Occupency, Detection, and Co-Occurence Rates of American Black and Mallard Ducks in the Saranac Lakes Wild Forest Area

American black duck populations have steadily decreased across the northeastern United States prompting researchers to examine causes of decline including habitat loss, hybridization with mallards, and competitive exclusion by mallards. We designed a survey of lakes and wetlands of the Saranac Lakes Wild Forest and estimated occupancy and detection rates for each species. Given the predominantly forested landscape and the low density of humans, we predicted American black ducks would have greater occupancy rates than Mallards. Our results show each species was approximately equally likely to occur and to be detected, and there was no evidence that mallards excluded American black ducks from habitats. Mallards did show greater affinity for habitats with more humans present compared to American black ducks. Less than half of the lakes and wetlands we surveyed were occupied by either species indicating there is an abundance of unoccupied habitats that could have population-level ramifications for both species

Polyethylene imine-based receptor immobilization for label free bioassays

Polyethylene imine (PEI) based immobilization of antibodies is described and the concept is proved on the label free assay of C-Reactive Protein (CRP). This novel immobilization method is composed of a hyperbranched PEI layer which was deposited at a high pH (9.5) on the sensor surface. The free amino groups of PEI were derivatized with neutravidin by Biotin N-hydroxysuccinimide ester and the biotinylated anti-CRP antibody immobilized on this layer. Direct binding assay of recombinant CRP was successfully performed in the low μg/ml concentrations using a label free optical waveguide biosensor

Game Theoretical Interactions of Moving Agents

Game theory has been one of the most successful quantitative concepts to describe social interactions, their strategical aspects, and outcomes. Among the payoff matrix quantifying the result of a social interaction, the interaction conditions have been varied, such as the number of repeated interactions, the number of interaction partners, the possibility to punish defective behavior etc. While an extension to spatial interactions has been considered early on such as in the "game of life", recent studies have focussed on effects of the structure of social interaction networks. However, the possibility of individuals to move and, thereby, evade areas with a high level of defection, and to seek areas with a high level of cooperation, has not been fully explored so far. This contribution presents a model combining game theoretical interactions with success-driven motion in space, and studies the consequences that this may have for the degree of cooperation and the spatio-temporal dynamics in the population. It is demonstrated that the combination of game theoretical interactions with motion gives rise to many self-organized behavioral patterns on an aggregate level, which can explain a variety of empirically observed social behaviors

The Rationality of Prejudices

We model an -player repeated prisoner's dilemma in which players are given traits (e.g., height, age, wealth) which, we assume, affect their behavior. The relationship between traits and behavior is unknown to other players. We then analyze the performance of “prejudiced” strategies—strategies that draw inferences based on the observation of some or all of these traits, and extrapolate the inferred behavior to other carriers of these traits. Such prejudiced strategies have the advantage of learning rapidly, and hence of being well adapted to rapidly changing conditions that might result, for example, from high migration or birth rates. We find that they perform remarkably well, and even systematically outperform both Tit-For-Tat and ALLD when the population changes rapidly

Learning and innovative elements of strategy adoption rules expand cooperative network topologies

Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoners Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems.Comment: 14 pages, 3 Figures + a Supplementary Material with 25 pages, 3 Tables, 12 Figures and 116 reference

A systematic review on health resilience to economic crises

Background The health effects of recent economic crises differ markedly by population group. The objective of this systematic review is to examine evidence from longitudinal studies on factors influencing resilience for any health outcome or health behaviour among the general population living in countries exposed to financial crises. Methods We systematically reviewed studies from six electronic databases (EMBASE, Global Health, MEDLINE, PsycINFO, Scopus, Web of Science) which used quantitative longitudinal study designs and included: (i) exposure to an economic crisis; (ii) changes in health outcomes/behaviours over time; (iii) statistical tests of associations of health risk and/or protective factors with health outcomes/behaviours. The quality of the selected studies was appraised using the Quality Assessment Tool for Quantitative Studies. PRISMA reporting guidelines were followed. Results From 14,584 retrieved records, 22 studies met the eligibility criteria. These studies were conducted across 10 countries in Asia, Europe and North America over the past two decades. Ten socio-demographic factors that increased or protected against health risk were identified: gender, age, education, marital status, household size, employment/occupation, income/ financial constraints, personal beliefs, health status, area of residence, and social relations. These studies addressed physical health, mortality, suicide and suicide attempts, mental health, and health behaviours. Women’s mental health appeared more susceptible to crises than men’s. Lower income levels were associated with greater increases in cardiovascular disease, mortality and worse mental health. Employment status was associated with changes in mental health. Associations with age, marital status, and education were less consistent, although higher education was associated with healthier behaviours. Conclusions Despite widespread rhetoric about the importance of resilience, there was a dearth of studies which operationalised resilience factors. Future conceptual and empirical research is needed to develop the epidemiology of resilience

Association Between Increased Platelet P-Selectin Expression and Obesity in Patients With Type 2 Diabetes: A BARI 2D (Bypass Angioplasty Revascularization Investigation 2 Diabetes) substudy

OBJECTIVE- To determine whether obesity increases platelet reactivity and thrombin activity in patients with type 2 diabetes plus stable coronary artery disease. RESEARCH DESIGN AND METHODS- We assessed platelet reactivity and markers of thrombin generation and activity in 193 patients from nine clinical sites of the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D). Blood taken at the time of enrollment was used for assay of the concentration of prothrombin fragment 1.2 (PT1.2, released when prothrombin is activated) and fibrinopeptide A (FPA, released when fibrinogen is cleaved). Platelet activation was identified with the use of flow cytometry in response to 0, 0.2, and 1 mu mol/l adenosine diphosphate (ADP). RESULTS- Concentrations of FPA, PT1.2, and platelet activation in the absence of agonist were low. Greater BMI was associated with higher platelet reactivity in response to 1 mu m ADP as assessed by surface expression of P-selectin (r = 0.29, P < 0.0001) but not reflected by the binding of fibrinogen to activated glycoprotein IIb-IIIa. BMI was not associated with concentrations of FPA or PT1.2. Platelet reactivity correlated negatively with A1C (P < 0.04), was not related to the concentration Of triglycerides in blood, and did not correlate with the concentration of C-reactive peptide. CONCLUSIONS- Among patients enrolled in this substudy of BARI 2D, a greater BMI was associated with higher platelet reactivity at the time of enrollment. Our results suggest that obesity and insulin resistance that accompanies obesity may influence platelet reactivity in patients with type 2 diabetes.National Heart, Lung, and Blood Institute (NHLBI/NIH)[R01 HL69146]National Heart, Lung, and Blood Institute (NHLBI/NIH)[R01 HL71306]NHLBI[U01 HL061746]NHLBI[U01 HL06171748]NHLBI[U01 HL06384]National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK/NIH)[HL061744

Spatial interactions in agent-based modeling

Agent Based Modeling (ABM) has become a widespread approach to model complex interactions. In this chapter after briefly summarizing some features of ABM the different approaches in modeling spatial interactions are discussed. It is stressed that agents can interact either indirectly through a shared environment and/or directly with each other. In such an approach, higher-order variables such as commodity prices, population dynamics or even institutions, are not exogenously specified but instead are seen as the results of interactions. It is highlighted in the chapter that the understanding of patterns emerging from such spatial interaction between agents is a key problem as much as their description through analytical or simulation means. The chapter reviews different approaches for modeling agents' behavior, taking into account either explicit spatial (lattice based) structures or networks. Some emphasis is placed on recent ABM as applied to the description of the dynamics of the geographical distribution of economic activities, - out of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with spatial structure, is used to illustrate the potential of such an approach for spatial policy analysis.Comment: 26 pages, 5 figures, 105 references; a chapter prepared for the book "Complexity and Geographical Economics - Topics and Tools", P. Commendatore, S.S. Kayam and I. Kubin, Eds. (Springer, in press, 2014