Miracle-dz/UniFAR-FTUs huggingface dataset:
Pembandingan Stabilitas Algoritma Seleksi Fitur menggunakan Transformasi Ranking Normal

We address the need for evaluating the ranking robustness on different classifiers in feature selection algorithm. We propose a normalized rank transformation metric to compare the stability on classifying target class on training and testing dataset. Using stability comparison is a promising effort to improve the choice decision on deploying any feature selection algorithms. We also show relationship between stability and scalability.
Monte Carlo averaging for uncertainty estimation in neural networks

Although convolutional neural networks (CNNs) are widely used in modern classifiers, they are affected by overfitting and lack robustness leading to overconfident false predictions (FPs). By preventing FPs, certain consequences (such as accidents and financial losses) can be avoided and the use of CNNs in safety- and/or mission-critical applications would be effective. In this work, we aim to improve the separability of true predictions (TPs) and FPs by enforcing the confidence determining uncertainty to be high for TPs and low for FPs. To achieve this, we must devise a suitable method. We proposed the use of Monte Carlo averaging (MCA) and thus compare it with related methods, such as baseline (single CNN), Monte Carlo dropout (MCD), ensemble, and mixture of Monte Carlo dropout (MMCD). This comparison is performed using the results of experiments conducted on four datasets with three different architectures. The results show that MCA performs as well as or even better than MMCD, which in turn performs better than baseline, ensemble, and MCD. Consequently, MCA could be used instead of MMCD for uncertainty estimation, especially because it does not require a predefined distribution and it is less expensive than MMCD.
SNER-CS: Self-training Named Entity Recognition in Computer Science

As the number of scientific publications grows, especially in computer science domain (CS), it is important to extract scientific entities from a large number of CS publications. Distantly supervised methods, generating distantly annotated training data by string match with external dictionary automatically, have been widely used in named entity recognition task. However, there are two challenges to use distantly supervised methods in computer science NER task. One is that more and more new tasks, methods and datasets in CS are proposed rapidly, which makes it difficult to build a computer science entity knowledge base with high coverage. The other is noisy annotation, because there is no uniform entity representation standard in computer science domain. To alleviate the two problems above, we propose a novel self-training method based pretraining language model with a distantly supervised label automatic construction system in CS (SNER-CS). Experimental results show that the proposed model SNER-CS performs previous state-of-the-art methods in computer science NER task.
PILOT: A Pixel Intensity Driven Illuminant Color Estimation Framework for Color Constancy

In this study, a CNN based Pixel Intensity driven iLluminant cOlor esTimation framework, PILOT, is proposed. The framework consists of a local illuminant estimation module and an illuminant uncertainty prediction module, obtained using a 3-phase training approach. The network with the well-designed microarchitecture of distillation building block and the macroarchitecture of bifurcated organization is of great representational capacity and efficacy for color-relevant vision tasks, which helps obtain a >20% relative improvement over prior algorithms and achieve state-of-the-art accuracy of illuminant estimation on benchmark datasets. The proposed framework is also computationally efficient and parameter-economic, making it suitable for applications deployed on mobile platforms. The great interpretability also makes PILOT possible to serve as a guidance for designing statistics-based models for those low-end devices with tight budgets of power consumption and computational capacity.
Multi cracks detection in Euler-Bernoulli beam subjected to a moving mass based on acceleration responses

ABSTRACT In this paper, a novel approach has been proposed to detect crack in beam structures under moving mass using extreme learning machine and the least square support vector machine. For this purpose, acceleration responses of beam under moving mass were used as input to train machines. This data are acquired by the analysis of cracked structure applying the finite element method. To demonstrate the potential of the proposed vibration analysis over existing ones, a validation study has been done. To evaluate the performance of the presented method, a simply supported beam and a three-span continuous beam with and without noise in acceleration responses were considered. Also, the effect of the discrepancy in stiffness between the finite element model and the actual tested dynamic system has been investigated. The obtained results indicated that this method can provide a reliable tool to accurately identify cracks in beam structures under moving mass.
Use of Psychotropic Drugs : a Follow-up General Practice

Four general practitioners (GPs) of Verona, a town in northern Italy of about 300,000 inhabitants, recruited in 1986 a cohort of 75 adult patients to whom they prescribed benzodiazepines or antidepressants for the ‘first time’. The patients, new users of psychotropic drugs, were 51 women (68 per cent) and 24 men (32 per cent). They were followed up during the 26 weeks after the first psychotropic drug prescription. At the end of the study 20 patients (26.7 per cent of the original cohort-‘long-term’ users) were still consuming psychotropic drugs (mainly benzodiazepines with or without an antidepressant). Severity of psychiatric symptoms (only for patients over 45 years), prescriptions of an antidepressant (but only for women under 45 years) and low educational level (only in males over 45 years) were identified as factors associated with long-term psychotropic drug consumption.
COASTAL DUNEFIELDS IN NORTHEASTERN BRAZIL

Extensive coastal dune fields occur on the Quaternary strandplain associated with the São Francisco River mouth. Two different generations of dunes are identified. One is inactive, already fixed by vegetation, comprising parabolic dunes. The other generation is active, bordering the present-day shoreline and transgressing over the inactive dune field. Three morphological provinces in the active coastal dune fields are recognized. On the updrift side of the São Francisco River mouth, they are: (a) sand-sheet with shrub coppice and shadow dunes; (b) isolated dunes of the barchan-transversal type up to 5 m high, and interdune areas; and (c) a 23 m high compound dune, with superimposed small dunes. The same provinces are recognized on the downdrift side of the river mouth, with two important exceptions: the barchan-transversal and compound dunes are replaced, respectively, by (i) zibar-type dunes up to 5 m high, and (ii) a 19 m high precipitation dune, which is associated with numerous blowouts. The prevailing eastern winds from August to January favour the development of the aeolian bedforms and the migration of dunes. The shoreline orientation almost transversal to the winds and the great supply of finegrained sediments contribute to the formation of barchan-transversal types and compound dunes in the updrift side. On the other hand, in the downdrift side the shoreline orientation is almost parallel to the prevailing winds. This fact, in association with a coarser grain size in the beachface, favours the formation of zibar-type and precipitation dunes with numerous blowouts. The rate of migration of individual dunes is about 20 to 24 m per year. This study suggests that the aeolian sedimentation is a relatively recent phenomenon at the Quaternary strandplain of the São Francisco River. The first generation of dune fields initiated some time after 3000 years BP and the second generation originated some centuries ago. Copyright © 2004 John Wiley & Sons, Ltd.
Triglyceride/high-density lipoprotein ratio as a predictor for insulin resistance in a sample of healthy Iraqi adults

Insulin resistance (IR) is a common pathophysiological condition associated with many metabolic diseases, including obesity, prediabetes, type 2 diabetes mellitus (T2DM), and cardiovascular disease. The widely used homeostasis model assessment for IR (HOMA-IR) is usually used to estimate IR. However, this model cannot be used for screening IR due to several logistic difficulties, such as costs and insulin instability, which are essential for measurement. Thus, finding feasible alternatives is of paramount importance. This study aimed to evaluate the value of triglyceride/high-density lipoprotein-cholesterol (TG/HDL-c) ratio in predicting IR in healthy adult individuals. The study involved 83 euglycemic non-diabetic adults (≥45 years old). Lipid profile, fasting insulin, fasting blood sugar (FBS), and glycated hemoglobin were measured for all participants. The TG/HDL-c ratio was calculated by dividing TG by HDL. Insulin resistance was calculated using the HOMA-IR formula. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the TG/HDL-c ratio. The prevalence of IR among healthy adult Iraqis was 28.92%. Subjects in the IR group showed a higher TG/HDL ratio than the insulin-sensitive group (3.69±0.68 versus 2.71±1.0) with a significant difference. The area under the curve (AUC) for this ratio was 0.849, 95% CI= 0.763-0.935, p<0.002. The sensitivity and specificity of the test were 83% and 81%, respectively, at a best cut-off value of 3.1 (TG/HDL ratio). The prevalence of IR among healthy adult Iraqis was 28.92%. Triglyceride/HDL-c ratio had a very good predictive value for IR.
Sensorimotor synchronization to music reduces pain

Pain-reducing effects of music listening are well-established, but the effects are small and their clinical relevance questionable. Recent theoretical advances, however, have proposed that synchronizing to music, such as clapping, tapping or dancing, has evolutionarily important social effects that are associated with activation of the endogenous opioid system (which supports both analgesia and social bonding). Thus, active sensorimotor synchronization to music could have stronger analgesic effects than simply listening to music. In this study, we show that sensorimotor synchronization to music significantly amplifies the pain-reducing effects of music listening. Using pressure algometry to the fingernails, pain stimuli were delivered to n = 59 healthy adults either during music listening or silence, while either performing an active tapping task or a passive control task. Compared to silence without tapping, music with tapping (but not simply listening to music) reduced pain with a large, clinically significant, effect size (d = 0.93). Simply tapping without music did not elicit such an effect. Our analyses indicate that both attentional and emotional mechanisms drive the pain-reducing effects of sensorimotor synchronization to music, and that tapping to music in addition to merely listening to music may enhance pain-reducing effects in both clinical contexts and everyday life. The study was registered as a clinical trial at ClinicalTrials.gov (registration number NCT05267795), and the trial was first posted on 04/03/2022.
In between the lines of the narrative map: Phenomenological analysis of war rape victims in Amhara Regional State, Ethiopia

Research conducted in the last four decades on rape and other forms of sexual violence shows that they are not only the result of transgression behaviors of some people but have been used as strategic, systemic, and calculated tools of war, ethnic cleansing, and genocide. Examining the nature and effect of wartime rape and sexual violence based on their distinctive features, context, and historical background is essential for research and service providers. This paper explores the lived experiences of sexual violence and gang rape victims during the North Ethiopian war in Amhara Region, Ethiopia. Data were collected from three girls and women survivors using a trauma and socio-culturally informed phenomenological approach. The finding shows that participants experienced a broad and complex range of psychological, physiological, emotional, and relational suffering after the rape. The result also shed light on some risk factors such as lack of awareness of the effect of traumatic events, stigma related to rape, and lacks victim protective legislation risk their journey to healing. The paper further discussed individual and community mental health responses for victims of war rape in culturally responsive and resource-poor settings.
Prevalence and predictors of COVID-19 vaccination hesitancy among healthcare workers in Sub-Saharan Africa: A systematic review and meta-analysis

Background The COVID-19 vaccination is regarded as an effective intervention for controlling the pandemic. However, COVID-19 vaccine hesitancy is hampering efforts geared towards reducing the burden of the pandemic. Therefore, examining COVID-19 hesitancy and its predictors among healthcare workers is essential to improving COVID-19 uptake. In sub-Saharan Africa, the pooled proportion of COVID-19 vaccine hesitancy is yet to be known. Purpose The present study was to estimate the pooled proportion of COVID-19 vaccine hesitancy and its predictors among healthcare workers in Sub-Saharan Africa. Methods A systematic search of articles was conducted in PubMed, Science Direct, African Journal Online, and Google Scholar. Data was extracted with the help of Excel. Data analysis was conducted using STATA 17. Heterogeneity in the studies was assessed using Cochrane Q and 12 tests. A random effects model was used to examine the pooled estimates to determine if heterogeneity was exhibited. Results A total of 15 studies involving 7498 participants were included in the final analysis. The pooled prevalence of COVID-19 vaccination hesitancy among healthcare workers was 46%, 95% CI (0.38–0.54). The predictors of COVID-19 hesitancy were negative beliefs towards vaccine 14.0% (OR = 1.05, 95% CI: 1.04, 1.06), perceived low risk of COVID-19 infection 24.0% (OR = 1.25, 95% CI: 1.23, 1.28), and vaccine side effects 25.0% (OR = 1.23, 95% CI: 1.21, 1.24). Conclusion The data revealed generally high hesitancy of COVID-19 vaccine among health workers in Sub-Saharan Africa. Future COVID-19 adoption and uptake should be improved by national and individual level efforts. In Sub-Saharan Africa, it is crucial to address the myths and obstacles preventing healthcare professionals from accepting the COVID-19 vaccination as soon as feasible since their willingness to get the vaccine serves as an important example for the broader public.
Knowledge, attitudes and practices (KAP) on COVID-19 among the general population in most affected districts of Nepal

The COVID-19 pandemic has become one of the global health challenges in the current context. In Nepal, the first confirmed case was reported on 23 January 2020, and since then, it has resulted in several negative impacts, including economic disruption and deterioration of physical and mental health. In such a pandemic, it is indispensable to understand the knowledge and behavioral patterns of the general population regarding COVID-19. Therefore, our study aimed to assess the knowledge, attitudes and practices on COVID-19 among the general population in most affected districts and its relationship with socio-demographic conditions. The cross-sectional study was conducted among the general population above the age of 18 years from eight districts of Nepal including Kathmandu, Bhaktapur, Lalitpur, Morang, Sunsari, Rupandehi, Chitwan, and Kaski. A convenient non-probability sampling method was considered with total sample size of 702. The questionnaire survey was conducted to collect data. Descriptive statistics, non-parametric statistical tests, and a logistic regression model were used for analysis. The study showed that 93.3% of respondents had knowledge of overall preventive practices, whereas only 32% had knowledge of overall symptoms of COVID-19. Regarding attitudes, only 14.3% strongly believed that the COVID-19 pandemic would end soon. The preventive practice was reduced after the lockdown compared to that of during the lockdown. The respondents with white-collar occupations, high-income, and unmarried were good at KAP. Similarly, highly educated and those residing in urban areas had good knowledge and practice. The study findings will help in the development of targeted programs to improve the general population’s knowledge, attitudes and practices on COVID-19, which is paramount to dealing with the existing pandemic and also such possible future waves of the pandemic.
Patterns of brain atrophy in recently-diagnosed relapsing-remitting multiple sclerosis

Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in recently-diagnosed RRMS using volumetry and voxel-based morphometry (VBM). RRMS patients (N = 354) underwent 3T structural MRI <6 months after diagnosis and 1-year follow-up, as part of the Scottish multicentre ‘FutureMS’ study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish regional patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the brain. Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, cerebellar GM, brainstem, amygdala, basal ganglia, hippocampus, accumbens, thalamus and ventral diencephalon. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 26 regions and 16/26; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe. Widespread GM and NAWM atrophy was observed in this large recently-diagnosed RRMS cohort, particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions; indicative of neurodegeneration across tissue types, and in accord with limited previous studies in early disease. Volumetric and VBM results emphasise different features of longitudinal lobar and loco-regional change, however identify consistent atrophy patterns across individuals. Atrophy measures targeted to specific brain regions may provide improved markers of neurodegeneration, and potential future imaging stratifiers and endpoints for clinical decision making and therapeutic trials.
Vibrio fluvialis Bacteremia With Hemorrhagic Bullae: A Case Report

V. fluvialis is a pathogenic Gram-negative bacillus typically resulting in gastroenteritis in humans. It has recently been identified as a growing concern for public health. The case presented is an uncommon case of V. fluvialis causing bacteremia, as well as hemorrhagic skin lesions. Other reported cases have also highlighted unexpected manifestations, such as cerebritis, bacterial peritonitis, and otitis externa. These atypical presentations can happen in immunocompromised individuals. There are no established guidelines currently for the treatment of V. fluvialis bacteremia. This case presents V. fluvialis bacteremia that improved with doxycycline without the need for incision and drainage of the patient’s lower extremity lesions.
Internet addiction and its relationship with attention deficit hyperactivity disorder (ADHD) symptoms, anxiety and stress among university students in Malaysia

Background and aims There is growing evidence on the contribution of psychological factors to internet addiction; yet it remains inconsistent and deserves further exploration. The aim of this study was to determine the relationship between the psychological symptoms (Attention Deficit Hyperactivity Disorder (ADHD) symptoms, stress, depression, anxiety and loneliness) and internet addiction (IA) among the university students in Malaysia. Materials and methods A total of 480 students from different faculties in a Malaysian public university participated in this study. They were selected by simple random sampling method. They completed self-administered questionnaires including the Malay Version of Internet Addiction Test (MVIAT)) to measure internet addiction and Adult Self-Report Scale (ASRS) Symptom Checklist, Depression Anxiety Stress Scales (DASS) and UCLA Loneliness Scale (Version 3) to assess for ADHD symptoms, depression, anxiety, stress, and loneliness respectively. Results The prevalence of IA among university students was 33.33% (n = 160). The respondents’ mean age was 21.01 ± 1.29 years old and they were predominantly females (73.1%) and Malays (59.4%). Binary logistic regression showed that gender (p = 0.002; OR = 0.463, CI = 0.284–0.754), ADHD inattention (p = 0.003; OR = 2.063, CI = 1.273–3.345), ADHD hyperactivity (p<0.0001; OR = 2.427, CI = 1.495–3.939), stress (p = 0.048; OR = 1.795, CI = 1.004–3.210) and loneliness (p = 0.022; OR = 1.741, CI = 1.084–2.794) were significantly associated with IA. Conclusion A third of university students had IA. In addition, we found that those who were at risk of IA were males, with ADHD symptoms of inattention and hyperactivity, who reported stress and loneliness. Preventive strategy to curb internet addiction and its negative sequelae may consider these factors in its development and implementation.
Effect of the oil from the fatty tissues of Crocodylus siamensis on gut microbiome diversity and metabolism in mice

Dietary fat can alter host metabolism and gut microbial composition. Crocodile oil (CO) was extracted from the fatty tissues of Crocodylus siamensis. CO, rich in monounsaturated- and polyunsaturated fatty acids, has been reported to reduce inflammation, counter toxification, and improve energy metabolism. The aim of this study was to investigate the effect of CO on gut microbiota (GM) in laboratory mice as well as the accompanying metabolic changes in the animals. Forty-five C57BL/6 male mice were randomly divided into five groups and orally administrated either sterile water (control [C]); 1 or 3% (v/w) CO (CO-low [CO-L] and CO-high [CO-H], respectively); or 1 or 3% (v/w) palm oil (PO-low and PO-high, respectively) for 11 weeks. Body weight gain, food intake, energy intake, blood glucose levels, and blood lipid profiles were determined. Samples from colon tissue were collected and the 16S rRNA genes were pyrosequenced to clarify GM analyses. The results showed that there were no differences in body weight and blood glucose levels. Food intake by the mice in the CO-L and CO-H groups was statistically significantly less when compared to that by the animals in the C group. However, neither CO treatment had a statistically significant effect on calorie intake when compared to the controls. The CO-H exhibited a significant increase in serum total cholesterol and low-density lipoprotein but showed a downward trend in triglyceride levels compared to the control. The GM analyses revealed that both CO treatments have no significant influence on bacterial diversity and relative abundance at the phylum level, whereas increases of Choa1 and abundance-based coverage estimator indexes, distinct β-diversity, and Proteobacteria abundance were observed in the PO-high group compared with the C group. Furthermore, the abundance of Azospirillum thiophilum and Romboutsia ilealis was significantly higher in the CO-L and CO-H groups which could be associated with energy metabolic activity. Thus, CO may be an alternative fat source for preserving host metabolism and gut flora.