Water scarcity and managing seasonal water crisis: lessons from the Kirindi Oya Project in Sri Lanka

Irrigation management / Water management / Irrigation programs / Irrigated farming / Rain / Crop production / Crop yield / Rice / Case studies / River basins / Catchment areas / Irrigation scheduling / Water allocation / Water use efficiency / Water scarcity / Water shortage / Water demand / Reservoirs / Flow / Farmer participation / Farmer-agency interactions / Farmers' associations / Seasonal variation / Water distribution / Sri Lanka / Kirindi Oya / Ellegala / Lunugamwehera Reservoir

Chest Computed Tomography in early and advanced cystic fibrosis lung disease: Optimizing protocols, image analysis and further validation

Cystic Fibrosis (CF) is one of the most common life-threatening autosomal recessive diseases in the Western World, with a reported incidence rate of approximately 1 in every 2.000 to 5.000 caucasian newborns in most European countries. The gene mutation that plays an important role in the pathoph

Karhunen-Loeve representation of stochastic ocean waves

A new stochastic representation of a seastate is developed based on the Karhunen–Loeve spectral decomposition of stochastic signals and the use of Slepian prolate spheroidal wave functions with a tunable bandwidth parameter. The new representation allows the description of stochastic ocean waves in terms of a few independent sources of uncertainty when the traditional representation of a seastate in terms of Fourier series requires an order of magnitude more independent components. The new representation leads to parsimonious stochastic models of the ambient wave kinematics and of the nonlinear loads and responses of ships and offshore platforms. The use of the new representation is discussed for the derivation of critical wave episodes, the derivation of up-crossing rates of nonlinear loads and responses and the joint stochastic representation of correlated wave and wind profiles for use in the design of fixed or floating offshore wind turbines. The forecasting is also discussed of wave elevation records and vessel responses for use in energy yield enhancement of compliant floating wind turbines.ALSTOM (Firm)Ente nazionale per l'energia elettricab_TE

Bronchiectases at early chest computed tomography in children with cystic fibrosis are associated with increased risk of subsequent pulmonary exacerbations and chronic pseudomonas infection

AbstractBackgroundChildren with cystic fibrosis (CF) are often Pseudomonas aeruginosa (PsA) free and exhibit normal spirometry between the ages of 5 and 7. It is reported that computed tomography (CT) is more sensitive than FEV1 as an instrument in the identification of pulmonary disease. It is not known whether CF-CT scores in childhood may be used to highlight children at risk of developing severe disease.Aims1 — To assess the number of respiratory exacerbations (RTEs) during a follow-up period of 6years and their correlation with the CF-CT scores in young CF children. 2 — To assess whether PsA-negative CF children with high chest CF-CT scores are more likely to develop chronic PsA lung infection.Methods68 chest CT performed in patients without chronic PsA infection were scored. All patients (median age 7.8years) had at least 4 clinical, functional and microbiologic assessments/year in the subsequent 6years. RTE was defined as hospitalization and IV antibiotic treatment for respiratory symptoms.Results86.8% patients had <3 RTEs in the 6year follow-up period. The number of RTEs in the 6years subsequent to the CT scan was correlated to the bronchiectasis CT score (BCTS) (r=0.612; p<0.001) and to FEV1 at baseline (r=−0.495, p<0.001). A BCTS ≥17.5 identified patients with >3 RTEs during follow-up (sensitivity: 100%, specificity: 85%), while FEV1 did not. Only BCTS was significant in a logistic multivariate model (RR 1.15). BCTS was significantly lower and FEV1 higher in patients who did not develop chronic PsA infection by the end of the study.ConclusionIn CF children free from chronic PsA, both CT scores and FEV1 values demonstrate significant correlation with disease severity in the subsequent 6years but CT score has higher predictive value in the identification of patients at risk

The scaling attractor and ultimate dynamics for Smoluchowski's coagulation equations

We describe a basic framework for studying dynamic scaling that has roots in dynamical systems and probability theory. Within this framework, we study Smoluchowski's coagulation equation for the three simplest rate kernels $K(x,y)=2$, $x+y$ and $xy$. In another work, we classified all self-similar solutions and all universality classes (domains of attraction) for scaling limits under weak convergence (Comm. Pure Appl. Math 57 (2004)1197-1232). Here we add to this a complete description of the set of all limit points of solutions modulo scaling (the scaling attractor) and the dynamics on this limit set (the ultimate dynamics). The main tool is Bertoin's L\'{e}vy-Khintchine representation formula for eternal solutions of Smoluchowski's equation (Adv. Appl. Prob. 12 (2002) 547--64). This representation linearizes the dynamics on the scaling attractor, revealing these dynamics to be conjugate to a continuous dilation, and chaotic in a classical sense. Furthermore, our study of scaling limits explains how Smoluchowski dynamics ``compactifies'' in a natural way that accounts for clusters of zero and infinite size (dust and gel)

Spectral Analysis of Multi-dimensional Self-similar Markov Processes

In this paper we consider a discrete scale invariant (DSI) process $\{X(t), t\in {\bf R^+}\}$ with scale $l>1$. We consider to have some fix number of observations in every scale, say $T$, and to get our samples at discrete points $\alpha^k, k\in {\bf W}$ where $\alpha$ is obtained by the equality $l=\alpha^T$ and ${\bf W}=\{0, 1,...\}$. So we provide a discrete time scale invariant (DT-SI) process $X(\cdot)$ with parameter space $\{\alpha^k, k\in {\bf W}\}$. We find the spectral representation of the covariance function of such DT-SI process. By providing harmonic like representation of multi-dimensional self-similar processes, spectral density function of them are presented. We assume that the process $\{X(t), t\in {\bf R^+}\}$ is also Markov in the wide sense and provide a discrete time scale invariant Markov (DT-SIM) process with the above scheme of sampling. We present an example of DT-SIM process, simple Brownian motion, by the above sampling scheme and verify our results. Finally we find the spectral density matrix of such DT-SIM process and show that its associated $T$-dimensional self-similar Markov process is fully specified by $\{R_{j}^H(1),R_{j}^H(0),j=0, 1,..., T-1\}$ where $R_j^H(\tau)$ is the covariance function of $j$th and $(j+\tau)$th observations of the process.Comment: 16 page

Endoscopic colorectal cancer screening: a cost-saving analysis

BACKGROUND: Comprehensive analyses have shown that screening for cancer usually induces net costs. In this study, the possible costs and savings of endoscopic colorectal cancer screening are explored to investigate whether the induced savings may compensate for the costs of screening. METHODS: A simulation model for evaluation of colorectal cancer screening, MISCAN-COLON, is used to predict costs and savings for the U.S. population, assuming that screening is performed during a period of 30 years. Plausible baseline parameter values of epidemiology, natural history, screening test characteristics, and unit costs are based on available data and expert opinion. Important parameters are varied to extreme but plausible values. RESULTS: Given the expert opinion-based assumptions, a program based on every 5-year sigmoidoscopy screenings could result in a net savings of direct health care costs due to prevention of cancer treatment costs that compensate for the costs of screening, diagnostic follow-up, and surveillance. This result persists when costs and health effects are discounted at 3%. The "break-even" point, the time required before savings exceed costs, is 35 years for a screening program that terminates after 30 years and 44 years for a screening program that continues on indefinitely. However, net savings increase or turn into net costs when alternative assumptions about natural history of colorectal cancer, costs of screening, surveillance, and diagnostics are considered. CONCLUSIONS: Given the present, limited knowledge of the disease process of colorectal cancer, test characteristics, and costs, it may well be that the induced savings by endoscopic colorectal cancer screening completely compensate for the costs

Model Reduction in Flexible-Aircraft Dynamics with Large Rigid-Body Motion

This paper investigates the model reduction, using balanced realizations, of the unsteady aerodynamics of maneuvering flexible aircraft. The aeroelastic response of the vehicle, which may be subject to large wing deformations at trimmed flight, is captured by coupling a displacement-based, flexible-body dynamics formulation with an aerodynamic model based on the unsteady vortex lattice method. Consistent linearization of the aeroelastic problem allows the projection of the structural degrees of freedom on a few vibration modes of the unconstrained vehicle, but preserves all couplings between the rigid and elastic motions and permits the vehicle fiight dynamics to have arbitrarily-large angular velocities. The high-order aerodynamic system, which defines the mapping between the small number of generalized coordinates and unsteady aerodynamic loads, is then reduced using the balanced truncation method. Numerical studies on a representative high-altitude, long-endurance aircraft show a very substantial reduction in model size, by up to three orders of magnitude, that leads to model orders (and computational cost) similar to those in conventional frequency-based methods but with higher modeling fidelity to compute maneuver loads. Closed-loop results for the Goland wing finally demonstrate the application of this approach in the synthesis of a robust flutter suppression controller. © 2013 by Henrik Hesse and Rafael Palacios

PCA-based lung motion model

Organ motion induced by respiration may cause clinically significant targeting errors and greatly degrade the effectiveness of conformal radiotherapy. It is therefore crucial to be able to model respiratory motion accurately. A recently proposed lung motion model based on principal component analysis (PCA) has been shown to be promising on a few patients. However, there is still a need to understand the underlying reason why it works. In this paper, we present a much deeper and detailed analysis of the PCA-based lung motion model. We provide the theoretical justification of the effectiveness of PCA in modeling lung motion. We also prove that under certain conditions, the PCA motion model is equivalent to 5D motion model, which is based on physiology and anatomy of the lung. The modeling power of PCA model was tested on clinical data and the average 3D error was found to be below 1 mm.Comment: 4 pages, 1 figure. submitted to International Conference on the use of Computers in Radiation Therapy 201

Выявление понятий и их взаимосвязей в рамках технологии контент-мониторинга

Приведены подходы к решению проблемы выявления фактографической информации из неструктурированных текстовых потоков. Описаны технологические решения, позволяющие извлекать из полнотекстовых документов такие понятия как фирмы, фамилии, географические названия и т.п., а также выявлять силу их взаимосвязей на основе применения двух алгоритмов. Первый из этих алгоритмов основывается на учете совместного вхождения понятий в одни и те же документы, а второй на учете общего для рассматриваемых понятий контекста.Наведено підходи до вирішення проблеми виявлення фактографічної інформації з неструктурованих текстових потоків. Описано технологічні рішення, що дозволяють добути з повнотекстових документів такі поняття як фірми, прізвища, географічні назви тощо, а також виявляти силу їхніх взаємозв’язків на базі застосування двох алгоритмів. Перший з цих алгоритмів базується на врахуванні спільного входження понять до одних і тих самих документів, а другий — на врахуванні загального для понять, що розглядаються, контексту.Approaches to the solution of a problem of revealing factual information from unstructured text flows are given. The technological solutions, allowing to take from text-through documents such concepts as a firm, a surname, place names, etc., and also to reveal force of their interrelations on the basis of application of two algorithms are described. The first of these algorithms is based on the account of joint concepts occurrence in the same documents, and the second one on the account of the context common for considered concepts