DPDnet: A Robust People Detector using Deep Learning with an Overhead Depth Camera

In this paper we propose a method based on deep learning that detects multiple people from a single overhead depth image with high reliability. Our neural network, called DPDnet, is based on two fully-convolutional encoder-decoder neural blocks based on residual layers. The Main Block takes a depth image as input and generates a pixel-wise confidence map, where each detected person in the image is represented by a Gaussian-like distribution. The refinement block combines the depth image and the output from the main block, to refine the confidence map. Both blocks are simultaneously trained end-to-end using depth images and head position labels. The experimental work shows that DPDNet outperforms state-of-the-art methods, with accuracies greater than 99% in three different publicly available datasets, without retraining not fine-tuning. In addition, the computational complexity of our proposal is independent of the number of people in the scene and runs in real time using conventional GPUs

Personality Disorders and Health Problems Distinguish Suicide Attempters from Completers in a Direct Comparison

Background Whether suicide attempters and completers represent the same population evaluated at different points along a progression towards suicide death, overlapping populations, or completely different populations is a problem still unresolved. Methods 446 Adult suicide attempters and knowledgeable collateral informants for 190 adult suicide probands were interviewed. Sociodemographic and clinical data was collected for both groups using semi-structured interviews and structured assessments. Univariate analyses and logistic regression models were conducted to explore the similarities and differences between suicide attempters and completers. Results Univariate analyses yielded significant differences in sociodemographics, recent life events, impulsivity, suicide intent, and distribution of Axis I and II disorders. A logistic regression model aimed at distinguishing suicide completers from attempters properly classified 90% of subjects. The most significant variables that distinguished suicide from attempted suicide were the presence of narcissistic personality disorder (OR=21.4; 95% CI=6.8–67.7), health problems (OR=20.6; 95% CI=5.6–75.9), male sex (OR=9.6; 95% CI=4.42–20.9), and alcohol abuse (OR=5.5; 95% CI=2.3–14.2). Limitations Our study shares the limitations of studies comparing suicide attempters and completers, namely that information from attempters can be obtained from the subject himself, whereas the assessment of completers depends on information from close family or friends. Furthermore, different semi-structured instruments assessed Axis I and Axis II disorders in suicide attempters and completers. Finally, we have no data on inter-rater reliability data. Conclusions Suicide completers are more likely to be male and suffer from alcohol abuse, health problems (e.g. somatic illness), and narcissistic personality disorder. The findings emphasize the importance of implementing suicide prevention programs tailored to suicide attempters and completers

P-P Total Cross Sections at VHE from Accelerator Data

Comparison of P-P total cross-sections estimations at very high energies - from accelerators and cosmic rays - shows a disagreement amounting to more than 10 %, a discrepancy which is beyond statistical errors. Here we use a phenomenological model based on the Multiple-Diffraction approach to successfully describe data at accelerator energies. The predictions of the model are compared with data On the basis of regression analysis we determine confident error bands, analyzing the sensitivity of our predictions to the employed data for extrapolation. : using data at 546 and 1.8 TeV, our extrapolations for p-p total cross-sections are only compatible with the Akeno cosmic ray data, predicting a slower rise with energy than other cosmic ray results and other extrapolation methods. We discuss our results within the context of constraints in the light of future accelerator and cosmic ray experimental results.Comment: 26 pages aqnd 11 figure

Daratumumab in combination with urelumab to potentiate anti-myeloma activity in lymphocytedeficient mice reconstituted with human NK cells

Daratumumab is an anti-CD38 fully human IgG1 mAb approved for multiple myeloma treatment. One of the proposed mechanisms of action is the induction of antibody-dependent cellular cytotoxicity (ADCC) mediated by NK cells. NK cells acquire surface CD137 expression in the presence of solid-phase-attached daratumumab and when encountering a daratumumab-coated CD38+ tumor cell line. In this setting, addition of the agonist anti-CD137 mAb urelumab enhances NK-cell activation increasing CD25 expression and IFNɣ production. However, in vitro ADCC is not increased by the addition of urelumab both in 4h or 24h lasting experiments. To study urelumab-increased daratumumab-mediated ADCC activity in vivo, we set up a mouse model based on the intravenous administration of a luciferase-transfected multiple myeloma cell line of human origin, human NK cells and daratumumab to immuno-deficient NSG mice. In this model, intravenous administration of urelumab 24h after daratumumab delayed tumor growth and prolonged mice survival

Targeted glutamate supply boosts insulin concentrations, ovarian activity, and ovulation rate in yearling goats during the anestrous season

The neuroendocrine regulation of the seasonal reproductive axis requires the integration of internal and external signals to ensure synchronized physiological and behavioral responses. Seasonal reproductive changes contribute to intermittent production, which poses challenges for optimizing goat product yields. Consequently, a significant objective in seasonal reproduction research is to attain continuous reproduction and enhance profitability in goat farming. Glutamate plays a crucial role as a modulator in several reproductive and metabolic processes. Hence, the aim of this study was to evaluate the potential impact of exogenous glutamate administration on serum insulin concentration and ovarian function during the out-of-season period in yearling goats. During the anestrous season, animals were randomly located in individual pens to form two experimental groups: (1) glutamate (n = 10, live weight (LW) = 29.1 ± 1.02 kg, body condition score (BCS) = 3.4 ± 0.2 units) and (2) control (n = 10; LW = 29.2 ± 1.07 kg, BCS = 3.5 ± 0.2), with no differences (p < 0.05) regarding LW and BCS. Then, goats were estrus-synchronized, and blood sampling was carried out for insulin quantification. Ovaries were ultrasonographically scanned to assess ovulation rate (OR), number of antral follicles (AFs), and total ovarian activity (TOA = OR + AF). The research outcomes support our working hypothesis. Certainly, our study confirms that those yearling goats treated with exogenous glutamate displayed the largest (p < 0.05) insulin concentrations across time as well as an augmented (p < 0.05) out-of-season ovarian activity

The 2HWC HAWC Observatory Gamma Ray Catalog

We present the first catalog of TeV gamma-ray sources realized with the recently completed High Altitude Water Cherenkov Observatory (HAWC). It is the most sensitive wide field-of-view TeV telescope currently in operation, with a 1-year survey sensitivity of ~5-10% of the flux of the Crab Nebula. With an instantaneous field of view >1.5 sr and >90% duty cycle, it continuously surveys and monitors the sky for gamma ray energies between hundreds GeV and tens of TeV. HAWC is located in Mexico at a latitude of 19 degree North and was completed in March 2015. Here, we present the 2HWC catalog, which is the result of the first source search realized with the complete HAWC detector. Realized with 507 days of data and represents the most sensitive TeV survey to date for such a large fraction of the sky. A total of 39 sources were detected, with an expected contamination of 0.5 due to background fluctuation. Out of these sources, 16 are more than one degree away from any previously reported TeV source. The source list, including the position measurement, spectrum measurement, and uncertainties, is reported. Seven of the detected sources may be associated with pulsar wind nebulae, two with supernova remnants, two with blazars, and the remaining 23 have no firm identification yet.Comment: Submitted 2017/02/09 to the Astrophysical Journa