Prevalence of Dyskinesia and OFF by 30-Minute Intervals Through the Day and Assessment of Daily Episodes of Dyskinesia and OFF: Novel Analyses of Diary Data from Gocovri Pivotal Trials.

BACKGROUND: Parkinson\u27s disease (PD) patients using levodopa commonly develop dyskinesia and OFF episodes that reduce quality of life. OBJECTIVE: Evaluate prevalence of troublesome dyskinesia and OFF through the day, assessed by 30-minute intervals, as well as the mean number and duration of troublesome dyskinesia and OFF episodes, transitions between PD states, and effects of Gocovri® (amantadine) extended release capsules on these episodes. METHODS: Evaluate diary data from pooled Gocovri phase 3, placebo-controlled trials-analyzed for 17 hours following wake-up-at baseline and week 12. RESULTS: Diaries were evaluable for 162 patients. At baseline, 67% of patients woke up OFF, with prevalence decreasing to 13% at 2 hours and then remaining relatively steady at ∼12% (range, 6-17%) across half-hour intervals thereafter. Troublesome dyskinesia prevalence rose steadily from 5% to 24% over the first 2 hours, then fluctuated between 20% and 44% through the rest of the waking day. At baseline, patients experienced a mean of 3.0 daily episodes of troublesome dyskinesia (average duration 2.0 hours each), and 2.2 daily episodes of OFF (average duration 1.1 hour each). At week 12, Gocovri-treated patients showed greater reductions than placebo in troublesome dyskinesia and OFF episodes per day (treatment difference: -1.0 episodes and -0.4 episodes, respectively) and average episode duration (treatment difference: -0.6 hours and -0.3 hours, respectively). Mean duration of individual episodes of ON without troublesome dyskinesia (Good ON) increased by 5.0 hours for Gocovri, compared with 2.0 hours for placebo. Patients taking Gocovri experienced 2.2 fewer transitions between states than patients taking placebo. CONCLUSIONS: Troublesome dyskinesia and OFF occurred in the morning and throughout the waking day. Gocovri-treated patients experienced fewer, shorter episodes of both troublesome dyskinesia and OFF, thereby increasing the duration of continuous Good ON episodes and reducing the frequency of transitions between motor states

Utilization of remote sensing techniques for the quantification of fire behavior in two pine stands

Quantification of field-scale fire behavior is necessary to improve the current scientific understanding of wildland fires and to develop and test relevant, physics-based models. In particular, detailed descriptions of individual fires are required, for which the available literature is limited. In this work, two such field-scale experiments, carried out in pine stands under mild conditions, are presented. A particular focus was placed on non-intrusive measurement, as the capabilities of advanced remote sensing techniques, along with more traditional approaches, are explored. A description of the fires is presented, with spread occurring predominantly in the surface fuels with intensities in the range of 200–4400 kW m-1, and punctuated by isolated regions of crown fire. The occurrence of crown fire is investigated and linked to regions of greater canopy density, and it is found that the total fire intensity may increase locally to as much as 21,000 kW m-1. The light winds do not appear to play a direct role in the changes in fire behavior, while fuel structure may be important. The measurements described herein provided a reasonable overall description of the fires, however, the current resolution (both spatial and temporal) falls short of definitively explaining some transitional aspects of the fire behavior, and future improvements are suggested

Low Cost Autonomous Field-Deployable Environment Sensors

An Autonomous Environmental Sensor (AES) is a miniature electronic package combining position location capability (using the Global Positioning System (GPS)), communications (packet or voice-synthesized radio), and environmental detection capability (thermal, gas, radiation, optical emissions) into a small, inexpensive, deployable package. AESs can now be made with commercial off-the-shelf components. The AES package can be deployed at a study site by airdrop or by workers on the ground, and operates as a data logger (recording data locally) or as a sentry (transmitting data real-time). Using current low-power electronics technology, an AES can operate for a number of weeks using a simple dry battery pack, and can be designed to have a transmitting range of several kilometers with current low power radio communication technology. A receiver to capture the data stream from the AES can be made as light, inexpensive and portable as the AES itself. In addition, inexpensive portable repeaters can be used to extend the range of the AES and to coordinate many probes into an autonomous network

A hybrid contextual approach to wildland fire detection using multispectral imagery

Abstract—We propose a hybrid contextual fire detection algorithm for airborne and satellite thermal images. The proposed algorithm essentially treats fire pixels as anomalies in images and can be considered a special case of the more general clutter or background suppression problem. It utilizes the local background around a potential fire pixel and discriminates fire pixels based on the squared Mahalanobis distance in multispectral feature space. It also employs the normalized thermal index to identify background fire pixels that should be excluded from the calculation of the statistical properties of the local background. The use of the squared Mahalanobis distance naturally incorporates the covariance of the multispectral image into the decision and requires the setting of a single detection threshold. By contrast, previous contextual algorithms only incorporate the statistical properties of individual bands and require the manual setting of multiple thresholds. Compared with the latest Moderate Resolution Imaging Spectroradiometer fire product (version 4), our algorithm improves user accuracy and producer accuracy by 1.5 % and 2.6 % on average, respectively, and up to 28 % for some images. In addition, the novel use of the squared Mahalanobis distance allows us to create fire probability images that are useful for fire propagation modeling. As an example, we demonstrate this use for the airborne data. Index Terms—Anomaly detection, Mahalanobis distance, multispectral images, wildland fire detection

Quantification of Fuel Moisture Effects on Biomass Consumed Derived from Fire Radiative Energy Retrivals

Satellite based fire radiant energy retrievals are widely applied to assess biomass consumed and emissions at regional to global scales. A known potential source of uncertainty in biomass burning estimates arises from fuel moisture but this impact has not been quantified in previous studies. Controlled fire laboratory experiments are used in this study to examine the biomass consumed and the radiant energy release (Fire Radiative Energy, FRE, (MJ)) for western white pine needle fuels burned with water content (WC, unitless) from 0.01 to 0.14. Results indicate a significant re lationship: FRE per kilogram of fuel consumed = -5.32 W C+3.025(r2=0.83, n = 24, P \u3c 0.001) and imply that not taking into account fuel moisture variations in the assumed relationship between FRE and fuel consumed can lead to systematic biases. A methodological framework to derive a revised formula that enables the estimation of biomass consumed from FRE, which explicitly takes into account fuel water content, is presented