Miracle-dz/UniFAR-FTUs huggingface dataset:
Phylogenetic approach to recover integration dates of latent HIV sequences within-host

Significance Studies characterizing within-host latent HIV sequence diversity have yielded insight into reservoir dynamics and persistence. Our understanding of these processes, however, can be further enhanced if reservoir diversity is interpreted in context of HIV’s within-host evolutionary history. Approaches to infer the original establishment (i.e., integration) dates of individual within-host latent HIV lineages would be particularly useful in this regard. We describe a phylogenetic framework to infer latent HIV ages from viral sequence information and apply it to latent HIV sequences sampled up to 10 y on suppressive therapy to yield insights into HIV reservoir dynamics. The ability to infer within-host latent HIV ages from sequence information has broad potential applications that may advance us toward an HIV cure. Given that HIV evolution and latent reservoir establishment occur continually within-host, and that latently infected cells can persist long-term, the HIV reservoir should comprise a genetically heterogeneous archive recapitulating within-host HIV evolution. However, this has yet to be conclusively demonstrated, in part due to the challenges of reconstructing within-host reservoir establishment dynamics over long timescales. We developed a phylogenetic framework to reconstruct the integration dates of individual latent HIV lineages. The framework first involves inference and rooting of a maximum-likelihood phylogeny relating plasma HIV RNA sequences serially sampled before the initiation of suppressive antiretroviral therapy, along with putative latent sequences sampled thereafter. A linear model relating root-to-tip distances of plasma HIV RNA sequences to their sampling dates is used to convert root-to-tip distances of putative latent lineages to their establishment (integration) dates. Reconstruction of the ages of putative latent sequences sampled from chronically HIV-infected individuals up to 10 y following initiation of suppressive therapy revealed a genetically heterogeneous reservoir that recapitulated HIV’s within-host evolutionary history. Reservoir sequences were interspersed throughout multiple within-host lineages, with the oldest dating to >20 y before sampling; historic genetic bottleneck events were also recorded therein. Notably, plasma HIV RNA sequences isolated from a viremia blip in an individual receiving otherwise suppressive therapy were highly genetically diverse and spanned a 20-y age range, suggestive of spontaneous in vivo HIV reactivation from a large latently infected cell pool. Our framework for reservoir dating provides a potentially powerful addition to the HIV persistence research toolkit.
An Investigation Into the Impact of Band Error Variance Estimation on Intrinsic Dimension Estimation in Hyperspectral Images

There have been a significant number of recent papers about hyperspectral imaging, which propose various methods for estimating the number of materials/endmembers in hyperspectral images. This is sometimes called the “intrinsic” dimension (ID) of the image. Estimation of the error variance in each spectral band is a critical first step in ID estimation. The estimated error variances can then be used to preprocess (e.g., whiten) the data, prior to ID estimation. A range of variance estimation methods have been advocated in the literature. We investigate the impact of five variance estimation methods (three using spatial information and two using spectral information) on five ID estimation methods, with the aid of four different, but semirealistic, sets of simulated hyperspectral images. Our findings are as follows: first, for all four sets, the two spectral variance estimation methods significantly outperform the three spatial methods; second, when used with the spectral variance estimation methods, two of the ID estimation methods (called random matrix theory and NWHFC) consistently outperform the other three ID estimation methods; third, the better spectral variance estimation method sometimes gives negative variance estimates; fourth, we introduce a simple correction that guarantees positivity; and fifth, we give a fast algorithm for its computation.
Relationship of food insecurity to women’s dietary outcomes: a systematic review

Abstract Context Food insecurity matters for women’s nutrition and health. Objective This review sought to comprehensively evaluate how food insecurity relates to a full range of dietary outcomes (food groups, total energy, macronutrients, micronutrients, and overall dietary quality) among adult women living in Canada and the United States. Data sources Peer-reviewed databases (PubMed/MEDLINE, CINAHL, Scopus, Web of Science) and gray literature sources from 1995 to 2016 were searched. Data extraction Observational studies were used to calculate a percentage difference in dietary intake for food-insecure and food-secure groups. Results Of the 24 included studies, the majority found food-insecure women had lower food group frequencies (dairy, total fruits and vegetables, total grains, and meats/meat alternatives) and intakes of macro- and micronutrients relative to food-secure women. Methodological quality varied. Among high-quality studies, food insecurity was negatively associated with dairy, fruits and vegetables, grains, meats/meats alternatives, protein, total fat, calcium, iron, magnesium, vitamins A and C, and folate. Conclusions Results hold practical relevance for selecting nutritional targets in programs, particularly for nutrient-rich foods with iron and folate, which are more important for women’s health.
ARIA: Air Pollutants Monitoring Using UAVs

UAV technology, and specifically networks and swarms, have been an open research topic for many years. This is because of their potentially huge benefits at an affordable cost in a wide range of tasks. UAVs are commonly used in public and private fields. Their usefulness still comes with a price and some serious limitations, not completely surpassed yet. There are many proposals for protocols and algorithms trying to improve drone swarms but they are massively dependent on the actual scenarios and use cases. UAVs can fill a gap in modern Wireless Sensor Network, mostly because of their mobility and ability to fly at different heights. While drone swarms are prolific research topics, there is almost no interest investigating benefits of vertical deployment of this technology. It is proven that air pollution changes abruptly even at relatively short distances, both horizontally and vertically. We aim to provide a new tool to study air quality at different heights that even private citizens could afford. We will present an overview of ARIA project, a vertical drone swarm for air pollution monitoring. Considering the scope of our project, we will only utilize low-cost UAVs and sensors. Knowing the hard challenges inherent to UAVs and environmental monitoring, we're looking at preliminary results but we think this will become a valuable proof-of-concept for further research.
Delay Compensation for a Telepresence System With 3D 360 Degree Vision Based on Deep Head Motion Prediction and Dynamic FoV Adaptation

The usability of telepresence applications is strongly affected by the communication delay between the user and the remote system. Special attention needs to be paid in case the distant scene is experienced by means of a Head Mounted Display. A high motion-to-photon latency, which describes the time needed to fully reflect the user's motion on the display, results in a poor feeling of presence. Further consequences involve unbearable motion sickness, indisposition, and termination of the telepresence session in the worst case. In this letter, we present our low-cost MAVI telepresence system, which is equipped with a stereoscopic 360° vision system and high-payload manipulation capabilities. Special emphasis is placed on the stereoscopic vision system and its delay compensation. More specifically, we propose velocity-based dynamic field-of-view adaptation techniques to decrease the emergence of simulator sickness and to improve the achievable level of delay compensation. The proposed delay compensation approach relies on deep learning to predict the prospective head motion. We use our previously described head motion dataset for training, validation, and testing. To prove the general validity of our approach, we perform cross validation with another independent dataset. We use both qualitative measures and subjective experiments for evaluation. Our results show that the proposed approach is able to achieve mean compensation rates of around 99.9% for latencies between 0.1 and 0.5 s.
Design of a Class of Filtering Couplers With Reconfigurable Frequency

This paper reports on, for the first time, the design of filtering couplers with reconfigurable frequency. The reconfigurable filtering transmission lines (RFTLs) with 90° or −90° phase shift are first designed, and then the reconfigurable filtering couplers are constructed by substituting the basic unit of quarter-wavelength (<inline-formula> <tex-math notation="LaTeX">$\lambda/4$ </tex-math></inline-formula>) transmission line in the conventional couplers with the proposed RFTL. The tunable capacitor loaded half-wavelength (<inline-formula> <tex-math notation="LaTeX">$\lambda/2$ </tex-math></inline-formula>) resonators are used to tune the center frequency of RFTL. By properly controlling the electric or magnetic coupling between the resonators, the phase shift of 90° or −90° of the RFTLs can be realized, respectively, while maintaining a near constant bandwidth. The external coupling along with a pair of transmission zeros is achieved by asymmetric tap feeding of the RFTLs. For verification, a class of frequency-reconfigurable filtering couplers is designed and fabricated. First, a reconfigurable filtering rat-race coupler is designed and fabricated. The measured center frequency is tuned from 700 to 1840 MHz while maintaining a 3-dB fractional bandwidth of 13% ± 0.5%/13.7% ± 0.6%, insertion loss of 8.1–6.9/8.3–5.9 dB, return loss of better than 13 dB, and isolation of better than 21 dB. Second, a reconfigurable filtering quadrature coupler is designed and fabricated. The measured center frequency is tuned from 947 to 1775 MHz while maintaining a 1-dB bandwidth of 75 ± 5/65 ± 10 MHz, insertion loss of 8.3–6.9/8.3–7.1 dB, return loss of better than 14 dB, and isolation of better than 14 dB.
Enabling Data Legitimacy in Data-Driven Projects

In the last decade, Science has been faced with an enormous amount of data from a wide range of sources, such as the Internet, social media, IoT devices, and so on. Increasingly it is essential to develop methods and tools that enable the most varied forms of understanding of the data and transformation processes involved in an experiment. The veracity dimension plays an essential role in meeting these needs, and it must be incorporated into a data management process. This paper presents a proposal of an architecture model for a Data Portal that provides users the ability of assessment of the legitimacy of datasets. Legitimacy consists of the communication of decisions in the construction of computational models and the provenance of the data. We present the proposed architecture and how it can be embedded in scientific data portals.
Narrow-Linewidth Microwave Generation by Optoelectronic Oscillators With AlGaInAs/InP Microcavity Lasers

The optoelectronic oscillators (OEOs) based on a 1.55-μm direct-modulated AlGaInAs/InP square microcavity laser without optical injection are demonstrated for narrow-linewidth photonic microwave signal generation. The square microcavity laser with a side length of 16 μm under an injection current of 14 mA is used in the experiment. High-quality photonic microwave signals with 3-dB linewidths around 30 Hz are obtained by the first harmonics of the single-loop and dual-loop OEOs. Single-sideband phase noise at 10 kHz frequency offset is as low as −116 dBc/Hz for the microwave signal. With the dual-loop OEO, the side-mode suppression ratios up to 55 dB are obtained for the first harmonics, and tunable microwave signals from 1.85 to 10.24 GHz are realized with narrow linewidths and low-phase noises.
TDHQ Enabling Fine-Granularity Adaptive Loading for SSB-DMT Systems

In this letter, we introduce time domain hybrid quadrature amplitude modulation (TDHQ) for the single sideband discrete multi-tone systems. The experimental results reveal that with a single precoding set and the proposed adaptive loading algorithm, the TDHQ scheme can achieve finer granularity and therefore smoother continuous growth of data rate than that with the conventional quadrature amplitude modulation. Besides, thanks to the frame construction and the tailored mapping rule, the scheme with TDHQ has an obviously better peak to an average power ratio.
I Like Your Tagged Photos, But Do We Know Each Other?: Analyzing the Role of Tags in Like Networks

With the development of smart devices and the popularization of social media, communication between users is becoming increasingly active in the online space, revitalizing a new relationships formed and developed. Individuals are connecting with various people, which makes many companies actively employ social media to communicate with existing and potential customers for marketing. While social networks comprise a mix of various activities such as liking, commenting, tagging, and following, little is known about the way in which liking and tagging characterize one's social networks. In this paper, we define two types of a like network: tag-based like network, non-tag-based like network and present a comparative analysis with regard to their structural and temporal aspects. Our study results show (1) a significant difference in the network size and the degree of components between the two networks and (2) the potential of the tag-based like network to have more followers than the non-tag-based like network. We highlight how the tag-based like network can be utilized to find users with the same interests, supporting additional, interest based social connection and interaction. Our study insights are expected to be developed and utilized as a web service system.
An Efficient Resource Scheduling Algorithm using Dynamic Priority in Grid Computing

Grid Computing is a dynamic, heterogeneous environment. Scheduling is the heart of Grid computing. There are two Basic categories of scheduling in Grid: Resource Scheduling and Job Scheduling. Resources can be selected as per user demand and on the basis of specific scheduling algorithm. User can submit their jobs in Grid and these jobs are allocated to the resources according to the selected algorithm. In Priority based Scheduling algorithm, Priority of jobs are basic concern. In this paper we provide the flexibility in priority of jobs in specific condition. So the Utilization of resources is high as in some specific situation lowest priority jobs can be allocated before to higher priority jobs to available resources without waiting its priority order. Because of this flexibility, proposed algorithm dramatically reduces the processing cost.
Blur-Countering Keypoint Detection via Eigenvalue Asymmetry

Well-known corner or local extrema feature based detectors such as FAST and DoG have achieved noticeable successes. However, detecting keypoints in the presence of blur has remained to be an unresolved issue. As a matter of fact, various kinds of blur (e.g., motion blur, out-of-focus and space-variant) remarkably increase challenges for keypoint detection. As a result, those methods have limited performance. To settle this issue, we propose a blur-countering method for detecting valid keypoints for various types and degrees of blurred images. Specifically, we first present a distance metric for derivative distributions, which preserves the distinctiveness of patch pairs well under blur. We then model the asymmetry by utilizing the difference of squared eigenvalues based on the distance metric. To make it scale-robust, we also extend it to scale space. The proposed detector is efficient as the main computational cost is the square of derivatives at each pixel. Extensive visual and quantitative results show that our method outperforms current approaches under different types and degrees of blur. Without any parallelization, our implementation achieves real-time performance for low-resolution images (e.g., $320\times 240$ pixel).
Length Dependent Surface Enhanced Raman Scattering Obtained from Copper nanorod array substrates*

The length dependence of surface enhanced Raman scattering has been investigated in Copper nanorod array substrates fabricated using an oblique angle deposition technique in this paper. The surface enhanced Raman scattering intensity of trans-l,2-bis(4-pyridyl) ethene was found to be proportional to the length of the nanorod.
Determinants of health-related quality of life in a multinational systemic sclerosis inception cohort.

OBJECTIVES To evaluate health-related quality of life (HRQoL) and its determinants in a systemic sclerosis (SSc) multinational inception cohort. We performed a meta-analysis of data from individual countries, and compared the meta-analysis to individual country results by pooling data from each of the countries. METHODS SSc patients within 2 years of disease onset were recruited from 5 countries participating in the International Systemic Sclerosis Inception Cohort (INSYNC). Data from each country's database were exported for analysis using a harmonised platform. HRQoL was assessed using the Medical Outcomes Short Form-36 (SF-36). Multivariate linear regression assessed associations between HRQoL and predictors in cohorts separately and meta-analyzed to generate pooled estimates. The analyses were repeated using individual patient data. RESULTS Of the 637 SSc patients recruited, the majority was female (80.2%-83.3%), aged between 52.4-56.7 years with limited cutaneous disease subtype (48.6%-66.7%). HRQoL scores were lower for SSc patients than the general population (SF-36 physical component summary (PCS) score (36.4-39.6), mental component summary (MCS) score (41.0-46.4)). Determinants of SF-36 PCS by meta-analysis included increasing age (β=-0.1, 95%CI -0.2, -0.01), diffuse cutaneous disease subtype (β=-8.4, 95%CI -10.6, -6.3), and pulmonary arterial hypertension (β=-10.9, 95%CI -16.6, -5.3). Increasing age (β=0.09, 95%CI 0.0, 0.18) was the only variable associated with SF-36 MCS. Analyses using individual patient data revealed similar results to those of the meta-analysis of cohort data. CONCLUSIONS Our study provides estimates of HRQoL in a large inception SSc cohort and provides evidence that individual patient data analysis is valid in the INSYNC dataset.
An Exoskeleton Type 4-DOF Force Feedback Device Using Magnetorheological Fluid Clutches and Artificial Muscles

Recently, virtual reality (VR) technology has been developed using a head mounted displays (HMD). Users can recognize virtual objects easily in a VR space. However, users cannot obtain haptic perception, such as operating actual objects. There are force feedback devices that can render its perception. General devices are desktop types which restrict the range of motion (ROM) of operators, whereas exoskeleton types achieve ROM like a human. Many force feedback devices using motors and decelerators lead to a loss of backdrivability and can harm the operator by active force. Therefore, we developed an exoskeleton type four degrees of freedom (DOF) force feedback device for the upper limb with magnetorheological fluid clutches and artificial muscles that are backdrivable and safe actuators; we confirmed that the proposed device can render an elastic force.
Predicting the Unemployment Rate Using Social Media Analysis

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.
Soft simple Compact Valve Inducing Self-excited Vibration Aimed for Mobile Robots Unnecessary for Electricity

This paper presents a novel valve for switching the pressure modes of to chambers by self-excited vibration instead of using electricity. The valve has a simple structure consisting of flexible tubes and small permanent magnets, which can be fabricated with compact size, lightweight and at low cost. When constant air pressure is applied to the input port of the valve, the magnet vibrates self-excitedly and two chambers which are connected to the output ports are alternately pressurized at the same frequency as the vibration. We present the principle of the valve and the modeling of the switching operation. Several switching experiments using a prototype valve were performed to show the characteristics of the proposed valve. Finally, the validity of our proposing method is verified by implementing it on a pneumatic mobile robot and realizing the line- free propulsion without electricity.
Gender Equality in Software Engineering

This is the collected work of four female software engineers and myself. Their writing describes their lived experiences in software engineering and as mothers of children in school, while my own describes my lived experience of teaching computing to my children and their peers in school, and in clubs and community events outside of school. The four female engineers, who had the bandwidth to write at this time, include different levels of seniority and experience; an engineer who has come to software engineering late, after a non-computing education; and software engineers who have taken up leadership roles in project management. The views I express are based on my independent research as part of my self-funded PhD in Educational Research with the University of Cumbria. The author of the paper is identifiable as the male engineer, while the writing of the four female engineers is presented anonymously.
Low-Cost Series-Fed Microstrip Antenna Arrays With Extremely Low Sidelobe Levels

This paper presents a new method of designing and implementing low-cost series-fed microstrip antenna arrays with low sidelobe levels by applying standard single-layer PCB technology. The method is based on the Z-parameter characteristics obtained from the electromagnetic full-wave simulation of the array elements by using a two-port network model. Two types of antenna arrays are designed and presented with the use of the proposed method. The first type is a uniform linear array with sidelobe level of 24.2 dB at the 24.125 GHz frequency band. The second type is a nonuniform linear array that provides at least 50% more physical space between the central patches to be used in 2-D arrays; this antenna has sidelobe level of 25 dB at 24.125 GHz. Both antennas achieve an excellent performance in the entire bandwidth of 250 MHz.