Social Odometry: Imitation Based Odometry in Collective Robotics

The improvement of odometry systems in collective robotics remains an important challenge for several applications. Social odometry is an online social dynamics which confers the robots the possibility to learn from the others. Robots neither share any movement constraint nor access to centralized information. Each robot has an estimate of its own location and an associated confidence level that decreases with distance traveled. Social odometry guides a robot to its goal by imitating estimated locations, confidence levels and actual locations of its neighbors. This simple online social form of odometry is shown to produce a self-organized collective pattern which allows a group of robots to both increase the quality of individuals’ estimates and efficiently improve their collective performanc

Barriers to Bystander Intervention in Sexual Harassment: The Dark Triad and Rape Myth acceptance in Indonesia, Singapore, and United Kingdom

Bystanders have an important role in preventing sexual violence, but they are often reluctant to intervene due to a range of barriers. In this study, we investigated relationships between the Dark Triad of personality (i.e. psychopathy, Machiavellianism and narcissism), rape myth acceptance and five bystander barriers. We addressed the paucity of research by collecting data from three countries (Indonesia, Singapore, and United Kingdom). In total, 716 University staff and students participated in an online survey. We found very few country-level differences in the correlations between the variables. In regression analyses, Machiavellianism and rape myth acceptance both had significant, positive relationships with failure to identify risk, failure to take responsibility, skills deficits and audience inhibition. Narcissism and psychopathy were significantly, negatively associated with audience inhibition and skills deficits. Findings indicate similarity in predictors of perceived barriers to bystander intervention across the three countries

Plasma copeptin as biomarker of disease progression and prognosis in cirrhosis

BACKGROUND & AIMS: Research on vasopressin (AVP) in cirrhosis and its role in the assessment of prognosis has been hindered by the difficulty of measuring AVP levels accurately. Copeptin, a 39-aminoacid glycopeptide, is released from the neurohypophysis together with AVP. Copeptin could have a role as biomarker of prognosis in cirrhosis as it may reflect circulatory dysfunction. The aim of this study is to investigate the role of copeptin as biomarker of disease progression and prognosis in cirrhosis. METHODS: This prospective study is divided in 2 study protocols including 321 consecutive patients. Plasma copeptin levels were measured in all patients at study inclusion. Protocol 1: to investigate the relationship of copeptin with kidney and circulatory function (56 patients). Protocol 2: to investigate the relationship between copeptin and prognosis, as assessed by the development of complications of cirrhosis or mortality at 3months (265 patients admitted to hospital for complications of cirrhosis). RESULTS: Patients with decompensated cirrhosis showed significantly higher plasma copeptin levels compared to those of patients with compensated cirrhosis. Copeptin levels had a significant positive correlation with model for end-satge liver disease (MELD) score, AVP, endogenous vasoconstrictor systems, and kidney function parameters. Patients developing complications of cirrhosis or mortality had significantly higher plasma copeptin levels compared to those of the remaining patients. Plasma copeptin levels were an independent predictive factor of both the development of complications and mortality at 3months. This was confirmed in a validation series of 120 patients. CONCLUSIONS: Copeptin is a novel biomarker of disease progression and prognosis in cirrhosis. LAY SUMMARY: Copeptin is a fragment of the vasopressin precursor, a hormone that is known to be increased in patients with cirrhosis and that plays a role in the development of complications of the disease. Vasopressin is difficult to measure, but copeptin is a more stable molecule and is easier to measure in blood. Solà and Kerbert and colleagues have shown in a series of 361 patients that copeptin is markedly increased in patients with cirrhosis who develop complications during the following 3months, compared to those patients who do not develop complications. Moreover, copeptin correlates with prognosis

Clinical validation of risk scoring systems to predict risk of delayed bleeding after EMR of large colorectal lesions

[Background and Aims]: The Endoscopic Resection Group of the Spanish Society of Endoscopy (GSEED-RE) model and the Australian Colonic Endoscopic Resection (ACER) model were proposed to predict delayed bleeding (DB) after EMR of large superficial colorectal lesions, but neither has been validated. We validated and updated these models.[Methods]: A multicenter cohort study was performed in patients with nonpedunculated lesions ≥20 mm removed by EMR. We assessed the discrimination and calibration of the GSEED-RE and ACER models. Difficulty performing EMR was subjectively categorized as low, medium, or high. We created a new model, including factors associated with DB in 3 cohort studies.[Results]: DB occurred in 45 of 1034 EMRs (4.5%); it was associated with proximal location (odds ratio [OR], 2.84; 95% confidence interval [CI], 1.31-6.16), antiplatelet agents (OR, 2.51; 95% CI, .99-6.34) or anticoagulants (OR, 4.54; 95% CI, 2.14-9.63), difficulty of EMR (OR, 3.23; 95% CI, 1.41-7.40), and comorbidity (OR, 2.11; 95% CI, .99-4.47). The GSEED-RE and ACER models did not accurately predict DB. Re-estimation and recalibration yielded acceptable results (GSEED-RE area under the curve [AUC], .64 [95% CI, .54-.74]; ACER AUC, .65 [95% CI, .57-.73]). We used lesion size, proximal location, comorbidity, and antiplatelet or anticoagulant therapy to generate a new model, the GSEED-RE2, which achieved higher AUC values (.69-.73; 95% CI, .59-.80) and exhibited lower susceptibility to changes among datasets.[Conclusions]: The updated GSEED-RE and ACER models achieved acceptable prediction levels of DB. The GSEED-RE2 model may achieve better prediction results and could be used to guide the management of patients after validation by other external groups. (Clinical trial registration number: NCT 03050333.)Research support for this study was received from “La Caixa/Caja Navarra” Foundation (ID 100010434;project PR15/11100006)

Plasma copeptin as biomarker of disease progression and prognosis in cirrhosis

Lay summary: Copeptin is a fragment of the vasopressin precursor, a hormone that is known to be increased in patients with cirrhosis and that plays a role in the development of complications of the disease. Vasopressin is difficult to measure, but copeptin is a more stable molecule and is easier to measure in blood. Sola and Kerbert and colleagues have shown in a series of 361 patients that copeptin is markedly increased in patients with cirrhosis who develop complications during the following 3 months, compared to those patients who do not develop complications. Moreover, copeptin correlates with prognosis. (C) 2016 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

A 6-minute sub-maximal run test to predict VO2 max

Maximal oxygen uptake (VO2 max) is a key indicator to assess health as well as sports performance. Currently, maximal exercise testing is the most accurate measure of maximal aerobic power, since submaximal approaches are still imprecise. In this paper, we propose a new method to predict VO2max from a submaximal, low intensity, test in sports men and women. 182 males and 108 females from the High Performance Center of Pontevedra (Spain), aged 10–46 years old, with a VO2max between 30.1 and 81.2 mL·min−1·kg−1, completed a maximal incremental test to volitional exhaustion. The test began at a speed of 6 km·h−1 and increased by 0.25 km·h−1 every 15 seconds. Using the data gathered during the first 6 minutes of the test, two different regression models were adjusted using functional data analysis and a traditional linear regression model with scalar covariates. The functional regression model obtained the best results, adjusted r2 = 0.845 and RMSE = 2.8 mL·min−1·kg−1, but the linear regression model also obtained a good fit, adjusted r2 = 0.798 and RMSE = 3.5 mL·min−1·kg−1. Both methods are more accurate than classical submaximal tests, although oxygen consumption needs to be measured during the test

Social Odometry: Imitation Based Odometry in Collective Robotics

The improvement of odometry systems in collective robotics remains an important challenge for several applications. Social odometry is an online social dynamics which confers the robots the possibility to learn from the others. Robots neither share any movement constraint nor access to centralized information. Each robot has an estimate of its own location and an associated confidence level that decreases with distance traveled. Social odometry guides a robot to its goal by imitating estimated locations, confidence levels and actual locations of its neighbors. This simple online social form of odometry is shown to produce a self-organized collective pattern which allows a group of robots to both increase the quality of individuals' estimates and efficiently improve their collective performance