Miracle-dz/UniFAR-FTUs huggingface dataset:
UvA-DARE (Digital Academic Repository) Simulation of dyslexia. How literacy and cognitive skills can help distinguish college students with dyslexia from malingerers

Academic accommodations associated with a diagnosis of dyslexia might be incentives for college students without reading or spelling difficulties to feign dyslexia and obtain the diagnosis unfairly. In the current study we examined malingering practices by comparing the performance of college students instructed to malinger dyslexia ( n = 28) to that of students actually diagnosed with dyslexia ( n = 16). We also included a control group of students without reading and spelling difficulties ( n = 28). The test battery included tasks tapping literacy skills as well as underlying cognitive skills associated with literacy outcomes. These tasks are commonly used in diagnosing dyslexia. We examined patterns in the performance of malingerers across tasks and tested whether malingerers could be identified based on their performance on a limited number of tasks. Results indicated that malingerers scored significantly lower than students with dyslexia on reading and spelling skills; i.e., the core characteristics of dyslexia. Especially reading performance was extremely low and not in line with students’ age and level of education. Findings for underlying cognitive skills were mixed. Overall, malingerers scored lower than students with dyslexia on tasks tapping mainly speed, whereas the two groups did not differ on tasks reflecting mainly accuracy. Based on word and pseudoword reading and letter and digit naming, the three groups could be distinguished with reasonable sensitivity and specificity. In all, results indicate that college students seem to understand on which tasks they should feign dyslexia, but tend to exaggerate difficulties on these tasks to the point where diagnosticians should mistrust performance.
Musculoskeletal Injury in Paddle Sport Athletes.

INTRODUCTION Kayak racing has been an Olympic sport since 1936. The sport is evolving with the introduction of ocean skis and stand-up-paddle boards (SUP). Musculoskeletal injury incidence surveys have been conducted for ultra-marathon events, but no data have been published for other racing formats. OBJECTIVE To identify and compare the rates and types of injuries sustained by paddling athletes as a function of discipline and training parameters in Sprint, Marathon, Ultra-Marathon, and Ocean events. METHODS Competitors from 6 kayak and/or ocean surf-ski races in Australia were surveyed. Before each race, competitors were asked to complete a questionnaire. The questionnaire investigated paddling-related injuries over the previous 5 years, athlete morphology, flexibility, equipment and its setup, training volume, and environment. RESULTS Five hundred eighty-three competitors were surveyed. Disciplines included 173 racing-kayak (K1), 202 touring-kayak, 146 ocean-skis, 42 SUP, and 20 other. The top 5 paddling-related injuries were shoulder (31%), low back (23.5%), wrist (16.5%), neck (13.7%), and elbow (11.0%). The highest percentage of injury was found in K1 paddlers for shoulder (40.5%), SUP for low back (33.3%), and ocean-ski for wrist (22.6%). After controlling for on-water training hours, the relative risk (RR) of wrist injury was significantly increased in ocean-ski paddlers (1.86) and in paddlers with decreased flexibility (1.53-1.83). Relative risk of shoulder and low-back injury was significantly increased in athletes with lower training volumes (1.82-2.07). Younger athletes had lower RR of wrist and shoulder injury (0.58-0.62).
On-Demand Deep Model Compression for Mobile Devices: A Usage-Driven Model Selection Framework

Recent research has demonstrated the potential of deploying deep neural networks (DNNs) on resource-constrained mobile platforms by trimming down the network complexity using different compression techniques. The current practice only investigate stand-alone compression schemes even though each compression technique may be well suited only for certain types of DNN layers. Also, these compression techniques are optimized merely for the inference accuracy of DNNs, without explicitly considering other application-driven system performance (e.g. latency and energy cost) and the varying resource availabilities across platforms (e.g. storage and processing capability). In this paper, we explore the desirable tradeoff between performance and resource constraints by user-specified needs, from a holistic system-level viewpoint. Specifically, we develop a usage-driven selection framework, referred to as AdaDeep, to automatically select a combination of compression techniques for a given DNN, that will lead to an optimal balance between user-specified performance goals and resource constraints. With an extensive evaluation on five public datasets and across twelve mobile devices, experimental results show that AdaDeep enables up to 9.8x latency reduction, 4.3x energy efficiency improvement, and 38x storage reduction in DNNs while incurring negligible accuracy loss. AdaDeep also uncovers multiple effective combinations of compression techniques unexplored in existing literature.
Refractive indices of layers and optical simulations of Cu(In,Ga)Se2 solar cells

Abstract Cu(In,Ga)Se2 -based solar cells have reached efficiencies close to 23%. Further knowledge-driven improvements require accurate determination of the material properties. Here, we present refractive indices for all layers in Cu(In,Ga)Se2 solar cells with high efficiency. The optical bandgap of Cu(In,Ga)Se2 does not depend on the Cu content in the explored composition range, while the absorption coefficient value is primarily determined by the Cu content. An expression for the absorption spectrum is proposed, with Ga and Cu compositions as parameters. This set of parameters allows accurate device simulations to understand remaining absorption and carrier collection losses and develop strategies to improve performances.
Test of Export-Led Growth Hypothesis: a Comparative Analysis on Turkey and Newly Developing Countries

The relation between exports and national income of a country has long been a frequently debated issue in both trade and growth theory. This issue is particularly important in providing arguments for 'free trade' (export-led growth) or 'protectionism' (import substitution) because presence of any causality between exports and income would imply supremacy of outward looking policies over inward looking policies. In order to test the export-led growth hypothesis, this work exam- ines the relation between trade (exports and imports) and income for Turkey and seven newly developing countries using Granger causality analysis. Our results suggest that the export-led growth hypothesis is not supported only in cases of Argentina, and Brazil and that there is a strong unidirectional causality running from exports to growth for Turkey, the Czech Republic, Hungary, Poland, India and China.
La parturition chez les adolescentes aux cliniques universitaires de Lubumbashi (Congo)

Cette etude porte sur 149 parturientes adolescentes recues a la maternite des cliniques universitaires de Lubumbashi (Congo), durant 12 mois. Les resultats obtenus sont les suivants: les adolescentes representent une proportion de 13,9% de toutes les parturientes; 31 % sont celibataires; 94,6 % ont arrete leurs etudes au niveau secondaire ; 5,36 % ont du travail. La parite de nos parturientes est dominee par les nullipares avec 79,19 %. Parmi elles, 30,2 % n'ont pas suivi de consultations prenatales. Selon l'âge gestationnel, 14,7% des accouchements sont prematures. Pour les grossesses a terme, le taux est de 54,3 %. Le depassement de terme est retrouve dans 3,3 %. Dans 98,6 l'etat du bassin est normal et dans 1,3 % le bassin est limite. L'accouchement est eutocique dans 89,93 % des cas mais dystocique dans 10,06% des cas. La toxenie gravidique est observee dans 1,3 % avec un tableau d'eclampsie. Le taux de cesarienne est de 3,35 %. La souffrance foetale aigue represente 4 %. D'une facon generale, le pronostic de l'accouchement est comparable chez les adolescentes et chez les adultes. Mais ici, l'environnement social, psychique et economique peut le rendre sombre.
Multi-level Wavelet-CNN for Image Restoration

The tradeoff between receptive field size and efficiency is a crucial issue in low level vision. Plain convolutional networks (CNNs) generally enlarge the receptive field at the expense of computational cost. Recently, dilated filtering has been adopted to address this issue. But it suffers from gridding effect, and the resulting receptive field is only a sparse sampling of input image with checkerboard patterns. In this paper, we present a novel multi-level wavelet CNN (MWCNN) model for better tradeoff between receptive field size and computational efficiency. With the modified U-Net architecture, wavelet transform is introduced to reduce the size of feature maps in the contracting subnetwork. Furthermore, another convolutional layer is further used to decrease the channels of feature maps. In the expanding subnetwork, inverse wavelet transform is then deployed to reconstruct the high resolution feature maps. Our MWCNN can also be explained as the generalization of dilated filtering and subsampling, and can be applied to many image restoration tasks. The experimental results clearly show the effectiveness of MWCNN for image denoising, single image super-resolution, and JPEG image artifacts removal.
Not so sweet refrain: sugar-sweetened beverage taxes, industry opposition and harnessing the lessons learned from tobacco control legal challenges

Abstract As a growing number of countries implement, or announce plans to introduce, a sugar-sweetened beverage (SSB) tax, this paper explores the public health rationale for such a tax and provides an overview of the international normative and policy instruments supporting the introduction of fiscal measures on sugary drinks. After examining parallels between the legal arguments raised by the food and beverage industry in opposition to SSB taxes and those raised by the tobacco industry in response to tobacco control measures, this paper draws four key lessons that will assist countries to design effective and robust SSB tax measures and counter food and beverage industry opposition: regulatory distinctions in tax coverage should be based on bona fide, evidence-based reasoning; evidence-based measures need to be tailored to a country’s public health objectives as part of a comprehensive strategy to address unhealthy diet consumption; procedural requirements and due process should be observed in the drafting and implementation of the measure; and regulatory space exists within domestic constitutions, laws and international trade and investment agreements recognising the sovereign right of states to regulate in the interests of public health.
Expression levels of breast cancer‐related GAS5 and LSINCT5 lncRNAs in cancer‐free breast tissue: Molecular associations with age at menarche and obesity

Long noncoding RNAs (lncRNAs) constitute a major class of the human transcriptome which play crucial roles in the key biological processes of both normal and malignant breast cells. Although the aberrant expression of lncRNAs has been well‐documented in breast cancer (BC), little is currently known about the association between their expression levels in the breast tissue of healthy women and BC risk factors, especially the reproductive or demographic characteristics that are among the most well‐known BC risk modifiers. This study was an attempt to investigate the correlation between the expression levels of 2 breast cancer‐related lncRNAs, including GAS5 and LSINCT5, and reproductive and demographic characteristics in 145 normal breast tissues that were obtained from women without breast cancer undergoing cosmetic surgery. Total RNA was extracted from fresh normal breast tissues, and the expression level of target lncRNAs was quantified using real‐time qPCR. Differences in the mean normalized gene expression among the subgroups of different variables were analyzed. The expression levels of both genes was lower in the overweight‐obese (BMI ≥ 25) subgroup than that in the normal BMI (BMI < 25) subgroup (GAS5 P = .019, LSINCT5 P = .036). Moreover, the expression level of GAS5 was negatively correlated with BMI (r: −.170, P: .041). The expression level of GAS5 was higher in women with late menarche (>13 years) than that with early menarche (≤13 years; P = .017). These findings may assist to obtain insights into the molecular mechanisms through which the reproductive or obesity‐related estrogen changes contribute to the breast carcinogenesis. In conclusion, this study presents the first evidence for the presence of a link between the lncRNA expression and the reproductive or obesity related factors in the breast tissue of healthy women.
Role of Oxidative Stress as Key Regulator of Muscle Wasting during Cachexia

Skeletal muscle atrophy is a pathological condition mainly characterized by a loss of muscular mass and the contractile capacity of the skeletal muscle as a consequence of muscular weakness and decreased force generation. Cachexia is defined as a pathological condition secondary to illness characterized by the progressive loss of muscle mass with or without loss of fat mass and with concomitant diminution of muscle strength. The molecular mechanisms involved in cachexia include oxidative stress, protein synthesis/degradation imbalance, autophagy deregulation, increased myonuclear apoptosis, and mitochondrial dysfunction. Oxidative stress is one of the most common mechanisms of cachexia caused by different factors. It results in increased ROS levels, increased oxidation-dependent protein modification, and decreased antioxidant system functions. In this review, we will describe the importance of oxidative stress in skeletal muscles, its sources, and how it can regulate protein synthesis/degradation imbalance, autophagy deregulation, increased myonuclear apoptosis, and mitochondrial dysfunction involved in cachexia.
Hepatitis B virus lymphotropism: emerging details and challenges

Abstract The hepatitis B virus (HBV) is predominantly a hepatotropic virus but also infects cells of the lymphatic system. HBV genomes (DNA, messenger (m)RNA, covalently closed circular (ccc) DNA) and proteins have been found in extrahepatic sites such as peripheral blood mononuclear cells (PBMC), lymph nodes, spleen, bone marrow and cerebrospinal fluid. HBV entry into hepatocytes occurs by binding of the HBV preS1 surface protein to its specific receptor, the bile acid transporter, sodium taurocholate co-transporting polypeptide (NTCP). Although the mechanism of HBV entry into lymphatic cells is unknown, the pre S1 encoded surface protein is thought to be involved. Extrahepatic HBV infection has been studied in both chronic HBV (CHB) and in occult HBV infection (OBI). Studies have shown that HBV genomes are present in different PBMC subsets from chronically infected carriers. Unique HBV variants have been found in PBMC compared to plasma or liver in both nucleos(t)ide analogue (NA) treated and untreated CHB carriers, suggesting replication and compartment specific evolution of HBV. In HBV coinfection, HBV genomes were found in PBMC from hepatitis C virus (HCV), human immunodeficiency virus (HIV) and hepatitis delta virus (HDV) co-infected individuals. Moreover, during pregnancy, the trans placental passage of HBV infected PBMC from highly viremic mothers to infants is one of the postulated means of vertical transmission of HBV. Taken together, HBV infection in extrahepatic sites (i.e., PBMC) is implicated in multiple facets of HBV pathogenesis such as persistence, viral evolution and vertical transmission.
SIRT1 inhibits rheumatoid arthritis fibroblast-like synoviocyte aggressiveness and inflammatory response via suppressing NF-κB pathway

Rheumatoid arthritis (RA) is an autoimmune disease of the joints characterized by synovial hyperplasia and chronic inflammation. Fibroblast-like synoviocytes (FLS) play a central role in RA initiation, progression, and perpetuation. Prior studies showed that sirtuin 1 (SIRT1), a deacetylase participating in a broad range of transcriptional and metabolic regulations, may impact cell proliferation and inflammatory responses. However, the role of SIRT1 in RA–FLS was unclear. Here, we explored the effects of SIRT1 on the aggressiveness and inflammatory responses of cultured RA-FLS. SIRT1 expression was significantly lower in synovial tissues and FLS from RA patients than from healthy controls. Overexpression of SIRT1 significantly inhibited RA-FLS proliferation, migration, and invasion. SIRT1 overexpression also significantly increased RA-FLS apoptosis and caspase-3 and -8 activity. Focusing on inflammatory phenotypes, we found SIRT1 significantly reduced RA-FLS secretion of TNF-α, IL-6, IL-8, and IL-1β. Mechanistic studies further revealed SIRT1 suppressed NF-κB pathway by reducing p65 protein expression, phosphorylation, and acetylation in RA-FLS. Our results suggest SIRT1 is a key regulator in RA pathogenesis by suppressing aggressive phenotypes and inflammatory response of FLS. Enhancing SIRT1 expression or function in FLS could be therapeutic beneficial for RA by inhibiting synovial hyperplasia and inflammation.
Abstractive Text Classification Using Sequence-to-convolution Neural Networks

We propose a new deep neural network model and its training scheme for text classification. Our model Sequence-to-convolution Neural Networks(Seq2CNN) consists of two blocks: Sequential Block that summarizes input texts and Convolution Block that receives summary of input and classifies it to a label. Seq2CNN is trained end-to-end to classify various-length texts without preprocessing inputs into fixed length. We also present Gradual Weight Shift(GWS) method that stabilizes training. GWS is applied to our model's loss function. We compared our model with word-based TextCNN trained with different data preprocessing methods. We obtained significant improvement in classification accuracy over word-based TextCNN without any ensemble or data augmentation.
Semantic Image Interpretation - Integration of Numerical Data and Logical Knowledge for Cognitive Vision

Semantic Image Interpretation (SII) is the process of generating a structured description of the content of an input image. This description is encoded as a labelled direct graph where nodes correspond to objects in the image and edges to semantic relations between objects. Such a detailed structure allows a more accurate searching and retrieval of images. In this thesis, we propose two well-founded methods for SII. Both methods exploit background knowledge, in the form of logical constraints of a knowledge base, about the domain of the images. The first method formalizes the SII as the extraction of a partial model of a knowledge base. Partial models are built with a clustering and reasoning algorithm that considers both low-level and semantic features of images. The second method uses the framework Logic Tensor Networks to build the labelled direct graph of an image. This framework is able to learn from data in presence of the logical constraints of the knowledge base. Therefore, the graph construction is performed by predicting the labels of the nodes and the relations according to the logical constraints and the features of the objects in the image. These methods improve the state-of-the-art by introducing two well-founded methodologies that integrate low-level and semantic features of images with logical knowledge. Indeed, other methods, do not deal with low-level features or use only statistical knowledge coming from training sets or corpora. Moreover, the second method overcomes the performance of the state-of-the-art on the standard task of visual relationship detection.
Maternal cardiovascular and endothelial function from first trimester to postpartum

Objective To explore noninvasively the complex interactions of the maternal hemodynamic system throughout pregnancy and the resulting after-effect six weeks postpartum. Methods Eighteen women were tested beginning at the 12th week of gestation at six time-points throughout pregnancy and six weeks postpartum. Heart rate, heart rate variability, blood pressure, pulse transit time (PTT), respiration, and baroreceptor sensitivity were analyzed in resting conditions. Additionally, hemoglobin, asymmetric and symmetric dimethylarginine and Endothelin (ET-1) were obtained. Results Heart rate and sympathovagal balance favoring sympathetic drive increased, the vagal tone and the baroreflex sensitivity decreased during pregnancy. Relative sympathetic drive (sympathovagal balance) reached a maximum at 6 weeks postpartum whereas the other variables did not differ compared to first trimester levels. Postpartum diastolic blood pressure was higher compared to first and second trimester. Pulse transit time and endothelial markers showed no difference throughout gestation. However, opposing variables PTT and asymmetric dimethylarginine (ADMA) were both higher six weeks postpartum. Conclusions The sympathetic up regulation throughout pregnancy goes hand in hand with a decreased baroreflex sensitivity. In the postpartum period, the autonomic nervous system, biochemical endothelial reactions and PTT show significant and opposing changes compared to pregnancy findings, indicating the complex aftermath of the increase of blood volume, the changes in perfusion strategies and blood pressure regulation that occur in pregnancy.
Gilles de la Tourette syndrome as a paradigmatic neuropsychiatric disorder

Gilles de la Tourette syndrome is a chronic and complex tic disorder accompanied by specific behavioral problems in the majority of patients. With its multifaceted interplay between motion and emotion, this condition is a paradigmatic example of the science and art of clinical neuropsychiatry. This review article encompasses the clinical phenomenology of motor and vocal tics and associated sensory experiences (premonitory urges), as well as the behavioral spectrum of the most common comorbidities, including obsessive-compulsive disorder, attention-deficit and hyperactivity disorder, affective symptoms, and impulsivity. Knowledge of the contributions of both tics and behavioral problems to patients’ health-related quality of life across the lifespan should assist treating clinicians in formulating a targeted management plan. Although the exact pathophysiology of Gilles de la Tourette syndrome remains elusive, research into therapeutic interventions has expanded the range of available interventions across multiple domains. A thorough understanding of the neurology and psychiatry of this condition is of key importance to meet the needs of this patient population, from the formulation of an accurate diagnosis to the implementation of effective treatment strategies.