Miracle-dz/UniFAR-FTUs huggingface dataset:
Familial Mediterranean Fever Mutation Analysis in Pediatric Patients With İnflammatory Bowel Disease: A Multicenter Study.

BACKGROUND The aim of the study was to evaluate familial Mediterranean fever (FMF) mutation analysis in pediatric patients with inflammatory bowel disease (IBD). The relation between MEFV mutations and chronic inflammatory diseases has been reported previously. METHODS Children with IBD (334 ulcerative colitis (UC), 224 Crohn's disease (CD), 39 indeterminate colitis (IC)) were tested for FMF mutations in this multicenter study. The distribution of mutations according to disease type, histopathological findings, and disease activity indexes was determined. RESULTS A total of 597 children (mean age: 10.8 ± 4.6 years, M/F: 1.05) with IBD were included in the study. In this study, 41.9% of the patients had FMF mutations. E148Q was the most common mutation in UC and CD, and M694V in IC (30.5%, 34.5%, 47.1%, respectively). There was a significant difference in terms of endoscopic and histopathological findings according to mutation types (homozygous/ heterozygous) in patients with UC (P < .05). There was a statistically significant difference between colonoscopy findings in patients with or without mutations (P = .031, P = .045, respectively). The patients with UC who had mutations had lower Pediatric Ulcerative Colitis Activity Index (PUCAI) scores than the patients without mutations (P = .007). CONCLUSION Although FMF mutations are unrelated to CD patients, but observed in UC patients with low PUCAI scores, it was established that mutations do not have a high impact on inflammatory response and clinical outcome of the disease.
Effect of Surface Morphology on the Ordered Water Layer at Room Temperature

The behavior of water, particularly the first water layer residing on solid surfaces with various unit cell sizes and charge defects, is studied by molecular dynamics simulations at room temperature. We found that both the unit cell size and presence of defects greatly affected the configurations of the first water layer, specifically the structure and stability of the two-dimensional hydrogen. -bond network within this layer. Consequently, the wetting behavior of water on the solid surface is significantly influenced. On certain wetted solid surfaces with water droplets distributed over the first water layer, the presence of defects at low ratios leads to partial disruption of the structure of the two-dimensional hydrogen-bond network within the first water layer and the existence of the irregular droplet profiles different from the conventional circular shapes. Due to the adsorption of the surface, the dwell time of the first water layer is extremely large and is about 1 order of magnitude larger than the rest of the water layers.
Overweight problem among primary health care workers in Suburban District of Hulu Langat, Selangor, Malaysia

Globally, overweight has become the epidemic due to world growth in industry, economy, urbanization and globalization. This study was conducted to highlight the overweight problem and its associated factors among health care workers in Suburban District of Hulu Langat, Selangor, Malaysia. A cross sectional study was conducted using IPAQ short version and Food Frequency Questionnaire to measure fat intake while knowledge was measured using a set of validated questionnaire. The anthropometric measurement was carried out using a calibrated SECA scale, body meter and measurement tape. Data was analyzed using software Diet 4. The overweight prevalence in this study is 46.1%. Age, sex, marital status, length of service, parity, education and income were significantly associated with overweight. However logistic regression showed that only education level and income has significant associations with overweight. It is concluded that the overweight prevalence among health workers is higher compared to previous studies in Malaysia. Higher income and low level of education are the predictors of overweight among health care workers.
N ov 2 01 9 B lock-coordinate and incremental aggregated proximal gradient methods for nonsmooth nonconvex problems

This paper analyzes block-coordinate proximal gradient methods for minimizing the sum of a separable smooth function and a (nonseparable) nonsmooth function, both of which are allowed to be nonconvex. The main tool in our analysis is the forwardbackward envelope (FBE), which serves as a particularly suitable continuous and realvalued Lyapunov function. Global and linear convergence results are established when the cost function satisfies the Kurdyka-Łojasiewicz property without imposing convexity requirements on the smooth function. Two prominent special cases of the investigated setting are regularized finite sum minimization and the sharing problem; in particular, an immediate byproduct of our analysis leads to novel convergence results and rates for the popular Finito/MISO algorithm in the nonsmooth and nonconvex setting with very general sampling strategies.
Quantitative Analysis of Fatty Esters of Marine Animal Oils by Gas-Liquid Chromatography

ジエチレングリコールコハク酸ポリエステル(DES)をカラム固定液相として用い,C14,C16,C18,C20,C22の飽和脂肪酸メチルおよびC18F1,C18F2,C18F3,C20F1,C22F1の不飽和脂肪酸メチルの熱伝導度型検出器におけるピーク面積の重量比に対する相対補正係数を求めた。 さらに,プロピレングリコールコハク酸ポリエステル(PS),およびジプロピレングリコールコハク酸ポリエステル(DPS)を合成し,DES,PS,DPSを固定液相として,サンマ油,鯨油脂肪酸メチルエステルを分析し,液相の比較検討と,組成脂肪酸の定量分析を行なった。 その結果,本実験の範囲内において,PSはDESに比較して分離能はほとんど変わらず,熱安定性および使用寿命の点で極めてすぐれていることを認めた。 また試料送入量を0に外挿してのDES,PS固定液相における各脂肪酸メチルエステルの相対保持容量を求めた。
A self-amplifying loop of YAP and SHH drives formation and expansion of heterotopic ossification

A self-amplifying and propagating loop of YAP-SHH is a core molecular mechanism underlying diverse forms of heterotopic ossification. Understanding heterotopic ossification Heterotopic ossification (HO), a condition where bone forms in nonskeletal tissues, is a common complication after soft tissue injury or surgery that remains incompletely understood, and treatment options are limited. Here, Cong and colleagues dissected out the molecular mechanisms of HO, finding that a positive feedback loop of YAP–Sonic hedgehog (SHH) signaling drove HO formation in several different mouse models of the disease. Pharmacological inhibition of YAP ameliorated HO expansion in both genetic and acquired HO murine models, suggesting that such inhibition may prevent or reduce HO expansion in humans. Heterotopic ossification (HO) occurs as a common complication after injury or in genetic disorders. The mechanisms underlying HO remain incompletely understood, and there are no approved prophylactic or secondary treatments available. Here, we identify a self-amplifying, self-propagating loop of Yes-associated protein (YAP)–Sonic hedgehog (SHH) as a core molecular mechanism underlying diverse forms of HO. In mouse models of progressive osseous heteroplasia (POH), a disease caused by null mutations in GNAS, we found that Gnas−/− mesenchymal cells secreted SHH, which induced osteoblast differentiation of the surrounding wild-type cells. We further showed that loss of Gnas led to activation of YAP transcription activity, which directly drove Shh expression. Secreted SHH further induced YAP activation, Shh expression, and osteoblast differentiation in surrounding wild-type cells. This self-propagating positive feedback loop was both necessary and sufficient for HO expansion and could act independently of Gnas in fibrodysplasia ossificans progressiva (FOP), another genetic HO, and nonhereditary HO mouse models. Genetic or pharmacological inhibition of YAP or SHH abolished HO in POH and FOP and acquired HO mouse models without affecting normal bone homeostasis, providing a previously unrecognized therapeutic rationale to prevent, reduce, and shrink HO.
Smartphone-based Content Annotation for Ground Truth Collection in Affective Computing

This paper presents a real-time emotion-annotation tool using a personal mobile device. To this end, an application based on the Valence-Arousal model was developed, following two different approaches (”Two-step Sequential Annotation” and ”One-step Matrix Annotation”). The application was tested through, an experiment where users performed annotations with each version of the app and then filled a feedback questionnaire. This questionnaire contained statements used to assess the usability and mental workload. A total of 16 (9 female) participants aged between 21 and 34 years old engaged in this experiment. Overall the results were quite encouraging in both versions, taking into account that this is still a work in progress. The ”Single-step Matrix Annotation” was considered the preferred version.
Towards Ubiquitous Learning: A First Measurement of On-Device Training Performance

We are witnessing the emergence of ubiquitous learning, where each device (smartphones, wearables, IoTs, etc) can learn from their environments either alone or collaboratively. Such a new paradigm is enabled by deep learning techniques, or more specifically, on-device training. Given its popularity in the machine learning community, unfortunately, there are no systematic understandings of a critical question: how much cost does it take to train typical deep models on commodity end devices? Therefore, this work performs comprehensive measurements of on-device training with the state-of-the-art training library, 6 mobile phones, and 5 classical neural networks. Our measurements report metrics of training time, energy consumption, memory footprint, hardware utilization, and thermal dynamics, thus help reveal a complete landscape of the on-device training performance. The observations from the measurements help guide us to several promising future directions to efficiently enable ubiquitous learning.
Systems thinking in health technology assessment: a scoping review

Abstract Objective Our objective was to assess how, and to what extent, a systems-level perspective is considered in decision-making processes for health interventions by illustrating how studies define the boundaries of the system in their analyses and by defining the decision-making context in which a systems-level perspective is undertaken. Method We conducted a scoping review following the Joanna Briggs Institute methodology. MEDLINE, EMBASE, Cochrane Library, and EconLit were searched and key search concepts included decision making, system, and integration. Studies were classified according to an interpretation of the “system” of analysis used in each study based on a four-level model of the health system (patient, care team, organization, and/or policy environment) and using categories (based on intervention type and system impacts considered) to describe the decision-making context. Results A total of 2,664 articles were identified and 29 were included for analysis. Most studies (16/29; 55%) considered multiple levels of the health system (i.e., patient, care team, organization, environment) in their analysis and assessed multiple classes of interventions versus a single class of intervention (e.g., pharmaceuticals, screening programs). Approximately half (15/29; 52%) of the studies assessed the influence of policy options on the system as a whole, and the other half assessed the impact of interventions on other phases of the disease pathway or life trajectory (14/29; 48%). Conclusions We found that systems thinking is not common in areas where health technology assessments (HTAs) are typically conducted. Against this background, our study demonstrates the need for future conceptualizations and interpretations of systems thinking in HTA.
Intimate partner and client‐perpetrated violence are associated with reduced HIV pre‐exposure prophylaxis (PrEP) uptake, depression and generalized anxiety in a cross‐sectional study of female sex workers from Nairobi, Kenya

UNAIDS has identified female sex workers (FSW) as a key HIV at‐risk population. FSW disproportionately experience gender‐based violence, which compounds their risk of HIV acquisition and may contribute to adverse mental health outcomes. Pre‐exposure prophylaxis (PrEP) is a powerful but underused HIV prevention tool for these women. This study explored the associations between intimate partner violence (IPV) and client‐perpetrated violence against FSW, mental health outcomes and PrEP use.
The longitudinal association between depression, anxiety symptoms and HIV outcomes, and the modifying effect of alcohol dependence among ART clients with hazardous alcohol use in Vietnam

Mental health disorders may negatively impact HIV outcomes, such as viral suppression (VS) and antiretroviral (ART) adherence among people with HIV (PWH) with hazardous alcohol use. This study evaluates the longitudinal association between depression, anxiety symptoms, VS and complete ART adherence among ART clients with hazardous alcohol use in Vietnam; and examines alcohol dependence as a modifier in this association.
Interventions to address the mental health of adolescents and young adults living with or affected by HIV: state of the evidence

Adolescents and young adults (AYA) remain vulnerable to HIV‐infection and significant co‐morbid mental health challenges that are barriers to treatment and prevention efforts. Globally millions of AYA are living with HIV (AYALH) and/or have been affected by HIV in their families (AYAAH), with studies highlighting the need for mental health programmes. With no current guidelines for delivering mental health interventions for AYALH or AYAAH, a scoping review was undertaken to explore current evidence‐based mental health interventions for AYALH and AYAAH to inform future work.
Characteristics of BCR–ABL gene variants in patients of chronic myeloid leukemia

Abstract Background Depending on breakpoints of rearrangement different types of BCR–ABL fusion protein can be generated in patients of chronic myeloid leukemia (CML). The aim of this study is to observe frequencies of major transcripts in CML patients by reverse transcriptase polymerase chain reaction (RT-PCR) and their hematological features at the time of presentation. Materials and methods This cross sectional study was performed at Molecular Lab of Riphah International University, Islamabad from January to June 2019. Consecutive peripheral blood samples of 70 newly diagnosed CML patients in chronic phase were analyzed by RT-PCR to detect different BCR–ABL transcripts. Routine blood cell counts were assessed by an automated hematology analyzer. Results All samples expressed typical BCR–ABL rearrangement. Expression of either e14a2 or e13a2 transcript was detected in 38 (54%) and 30 (43%) patients, respectively. Coexpression of e13a2 + e14a2 was found in 2 (3%) patients. The mean total leukocyte count was higher in group expressing e13a2 (P = 0.01). Higher mean platelet count was noted in patients with e14a2 transcript, but this difference was statistically insignificant (P = 0.1). The association of male gender was observed with the group exhibiting e14a2 (P = 0.01). There was no statistically significant association between transcript type and different ranges of age, hemoglobin levels, and platelet and total leukocyte counts (P > 0.05). Conclusion e14a2 transcript was most common transcript in CML patients. Patients exhibiting e13a2 subgroup presented with significantly higher mean white blood cell count at the time of presentation. Significantly higher proportion of male patients was found to express e14a2 transcript over e13a2.
Explanation of Siamese Neural Networks for Weakly Supervised Learning

A new method for explaining the Siamese neural network (SNN) as a black-box model for weakly supervised learning is proposed under condition that the output of every subnetwork of the SNN is a vector which is accessible. The main problem of the explanation is that the perturbation technique cannot be used directly for input instances because only their semantic similarity or dissimilarity is known. Moreover, there is no an “inverse” map between the SNN output vector and the corresponding input instance. Therefore, a special autoencoder is proposed, which takes into account the proximity of its hidden representation and the SNN outputs. Its pre-trained decoder part as well as the encoder are used to reconstruct original instances from the SNN perturbed output vectors. The important features of the explained instances are determined by averaging the corresponding changes of the reconstructed instances. Numerical experiments with synthetic data and with the well-known dataset MNIST illustrate the proposed method.
Transient Non-stationarity and Generalisation in Deep Reinforcement Learning

Non-stationarity can arise in Reinforcement Learning (RL) even in stationary environments. For example, most RL algorithms collect new data throughout training, using a non-stationary behaviour policy. Due to the transience of this non-stationarity, it is often not explicitly addressed in deep RL and a single neural network is continually updated. However, we find evidence that neural networks exhibit a memory effect where these transient non-stationarities can permanently impact the latent representation and adversely affect generalisation performance. Consequently, to improve generalisation of deep RL agents, we propose Iterated Relearning (ITER). ITER augments standard RL training by repeated knowledge transfer of the current policy into a freshly initialised network, which thereby experiences less non-stationarity during training. Experimentally, we show that ITER improves performance on the challenging generalisation benchmarks ProcGen and Multiroom.
Trends in COVID-19 Vaccination Intent, Determinants and Reasons for Vaccine Hesitancy: Results from Repeated Cross-Sectional Surveys in the Adult General Population of Greece during November 2020–June 2021

Background: Vaccine hesitancy is a major barrier to achieve large-scale COVID-19 vaccination. We report trends in vaccination intention and associated determinants from surveys in the adult general population in Greece. Methods: Four cross-sectional phone surveys were conducted in November 2020, February, April and May 2021 on nationally representative samples of adults in Greece. Multinomial logistic regression was used on the combined data of the surveys to evaluate independent predictors of vaccination unwillingness/uncertainty. Results: Vaccination intention increased from 67.6% in November 2020 to 84.8%. in May 2021. Individuals aged 65 years or older were more willing to get vaccinated (May 2021: 92.9% vs. 79.5% in 18-39 years, p<0.001) but between age-groups differences decreased over time. Vaccination intention increased substantially in both sexes, though earlier among men than women and was higher in individuals with postgraduate studies (May 2021: 91.3% vs. 84.0% up to junior high). From multivariable analysis, unwillingness and/or uncertainty to get vaccinated was associated with younger age, female gender (in particular in the April 2021 survey), lower educational level and living with a child [≤]12 years old. Among those with vaccine hesitancy, concerns about vaccine effectiveness declined over time (21.6% in November 2020 vs. 9.6% in May 2021, p=0.014) and were reported more often by men; safety concerns remained stable over time (66.3% in November 2020 vs. 62.1% in May 2021, p=0.658) and were reported more often by women. Conclusions: Vaccination intention increased substantially over time. Tailored communication is needed to address vaccine hesitancy and concerns regarding vaccine safety.
Reduction in Severity of All-Cause Gastroenteritis Requiring Hospitalisation in Children Vaccinated against Rotavirus in Malawi

Background: Rotavirus is the major cause of severe gastroenteritis in children aged <5 years. Introduction of Rotarix rotavirus vaccine (RV1) in Malawi in 2012 has reduced rotavirus-associated hospitalisations and diarrhoeal mortality. However, RV1 impact on gastroenteritis severity remains unknown. We conducted a hospital-based surveillance study to assess RV1 impact on gastroenteritis severity in children aged <5 years, in Malawi. Methods: Stool samples were collected from children hospitalised with acute gastroenteritis from December 2011 to October 2019. Gastroenteritis severity was determined using Ruuska and Vesikari scores. Rotavirus was detected in stool using Enzyme Immunoassay. Rotavirus genotypes were determined using nested RT-PCR. Associations between RV1 vaccination and gastroenteritis severity were investigated using adjusted linear regression. Results: In total, 3,159 children were recruited. After adjusting for Mid-Upper Arm Circumference, age, weight, gender and receipt of other vaccines, all-cause gastroenteritis severity scores were 2.21 units lower (95% CI 1.85, 2.56; p<0.001) among RV1-vaccinated (n=2,224) compared to RV1-unvaccinated children (n=935); the decrease was comparable between rotavirus-positive and rotavirus-negative cases in all age groups. The reduction in severity score was observed against every rotavirus genotype, although the magnitude was smaller among those infected with G12P[6] compared to the remaining genotypes (p=0.011). Other than RV1 vaccination, age was the only variable associated with gastroenteritis severity. Each one-year increment in age was associated with a decrease of 0.43 severity score (95% CI 0.26, 0.60; p<0.001). Conclusion: Our findings provide additional evidence of RV1 impact in a high disease burden, low-income country, lending further support to rotavirus vaccine programme in Malawi.
Multi-Level Local SGD for Heterogeneous Hierarchical Networks

We propose Multi-Level Local SGD, a distributed gradient method for learning a smooth, non-convex objective in a heterogeneous multi-level network. Our network model consists of a set of disjoint sub-networks, with a single hub and multiple worker nodes; further, worker nodes may have different operating rates. The hubs exchange information with one another via a connected, but not necessarily complete communication network. In our algorithm, sub-networks execute a distributed SGD algorithm, using a hub-and-spoke paradigm, and the hubs periodically average their models with neighboring hubs. We first provide a unified mathematical framework that describes the Multi-Level Local SGD algorithm. We then present a theoretical analysis of the algorithm; our analysis shows the dependence of the convergence error on the worker node heterogeneity, hub network topology, and the number of local, sub-network, and global iterations. We back up our theoretical results via simulation-based experiments using both convex and non-convex objectives.
Active Contrastive Learning of Audio-Visual Video Representations

Contrastive learning has been shown to produce generalizable representations of audio and visual data by maximizing the lower bound on the mutual information (MI) between different views of an instance. However, obtaining a tight lower bound requires a sample size exponential in MI and thus a large set of negative samples. We can incorporate more samples by building a large queue-based dictionary, but there are theoretical limits to performance improvements even with a large number of negative samples. We hypothesize that random negative sampling leads to a highly redundant dictionary that results in suboptimal representations for downstream tasks. In this paper, we propose an active contrastive learning approach that builds an actively sampled dictionary with diverse and informative items
Ringing ReLUs: Harmonic Distortion Analysis of Nonlinear Feedforward Networks

In this paper, we apply harmonic distortion analysis to understand the effect of nonlinearities in the spectral domain. Each nonlinear layer creates higherfrequency harmonics, which we call "blueshift", whose magnitude increases with network depth, thereby increasing the “roughness” of the output landscape. Unlike differential models (such as vanishing gradients, sharpness), this provides a more global view of how network architectures behave across larger areas of their parameter domain. For example, the model predicts that residual connections are able to counter the effect by dampening corresponding higher frequency modes. We empirically verify the connection between blueshift and architectural choices, and provide evidence for a connection with trainability.