Miracle-dz/UniFAR-FTUs huggingface dataset:
CONDIÇÕES DE SAÚDE ENTRE PROFISSIONAIS DA ATENÇÃO BÁSICA EM SAÚDE DO MUNICÍPIO DE SANTA MARIA - RS

Objective: To evaluate the health conditions and quality of life of primary healthcare professionals from Santa Maria, Rio Grande do Sul, Brazil. Material and Methods: This was a cross-sectional study performed in six primary healthcare units. The sample was composed by 42 professionals who responded a semi-open questionnaire and one healthcare facility was randomly selected to participate of a focus group. Quantitative and qualitative data were analyzed using descriptive statistics and thematic content analysis, respectively. Results: 60% of the sample presented pain or physical complaints, particularly musculoskeletal problems and headache. In addition, 48% of the professionals reported having had depressive episodes and not having looked for help; 55% of respondents considered themselves stressed out, while 50% and 40% of them did not perform physical or leisure activities, respectively. A total of 72% of the professionals reported that work affects their health and quality of life and 62% reported that their health influences the performance of their work in primary care. Conclusions: Primary healthcare professionals presented physical and emotional fatigue and showed low practice of healthy behaviors. This may be a result of their work routine, which compromises their quality of life. Despite providing a low-technology assistance, primary healthcare brings a great demand of workload, suggesting that the government policy focused on the workers’ health should have a special look into primary healthcare professionals. DESCRIPTORS Health Status. Health Personnel. Primary Health Care.
Control of risk factors for nephropathy among Nigerian outpatients with Type 2 diabetes mellitus

Background and Objectives : To determine the proportion of type 2 diabetic outpatients with adequate control of risk factors for nephropathy in a Nigerian teaching hospital. Methods : Between April and July 2005, 160 type 2 diabetic outpatients were assessed for control of average fasting blood glucose and blood pressure over 3 visits, and current use of ACE inhibitors. All patients were over 30 years of age and had been followed up for at least one year with at least 6 prior clinic visits. Results : We studied 58 male and 102 female subjects with a mean (±SD) age of 54±10 years. The majority (54.7%) had diabetes between 1 and 5 years, and 95% were on antidiabetic drugs, most commonly both a sulphonylurea and metformin (64.5%). 114 (71.2%) were being treated for hypertension. The mean fasting blood glucose (FBS) was 7.6±2.9mmol/L, and 73 (45.6%) had good glycaemic control (mean FBS≤ 5.6mmol/L). A total of 51 (31.9%) had good blood pressure control (<140/90mmHg in non-hypertensives and <130/80mmHg in hypertensives), and 73 (45.6%) were currently receiving ACE inhibitors. Only five (3.1%) had the combination of good glycaemic control, good blood pressure control and received ACE inhibitors. Conversely, 23 (14.4%) had a combination of poor glycaemic control, poor blood pressure control, and were not receiving ACE inhibitors. Duration of diabetes (p<0.01), elevated creatinine (p<0.01), and elevated systolic blood pressure (p<0.01) were independently associated with proteinuria. Conclusion : Despite the availability of measures to prevent the progression of diabetic nephropathy, control of risk factors was poor. Physicians and diabetic patients in Nigeria must work together to improve their management of risk factors for nephropathy. Key words : Diabetes mellitus, chronic kidney disease, renoprotection
Effects of spirituality training on the moral sensitivity of nursing students: A clinical randomized controlled trial

Training nurses on spiritual principles and values helps to stimulate moral imagery and a deep understanding of moral problems in them. However, spirituality issue was not included in ethical educational content. There was still no interventional study on the effect of spirituality education on ethical sensitivity. This study was conducted to determine the effect of spirituality training on moral sensitivity of nursing students. A randomized controlled trial design was used. Data were collected by a moral sensitivity questionnaire and analyzed using Chi-square, Fisher, independent and paired t-test in SPSS 13v. This research was performed on 60 nursing students of Kashan University of Medical Sciences, Iran, in 2018. Participants were randomly assigned to two groups. The intervention group was under the spirituality group training in seven 60 min sessions. The control group was traditionally trained. Baseline characteristics were similar in the two groups. The differences between the two groups were statistically significant in the moral sensitivity score (p < 0.0001). A significant difference was observed between the mean of moral sensitivity score of the intervention group, before and after the training (p < 0.001), while no significant change was observed in the control group, before and after the study (p = 0.93). The spirituality education increased the moral sensitivity of nursing students. That provides a new perspective on the role and effect of spirituality education on the ethical sensitivity of nursing students.
A Hedge Algebras Based Fuzzy Inference System for clustering in Multi-hop WSNs

To prolong the lifetime of wireless sensor networks, the clustering technique is a key point to create optimized sensor node groups for effective transmission processes. There are many factors affected the efficiency of clustering algorithms that come from uncertain characteristics of both inside and outside network conditions. Therefore, the fuzzy logic-based clustering technique can be seen as a promising technique since it allows combining and evaluating diverse parameters in an efficient sense. Moreover, the Fuzzy Inference System (FIS) is an efficient modeling tool to utilize the best input data features and expert knowledge for supporting appropriate decisions. However, using the human reasoning process to assign linguistic terms for setting fuzzy rules may lead to ineffective results because of intuitively heavily dependent problem. Otherwise, thanks to a good property of hedge algebras that provides a mathematical formalism for designing the order-based semantic structure of term domains of linguistic variables as a quantitative model. Hence, this paper proposes a novel fuzzy inference system based hedge algebras which combine for forming clusters in multi-hop sensor networks. The numerical results are shown in this paper to validate the efficiency of the proposed model.
Draw with me: human-in-the-loop for image restoration

The purpose of image restoration is to recover the original state of damaged images. To overcome the disadvantages of the traditional, manual image restoration process, like the high time consumption and required domain knowledge, automatic inpainting methods have been developed. These methods, however, can have limitations for complex images and may require a lot of input data. To mitigate those, we present "interactive Deep Image Prior", a combination of manual and automated, Deep-Image-Prior-based restoration in the form of an interactive process with the human in the loop. In this process a human can iteratively embed knowledge to provide guidance and control for the automated inpainting process. For this purpose, we extended Deep Image Prior with a user interface which we subsequently analyzed in a user study. Our key question is whether the interactivity increases the restoration quality subjectively and objectively. Secondarily, we were also interested in how such a collaborative system is perceived by users. Our evaluation shows that, even with very little human guidance, our interactive approach has a restoration performance on par or superior to other methods. Meanwhile, very positive results of our user study suggest that learning systems with the human-in-the-loop positively contribute to user satisfaction. We therefore conclude that an interactive, cooperative approach is a viable option for image restoration and potentially other ML tasks where human knowledge can be a correcting or guiding influence.
Understanding the effectiveness of adaptive guidance for narrative visualization: a gaze-based analysis

We study the effectiveness of adaptive guidance at helping users process textual documents with embedded visualizations, known as narrative visualizations. We do so by leveraging eye tracking to analyze in depth the effect that adaptations meant to guide the user's gaze to relevant parts of the visualizations has on users with different levels of visualization literacy. Results indicate that the adaptations succeed in guiding attention to salient components of the narrative visualizations, especially by generating more transitions between key components of the visualization (i.e., datapoints, labels and legend). We also show that the adaptation helps users with lower levels of visualization literacy to better map datapoints to the legend, which leads in part to improved comprehension of the visualization. These findings shed light on how adaptive guidance helps users with different levels of visualization literacy, informing the design of personalized narrative visualizations.
Towards In-network Acceleration of Erasure Coding

In distributed storage systems, erasure coding (EC) is a crucial technology to enable high fault tolerance with lower storage overheads than data replication. EC can reconstruct missing data by downloading parity data from survived machines. However, downloading streams of EC multiplex the available network I/O on the receiving end, leading to a substantially low data reconstruction speed. In this paper, we present NetEC, a novel in-network accelerating system that fully offloads EC to programmable switching ASICs. NetEC prevents multiplexing network I/O through on-switch downloading stream aggregation, thus significantly improving reconstruction speed. NetEC addresses three key challenges: computation offloading of complex EC operations, rate synchronization of multiple downloading streams, and deep payload inspection/assembly. We implement NetEC on hardware programmable switches. Evaluation shows that compared to HDFS-EC, NetEC significantly improves reconstruction rate by 2.7x-9.0x and eliminates CPU overheads, with low switch memory usage.
Calibration of game dynamics for a more even multi-player experience

When designing a serious game it is paramount to take into account that the players' performance may greatly vary. In many types of games the performance will impact the game experience, as it is related to a point acquisition mechanic. In specific contexts, such as multi-player non-competitive or collaborative games, the designer may desire to minimize this variability, reducing the difference in game progression between low-performing and high-performing players. In this paper we detail such a context: an educational serious game for sustainability addressed to classes of a primary school, where the low performance of a class may not be necessarily related to the children's effort. We thus present and evaluate a novel approach for the calibration of the game dynamics for achieving a more even player experience.
SSVEP Offline Analysis Procedures for Low Cost BCI Systems

Setting low-cost brain computer interfaces (BCIs) has been a topic of interest in developing countries. There is a variety of EEG equipment, and mathematical techniques that can help achieve this goal, but some of these techniques may have some flaws by their own. A low complexity alternative using an OpenBCI optimized equipment and based on two mathematical techniques here is discussed for an ongoing develoment of a low-cost BCI project. The selected techniques for data analysis inspection are linear discriminant analysis (LDA) and multivariate synchronization index (MSI). The procedure will be shown from the basics, the OpenBCI optimized equipment is validated offline against a g.Nautilus EEG and the performance of the techniques is shown individually. Therefore, it is discussed the possibility of combining both feature extraction techniques (LDA and MSI) for steady state visual evoked potentials (SSVEP), in order to achieve a concept with better performance for an SSVEP BCI.
PororoGAN: An Improved Story Visualization Model on Pororo-SV Dataset

Generating a sequence of images from a multi-sentence paragraph is a recently proposed task called Story-Visualization. In this task, how to keep the global consistency across dynamic scenes and characters in the story flow is the distinct difference from other single-image works, which is also a significant challenge. However, the visual quality and semantic relevance of existing results are not satisfying when handling datasets with high semantic complexity, such as Pororo-SV cartoon dataset. To address this issue, we propose a new story visualization model named PororoGAN, which jointly considers story-to-image-sequence, sentence-to-image and word-to-image-patch alignment. In particular, we introduce ASE (aligned sentence encoder) and AWE (attentional word encoder) to improve global and local relevance, respectively. Additionally, we add an image patches discriminator to improve the reality of results. Both quantitative and qualitative studies show that PororoGAN outperforms the state-of-the-art models.
Ultrasound shear wave elastography and liver biopsy to determine liver fibrosis in adult patients

Introduction: Liver biopsy is considered as the gold standard for diagnosis of chronic liver disease, yet liver biopsy is an invasive method that may be associated with complications. Therefore, non-invasive methods are needed to diagnose fibrosis. This study was conducted to compare liver stiffness measured by Shear-wave Elastography (SWE) to fibrosis in liver biopsy. Method and Materials: In this prospective study, 176 adult patients with chronic liver disease of different etiologies were included. All patients were evaluated using SWE and a liver biopsy. The diagnostic accuracy of SWE was evaluated using receiver operating characteristics (ROC) plots based on the degree of fibrosis (METAVIR score). SPSS software version 19 was used for statistical analysis and P < 0.05 considered significant. Results: There was a significant correlation between liver stiffness and fibrosis stage (ρ=0.939; P < 0.0001). The ROC curve AUC were 0.871, 0.895 and 0.937 for fibrosis stages F2, F3 and F4 respectively. The cutoff values were 8.6 kPa for F2, 10.7 kPa for F3, and 13.8 kPa for F4, with sensitivity and specificity of 81.76% and 77.01%, 90.20% and 78.40%, 89.53% and 94.38% respectively. Conclusion: The results of this study showed that liver SWE is an effective non-invasive method for assessing liver fibrosis in patients with chronic liver disease of different etiologies.
A distinct fibro-osseous lesion of the jaws affecting the maxilla

The differential diagnosis of fibro-osseous lesions (FOL) presents oral clinician stomatologists with a challenging task because of their similar clinical, radiographic and histopathological behavior that will also hinder the therapeutic planning. Presentation of case to describe the clinical, radiographic and histopathological features of an unusual case of FOL presented by the patient, a Black woman, and the results obtained with the conservative surgical treatment and 3-month follow-up. The presence of cementum in the histopathological analysis of cemento-osseous dysplasias, according to the current literature, is an important factor for the diagnosis of this lesion. Considering the characteristics presented by this particular case, we could suggest another entity that could be named a benign cemento-osseous lesion with adult onset. Some occurrences, as in the present case, do not fit properly into the current World Health Organization classification, thereby generating some doubts concerning the correct management of these patients. Conservative surgical treatment is the first choice in the management of these lesions due to their self-limiting nature, which show a behavior of clinical involution.
Predictors of dengue-related mortality in young adults in a tertiary care centre in North India

Background: Outbreaks of dengue fever cause widespread mortality. There is a paucity of studies on predictors of morbidity and mortality in dengue. This observational study was performed to study the factors predicting adverse outcomes caused due to dengue fever thereby optimally manage the patient's to reduce mortality. Methods: The study included a 1-year retrospective and 1-year prospective period were clinical, laboratory and outcome data of patients between 18–30 years of age, having serology proven (NS1/dengue IgM) dengue fever were recorded and analysed. Results: Out of 418 patients, 404 (96.64%) recovered and 14 (3.35%) expired, resulting in a 3.35% mortality rate. Platelet count did not determine the outcome in dengue patients. The shock factor was present in 45 (11.1%) patients who recovered and 10 out of 14 patients who expired (71.4%), P value was statistically significant. Mean value of SGOT and SGPT in dengue patients who expired were 2865.43 and 1510.07 IU/L, respectively, which were significantly higher than the mean values of SGOT and SGPT in those who survived. Bleeding was present in 39 (9.7%) patients who recovered. Out of the 14 expired patients, bleeding was present in 5 (35.7%) which is statistically significant. Hence, on multivariate logistics analysis, bleeding, a higher SGOT and SGPT value and shock were found to be significant risk factors for mortality in dengue fever patients. Conclusion: Bleeding, shock and raised SGOT and SGPT levels were identified as predictors of adverse outcomes and mortality in dengue fever. Timely identification of these risk factors and active management is important to reduce dengue-related mortality.
Effectiveness of cognitive behavioral therapy and basic health education for tobacco cessation among adult tobacco users attending a private tobacco cessation center

Background: India being major consumer of tobacco faces various problems involved for its cessation. Over the time enormous methods have been evolved which may aid in tobacco cessation. Materials and Methods: The present study was conducted among 100 adult tobacco users attending tobacco cessation clinic. The individuals where randomized into 2 counselling groups: Group A - Basic health education (BHE) and Group B Cognitive Behavioral Therapy (CBT). Baseline evaluation of demographic parameters, smoking/smokeless behavior was recorded and Fagerstrom's test for Nicotine Dependence (FTND) was utilized to assess subjects' nicotine addiction levels. Follow up was done at intervals of 2 weeks and 4 weeks to assess the reduction in the mean FTND score. Appropriate statistical test was utilized to evaluate the results. Results: The majority of individuals in the study were male in age group of 41-60 years. The reduction in mean FTND score was found in both Group A and B on follow-up. But when both groups were compared, reductions in mean Fagerstrom scores were found to be more in CBT group than in BHE group at all time intervals. Conclusion: Individuals in both the group have quit the tobacco use by both the interventions followed by proper schematic follow up.
3D Tracking of Human Motion Using Visual Skeletonization and Stereoscopic Vision

The design of markerless systems to reconstruct human motion in a timely, unobtrusive and externally valid manner is still an open challenge. Artificial intelligence algorithms based on automatic landmarks identification on video images opened to a new approach, potentially e-viable with low-cost hardware. OpenPose is a library that t using a two-branch convolutional neural network allows for the recognition of skeletons in the scene. Although OpenPose-based solutions are spreading, their metrological performances relative to video setup are still largely unexplored. This paper aimed at validating a two-cameras OpenPose-based markerless system for gait analysis, considering its accuracy relative to three factors: cameras' relative distance, gait direction and video resolution. Two volunteers performed a walking test within a gait analysis laboratory. A marker-based optical motion capture system was taken as a reference. Procedures involved: calibration of the stereoscopic system; acquisition of video recordings, simultaneously with the reference marker-based system; video processing within OpenPose to extract the subject's skeleton; videos synchronization; triangulation of the skeletons in the two videos to obtain the 3D coordinates of the joints. Two set of parameters were considered for the accuracy assessment: errors in trajectory reconstruction and error in selected gait space-temporal parameters (step length, swing and stance time). The lowest error in trajectories (~20 mm) was obtained with cameras 1.8 m apart, highest resolution and straight gait, and the highest (~60 mm) with the 1.0 m, low resolution and diagonal gait configuration. The OpenPose-based system tended to underestimate step length of about 1.5 cm, while no systematic biases were found for swing/stance time. Step length significantly changed according to gait direction (p = 0.008), camera distance (p = 0.020), and resolution (p < 0.001). Among stance and swing times, the lowest errors (0.02 and 0.05 s for stance and swing, respectively) were obtained with the 1 m, highest resolution and straight gait configuration. These findings confirm the feasibility of tracking kinematics and gait parameters of a single subject in a 3D space using two low-cost webcams and the OpenPose engine. In particular, the maximization of cameras distance and video resolution enabled to achieve the highest metrological performances.
Exploring the HeLa Dark Mitochondrial Proteome

In the framework of the Human Proteome Project initiative, we aim to improve mapping and characterization of mitochondrial proteome. In this work we implemented an experimental workflow, combining classical biochemical enrichments and mass spectrometry, to pursue a much deeper definition of mitochondrial proteome and possibly mine mitochondrial uncharacterized dark proteins. We fractionated in two compartments mitochondria enriched from HeLa cells in order to annotate 4230 proteins in both fraction by means of a multiple-enzyme digestion (trypsin, chymotrypsin and Glu-C) followed by mass spectrometry analysis using a combination of Data Dependent Acquisition (DDA) and Data Independent Acquisition (DIA). We detected 22 mitochondrial dark proteins not annotated for their function and we provide their relative abundance inside the mitochondrial organelle. Considering this work as a pilot study we expect that the same approach, in different biological system, could represent an advancement in the characterization of the human mitochondrial proteome providing uncharted ground to explore the mitonuclear phenotypic relationships. All spectra have been deposited to ProteomeXchange with PXD014201 and PXD014200 identifier.