Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualizing Gaze Direction to Support Video Coding of Social Attention for Children with Autism Spectrum Disorder

This paper presents a novel interface to support video coding of social attention in the assessment of children with autism spectrum disorder. Video-based evaluations of social attention during therapeutic activities allow observers to find target behaviors while handling the ambiguity of attention. Despite the recent advances in computer vision-based gaze estimation methods, fully automatic recognition of social attention under diverse environments is still challenging. The goal of this work is to investigate an approach that uses automatic video analysis in a supportive manner for guiding human judgment. The proposed interface displays visualization of gaze estimation results on videos and provides GUI support to allow users to facilitate agreement between observers by defining social attention labels on the video timeline. Through user studies and expert reviews, we show how the interface helps observers perform video coding of social attention and how human judgment compensates for technical limitations of the automatic gaze analysis.
Generalized matrix completion for low complexity transceiver processing in cache-aided Fog-RAN via the Burer-Monteiro approach

The emerging concept of Dense Fog Radio Access Network (Fog-RAN) pushes computation and storage resources to network edges as an effective architecture for wirelessly storing, processing, and exchanging big data information. However, the corresponding traffic overhead for massive channel state information (CSI) acquisition poses a serious obstacle to the design objective of achieving low network latency. This paper studies a cache-aided dense Fog-RAN by proposing a topo-logical content delivery approach to maximize the achievable degrees-of-freedom (DoF) based only on the network topologies and side message information. Specifically, we present a generalized low-rank matrix completion approach, for which, we propose a Riemannian trust-region algorithm based on Burer-Monteiro factorization to solve a fixed rank subproblem in complex field by semidefinite lifting. Our results demonstrate the performance benefit of the proposed algorithm over known methods.
Multi-task regression using minimal penalties

In this paper we study the kernel multiple ridge regression framework, which we refer to as multitask regression, using penalization techniques. The theoretical analysis of this problem shows that the key element appearing for an optimal calibration is the covariance matrix of the noise between the different tasks. We present a new algorithm to estimate this covariance matrix, based on the concept of minimal penalty, which was previously used in the single-task regression framework to estimate the variance of the noise. We show, in a non-asymptotic setting and under mild assumptions on the target function, that this estimator converges towards the covariance matrix. Then plugging this estimator into the corresponding ideal penalty leads to an oracle inequality. We illustrate the behavior of our algorithm on synthetic examples.
Loss of α-Synuclein Does Not Affect Mitochondrial Bioenergetics in Rodent Neurons

Abstract Increased α-synuclein (αsyn) and mitochondrial dysfunction play central roles in the pathogenesis of Parkinson’s disease (PD), and lowering αsyn is under intensive investigation as a therapeutic strategy for PD. Increased αsyn levels disrupt mitochondria and impair respiration, while reduced αsyn protects against mitochondrial toxins, suggesting that interactions between αsyn and mitochondria influences the pathologic and physiologic functions of αsyn. However, we do not know if αsyn affects normal mitochondrial function or if lowering αsyn levels impacts bioenergetic function, especially at the nerve terminal where αsyn is enriched. To determine if αsyn is required for normal mitochondrial function in neurons, we comprehensively evaluated how lowering αsyn affects mitochondrial function. We found that αsyn knockout (KO) does not affect the respiration of cultured hippocampal neurons or cortical and dopaminergic synaptosomes, and that neither loss of αsyn nor all three (α, β and γ) syn isoforms decreased mitochondria-derived ATP levels at the synapse. Similarly, neither αsyn KO nor knockdown altered the capacity of synaptic mitochondria to meet the energy requirements of synaptic vesicle cycling or influenced the localization of mitochondria to dopamine (DA) synapses in vivo. Finally, αsyn KO did not affect overall energy metabolism in mice assessed with a Comprehensive Lab Animal Monitoring System. These studies suggest either that αsyn has little or no significant physiological effect on mitochondrial bioenergetic function, or that any such functions are fully compensated for when lost. These results implicate that αsyn levels can be reduced in neurons without impairing (or improving) mitochondrial bioenergetics or distribution.
Environmental variables across Pan troglodytes study sites correspond with the carbon, but not the nitrogen, stable isotope ratios of chimpanzee hair

Diet influences the stable isotope ratios of carbon and nitrogen (δ13C and δ15N values) in animal tissue; but here we explore the influences of particular aspects of the local environment on those values in chimpanzees (Pan troglodytes). In this article we present new δ13C and δ15N values in Gombe chimpanzees using hairs collected from night nests in 1989. Then, we explore the influence of environmental factors by comparing our Gombe data to those from eight additional Pan study sites with previously published stable isotope data. We compare chimpanzee δ13Chair and δ15Nhar values to specific characteristics of local site ecology (biome and ecoregion) and to local Mean Annual Precipitation (MAP) to test hypotheses based on known effects of these variables on the δ13C and δ15N values in plant tissues. The comparison shows that hair from chimpanzees living in savanna sites with lower MAP have higher δ13Chair values than do chimpanzees living in woodland and forested sites with higher MAP. These results demonstrate the potential of using δ13C values in primate tissue to indicate aspects of their local ecology in cases where the ecology is uncertain, such as samples collected early in the last century and in fossil hominins. In contrast to expectations, however, chimpanzee δ15Nhair values from some savanna sites with lower MAP are lower, not higher, than those living in more forested areas with higher MAP. It is likely that diet selectivity by chimpanzees affects δ15Nhair values to a greater extent than does the influence of precipitation on plants. Am. J. Primatol. 78:1055–1069, 2016. © 2015 Wiley Periodicals, Inc
An enhanced IAF-MPNLMS algorithm for sparse system identification

For a highly sparse impulse response the modified proportionate normalized least-mean-square (MPNLMS) algorithm converges slowly during the update of small coefficients, because the proportionality of these coefficients is ignored in the learning process of the algorithm. An individual-activation factor (IAF)-MPNLMS algorithm resolves this problem by assigning individual activation factors for the coefficients. However, it suffers from slow convergence if the input signal is highly correlated. In Enhanced (E)IAF-PNLMS algorithm, a new gain distribution strategy for the coefficients that have already almost converged is introduced. In this paper, a square-root(non-linear) activation factor is suggested for the IAF-MPNLMS algorithm and subsequently, gain redistribution strategy following the procedure given in the EIAF-PNLMS algorithm is adopted in updating the tap coefficients. The proposed algorithm converges faster than EIAF-PNLMS as well as with the other well-known MPNLMS and IAF-MPNLMS algorithms for identification of sparse system when input signal becomes highly correlated. We conclude numerical experiments to illustrate the performance of the proposed (EIAF-MPNLMS) algorithm. Simulation results exhibit that the EIAF-MPNLMS algorithm achieves faster convergence, outperforming the EIAF-PNLMS and other existing PNLMS type algorithms.
A cell engineering strategy to enhance supercoiled plasmid DNA production for gene therapy

ABSTRACT With the recent revival of the promise of plasmid DNA vectors in gene therapy, a novel synthetic biology approach was used to enhance the quantity, (yield), and quality of the plasmid DNA. Quality was measured by percentage supercoiling and supercoiling density, as well as improving segregational stability in fermentation. We examined the hypothesis that adding a Strong Gyrase binding Site (SGS) would increase DNA gyrase‐mediated plasmid supercoiling. SGS from three different replicons, (the Mu bacteriophage and two plasmids, pSC101 and pBR322) were inserted into the plasmid, pUC57. Different sizes of these variants were transformed into E. coli DH5α, and their supercoiling properties and segregational stability measured. A 36% increase in supercoiling density was found in pUC57‐SGS, but only when SGS was derived from the Mu phage and was the larger sized version of this fragment. These results were also confirmed at fermentation scale. Total percentage supercoiled monomer was maintained to 85–90%. A twofold increase in plasmid yield was also observed for pUC57‐SGS in comparison to pUC57. pUC57‐SGS displayed greater segregational stability than pUC57‐cer and pUC57, demonstrating a further potential advantage of the SGS site. These findings should augment the potential of plasmid DNA vectors in plasmid DNA manufacture. Biotechnol. Bioeng. 2016;113: 2064–2071. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.
A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization

Mendelian randomization (MR) uses genetic data to probe questions of causality in epidemiological research, by invoking the Instrumental Variable (IV) assumptions. In recent years, it has become commonplace to attempt MR analyses by synthesising summary data estimates of genetic association gleaned from large and independent study populations. This is referred to as two‐sample summary data MR. Unfortunately, due to the sheer number of variants that can be easily included into summary data MR analyses, it is increasingly likely that some do not meet the IV assumptions due to pleiotropy. There is a pressing need to develop methods that can both detect and correct for pleiotropy, in order to preserve the validity of the MR approach in this context. In this paper, we aim to clarify how established methods of meta‐regression and random effects modelling from mainstream meta‐analysis are being adapted to perform this task. Specifically, we focus on two contrastin g approaches: the Inverse Variance Weighted (IVW) method which assumes in its simplest form that all genetic variants are valid IVs, and the method of MR‐Egger regression that allows all variants to violate the IV assumptions, albeit in a specific way. We investigate the ability of two popular random effects models to provide robustness to pleiotropy under the IVW approach, and propose statistics to quantify the relative goodness‐of‐fit of the IVW approach over MR‐Egger regression. © 2017 The Authors. Statistics in Medicine Published by JohnWiley & Sons Ltd
Dynamics of Hydration of Nanocellulose Films

The design of materials capable of mechanical responses to physical and chemical stimuli represents one of the most exciting and challenging areas of scientific research because of the huge number of their potential applications. This article is focused on the molecular events occurring in thin films of carboxylated nanocellulose fibers, which are capable of converting water gradients into mechanical movements at the macroscopic scale. The analysis of the mechano‐actuation, and of the conditions to obtain it, shows that the film movement is fast and reproducible, the gradient intensity is transduced into rate of displacement, and the response is observed at vapor pressures as low as 1.2 mm Hg. The actuation mechanism is associated to an efficient and reversible water sorption process by the hydrophilic nanocellulose fibers at the film interface. Conversely, water desorption is slow and follows a kinetic behavior supporting the presence of two binding sites for water molecules. The adsorbed water induces swelling of the surface nanocellulose layers and local structural rearrangement, however transitions between ordered and random coil conformations are not observed. The understanding of the actuation mechanisms of nanocellulose offers exciting opportunities to design macroscopic structures responding to chemical gradients by the assembly of simple molecular components.
Racial and Ethnic Differences in Mental Health among Asian Americans and Non-Hispanic Whites: Based on California Health Interview Survey

ABSTRACT While Asians are becoming the largest ethnic group in the United States, studies have focused on Asians as a single population. The purpose of this study was to explore the racial and ethnic mental health differences between non-Hispanic Whites and Asians, with an emphasis on understudied subgroups, from the California Health Interview Survey 2011/2012. In this dataset Asians had significantly lower adjusted odds ratios for both mental distress and serious mental illness. However, when Asians were divided into subgroups and compared to Whites, Vietnamese and Japanese subgroups were significantly lower than Whites for mental distress while Koreans were significantly higher. Vietnamese and Chinese were found to have significantly less serious mental illness than Whites in the subgroup analyses. Our results underscore the importance of recognizing that Asian subgroups should not be overlooked, and all Asians should not automatically be treated as a homogenous group.
The Effectiveness of Simulator Motion in the Transfer of Performance on a Tracking Task Is Influenced by Vision and Motion Disturbance Cues

Objective: To examine the importance of platform motion to the transfer of performance in motion simulators. Background: The importance of platform motion in simulators for pilot training is strongly debated. We hypothesized that the type of motion (e.g., disturbance) contributes significantly to performance differences. Methods: Participants used a joystick to perform a target tracking task in a pod on top of a MOOG Stewart motion platform. Five conditions compared training without motion, with correlated motion, with disturbance motion, with disturbance motion isolated to the visual display, and with both correlated and disturbance motion. The test condition involved the full motion model with both correlated and disturbance motion. We analyzed speed and accuracy across training and test as well as strategic differences in joystick control. Results: Training with disturbance cues produced critical behavioral differences compared to training without disturbance; motion itself was less important. Conclusion: Incorporation of disturbance cues is a potentially important source of variance between studies that do or do not show a benefit of motion platforms in the transfer of performance in simulators. Application: Potential applications of this research include the assessment of the importance of motion platforms in flight simulators, with a focus on the efficacy of incorporating disturbance cues during training.
Optimal placement and charge/discharge scheduling of electric parking lots considering reactive power generation capability

Increasing the number of electric parking lots (EPLs) in the distribution systems may have some important impacts on their performances. These impacts can improve or deteriorate the system's performance depending on the EPLs' charge/discharge scheduling (CDS), location and size of these resources. This paper presents an approach to firstly determine an appropriate charge/discharge scheduling for an EPL in a 24-hour time period. Secondly, the optimal location is specified for an EPL to reduce energy loss, improve voltage stability, and voltage profile considering the reactive power capability of the EPL's inverter. The proposed method is implemented on the IEEE 33-bus standard distribution system. The genetic algorithm and backward-forward power flow method are utilized to evaluate the effectiveness of the proposed method.
Pulmonary embolism detection using localized vessel-based features in dual energy CT

Pulmonary embolism (PE) affects up to 600,000 patients and contributes to at least 100,000 deaths every year in the United States alone. Diagnosis of PE can be difficult as most symptoms are unspecific and early diagnosis is essential for successful treatment. Computed Tomography (CT) images can show morphological anomalies that suggest the existence of PE. Various image-based procedures have been proposed for improving computer-aided diagnosis of PE. We propose a novel method for detecting PE based on localized vessel-based features computed in Dual Energy CT (DECT) images. DECT provides 4D data indexed by the three spatial coordinates and the energy level. The proposed features encode the variation of the Hounsfield Units across the different levels and the CT attenuation related to the amount of iodine contrast in each vessel. A local classification of the vessels is obtained through the classification of these features. Moreover, the localization of the vessel in the lung provides better comparison between patients. Results show that the simple features designed are able to classify pulmonary embolism patients with an AUC (area under the receiver operating curve) of 0.71 on a lobe basis. Prior segmentation of the lung lobes is not necessary because an automatic atlas-based segmentation obtains similar AUC levels (0.65) for the same dataset. The automatic atlas reaches 0.80 AUC in a larger dataset with more control cases.
Piezoelectric Thin Films of ZnO-Nanorods/Nanowalls Grown by Chemical Bath Deposition

This study presents a comparison of the piezoelectric properties of nanostructured thin films made of arrays of vertically oriented ZnO-nanorods (ZnO-NRs) over ITO-glass substrate and of ZnO-nanowalls (ZnO-NWs) over aluminium substrate. Both nanostructures were synthesized on a large area through chemical bath deposition. The morphological, structural, and chemical characteristics of the produced nanostructures were investigated in order to assess the crystal quality and purity. To this purpose, we used different techniques, such as field-emission scanning electron microscopy, atomic force microscopy, energy dispersive x-ray analysis, powder x-ray diffraction, x-ray photoelectron spectroscopy, and photoluminescence spectroscopy. Moreover, the piezoelectric response of the nanostructured films was assessed through piezoresponse force microscopy. This technique was employed to obtain a quantitative evaluation of the piezoelectric coefficient (<inline-formula><tex-math notation="LaTeX">${d_{33}}$</tex-math></inline-formula>) of the film. We obtained <inline-formula><tex-math notation="LaTeX">${d_{33}}$</tex-math></inline-formula> values as high as (7.01 ± 0.33) pm/V for ZnO-NRs and (2.63 ± 0.49) pm/V for ZnO-NWs films.
Molecular Basis of a Dominant T Cell Response to an HIV Reverse Transcriptase 8-mer Epitope Presented by the Protective Allele HLA-B*51:01

CD8+ CTL responses directed toward the HLA-B*51:01–restricted HIV-RT128–135 epitope TAFTIPSI (TI8) are associated with long-term nonprogression to AIDS. Clonotypic analysis of responses to B51-TI8 revealed a public clonotype using TRAV17/TRBV7-3 TCR genes in six out of seven HLA-B*51:01+ patients. Structural analysis of a TRAV17/TRBV7-3 TCR in complex with HLA–B51-TI8, to our knowledge the first human TCR complexed with an 8-mer peptide, explained this bias, as the unique combination of residues encoded by these genes was central to the interaction. The relatively featureless peptide-MHC (pMHC) was mainly recognized by the TCR CDR1 and CDR2 loops in an MHC-centric manner. A highly conserved residue Arg97 in the CDR3α loop played a major role in recognition of peptide and MHC to form a stabilizing ball-and-socket interaction with the MHC and peptide, contributing to the selection of the public TCR clonotype. Surface plasmon resonance equilibrium binding analysis showed the low affinity of this public TCR is in accordance with the only other 8-mer interaction studied to date (murine 2C TCR–H-2Kb-dEV8). Like pMHC class II complexes, 8-mer peptides do not protrude out the MHC class I binding groove like those of longer peptides. The accumulated evidence suggests that weak affinity might be a common characteristic of TCR binding to featureless pMHC landscapes.
A Machine Learning-based Method for Question Type Classification in Biomedical Question Answering

Summary Background and Objective: Biomedical question type classification is one of the important components of an automatic biomedical question answering system. The performance of the latter depends directly on the performance of its biomedical question type classification system, which consists of assigning a category to each question in order to determine the appropriate answer extraction algorithm. This study aims to automatically classify biomedical questions into one of the four categories: (1) yes/no, (2) factoid, (3) list, and (4) summary. Methods: In this paper, we propose a biomedical question type classification method based on machine learning approaches to automatically assign a category to a biomedical question. First, we extract features from biomedical questions using the proposed handcrafted lexico-syntactic patterns. Then, we feed these features for machine- learning algorithms. Finally, the class label is predicted using the trained classifiers. Results: Experimental evaluations performed on large standard annotated datasets of biomedical questions, provided by the BioASQ challenge, demonstrated that our method exhibits significant improved performance when compared to four baseline systems. The proposed method achieves a roughly 10-point increase over the best baseline in terms of accuracy. Moreover, the obtained results show that using handcrafted lexico-syntactic patterns as features’ provider of support vector machine (SVM) lead to the highest accuracy of 89.40%. Conclusion: The proposed method can automatically classify BioASQ questions into one of the four categories: yes/no, factoid, list, and summary. Furthermore, the results demonstrated that our method produced the best classification performance compared to four baseline systems.