Miracle-dz/UniFAR-FTUs huggingface dataset:
Health care seeking and financial behaviours of the elderly during wartime in Goma, Democratic Republic of Congo

ABSTRACT Background Health and social services utilisation is seen to be more closely related to age than to other socio-demographic characteristics. Many health problems are known to increase with age and this demographic trend may lead to an increase in the absolute number of health conditions in this population. However, questions are still emerging as to how the elderly seek care in response to their needs in the context of a war-torn region. Objectives The aim of this study was to determine the behaviour of the elderly in seeking care during a time of conflict. Method A descriptive cross-sectional study was carried out in the health district Goma, in the Democratic Republic of the Congo (DRC), using a multistage sampling of 500 senior citizens. Eight trained field-workers were deployed in the field where they administered a structured questionnaire. Results The public health sector was well known and preferred by 186 participants (37.2%), but only used by 16 (3.2%) participants. Financial support received by the elderly came from their own relatives and fellow believers in 33.5% and 20.2% of cases, respectively. Almost 71% of monetary support is the result of begging and unknown sources – there is no government involvement whatsoever. Much of the external support that the elderly receive involves support in the form of food. Disease expenses remain a main concern of the elderly themselves. Conclusion Government support for the elderly in the DRC is non-existent. There is an overuse of private sector and traditional medicine, despite the preference indicated for the public health sector. As a recommendation, a general increase in income-related activities could contribute to alleviating the health state of the elderly in a war situation. Further studies might explore in future the contribution of those results on the health of elders.
Inaccuracy of Affordance Judgments for Firefighters Wearing Personal Protective Equipment

ABSTRACT In order to safely negotiate cluttered and dangerous environments, firefighters must efficiently and effectively make affordance judgments. Failure to do so could put them at risk for slips, trips, and falls, which are major causes of injuries for firefighters. We examined how well firefighters were able to perceive their obstacle crossing abilities while wearing firefighting protective equipment. Firefighters were asked to judge whether they could cross over, under, and through different obstacles that simulated idealized fireground situations. Perceptual judgment errors were found for each obstacle type, the largest occurring with an overestimation of ability to pass under an obstacle. Years of experience had a moderate positive correlation with absolute judgment error in the “over” and “under” obstacles. Overall, a general lack of awareness of their personal protective equipment for obstacle crossing ability was observed. A better understanding of how to reduce judgment error while wearing firefighter protective gear would likely decrease the risk of injuries on the fireground.
Primary myocardial dysfunction in autosomal dominant EDMD. A tissue doppler and cardiovascular magnetic resonance study.

BACKGROUND Emery-Dreifuss muscular dystrophy is a genetically heterogeneous form of muscular dystrophy. One form is inherited in an X-linked fashion and is secondary to mutations in the gene encoding the nuclear protein emerin. A more common variant is inherited in an autosomal dominant way (EDMD2) due to mutations affecting the nuclear lamina protein lamin A/C. Typical features of both conditions are relatively mild skeletal muscle weakness, but cardiac involvement develops almost invariably by adult age, including conduction defects, arrhythmias and cardiomyopathy. Thus, early detection of cardiac abnormalities may be important for planning early therapeutic intervention. AIM In this study, we hypothesized that early myocardial dysfunction can be detected by tissue Doppler echocardiography and CMR in unselected patients with the autosomal dominant form of Emery-Dreifuss muscular dystrophy. This would suggest that fibrosis could be implicated in the pathogenesis of cardiac dysfunction in EDMD2. METHODS Eight consecutive patients with genetically proven EDMD2 without pacemakers were enrolled in the study and compared to eight age-matched controls. All patients and controls first underwent a comprehensive echocardiographic-Doppler examination, followed by measurement of mitral annular velocities using pulsed tissue Doppler. Color M-mode tissue images were recorded from the parasternal long axis projections to derive Myocardial Velocity Gradients (MVG). Subsequently, all subjects underwent cardiovascular magnetic resonance (CMR) imaging for function, intrinsic myocardial tissue contrast using T1 and T2 weighted spin echo (TSE) for fat deposition and extrinsic contrast (Gadolinium-DTPA late fibrosis imaging). Strain measurements, using harmonic phase imaging (HARP) tagging were also derived. RESULTS Cavity dimensions LV mass and fractional shortening were similar between patients and controls. The overall body mass index was less in patients than in controls (14.5 +/- 1.4 vs. 18.1 +/- 2.4 g/m2, p < 0.002). While systolic MVG were similar between groups, the early diastolic MVG was lower in patients than in controls (4 +/- 1.2 s-1 vs. 7.1 +/- 2.7, p < 0.02). On CMR, LA and LV, RV volumes were similar between patients and controls. CMR strain patterns, however, showed a significant reduction in inferior wall contractility in patients compared to controls (-0.06 +/- 0.02 vs -0.09 +/- 0.03, p < 0.05). No patient showed late gadolinium enhancement. CONCLUSION Patients with EDMD2 have abnormal left ventricular function prior to developing any cardiac symptoms. The absence of myocardial fibrosis, however, by CMR suggests that this functional abnormality may not be secondary to scarring but could precede it. Tissue Doppler echocardiography and CMR are sensitive methods of assessing the presence of myocardial dysfunction prior to the development of any cardiovascular symptoms.
Generative Steganography by Sampling

In this paper, a novel data-driven information hiding scheme called “generative steganography by sampling” (GSS) is proposed. Unlike in traditional modification-based steganography, in our method the stego image is directly sampled by a powerful generator: no explicit cover is used. Both parties share a secret key used for message embedding and extraction. The Jensen-Shannon divergence is introduced as a new criterion for evaluating the security of generative steganography. Based on these principles, we propose a simple practical generative steganography method that uses semantic image inpainting. The message is written in advance to an uncorrupted region that needs to be retained in the corrupted image. Then, the corrupted image with the secret message is fed into a Generator trained by a generative adversarial network (GAN) for semantic completion. Message loss and prior loss terms are proposed for penalizing message extraction error and unrealistic stego image. In our design, we first train a generator whose training target is the generation of new data samples from the same distribution as that of existing training data. Next, for the trained generator, backpropagation to the message and prior loss are introduced to optimize the coding of the input noise data for the generator. The presented experiments demonstrate the potential of the proposed framework based on both qualitative and quantitative evaluations of the generated stego images.
Querying Graphs with Data

Graph databases have received much attention as of late due to numerous applications in which data is naturally viewed as a graph; these include social networks, RDF and the Semantic Web, biological databases, and many others. There are many proposals for query languages for graph databases that mainly fall into two categories. One views graphs as a particular kind of relational data and uses traditional relational mechanisms for querying. The other concentrates on querying the topology of the graph. These approaches, however, lack the ability to combine data and topology, which would allow queries asking how data changes along paths and patterns enveloping it. In this article, we present a comprehensive study of languages that enable such combination of data and topology querying. These languages come in two flavors. The first follows the standard approach of path queries, which specify how labels of edges change along a path, but now we extend them with ways of specifying how both labels and data change. From the complexity point of view, the right type of formalisms are subclasses of register automata. These, however, are not well suited for querying. To overcome this, we develop several types of extended regular expressions to specify paths with data and study their querying power and complexity. The second approach adopts the popular XML language XPath and extends it from XML documents to graphs. Depending on the exact set of allowed features, we have a family of languages, and our study shows that it includes efficient and highly expressive formalisms for querying both the structure of the data and the data itself.
Parallel Hardware Merge Sorter

Sorting has tremendous usage in the applications that handle massive amount of data. Existing techniques accelerate sorting using multiprocessors or GPGPUs where a data set is partitioned into disjunctive subsets to allow multiple sorting threads working in parallel. Hardware sorters implemented in FPGAs have the potential of providing high-speed and low-energy solutions but the partition algorithms used in software systems are so data dependent that they cannot be easily adopted. The speed of most current sequential sorters still hangs around 1 number/cycle. Recently a new hardware merge sorter broke this speed limit by merging a large number of sorted sequences at a speed proportional to the number of sequences. This paper significantly improves its area and speed scalability by allowing stalls and variable sorting rate. A 32-port parallel merge-tree that merges 32 sequences is implemented in a Virtex-7 FPGA. It merges sequences at an average rate of 31.05 number/cycle and reduces the total sorting time by 160 times compared with traditional sequential sorters.
Environmental conditions leading to spinup and intensi cation during the 2008 West Paci c tropical cyclone season

The large-scale features favoring tropical cyclogenesis and development are low vertical wind shear, below normal sea-level pressure and abnormally warm ocean temperatures. High wind shear is thought to inhibit development by preventing cumulonimbus condensation from collecting into a distinct heat source at the core of a disturbance. Also, it shears the initially delicate pattern of circulation created by azimuthal winds, which are forced into cyclonic rotation by the Coriolis and pressure gradient forces. Low surface pressure assists this process by e ecting an in ow into the core region in order to drive radial winds that pick up heat and moisture from the air/sea interface.
Identification of molecular mechanisms used by Finegoldia magna to penetrate and colonize human skin

Finegoldia magna is a Gram‐positive anaerobic commensal of the human skin microbiota, but also known to act as an opportunistic pathogen. Two primary virulence factors of F. magna are the subtilisin‐like extracellular serine protease SufA and the adhesive protein FAF. This study examines the molecular mechanisms F. magna uses when colonizing or establishing an infection in the skin. FAF was found to be essential in the initial adherence of F. magna to human skin biopsies. In the upper layers of the epidermis FAF mediates adhesion through binding to galectin‐7 – a keratinocyte cell marker. Once the bacteria moved deeper into the skin to the basement membrane layer, SufA was found to degrade collagen IV which forms the backbone structure of the basement membrane. It also degraded collagen V, whereby F. magna could reach deeper dermal tissue sites. In the dermis, FAF interacts with collagen V and fibrillin, which presumably helps the bacteria to establish infection in this area. The findings of this study paint a clear picture of how F. magna interacts with human skin and explain how it is such a successful opportunistic pathogen in chronic wounds and ulcers.
Boosting-like Deep Learning For Pedestrian Detection

This paper proposes boosting-like deep learning (BDL) framework for pedestrian detection. Due to overtraining on the limited training samples, overfitting is a major problem of deep learning. We incorporate a boosting-like technique into deep learning to weigh the training samples, and thus prevent overtraining in the iterative process. We theoretically give the details of derivation of our algorithm, and report the experimental results on open data sets showing that BDL achieves a better stable performance than the state-of-the-arts. Our approach achieves 15.85% and 3.81% reduction in the average miss rate compared with ACF and JointDeep on the largest Caltech benchmark dataset, respectively.
Effects of Politics, Emotional Stability, and LMX on Job Dedication

Efforts to identify antecedents of job dedication (i.e., being loyal and cooperative) are likely to offer value to managers. The authors examined the combined effects of organizational politics and emotional stability on the relationship between leader–member exchange and job dedication. Results of analyses conducted on 156 private sector workers revealed that leader–member exchange quality yielded high levels of job dedication among all employees except the emotionally unstable working in highly political climates. These results not only reinforce the need to hire emotionally stable workers and keep organizational politics at low levels but also point to the limitations of leader influences on employee contextual performance.
Capital-Goods Imports , Investment-Speci c Productivity , and U . S . Growth

Capital-goods imports have become an increasing source of growth for the U.S. economy. To understand this phenomenon, we build a neoclassical growth model with international trade in capital goods in which agents face exogenous paths of total factor and investment-speci c productivity. Investment-speci c productivity is reected by the price of capital-goods imports and the price of investment in domestically-produced equipment and software relative to the price of consumption. We use observed prices to solve for optimal investment decision and understand the underlying sources of growth in the U.S. economy. We nd that the model allocation decisions coming from changes in relative prices explain well the dynamics of capital-goods imports in aggregate investment in equipment and software, and in U.S. output. Using the model economy, we show that the U.S. could have lost more than 20 percent of its growth in output per hour without capital-goods imports technology over the past 20 years. jel classification codes: E2; F2; F4; O3; O4 First version: October 2007. We appreciate valuable comments from Roc Armenter, Marianne Baxter, Russell Cooper, Dean Corbae, Mario Crucini, Michael Devereux, Jim Dolmas, Robert Feenstra, John Fernald, Dale Jorgenson, Tim Kehoe, Enrique Mendoza, Erwan Quintin, Kim Ruhl, and Kadee Russ. Seminar participants at the Board of Governors of the Federal Reserve System, 2007 Federal Reserve SCIEA meeting, International Monetary Fund, University of British Columbia, University of California at Berkeley, University of California at Davis, University of Oregon, and Vanderbilt University provided helpful feedback. The views in this paper are solely our responsibility and should not be interpreted as reecting the views of the Board of Governor of the Federal Reserve System, the Federal Reserve Bank of Dallas, or the Federal Reserve System. yEmail: Michele.Cavallo@frb.gov zEmail: Anthony.Landry@dal.frb. org
Placental abruption and analysis of risk factors

Objective: It was aimed to evaluate pregnancies with suspected placental abruption and investigate the related risk factors. Methods: Ninety-four pregnancies who delivered by cesarean section for suspected placental abruption in Zeynep Kamil Hospital between 01.03. 2012 and 31.01. 2013 were included in this study. During the operation, the placenta was examined macroscopically. The presence of retroplacental bleeding or clots in the placenta confirmed the diagnosis of placental abruption. Age, parity, height, weight, blood group, placental localization, previous delivery type, presenting symptoms, pregnancy complications were recorded. Results: The diagnosis of placental abruption was confirmed in 43 (46%) patients while 51 of them (54%) were not confirmed. There was no significant difference between the groups in terms of maternal age, gestational age and body mass index. Mean arterial pressure (MAP) was 95.1±17.8 at the group with placental abruption confirmed and 85.4±8.7 (p=0.006) at the group with placental abruption not confirmed. Placental abruption is more frequent in patients with preeclampsia (OR=8.5; p=0.022). When the groups were compared according to their blood groups; 87.5% of pregnant women with 0 Rh (+) blood group was confirmed for diagnosis of placental abruption (OR=8.7; P=0.005). Conclusion: Identification of risk factors for placental abruption is the basic criterion for the management and reduction of potential complications.
GM Canola : The Canadian Experience

This article examines the agronomic, economic and environmental impacts of genetically modified (GM) herbicide-resistant (HR) canola (Brassica napus) after 15 years of cultivation in Canada. The rapid adoption of GM canola is due to improved weed control, greater yields and higher economic returns. GM canola has reduced the environmental impact of herbicides compared with their non-HR crop counterparts. There are no marked changes in volunteer weed problems associated with GM canola, except in no-till systems when glyphosate was used alone to control volunteers. GM canola has not reduced weed species diversity. Moreover, GM canola has provided new in-crop herbicide modes of action and has been an important management tool for slowing weed resistance to high-risk herbicides. Reliance on GM crops in rotations using the same mode-of-action herbicide and/or multiple in-crop herbicide applications over time can result in intense selection pressure for weed resistance. With current favourable economic returns from growing canola, many farmers are shortening their GM canola rotations. To date, evolved glyphosateor glufosinate-resistant weeds in GM canola in Canada has not yet occurred.
A Traveling Distance Prediction Based Method to Minimize Unnecessary Handovers from Cellular Networks to WLANs

We propose a handover decision method based on the prediction of traveling distance within an IEEE 802.11 wireless local area network (WLAN) cell. The method uses two thresholds which are calculated by the mobile terminal (MT) as it enters the WLAN cell. The predicted traveling distance is compared against these thresholds to make a handover decision in order to minimize the probability of handover failures or unnecessary handovers from a cellular network to a WLAN. Our analysis shows that the proposed method successfully keeps the number of failed or unnecessary handovers low.
Solutions of Two-Dimensional Viscous Accretion and Winds in Kerr Black Hole Geometry

We extend our previous studies of shock waves and shock-free solutions in thin accretion and winds in pseudo-Newtonian geometry to the case in which the flow is two-dimensional and around a Kerr black hole. We present equations for fully general relativistic viscous transonic flows and classify the parameter space according to whether or not shocks form in an inviscid flow. We discuss the behaviors of shear, angular momentum distribution, and heating and cooling in viscous FLows. We obtain a very significant result: in the weak-viscosity limit, the presence of standing shock waves is more generic, in the sense that flows away from the equatorial plane can produce shock waves in a wider range of parameter space. A similar conclusion also holds when the angular momentum of the black hole is increased. Generally, our conclusions regarding the shape of the shock waves are found to agree with results of the existing numerical simulations of two-dimensional accretion in Schwarzschild geometry. In the strong-viscosity limit, the shocks may be located farther out or disappear completely, as in the pseudo-Newtonian geometry.
Evaluation of Primers Targeting the Diazotroph Functional Gene and Development of NifMAP – A Bioinformatics Pipeline for Analyzing nifH Amplicon Data

Diazotrophic microorganisms introduce biologically available nitrogen (N) to the global N cycle through the activity of the nitrogenase enzyme. The genetically conserved dinitrogenase reductase (nifH) gene is phylogenetically distributed across four clusters (I–IV) and is widely used as a marker gene for N2 fixation, permitting investigators to study the genetic diversity of diazotrophs in nature and target potential participants in N2 fixation. To date there have been limited, standardized pipelines for analyzing the nifH functional gene, which is in stark contrast to the 16S rRNA gene. Here we present a bioinformatics pipeline for processing nifH amplicon datasets – NifMAP (“NifH MiSeq Illumina Amplicon Analysis Pipeline”), which as a novel aspect uses Hidden-Markov Models to filter out homologous genes to nifH. By using this pipeline, we evaluated the broadly inclusive primer pairs (Ueda19F–R6, IGK3–DVV, and F2–R6) that target the nifH gene. To evaluate any systematic biases, the nifH gene was amplified with the aforementioned primer pairs in a diverse collection of environmental samples (soils, rhizosphere and roots samples, biological soil crusts and estuarine samples), in addition to a nifH mock community consisting of six phylogenetically diverse members. We noted that all primer pairs co-amplified nifH homologs to varying degrees; up to 90% of the amplicons were nifH homologs with IGK3–DVV in some samples (rhizosphere and roots from tall oat-grass). In regards to specificity, we observed some degree of bias across the primer pairs. For example, primer pair F2–R6 discriminated against cyanobacteria (amongst others), yet captured many sequences from subclusters IIIE and IIIL-N. These aforementioned subclusters were largely missing by the primer pair IGK3–DVV, which also tended to discriminate against Alphaproteobacteria, but amplified sequences within clusters IIIC (affiliated with Clostridia) and clusters IVB and IVC. Primer pair Ueda19F–R6 exhibited the least bias and successfully captured diazotrophs in cluster I and subclusters IIIE, IIIL, IIIM, and IIIN, but tended to discriminate against Firmicutes and subcluster IIIC. Taken together, our newly established bioinformatics pipeline, NifMAP, along with our systematic evaluations of nifH primer pairs permit more robust, high-throughput investigations of diazotrophs in diverse environments.