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The Advancement in Spring Vegetation Phenology in the Northern Hemisphere Will Reverse After 2060 Under Future Moderate Warming Scenarios

Global warming has largely advanced spring vegetation phenology, which has subsequently affected terrestrial carbon and water cycles. However, further shifts in vegetation phenology under future climate change remain unclear. We estimated the start of the growing season (SOS) by applying multiple extraction methods based on the NDVI3g data set, and then parameterized and evaluated 11 spring vegeta

Gigantic solar farms of the future might impact how much solar power can be generated on the other side of the world

The Sun’s energy is effectively limitless. While resources such as coal or gas are finite, if you are able to capture and use solar power it doesn’t prevent anyone else from also using as much sunshine as they need.Except that isn’t quite the full story. Beyond a certain size, solar farms become large enough to affect the weather around them and ultimately the climate as a whole. In our new resear

An Extended Triple Collocation Method With Maximized Correlation for Near Global-Land Precipitation Fusion

An Extended Triple Collocation for maximized Correlation (ETCC) method was proposed with a unique correlation function, the purpose of which is to maximize the correlation between the merged product and unknown truth. The method was tested over quasi-global land by combining three independent precipitation products. The performance of the ETCC-merged product was then evaluated against three refere

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Because of varied topography and landscape heterogeneity,Tianshan Mountain has extremely complex hydrological processes. Considering that the climate change poses a great threat to the water security,it’s necessary to simulate the change of water elements quantitatively and systematically along with elevation. In this study,we applied the modified FLEXG-Δh model to four classic river basins in Tia

Input and state constrained inverse optimal control with application to power networks

We study input and state constrained inverse optimal control problems starting from a stabilizing controller with a control Lyapunov function, where the goal is to make the controller an explicit solution of the resulting constrained optimal control problem. For an appropriate cost design and initial states for which a sublevel set of the Lyapunov function is contained in the state constraint set

Optimal Linear Control over Channels with Signal-to-Noise Ratio Constraints

We consider a networked control system where a linear time-invariant (LTI) plant, subject to a stochastic disturbance, is controlled over a communication channel with colored noise and a signal-to-noise ratio (SNR) constraint. The controller is based on output feedback and consists of an encoder that measures the plant output and transmits over the channel, and a decoder that receives the channel

The Fall of Reichenbach

Reichenbach’s constraint is the methodological imperative formulated by Reichenbach in the following passage: “If we want to construct a philosophy of science, we have to distinguish carefully between two kinds of context in which scientific theories may be considered. The context of discovery is to be separated from the context of justification; the former belongs to the psychology of scient

Adaptive Resource Management Made Real

The adaptive resource management framework implemented in the European ACTORS project is presented. A resource manager has been developed that collaborates with a new Linux scheduler providing support for hard constant bandwidth server reservations, in order to adapt applications to changes in resource availability and to adapt the resource allocation to changes in application requirements. The fo

Automated Design of Self-Adaptive Software with Control-Theoretical Formal Guarantees

Self-adaptation enables software to execute successfully in dynamic, unpredictable, and uncertain environments. Control theory provides a broad set of mathematically grounded techniques for adapting the behavior of dynamic systems. While it has been applied to specific software control problems, it has proved difficult to define methodologies allowing non-experts to systematically apply control te

Modeling the Impact of a Standardized Breakfast on T1DM Fasting Blood Glucose

The design of a controller for glycemia regulation, either in open or in closed-­‐loop, relies on models able to describe the effects of a meal intake and an insulin injection on blood glucose dynamics. The purpose of this study was therefore to propose a physiological relevant yet parsimonious model for carbohydrate action on fasting blood glucose in T1DM patients when no insulin is taken.

Investigating temporal relationships between rainfall, soil moisture and MODIS-derived NDVI and EVI for six sites in Africa

This study investigates temporal relationships between vegetation growth, rainfall, and soil moisture for six sites located in sub-Saharan and southern Africa for the period 2005-2009. Specifically, seasonal components of time series of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) composites from the Moderate Resolution Imaging Spectroradiometer (MODIS) and hal

A Generalized Software System for Accurate and Efficient Management of Application Performance Goals

A number of techniques have been proposed to provide run- time performance guarantees while minimizing power consumption. One drawback of existing approaches is that they work only on a fixed set of components (or actuators) that must be specified at design time. If new components become available, these management systems must be redesigned and reimplemented. In this paper, we propose PTRADE, a n

A Scalable Formulation for Engineering Combination Therapies for Evolutionary Dynamics of Disease

It has been shown that optimal controller synthesis for positive systems can be formulated as a linear program. Leveraging these results, we propose a scalable iterative algorithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model. We achieve the desired feedback structure by augmenting the optimization problems w