On the evolution of harming and recognition in finite panmictic and infinite structured populations.

Natural selection may favor two very different types of social behaviors that have costs in vital rates (fecundity and/or survival) to the actor: helping behaviors, which increase the vital rates of recipients, and harming behaviors, which reduce the vital rates of recipients. Although social evolutionary theory has mainly dealt with helping behaviors, competition for limited resources creates ecological conditions in which an actor may benefit from expressing behaviors that reduce the vital rates of neighbors. This may occur if the reduction in vital rates decreases the intensity of competition experienced by the actor or that experienced by its offspring. Here, we explore the joint evolution of neutral recognition markers and marker-based costly conditional harming whereby actors express harming, conditional on actor and recipient bearing different conspicuous markers. We do so for two complementary demographic scenarios: finite panmictic and infinite structured populations. We find that marker-based conditional harming can evolve under a large range of recombination rates and group sizes under both finite panmictic and infinite structured populations. A direct comparison with results for the evolution of marker-based conditional helping reveals that, if everything else is equal, marker-based conditional harming is often more likely to evolve than marker-based conditional helping.

Block structured dynamics and neuronal coding

When certain control parameters of nervous cell models are varied, complex bifurcation structures develop in which the dynamical behaviors available appear classified in blocks, according to criteria of dynamical likelihood. This block structured dynamics may be a clue to understand how activated neurons encode information by firing spike trains of their action potentials.

Impacts of different thinning regimes in the yield of uneven-structured Scots pine stands on drained peatland

Abstract

Structured running program for health and performance promotion in hospital employees.

Introduction Our institution (University hospital) is encouraging physical activities for health through various popular sporting events in the city of Lausanne, the biggest of which is a road race of 2, 4, 10 and 20km. Objective To create an efficient and sustainable training program in preparation of the race for a group of motivated hospital employees without any prior experience with structured training and to identifying the benefits and limitations encountered.. Methods Subjects of various fitness levels were recruited by add and agreed to undergo lab and field testing before a 12-week 3 times/week running program, based on maximal aerobic speed (MAS-30/30 sec intervals), running technique exercises and endurance training. The interval session was the only one supervised. Their goal was the 10km (11 subjects) and the 20km (6 subjects). Results A group of 17 subjects (7 male and 10 female), mean age 36.6±7.3 years, VO2max 44.0±5.5 ml/kg/min, filed test interval MAS 15.1±2.4 km/h started the program. 2 were lost because of injury (while skiing). Adherence to interval sessions was excellent, although 3 weekly training sessions proved to be difficult for most of the subjects. Performance in the race was satisfying for all of them, 6/7 subjects having improved their running time from the previous year, the others participated for the first time and 7/8 completed the race satisfyingly, one DNF-ed because of sinusitis. Repeat MAS field test was available for 6 subjects, who improved by 5.9% (p<0.01). Subjectively, all of the participants were very satisfied with improvement, interaction with colleagues from various professions, and with self achievement and confidence. Conclusions Implementation of a structured training program for recreational or non-athletes can be very successful in creating a better self-confidence, a better working environment inside a hospital facility and obviously in improvement of physical fitness and athletic performance. Above all, it can only encourage health institutions to promote the health of their own employees through physical activity, which can allow people to connect through sports. As a result, subjects in this study tend to encourage other employees to be more active and are hungry for more advice and continued offers for physical activities benefiting both them and the institution through better efficiency at work and less absenteeism common to more active people.

Involvement of family physicians in structured programs for chronic diseases or multi-morbidity in Switzerland.

The increasing prevalence of chronic diseases and multi-morbidity represents challenges for health systems worldwide. In that perspective, the current organization of healthcare delivery, fragmentation of care, limited use of evidence-based guidelines and patients'insufficient empowerment are some reasons explaining the current limited effectiveness of the management of chronically ill patients. Based on theoretical models such as the Chronic Care Model (CCM), initiatives targeting improvements in the care of patients with chronic diseases have been implemented worldwide since more than a decade. Their development in Switzerland, a health system where more than half of practices are still single handed [6], is only recent and infrequent. Structured programs for patients with chronic diseases or multimorbidity usually propose patient-centered interventions and consider an integrative multidisciplinary approach. Currently, little is known on the existence of such programs and on the role of family physicians (FPs)within these programs, in Switzerland. The objective of this study was to identify and describe current structured programs targeting chronic diseases or multi-morbidity in Switzerland. This may help in examining innovative approaches that are only developed locally but would deserve wider interest for further implementation. We conducted a telephone-based survey between June and November 2013 and contacted systematically key institutions, informants and stakeholders nationwide and in the 26 cantons...

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

The impact of balancing on problem hardness in a highly structured domain

Random problem distributions have played a key role in the study and design of algorithms for constraint satisfaction and Boolean satisfiability, as well as in ourunderstanding of problem hardness, beyond standard worst-case complexity. We consider random problem distributions from a highly structured problem domain that generalizes the Quasigroup Completion problem (QCP) and Quasigroup with Holes (QWH), a widely used domain that captures the structure underlying a range of real-world applications. Our problem domain is also a generalization of the well-known Sudoku puz- zle: we consider Sudoku instances of arbitrary order, with the additional generalization that the block regions can have rectangular shape, in addition to the standard square shape. We evaluate the computational hardness of Generalized Sudoku instances, for different parameter settings. Our experimental hardness results show that we can generate instances that are considerably harder than QCP/QWH instances of the same size. More interestingly, we show the impact of different balancing strategies on problem hardness. We also provide insights into backbone variables in Generalized Sudoku instances and how they correlate to problem hardness.

Measurement of a Structured Backflow in an Open Small Channel Induced by Surface-Tension Gradients

We present experiments in which the laterally confined flow of a surfactant film driven by controlled surface tension gradients causes the subtended liquid layer to self-organize into an inner upstream microduct surrounded by the downstream flow. The anomalous interfacial flow profiles and the concomitant backflow are a result of the feedback between two-dimensional and three-dimensional microfluidics realized during flow in open microchannels. Bulk and surface particle image velocimetry data combined with an interfacial hydrodynamics model explain the dependence of the observed phenomena on channel geometry.

Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI.

We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in the field perform the reconstruction on a voxel-by-voxel level, promoting sparsity of the orientation distribution. Recent methods have proposed a global denoising of the diffusion data using spatial information prior to reconstruction, while others promote spatial regularisation through an additional empirical prior on the diffusion image at each q-space point. Our approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels. The method is shown, through both simulated and real data, to enable accurate FOD reconstruction from a much lower number of q-space samples than the state of the art, typically 15 samples, even for quite adverse noise conditions.

Evolutionary dynamics of collective action in spatially structured populations.

Many models proposed to study the evolution of collective action rely on a formalism that represents social interactions as n-player games between individuals adopting discrete actions such as cooperate and defect. Despite the importance of spatial structure in biological collective action, the analysis of n-player games games in spatially structured populations has so far proved elusive. We address this problem by considering mixed strategies and by integrating discrete-action n-player games into the direct fitness approach of social evolution theory. This allows to conveniently identify convergence stable strategies and to capture the effect of population structure by a single structure coefficient, namely, the pairwise (scaled) relatedness among interacting individuals. As an application, we use our mathematical framework to investigate collective action problems associated with the provision of three different kinds of collective goods, paradigmatic of a vast array of helping traits in nature: "public goods" (both providers and shirkers can use the good, e.g., alarm calls), "club goods" (only providers can use the good, e.g., participation in collective hunting), and "charity goods" (only shirkers can use the good, e.g., altruistic sacrifice). We show that relatedness promotes the evolution of collective action in different ways depending on the kind of collective good and its economies of scale. Our findings highlight the importance of explicitly accounting for relatedness, the kind of collective good, and the economies of scale in theoretical and empirical studies of the evolution of collective action.

Structured sparsity through reweighting and application to diffusion MRI

We consider the problem of multiple correlated sparse signals reconstruction and propose a new implementation of structured sparsity through a reweighting scheme. We present a particular application for diffusion Magnetic Resonance Imaging data and show how this procedure can be used for fibre orientation reconstruction in the white matter of the brain. In that framework, our structured sparsity prior can be used to exploit the fundamental coherence between fibre directions in neighbour voxels. Our method approaches the ℓ0 minimisation through a reweighted ℓ1-minimisation scheme. The weights are here defined in such a way to promote correlated sparsity between neighbour signals.