Miracle-dz/UniFAR-FTUs huggingface dataset:
Proximal Algorithms for Structured Nonconvex Optimization

Due to their simplicity and versatility, splitting algorithms are often the methods of choice for many optimization problems arising in engineering. “Splitting” complex problems into simpler subtasks, their complexity scales well with problem size, making them particularly suitable for large-scale applications where other popular methods such as IP or SQP cannot be employed. There are, however, two major downsides: 1) there is no satisfactory theory in support of their employment for nonconvex problems, and 2) their efficacy is severely affected by ill conditioning. Many attempts have been made to overcome these issues, but only incomplete or case-specific theories have been established, and some enhancements have been proposed which however either fail to preserve the simplicity of the original algorithms, or can only offer local convergence guarantees. This thesis aims at overcoming these downsides. First, we provide novel tight convergence results for the popular DRS and ADMM schemes for nonconvex problems, through an elegant unified framework reminiscent of Lyapunov stability theory. “Proximal envelopes”, whose analysis is here extended to nonconvex problems, prove to be the suitable Lyapunov functions. Furthermore, based on these results we develop enhancements of splitting algorithms, the first that 1) preserve complexity and convergence properties, 2) are suitable for nonconvex problems, and 3) achieve asymptotic superlinear rates.
Aging, cognitive decline, apolipoprotein E and docosahexaenoic acid metabolism

In Canada, ∼17 millions of adults between 30–64 years old could benefit from a prevention strategy to lower the risk of Alzheimer’s disease (AD). My group is working on a population that is particularly at risk of AD, the carriers of an epsilon 4 allele of apolipoprotein E (E4), a genetic risk. Around 20% of the population in industrial countries have this genetic risk but not all carriers will develop AD, suggesting that environmental factors modulate the clinical manifestation and risk of AD in the carriers. My group has discovered that the metabolism of docosahexaenoic acid (DHA) is disrupted during aging and in E4 carriers, a finding replicated in homozygous mice knocked-in for human E4 allele (hAPOE4). We recently showed that a diet containing DHA prevented behavioral deficits in hAPOE4 mice. Another group reported in E4 carriers that the ratio of arachidonic acid (ARA): DHA is disrupted in the plasma and constitute a preclinical marker of mild cognitive impairment/AD in E4 carriers. Using our kinetics approaches with uniformly labelled carbon 13 fatty acids, we showed that the kinetics of 13C-DHA is modified by age and E4 carriage. The kinetics of 13C-arachidonic acid was however not modified by age conversely to that of 13C-eicosapentaenoic acid (EPA). We also reported that the synthesis of 13C-DHA from 13C-EPA started 2 h after the tracer intake in older adults conversely to 7 d in young men. Whether old men needs in DHA is higher or whether their ability to use it is lower remains to be established. These differences in the DHA and EPA metabolism seems, however related to physiological modifications occurring during aging and in E4 carriers and obscure the relationship between plasma DHA and EPA levels, dietary fatty fish intake and cognitive status.
Early tracheostomy in patient with severe traumatic brain injury clinical experiences in rural and remote areas

Background: Brain injury accounts for most of the causes of death from trauma. Brain injury is defined as a change in brain function, or brain pathology, caused by external forces. Patients with severe brain injury usually required rapid evacuation and special care in the Intensive Care Unit (ICU) room for respiratory control, mechanical ventilation, neurosurgical evaluation, and intracranial pressure monitoring (ICP). During admission to ICU, patients using tracheostomy, because it requires analgesia, sedation, and prolonged ventilation.Methods: Descriptive retrospective study conducted in February and March 2018 at Medical Record Installation of General Hospital Province of West Nusa Tenggara. The sample size is determined by consecutive sampling method.Results: Sample size were 60 people from medical record. Male patient more common than female (90 %). Based on Age more patients are 40 years old (43.3%). More Patient with early tracheostomy was survived (68,33%), and the rest died (31,67%). Conclusions: Severe head injury patients with tracheostomy are common at <18 years and >40 years. Patients with Severe brain injury who get early tracheostomy have more good outcomes, and have relatively short duration of ICU care.
Think Spatially With Game Engine

Spatial thinking and spatial orientation skills are involved in tasks related to the recognition of landforms, mapping, spatial interpretation, and landscape analysis, and can be developed with specific training. Game engines can facilitate the creation of 3D virtual landforms and provide powerful rendering engines for the graphical representation of landscapes from a first-person perspective. In the present research, 27 engineering students participated in a workshop in a first-person virtual environment using landforms created with a game engine. The Spatial Thinking Ability Test and the Perspective Taking-Spatial Orientation Test measured improvement in spatial thinking and spatial orientation as a result of this workshop. The gain in spatial thinking (8.31%) is within the range observed in previous research in the field of geography using a web-based GIS strategy (7.31%–10.00%). The gain in Spatial Orientation skill (15.76%) is comparable with previous research using both first-person strategies based in urban virtual environments (14.23%), and Spatial Data Infrastructures (gains between 21.17% and 21.34%). Participants with better self-reported sense of direction had better performance on the spatial orientation test.
TYPE 2 DIABETIC PATIENTS

Background: Peripheral neuropathic pain is a devastating complication intype 2 diabetic patients with significant morbidity and mortality. Objectives: To investigate theeffect of oral vitamin D supplementation on symptoms of peripheral neuropathic pain in type 2diabetic patients. Study Design: Prospective randomized placebo controlled trial. Setting:Diabetic Clinic of Sheikh Zayed Medical College/Hospital Rahim Yar Khan. Period: Overa period of 6 months from Jan-July 2017. Methods: 116 vitamin D deficient type 2 diabeticpatients with symptoms of peripheral neuropathic pain were divided in to two groups toprescribed either oral vitamin D3 capsule 50000IU weekly or Placebo capsule for a periodof 12 weeks. Symptoms of diabetic neuropathic pain were assessed by neuropathysymptoms score (NSS) and neuropathy disability score (NDS) while Vitamin D status wasestimated by measuring the serum total 25(OH) D concentration. The primary end pointwas changes in NSS and NDS while secondary end point was changes in HbA1C and 25(OH) D concentrations from baseline. Results: After 12 weeks of vitamin D therapy, vitaminD improved its own level in interventional group (28.5±12.5 to 48.2±15.6) vs placebo group(30.6±16.2 to31.5±12.6) with p-value (0.001). This rise was accompanied by improvementin HbAIc (8.2±1.8 to 7.5±2.2) vs Placebo (7.8±1.5 to 8.0±1.8) with p-value (0.004) and NSSscore (6.02±1.5 to 4.52±0.8) vs placebo (5.82 ±1.8 to 5.65±1.5) with p-value (0.002). Howeverno significant changes were seen in NDS in both study groups. Conclusion: Oral vitamin D3therapy has positive impact on its own status as well as symptoms of peripheral neuropathicpain in type 2 diabetic patients.
Methods and Materials of the Social networks and fertility survey (Sociale relaties en kinderkeuzes)

Here you can find methods and materials of the Social networks and fertility survey (Sociale relaties en kinderkeuzes), including: 1) A short description on the sample and how it was obtained; 2) A codebook in Dutch (and English translation) with all survey questions and variable names; 3) JavaScript files to produce the GENSI-survey; 4) The link to the survey: https://stulp.gmw. rug.nl/phptmp/survey.php; 5) R-code to process all variables and correct errors in LISS-panel data; 6) R-code to process all alter-alter-relationships and correct errors; 7) csv-files that describe all manual classifications.
Prevalencia de la sintomatología respiratoria en trabajadores mineros del municipio de Socotá, Boyacá, 2017

Introduction. Mining has been related to respiratory health problems, caused by exposure to carbon and various air suspended components that remain in mines, this particulate material increments the risk to contract respiratory diseases, classically manifest by cough, expectoration, hemoptysis and chest pain, and other symptoms.Objective. To determine the prevalence of respiratory symptoms in mining workers of Socota City (Boyaca) on December 2017.Methods. An observational, descriptive and cross-sectional study was carried out. 794 workers were included to screen symptoms indicative of an important respiratory disorder, giving great importance to the definition of respiratory symptoms.Results. There was predominance of age group between 36 to 45 years (240 individuals, 30.23%). Most symptomatic group was B group, who had 48 to 69 months working. The prevalence of respiratory was 5% (n = 40). The most prevalent symptom was fatigue 16.88% (n = 134), When doing a multivariate logistic regression divided by a stratification in months of work and making the comparison of whole population against group B (48 to 96 months), the symptoms of weight loss, sweating and chest pain show a statistically significant relationship.Conclusions. Respiratory symptoms prevalence was low, about 5% (n = 40) in this population. However, the regression gave an indication that appearance of symptoms is proportional to time of occupational exposure.
Cloud-Driven Multi-Way Multiple-Antenna Relay Systems: Joint Detection, Best-User-Link Selection and Analysis

In this work, we present a cloud-driven uplink framework for multi-way multiple-antenna relay systems which aids joint symbol detection in the cloud and where users are selected to simultaneously transmit to each other aided by relays. We also investigate relay selection techniques for the proposed cloud-driven uplink framework that uses cloud-based buffers and XOR network coding. In particular, we develop a novel multi-way relay selection protocol based on the selection of the best link, denoted as Multi-Way Cloud-Driven Best-User-Link (MWC-Best-User-Link). We then devise maximum-minimum-distance and channel-norm based relay selection criteria along with algorithms that are incorporated into the proposed MWC-Best-User-Link protocol. An analysis of the proposed MWC-Best-User-Link protocol in terms of computational cost, pairwise error probability, sum-rate and average delay is carried out. Simulations show that MWC-Best-User-Link outperforms previous works in terms of sum-rate, pairwise error probability, average delay and bit error rate.
Link Adaptation on an Underwater Communications Network Using Machine Learning Algorithms: Boosted Regression Tree Approach

Interest in the study of next-generation underwater sensor networks for ocean investigations has increased owing to developing concerns over their utilization in areas such as oceanography, commercial operations in maritime areas, and military surveillance. Underwater acoustic communications (UAC) network channels are fast-varying (spatially and temporally) according to environmental conditions. It is tempting to use adaptive modulation and coding (AMC) for UAC networks to improve the system efficiency by matching transmission parameters to channel variations. This paper focuses on analyzing a measured sea trial dataset by using a rule-based strategy (i.e., three-dimensional analysis, modulation-wise analysis, and a fixed-SNR strategy) to find the suitable link adaptation procedure depending on the channel quality. Hence, we plot a scenario of the measured UAC network data rate vs. Signal to Noise Ratio (SNR) and/or Bit Error Rate (BER) to pick the best AMC combinations in the context of adaptivity to the channel. Due to non-reversibility limitation of rule-based strategy, the work further extends to use machine learning (ML) algorithms to classify the MCS levels by investigating the channel characteristics. Boosted regression tree, from among the four ML algorithms we adopted for the analysis, shows formidable accuracy of 99.97% in classifying MCS levels. This ensemble of trees learns from the uplink data of the buoy and the base station and relates the MCS levels to channel metrics and signal characteristics especially subject to SNR and BER constraints.
The Effect of Dental Unit Waterline Flushing on the Quality of Water in Dental Teaching Center in Malaysia

The aim of this study to assess the efficiency of flushing method of Dental Unit Waterline (DUWL) system in reducing the number of microorganism. Water samples were taken before and after two minutes of flushing from air-water syringes system in ten randomly selected dental units in a Dental Teaching Centre. These samples were immediately transferred to the microbiology laboratory in the cool box within 8 hours for the heterotrophic plate count (HPC) test. Paired t-test was used to analyse number of microbe before and after flushing. The numbers of colony forming unit (CFU) ranged from 13,000 to 120,000CFU/ml in unflushed samples, and 3,000 to 15,000CFU/ml in flushed samples. The mean HPC post-flushing was lower than pre-flushing [8360.00 (4561.48) vs 63300.00 (44587.12) CFU/ml]. The mean HPC between pre- and post-flushing was significantly different (P=0.004, 95% CI 22039.52, 87840.48). The coliform count from the control was 140 CFU/ml. In conclusion, flushing method of DUWL system significantly reduces the number of microorganisms in the dental unit. However, the level of microorganisms still does not meet the standard guideline by Environmental Protection Agency for safe drinking water, which should be below 500 CFU/ml. In our opinion, the duration of flushing should be increased and additional chemical treatments of the dental units should be implemented to ensure the safety of patients and dental personnel.
Does level of training predetermine the success rate of prehospital sepsis assessment? A prospective survey on early recognition

Sepsis is a challenge for health professionals. The increasing number of cases emphasizes the importance of early recognition resulting in better survival. Questionnaires were spread focusing on the prehospital recognition, treatment, and care pathway of septic patients. After presenting an initial scenario, other sepsis-like diseases were given as diagnosis of choice and the answers were registered. After redefining the situation, the same potential diagnoses were given and the difference in correct answers was detected. The number of responders was 120. Among them, 33% of responders chose hypovolaemia, 10% allergic reaction, 2.5% endocrine disease, 30.8% systemic inflammatory response syndrome/sepsis, 0.83% internal bleeding, 0.83% drug effect, 2.5% pulmonary embolism, and 19.17% metabolic disorder as primary diagnosis with a significantly higher number of trained paramedics highlighting the correct answer. After redefining the scenario, 63% changed the diagnosis, while 37% did not change (p < .001). Further management was correctly chosen by the majority of responders. The small number of correct answers from non-paramedics highlights the need for more education in identifying the pitfalls of early recognition and therapy of those who attend patients first. Trained paramedics recognize the sepsis better than other representatives, necessitating the introduction of new guidelines.
Multi-object Cosegmentation Using Density-based Clustering

Cosegmentation is one of the interesting and popular topics in computer vision. The goal of cosegmentation is to extract the common foreground objects from an image set with minimum additional information. The existing cosegmentation algorithms could be classified into two categories. One is to extract one kind of foreground objects in the image set under unsupervised approaches; the other one is to find different kinds of common foreground objects in the image set under supervised approaches of which the number of kinds should be predefined. In this paper, we propose an unsupervised cosegmentation method for multiple foreground objects, which need not preset the number of object kinds. Moreover, most of the existing cosegmentation algorithms assume that the common foreground objects should appear in all images of the image set. However, if the foreground object only appears in a few images, the object is often misclassified. Our proposed algorithm can segment different kinds of common objects and have a higher segmentation rate for some foreground objects not appearing in all images. In the proposed work, an image is considered as the combination of several objects, and each object is composed of object elements. The image set could be decomposed into lots of object elements, and then object elements with similar features could be clustered into one sub-object class representing one part of an object. According to the class distribution of elements, common objects are extracted by the selection criteria. The concept of independent object elements is also proposed to increase the segmentation rate. In the experimental results, we demonstrate that the proposed approach could get better segmentation results compared with other methods.
Highly active antiretroviral therapy increases fibrinolytic and protein activity in pregnant women

BACKGROUNDVarious studies have examined optimal methods for Prevention of Mother to Child Transmission (PMTCT) of human immunodeficiency virus (HIV) and subsequent outcome of response to highly active antiretroviral therapy (HAART) as well as the impact of pregnancy on outcomes of HIV in the Pre-HAART era. Little is known of the impact of pregnancy in response to HAART in Africa. This study is aimed to evaluate euglobulin lysis time (ELT), protein C and protein S in HIV-positive pregnant women on HAART. METHODSThis was a cross-sectional study comprised of 150 participants attending Ante-Natal Clinic (ANC) in Central Hospital, Benin City. Pregnant women on HAART (Test subjects) (n=50, mean age 34 years), 50 pregnant newly diagnosed HIV-positive women that had not yet commenced HAART (n=50, mean age 31 years) and 50 pregnant HIV-negative women (n=50, mean age 30 years) which served as controls. The ELT was determined by methods described by Bain, protein C and protein S were determined using Enzyme Linked Immunosorbent Assay (ELISA). RESULTSThere was a significant increase in ELT in both pregnant women on HAART and not on HAART) when compared to HIV-negative pregnant women (p<0.05). There was a significant decrease in protein C in test subjects when compared with controls (p<0.05) and protein S increased significantly in HIV-positive pregnant women on HAART when compared to those not on HAART and HIV-negative pregnant women (p<0.05). CONCLUSIONThere are changes in ELT, protein C and protein S parameters with the introduction of HAART in pregnancy.
Chemotherapy adherence is a favorable prognostic factor for elderly patients with multiple myeloma who are treated with a frontline bortezomib-containing regimen

Background Elderly patients with multiple myeloma (MM) are vulnerable to adverse events (AEs). This study evaluated adherence to chemotherapy and treatment outcomes in elderly patients treated with a frontline bortezomib (BTZ), melphalan, and prednisone (VMP) regimen and regimens without BTZ. Methods One-hundred and forty elderly patients who were diagnosed with MM from March 2007 to March 2015 were included in this retrospective study. To evaluate regimen adherence, patients who were treated with more than 4 cycles were assigned to the good adherence group. Results Among the 140 patients, 71 were treated with a frontline VMP and 69 with non-BTZ regimens. The median age was 71 years (range, 65-90 years). The VMP group showed a higher complete response rate than the non-BTZ group: 26.8% vs. 7.2%. More patients in the VMP group achieved ≥very good partial response (VGPR) and ≥PR. In the VMP group, 27 patients (38.0%) received less than 4 cycles. The VMP good adherence group showed a higher 3-year overall survival (OS) rate (70.9%) than the poor adherence group (60.2%, p=0.059). In the multivariate analysis, treatment with ≥4 cycles of VMP was a favorable factor for OS. Conclusion A good adherence to a frontline VMP regimen resulted in favorable long-term survival. Adequate management of AEs will be needed to achieve favorable outcomes in elderly patients with MM.
Diabetes and Metabolic Syndrome: Clinical Research and Reviews

Nephropathy in diabetes patients is the most common etiology of end-stage kidney disease (ESKD). Strict glycemic control reduces the development and progression of diabetes-related complications, and there is evidence that improved metabolic control improves outcomes in subjects having diabetes mellitus with advanced chronic kidney disease (CKD). Glycemic control in people with kidney disease is complex. Changes in glucose and insulin homoeostasis may occur as a consequence of loss of kidney function and dialysis. The reliability of measures of long-term glycemic control is affected by CKD and the accuracy of glycated haemoglobin (HbA1c) in the setting of CKD and ESKD is questioned. Despite the altered character of diabetes in CKD, current guidelines for diabetes management are not specifically adjusted for this patient group. The validity of indicators of long-term glycemic control has been the focus of increased recent research. This review discusses the current understanding of commonly used indicators of metabolic control (HbA1c, fructosamine, glycated albumin) in the setting of advanced CKD.
Chinese researchers' perceptions and use of open access journals: Results of an online questionnaire survey

This paper reports the results of a survey on Chinese researchers' perceptions and use of open access journals (OAJs). A total of 381 Chinese researchers from different universities and disciplines were investigated through an online questionnaire survey in August and September 2018. The results showed that most Chinese researchers are familiar with and have positive attitude to OAJs. They know OAJs mainly through their peers, colleagues, and friends. PubMed Central, PLoS, and COAJ (China Open Access Journals) are the most well‐known OAJ websites among Chinese researchers. As for use, most of the respondents read and cite OAJs frequently and have experience of publishing in OAJs. However, they strongly prefer to use OAJs indexed in reputable databases (e.g. Web of Science, WoS) when making publishing decisions. Significant differences can be seen among disciplines, with researchers in HSS areas using OAJs less frequently than researchers from other disciplines, although they have the same positive attitudes and are equally well informed about them. Younger researchers preferred to rely on prestigious institutions and authors when using OAJs.