Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of Tuberculosis Intensive Case Finding, Isoniazid Preventive Therapy, and Infection Control ("Three I's") and HIV-Tuberculosis Service Integration in Lower Income Countries

Setting World Health Organization advocates for integration of HIV-tuberculosis (TB) services and recommends intensive case finding (ICF), isoniazid preventive therapy (IPT), and infection control (“Three I’s”) for TB prevention and control among persons living with HIV. Objective To assess the implementation of the “Three I’s” of TB-control at HIV treatment sites in lower income countries. Design Survey conducted between March-July, 2012 at 47 sites in 26 countries: 6 (13%) Asia Pacific, 7 (15%), Caribbean, Central and South America, 5 (10%) Central Africa, 8 (17%) East Africa, 14 (30%) Southern Africa, and 7 (15%) West Africa. Results ICF using symptom-based screening was performed at 38% of sites; 45% of sites used symptom-screening plus additional diagnostics. IPT at enrollment or ART initiation was implemented in only 17% of sites, with 9% of sites providing IPT to tuberculin-skin-test positive patients. Infection control measures varied: 62% of sites separated smear-positive patients, and healthcare workers used masks at 57% of sites. Only 12 (26%) sites integrated HIV-TB services. Integration was not associated with implementation of TB prevention measures except for IPT provision at enrollment (42% integrated vs. 9% non-integrated; p = 0.03). Conclusions Implementation of TB screening, IPT provision, and infection control measures was low and variable across regional HIV treatment sites, regardless of integration status.
GSTP 1 Ile 105 Val and XRCC 1 Arg 399 Gln gene polymorphisms contribute to the clinical outcome of patients with advanced non-small cell lung cancer

Glutathione S-transferase P1 (GSTP1) and X-ray repair cross-complementing group 1 (XRCC1) genetic variations may influence the efficacy of chemotherapy in various cancers. We investigated the possible roles of GSTP1 Ile105Val and XRCC1 Arg194Trp, and Arg399Gln gene polymorphisms in the prognosis of advanced non-small cell lung carcinoma (NSCLC) patients with cisplatin-based chemotherapy. Between January 2010 and December 2012, this study consecutively recruited 141 patients with advanced NSCLC from the First People’s Hospital of Yunnan Province. Logistic regression analysis showed that individuals carrying the GG genotype were associated with a better response to chemotherapy than those with the wide-type genotype, with an adjusted odds ratio (95% confidence interval, CI) of 4.07 (1.06-25.06). Moreover, we observed that the AA genotype of
Effects of climate legacies on above‐ and belowground community assembly

The role of climatic legacies in regulating community assembly of above‐ and belowground species in terrestrial ecosystems remains largely unexplored and poorly understood. Here, we report on two separate regional and continental empirical studies, including >500 locations, aiming to identify the relative importance of climatic legacies (climatic anomaly over the last 20,000 years) compared to current climates in predicting the relative abundance of ecological clusters formed by species strongly co‐occurring within two independent above‐ and belowground networks. Climatic legacies explained a significant portion of the variation in the current community assembly of terrestrial ecosystems (up to 15.4%) that could not be accounted for by current climate, soil properties, and management. Changes in the relative abundance of ecological clusters linked to climatic legacies (e.g., past temperature) showed the potential to indirectly alter other clusters, suggesting cascading effects. Our work illustrates the role of climatic legacies in regulating ecosystem community assembly and provides further insights into possible winner and loser community assemblies under global change scenarios.
LinkScope: Toward Detecting Target Link Flooding Attacks

A new class of target link flooding attacks (LFAs) can cut off the Internet connections of a target area without being detected, because they employ legitimate flows to congest selected links. Although new mechanisms for defending against LFA have been proposed, the deployment issues limit their usage, since they require either additional modules to enhance routers or using the software-defined network to replace the traditional routers. In this paper, we propose a novel framework that employs both the end-to-end and hop-by-hop network measurement techniques to capture the abnormal path performance degradation for detecting LFA and then locate the target links or areas whenever possible, and develop a prototype of the framework named LinkScope. Although using network measurement to capture network anomaly is not new, we tackle a number of challenging issues, such as conducting large-scale Internet path monitoring via non-cooperative measurement so that users do not need to install LinkScope on every host, profiling the performance of asymmetric Internet paths and detecting LFA. The extensive evaluation in a testbed and the Internet shows that with limited bandwidth and computational overhead, LinkScope can achieve timely detection and diagnosis of LFA with high detection rate and low false positive rate.
Coupled systems of two-dimensional turbulence

Abstract Ordinary two-dimensional turbulence corresponds to a Hamiltonian dynamics that conserves energy and the vorticity on fluid particles. This paper considers coupled systems of two-dimensional turbulence with three distinct governing dynamics. One is a Hamiltonian dynamics that conserves the vorticity on fluid particles and a quantity analogous to the energy that causes the system members to develop a strong correlation in velocity. The other two dynamics considered are non-Hamiltonian. One conserves the vorticity on particles but has no conservation law analogous to energy conservation; the other conserves energy and enstrophy but it does not conserve the vorticity on fluid particles. The coupled Hamiltonian system behaves like two-dimensional turbulence, even to the extent of forming isolated coherent vortices. The other two dynamics behave very differently, but the behaviours of all four dynamics are accurately predicted by the methods of equilibrium statistical mechanics.
Fabrication of Circular Obelisk-Type Multilayer Microneedles Using Micro-Milling and Spray Deposition

In this study we present the fabrication of multilayer microneedles with circular obelisk and beveled-circular obelisk geometries, which have potential applications in implantable drug delivery devices. Micro-milling was adopted as an environmental-friendly and cost-effective way to fabricate primary metal microneedle masters. Polylactic acid (PLA) microneedles with sharp tips were then obtained by micromolding followed by oxygen plasma etching and used for preparing polydimethylsiloxane (PDMS) microneedle molds. A spray deposition process was employed for microneedle fabrication to facilitate the formation of multilayer microneedles while helping in maintenance of drug stability. Multilayer microneedles were successfully formed by sequential spraying of poly(lactic-co-glycolic acid) (PLGA) and polyvinylpyrrolidone (PVP) solutions into the mold. The fabricated PLGA-PVP multilayer microneedles penetrated the pig cadaver skin without breakage and released dyes in the skin at different rates, which reveals the potential for implantable microneedles enabling controlled release. Mechanical testing demonstrated that the obelisk-shaped microneedles were mechanically stronger than a pyramid-shaped microneedle and suggested that strong adhesion between PLGA and PVP layers was achieved as well. Structural stability and functionality of a model drug, horseradish peroxidase (HRP), upon spray deposition was examined using circular dichroism (CD) spectroscopy and enzyme activity assay. HRP retained its secondary structure and activity in PVP, whereas HRP in PLGA showed structural changes and reduced activity. Combination of micro-milling and spray deposition would be an attractive way of fabricating drug-containing polymer microneedles with various geometries while reducing prototyping time and process-induced drug instability.
Estimating the Fine-Grained PM2.5 for Airbox Sensor Fault Detection in Taiwan

Recently, PM2.5 becomes one critical threat for the health of human. To monitor the PM2.5, the Airbox project that consists of more than 2000 PM2.5 sensors is executing in Taiwan. Thanks to the Airbox sensors, people can know the fine-grained air quality. However, Airbox sensors can fail and it is important to detect which sensor is failed to prevent the noise in the data. In this work, we focus on fault detection and value estimation for PM2.5 monitoring. To achieve our goal, we utilize the data from Environmental Protection Administration(EPA) for estimation. We firstly propose two estimation methods which consider the distance and similarity between the Airbox sensors and EPA monitoring stations for PM2.5 estimation. Then based on the estimation result, we detect which sensors is failed. We collect the data from Airbox Edimax web page and Taiwan's Environmental Protection Administration for our experiment. The experiment results reveal the good performance of our proposed methods.
Genital mycoplasmas and ureaplasmas in cervicovaginal self-collected samples of reproductive-age women: prevalence and risk factors

The purpose of this study was to characterise the prevalence and risk factors associated with genital mycoplasmas (Mycoplasma hominis [MH], M. genitalium [MG]) and ureaplasmas (Ureaplasma urealyticum [UU], U. parvum [UP]) in Portuguese women of reproductive age. The cross-sectional study included 612 cervicovaginal self-collected samples from women aged 15–44 years, tested for MH, MG, UU, UP by polymerase chain reaction. Y chromosome (Yc) DNA was detected as a biomarker of recent unprotected sexual intercourse. The prevalences of UU, UP, MH and MG were 28.4% (95% confidence interval [CI] 25.0–32.1), 22.4% (95% CI 19.3–25.9), 8.5% (95% CI 6.5–11.0) and 0.8% (95% CI 0.4–1.9), respectively. Overall, women aged 20–29 years (odds ratio [OR] 1.78; P = 0.010) and the presence of Yc-DNA (OR 2.33; P = 0.038) were associated with an increased risk of UU. Lifetime number of sexual partners was a predictor of UU, UP and MH (OR 2.46; P < 0.001, OR 2.78; P < 0.001 and OR 1.55; P < 0.001, respectively, for more than one versus one partner). The prevalence of MG was low, while UU, UP and MH were common in Portuguese women of reproductive age. The presence of UU, UP and MH was associated with sexual activity (number of sexual partners), although the consequences of its prevalence are not fully understood and should be further investigated.
An 8-11GHz low phase noise ring voltage controlled oscillator

This paper presents a low phase noise ring voltage controlled oscillator (ring VCO) based on two differential delay cells with cross-coupled MOSFET pair which provide proper initial condition and sustain oscillating. The phase noise of VCO has been improved by using MOSFETs working in linear region as voltage controlled devices instead of working in saturation region (current source). Besides, the cross-coupled pMOS pairs was adopted instead inverters to save power. The VCO was designed in SMIC 40nm CMOS technology, covering a wide tuning range of 8-11GHz under the 1.1V supply. The VCO's phase noise is - 86.2dBc/Hz@1MHz at 10GHz with 8.2mW power consumption.
Vertical Writes: Closing the Throughput Gap between Deeply Scaled STT-MRAM and DRAM

STT-MRAM is a second generation MRAM technology that addresses many of the scaling problems of earlier generation magnetic RAMs, and is a promising candidate to replace DRAM due to its high operational speed, scalable energy characteristics, and high write endurance. However, making the density of STT-MRAM competitive with that of DRAM while maintaining DRAM-like write throughput has proven challenging. Reducing the area of an STT-MRAM cell requires decreasing the width of the cell access transistor, which lowers the magnitude of the switching current supplied to the storage element during writes, and significantly hampers the switching speed. Consequently, write throughput constitutes a fundamental performance bottleneck for memory systems built from deeply scaled, dense STT-MRAM cells. This paper introduces vertical writes, a new technique that improves the write throughput of memory systems built from high-density STT-MRAM. Vertical writes exploit the observation that once the switching voltage has been applied across the bitlines and and sourcelines in an STT-MRAM array, it is possible to initiate the write operation for additional cells that are attached to the same column by simply turning on the corresponding wordlines. By leveraging the ability to write a 0 or a 1 to multiple cells at once, vertical writes improve average system performance by 21 percent, and enable an STT-MRAM based system to come within 5 percent of the performance of a DRAM based system.
Expected Likelihood: Not a Good Metric for Gaussian Embeddings

The success of neural network methods in Natural Language Processing (NLP) tasks is fairly related to the widely use of word embeddings in which a word is represented as a point in a vector space. Previous research has shown that high quality word embeddings can improve the performance of NLP models. Since natural language is intrinsically ambiguous, different senses of a word should be in different positions of the vector space. So that representing a word as a single point in the vector space is problematic. Some recent work proposed to use Gaussian distributions to represent a word which is named Gaussian embeddings. This idea is very natural and proved to be useful in tasks like word similarity and word entailment. However, Gaussian embeddings are very difficult to train, especially for the commonly used loss function based on Expected Likelihood (EL). In this paper, we study the training process of Gaussian embeddings based on EL. Supported by our experimental results, we find that EL is not suitable for training Gaussian embeddings. Besides, we propose an effective algorithm to train Gaussian embeddings and improve the performance on word similarity tasks.
Multiple Imputation for Multilevel Data with Continuous and Binary Variables

We present and compare multiple imputation methods for multilevel continuous and binary data where variables are systematically and sporadically missing. The methods are compared from a theoretical point of view and through an extensive simulation study motivated by a real dataset comprising multiple studies. The comparisons show that these multiple imputation methods are the most appropriate to handle missing values in a multilevel setting and why their relative performances can vary according to the missing data pattern, the multilevel structure and the type of missing variables. This study shows that valid inferences can only be obtained if the dataset includes a large number of clusters. In addition, it highlights that heteroscedastic multiple imputation methods provide more accurate inferences than homoscedastic methods, which should be reserved for data with few individuals per cluster. Finally, guidelines are given to choose the most suitable multiple imputation method according to the structure of the data.
Finite-size effects in a mean-field kinetically constrained model: dynamical glassiness and quantum criticality

On the example of a mean-field Fredrickson–Andersen kinetically constrained model, we focus on the known property that equilibrium dynamics take place at a first-order dynamical phase transition point in the space of time realizations. We investigate the finite-size properties of this first-order transition. By discussing and exploiting a mapping of the classical dynamical transition—an argued glassiness signature—to a first-order quantum transition, we show that the quantum analogy can be exploited to extract finite-size properties, which in many respects are similar to those in genuine mean-field quantum systems with a first-order transition. We fully characterize the finite-size properties of the order parameter across the first-order transition.
The Impact of Social Support Networks on Maternal Employment: A Comparison of West German, East German and Migrant Mothers of Pre-School Children

Given shortages in public child care in Germany, this paper asks whether social support with child care and domestic work by spouses, kin and friends can facilitate mothers’ return to full-time or part-time positions within the first six years after birth. Using SOEP data from 1993-2009 and event history analyses for competing risks, the author compares the employment transitions of West German, East German and migrant mothers of pre-school children. The results indicate that West German and migrant mothers return to work sooner if they have access to kin, and that kinship support is particularly important when public child care is unavailable. Furthermore, West German and migrant mothers are more likely to work full-time if their spouses partipate in domestic work. In contrast, social support does not affect employment transitions in East Germany where public child care is more easily accessible and continuous female employment is a prevalent social norm.
Optimization frequency design of eddy current testing

The purposes of this research were to construct the nondestructive metal testing intrument by using eddy current method and to find an optimal frequency for the metal testing intrument. The testing intrument consist of a sine wave oscillator circuit which can adjust the frequency between 20 - 90 kHz, and a 50 ohms sensor circuit. There are three kinds of testing intrument. The first was the nondestructive imperfection testing by using eddy current method. The sample irons are constructed with different imperfection on surface. The output signals of testing from the sensor circuit are compared. The second was the nondestructive categorization metal testing by using eddy current method. Many kinds of metals are taken to testing. The last one was the nondestructive testing for finding the thickness of films on iron by using eddy current method. In this testing the thickness of films varied between 100 - 700 microns. In all testing, differences of the signal testing were compared to analyze the optimal frequency for the testing intrument. The results of research showed that the nondestructive metal testing intrument by using eddy current method can be used to find a different imperfective iron, categorize the metal and find thickness of films. In addition, the range of an optimal frequency is 30 kHz to 70 kHz for testing intrument.
Functional Data Analysis

With the advance of modern technology, more and more data are being recorded continuously during a time interval or intermittently at several discrete time points. These are both examples of functional data, which has become a commonly encountered type of data. Functional data analysis (FDA) encompasses the statistical methodology for such data. Broadly interpreted, FDA deals with the analysis and theory of data that are in the form of functions. This paper provides an overview of FDA, starting with simple statistical notions such as mean and covariance functions, then covering some core techniques, the most popular of which is functional principal component analysis (FPCA). FPCA is an important dimension reduction tool, and in sparse data situations it can be used to impute functional data that are sparsely observed. Other dimension reduction approaches are also discussed. In addition, we review another core technique, functional linear regression, as well as clustering and classification of functional d.
Legume Proportion, Poultry Litter, and Tillage Effects on Cover Crop Decomposition

Cover crop residues and animal waste products can be important sources of N in cropping systems. The objectives of this research were to determine, under field conditions, the effects of hairy vetch (legume; Vicia villosa Roth)/cereal rye (grass; Secale cereale L.) proportion and pelletized poultry litter (PPL) management (no PPL, subsurface banded, broadcast, or incorporated with tillage) on the extent and rate of cover crop residue mass loss and N release during a subsequent growing season. Measuring cover crop residues placed in mesh litter bags, or residues+PPL in litter bags for the broadcast treatment, we found that increasing hairy vetch proportion led to greater proportional mass loss and N release (cumulative mass loss ranged from 40 to 80% and N release ranged from 0–90% of initial), as well as greater rates of mass loss in all PPL treatments. Nitrogen release rates were generally unaffected by species proportions; however, N release rates for pure cereal rye residue in all PPL treatments except broadcast could not be estimated due to minimal N release. Incorporation of residues and PPL increased the rates of mass loss and N release for pure hairy vetch and hairy vetch–cereal rye mixtures. Although broadcast PPL application and incorporation affected decomposition patterns, subsurface banded PPL application did not. Results suggest that cereal rye provides the greatest mulch persistence, hairy vetch provides the greatest N release, and mixtures provide moderate delivery of these two services. Subsurface banding is the recommended PPL application method to conserve surface residues.
Simulative verification of channel reciprocity in free-space optical inter-HAP links

Channel reciprocity in a bidirectional turbulent channel implies that the received powers are correlated to a certain extent at both link ends. In this paper, we investigate by numerical phase-screen propagation simulation the variation of the channel correlation under various boundary conditions, namely orthogonal wind speed, link distance, receiver aperture and turbulence-strength profile for inter High Altitude Platform (HAP) FSO links. Finally, we provide an outlook to different Error Control Coding (ECC) methods that make use of the reciprocity effect.
A Survey of Decision-Theoretic Models for Cognitive Internet of Things (CIoT)

Communication technology and wide spread usage of Internet of Things (IoT) are rapidly becoming the core enabler for consumers to use their smart devices in their daily routine. These smart devices are gradually transforming the IoT scenario into a new paradigm called cognitive Internet of Things (CIoT). We believe that CIoT will revolutionize many service sectors including smart cities, transportation, health-care, and environmental monitoring. The current development in CIoT is still elusive as it has to achieve effective interoperability and autonomous decision making. Most importantly, the decision theoretic models are seen as an enabler to achieve effective interoperability among heterogeneous CIoT objects. In this paper, we provide a survey of the existing decision theoretic models and their usage for CIoT, an architectural CIoT framework is also proposed to discuss the open issues and solution for potential challenges emerging in the area of CIoT research.
Haplotype-aware graph indexes

Motivation The variation graph toolkit (VG) represents genetic variation as a graph. Although each path in the graph is a potential haplotype, most paths are nonbiological, unlikely recombinations of true haplotypes. Results We augment the VG model with haplotype information to identify which paths are more likely to exist in nature. For this purpose, we develop a scalable implementation of the graph extension of the positional Burrows–Wheeler transform (GBWT). We demonstrate the scalability of the new implementation by building a whole-genome index of the 5,008 haplotypes of the 1000 Genomes Project, and an index of all 108,070 TOPMed Freeze 5 chromosome 17 haplotypes. We also develop an algorithm for simplifying variation graphs for k-mer indexing without losing any k-mers in the haplotypes. Availability Our software is available at https://github.com/vgteam/vg, https://github.com/jltsiren/gbwt, and https://github.com/jltsiren/gcsa2. Contact jouni.siren@iki.fi Supplementary information Supplementary data are available.