Competition-related factors directly influence preferences for facial cues of dominance in allies

Alliance formation is a critical dimension of social intelligence in political, social and biological systems. As some allies may provide greater ‘leverage’ than others during social conflict, the cognitive architecture that supports alliance formation in humans may be shaped by recent experience, for example in light of the outcomes of violent or non-violent forms intrasexual competition. Here we used experimental priming techniques to explore this issue. Consistent with our predictions, while men’s preference for dominant allies strengthened following losses (compared to victories) in violent intrasexual contests, women’s preferences for dominant allies weakened following losses (compared to victories) in violent intrasexual contests. Our findings suggest that while men may prefer dominant (i.e. masculine) allies following losses in violent confrontation in order to facilitate successful resource competition, women may ‘tend and befriend’ following this scenario and seek support from prosocial (i.e. feminine) allies and/or avoid the potential costs of dominant allies as long-term social partners. Moreover, they demonstrate facultative responses to signals related to dominance in allies, which may shape sex differences in sociality in light of recent experience and suggest that intrasexual selection has shaped social intelligence in humans

World crude oil resources : evidence from estimating supply functions for 41 countries

Evidence to support or deny expectations of future scarcity or abundance of crude oil must show whether crude oil supply functions are shifting and, if so, in what direction. The authors estimate oil supply functions for 41 countries for which suitable data are available. Because of the poor quality of data, especially for reserves, the model specification is simple. Their model relates reserve additions to the imputed"in situ"price of discovered but undeveloped reserves and to the passage of time. The passage of time is a surrogate for measuring the net impact on supply conditions of the chance of finding oil, resource depletion, cost efficiency, and technology. Time's impact could be expansionary or contractionary. They test two main versions of the model, one a straightforward linear function, the other nonlinear, assuming decreasing returns. Both models yield similar results. In most cases the models fit the data reasonably closely, after adjustment for outliers. The complete model results show 26 countries with statistically significant shifts in supply functions -in almost equal parts expansionary and contractionary. The shift is often contractionary in countries with a long production history (including Burma, Trinidad and Tobago, and the United States). Some are OPEC countries, to which a model specification involving market price response does not properly apply. Tests on a small sample of countries for differences between earlier and later periods reveal limited evidence of an expansionary shift from 1980 onward. There is partial evidence that lower oil prices stimulate productivity. The authors suggest that a gloomy outlook for non-OPEC supply is unwarranted. Several countries are still in an expansionary phase. Others show no evidence of entering a period of decline. And countries in a contractionary phase will continue to add to reserves. Further research requires improving the database rather than employing more elaborate models.Labor Policies,Economic Theory&Research,Environmental Economics&Policies,Markets and Market Access,Health Economics&Finance,Economic Theory&Research,Environmental Economics&Policies,Access to Markets,Markets and Market Access,Oil Refining&Gas Industry

The Alternating Surface Segmented Lap Joint: a Design for Thin Highly Loaded Joints

The combination of thin airfoil sections and high aerodynamic loads on many wind tunnel models presents a major problem for attachment of flap elements. Conventional methods of attaching fixed control elements such as lap and tongue-in-groove joints are not rigid enough to provide surface continuity required in high Reynolds number research. For the extreme cases, the solution has been to fabricate separate wings for each flap setting with the flap element being and integral part of the wing. Here an attractive solution to this problem, the alternating surface segmented lap joint, is discussed. This joint provides increased rigidity and lower stress levels than conventional joints. Additionally, attachment fastener loading is low and the joint can be designed to accommodate high shear levels due to bending without the use of dowel pins

An agent-based model of jaguar movement through conservation corridors

Wildlife corridors mitigate against habitat fragmentation by connecting otherwise isolated regions, bringing well established benefits to conservation both in principle and practice. Populations of large mammals in particular may depend on habitat connectivity, yet conservation managers struggle to optimise corridor designs with the rudimentary information generally available on movement behaviours. We present an agent-based model of jaguars (Panthera onca), scaled for fragmented habitat in Belize where proposals already exist for creating a jaguar corridor. We use a leastcost approach to simulate movement paths through alternative possible landscapes. Six different types of corridor and three control conditions differ substantially in their effectiveness at mixing agents across the environment despite relatively little difference in individual welfare. Our best estimates of jaguar movement behaviours suggest that a set of five narrow corridors may out-perform one wide corridor of the same overall area. We discuss the utility of ALife modelling for conservation management

Investigation of Low-temperature Solders for Cryogenic Wind Tunnel Models

The advent of high Reynolds number cryogenic wind tunnels has forced alteration of manufacturing and assembly techniques and eliminated usage of many materials associated with conventional wind tunnel models. One of the techniques affected is soldering. Solder alloys commonly used for wind tunnel models are susceptible to low-temperature embrittlement and phase transformation. The low-temperature performance of several solder alloys is being examined during research and development activities being conducted in support of design and fabrication of cryogenic wind tunnel models. Among the properties examined during these tests are shear strength, surface quality, joint stability, and durability when subjected to dynamic loading. Results of these tests and experiences with recent models are summarized

Pseudo-nonstationarity in the scaling exponents of finite-interval time series

The accurate estimation of scaling exponents is central in the observational study of scale-invariant phenomena. Natural systems unavoidably provide observations over restricted intervals; consequently, a stationary stochastic process (time series) can yield anomalous time variation in the scaling exponents, suggestive of nonstationarity. The variance in the estimates of scaling exponents computed from an interval of N observations is known for finite variance processes to vary as ~1/N as N for certain statistical estimators; however, the convergence to this behavior will depend on the details of the process, and may be slow. We study the variation in the scaling of second-order moments of the time-series increments with N for a variety of synthetic and “real world” time series, and we find that in particular for heavy tailed processes, for realizable N, one is far from this ~1/N limiting behavior. We propose a semiempirical estimate for the minimum N needed to make a meaningful estimate of the scaling exponents for model stochastic processes and compare these with some “real world” time series

Deep Ordinal Reinforcement Learning

Reinforcement learning usually makes use of numerical rewards, which have nice properties but also come with drawbacks and difficulties. Using rewards on an ordinal scale (ordinal rewards) is an alternative to numerical rewards that has received more attention in recent years. In this paper, a general approach to adapting reinforcement learning problems to the use of ordinal rewards is presented and motivated. We show how to convert common reinforcement learning algorithms to an ordinal variation by the example of Q-learning and introduce Ordinal Deep Q-Networks, which adapt deep reinforcement learning to ordinal rewards. Additionally, we run evaluations on problems provided by the OpenAI Gym framework, showing that our ordinal variants exhibit a performance that is comparable to the numerical variations for a number of problems. We also give first evidence that our ordinal variant is able to produce better results for problems with less engineered and simpler-to-design reward signals.Comment: replaced figures for better visibility, added github repository, more details about source of experimental results, updated target value calculation for standard and ordinal Deep Q-Networ