Photolytic and thermolytic decomposition products from iron pentacarbonyl adsorbed on Y zeolite

Zeolite supported iron systems obtained by photolysis and thermolysis of Fe(CO)5/Na---Y adducts are characterized via evaluation of the respective magnetic isotherms taken with a FONER magnetometer at T = 4.2 K. Thermolysis under fast heating in inert gas and under fluidized shallow bed conditions completes within a few minutes at not, vert, similar 500 K, and gives iron clusters of which at least 70 to 90 wt% is smaller than 1 nm. Prolonged photolysis at 290 K in the same fluidized bed conditions does not result in the formation of ‘naked’ iron(O) clusters, but gives a limited fraction of magnetically coupled Fex(CO)y entities. Photodimerization cannot be excluded to be the main reaction path

Subtle Fluorination of Conjugated Molecules Enables Stable Nanoscale Assemblies on Metal Surfaces

In molecular self-assembly on surfaces, the structure is governed by the intricate balance of attractive and repulsive forces between molecules as well as between molecules and the substrate. Frequently, repulsive interactions between molecules adsorbed on a metal surface dominate in the low-coverage regime, and dense self-assembled structures can only be observed close to full monolayer coverage. Here, we demonstrate that fluorination at selected positions of conjugated molecules provides for sufficiently strong, yet nonrigid, H···F bonding capability that (i) enables the formation of stable nanoscale molecular assemblies on a metal surface and (ii) steers the assemblies’ structure. This approach should be generally applicable and will facilitate the construction and study of individual nanoscale molecular assemblies with structures that are not attainable in the high-coverage regime

The Evidence Does Not Speak for Itself: The Role of Research Evidence in Shaping Policy Change for the Implementation of Publicly Funded Syringe Exchange Programs in Three US Cities

BACKGROUND: A breadth of literature exists that explores the utilization of research evidence in policy change processes. From this work, a number of studies suggest research evidence is applied to change processes by policy change stakeholders primarily through instrumental, conceptual, and/or symbolic applications, or is not used at all. Despite the expansiveness of research on policy change processes, a deficit exists in understanding the role of research evidence during change processes related to the implementation of structural interventions for HIV prevention among injection drug users (IDU). This study examined the role of research evidence in policy change processes for the implementation of publicly funded syringe exchange services in three US cities: Baltimore, MD, Philadelphia, PA, and Washington, DC. METHODS: In-depth qualitative interviews were conducted with key stakeholders (n=29) from each of the study cities. Stakeholders were asked about the historical, social, political, and scientific contexts in their city during the policy change process. Interviews were transcribed and analyzed for common themes pertaining to applications of research evidence. RESULTS: In Baltimore and Philadelphia, the typological approaches (instrumental and symbolic/conceptual, respectively) to the applications of research evidence used by harm reduction proponents contributed to the momentum for securing policy change for the implementation of syringe exchange services. Applications of research evidence were less successful in DC because policymakers had differing ideas about the implications of syringe exchange program implementation and because opponents of policy change used evidence incorrectly or not at all in policy change discussions. CONCLUSION: Typological applications of research evidence are useful for understanding policy change processes, but their efficacy falls short when sociopolitical factors complicate legislative processes. Advocates for harm reduction may benefit from understanding how to effectively integrate research evidence into policy change processes in ways that confront the myriad of factors that influence policy change

A new potential for methylammonium lead iodide.

We present a new set of interatomic potentials for modelling methylammonium lead iodide. The potential model uses existing potentials for lead iodide and methylammonium, and new functions are fitted to enable these pre-existing potentials to be used together, while still being capable of modelling lead iodide and methylammonium iodide as separate materials. Fitting was performed using a combination of ab initio and experimental reference data. Our simulations are in agreement with experiment and reveal the short and long range ordering of the molecular cations and lead iodide octahedra

Association between health systems performance and treatment outcomes in patients co-infected with MDR-TB and HIV in KwaZulu-Natal, South Africa: implications for TB programmes.

CAPRISA, 2014.Objective: To improve the treatment of MDR-TB and HIV co-infected patients, we investigated the relationship between health system performance and patient treatment outcomes at 4 decentralised MDR-TB sites. Methods: In this mixed methods case study which included prospective comparative data, we measured health system performance using a framework of domains comprising key health service components. Using Pearson Product Moment Correlation coefficients we quantified the direction and magnitude of the association between health system performance and MDR-TB treatment outcomes. Qualitative data from participant observation and interviews analysed using systematic text condensation (STC) complemented our quantitative findings. Findings: We found significant differences in treatment outcomes across the sites with successful outcomes varying from 72% at Site 1 to 52% at Site 4 (p<0.01). Health systems performance scores also varied considerably across the sites. Our findings suggest there is a correlation between treatment outcomes and overall health system performance which is significant (r = 0.99, p<0.01), with Site 1 having the highest number of successful treatment outcomes and the highest health system performance. Although the 'integration' domain, which measured integration of MDR-TB services into existing services appeared to have the strongest association with successful treatment outcomes (r = 0.99, p<0.01), qualitative data indicated that the 'context' domain influenced the other domains. Conclusion: We suggest that there is an association between treatment outcomes and health system performance. The chance of treatment success is greater if decentralised MDR-TB services are integrated into existing services. To optimise successful treatment outcomes, regular monitoring and support are needed at a district, facility and individual level to ensure the local context is supportive of new programmes and implementation is according to guidelines

How much can we gain from improved efficiency? An examination of performance of national HIV/AIDS programs and its determinants in low- and middle-income countries

<p>Abstract</p> <p>Background</p> <p>The economic downturn exacerbates the inadequacy of resources for combating the worldwide HIV/AIDS pandemic and amplifies the need to improve the efficiency of HIV/AIDS programs.</p> <p>Methods</p> <p>We used data envelopment analysis (DEA) to evaluate efficiency of national HIV/AIDS programs in transforming funding into services and implemented a Tobit model to identify determinants of the efficiency in 68 low- and middle-income countries. We considered the change from the lowest quartile to the average value of a variable a "notable" increase.</p> <p>Results</p> <p>Overall, the average efficiency in implementing HIV/AIDS programs was moderate (49.8%). Program efficiency varied enormously among countries with means by quartile of efficiency of 13.0%, 36.4%, 54.4% and 96.5%. A country's governance, financing mechanisms, and economic and demographic characteristics influence the program efficiency. For example, if countries achieved a notable increase in "voice and accountability" (e.g., greater participation of civil society in policy making), the efficiency of their HIV/AIDS programs would increase by 40.8%. For countries in the lowest quartile of per capita gross national income (GNI), a notable increase in per capita GNI would increase the efficiency of AIDS programs by 45.0%.</p> <p>Conclusions</p> <p>There may be substantial opportunity for improving the efficiency of AIDS services, by providing more services with existing resources. Actions beyond the health sector could be important factors affecting HIV/AIDS service delivery.</p

Roadmap on Machine learning in electronic structure

AbstractIn recent years, we have been witnessing a paradigm shift in computational materials science. In fact, traditional methods, mostly developed in the second half of the XXth century, are being complemented, extended, and sometimes even completely replaced by faster, simpler, and often more accurate approaches. The new approaches, that we collectively label by machine learning, have their origins in the fields of informatics and artificial intelligence, but are making rapid inroads in all other branches of science. With this in mind, this Roadmap article, consisting of multiple contributions from experts across the field, discusses the use of machine learning in materials science, and share perspectives on current and future challenges in problems as diverse as the prediction of materials properties, the construction of force-fields, the development of exchange correlation functionals for density-functional theory, the solution of the many-body problem, and more. In spite of the already numerous and exciting success stories, we are just at the beginning of a long path that will reshape materials science for the many challenges of the XXIth century

Roadmap on Machine learning in electronic structure

In recent years, we have been witnessing a paradigm shift in computational materials science. In fact, traditional methods, mostly developed in the second half of the XXth century, are being complemented, extended, and sometimes even completely replaced by faster, simpler, and often more accurate approaches. The new approaches, that we collectively label by machine learning, have their origins in the fields of informatics and artificial intelligence, but are making rapid inroads in all other branches of science. With this in mind, this Roadmap article, consisting of multiple contributions from experts across the field, discusses the use of machine learning in materials science, and share perspectives on current and future challenges in problems as diverse as the prediction of materials properties, the construction of force-fields, the development of exchange correlation functionals for density-functional theory, the solution of the many-body problem, and more. In spite of the already numerous and exciting success stories, we are just at the beginning of a long path that will reshape materials science for the many challenges of the XXIth century.</p

Roadmap on machine learning in electronic structure

In recent years, we have been witnessing a paradigm shift in computational materials science. In fact, traditional methods, mostly developed in the second half of the XXth century, are being complemented, extended, and sometimes even completely replaced by faster, simpler, and often more accurate approaches. The new approaches, that we collectively label by machine learning, have their origins in the fields of informatics and artificial intelligence, but are making rapid inroads in all other branches of science. With this in mind, this Roadmap article, consisting of multiple contributions from experts across the field, discusses the use of machine learning in materials science, and share perspectives on current and future challenges in problems as diverse as the prediction of materials properties, the construction of force-fields, the development of exchange correlation functionals for density-functional theory, the solution of the many-body problem, and more. In spite of the already numerous and exciting success stories, we are just at the beginning of a long path that will reshape materials science for the many challenges of the XXIth century