Gestão sustentável de resíduos sólidos em grandes eventos : Rio+20 e jogos olímpicos de Londres

Dissertação (mestrado)—Universidade de Brasília, Centro de Desenvolvimento Sustentável, 2015

Average-case analysis of power consumption in embedded systems

Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact with the other hardware components of the system. The power consumption of the processor core(s) has an important impact on the total power dissipated in the system. Hence, the processor power optimization is crucial in satisfying the power consumption constraints, and developing low-power embedded systems. A key aspect of research in processor power optimization and management is “power estimation”. Having a fast and accurate method for processor power estimation at design time helps the designer to explore a large space of design possibilities, to make the optimal choices for developing a power efficient processor. Likewise, understanding the processor power dissipation behaviour of a specific software/application is the key for choosing appropriate algorithms in order to write power efficient software. Simulation-based methods for measuring the processor power achieve very high accuracy, but are available only late in the design process, and are often quite slow. Therefore, the need has arisen for faster, higher-level power prediction methods that allow the system designer to explore many alternatives for developing powerefficient hardware and software. The aim of this thesis is to present fast and high-level power models for the prediction of processor power consumption. Power predictability in this work is achieved in two ways: first, using a design method to develop power predictable circuits; second, analysing the power of the functions in the code which repeat during execution, then building the power model based on average number of repetitions. In the first case, a design method called Asynchronous Charge Sharing Logic (ACSL) is used to implement the Arithmetic Logic Unit (ALU) for the 8051 microcontroller. The ACSL circuits are power predictable due to the independency of their power consumption to the input data. Based on this property, a fast prediction method is presented to estimate the power of ALU by analysing the software program, and extracting the number of ALU-related instructions. This method achieves less than 1% error in power estimation and more than 100 times speedup in comparison to conventional simulation-based methods. In the second case, an average-case processor energy model is developed for the Insertion sort algorithm based on the number of comparisons that take place in the execution of the algorithm. The average number of comparisons is calculated using a high level methodology called MOdular Quantitative Analysis (MOQA). The parameters of the energy model are measured for the LEON3 processor core, but the model is general and can be used for any processor. The model has been validated through the power measurement experiments, and offers high accuracy and orders of magnitude speedup over the simulation-based method.

Characterisation and investigation of local variations in mechanical behaviour in cast aluminium using gradient solidification, Digital Image Correlation and finite element simulation

Due to design and process-related factors, there are local variations in the microstructure and mechanical behaviour of cast components. This work establishes a Digital Image Correlation (DIC) based method for characterisation and investigation of the effects of such local variations on the behaviour of a high pressure, die cast (HPDC) aluminium alloy. Plastic behaviour is studied using gradient solidified samples and characterisation models for the parameters of the Hollomon equation are developed, based on microstructural refinement. Samples with controlled microstructural variations are produced and the observed DIC strain field is compared with Finite Element Method (FEM) simulation results. The results show that the DIC based method can be applied to characterise local mechanical behaviour with high accuracy. The microstructural variations are observed to cause a redistribution of strain during tensile loading. This redistribution of strain can be predicted in the FEM simulation by incorporating local mechanical behaviour using the developed characterization model. A homogeneous FEM simulation is unable to predict the observed behaviour. The results motivate the application of a previously proposed simulation strategy, which is able to predict and incorporate local variations in mechanical behaviour into FEM simulations already in the design process for cast components.

Estudio molecular en dos hermanas afectadas por ictiosis congénita autosómica recesiva : descripción de una nueva mutación causal en TGM1

Se describe la variante homocigota c.320-2A>G de TGM1 en dos hermanas con ictiosis congénita autosómica recesiva. El clonaje de los transcritos generados por esta variante permitió identificar tres mecanismos moleculares de splicing alternativos.

Leaf water potential and sap flow as indicators of water stress in Crimson ‘seedless’ grapevines under different irrigation strategies

Vitis vinifera L. cv. Crimson Seedless is a late season red table grape developed in 1989, with a high market value and increasingly cultivated under protected environments to extend the availability of seedless table grapes into the late fall. The purpose of this work was to evaluate leaf water potential and sap flow as indicators of water stress in Crimson Seedless vines under standard and reduced irrigation strategy, consisting of 70 % of the standard irrigation depth. Additionally, two sub-treatments were applied, consisting of normal irrigation throughout the growing season and a short irrigation induced stress period between veraison and harvest. Leaf water potential measurements coherently signaled crop-available water variations caused by different irrigation treatments, suggesting that this plant-based method can be reliably used to identify water-stress conditions. The use of sap flow density data to establish a ratio based on a reference ‘well irrigated vine’ and less irrigated vines can potentially be used to signal differences in the transpiration rates, which may be suitable for improving irrigation management strategies while preventing undesirable levels of water stress. Although all four irrigation strategies resulted in the production of quality table grapes, significant differences (p ≤ 0.05) were found in both berry weight and sugar content between the standard irrigation and reduced irrigation treatments. Reduced irrigation increased slightly the average berry size as well as sugar content and technical maturity index. The 2-week irrigation stress period had a negative effect on these parameters.

Leaf water potential and sap flow as indicators of water stress in Crimson 'seedless' grapevines under different irrigation strategies

Abstract Vitis vinifera L. cv. Crimson Seedless is a late season red table grape developed in 1989, with a high market value and increasingly cultivated under protected environments to extend the availability of seedless table grapes into the late fall. The purpose of this work was to evaluate leaf water potential and sap flow as indicators of water stress in Crimson Seedless vines under standard and reduced irrigation strategy, consisting of 70 % of the standard irrigation depth. Additionally, two sub-treatments were applied, consisting of normal irrigation throughout the growing season and a short irrigation induced stress period between veraison and harvest. Leaf water potential measurements coherently signaled crop-available water variations caused by different irrigation treatments, suggesting that this plant-based method can be reliably used to identify water-stress conditions. The use of sap flow density data to establish a ratio based on a reference ‘well irrigated vine’ and less irrigated vines can potentially be used to signal differences in the transpiration rates, which may be suitable for improving irrigation management strategies while preventing undesirable levels of water stress. Although all four irrigation strategies resulted in the production of quality table grapes, significant differences (p ≤ 0.05) were found in both berry weight and sugar content between the standard irrigation and reduced irrigation treatments. Reduced irrigation increased slightly the average berry size as well as sugar content and technical maturity index. The 2-week irrigation stress period had a negative effect on these parameters.

The dark and bright side of remote work: social isolation, concentration, and performance of remote workers

This dissertation, comprised of three separate studies, focuses on the relationship between remote work adoption and employee job performance, analyzing employee social isolation and job concentration as the main mediators of this relationship. It also examines the impact of concern about COVID-19 and emotional stability as moderators of these relationships. Using a survey-based method in an emergency homeworking context, the first study found that social isolation had a negative effect on remote work productivity and satisfaction, and that COVID-19 concerns affected this relationship differently for individuals with high and low levels of concern. The second study, a diary study analyzing hybrid workers, found a positive correlation between work from home (WFH) adoption and job performance through social isolation and job concentration, with emotional stability serving respectively as a buffer and booster in the relationships between WFH and the mediators. The third study, even in this case a diary study of hybrid workers, confirmed the benefits of work from home on job performance and the importance of job concentration as a mediator, while suggesting that social isolation may not be significant when studying employee job performance, but it is relevant for employee well-being. Although each study provides autonomously a discussion and research and practical implications, this dissertation also presents a general discussion on remote work and its psychological implications, highlighting areas for future research

Left Ventricle Modification After Endovascular Aortic Repair

INTRODUCTION Endograft deployment is a well-known cause of arterial stiffness increase as well as arterial stiffness increase represent a recognized cardiovascular risk factor. A harmful effect on cardiac function induced by the endograft deployment should be investigated. Aim of this study was to evaluate the impact of endograft deployment on the arterial stiffness and cardiac geometry of patients treated for aortic aneurysm in order to detect modifications that could justify an increased cardiac mortality at follow-up. MATHERIALS AND METHODS Over a period of 3 years, patients undergoing elective EVAR for infrarenal aortic pathologies in two university centers in Emilia Romagna were examined. All patients underwent pre-operative and six-months post-operative Pulse Wave Velocity (PWV) examination using an ultrasound-based method performed by vascular surgeons together with trans-thoracic echocardiography examination in order to evaluate cardiac chambers geometry before and after the treatment. RESULTS 69 patients were enrolled. After 36 months, 36 patients (52%) completed the 6 months follow-up examination.The ultrasound-based carotid-femoral PWV measurements performed preoperatively and 6 months after the procedure revealed a significant postoperative increase of cf-PWV (11,6±3,6 m/sec vs 12,3±8 m/sec; p.value:0,037).Postoperative LVtdV (90±28,3 ml/m2 vs 99,1±29,7 ml/m2; p.value:0.031) LVtdVi (47,4±15,9 ml/m2 vs 51,9±14,9 ml/m2; p.value:0.050), IVStd (12±1,5 mm vs 12,1±1,3 mm; p.value:0,027) were significantly increased if compared with preoperative measures.Postoperative E/A (0,76±0,26 vs 0,6±0,67; p.value:0,011), E’ lateral (9,5±2,6 vs 7,9±2,6; p.value:0,024) and A’ septal (10,8±1,5 vs 8,9±2; p.value0,005) were significantly reduced if compared with preoperative measurements CONCLUSION The endovascular treatment of the abdominal aorta causes an immediate and significant increase of the aortic stiffness.This increase reflects negatively on patients’ cardiac geometry inducing left ventricle hypertrophy and mild diastolic disfunction after just 6 months from endograft’s implantation.Further investigations and long-term results are necessary to access if this negative remodeling could affect the cardiac outcome of patient treated using the endovascular approach.

Analysis of earthquakes predictability

Earthquake prediction is a complex task for scientists due to the rare occurrence of high-intensity earthquakes and their inaccessible depths. Despite this challenge, it is a priority to protect infrastructure, and populations living in areas of high seismic risk. Reliable forecasting requires comprehensive knowledge of seismic phenomena. In this thesis, the development, application, and comparison of both deterministic and probabilistic forecasting methods is shown. Regarding the deterministic approach, the implementation of an alarm-based method using the occurrence of strong (fore)shocks, widely felt by the population, as a precursor signal is described. This model is then applied for retrospective prediction of Italian earthquakes of magnitude M≥5.0,5.5,6.0, occurred in Italy from 1960 to 2020. Retrospective performance testing is carried out using tests and statistics specific to deterministic alarm-based models. Regarding probabilistic models, this thesis focuses mainly on the EEPAS and ETAS models. Although the EEPAS model has been previously applied and tested in some regions of the world, it has never been used for forecasting Italian earthquakes. In the thesis, the EEPAS model is used to retrospectively forecast Italian shallow earthquakes with a magnitude of M≥5.0 using new MATLAB software. The forecasting performance of the probabilistic models was compared to other models using CSEP binary tests. The EEPAS and ETAS models showed different characteristics for forecasting Italian earthquakes, with EEPAS performing better in the long-term and ETAS performing better in the short-term. The FORE model based on strong precursor quakes is compared to EEPAS and ETAS using an alarm-based deterministic approach. All models perform better than a random forecasting model, with ETAS and FORE models showing better performance. However, to fully evaluate forecasting performance, prospective tests should be conducted. The lack of objective tests for evaluating deterministic models and comparing them with probabilistic ones was a challenge faced during the study.

Advanced statistical models for the segregation, identification and measurement of coexisting sound sources

Long-term monitoring of acoustical environments is gaining popularity thanks to the relevant amount of scientific and engineering insights that it provides. The increasing interest is due to the constant growth of storage capacity and computational power to process large amounts of data. In this perspective, machine learning (ML) provides a broad family of data-driven statistical techniques to deal with large databases. Nowadays, the conventional praxis of sound level meter measurements limits the global description of a sound scene to an energetic point of view. The equivalent continuous level Leq represents the main metric to define an acoustic environment, indeed. Finer analyses involve the use of statistical levels. However, acoustic percentiles are based on temporal assumptions, which are not always reliable. A statistical approach, based on the study of the occurrences of sound pressure levels, would bring a different perspective to the analysis of long-term monitoring. Depicting a sound scene through the most probable sound pressure level, rather than portions of energy, brought more specific information about the activity carried out during the measurements. The statistical mode of the occurrences can capture typical behaviors of specific kinds of sound sources. The present work aims to propose an ML-based method to identify, separate and measure coexisting sound sources in real-world scenarios. It is based on long-term monitoring and is addressed to acousticians focused on the analysis of environmental noise in manifold contexts. The presented method is based on clustering analysis. Two algorithms, Gaussian Mixture Model and K-means clustering, represent the main core of a process to investigate different active spaces monitored through sound level meters. The procedure has been applied in two different contexts: university lecture halls and offices. The proposed method shows robust and reliable results in describing the acoustic scenario and it could represent an important analytical tool for acousticians.

Embedding Video Object Detection Capabilities on Low-Power Nano-Drones

Our objective for this thesis work was the deployment of a Neural Network based approach for video object detection on board a nano-drone. Furthermore, we have studied some possible extensions to exploit the temporal nature of videos to improve the detection capabilities of our algorithm. For our project, we have utilized the Mobilenetv2/v3SSDLite due to their limited computational and memory requirements. We have trained our networks on the IMAGENET VID 2015 dataset and to deploy it onto the nano-drone we have used the NNtool and Autotiler tools by GreenWaves. To exploit the temporal nature of video data we have tried different approaches: the introduction of an LSTM based convolutional layer in our architecture, the introduction of a Kalman filter based tracker as a postprocessing step to augment the results of our base architecture. We have obtain a total improvement in our performances of about 2.5 mAP with the Kalman filter based method(BYTE). Our detector run on a microcontroller class processor on board the nano-drone at 1.63 fps.

Numerical method for determination of the NMR frequency of the single-qubit operation in a silicon-based solid-state quantum computer

A numerical method is introduced to determine the nuclear magnetic resonance frequency of a donor (P-31) doped inside a silicon substrate under the influence of an applied electric field. This phosphorus donor has been suggested for operation as a qubit for the realization of a solid-state scalable quantum computer. The operation of the qubit is achieved by a combination of the rotation of the phosphorus nuclear spin through a globally applied magnetic field and the selection of the phosphorus nucleus through a locally applied electric field. To realize the selection function, it is required to know the relationship between the applied electric field and the change of the nuclear magnetic resonance frequency of phosphorus. In this study, based on the wave functions obtained by the effective-mass theory, we introduce an empirical correction factor to the wave functions at the donor nucleus. Using the corrected wave functions, we formulate a first-order perturbation theory for the perturbed system under the influence of an electric field. In order to calculate the potential distributions inside the silicon and the silicon dioxide layers due to the applied electric field, we use the multilayered Green's functions and solve an integral equation by the moment method. This enables us to consider more realistic, arbitrary shape, and three-dimensional qubit structures. With the calculation of the potential distributions, we have investigated the effects of the thicknesses of silicon and silicon dioxide layers, the relative position of the donor, and the applied electric field on the nuclear magnetic resonance frequency of the donor.

Risk-based decision making method for maintenance policy selection of thermal power plant equipment

This study presents a decision-making method for maintenance policy selection of power plants equipment. The method is based on risk analysis concepts. The method first step consists in identifying critical equipment both for power plant operational performance and availability based on risk concepts. The second step involves the proposal of a potential maintenance policy that could be applied to critical equipment in order to increase its availability. The costs associated with each potential maintenance policy must be estimated, including the maintenance costs and the cost of failure that measures the critical equipment failure consequences for the power plant operation. Once the failure probabilities and the costs of failures are estimated, a decision-making procedure is applied to select the best maintenance policy. The decision criterion is to minimize the equipment cost of failure, considering the costs and likelihood of occurrence of failure scenarios. The method is applied to the analysis of a lubrication oil system used in gas turbines journal bearings. The turbine has more than 150 MW nominal output, installed in an open cycle thermoelectric power plant. A design modification with the installation of a redundant oil pump is proposed for lubricating oil system availability improvement. (C) 2009 Elsevier Ltd. All rights reserved.

Surgery for Hirschsprung's disease: comparison between the Duhamel method and the transanal endorectal pull-through based on 59 patients and a review of the literature

Background:¦Hirschsprung's disease (HSCR) is a congenital malformation of the enteric nervous system due to the¦arrest of migration of neural crest cells to form the myenteric and submucosal plexuses. It leads to an anganglionic intestinal segment, which is permanently contracted causing intestinal obstruction. Its incidence is approximately 1/5000 birth, and males are more frequently affected with a male/female ratio of 4/1. The diagnosis is in most cases made within the first year of life. The rectal biopsy of the mucosa and sub-mucosa is the diagnostic gold standard.¦Purpose:¦The aim of this study was to compare two surgical approaches for HSCR, the Duhamel technique and the transanal endorectal pull-through (TEPT) in term of indications, duration of surgery, duration of hospital stay, postoperative treatment, complications, frequency of enterocolitis and functional outcomes.¦Methods:¦Fifty-nine patients were treated for HSCR by one of the two methods in our department of pediatric¦surgery between 1994 and 2010. These patients were separated into two groups (I: Duhamel, II: TEPT), which were compared on the basis of medical records. Statistics were made to compare the two groups (ANOVA test). The first group includes 43 patients and the second 16 patients. It is noteworthy that twenty-four patients (about 41% of all¦patients) were referred from abroad (Western Africa). Continence was evaluated with the Krickenbeck's score.¦Results:¦Statistically, this study showed that operation duration, hospital stay, postoperative fasting and duration of postoperative antibiotics were significantly shorter (p value < 0.05) in group II (TEPT). But age at operation and length of aganglionic segment showed no significant difference between the two groups. The continence follow-up showed generally good results (Krickenbeck's scores 1; 2.1; 3.1) in both groups with a slight tendency to constipation in group I and soiling in group II.¦Conclusion:¦We found two indications for the Duhamel method that are being referred from a country without¦careful postoperative surveillance and/or having a previous colostomy. Even if the Duhamel technique tends to be replaced by the TEPT, it remains the best operative approach for some selected patients. TEPT has also proved some advantages but must be followed carefully because, among other points, of the postoperative dilatations. Our postoperative standards, like digital rectal examination and anal dilatations seem to reduce the occurrence of complications like rectal spur and anal/anastomosis stenosis, respectively in the Duhamel method and the TEPT technique.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.