Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Performance Comparison of Metamaterial Based Antenna for 4 G / 5 G Mobile Devices

Abstract—This paper presents the design and performance evaluation of multiband metamaterial based antenna operating in the 3.6 GHz (4G), 14.33 GHz, and 28.86 GHz (5G) frequency bands, for future mobile and handheld devices. The radiating element of the proposed design is made up of a conductive material supported by a 1.524 mm thicker Rogers-4003 substrate, having a relative dielectric constant and loss tangent of 3.55 and 0.0027, respectively. The substrate is backed by truncated ground plane. The future mobile communication system is based on higher frequencies, which are highly affected by the atmospheric conditions. Therefore, to overcome the path loss problem, essential enhancements and improvements must be made in the overall performance of the antenna. The traditional ground plane does not provide the in-phase reflection and surface wave suppression due to which side and back lobes are produced. This will affect the antenna performance in terms of gain and efficiency. To enhance the overall performance of the antenna, a metamaterial acting as a high impedance surface (HIS) is used as a reflector in the proposed design. The simulated gain of the metamaterial based antenna is enhanced from {2.76-6.47, 4.83-6.71 and 7.52-7.73} dB at 3.6, 14.33 and 28.89 GHz, respectively relative to the gain of the antenna backed by a traditional ground plane. The proposed antenna radiated efficiently with a radiated efficiency (>85 %) in all the three frequency bands with and without metamaterial surface. The total volume of the antenna is (L x W x h=45 x 40 x 1.524) mm. The antenna can be potentially used for wireless handheld devices and mobile terminal. All the simulations have been performed using the Computer Simulation Technology (CST) software.
Energy Efficiency Joint Cell Selection and Power Allocation for HetNets

Aiming at the heterogeneity of transmission performance in heterogeneous networks (HetNets) consisting of multiple cells, an optimal cell selection and power allocation scheme is proposed to improve QoS and QoE of users. For one UE case, the proposed scheme selects the optimal cell corresponding to the maximum energy efficiency of the UE. In the case of multiple UEs, the QoS and power constrained energy optimization problem is equivalently transformed into two sub-problems, which are power allocation of each UE-cell pair and cell selection of UEs. The two sub-problems are solved respectively by applying Lagrange dual method and Kuhn-Munkres (K-M) algorithm. Numerical results demonstrate the efficiency of the proposed algorithm.
The Location-Scale Mixture of Generalized Gamma Distribution: Estimation and Case Influence Diagnostics

One of the most interesting problems in distribution theory is constructing the distributions, which are appropriate for fitting skewed and heavy-tailed data sets. In this paper, we introduce a skew-slash distribution by using the scale mixture of the generalized gamma distribution. Some properties of this distribution are obtained. An EM-type algorithm is presented to estimate the parameters. Finally, we provide a simulation study and an application to real data to illustrate the modeling strength of the proposed distribution.
INDOOR POSITIONING USING WLAN FINGERPRINT MATCHING AND PATH ASSESSMENT WITH RETROACTIVE ADJUSTMENT ON MOBILE DEVICES

Abstract. With the increasing number and usage of mobile devices in people’s daily life, indoor positioning has attracted a lot attention from both academia and industry for the purpose of providing location-aware services. This work proposes an indoor positioning system, primarily based on WLAN fingerprint matching, that includes various minor improvements to improve the positioning accuracy of the algorithm, as well as improve the quality and reduce the collection time of the reference fingerprints. In addition, a novel Path Evaluation and Retroactive Adjustment module is employed; it intends to improve the positioning accuracy of the system in a similar fashion to a Pedestrian Dead Reckoning implemented along with WLAN Fingerprint Matching in a Sensor Fusion system. The benefit of this approach being that it avoids the requirement of inertial sensor data, as well as its intensive computation and power use, while providing a similar accuracy improvement to Pedestrian Dead Reckoning. Our experimental results demonstrate that this may be a viable approach for positioning using mobile devices in an indoor environment.
Differential expression of cysteine protease inhibitor (CPI) gene of Polygonum sibiricum Laxm. leaves, stems and rhizomes in response to NaHCO3

A cDNA clone which encodes a cysteine protease inhibitor gene, named PsCPI, has been identified in Polygonum sibiricum Laxm. by the rapid amplification of cDNA ends method (RACE). Analysis of the nucleotide sequence reveals that the PsCPI gene cDNA clone consists of 437 bp, containing 38 bp in the 5' untranslated region, 336 bp in the open reading frame (ORF) encoding 111 amino acids and 63 bp in 3' untranslated region. The gene accession nucleotide sequence number in GenBank is GU562861. Expression analysis by real-time quantitative PCR reveals that the PsCPI gene is expressed in leaves, stems and rhizomes. The result shows that PsCPI gene expression can be induced by 3% NaHCO3 in the three earlier mentioned tissues, but there are different expression modes in leaves, stems and rhizomes under the salinity-alkalinity stress.
Reentry Trajectory Optimization for a Hypersonic Vehicle Based on an Improved Adaptive Fireworks Algorithm

Generation of optimal reentry trajectory for a hypersonic vehicle (HV) satisfying both boundary conditions and path constraints is a challenging task. As a relatively new swarm intelligent algorithm, an adaptive fireworks algorithm (AFWA) has exhibited promising performance on some optimization problems. However, with respect to the optimal reentry trajectory generation under constraints, the AFWA may fall into local optimum, since the individuals including fireworks and sparks are not well informed by the whole swarm. In this paper, we propose an improved AFWA to generate the optimal reentry trajectory under constraints. First, via the Chebyshev polynomial interpolation, the trajectory optimization problem with infinite dimensions is transformed to a nonlinear programming problem (NLP) with finite dimension, and the scope of angle of attack (AOA) is obtained by path constraints to reduce the difficulty of the optimization. To solve the problem, an improved AFWA with a new mutation strategy is developed, where the fireworks can learn from more individuals by the new mutation operator. This strategy significantly enhances the interactions between the fireworks and sparks and thus increases the diversity of population and improves the global search capability. Besides, a constraint-handling technique based on an adaptive penalty function and distance measure is developed to deal with multiple constraints. The numerical simulations of two reentry scenarios for HV demonstrate the validity and effectiveness of the proposed improved AFWA optimization method, when compared with other optimization methods.
Screening Methods for Aluminum Tolerance in Alfalfa

Reliable phenotypic assays are essential to identify genetic variation for factors limiting crop productivity. Aluminum in the soil is highly phytotoxic and is a major limitation to crop production. Current methods to evaluate Al tolerance in alfalfa (Medicago sativa L.) based on root characteristics are time consuming, labor intensive, and subject to microenvironmental variation. Our objective was to develop two rapid wholeplant assays, one in culture media and one in soil, to evaluate acid and Al tolerance in alfalfa. The culture-media method involved measuring root growth and architecture 2 wk after growing the plants in media at pH 7.0 without Al, pH 4.0 without Al, and pH 4.0 with Al. The greenhousebased soil method is simpler, faster, and more effi cient than previously used soil assays. The two assays produced similar results, consistently distinguishing between Al-sensitive and Al-tolerant alfalfa genotypes in accord with previously described assays. These whole-plant assay methods will enable the screening of breeding populations to improve Al tolerance and the dissection of the genetic determinants underlying variation in tolerance responses.
Models for droplet heating and evaporation: an application to biodiesel, Diesel and gasoline fuels

This paper presents our recent progress in the modelling of automotive fuel droplet heating and evaporation processes in conditions close to those in direct-injection internal-combustion engines. Three types of automotive-fuels are considered: biodiesel, diesel and gasoline fuels. Modelling of biodiesel fuel droplets is based on the application of the discrete component (DC) model. A distinctive feature of this model is that it is based on the analytical solutions to the transient heat conduction and species diffusion equations in the liquid phase, taking into account the effects of recirculation. The application of the DC model to fossil fuels (containing potentially hundreds of components), however, is computationally expensive. The modelling of these fuels is based on the recently introduced multi-dimensional quasi-discrete (MDQD) model. This model replaces a large number of components in diesel and gasoline fuels with a much smaller number of quasi-components/components without losing the main features of the original DC model. The MDQD model is shown to accurately predict droplet temperatures and evaporation times and to be much more computationally efficient than the DC model. The main features of these models and their applications to three types of automotive fuel droplets are summarised and discussed.
Privacy-Preserving Scoring of Tree Ensembles: A Novel Framework for AI in Healthcare

Machine Learning (ML) techniques now impact a wide variety of domains. Highly regulated industries such as healthcare and finance have stringent compliance and data governance policies around data sharing. Advances in secure multiparty computation (SMC) for privacy-preserving machine learning (PPML) can help transform these regulated industries by allowing ML computations over encrypted data with personally identifiable information (PII). Yet very little of SMC-based PPML has been put into practice so far. In this paper we present the very first framework for privacy-preserving classification of tree ensembles with application in healthcare. We first describe the underlying cryptographic protocols that enable a healthcare organization to send encrypted data securely to a ML scoring service and obtain encrypted class labels without the scoring service actually seeing that input in the clear. We then describe the deployment challenges we solved to integrate these protocols in a cloud based scalable risk-prediction platform with multiple ML models for healthcare AI. Included are system internals, and evaluations of our deployment for supporting physicians to drive better clinical outcomes in an accurate, scalable, and provably secure manner. To the best of our knowledge, this is the first such applied framework with SMC-based privacy-preserving machine learning for healthcare.
Classification of Bank Customers for Granting Banking Facility Using Fuzzy Expert System Based on Rules Extracted from the Banking Data

Banking facility in recent years is faced with problems such as customer credit risk. And more accurately predict of worthiness of customers is the overall purpose of granting credit. So far many techniques using advanced artificial intelligence systems have been used for this purpose. But they all had advantages and disadvantages. In this article moreover we try to classify customer credit using fuzzy expert system based on rule extracting from banking data, the weaknesses of previous methods, most notably the indescribable and the dependency of experts will address. In the implemented system, the rules were extracted of data rather than expert. So there is no longer dependence on the expert knowledge and the banking rule. And also changes in banking regulations will not cause the system to lose its efficiency. Because of the fuzzy rules, the proposed system is describable and an expert who can accept the validity of the decision to approve or reject it. The results of comparing fuzzy expert systems with the existing methods show that the proposed method is more accurate and will not have the drawbacks of previous methods. The using data was collected from Ansar Bank in Iran.
Considerations to Calculate Expected Genotypic Frequencies and Formal Statistical Testing of Hardy-Weinberg Assumptions for nonpseudoautosomal X chromosome SNPs

HWE is a popular concept from population genetics that provides the investigator with an expectation regarding how genotypes are distributed in a given population. Although relying on a set of assumptions, HWE has been proven useful for genetic studies and, among its several applications, has been used as a quality control metric in GWAS. In this correspondence, the calculation to obtain expected genotypic frequencies of non-pseudoautosomal X chromosome SNPs (assuming HWE holds) by weighting within-sex expected genotypic frequencies by the prevalence of the respective sex in the sample is shown. It is also described that, under the assumption that each sex represents 50% of the sample, a one degree of freedom test can be derived. The calculation is simple and intuitive and, therefore, straightforward to incorporate in routine quality control analyses. This correspondence fills an existing gap in GWAS and may contribute to future investigations.
General Contributions How Youths ’ Profiles of Extracurricular and Leisure Activity Affect Their Social Development and Academic Achievement

Research has shown that participation in extracurricular activities has a positive effect on adolescents’ social behaviour and academic performance; however, the reciprocal influence of extracurricular activities and leisure on the development of adolescents’ academic performance and social behaviour is unclear. In our study, we investigate the effect of school based and out-of-school leisure activities on adolescent’s social and scholastic development. We also explore how students’ gender, socioeconomic status and ethnicity influence their choice of, and engagement in activities. A sample of 5278 students (females 50%; migrant background 26%) filled in questionnaires in grade 5 and 7 and provided personal background information as well as evidence of their engagement in extracurricular and leisure activities, their social behaviour and academic performance. Using latent class analysis, we distinguished five identity-related patterns of engagement in extracurricular and leisure activities among 5th-graders. We found a connection between adolescents’ gender, socioeconomic status, and ethnicity and their choice of, and engagement in, extracurricular and leisure activities, social behaviour and grades. We also identified a link between adolescents’ patterns of engagement in extracurricular and leisure activities and developmental tendencies in their social behaviour and scholastic achievement between grades 5 and 7.
Teacher Electronic Portfolio and its Relation to EFL Student Teacher Performance and Attitude

E-portfolio is a promising approach to develop teachers into reflective practitioners who show that they can adapt to new technologies, new criteria, and new environments. The current research explored the quality of EFL student teachers’ e-portfolios and their attitudes towards using them. The research was conducted on 30 EFL female student teachers at Princess Noura bint Abdulrahman University, Saudi Arabia. The participants were engaging in practical training at schools and reflecting their skills and experiences in their e-portfolios. This research posed further questions about the relationships between the quality of EFL student teachers’ e-portfolios, their attitudes towards using them and their teaching performance. In order to explore the possible answers, the participants’ teaching performance were observed, their e-portfolios were evaluated by a rubric, and a 24-item questionnaire was administered to them. The results proved high proficiency level of the EFL student teachers’ e-portfolios and positive attitudes towards using e-portfolios among EFL student teachers. Furthermore, the results denoted a statistically significant positive relationship between the quality of EFL student teachers’ e-portfolio and their teaching performance. The results of this study may encourage policy makers to integrate the idea of e-portfolio and reflection as an effective component in teacher education and development.
Brokerage as a Process: Decoupling Third Party Action from Social Network Structure

Abstract We argue for a broadened approach to brokerage by distinguishing between brokerage emphasizing a particular structural pattern in which two otherwise disconnected alters are connected through a third party (“brokerage structure”) and the social behavior of third parties (“brokerage process”). We explore a processual view of brokerage by examining three fundamental strategic orientations toward brokerage: conduit, tertius gaudens, and tertius iungens that occur in many different forms and combinations. This processual view is especially relevant in increasingly complex and dynamic environments where brokerage behavior is highly varied, intense, and purposeful, and has theoretical implications for studying multiplexity, heterogeneity, and brokerage intensity.
Power-Control and Rate Selection Medium Access Control for Full-duplex Asymmetric Transmission

Full-duplex asymmetric transmission can improve the system throughput and transmission fairness effectively. However, in the real WIFI network, the length of downlink packet is usually much longer than that of uplink, which can decrease the system performance. In this paper, a WIFI network with a full-duplex access point (FD_AP) and half-duplex stations is studied and a full-duplex Medium Access Control (MAC) protocol based on power control and rate selection (PCRS) is proposed to reduce the effect of Inter Client Interference (ICI) and improve the system throughput and transmission fairness. Furthermore, the differences in packet length and minimum sensitivity are taken into consideration. Simulation results show that PCRS MAC protocol can achieve higher throughput, as compared to the current Distributed Coordination Function (DCF) and a simple fullduplex MAC protocol without PCRS. PCRS MAC also maintains a high level of fairness.
Coverage Path Planning with Adaptive Viewpoint Sampling to Construct 3D Models of Complex Structures for the Purpose of Inspection

In this paper, we introduce a coverage path planning algorithm with adaptive viewpoint sampling to construct accurate 3D models of complex large structures using Unmanned Aerial Vehicle (UAV). The developed algorithm, Adaptive Search Space Coverage Path Planner (ASSCPP), utilizes an existing 3D reference model of the complex structure and the onboard sensors' noise models to generate paths that are evaluated based on the traveling distance and the quality of the model. The algorithm generates a set of viewpoints by performing adaptive sampling that directs the search towards areas with low accuracy and low coverage. The algorithm predicts the coverage percentage obtained by following the generated coverage path using the reference model. A set of experiments were conducted in real and simulated environments with structures of different complexities to test the validity of the proposed algorithm.
CHOLESTATIC LIVER FIBROSIS IN A RAT MODEL OF BILE DUCT LIGATION: EVALUATING BIOCHEMICAL VERSUS HISTOPATHOLOGICAL CHANGES

Objective : Bile duct ligation (BDL), chronic liver injury model, was extensively used in studying mechanisms of fibrogenesis and antifibrotic agents. Considering the liver regenerative capacity and the diverse results from BDL, the present study aimed to evaluate the biochemical and histopathological changes over 10 weeks following BDL assessing if BDL-induced changes remain in a deterioration state or improve at a certain stage. Methods : Sham operation and BDL were conducted in Male Wistar rats. Serum AST, ALT, total bilirubin and albumin and hepatic hydroxyproline (HYP), reduced glutathione (GSH) and malondialdehyde (MDA) were measured in sham-operated (n=3) and BDL-rats (n=6) at 0, 1, 2, 4, 6, 8 and 10 weeks following operation. Liver tissue was also processed for histopathological analysis (H&E and Sirus red staining). Results : Progressive liver injury (H&E) and collagen deposition (Sirus red and HYP) in BDL-rats were observed starting from the first week post-operation and reached their maximum with early signs of cirrhosis on the 10 th week of BDL. Severe and sustained cholestatic injury appeared in 2 weeks (increased ALT, AST, bilirubin along with decreased albumin (P<0.001) compared to sham-operated rats). AST peaked on first week, however, bilirubin, ALT and MDA peaked on the 4 th week (P<0.001) then gradually decreased compared to their peaks. Conclusion : The relative improvement in liver function/cholestasis following their peaks in BDL model despite progression of fibrosis and hepatic injury require investigators using this model to consider not only biochemical, but also histopathological findings to guarantee an accurate interpretation of their results.
Mode evolution and nanofocusing of grating-coupled surface plasmon polaritons on metallic tip

We present a detailed analysis on mode evolution of grating-coupled surface plasmonic polaritons (SPPs) on a conical metal tip based on the guided-wave theory. The eigenvalue equations for SPPs modes are discussed, revealing that cylindrical metal waveguides only support TM01 and HEm1 surface modes. During propagation on the metal tip, the grating-coupled SPPs are converted to HE31, HE21, HE11 and TM01 successively, and these modes are sequentially cut off except TM01. The TM01 mode further propagates with drastically increasing effective mode index and is converted to localized surface plasmons (LSPs) at the tip apex, which is responsible for plasmonic nanofocusing. The gap-mode plasmons can be excited with the focusing TM01 mode by approaching a metal substrate to the tip apex, resulting in further enhanced electric field and reduced size of the plasmonic focus.
Face Detection with Deep Learning

The project here presents the implementation of face detection technology by using deep learning. The main idea used in this project is multi-task Cascaded Convolutional Neural Networks, which contains three sub-networks together to learn to recognize human faces after several stages of decomposition and filtering. The dataset that is going to be used is FDDB dataset, which contains over five thousand faces in a set of around two thousand and eight hundred images.
Electromagnetic transition strengths for light nuclei in the Skyrme model

This work was partly undertaken on the COSMOS Shared Memory system at DAMTP, University of Cambridge operated on behalf of the STFC DiRAC HPC Facility. This equipment is funded by BIS National E-infrastructure capital grant no. ST/J005673/1 and STFC grants no. ST/J001341/1, ST/H008586/1, ST/K00333X/1. M.H. has been partially funded by the UK Science and Technology Facilities Council under grant no. ST/J000434/1. M.H. thanks Andrzej Wereszczynski and the Jagiellonian University, Krakow for hospitality. P.H. C.L. thanks Ling-Yan Hung and Fudan University in Shanghai for hospitality. P.H. C.L. acknowledges support as an International Research Fellow of the Japan Society for the Promotion of Science (JSPS).