Deep Regionlets for Object Detection

In this paper, we propose a novel object detection framework named "Deep Regionlets" by establishing a bridge between deep neural networks and conventional detection schema for accurate generic object detection. Motivated by the abilities of regionlets for modeling object deformation and multiple aspect ratios, we incorporate regionlets into an end-to-end trainable deep learning framework. The deep regionlets framework consists of a region selection network and a deep regionlet learning module. Specifically, given a detection bounding box proposal, the region selection network provides guidance on where to select regions to learn the features from. The regionlet learning module focuses on local feature selection and transformation to alleviate local variations. To this end, we first realize non-rectangular region selection within the detection framework to accommodate variations in object appearance. Moreover, we design a "gating network" within the regionlet leaning module to enable soft regionlet selection and pooling. The Deep Regionlets framework is trained end-to-end without additional efforts. We perform ablation studies and conduct extensive experiments on the PASCAL VOC and Microsoft COCO datasets. The proposed framework outperforms state-of-the-art algorithms, such as RetinaNet and Mask R-CNN, even without additional segmentation labels.Comment: Accepted to ECCV 201

It's OK not to be OK: Shared Reflections from two PhD Parents in a Time of Pandemic

Adopting an intersectional feminist lens, we explore our identities as single and co‐parents thrust into the new reality of the UK COVID‐19 lockdown. As two PhD students, we present shared reflections on our intersectional and divergent experiences of parenting and our attempts to protect our work and families during a pandemic. We reflect on the social constructions of ‘masculinities’ and ‘emphasized femininities’ as complicated influence on our roles as parents. Finally, we highlight the importance of time and self‐care as ways of managing our shared realities during this uncertain period. Through sharing reflections, we became closer friends in mutual appreciation and solidarity as we learned about each other’s struggles and vulnerabilities

The challenge of parenting girls in neighborhoods of different perceived quality

It is well-known that disadvantaged neighborhoods, as officially identified through census data, harbor higher numbers of delinquent individuals than advantaged neighborhoods. What is much less known is whether parents’ perception of the neighborhood problems predicts low parental engagement with their girls and, ultimately, how this is related to girls’ delinquency, including violence. This paper elucidates these issues by examining data from the Pittsburgh Girls Study, including parent-report of neighborhood problems and level of parental engagement and official records and girl-reported delinquency at ages 15, 16, and 17. Results showed higher stability over time for neighborhood problems and parental engagement than girls’ delinquency. Parents’ perception of their neighborhood affected the extent to which parents engaged in their girls’ lives, but low parental engagement did not predict girls being charged for offending at age 15, 16 or 17. These results were largely replicated for girls’ self-reported delinquency with the exception that low parental engagement at age 16 was predictive of the frequency of girls’ self-reported delinquency at age 17 as well. The results, because of their implications for screening and early interventions, are relevant to policy makers as well as practitioners

Effect of site of lactate infusion on regional lactate exchange in pigs

Background The rate of extra-hepatic lactate production and the route of influx of lactate to the liver may influence both hepatic and extra-hepatic lactate exchange. We assessed the dose-response of hepatic and extra-hepatic lactate exchange during portal and central venous lactate infusion. Methods Eighteen pigs randomly received either portal (n=5) or central venous (n=7) lactate infusion or saline (n=6). Sodium lactate was infused at 33, 66, 99, and 133 µmol kg−1 min−1 for 20 min each. Systemic and regional abdominal blood flows and plasma lactate were measured at 20 min intervals until 1 h post-infusion, and regional lactate exchange was calculated (area under lactate uptake-time curve). Results Total hepatic lactate uptake [median (95% confidence interval)] during the experimental protocol (140 min) was higher during portal [8198 (5487-12 798) µmol kg−1] than during central venous lactate infusion [4530 (3903-5514) µmol kg−1, P<0.05]. At a similar hepatic lactate delivery (∼400 µmol kg−1 min−1), hepatic lactate uptake [mean and standard deviation (sd)] was higher during portal [118 (sd 55) µmol kg−1 min−1] than during central venous lactate infusion [44 (12) µmol kg−1 min−1, P<0.05]. Time courses of arterial lactate concentrations and lactate uptake at other measured regions were similar in both groups. Conclusions Higher hepatic lactate uptake during portal compared with central venous lactate infusion at a similar total hepatic lactate influx underlines the role of portal vein lactate concentration in total hepatic lactate uptake capacity. Arterial lactate concentration does not depend on the site of lactate infusion. At higher arterial lactate concentrations, all regions participated in lactate uptak

Development of the electroweak phase transition and baryogenesis

We investigate the evolution of the electroweak phase transition, using a one-Higgs effective potential that can be regarded as an approximation for the Minimal Supersymmetric Standard Model. The phase transition occurs in a small interval around a temperature T_t below the critical one. We calculate this temperature as a function of the parameters of the potential and of a damping coefficient related to the viscosity of the plasma. The parameters that are relevant for baryogenesis, such as the velocity and thickness of the walls of bubbles and the value of the Higgs field inside them, change significantly in the range of temperatures where the first-order phase transition can occur. However, we find that in the likely interval for T_t there is no significant variation of these parameters. Furthermore, the temperature T_t is in general not far below the temperature at which bubbles begin to nucleate.Comment: 26 pages, 7 figures; typos corrected, reference adde

Panel: Going Virtual: Are there Real Opportunities for Business in Virtual Worlds?

Summary of Panel Topic (related to ICIS track theme on Social Networking

Signal Space Separation Beamformer

We have combined Signal Space Separation and beamformers (SSS beamformer). The SSS beamformer was tested by simulation in the presence of simulated brain noise. The SSS beamformer performs at least as well as the conventional beamformer, provided that the expansion order is sufficiently high. For beamformer outputs which depend on power or power difference normalized by the projected noise, the spatial resolution of the SSS beamformer is significantly better than that of the conventional beamformers if the sources are deeper, and about the same as that of the conventional beamformer when the sources are superficial. For beamformer outputs which depend on the ratio of powers, the spatial resolutions of the SSS and conventional beamfomers are the same. The sensor noise covariance matrix in the SSS basis is non-diagonal. The SSS beamformers with diagonalized noise covariance matrix exhibit better spatial resolution than that with non-diagonal noise covariance matrix. The SSS beamformers are computationally more efficient than the conventional beamformers

Children's health and parental socioeconomic factors: a population-based survey in Finland

<p>Abstract</p> <p>Background</p> <p>Socioeconomic inequalities in health are a global problem, not only among the adult population but also among children. However, studies concerning young children especially are rare. The aim of this study was to describe the health of Finnish children under 12 years of age, and the socioeconomic factors associated with health. The socioeconomic factors were parental education level, household net income, and working status.</p> <p>Methods</p> <p>A population-based survey among Finnish children aged under 12 years (n = 6,000) was conducted in spring 2007. A questionnaire was sent to parents, and a response rate of 67% was achieved. Each child's health was explored by asking a parent to report the child's health status on a 5-point Likert scale, current symptoms from a symptoms list, and current disease(s) diagnosed by a physician. The final three outcome measures were poor health, the prevalences of psychosomatic symptoms, and long-term diseases. Data were analysed using Pearson's Chi-Square tests, and logistic regression analysis with 95% confidence intervals (CIs). P-values ≤0.05 were considered as statistically significant.</p> <p>Results</p> <p>In total, 3% of parents reported that their child's health status was poor. The prevalences of psychosomatic symptoms and long-term diseases were both 11%. The probability for poor health status was lowest among children aged 3-6 and 7-11 years, and for psychosomatic symptoms among 3-6-year-old children, whereas the odds ratios for long-term diseases was highest among children aged 7-11 years. Parental socioeconomic factors were not associated with the children's health.</p> <p>Conclusions</p> <p>Most of the children were reported by their parent to have good health status, and approximately one tenth had experienced some psychosomatic symptoms or long-term diseases. Our study suggests that parental socioeconomic factors are not associated with the health of children aged under 12 years in Finland.</p

AVEC 2011 – the first international Audio/Visual Emotion Challenge

Abstract. The Audio/Visual Emotion Challenge andWorkshop (AVEC 2011) is the first competition event aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual and audiovisual emotion analysis, with all participants competing under strictly the same conditions. This paper first describes the challenge par-ticipation conditions. Next follows the data used – the SEMAINE corpus – and its partitioning into train, development, and test partitions for the challenge with labelling in four dimensions, namely activity, expectation, power, and valence. Further, audio and video baseline features are intro-duced as well as baseline results that use these features for the three sub-challenges of audio, video, and audiovisual emotion recognition