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The paper guides three scenarios of power planning for Vietnam for the 2018–2030 period under CO2 emission targets. The analysis employs a model of energy expansion in the form of an optimization problem with the objective of the discounted entire system cost minimization. With each CO2 emission allowance, a scenario of the newly installed capacity structure will be carried out. The results indicate that instead of 42.6% coal-fired installed capacity as indicated in the National Power Development Master Plan for the 2011–2020 period with the Vision to 2030 (known as PDP VII), by 2030 the share of this power source will be around 29% (8% CO2 reduction scenario) and 19% (25% CO2 reduction scenario). Also, the lower emission sources such as hydro, wind, and solar power will be a priority for investment in the next decade. There is an existence of coal-fired power plants replacement by natural gas stations. Keywords: Power planning, Optimization problem, CO2 reduction target

Cataloged from PDF version of article. This article develops a new framework for understanding environment-conflict relations, on both theoretical grounds and through a qualitative historical analysis of the links between water and conflict in the states of Sudan and South Sudan. Theoretically, the article critiques the dominant emphases on ‘scarcity’, ‘state failure’ and ‘under-development’ within discussions of environmental security, and proposes an alternative model of environment-conflict relations centring on resource abundance and globally-embedded processes of state-building and development. Empirically, it examines three claimed (or possible) linkages between water and conflict in the Sudans: over trans-boundary waters of the Nile; over the links between internal resource scarcities and civil conflict; and over the internal conflict impacts of water abundance and development.We find thatthere exists only limited evidence in support ofthefirst two of these linkages, but plentiful evidence that water abundance, and state-directed processes of economic development and internal colonisation relating to water, have had violent consequences. We conclude that analysts and policymakers should pay more attention to the impacts of resource abundance, militarised state power and global political economic forces in their assessments of the potential conflict impacts of environmental and especially climate change. 2014 Elsevier Ltd. All rights reserved.

The introduction of automated oscillometric blood pressure monitors was the basis for today’s widespread use of blood pressure self-measurement. However, in atrial fibrillation, there is a controversial debate on the use of oscillometry because there is a high variability of heart rate and stroke volume. To date, the accuracy of oscillometric blood pressure monitoring in atrial fibrillation has only been investigated using auscultatory sphygmomanometry as reference method, which may be biased by arrhythmia as well. We performed a cross-sectional study in 102 patients (52 sinus rhythm, 50 atrial fibrillation) assessing the accuracy of an automated and validated oscillometric upper arm (M5 Professional, Omron) and wrist device (R5 Professional, Omron) to invasively assessed arterial pressure. Blood pressure values were calculated as the mean of 3 consecutive measurements. Systolic and diastolic blood pressure did not significantly differ in patients with sinus rhythm and atrial fibrillation, independent of the method of measurement ( P >0.05 each). The within-subject variability of the oscillometric measurements was higher in patients with atrial fibrillation compared with sinus rhythm ( P P >0.05 each). In conclusion, atrial fibrillation did not significantly affect the accuracy of oscillometric measurements, if 3 repeated measurements were performed.

Intermittent renewable power production from wind and sun requires significant backup generation to cover the power demand at all times. This holds even if wind and sun produce on average 100% of the required energy. Backup generation can be reduced through storage – averaging in time – and/or grid extensions – averaging in space. This report examines the interplay of these technologies with respect to the reduction of required backup energy. We systematically explore a wide parameter space of combinations of both technologies. Our simple, yet informative approach quantifies the backup energy demand for each scenario. We also estimate the resulting total system costs which allow us to discuss cost-optimal system designs.

Motivated by a strongly growing interest in anonymizing social network data, we investigate the NP-hard Degree Anonymization problem: given an undirected graph, the task is to add a minimum number of edges such that the graph becomes k-anonymous. That is, for each vertex there have to be at leastak '—' 1 other vertices of exactly the same degree. The model of degree anonymization has been introduced by Liu and Terzia[ACM SIGMOD'08], who also proposed and evaluated a two-phase heuristic. We present an enhancement of this heuristic, including new algorithms for each phase which significantly improve on the previously known theoretical and practical running times. Moreover, our algorithms are optimized for large-scale social networks and provide upper and lower bounds for the optimal solution. Notably, on about 26 % of the real-world data we provide (provably) optimal solutions; whereas in the other cases our upper bounds significantly improve on known heuristicasolutions.

The renewable power generation aggregated across Europe exhibits strong seasonal behaviors. Wind power generation is much stronger in winter than in summer. The opposite is true for solar power generation. In a future Europe with a very high share of renewable power generation those two opposite behaviors are able to counterbalance each other to a certain extent to follow the seasonal load curve. The best point of counterbalancing represents the seasonal optimal mix between wind and solar power generation. It leads to a pronounced minimum in required stored energy. For a 100% renewable Europe the seasonal optimal mix becomes 55% wind and 45% solar power generation. For less than 100% renewable scenarios the fraction of wind power generation increases and that of solar power generation decreases.

Background Kidney allograft function crucially depends on the quality of organ perfusion. Duplex sonography, however, frequently reveals hypoperfused segments that remained undetectable to visual inspection intraoperatively. To date, no imaging system supplementing the surgeon's experience has achieved clinical acceptance. The present work examines whether laser-assisted indocyanine green (ICG) fluorescence-videography can be used as a safe and sensitive technique for the intraoperative assessment of renal allograft perfusion. Methods Intraoperative assessment of organ perfusion by laser-assisted ICG fluorescence videography (IC-VIEW) was performed in 10 consecutive de novo renal transplantations. The IC-VIEW system allows the visualization of graft perfusion by the fluorescein dye ICG that emits infrared light after exposure to laser light. Results Perfusion measurements were successful in all 10 transplant recipients. Fluorescence videography produced brilliant, sharply contrasted images of the organs, allowing the detection of even small perfusion deficits. Remarkably, this technique detected 1 large perfusion defect that had remained imperceptible to visual inspection. Repositioning of the graft led to a homogeneous overall perfusion. There were no complications with the ICG injection or the imaging device. Conclusion Laser-assisted ICG fluorescence videography is a feasible and safe technique for the intraoperative assessment of renal allograft perfusion.

The increasing share of decentralized small and medium power plants opens up interesting options for a paradigmatic change of network operation strategies. On the one hand fluctuating generation principally endanger robust network operation. On the other hand there is an economic and ecological pressure to maximize the infeed of renewable energy sources. There is therefore a need for a cheap and scalable solution to meet these challenges. The solution we propose requires more decision intelligence and communication between the players in the electrical network. Scalability is achieved if the central control task is distributed among the intelligent players. Optimization of the control problem then means to devise a set of roles for the players and rules among them. We present such a basic set of roles and rules. We discuss the self-organization that occurs on the basis of these rules, the system performance as well as the consequences for the evolution of present-day strategies of network operation.

Estimation of removable excess body fluid is difficult in critically ill patients with renal failure. Volumetric hemodynamic parameters are increasingly being used to guide fluid therapy in the intensive care unit, but their suitability to monitor fluid removal with hemodialysis in critically ill patients is not known. Changes in the extravascular lung water index (EVLWI) and intrathoracic blood volume index (ITBVI) measured with transpulmonary thermodilution immediately before and after hemodialysis were analyzed from 39 hemodialysis sessions of 9 patients consecutively treated in the medical intensive care unit of a German University Hospital. Additional hemodynamic, ventilation, and oxygenation-related parameters were recorded at the same time. Online relative blood volume (RBV) monitoring was performed in 29 sessions. Comparisons of pre and postdialysis values showed a significant reduction of the EVLWI with fluid removal (p=0.009), with only a slight nonsignificant decrease in the ITBVI. The cardiac index (CI) also decreased significantly (p=0.010), whereas blood pressure remained stable. Oxygenation improved significantly (p=0.005), and the hematocrit increased significantly with dialysis (p=0.039). There was no correlation between hematocrit changes and RBV measurements. Significant correlations existed between ITBVI and CI changes (p

In this paper, nonlinear Bayesian filtering techniques are applied to the localization of mobile radio communication devices. The application of this approach is demonstrated for the localization of DECT mobile telephones in a scenario with several base stations and a mobile handset. The received signal power, measured by the mobile handsets, is related to their position by nonlinear measurement equations. These consist of a deterministic part, modeling the received signal power as a function of the position, and a stochastic part, describing model errors and measurement noise. Additionally, user models are considered, which express knowledge about the motion of the user of the handset. The new Prior Density Splitting Mixture Estimator (PDSME), a Gaussian mixture filtering algorithm, significantly improves the localization quality compared to standard filtering techniques as the Extended Kalman Filter (EKF).