As a part of a large scale hyperspectral remote sensing campaign, water bio-optical properties were measured at 151 field stations from 2002 to 2008 at five U.S. estuaries: Apalachicola Bay, FL; ACE basin, SC; Grand Bay, MS; Delaware Bay, DE; and Chesapeake Bay, MD. At each station, water irradiance reflectance R(λ) spectra were acquired by ocean optic 2000 spectroradiometers. Simultaneously, concentrations of chlorophyll a and total suspended solids, as well as absorption of colored dissolved organic matter (CDOM) were measured. This paper focused on the relationships between reflectance R(λ) spectra and the in situ bio-optical constituents. A principal component analysis was conducted to characterize the general variability of reflectance R(λ) spectra, and a Canonical Correspondence Analysis was further performed to explore the relationships between spectral reflectance and water optically active constituents in coastal environments. The results suggested that water reflectance spectra in estuarine waters are the results of complex interactions among phytoplankton pigments, total suspended solids, and CDOM. The first principal component, which represents 72% of total variance of R(λ), is affected by backscattering of total suspended solids, and the absorption of CDOM at blue-green region of spectra; while the second principal component that representing 20% of variation of R(λ), is mainly driven by the absorption of Chlorophyll a in red and near infrared spectral regions. Furthermore, the results of this study could provide insights for using hyperspectral remote sensing as a cost effective approach for monitoring water quality in coastal waters.

Hyperspectral remote sensing reflectance was measured for a series of phytoplankton cultures as the first step in determining major taxon in an algal bloom by remote sensing. Two common bloom-forming species: Dinophyta, the dinoflagellate Prorocentrum minimum, and Cyanophyta, the cyanobacteria Synechococcus sp. were grown as mono cell cultures. Optical spectral measurements were taken from the cultures during logarithmic growth phases with progressive dilutions and culture mixtures. The primary objective of this study was to obtain base line reflectance spectra which can be used as references for remote sensing of algal blooms. Furthermore, the derivative analysis was applied to the reflectance spectra to explore the spectral features that can be used to identify phytoplankton taxon. Results showed that spectral reflectance correlated with phytoplankton biomass. Applying mathematical operators to the spectra of mono cell cultures corresponded to observed spectra of culture mixtures. Our results further corroborate previous findings that for some cases, remote sensing reflectance (Rrs) can be used to identify the primary taxon in algal blooms.

The ability to review and analyze large amounts of data reliably and cost-effectively is important in both biomedical research and clinical care. We hypothesized that converting raw digital data to standard scores (Z scores) and gray-scale them based on their corresponding P values can be used to accomplish this. In Part 1 of the study, we recorded continuous digital electrocardiographic (ECG) and heart sound data from a subject undergoing acute anterior myocardial infarction (MI). We then computed Z scores of the digital data using the means and standard deviations of the data obtained during the pre-infarction period. In Part 2 of the study, we analyzed the digital ECG data from 576 subjects who had undergone coronary angiography and left ventriculography for the evaluation of possible coronary disease. We used the durations of Q waves in Lead aVF and of the initial R waves in Lead V2 as the ECG criteria of prior inferior and anterior MI, respectively. We calculated Z scores for these durations using the means and standard deviations of the subjects who had no angiographic evidence of coronary disease. Results show that in Part 1 of the study, the continuous recording of the gray-scale Z scores produced a highly intuitive display of the direction and statistical significance of simultaneous changes in five quantitative parameters known to be important for the detection and assessment of acute MI. In Part 2 of the study, the use of gray-scale Z scores revealed, in each of three subgroups, the distributions of subjects who met ECG criteria for inferior and anterior MI, respectively. Analyzing the Z scores to calculate diagnostic performances yielded results similar to those obtained using receiver-operating characteristic curves of the raw data. We conclude that the use of gray-scale Z scores is a highly efficient and statistically meaningful way to display diagnostic data produced by both continuous and individual recordings.

Abnormal resting state electroencephalogram (EEG) oscillations are reported in schizophrenia (SZ) and bipolar disorder, illnesses with overlapping symptoms and genetic risk. However, less evidence exists on whether similar EEG spectral abnormalities are present in individuals with both disorders or whether these abnormalities are present in first-degree relatives, possibly representing genetic predisposition for these disorders.Investigators examined 64-channel resting state EEGs of 225 SZ probands and 201 first-degree relatives (SZR), 234 psychotic bipolar (PBP) probands and 231 first-degree relatives (PBPR), and 200 healthy control subjects. Eight independent resting state EEG spectral components and associated spatial weights were derived using group independent component analysis. Analysis of covariance was conducted on spatial weights to evaluate group differences. Relative risk estimates and familiality were evaluated on abnormal spectral profiles in probands and relatives.Both SZ and PBP probands exhibited increased delta, theta, and slow and fast alpha activity. Post-hoc pair-wise comparison revealed increased frontocentral slow beta activity in SZ and PBP probands as well as SZR and PBPR. Augmented frontal delta activity was exhibited by SZ probands and SZR, whereas PBP probands and PBPR showed augmented fast alpha activity.Both SZ and PBP probands demonstrated aberrant low-frequency activity. Slow beta activity was abnormal in SZ and PBP probands as well as SZR and PBPR perhaps indicating a common endophenotype for both disorders. Delta and fast alpha activity were unique endophenotypes for SZ and PBP probands, respectively. The EEG spectral activity exhibited moderate relative risk and heritability estimates, serving as intermediate phenotypes in future genetic studies for examining biological mechanisms underlying the pathogenesis of the two disorders.

resource. The purpose of this study was to evaluate the utility of telemetry monitoring guidelines in predicting clinically significant arrhythmias. Methods: We performed a retrospective study of 562 patients admitted to the telemetry unit. Differences in the arrhythmia event rates was determined between the patients whose monitoring was appropriately indicated by the guidelines compared with the group in which monitoring was not indicated by the guidelines. In addition to tabulating the absolute number of arrhythmias, the clinical significance of the arrhythmiaswas also determined. Arrhythmiaswere defined as clinically significant if there was an intervention or change in management, such as a change in drug type or dosage; cardioversion; electrophysiological study; or transfer to an intensive care unit. Results: Fifty-one (12%) vs six (4%) patients had at least one arrhythmic event on telemetry in the indicated group compared with the telemetry not indicated group. None of the patients in the group whom telemetry was not indicated had a clinically significant arrhythmia. In contrast though, in patients in the indicated group who had at least one arrhythmic event, 36% of these events were clinically significant with P b .001. Conclusion: This study supports the effectiveness and utility of telemetry guidelines and reinforces the fact, patients not meriting the criteria for cardiac monitoring are unlikely to have clinically significant arrhythmic event. Even if they did have an arrhythmic event it would be very unlikely to be clinically significant that would change patient management in any way.

Left ventricular hypertrophy (LVH) and obesity are important cardiovascular risk factors. This study evaluates the influence of obesity on the diagnostic performance of the most used electrocardiographic criteria for LVH in hypertensive patients.One thousand two hundred four outpatients from the Hypertensive Unit of the Hospital São Paulo, São Paulo, SP, Brazil, were studied. All underwent 12-lead electrocardiogram and echocardiogram. The most known electrocardiographic criteria for LVH were assessed and compared with the left ventricular mass index obtained by echocardiogram in obese and nonobese groups of hypertensive patients.The population's mean age was 57.4 ± 4.7 years; 351 were men (29.1%) and 853 women (70.8%). Cornell voltage, Cornell duration, Sokolow-Lyon voltage, Romhilt-Estes criteria, and R wave in aVL 11 mm or higher showed a positive correlation with left ventricular mass index (P < .05). Notwithstanding, there were no changes regarding specificity for obese or nonobese characteristics. However, sensitivity had a statistically significant decrease in obese patients in regard to Sokolow-Lyon voltage and Romhilt-Estes criteria and strain pattern (P < .05).Cornell voltage and Cornell duration criteria, Perugia score, R wave in aVL, and QTc variable had no significant changes in diagnostic sensitivity in the obese patients.