Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduced distractor interference in neurotypical adults with high expression of autistic traits irrespective of stimulus type

Attention atypicality is evident in autism spectrum disorder (ASD) and its broader phenotype with previous studies suggesting that in some cases participants can be more efficient at ignoring distracting irrelevant information. However, it is not clear to what extent this improved filtering capacity is driven by perceptual atypicality, such as local bias or atypical face processing, which is also sometimes reported in these populations. For instance, better ability to ignore the global aspect of a display could stem from a local perceptual bias rather than from improved distractor inhibition. To test whether distractor suppression per se, is associated with high expression of autistic traits, in the present study a large cohort of neurotypical participants (n = 218), in whom expression of autistic traits was assessed, performed two nonspatial attention selection tasks with different categories of stimuli (global/local and face/scene). Importantly, both tasks involved a conflict with one aspect of the stimuli designated as the target and the other designated as the distractor. Across the two experiments adults with high autistic traits were overall, better able to ignore distractors than adults with low autistic traits, irrespective of the type of perceptual processing involved. These results support the notion that autistic tendencies are associated with increased attention filtering (at least when target and distractor remain constant) which is not dependent on perceptual biases. Thus, future work in the broader autism phenotype should explicitly consider the effect played by attention mechanisms in this population. Autism Res 2018, 11: 1345–1355. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.
SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation

Collaborative Filtering (CF) is one of the most successful approaches for recommender systems. With the emergence of online social networks, social recommendation has become a popular research direction. Most of these social recommendation models utilized each user's local neighbors' preferences to alleviate the data sparsity issue in CF. However, they only considered the local neighbors of each user and neglected the process that users' preferences are influenced as information diffuses in the social network. Recently, Graph Convolutional Networks~(GCN) have shown promising results by modeling the information diffusion process in graphs that leverage both graph structure and node feature information. To this end, in this paper, we propose an effective graph convolutional neural network based model for social recommendation. Based on a classical CF model, the key idea of our proposed model is that we borrow the strengths of GCNs to capture how users' preferences are influenced by the social diffusion process in social networks. The diffusion of users' preferences is built on a layer-wise diffusion manner, with the initial user embedding as a function of the current user's features and a free base user latent vector that is not contained in the user feature. Similarly, each item's latent vector is also a combination of the item's free latent vector, as well as its feature representation. Furthermore, we show that our proposed model is flexible when user and item features are not available. Finally, extensive experimental results on two real-world datasets clearly show the effectiveness of our proposed model.
Is ctDNA the Road Map to the Landscape of the Clonal Mutational Evolution in Drug Resistance? Lessons from the PALOMA-3 Study and Implications for Precision Medicine.

The correlative circulating tumor DNA (ctDNA) studies of the PALOMA-3 clinical trial showed that acquired resistance to fulvestrant and palbociclib is associated with clonal evolution and acquired mutations in RB1, PIK3CA, and ESR1, with the latter two related to fulvestrant resistance. These results highlight the potential of ctDNA as a tool to detect mechanisms of resistance and infer the next line of treatment. Cancer Discov; 8(11); 1352-4. ©2018 AACR See related article by O'Leary et al., p. 1390.
Phlegmasia Cerulea Dolens with Compartment Syndrome

Venous thromboembolism (VTE) is a major healthcare problem that results in significant mortality, morbidity, and expenditure of resources. It compounds with pulmonary embolism (PE) and deep vein thrombosis (DVT). Phlegmasia cerulea dolens (PCD) is an uncommon but potentially life-threatening complication of acute DVT characterized by marked swelling of the extremities with pain and cyanosis, which in turn may lead to arterial ischemia and ultimately gangrene with high amputation and mortality rates. The key in treating such patients is to provide quick and effective treatment to save the limbs and the patient.
Using Independent Component Analysis and Estimated Thin-Cloud Reflectance to Remove Cloud Effect on Landsat-8 Oli Band Data

Coupled with the independent component analysis (ICA) and estimated thin-cloud reflectance data, an algorithm to remove thin-cloud effects on the operational land imager (OLI) data of Landsat-8 was studied. The algorithm was evaluated with a subimage extracted from Landsat-8 041/036 scene acquired on 16 March 2015. Thin clouds were effectively removed visually after the algorithm. In the algorithm validation, a cloud-free Landsat-8 image acquired on 1 April 2015 was selected as the “truth”. Spatial correlation coefficients of the March image before the cloud-removal algorithm and April image and of the March image after the algorithm and April image were evaluated on the band-by-band basis. The coefficients increased significantly after the algorithm. Thus, the developed algorithm was quantitatively effective and valid.
New parallel Genetic Algorithms on GPU for solving Max-CSPs

Constraint Satisfaction Problems (CSPs) are among the easiest and more used formalisms to model real-world-constrained problems (transport, planning, scheduling, Indeed, the Genetic Algorithm (GA) is one of the optimization methods used to solve CSPs. This meta-heuristic finds a good solution in a reasonable time. However, it could be inefficient when dealing with very large-scale problems, in particular CSPs. Therefore, the High Performance Computing (HPC) is recommended, as an additional way, to accelerate the research. This paper introduces two parallel genetic algorithm-based approaches using GPU for solving Maximal Constraint Satisfaction Problems (Max-CSPs). The first approach is based on one parallelism level, while the second approach is based on two parallelism levels. The experimental results presented in this work, prove how efficient our proposed approaches are.
Effect of Physical Parameters on Outcomes of Total Knee Arthroplasty

Background: Increasing body mass index (BMI) has been shown to correlate with increased rates of complications after total knee arthroplasty. To our knowledge, body surface area, body mass, and height have not been investigated in this manner. BMI and body surface area are affected differently by changes in height, and they are affected similarly by changes in weight. The purpose of this study was to quantify revision for any reason, mechanical failure, aseptic loosening, polyethylene wear, reoperation, and any infection after total knee arthroplasty using BMI, body surface area, body mass, and height as continuous variables. Methods: Prospectively collected data from a single institution’s total joint registry were used to analyze 22,243 consecutive knees, in 16,106 patients, treated with a primary total knee arthroplasty from 1985 to 2012. The Kaplan-Meier survival method was used to evaluate revision and other common complications, with outcomes assessed using Cox regression analysis. Smoothing spline parameterization was used on physical parameters in these models. Results: Increasing BMI, body surface area, body mass, and height were associated with an increased risk of any revision surgical procedure, mechanical failure, and aseptic loosening after total knee arthroplasty. The risk of a revision surgical procedure was directly associated with each 1 standard deviation increase in BMI (hazard ratio [HR], 1.19; p < 0.01), body surface area (HR, 1.37; p < 0.01), body mass (HR, 1.30; p < 0.01), and height (HR, 1.22; p < 0.01). This association was especially demonstrated with revision for mechanical failure (BMI: HR, 1.15; p < 0.01; body surface area: HR, 1.35; p < 0.01; body mass: HR, 1.27; p < 0.01; and height: HR, 1.23; p < 0.01). The risk of failure in the subgroups of mechanical failure including a revision surgical procedure for aseptic loosening or polyethylene wear was also associated with increasing body surface area, body mass, and height. Increasing BMI (HR, 1.22; p < 0.01), body surface area (HR, 2.56; p < 0.01), and body mass (HR, 2.54; p < 0.01) were also associated with increased risk of any infection. Conclusions: Increasing BMI, body surface area, body mass, and height were strongly associated with the rates of revision, aseptic loosening, and other common complications following total knee arthroplasty. Body surface area and body mass appear to correlate more strongly with mechanical failure outcomes than BMI or height. Level of Evidence: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.
Exploring the Influential Factors in Continuance Usage of Online Dating Apps: Gratification, Subjective Well-Being and Self-Disclosure

Nowadays, finding a romantic partner using online dating apps have become a prevalent phenomenon. This study proposes a research model for investigating the antecedents of users’ intention to use online dating apps continually. In this study, we explore the influence of subjective well-being, self-disclosure and perceived usefulness on users’ continuance intention. Furthermore, this study examines whether gratification in online dating increases users’ subjective well-being and their perceived usefulness of online dating apps. For developing a more thorough research model, this study employs self-disclosure variables as second order construct that consist of depth, intent, honesty and valence. In addition, this research also explores subjective well-being’s influence on self-disclosure. The proposed research model is analyzed by partial least square approach, with 692 respondents. The result shows that subjective well-being, perceived usefulness and self-disclosure have significant influence on user’s continuance intention. Furthermore, subjective well-being is affected by several gratifications provided in online dating.
Sex roles and sexual selection: lessons from a dynamic model system

Abstract Our understanding of sexual selection has greatly improved during the last decades. The focus is no longer solely on males, but also on how female competition and male mate choice shape ornamentation and other sexually selected traits in females. At the same time, the focus has shifted from documenting sexual selection to exploring variation and spatiotemporal dynamics of sexual selection, and their evolutionary consequences. Here, I review insights from a model system with exceptionally dynamic sexual selection, the two-spotted goby fish Gobiusculus flavescens. The species displays a complete reversal of sex roles over a 3-month breeding season. The reversal is driven by a dramatic change in the operational sex ratio, which is heavily male-biased at the start of the season and heavily female-biased late in the season. Early in the season, breeding-ready males outnumber mature females, causing males to be highly competitive, and leading to sexual selection on males. Late in the season, mating-ready females are in excess, engage more in courtship and aggression than males, and rarely reject mating opportunities. With typically many females simultaneously courting available males late in the season, males become selective and prefer more colorful females. This variable sexual selection regime likely explains why both male and female G. flavescens have ornamental colors. The G. flavescens model system reveals that sexual behavior and sexual selection can be astonishingly dynamic in response to short-term fluctuations in mating competition. Future work should explore whether sexual selection is equally dynamic on a spatial scale, and related spatiotemporal dynamics.
The effects of estradiol and testosterone on renal tissues oxidative after central injection of angiotensin II in female doca – salt treated rats

Abstract Background Although numerous studies have proven that estrogen (Est) has a protective effect on the development of hypertension, more research needs to be done to show its detailed mechanism in a variety of hypertension. The important role of active oxygen species in blood pressure is well defined. We examined whether or not sex hormones change the growth of reactive oxygen species (ROS) ‎in kidneys after central microinjection of angiotensin II (Ang II). ‎ Materials and methods Female Wistar rats, 8 weeks old (200 ± 10 g) were used in this study. The animal groups were (1) Sham, (2) Ovariectomy (OVX), (3) Sham-Hypertension (Sham-Hyper), (4) OVX-Hypertension (OVX-Hyper), (5) Sham-Hyper-Est, (6) OVX-Hyper-Est‎;‎ (7) Sham-Hyper-Testosterone (Tst) and (8) OVX-Hyper-Tst. Solutions of 1% NaCl and 0.1 KCl ‎were used and desoxycorticostrone (doca-salt) was injected (45 mg/kg) 3 times a week in Hypertension groups. Estradiol and Tst (2 mg/kg and ‎5 mg/kg‎; daily; subcutaneously) for 4 weeks. Ang II (50 μM, 5 μL) was microinjected by intracerebroventricular ( i.c.v.) infusion and malondialdehyde (MDA) and thiol in the kidneys were measured. Results MDA in the kidneys was increased by Ang II and doca-salt treatments. Both estradiol and Tst decreased the kidney’s MDA. The level of thiol was higher in Hyper ‎groups and reversed after treatment with estradiol and Tst. Conclusions Our findings suggest that central effect of Ang II on blood pressure and kidney ‎disease is accompanied with increased levels of oxidative stress in the kidneys. Indeed sex hormones change the ROS level in the kidneys after central ‎microinjection of Ang II. ‎‎
Facilitating Collocated Crowdsourcing on Situated Displays

Online crowdsourcing enables the distribution of work to a global labor force as small and often repetitive tasks. Recently, situated crowdsourcing has emerged as a complementary enabler to elicit labor in specific locations and from specific crowds. Teamwork in online crowdsourcing has been recently shown to increase the quality of output, but teamwork in situated crowdsourcing remains unexplored. We set out to fill this gap. We present a generic crowdsourcing platform that supports situated teamwork and provide experiences from a laboratory study that focused on comparing traditional online crowdsourcing to situated team-based crowdsourcing. We built a crowdsourcing desk that hosts three networked terminal displays. The displays run our custom team-driven crowdsourcing platform that was used to investigate collocated crowdsourcing in small teams. In addition to analyzing quantitative data, we provide findings based on questionnaires, interviews, and observations. We highlight 1) emerging differences between traditional and collocated crowdsourcing, 2) the collaboration strategies that teams exhibited in collocated crowdsourcing, and 3) that a priori team familiarity does not significantly affect collocated interaction in crowdsourcing. The approach we introduce is a novel multi-display crowdsourcing setup that supports collocated labor teams and along with the reported study makes specific contributions to situated crowdsourcing research.
Monitoring Three Dimensional Displacements of the Shuping Landslide, Three Gorges Area with Multi- Temporal Terrasar-X Sar Images

Three dimensional displacements are more convenient for people understanding ground processes. However, only azimuth or line of sight (LOS) measurements can be directly extracted from SAR images which restrict further applications, especially for people who are not expertise in radar remote sensing. Aiming at this problem, we proposed an approach of retrieving time series three-dimensional displacements from multi-angular SAR datasets. Firstly, time series displacements in the azimuth and LOS direction can be estimated using traditional methods of SAR interferometry (InSAR) and SAR pixel offset tracking. Then, a fitting and interpolation procedure was applied to parameterize the displacement history and interpolate the displacements from different datasets with identical dates. Thus, three dimensional displacements can be obtained by making use of the different observation geometry of different SAR datasets. Our method was applied to retrieve three dimensional displacements history of the Shuping landslide, Three Gorges area, China.
Fusion of Lidar, Hyperspectral and RGB Data for Urban Land Use and Land Cover Classification

In this paper, we present an ensemble-based classification approach for urban land use and land cover classification based on multispectral LiDAR, hyperspectral and very high resolution RGB data. The approach has been evaluated on the data set provided for the IEEE GRSS 2018 Data Fusion Contest organized by the GRSS IADF technical committee and has been proven to have a high operational performance, being able to distinguish between different grass-, building- and street-types among other classes like water, railways and parking lots as well as other non-typical classes like cars, trains, stadium seats, etc.
The Janus of macrophysiology: stronger effects of evolutionary history, but weaker effects of climate on upper thermal limits are reversed for lower thermal limits in ants

Abstract Species may exhibit similar traits via different mechanisms: environmental filtering and local adaptation (geography) and shared evolutionary history (phylogeny) can each contribute to the resemblance of traits among species. Parsing trait variation into geographic and phylogenetic sources is important, as each suggests different constraints on trait evolution. Here, we explore how phylogenetic distance, geographic distance, and geographic variation in climate shape physiological tolerance of high and low temperatures using a global dataset of ant thermal tolerances. We found generally strong roles for evolutionary history and geographic variation in temperature, but essentially no detectable effects of spatial proximity per se on either upper or lower thermal tolerance. When we compared the relative importance of the factors shaping upper and lower tolerances, we found a much stronger role for evolutionary history in shaping upper versus lower tolerance, and a moderately weaker role for geographic variation in temperature in shaping upper tolerance when compared with lower tolerance. Our results demonstrate how geographic variation in climate and evolutionary history may have differential effects on the upper and lower endpoints of physiological tolerance. This Janus effect, where the relative contributions of geographic variation in climate and evolutionary history are reversed for lower versus upper physiological tolerances, has gained some support in the literature, and our results for ant physiological tolerances provide further evidence of this pattern. As the climate continues to change, the high phylogenetic conservatism of upper tolerance may suggest potential constraints on the evolution of tolerance of high temperatures.
Analysis of radio frequency interference mitigation using two reference antennas and closure relations in interferometric arrays

Radio-frequency interference (RFI) is a critical problem in radio astronomy observations. A powerful RFI mitigation technique introduced by Briggs in 2000, uses closure relations and an independent reference signal to estimate and effectively remove RFI term from the power spectra of dish-based telescopes. However, the proposed technique assumes reference antennas receive zero or negligible astronomical signal, which causes biased error in the outcome of cancellation, especially for low-frequency interferometric arrays with wide field of view (FoV). This paper revisits the proposed technique for RFI removal of interferometric arrays using two reference antennas with significant sky signal. The relationship between the residual error of the cancellation and the pattern of the reference antenna is investigated, providing a general guideline on design specifications of the reference antennas. This analysis potentially leads to further application in any wide FoV telescopes to alleviate the contamination of terrestrial FM and Digital TV RFI broadcast signals in radio astronomy observations.
Achieving Sar Target Configuration Recognition By Combining Sparse Graph And Locality Preserving Projections

Synthetic aperture radar (SAR) target configuration recognition is a challenging task, and the key point is to realize effective feature extraction. An algorithm combing the advantages of sparse graph and locality preserving projections (LPP) is proposed to achieve SAR target configuration recognition. Taking the merits of sparse representation (SR) into consideration, an affinity matrix is established to realize effective structure preserving of the dataset. Besides, the problem of matrix singularity in LPP is effectively resolved by diagonal loading. Experimental results on the moving and stationary target acquisition and recognition (MSTAR) database validate the effectiveness and superiority of the proposed algorithm.
Deformation Monitoring of the Northern Sector of the Valencia Basin (E Spain) Using Ps-Insar (1993–2010)

Synthetic Aperture Radar Interferometry (InSAR) is a remote sensing technique very effective for the measurement of small displacements of the Earth's surface over large areas at a very low cost in comparison with conventional geodetic techniques. Advanced InSAR time series (Multi-Temporal InSAR or MT - InSAR) algorithms for monitoring and investigating surface displacement on Earth are based on conventional radar interferometry. These techniques allow us to measure deformation with uncertainties of one millimeter per year, interpreting time series of interferometric phases at coherent point scatterers (PS) without the need for human or special equipment presence. By applying InSAR processing techniques to a series of radar images over the same region, it is possible to monitor large areas and detect vertical displacements of ground, and infrastructures on the ground, and therefore identify abnormal or excessive movements indicating potential problems requiring detailed ground investigation. In this paper, we apply the PS- InSAR technique to a dataset of ERS-1/2 and Envisat radar images covering the period 1993–2010, to monitor the northern sector of the Valencia basin (Valencia city and its surroundings). Some subsiding areas were detected, with rates up to −5 mm/yr, whose causes are being investigated.
Interferometric Processing of Circular SAR Using Fully Polarimetric C-Band Data

The combination of interference and circular SAR (CSAR) can reduce the influence of high sidelobes in the vertical direction of CSAR while retaining the merits of CSAR, such as subwavelength resolution and 3D imaging capability. However, C-band repeated pass interference is difficult due to short wavelength and decorrelation. This paper introduces interferometric processing of CSAR using fully polarimetric C-band circular data which is acquired over a test site in Zhuhai, China. The phase of 2D CSAR images obtained at two different platform height in the same subaperture is different. And the interferogram is acquired based on the phase difference. The experiment verifies the feasibility of repeated pass interference model for CSAR at C-band.