Maple-Swarm: programming collective behavior for ensembles by extending HTN-planning

Programming goal-oriented behavior in collective adaptive systems is complex, requires high effort, and is failure-prone. If the system's user wants to deploy it in a real-world environment, hurdles get even higher: Programs urgently require to be situation-aware. With our framework Maple, we previously presented an approach for easing the act of programming such systems on the level of particular robot capabilities. In this paper, we extend our approach for ensemble programming with the possibility to address virtual swarm capabilities encapsulating collective behavior to whole groups of agents. By using the respective concepts in an extended version of hierarchical task networks and by adapting our self-organization mechanisms for executing plans resulting thereof, we can achieve that all agents, any agent, any other set of agents, or a swarm of agents execute (swarm) capabilities. Moreover, we extend the possibilities of expressing situation awareness during planning by introducing planning variables that can get modified at design-time or run-time as needed. We illustrate the possibilities with examples each. Further, we provide a graphical front-end offering the possibility to generate mission-specific problem domain descriptions for ensembles including a lightweight simulation for validating plans

Comparison of knowledge scores of medical students in problem-based learning and traditional curriculum on public health topics

BACKGROUND: The purpose of the study was to compare the knowledge scores of medical students in Problem-based Learning and traditional curriculum on public health topics. METHODS: We planned a cross-sectional study including the fifth and sixth year medical students of Dokuz Eylul University in Turkey. The fifth year students (PBL group, n = 56) were the pioneers educated with PBL curriculum since the 1997–1998 academic year. The sixth year students (traditional education group, n = 78) were the last students educated with traditional education methods. We prepared 25 multiple-choice questions in order to assess knowledge scores of students on selected subjects of Public Health. Our data were collected in year 2002. RESULTS: Mean test scores achieved in PBL and traditional groups were 65.0 and 60.5 respectively. PBL students were significantly more successful in the knowledge test (p = 0.01). The knowledge scores of two topics were statistically higher among PBL students. These topics were health management and chronic diseases. CONCLUSION: We found that mean total evaluation score in the PBL group was 4.5 points higher than in the traditional group in our study. Focusing only on the knowledge scores of students is the main limitation of our study. Upon the graduation of the first PBL students in the 2002–2003 academic year, we are planning additional studies regarding the other functions of a physician such as skill, behaviour and attitude

Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

In this work, the variations in the metabolic profile of blood plasma from lung cancer patients and healthy controls were investigated through NMR-based metabonomics, to assess the potential of this approach for lung cancer screening and diagnosis. PLS-DA modeling of CPMG spectra from plasma, subjected to Monte Carlo Cross Validation, allowed cancer patients to be discriminated from controls with sensitivity and specificity levels of about 90%. Relatively lower HDL and higher VLDL + LDL in the patients' plasma, together with increased lactate and pyruvate and decreased levels of glucose, citrate, formate, acetate, several amino acids (alanine, glutamine, histidine, tyrosine, valine), and methanol, could be detected. These changes were found to be present at initial disease stages and could be related to known cancer biochemical hallmarks, such as enhanced glycolysis, glutaminolysis, and gluconeogenesis, together with suppressed Krebs cycle and reduced lipid catabolism, thus supporting the hypothesis of a systemic metabolic signature for lung cancer. Despite the possible confounding influence of age, smoking habits, and other uncontrolled factors, these results indicate that NMR-based metabonomics of blood plasma can be useful as a screening tool to identify suspicious cases for subsequent, more specific radiological tests, thus contributing to improved disease management.ERDF - Competitive Factors Thematic Operational ProgrammeFCT/PTDC/ QUI/68017/2006FCOMP-01-0124-FEDER-007439SFRH/BD/ 63430/2009National UNESCO Committee - L'Oréal Medals of Honor for Women in Science 200Portuguese National NMR Network - RNRM

Impact of sex-specific target dose in chronic heart failure patients with reduced ejection fraction

Aims A recent study suggested that women with heart failure and heart failure reduced ejection fraction might hypothetically need lower doses of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers ( = renin-angiotensin-system inhibitors) and beta-blockers than men to achieve the best outcome. We assessed the current medical treatment of heart failure reduced ejection fraction in men and women in a large contemporary cohort and address the hypothetical impact of changing treatment levels in women. Methods This analysis is part of a large contemporary quality of heart failure care project which includes 5320 (64%) men and 3003 (36%) women with heart failure reduced ejection fraction. Detailed information on heart failure therapy prescription and dosage were collected. Results Women less often received renin-angiotensin-system inhibitors (79% vs 83%, p 100% of the new hypothetical target dose would be 24% for beta-blockers and 52% for renin-angiotensin-system inhibitors, which can be considered as relatively overdosed. Conclusion In this large contemporary heart failure registry, there were significant but relatively small differences in drug dose between men and women with heart failure reduced ejection fraction. Implementation of the hypothetical sex-specific target dosing schedule would lead to considerably more women adequately treated. In contrast, we identified a group of women who might have been relatively overdosed with increased risk of side-effects and intolerance

The Impact of Dementia on Women Internationally: an Integrative Review

Women are disproportionately affected by dementia, both in terms of developing dementia and becoming caregivers. We conducted an integrative review of English language literature of the issues affecting women in relation to dementia from an international perspective. The majority of relevant studies were conducted in high income countries, and none were from low-income countries. The effects of caregiving on health, wellbeing and finances are greater for women; issues facing women, particularly in low and middle-income countries need to be better understood. Research should focus on building resilience to help people adjust and cope long term

Monocular Expressive Body Regression through Body-Driven Attention

To understand how people look, interact, or perform tasks, we need to quickly and accurately capture their 3D body, face, and hands together from an RGB image. Most existing methods focus only on parts of the body. A few recent approaches reconstruct full expressive 3D humans from images using 3D body models that include the face and hands. These methods are optimization-based and thus slow, prone to local optima, and require 2D keypoints as input. We address these limitations by introducing ExPose (EXpressive POse and Shape rEgression), which directly regresses the body, face, and hands, in SMPL-X format, from an RGB image. This is a hard problem due to the high dimensionality of the body and the lack of expressive training data. Additionally, hands and faces are much smaller than the body, occupying very few image pixels. This makes hand and face estimation hard when body images are downscaled for neural networks. We make three main contributions. First, we account for the lack of training data by curating a dataset of SMPL-X fits on in-the-wild images. Second, we observe that body estimation localizes the face and hands reasonably well. We introduce body-driven attention for face and hand regions in the original image to extract higher-resolution crops that are fed to dedicated refinement modules. Third, these modules exploit part-specific knowledge from existing face- and hand-only datasets. ExPose estimates expressive 3D humans more accurately than existing optimization methods at a small fraction of the computational cost. Our data, model and code are available for research at https://expose.is.tue.mpg.de .Comment: Accepted in ECCV'20. Project page: http://expose.is.tue.mpg.d

Consumer trust and confidence in the compliance of Islamic banks

Islamic banks compete with traditional (non-Islamic) banks for customers. This article aims to provide insight into why some Muslims choose to bank with Islamic banks in Pakistan, while others do not. Specifically, it addresses the questions: to what extent are trust and confidence active influencers in the decision-making process, are they differentiated or are they one of the same? Also how does the Pakistani collective cultural context further complicate the application of these concepts? For the purposes of this article trust refers to people and their interpersonal or social relations whereas confidence concerns institutions such as banks. Drawing on interviews with Muslim consumers in Pakistan, this study provides further insight into consumer behaviour within financial services and specifically Islamic banking and contributes to our theoretical understanding of the concepts of trust and confidence

Motion Capture of Hands in Action Using Discriminative Salient Points

Abstract. Capturing the motion of two hands interacting with an object is a very challenging task due to the large number of degrees of freedom, self-occlusions, and similarity between the fingers, even in the case of multiple cameras observing the scene. In this paper we propose to use discriminatively learned salient points on the fingers and to estimate the finger-salient point associations simultaneously with the estimation of the hand pose. We introduce a differentiable objective function that also takes edges, optical flow and collisions into account. Our qualitative and quantitative evaluations show that the proposed approach achieves very accurate results for several challenging sequences containing hands and objects in action.