Ternary nucleation of H_2SO_4, NH_3 and H_2O

A classical theory of the ternary homogeneous nucleation of sulfuric acid—ammonia—water is presented. For NH3 mixing ratios exceeding 1 ppt, the presence of ammonia enhances the binary (sulfuric acid—water) nucleation rate by several orders of magnitude. However, the limiting component for ternary nucleation—as for binary nucleation—is sulfuric acid. The sulfuric acid concentration needed for significant ternary nucleation is several orders of magnitude below that required in binary case

Shaping public opinion about regional integration: the rhetoric of justification and party cues

The article investigates how justifications used by politicians to explain their positions on policies of regional integration shape public opinion about these policies. I argue that support for a policy position increases when politicians tailor their justifications to the expectations of their audience; and I suggest that this happens even when party cues offer a less effortful way of forming opinions. I test my theoretical expectations in laboratory experiments with diverse samples, which manipulate party cues and justifications for a policy of European integration. I find that citizens use justifications and cues to form opinions. The relative importance of the two factors depends on individual dispositions and political context. In a non-competitive context (study 1), politically invested citizens use cues, while uninvested citizens use justifications. In a competitive context (study 2), the opinions of politically invested citizens are shaped by both factors, while the opinions of uninvested citizens become erratic

Automatic Control System for Dispensing Precise Amounts of FInely Divided Solids

A device for automatic dispensing of precise amounts of finely divided solids has been developed. Precision is a function of dispensing time. Smaller than gram quantities may be dispensed at a rate of about 1/3 g/min with a precision corresponding to a weight range of about 0.001 g for a series. The process consists in moving the material with the effect of the vibratory motion of a miniature air-powered vibrator. Operation is automatically controlled by the electronic system of the weighing unit interfaced to the pneumatic dispensing device via a combination fluidic and pneumatic control system

New approaches to model and study social networks

We describe and develop three recent novelties in network research which are particularly useful for studying social systems. The first one concerns the discovery of some basic dynamical laws that enable the emergence of the fundamental features observed in social networks, namely the nontrivial clustering properties, the existence of positive degree correlations and the subdivision into communities. To reproduce all these features we describe a simple model of mobile colliding agents, whose collisions define the connections between the agents which are the nodes in the underlying network, and develop some analytical considerations. The second point addresses the particular feature of clustering and its relationship with global network measures, namely with the distribution of the size of cycles in the network. Since in social bipartite networks it is not possible to measure the clustering from standard procedures, we propose an alternative clustering coefficient that can be used to extract an improved normalized cycle distribution in any network. Finally, the third point addresses dynamical processes occurring on networks, namely when studying the propagation of information in them. In particular, we focus on the particular features of gossip propagation which impose some restrictions in the propagation rules. To this end we introduce a quantity, the spread factor, which measures the average maximal fraction of nearest neighbors which get in contact with the gossip, and find the striking result that there is an optimal non-trivial number of friends for which the spread factor is minimized, decreasing the danger of being gossiped.Comment: 16 Pages, 9 figure

Tensile Fracture of Welded Polymer Interfaces: Miscibility, Entanglements and Crazing

Large-scale molecular simulations are performed to investigate tensile failure of polymer interfaces as a function of welding time $t$. Changes in the tensile stress, mode of failure and interfacial fracture energy $G_I$ are correlated to changes in the interfacial entanglements as determined from Primitive Path Analysis. Bulk polymers fail through craze formation, followed by craze breakdown through chain scission. At small $t$ welded interfaces are not strong enough to support craze formation and fail at small strains through chain pullout at the interface. Once chains have formed an average of about one entanglement across the interface, a stable craze is formed throughout the sample. The failure stress of the craze rises with welding time and the mode of craze breakdown changes from chain pullout to chain scission as the interface approaches bulk strength. The interfacial fracture energy $G_I$ is calculated by coupling the simulation results to a continuum fracture mechanics model. As in experiment, $G_I$ increases as $t^{1/2}$ before saturating at the average bulk fracture energy $G_b$. As in previous simulations of shear strength, saturation coincides with the recovery of the bulk entanglement density. Before saturation, $G_I$ is proportional to the areal density of interfacial entanglements. Immiscibiltiy limits interdiffusion and thus suppresses entanglements at the interface. Even small degrees of immisciblity reduce interfacial entanglements enough that failure occurs by chain pullout and $G_I \ll G_b$

Fitness benefits of prolonged post-reproductive lifespan in women

Most animals reproduce until they die, but in humans, females can survive long after ceasing reproduction. In theory, a prolonged post-reproductive lifespan will evolve when females can gain greater fitness by increasing the success of their offspring than by continuing to breed themselves. Although reproductive success is known to decline in old age, it is unknown whether women gain fitness by prolonging lifespan post-reproduction. Using complete multi-generational demographic records, we show that women with a prolonged post-reproductive lifespan have more grandchildren, and hence greater fitness, in pre-modern populations of both Finns and Canadians. This fitness benefit arises because post-reproductive mothers enhance the lifetime reproductive success of their offspring by allowing them to breed earlier, more frequently and more successfully. Finally, the fitness benefits of prolonged lifespan diminish as the reproductive output of offspring declines. This suggests that in female humans, selection for deferred ageing should wane when one's own offspring become post-reproductive and, correspondingly, we show that rates of female mortality accelerate as their offspring terminate reproduction

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models

The Pattern Speeds of M51, M83 and NGC 6946 Using CO and the Tremaine-Weinberg Method

In spiral galaxies where the molecular phase dominates the ISM, the molecular gas as traced by CO emission will approximately obey the continuity equation on orbital timescales. The Tremaine-Weinberg method can then be used to determine the pattern speed of such galaxies. We have applied the method to single-dish CO maps of three nearby spirals, M51, M83 and NGC 6946 to obtain estimates of their pattern speeds: 38 +/- 7 km/s/kpc, 45 +/- 8 km/s/kpc and 39 +/- 8 km/s/kpc, respectively, and we compare these results to previous measurements. We also analyze the major sources of systematic errors in applying the Tremaine-Weinberg method to maps of CO emission.Comment: 33 pages, figures already in pdf. To appear in 2004 ApJ 607 28

Toward an integrative understanding of social behavior: new models and new opportunities.

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur

Topology and Computational Performance of Attractor Neural Networks

To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world and scale-free topologies. The random net is the most efficient for storage and retrieval of patterns by the entire network. However, in the scale-free case retrieval errors are not distributed uniformly: the portion of a pattern encoded by the subset of highly connected nodes is more robust and efficiently recognized than the rest of the pattern. The scale-free network thus achieves a very strong partial recognition. Implications for brain function and social dynamics are suggestive.Comment: 2 figures included. Submitted to Phys. Rev. Letter