High-risk patients and high-risk grafts in infrainguinal bypass for critical limb ischaemia

The main purpose of revascularization procedures for critical limb ischaemia (CLI) is to preserve the leg and sustain the patient s ambulatory status. Other goals are ischaemic pain relief and healing of ischaemic ulcers. Patients with CLI are usually old and have several comorbidities affecting the outcome. Revascularization for CLI is meaningless unless both life and limb are preserved. Therefore, the knowledge of both patient- and bypass-related risk factors is of paramount importance in clinical decision-making, patient selection and resource allocation. The aim of this study was to identify patient- and graft-related predictors of impaired outcome after infrainguinal bypass for CLI. The purpose was to assess the outcome of high-risk patients undergoing infrainguinal bypass and to evaluate the usefulness of specific risk scoring methods. The results of bypasses in the absence of optimal vein graft material were also evaluated, and the feasibility of the new method of scaffolding suboptimal vein grafts was assessed. The results of this study showed that renal insufficiency - not only renal failure but also moderate impairment in renal function - seems to be a significant risk factor for both limb loss and death after infrainguinal bypass in patients with CLI. Low estimated GFR (PIENEMPI KUIN 30 ml/min/1.73 m2) is a strong independent marker of poor prognosis. Furthermore, estimated GFR is a more accurate predictor of survival and leg salvage after infrainguinal bypass in CLI patients than serum creatinine level alone. We also found out that the life expectancy of octogenarians with CLI is short. In this patient group endovascular revascularization is associated with a better outcome than bypass in terms of survival, leg salvage and amputation-free survival especially in presence of coronary artery disease. This study was the first one to demonstrate that Finnvasc and modified Prevent III risk scoring methods both predict the long-term outcome of patients undergoing both surgical and endovascular infrainguinal revascularization for CLI. Both risk scoring methods are easy to use and might be helpful in clinical practice as an aid in preoperative patient selection and decision-making. Similarly than in previous studies, we found out that a single-segment great saphenous vein graft is superior to any other autologous vein graft in terms of mid-term patency and leg salvage. However, if optimal vein graft is lacking, arm vein conduits are superior to prosthetic grafts especially in infrapopliteal bypasses for CLI. We studied also the new method of scaffolding suboptimal quality vein grafts and found out that this method may enable the use of vein grafts of compromised quality otherwise unsuitable for bypass grafting. The remarkable finding was that patients with the combination of high operative risk due to severe comorbidities and risk graft have extremely poor survival, suggesting that only relatively fit patients should undergo complex bypasses with risk grafts. The results of this study can be used in clinical practice as an aid in preoperative patient selection and decision-making. In the future, the need of vascular surgery will increase significantly as the elderly and diabetic population increases, which emphasises the importance of focusing on those patients that will gain benefit from infrainguinal bypass. Therefore, the individual risk of the patient, ambulatory status, outcome expectations, the risk of bypass procedure as well as technical factors such as the suitability of outflow anatomy and the available vein material should all be assessed and taken into consideration when deciding on the best revascularization strategy.

A radical cyclisation based strategy to cuparenoids; synthesis of (±)-α-cuparenone, (±)-epilaurene and laurenes

Mercuric acetate catalysed one pot Claisen rearrangement of the cinnamyl alcohol Image , generated the pent-4-enal Image , which on homologation resulted the hex-5-enal Image . Radical cyclisation of the radical anion derived from Image , followed by oxidation provided the ketone mixture Image , a known precursor to the sesquiterpenes (Image )-α-cuparenone (Image ), (Image )-epilaurene (Image ) and laurene (Image )

Information and Decision Technologies

Production scheduling in a flexible manufacturing system (FMS) is a real-time combinatorial optimization problem that has been proved to be NP-complete. Solving this problem needs on-line monitoring of plan execution and requires real-time decision-making in selecting alternative routings, assigning required resources, and rescheduling when failures occur in the system. Expert systems provide a natural framework for solving this kind of NP-complete problems.In this paper an expert system with a novel parallel heuristic approach is implemented for automatic short-term dynamic scheduling of FMS. The principal features of the expert system presented in this paper include easy rescheduling, on-line plan execution, load balancing, an on-line garbage collection process, and the use of advanced knowledge representational schemes. Its effectiveness is demonstrated with two examples.

A Strategy for Conserving the Biodiversity of the Uttara Kannada District in South India

Taking the various values ascribed to biodiversity as its point of departure rather many years ago, the present study aims at deriving a conservation strategy for Uttara Kannada. This hilly district, with the highest proportion of its area under forests in South India, is divided into five ecological zones: coastal, northern evergreen, southern evergreen, moist deciduous, and dry deciduous. The heavily-populated coastal zone includes mangrove forests and estuarine wetlands. The evergreen forests are particularly rich in the diversity of plant species which they support - including wild relatives of a number of cultivated plants. They also serve a vital function in watershed conservation. The moist deciduous forests are rich in bird species; both moist and dry deciduous forests include a number of freshwater ponds and lakes that support a high diversity of aquatic birds.Reviewing the overall distribution of biodiversity, we identify specific localities - including estuaries, evergreen forests, and moist deciduous forests - which should be set aside as Nature reserves. These larger reserves must be complemented by a network of traditionally-protected sacred groves and sacred trees that are distributed throughout the district and that protect today, for instance, the finest surviving stand of dipterocarp trees.We also spell out the necessary policy-changes in overall development strategy that should stem the ongoing decimation of biodiversity. These include (1) revitalizing community-based systems of sustainable management of village forests and protection of sacred groves and trees; (2) reorienting the usage-pattern of reserve forests from production of a limited variety of timber and softwood species for industrial consumers, to production of a larger diversity of non-wood forest produce of commercial value to support the rural economy; (3) utilizing marginal lands under private ownership for generating industrial wood supplies; and (4) provision of incentives for in situ maintenance of land-races of cultivated plants - especially evergreen, fruit-yielding trees - by the local people.It is proposed that this broad framework be now taken to the local communities, and that an action-plan be developed on the basis of inputs provided - and initiatives taken - by them.

A monolithic strategy for fluid-structure interaction problems

In this work, we present a new monolithic strategy for solving fluid-structure interaction problems involving incompressible fluids, within the context of the finite element method. This strategy, similar to the continuum dynamics, conserves certain properties, and thus provides a rational basis for the design of the time-stepping strategy; detailed proofs of the conservation of these properties are provided. The proposed algorithm works with displacement and velocity variables for the structure and fluid, respectively, and introduces no new variables to enforce velocity or traction continuity. Any existing structural dynamics algorithm can be used without change in the proposed method. Use of the exact tangent stiffness matrix ensures that the algorithm converges quadratically within each time step. An analytical solution is presented for one of the benchmark problems used in the literature, namely, the piston problem. A number of benchmark problems including problems involving free surfaces such as sloshing and the breaking dam problem are used to demonstrate the good performance of the proposed method. Copyright (C) 2010 John Wiley & Sons, Ltd.

Radical Annulation Strategy to Chiral Pupukeanones: Total Synthesis of (+)-10-ex&l(- Naphthyl)pupukean-9-onea nd (+)-lO-exo-l(- Naphthyl)-5-epipupukean-9-ones1

Intramolecular alkylation reaction of the bromoenone 12, obtained from S-carvone in three steps, furnished the bicyclo[2.2.2]octenone 13. Contrary to the anticipated radical annulation reaction, the bicyclic bromides 14 and 15, obtained from the enone 13, generated exclusively the cyclopropane product 18 via a 3-exo-trig radical cyclization on reaction with nBu3SnH and AIBN, even in the presence of a large excess of a radicophile. On the other hand, bromoenone 24, synthesized from R-carvone via S-naphthylcarvone 21, underwent radical annulation reaction in the presence of radicophiles to furnish the isotwistanes 25-28 in a regio- and stereospecific manner. Hydrogenation of the olefin 34, obtained from the diketone 27 via a regiospecific Wittig reaction, furnished the naphthyl-5-epipupukean-9-one 33, whereas stereoselective hydrogenation of the enone 36, prepared from the keto ester 25 via a Grignard reaction and dehydration sequence, generated the naphthylpupukeanone 32.

Speedup Macroblock Mode Decision in H.264/SVC Encoding Using Cost-Sensitive Learning

In this paper we present a novel macroblock mode decision algorithm to speedup H.264/SVC Intra frame encoding. We replace the complex mode-decision calculations by a classifier which has been trained specifically to minimize the reduction in RD performance. This results in a significant speedup in encoding. The results show that machine learning has a great potential and can reduce the complexity substantially with negligible impact on quality. The results show that the proposed method reduces encoding time to about 70% in base layer and up to 50% in enhancement layer of the reference implementation with a negligible loss in quality.

A regiospecific radical annulation strategy to functionalised chiral bicyclo[3.3.l]nonanes

A radical annulation, i.e. an intermolecular radical Michael addition followed by an intramolecular Michael addition of the resultant radical (radical cyclisation) has been employed for the construction of chiral functionalised bicyclo[3.3,1]-nonanes. Thus reaction of carvone hydrohalides 7 with (n)Bu(3)SnH and AIBN in the presence of excess of radicophiles 4 furnished, regiospecifically bicyclo[3.3.1]nonanes 8-14, introducing three new chiral centres in a stereoselective manner. Analogously the bromide 18 generated the bridgehead substituted bicyclo[3.3.1]-nonanes 19-21.

An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes

We develop in this article the first actor-critic reinforcement learning algorithm with function approximation for a problem of control under multiple inequality constraints. We consider the infinite horizon discounted cost framework in which both the objective and the constraint functions are suitable expected policy-dependent discounted sums of certain sample path functions. We apply the Lagrange multiplier method to handle the inequality constraints. Our algorithm makes use of multi-timescale stochastic approximation and incorporates a temporal difference (TD) critic and an actor that makes a gradient search in the space of policy parameters using efficient simultaneous perturbation stochastic approximation (SPSA) gradient estimates. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal policy. (C) 2010 Elsevier B.V. All rights reserved.

Mining Land Cover Information Using Multilayer Perceptron and Decision Tree from MODIS Data

Land cover (LC) changes play a major role in global as well as at regional scale patterns of the climate and biogeochemistry of the Earth system. LC information presents critical insights in understanding of Earth surface phenomena, particularly useful when obtained synoptically from remote sensing data. However, for developing countries and those with large geographical extent, regular LC mapping is prohibitive with data from commercial sensors (high cost factor) of limited spatial coverage (low temporal resolution and band swath). In this context, free MODIS data with good spectro-temporal resolution meet the purpose. LC mapping from these data has continuously evolved with advances in classification algorithms. This paper presents a comparative study of two robust data mining techniques, the multilayer perceptron (MLP) and decision tree (DT) on different products of MODIS data corresponding to Kolar district, Karnataka, India. The MODIS classified images when compared at three different spatial scales (at district level, taluk level and pixel level) shows that MLP based classification on minimum noise fraction components on MODIS 36 bands provide the most accurate LC mapping with 86% accuracy, while DT on MODIS 36 bands principal components leads to less accurate classification (69%).

Multi-Agent Rendezvous Algorithm with Rectilinear Decision Domain

The aim of this paper is to develop a computationally efficient decentralized rendezvous algorithm for a group of autonomous agents. The algorithm generalizes the notion of sensor domain and decision domain of agents to enable implementation of simple computational algorithms. Specifically, the algorithm proposed in this paper uses a rectilinear decision domain (RDD) as against the circular decision domain assumed in earlier work. Because of this, the computational complexity of the algorithm reduces considerably and, when compared to the standard Ando's algorithm available in the literature, the RDD algorithm shows very significant improvement in convergence time performance. Analytical results to prove convergence and supporting simulation results are presented in the paper.

Positional Consensus of Multi-Agent Systems Using Linear Programming Based Decentralized Control with Rectilinear Decision Domain

In this paper we develop a Linear Programming (LP) based decentralized algorithm for a group of multiple autonomous agents to achieve positional consensus. Each agent is capable of exchanging information about its position and orientation with other agents within their sensing region. The method is computationally feasible and easy to implement. Analytical results are presented. The effectiveness of the approach is illustrated with simulation results.

An Efficient Random Walk Strategy for Sampling Based Robot Motion Planners

Sampling based planners have been successful in path planning of robots with many degrees of freedom, but still remains ineffective when the configuration space has a narrow passage. We present a new technique based on a random walk strategy to generate samples in narrow regions quickly, thus improving efficiency of Probabilistic Roadmap Planners. The algorithm substantially reduces instances of collision checking and thereby decreases computational time. The method is powerful even for cases where the structure of the narrow passage is not known, thus giving significant improvement over other known methods.