Mesoscale geomorphic change on barrier estuarine regime at the tropical coast of Chandipur, India: Evidence from assessment of grain-size distribution

It is crucial for policy makers and environmental managers to determine the future dynamics of coastal wetlands, especially the existence of their response, disruption, and recovery regimes. Reconstruction of meso-scale evolution in coastal ecosystems can help to adapt coastal resource management techniques to the natural scales of system activity, thereby encouraging true biodiversity. This research provides an overview of decadal (mesoscale) geomorphic transition by high-resolution grain size analysis of a sediment deposit from a barrier estuary regime on the Chandipur coast, India. Coastal marshland’s grain size distribution (GSD) has generally been analyzed using End Member Mixing Models (EMMA) and Probability Density Function (PDF) methods (e.g. log-normal, log skew-Laplace). Although these techniques do not consider the compositional nature of the records, which can undermine the outcomes of the interpretation of sedimentary deposits. The approach to reliable granulometric analysis of lithostratigraphic sequences aims at establishing direct links between fluid dynamics and subsequent shifts in the texture of sediments. In this study, GSD analysis of marsh sediment is represented by compositional data analysis (CoDa) and a multivariate statistical framework. Barrier estuary evolution, presented by time lapses of satellite maps coupled with grain size and carbon content of marsh sediment, primarily reflects the evolving hydrodynamics of the back barrier area. These findings will provide a statistically robust analysis of the depositional system in coastal marshland. Multiannual environmental variations in the back barrier configuration illustrate the importance of this applied approach with respect to bridging the basis of estuarine evolution and process information.

Cross-Sectional Associations Between 24-hour Activity Behaviours and Motor Competence in Youth: A Compositional Data Analysis

Background The study aimed to examine the cross-sectional associations between 24-hour activity compositions and motor competence in children and adolescents, while stratifying by sex and school type, and investigate the predicted differences in motor competence when time was reallocated between activity behaviours. Methods Data were collected from 359 participants (aged 11.5±1.4 years; 49.3% boys; 96.9% White British). Seven-day 24-hour activity behaviours (sleep, sedentary time, light physical activity (LPA), moderate-to-vigorous physical activity (MVPA)) were assessed using wrist-worn accelerometers. Motor competence outcomes were obtained using the Dragon Challenge (process, product, time, and overall scores). Linear mixed models examined associations between activity behaviour compositions and motor competence outcomes for all participants and stratified by school type (primary or secondary) and sex. Post-hoc analyses modelled the influence of reallocating fixed durations of time between activity behaviours on outcomes. Results In all participants, relative to other activity behaviours, MVPA had the strongest associations with motor competence outcomes. The stratified models displayed that MVPA had the strongest associations with outcomes in both sexes, irrespective of school type. The largest positive, and negative predicted differences occurred when MVPA replaced LPA or sleep, and when LPA or sleep replaced MVPA, respectively. Conclusions Relative to other activity behaviours, MVPA appears to have the greatest influence overall on motor competence outcomes. Reallocating time from LPA or sleep to MVPA reflected the largest positive predicted changes in motor competence outcomes. Therefore, our findings reinforce the key role of MVPA for children’s and adolescents’ motor competence.

A novel adaptive discrete grey prediction model for forecasting development in energy consumption structure—from the perspective of compositional data

PurposeThe purpose of this study is to make a prediction of China's energy consumption structure from the perspective of compositional data and construct a novel grey model for forecasting compositional data.Design/methodology/approachDue to the existing grey prediction model based on compositional data cannot effectively excavate the evolution law of correlation dimension sequence of compositional data. Thus, the adaptive discrete grey prediction model with innovation term based on compositional data is proposed to forecast the integral structure of China's energy consumption. The prediction results from the new model are then compared with three existing approaches and the comparison results indicate that the proposed model generally outperforms existing methods. A further prediction of China's energy consumption structure is conducted into a future horizon from 2021 to 2035 by using the model.FindingsChina's energy structure will change significantly in the medium and long term and China's energy consumption structure can reach the long-term goal. Besides, the proposed model can better mine and predict the development trend of single time series after the transformation of compositional data.Originality/valueThe paper considers the dynamic change of grey action quantity, the characteristics of compositional data and the impact of new information about the system itself on the current system development trend and proposes a novel adaptive discrete grey prediction model with innovation term based on compositional data, which fills the gap in previous studies.

Geochemistry of Sub-Depositional Environments in Estuarine Sediments: Development of an Approach to Predict Palaeo-Environments from Holocene Cores

In the quest to use modern analogues to understand clay mineral distribution patterns to better predict clay mineral occurrence in ancient and deeply buried sandstones, it has been necessary to define palaeo sub-environments from cores through modern sediment successions. Holocene cores from Ravenglass in the NW of England, United Kingdom, contained metre-thick successions of massive sand that could not be unequivocally interpreted in terms of palaeo sub-environments using conventional descriptive logging facies analysis. We have therefore explored the use of geochemical data from portable X-ray fluorescence analyses, from whole-sediment samples, to develop a tool to uniquely define the palaeo sub-environment based on geochemical data. This work was carried out through mapping and defining sub-depositional environments in the Ravenglass Estuary and collecting 497 surface samples for analysis. Using R statistical software, we produced a classification tree based on surface geochemical data from Ravenglass that can take compositional data for any sediment sample from the core or the surface and define the sub-depositional environment. The classification tree allowed us to geochemically define ten out of eleven of the sub-depositional environments from the Ravenglass Estuary surface sediments. We applied the classification tree to a core drilled through the Holocene succession at Ravenglass, which allowed us to identify the dominant paleo sub-depositional environments. A texturally featureless (massive) metre-thick succession, that had defied interpretation based on core description, was successfully related to a palaeo sub-depositional environment using the geochemical classification approach. Calibrated geochemical classification models may prove to be widely applicable to the interpretation of sub-depositional environments from other marginal marine environments and even from ancient and deeply buried estuarine sandstones.

The Evaluation of the Impact of a Saharan Event on Particulate Matter Using Compositional Data Analysis

The proposed approach based on compositional data analysis was applied on simultaneous measurements of the mineral element concentrations of PM10 and PM2.5 from a typical suburban site with and without a Saharan event. The suburban site is located in the city of Rome. The selected mineral elements were Al, Si, Ca, Fe, Ti, Mg, and Sr. The data relating to these elements are reported in a previous study. The considered elements are mainly related to mineral matter. The proposed approach allows statistically validating that the mineral element concentrations of PM during days with a Saharan event differ from those without a Saharan event in terms of mineral element composition and size distribution. In particular, the results showed that the compositional data analysis applied to simultaneous measurements of mineral element concentrations of PM10 and PM2.5 is a helpful technique that can be used to study environmental sites affected by natural sources such as Saharan events. Moreover, the presented technique can be handy in all those conditions where it is important to discriminate whether the occurrence of an exceedance or a violation of the daily limit value established for PM could also be due to natural sources.

Changes in sedentary behavior patterns during the transition from childhood to adolescence and their association with adiposity: a prospective study based on compositional data analysis

Background To date, no longitudinal study using a compositional approach has examined sedentary behavior (SB) patterns in relation to adiposity in the pediatric population. Therefore, our aims were to (1) investigate the changes in SB patterns and adiposity from childhood to adolescence, (2) analyze the prospective compositional associations between changes in SB patterns and adiposity, and (3) estimate the changes in adiposity associated with substituting SB with physical activity (PA) of different intensities. Methods The study presents a longitudinal design with a 5-year follow-up. A total of 88 participants (61% girls) were included in the analysis. PA and SB were monitored for seven consecutive days using a hip-worn accelerometer. Adiposity markers (fat mass percentage [FM%], fat mass index [FMI], and visceral adiposity tissue [VAT]) were assessed using the multi-frequency bioimpedance analysis. The prospective associations were examined using compositional data analysis. Results Over the follow-up period, the proportion of time spent in total SB increased by 154.8 min/day (p < 0.001). The increase in total SB was caused mainly by an increase in middle and long sedentary bouts, as these SB periods increased by 79.8 min/day and 62.0 min/day (p < 0.001 for both), respectively. FM%, FMI, and VAT increased by 2.4% points, 1.0 kg/m2, and 31.5 cm2 (p < 0.001 for all), respectively. Relative to the remaining movement behaviors, the increase in time spent in middle sedentary bouts was significantly associated with higher FM% (βilr1 = 0.27, 95% confidence interval [CI]: 0.02 to 0.53) at follow-up. Lower VAT by 3.3% (95% CI: 0.8 to 5.7), 3.8% (95% CI: 0.03 to 7.4), 3.9% (95% CI: 0.8 to 6.9), and 3.8% (95% CI: 0.7 to 6.9) was associated with substituting 15 min/week spent in total SB and in short, middle, and long sedentary bouts, respectively, with an equivalent amount of time spent in vigorous PA. Conclusions This study showed unfavorable changes in SB patterns and adiposity status in the transition from childhood to adolescence. Incorporating high-intensity PA at the expense of SB appears to be an appropriate approach to reduce the risk of excess adiposity in the pediatric population.

Chemical Differentiation of Planets: A Core Issue

By plotting empirical chemical element abundances on Earth relative to the Sun and normalized to silicon versus their first ionization potentials, we confirm the existence of a correlation reported earlier. To explain this, we develop a model based on principles of statistical physics that predicts differentiated relative abundances for any planetary body in a solar system as a function of its orbital distance. This simple model is successfully tested against available chemical composition data from CI chondrites and surface compositional data of Mars, Earth, the Moon, Venus, and Mercury. We show, moreover, that deviations from the proposed law for a given planet correspond to later surface segregation of elements driven both by gravity and chemical reactions. We thus provide a new picture for the distribution of elements in the solar system and inside planets, with important consequences for their chemical composition. Particularly, a 4 wt% initial hydrogen content is predicted for bulk early Earth. This converges with other works suggesting that the interior of the Earth could be enriched with hydrogen.

Tuning the Morphology in the Nanoscale of NH4CN Polymers Synthesized by Microwave Radiation: A Comparative Study

A systematic study is presented to explore the NH4CN polymerization induced by microwave (MW) radiation, keeping in mind the recent growing interest in these polymers in material science. Thus, a first approach through two series, varying the reaction times and the temperatures between 130 and 205 °C, was conducted. As a relevant outcome, using particular reaction conditions, polymer conversions similar to those obtained by means of conventional thermal methods were achieved, with the advantage of a very significant reduction of the reaction times. The structural properties of the end products were evaluated using compositional data, spectroscopic measurements, simultaneous thermal analysis (STA), X-ray diffraction (XRD), and scanning electron microscopy (SEM). As a result, based on the principal component analysis (PCA) from the main experimental results collected, practically only the crystallographic features and the morphologies in the nanoscale were affected by the MW-driven polymerization conditions with respect to those obtained by classical syntheses. Therefore, MW radiation allows us to tune the morphology, size and shape of the particles from the bidimensional C=N networks which are characteristic of the NH4CN polymers by an easy, fast, low-cost and green-solvent production. These new insights make these macromolecular systems attractive for exploration in current soft-matter science.