Demo abstract: wind measurements for water quality studies in urban reservoirs

Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.

Fracture prediction from repeat BMD measurements in clinical practice

Summary: We investigated whether repeat BMD measurements in clinical populations are useful for fracture risk assessment. We report that repeat BMD measurements are a robust predictor of fracture in clinical populations; this is not affected by preceding BMD change or recent osteoporosis therapy. Introduction: In clinical practice, many patients selectively undergo repeat bone mineral density (BMD) measurements. We investigated whether repeat BMD measurements in clinical populations are useful for fracture risk assessment and whether this is affected by preceding change in BMD or recent osteoporosis therapy. Methods: We identified women and men aged ≥50 years who had a BMD measurement during 1990–2009 from a large clinical BMD database for Manitoba, Canada (n = 50,215). Patient subgroups aged ≥50 years at baseline with repeat BMD measures were identified. Data were linked to an administrative data repository, from which osteoporosis therapy, fracture outcomes, and covariates were extracted. Using Cox proportional hazards models, we assessed covariate-adjusted risk for major osteoporotic fracture (MOF) and hip fracture according to BMD (total hip, lumbar spine, femoral neck) at different time points. Results: Prevalence of osteoporosis therapy increased from 18 % at baseline to 55 % by the fourth measurement. Total hip BMD was predictive of MOF at each time point. In the patient subgroup with two repeat BMD measurements (n = 13,481), MOF prediction with the first and second measurements was similar: adjusted-hazard ratio (HR) per SD 1.45 (95 % CI 1.34–1.56) vs. 1.64 (95 % CI 1.48–1.81), respectively. No differences were seen when the second measurement results were stratified by preceding change in BMD or osteoporosis therapy (both p-interactions >0.2). Similar results were seen for hip fracture prediction and when spine and femoral neck BMD were analyzed. Conclusion: Repeat BMD measurements are a robust predictor of fracture in clinical populations; this is not affected by preceding BMD change or recent osteoporosis therapy.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

Spontaneous Interblink Time Distributions in Patients with Graves' Orbitopathy and Normal Subjects

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Time course of training-induced microcirculatory changes and of vegf expression in skeletal muscles of spontaneously hypertensive female rats

Exercise-induced vessel changes modulate arterial pressure (AP) in male spontaneously hypertensive rats (SHR). Vascular endothelial growth factor (VEGF) is important for angiogenesis of skeletal muscle. The present study evaluated the time course of VEGF and angiogenesis after short- and long-term exercise training of female SHR and Wistar Kyoto (WKY) rats, 8-9 weeks (200-250 g). Rats were allocated to daily training or remained sedentary for 3 days (N = 23) or 13 weeks (N = 23). After training, the carotid artery was catheterized for AP measurements. Locomotor (tibialis anterior and gracilis) and non-locomotor skeletal muscles (temporalis) were harvested and prepared for histologic and protein expression analyses. Training increased treadmill performance by all groups (SHR = 28%, WKY = 64%, 3 days) and (SHR = 141%, WKY = 122%, 13 weeks). SHR had higher values of AP than WKY (174 ± 4 vs 111 ± 2 mmHg) that were not altered by training. Three days of running increased VEGF expression (SHR = 28%, WKY = 36%) simultaneously with an increase in capillary-to-fiber ratio in gracilis muscle (SHR = 19%, WKY = 15%). In contrast, 13 weeks of training increased gracilis capillary-to-fiber ratio (SHR = 18%, WKY = 19%), without simultaneous changes in VEGF expression. Training did not change VEGF expression and capillarity of temporalis muscle. We conclude that training stimulates time- and tissue-dependent VEGF protein expression, independent of pressure levels. VEGF triggers angiogenesis in locomotor skeletal muscle shortly after the exercise starts, but is not involved in the maintenance of capillarity after long-term exercise in female rats.

A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements

The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.

Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Structural Health Monitoring in Smart Structures Through Time Series Analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Setting time and thermal expansion of two endodontic cements

The purpose of this study was to evaluate the setting time and the thermal expansion coefficient of 2 endodontic cements, MTA-Angelus and a novel cement called CER. The setting time was determined in accordance to ANSI/ADA specifications no. 57. Three samples of 10 mm diameter and 2 mm thickness were prepared for each cement. The thermal expansion measurements were performed by strain gauge technique. Four samples of each cement were prepared using silicone rings of 5 mm diameter and 2 mm thickness. The data were analyzed statistically using the Student t test. The setting time obtained for the MTA-Angelus and CER cements was 15 (SD 1) min and 7 (SD 1) min, respectively. The linear coefficient of thermal expansion was 8.86 (SD 0.28) mu strain/degrees C for MTA-Angelus and 11.76 (SD 1.20) mu strain/degrees C for CER. The statistical analysis showed significant difference (P < .05) in the setting time and linear coefficient of thermal expansion between the 2 cements. The CER cement has a coefficient of expansion similar to dentin, which could contribute to a decrease of microleakage degree.

Real-time ultrasound to predict rabbit carcass composition and volume of longissimus dorsi muscle

Real-time ultrasonography (RTU) was used to measure the longissimus dorsi muscle (LM) volume in vivo and to predict the carcass composition of rabbits. For this, 63 New Zealand White × Californian rabbits with 2093±63 g live weight were used. Animals were scanned between the 6th and 7th lumbar vertebrae using an RTU equipment with a 7.5 MHz probe. Measurements of LM volume were obtianed both in vivo and on carcass. Regression equations were used for the prediction of carcass composition and LM volume using the LM volume measured obtained with RTU (LMVU) as independent variable. Carcass meat, bone and total dissectible fat weights represented 780, 164 and 56 g/kg of the reference carcass weight, respectively. Regression equations showed a strong relationship between LMVU and the correspondent volume in carcass. Furthermore, LMVU was also useful in predicting the amounts of carcass tissues. It is possible to predict LM volume in the carcass using the LM volume measured in vivo by RTU. The amount of carcass tissues can be predicted by the LM volume measured in vivo by RTU.

TIME-COURSE DIFFUSION of HYDROGEN PEROXIDE USING MODERN TECHNOLOGIES

The concern with the hydrogen penetration towards the pulp can be observed on the literature by the great number of papers published on this topic; Those measurements often uses chemical agents to quantify the concentration of the bleaching agent that cross the enamel and dentin. The objective of this work was the quantification of oxygen free radicals by fluorescence that are located in the interface between enamel and dentin. It was used to accomplish our objectives a Ruthenium probe (FOXY R - Ocean Optics(R)) a 405nm LED, a bovine tooth and a portable diagnostic system (Science and support LAB - LAT - IFSC/USP). The fluorescence of the probe is suppressed in presence of oxygen free radicals in function of time. The obtained results clearly shows that the hydrogen peroxide when not catalyzed should be kept in contact with the tooth for longer periods of time.

Influence of surface sealant on the translucency of composite resin: effect of immersion time and immersion media

This study evaluated the effect of surface sealant on the translucency of composite resin immersed in different solutions. The study involved the following materials: Charisma, Fortify and coffee, Coca-Cola®, tea and artificial saliva as solutions. Sixty-four specimens (n = 8) were manufactured and immersed in artificial saliva at 37 ± 1 °C. Samples were immersed in the solutions for three times a day and re-immersed in artificial saliva until the translucency readings. The measurements were carried out at nine times: T1 - 24 hours after specimen preparation, T2 - 24 hours after immersion in the solutions, T3 - 48 hours and T4 to T9 - 7, 14, 21, 30, 60 and 90 days, respectively, after immersion. The translucency values were measured using a JOUAN device. The results were subjected to ANOVA and Tukey's test at 5%. The surface sealant was not able to protect the composite resin against staining, the coffee showed the strongest staining action, followed by tea and regarding immersion time, a significant alteration was noted in the translucency of composite resin after 21 days.

Time-dependent expression of annexin 1 in a model of chronic granulomatous inflammation

Objective and design: To determine the expression pattern and distribution of the glucocorticoid-inducible protein annexin 1 (ANXA1) in a murine model of chronic granulomatous inflammation.Materials or subjects: TO Mouse.Treatment: Chronic granulomatous inflammation was induced by injecting into dorsal sub-cutaneous air-pouches in mice, a mixture of croton oil and Freund's complete adjuvant (CO/FCA).Methods: Western and northern analysis, corticosterone assay, and immunohistochemistry. Statistical analysis was performed using ANOVA followed by Tukey's pair-wise comparisons or Dunnett's multiple comparisons.Results: ANXA1 protein levels changed significantly throughout the 4-week time course, with an initial peak at day 7 and a later elevation at 28 days. ANXA1 mRNA levels peaked at days 1 and 3, with a significant decline at day 7 followed by an upward trend to day 28. Plasma corticosterone measurements taken throughout the time course revealed an increase from 14 days onward, suggesting that corticosterone does not influence ANXA1 expression during the initial stages of the model. Immunogold staining revealed that ANXA1 expression in the inflamed tissue was mainly in extravasated neutrophils, with intact protein (37 kDa) being predominantly observed on the cell membrane.Conclusions: the pattern of ANXA1 expression indicates that infiltrated neutrophils are responsible for the majority of ANXA1 present both at early and later stages of this model of granulomatous inflammation.

Combined D0 measurements constraining the CP-violating phase and width difference in the B-s(0) system

We combine the D0 measurement of the width difference between the light and heavy B-s(0) mass eigenstates and of the CP-violating mixing phase determined from the time-dependent angular distributions in the B-s(0)-> J/psi phi decays along with the charge asymmetry in semileptonic decays also measured with the D0 detector. With the additional constraint from the world average of the flavor-specific B-s(0) lifetime, we obtain Delta Gamma(s)equivalent to(Gamma(L)-Gamma(H))=0.13 +/- 0.09 ps(-1) and vertical bar phi(s)vertical bar=0.70(-0.47)(+0.39) or Delta Gamma(s)=-0.13 +/- 0.09 ps(-1) and vertical bar phi(s)vertical bar=2.44(-0.39)(+0.47). The data sample corresponds to an integrated luminosity of 1.1 fb(-1) accumulated with the D0 detector at the Fermilab Tevatron Collider.

Quartz Crystal Microbalance monitoring the real-time binding of lectin with carbohydrate with high and low molecular mass

Quartz Crystal Microbalance (QCM) was used to monitor the mass changes on a quartz crystal surface containing immobilized lectins that interacted with carbohydrates. The strategy for lectin immobilization was developed on the basis of a multilayer system composed of Au-cystamine-glutaraldehyde-lectin. Each step of the immobilization procedure was confirmed by FTIR analysis. The system was used to study the interactions of Concanavalin A (ConA) with maltose and Jacalin with Fetuin. The real-time binding of different concentrations of carbohydrate to the immobilized lectin was monitored by means of QCM measurements and the data obtained allowed for the construction of Langmuir isotherm curves. The association constants determined for the specific interactions analyzed here were (6.4 +/- 0.2) X 10(4) M-1 for Jacalin-Fetuin and (4.5 +/- 0.1) x 10(2) M-1 for ConA-maltose. These results indicate that the QCM constitutes a suitable method for the analysis of lectin-carbohydrate interactions, even when assaying low molecular mass ligands such as disaccharides. Published by Elsevier B.V.