Pentafecta: A New Concept for Reporting Outcomes of Robot-Assisted Laparoscopic Radical Prostatectomy

Background: Widespread use of prostate-specific antigen screening has resulted in younger and healthier men being diagnosed with prostate cancer. Their demands and expectations of surgical intervention are much higher and cannot be adequately addressed with the classic trifecta outcome measures. Objective: A new and more comprehensive method for reporting outcomes after radical prostatectomy, the pentafecta, is proposed. Design, setting, and participants: From January 2008 through September 2009, details of 1111 consecutive patients who underwent robot-assisted radical prostatectomy performed by a single surgeon were retrospectively analyzed. Of 626 potent men, 332 who underwent bilateral nerve sparing and who had 1 yr of follow-up were included in the study group. Measurements: In addition to the traditional trifecta outcomes, two perioperative variables were included in the pentafecta: no postoperative complications and negative surgical margins. Patients who attained the trifecta and concurrently the two additional outcomes were considered as having achieved the pentafecta. A logistic regression model was created to evaluate independent factors for achieving the pentafecta. Results and limitations: Continence, potency, biochemical recurrence-free survival, and trifecta rates at 12 mo were 96.4%, 89.8%, 96.4%, and 83.1%, respectively. With regard to the perioperative outcomes, 93.4% had no postoperative complication and 90.7% had negative surgical margins. The pentafecta rate at 12 mo was 70.8%. On multivariable analysis, patient age (p = 0.001) was confirmed as the only factor independently associated with the pentafecta. Conclusions: A more comprehensive approach for reporting prostate surgery outcomes, the pentafecta, is being proposed. We believe that pentafecta outcomes more accurately represent patients` expectations after minimally invasive surgery for prostate cancer. This approach may be beneficial and may be used when counseling patients with clinically localized disease. (C) 2011 European Association of Urology. Published by Elsevier B. V. All rights reserved.

Recognition by toll-like receptor 2 induces antigen-presenting cell activation and Th1 programming during infection by Neospora caninum

Neospora caninum is an apicomplexan parasite responsible for major economic losses due to abortions in cattle. Toll-like receptors (TLRs) sense specific microbial products and direct downstream signaling pathways in immune cells, linking innate, and adaptive immunity. Here, we analyze the role of TLR2 on innate and adaptive immune responses during N. caninum infection. Inflammatory peritoneal macrophages and bone marrow-derived dendritic cells exposed to N. caninum-soluble antigens presented an upregulated expression of TLR2. Increased receptor expression was correlated to TLR2/MyD88-dependent antigen-presenting cell maturation and pro-inflammatory cytokine production after stimulation by antigens. Impaired innate responses observed after infection of mice genetically deficient for TLR2((-/-)) was followed by downregulation of adaptive T helper 1 (Th1) immunity, represented by diminished parasite-specific CD4(+) and CD8(+) T-cell proliferation, IFN-gamma:interleukin (IL)-10 ratio, and IgG subclass synthesis. In parallel, TLR2(-/-) mice presented higher parasite burden than wild-type (WT) mice at acute and chronic stages of infection. These results show that initial recognition of N. caninum by TLR2 participates in the generation of effector immune responses against N. caninum and imply that the receptor may be a target for future prophylactic strategies against neosporosis. Immunology and Cell Biology (2010) 88, 825-833; doi:10.1038/icb.2010.52; published online 20 April 2010

MapScript: A map algebra programming language incorporating neighborhood analysis

Map algebra is a data model and simple functional notation to study the distribution and patterns of spatial phenomena. It uses a uniform representation of space as discrete grids, which are organized into layers. This paper discusses extensions to map algebra to handle neighborhood operations with a new data type called a template. Templates provide general windowing operations on grids to enable spatial models for cellular automata, mathematical morphology, and local spatial statistics. A programming language for map algebra that incorporates templates and special processing constructs is described. The programming language is called MapScript. Example program scripts are presented to perform diverse and interesting neighborhood analysis for descriptive, model-based and processed-based analysis.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

An optical flow-based sensing system for reactive mobile robot navigation

This work discusses the use of optical flow to generate the sensorial information a mobile robot needs to react to the presence of obstacles when navigating in a non-structured environment. A sensing system based on optical flow and time-to-collision calculation is here proposed and experimented, which accomplishes two important paradigms. The first one is that all computations are performed onboard the robot, in spite of the limited computational capability available. The second one is that the algorithms for optical flow and time-to-collision calculations are fast enough to give the mobile robot the capability of reacting to any environmental change in real-time. Results of real experiments in which the sensing system here proposed is used as the only source of sensorial data to guide a mobile robot to avoid obstacles while wandering around are presented, and the analysis of such results allows validating the proposed sensing system.

Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach

This paper is on the problem of short-term hydro, scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach.

Addressing the facilities layout design problem through constraint logic programming

One of the most difficult problems that face researchers experimenting with complex systems in real world applications is the Facility Layout Design Problem. It relies with the design and location of production lines, machinery and equipment, inventory storage and shipping facilities. In this work it is intended to address this problem through the use of Constraint Logic Programming (CLP) technology. The use of Genetic Algorithms (GA) as optimisation technique in CLP environment is also an issue addressed. The approach aims the implementation of genetic algorithm operators following the CLP paradigm.

Hybrid fuzzy Monte Carlo and logic programming model for distribution network reconfiguration in the presence of outages

This paper presents a methodology for distribution networks reconfiguration in outage presence in order to choose the reconfiguration that presents the lower power losses. The methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modelling for system component outage parameters. Fuzzy membership functions of system component outage parameters are obtained by statistical records. A hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. Once obtained the system states by Monte Carlo simulation, a logical programming algorithm is applied to get all possible reconfigurations for every system state. In order to evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation a distribution power flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology to a practical case, the paper includes a case study that considers a real distribution network.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Simulação e programação offline de robôs industriais afectos a tarefas de lixagem

Este trabalho teve o intuito de testar a viabilidade da programação offline para tarefas de lixamento na empresa Grohe Portugal. Para tal era necessário perceber o que é a programação offline e para isso foi efectuada uma pesquisa referente a essa temática, onde ficou evidente que a programação offline é em tudo semelhante à programação online, tendo apenas como principal diferença o facto de não usar o robô propriamente dito durante o desenvolvimento do programa. Devido à ausência do robô, a programação offline exige que se conheça detalhadamente a célula de trabalho, bem como todas as entradas e saídas associadas à célula, sendo que o conhecimento das entradas e saídas pode ser contornada carregando um backup do robô ou carregando os módulos de sistema. No entanto os fabricantes habitualmente não fornecem informação detalhada sobre as células de trabalho, o que dificulta o processo de implementação da unidade no modelo 3D para a programação offline. Após este estudo inicial, foi efectuado um estudo das características inerentes a cada uma das células existentes, com o objectivo de se obter uma melhor percepção de toda a envolvente relacionada com as tarefas de lixamento. Ao longo desse estudo efectuaram-se vários testes para validar os diversos programas desenvolvidos, bem como para testar a modelação 3D efectuada. O projecto propriamente dito consistiu no desenvolvimento de programas offline de forma a minimizar o impacto (em especial o tempo de paragem) da programação de novos produtos. Todo o trabalho de programação era até então feito utilizando o robô, o que implicava tempos de paragem que podiam ser superiores a três dias. Com o desenvolvimento dos programas em modo offline conseguiu-se reduzir esse tempo de paragem dos robôs para pouco mais de um turno (8h), existindo apenas a necessidade de efectuar algumas afinações e correcções nos movimentos de entrada, saída e movimentações entre rotinas e unidades, uma vez que estes movimentos são essenciais ao bom acabamento da peça e convém que seja suaves. Para a realização e conclusão deste projecto foram superadas diversas etapas, sendo que as mais relevantes foram: - A correcta modelação 3D da célula, tendo em conta todo o cenário envolvente, para evitar colisões do robô com a célula; - A adaptação da programação offline para uma linguagem mais usual aos afinadores, ou seja, efectuar a programação com targets inline e criar diferentes rotinas para cada uma das partes da peça, facilitando assim a afinação; - A habituação à programação recorrendo apenas ao uso de módulos para transferir os programas para a célula, bem como a utilização de entradas, saídas e algumas rotinas e funcionalidades já existentes.