Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Learning Strategy versus Inherent Architecture Properties on the Ability of Convolutional Neural Networks to Develop Transformation Invariance

As object recognition becomes an increasingly common ML task, and recent research demonstrating CNNs vulnerability to attacks and small image perturbations necessitate fully understanding the foundations of object recognition. We focus on understanding the mechanisms behind how neural networks generalize to spatial transformations of complex objects. While humans excel at discriminating between objects shown at new positions, orientations, and scales, past results demonstrate that this may be limited to familiar objects - humans demonstrate low tolerance of spatial-variances for purposefully constructed novel objects. Because training artificial neural networks from scratch is similar to showing novel objects to humans, we seek to understand the factors influencing the tolerance of CNNs to spatial transformations. We conduct a thorough empirical examination of seven Convolutional Neural Network (CNN) architectures. By training on a controlled face image dataset, we measure model accuracy across different degrees of 5 transformations: position, size, rotation, Gaussian blur, and resolution transformation due to resampling. We also examine how learning strategy affects generalizability by examining how different amounts of pre-training have on model robustness. Overall, we find that the most significant contributor to transformation invariance is pre-training on a large, diverse image dataset. Moreover, while AlexNet tends to be the least robust network, VGG and ResNet architectures demonstrate higher robustness for different transformations. Along with kernel visualizations and qualitative analyses, we examine differences between learning strategy and inherent architectural properties in contributing to invariance of transformations, providing valuable information towards understanding how to achieve greater robustness to transformations in CNNs.
A Streamlined Encoder/decoder Architecture for Melody Extraction

Melody extraction in polyphonic musical audio is important for music signal processing. In this paper, we propose a novel streamlined encoder/decoder network that is designed for the task. We make two technical contributions. First, drawing inspiration from a state-of-the-art model for semantic pixel-wise segmentation, we pass through the pooling indices between pooling and un-pooling layers to localize the melody in frequency. We can achieve result close to the state-of-the-art with much fewer convolutional layers and simpler convolution modules. Second, we propose a way to use the bottleneck layer of the network to estimate the existence of a melody line for each time frame, and make it possible to use a simple argmax function instead of ad-hoc thresholding to get the final estimation of the melody line. Our experiments on both vocal melody extraction and general melody extraction validate the effectiveness of the proposed model.
Temperature sensitivity in multiple sclerosis: An overview of its impact on sensory and cognitive symptoms

ABSTRACT Multiple sclerosis (MS) is an autoimmune neurodegenerative disease characterized by demyelination of the central nervous system (CNS). The exact cause of MS is still unknown; yet its incidence and prevalence rates are growing worldwide, making MS a significant public health challenge. The heterogeneous distribution of demyelination within and between MS patients translates in a complex and varied array of autonomic, motor, sensory and cognitive symptoms. Yet a unique aspect of MS is the highly prevalent (60–80%) temperature sensitivity of its sufferers, where neurological symptoms are temporarily exacerbated by environmental- or exercise-induced increases (or decreases) in body temperature. MS temperature sensitivity is primarily driven by temperature-dependent slowing or blocking of neural conduction within the CNS due to changes in internal (core) temperature; yet changes in skin temperature could also contribute to symptom exacerbation (e.g. during sunlight and warm ambient exposure). The impact of temperature sensitivity, and particularly of increases in core temperature, on autonomic (e.g. thermoregulatory/cardiovascular function) and motor symptoms (e.g. fatigue) is well described. However, less attention has been given to how increases (and decreases) in core and skin temperature affect sensory and cognitive symptoms. Furthermore, it remains uncertain whether changes in skin temperature alone could also trigger worsening of symptoms. Here we review the impact of temperature sensitivity on MS sensory and cognitive function and discuss additional factors (e.g. changes in skin temperature) that potentially contribute to temperature-induced worsening of symptoms in the absence of alteration in core temperature.
SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark

Reproducibility has been a significant challenge in deep reinforcement learning and robotics research. Open-source frameworks and standardized benchmarks can serve an integral role in rigorous evaluation and reproducible research. We introduce SURREAL, an open-source scalable framework that supports stateof-the-art distributed reinforcement learning algorithms. We design a principled distributed learning formulation that accommodates both on-policy and off-policy learning. We demonstrate that SURREAL algorithms outperform existing opensource implementations in both agent performance and learning efficiency. We also introduce SURREAL Robotics Suite, an accessible set of benchmarking tasks in physical simulation for reproducible robot manipulation research. We provide extensive evaluations of SURREAL algorithms and establish strong baseline results.
Cardiorespiratory and metabolic determinants during moderate and high resistance exercise intensities until exhaustion using dynamic leg press: comparison with critical load

The objective of this study was to assess cardiovascular, respiratory, and metabolic responses during a commonly used dynamic leg press resistance exercise until exhaustion (TEx) at different intensities and compare with critical load (CL). This was a prospective, cross-sectional, controlled, and crossover study. Twelve healthy young men (23±2.5 years old) participated. The subjects carried out three bouts of resistance exercise in different percentages of 1 repetition maximum (60, 75, and 90% 1RM) until TEx. CL was obtained by means of hyperbolic model and linearization of the load-duration function. During all bout intensities, oxygen uptake (VO2), carbon dioxide production (VCO2), ventilation (VE), and respiratory exchange ratio (RER) were obtained. Variations (peak-rest=Δ) were corrected by TEx. In addition, systolic and diastolic blood pressure (SBP and DBP), blood lactate concentration [La-] and Borg scores were obtained at the peak and corrected to TEx. CL induced greater TEx as well as number of repetitions when compared to all intensities (P<0.001). During CL, Borg/TEx, ΔSBP/TEx, ΔDBP/TEx, and [La-] were significantly lower compared with 90% load (P<0.0001). In addition, VO2, VCO2, VE, and RER were higher during CL when compared to 90 or 75%. TEx was significantly correlated with VO2 on CL (r=0.73, P<0.05). These findings support the theory that CL constitutes the intensity that can be maintained for a very long time, provoking greater metabolic and ventilatory demand and lower cardiovascular and fatigue symptoms during resistance exercise.
HEALTH-RELATED QUALITY OF LIFE IN OLDER ADULTS : FINDINGS FROM 2007-2014 NATIONAL HEALTH AND NUTRITION EXAMINATION SURVEY

Background: A growing body of research shows that diet quality and physical activity (PA) are associated with health-related quality of life (HRQOL). However, no study to date has assessed this association using the Healthy Eating Index-2015 as a measure of diet quality. Furthermore, few studies have examined the association between PA dose and HRQOL among a nationally representative sample of older adults. Objectives: To investigate the relationship between diet quality, physical activity, and HRQOL. Design: A cross-sectional analysis was conducted using data obtained from 5,311 adults aged 60+ years who took part in the National Health and Nutrition Examination Survey between 2007 and 2014. Measurements: HRQOL was assessed by general health status, and number of physically unhealthy days, mentally unhealthy days, and inactive days in past 30 days. Diet quality was assessed by the Healthy Eating Index-2015 using data generated by two 24-hour dietary recalls. PA was measured by the Global Physical Activity Questionnaire. Multivariate logistic/or linear regression models were used to examine the association between diet quality, PA and HRQOL controlling for confounders and accounting for complex sampling. Results: Approximately half of the participants (55.2%) were women, 45.1% met current PA recommendations, 65% had less healthful diets according to the Healthy Eating Index-2015. Diet quality was associated with HROQL. For every 1-point diet quality score increase, the likelihood of respondents rating their general health as being excellent/good increased by 3% (OR=1.03, 95%CI: 1.02, 1.04), and number of inactive days (β =-0.03, 95%CI: -0.05, 0.00) and mental unhealthy days (β =-0.03, 95%CI: -0.05, -0.01) declined by 0.03 days. PA was associated with all HROQL measures and respondents with high PA levels reported better general health (OR=3.53, 95%CI: 2.69, 4.63), fewer inactive days (β =-1.53, 95%CI: -2.11, -0.95), fewer physical unhealthy days (β =-1.88, 95%CI: -2.74, -1.02) than individuals with low PA levels but not fewer mentally unhealthy days. Conclusions: Among older adults in this study, eating a healthier diet and being physically active were associated with better general health and reporting fewer physical unhealthy days and inactive days. Study results provide valuable information that could inform policies, programs and interventions designed to improve HRQOL in older adults and reduce potentially preventable health disparities.
Zebrafish—A Model Organism for Studying the Neurobiological Mechanisms Underlying Cognitive Brain Aging and Use of Potential Interventions

1 Interdisciplinary Neuroscience Program, Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey, Department of Psychology, Bilkent University, Ankara, Turkey, National Nanotechnology Research Center (UNAM), Bilkent University, Ankara, Turkey, Department of Molecular Biology and Genetics Department Zebrafish Facility, Bilkent University, Ankara, Turkey, National Magnetic Resonance Research Center (UMRAM), Aysel Sabuncu Brain Research Center, Bilkent University, Ankara, Turkey
Clade‐specific evolutionary diversification along ontogenetic major axes in avian limb skeleton

The evolutionary diversification of birds has been facilitated by specializations for various locomotor modes, with which the proportion of the limb skeleton is closely associated. However, recent studies have identified phylogenetic signals in this system, suggesting the presence of historical factors that have affected its evolutionary variability. In this study, to explore potential roles of ontogenetic integration in biasing the evolution in the avian limb skeleton, evolutionary diversification patterns in six avian families (Anatidae, Procellariidae, Ardeidae, Phalacrocoracidae, Laridae, and Alcidae) were examined and compared to the postnatal ontogenetic trajectories in those taxa, based on measurement of 2641 specimens and recently collected ontogenetic series, supplemented by published data. Morphometric analyses of lengths of six limb bones (humerus, ulna, carpometacarpus, femur, tibiotarsus, and tarsometatarsus) demonstrated that: (1) ontogenetic trajectories are diverse among families; (2) evolutionary diversification is significantly anisotropic; and, most importantly, (3) major axes of evolutionary diversification are correlated with clade‐specific ontogenetic major axes in the shape space. These results imply that the evolutionary variability of the avian limbs has been biased along the clade‐specific ontogenetic trajectories. It may explain peculiar diversification patterns characteristic to some avian groups, including the long‐leggedness in Ardeidae and tendency for flightlessness in Anatidae.
Divergent approaches in the vaccination of recently arrived migrants to Europe: a survey of national experts from 32 countries, 2017

Background Migrants within the European Union and European Economic Area (EU/EEA) may be underimmunised and lack documentation on previous vaccinations. We investigated approaches to vaccination in recently arrived adult and child migrants, and guideline availability and implementation. Methods: Between March and May 2017, a national vaccination expert from every EU/EEA country and Switzerland completed an electronic questionnaire. We used descriptive analyses to calculate percentages, and framework analysis to synthesise free-text responses. Results: We approached 32 countries (response rate 100%). Although 28 experts reported vaccination guidance at national level, specific guidelines for recently arrived migrants were only available in six countries and not consistently implemented. Twenty-three countries administered vaccinations during on-arrival health checks. Most experts recommended multiple vaccination opportunities be made available: at point of entry (n = 13) or at holding level (reception centres, migrant camps, detention centres) (n = 21). In 30 countries, child migrants without evidence of previous vaccination were re-vaccinated according to the national schedule. Diphtheria-pertussis-tetanus and polio vaccinations were given to migrant children in all countries, measles-mumps-rubella (MMR) in 31 countries, hepatitis B vaccination in 25. Low levels of catch-up vaccination were reported in adult migrants, with only 13 countries offering MMR and 10 countries charging fees. Conclusion: Existing guidance is often not migrant-specific and may not be applied in practice; clarification is needed on which vaccines should be given. Strategies are needed specifically for catch-up vaccination in adult migrants. Vaccinations should be offered in multiple settings, free of charge, with sufficient guidance and training provided to front-line healthcare professionals.
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This paper presents a novel approach to the facial expression generation problem. Building upon the assumption of the psychological community that emotion is intrinsically continuous, we first design our own continuous emotion representation with a 3-dimensional latent space issued from a neural network trained on discrete emotion classification. The so-obtained representation can be used to annotate large in the wild datasets and later used to trained a Generative Adversarial Network. We first show that our model is able to map back to discrete emotion classes with a objectively and subjectively better quality of the images than usual discrete approaches. But also that we are able to pave the larger space of possible facial expressions, generating the many moods of emotion. Moreover, two axis in this space may be found to generate similar expression changes as in traditional continuous representations such as arousalvalence. Finally we show from visual interpretation, that the third remaining dimension is highly related to the well-known dominance dimension from psychology.
Finding Cryptocurrency Attack Indicators Using Temporal Logic and Darkweb Data

With the recent prevalence of darkweb/deepweb (D2web) sites specializing in the trade of exploit kits and malware, malicious actors have easy-access to a wide-range of tools that can empower their offensive capability. In this study, we apply concepts from causal reasoning, itemset mining, and logic programming on historical cryptocurrency-related cyber incidents with intelligence collected from over 400 D2web hacker forums. Our goal was to find indicators of cyber threats targeting cryptocurrency traders and exchange platforms from hacker activity. Our approach found interesting activities that, when observed together in the D2web, subsequent cryptocurrency-related incidents are at least twice as likely to occur than they would if no activity was observed. We also present an algorithmic extension to a previously-introduced algorithm called APT-Extract that allows to model new semantic structures that are specific to our application.
Improved Bounds for Randomly Sampling Colorings via Linear Programming

A well-known conjecture in computer science and statistical physics is that Glauber dynamics on the set of $k$-colorings of a graph $G$ on $n$ vertices with maximum degree $\Delta$ is rapidly mixing for $k\ge\Delta+2$. In FOCS 1999, Vigoda showed that the flip dynamics (and therefore also Glauber dynamics) is rapidly mixing for any $k>\frac{11}{6}\Delta$. It turns out that there is a natural barrier at $\frac{11}{6}$, below which there is no one-step coupling that is contractive with respect to the Hamming metric, even for the flip dynamics. We use linear programming and duality arguments to fully characterize the obstructions to going beyond $\frac{11}{6}$. These extremal configurations turn out to be quite brittle, and in this paper we use this to give two proofs that the Glauber dynamics is rapidly mixing for any $k\ge\left(\frac{11}{6} - \epsilon_0\right)\Delta$ for some absolute constant $\epsilon_0>0$. This is the first improvement to Vigoda's result that holds for general graphs. Our first approach analyzes a variable-length coupling in which these configurations break apart with high probability before the coupling terminates, and our other approach analyzes a one-step path coupling with a new metric that counts the extremal configurations. Additionally, our results extend to list coloring, a widely studied generalization of coloring, where the previously best known results required $k > 2 \Delta$.
Evaluation of spike sorting algorithms: Simulations and application to human Subthalamic Nucleus recordings

An important prerequisite for the analysis of spike synchrony in extracellular recordings is the extraction of single unit activity from the recorded multi unit signal. To identify single units (SUs), potential spikes are detected and separated with respect to their potential neuronal origins ('spike sorting'). However, different sorting algorithms yield inconsistent unit assignments which seriously influences the subsequent analyses of the spiking activity. To evaluate the quality of spike sortings performed with different prevalent algorithms offered by the 'Plexon Offline Sorter' we first apply these algorithms to experimental data (ED), namely recordings in the Subthalamic Nucleus of patients with Parkinson's disease, obtained during Deep Brain Stimulation surgery. Since this procedure leaves us unsure about the best sorting result we then apply all methods again to artificial data (AD) with known ground truth (GT). AD consists of pairs of SUs with different shape similarity embedded in the background noise of the ED. The sorting evaluation is based on the influence of the respective methods on the SU assignments and its effect on the resulting firing characteristics. We find a high variability in the sorting results obtained by different algorithms that increases with SU shape similarity. We also find significant differences in the resulting firing characteristics of the ED. We conclude that Valley-Seeking produces the most accurate results if the exclusion of artifacts as unsorted events is important. If the latter is less important ('clean' data) K-Means is a better option. Our results strongly argue for the need of standardized validation procedures for spike sorting based on GT data. The recipe suggested here is simple enough to become a standard procedure.
ACVIM consensus statement: Support for rational administration of gastrointestinal protectants to dogs and cats

The gastrointestinal (GI) mucosal barrier is continuously exposed to noxious toxins, reactive oxygen species, microbes, and drugs, leading to the development of inflammatory, erosive, and ultimately ulcerative lesions. This report offers a consensus opinion on the rational administration of GI protectants to dogs and cats, with an emphasis on proton pump inhibitors (PPIs), histamine type‐2 receptor antagonists (H2RAs), misoprostol, and sucralfate. These medications decrease gastric acidity or promote mucosal protective mechanisms, transforming the management of dyspepsia, peptic ulceration, and gastroesophageal reflux disease. In contrast to guidelines that have been established in people for the optimal treatment of gastroduodenal ulcers and gastroesophageal reflux disease, effective clinical dosages of antisecretory drugs have not been well established in the dog and cat to date. Similar to the situation in human medicine, practice of inappropriate prescription of acid suppressants is also commonplace in veterinary medicine. This report challenges the dogma and clinical practice of administering GI protectants for the routine management of gastritis, pancreatitis, hepatic disease, and renal disease in dogs and cats lacking additional risk factors for ulceration or concerns for GI bleeding. Judicious use of acid suppressants is warranted considering recent studies that have documented adverse effects of long‐term supplementation of PPIs in people and animals.
Progress in diagnosis and treatment of bipolar disorder among children and adolescents: an international perspective

Bipolar disorder (BPD) is a potentially lifelong condition characterised by extreme changes in mood that may begin in childhood and cause substantial impairment. Over the past decades, BPD has been the focus of increased attention mainly due to controversies surrounding its prevalence, diagnosis and treatment in children and adolescents. This report addresses these controversies by reviewing the extant evidence base, providing clinicians with a summary of the literature on diagnosis, phenomenology and treatment of paediatric BPD. The debate regarding diagnosing children with BPD based on severe irritability and aggression is mostly resolved. The current data support utilising the diagnostic criteria based on episodic changes of mood polarity. Therefore, longitudinal course of illness should be explored in detail when diagnosing BPD. Given high rates of genetic predisposition for BPD, assessment of youth should focus on obtaining accurate family history of this condition. Additionally, there has been a substantial increase in randomised placebo-controlled clinical trials evaluating pharmacological agents for mood stabilisation in children and adolescents, which we summarise in this review. Despite significant progress being made in the field of paediatric BPD, more research is needed in the areas of phenomenology, pathophysiology, course and treatment of this condition in youth.