Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduction of volume integral equations for penetrable body-of-revolution structures

Electromagnetic (EM) interaction with body-of-revolution (BOR) objects has been widely studied, but the effort mainly focuses on conducting or homogeneous dielectric objects which are governed through surface integral equations (SIEs). Due to the symmetry of objects along their revolving axis, the three-dimensional (3D) SIEs can be reduced to a two-dimensional (2D) formulation by performing a Fourier series expansion with the use of its orthogonality. In this work, we consider the penetrable BOR structures described by volume integral equations (VIEs) and develop the reduced SIEs by Fourier series expansion. A numerical example is presented to demonstrate the formulation and its effectiveness is verified.
Leader-following consensus control for Markovian switching multi-agent systems with interval time-varying delays

This paper considers multi-agent systems with interval time-varying delays and Markovian switching interconnection topology. By construction of a suitable Lyapunov-Krasovskii functional and utilization of reciprocally convex approach, new delay-dependent consensus analysis and control for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the effectiveness of the proposed methods.
A Semantic Hash Tree Based Verifiable Data Access Protocol on the Cloud

With the popularity of outsourcing data to the cloud, security of cloud storage has drawn considerable attention. While many research efforts have been devoted to verifying the availability and integrity of the outsourced data, it remains a critical challenge how to efficiently verify the correctness of the cloud's response on data access request. In particular, when a user requests a data item from a mobile or Web interface, what if the cloud claims that the data item does not exist while the item does exist? We refer to this as verifiable data access. In this paper, we present a formal model for verifiable data access, and then propose a privacy-preserving and provably secure protocol to address the problem. In order to achieve the verifiability, we develop a novel mechanism called semantic hash tree. Through a sophisticated design of such a tree, our protocol supports verifiable data access in constant time with logarithm communication cost. Experimental evaluation further validates the practicality and efficiency of our protocol.
Non-orthogonal multiple access based hybrid beamforming in 5G mmWave systems

In this paper, we propose a non-orthogonal multiple access(NOMA) based hybrid beamforming design in 5G mmWave systems. The proposed design depends on the known array geometry and incurs a low training and feedback overhead. Our model assumes that each user employs analog-only beamforming while the BS performs hybrid analog and digital beamforming. To achieve a higher sum capacity, multiple users are allowed to share the same beam based on NOMA mechanism. However, the use of analog beamformer from different localized users means that the BS's digital beamformers are not perfectly aligned with the users' baseband effective channels and multiple users may be assigned similar or even identical beamformers. In the meantime, a user pairing and power allocation algorithm is proposed to mitigate interference from other beams so as to maximize the sum capacity. Simulation results verify the significant advantage of the proposed scheme in sum capacity.
Balancing Strategies Evaluation Framework Using Available Multi-Area Data

The penetration of variable renewable energy sources, the deregulation of electricity markets, and the expansion of HVDC-transmission capacities all increase the variability, uncertainty, and imbalances for system operators (SOs) to handle. Meanwhile, frequency quality has deteriorated and occurrence of balancing problems has increased. Therefore, there is an increased need for SOs to improve their balancing strategies. In this paper, we present a new balancing evaluation framework. The main idea of the framework is to be applicable for real and large power systems and provide support for SOs when comparing already used balancing strategies with new ones using historical available data. This is important as only comparatively low-resolution data measurements such as hourly mean values for production, consumption, and HVDC transmission are stored in many power systems. The framework consists of model building, system parameter identification, testing different strategies, and targets supporting the corporate missions of the SOs. In a case study, the framework is tested for a real power system where the model setup mimics measured frequency accurately. The case study illustrates how the framework can be used to evaluate the impact of different balancing strategies on a series of selected targets, which support the cooperate missions of ENTSO-E.
Epidemiology of Herpes Human Virus 6 and 7 Infections in Salivary Gland Neoplasms in Isfahan, Iran

Background: The previous studies showed that herpes human virus-6 (HHV-6) and HHV-7 exist in salivary glands. One of the important areas in oral and maxillofacial pathology field is tumors of the salivary glands. In this study, to declare the major sites of persistent infection with HHV-6 and HHV-7, the existence of HHV-6 and HHV-7 genomes in formalin-fixed paraffin embedded tissue samples of salivary gland tumors. Methods: This analytical study was performed in 60 paraffin blocks samples of malignant and benign neoplasms of both major and minor salivary glands. This study performed with highly sensitive real time PCR method. Results: Among 60 paraffin blocks salivary gland tumors with equal chances of presence of the HHV-7 and HHV-6 in the samples, 34% were positive for both HHV-7 and HHV-6 while 47.2% were only positive for HHV-7, 18.9% samples were positive for HHV-6. A relationship was noticed between HHV-7 and HHV-6 genomes. Conclusion: In conclusion, this study showed no relation between virus and diseases with P=0.953. Also it could be inferred that there is a relationship between HHV-6 and 7 in salivary glands neoplasms.
Simultaneous Conversions with the Residue Number System Using Linear Algebra

We present an algorithm for simultaneous conversions between a given set of integers and their Residue Number System representations based on linear algebra. We provide a highly optimized implementation of the algorithm that exploits the computational features of modern processors. The main application of our algorithm is matrix multiplication over integers. Our speed-up of the conversions to and from the Residue Number System significantly improves the overall running time of matrix multiplication.
Measuring of Fiber/Matrix Adhesion in Thermoplastic Polymer Composites: A Preliminary Study

The possibilities of the application of microbond test and cylinder tests for determining the interfacial shear strength at the fiber-matrix interface in thermoplastic matrix polymer composites were investigated. Possibilities of test specimen preparation were also investigated. Finally the applicability of the method to make high precision measurement of interfacial shear strength was evaluated.
Robust vehicle detection from noisy acceleration signal for bridge monitoring systems

The Internet of Things (IoT) - sensors and actuators connected via internet infrastructure to computing systems - has received enormous research attention. It has found applications in nearly every field, especially, in transportation where bridge monitoring systems are well known examples. This paper proposes a vehicle detection method from acceleration signals acquired from sensors of the bridge monitoring systems. The accelerometers based on micro-electro-mechanical system (MEMs) technology, are sensitive to environmental disturbances such as shock or temperature changes, so that the generated signal is contaminated by various types of noise. Our method first performs noise reduction, retaining only signal components that represent real measurements of forces induced by passing vehicles. The signal is then processed in the second phase using a wavelet-based pattern matching technique. Experimental results on real-world data demonstrate the high performance of both phases of the proposed method.
Active learning for high-density crowd count regression

Efficient crowd counting is an essential task in crowd monitoring, and significant advances have been made in this field recently by counting-by-regression techniques. We propose in this work a learning-to-count strategy with a generic detection algorithm which benefits from a counting regressor in order to identify crowded subregions with inadequate head detection performance, and to improve their representativeness in the training set. A straightforward but crucial step is proposed in order to take into account perspective correction within the proposed framework. An evaluation on Makkah images with medium to very high densities demonstrates the effectiveness of our algorithm and its capability to reach a count error of less than 5% in this difficult setting.
The polymorphism of rs266729 in adiponectin gene and type 2 diabetes mellitus

Abstract Genome-wide association studies and meta-analyses indicate that the polymorphism of rs266729 in adiponectin gene increases the risk of type 2 diabetes mellitus (T2DM); however, these study methods have not been able to identify the underlying genetic effect on the development of T2DM. A genetic model-free approach was conducted to determine the underlying genetic model of inheritance of T2DM because of rs266729 in adiponectin gene. We searched available studies on the association between the rs266729 in adiponectin gene and T2DM in accordance with the inclusion and exclusion criteria. Based on the information extracted from the studies, generalized odds ratio value (GOR) was used to evaluate whether the rs266729 polymorphism was a risk factor for T2DM. The parameter &lgr; was calculated to estimate the genetic model, which was defined as the quotient of natural logarithm odds ratio of GC to CC divided by the natural logarithm odds ratio of GG to CC. Finally, binary logistic regression analysis was used to calculate the genetic effect of rs266729 on T2DM. Data from 7 studies were included in this meta-analysis. The total number of subjects was 12,323, comprising 5,948 cases and 6,395 controls. Mean (standard deviation) age of cases was 59.50 (11.53), and that of the controls was 53.80 (11.65), whereas the proportion of male was 40.9 and 50.0%, respectively. GOR was 1.13 (1.02, 1.25) and &lgr; was 0.47 (0.29, 0.64). The result of logistic regression indicated that the G allele influenced the development of T2DM in the additive model, whereas the genetic effect was 1.13 (1.06, 1.19). Sources of control populations were the cause of between-study heterogeneity; nonetheless, there was no publication bias among studies. The G allele of rs266729 in adiponectin gene increases the risk of T2DM through an additive genetic model with an effect of 1.13 (1.06, 1.19).
Selective Sampling Importance Resampling Particle Filter Tracking With Multibag Subspace Restoration

The focus of this paper is a novel object tracking algorithm which combines an incrementally updated subspace-based appearance model, reconstruction error likelihood function and a two stage selective sampling importance resampling particle filter with motion estimation through autoregressive filtering techniques. The primary contribution of this paper is the use of multiple bags of subspaces with which we aim to tackle the issue of appearance model update. The use of a multibag approach allows our algorithm to revert to a previously successful appearance model in the event that the primary model fails. The aim of this is to eliminate tracker drift by undoing updates to the model that lead to error accumulation and to redetect targets after periods of occlusion by removing the subspace updates carried out during the period of occlusion. We compare our algorithm with several state-of-the-art methods and test on a range of challenging, publicly available image sequences. Our findings indicate a significant robustness to drift and occlusion as a result of our multibag approach and results show that our algorithm competes well with current state-of-the-art algorithms.
The Hamming Ball Sampler

ABSTRACT We introduce the Hamming ball sampler, a novel Markov chain Monte Carlo algorithm, for efficient inference in statistical models involving high-dimensional discrete state spaces. The sampling scheme uses an auxiliary variable construction that adaptively truncates the model space allowing iterative exploration of the full model space. The approach generalizes conventional Gibbs sampling schemes for discrete spaces and provides an intuitive means for user-controlled balance between statistical efficiency and computational tractability. We illustrate the generic utility of our sampling algorithm through application to a range of statistical models. Supplementary materials for this article are available online.
A dynamic output integration mechanism for LQG power networks with random type parameters

We consider a dynamic game model of power networks with generators and/or consumers, called agents, and one public commission, called the utility; a game with a prescribed dynamic mechanism is performed such that each agent decides a private control to minimize its own cost functional, and the utility manages information transmissions between the utility and agents and decides command signals, called prices, to minimize a public cost functional. In this problem setting, we propose a dynamic output integration mechanism for LQG power networks. The LQG power networks is a generic linear Gaussian model of power networks, which is motivated by so-called average system frequency models. In each model of the agents, we include the type parameter presenting each agent's private information. Also, we consider the estimation in calculation of prices by the utility. The proposed mechanism satisfies the public optimality of the optimal private controls, incentive compatibility, and individual rationality, in both fixed horizon and receding horizon cases.
Pharmacological treatment of osteoporosis in the oldest old

The incidence of osteoporotic fractures increases with age. Consequently, the global prevalence of osteoporotic fractures will increase with the aging of the population. In old age, osteoporosis is associated with a substantial burden in terms of morbidity and mortality. Nevertheless, osteoporosis in old age continues to be underdiagnosed and undertreated. This may, at least partly, be explained by the fact that evidence of the antifracture efficacy of osteoporosis treatments comes mainly from randomized controlled trials in postmenopausal women with a mean age of 70–75 years. However, in the last years, subgroup analyses of these landmark trials have been published investigating the efficacy and safety of osteoporosis treatment in the very elderly. Based on this evidence, this narrative review discusses the pharmacological management of osteoporosis in the oldest old (≥80 years). Because of the high prevalence of calcium and/or vitamin D deficiency in old age, these supplements are essential in the management of osteoporosis in the elderly people. Adding antiresorptive or anabolic treatments or combinations, thereof, reduces the risk of vertebral fractures even more, at least in the elderly with documented osteoporosis. The reduction of hip fracture risk by antiresorptive treatments is less convincing, which may be explained by insufficient statistical power in some subanalyses and/or a higher impact of nonskeletal risk factors in the occurrence of hip fractures. Compared with younger individuals, a larger absolute risk reduction is observed in the elderly because of the higher baseline fracture risk. Therefore, the elderly will benefit more of treatment. In addition, current osteoporosis therapies also appear to be safe in the elderly. Although more research is required to further clarify the effect of osteoporosis drugs in the elderly, especially with respect to hip fractures, there is currently sufficient evidence to initiate appropriate treatment in the elderly with osteoporosis and osteoporotic fractures.
Analysing the spectral response of resonant structures at THz frequencies

The article presents results of fabrication and characterization of planar resonators arrays designed for THz frequencies. The resonance frequency of each array's element in THz domain is achieved by down-scaling its geometry to micrometers dimensions. The design of the samples stems from the results of numerical analyses. Five samples — dipole arrays, were fabricated and underwent the experimental characterization by means of spectroscopic measurement. Results of theoretically determined resonant frequencies were in a good match to the measured values.
The Kinetic Research on the Disperse Dyeing Process for PLA Fabric

In this paper, three disperse dyes were selected to study the kinetic dyeing model of PLA fabric. Based on the dyeing results and the SEM spectrum of PLA fabric before/after dyeing, the kinetic dyeing model was established. Besides, the half-dyeing time and the diffusion coefficient of the disperse dyeing process were also tested. These research results will be very helpful to the development of the application of PLA fabric and also set a theoretical base for the dyeing of such environmentally friendly fabric.
Level Discrimination of Speech Sounds by Hearing-Impaired Individuals With and Without Hearing Amplification

Objectives: The current study was designed to see how hearing-impaired individuals judge level differences between speech sounds with and without hearing amplification. It was hypothesized that hearing aid compression should adversely affect the user's ability to judge level differences. Design: Thirty-eight hearing-impaired participants performed an adaptive tracking procedure to determine their level-discrimination thresholds for different word and sentence tokens, as well as speech-spectrum noise, with and without their hearing aids. Eight normal-hearing participants performed the same task for comparison. Results: Level discrimination for different word and sentence tokens was more difficult than the discrimination of stationary noises. Word level discrimination was significantly more difficult than sentence level discrimination. There were no significant differences, however, between mean performance with and without hearing aids and no correlations between performance and various hearing aid measurements. Conclusions: There is a clear difficulty in judging the level differences between words or sentences relative to differences between broadband noises, but this difficulty was found for both hearing-impaired and normal-hearing individuals and had no relation to hearing aid compression measures. The lack of a clear adverse effect of hearing aid compression on level discrimination is suggested to be due to the low effective compression ratios of currently fit hearing aids.
Sliding Mode Control for Discrete-Time Systems With Markovian Packet Dropouts

This paper presents the design of a sliding mode controller for networked control systems subject to successive Markovian packet dropouts. This paper adopts the Gilbert-Elliott channel model to describe the temporal correlation among packet losses, and proposes an update scheme to select the assumed available states for use in a sliding mode control law. A technique used in the theory of discrete-time Markov jump linear systems is applied to tackle the effect of the packet losses. This involves introducing a couple of Lyapunov functions dependent on the indicator functions of the instantaneous packet loss, and proving that the sliding mode controller is able to drive the system state trajectories into the neighborhood of the designed integral sliding surface in mean-square sense given that the corresponding Lyapunov inequalities are satisfied. The system is guaranteed thereafter to remain inside the neighborhood of the sliding surface. Simulated case studies are presented to illustrate the effectiveness of the control law.
A 700MHz to 2.5GHz Cascode GaAs Power Amplifier for Multi-Band Pico-Cell Achieving 20dB Gain, 40dBm to 45dBm OIP3 and 66% Peak PAE

Recent development and technology advancement in wireless communication systems to accommodate higher data rate poses a great challenge for wideband operation. This is due to the employment of modulation scheme, such as OFDM, which is subject to high peak to average ratio. Hence communication systems, such as LTE have to operate in multiple operating bands at the moment in order to transmit the OFDM signals linearly with high gain. The power amplifier serves as the bottle neck for high gain linear operation over wide bandwidth. This paper addresses this issue and further presents a novel integrated feedback and analog pre-distortion linearization technique as a solution to achieve wideband flat gain and linear output power while preserving the power amplifier’s power added efficiency (PAE). A maximally flat gain is achieved through the dual parallel feedback technique. The analog pre-distorter on the other hand introduces an optimum third order nonlinear signal components cancellation mechanism over wide frequency range. A prototype of 700 MHz to 2.5 GHz power amplifier is implemented in $0.25~\mu \text{m}$ PHEMT. It achieves an input and output return loss of less than −10 dB followed by flat power gain of 20 dB across the operating band, while sustaining an unconditional stability performance up to 20 GHz. With 1-dB compression point output power (P1dB) of 24.0 dBm, the PA delivers an OIP3 of more than 40 dBm with peak PAE of 66%. The fully integrated circuit consumes an area of 0.8 mm2. The proposed circuit serves to be a good solution to be integrated as a part of the wideband transmitter system for picocell application.
Differential Long-Chain Polyunsaturated Fatty Acids Status and Placental Transport in Adolescent Pregnancies

Adolescent pregnancy increases risk of adverse perinatal outcomes. Placental delivery of long-chain polyunsaturated fatty acids (LCPUFA) is essential for fetal growth and development. In this pilot study, we aimed to assess maternal and fetal status of fatty acids (FA) measured at birth and the expression of key genes involved in FA uptake, transport and metabolism in the placenta of fifteen adolescents and fifteen adults. FA were quantified by gas-liquid chromatography. Placental expression of FA transporters was assessed by quantitative real-time polymerase chain reaction (qRT-PCR) and peroxisome proliferator-activated receptor gamma (PPARγ) was quantified by Western Blot. Adolescents had lower docosahexaenoic acid (DHA, 22:6 n-3) and total n-3 FA levels in maternal erythrocytes and placenta, but these were not different in fetal erythrocytes. Arachidonic acid (AA, 20:4 n-6) concentration was increased in placenta but lower in fetal circulation. Plasma membrane fatty acid binding protein (FABPpm) and fatty acid transport protein (FATP) 4 mRNA expressions were not different, however FATP1, fatty acid translocase (FAT/CD36) and fatty acid binding protein 3 (FABP3) mRNA and PPARγ protein levels were decreased in placenta of adolescents. Despite significant downregulation of FATP1, CD36 and FABP3, there was only a modest decrease in LCPUFA (10%) and AA (12%) and no difference in DHA content in cord blood, suggesting that FA transfer to the fetus was partially protected by other factors in adolescents from this cohort.