Miracle-dz/UniFAR-FTUs huggingface dataset:
Verifocal: a platform for vision correction and accommodation in head-mounted displays

The vergence-accommodation conflict is a fundamental cause of discomfort in today's Virtual and Augmented Reality (VR/AR). We present a novel software platform and hardware for varifocal head-mounted displays (HMDs) to generate consistent accommodation cues and account for the user's prescription. We investigate multiple varifocal optical systems and propose the world's first varifocal mobile HMD based on Alvarez lenses. We also introduce a varifocal rendering pipeline, which corrects for distortion introduced by the optical focus adjustment, approximates retinal blur, incorporates eye tracking and leverages on rendered content to correct noisy eye tracking results. We demonstrate the platform running in compact VR headsets and present initial results in video pass-through AR.
Micronuclei in Exfoliated Buccal Cells of Children Living in a Cluster Area of Salento (Southern Italy) with a High Incidence of Lung Cancer: The IMP.AIR Study

During the years 2014–2016 the University of Salento performed the “Impact of Air Quality on Health of Residents in the Municipalities of Cutrofiano, Galatina, Sogliano Cavour, Soleto and Sternatia” (IMP.AIR) study, an epidemiological-molecular research project aiming to evaluate early DNA damage in children living in an area of Salento with high incidence of lung cancer among the male population. One hundred and twenty-two children aged 6–8 years attending primary school were enrolled and the frequency of micronucleated cells (MNC) in oral mucosa was evaluated. In addition, a questionnaire was administered to parents to obtain information about personal data, anthropometric characteristics and lifestyles (physical activity, food habits, family context) of the children and perform a multivariate analysis to detect any factors associated with MNC occurrence. Data on airborne pollutants detected in the study area were acquired by the Regional Agency for the Environmental Protection. The presence of MNC was highlighted in about 42% of children with a mean MNC frequency of 0.49‰. The frequency of MNC was associated to obesity, consumption of red or processed meat and having a mother who smokes. Moreover, the prevalence of biomarkers was higher than in another area of Salento not included in the cluster area.
EGAIM: Enhanced Genetic Algorithm based Incentive Mechanism for Mobile Crowdsensing

Mobile Crowdsensing (MCS) systems take advantage of the ubiquity and sensing power of smartphones in data gathering. Designing an incentive mechanism for motivating the individuals to participate in such systems is vital. Reverse auction is a popular incentive framework in which the users bid their expected returns for their contributions, and the mechanism then selects a number of them as the participants based on their value for the system. In this paper, we consider the goal of participant selection as maximising the total contribution within a budget constraint where the user contributions may be disparate and coverage overlap is possible. We propose a genetic algorithm approximation solution for this optimisation problem. We call the mechanism as Genetic Algorithm based Incentive Mechanism (GAIM). We also propose an enhanced version of this approach (EGAIM) in which an improved parent selection strategy is utilised to overcome two limitations of GAIM which arise in situations where the budget is limited. We compare EGAIM with GAIM and a greedy algorithm under two real-world scenarios, and show that using EGAIM can save up to 55% of budget for achieving at the same level of contribution.
Differences in Developmental Concerns of Young Children with Autism Spectrum Disorder Across Racial/Ethnic Groups

ABSTRACT Purpose: Parents/caregivers of children with autism spectrum disorder (ASD) have varying types of initial concerns regarding their child’s development, which may be culturally bound to parents’ perceptions of their child’s development. This study investigated differences in the types of initial developmental concerns reported by parents or caregivers of different racial/ethnic groups with children in an early intervention program. Method: This study examined the frequency of endorsement of different types of concerns in African American, Caucasian, and Hispanic families. Results: No significant differences between racial/ethnic groups were found in the endorsement of concerns related to communication, language/speech, motor, problem behavior, sensory, feeding, prematurity, attention, adaptive functioning, and medical conditions. Racial/ethnic groups differed significantly in their endorsement for social concerns. Conclusion: Racial/ethnic group differences were confirmed regarding initial developmental concerns related to social behavior, which may be due to cultural beliefs. The implications of these findings on early identification are discussed.
Profiling and Predicting User Activity on a Home Network

This paper reports a study on the characterization of in-home Internet activity behavior based on application usage logs. We collected online activity data from 86 Belgium households for 60 days. We analyzed the activity traces to gain insights on the temporal traffic distribution, interaction regularity, and activity correlations. This analysis is then used to develop a generic method to segment households into designated groups showing similar behavioral profiles. Our technique combines interaction frequencies and regularities across activities for segmentation, and is able to reveal interesting time-slotted profile for each segment. These profiles aim to show the strength of routine behaviors in Internet usage, based on which we present a novel algorithm to predict future Internet activities of a household. Our algorithm shows that 60% of the households online activities can be predicted accurately 70% of times.
A Review of Learning with Deep Generative Models from perspective of graphical modeling

This document aims to provide a review on learning with deep generative models (DGMs), which is an highly-active area in machine learning and more generally, artificial intelligence. This review is not meant to be a tutorial, but when necessary, we provide self-contained derivations for completeness. This review has two features. First, though there are different perspectives to classify DGMs, we choose to organize this review from the perspective of graphical modeling, because the learning methods for directed DGMs and undirected DGMs are fundamentally different. Second, we differentiate model definitions from model learning algorithms, since different learning algorithms can be applied to solve the learning problem on the same model, and an algorithm can be applied to learn different models. We thus separate model definition and model learning, with more emphasis on reviewing, differentiating and connecting different learning algorithms. We also discuss promising future research directions.
Gene-Metabolite Interaction in the One Carbon Metabolism Pathway: Predictors of Colorectal Cancer in Multi-Ethnic Families

For personalized healthcare, the purpose of this study was to examine the key genes and metabolites in the one-carbon metabolism (OCM) pathway and their interactions as predictors of colorectal cancer (CRC) in multi-ethnic families. In this proof-of-concept study, we included a total of 30 participants, 15 CRC cases and 15 matched family/friends representing major ethnic groups in southern California. Analytics based on supervised machine learning were applied, with the target variable being specified as cancer, including the ensemble method and generalized regression (GR) prediction. Elastic Net with Akaike’s Information Criterion with correction (AICc) and Leave-One-Out cross validation GR methods were used to validate the results for enhanced optimality, prediction, and reproducibility. The results revealed that despite some family members sharing genetic heritage, the CRC group had greater combined gene polymorphism-mutations than the family controls (p < 0.1) for five genes including MTHFR C677T, MTHFR A1298C, MTR A2756G, MTRR A66G, and DHFR 19bp. Blood metabolites including homocysteine (7 µmol/L), methyl-folate (40 nmol/L) with total gene mutations (≥4); age (51 years) and vegetable intake (2 cups), and interactions of gene mutations and methylmalonic acid (MMA) (400 nmol/L) were significant predictors (all p < 0.0001) using the AICc. The results were validated by a 3% misclassification rate, AICc of 26, and >99% area under the receiver operating characteristic curve. These results point to the important roles of blood metabolites as potential markers in the prevention of CRC. Future intervention studies can be designed to target the ways to mitigate the enzyme-metabolite deficiencies in the OCM pathway to prevent cancer.
Association between baseline platelet count and severe adverse outcomes following percutaneous coronary intervention

Objective The aim is to evaluate the association between baseline platelet count (PC) and severe adverse outcomes following percutaneous coronary intervention (PCI) in current real-world practice. Methods A total of 18,788 patients underwent PCI with drug-eluting stents constituted the study population. Patients were categorized as having low (< 150 × 1000/µL), normal (150–300 × 1000/µL), and high (≥ 300 × 1000/µL) baseline PC. The primary endpoints included in-hospital and follow-up all-cause mortality. The secondary endpoint was major bleeding requiring a blood transfusion. Results In-hospital mortality rates for patients with low, normal, and high baseline PC were 0.6%, 0.4%, and 0.4%, respectively (P = 0.259). Similarly, mortality rates during long-term follow-up (median 23.8 months) for patients with low, normal, and high baseline PC were 0.9%, 0.6%, and 0.7%, respectively (P = 0.079). After multivariate adjustment, patients with low or high baseline PC tended to have similar risks for both in-hospital and follow-up mortality compared with the normal group. Subgroup analyses failed to demonstrate an independent prognostic value of baseline PC in specific population groups except patients who undwent transfemoral PCI. There was also no significant difference in the incidence of major bleeding requiring a blood transfusion in the low, normal, and high groups (0.5%, 0.3%, and 0.3%, respectively; P = 0.320). After multivariate adjustment, low or high baseline PC did not significantly increase the risk of major bleeding. Conclusion There is no significant association between baseline PC and severe adverse outcomes following PCI in current real-world practice.
Functional segregation of basal ganglia pathways in Parkinson’s disease

Dopamine exerts modulatory signals on cortex-basal ganglia circuits to enable flexible motor control. Parkinson's disease is characterized by a loss of dopaminergic innervation in the basal ganglia leading to complex motor and non-motor symptoms. Clinical symptom alleviation through dopaminergic medication and deep brain stimulation in the subthalamic nucleus likely depends on a complex interplay between converging basal ganglia pathways. As a unique translational research platform, deep brain stimulation allows instantaneous investigation of functional effects of subthalamic neuromodulation in human patients with Parkinson's disease. The present study aims at disentangling the role of the inhibitory basal ganglia pathways in cognitive and kinematic aspects of automatic and controlled movements in healthy and parkinsonian states by combining behavioural experiments, clinical observations, whole-brain deep brain stimulation fibre connectivity mapping and computational modelling. Twenty patients with Parkinson's disease undergoing subthalamic deep brain stimulation and 20 age-matched healthy controls participated in a visuomotor tracking task requiring normal (automatic) and inverted (controlled) reach movements. Parkinsonian patients on and off deep brain stimulation presented complex patterns of reaction time and kinematic changes, when compared to healthy controls. Stimulation of cortico-subthalamic fibres was correlated with reduced reaction time adaptation to task demand, but not kinematic aspects of motor control or alleviation of Parkinson's disease motor signs. By using clinically, behaviourally and fibre tracking informed computational models, our study reveals that loss of cognitive adaptation can be attributed to modulation of the hyperdirect pathway, while kinematic depends on suppression of indirect pathway activity. Our findings suggest that hyperdirect and indirect pathways, converging in the subthalamic nucleus, are differentially involved in cognitive aspects of cautious motor preparation and kinematic gain control during motor performance. Subthalamic deep brain stimulation modulates but does not restore these functions. Intelligent stimulation algorithms could re-enable flexible motor control in Parkinson's disease when adapted to instantaneous environmental demand. Our results may inspire new innovative pathway-specific approaches to reduce side effects and increase therapeutic efficacy of neuromodulation in patients with Parkinson's disease.
Sphingosine Kinase Regulates Neuropeptide Secretion During the Oxidative Stress-Response Through Intertissue Signaling

The Nrf2 antioxidant transcription factor promotes redox homeostasis in part through reciprocal signaling between neurons and neighboring cells, but the signals involved in intertissue signaling in response to Nrf2 activation are not well defined. In Caenorhabditis elegans, activation of SKN-1/Nrf2 in the intestine negatively regulates neuropeptide secretion from motor neurons. Here, we show that sphingosine kinase (SPHK-1) functions downstream of SKN-1/Nrf2 in the intestine to regulate neuropeptide secretion from motor neurons during the oxidative stress response in C. elegans hermaphrodites. SPHK-1 localizes to mitochondria in the intestine and SPHK-1 mitochondrial localization and kinase activity are essential for its function in regulating motor neuron function. SPHK-1 is recruited to mitochondria from cytosolic pools and its mitochondrial abundance is negatively regulated by acute or chronic SKN-1 activation. Finally, the regulation of motor function by SKN-1 requires the activation of the p38 MAPK cascade in the intestine and occurs through controlling the biogenesis or maturation of dense core vesicles in motor neurons. These findings show that the inhibition of SPHK-1 in the intestine by SKN-1 negatively regulates neuropeptide secretion from motor neurons, revealing a new mechanism by which SPHK-1 signaling mediates its effects on neuronal function in response to oxidative stress. SIGNIFICANCE STATEMENT Neurons are highly susceptible to damage by oxidative stress, yet have limited capacity to activate the SKN-1/Nrf2 oxidative stress response, relying instead on astrocytes to provide redox homeostasis. In Caenorhabditis elegans, intertissue signaling from the intestine plays a key role in regulating neuronal function during the oxidative stress response. Here, through a combination of genetic, behavioral, and fluorescent imaging approaches, we found that sphingosine kinase functions in the SKN-1/Nrf2 pathway in the intestine to regulate neuropeptide biogenesis and secretion in motor neurons. These results implicate sphingolipid signaling as a new component of the oxidative stress response and suggest that C. elegans may be a genetically tractable model to study non-cell-autonomous oxidative stress signaling to neurons.
Where The Light Gets In: Analyzing Web Censorship Mechanisms in India

In this work we present a detailed study of the Internet censorship mechanism in India. We consolidated a list of potentially blocked websites from various public sources to assess censorship mechanisms used by nine major ISPs. To begin with, we demonstrate that existing censorship detection tools like OONI are grossly inaccurate. We thus developed various techniques and heuristics to correctly assess censorship and study the underlying mechanism used by these ISPs. At every step we corroborated our finding manually to test the efficacy of our approach, an exercise largely ignored by several others. We fortify our findings by adjudging the coverage and consistency of censorship infrastructure, broadly in terms of average number of network paths and requested domains the infrastructure censors. Our results indicate a clear disparity among the ISPs, on how they install censorship infrastructure. For instance, in Idea network we observed the censorious middleboxes in over 90% of our tested intra-AS paths, whereas for Vodafone, it is as low as 2.5%. We conclude our research by devising our own novel anti-censorship strategies, that does not depend on third party tools (like proxies, Tor and VPNs etc.). We managed to access all blocked websites in all ISPs under test.
Do Gender-Related Stereotypes Affect Spatial Performance? Exploring When, How and to Whom Using a Chronometric Two-Choice Mental Rotation Task

It is a common belief that males have superior visuospatial abilities and that differences in this and other cognitive domains (e.g., math) contribute to the reduced interest and low representation of girls and women in STEM education and professions. However, previous studies show that gender-related implicit associations and explicit beliefs, as well as situational variables, might affect cognitive performance in those gender-stereotyped domains and produce between-gender spurious differences. Therefore, the present study aimed to provide information on when, how and who might be affected by the situational reactivation of stereotypic gender-science beliefs/associations while performing a 3D mental rotation chronometric task (3DMRT). More specifically, we assessed the explicit beliefs and implicit associations (by the Implicit Association Test) held by female and male students of humanities and STEM majors and compared their performance in a 3DMRT after receiving stereotype- congruent, incongruent and nullifying experimental instructions. Our results show that implicit stereotypic gender-science associations correlate with 3DMRT performance in both females and males, but that inter-gender differences emerge only under stereotype-reactivating conditions. We also found that changes in self-confidence mediate these instructions’ effects and that academic specialization moderates them, hence promoting 3DMRT performance differences between male and female humanities, but not STEM, students. Taken together, these observations suggest that the common statement “males have superior mental rotation abilities” simplifies a much more complex reality and might promote stereotypes which, in turn, might induce artefactual performance differences between females and males in such tasks.
Model-based fault detection and diagnosis of complex chemical processes: A case study of the Tennessee Eastman process

Fault detection and diagnosis for industrial systems has been an important field of research during the past years. Among these systems, the Tennessee Eastman process is extensively used as a realistic benchmark to test and compare different fault detection and diagnosis strategies. In this context, data-driven approach has been widely applied for fault detection and diagnosis of the Tennessee Eastman process, by exploiting the massive amount of available measurement data. However, only few published works had attempted to deal with the dynamic behavior of the whole system including the mixing zone, circulating pumps, the reactor, the separator, the stripper, and so on, because of the difficulty of modeling physical phenomena that may occur in such complex system. In this article, an accurate model of the Tennessee Eastman process, properly tailored for fault detection and diagnosis purposes, is provided. This model shows better fault detection and diagnosis performances than all the others proposed in the literature and gives better or comparable results with the data-driven approaches. This work uses the bond graph methodology to systematically develop computational and graphical model. This methodology provides a physical understanding of the system and a description of its dynamic behavior. The bond graph model is then used for monitoring purposes by generating formal fault indicators, called residuals, and algorithms for fault detection and diagnosis. Hence, abnormal situations are detected by supervising the residuals’ evolution and faults are isolated using the nature of the violated residuals. Therefore, the dynamic model of the Tennessee Eastman process can now be used as a basis to achieve accurately different analysis through the causal and structural features of the bond graph tool.
STATISTICAL APPROACH FOR HUMAN ELECTROMAGNETIC EXPOSURE ASSESSMENT IN FUTURE WIRELESS ATTO-CELL NETWORKS

Abstract In this article, we study human electromagnetic exposure to the radiation of an ultra dense network of nodes integrated in a floor denoted as ATTO-cell floor, or ATTO-floor. ATTO-cells are a prospective 5 G wireless networking technology, in which humans are exposed by several interfering sources. To numerically estimate this exposure we propose a statistical approach based on a set of finite difference time domain simulations. It accounts for variations of antenna phases and makes use of a large number of exposure evaluations, based on a relatively low number of required simulations. The exposure was expressed in peak-spatial 10-g SAR average (psSAR10g). The results show an average exposure level of ~4.9 mW/kg and reaching 7.6 mW/kg in 5% of cases. The maximum psSAR10g value found in the studied numerical setup equals around 21.2 mW/kg. Influence of the simulated ATTO-floor size on the resulting exposure was examined. All obtained exposure levels are far below 4 W/kg ICNIRP basic restriction for general public in limbs (and 20 W/kg basic restriction for occupational exposure), which makes ATTO-floor a potential low-exposure 5 G candidate.
Bullying at Workplace and Brain-Imaging Correlates

The relationship between psychosocial stress at work and mental health outcome is well-known. Brain-imaging studies hypothesize morphological brain modifications connected to work-related stress. To our knowledge this is the first study describing the link between work characteristics and brain imaging in a sample of work-related psychiatric patients assessed according to standardized clinical and diagnostic criteria. The aims of the study are: (1) to evaluate hippocampal and whole brain volumes in work-related psychiatric disturbances; (2) to verify the relationship between brain changes and the anxious and/or depressive symptoms; (3) to observe the relationship between the brain changes and the degree of the bullying at workplace. The hippocampus and whole brain volumes of 23 patients with work-related adjustment-disorders were compared with 15 controls by means of MRI. MR images highlight a smaller hippocampal volume in patients compared with controls. Significant reduction in the patients’ gray matter was found in three brain areas: right inferior temporal gyrus, left cuneus, left inferior occipital gyrus. The reduction of the hippocampi volumes was related to work distress and, above all, to bullying at workplace. The results confirm that the morphological brain abnormalities could be involved in work-related psychiatric disturbances.