Intelligent Computations for Flood Monitoring

Floods represent the most devastating natural hazards in the world, affecting more people and causing more property damage than any other natural phenomena. One of the important problems associated with flood monitoring is flood extent extraction from satellite imagery, since it is impractical to acquire the flood area through field observations. This paper presents a method to flood extent extraction from synthetic-aperture radar (SAR) images that is based on intelligent computations. In particular, we apply artificial neural networks, self-organizing Kohonen’s maps (SOMs), for SAR image segmentation and classification. We tested our approach to process data from three different satellite sensors: ERS-2/SAR (during flooding on Tisza river, Ukraine and Hungary, 2001), ENVISAT/ASAR WSM (Wide Swath Mode) and RADARSAT-1 (during flooding on Huaihe river, China, 2007). Obtained results showed the efficiency of our approach.

A self-referenced optical intensity sensor network using POFBGs for biomedical applications

This work bridges the gap between the remote interrogation of multiple optical sensors and the advantages of using inherently biocompatible low-cost polymer optical fiber (POF)-based photonic sensing. A novel hybrid sensor network combining both silica fiber Bragg gratings (FBG) and polymer FBGs (POFBG) is analyzed. The topology is compatible with WDM networks so multiple remote sensors can be addressed providing high scalability. A central monitoring unit with virtual data processing is implemented, which could be remotely located up to units of km away. The feasibility of the proposed solution for potential medical environments and biomedical applications is shown.

Methotrexate polyglutamates as a potential marker of adherence to long-term therapy in children with juvenile idiopathic arthritis and juvenile dermatomyositis:an observational, cross-sectional study

Introduction: Methotrexate (MTX) is a cornerstone of treatment in a wide variety of inflammatory conditions, including juvenile idiopathic arthritis (JIA) and juvenile dermatomyositis (JDM). However, owing to its narrow therapeutic index and the considerable interpatient variability in clinical response, monitoring of adherence to MTX is important. The present study demonstrates the feasibility of using methotrexate polyglutamates (MTXPGs) as a biomarker to measure adherence to MTX treatment in children with JIA and JDM. Methods: Data were collected prospectively from a cohort of 48 children (median age 11.5 years) who received oral or subcutaneous (SC) MTX therapy for JIA or JDM. Dried blood spot samples were obtained from children by finger pick at the clinic or via self- or parent-led sampling at home, and they were analysed to determine the variability in MTXPG concentrations and assess adherence to MTX therapy. Results: Wide fluctuations in MTXPG total concentrations (>2.0-fold variations) were found in 17 patients receiving stable weekly doses of MTX, which is indicative of nonadherence or partial adherence to MTX therapy. Age (P = 0.026) and route of administration (P = 0.005) were the most important predictors of nonadherence to MTX treatment. In addition, the study showed that MTX dose and route of administration were significantly associated with variations in the distribution of MTXPG subtypes. Higher doses and SC administration of MTX produced higher levels of total MTXPGs and selective accumulation of longer-chain MTXPGs (P < 0.001 and P < 0.0001, respectively). Conclusions: Nonadherence to MTX therapy is a significant problem in children with JIA and JDM. The present study suggests that patients with inadequate adherence and/or intolerance to oral MTX may benefit from SC administration of the drug. The clinical utility of MTXPG levels to monitor and optimise adherence to MTX in children has been demonstrated. Trial registration: ISRCTN Registry identifier: ISRCTN93945409. Registered 2 December 2011.

A digital signal processing approach for affective sensing of a computer user through pupil diameter monitoring

Recent research has indicated that the pupil diameter (PD) in humans varies with their affective states. However, this signal has not been fully investigated for affective sensing purposes in human-computer interaction systems. This may be due to the dominant separate effect of the pupillary light reflex (PLR), which shrinks the pupil when light intensity increases. In this dissertation, an adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a processed MPD (PMPD) signal, from which a classification feature, PMPDmean, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of stress states in the subject from whom the pupil diameter signal was recorded, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of stress and relaxation states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. The discriminating potential of each individual feature extracted from GSR, BVP and PD was studied by analysis of its receiver operating characteristic (ROC) curve. The ROC curve found for the PMPDmean feature encompassed the largest area (0.8546) of all the single-feature ROCs investigated. The encouraging results seen in affective sensing based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the benefits of using the AIC implementation with the HITV adaptive algorithm to isolate the PAR and the potential of using PD monitoring to sense the evolving affective states of a computer user.

Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

Medical advice, diabetes self-management, and health outcomes of a multi-ethnic population from the National Health and Nutrition Examination Survey 2007--2008

Diabetes self-management, an essential component of diabetes care, includes weight control practices and requires guidance from providers. Minorities are likely to have less access to quality health care than White non-Hispanics (WNH) (American College of Physicians-American Society of Internal Medicine, 2000). Medical advice received and understood may differ by race/ethnicity as a consequence of the patient-provider communication process; and, may affect diabetes self-management. ^ This study examined the relationships among participants’ report of: (1) medical advice given; (2) diabetes self-management, and; (3) health outcomes for Mexican-Americans (MA) and Black non-Hispanics (BNH) as compared to WNH (reference group) using data available through the National Health and Nutrition Examination Survey (NHANES) for the years 2007–2008. This study was a secondary, single point analysis. Approximately 30 datasets were merged; and, the quality and integrity was assured by analysis of frequency, range and quartiles. The subjects were extracted based on the following inclusion criteria: belonging to either the MA, BNH or WNH categories; 21 years or older; responded yes to being diagnosed with diabetes. A final sample size of 654 adults [MA (131); BNH (223); WNH (300)] was used for the analyses. The findings revealed significant statistical differences in medical advice reported given. BNH [OR = 1.83 (1.16, 2.88), p = 0.013] were more likely than WNH to report being told to reduce fat or calories. Similarly, BNH [OR = 2.84 (1.45, 5.59), p = 0.005] were more likely than WNH to report that they were told to increase their physical activity. Mexican-Americans were less likely to self-monitor their blood glucose than WNH [OR = 2.70 (1.66, 4.38), p<0.001]. There were differences among ethnicities for reporting receiving recent diabetes education. Black, non-Hispanics were twice as likely to report receiving diabetes education than WNH [OR = 2.29 (1.36, 3.85), p = 0.004]. Medical advice reported given and ethnicity/race, together, predicted several health outcomes. Having recent diabetes education increased the likelihood of performing several diabetes self-management behaviors, independent of race. ^ These findings indicate a need for patient-provider communication and care to be assessed for effectiveness and, the importance of ongoing diabetes education for persons with diabetes.^

Energy-efficient self -organization of wireless acoustic sensor networks for ground target tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Lifestyle Behaviors and Self-Rated Health: The Living for Health Program

Background. Lack of adherence to dietary and physical activity guidelines has been linked to an increase in chronic diseases in the United States (US). The aim of this study was to assess the association of lifestyle behaviors with self-rated health (SRH). Methods. This cross-sectional study used self-reported data from Living for Health Program ( 1,701) which was conducted from 2008 to 2012 in 190 health fair events in South Florida, US. Results. Significantly higher percent of females as compared to males were classified as obese (35.4% versus 27.0%), reported poor/fair SRH (23.4% versus 15.0%), and were less physically active (33.9% versus 25.4%). Adjusted logistic regression models indicated that both females and males were more likely to report poor/fair SRH if they consumed 2 servings of fruits and vegetables per day (, 95% CI 1.30–3.54; , 95% CI 1.12–7.35, resp.) and consumed mostly high fat foods (, 95% CI 1.03–2.43; , 95% CI 1.67–2.43, resp.). The association of SRH with less physical activity was only significant in females (, 95% CI 1.17–2.35). Conclusion. Gender differences in health behaviors should be considered in designing and monitoring lifestyle interventions to prevent cardiovascular diseases.

Diabetes Self Management: Are Cuban Americans Receiving Quality Health Care?

Objectives: We investigated the relationship among factors predicting inadequate glucose control among 182 Cuban-American adults (Females=110, Males=72) with type 2 diabetes mellitus (CAA). Study Design: Cross-sectional study of CAA from a randomized mailing list in two counties of South Florida Methods: Fasted blood parameters and anthropometric measures were collected during the study. BMI was calculated (kg/ m2). Characteristics and diabetes care of CAA were self-reported Participants were screened by trained interviewers for heritage and diabetes status (inclusion criteria: self-reported having type 2 diabetes; age  35 years, male and female; not pregnant or lactating; no thyroid disorders; no major psychiatric disorders). Participants signed informed consent form. Statistical analyses used SPSS and included descriptive statistic, multiple logistic and ordinal logistic regression models, where all CI 95%. Results: Eighty-eight percent of CAA had BMI of ≥ 25 kg/ m2. Only 54% reported having a diet prescribed/told to schedule meals. We found CAA told to schedule meals were 3.62 more likely to plan meals (1.81, 7.26), p<0.001) and given a prescribed diet, controlling for age, corresponded with following a meal plan OR 4.43 (2.52, 7.79, p<0.001). The overall relationship for HbA1c < 8.5 to following a meal plan was OR 9.34 (2.84, 30.7. p<0.001). Conclusions: The advantage of having a medical professional prescribe a diet seems to be an important environmental support factor in this sample’s diabetes care, since obesity rates are well above the national average. Nearly half CAA are not given dietary guidance, yet our results indicate CAA may improve glycemic control by receiving dietary instructions.

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

A Digital Signal Processing Approach for Affective Sensing of a Computer User through Pupil Diameter Monitoring

Recent research has indicated that the pupil diameter (PD) in humans varies with their affective states. However, this signal has not been fully investigated for affective sensing purposes in human-computer interaction systems. This may be due to the dominant separate effect of the pupillary light reflex (PLR), which shrinks the pupil when light intensity increases. In this dissertation, an adaptive interference canceller (AIC) system using the H∞ time-varying (HITV) adaptive algorithm was developed to minimize the impact of the PLR on the measured pupil diameter signal. The modified pupil diameter (MPD) signal, obtained from the AIC was expected to reflect primarily the pupillary affective responses (PAR) of the subject. Additional manipulations of the AIC output resulted in a processed MPD (PMPD) signal, from which a classification feature, PMPDmean, was extracted. This feature was used to train and test a support vector machine (SVM), for the identification of stress states in the subject from whom the pupil diameter signal was recorded, achieving an accuracy rate of 77.78%. The advantages of affective recognition through the PD signal were verified by comparatively investigating the classification of stress and relaxation states through features derived from the simultaneously recorded galvanic skin response (GSR) and blood volume pulse (BVP) signals, with and without the PD feature. The discriminating potential of each individual feature extracted from GSR, BVP and PD was studied by analysis of its receiver operating characteristic (ROC) curve. The ROC curve found for the PMPDmean feature encompassed the largest area (0.8546) of all the single-feature ROCs investigated. The encouraging results seen in affective sensing based on pupil diameter monitoring were obtained in spite of intermittent illumination increases purposely introduced during the experiments. Therefore, these results confirmed the benefits of using the AIC implementation with the HITV adaptive algorithm to isolate the PAR and the potential of using PD monitoring to sense the evolving affective states of a computer user.

Simultaneous high-resolution pH and spectrophotometric recordings of oxygen binding in native blood microvolumes, link to supplementary material

Oxygen equilibrium curves have been widely used to understand oxygen transport in numerous organisms. A major challenge has been to monitor oxygen binding characteristics and concomitant pH changes as they occur in vivo, in limited sample volumes. Here we report a technique allowing highly resolved and simultaneous monitoring of pH and blood pigment saturation in minute blood volumes. We equipped a gas diffusion chamber with a broad range fibre optic spectrophotometer and a micro-pH optode and recorded changes of pigment oxygenation along PO2 and pH gradients to test the setup. Oxygen binding parameters derived from measurements in only 15 µl of haemolymph from the cephalopod Octopus vulgaris showed low instrumental error (0.93%) and good agreement with published data. Broad range spectra, each resolving 2048 data points, provided detailed insight into the complex absorbance characteristics of diverse blood types. After consideration of photobleaching and intrinsic fluorescence, pH optodes yielded accurate recordings and resolved a sigmoidal shift of 0.03 pH units in response to changing PO2 from 0-21 kPa. Highly resolved continuous recordings along pH gradients conformed to stepwise measurements at low rates of pH changes. In this study we showed that a diffusion chamber upgraded with a broad range spectrophotometer and an optical pH sensor accurately characterizes oxygen binding with minimal sample consumption and manipulation. We conclude that the modified diffusion chamber is highly suitable for experimental biologists who demand high flexibility, detailed insight into oxygen binding as well as experimental and biological accuracy combined in a single set up.

The association of antihypertensives with postural blood pressure and falls among seniors residing in the community : a case control study

Date of Acceptance: 22/07/2015 This article is protected by copyright. All rights reserved.

The association of antihypertensives with postural blood pressure and falls among seniors residing in the community : a case control study

Date of Acceptance: 22/07/2015 This article is protected by copyright. All rights reserved.

The association of antihypertensives with postural blood pressure and falls among seniors residing in the community : a case control study

Date of Acceptance: 22/07/2015 This article is protected by copyright. All rights reserved.