Similar Standard Deviations Research Articles

CT Perfusion imaging as prognostic factor for outcome of lacunar stroke

BackgroundEarly neurological deterioration (END) affects 20–30% of patients with lacunar stroke within 48 h despite optimal treatment. Previously established markers included infection and infarct location on imaging. We studied the utility of measuring global cerebral blood flow (gCBF) measured by CT-Perfusion (CTP) as an early predictor of END in patients with lacunar strokes.Methods162 patients with lacunar stroke were measured for gCBF including both cerebral hemispheres and cerebellum. We stratified patients by normal gCBF (> 40 ml/100 mg/min) vs. low gCBF (< 40 ml/100 mg/min). Stroke location, vascular risk factors, age and gender were assessed. The primary outcome was the change in the NIHSS score after 48 h from index stroke.ResultsMean gCBF of the overall cohort was 37.72 ml/100 mg/min. Both groups had a baseline NIHSS score of 4.2 with similar standard deviations. The NIHSS score decreased by 1.3 points in normal gCBF group and increased by 1.1 points in the low gCBF group. All stroke sites deteriorated in the low gCBF group, particularly the capsula interna, corona radiata, and lateral pontine area. END occurred in 37.8% in low gCBF compared to 3.1% in the normal gCBF patients. In contrast, clinical improvement after 48 h occurred in 64.2% of patients with normal gCBF but only 6.1% with low gCBF.ConclusionOur study supports measurement of gCBF by CTP as a potential imaging biomarker for END. Additionally, it adds evidence to the body of supporting the vulnerability of capsula interna and pontine infarctions to END.

Combining spaceborne lidar from the Global Ecosystem Dynamics Investigation with local knowledge for monitoring fragmented tropical landscapes: A case study in the forest-agriculture interface of Ucayali, Peru.

Improving our ability to monitor fragmented tropical ecosystems is a critical step in supporting the stewardship of these complex landscapes. We investigated the structural characteristics of vegetation classes in Ucayali, Peru, employing a co-production approach. The vegetation classes included three agricultural classes (mature oil palm, monocrop cacao, and agroforestry cacao plantations) and three forest regeneration classes (mature lowland forest, secondary lowland forest, and young lowland vegetation regrowth). We combined local knowledge with spaceborne lidar from NASA's Global Ecosystem Dynamics Investigation mission to classify vegetation and characterize the horizontal and vertical structure of each vegetation class. Mature lowland forest had consistently higher mean canopy height and lower canopy height variance than secondary lowland forest (μ = 29.40 m, sd = 6.89 m vs. μ = 20.82 m, sd = 9.15 m, respectively). The lower variance of mature forest could be attributed to the range of forest development ages in the secondary forest patches. However, secondary forests exhibited a similar vertical profile to mature forests, with each cumulative energy percentile increasing at similar rates. We also observed similar mean and standard deviations in relative height ratios (RH50/RH95) for mature forest, secondary forest, and oil palm even when removing the negative values from the relative height ratios and interpolating from above-ground returns only (mean RH50/RH95 of 0.58, 0.54, and 0.53 for mature forest, secondary forest, and oil palm, respectively) (p < .0001). This pattern differed from our original expectations based on local knowledge and existing tropical forest succession studies, pointing to opportunities for future work. Our findings suggest that lidar-based relative height metrics can complement local information and other remote sensing approaches that rely on optical imagery, which are limited by extensive cloud cover in the tropics. We show that characterizing ecosystem structure with a co-production approach can support addressing both the technical and social challenges of monitoring and managing fragmented tropical landscapes.

Performance Evaluation and Application Field Analysis of Precise Point Positioning Based on Different Real-Time Augmentation Information

The most commonly used real-time augmentation services in China are the International GNSS Service’s (IGS) real-time service (RTS), PPP-B2b service, and Double-Frequency Multi-Constellation (DFMC) service of the BeiDou Satellite-Based Augmentation System (BDSBAS) service. However, research on the performance evaluation, comparison, and application scope of these three products is still incomplete. This article introduces methods for obtaining real-time augmentation information and real-time orbit and clock offset recovery. Based on real-time orbit and clock offset accuracy, positioning accuracy, and positioning availability, this article systematically evaluates the performance and analyzes the application fields of Centre National d’Études Spatiales (CNES), PPP-B2b, and BDSBAS augmentation information. The results of the evaluation revealed that the radial accuracy of the CNES and PPP-B2b real-time orbit product is consistent, and the Root Mean Square (RMS) is better than 5 cm. The CNES real-time orbit product can achieve centimeter-level accuracy in both along-track and cross-track components, surpassing PPP-B2b’s decimeter-level accuracy. Both services demonstrate consistent accuracy in the real-time clock offset, with PPP-B2b showing similar standard deviations (STDs) of 0.16 ns for different satellites. However, for CNES, the STD of the real-time clock offset varies, with values of 0.10 ns, 0.19 ns, and 0.60 ns, respectively, for GPS, BDS-3 Medium Earth Orbit (MEO), and BDS-3 Inclined Geosynchronous Satellite Orbit (IGSO) satellites. Centimeter-level accuracy is achieved after convergence and positioning availability exceeds 99% for CNES and PPP-B2b services. Therefore, the difference between the two services in application areas depends on the acquisition of augmentation information. However, BDSBAS, which concentrates on code observations, demonstrates inferior performance in real-time orbit, clock offset, positioning accuracy, and positioning availability when compared to the other two services. Its primary application is in the aviation and maritime domains, where there is a greater need for service integrity, continuity, and reliability.

ASTM interlaboratory study on tensile testing of AM deposited and wrought steel using miniature specimens

An interlaboratory study, involving eigth international laboratories and coordinated by COMTES FHT (Czech Republic), was conducted to validate tensile measurements obtained using miniature specimens on additively manufactured (AM) components and artifacts. In addition to AM 316L stainless steel (316L SS), a wrought high-strength steel (34CrNiMo6V, equivalent to AISI 4340) was also used. Based on the results, a precision statement in accordance with ASTM E691 standard practice was developed, intended for inclusion in a proposed annex to the ASTM E8/E8M tension testing method. The primary outcomes of the study highlighted the agreement between yield and tensile strength measured from miniature and standard-sized tensile specimens. Furthermore, most tensile properties exhibited similar standard deviations, offering users insight into the efficacy of miniature specimen applications.

Validating Parallel-Forms Tests for Assessing Anesthesia Resident Knowledge.

We created a serious game to teach first year anesthesiology (CA-1) residents to perform general anesthesia for cesarean delivery. We aimed to investigate resident knowledge gains after playing the game and having received one of 2 modalities of debriefing. We report on the development and validation of scores from parallel test forms for criterion-referenced interpretations of resident knowledge. The test forms were intended for use as pre- and posttests for the experiment. Validation of instruments measuring the study's primary outcome was considered essential for adding rigor to the planned experiment, to be able to trust the study's results. Parallel, multiple-choice test forms development steps included: (1) assessment purpose and population specification; (2) content domain specification and writing/selection of items; (3) content validation by experts of paired items by topic and cognitive level; and (4) empirical validation of scores from the parallel test forms using Classical Test Theory (CTT) techniques. Field testing involved online administration of 52 shuffled items from both test forms to 24 CA-1's, 21 second-year anesthesiology (CA-2) residents, 2 fellows, 1 attending anesthesiologist, and 1 of unknown rank at 3 US institutions. Items from each form yielded near-normal score distributions, with similar medians, ranges, and standard deviations. Evaluations of CTT item difficulty (item p values) and discrimination (D) indices indicated that most items met assumptions of criterion-referenced test design, separating experienced from novice residents. Experienced residents performed better on overall domain scores than novices (P < .05). Kuder-Richardson Formula 20 (KR-20) reliability estimates of both test forms were above the acceptability cut of .70, and parallel forms reliability estimate was high at .86, indicating results were consistent with theoretical expectations. Total scores of parallel test forms demonstrated item-level validity, strong internal consistency and parallel forms reliability, suggesting sufficient robustness for knowledge outcomes assessments of CA-1 residents.

A Geometric Approach for the Calculation of the Nonrandomness Factor Using Computational Chemistry.

The nonrandomness factor (α) is a parameter related to the polarity (and consequent randomness of spatial orientation) of the molecules and is generally fixed between 0.20 and 0.47 since no technique has been developed so far for its accurate estimation. However, the consideration of a constant nonrandomness factor for mixtures is known to harden azeotrope description and to cause convergence issues in both the Nonrandom Two-Liquid (NRTL) and Universal Quasi-chemical (UNIQUAC) models, which have been widely applied in the correlation of phase equilibria. In this work, a novel geometric methodology, named Porto's approach, was applied in the calculation of the nonrandomness factors for 50 pure components (mainly alkanes, alcohols, and ketones) at 298.15 K and 0.1 MPa. This methodology relied on computational chemistry (Density Functional Theory, DFT) to minimize the energy of molecules in a cavity within a solvent composed of molecules of their own (applying the Polarizable Continuum Model, PCM), and thereafter define the most stable chemical configuration in the pure liquid state. Then, the nonrandomness factor of each component was determined based on its molecular dipole moment, which was calculated after a population analysis of the optimized partial electrical charges with the Natural Bond Orbital (NBO) function. This innovative approach was applied in the correlation of liquid-liquid equilibria (LLE) data for 15 ternary systems comprising only neutral molecules with NRTL and UNIQUAC. The classical methods (α = 0.2 or 0.3 for NRTL and α = 0.2 for UNIQUAC) were compared against the usage of a component-specific nonrandomness factor, and similar standard deviations were obtained. Hence, this work is considered a strong advance in the application of these excess free Gibbs energy models to phase equilibria estimation and opens the door to more accurate thermodynamic modeling of nonideal mixtures (such as the ones containing electrolytes) by providing enhanced physical meaning to the nonrandomness factors.

The Generic Conspiracist Beliefs Scale-5: further psychometric evaluation using a United Kingdom-based sample

The 5-item Generic Conspiracist Beliefs Scale (GCB-5) is an abridged version of the 15-item GCBS. It was developed as a global measure of the tendency to engage in non-event-based, conspiracy-related ideation. The GCB-5 is appealing to researchers because of its brevity, which facilitates the measurement of belief in conspiracies alongside multiple constructs and/or in situations where resources are limited (time, etc.). Noting that several studies failed to find an adequate unidimensional fit in the parent GCBS measures across different contexts, the present study further assessed the psychometric properties of the GCB-5. This was necessary since the GCB-5 was validated using North American samples. Thus, to ensure that the GCB-5 was satisfactory for use with samples in the United Kingdom (UK), GCBS/GCB-5 items were administered to a large, representative UK-based sample (N = 1,331), alongside a range of validated conspiracy scales. Confirmatory factor analysis found that a one-factor GCB-5 model produced a good model fit. This specified that the GCB-5 was underpinned by a single dimension. Furthermore, the performance of the GCB-5 was equivalent to the longer GCBS. Both instruments produced similar mean item scores and standard deviations and were comparably positively correlated with concurrent measures. Although the GCB-5 internal reliability was lower than the GCBS, it was good. The GCB-5 also demonstrated configural, metric, and scalar invariance (among gender and age subgroups). This indicated that the GCB-5 was interpreted similarly by men and women and different age groups. Overall, results supported the assertion that the GCB-5 is a psychometrically satisfactory global measure of non-event-based, conspiratorial ideation.

Exploring the Intensity, Frequency, and Duration of Pediatric Constraint Induced Movement Therapy Published Research: A Content Analysis.

Constraint Induced Movement Therapy (CIMT) utilizes a behavioral approach to neurorehabilitation involving constraint of an unaffected upper extremity which forces the use of the affected extremity. There is substantial evidence supporting the effectiveness of CIMT among both children and adults. The purpose of this study was to explore the frequency, intensity, and duration parameters across the published clinical outcomes related to pediatric CIMT (pCIMT) among children and youth populations. A content analysis approach was used to search the following databases Google Scholar, OT seeker, American Occupational Therapy Association special interest section, Medline, EbscoHost, and Cinhal. A total of 141 studies were identified via the initial search, with 51 studies meeting inclusion criteria. The findings revealed that 100% of the studies included restraint of the non-affected upper extremity, 73% incorporated repetitive task-oriented training, but less than half prescribed home practice strategies. Further, only 34% of the studies reviewed included all three components of CIMT. Outpatient hospital clinics and home-based settings were the most utilized settings for research studies. The mean minutes per session was M = 205.53, SD = 164.99. As part of the plan of care, the duration and frequency of therapy both had similar means (~M = 3.60) and standard deviations (~SD = 1.65). There was a significant variance of hours during (SD = 139.54) and outside of therapy (SD = 130.06). The results of this study, together with other emerging evidence, can assist practitioners in prescribing dosages dependent on the setting, the pediatric client, and their current functional status.

Measurement Error Versus Repeated Measurements: A Guide Describing Two Methods for Computing Bias and Precision of Migration Measurements From Double Examinations Using Radiostereometric Analysis.

Radiostereometric analysis is a method to measure implant migration where an ISO standard recommends double examinations (i.e., acquisition of two independent sets of biplanar images on the same day) to compute bias (i.e., mean) and precision (i.e., standard deviation) of differences in repeated migration measurements (termed repeated measurement statistics). However, repeated measurement statistics do not provide information regarding trueness of the measurements. Double examinations also can be used to compute measurement error statistics (i.e., mean and standard deviation of migration measurements relative to trueness). Our objectives were to derive measurement error and repeated measurement population parameters in six degrees of freedom (6DOF) and in maximum total point motion (MTPM), demonstrate quantitative differences by computing measurement error and repeated measurement statistics from a clinical study for an example implant, and demonstrate the importance of determining mean measurement error in MTPM. Three key findings were: (1) in 6DOF, measurement error and repeated measurement statistics were nearly identical; (2) for MTPM, measurement error and repeated measurement statistics had different means of 0.21 mm and 0.00 mm, respectively, but similar standard deviations; and (3) mean measurement error in MTPM is important for drawing conclusions about early implant stability. Because measurement error statistics are the same as repeated measurement statistics in 6DOF but provide additional information in the form of mean measurement error in MTPM, researchers should report measurement error instead of repeated measurement statistics. Furthermore, the ISO standard should be revised to include measurement error statistics.

Evaluation of the variation in relative response factors of GC-MS analysis with the internal standard methods: Application for the alcoholic products quality control

This paper focuses on the evaluation of variation of relative response factors (RRFs) obtained by two internal standard (IS) methods that are used to control the quality of alcoholic products. A standard IS method using 1-pentanol was compared with an “Ethanol as IS” method. The variation of RRF values for both methods was determined using standard solutions based on 20, 40 and 96% ethanol-water matrices. For this purpose, solutions of the ten most abundant volatile compounds were analysed at four different concentrations (250, 500, 1000 and 5000 mg L−1 absolute alcohol, AA) within these matrices. Each solution was measured four times by gas chromatography-mass spectrometry (GC-MS) in single ion monitoring (SIM) mode under repeatability conditions. Our results showed that for the 40% and 96% matrices, the ethanol and standard IS methods showed similar relative standard deviations (RSDs) variation of no more than 2% within the 250–1000 mg L−1 AA volatile compounds concentration range. For the 20% matrix as well as for the 250–5000 mg L−1 AA concentration range the resulting variation in calibration factors reaches 10% for both methods. As for the whole range of 20–96% alcohol by volume (ABV) and 250–5000 mg L−1 AA volatile concentration range, the resultant RRFs for the standard IS method (8% RSD) were more stable than those for the ethanol IS method (almost 40% RSD). Nonlinearity of the signal-to-amount dependence was also assessed with respect to the injection and detection processes.

Klinischer Vergleich eines neu entwickelten Prototyps zur Messung der Hornhautsensibilität zum aktuellen Goldstandard

Purpose. The aim of the study was to test a newly developed prototype for corneal sensitivity measurement (liquid jet (LJ) with saline as stimulus) for repeatability and correlation with the Cochet-Bonnet esthesiometer (CB). This is an excerpt of a master thesis, which was part of a larger study Material and Methods. Corneal sensitivity thresholds (CST) were determined for 30 subjects, in a clinical trial with 30 subjects, with each device on two separate dates (with inter- vals of at least one day and a maximum of fourteen days). In addition, the pain sensitivity questionnaire (PSQ) was applied to determine any possible correlation with corneal sensitivity. Results. Similar standard deviations of the CSTs for LJ and CB were obtained (LJ (M ± SD): 24.3 ± 2.0 dB; CB (M ± SD): 20.0 ± 2.0 dB). No statistically significant difference in CST was found between the two visits for LJ (mean differen- ce: -0.063 dB, p = 0.78), however there was a statistically significant difference for CB (mean difference: -0.641 dB, p = 0.003). LJ CSTs correlated moderately positively with CB CSTs and PSQ (LJ-CB: r = 0.476, p &lt; 0.001; LJ-PSQ: r = 0.437, p &lt; 0.001). Conclusion. LJ offers a significantly larger stimulus bandwidth than CB. Better reproducibility was observed for LJ, while correlation between the results for the two instruments was good. Significant moderate positive correlation was found between LJ CSTs and general pain sensitivity. Keywords esthesiometry, Cochet-Bonnet, Liquid Jet, prototype, PSQ

Detection enhancement at parts per billion level of aluminum in water droplets by a combination of acoustic levitation and nanoparticle enhanced laser induced breakdown spectroscopy

Nowadays, detecting metals dissolved in water is a paramount health concern, due to the sustained contamination of water reservoirs for human consumption. Limits of detection in the sub-ppm range are required, but a simple and fast method suitable to measure such levels is not easy to implement. Laser induced breakdown spectroscopy (LIBS) is a simple technique and can be employed on field, but its lack of sensitivity at sub-ppm has restricted its application. With the recent use of metallic nanoparticles to enhance the plasma emission, ppb limits of detection are achieved. In combination with liquid droplet acoustic levitation, this work demonstrate that few ppb limit of detection is possible measuring directly in the liquid sample without any pretreatment. When limits of detection obtained with and without the use of metallic nanoparticles are compared, improvements up to three orders of magnitude were obtained for aluminum dissolved in water, keeping similar relative standard deviations in the range of 10–20%. It is also important to note that after optimization, excitation energies as low as 1 mJ are sufficient to generate spectra with signal to noise ratios around 7 at concentrations below 1 ppb. The resulting spectra are suitable to be analyzed for quantification, opening the real possibility of its implementation on field applications.

Deep learning object detection to estimate the nectar sugar mass of flowering vegetation

Abstract Floral resources are a key driver of pollinator abundance and diversity, yet their quantification in the field and laboratory is laborious and requires specialist skills. Using a dataset of 25,000 labelled tags of fieldwork‐realistic quality, a convolutional neural network (Faster R‐CNN) was trained to detect the nectar‐producing floral units of 25 taxa in surveyors’ quadrat images of native, weed‐rich grassland in the United Kingdom. Floral unit detection on a test set of 50 model‐unseen images of comparable vegetation returned a precision of 90%, recall of 86% and F1 score (the harmonic mean of precision and recall) of 88%. Model performance was consistent across the range of floral abundance in this habitat. Comparison of the nectar sugar mass estimates made by the CNN and three human surveyors returned similar means and standard deviations. Over half of the nectar sugar mass estimates made by the model fell within the absolute range of those of the human surveyors. The optimal number of quadrat image samples was determined to be the same for the CNN as for the average human surveyor. For a standard quadrat sampling protocol of 10–15 replicates, this application of deep learning could cut pollinator‐plant survey time per stand of vegetation from hours to minutes. The CNN is restricted to a single view of a quadrat, with no scope for manual examination or specimen collection, though in contrast to human surveyors its object detection is deterministic and its floral unit definition is standardized. As agri‐environment schemes move from prescriptive to results‐based, this approach provides an independent barometer of grassland management which is usable by both landowner and scheme administrator. The model can be adapted to visual estimations of other ecological resources such as winter bird food, floral pollen volume, insect infestation and tree flowering/fruiting, and by adjustment of classification threshold may show acceptable taxonomic differentiation for presence–absence surveys.

A Digital Twins Machine Learning Model for Forecasting Disease Progression in Stroke Patients

Background: Machine learning methods have been developed to predict the likelihood of a given event or classify patients into two or more diagnostic categories. Digital twin models, which forecast entire trajectories of patient health data, have potential applications in clinical trials and patient management. Methods: In this study, we apply a digital twin model based on a variational autoencoder to a population of patients who went on to experience an ischemic stroke. The digital twin’s ability to model patient clinical features was assessed with regard to its ability to forecast clinical measurement trajectories leading up to the onset of the acute medical event and beyond using International Classification of Diseases (ICD) codes for ischemic stroke and lab values as inputs. Results: The simulated patient trajectories were virtually indistinguishable from real patient data, with similar feature means, standard deviations, inter-feature correlations, and covariance structures on a withheld test set. A logistic regression adversary model was unable to distinguish between the real and simulated data area under the receiver operating characteristic (ROC) curve (AUCadversary = 0.51). Conclusion: Through accurate projection of patient trajectories, this model may help inform clinical decision making or provide virtual control arms for efficient clinical trials.

Hot Subdwarf Stars Identified in Gaia DR2 with Spectra of LAMOST DR6 and DR7. II.Kinematics

Abstract Combining LAMOST radial velocities with Gaia parallaxes and proper motions, we present 3D Galactic space motions and the orbits of 182 single-lined hot subdwarf stars. These stars were identified by Lei et al. in Gaia DR2 with LAMOST DR6 and DR7 spectra. He-rich hot subdwarf stars with show the largest standard deviations of the Galactic velocity components and orbital parameters, while those with exhibit the second largest standard deviations. The two groups of He-deficient stars with show similar standard deviations, which are systematically lower compared to He-rich stars. We also present a kinematic population classification of the four hot subdwarf helium groups based on their positions in the U − V velocity diagram, the eccentricity diagram, and their Galactic orbits. The overall tendency of the fractional distributions of the four hot subdwarf helium groups in the halo, thin disk, and thick disk is largely consistent with the findings reported by Luo et al. based on LAMOST DR5, which appears to support predictions of binary population synthesis. He-deficient stars with likely originate from a stable Roche lobe overflow channel, He-deficient stars with from the common envelope ejection channel, and He-rich stars with from the merger channel of double He white dwarf stars. The fraction of He-rich hot subdwarf stars with in the thin disk and the halo is far higher than that in the thick disk, which implies that these stars have different formation channels in the thin disk and in the halo.

LC-Swan Probe: An Integrated In Situ Sampling Interface for Liquid Chromatography Separation and Mass Spectrometry Analysis

In situ sampling mass spectrometry (MS) systems can achieve rapid analysis of samples, while most of them do not have the pretreatment capability of chromatographic separation. This Article describes the design, fabrication, and application of a swan-shaped in situ sampling MS probe with liquid chromatography (LC) separation capacity. The LC-Swan probe was fabricated based on a single capillary with a micrometer-sized hole at its U-shaped bottom for sampling, a monolithic column for separation, and a tapered tip for electrospray. Four functions including in situ sampling, sample injection, chromatographic separation, and MS electrospray were integrated in the LC-Swan probe. Direct sampling and contacting-dissolution-injection sampling modes were developed to perform in situ sampling and injection of liquid samples and dry spot samples, respectively, in the high flow-resistance LC system. A pressing-sealing method was also developed using a polydimethylsiloxane (PDMS) sealer to achieve the sealing of the probe sampling hole during the high-pressure chromatographic separation process. The LC-Swan probe-based system exhibited effective desalting capacity in the analysis of angiotensin II with similar relative standard deviations (RSDs) of retention time and peak area below 3% and 19% (n = 3) for both salt-containing and salt-free samples. The present system was applied for analyzing cytochrome C digest to test its separation capability for samples with complex compositions, and 19 peptides were detected in 13 min with an amino acid coverage of 85%. We also applied the system in metabolite analysis of mouse organ sections of brain, liver, and kidney to preliminarily demonstrate its application potential in MS imaging analysis.

Indonesian Public Attitudes Toward Epilepsy (PATE) scale: Translation and psychometric evaluation

IntroductionEpilepsy stigma has been associated with poor quality of life among people with epilepsy (PWE). It is important to understand the variation and degree of epilepsy stigma in one of the most populous and culturally diverse nations in the world, Indonesia. Hence, this study aimed to test the validity and reliability of the Indonesian version of the Public Attitudes Toward Epilepsy (PATE) scale. MethodThe translation was performed according to standard principles and tested in 200 native Indonesian speakers who were aged above 18-year-old for psychometric validation. ResultsThe items in each domain had similar means and standard deviations (equal item variance), means ranging from 2.17 to 2.86 in general domain and 2.75 to 3.56 in personal domain and, standard deviations ranging from 0.87 to 1.05 and 0.88 to 1.01 in general and personal domain, respectively. Item-domain correlations were more than 0.5 for all items, and they correlate higher within their own domain compare with the other domain (convergent and divergent validity). Multitrait analysis showed similar variance, floor, and ceiling patterns to a great extent compared with the initial study. The Indonesian PATE scale also showed mostly similar correlation with demographic characteristics except monthly income. Principle axis analysis revealed strong factor loading (>0.3) in their hypothesized domain, except item 14. The Cronbach's α values for general and personal domains were 0.836 and 0.765, which were within the accepted range of 0.7 to 0.9. ConclusionThe Indonesian PATE scale is a validated and reliable translation for measuring public attitudes toward epilepsy.

Evaluation of gap-filling methods for Landsat 7 ETM+ SLC-off image for LULC classification in a heterogeneous landscape of West Africa

ABSTRACTThe Landsat mission which has existed over five decades has remained at the forefront of providing consistent moderate spatial and temporal resolution optical images of the earth. The failure of the scan line corrector (SLC) on board the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) in May 2003 has permanently resulted in data gaps on each Landsat 7 scene. Due to the obvious negative impacts on the image usability, a number of methods have been developed to fill the no-data areas in the image. This study assessed the performance of four Landsat 7 ETM+ SLC-off gap-filling methods in a highly heterogeneous landscape of West Africa for two different seasons (dry and rainy). The methods considered are: (1) Weighted Linear Regression (WLR) integrated with Laplacian Prior Regularization Method (LPRM), (2) Localised Linear Histogram Matching (LLHM), (3) Neighbourhood Similar Pixel Interpolator (NSPI) and (4) Geostatistical Neighbourhood Similar Pixel Interpolator (GNSPI). All the images used were Landsat 7 ETM+ SLC-off images, temporally close and from the same season for each set of time step. Visual comparison, mean, and standard deviations of the histograms of all bands of only the filled areas were used to assess the results. Additionally, overall accuracy (OA), kappa coefficient (κ), and balanced accuracy (BA) per class were used to evaluate a land use/cover (LULC) classification based on the gap-filled images. Visually, all the four methods were able to completely fill the gaps in the Landsat 7 ETM+ SLC-off image. They all look similar and spatially continuous with no anomalies or artefacts on them. The histograms from each band for only the filled areas for all the four methods also gave similar means and standard deviations in most cases. All the four gap-filling methods provided satisfactory results (OA >96% and κ> 0.937 in all methods for images in the dry season and OA >93% and κ> 0.877 for the image in the rainy season) in the land cover classification considering the complexity of the study area. But the GNSPI was superiority in all cases with the highest OA of 97.1% and κ of 0.947 in the dry season and OA of 94.6% and κ of 0.899 in the rainy season. This implies that the GNSPI is more robust in gap filling of Landsat 7 ETM+ SLC-off images than the other three methods in a heterogeneous landscape of West Africa regardless of the season. This study suggests that gap filling of Landsat 7 ETM+ SLC-off images will help to increase the number of Landsat images needed to build time-series data for a data-scarce region such as West Africa.

Comparing GAAP With NIPA Earnings

The U.S. Bureau of Economic Analysis produces a measure of aggregate corporate profits (national income and product accounts [NIPA] earnings), which is an integral component of the accounting for gross domestic product (GDP). Interesting features of NIPA earnings include consistent accounting rules over time and determination with little or no managerial discretion. Thus, NIPA earnings provide a useful benchmark for generally accepted accounting principles (GAAP) earnings, especially in parsing out the effects of real-economy versus the accounting in explaining the documented temporal increase in volatility and decline in persistence of GAAP earnings. We find that GAAP and NIPA earnings are closely related in the early years, with similar means and standard deviations, and with earnings changes correlating at .90 during 1950-1983. This close relation substantially deteriorates, however, during the second half of the sample period, 1984-2016. Although the behavior of NIPA earnings remains roughly the same, the volatility of GAAP earnings increases 10-fold, and the correlation between GAAP and NIPA earnings changes falls to .39. Additional tests reveal that the increase in the volatility of GAAP earnings is mostly due to rapid earnings reversals, especially the effect of large transient items during economic downturns. The frequency and severity of such downturns, however, are roughly the same across the two periods. In addition, there is little change in the properties of aggregate cash flow from operations and revenue over time. Overall, this evidence suggests that in addition to changes in the real economy, changing GAAP rules and their application are significant factors in the changing properties of GAAP earnings.

Obstacle recognition and avoidance during robot navigation in unknown environment

In this paper, firstly, a model for robot navigation in unknown environment is presented as a Simulink model. This model is applicable for obstacles avoidance during the robot navigation. However, the first model is unable to recognize the re-occurrences of the obstacles during the navigation. Secondly, an advanced algorithm, based on the standard deviations of laser scan range vectors, is proposed and implemented for robot navigation. The standard deviations of the lasers scans, robot positions and the time of scans with similar standard deviations are used to obtain the obstacle recognition feature. In addition to the obstacle avoidance, the second algorithm recognizes the re-appearances of the obstacles in the navigation path. Further, the obstacle recognition feature is used to break the repetitive path loop in the robot navigation. The experimental work is carried out on the simulated Turtlebot robot model using the Gazebo simulator.