Miracle-dz/UniFAR-FTUs huggingface dataset:
The Prevalence of Sexual Abuse in Adolescence in Suriname

ABSTRACT Studies conducted to ascertain the prevalence of child sexual abuse (CSA) in the Caribbean are poorly synthesized. Present study reports on the lifetime and year prevalence of unwanted sexual experiences, the risk of CSA at different ages within adolescence, and differences between the three largest ethnic groups in Suriname. One thousand one hundred and twenty (1,120) adolescents completed a questionnaire on child maltreatment, including CSA. The study’s stratified sample consisted of students (ages 12 to 17) from five districts in Suriname. More than 16% of all boys and 15% of all girls indicated that they had been exposed to some form of CSA in the past 12 months. Girls reported significantly more intrafamilial CSA by a minor than boys. Boys reported significantly more experiences of being touched or forced by a minor outside the family to look at/touch the abuser’s private parts than girls. Besides, 16 and 17-year olds were the most vulnerable. An increased risk of CSA (year prevalence) was found as adolescence progresses. A significant portion of CSA constituted peer-to-peer sexual victimization. Afro Surinamese adolescents were found to report the highest rates of CSA. Appropriate legislation, policies, and services for prevention and recovery are needed in Suriname.
Targeting MicroRNA-143 Leads to Inhibition of Glioblastoma Tumor Progression

Glioblastoma (GBM) is the most common and aggressive of all brain tumors, with a median survival of only 14 months after initial diagnosis. Novel therapeutic approaches are an unmet need for GBM treatment. MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression at the post-transcriptional level. Several dysregulated miRNAs have been identified in all cancer types including GBM. In this study, we aimed to uncover the role of miR-143 in GBM cell lines, patient samples, and mouse models. Quantitative real-time RT-PCR of RNA extracted from formalin-fixed paraffin-embedded (FFPE) samples showed that the relative expression of miR-143 was higher in GBM patients compared to control individuals. Transient transfection of GBM cells with a miR-143 oligonucleotide inhibitor (miR-143-inh) resulted in reduced cell proliferation, increased apoptosis, and cell cycle arrest. SLC30A8, a glucose metabolism-related protein, was identified as a direct target of miR-143 in GBM cells. Moreover, multiple injections of GBM tumor-bearing mice with a miR-143-inh-liposomal formulation significantly reduced tumor growth compared to control mice. The reduced in vitro cell growth and in vivo tumor growth following miRNA-143 inhibition suggests that miR-143 is a potential therapeutic target for GBM therapy.
Polygenic adaptation and convergent evolution on growth and cardiac genetic pathways in African and Asian rainforest hunter-gatherers

Significance The “pygmy” phenotype is a classic example of convergent adaptation in humans, having evolved independently in both African and Asian rainforest hunter-gatherers. By focusing on indications of subtle allele-frequency changes occurring in aggregate across variants in many genes (polygenic adaptation), we observed signatures of positive natural selection on the same growth-related pathways in rainforest hunter-gatherer populations from both continents. Unexpectedly, we also observed signatures of convergent positive selection on heart development pathway genes. We hypothesize that the heart pathway result may reflect compensatory changes following height-related adaptation in the GH/IGF1 pathway, which in addition to general growth processes also affects heart development. Our results exemplify the insights that can be gained from comparative studies of diverse human populations. Different human populations facing similar environmental challenges have sometimes evolved convergent biological adaptations, for example, hypoxia resistance at high altitudes and depigmented skin in northern latitudes on separate continents. The “pygmy” phenotype (small adult body size), characteristic of hunter-gatherer populations inhabiting both African and Asian tropical rainforests, is often highlighted as another case of convergent adaptation in humans. However, the degree to which phenotypic convergence in this polygenic trait is due to convergent versus population-specific genetic changes is unknown. To address this question, we analyzed high-coverage sequence data from the protein-coding portion of the genomes of two pairs of populations: Batwa rainforest hunter-gatherers and neighboring Bakiga agriculturalists from Uganda and Andamanese rainforest hunter-gatherers and Brahmin agriculturalists from India. We observed signatures of convergent positive selection between the rainforest hunter-gatherers across the set of genes with “growth factor binding” functions (P<0.001). Unexpectedly, for the rainforest groups, we also observed convergent and population-specific signatures of positive selection in pathways related to cardiac development (e.g., “cardiac muscle tissue development”; P=0.001). We hypothesize that the growth hormone subresponsiveness likely underlying the adult small body-size phenotype may have led to compensatory changes in cardiac pathways, in which this hormone also plays an essential role. Importantly, in the agriculturalist populations, we did not observe similar patterns of positive selection on sets of genes associated with growth or cardiac development, indicating our results most likely reflect a history of convergent adaptation to the similar ecology of rainforests rather than a more general evolutionary pattern.
Accurately Interpreting Clickthrough Data as Implicit Feedback

This paper examines the reliability of implicit feedback generated from clickthrough data in WWW search. Analyzing the users' decision process using eyetracking and comparing implicit feedback against manual relevance judgments, we conclude that clicks are informative but biased. While this makes the interpretation of clicks as absolute relevance judgments difficult, we show that relative preferences derived from clicks are reasonably accurate on average.
A Modified Kulka Micromethod for the Rapid and Safe Analysis of Fructose and 1-Deoxy-d-xylulose-5-phosphate

The Kulka resorcinol assay (Kulka, R.G., Biochemistry 1956, 63, 542–548) for ketoses has been widely used in the literature but suffers from two major disadvantages: (a) it employs large amounts of potentially harmful reagents for a general biology laboratory environment; and (b) in its original formulation, it is unsuited for modern high-throughput applications. Here, we have developed a modified Kulka assay, which contains a safer formulation, employing approx. 5.4 M HCl in 250 µL aliquots, and is suitable for use in high-throughput systems biology or enzymatic applications. The modified assay has been tested extensively for the measurement of two ketoses—fructose (a common substrate in cell growth experiments) and 1-deoxy-d-xylulose-5-phosphate (DXP), the product of the DXP-synthase reaction—which until now has only been assayable using time-consuming chromatographic methods or radioactivity. The Kulka microassay has a sensitivity of 0–250 nmol fructose or 0–500 nmol DXP. The assay is suitable for monitoring the consumption of fructose in bacterial growth experiments but is too insensitive to be used directly for the measurement of DXP in in vitro enzyme assays. However, we show that after concentration of the DXP-enzyme mix by butanol extraction, the Kulka resorcinol method can be used for enzyme assays.
LEARNING SPARSE STRUCTURED ENSEMBLES WITH STOCHASTIC GRADIENT MCMC SAMPLING AND NETWORK PRUNING

An ensemble of neural networks is known to be more robust and accurate than an individual network, however usually with linearly-increased cost in both training and testing. In this work, we propose a two-stage method to learn Sparse Structured Ensembles (SSEs) for neural networks. In the first stage, we run SG-MCMC with group sparse priors to draw an ensemble of samples from the posterior distribution of network parameters. In the second stage, we apply weight-pruning to each sampled network and then perform retraining over the remained connections. In this way of learning SSEs, we not only achieve high prediction accuracy but also reduce memory and computation cost in both training and testing. We conduct a series of evaluation experiments by learning SSE ensembles with both FNNs and LSTMs. To the best of our knowledge, this work represents the first methodology and empirical study of integrating SG-MCMC, group sparse prior and network pruning together for learning NN ensembles.
Activation of PP2A and Inhibition of mTOR Synergistically Reduce MYC Signaling and Decrease Tumor Growth in Pancreatic Ductal Adenocarcinoma.

In cancer, kinases are often activated and phosphatases suppressed, leading to aberrant activation of signaling pathways driving cellular proliferation, survival, and therapeutic resistance. Although pancreatic ductal adenocarcinoma (PDA) has historically been refractory to kinase inhibition, therapeutic activation of phosphatases is emerging as a promising strategy to restore balance to these hyperactive signaling cascades. In this study, we hypothesized that phosphatase activation combined with kinase inhibition could deplete oncogenic survival signals to reduce tumor growth. We screened PDA cell lines for kinase inhibitors that could synergize with activation of protein phosphatase 2A (PP2A), a tumor suppressor phosphatase, and determined that activation of PP2A and inhibition of mTOR synergistically increase apoptosis and reduce oncogenic phenotypes in vitro and in vivo. This combination treatment resulted in suppression of AKT/mTOR signaling coupled with reduced expression of c-MYC, an oncoprotein implicated in tumor progression and therapeutic resistance. Forced expression of c-MYC or loss of PP2A B56α, the specific PP2A subunit shown to negatively regulate c-MYC, increased resistance to mTOR inhibition. Conversely, decreased c-MYC expression increased the sensitivity of PDA cells to mTOR inhibition. Together, these studies demonstrate that combined targeting of PP2A and mTOR suppresses proliferative signaling and induces cell death and implicates this combination as a promising therapeutic strategy for patients with PDA. SIGNIFICANCE: These findings present a combinatorial strategy targeting serine/threonine protein phosphatase PP2A and mTOR in PDA, a cancer for which there are currently no targeted therapeutic options.Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/79/1/209/F1.large. jpg.
Query expansion using local and global document analysis

Automatic query expansion has long been suggested as a technique for dealing with the fundamental issue of word mismatch in information retrieval. A number of approaches to ezpanrnion have been studied and, more recently, attention has focused on techniques that analyze the corpus to discover word relationship (global techniques) and those that analyze documents retrieved by the initial quer~ ( local feedback). In this paper, we compare the effectiveness of these approaches and show that, although global analysis haa some advantages, local analysia is generally more effective. We also show that using global analysis techniques, such as word contezt and phrase structure, on the local aet of documents produces re-sults that are both more effective and more predictable than simple local feedback.
Robust Powerline Equipment Inspection System Based on a Convolutional Neural Network

Electric power line equipment such as insulators, cut-out-switches, and lightning-arresters play important roles in ensuring a safe and uninterrupted power supply. Unfortunately, their continuous exposure to rugged environmental conditions may cause physical or electrical defects in them which may lead to the failure to the electrical system. In this paper, we present an automatic real-time electrical equipment detection and defect analysis system. Unlike previous handcrafted feature-based approaches, the proposed system utilizes a Convolutional Neural Network (CNN)-based equipment detection framework, making it possible to detect 17 different types of powerline insulators in a highly cluttered environment. We also propose a novel rotation normalization and ellipse detection method that play vital roles in the defect analysis process. Finally, we present a novel defect analyzer that is capable of detecting gunshot defects occurring in electrical equipment. The proposed system uses two cameras; a low-resolution camera that detects insulators from long-shot images, and a high-resolution camera which captures close-shot images of the equipment at high-resolution that helps for effective defect analysis. We demonstrate the performances of the proposed real-time equipment detection with up to 93% recall with 92% precision, and defect analysis system with up to 98% accuracy, on a large evaluation dataset. Experimental results show that the proposed system achieves state-of-the-art performance in automatic powerline equipment inspection.
Fast OBDD Reordering using Neural Message Passing on Hypergraph

Ordered binary decision diagrams (OBDDs) are an efficient data structure for representing and manipulating Boolean formulas. With respect to different variable orders, the OBDDs' sizes may vary from linear to exponential in the number of the Boolean variables. Finding the optimal variable order has been proved a NP-complete problem. Many heuristics have been proposed to find a near-optimal solution of this problem. In this paper, we propose a neural network-based method to predict near-optimal variable orders for unknown formulas. Viewing these formulas as hypergraphs, and lifting the message passing neural network into 3-hypergraph (MPNN3), we are able to learn the patterns of Boolean formula. Compared to the traditional methods, our method can find a near-the-best solution with an extremely shorter time, even for some hard examples.To the best of our knowledge, this is the first work on applying neural network to OBDD reordering.
Vitamin D Status and Analysis of Specific Correlates in Preschool Children: A Cross-Sectional Study in Southern Croatia

Vitamin D deficiency is a globally important problem, particularly in children, but there is a lack of information regarding this deficiency in preschool children from southeastern Europe. This study aimed to establish the levels of 25-hydroxyvitamin D (25(OH)D) and associations of gender, time spent outdoors, physical activity (PA), and body mass index (as predictors) with the 25(OH)D level (outcome) in healthy preschool children. The participants were preschoolers (all 5–6 years of age) from southern Croatia. All the participants were tested during their mandatory medical examination 6–7 months prior to school enrollment. The PA was obtained using the preschool-age physical activity questionnaire (Pre-PAQ), which categorizes PA into five levels (from sedentary to vigorous PA). The prevalence of 25(OH)D deficiency was high: 58% of the children had 25(OH)D levels of <50 nmol/L (deficiency), and an additional 29% had an insufficient level of 25(OH)D (50–75 nmol/L). Boys had higher levels of 25(OH)D than girls. A multinomial regression using 25(OH)D categories as the outcome and a sufficient level (>75 nmol/L) as the reference value identified gender as the only significant predictor of 25(OH)D status, with boys being at lower risk for 25(OH)D deficiency than girls. These results showed a high prevalence of 25(OH)D deficiency in preschoolers from the southern part of Croatia, which is additionally alarming based on the geographical position of the studied region (42° N) and its high number of sunshine hours (>2600 h per year). Future studies examining other potential correlates of 25(OH)D in the region are warranted.
Non-tree routing for reliability and yield improvement

We propose to introduce redundant interconnects for manufacturing yield and reliability improvement. By introducing redundant interconnects, the potential for open faults is reduced at the cost of increased potential for short faults; overall, manufacturing yield and fault tolerance can be improved. We focus on a post-processing, tree augmentation approach which can be easily integrated in current physical design flows. Experiments on randomly generated and industry testcases show that our greedy augmentation method achieves significant increase in reliability (as measured by the percentage of biconnected tree edges) with very small increase in wirelength. SPICE simulations imply that non-tree routing has smaller delay variation due to process variability.
CROSS-CORPUS EEG-BASED EMOTION RECOGNITION

Lack of generalization is a common problem in automatic emotion recognition. The present study aims to explore the suitability of the existing EEG features for emotion recognition and investigate the performance of emotion recognition methods across different corpora. We introduce a novel dataset which includes spontaneous emotions and was analyzed in addition to the existing datasets for cross-corpus evaluation. We demonstrate that the performance of the existing methods significantly decreases when evaluated across different corpora. The best results are obtained by a convolutional neural network fed by spectral topography maps from different bands. We provide some evidence that stimuli-related sensory information is learned by machine learning models for emotion recognition using EEG signals.
MC2

Real-world, long-running wireless sensor networks (WSNs) require intense user intervention in the development, hardware testing, deployment, and maintenance stages. A majority of network design is network centric and focuses primarily on network performance, for example, efficient sensing and reliable data delivery. Although several tools have been developed to assist debugging and fault diagnosis, it is yet to systematically examine the underlying heavy burden that users face throughout the lifetime of WSNs. In this article, we propose a general Multimode user-CentriC (MC2) framework that can, with simple user inputs, adjust itself to assist user operation and thus reduce the users' burden at various stages. In particular, we have identified utilities that are essential at each stage and grouped them into modes. In each mode, only the corresponding utilities will be loaded, and modes can be easily switched using the customized MC2 sensor platform. As such, we reduce the runtime interference between various utilities and simplify their development as well as their debugging. We validated our MC2 software and the sensor platform in a long-lived microclimate monitoring system deployed at a wildland heritage site, Mogao Grottoes. In our current system, 241 sensor nodes have been deployed in 57 caves, and the network has been running for over five years. Our experimental validation shows that the MC2 framework shortens the time for network deployment and maintenance, and makes network maintenance doable by field experts (in our case, historians).
The long term effect of metabolic profile and microbiota status in early gastric cancer patients after subtotal gastrectomy

Long term effects of subtotal gastrectomy on gut microbiota modifications with subsequent metabolic profiles are limited. We aimed to investigate and compare long-term effects of metabolic profiles and microbiota status in early gastric cancer patients post curative subtotal gastrectomy to the controls. In this cross-sectional study, we analyzed type II diabetes mellitus and metabolic syndrome occurrence in two groups: 111 patients after curative subtotal gastrectomy with Billroth II (BII) anastomosis and Roux-en-Y gastrojejuno (RYGJ) anastomosis and 344 age-sex matched controls. Fecal samples from those with BII, RYGJ, and controls were analyzed by next-generation sequencing method. Metabolic syndrome and type II diabetes mellitus occurrences were significantly lower in patients after subtotal gastrectomy with RYGJ than in controls over the long term (> 8 years) follow-up (P < 0.05). The richness and diversity of gut microbiota significantly increased after subtotal gastrectomy with RYGJ (P < 0.05). Compared with the control group, the principal component analysis revealed significant differences in bacterial genera abundance after subtotal gastrectomy with BII and RYGJ (P < 0.001). Genera of Oscillospira, Prevotella, Coprococcus, Veillonella, Clostridium, Desulfovibrio, Anaerosinus, Slackia, Oxalobacter, Victivallis, Butyrivibrio, Sporobacter, and Campylobacter shared more abundant roles both in the RYGJ group and BII groups. Early gastric cancer patients after subtotal gastrectomy with RYGJ had a lower occurrence of metabolic syndrome and type II diabetes mellitus than the controls during long term follow-up. In parallel with the metabolic improvements, gut microbial richness and diversity also significantly increased after subtotal gastrectomy with RYGJ.
Shopping Over Distance through a Telepresence Robot

Computer mediated-communication tools (CMC) support loved ones in maintaining connections with one another over distance, yet it can be difficult to do activities together. We studied the use of telepresence robots for supporting distance-separated loved ones in engaging in the joint activity of shopping over distance. One partner shopped in person while the other used either a telepresence robot or a tablet from a remote location. Compared to the tablet group, we found that when partners communicated through a telepresence robot, the remote partner's personality and presence were expressed through the movements and physicality of the medium. However, the use of the telepresence robot introduced tension between partners regarding responsibility, dependency, and contribution to the act of shopping. These results demonstrate the benefits of a mobile embodiment for remote partners, as well as the need for greater physical capabilities to support both physical connection and remote contribution to leisure activities.