Real-time temperature estimation for power MOSFETs considering thermal ageing effects

This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications.

State detection of bond wires in IGBT modules using eddy current pulsed thermography

Insulated gate bipolar transistor (IGBT) modules are important safety critical components in electrical power systems. Bond wire lift-off, a plastic deformation between wire bond and adjacent layers of a device caused by repeated power/thermal cycles, is the most common failure mechanism in IGBT modules. For the early detection and characterization of such failures, it is important to constantly detect or monitor the health state of IGBT modules, and the state of bond wires in particular. This paper introduces eddy current pulsed thermography (ECPT), a nondestructive evaluation technique, for the state detection and characterization of bond wire lift-off in IGBT modules. After the introduction of the experimental ECPT system, numerical simulation work is reported. The presented simulations are based on the 3-D electromagnetic-thermal coupling finite-element method and analyze transient temperature distribution within the bond wires. This paper illustrates the thermal patterns of bond wires using inductive heating with different wire statuses (lifted-off or well bonded) under two excitation conditions: nonuniform and uniform magnetic field excitations. Experimental results show that uniform excitation of healthy bonding wires, using a Helmholtz coil, provides the same eddy currents on each, while different eddy currents are seen on faulty wires. Both experimental and numerical results show that ECPT can be used for the detection and characterization of bond wires in power semiconductors through the analysis of the transient heating patterns of the wires. The main impact of this paper is that it is the first time electromagnetic induction thermography, so-called ECPT, has been employed on power/electronic devices. Because of its capability of contactless inspection of multiple wires in a single pass, and as such it opens a wide field of investigation in power/electronic devices for failure detection, performance characterization, and health monitoring.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Finite element model updating of a RC building considering seismic response trends

Peer reviewed

Two-Path All-pass Based Half-Band Infinite Impulse Response Decimation Filters and the Effects of Their Non-Linear Phase Response on ECG Signal Acquisition

This paper is based on the novel use of a very high fidelity decimation filter chain for Electrocardiogram (ECG) signal acquisition and data conversion. The multiplier-free and multi-stage structure of the proposed filters lower the power dissipation while minimizing the circuit area which are crucial design constraints to the wireless noninvasive wearable health monitoring products due to the scarce operational resources in their electronic implementation. The decimation ratio of the presented filter is 128, working in tandem with a 1-bit 3rd order Sigma Delta (ΣΔ) modulator which achieves 0.04 dB passband ripples and -74 dB stopband attenuation. The work reported here investigates the non-linear phase effects of the proposed decimation filters on the ECG signal by carrying out a comparative study after phase correction. It concludes that the enhanced phase linearity is not crucial for ECG acquisition and data conversion applications since the signal distortion of the acquired signal, due to phase non-linearity, is insignificant for both original and phase compensated filters. To the best of the authors’ knowledge, being free of signal distortion is essential as this might lead to misdiagnosis as stated in the state of the art. This article demonstrates that with their minimal power consumption and minimal signal distortion features, the proposed decimation filters can effectively be employed in biosignal data processing units.

Dental caries and obesity: their relationship in children

This evidence summary of dental caries and obesity: explores whether they are found in the same individuals and populations reviews and summarises what is currently known about their relationship using the published literature and routine public health monitoring data supports the dental public health and obesity teams, who may be asked about the relationship between these two outcomes

IoT Based Pain Management using Physiological Parameters

The continuous technology evaluation is benefiting our lives to a great extent. The evolution of Internet of things and deployment of wireless sensor networks is making it possible to have more connectivity between people and devices used extensively in our daily lives. Almost every discipline of daily life including health sector, transportation, agriculture etc. is benefiting from these technologies. There is a great potential of research and refinement of health sector as the current system is very often dependent on manual evaluations conducted by the clinicians. There is no automatic system for patient health monitoring and assessment which results to incomplete and less reliable heath information. Internet of things has a great potential to benefit health care applications by automated and remote assessment, monitoring and identification of diseases. Acute pain is the main cause of people visiting to hospitals. An automatic pain detection system based on internet of things with wireless devices can make the assessment and redemption significantly more efficient. The contribution of this research work is proposing pain assessment method based on physiological parameters. The physiological parameters chosen for this study are heart rate, electrocardiography, breathing rate and galvanic skin response. As a first step, the relation between these physiological parameters and acute pain experienced by the test persons is evaluated. The electrocardiography data collected from the test persons is analyzed to extract interbeat intervals. This evaluation clearly demonstrates specific patterns and trends in these parameters as a consequence of pain. This parametric behavior is then used to assess and identify the pain intensity by implementing machine learning algorithms. Support vector machines are used for classifying these parameters influenced by different pain intensities and classification results are achieved. The classification results with good accuracy rates between two and three levels of pain intensities shows clear indication of pain and the feasibility of this pain assessment method. An improved approach on the basis of this research work can be implemented by using both physiological parameters and electromyography data of facial muscles for classification.

Desenvolvimento de protótipo de aplicativo móvel em Android® para o controle e acompanhamento nutricional da saúde óssea em mulheres menopáusicas

Following a drop in estrogen in the period of menopause some women begin to lose bone mass more than 1% per year reaching the end of five years with loss greater than 25%. In this regard, factors such as older age, low calcium intake and premature menopause favor the onset of osteoporosis. Preventive methods such as nutritional counseling to a proper diet and the support of technology through applications that assess dietary intake are essential. Thus, this study aimed to develop an application for Android® platform focused on the evaluation of nutritional and organic conditions involved in bone health and risks for developing osteoporosis in postmenopausal women. To achieve this goal we proceeded to a study of 72 women aged 46-79 years, from the physical exercise for bone health of the Laboratory for Research in Biochemistry and Densitometry the Federal Technological University of Paraná program. Data were collected in the second half of 2014 through tests Bone Densitometry and Body Composition, Blood Tests, Anthropometric data and Nutrition Assessment. The study included women with a current diagnosis of osteopenia or osteoporosis primary, aged more than 45 years postmenopausal. For the assessment of bone mineral density and body composition used the device Absorptiometry Dual Energy X-ray (DXA) brand Hologic Discovery TM Model A. For anthropometric assessment was included to body mass, height, abdominal circumference, Waist circumference and hip circumference. The instrument for assessing food consumption was used Recall 24 hours a day (24HR). The estimated intake of energy and nutrients was carried from the tabulation of the food eaten in the Software Diet Pro 4®. In a sub sample of 30 women with osteopenia / osteoporosis serum calcium and alkaline phosphatase tests were performed. The results demonstrated a group of women (n = 30) average calcium intake of 570mg / day (± 340). The analysis showed a mean serum calcium within the normal range (10,20mg / dl ± 0.32) and average values and slightly increased alkaline phosphatase (105.40 U / L ± 23.70). Furthermore, there was a significant correlation between the consumption of protein and the optimal daily intake of calcium (0.375 p-value 0.05). Based on these findings, we developed an application early stage in Android® platform operating system Google®, being called OsteoNutri. We chose to use Java Eclipse® where it was executed Android® version of the project; choice of application icons and setting the visual editor for building the application layouts. The DroidDraw® was used for development of the three application GUIs. For practical tests we used a cell compatible with the version that was created (4.4 or higher). The prototype was developed in conjunction with the Group and Instrumentation Applications Development (GDAI) of the Federal Technological University of Paraná. So this application can be considered an important tool in dietary control, allowing closer control consumption of calcium and dietary proteins.

Beech bark disease distribution and resistance in Michigan and fungal endophyte ecology of resistant and susceptible beech (Fagus grandifolia Ehrh.)

Beech bark disease (BBD), a non-native association of the fungal pathogen Neonectria faginata and the beech scale insect Cryptococcus fagisuga, has dramatically affected American beech within North American forests. To monitor the spread and effects of BBD in Michigan, a network of forest health monitoring plots was established in 2001 following the disease discovery in Ludington State Park (Mason County). Forest health canopy condition and basic forestry measurements including basal area were reassessed on beech trees in these plots in 2011 and 2012. The influence of bark-inhabiting fungal endophytes on BBD resistance was investigated by collecting cambium tissue from apparently resistant and susceptible beech. Vigor rating showed significant influences of BBD in sample beech resulting in reduced health and substantiated by significant increases of dead beech basal area over time. C. fagisuga distribution was found to be spatially clustered and widespread in the 22 counties in Michigan's Lower Peninsula which contained monitoring plots. Neonectria has been found in Emmet, Cheboygan and Wexford in the Lower Peninsula which may coincide with additional BBD introduction locations. Surveys for BBD resistance resulted in five apparently resistant beech which were added to a BBD resistance database. The most frequently isolated endophytes from cambium tissue were identified by DNA sequencing primarily as Deuteromycetes and Ascomycetes including Chaetomium globosum, Neohendersonia kickxii and Fusarium flocciferum. N. faginata in antagonism trials showed significant growth reduction when paired with three beech fungal endophytes. The results of the antagonism trial and decay tests indicate that N. faginata may be a relatively poor competitor in vivo with limited ability to degrade cellulose.

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.

Cardiorespiratory fitness and cardiometabolic risk factors in schoolchildren from Colombia: The FUPRECOL Study

The objectives of this study are to investigate the association between cardiorespiratory fitness and cardiovascular risk factors in schoolchildren and to evaluate the degree of association between overall and abdominal adiposity and cardiorespiratory fitness. A total of 1,875 children and adolescents attending public schools in Bogota, Colombia (56.2% girls; age range of 9–17.9 years). A cardiovascular risk score (Z-score) was calculated and participants were divided into tertiles according to low and high levels of overall (sum of the skinfold thicknesses) and abdominal adiposity. Schoolchildren with a high level of overall adiposity demonstrated significant differences in seven of the 10 variables analyzed (i.e. systolic and diastolic blood pressure, triglycerides, triglycerides/HDL-c ratio, total cholesterol, glucose and cardiovascular risk score). Schoolchildren with high levels of both overall and abdominal adiposity and low cardiorespiratory fitness had the least favorable cardiovascular risk factors score. These findings may be relevant to health promotion in Colombian youth.

Application of a model updating technique for health condition monitoring and damage detection of flexible structures

This paper discusses the application of a damage detection methodology to monitor the location and extent of partial structural damage. The methodology combines, in an iterative way, the model updating technique based on frequency response functions (FRF) with monitoring data aiming at identifying the damage area of the structure. After the updating procedure reaches a good correlation between the models, it compares the parameters of the damage structure with those of the undamaged one to find the deteriorated area. The influence of the FEM mesh size on the evaluation of the extent of the damage has also been discussed. The methodology is applied using real experimental data from a spatial frame structure.

NMR structural analysis of cardiac troponin C: Monitoring conformational changes induced by binding calcium, troponin I, and calcium -sensitizing drugs

Contraction of cardiac muscle is regulated through the Ca2+ dependent protein-protein interactions of the troponin complex (Tn). The critical role cardiac troponin C (cTnC) plays as the Ca2+ receptor in this complex makes it an attractive target for positive inotropic compounds. In this study, the ten Met methyl groups in cTnC, [98% 13C ϵ]-Met cTnC, are used as structural markers to monitor conformational changes in cTnC and identify sites of interaction between cTnC and cardiac troponin I (cTnI) responsible for the Ca2+ dependent interactions. In addition the structural consequences that a number of Ca2+-sensitizing compounds have on free cTnC and the cTnC·cTnI complex were characterized. Using heteronuclear NMR experiments and monitoring chemical shift changes in the ten Met methyl 1H-13C correlations in 3Ca2+ cTnC when bound to cTnI revealed an anti-parallel arrangement for the two proteins such that the N-domain of cTnI interacts with the C-domain of cTnC. The large chemical shifts in Mets-81, -120, and -157 identified points of contact between the proteins that include the C-domain hydrophobic surface in cTnC and the A, B, and D helical interface located in the regulatory N-domain of cTnC. TnI association [cTnI(33–80), cTnI(86–211), or cTnI(33–211)] was found also to dramatically reduce flexibility in the D/E central linker of cTnC as monitored by line broadening in the Met 1H- 13C correlations of cTnC induced by a nitroxide spin label, MTSSL, covalently attached to cTnC at Cys 84. TnI association resulted in an extended cTnC that is unlike the compact structure observed for free cTnC. The Met 1H-13C correlations also allowed the binding characteristics of bepridil, TFP, levosimendan, and EMD 57033 to the apo, 2Ca2+, and Ca2+ saturated forms of cTnC to be determined. In addition, the location of drug binding on the 3Ca2+cTnC·cTnI complex was identified for bepridil and TFP. Use of a novel spin-labeled phenothiazine, and detection of isotope filtered NOEs, allowed identification of drug binding sites in the shallow hydrophobic cup in the C-terminal domain, and on two hydrophobic surfaces on N-regulatory domain in free 3Ca2+ cTnC. In contrast, only one N-domain drug binding site exists in 3Ca2+ cTnC·cTnI complex. The methyl groups of Met 45, 60 and 80, which are grouped in a hydrophobic patch near site II in cTnC, showed the greatest change upon titration with bepridil or TFP, suggesting that this is a critical site of drug binding in both free cTnC and when associated with cTnI. The strongest NOEs were seen for Met-60 and -80, which are located on helices C and D, respectively, of Ca2+ binding site II. These results support the conclusion that the small hydrophobic patch which includes Met-45, -60, and -80 constitutes a drug binding site, and that binding drugs to this site will lead to an increase in Ca2+ binding affinity of site II while preserving maximal cTnC activity. Thus, the subregion in cTnC makes a likely target against which to design new and selective Ca2+-sensitizing compounds. ^

Brain Structural Variability due to Aging and Gender in Cognitively Healthy Elders: Results from the Sao Paulo Ageing and Health Study

BACKGROUND AND PURPOSE: Several morphometric MR imaging studies have investigated age- and sex-related cerebral volume changes in healthy human brains, most often by using samples spanning several decades of life and linear correlation methods. This study aimed to map the normal pattern of regional age-related volumetric reductions specifically in the elderly population. MATERIALS AND METHODS: One hundred thirty-two eligible individuals (67-75 years of age) were selected from a community-based sample recruited for the Sao Paulo Ageing and Health (SPAH) study, and a cross-sectional MR imaging investigation was performed concurrently with the second SPAH wave. We used voxel-based morphometry (VBM) to conduct a voxelwise search for significant linear correlations between gray matter (GM) volumes and age. In addition, region-of-interest masks were used to investigate whether the relationship between regional GM (rGM) volumes and age would be best predicted by a nonlinear model. RESULTS: VBM and region-of-interest analyses revealed selective foci of accelerated rGM loss exclusively in men, involving the temporal neocortex, prefrontal cortex, and medial temporal region. The only structure in which GM volumetric changes were best predicted by a nonlinear model was the left parahippocampal gyrus. CONCLUSIONS: The variable patterns of age-related GM loss across separate neocortical and temporolimbic regions highlight the complexity of degenerative processes that affect the healthy human brain across the life span. The detection of age-related Ill GM decrease in men supports the view that atrophy in such regions should be seen as compatible with normal aging.