Unified detection and tracking of instruments during retinal microsurgery

Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not naturally take advantage of target motion continuity during detection. The advantage of local optimization is efficiency and accuracy, but it requires additional algorithms to initialize tracking when the target is lost. To bridge these two approaches, we propose a framework for unified detection and tracking as a time-series Bayesian estimation problem. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a target in each frame. To do this we integrate the Active Testing (AT) paradigm with Bayesian filtering, and this results in a framework capable of both detecting and tracking robustly in situations where the target object enters and leaves the field of view regularly. We demonstrate our approach on a retinal tool tracking problem and show through extensive experiments that our method provides an efficient and robust tracking solution.

Dexmedetomidine versus standard care sedation with propofol or midazolam in intensive care: an economic evaluation.

INTRODUCTION Dexmedetomidine was shown in two European randomized double-blind double-dummy trials (PRODEX and MIDEX) to be non-inferior to propofol and midazolam in maintaining target sedation levels in mechanically ventilated intensive care unit (ICU) patients. Additionally, dexmedetomidine shortened the time to extubation versus both standard sedatives, suggesting that it may reduce ICU resource needs and thus lower ICU costs. Considering resource utilization data from these two trials, we performed a secondary, cost-minimization analysis assessing the economics of dexmedetomidine versus standard care sedation. METHODS The total ICU costs associated with each study sedative were calculated on the basis of total study sedative consumption and the number of days patients remained intubated, required non-invasive ventilation, or required ICU care without mechanical ventilation. The daily unit costs for these three consecutive ICU periods were set to decline toward discharge, reflecting the observed reduction in mean daily Therapeutic Intervention Scoring System (TISS) points between the periods. A number of additional sensitivity analyses were performed, including one in which the total ICU costs were based on the cumulative sum of daily TISS points over the ICU period, and two further scenarios, with declining direct variable daily costs only. RESULTS Based on pooled data from both trials, sedation with dexmedetomidine resulted in lower total ICU costs than using the standard sedatives, with a difference of €2,656 in the median (interquartile range) total ICU costs-€11,864 (€7,070 to €23,457) versus €14,520 (€7,871 to €26,254)-and €1,649 in the mean total ICU costs. The median (mean) total ICU costs with dexmedetomidine compared with those of propofol or midazolam were €1,292 (€747) and €3,573 (€2,536) lower, respectively. The result was robust, indicating lower costs with dexmedetomidine in all sensitivity analyses, including those in which only direct variable ICU costs were considered. The likelihood of dexmedetomidine resulting in lower total ICU costs compared with pooled standard care was 91.0% (72.4% versus propofol and 98.0% versus midazolam). CONCLUSIONS From an economic point of view, dexmedetomidine appears to be a preferable option compared with standard sedatives for providing light to moderate ICU sedation exceeding 24 hours. The savings potential results primarily from shorter time to extubation. TRIAL REGISTRATION ClinicalTrials.gov NCT00479661 (PRODEX), NCT00481312 (MIDEX).

A total variation discontinuous Galerkin approach for image restoration

The focal point of this paper is to propose and analyze a P 0 discontinuous Galerkin (DG) formulation for image denoising. The scheme is based on a total variation approach which has been applied successfully in previous papers on image processing. The main idea of the new scheme is to model the restoration process in terms of a discrete energy minimization problem and to derive a corresponding DG variational formulation. Furthermore, we will prove that the method exhibits a unique solution and that a natural maximum principle holds. In addition, a number of examples illustrate the effectiveness of the method.

Digital vs. conventional implant prosthetic workflows: a cost/time analysis.

OBJECTIVES The aim of this prospective cohort trial was to perform a cost/time analysis for implant-supported single-unit reconstructions in the digital workflow compared to the conventional pathway. MATERIALS AND METHODS A total of 20 patients were included for rehabilitation with 2 × 20 implant crowns in a crossover study design and treated consecutively each with customized titanium abutments plus CAD/CAM-zirconia-suprastructures (test: digital) and with standardized titanium abutments plus PFM-crowns (control conventional). Starting with prosthetic treatment, analysis was estimated for clinical and laboratory work steps including measure of costs in Swiss Francs (CHF), productivity rates and cost minimization for first-line therapy. Statistical calculations were performed with Wilcoxon signed-rank test. RESULTS Both protocols worked successfully for all test and control reconstructions. Direct treatment costs were significantly lower for the digital workflow 1815.35 CHF compared to the conventional pathway 2119.65 CHF [P = 0.0004]. For subprocess evaluation, total laboratory costs were calculated as 941.95 CHF for the test group and 1245.65 CHF for the control group, respectively [P = 0.003]. The clinical dental productivity rate amounted to 29.64 CHF/min (digital) and 24.37 CHF/min (conventional) [P = 0.002]. Overall, cost minimization analysis exhibited an 18% cost reduction within the digital process. CONCLUSION The digital workflow was more efficient than the established conventional pathway for implant-supported crowns in this investigation.

Game Theoretic Bidding Strategies for Auctions in Green Electricity Markets

Electricity markets in the United States presently employ an auction mechanism to determine the dispatch of power generation units. In this market design, generators submit bid prices to a regulation agency for review, and the regulator conducts an auction selection in such a way that satisfies electricity demand. Most regulators currently use an auction selection method that minimizes total offer costs ["bid cost minimization" (BCM)] to determine electric dispatch. However, recent literature has shown that this method may not minimize consumer payments, and it has been shown that an alternative selection method that directly minimizes total consumer payments ["payment cost minimization" (PCM)] may benefit social welfare in the long term. The objective of this project is to further investigate the long term benefit of PCM implementation and determine whether it can provide lower costs to consumers. The two auction selection methods are expressed as linear constraint programs and are implemented in an optimization software package. Methodology for game theoretic bidding simulation is developed using EMCAS, a real-time market simulator. Results of a 30-day simulation showed that PCM reduced energy costs for consumers by 12%. However, this result will be cross-checked in the future with two other methods of bid simulation as proposed in this paper.

Input Price Variation Across Locations and a Generalized Measure of Cost Efficiency

We propose a nonparametric model for global cost minimization as a framework for optimal allocation of a firm's output target across multiple locations, taking account of differences in input prices and technologies across locations. This should be useful for firms planning production sites within a country and for foreign direct investment decisions by multi-national firms. Two illustrative examples are included. The first example considers the production location decision of a manufacturing firm across a number of adjacent states of the US. In the other example, we consider the optimal allocation of US and Canadian automobile manufacturers across the two countries.

Environmental sustainability and the human element: Decision making in National Cancer Institute-designated cancer centers and Practice Greenhealth subscribing institutions

Background. Various aspects of sustainability have taken root in the hospital environment; however, decisions to pursue sustainable practices within the framework of a master plan are not fully developed in National Cancer Institute (NCI) -designated cancer centers and subscribing institutions to the Practice Greenhealth (PGH) listserv.^ Methods. This cross sectional study was designed to identify the organizational characteristics each study group pursed to implement sustainability practices, describe the barriers they encountered and reasons behind their choices for undertaking certain sustainability practices. A web-based questionnaire was pilot tested, and then sent out to 64 NCI-designated cancer centers and 1638 subscribing institutions to the PGH listserv.^ Results. Complete responses were received from 39 NCI-designated cancer centers and 58 subscribing institutions to the PGH listserv. NCI-designated cancer centers reported greater progress in integrating sustainability criteria into design and construction projects than hospitals of institutions subscribing to the PHG listserv (p-value = <0.05). Statistically significant differences were also identified between these two study groups in undertaking work life options, conducting energy usage assessments, developing energy conservation and optimization plans, implementing solid waste and hazardous waste minimization programs, using energy efficient vehicles and reporting sustainability progress to external stakeholders. NCI-designated cancer centers were further along in implementing these programs (p-value = <0.05). In comparing the self-identified NCI-designated cancer centers to centers that indicated they were both and NCI and PGH, the later had made greater progress in using their collective buying power to pursue sustainable purchasing practices within the medical community (p-value = <0.05). In both study groups, recycling programs were well developed.^ Conclusions. Employee involvement was viewed as the most important reason for both study groups to pursue recycling initiatives and incorporated environmental criteria into purchasing decisions. A written sustainability commitment did not readily translate into a high percentage that had developed a sustainability master plan. Coordination of sustainability programs through a designated sustainability professional was not being undertaken by a large number of institutions within each study group. This may be due to the current economic downturn or management's attention to the emerging health care legislation being debated in congress. ^ Lifecycle assessments, an element of a carbon footprint, are seen as emerging areas of opportunity for health care institutions that can be used to evaluate the total lifecycle costs of products and services.^

A Logarithmic Image Prior for Blind Deconvolution

Blind Deconvolution consists in the estimation of a sharp image and a blur kernel from an observed blurry image. Because the blur model admits several solutions it is necessary to devise an image prior that favors the true blur kernel and sharp image. Many successful image priors enforce the sparsity of the sharp image gradients. Ideally the L0 “norm” is the best choice for promoting sparsity, but because it is computationally intractable, some methods have used a logarithmic approximation. In this work we also study a logarithmic image prior. We show empirically how well the prior suits the blind deconvolution problem. Our analysis confirms experimentally the hypothesis that a prior should not necessarily model natural image statistics to correctly estimate the blur kernel. Furthermore, we show that a simple Maximum a Posteriori formulation is enough to achieve state of the art results. To minimize such formulation we devise two iterative minimization algorithms that cope with the non-convexity of the logarithmic prior: one obtained via the primal-dual approach and one via majorization-minimization.

Legal Aspects which Implement Good Practice Measures in the Management of Construction and Demolition Waste

The construction industry, one of the most important ones in the development of a country, generates unavoidable impacts on the environment. The social demand towards greater respect for the environment is a high and general outcry. Therefore, the construction industry needs to reduce the impact it produces. Proper waste management is not enough; we must take a further step in environmental management, where new measures need to be introduced for the prevention at source, such as good practices to promote recycling. Following the amendment of the legal frame applicable to Construction and Demolition Waste (C&D waste), important developments have been incorporated in European and International laws, aiming to promote the culture of reusing and recycling. This change of mindset, that is progressively taking place in society, is allowing for the consideration of C&D waste no longer as an unusable waste, but as a reusable material. The main objective of the work presented in this paper is to enhance C&D waste management systems through the development of preventive measures during the construction process. These measures concern all the agents intervening in the construction process as only the personal implication of all of them can ensure an efficient management of the C&D waste generated. Finally, a model based on preventive measures achieves organizational cohesion between the different stages of the construction process, as well as promoting the conservation of raw materials through the use and waste minimization. All of these in order to achieve a C&D waste management system, whose primary goal is zero waste generation

A Generalized Regression Methodology for Bivariate Heteroscedastic Data

We present a methodology for reducing a straight line fitting regression problem to a Least Squares minimization one. This is accomplished through the definition of a measure on the data space that takes into account directional dependences of errors, and the use of polar descriptors for straight lines. This strategy improves the robustness by avoiding singularities and non-describable lines. The methodology is powerful enough to deal with non-normal bivariate heteroscedastic data error models, but can also supersede classical regression methods by making some particular assumptions. An implementation of the methodology for the normal bivariate case is developed and evaluated.

Explicitly Context-Aware Publish/Subscribe with Context-Invariant Subscriptions

Although context could be exploited to improve the performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) model of communication, only very few works have explored domains with highly dynamic context, whereas most adopted models are context agnostic. In this paper, we present the key design principles underlying a novel context-aware content-based P/S (CA-CBPS) model of communication, where the context is explicitly managed, focusing on the minimization of network overhead in domains with recurrent context changes thanks to contextual scoping. We highlight how we dealt with the main shortcomings of most of the current approaches. Our research is some of the first to study the problem of explicitly introducing context-awareness into the P/S model to capitalize on contextual information. The envisioned CA-CBPS middleware enables the cloud ecosystem of services to communicate very efficiently, in a decoupled, but contextually scoped fashion.

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems.

Removing superfluous versions in polyvariant specialization of prolog programs.

Polyvariant specialization allows generating múltiple versions of a procedure, which can then be separately optimized for different uses. Since allowing a high degree of polyvariance often results in more optimized code, polyvariant specializers, such as most partial evaluators, can genérate a large number of versions. This can produce unnecessarily large residual programs. Also, large programs can be slower due to cache miss effects. A possible solution to this problem is to introduce a minimization step which identifies sets of equivalent versions, and replace all occurrences of such versions by a single one. In this work we present a unifying view of the problem of superfluous polyvariance. It includes both partial deduction and abstract múltiple specialization. As regards partial deduction, we extend existing approaches in several ways. First, previous work has dealt with puré logic programs and a very limited class of builtins. Herein we propose an extensión to traditional characteristic trees which can be used in the presence of calis to external predicates. This includes all builtins, librarles, other user modules, etc. Second, we propose the possibility of collapsing versions which are not strictly equivalent. This allows trading time for space and can be useful in the context of embedded and pervasive systems. This is done by residualizing certain computations for external predicates which would otherwise be performed at specialization time. Third, we provide an experimental evaluation of the potential gains achievable using minimization which leads to interesting conclusions.

A Model of Emotion as Patterned Metacontrol

Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1.

Energy Analysis of Bare Electrodynamic Tethers

The design of an electrodynamic tether is a complex task that involves the control of dynamic instabilities, optimization of the generated power (or the descent time in deorbiting missions), and minimization of the tether mass. The electrodynamic forces on an electrodynamic tether are responsible for variations in the mechanical energy of the tethered system and can also drive the system to dynamic instability. Energy sources and sinks in this system include the following: 1) ionospheric impedance, 2) the potential drop at the cathodic contactor, 3) ohmic losses in the tether, 4) the corotational plasma electric field, and 5) generated power and/or 6) input power. The analysis of each of these energy components, or bricks, establishes parameters that are useful tools for tether design. In this study, the nondimensional parameters that govern the orbital energy variation, dynamic instability, and power generation were characterized, and their mutual interdependence was established. A space-debris mitigation mission was taken as an example of this approach for the assessment of tether performance. Numerical simulations using a dumbbell model for tether dynamics, the International Geomagnetic Reference Field for the geomagnetic field, and the International Reference Ionosphere for the ionosphere were performed to test the analytical approach. The results obtained herein stress the close relationships that exist among the velocity of descent, dynamic stability, and generated power. An optimal tether design requires a detailed tradeoff among these performances in a real-world scenario.