How policy can influence human capital accumulation and environment quality.

This paper considers the implications of education and environment policy for growth in a model where the interactions between health, education, and the environment are taken into account. With respect to previous works, in which one of these three dimensions is omitted, we consider their combined effects, arriving to novel results in the literature. According to our model, higher taxes and environment spending share in total public spending do not affect welfare significantly, but they have an important positive impact on human capital and environment quality. Here, a positive relationship between public education spending and environment quality emerges as well as between environment maintenance expenditure and human capital. At the same time, countries with a high environmental quality should spend less on environment maintenance compared to heavily polluted countries. Finally, for countries with advanced abatement technologies, the relationship between human capital and environment is positive, which is compatible with the environmental Kuznets curve

An Approach to Support the Performance Management of Public Health Authorities using an IT based Modeling Method

In this paper we describe a modeling method for supportingperformance management by building upon the currentchallenges of public health authorities. Through focusingon the performance management requirements of nationalcompetent authorities (NCA) that fulll several duties inregard to the marketing authorization of medicinal products,we derive a modeling language, an according modeling procedureand mechanisms and algorithms. Thereby, particularrequirements in regard to the compliance to legal regulations,the competition of NCAs within the European Union, theallocation of resources under uncertainty, and the specichuman resource requirements of NCAs have to be taken intoaccount. The modeling language is formally described usinga meta model based approach and implemented on a metamodeling platform. For the evaluation, the modeling methodhas been applied in a scientic study with the Austriannational competent authority AGES PharmMed

How policy can influence human capital accumulation and environment quality.

This paper considers the implications of education and environment policy for growth in a model where the interactions between health, education, and the environment are taken into account. With respect to previous works, in which one of these three dimensions is omitted, we consider their combined effects, arriving to novel results in the literature. According to our model, higher taxes and environment spending share in total public spending do not affect welfare significantly, but they have an important positive impact on human capital and environment quality. Here, a positive relationship between public education spending and environment quality emerges as well as between environment maintenance expenditure and human capital. At the same time, countries with a high environmental quality should spend less on environment maintenance compared to heavily polluted countries. Finally, for countries with advanced abatement technologies, the relationship between human capital and environment is positive, which is compatible with the environmental Kuznets curve

Is there an additional benefit from coronary revascularization in diabetic patients with acute coronary syndromes or stable angina who are already on optimal medical treatment?

Cardiovascular disease (CVD) is common in patients with diabetes mellitus (DM) and related clinical outcomes are worse compared with non-diabetics. The optimal treatment in diabetic patients with coronary heart disease (CHD) is currently not established. We searched MEDLINE (1975-2010) using the key terms diabetes mellitus, coronary heart disease, revascularization, coronary artery bypass, angioplasty, coronary intervention and medical treatment. Most studies comparing different revascularization procedures in patients with CHD favoured coronary artery bypass graft (CABG) surgery in patients with DM. However, most of this evidence comes from subgroup analyses. Recent evidence suggests that advanced percutaneous coronary intervention (PCI) techniques along with best medical treatment may be non-inferior and more cost-effective compared with CABG. Treatment of vascular risk factors is a key option in terms of improving CVD outcomes in diabetic patients with CHD. The choice between medical therapy and revascularization warrants further assessment

Could the U.S. Energy Sector Become New Engine For Growth?

The intent of this paper is to discuss the U.S. energy sector in the context of economic growth, employment conditions, manufacturing competitiveness, and trade deficits. The paper carefully examines how utilization of domestic energy resources can strengthen the United States economic position in both domestic and foreign markets. Consideration is given to expanding the use of domestic energy resources to improve competitiveness in the global goods market and reduce dependency on foreign oil. In particular, the sections of the paper discuss: the current U.S. macroeconomic situation with an emphasis on economic growth and labor market; domestic oil and gas production; energy security; institutional arrangements necessary to deliver reliable U.S. energy resources to domestic and foreign markets; and policy considerations deemed necessary to boost energy growth. Keywords: Economic growth, Energy consumption, Energy production, development policy JEL Classifications: O;

Quality of Service Abstractions for Software-defined Networks

ABSTRACT Software-defined networking (SDN) provides a means of configuring the packet-forwarding behavior of a network from a logically-centralized controller. Expressive, high-level languages have emerged for expressing data-plane configurations, and new tools allow for verifying packet reachability properties in real time. But SDN largely ignores quality of service (QoS) primitives, such as queues, queuing disciplines, and rate limiters, leaving configuration of these elements to be performed out of band in an ad-hoc manner. Not only does this make QoS elements difficult to configure, it also leads to a "try it and see" approach to analysis and verification of QoS properties. We propose a new language for configuring SDNs with quality of service primitives. Our language comes equipped with a well-defined semantics drawn from the network calculus, which we believe will yield an equational theory for reasoning about network quality of service as well as decision procedures for verifying QoS properties

Artificial pancreas treatment for outpatients with type 1 diabetes: systematic review and meta-analysis.

OBJECTIVE: To evaluate the efficacy and safety of artificial pancreas treatment in non-pregnant outpatients with type 1 diabetes. DESIGN: Systematic review and meta-analysis of randomised controlled trials. DATA SOURCES: Medline, Embase, Cochrane Library, and grey literature up to 2 February 2018. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials in non-pregnant outpatients with type 1 diabetes that compared the use of any artificial pancreas system with any type of insulin based treatment. Primary outcome was proportion (%) of time that sensor glucose level was within the near normoglycaemic range (3.9-10 mmol/L). Secondary outcomes included proportion (%) of time that sensor glucose level was above 10 mmol/L or below 3.9 mmol/L, low blood glucose index overnight, mean sensor glucose level, total daily insulin needs, and glycated haemoglobin. The Cochrane Collaboration risk of bias tool was used to assess study quality. RESULTS: 40 studies (1027 participants with data for 44 comparisons) were included in the meta-analysis. 35 comparisons assessed a single hormone artificial pancreas system, whereas nine comparisons assessed a dual hormone system. Only nine studies were at low risk of bias. Proportion of time in the near normoglycaemic range (3.9-10.0 mmol/L) was significantly higher with artificial pancreas use, both overnight (weighted mean difference 15.15%, 95% confidence interval 12.21% to 18.09%) and over a 24 hour period (9.62%, 7.54% to 11.7%). Artificial pancreas systems had a favourable effect on the proportion of time with sensor glucose level above 10 mmol/L (-8.52%, -11.14% to -5.9%) or below 3.9 mmol/L (-1.49%, -1.86% to -1.11%) over 24 hours, compared with control treatment. Robustness of findings for the primary outcome was verified in sensitivity analyses, by including only trials at low risk of bias (11.64%, 9.1% to 14.18%) or trials under unsupervised, normal living conditions (10.42%, 8.63% to 12.2%). Results were consistent in a subgroup analysis both for single hormone and dual hormone artificial pancreas systems. CONCLUSIONS: Artificial pancreas systems are an efficacious and safe approach for treating outpatients with type 1 diabetes. The main limitations of current research evidence on artificial pancreas systems are related to inconsistency in outcome reporting, small sample size, and short follow-up duration of individual trials

Decentralized Task-aware Scheduling for Data Center Networks.

ABSTRACT Many data center applications perform rich and complex tasks (e.g., executing a search query or generating a user's news-feed). From a network perspective, these tasks typically comprise multiple flows, which traverse different parts of the network at potentially different times. Most network resource allocation schemes, however, treat all these flows in isolation -rather than as part of a task -and therefore only optimize flow-level metrics. In this paper, we show that task-aware network scheduling, which groups flows of a task and schedules them together, can reduce both the average as well as tail completion time for typical data center applications. To achieve these benefits in practice, we design and implement Baraat, a decentralized task-aware scheduling system. Baraat schedules tasks in a FIFO order but avoids head-of-line blocking by dynamically changing the level of multiplexing in the network. Through experiments with Memcached on a small testbed and large-scale simulations, we show that Baraat outperforms state-of-the-art decentralized schemes (e.g., pFabric) as well as centralized schedulers (e.g., Orchestra) for a wide range of workloads (e.g., search, analytics, etc)