Miracle-dz/UniFAR-FTUs huggingface dataset:
Existential loneliness: An attempt at an analysis of the concept and the phenomenon

Background: According to ethical guidelines, healthcare professionals should be able to provide care that allows for the patients’ values, customs and beliefs, and the existential issues that are communicated through them. One widely discussed issue is existential loneliness. However, much of the debate dealing with existential loneliness concludes that both the phenomenon and the concept are quite vague. Aim: To clarify what constitutes existential loneliness, and to describe its lived experiences. A further aim was to provide a definition of existential loneliness that can function as a tool for identifying the phenomenon and for differentiating it from other kinds of loneliness. Method: A literature review including theoretical and empirical studies. Different search strategies were used to gather the articles included in the study. The analysis of the empirical studies had an interpretative approach. The articles were also analysed with the aim of providing a definition of existential loneliness. This was done by means of criteria such as language, uniqueness, theory and usefulness. This study is not empirical and does therefore not require an ethics review. Results: The analysis resulted in two main characteristics. The first one was perceiving oneself as inherently separated (disconnected) from others and from the universe. The second one brings out emotional aspects of EL, such as isolation, alienation, emptiness and a feeling of being abandoned. The empirical findings were divided into two categories: experiences of EL and circumstances in which EL arises. A definition of EL is also suggested, based on the two main characteristics identified. Conclusion: In order to meet patients’ needs, it is an ethical duty for healthcare staff to be able to recognise experiences of EL, that is, to communicate with the patients about these experiences in an appropriate manner. This in turn demands knowledge about existential issues and skills to deal with them.
Effects of a high-intensity functional exercise programme on depressive symptoms and psychological well-being among older people living in residential care facilities: A cluster-randomized controlled trial

Objectives: To evaluate the effects of a high-intensity functional exercise programme on depressive symptoms and psychological well-being among older people dependent in activities of daily living (ADL) and living in residential care facilities. Method: Cluster-randomized controlled study. Participants were 191 older people, aged 65–100, dependent in ADL and with Mini Mental State Examination scores between 10 and 30. One-hundred (52%) of the participants had a diagnosed dementia disorder. A high-intensity functional weight-bearing exercise programme and a control activity were performed in groups. Sessions were held five times over each two week period for three months, a total of 29 times. The outcome measures, Geriatric Depression Scale (GDS-15) and Philadelphia Geriatric Center Morale Scale (PGCMS) were blindly assessed at baseline, three and six months. Results: At baseline, mean ± SD (range) for GDS was 4.4 ± 3.2 (0–14), and for PGCMS 11.0 ± 3.5 (2–17). There were no significant differences in GDS or PGCMS between the exercise and the control group at the three and six month follow-ups in the total sample. Among people with dementia, there was a between-group difference at three months in PGCMS scores in favour of the exercise group. Conclusion: A high-intensity functional exercise programme seems generally not to influence depressive symptoms or psychological well-being among older people dependent in ADL and living in residential care facilities. An individualized and multifactorial intervention may be needed in this group. However, an exercise programme as a single intervention may have a short-term effect on well-being among people with dementia.
Sybil-Resilient Online Content Voting

Obtaining user opinion (using votes) is essential to ranking user-generated online content. However, any content voting system is susceptible to the Sybil attack where adversaries can out-vote real users by creating many Sybil identities. In this paper, we present SumUp, a Sybilresilient vote aggregation system that leverages the trust network among users to defend against Sybil attacks. SumUp uses the technique of adaptive vote flow aggregation to limit the number of bogus votes cast by adversaries to no more than the number of attack edges in the trust network (with high probability). Using user feed-back on votes, SumUp further restricts the voting power of adversaries who continuously misbehave to below the number of their attack edges. Using detailed evaluation of several existing social networks (YouTube, Flickr), we show SumUp's ability to handle Sybil attacks. By applying SumUp on the voting trace of Digg, a popular news voting site, we have found strong evidence of attack on many articles marked "popular" by Digg.
GPU Enhanced Smoothed Particle Hydrodynamics Simulation

: Smoothed Particle Hydrodynamics is a powerful tool for simulating fluid dynamics. Moreover, it is easily parallelizable, as the interaction between two particles is independent of the others. However, with a large number of particles there would be a significant amount of computation involved for calculating the interaction between the particles. So its necessity of an algorithm that is suitable for such parallelization using GPUs. An analysis of the implementation of smoothed particle hydrodynamics (SPH) simulation in a parallelized manner is presented here. In normal implementation, there is very much data transfer overhead. It is because, after performing physical computation every time it copies all data to the main memory for displaying them. But constantly sending this data makes this computation extremely slow. So to overcome this problem, a parallel implementation of SPH simulation using shared memory is used in proposed work. Speaking simply, proposed work performs all the physical computations at GPU and updated data is sent to the main memory only when it needs to be displayed. This will help to minimize the CPU-GPU data transfer overhead and speeding-up the performance.
Post-exercise hypotensive responses following an acute bout of aquatic and overground treadmill walking in people post-stroke: a pilot study

Abstract Background: The purpose of this study is to investigate the effects of a single-bout of aquatic treadmill walking (ATW) and overground treadmill walking (OTW) on the magnitude and duration of post-exercise ambulatory blood pressure (BP) in people post-stroke. Methods: Seven people post-stroke participated in a cross-sectional comparative study. BP was monitored for up to 9 hours after a 15-minute bout of ATW and OTW at approximately 70% of maximal oxygen consumption (VO2max), performed on separate days. Mean systolic and diastolic BP values were compared between both exercise conditions and a day without exercise (control). Results: Three hours after OTW, mean SBP increased by 9% from pre-exercise baseline compared to a 3% decrease during the control day (P < 0.05). A similar trend was observed after the third hour of ATW (P = 0.06). However, ATW demonstrated a 3% overall decline in DBP after exercise compared to a 1% DBP increase of the control day (P < 0.05). Additionally, ATW showed a 6% reduction in mean systolic BP at the ninth hour post-exercise (P < 0.05) compared to baseline. Conclusion: Our results indicate people post-stroke can sustain sufficient walking intensities necessary to reduce BP following cardiovascular exercise. Also, these data suggest that ATW can elicit clinically meaningful reductions in DBP and night-time SBP. Thus, it is recommended for clinicians to consider ATW as a non-pharmaceutical means to regulate DBP and promote nighttime dipping of SBP in people post-stroke. However, caution is advised during the immediate hours after exercise, a period of possible BP inflation.
On the use of machine translation-based approaches for vietnamese diacritic restoration

This paper presents an empirical study of two machine translation-based approaches for Vietnamese diacritic restoration problem, including phrase-based and neural-based machine translation models. This is the first work that applies neural-based machine translation method to this problem and gives a thorough comparison to the phrase-based machine translation method which is the current state-of-the-art method for this problem. On a large dataset, the phrase-based approach has an accuracy of 97.32% while that of the neural-based approach is 96.15%. While the neural-based method has a slightly lower accuracy, it is about twice faster than the phrase-based method in terms of inference speed. Moreover, neural-based machine translation method has much room for future improvement such as incorporating pre-trained word embeddings and collecting more training data.
A Global View of Cross-Border Migration

This paper evaluates the welfare impact of observed levels of migration and remittances in both origins and destinations, using a quantitative multi-sector model of the global economy calibrated to aggregate and firm-level data on 60 developed and developing countries. Our framework accounts jointly for origin and destination characteristics, as well as the inherently multi-country nature of both migration and other forms of integration, such as international trade and remittance flows. In the presence of firm heterogeneity and imperfect competition larger countries enjoy a greater number of varieties and thus higher welfare, all else equal. Because of this effect, natives in countries that received a lot of migration – such as Canada or Australia – are better off. The remaining natives in countries with large emigration flows – such as Jamaica or El Salvador – are also better off due to migration, but for a different reason: remittances. The quantitative results show that the welfare impact of observed levels of migration is substantial, at about 5 to 10% for the main receiving countries and about 10% for the main sending countries.
Semi-supervised classification based on anchor-spatial graph for large polarimetric SAR data

Recently a few works of semi-supervised learning methods based on graph have been proposed for remote sensing. The common idea of these methods are that they build a graph using the samples of the image. Most of their time complexity is relatively large, and they ignore the spatial information of the image, which leads to unsatisfactory classification results. this paper proposes a novel semi-supervised classification method based on anchor-spatial graph for large PolSAR data. Firstly the unsupervised Wishart clustering is performed to select representative samples, which served as anchors according to the least distance between samples. Then an anchor graph is built using the selected anchors according to the multiple features of the samples. And it is further combined with the spatial information of the samples to construct an anchor-spatial graph. Finally the class information from small quantities of labeled samples propagates to the unlabeled ones. Experimental results show that the proposed method has a low time complexity compared with existing works and it could effectively cut down the processing time for large PolSAR data meanwhile keeps the classification accuracy.
An Intervention to Reduce Bicycle Injuries among Middle School Students in Rural China

This study aimed to evaluate the effectiveness of an intervention to reduce bicycle injuries among rural middle school students in China. A one-year cluster-randomized controlled trial was conducted with seventh grade students from six middle schools in two towns in rural Chaoshan, China. The two towns were randomly assigned to either the intervention or control group. Road safety education materials, two lectures on road safety, and a series of health education activities were delivered to 1312 students in the intervention group over one year, and the content of the intervention included traffic safety knowledge, methods of preventing bicycle injury and management of bicycle injuries. Questionnaires weere administered to the two groups before and after the intervention to measure the incidence, cognitions, and behaviors related to bicycle injuries. The pre-intervention incidence of bicycle injuries exhibited no significant difference between the two groups, while the difference reached significance after the intervention (χ2 = 13.409, p < 0.001). In the intervention group, the incidence decreased significantly after the intervention (χ2 = 8.137, p = 0.004), while no significant change was observed in the control group. Publicity and education intervention measures have certain short-term effects on the prevention of bicycle injuries among rural middle school students; we should approach intervention measures according to the characteristics of traffic injuries in different areas.
3-D LER and RDF Matching Performance of Nanowire FETs in Inversion, Accumulation, and Junctionless Modes

Nanowire field-effect transistors (NWFETs) have emerged as promising candidates for realization of advanced CMOS technology nodes. Due to small nanowire dimensions, NWFETs are vulnerable to the impact of process-induced random local variations, such as the line edge roughness (LER) and random dopant fluctuation (RDF). NWFETs have three different device modes, namely, the inversion mode (IM), the accumulation mode (AM), and the junctionless (JL) mode. In this paper, a 3-D quasi-atomistic LER model is used for the analysis of LER-induced mismatch in JL, IM, and AM NWFETs. We have also compared the impact of 3-D LER with that of 2-D LER. In addition, another emerging simulation methodology known as statistical impedance field method is utilized to analyze the impact of RDF on the three flavors of NWFETs. We show that JL NWFETs have much higher mismatch due to both LER and RDF than their IM and AM NWFET counterparts with otherwise identical device structure.
Efficacy and cost-effectiveness of consensus interferon monotherapy with high-dose induction for hepatitis C patients with genotype 2

Abstract Objective. Several treatment strategies for patients with chronic hepatitis C have been compared mainly in terms of their efficacy, and it has been found that pegylated interferon (IFN) plus ribavirin has become the standard therapy, but aged patients may not tolerate ribavirin and the cost-effectiveness of treatment should also be further considered. We conducted a study to evaluate the efficacy, safety, and cost-effectiveness of consensus IFN monotherapy with high-dose induction for patients with chronic hepatitis C in clinical practice. Material and Methods. We consecutively enrolled 104 patients with chronic hepatitis C. Patients were scheduled to receive 12 or 18 μg of consensus IFN daily for 2 weeks, then three times a week for 22 weeks. Efficacy, safety, and cost-effectiveness were assessed. A Markov model was developed to investigate cost-effectiveness in patients with chronic hepatitis C treated by different IFN-based treatment strategies. Results. Of the 104 study patients, a sustained virological response (SVR) was achieved in 66 (63%). Logistic regression analysis revealed that genotype 2, lower hepatitis C virus RNA levels, and patient age were independently associated with SVR. The response rate was significantly higher in patients with genotype 2 (51/66, 77%) versus genotype 1 (15/38, 40%). Cost-effectiveness analysis in patients with genotype 2 revealed that high-dose induction with consensus IFN monotherapy was as highly cost-effective as pegylated IFN plus ribavirin. Conclusion. Consensus IFN monotherapy with high-dose induction shows high efficacy and cost-effectiveness in chronic hepatitis C patients with genotype 2 infection. Thus, it may be a reliable alternative in aged patients and for those excluded from standard combination therapy.
Preparation of Monolithic Silica Aerogel of Low Thermal Conductivity by Ambient Pressure Drying

Monolithic silica aerogels with thermal conductivity as low as 0.036 W·(m·K)−1 and porosity as high as 97% were successfully prepared by ambient pressure drying through a multiple modification approach. This approach may replace the more costly and dangerous operation of supercritical drying. The tetraethoxysilane (TEOS)-derived wet gel was made hydrophobic with multiple treatments of trimethylchlorosilane and dried under ambient pressure. The multiple treatments were found to be necessary to achieve sufficient modification of the wet gel for reduction in drying-induced surface tension force to maintain product integrity and high porosity. Comparisons in nuclear magnetic resonance spectroscopy and Fourier transform infrared spectroscopy for surface bonding and contact angle measurement for hydrophobicity between the no, single, and multiple surface modification (MSM) samples were conducted to reveal the difference in the extent of the resulting surface modification. In conclusion, the MSM procedure reduced the volume shrinkage, increased the monolithicity and porosity, and lowered the thermal conductivity of the resulting aerogels.
Safety and tolerability of intensified, N‐terminal pro brain natriuretic peptide‐guided compared with standard medical therapy in elderly patients with congestive heart failure: results from TIME‐CHF

NT‐proBNP‐guided therapy results in intensification of medical heart failure (HF) therapy and is suggested to improve outcome. However, it is feared that an intensified, NT‐proBNP‐guided therapy carries a risk of adverse effects. Therefore, the safety and tolerability of NT‐proBNP‐guided therapy in the Trial of Intensified vs standard Medical therapy in Elderly patients with Congestive Heart Failure (TIME‐CHF) was assessed.
Deformable multi-scale scheme for biometric personal identification

Human identification has now been a social liability due to frequent terror threats and corrupt bureaucratic practices, especially in rural countries like India. It has been surprisingly observed that fingerprint quality is poor as compared with finger knuckle quality of rural users as they exist on the outer hand side. In this paper, we are proposing a novel finger-knuckle-print based identification system. Initially, finger knuckle image is pre-processed using proposed local and adaptive image transformations. Then, finger knuckle image matching has been performed using multi-scale Deep-Matching technique. Finally, score level fusion rule has been employed to achieve competitive performance over public FKP database.
DNA barcodes discriminate freshwater fishes from the Paraíba do Sul River Basin, São Paulo, Brazil

Background and aims: Considering the promising use of DNA barcoding for species identification, the importance of the freshwater fish fauna of the Paraíba do Sul River Basin, and its advanced stage of degradation, the present study evaluated the effectiveness of DNA barcoding to identify the fish species in this basin. Materials and methods: A total of 295 specimens representing 58 species belonging to 40 genera, 17 families, and 5 orders were sequenced. Results: The DNA barcodes discriminated all species analyzed without ambiguity. The results showed a pronounced difference between conspecific and congeneric pair-wise sequence comparisons, demonstrating the existence of a “barcode gap” for the species analyzed. The nearest-neighbor distance analysis showed only three cases with Kimura two-parameter values lower than a 2% divergence threshold. However, the patterns of divergence observed in each case remained sufficient to discriminate each species, revealing the accuracy of DNA barcoding even cases with relatively low genetic divergence. At the other extreme, three species displayed high genetic sequence divergence among conspecifics. For two cases, Characidium alipioi and Geophagus proximus, barcoding proved effective at flagging possible new species. For another case, Astyanax bimaculatus, the use of DNA barcoding of the comparison of shared freshwater fish fauna between different basins revealed itself as highly useful in disclosing that the previously identified A. bimaculatus “cluster A” probably represents the species Astyanax altiparanae. Conclusion: The present study is among the first to assess the efficiency of barcoding for the Brazilian freshwater fishes. The results demonstrate the utility of barcoding to identify the fauna from this basin, contribute to an enhanced understanding of the differentiation among species, and to help flag the presence of overlooked species.
The Oviduct and Serous Cancer Risk Assessment

Abstract : The proposal was designed to address three issues. First could we identify stem cells fromthe fallopian tube, including from patients with high grade serous cancer (HGSC). Second,could we link the molecular abnormalities in cancer associated stem cells and validate themin pathologic material, specifically in what we feel are stem cell outgrowths or SCOUTs andthird could we identify molecular alterations that would place the oviduct or the patient atrisk for HGSC. In essence we wished to drill down to the cell of origin and link it to cancerrisk, identifying an assay that could predict the presence of cancer by analyzing lowergenital tract fluids or other samples. All of these aims have been addressed and our studieshave reinforced the likelihood that novel pathways to ovarian cancer exist, but evidencepoints to more than one mechanism and site of origin.
Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes

We propose to model complex visual scenes using a non-parametric Bayesian model learned from weakly labelled images abundant on media sharing sites such as Flickr. Given weak image-level annotations of objects and attributes without locations or associations between them, our model aims to learn the appearance of object and attribute classes as well as their association on each object instance. Once learned, given an image, our model can be deployed to tackle a number of vision problems in a joint and coherent manner, including recognising objects in the scene (automatic object annotation), describing objects using their attributes (attribute prediction and association), and localising and delineating the objects (object detection and semantic segmentation). This is achieved by developing a novel Weakly Supervised Markov Random Field Stacked Indian Buffet Process (WS-MRF-SIBP) that models objects and attributes as latent factors and explicitly captures their correlations within and across superpixels. Extensive experiments on benchmark datasets demonstrate that our weakly supervised model significantly outperforms weakly supervised alternatives and is often comparable with existing strongly supervised models on a variety of tasks including semantic segmentation, automatic image annotation and retrieval based on object-attribute associations.
Graph-based resource allocation scheme in interference-restricted two-tier OFDMA femtocell networks

With the increasing requirements for seamless coverage and high date rate for indoor users, femtocells are widely used as a compliment to macrocells. In this paper, we primarily address the OFDMA downlink co-tier interference resulting from "plug-and-play" by resource partitioning in two-tier femtocell networks. The main objective is to achieve the maximization of system throughput despite the harmful downlink interference. For this purpose, a novel resource allocation scheme based on interference graph with QoS ensured is proposed, which consists of three parts, i.e. triangulation, clique degree and dynamic resource reuse. The proposed algorithm identifies the interference of each user in a more accurate way by clique degree, which is an extension of degree in conventional graph theory. As shown in our simulation results, the aggregate and average throughput of femtocells are increased obviously with the consideration of fairness for femtocell users.