Conservative fluid management or deresuscitation for patients with sepsis or acute respiratory distress syndrome following the resuscitation phase of critical illness: a systematic review and meta-analysis

Background

It is unknown whether a conservative approach to fluid administration or deresuscitation (active removal of fluid using diuretics or renal replacement therapy) is beneficial following haemodynamic stabilisation of critically ill patients.

Purpose

To evaluate the efficacy and safety of conservative or deresuscitative fluid strategies in adults and children with acute respiratory distress syndrome (ARDS), sepsis or systemic inflammatory response syndrome (SIRS) in the post-resuscitation phase of critical illness.

Methods

We searched Medline, EMBASE and the Cochrane central register of controlled trials from 1980 to June 2016, and manually reviewed relevant conference proceedings from 2009 to the present. Two reviewers independently assessed search results for inclusion and undertook data extraction and quality appraisal. We included randomised trials comparing fluid regimens with differing fluid balances between groups, and observational studies investigating the relationship between fluid balance and clinical outcomes.

Results

Forty-nine studies met the inclusion criteria. Marked clinical heterogeneity was evident. In a meta-analysis of 11 randomised trials (2051 patients) using a random-effects model, we found no significant difference in mortality with conservative or deresuscitative strategies compared with a liberal strategy or usual care [pooled risk ratio (RR) 0.92, 95 % confidence interval (CI) 0.82–1.02, I2 = 0 %]. A conservative or deresuscitative strategy resulted in increased ventilator-free days (mean difference 1.82 days, 95 % CI 0.53–3.10, I2 = 9 %) and reduced length of ICU stay (mean difference −1.88 days, 95 % CI −0.12 to −3.64, I2 = 75 %) compared with a liberal strategy or standard care.

Conclusions

In adults and children with ARDS, sepsis or SIRS, a conservative or deresuscitative fluid strategy results in an increased number of ventilator-free days and a decreased length of ICU stay compared with a liberal strategy or standard care. The effect on mortality remains uncertain. Large randomised trials are needed to determine optimal fluid strategies in critical illness.

Improved Implicit Optimal Modeling of the Labor Shift Scheduling Problem

This paper presents an integer programming model for developing optimal shift schedules while allowing extensive flexibility in terms of alternate shift starting times, shift lengths, and break placement. The model combines the work of Moondra (1976) and Bechtold and Jacobs (1990) by implicitly matching meal breaks to implicitly represented shifts. Moreover, the new model extends the work of these authors to enable the scheduling of overtime and the scheduling of rest breaks. We compare the new model to Bechtold and Jacobs' model over a diverse set of 588 test problems. The new model generates optimal solutions more rapidly, solves problems with more shift alternatives, and does not generate schedules violating the operative restrictions on break timing.

Ancient clam gardens, traditional management portfolios, and the resilience of coupled human-ocean systems

Indigenous communities have actively managed their environments for millennia using a diversity of resource use and conservation strategies. Clam gardens, ancient rock-walled intertidal beach terraces, represent one example of an early mariculture technology that may have been used to improve food security and confer resilience to coupled human-ocean systems. We surveyed a coastal landscape for evidence of past resource use and management to gain insight into ancient resource stewardship practices on the central coast of British Columbia, Canada. We found that clam gardens are embedded within a diverse portfolio of resource use and management strategies and were likely one component of a larger, complex resource management system. We compared clam diversity, density, recruitment, and biomass in three clam gardens and three unmodified nonwalled beaches. Evidence suggests that butter clams (Saxidomus gigantea) had 1.96 times the biomass and 2.44 times the density in clam gardens relative to unmodified beaches. This was due to a reduction in beach slope and thus an increase in the optimal tidal range where clams grow and survive best. The most pronounced differences in butter clam density between nonwalled beaches and clam gardens were found at high tidal elevations at the top of the beach. Finally, clam recruits (0.5-2 mm in length) tended to be greater in clam gardens compared to nonwalled beaches and may be attributed to the addition of shell hash by ancient people, which remains on the landscape today. As part of a broader social-ecological system, clam garden sites were among several modifications made by humans that collectively may have conferred resilience to past communities by providing reliable and diverse access to food resources.

Diagnostic Tests and their Application in the Management of Soil- and Water-borne Oomycete Pathogen Species

Oomycete diseases cause significant losses across a broad range of crop and aquaculture commodities worldwide. These losses can be greatly reduced by disease management practices steered by accurate and early diagnoses of pathogen presence. Determinations of disease potential can help guide optimal crop rotation regimes, varietal selections, targeted control measures, harvest timings and crop post-harvest handling. Pathogen detection prior to infection can also reduce the incidence of disease epidemics. Classical methods for the isolation of oomycete pathogens are normally deployed only after disease symptom appearance. These processes are often-time consuming, relying on culturing the putative pathogen(s) and the availability of expert taxonomic skills for accurate identification; a situation that frequently results in either delayed application, or routine ‘blanket’ over-application of control measures. Increasing concerns about pesticides in the environment and the food chain, removal or restriction of their usage combined with rising costs have focussed interest in the development and improvement of disease management systems. To be effective, these require timely, accurate and preferably quantitatve diagnoses. A wide range of rapid diagnostic tools, from point of care immunodiagnostic kits to next generation nucleotide sequencing have potential application in oomycete disease management. Here we review currently-available as well as promising new technologies in the context of commercial agricultural production systems, considering the impacts of specific biotic and abiotic and other important factors such as speed and ease of access to information and cost effectiveness

Skapandet av ett webbaserat ärendehanteringssystem för affärssystemet Pyramid med Scrum : Creation of a web based case management system for the business system Pyramid with Scrum

The business system known as Pyramid does today not provide its user with a reasonable system regarding case management for support issues. The current system in place requires the customer to contact its provider via telephone to register new cases. In addition to this, current system doesn’t include any way for the user to view any of their current cases without contacting the provider.A solution to this issue is to migrate the current case management system from a telephone contact to a web based platform, where customers could easier access their current cases, but also directly through the website create new cases. This new system would reduce the time required to manually manage each individual case, for both customer and provider, resulting in an overall reduction in cost for both parties.The result is a system divided into two different sections, the first one is an API created in Pyramid that acts as a web service, and the second one a website which customers can connect to. The website will allow users to overview their current cases, but also the option to create new cases directly through the site. All the information used to the website is obtained through the web service inside Pyramid. Analyzing the final design of the system, the developers where able to conclude both positive and negative aspects of the systems’ final design. If the platform chosen was the optimal choice or not, and also what can be include if the system is further developed, will be discussed.The development process and the method used during development will also be analyzed and discussed, what positive and negative aspects that where encountered. In addition to this the cause and effect of a development team smaller than the suggested size will also be analyzed. Lastly an analysis of actions that could’ve been made in order to prevent certain issues from occurring will.

An iterative analytical design framework for the optimal designing of an off-grid renewable energy based hybrid smart micro-grid

Creative ways of utilising renewable energy sources in electricity generation especially in remote areas and particularly in countries depending on imported energy, while increasing energy security and reducing cost of such isolated off-grid systems, is becoming an urgently needed necessity for the effective strategic planning of Energy Systems. The aim of this research project was to design and implement a new decision support framework for the optimal design of hybrid micro grids considering different types of different technologies, where the design objective is to minimize the total cost of the hybrid micro grid while at the same time satisfying the required electric demand. Results of a comprehensive literature review, of existing analytical, decision support tools and literature on HPS, has identified the gaps and the necessary conceptual parts of an analytical decision support framework. As a result this research proposes and reports an Iterative Analytical Design Framework (IADF) and its implementation for the optimal design of an Off-grid renewable energy based hybrid smart micro-grid (OGREH-SμG) with intra and inter-grid (μG2μG & μG2G) synchronization capabilities and a novel storage technique. The modelling design and simulations were based on simulations conducted using HOMER Energy and MatLab/SIMULINK, Energy Planning and Design software platforms. The design, experimental proof of concept, verification and simulation of a new storage concept incorporating Hydrogen Peroxide (H2O2) fuel cell is also reported. The implementation of the smart components consisting Raspberry Pi that is devised and programmed for the semi-smart energy management framework (a novel control strategy, including synchronization capabilities) of the OGREH-SμG are also detailed and reported. The hybrid μG was designed and implemented as a case study for the Bayir/Jordan area. This research has provided an alternative decision support tool to solve Renewable Energy Integration for the optimal number, type and size of components to configure the hybrid μG. In addition this research has formulated and reported a linear cost function to mathematically verify computer based simulations and fine tune the solutions in the iterative framework and concluded that such solutions converge to a correct optimal approximation when considering the properties of the problem. As a result of this investigation it has been demonstrated that, the implemented and reported OGREH-SμG design incorporates wind and sun powered generation complemented with batteries, two fuel cell units and a diesel generator is a unique approach to Utilizing indigenous renewable energy with a capability of being able to synchronize with other μ-grids is the most effective and optimal way of electrifying developing countries with fewer resources in a sustainable way, with minimum impact on the environment while also achieving reductions in GHG. The dissertation concludes with suggested extensions to this work in the future.

Life cycle management of TVO nuclear power plant

Tämä diplomityö tutkii eri elinkaarihallinnan menetelmiä ja vertaa niitä TVO:n menetelmiin. Lisäksi TVO:n prosessin ongelmakohdat tunnistetaan ja niihin esitetään ratkaisuja. Vertailukohteina toimii ydinvoimateollisuuden lisäksi vesivoima, fossiiliset voimalaitokset sekä paperiteollisuus. Sähkön hinnan jatkaessa laskuaan on elinkaariajattelusta tullut ajankohtaista myös ydinvoimayhtiöille. Ydinvoimalaitoksien pitkän suunnitellun käyttöiän ansiosta laitoksen elinkaaren aikana voi tapahtua useita asioita, jotka vaikuttavat laitoksen investointitarpeisiin. Turvallisen sähköntuotannon varmistamiseksi eri laitososia on joko muokattava tai uusittava. Elinkaariajatteluun kuuluu tehokas laitoksen kunnon valvonta, laitoksen ikääntymiseen vaikuttavien ilmiöiden tunnistaminen, sekä ikääntymistä hillitsevien toimenpiteiden pitkän tähtäimen suunnittelu. Hyvällä ennakkosuunnittelulla pyritään varmistamaan se, että laitoksella voidaan tuottaa sähköä koko sen jäljellä olevan käyttöiän aikana. Kun tarpeiden tunnistus ja suunnittelu tehdään hyvissä ajoin mahdollistetaan myös investointien optimointi. Paras hyöty pyritään saamaan ajoittamalla oikeat investoinnit oikeaan aikaan.

Coordinated pricing and inventory management

This dissertation mainly focuses on coordinated pricing and inventory management problems, where the related background is provided in Chapter 1. Several periodic-review models are then discussed in Chapters 2,3,4 and 5, respectively. Chapter 2 analyzes a deterministic single-product model, where a price adjustment cost incurs if the current selling price is changed from the previous period. We develop exact algorithms for the problem under different conditions and find out that computation complexity varies significantly associated with the cost structure. %Moreover, our numerical study indicates that dynamic pricing strategies may outperform static pricing strategies even when price adjustment cost accounts for a significant portion of the total profit. Chapter 3 develops a single-product model in which demand of a period depends not only on the current selling price but also on past prices through the so-called reference price. Strongly polynomial time algorithms are designed for the case without no fixed ordering cost, and a heuristic is proposed for the general case together with an error bound estimation. Moreover, our illustrates through numerical studies that incorporating reference price effect into coordinated pricing and inventory models can have a significant impact on firms' profits. Chapter 4 discusses the stochastic version of the model in Chapter 3 when customers are loss averse. It extends the associated results developed in literature and proves that the reference price dependent base-stock policy is proved to be optimal under a certain conditions. Instead of dealing with specific problems, Chapter 5 establishes the preservation of supermodularity in a class of optimization problems. This property and its extensions include several existing results in the literature as special cases, and provide powerful tools as we illustrate their applications to several operations problems: the stochastic two-product model with cross-price effects, the two-stage inventory control model, and the self-financing model.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

Active versus passive management : the case of BOVESPA

Mestrado em Finanças

Standardized environmental management systems as an internal management tool

In a principal-agent model we analyze the firm’s decision to adopt an informal or a standardized Environmental Management System (EMS). Our results are consistent with empirical evidence in several respects. A standardized EMS increases the internal control at the cost of introducing some degree of rigidity that entails an endogenous setup cost. Standardized systems are more prone to be adopted by big and well established firms and under tougher environmental policies. Firms with standardized EMS tend to devote more effort to abatement although this effort results in lower pollution only if public incentives are strong enough, suggesting a complementarity relationship between standardized EMS and public policies. Emission charges have both a marginal effect on abatement and a qualitative effect on the adoption decision that may induce a conflict between private and public interests. As a result of the combination of these two effects it can be optimal for the government to distort the tax in a specific way in order to push the firm to choose the socially optimal EMS. The introduction of standardized systems can result in win-win situations where firms, society and the environment get better off.

The effect of sample and sample matrix on DNA processing: Mechanisms for the detection and management of inhibition in forensic samples

The presence of inhibitory substances in biological forensic samples has, and continues to affect the quality of the data generated following DNA typing processes. Although the chemistries used during the procedures have been enhanced to mitigate the effects of these deleterious compounds, some challenges remain. Inhibitors can be components of the samples, the substrate where samples were deposited or chemical(s) associated to the DNA purification step. Therefore, a thorough understanding of the extraction processes and their ability to handle the various types of inhibitory substances can help define the best analytical processing for any given sample. A series of experiments were conducted to establish the inhibition tolerance of quantification and amplification kits using common inhibitory substances in order to determine if current laboratory practices are optimal for identifying potential problems associated with inhibition. DART mass spectrometry was used to determine the amount of inhibitor carryover after sample purification, its correlation to the initial inhibitor input in the sample and the overall effect in the results. Finally, a novel alternative at gathering investigative leads from samples that would otherwise be ineffective for DNA typing due to the large amounts of inhibitory substances and/or environmental degradation was tested. This included generating data associated with microbial peak signatures to identify locations of clandestine human graves. Results demonstrate that the current methods for assessing inhibition are not necessarily accurate, as samples that appear inhibited in the quantification process can yield full DNA profiles, while those that do not indicate inhibition may suffer from lowered amplification efficiency or PCR artifacts. The extraction methods tested were able to remove >90% of the inhibitors from all samples with the exception of phenol, which was present in variable amounts whenever the organic extraction approach was utilized. Although the results attained suggested that most inhibitors produce minimal effect on downstream applications, analysts should practice caution when selecting the best extraction method for particular samples, as casework DNA samples are often present in small quantities and can contain an overwhelming amount of inhibitory substances.^

Improving Resource Management in Virtualized Data Centers using Application Performance Models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

Management and outcome of cholesterol embolus identified in a diabetic retinopathy screening program

Purpose. We examined the incidence, management, and outcomes of patients known to be at high cardiovascular risk, and to assess whether specialist referral to an ophthalmic medical clinic is worthwhile. Methods. Patients in the East Birmingham area with cholesterolembolus who were identified on digital diabetic retinopathy screening over a 3-year period were referred to a specialist ophthalmic medicine clinic within Heart of England NHS Trust for management and investigation. Results. A total of 33 patients were referred for clinical management.(male:female = 22:11, mean age 72 years). A total of 28 patients were known to be receiving medication: 14 anti hypertensive therapy(42%), 19 aspirin (59%), and 21 statin (64%). A total of 18 patients had known cardiovascular disease, 10 of whom had received carotid stenting or coronary artery bypass surgery. Ten patients diagnosed with embolus required and consented to carotid Doppler studies. Six patients were confirmed with significant carotid stenosis and 2 (6%)of these patients required carotid endarterectomy surgery. Overall, 4patients died, a mortality rate of 12% over 3 years. Conclusions. Annual diabetic retinopathy screening provide sopportunistic identification of asymptomatic cholesterol emboli and provides an opportunity for review of medical management in the high-risk patient group with appropriate identification and referral for carotid stenosis surgery. A total of 11 patients were identified with sub optimal cardiovascular risk management: e.g., statin use.