Miracle-dz/UniFAR-FTUs huggingface dataset:
Contraceptive use dynamics in Pakistan 2008-09

ii The Population Council, an international, non-profit, non-governmental organization established in 1952, seeks to improve the well-being and reproductive health of current and future generations around the world and to help achieve a humane, equitable, and sustainable balance between people and resources. The Council analyzes population issues and trends; conducts research in the reproductive sciences; develops new contraceptives; works with public and private agencies to improve the quality and outreach of family planning and reproductive health services; helps governments design and implement effective population policies; communicates the results of research in the population field to diverse audiences; and helps strengthen professional resources in developing countries through collaborative research and programs, technical exchange, awards, and fellowships. The Population Council reserves all rights of ownership of this document. No part of this publication may be reproduced, stored or transmitted in any form by any means-electronic, photocopying, recording or otherwise-without the permission of the Population Council. Disclaimer " This study/report is made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of the Population Council, Islamabad and do not necessarily reflect the views of USAID or the United States Government. " iii Table 2.2: Knowledge, ever-use and current use of contraceptive methods among currently married women of reproductive age by method and comparison with 2006
Exploiting the Spatio-Temporal Patterns in IoT Data to Establish a Dynamic Ensemble of Distributed Learners

Internet of Things applications can greatly benefit from accurate prediction models. The performance of prediction models is highly dependent on the quantity and quality of their training data. In this paper, we investigate the creation of a dynamic ensemble from distributed deep learning models by considering the spatiotemporal patterns embedded in the training data. Our dynamic ensemble does not depend on offline configurations. Instead, it exploits the spatiotemporal patterns embedded in the training data to generate dynamic weights for the underlying weak distributed deep learners to create a stronger learner. Our evaluation experiments using three real-world datasets in the context of the smart city show that our proposed dynamic ensemble strategy leads to an improved error rate of up to 33% compared to the baseline strategy even when using $\frac {1}{3}$ of the training data. Moreover, using only 20% of the training data, the error rate of the model slightly increased by up to 2 in terms of mean square error. This increase is 82% less than the 11.3 increase seen in the baseline model. Therefore, our approach contributes to the reduced network traffic while not hindering the accuracy significantly.
Efficient global redundant configuration resolution via sub-energy tunneling and terminal repelling

A method for the global configuration resolution for kinematically redundant manipulators is presented. This method is based on an efficient global optimization algorithm which uses a sub-energy tunneling function and terminal repellers. This optimization algorithm is reviewed, and its specialization to redundancy resolution is developed. Applications of this method and comparisons to null-space projection are presented. <<ETX>>
Towards More Graceful Interaction: A Survey of Question-Answering Programs

One of the aims of Natural Language Processing (NLP) is to facilitate the use of computers by allowing users to interact with systems in natural language. Since such interactions often take the form of question-answering sessions, the process of question-answering is an important part of NLP. In this paper, we are concerned with the progress made towards building question-answering systems which are natural and satisfying to users, allowing them to express themselves freely and answering questions appropriately. Such systems are said to provide graceful interaction. We survey the evolution of question-answering programs, presenting steps and approaches that have been taken towards providing graceful man-machine interaction, and pointing out efficiencies of existing programs and theories. Our emphasis is on the various issues and difficulties encountered in building a user-friendly question-answering program.
Genomic insights into the metabolism of ‘Candidatus Defluviicoccus seviourii’, a member of Defluviicoccus cluster III abundant in industrial activated sludge

&NA; Filamentous cluster III Defluviicoccus (DF3) are known to proliferate and cause bulking issues in industrial wastewater treatment plants. Members of the genus Defluviicoccus are also known to exhibit the glycogen accumulating organism (GAO) phenotype, which is suggested to be detrimental to enhanced biological phosphorus removal (EBPR). Despite the reported negative impact members of the DF3 have on activated sludge wastewater treatment systems, limited research has focused on understanding the physiological traits that allow them to compete in these environments. In this study, a near complete genome of an abundant filamentous DF3 named ‘Candidatus Defluviicoccus seviourii’ was obtained from a full‐scale sequencing batch reactor (SBR) treating winery wastewater. Annotation of the ‘Ca. D. seviourii’ genome revealed interesting metabolic features that help to understand the abundance of this microorganism in industrial wastewater treatment plants. Their potential for the storage of polyhydroxyalkanoates (PHA) is suggested to favour these organisms with the intermittent availability of carbon in these systems. An ability to fix nitrogen and take up urea may provide them with an additional advantage with the characteristically high carbon to nitrogen content of industrial waste. The genome and preliminary findings of this study provide a foundation for further research into these biotechnologically relevant organisms. &NA; Graphical Abstract Figure. Genomic insights into the Defluviicoccus cluster III.
Space-efficient terrain rendering using constrained Delaunay triangulation

Proposes a new terrain visualization technique associated with the conversion process from a contour-based data model to a triangulated irregular network (TIN) model. The main research related to processing these contour lines had been focused on interpolation methods to create the digital terrain model (DTM). We introduce a novel approach for visualizing terrain by using contour line data which are obtained from the digital elevation model (DEM). Our approach uses the marching square algorithm to extract contour lines from the DEM and classify contours into open contours and closed contours to calculate local minimum/maximum points. To minimize the search space for calculating local minimum/maximum, we construct the containment tree of the closed contour. Then we only achieve an approximation procedure for calculating minimum/maximum points at leaf nodes in the containment tree. Finally, we can easily reconstruct the terrain by performing constrained Delaunay triangulation that uses approximation points and contour data as inputs. In the experiments, we compare our algorithm with DEM processing in terms of the processing speed and data size.
Influenza: annual seasonal severity

Purpose of review Influenza remains a major cause of morbidity and mortality. The 2017–2018 season was one of the most severe in the past decade. The exact factors determining the severity of a particular influenza season are complex and often poorly understood. Recent findings Factors impacting annual influenza severity include characteristics of the specific virus, influenza vaccination, and antiviral use. Although viral virulence factors are important in this context and our knowledge of these is growing, there is a complex interplay between expression of these factors and their impact on a particular patient population. Vaccination has demonstrated efficacy in preventing disease, but vaccination rates remain sub-optimal and vaccine effectiveness can vary significantly between influenza strains and patient populations. Finally, while antiviral treatment is available and has shown benefits, many patients with influenza do not receive treatment. Summary Strides have been made in recent years towards understanding the many factors that contribute to the severity of any particular influenza season. Obvious areas for improvement include improved vaccination rates and antiviral use. Additionally, a more complete understanding of reasons for poor strain and population-specific vaccine effectiveness may help reduce the severity of future influenza seasons.
The Emerging Role of Altered Cerebellar Synaptic Processing in Alzheimer’s Disease

The role of the cerebellum in Alzheimer’s disease (AD) has been neglected for a long time. Recent studies carried out using transgenic mouse models have demonstrated that amyloid-β (Aβ) is deposited in the cerebellum and affects synaptic transmission and plasticity, sometimes before plaque formation. A wide variability of motor phenotype has been observed in the different murine models of AD, without a consistent correlation with the extent of cerebellar histopathological changes or with cognitive deficits. The loss of noradrenergic drive may contribute to the impairment of cerebellar synaptic function and motor learning observed in these mice. Furthermore, cerebellar neurons, particularly granule cells, have been used as in vitro model of Aβ-induced neuronal damage. An unexpected conclusion is that the cerebellum, for a long time thought to be somehow protected from AD pathology, is actually considered as a region vulnerable to Aβ toxic damage, even at the early stage of the disease, with consequences on motor performance.
Big Data in Medical Research and Application

With the advanced instruments and information technology integrated in biomedical science more and more extensively, the advent of the big data era has had a significant impact on biomedical research, making human awareness of themselves and diseases more profound. The future medicine tends to combine data and medicine, to master gene database and medical human disease data, then to apply data statistics and analysis and application in healthcare. New techniques of big data in medicine are bound to make medical research and application more predictable. This paper introduces the main sources and characteristics of medical big data, points out the necessity of big data research in medical field, summarizes the current research in medical big data and its application in disease prediction, clinical assistance and pharmaceutical research and development. In other aspects, it analyses the problems of medical big data in applied research.
SERVICE QUALITY ASYMMETRIC EFFECT ON PATIENT SATISFACTION FOR PRIMARY HEALTHCARE SERVICES

Primary health care services delivery and its effects on patient satisfaction are very important for healthcare managers as it affects healthcare results and organizations operational expenses’ management. Patient satisfaction is typically view it as a multidimensional construct. The purpose of this study is to exploit the theoretical frameworks of three-factor theory in order to identify the service delivery factors affecting patient satisfaction formation and to investigate whether there is an asymmetric service quality-satisfaction relationship. Regression analysis with dummy variables was used to analyze the responses of 407 primary healthcare services’ users, which were collected via personal interviews using a properly designed questionnaire. The results showed empirical support to the three-factor theory in the context of primary health care services by confirming the asymmetric relationship between service delivery performance assessment and patient satisfaction. Implications for practice and directions for future research are then discussed.
The eXpress data path: fast programmable packet processing in the operating system kernel

Programmable packet processing is increasingly implemented using kernel bypass techniques, where a userspace application takes complete control of the networking hardware to avoid expensive context switches between kernel and userspace. However, as the operating system is bypassed, so are its application isolation and security mechanisms; and well-tested configuration, deployment and management tools cease to function. To overcome this limitation, we present the design of a novel approach to programmable packet processing, called the eXpress Data Path (XDP). In XDP, the operating system kernel itself provides a safe execution environment for custom packet processing applications, executed in device driver context. XDP is part of the mainline Linux kernel and provides a fully integrated solution working in concert with the kernel's networking stack. Applications are written in higher level languages such as C and compiled into custom byte code which the kernel statically analyses for safety, and translates into native instructions. We show that XDP achieves single-core packet processing performance as high as 24 million packets per second, and illustrate the flexibility of the programming model through three example use cases: layer-3 routing, inline DDoS protection and layer-4 load balancing.
Efficient Runtime Frame ECC Recomputation for Reliable Task Execution on Xilinx FPGAs

Many beneficial techniques in reconfigurable computing including clock management, communication and relocation sometimes rely on runtime editing of configuration bitstream. However, there is a major reliability issue with editing the content of the configuration memory of a design in runtime, especially for safety critical applications as these designs rely on using the frame Error Correcting Code (ECC) in the bitstream to track un-wanted bit flips. Hence, it is necessary that the process of editing configuration bitstream be accompanied by re-computing the Frame ECC. In this paper, we present an efficient implementation of a runtime re-computation of frame ECC for Xilinx FPGA configuration bitstream. A re-computation engine makes it possible to carry out desired editing to a design bitstream in runtime without losing the protection offered by the soft error mitigation (SEM) mechanisms. The implementation occupies only 364 LUTs, 193 flip flops and 3 lS-Kb BRAM on the Xilinx xc7a35tcpg236–1 chip and has a Iatency of only 104 clock cycles for each frame. We have shown that the Iatency does not introduce any delay to task configuration if the Frame ECC engine and the configuration controller are enabled at the same time. We have tested the scheme by successfully updating the clock frequency of a design protected by SEM mechanism in runtime, while the design was still able to detect and recover from soft errors.
The MTA: An Advanced and Versatile Thermal Simulator for Integrated Systems

Fast and accurate thermal analysis is crucial for determining the propagation of heat and tracking the formation of hotspots in integrated circuits (ICs). Existing academic thermal analysis tools primarily use compact models to accelerate thermal simulations but are limited to linear problems on relatively simple circuit geometries. The Manchester Thermal Analyzer (MTA) is a comprehensive tool that allows for fast and highly accurate linear and nonlinear thermal simulations of complex physical structures including the IC, the package, and the heatsink. The MTA is targeted for 2.5/3-D IC designs but also handles standard planar ICs. The MTA discretizes the heat equation in space using the finite element method and performs the time integration with unconditionally stable implicit time stepping methods. To improve the computational efficiency without sacrificing accuracy, the MTA features adaptive spatiotemporal refinement. The large-scale linear systems that arise during the simulation are solved with fast preconditioned Krylov subspace methods. The MTA supports thermal analysis of realistic integrated systems and surpasses the computational capabilities and performance of existing academic thermal simulators. For example, the simulation of a processor in a package attached to a heat sink, modeled by a computational grid consisting of over 3 million nodes, takes less than 3 min. The MTA is fully parallel and publicly available.1
Conventional and emerging roles of the energy sensor Snf1/AMPK in Saccharomyces cerevisiae

All proliferating cells need to match metabolism, growth and cell cycle progression with nutrient availability to guarantee cell viability in spite of a changing environment. In yeast, a signaling pathway centered on the effector kinase Snf1 is required to adapt to nutrient limitation and to utilize alternative carbon sources, such as sucrose and ethanol. Snf1 shares evolutionary conserved functions with the AMP-activated Kinase (AMPK) in higher eukaryotes which, activated by energy depletion, stimulates catabolic processes and, at the same time, inhibits anabolism. Although the yeast Snf1 is best known for its role in responding to a number of stress factors, in addition to glucose limitation, new unconventional roles of Snf1 have recently emerged, even in glucose repressing and unstressed conditions. Here, we review and integrate available data on conventional and non-conventional functions of Snf1 to better understand the complexity of cellular physiology which controls energy homeostasis.
All-Additive Solution Processed SilverSilver Chloride Reference Electrode for Handheld Ion-Sensitive Field-Effect Transistor Sensing System

Silversilver chloride (AgAgCl) reference electrodes (REs) for ion-sensitive field-effect transistors (ISEFTs) are fabricated using all-additive solution processes based on dispensing of Ag paste on large-size plastic substrate, which has the advantages of vacuum-free low-cost manufacturing with great material saving and capability of constructing miniaturized electrochemical systems. After deposition of a polyvinyl butyral protective layer on top, the fabricated AgAgCl REs can maintain stable electrochemical potential in KCl solution with a negligible drift rate of 0.37mVh and remain stable under different light conditions and in different electrolyte solutions over a wide range of concentration from 10<sup>7</sup> to 10<sup>1</sup> molL. ISFET measurements for hydrogen ions using the fabricated RE combing with an indium tin oxide working electrode show a high sensitivity of 58.47mVpH with excellent linearity in a wide range from <inline-formula> <tex-math notation="LaTeX">${\text{pH}}= {\text{2}}$</tex-math> </inline-formula> to <inline-formula> <tex-math notation="LaTeX">${\text{pH}}= {\text{12}}$</tex-math> </inline-formula>. Finally, the feasibility of the reliable AgAgCl RE is demonstrated by constructing a handheld ISFET pH measurement system with a calibration program to effectively compensate the variations among different samples and directly convert the measured signals to pH values.
Distributed Password Cracking

Abstract : Password cracking requires significant processing power which in today's world is located at a workstation or home in the form of a desktop computer. Berkeley Open Infrastructure for Network Computing (BOINC) is the conduit to this significant source of processing power and John the Ripper is the key. BOINC is a distributed data processing system that incorporates client-server relationships to generically process data. The BOINC structure supports any system that requires large amounts of data to be processed without changing significant portions of the structure. John the Ripper is a password cracking program that takes a password file and attempts to determine the password by a guess and check method. The merger of these two programs enables companies and diverse groups to verify the strength of their password security policy. This thesis goes into detail on the inner workings of BOINC, John the Ripper, and the merger of the two programs. It also details the work required to test the system to its full capability.
Association between Chiari-like malformation and syringomyelia in cavalier King Charles spaniels

CHIARI-like malformation and syringomyelia is a disease complex commonly described in cavalier King Charles spaniels. It is characterised by foramen magnum cerebellar herniation and the development of fluid filled cavities (syringes) within the spinal cord. This retrospective study assessed whether
Tagrec-CMTF: Coupled Matrix and Tensor Factorization for Tag Recommendation

In order to address data sparsity, missing value, and over-fitting problems in a social tagging system, a coupled matrix and tensor factorization (CMTF) method named Tagrec-CMTF for tag recommendation is proposed in this paper. In the CMTF method, we decompose the tag-item-user tensor joint with tag graph and two auxiliary matrices by using the CMTF, optimize the learning parameters with an alternating direction method of multipliers algorithm, and recommend the tag according to the predicted tensor. Our algorithm infuses the homogeneous and heterogeneous information of the tag and provides good prediction performance. Experiment results show that Tagrec-CMTF outperforms existing methods that do not utilize the homogeneous and heterogeneous information of the tag simultaneously.
Electric Field Reduction in an EHV Substation for Occupational Exposure via Transposition of Conductors

An attempt is made to reduce the maximum value of rms electric field (E-field) via the transposition of conductors in a 765-kV substation with reference to the occupational exposure. The method is applied to a extra-high-voltage substation, which is under construction. The effect of transposing the bay conductors (alone) and the bus conductors (alone) on the E-field distribution (at 2 m above the ground) over the area of the substation is discussed. Also, the topology of substation conductors that results in the minimum value for the maximum of rms E-fields is obtained via simultaneous transpositions of the bus and bay conductors. The area of the substation where the rms E-field exceeds the reference value of 10 kV/m (International Commission on Non-Ionizing Radiation Protection occupational exposure limit) is also reported for the existing topology. For this topology, the computed maximum value of the rms E-field over the area of the substation is 13.06 kV/m. This E-field is reduced to 7.999 kV/m with the best configuration of substation conductors obtained via transposition. The charge-simulation-method-based generalized algorithm for obtaining the best topology (among all permutations) of substation conductors, which results in the minimum value for the maximum of rms E-field magnitudes over the substation area is also reported.
BP: Integrating Cyber Vulnerability Assessments Earlier into the Systems Development Lifecycle: A Methodology to Conduct Early-Cycle Cyber Vulnerability Assessments

During development of high assurance cyber systems, third-party security evaluations such as cyber vulnerability assessments (CVAs) and red teaming may not be conducted until after system implementation. This late in the systems development lifecycle (SDLC), mitigating a single implementation vulnerability may require altering the system requirements, architecture, and design, resulting in a cascade of secondary effects that necessitate additional implementation changes. This paper proposes to identify and mitigate vulnerabilities earlier in the SDLC by conducting early-cycle CVAs (eCVAs). eCVAs initiate the vulnerability assessment process earlier and integrate three CVAs into the SDLC. The three types of assessments include a requirements CVA to analyze system requirements specifications, an architecture and design CVA to evaluate architecture and design artifacts, and an implementation CVA with a focus on manual code review, static and dynamic analysis, and researching leveraged code for known vulnerabilities. This paper describes the three types of CVAs and outlines the results of a year-long pilot effort carried out by the Air Force Research Laboratory Information Directorate eCVA team.