Stress relief as the driving force for self-assembled Bi nanolines

Stress resulting from mismatch between a substrate and an adsorbed material has often been thought to be the driving force for the self-assembly of nanoscale structures. Bi nanolines self-assemble on Si(001), and are remarkable for their straightness and length -- they are often more than 400 nm long, and a kink in a nanoline has never been observed. Through electronic structure calculations, we have found an energetically favourable structure for these nanolines that agrees with our scanning tunneling microscopy and photoemission experiments; the structure has an extremely unusual subsurface structure, comprising a double core of 7-membered rings of silicon. Our proposed structure explains all the observed features of the nanolines, and shows that surface stress resulting from the mismatch between the Bi and the Si substrate are responsible for their self-assembly. This has wider implications for the controlled growth of nanostructures on semiconductor surfaces.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Let

Pseudo spin-orbit coupling of Dirac particles in graphene spintronics

We study the pseudo spin-orbital (SO) effects experienced by massive Dirac particles in graphene, which can potentially be of a larger magnitude compared to the conventional Rashba SO effects experienced by particles in a 2DEG semiconductor heterostructure. In order to generate a uniform vertical pseudo SO field, we propose an artificial atomic structure, consisting of a graphene ring and a charged nanodot at the center which produces a large radial electric field. In this structure, a large pseudo SO coupling strength can be achieved by accelerating the Dirac particles around the ring, due to the small energy gap in graphene and the large radial electric field emanating from the charged nanodot. We discuss the theoretical possibility of harnessing the pseudo SO effects in mesoscopic applications, e.g. pseudo spin relaxation and switching.Comment: 12 pages, 1 figur

Inverse Ising inference using all the data

We show that a method based on logistic regression, using all the data, solves the inverse Ising problem far better than mean-field calculations relying only on sample pairwise correlation functions, while still computationally feasible for hundreds of nodes. The largest improvement in reconstruction occurs for strong interactions. Using two examples, a diluted Sherrington-Kirkpatrick model and a two-dimensional lattice, we also show that interaction topologies can be recovered from few samples with good accuracy and that the use of $l_1$-regularization is beneficial in this process, pushing inference abilities further into low-temperature regimes.Comment: 5 pages, 2 figures. Accepted versio

Deep ocean disposal of sewage sludge off Orange County, California: a research plan

Even though the discharge of sludge into the ocean via an outfall is not now permitted, this research plan has been prepared to show what could be learned with a full scale experimental sludge discharge of 150 dry tons/day by the County Sanitation Districts of Orange County into deep water (over 1000 feet). To provide a wide range of inputs and evaluation, a broad-based Research Planning Committee was established to advise the Environmental Quality Laboratory on the overall content and details of the research plan. Two meetings were held at EQL on: March 4-5, 1982: The entire Committee July 19-20, 1982: A working subgroup of the Committee The entire Committee is listed in Appendix B, with footnotes to indicate meeting attendance. Those unable to come to a meeting were asked to comment on the drafts by mail or telephone. We gratefully acknowledge the members of the Research Planning Committee for their generous help in formulating the research tasks and reviewing report drafts

Comparing the Efficacy of Drug Regimens for Pulmonary Tuberculosis: Meta-analysis of Endpoints in Early-Phase Clinical Trials

Background A systematic review of early clinical outcomes in tuberculosis was undertaken to determine ranking of efficacy of drugs and combinations, define variability of these measures on different endpoints, and to establish the relationships between them. Methods Studies were identified by searching PubMed, Medline, Embase, LILACS (Latin American and Caribbean Health Sciences Literature), and reference lists of included studies. Outcomes were early bactericidal activity results over 2, 7, and 14 days, and the proportion of patients with negative culture at 8 weeks. Results One hundred thirty-three trials reporting phase 2A (early bactericidal activity) and phase 2B (culture conversion at 2 months) outcomes were identified. Only 9 drug combinations were assessed on >1 phase 2A endpoint and only 3 were assessed in both phase 2A and 2B trials. Conclusions The existing evidence base supporting phase 2 methodology in tuberculosis is highly incomplete. In future, a broader range of drugs and combinations should be more consistently studied across a greater range of phase 2 endpoints

The role of type 4 phosphodiesterases in generating microdomains of cAMP: Large scale stochastic simulations

Cyclic AMP (cAMP) and its main effector Protein Kinase A (PKA) are critical for several aspects of neuronal function including synaptic plasticity. Specificity of synaptic plasticity requires that cAMP activates PKA in a highly localized manner despite the speed with which cAMP diffuses. Two mechanisms have been proposed to produce localized elevations in cAMP, known as microdomains: impeded diffusion, and high phosphodiesterase (PDE) activity. This paper investigates the mechanism of localized cAMP signaling using a computational model of the biochemical network in the HEK293 cell, which is a subset of pathways involved in PKA-dependent synaptic plasticity. This biochemical network includes cAMP production, PKA activation, and cAMP degradation by PDE activity. The model is implemented in NeuroRD: novel, computationally efficient, stochastic reaction-diffusion software, and is constrained by intracellular cAMP dynamics that were determined experimentally by real-time imaging using an Epac-based FRET sensor (H30). The model reproduces the high concentration cAMP microdomain in the submembrane region, distinct from the lower concentration of cAMP in the cytosol. Simulations further demonstrate that generation of the cAMP microdomain requires a pool of PDE4D anchored in the cytosol and also requires PKA-mediated phosphorylation of PDE4D which increases its activity. The microdomain does not require impeded diffusion of cAMP, confirming that barriers are not required for microdomains. The simulations reported here further demonstrate the utility of the new stochastic reaction-diffusion algorithm for exploring signaling pathways in spatially complex structures such as neurons