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An evidence game is a strategic disclosure game in which an informed agent who has some pieces of verifiable evidence decides which ones to disclose to an uninformed principal who chooses a reward. The agent, regardless of his information, prefers the reward to be as high as possible. We compare the setup in which the principal chooses the reward after the evidence is disclosed to the mechanism-design setup where he can commit in advance to a reward policy, and show that under natural conditions related to the evidence structure and the inherent prominence of truth, the two setups yield the same outcome.

Unicellular living organisms, such as bacteria and algae, propel themselves through a medium via cyclic strokes involving the motion of cilia and flagella. Dense populations of such \"active particles\" or \"swimmers\" exhibit a rich collective behavior at large scales. Starting with a minimal physical model of a stroke-averaged swimmer in a fluid, we derive a continuum description of a suspension of active organisms that incorporates fluid-mediated, long-range hydrodynamic interactions among the swimmers. Our work demonstrates that hydrodynamic interactions provide a simple, generic origin for several nonequilibrium phenomena predicted or observed in the literature. The continuum model derived here does not depend on the microscopic physical model of the individual swimmer. The details of the large-scale physics do, however, differ for \"shakers\" (particles that are active but not self-propelled, such as melanocytes) and \"movers\" (self-propelled particles), \"pushers\" (most bacteria) and \"pullers\" (algae like Chlamydomonas). Our work provides a classification of the large-scale behavior of all these systems.

Significance The cerebral cortex can be divided into a number of distinct areas on the basis of anatomy and function. Understanding the complex pattern of connections among these areas is essential to uncovering how the brain performs its distributed computations. We report a systematic relation between the connectivity and functional similarity of cortical areas in the monkey, human, and mouse cortex. Motivated by observations that the cortical areal network is densely connected and that connections have a strong dependence on wiring length, we introduce a spatially embedded, generative model of the areal network that accounts for many observed features of cortical connectivity. Recent anatomical tracing studies have yielded substantial amounts of data on the areal connectivity underlying distributed processing in cortex, yet the fundamental principles that govern the large-scale organization of cortex remain unknown. Here we show that functional similarity between areas as defined by the pattern of shared inputs or outputs is a key to understanding the areal network of cortex. In particular, we report a systematic relation in the monkey, human, and mouse cortex between the occurrence of connections from one area to another and their similarity distance. This characteristic relation is rooted in the wiring distance dependence of connections in the brain. We introduce a weighted, spatially embedded random network model that robustly gives rise to this structure, as well as many other spatial and topological properties observed in cortex. These include features that were not accounted for in any previous model, such as the wide range of interareal connection weights. Connections in the model emerge from an underlying distribution of spatially embedded axons, thereby integrating the two scales of cortical connectivity—individual axons and interareal pathways—into a common geometric framework. These results provide insights into the origin of large-scale connectivity in cortex and have important implications for theories of cortical organization.

We report here a series of four- and five-coordinate Fe model complexes that feature an axial tri(silyl)methyl ligand positioned trans to a substrate-binding site. This arrangement is used to crudely model a single-belt Fe site of the FeMo-cofactor that might bind N ₂ at a position trans to the interstitial C atom. Reduction of a trigonal pyramidal Fe(I) complex leads to uptake of N ₂ and subsequent functionalization furnishes an open-shell Fe–diazenido complex. A related series of five-coordinate Fe–CO complexes stable across three redox states is also described. Spectroscopic, crystallographic, and Density Functional Theory (DFT) studies of these complexes suggest that a decrease in the covalency of the Fe–C ₐₗₖyₗ interaction occurs upon reduction and substrate binding. This leads to unusually long Fe–C ₐₗₖyₗ bond distances that reflect an ionic Fe–C bond. The data presented are contextualized in support of a hypothesis wherein modulation of a belt Fe–C interaction in the FeMo-cofactor facilitates substrate binding and reduction.

Densely packed and twisted assemblies of filaments are crucial structural motifs in macroscopic materials (cables, ropes, and textiles) as well as synthetic and biological nanomaterials (fibrous proteins). We study the unique and nontrivial packing geometry of this universal material design from two perspectives. First, we show that the problem of twisted bundle packing can be mapped exactly onto the problem of disc packing on a curved surface, the geometry of which has a positive, spherical curvature close to the center of rotation and approaches the intrinsically flat geometry of a cylinder far from the bundle center. From this mapping, we find the packing of any twisted bundle is geometrically frustrated, as it makes the sixfold geometry of filament close packing impossible at the core of the fiber. This geometrical equivalence leads to a spectrum of close-packed fiber geometries, whose low symmetry (five-, four-, three-, and twofold) reflect non-Euclidean packing constraints at the bundle core. Second, we explore the ground-state structure of twisted filament assemblies formed under the influence of adhesive interactions by a computational model. Here, we find that the underlying non-Euclidean geometry of twisted fiber packing disrupts the regular lattice packing of filaments above a critical radius, proportional to the helical pitch. Above this critical radius, the ground-state packing includes the presence of between one and six excess fivefold disclinations in the cross-sectional order.

The plasmon resonances of a concentric metallic nanoshell arise from the hybridization of primitive plasmon modes of the same angular momentum on its inner and outer surfaces. For a nanoshell with an offset core, the reduction in symmetry relaxes these selection rules, allowing for an admixture of dipolar components in all plasmon modes of the particle. This metallodielectric nanostructure with reduced symmetry exhibits a core offset-dependent multipeaked spectrum, seen in single-particle spectroscopic measurements, and exhibits significantly larger local-field enhancements on its external surface than the equivalent concentric spherical nanostructure.

A series of aluminum salen-type complexes [where salen is N,N'-bis(salicylaldimine)-1,2-ethylenediamine] bearing ligands that differ in their steric and electronic properties have been synthesized and investigated for the polymerization of rac-lactide. X-ray crystal structures on key precatalysts reveal metal coordination geometries intermediate between trigonal bipyramidal and square-based pyramidal. Both the phenoxy substituents and the backbone linker have a significant influence over the polymerization. Electronwithdrawing groups attached to the phenoxy donor generally gave an increased polymerization rate, whereas large ortho substituents generally slowed down the polymerization. The vast majority of the initiators afforded polylactide with an isotactic bias; only one exhibited a bias toward heteroselectivity. Isoselectivity generally increases with increased flexibility of the backbone linker, which is presumed to be better able to accommodate any potential steric clashes between the propagating polymer chain, the inserting monomer unit, and the substituents on the phenoxy donor.

The National Institutes of Health Mammalian Gene Collection (MGC) Program is a multiinstitutional effort to identify and sequence a cDNA clone containing a complete ORF for each human and mouse gene. ESTs were generated from libraries enriched for full-length cDNAs and analyzed to identify candidate full-ORF clones, which then were sequenced to high accuracy. The MGC has currently sequenced and verified the full ORF for a nonredundant set of >9,000 human and >6,000 mouse genes. Candidate full-ORF clones for an additional 7,800 human and 3,500 mouse genes also have been identified. All MGC sequences and clones are available without restriction through public databases and clone distribution networks (see http://mgc.nci.nih.gov).

In dealing with a dynamic world, people have the ability to maintain selective attention on a subset of moving objects in the environment. Performance in such multiple-object tracking is limited by three primary factors— the number of objects that one can track, the speed at which one can track them, and how close together they can be. We argue that this last limit, of object spacing, is the root cause of all performance constraints in multiple-object tracking. In two experiments, we found that as long as the distribution of object spacing is held constant, tracking performance is unaffected by large changes in object speed and tracking time. These results suggest that barring object-spacing constraints, people could reliably track an unlimited number of objects as fast as they could track a single object.

Molecular analyses of hair follicle formation provide evidence to support the most well-known mathematical model for biological pattern formation. Researchers propose that spatial patterns result from a phenomenon termed \"diffusion-driven instability.\"