Prominent Attribute Modification using Attribute Dependent Generative Adversarial Network

Modifying the facial images with desired attributes is important, though challenging tasks in computer vision, where it aims to modify single or multiple attributes of the face image. Some of the existing methods are either based on attribute independent approaches where the modification is done in the latent representation or attribute dependent approaches. The attribute independent methods are limited in performance as they require the desired paired data for changing the desired attributes. Secondly, the attribute independent constraint may result in the loss of information and, hence, fail in generating the required attributes in the face image. In contrast, the attribute dependent approaches are effective as these approaches are capable of modifying the required features along with preserving the information in the given image. However, attribute dependent approaches are sensitive and require a careful model design in generating high-quality results. To address this problem, we propose an attribute dependent face modification approach. The proposed approach is based on two generators and two discriminators that utilize the binary as well as the real representation of the attributes and, in return, generate high-quality attribute modification results. Experiments on the CelebA dataset show that our method effectively performs the multiple attribute editing with preserving other facial details intactly

Heaviness, health and happiness: a cross-sectional study of 163 066 UK Biobank participants

<b>Background</b><p></p> Obesity is known to increase the risk of many diseases and reduce overall quality of life. This study examines the relationship with self-reported health (SRH) and happiness.<p></p> <b>Methods</b> <p></p>We conducted a cross-sectional study of the 163 066 UK Biobank participants who completed the happiness rating. The association between adiposity and SRH and happiness was examined using logistic regression. SRH was defined as good (excellent, good), or poor (fair, poor). Self-reported happiness was defined as happy (extremely, very, moderately) or unhappy (moderately, very, extremely). <p></p> <b>Results</b> <p></p>Poor health was reported by 44 457 (27.3%) participants. The adjusted ORs for poor health were 3.86, 2.92, 2.60 and 6.41 for the highest, compared with lowest, deciles of Body Mass Index, waist circumference, waist to hip ratio and body fat percent, respectively. The associations were stronger in men (p<0.001). Overall, 7511 (4.6%) participants felt unhappy, and only class III obese participants were more likely to feel unhappy (adjusted OR 1.33, 95% CI 1.15 to 1.53, p<0.001) but the associations differed by sex (p<0.001). Among women, there was a significant association between unhappiness and all levels of obesity. By contrast, only class III obese men had significantly increased risk and overweight and class I obese men were less likely to be unhappy. <p></p> <b>Conclusions</b><p></p>Obesity impacts adversely on happiness as well as health, but the association with unhappiness disappeared after adjustment for self-reported health, indicating this may be mediated by health. Compared with obese men, obese women are less likely to report poor health, but more likely to feel unhappy. <p></p&gt

Breast Milk from Tanzanian Women has Divergent Effects on Cell-Free and Cell-Associated HIV-1 Infection in Vitro.

Transmission of HIV-1 during breastfeeding is a significant source of new pediatric infections in sub-Saharan Africa. Breast milk from HIV-positive mothers contains both cell-free and cell-associated virus; however, the impact of breast milk on HIV-1 infectivity remains poorly understood. In the present study, breast milk was collected from HIV-positive and HIV-negative Tanzanian women attending antenatal clinics in Dar es Salaam. Milk was analyzed for activity in vitro against both cell-free and cell-associated HIV-1. Potent inhibition of cell-free R5 and X4 HIV-1 occurred in the presence of milk from all donors regardless of HIV-1 serostatus. Inhibition of cell-free HIV-1 infection positively correlated with milk levels of sialyl-Lewis(X) from HIV-positive donors. In contrast, milk from 8 of 16 subjects enhanced infection with cell-associated HIV-1 regardless of donor serostatus. Milk from two of these subjects contained high levels of multiple pro-inflammatory cytokines including TNFα, IL-1β, IL-6, IL-8, MIP-1α, MIP-1β, MCP-1 and IP-10, and enhanced cell-associated HIV-1 infection at dilutions as high as 1∶500. These findings indicate that breast milk contains innate factors with divergent activity against cell-free and cell-associated HIV-1 in vitro. Enhancement of cell-associated HIV-1 infection by breast milk may be associated with inflammatory conditions in the mother and may contribute to infant infection during breastfeeding

Numerical study of Williamson nano fluid flow in an asymmetric channel

AbstractThis article investigates with the peristaltic flow of a Williamson nano fluid in an asymmetric channel. The related modeling of the problem has been done in Cartesian coordinate system. Problem has been simplified with the reliable assumptions i.e. long wave length and small Reynolds number. Numerical solutions have been evaluated for stream function, velocity profile, temperature profile, nano particle phenomena and pressure rise. Graphical results have been presented and discussed for various involved parameters

A Study of Partisan News Sharing in the Russian invasion of Ukraine

Since the Russian invasion of Ukraine, a large volume of biased and partisan news has been spread via social media platforms. As this may lead to wider societal issues, we argue that understanding how partisan news sharing impacts users' communication is crucial for better governance of online communities. In this paper, we perform a measurement study of partisan news sharing. We aim to characterize the role of such sharing in influencing users' communications. Our analysis covers an eight-month dataset across six Reddit communities related to the Russian invasion. We first perform an analysis of the temporal evolution of partisan news sharing. We confirm that the invasion stimulates discussion in the observed communities, accompanied by an increased volume of partisan news sharing. Next, we characterize users' response to such sharing. We observe that partisan bias plays a role in narrowing its propagation. More biased media is less likely to be spread across multiple subreddits. However, we find that partisan news sharing attracts more users to engage in the discussion, by generating more comments. We then built a predictive model to identify users likely to spread partisan news. The prediction is challenging though, with 61.57% accuracy on average. Our centrality analysis on the commenting network further indicates that the users who disseminate partisan news possess lower network influence in comparison to those who propagate neutral news

Coherent electrical readout of defect spins in 4H-SiC by photo-ionization at ambient conditions

Quantum technology relies on proper hardware, enabling coherent quantum state control as well as efficient quantum state readout. In this regard, wide-bandgap semiconductors are an emerging material platform with scalable wafer fabrication methods, hosting several promising spin-active point defects. Conventional readout protocols for such defect spins rely on fluorescence detection and are limited by a low photon collection efficiency. Here, we demonstrate a photo-electrical detection technique for electron spins of silicon vacancy ensembles in the 4H polytype of silicon carbide (SiC). Further, we show coherent spin state control, proving that this electrical readout technique enables detection of coherent spin motion. Our readout works at ambient conditions, while other electrical readout approaches are often limited to low temperatures or high magnetic fields. Considering the excellent maturity of SiC electronics with the outstanding coherence properties of SiC defects the approach presented here holds promises for scalability of future SiC quantum devices

Analysis of Growing Tumor on the Flow Velocity of Cerebrospinal Fluid in Human Brain Using Computational Modeling and Fluid-Structure Interaction

Cerebrospinal fluid (CSF) plays a pivotal role in normal functioning of Brain. Intracranial compartments such as blood, brain and CSF are incompressible in nature. Therefore, if a volume imbalance in one of the aforenoted compartments is observed, the other reaches out to maintain net change to zero. Whereas, CSF has higher compliance over long term. However, if the CSF flow is obstructed in the ventricles, this compliance may get exhausted early. Brain tumor on the other hand poses a similar challenge towards destabilization of CSF flow by compressing any section of ventricles thereby ensuing obstruction. To avoid invasive procedures to study effects of tumor on CSF flow, numerical-based methods such as Finite element modeling (FEM) are used which provide excellent description of underlying pathological interaction. A 3D fluid-structure interaction (FSI) model is developed to study the effect of tumor growth on the flow of cerebrospinal fluid in ventricle system. The FSI model encapsulates all the physiological parameters which may be necessary in analyzing intraventricular CSF flow behavior. Findings of the model show that brain tumor affects CSF flow parameters by deforming the walls of ventricles in this case accompanied by a mean rise of 74.23% in CSF flow velocity and considerable deformation on the walls of ventricles