IMPROVED SENSITIVITY OF RESONANT MASS SENSOR BASED ON MICRO TILTING PLATE AND MICRO CANTILEVER

Vapor sensors have been used for many years. Their applications range from detection of toxic gases and dangerous chemicals in industrial environments, the monitoring of landmines and other explosives, to the monitoring of atmospheric conditions. Microelectrical mechanical systems (MEMS) fabrication technologies provide a way to fabricate sensitive devices. One type of MEMS vapor sensors is based on mass changing detection and the sensors have a functional chemical coating for absorbing the chemical vapor of interest. The principle of the resonant mass sensor is that the resonant frequency will experience a large change due to a small mass of gas vapor change. This thesis is trying to build analytical micro-cantilever and micro-tilting plate models, which can make optimization more efficient. Several objectives need to be accomplished: (1) Build an analytical model of MEMS resonant mass sensor based on micro-tilting plate with the effects of air damping. (2) Perform design optimization of micro-tilting plate with a hole in the center. (3) Build an analytical model of MEMS resonant mass sensor based on micro-cantilever with the effects of air damping. (4) Perform design optimization of micro-cantilever by COMSOL. Analytical models of micro-tilting plate with a hole in the center are compared with a COMSOL simulation model and show good agreement. The analytical models have been used to do design optimization that maximizes sensitivity. The micro-cantilever analytical model does not show good agreement with a COMSOL simulation model. To further investigate, the air damping pressures at several points on the micro-cantilever have been compared between analytical model and COMSOL model. The analytical model is inadequate for two reasons. First, the model’s boundary condition assumption is not realistic. Second, the deflection shape of the cantilever changes with the hole size, and the model does not account for this. Design optimization of micro-cantilever is done by COMSOL.

THE EFFECT OF ANNEALING ON AMORPHOUS SILICON BASED SOLAR PHOTOVOLTAIC THERMAL SYSTEM (PV/T) AND APPROPRIATE GLOBAL DISPATCH STRATEGIES

Previous work has shown that high-temperature short-term spike thermal annealing of hydrogenated amorphous silicon (a-Si:H) photovoltaic thermal (PVT) systems results in higher electrical energy output. The relationship between temperature and performance of a-Si:H PVT is not simple as high temperatures during thermal annealing improves the immediate electrical performance following an anneal, but during the anneal it creates a marked drop in electrical performance. In addition, the power generation of a-Si:H PVT depends on both the environmental conditions and the Staebler-Wronski Effect kinetics. In order to improve the performance of a-Si:H PVT systems further, this paper reports on the effect of various dispatch strategies on system electrical performance. Utilizing experimental results from thermal annealing, an annealing model simulation for a-Si:Hbased PVT was developed and applied to different cities in the U.S. to investigate potential geographic effects on the dispatch optimization of the overall electrical PVT systems performance and annual electrical yield. The results showed that spike thermal annealing once per day maximized the improved electrical energy generation. In the outdoor operating condition this ideal behavior deteriorates and optimization rules are required to be implemented.

Development of Physics-based Models and Design Optimization of Power Electronic Conversion Systems

The main objective for physics based modeling of the power converter components is to design the whole converter with respect to physical and operational constraints. Therefore, all the elements and components of the energy conversion system are modeled numerically and combined together to achieve the whole system behavioral model. Previously proposed high frequency (HF) models of power converters are based on circuit models that are only related to the parasitic inner parameters of the power devices and the connections between the components. This dissertation aims to obtain appropriate physics-based models for power conversion systems, which not only can represent the steady state behavior of the components, but also can predict their high frequency characteristics. The developed physics-based model would represent the physical device with a high level of accuracy in predicting its operating condition. The proposed physics-based model enables us to accurately develop components such as; effective EMI filters, switching algorithms and circuit topologies [7]. One of the applications of the developed modeling technique is design of new sets of topologies for high-frequency, high efficiency converters for variable speed drives. The main advantage of the modeling method, presented in this dissertation, is the practical design of an inverter for high power applications with the ability to overcome the blocking voltage limitations of available power semiconductor devices. Another advantage is selection of the best matching topology with inherent reduction of switching losses which can be utilized to improve the overall efficiency. The physics-based modeling approach, in this dissertation, makes it possible to design any power electronic conversion system to meet electromagnetic standards and design constraints. This includes physical characteristics such as; decreasing the size and weight of the package, optimized interactions with the neighboring components and higher power density. In addition, the electromagnetic behaviors and signatures can be evaluated including the study of conducted and radiated EMI interactions in addition to the design of attenuation measures and enclosures.

Physics-Based Modeling of Power System Components for the Evaluation of Low-Frequency Radiated Electromagnetic Fields

The low-frequency electromagnetic compatibility (EMC) is an increasingly important aspect in the design of practical systems to ensure the functional safety and reliability of complex products. The opportunities for using numerical techniques to predict and analyze system’s EMC are therefore of considerable interest in many industries. As the first phase of study, a proper model, including all the details of the component, was required. Therefore, the advances in EMC modeling were studied with classifying analytical and numerical models. The selected model was finite element (FE) modeling, coupled with the distributed network method, to generate the model of the converter’s components and obtain the frequency behavioral model of the converter. The method has the ability to reveal the behavior of parasitic elements and higher resonances, which have critical impacts in studying EMI problems. For the EMC and signature studies of the machine drives, the equivalent source modeling was studied. Considering the details of the multi-machine environment, including actual models, some innovation in equivalent source modeling was performed to decrease the simulation time dramatically. Several models were designed in this study and the voltage current cube model and wire model have the best result. The GA-based PSO method is used as the optimization process. Superposition and suppression of the fields in coupling the components were also studied and verified. The simulation time of the equivalent model is 80-100 times lower than the detailed model. All tests were verified experimentally. As the application of EMC and signature study, the fault diagnosis and condition monitoring of an induction motor drive was developed using radiated fields. In addition to experimental tests, the 3DFE analysis was coupled with circuit-based software to implement the incipient fault cases. The identification was implemented using ANN for seventy various faulty cases. The simulation results were verified experimentally. Finally, the identification of the types of power components were implemented. The results show that it is possible to identify the type of components, as well as the faulty components, by comparing the amplitudes of their stray field harmonics. The identification using the stray fields is nondestructive and can be used for the setups that cannot go offline and be dismantled

A Multi-Criteria GIS-Based Route Selection Tool for Hazardous Material Transport: Consideration of Environmental Consequence, Traffic Congestions and Costs

Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year. The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with identification of inhalation hazard impact zones and explosion protective areas around the location of hypothetical hazardous material releases, considering different parameters (i.e., chemicals characteristics, release quantities, atmospheric condition, etc.). Results showed that depending on the quantity of release, chemical, and atmospheric stability (a function of wind speed, meteorology, sky cover, time and location of accidents, etc.) the consequence of these incidents can differ. The study was extended by selection of other evaluation criteria for further investigation because health risk as an evaluation criterion would not be the only concern in selection of routes. Transportation difficulties (i.e., road blockage and congestion) were incorporated as important factor due to their indirect impact/cost on the users of transportation networks. Trucking costs were also considered as one of the primary criteria in selection of hazardous material paths; otherwise the suggested routes would have not been convincing for the shipping companies. The last but not least criterion was proximity of public places to the routes. The approach evolved from a simple framework to a complicated and efficient GIS-based tool able to investigate transportation networks of any given study area, and capable of generating best routing options for cargos. The suggested tool uses a multi-criteria-decision-making method, which considers the priorities of the decision makers in choosing the cargo routes. Comparison of the routing options based on each criterion and also the overall suitableness of the path in regards to all the criteria (using a multi-criteria-decision-making method) showed that using similar tools as the one proposed by this study can provide decision makers insights in the area of hazardous material transport. This tool shows the probable consequences of considering each path in a very easily understandable way; in the formats of maps and tables, which makes the tradeoffs of costs and risks considerably simpler, as in some cases slightly compromising on trucking cost may drastically decrease the probable health risk and/or traffic difficulties. This will not only be rewarding to the community by making cities safer places to live, but also can be beneficial to shipping companies by allowing them to advertise as environmental friendly conveyors.

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

Design of maintenance structures for rural electrification with solar home systems. The case of the Moroccan program.

n decentralised rural electrification through solar home systems, private companies and promoting institutions are faced with the problem of deploying maintenance structures to operate and guarantee the service of the solar systems for long periods (ten years or more). The problems linked to decentralisation, such as the dispersion of dwellings, difficult access and maintenance needs, makes it an arduous task. This paper proposes an innovative design tool created ad hoc for photovoltaic rural electrification based on a real photovoltaic rural electrification program in Morocco as a special case study. The tool is developed from a mathematical model comprising a set of decision variables (location, transport, etc.) that must meet certain constraints and whose optimisation criterion is the minimum cost of the operation and maintenance activity assuming an established quality of service. The main output of the model is the overall cost of the maintenance structure. The best location for the local maintenance headquarters and warehouses in a given region is established, as are the number of maintenance technicians and vehicles required.

Health profile of centenarians in Portugal: a census-based approach

Background: The number of centenarians is rapidly increasing in Europe. In Portugal, it has almost tripled over the last 10 years and constitutes one of the fastest-growing segments of the population. This paper aims to describe the health and sociodemographic characteristics of Portuguese centenarians as given in the 2011 census and to identify sex differences. Methods: All persons living in Portugal mainland and Madeira and Azores islands aged 100 years old at the time of the 2011 census (N = 1,526) were considered. Measures include sociodemographic characteristics and perceived difficulties in six functional domains of basic actions (seeing, hearing, walking, cognition, self-care, and communication) as assessed by the Portuguese census official questionnaires. Results: Most centenarians are women (82.1 %), widowed (82 %), never attended school (51 %), and live in private households (71 %). The majority show major constraints in seeing (67.4 %), hearing (72.3 %), and particularly in their mobility (83.7 % cannot/have great difficulties in walking/climbing stairs and 80.7 % in bathing/dressing). In general, a better outcome was found for reported memory/concentration and understanding, with 39.1 % and 42.5 % presenting no or mild difficulty, respectively. Top-level functioning (no/mild difficulties in all dimensions concurrently) was observed in a minority of cases (5.96 %). Women outnumber men by a ratio of 4.6, and statistically significant differences were found between men and women for all health-related variables, with women presenting a higher percentage of difficulties. Conclusion: Portuguese centenarians experience great difficulties in sensory domains and basic daily living activities, and to a lesser extent in cognition and communication. The obtained profile, though self-reported, is important in considering the potential of social and family participation of this population regardless of their functional and sensory limitations. Based on the observed differences between men and women, gender-specific and gender-sensitive interventions are recommended in order to acknowledge women’s worse overall condition.

Classifying And Predicting Software Security Vulnerabilities based on Reproducibility

Security defects are common in large software systems because of their size and complexity. Although efficient development processes, testing, and maintenance policies are applied to software systems, there are still a large number of vulnerabilities that can remain, despite these measures. Some vulnerabilities stay in a system from one release to the next one because they cannot be easily reproduced through testing. These vulnerabilities endanger the security of the systems. We propose vulnerability classification and prediction frameworks based on vulnerability reproducibility. The frameworks are effective to identify the types and locations of vulnerabilities in the earlier stage, and improve the security of software in the next versions (referred to as releases). We expand an existing concept of software bug classification to vulnerability classification (easily reproducible and hard to reproduce) to develop a classification framework for differentiating between these vulnerabilities based on code fixes and textual reports. We then investigate the potential correlations between the vulnerability categories and the classical software metrics and some other runtime environmental factors of reproducibility to develop a vulnerability prediction framework. The classification and prediction frameworks help developers adopt corresponding mitigation or elimination actions and develop appropriate test cases. Also, the vulnerability prediction framework is of great help for security experts focus their effort on the top-ranked vulnerability-prone files. As a result, the frameworks decrease the number of attacks that exploit security vulnerabilities in the next versions of the software. To build the classification and prediction frameworks, different machine learning techniques (C4.5 Decision Tree, Random Forest, Logistic Regression, and Naive Bayes) are employed. The effectiveness of the proposed frameworks is assessed based on collected software security defects of Mozilla Firefox.

‘‘Model age-based” and ‘‘copy when uncertain” biases in children’s social learning of a novel task

Theoretical models of social learning predict that individuals can benefit from using strategies that specify when and whom to copy. Here the interaction of two social learning strategies, model age-based biased copying and copy when uncertain, was investigated. Uncertainty was created via a systematic manipulation of demonstration efficacy (completeness) and efficiency (causal relevance of some actions). The participants, 4- to 6-year-old children (N = 140), viewed both an adult model and a child model, each of whom used a different tool on a novel task. They did so in a complete condition, a near-complete condition, a partial demonstration condition, or a no-demonstration condition. Half of the demonstrations in each condition incorporated causally irrelevant actions by the models. Social transmission was assessed by first responses but also through children’s continued fidelity, the hallmark of social traditions. Results revealed a bias to copy the child model both on first response and in continued interactions. Demonstration efficacy and efficiency did not affect choice of model at first response but did influence solution exploration across trials, with demonstrations containing causally irrelevant actions decreasing exploration of alternative methods. These results imply that uncertain environments can result in canalized social learning from specific classes of mode

Using an evidence-based online module to improve parents’ ability to manage their child with Developmental Coordination Disorder

Background : Developmental coordination disorder (DCD) is a prevalent neurodevelopmental disorder. Best practices include raising parents’ awareness and building capacity but few interventions incorporating these best practices are documented. Objective : To examine whether an evidence-based online module can increase the perceived knowledge and skills of parents of children with DCD, and lead to behavioural changes when managing their child’s health condition. Methods : A mixed-methods, before-after-follow-up design guided by the theory of planned behaviour was employed. Data about the knowledge, skills and behaviours of parents of children with DCD were collected using questionnaires prior to completing the module, immediately after, and three months later. One-way repeated measures ANOVAs and thematic analyses were performed on data as appropriate. Results : Fifty-eight participants completed all questionnaires. There was a significant effect of time on self-reported knowledge [F(2.00,114.00)=16.37, p=0.00] and skills [F(1.81,103.03)=51.37, p=0.00] with higher post- and follow-up scores than pre-intervention scores. Thirty-seven (65%) participants reported an intention to change behaviour postintervention; 29 (50%) participants had tried recommended strategies at follow-up. Three themes emerged to describe parents’ behavioural change: sharing information, trialing strategies and changing attitudes. Factors influencing parents’ ability to implement these behavioural changes included clear recommendations, time, and ‘right’ attitude. Perceived outcomes associated with the parental behavioural changes involved improvement in well-being for the children at school, at home, and for the family as a whole. Conclusions : The online module increased parents’ self-reported knowledge and skills in DCD management. Future research should explore its impacts on children’s outcomes long-term.

Using an evidence-based online module to improve parents’ ability to manage their child with Developmental Coordination Disorder

Background : Developmental coordination disorder (DCD) is a prevalent neurodevelopmental disorder. Best practices include raising parents’ awareness and building capacity but few interventions incorporating these best practices are documented. Objective : To examine whether an evidence-based online module can increase the perceived knowledge and skills of parents of children with DCD, and lead to behavioral changes when managing their child’s health condition. Methods : A mixed-methods, before-after design guided by the theory of planned behavior was employed. Data about the knowledge, skills and behaviors of parents of children with DCD were collected using questionnaires prior to completing the module, immediately after, and three months later. Paired T-tests, sensitivity analyses and thematic analyses were performed on data as appropriate. Results: One hundred-sixteen, 81 and 58 participants respectively completed the three questionnaires. For knowledge and skills, post- and follow-up scores were significantly higher than baseline scores (p<0.01). Fifty-two (64%) participants reported an intention to change behavior post-intervention and 29 (50%) participants had tried recommended strategies at follow-up. Three themes emerged to describe parents’ behavioral change: sharing information, trialing strategies and changing attitudes. Factors influencing parents’ ability to implement these behavioral changes included clear recommendations, time, and ‘right’ attitude. Perceived outcomes associated with the parental behavioral changes involved improvement in well-being for the children at school, at home, and for the family as a whole. Conclusions : The online module increased parents’ self-reported knowledge and skills in DCD management. Future research should explore its impacts on children’s long-term outcomes.

Normative reference values for the 20-meter shuttlerun test in a population-based sample of schoolchildren in Bogota, Colombia: The FUPRECOL Study

Our aim was to determine the normative reference values of cardiorespiratory fitness (CRF) and to establish the proportion of subjects with low CRF suggestive of future cardio-metabolic risk.

Ketamina para el tratamiento de la hiperalgesia causada por remifentanil en cirugía: revisión sistemática de literatura

La hiperalgesia secundaria a la administración de remifentanil se ha documentado tanto en estudios animales como en estudios experimentales en humanos y ha aumentado su incidencia dado su uso cada vez más frecuente para el mantenimiento durante diferentes procedimientos anestésicos, anestesia general balanceada, anestesia total intravenosa y sedaciones. La hiperalgesia secundaria al uso de remifentanil es un proceso pro-nociceptivo relacionado pero que difiere de la tolerancia aguda, en el que los neurotransmisores excitatorios de N- metil D aspartato (NMDA) juegan un rol central. Por tanto la ketamina se ha utilizado en diferentes dosis para la prevención de dicha hiperalgesia sin que se haya establecido su efectividad para la prevención y tratamiento de esta condición. Se encontraron 8 estudios publicados en los últimos 10 años que proponen a la ketamina como una estrategia útil y efectiva el tratamiento de la hiperalgesia inducida por el uso de remifentanil. Los resultados demuestran que la ketamina es un tratamiento costo efectivo para el tratamiento de la hiperalgesia en diferentes poblaciones sometidas a diversos procedimientos quirúrgicos y anestésicos que incluyan la administración de remifentanil tanto en la inducción como en el mantenimiento anestésico sin generar efectos secundarios adicionales, así como que logra disminuir el consumo de opioides y la EVA en el posoperatorio.

Caracterización y prevalencia del compromiso ocular en pacientes con enfermedad autoinmune y autoinflamatoria en un centro de referencia reumatológica en Colombia entre los años 2000 a 2015

RESUMEN Objetivo: Estimar la prevalencia de las diferentes enfermedades oftalmológicas que aparecen en el contexto de una enfermedad autoinmune (EAI) en pacientes de un centro de referencia reumatológica en Colombia, según características clínicas y sociodemográficas durante un período de 15 años, comprendido entre los años 2000 a 2015. Métodos: Se realizó un estudio descriptivo, observacional de prevalencia. El tipo de muestreo fue aleatorio estratificado con asignación proporcional en el programa Epidat 3.4. Los datos se analizaron en el programa SPSS v22.0 y se realizó análisis univariado de las variables categóricas, para las variables cuantitativas se realizaron medidas de tendencia central. Resultados: De 1640 historias clínicas revisadas, se encontraron 634 pacientes (38,65%) con compromiso ocular. Si excluimos los pacientes con SS, que por definición presentan ojo seco, 222 pacientes (13,53%) presentaron compromiso oftalmológico. Del total de pacientes, el 83,3% fueron mujeres. La AR fue la enfermedad autoinmune con mayor compromiso oftalmológico con 138 pacientes (62,2%), y en último lugar la sarcoidosis con 1 solo paciente afectado. La QCS fue la manifestación más común en todos los grupos diagnósticos de EAI, con 146 pacientes (63,5%). De 414 pacientes con Síndrome de Sjögren (SS) y QCS 8 presentaron compromiso ocular adicional, siendo la uveítis la segunda patología ocular asociada en pacientes con SS y la primera causa en las espondiloartropatias (71,4 %). Los pacientes con catarata (4,1%) presentaron la mayor prevalencia de uso de corticoide (88.8%). De 222 pacientes, 28 (12,6%) presentaron uveítis. Del total de pacientes, 16 (7,2%) presentaron maculopatía por antimalaráricos y 6 (18,75%) de los pacientes con LES. Los ANAS se presentaron en el 100% los pacientes con trastorno vascular de la retina. Los pacientes con epiescleritis presentaron la mayor proporción de positivización de anticuerpos anti-DNA. La EAI que más presentó epiescleritis fue LES con 4 pacientes (12,5%) El 22% de paciente con anticuerpos anti-RNP presentaron escleritis y 32,1% de los pacientes con uveítis presentaron HLA-B27 positivo. Las manifestaciones oftalmológicas precedieron a las sistémicas entre un 11,1% y un 33,3% de los pacientes. Conclusión: Las enfermedades oculares se presentan con frecuencia en los pacientes colombianos con EAI (38.65%), siendo la AR la enfermedad con mayor compromiso ocular (62,2%) y la QCS la enfermedad ocular con mayor prevalencia en todas las EAI (63,5%). La uveítis se presentó en 28 pacientes (12,6%). Las manifestaciones oftalmológicas pueden preceder a las sistémicas. El examen oftalmológico debe ser incluido en los pacientes con EAI, por ser la enfermedad ocular una comorbilidad frecuente. Adicionalmente, los efectos oftalmológicos de las medicaciones sistémicas utilizadas en EAI deben ser estrechamente monitorizados, durante el curso del tratamiento.