Activities of daily living in children with developmental coordination disorder: Performance, learning, and participation

Background Children with developmental coordination disorder (DCD) face evident motor difficulties in daily functioning. Little is known, however, about their difficulties in specific activities of daily living (ADL). Objective The purposes of this study were: (1) to investigate differences between children with DCD and their peers with typical development for ADL performance, learning, and participation, and (2) to explore the predictive values of these aspects. Design. This was a cross-sectional study. Methods In both a clinical sample of children diagnosed with DCD (n=25 [21 male, 4 female], age range=5-8 years) and a group of peers with typical development (25 matched controls), the children’s parents completed the DCDDaily-Q. Differences in scores between the groups were investigated using t tests for performance and participation and Pearson chi-square analysis for learning. Multiple regression analyses were performed to explore the predictive values of performance, learning, and participation. Results Compared with their peers, children with DCD showed poor performance of ADL and less frequent participation in some ADL. Children with DCD demonstrated heterogeneous patterns of performance (poor in 10%-80% of the items) and learning (delayed in 0%-100% of the items). In the DCD group, delays in learning of ADL were a predictor for poor performance of ADL, and poor performance of ADL was a predictor for less frequent participation in ADL compared with the control group. Limitations A limited number of children with DCD were addressed in this study. Conclusions This study highlights the impact of DCD on children’s daily lives and the need for tailored intervention.

Development and psychometric properties of the DCDDaily: a new test for clinical assessment of capacity in activities of daily living in children with developmental coordination disorder

Objective To develop the DCDDaily, an instrument for objective and standardized clinical assessment of capacity in activities of daily living (ADL) in children with developmental coordination disorder (DCD), and to investigate its usability, reliability, and validity. Subjects Five to eight-year-old children with and without DCD. Main measures The DCDDaily was developed based on thorough review of the literature and extensive expert involvement. To investigate the usability (assessment time and feasibility), reliability (internal consistency and repeatability), and validity (concurrent and discriminant validity) of the DCDDaily, children were assessed with the DCDDaily and the Movement Assessment Battery for Children-2 Test, and their parents filled in the Movement Assessment Battery for Children-2 Checklist and Developmental Coordination Disorder Questionnaire. Results 459 children were assessed (DCD group, n = 55; normative reference group, n = 404). Assessment was possible within 30 minutes and in any clinical setting. For internal consistency, Cronbach’s α = 0.83. Intraclass correlation = 0.87 for test–retest reliability and 0.89 for inter-rater reliability. Concurrent correlations with Movement Assessment Battery for Children-2 Test and questionnaires were ρ = −0.494, 0.239, and −0.284, p < 0.001. Discriminant validity measures showed significantly worse performance in the DCD group than in the control group (mean (SD) score 33 (5.6) versus 26 (4.3), p < 0.001). The area under curve characteristic = 0.872, sensitivity and specificity were 80%. Conclusions The DCDDaily is a valid and reliable instrument for clinical assessment of capacity in ADL, that is feasible for use in clinical practice.

Prevention and management of foot problems in diabetes: A summary guidance for daily practice 2015, based on the IWGDF Guidance Documents

In this 'Summary Guidance for Daily Practice', we describe the basic principles of prevention and management of foot problems in persons with diabetes. This summary is based on the International Working Group on the Diabetic Foot (IWGDF) Guidance 2015. There are five key elements that underpin prevention of foot problems: (1) identification of the at-risk foot; (2) regular inspection and examination of the at-risk foot; (3) education of patient, family and healthcare providers; (4) routine wearing of appropriate footwear, and; (5) treatment of pre-ulcerative signs. Healthcare providers should follow a standardized and consistent strategy for evaluating a foot wound, as this will guide further evaluation and therapy. The following items must be addressed: type, cause, site and depth, and signs of infection. There are seven key elements that underpin ulcer treatment: (1) relief of pressure and protection of the ulcer; (2) restoration of skin perfusion; (3) treatment of infection; (4) metabolic control and treatment of co-morbidity; (5) local wound care; (6) education for patient and relatives, and; (7) prevention of recurrence. Finally, successful efforts to prevent and manage foot problems in diabetes depend upon a well-organized team, using a holistic approach in which the ulcer is seen as a sign of multi-organ disease, and integrating the various disciplines involved.

Variability of Indian summer monsoon rainfall in daily data from gauge and satellite

It has long been thought that tropical rainfall retrievals from satellites have large errors. Here we show, using a new daily 1 degree gridded rainfall data set based on about 1800 gauges from the India Meteorology Department (IMD), that modern satellite estimates are reasonably close to observed rainfall over the Indian monsoon region. Daily satellite rainfalls from the Global Precipitation Climatology Project (GPCP 1DD) and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are available since 1998. The high summer monsoon (June-September) rain over the Western Ghats and Himalayan foothills is captured in TMPA data. Away from hilly regions, the seasonal mean and intraseasonal variability of rainfall (averaged over regions of a few hundred kilometers linear dimension) from both satellite products are about 15% of observations. Satellite data generally underestimate both the mean and variability of rain, but the phase of intraseasonal variations is accurate. On synoptic timescales, TMPA gives reasonable depiction of the pattern and intensity of torrential rain from individual monsoon low-pressure systems and depressions. A pronounced biennial oscillation of seasonal total central India rain is seen in all three data sets, with GPCP 1DD being closest to IMD observations. The new satellite data are a promising resource for the study of tropical rainfall variability.

A conditional random field-based downscaling method for assessment of climate change impact on multisite daily precipitation in the Mahanadi basin

Downscaling to station-scale hydrologic variables from large-scale atmospheric variables simulated by general circulation models (GCMs) is usually necessary to assess the hydrologic impact of climate change. This work presents CRF-downscaling, a new probabilistic downscaling method that represents the daily precipitation sequence as a conditional random field (CRF). The conditional distribution of the precipitation sequence at a site, given the daily atmospheric (large-scale) variable sequence, is modeled as a linear chain CRF. CRFs do not make assumptions on independence of observations, which gives them flexibility in using high-dimensional feature vectors. Maximum likelihood parameter estimation for the model is performed using limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) optimization. Maximum a posteriori estimation is used to determine the most likely precipitation sequence for a given set of atmospheric input variables using the Viterbi algorithm. Direct classification of dry/wet days as well as precipitation amount is achieved within a single modeling framework. The model is used to project the future cumulative distribution function of precipitation. Uncertainty in precipitation prediction is addressed through a modified Viterbi algorithm that predicts the n most likely sequences. The model is applied for downscaling monsoon (June-September) daily precipitation at eight sites in the Mahanadi basin in Orissa, India, using the MIROC3.2 medium-resolution GCM. The predicted distributions at all sites show an increase in the number of wet days, and also an increase in wet day precipitation amounts. A comparison of current and future predicted probability density functions for daily precipitation shows a change in shape of the density function with decreasing probability of lower precipitation and increasing probability of higher precipitation.

Effects of transit quality of service characteristics on daily bus ridership

A case study of Brisbane, the capital city of Queensland, Australia, explored how explicit measures of transit quality of service (e.g., service frequency, service span, and travel time ratio) and implicit environmental predictors (e.g., topographic grade factor) influenced bus ridership. The primary hypothesis tested was that bus ridership was higher in suburbs with high transit quality of service than in suburbs with limited service quality. Multiple linear regression, used to identify a strong positive relationship between route intensity (bus-km/h-km2) and bus ridership, indicated that both increased service frequency and spatial route density corresponded to higher bus ridership. Additionally, the travel time ratio (i.e., the ratio of in-vehicle transit travel time to in-vehicle automobile travel time) had a significant negative association with suburban ridership: transit use declined as travel time ratio increased. In contrast, topographic grade and service span did not significantly affect suburban bus ridership. The study findings enhance the fundamental understanding of traveler behavior, which is informative to urban transportation policy, planning, and provision.

Towards an analysis framework of technology habituation by older users

Smart everyday objects could support the wellbeing, independent living and social connectedness of ageing people, but their successful adoption depends upon them fitting with their skills, values and goals. Many technologies fail in this respect. Our work is aimed at designs that engage older people by building on their individual affective attachment to habituated objects and leveraging, from a participatory design perspective, the creative process through which people continuously adapt their homes and tools to their own lifestyle. We contribute a novel analytic framework based on an analysis of related research on appropriation and habituated objects. It identifies steps in appropriation from inspection to performance and habituation. We test this framework with the preliminary testing of an augmented habituated object, a messaging kettle. While only used in one home so far, its daily use has provoked many thoughts, scenarios and projections about use by friends, both practical, utopian and dystopian.

Book Review: "The Interface: IBM and the Transformation of Corporate Design, 1945-1975", John Harwood, Minneapolis: University of Minnesota Press, 2011

Within the history of twentieth-century design, there are a number of well-known objects and stories that are invoked time and time again to capture a pivotal moment or summarize a much broader historical transition. For example, Marcel Breuer’s Model B3 chair is frequently used as a stand-in for the radical investigations of form and new industrial materials occurring at the Bauhaus in the mid-1920s. Similarly, Raymond Loewy’s streamlined pencil sharpener has become historical shorthand for the emergence of modern industrial design in the 1930s. And any discussion of the development of American postwar “organic design” seems incomplete without reference to Charles and Ray Eames’s molded plywood leg splint of 1942. Such objects and narratives are dear to historians of modern design. They are tangible, photogenic subjects that slot nicely into exhibitions, historical surveys, and coffee-table best sellers...

Consumer’s comparison between local and imported organic products: A hedonic analysis of the Japanese table wine market

Although hundreds of thousands of organic products are traded on a daily basis, it is less known how imported organic products are evaluated by consumers in an importing country. The paper analyzes Japanese wine point of sale (POS) data to examine whether consumers differentiate between local and imported organic products. The results of our hedonic analyses show that the premium for imported organic red (white) wines is about 42.996 % (8.872 %) while that for domestic red (white) organic wines is about 6.440 % (1.214 %), implying that Japanese consumers pay higher premiums for imported organic agricultural products than for those produced in Japan.

Nonlinear ensemble prediction of chaotic daily rainfall

The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

Fidgeting is associated with lower mortality risk

Context Evidence from prospective cohort studies has suggested that high volumes of reported daily sitting time is associated with mortality.1 ,2 However, not all have observed the same association.3 Fidgeting (small movements associated with nervousness or impatience), could provide additional energy expenditure when sitting, although the relationship with sitting and health outcomes had yet to be examined. Hagger-Johnson et al examined data from nearly 13 000 women to determine whether fidgeting modified the association between sitting time and mortality. Methods This study featured prospective data from 12 778 participants (aged 37–78 years) in the Women's Cohort Study (UK). Average daily sitting time was reported for weekdays and weekend days, and combined …

Towards Multiculturalism in Turkish Public Service Broadcasting

The announcement of Turkey as a European Union (EU) candidate country in the Helsinki Summit (10, 11 December 1999) marked a distinct change of identity policy and attitudes towards its citizens. A result in the shift of mindset has been the launch of the first public service broadcasting TV channel for Kurdish people on the 1st of January 2009. TRT 6 (Şeş) broadcasting in unofficial Kurdish language is run by Turkish Radio and Television Corporation (TRT). The thesis attempts to elaborate on the discussions surrounding the launch of TRT 6, Turkey’s first public service broadcasting TV channel for its Kurdish citizens. The research aims at finding the discourses of multiculturalism and public service broadcasting through the mainstream Turkish newspapers, Cumhuriyet, Hurriyet, Sabah, Taraf and Zaman. The method used for the research is Critical Discourse Analysis (CDA) and the representative newspapers of the Turkish print media are under the question: How has the launch of TRT 6, as the first public service broadcasting channel of Turkey in Kurdish language, been discussed by Turkish daily newspapers in terms of multiculturalism and minority media? The most significant results of the research is that the concerning newspapers have mostly discussed the launch of TRT 6 in the same line with their political affiliation. Thus it is comprehensively concluded that the selected newspapers proved holding a high level of political parallelism, and low professionalism. However, it should be noted that Taraf differs itself from others while challenging the hegemonic discourses embedded in the articles of the other newspapers. Moreover, the study detected three types of discourses: Pro-multiculturalism discourse, Unification discourse, and Assimilation discourse. It can be concluded that in Turkey, media owners and even individual journalists have incentives to form ideological alliances with political parties, and media appears to be an instrument of power struggle. Today, Turkey seems to restore Kurdish identity in its identity policy and aims to proceed with the negotiation for membership of the European Union (EU). The country still strives to transform from the traditional nation-state to a multiethnic democratic state, with multiculturalism as a policy discussed throughout the two terms that the AKP government has been in power. However, this transformation is not an easy process because of the deep-rooted traditions of the nation-state structure that has also polarized the Turkish press.

Predictive uncertainty of chaotic daily streamflow using ensemble wavelet networks approach

Perfect or even mediocre weather predictions over a long period are almost impossible because of the ultimate growth of a small initial error into a significant one. Even though the sensitivity of initial conditions limits the predictability in chaotic systems, an ensemble of prediction from different possible initial conditions and also a prediction algorithm capable of resolving the fine structure of the chaotic attractor can reduce the prediction uncertainty to some extent. All of the traditional chaotic prediction methods in hydrology are based on single optimum initial condition local models which can model the sudden divergence of the trajectories with different local functions. Conceptually, global models are ineffective in modeling the highly unstable structure of the chaotic attractor. This paper focuses on an ensemble prediction approach by reconstructing the phase space using different combinations of chaotic parameters, i.e., embedding dimension and delay time to quantify the uncertainty in initial conditions. The ensemble approach is implemented through a local learning wavelet network model with a global feed-forward neural network structure for the phase space prediction of chaotic streamflow series. Quantification of uncertainties in future predictions are done by creating an ensemble of predictions with wavelet network using a range of plausible embedding dimensions and delay times. The ensemble approach is proved to be 50% more efficient than the single prediction for both local approximation and wavelet network approaches. The wavelet network approach has proved to be 30%-50% more superior to the local approximation approach. Compared to the traditional local approximation approach with single initial condition, the total predictive uncertainty in the streamflow is reduced when modeled with ensemble wavelet networks for different lead times. Localization property of wavelets, utilizing different dilation and translation parameters, helps in capturing most of the statistical properties of the observed data. The need for taking into account all plausible initial conditions and also bringing together the characteristics of both local and global approaches to model the unstable yet ordered chaotic attractor of a hydrologic series is clearly demonstrated.

Multivariate nonlinear ensemble prediction of daily chaotic rainfall with climate inputs

The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.