Miracle-dz/UniFAR-FTUs huggingface dataset:
Marginalization and social change processes among lesbian, gay, bisexual and transgender persons in Swaziland: implications for HIV prevention

ABSTRACT Swaziland has among the highest national adult HIV prevalence globally. There is limited knowledge of HIV vulnerabilities and prevention engagement among lesbian, gay, bisexual and transgender (LGBT) persons in the context of Swaziland’s criminalization of consensual same-sex practices. This study explored social processes of marginalization to assess how they could potentiate HIV vulnerabilities and limit engagement in HIV prevention services. Additionally, we assessed positive change to better understand existing strategies employed by LGBT persons to challenge these HIV prevention barriers. Guided by community-based research methodology and conducted in Mbabane and Manzini, Swaziland, data were collected by LGBT peer-research assistants (PRA) in collaboration with an LGBT community organization in Manzini. Semi-structured interviews were conducted by trained PRAs and explored HIV prevention, including experiences of stigma and coping. Audio files were transcribed verbatim, translated to English, and analyzed using thematic techniques. Among participants (n = 51; mean age: 26.47, SD: 4.68), 40 self-identifed as gay or lesbian (78.4%), 11 bisexual (22.6%), and 12 (23.5%) identified as transgender. Findings highlighted three primary processes of marginalization and positive change in structural, community, and internal domains. First, structural marginalization, which included criminalization, healthcare discrimination, and a scarcity of LGBT tailored HIV prevention resources was challenged by grassroots networks created to access and share specific HIV resources with LGBT persons and the Ministry of Health. Second, community marginalization included stigma and multi-dimensional forms of violence, however, this was met with LGBT persons providing mutual peer support, including for accessing HIV testing services. Thirdly, internal marginalization comprised of self-stigma and associated sexual risk practices was contrasted with coping strategies focused on self-acceptance, stemming from social support and leading to healthcare utilization. Jointly, these findings can inform the implementation of community-based and rights affirming HIV prevention and care cascade strategies that improve coverage of services with LGBT persons in Swaziland.
Efficient Algorithms and Lower Bounds for Robust Linear Regression

We study the problem of high-dimensional linear regression in a robust model where an $\epsilon$-fraction of the samples can be adversarially corrupted. We focus on the fundamental setting where the covariates of the uncorrupted samples are drawn from a Gaussian distribution $\mathcal{N}(0, \Sigma)$ on $\mathbb{R}^d$. We give nearly tight upper bounds and computational lower bounds for this problem. Specifically, our main contributions are as follows: For the case that the covariance matrix is known to be the identity, we give a sample near-optimal and computationally efficient algorithm that outputs a candidate hypothesis vector $\widehat{\beta}$ which approximates the unknown regression vector $\beta$ within $\ell_2$-norm $O(\epsilon \log(1/\epsilon) \sigma)$, where $\sigma$ is the standard deviation of the random observation noise. An error of $\Omega (\epsilon \sigma)$ is information-theoretically necessary, even with infinite sample size. Prior work gave an algorithm for this problem with sample complexity $\tilde{\Omega}(d^2/\epsilon^2)$ whose error guarantee scales with the $\ell_2$-norm of $\beta$. For the case of unknown covariance, we show that we can efficiently achieve the same error guarantee as in the known covariance case using an additional $\tilde{O}(d^2/\epsilon^2)$ unlabeled examples. On the other hand, an error of $O(\epsilon \sigma)$ can be information-theoretically attained with $O(d/\epsilon^2)$ samples. We prove a Statistical Query (SQ) lower bound providing evidence that this quadratic tradeoff in the sample size is inherent. More specifically, we show that any polynomial time SQ learning algorithm for robust linear regression (in Huber's contamination model) with estimation complexity $O(d^{2-c})$, where $c>0$ is an arbitrarily small constant, must incur an error of $\Omega(\sqrt{\epsilon} \sigma)$.
Drawing off the page: How new 3D technologies provide insight into cognitive and pedagogical assumptions about mathematics

Mathematics has a history of being a two-dimensional inscribing practice. We describe the potential evolution in doing, thinking, and learning mathematics with the emergence of a technological innovation that enables real-time 3D virtual and material interactions. Using the 3D drawing pen as a simple and recently available technology, we highlight how it helps rethink long-standing assumptions and dichotomies in mathematics education including, for example, the material distinction between diagram and manipulative, the semiotic distinction between icon and index, and the developmental progression of action-icon-symbol. We then speculate on the future possibilities of the shift in technological infrastructure that 3D pens and similar technology may give rise to.
Role-specific Language Models for Processing Recorded Neuropsychological Exams

Neuropsychological examinations are an important screening tool for the presence of cognitive conditions (e.g. Alzheimer’s, Parkinson’s Disease), and require a trained tester to conduct the exam through spoken interactions with the subject. While audio is relatively easy to record, it remains a challenge to automatically diarize (who spoke when? ), decode (what did they say? ), and assess a subject’s cognitive health. This paper demonstrates a method to determine the cognitive health (impaired or not) of 92 subjects, from audio that was diarized using an automatic speech recognition system trained on TED talks and on the structured language used by testers and subjects. Using leave-one-out cross validation and logistic regression modeling we show that even with noisily decoded data (81% WER) we can still perform accurate enough diarization (0.02% confusion rate) to determine the cognitive state of a subject (0.76 AUC).
SemEval-2018 Task 5: Counting Events and Participants in the Long Tail

This paper discusses SemEval-2018 Task 5: a referential quantification task of counting events and participants in local, long-tail news documents with high ambiguity. The complexity of this task challenges systems to establish the meaning, reference and identity across documents. The task consists of three subtasks and spans across three domains. We detail the design of this referential quantification task, describe the participating systems, and present additional analysis to gain deeper insight into their performance.
Nutrition Research and the Impact of Computational Systems Biology

The value of computational modelling in improving our understanding of complex nutrient-based pathways is becoming increasingly recognised. This is due to the integral role that computer modelling is playing within the multidisciplinary field of systems biology, where in silico quantitative simulations are being used to compliment more traditional wet-laboratory investigations. A large number of computational models are accessible via the Biomodels database, an archive of openly available peer reviewed models of biological systems. Moreover, there has been an explosion in the availability of free modelling software tools that can be used to assemble and simulate the dynamic behaviour of nutrient mediated systems. Computational modelling will continue to play an increasingly significant role in nutrition research. Thus, it is important that freely accessible models and resources relevant to nutrition research are highlighted. In response to these needs, we firstly examined the Biomodels database, to identify and categorise nutrition themed models. The outcome of the analysis revealed 163 nutrition themed models. These models are mainly cellular in nature, with intracellular representations of calcium oscillations the most common. Secondly, a generic nutrition centred modelling framework was used, to explore recent advances, data repositories and software relevant to model building. We conclude this paper by using our review findings to discuss areas of nutrition that could further exploit the potential of computational modelling in the future.
ELiRF-UPV at SemEval-2018 Task 10: Capturing Discriminative Attributes with Knowledge Graphs and Wikipedia

This paper describes the participation of ELiRF-UPV team at task 10, Capturing Discriminative Attributes, of SemEval-2018. Our best approach consists of using ConceptNet, Wikipedia and NumberBatch embeddings in order to stablish relationships between concepts and attributes. Furthermore, this system achieves competitive results in the official evaluation.
Recurrent Loss, Horizontal Transfer, and the Obscure Origins of Mitochondrial Introns in Diatoms (Bacillariophyta)

Abstract We sequenced mitochondrial genomes from five diverse diatoms (Toxarium undulatum, Psammoneis japonica, Eunotia naegelii, Cylindrotheca closterium, and Nitzschia sp.), chosen to fill important phylogenetic gaps and help us characterize broadscale patterns of mitochondrial genome evolution in diatoms. Although gene content was strongly conserved, intron content varied widely across species. The vast majority of introns were of group II type and were located in the cox1 or rnl genes. Although recurrent intron loss appears to be the principal underlying cause of the sporadic distributions of mitochondrial introns across diatoms, phylogenetic analyses showed that intron distributions superficially consistent with a recurrent-loss model were sometimes more complicated, implicating horizontal transfer as a likely mechanism of intron acquisition as well. It was not clear, however, whether diatoms were the donors or recipients of horizontally transferred introns, highlighting a general challenge in resolving the evolutionary histories of many diatom mitochondrial introns. Although some of these histories may become clearer as more genomes are sampled, high rates of intron loss suggest that the origins of many diatom mitochondrial introns are likely to remain unclear.
Structural Health Monitoring of Multi-Rotor Micro Aerial Vehicles

Structural Health Monitoring (SHM) is a key troubleshooting methodology for assessing the working condition and health of (manned or unmanned) aerial vehicles; however, its understanding with respect to the multi-rotor class of Micro Aerial Vehicles (MAV) is limited. The portentous structural failure sources, in this case, are the two moving components: motors and propellers. In this paper, we undertake a detailed exercise of characterizing the common and frequent faults of these units using multi-modal sensing of vibration, acoustic noise, input power, and thrust profiles; and then use relevant features to perform a two-level diagnosis. Through our empirical fault studies on our custom designed test rig, we propose a set of befitting features in each sensory domain; which result in high fault detection and classification accuracy that exceeds 90%.
Learning electronics through head, heart and hands: An unconventional and holistic approach in engineering education

This paper shows an approach practiced in the field of learning basic electronics now for more than 10 years. The practicalities have been developed by trial and error as well as intensive discussions with the students. The paper focuses on (1) the learning strategy and learning environment and (2) the reflections on the background and goals for effective learning. The described learning strategy is based mainly on problem-based learning and self-directed learning. The learning activity is guided by the 3H-learning approach (Head, Heart and Hands). Special focus also is put on side topics like (1) changing from teacher to trainer, (2) balancing the different aspects in the projects, (3) valuing the learning support by the peer group and (4) motivating the "engineer inside" instead of keeping the "pupil" alive. This paper will help to open the "fences" around students which limit their inside motivation and such as their energy and put them to an open learning environment.
Three-dimensional aspects of fluid flows in channels. I. Meniscus and thin film regimes

We study the forced displacement of a fluid-fluid interface in a three-dimensional channel formed by two parallel solid plates. Using a lattice-Boltzmann method, we study situations in which a slip velocity arises from diffusion effects near the contact line. The difference between the slip and channel velocities determines whether the interface advances as a meniscus or a thin film of fluid is left adhered to the plates. We find that this effect is controlled by the capillary and Peclet numbers. We estimate the crossover from a meniscus to a thin film and find good agreement with numerical results. The penetration regime is examined in the steady state. We find that the occupation fraction of the advancing finger relative to the channel thickness is controlled by the capillary number and the viscosity contrast between the fluids. For high viscosity contrast, lattice-Boltzmann results agree with previous results. For zero viscosity contrast, we observe remarkably narrow fingers. The shape of the finger is.
Genome-Wide Mapping of Gene–Phenotype Relationships in Experimentally Evolved Populations

Model organisms subjected to sustained experimental evolution often show levels of phenotypic differentiation that dramatically exceed the phenotypic differences observed in natural populations. Genome-wide sequencing of pooled populations then offers the opportunity to make inferences about the genes that are the cause of these phenotypic differences. We tested, through computer simulations, the efficacy of a statistical learning technique called the "fused lasso additive model" (FLAM). We focused on the ability of FLAM to distinguish between genes which are differentiated and directly affect a phenotype from differentiated genes which have no effect on the phenotype. FLAM can separate these two classes of genes even with relatively small samples (10 populations, in total). The efficacy of FLAM is improved with increased number of populations, reduced environmental phenotypic variation, and increased within-treatment among-replicate variation. FLAM was applied to SNP variation measured in both twenty-population and thirty-population studies of Drosophila subjected to selection for age-at-reproduction, to illustrate the application of the method.
Secure Grouping and Aggregation with MapReduce

MapReduce programming paradigm allows to process big data sets in parallel on a large cluster. We focus on a scenario where the data owner outsources her data on an honest-but-curious server. Our aim is to evaluate grouping and aggregation with SUM, COUNT, AVG, MIN, and MAX operations for an authorized user. For each of these five operations, we assume that the public cloud provider and the user do not collude i.e., the public cloud does not know the secret key of the user. We prove the security of our approach for each operation.
Peer Group Metadata-Informed LSTM Ensembles for Insider Threat Detection

The problem of detecting insider threats i.e. authorized individuals who pose a threat to an organization is challenging. Since insiders have authorized access to and use sensitive data and systems on a day-to-day basis, the difference between an attack and benign normal behavior is small. We propose a method to address these issues by leveraging peer group metadata to build more robust models of normal behavior and investigate how to make use of multiple of these models and aggregate the results. Our experiments show that the use of peer group metadata improves performance over individual models trained using either hand-crafted features
Activity of oxidative stress biomarkers in the white muscle of red mullet (Mullus barbatus L.) from the Adriatic sea

The aim of this study was to investigate the activity of oxidative stress biomarkers (total superoxide dismutase - Tot SOD; and copper and zinc-containing superoxide dismutase - CuZn SOD; manganese-containing superoxide dis- mutase - Mn SOD; catalase - CAT; glutathione peroxidase - GSH-Px; and glutathione reductase - GR), as well as the biotransformation phase II enzyme glutathione-S-transferase (GST), in the white muscle of red mullet (Mullus barbatus L.) at Platamuni (PL) and Valdanos (VAL) in the Adriatic Sea during the winter and spring seasons. The obtained results show both site and seasonal influences on the investigated parameters, with lower enzyme activities at VAL than at PL and in spring than in winter.
Fingerprinting Protocol at Bit-Level Granularity: A Graph-Based Approach Using Cell Embedding

Traffic identification is defined as the act of ascertaining which application or service or protocol is contributing to the network traffic by using a fingerprint, which is a distinguishable unique pattern representing a particular applications traffic. The continual appearance of new applications and their frequent updates emphasize the need for automatic protocol fingerprints generation. In this paper, we propose BitGrapher, a novel graph-based approach that accurately infers protocol fingerprints at bit-level granularity for accurate traffic identification. The proposal is designed to accommodate to various protocol traces including text-based and binary-based protocols, and even possible unknown proprietary communication protocols. Our proposed approach introduces a new concept of cell that allows BitGrapher to encode protocol payloads as a graphical model, and then converts fingerprinting protocol problem as a series of graph operations (e.g., graph construction, pruning, partition). The key insight of the graphical model use cell embeddings that captures the distinguishable positions with their values and distinguishable correlation among them. We implement and evaluate BitGrapher on real-world traces, including DNS, QQLive, SopCast, SMB, HTTP, and SMTP, and our experimental results show that BitGrapher can accurately identify the protocol trace with an average precision of about 97.28% and an average recall of about 99.12%. We also compare the results of BitGrapher to two state-of-the-art approaches ProWord and ProDigger, which shows that BitGrapher provides significant improvements in precision and recall for protocol identification task.
What to Do, and How to Do It

In Photo Restoration: From Snapshots to Great Shots, author Robert Correll carefully guides you through the process of restoring your photos, teaching you the most effective techniques to preserve and repair your damaged or aging images. Organized based on a helpful photo restoration workflow, the book will feature Adobe Photoshop as the primary software solution of choice, with coverage of Photoshop Elements and Lightroom as well. Read the book from start to finish or quickly access the information you need for the specific photo problems at hand. The book will start by covering the basics, such as how to evaluate how a photo is damaged and then move to the appropriate solution; how to properly handle and scan/import your photos; and how to use Photoshop as a photo retouching tool, with information on how Photoshop Elements and Lightroom can also play a role in restoring your images. The book then dives into specific issues that arise with old or damaged photos, such as removal of dust, scuff marks, and stains; repairing actual damage such as creases or missing corners; correcting color-related problems like blue or yellow-tinted images and oversaturation; and improving the contrast and brightness of both color and black-and-white images. Finally, the book finishes up by showing you how to add a special touch of greatness and creativity to your photos, in addition to printing and archiving. Download ebook, read file pdf From Snapshots to Great Shots
High performance and low power timing controller design for LCoS microdisplay system

A liquid crystal on silicon (LCoS) microdisplay is attractive for a wearable device to realize augmented reality (AR) and virtual reality (VR), but it requires a design that consumes lower power while improving picture quality. We propose a timing controller architecture to reduce power consumption, as well as image processing that can compensate for screen distortion and improve brightness/contrast, and so on. In this paper we verify the operation with FHD LCoS panels and confirm that it shows better performance than other chips.
Communication challenges in international education

Distance and collaborative education has many potential benefits, most notably is the ability to overcome the temporal and spatial restrictions of traditional educational settings, but changes in general communication processes between educators and students, educators themselves and students themselves are also predominant. With both business and personal life becoming more collaborative and less geo-centric (just consider examples of social networks like Facebook or LinkedIn, or examples of collaborative economy like Uber or Airbnb), the authors' institution, with its international campuses in Eastern Europe and the Middle East, is setting a new level of distance and collaborative education that enables students form different cultures and time zones to work together on real projects in a controlled, academic setting, but in a manner that mirrors business and industry projects to a very significant degree. Three instructors and more than 50 students are working jointly on the same projects and relying greatly on effective communication. In this work, the authors address and describe their experiences and challenges in communication and collaborative education from both their perspective and the students' perspective. The main intention is to make the educational process more efficient and to introduce more interaction between the students and their teachers, who act more as project advisors.
Trade Liberalization and Poverty Reduction: New Evidence from Indian States

As is widely acknowledged, the incidence of poverty in India has declined steadily over the last several decades. What is debated, however, is the pace at which poverty has declined and its relationship with India's economic reforms. In particular, a key concern among policymakers and researchers alike is that trade liberalization undertaken in the early 1990s may have slowed the progress made in reducing poverty. In this paper, we update our previous econometric analysis on the links between trade liberalization and poverty reduction in India. By incorporating measures of poverty based on the 2004-05 consumer expenditure survey carried out by India's National Sample Survey Organisation, we are able to sidestep the controversy-ridden poverty measures based on the 1999-2000 survey. Our new results are in line with the earlier ones in Hasan, Mitra and Ural (2007): States, and regions within states, that were more exposed to trade liberalization on account of their employment structures did not experience slower reduction in poverty; on the contrary, to the extent that we find a statistically significant relationship between trade liberalization and poverty reduction, the evidence points to faster poverty reduction in states and regions experiencing greater increases in exposure to trade. Moreover, this relationship is typically stronger in states with more flexible labor regulations, better quality transportation infrastructure, and more developed financial systems.