Photo-electrochemical Hydrogen Sulfide Splitting using SnIV-doped Hematite Photo-anodes

© 2016 The Authors. Published by Elsevier B.V.Spray-pyrolysed SnIV-doped α-Fe2O3 photo-anodes were used for photo-assisted splitting of HS- ions in alkaline aqueous solutions, producing polysulfide (Sn2 -) ions together with hydrogen at the cathode. Subsequent aerial oxidation of polysulfide could be used to produce elemental sulfur. At an applied electrode potential of 1.07 V (RHE) and an irradiance of 5.6 kW m- 2, stable photocurrents of ca. 11 A m- 2 (2 × 10- 3 A W- 1) were recorded over 75 h, polysulfide concentrations increasing linearly with time. Despite being predicted thermodynamically to form iron sulfide(s) in sulfide solutions, such photo-anodes appeared to be stable. In comparison with conventional water splitting under alkaline conditions, the coupled processes of hydrogen sulfide ion oxidation and water reduction had a lower energy requirement

History-sensitive versus future-sensitive approaches to security in distributed systems

We consider the use of aspect-oriented techniques as a flexible way to deal with security policies in distributed systems. Recent work suggests to use aspects for analysing the future behaviour of programs and to make access control decisions based on this; this gives the flavour of dealing with information flow rather than mere access control. We show in this paper that it is beneficial to augment this approach with history-based components as is the traditional approach in reference monitor-based approaches to mandatory access control. Our developments are performed in an aspect-oriented coordination language aiming to describe the Bell-LaPadula policy as elegantly as possible. Furthermore, the resulting language has the capability of combining both history- and future-sensitive policies, providing even more flexibility and power.Comment: In Proceedings ICE 2010, arXiv:1010.530

Serving GODAE Data and Products to the Ocean Community

The Global Ocean Data Assimilation Experiment (GODAE [http:// www.godae.org]) has spanned a decade of rapid technological development. The ever-increasing volume and diversity of oceanographic data produced by in situ instruments, remote-sensing platforms, and computer simulations have driven the development of a number of innovative technologies that are essential for connecting scientists with the data that they need. This paper gives an overview of the technologies that have been developed and applied in the course of GODAE, which now provide users of oceanographic data with the capability to discover, evaluate, visualize, download, and analyze data from all over the world. The key to this capability is the ability to reduce the inherent complexity of oceanographic data by providing a consistent, harmonized view of the various data products. The challenges of data serving have been addressed over the last 10 years through the cooperative skills and energies of many individuals

Temperament Factors and Dimensional, Latent Bifactor Models of child psychopathology: Transdiagnostic and Specific Associations in Two Youth Samples

Common emotional and behavioral symptoms co-occur and are associated with core temperament factors. This study investigated links between temperament and dimensional, latent psychopathology factors, including a general common psychopathology factor (p factor) and specific latent internalizing and externalizing liabilities, as captured by a bifactor model, in two independent samples of youth. Specifically, we tested the hypothesis that temperament factors of negative affectivity (NA), positive affectivity (PA), and effortful control (EC) could serve as both transdiagnostic and specific risks in relation to recent bifactor models of child psychopathology. Sample 1 included 571 youth (average age 13.6, SD = 2.37, range 9.3–17.5) with both youth and parent report. Sample 2 included 554 preadolescent children (average age 7.7, SD = 1.35, range = 5–11 years) with parent report. Structural equation modeling showed that the latent bifactor models fit in both samples. Replicated in both samples, the p factor was associated with lower EC and higher NA (transdiagnostic risks). Several specific risks replicated in both samples after controlling for co-occurring symptoms via the p factor: internalizing was associated with higher NA and lower PA, lower EC related to externalizing problems

Personalized Depression Prevention: A Randomized Controlled Trial to Optimize Effects Through Risk-Informed Personalization

Objective: To evaluate whether evidence-based depression prevention programs can be optimized by matching youths to interventions that address their psychosocial vulnerabilities. Method: This randomized controlled trial included 204 adolescents (mean [SD] age ¼ 14.26 [1.65] years; 56.4% female). Youths were categorized as high or low on cognitive and interpersonal risks for depression and randomly assigned to Coping With Stress (CWS), a cognitive-behavioral program, or Interpersonal Psychotherapy–Adolescent Skills Training (IPT-AST), an interpersonal program. Some participants received a match between risk and prevention (eg, high cognitive–low interpersonal risk teen in CWS, low cognitive–high interpersonal risk teen in IPT-AST), others received a mismatch (eg, low cognitive-high interpersonal risk teen in CWS). Outcomes were depression diagnoses and symptoms through 18 months postintervention (21 months total). Results: Matched adolescents showed significantly greater decreases in depressive symptoms than mismatched adolescents from postintervention through 18-month follow-up and across the entire 21-month study period (effect size [d] ¼ 0.44, 95% CI ¼ 0.02, 0.86). There was no significant difference in rates of depressive disorders among matched adolescents compared with mismatched adolescents (12.0% versus 18.3%, t193 ¼ .78, p ¼ .44). Conclusion: This study illustrates one approach to personalizing depression prevention as a form of precision mental health. Findings suggest that risk-informed personalization may enhance effects beyond a one-size-fits-all approach. Clinical trial registration information: Bending Adolescent Depression Trajectories Through Personalized Prevention; https://www.clinicaltrials. gov/; NCT01948167

Casimir micro-sphere diclusters and three-body effects in fluids

Our previous article [Phys. Rev. Lett. 104, 060401 (2010)] predicted that Casimir forces induced by the material-dispersion properties of certain dielectrics can give rise to stable configurations of objects. This phenomenon was illustrated via a dicluster configuration of non-touching objects consisting of two spheres immersed in a fluid and suspended against gravity above a plate. Here, we examine these predictions from the perspective of a practical experiment and consider the influence of non-additive, three-body, and nonzero-temperature effects on the stability of the two spheres. We conclude that the presence of Brownian motion reduces the set of experimentally realizable silicon/teflon spherical diclusters to those consisting of layered micro-spheres, such as the hollow- core (spherical shells) considered here.Comment: 11 pages, 9 figure

Efficient Numerical Frameworks for Multi-objective Cyber Security Planning

We consider the problem of optimal investment in cyber-security by an enterprise. Optimality is measured with respect to the overall (1) monetary cost of implementation, (2) negative side-effects of cyber-security controls (indirect costs), and (3) mitigation of the cyber-security risk. We consider “passive” and “reactive” threats, the former representing the case where attack attempts are independent of the defender’s plan, the latter, where attackers can adapt and react to an implemented cyber-security defense. Moreover, we model in three different ways the combined effect of multiple cyber-security controls, depending on their degree of complementarity and correlation. We also consider multi-stage attacks and the potential correlations in the success of different stages. First, we formalize the problem as a non-linear multi-objective integer programming. We then convert them into Mixed Integer Linear Programs (MILP) that very efficiently solve for the exact Pareto-optimal solutions even when the number of available controls is large. In our case study, we consider 27 of the most typical security controls, each with multiple intensity levels of implementation, and 37 common vulnerabilities facing a typical SME. We compare our findings against expert-recommended critical controls. We then investigate the effect of the security models on the resulting optimal plan and contrast the merits of different security metrics. In particular, we show the superior robustness of the security measures based on the “reactive” threat model, and the significance of the hitherto overlooked role of correlations