Optimal Rehabilitation Strategy In Water Distribution Systems Considering Reduction In Greenhouse Gas Emissions

Most of water distribution systems (WDS) need rehabilitation due to aging infrastructure leading to decreasing capacity, increasing leakage and consequently low performance of the WDS. However an appropriate strategy including location and time of pipeline rehabilitation in a WDS with respect to a limited budget is the main challenge which has been addressed frequently by researchers and practitioners. On the other hand, selection of appropriate rehabilitation technique and material types is another main issue which has yet to address properly. The latter can affect the environmental impacts of a rehabilitation strategy meeting the challenges of global warming mitigation and consequent climate change. This paper presents a multi-objective optimization model for rehabilitation strategy in WDS addressing the abovementioned criteria mainly focused on greenhouse gas (GHG) emissions either directly from fossil fuel and electricity or indirectly from embodied energy of materials. Thus, the objective functions are to minimise: (1) the total cost of rehabilitation including capital and operational costs; (2) the leakage amount; (3) GHG emissions. The Pareto optimal front containing optimal solutions is determined using Non-dominated Sorting Genetic Algorithm NSGA-II. Decision variables in this optimisation problem are classified into a number of groups as: (1) percentage proportion of each rehabilitation technique each year; (2) material types of new pipeline for rehabilitation each year. Rehabilitation techniques used here includes replacement, rehabilitation and lining, cleaning, pipe duplication. The developed model is demonstrated through its application to a Mahalat WDS located in central part of Iran. The rehabilitation strategy is analysed for a 40 year planning horizon. A number of conventional techniques for selecting pipes for rehabilitation are analysed in this study. The results show that the optimal rehabilitation strategy considering GHG emissions is able to successfully save the total expenses, efficiently decrease the leakage amount from the WDS whilst meeting environmental criteria.

Structural and reduction studies of ZrO2-CeO2:Ni for application in SOFC anodes.

Zirconia-ceria solid-solutions are extensively used as promoters for three-way catalysts, which are applied in the control of NOx, CO and hydrocarbons emission from automotive exhausts. In addition, thesematerials can be used as anodes in solid oxide fuel cells (SOFCs) operated with hydrocarbons. There areonly few works on ZrO2-CeO2 ordered mesoporous materials for catalytic applications and for anodes inSOFCs. The interest in these anodes relies on the fact that ZrO2-CeO2materials are mixed ionic/electronic conductors in reducing atmosphere and, therefore, fuel oxidation is produced on its entire surface, while it only occurs in the [anode/electrolyte/gas] interface (triple-phase boundaries) for electronic conductors. In this work, a synthesis method was developed usingZr and Ce chloride precursors, HCl aqueous solution, Pluronic P123 as the structure directing agent, NH4OH to adjust the pH (3-4) and a Teflon autoclave to perform hydrothermal treatment (80ºC/48 hours). The samples were dried and calcined, until 540ºC in N2and 4 hours in air. The X-ray diffraction data showed that powders with higher CeO2 content are formed by a larger fraction of the cubic CeO2 phase, while for a lower CeO2content the major crystalline structure is the tetragonal ZrO2 phase. The NiO impregnation was made with an ethanol dispersion of Ni(NO3)×6H2O. The resulting powder was calcinated in air until 350ºC for 2 hours. Temperature-programmed reduction (TPR) data were collected in order to evaluate the reduction profiles of ZrO2-x%CeO2:Ni samples in H2/Ar atmosphere. Results showed lower reduction temperatures for all ceria content in samples comparing to a NiO standard.

Learning What Works: Demonstrating Practice Effectiveness with Children and Families Through Retrospective Investigation

Intensive family preservation services (IFPS), designed to stabilize at-risk families and avert out-of-home care, have been the focus of many randomized, experimental studies. Employing a retrospective “clinical data-mining” (CDM) methodology (Epstein, 2001), this study makes use of available information extracted from client records in one IFPS agency over the course of two years. The primary goal of this descriptive and associational study was to gain a clearer understanding of IFPS service delivery and effectiveness. Interventions provided to families are delineated and assessed for their impact on improved family functioning, their impact on the reduction of family violence, as well as placement prevention. Findings confirm the use of a wide range of services consistent with IFPS program theory. Because the study employs a quasi-experimental, retrospective use of available information, clinical outcomes described cannot be causally attributed to interventions employed as with randomized controlled trials. With regard to service outcomes, findings suggest that family education, empowerment services and advocacy are most influential in placement prevention and in ameliorating unmanageable behaviors in children as well as the incidence of family violence.

Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics

In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.

Lead time reduction for new products

The research, which was given the terms of reference, "To cut the lead time for getting new products into volume production", was sponsored by a company which develops and manufactures telecommunications equipment. The research described was based on studies made of the development of two processors which were designed to control telephone exchanges in the public network. It was shown that for each of these products, which were large electronic systems containing both hardware and software, most of their lead time was taken up with development. About half of this time was consumed by activities associated with redesign resulting from changes found to be necessary after the original design had been built. Analysing the causes of design changes showed the most significant to be Design Faults. The reasons why these predominated were investigated by seeking the collective opinion from design staff and their management using a questionnaire. Using the results from these studies to build upon the works of other authors, a model of the development process of large hierarchical systems is derived. An important feature of this model is its representation of iterative loops due to design changes. In order to reduce the development time, two closely related philosophies are proposed: By spending more time at the early stages of development (detecting and remedying faults in the design) even greater savings can be made later on, The collective performance of the development organisation would be improved by increasing the amount and speed of feedback about that performance. A trial was performed to test these philosophies using readily available techniques for design verification. It showed that about an 11 per cent saving would be made on the development time and that the philosophies might be equally successfully applied to other products and techniques.

Iterative reconstruction as a novel method of radiation dose reduction at computed tomography in patients with Crohn's disease

Prior work of our research group, that quantified the alarming levels of radiation dose to patients with Crohn’s disease from medical imaging and the notable shift towards CT imaging making these patients an at risk group, provided context for this work. CT delivers some of the highest doses of ionising radiation in diagnostic radiology. Once a medical imaging examination is deemed justified, there is an onus on the imaging team to endeavour to produce diagnostic quality CT images at the lowest possible radiation dose to that patient. The fundamental limitation with conventional CT raw data reconstruction was the inherent coupling of administered radiation dose with observed image noise – the lower the radiation dose, the noisier the image. The renaissance, rediscovery and refinement of iterative reconstruction removes this limitation allowing either an improvement in image quality without increasing radiation dose or maintenance of image quality at a lower radiation dose compared with traditional image reconstruction. This thesis is fundamentally an exercise in optimisation in clinical CT practice with the objectives of assessment of iterative reconstruction as a method for improvement of image quality in CT, exploration of the associated potential for radiation dose reduction, and development of a new split dose CT protocol with the aim of achieving and validating diagnostic quality submillisiever t CT imaging in patients with Crohn’s disease. In this study, we investigated the interplay of user-selected parameters on radiation dose and image quality in phantoms and cadavers, comparing traditional filtered back projection (FBP) with iterative reconstruction algorithms. This resulted in the development of an optimised, refined and appropriate split dose protocol for CT of the abdomen and pelvis in clinical patients with Crohn’s disease allowing contemporaneous acquisition of both modified and conventional dose CT studies. This novel algorithm was then applied to 50 patients with a suspected acute complication of known Crohn’s disease and the raw data reconstructed with FBP, adaptive statistical iterative reconstruction (ASiR) and model based iterative reconstruction (MBIR). Conventional dose CT images with FBP reconstruction were used as the reference standard with which the modified dose CT images were compared in terms of radiation dose, diagnostic findings and image quality indices. As there are multiple possible user-selected strengths of ASiR available, these were compared in terms of image quality to determine the optimal strength for this modified dose CT protocol. Modified dose CT images with MBIR were also compared with contemporaneous abdominal radiograph, where performed, in terms of diagnostic yield and radiation dose. Finally, attenuation measurements in organs, tissues, etc. with each reconstruction algorithm were compared to assess for preservation of tissue characterisation capabilities. In the phantom and cadaveric models, both forms of iterative reconstruction examined (ASiR and MBIR) were superior to FBP across a wide variety of imaging protocols, with MBIR superior to ASiR in all areas other than reconstruction speed. We established that ASiR appears to work to a target percentage noise reduction whilst MBIR works to a target residual level of absolute noise in the image. Modified dose CT images reconstructed with both ASiR and MBIR were non-inferior to conventional dose CT with FBP in terms of diagnostic findings, despite reduced subjective and objective indices of image quality. Mean dose reductions of 72.9-73.5% were achieved with the modified dose protocol with a mean effective dose of 1.26mSv. MBIR was again demonstrated superior to ASiR in terms of image quality. The overall optimal ASiR strength for the modified dose protocol used in this work is ASiR 80%, as this provides the most favourable balance of peak subjective image quality indices with less objective image noise than the corresponding conventional dose CT images reconstructed with FBP. Despite guidelines to the contrary, abdominal radiographs are still often used in the initial imaging of patients with a suspected complication of Crohn’s disease. We confirmed the superiority of modified dose CT with MBIR over abdominal radiographs at comparable doses in detection of Crohn’s disease and non-Crohn’s disease related findings. Finally, we demonstrated (in phantoms, cadavers and in vivo) that attenuation values do not change significantly across reconstruction algorithms meaning preserved tissue characterisation capabilities with iterative reconstruction. Both adaptive statistical and model based iterative reconstruction algorithms represent feasible methods of facilitating acquisition diagnostic quality CT images of the abdomen and pelvis in patients with Crohn’s disease at markedly reduced radiation doses. Our modified dose CT protocol allows dose savings of up to 73.5% compared with conventional dose CT, meaning submillisievert imaging is possible in many of these patients.