Oral clonidine: an effective adjuvant in functional endoscopic sinus surgery

Background: A comparative study to evaluate the efficacy of intravenous Dexmedetomidine as a hypotensive agent in comparison to oral Clonidine in Endoscopic Nasal Surgery or Functional Endoscopic Sinus Surgery (FESS).Methods: Forty patients ASA I or II scheduled for Endoscopic Nasal Surgery were equally randomly assigned to receive either dexmedetomidine 1μg/Kg over 10 min before induction of anesthesia followed by 0.5μg/Kg/h infusion during maintenance (Group D), or oral Clonidine (Group C) 2µg/kg with minimal water 1 hour prior starting of surgery. Rescue bolus doses of Propofol (10mg/dose) were given to maintain mean arterial blood pressure (MAP) between (50-70mmHg). General anesthesia was maintained with Isoflurane 1%-2%. The surgical field was assessed using Average Category Scale. Hemodynamic variables (MAP and HR) were recorded at 10 minutes interval.Results: Both group C and group D reached the desired MAP (50-70mmHg) with no intergroup differences in HR but a statistically significant lower MAP was noticed in group C. The quality of the surgical field in the range of MAP (50-70mmHg) were 2-3 as per average category Scale with significantly lower score in Group C. Mean intraoperative propofol consumption was significantly higher in group D than C group.Conclusions: Both Dexmedetomidine or oral clonidine with isoflurane are safe agents for controlled hypotension, but oral clonidine provides lower MAP and better surgical field. Compared with Dexmedetomidine, oral clonidine offers the advantage of less consumption of propofol

Remnant vegetation in farmland - its significance in ethnobotany and local ecosystem

This paper evaluated the structure of remnant vegetation (RV) in and around the farmlands of Kancheepuram District, Tamil Nadu of Southern India, to understand its significance in the local ecosystem. Stratified quadrats along nine randomly selected transects were used for sampling vegetation. The study recorded 2495 specimens of 96 plant species under 43 families in 1848 quadrats (88 of 10 m × 10 m, 352 of 5 m × 5 m and 1408 of 1 m × 1 m dimensions) while there was a possibility of recording more species with better sampling efforts. To know the ethnobotanical uses of plants, interviews were conducted with local villagers and people belonging to the Irula tribe, and later the data were collated with published information. Sixty -six plant species were recorded with traditional uses in food, fodder, fuel, condiment and medicine. Prosopis juliflora, an alien invasive species, was a serious threat to the native flora since higher P. juliflora abundance was associated with declining diversity of other plants. The study found that the absence of monitoring and management protocols leading to uncontrolled propagation of invasive species could cause potential damage to the region’s dry evergreen forests, which were often located near the farmlands

Fault detection in a centrifugal pump using vibration and motor current signature analysis

Due to growth of mechanisation and automation, today’s industrial systems are becoming more complex. A small breakdown of any non-redundant machine component affects the operation of the entire system. To increase the availability and reliability, automated health monitoring and self-diagnostic capability (SDC) becoming essential to many industrial machineries like pumps, motors, etc. Condition monitoring does not prevent the failure, but it can predict the possibility of future failure by measuring certain machine parameters. Though there are various condition monitoring techniques, vibration analysis and motor current signature analysis (MCSA) are most suitable for detection of faults and abnormalities in machine systems. This work attempts to develop an SDC framework and diagnose the impeller condition of a centrifugal pump using MCSA. Time and frequency domain analyses are done for different impeller conditions of the pump, such as normal impeller and defective impellers. Significant differences are observed and a fault prediction strategy is recommended.Peer reviewe

Automatic identification of epileptic and background EEG signals using frequency domain parameters

The analysis of electroencephalograms continues to be a problem due to our limited understanding of the signal origin. This limited understanding leads to ill-defined models, which in turn make it hard to design effective evaluation methods. Despite these shortcomings, electroencephalogram analysis is a valuable tool in the evaluation of neurological disorders and the evaluation of overall cerebral activity. We compared different model based power spectral density estimation methods and different classification methods. Specifically, we used the autoregressive moving average as well as from Yule-Walker and Burg's methods, to extract the power density spectrum from representative signal samples. Local maxima and minima were detected from these spectra. In this paper, the locations of these extrema are used as input to different classifiers. The three classifiers we used were: Gaussian mixture model, artificial neural network, and support vector machine. The classification results are documented with confusion matrices and compared with receiver operating characteristic curves. We found that Burg's method for spectrum estimation together with a support vector machine classifier yields the best classification results. This combination reaches a classification rate of 93.33%, the sensitivity is 98.33% and the specificy is 96.67%

Results from a natural experiment: initial neighbourhood investments do not change objectively-assessed physical activity, psychological distress or perceptions of the neighbourhood

Abstract Background Few studies have assessed objectively measured physical activity (PA), active transportation, psychological distress and neighborhood perceptions among residents of a neighborhood before and after substantial improvements in its physical environment. Also, most research-to-date has employed study designs subject to neighborhood selection, which may introduce bias in reported findings. We built upon a previously enrolled cohort of households from two low-income predominantly African American Pittsburgh neighborhoods, matched on socio-demographic composition including race/ethnicity, income and education. One of the two neighborhoods received substantial neighborhood investments over the course of this study including, but not limited to public housing development and greenspace/landscaping. We implemented a natural experiment using matched intervention and control neighborhoods and conducted pre-post assessments among the cohort. Our comprehensive assessments included accelerometry-based PA, active transportation, psychological distress and perceptions of the neighborhood, with assessments conducted both prior to and following the neighborhood changes. In 2013, we collected data from 1003 neighborhood participants and in 2016, we re-interviewed 676 of those participants. We conducted an intent to treat analysis, with a difference-in-difference estimator using attrition weighting to account for nonresponse between 2013 and 2016. In addition, we derived an individual-level indicator of exposure to neighbourhood investment and estimated effect of exposure to investment on the same set of outcomes using covariate-adjusted models. Results We observed no statistically significant differences in activity, psychological distress, satisfaction with one’s neighborhood as a place to live or any of the other measures we observed prior to and after the neighborhood investments between the intervention and control neighborhoods or those exposed vs not exposed to investments. Conclusions Using this rigorous study design, we observed no significant changes in the intervention neighborhood above and beyond secular trends present in the control neighborhood. Although neighborhood investment may have other benefits, we failed to see improvement in PA, psychological distress or related outcomes in the low-income African American neighborhoods in our study. This may be an indication that improvements in the physical environment may not directly translate into improvements in residents’ physical activity or health outcomes without additional individual-level interventions. It is also possible that these investments were not dramatic enough to spur change within the three year period. Additional studies employing similar design with other cohorts in other settings are needed to confirm these results. Trial registration Trial Registration is not applicable since we did not prospectively assign individuals to a health-related intervention.https://deepblue.lib.umich.edu/bitstream/2027.42/148333/1/12966_2019_Article_793.pd

Pathways through which higher neighborhood crime is longitudinally associated with greater body mass index

Abstract Background Although crime and perceived safety are associated with obesity and body mass index (BMI), the pathways are less clear. Two likely pathways by which crime and perceived safety may impact obesity are through distress and physical activity. Methods We examined data from 2013 to 2014 for 644 predominantly African-American adults (mean age 57 years; 77% female) living in low-income Pittsburgh, PA neighborhoods, including self-reported perceptions of safety and emotional distress, interviewer-measured height/weight, and physical activity measured via accelerometry. We used secondary data on neighborhood crime from 2011 to 2013. We built a structural equation model to examine the longitudinal direct and indirect pathways from crime to BMI through perceived safety, distress and physical activity. Results Long-term exposure to crime was positively associated with lack of perceived safety (β = 0.11, p = 0.005) and lack of perceived safety was positively associated with BMI (β = 0.08, p = 0.03). The beneficial association between physical activity and BMI (β = −0.15, p < 0.001) was attenuated by a negative association between crime and physical activity (β = −0.09, p = 0.01). Although crime was associated with distress we found no evidence of a path from crime to BMI via distress. Conclusions Our findings suggest decrements in perceived safety and physical activity are important processes that might explain why neighborhood crime is associated with greater BMI.https://deepblue.lib.umich.edu/bitstream/2027.42/139054/1/12966_2017_Article_611.pd

A novel selection of optimal statistical features in the DWPT domain for discrimination of ictal and seizure-free electroencephalography signals

Properly determining the discriminative features which characterize the inherent behaviors of electroencephalography (EEG) signals remains a great challenge for epileptic seizure detection. In this present study, a novel feature selection scheme based on the discrete wavelet packet decomposition and cuckoo search algorithm (CSA) was proposed. The normal as well as epileptic EEG recordings were frst decomposed into various frequency bands by means of wavelet packet decomposition, and subsequently, statistical features at all developed nodes in the wavelet packet decomposition tree were derived. Instead of using the complete set of the extracted features to construct a wavelet neural networks-based classifer, an optimal feature subset that maximizes the predictive competence of the classifer was selected by using the CSA. Experimental results on the publicly available benchmarks demonstrated that the proposed feature subset selection scheme achieved promising recognition accuracies of 98.43–100%, and the results were statistically signifcant using z-test with p value <0.0001

ENERGY BALANCE IN ADOLESCENT GIRLS: THE TRIAL OF ACTIVITY FOR ADOLESCENT GIRLS COHORT

ObjectivesTo study correlates of change in BMI percentile and body fat among adolescent girlsDesign and MethodsA longitudinal prospective study following 265 girls from the Trial of Activity for Adolescent Girls (TAAG) cohort measured in 8th grade and during 10 and 11th grade or 11th and 12th grade. Twice during 2009-2011 girls wore an accelerometer and completed a food frequency questionnaire and 7-day diary documenting trips and food eaten away from home and school. Physical activity, BMI, and percent body fat were objectively measured at each time point.ResultsModerate to vigorous physical activity (MVPA) declined, but was not independently associated with changes in BMI percentile. Increased vigorous physical activity was associated with reductions in body fat. Diet was associated with both changes in BMI percentile and body fat. Girls who increased the percentage of caloric intake from snacks and desserts reduced their BMI percentile and body fat.ConclusionsSome relationships between energy balance behaviors and BMI and body composition were counter-intuitive. While it is plausible that vigorous activity would result in reductions of body fat, until more accurate methods are devised to measure diet, the precise contribution of dietary composition to health will be difficult to assess