrates the potential application of using high-resolution remote sensing technique to investigate the building areas on both sides of HSR lines regularly, in order to detect the hazardous building areas.
Silicon-Based 0.450-0.475 THz Series-Fed Double Dielectric Resonator On-Chip Antenna Array Based on Metamaterial Properties for Integrated-Circuits

The antenna array designed to operate over 0.450-0.475 Terahertz comprises two dielectric resonators (DRs) that are stacked vertically on top of each other and placed on the surface of the slot antenna fabricated on a silicon substrate using standard CMOS technology. The slot created in the silicon substrate is meandering and is surrounded by metallic via-wall to prevent energy dissipation. The antenna has a maximum gain of 4.5dBi and radiation efficiency of 45.7% at 0.4625 THz. The combination of slot and vias transform the antenna to a metamaterial structure that provides a relatively small antenna footprint. The proposed series-fed double DRs on-chip antenna array is useful for applications in THz integrated circuits.
Ground Observation Experiments of Soil Moisture Based on Different Vegetation Coverage

The ground-based microwave radiometer has a strong ability to observe the earth's surface throughout all-time and allweather conditions, which is widely used in the experiments of soil moisture, freeze-thaw and other surface parameters of microwave remote sensing. The observed data could not only be used to establish and verify microwave radiation model and interpret the transmission process and mechanism, but also could be used to improve the retrieval algorithm of surface parameters by optimizing different target parameters. Base on the observation experiment of soil moisture, the design of its experimental scheme was described, and the multi-frequency microwave radiation characteristics of soil moisture were analyzed under different land-cover types in this paper.
A Context Knowledge Map Guided Coarse-to-Fine Action Recognition

Human actions involve a wide variety and a large number of categories, which leads to a big challenge in action recognition. However, according to similarities on human body poses, scenes, interactive objects, human actions can be grouped into some semantic groups, i.e. sports, cooking, etc. Therefore, in this paper, we propose a novel approach which recognizes human actions from coarse to fine. Taking full advantage of contributions from high-level semantic contexts, a context knowledge map guided recognition method is designed to realize the coarse-to-fine procedure. In the approach, we define semantic contexts with interactive objects, scenes and body motions in action videos, and build a context knowledge map to automatically define coarse-grained groups. Then fine-grained classifiers are proposed to realize accurate action recognition. The coarse-to-fine procedure narrows action categories in target classifiers, so it is beneficial to improving recognition performance. We evaluate the proposed approach on the CCV, the HMDB-51, and the UCF101 database. Experiments verify its significant effectiveness, on average, improving more than 5% of recognition precisions than current approaches. Compared with the state-of-the-art, it also obtains outstanding performance. The proposed approach achieves higher accuracies of 93.1%, 95.4% and 74.5% in the CCV, the UCF-101 and the HMDB51 database, respectively.
An Imaging Method For Co-Prime-Sampling Spaceborne SAR

The co-prime-sampling SAR can effectively alleviate the contradictory relationship between spatial resolution and swath width by applying co-prime sampling in azimuth. In order to achieve accurate imaging of co-prime-sampling SAR on the condition of non-negligible range cell migration, an imaging method based on 2D sparse signal reconstruction is proposed. The 2D observed signal is intercepted and the corresponding sparse dictionary is constructed both according to the Doppler parameters of each range gate. An improved 2D signal sparse reconstruction algorithm is used to perform sparse scene reconstruction. Simulation results are provided to demonstrate the effectiveness of the proposed method for sparse scene imaging.
Sentinel-2 “low resolution band” optimization using Super-Resolution techniques:Lysimachia Lake pilot area of analysis

This work super-resolves the lowest-resolution 60m/pixel Sentinel-2 B1 and B9 to the highest-resolution 10m/pixel. Two different categories of super-resolution (SR) techniques are utilized, in specific a SR technique which performs information transfer among different bands and the stochastic regularized SR technique Var-norm+BTV. The study area is the Lysimachia Lake, Western Greece. The Sentinel-2 image of 10th November 2018 has been selected to test the different techniques.
MPC-based Unified Trajectory Planning and Tracking Control Approach for Automated Guided Vehicles*

Autonomous navigation of Automated Guided Vehicles (AGVs) in manufacturing environment is an important part of industrial automation. This paper presents an MPC-based unified trajectory planning and tracking control approach for AGVs. Based on the model of the AGV, improved path planning and reference velocity planning techniques are developed. Then a model predictive controller is designed to track the generated trajectory. In addition, obstacle avoidance capability is also incorporated in the navigation framework. To evaluate the proposed method, simulations and experiments are conducted. The results show that the AGV can achieve high trajectory tracking accuracy with smooth movement.
Classification of Forest Vegetation Type Using Fused NDVI Time Series Data Based on STNLFFM

Forest resources play an important ecological role on the earth. The traditional forest resource inventory methods are grueling and time-consuming. It is insufficient by using single-date remote sensing data to identify the forest vegetation types. Fortunately, multitemporal images have advantages of seasonal variation pattern in different forest vegetation. Duchang County as a study case, GF-1, Landsat8 and MODIS NDVI data were fused to obtain enough spatial and temporal resolution for forest types distinguished by utilizing STNLFFM model and Savitzky-Golay filter. Then, the forest types were classified with the aid of forest inventory data by the SVM method. The classification results showed that the overall accuracy of twice confusion (82%) are significantly better than that of single fusion (72%) only based on Landsat8 and MODIS data. It proved that the more complete temporal data series with higher spatial resolution is very vital even they are derived from different sensors.
RbfA and IF3 couple ribosome biogenesis and translation initiation to increase stress tolerance

Abstract Bacterial ribosome biogenesis and translation occur in the same cellular compartment. Therefore, a biochemical gate-keeping step is required to prevent error-prone immature ribosomes from engaging in protein synthesis. Here, we provide evidence for a previously unknown quality control mechanism in which the abundant ribosome assembly factor, RbfA, suppresses protein synthesis by immature Escherichia coli 30S subunits. After 30S maturation, RbfA is displaced by initiation factor 3 (IF3), which promotes translation initiation. Genetic interactions between RbfA and IF3 show that RbfA release by IF3 is important during logarithmic growth as well as during stress encountered during stationary phase, low nutrition, low temperature, and antibiotics. By gating the transition from 30S biogenesis to translation initiation, RbfA and IF3 maintain the fidelity of bacterial protein synthesis.
Modeling the Anisotropic Reflectance of Snow in a Kernel-Driven BRDF Model Framework Using a Snow Kernel

The linear kernel-driven RossThick-LiSparseReciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was originally developed for modeling the simplified scenarios of the continuous and discreet vegetation canopies, and has been widely used to fit the multiangle observations for the vegetation-soil system of the land surface in many fields. However, there is a need to develop this model to characterize the light scattering properties of snow, which tends to exhibit strongly forward scattering behaviors. This study proposes a snow kernel to describe the reflectance anisotropy of snow, mainly based on the asymptotic radiative transfer theory (ART) for a semi-infinite weakly absorbing layer of snow, and then applies this kernel to the framework of kernel-driven BRDF model. This snow kernel adopts the analytic form of the ART model with an improved ability in forward scattering direction, particularly in a case of a large viewing zenith angle (> 60°) where the simulation accuracy of the ART model somewhat decreases in the principal plane (PP). Validation of this method was implemented using observed multiangle data. Pure snow targets were selected from the entire archive of the POLDER BRDF data. This validation demonstrates that this proposed snow kernel in the framework of the kernel-driven RTLSR model show potentials for many potential applications, particularly in the field of Earth’s water cycle and radiation budget where snow cover plays an important role.
Quasi-Optical Excitation of Modulated Metasurface Antennas

We present a new architecture for modulated metasurface (MTS) antennas with rectangular shape and fed by means of a pillbox-type quasi-optical beamformer. Two design examples were numerically simulated, the first one consists of a linearly-polarized antenna with amplitude tapering to increase the aperture efficiency, while the second one provides a circularly-polarized pencil beam. We show that the proposed structure is able to provide high aperture efficiencies similar to those already demonstrated with circular apertures. Moreover, the use of multiple sources in the focal plane allows us to introduce multi-beam capabilities.
Generation Of the Tandem-X Change Dem From the New Global Acquisitions (2017-2019)

With the global TanDEM-X DEM generation being finished in 2016, the mission is now acquiring a new dataset to provide an independent DEM, the so-called "TanDEM-X Change DEM". It is based on a completely new dataset acquired from 2017 – 2019 in contrast to the acquisitions for the global DEM between 2010 and 2015 in the aim to characterise terrain changes. It benefits from improvements in the acquisition planning process and in the data processing which enable to achieve reliable DEM data of high accuracy with fewer acquisitions. For this goal, the use of an edited TanDEM-X DEM as "starting point" for the processing is mandatory. Detectable 3d elevation changes are presented exemplarily in Indonesian forest and on an outlet glacier in Antarctica.
Continuous-Time Algorithm For Distributed Constrained Optimization Over Directed Graphs

This paper presents a distributed continuous-time algorithm to solve the convex optimization problem with local inequality constraints and a globally coupled equality constraint. Unlike the existing related results only considering quadratic or nonquadratic but smooth local objective function, this work takes into account a wider class of objective functions which could be nonquadratic and nonsmooth. Moreover, the communication graphs considered in this paper are weight-balanced digraphs other than the undirected graphs required in most existing results. Although the symmetry property of graphs is no longer satisfied, the proposed algorithm still converges to the optimal solution of the optimization problem. Finally, the efficacy of the proposed algorithm is verified by both theoretical analysis and simulation results.
Inter-Calibration of Nighttime Light Data Between DMSP/OLS And NPP/VIIRS in the Economic Corridors of Belt And Road Initiative

The nighttime light images acquired by the Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) and the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) can reflect the comprehensive information of human activities. However, there are radiometric inconsistent problems between the existing DMSP/OLS nighttime lighting data such as lack of on-board radiation corrections, pixel saturation, and timescale discontinuities. The radiometric inconsistency between DMSP/OLS and VIIRS also limit the long-term night time light data-based studies. This paper proposes a new method for the inter-calibration of nighttime light data between DMSP/OLS and NPP/VIIRS in the economic corridors of Belt and Road Initiative. An automatic invariant pixel selection method was developed for the fitting of the inter-calibration models. Results revealed that combined with the NPP/VIIRS nighttime light data, the calibrated DMSP/OLS images at NPP/VIIRS radiometric level can well reflect the long-term socio-economic development trends along the economic corridors.
Multi-Targets Deception Jamming for ISAR With Frequency Diverse Array

Since many target features can be acquired via inverse synthetic aperture radar (ISAR), the key of implementing deception jamming on ISAR lies in inducing decoy images imitating the scattering features of real target. In this paper, based on the combination of the frequency diverse array (FDA) and scatter-wave jamming (SWJ), an approach producing multiple two-dimensional decoy images with real target features is presented, the distribution and number of which can be arbitrarily manipulated through designing FDA parameters. Details of the jamming on ISAR is provided along with the simulation results, which illuminates the feasibility and validity of the proposed method.
A Compact Right Hand Circular Polarization Microstrip Antenna using Inverted-L Shaped Feedline for GPS Receiver

In this paper, a compact right-hand circular polarized microstrip antenna for GPS receiver is presented. This antenna has an inverted-L shaped in feedline, which is used to obtain circular polarization. The dimension of the antenna is 40 mm x 40 mm using FR4 as a substrate, with 4.4 of the dielectric constant and 1.6 mm of height. The simulation result shows that at operating frequency 1575.42 MHz has −18.9 dB of return loss and 2.04 dB of gain. Furthermore, impedance bandwidth and circular polarization bandwidth (CPBW) simulation are 102 MHz and 27 MHz respectively. The measurement result obtained 58.1 MHz of the impedance bandwidth at the frequency range from 1524.7 MHz - 1582.8 MHz and the value of gain at 1575.42 MHz is 1.24 dB.
Severe Infra-Occlusion and Failed Eruption of Deciduous Molars Associated with Eruptive and Developmental Disturbances in the Permanent Dentition: A Report of 28 Selected Cases

Retrospective analysis of 28 children suffering from severe infra-occlusion and/or primary failure of eruption of deciduous molars revealed an association with eruptive and developmental disturbances in the permanent dentition, including ectopically placed teeth and aplasia of teeth. Taurodont permanent molars were evident in 19 of the 28 selected cases which suggests a possible developmental relationship between these factors. Problems in relation to treatment of these cases are discussed.
Scaling Laws for Simple User Selection Algorithm in MIMO Broadcast Channels

This paper discusses the scaling laws of sum capacity for simple user selection algorithm in MIMO broadcast channels. We present an efficient user selection algorithm, named as simple user selection algorithm (or just simple algorithm). This algorithm is based on the top NI users selected from Nu total users in the system. The asymptotic behavior of throughput for MU-MIMO BC (Multi User MIMO Broadcast) system with simple algorithm is studied. It is shown that the upper bound on sum capacity remains unchanged as that of DPC (Dirty Paper Coding). The simple algorithm takes NI largest power users, reducing the search subset for scheduling from Nu to NI , while achieving the same upper bound. This is an important result in the large number of users regime (or devices for IoT scenario) where users try to get the scared communication resource. In the end, we showed that by reducing the search subset does not reduce the degrees of freedom in the system.