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Background: Understanding how sleep, sedentary behavior (SED), and physical activity (PA) (24-h movement profile) changes across pregnancy in individuals with prepregnancy overweight or obesity and how parity (previous births) impacts these changes can help inform interventions. Methods: In 155 participants, movement was measured using wrist-worn accelerometers, and sleep was self-reported in early (8–15 wk) and late (29–38 wk) pregnancy. The 24-hour movement profiles were analyzed using compositional analyses. Results: Nulliparous participants (no previous births) spent 33.95%, 38.14%, 25.32%, and 2.58% of the 24-hour day in early pregnancy in sleep, SED, light-intensity PA, and moderate/vigorous-intensity PA, respectively. Multiparous participants (≥1 previous birth) spent 2.50 percentage points less in SED (mean log-ratio difference = −0.068; 95% confidence interval [CI], −0.129 to −0.009) and 2.73 percentage points more in light-intensity PA (mean log-ratio difference = 0.102; 95% CI, 0.035 to 0.180). From early to late pregnancy, participants decreased the proportion of the 24-hour day spent asleep by 1.67 percentage points (mean log-ratio difference = −0.050; 95% CI, −0.092 to −0.011) and increased light-intensity PA by 1.56 percentage points (mean log-ratio difference = 0.057; 95% CI, 0.003 to 0.108), with no change in other behaviors. Conclusions: Nulliparous and multiparous individuals with prepregnancy overweight or obesity both had high levels of SED, with no change across pregnancy, and may require interventions to reduce SED. [ABSTRACT FROM AUTHOR]

Background: Daily time spent in moderate-to-vigorous physical activity (MVPA), light-intensity physical activity (LIPA), sedentary behaviour (SB) and sleep (collectively known as 'movement behaviours') are compositional, co-dependent variables. However, most studies examining effects of these behaviours on depression outcomes in older adults do not account for this. Study objectives were to use compositional data analysis methods to (1) examine the relationship between movement behaviour composition (daily time spent in MVPA, LIPA, SB, sleep) and depression symptoms, (2) estimate the extent to which changing time spent in any given movement behaviour within the movement behaviour composition was associated with changes in depression symptoms. Methods: 5643 older Canadian adults ≥ 65 years of age from the Canadian Longitudinal Study on Aging were studied using a quasi-longitudinal study design. Exposure was baseline daily movement behaviours; time spent in MVPA, LIPA and SB were derived from self-reported Physical Activity Scale for the Elderly responses. Night-time sleep was self-reported separately. Outcome was depression symptoms at follow-up obtained using the ten item Center for Epidemiologic Studies Depression Scale. Compositional data analysis was used to investigate associations between movement behaviours and depression symptoms. Results: Movement behaviour composition was significantly associated with depression symptoms. Time spent in MVPA [exp(B) = 0.97 (95% CI: 0.94, 0.99)] and sleep [exp(B) = 0.91 (95% CI: 0.85, 0.97)] relative to the remaining movement behaviours were associated with lower depression symptoms scores. Relative time spent in SB was associated with higher depression symptoms scores [exp(B) = 1.09 (95% CI: 1.04, 1.15)]. Time displacement estimates revealed that the greatest change in depression symptoms scores occurred when time spent in MVPA was decreased and replaced with LIPA, SB, sleep or combination of these behaviours (+ 0.22 to 0.26 points increase on depression symptoms scores for 30 min/day displacements). Conclusions: Daily movement behaviour composition was associated with depression symptoms in older Canadians. Replacing time in MVPA with equivalent time from any other behaviour was associated with increased depression symptoms. Preserving time spent in MVPA may play a key role in mitigating and improving mental health in this demographic. [ABSTRACT FROM AUTHOR]

Data derived from synthetic aperture radar (SAR) are widely employed to predict soil properties, particularly soil moisture and soil carbon content. However, few studies address the use of microwave sensors for soil texture retrieval and those that do are typically constrained to bare soil conditions. Here, we test two statistical modelling approaches—linear (with and without interaction terms) and tree‐based models, namely compositional linear regression model (LRM) and random forest (RF)—and both nongeophysical (e.g., surface soil moisture, topographic, etc) and geophysical‐based (electromagnetic, magnetic and radiometric) covariates to estimate soil texture (sand %, silt % and clay %), using microwave remote sensing data (ESA Sentinel‐1). The statistical models evaluated explicitly consider the compositional nature of soil texture and were evaluated with leave‐one‐out cross‐validation (LOOCV). Our findings indicate that both modelling approaches yielded better estimates when fitted without the geophysical covariates. Based on the Nash–Sutcliffe efficiency coefficient (NSE), LRM slightly outperformed RF, with NSE values for sand, silt and clay of 0.94, 0.62 and 0.46, respectively; for RF, the NSE values were 0.93, 0.59 and 0.44. When interaction terms were included, RF was found to outperform LRM. The inclusion of interactions in the LRM resulted in a decrease in NSE value and an increase in the size of the residuals. Findings also indicate that the use of radar‐derived variables (e.g., VV, VH, RVI) alone was not able to predict soil particle size without the aid of other covariates. Our findings highlight the importance of explicitly considering the compositional nature of soil texture information in statistical analysis and regression modelling. As part of the continued assessment of microwave remote sensing data (e.g., ESA Sentinel‐1) for predicting topsoil particle size, we intend to test surface scattering information derived from the dual‐polarimetric decomposition technique and integrate that predictor into the models in order to deal with the effects of vegetation cover on topsoil backscattering. [ABSTRACT FROM AUTHOR]

Abstract The microbiome plays a key role in the health of the human body. Interest often lies in finding features of the microbiome, alongside other covariates, which are associated with a phenotype of interest. One important property of microbiome data, which is often overlooked, is its compositionality as it can only provide information about the relative abundance of its constituting components. Typically, these proportions vary by several orders of magnitude in datasets of high dimensions. To address these challenges we develop a Bayesian hierarchical linear log-contrast model which is estimated by mean field Monte-Carlo co-ordinate ascent variational inference (CAVI-MC) and easily scales to high dimensional data. We use novel priors which account for the large differences in scale and constrained parameter space associated with the compositional covariates. A reversible jump Monte Carlo Markov chain guided by the data through univariate approximations of the variational posterior probability of inclusion, with proposal parameters informed by approximating variational densities via auxiliary parameters, is used to estimate intractable marginal expectations. We demonstrate that our proposed Bayesian method performs favourably against existing frequentist state of the art compositional data analysis methods. We then apply the CAVI-MC to the analysis of real data exploring the relationship of the gut microbiome to body mass index.

Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion mean--variability association, being aware of outliers. sccomp provides a comprehensive analysis framework that offers realistic data simulation and cross-study knowledge transfer. Here, we demonstrate that mean--variability association is ubiquitous across technologies, highlighting the inadequacy of the very popular Dirichlet-multinomial distribution. We show that sccomp accurately fits experimental data, significantly improving performance over state-of-the-art algorithms. Using sccomp, we identified differential constraints and composition in the microenvironment of primary breast cancer. [ABSTRACT FROM AUTHOR]

This article investigates changes in routine tasks and computer use in European jobs in the period 1995–2015, putting them in the context of the debates on the future of work and the impact of automation. Digital technologies not only affect employment shifts but also shape work organization. A shift-share analysis combining European Working Conditions Survey and European Labour Force Survey data assesses to what extent recent changes in tasks are the result of changes in the structure of employment (shifts in employment across jobs) or changes in the content of work itself (transformation in the task contents and methods within jobs). The results suggest contrasting trends between observed changes in tasks measures within jobs and compositional shifts in employment for routine tasks indexes. Employment structures are de-routinizing while work itself is becoming more routine. These results seem also related to the increased use of computers at work during the same period. [ABSTRACT FROM AUTHOR]

The microbiome plays a key role in the health of the human body. Interest often lies in finding features of the microbiome, alongside other covariates, which are associated with a phenotype of interest. One important property of microbiome data, which is often overlooked, is its compositionality as it can only provide information about the relative abundance of its constituting components. Typically, these proportions vary by several orders of magnitude in datasets of high dimensions. To address these challenges we develop a Bayesian hierarchical linear log-contrast model which is estimated by mean field Monte-Carlo co-ordinate ascent variational inference (CAVI-MC) and easily scales to high dimensional data. We use novel priors which account for the large differences in scale and constrained parameter space associated with the compositional covariates. A reversible jump Monte Carlo Markov chain guided by the data through univariate approximations of the variational posterior probability of inclusion, with proposal parameters informed by approximating variational densities via auxiliary parameters, is used to estimate intractable marginal expectations. We demonstrate that our proposed Bayesian method performs favourably against existing frequentist state of the art compositional data analysis methods. We then apply the CAVI-MC to the analysis of real data exploring the relationship of the gut microbiome to body mass index. [ABSTRACT FROM AUTHOR]

The central aims of many host or environmental microbiome studies are to elucidate factors associated with microbial community compositions and to relate microbial features to outcomes. However, these aims are often complicated by difficulties stemming from high-dimensionality, non-normality, sparsity, and the compositional nature of microbiome data sets. A key tool in microbiome analysis is beta diversity, defined by the distances between microbial samples. Many different distance metrics have been proposed, all with varying discriminatory power on data with differing characteristics. Here, we propose a compositional beta diversity metric rooted in a centered log-ratio transformation and matrix completion called robust Aitchison PCA. We demonstrate the benefits of compositional transformations upstream of beta diversity calculations through simulations. Additionally, we demonstrate improved effect size, classification accuracy, and robustness to sequencing depth over the current methods on several decreased sample subsets of real microbiome data sets. Finally, we highlight the ability of this new beta diversity metric to retain the feature loadings linked to sample ordinations revealing salient intercommunity niche feature importance. IMPORTANCE By accounting for the sparse compositional nature of microbiome data sets, robust Aitchison PCA can yield high discriminatory power and salient feature ranking between microbial niches. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/DEICODE; additionally, a QIIME 2 plugin is provided to perform this analysis at https://library.qiime2.org/plugins/deicode/.

Political ressourcement is a strategy for decolonizing political imaginations by drawing on means of human organization that predate European colonialism. One such resource in this regard is the millennia-old tradition of compositional politics in sub-Saharan Africa. The compositional tradition's insights for contemporary political theology are twofold. First, basing a community's identity upon amalgamation rather than exclusion offers a powerful means of building lasting political association. Second, such amalgamation has become a proven way of challenging colonial politics' exclusivist understandings of tribal, ethnic, and racial identities. In commending this tradition as a means of political ressourcement, the essay draws from Paul Landau's historical research of the South African highveld. It engages a wider conversation in African studies on the compositional tradition, then shows how this tradition has proven a vibrant strategy for decolonial action for twentieth and twenty-first century Christian churches. [ABSTRACT FROM AUTHOR]

• Deprivation was associated with aberrant immune and neuroendocrine activity. • Immune and neuroendocrine changes depended on individual-compositional factors. • Lifestyle accounted for the greatest variance in associations with inflammation. • Demographics were most salient to associations with neuroendocrine activity. Socioeconomic determinants are well-established modulators of inflammation and neuroendocrine activity. Less clear is whether neighbourhood-contextual or individual-compositional factors are more closely associated with gradients in these biomarkers. Here, we examine how immune and neuroendocrine activity are cross-sectionally and longitudinally nested in meso-level socioeconomic characteristics. Participants, male and female, aged ≥50, were recruited from the English Longitudinal Study of Ageing (ELSA). Neighbourhood (Index of Multiple Deprivation [IMD]) and individual (Wealth/Education/Occupational Social Class [Occupation]) factors were drawn from wave 4 (baseline; 2008). Immune and neuroendocrine biomarkers (indexed by C-reactive protein [CRP; n = 3,968]; fibrinogen [ n = 3,932]; white blood cell counts [WBCC; n = 4,022]; insulin-like growth factor-1 [IGF-1; n = 4,056]) were measured at baseline and 4-years later (wave 6; 2012). Covariates at baseline included demographic, clinical, and lifestyle variables. Lower socioeconomic status was associated with heighted inflammation and lower neuroendocrine activity unadjusted both cross-sectionally and longitudinally. With few exceptions, cross-sectional associations remained significant after full adjustment. Prospectively, low IMD remained associated with higher CRP and WBCC; wealth with WBCC; and education and occupation with fibrinogen and WBCC. IMD-biomarker associations were reduced when wealth was simultaneously taken into account. Lifestyle accounted for the greatest variance in associations between socioeconomic indicators and inflammation (≤42.11%), but demographics were more salient to neuroendocrine activity (≤88.46%). Neighbourhood-contextual factors were stronger indicators of aberrant biomarker activity than individual-compositional factors in cross-sectional analyses but were largely explained by wealth differences prospectively. Therefore, immune and neuroendocrine changes depended on the composition of the population living in an area, rather than the area itself. [ABSTRACT FROM AUTHOR]

A study was undertaken to determine the effect of the incorporation of grated carrot in chicken patties. Chicken patties were prepared by replacing lean meat with grated carrot at 3 levels, i.e., 10, 15, 20 %. The three treatments along with control were evaluated for physico chemical properties, sensory evaluation and β-carotene estimation. Each experiment was repeated four times. There was a significant increase (P<0.05) in cooking yield, moisture, crude fibre and ash content with an increasing level of grated carrot incorporation. Product pH, crude protein and crude fat showed a significant decrease (P<0.05) with an increase in the level of incorporation of grated carrot. Mean sensory scores for treatments were found to be significantly higher (P<0.05) for texture and overall acceptability, while general appearance was similar when compared to control. The optimum incorporation level of grated carrot was found to be 15 % for chicken patties preparation. Mean sensory scores of 15% grated carrot treatment for general appearance, flavour, texture, juiciness and overall acceptability were comparable with control treatment during the storage period. Chicken patties could be stored safely in LDPE pouches for 9 days at refrigeration temperature (4±1°C). [ABSTRACT FROM AUTHOR]

The work investigated in this paper focused on the fabrication of WO3 films by the spray pyrolysis technique, and different analyses were made to find optimized samples for studying properties suitable for the application of gas sensing. The substrate temperature is the most important parameter among other spray parameters for the synthesis of thin films hence WO3 thin films were deposited on glass substrates by maintaining the substrate temperature at 350 °C, 450 °C, 550 °C, and 650 °C using compressed air as a carrier gas. The influence of the substrate temperature on the structural, morphological, compositional, and optical properties of the WO3 thin films has been justified using XRD data. Good and enhanced crystallinity is observed for the film deposited at a substrate temperature of 550 °C. The nonconventional properties were studied by different investigations and confirmed by past research work. The manipulation of surface morphology with the different deposition temperatures is monitored. Only the characteristic peaks of W and O are present in the fabricated WO3 thin films. The optical activity of about 70 to 80 % of the selected sample in the visible region (300 to 1200 nm) is found. The selective absorption activity of light in the ultraviolet region and visible region is checked. The obtained IR bands confirmed the inter bridge stretching and bending modes of W-O and O-W-O. A high response towards ammonia compared to other test gases is exhibited. The repeatability of WO3 towards NH3 over three periodic sensing cycles, response, and recovery time has also been discussed. From all the characteristic studies, it has been suggested that the fabricated WO3 thin films have been used in the health care field to detect the toxic NH3 gas. [ABSTRACT FROM AUTHOR]

This paper presents a computational framework for Natural Language Inference (NLI) using logic-based semantic representations and theorem-proving. We focus on logical inferences with comparatives and other related constructions in English, which are known for their structural complexity and difficulty in performing efficient reasoning. Using the so-called A-not-A analysis of comparatives, we implement a fully automated system to map various comparative constructions to semantic representations in typed first-order logic via Combinatory Categorial Grammar parsers and to prove entailment relations via a theorem prover. We evaluate the system on a variety of NLI benchmarks that contain challenging inferences, in comparison with other recent logic-based systems and neural NLI models. [ABSTRACT FROM AUTHOR]

Abstract Background Sedentary behaviour is potentially a modifiable risk factor for depression and anxiety disorders, but findings have been inconsistent. To assess the associations of sedentary behaviour with depression and anxiety symptoms and estimate the impact of replacing daily time spent in sedentary behaviours with sleep, light, or moderate to vigorous physical activity, using compositional data analysis methods. Methods We conducted a prospective cohort study in 60,235 UK Biobank participants (mean age: 56; 56% female). Exposure was baseline daily movement behaviours (accelerometer-assessed sedentary behaviour and physical activity, and self-reported total sleep). Outcomes were depression and anxiety symptoms (Patient Health Questionnaire-9 and Generalised Anxiety Disorders-7) at follow-up. Results Replacing 60 min of sedentary behaviour with light activity, moderate-to-vigorous activity, and sleep was associated with lower depression symptom scores by 1.3% (95% CI, 0.4–2.1%), 12.5% (95% CI, 11.4–13.5%), and 7.6% (95% CI, 6.9–8.4%), and lower odds of possible depression by 0.95 (95% CI, 0.94–0.96), 0.75 (95% CI, 0.74–0.76), and 0.90 (95% CI, 0.90–0.91) at follow-up. Replacing 60 min of sedentary behaviour with moderate-to-vigorous activity and sleep was associated with lower anxiety symptom scores by 6.6% (95% CI, 5.5–7.6%) and 4.5% (95% CI, 3.7–5.2%), and lower odds of meeting the threshold for a possible anxiety disorder by 0.90 (95% CI, 0.89–0.90) and 0.97 (95%CI, 0.96–0.97) at follow-up. However, replacing 60 min of sedentary behaviour with light activity was associated with higher anxiety symptom scores by 4.5% (95% CI, 3.7–5.3%) and higher odds of a possible anxiety disorder by 1.07 (95% CI, 1.06–1.08). Conclusions Sedentary behaviour is a risk factor for increased depression and anxiety symptoms in adults. Replacing sedentary behaviour with moderate-to-vigorous activity may reduce mental health risks, but more work is necessary to clarify the role of light activity.

Background Emerging evidence suggests accruing sedentary behavior (SB) in relatively more prolonged periods may convey additional cardiometabolic risks, but few studies have examined prospective outcomes. We examined the association of SB accumulation patterns with incident cardiovascular disease (CVD), cancer, and all‐cause mortality (ACM). Methods and Results Data were from 7671 EPIC‐Norfolk (European Prospective Investigation Into Cancer and Nutrition–Norfolk) cohort middle‐ to older‐aged adults who wore accelerometers on the right hip for 4 to 7 days. Cox proportional hazards regression modeled associations between 2 measures of SB accumulation and incident CVD, cancer, and ACM. These were usual SB bout duration (the midpoint of each individual’s SB accumulation curve, fitted using nonlinear regression) and alpha (hybrid measure of bout frequency and duration, with higher values indicating relatively shorter bouts and fewer long bouts). Models were adjusted for potential confounders, then further for 24‐hour time‐use compositions. During mean follow‐up time of 6.4 years, 339 ACM, 1106 CVD, and 516 cancer events occurred. Elevated rates of incident cancer and ACM were seen with more prolonged SB accumulation (lower alpha, higher usual SB bout duration) but not CVD. For usual SB bout duration and alpha, respectively, the confounder‐adjusted hazard ratios per SD of the exposure were 1.12 (95% CI, 1.02–1.23) and 0.88 (95% CI, 0.79–0.98) with incident cancer and 1.16 (95% CI, 1.07–1.26) and 0.80 (95% CI, 0.72–0.89) with ACM (all P

The relevance of the research is conditioned by the processes of retrograde condensation while developing gas-condensate reservoirs at oil and gas fields. Due to these processes the reservoir losses its significant volumes of high-boiling components of С5+ hydrocarbon group, the production of which would be an additional income source for oil companies. The total reserves of gas condensate in Russia is about 2 billion tons. Therefore, to solve the problem of the fullest extraction of gas-condensate reservoir components it is necessary to implement new production methods. The research aim is to justify the efficiency of cycling technology in gas-condensate reservoir development. Subject: N field located in the territory of the Eastern Siberia. Methods: compositional, geologic, and hydrodynamic simulation of gas-condensate reservoir. Results. The paper presents the results of gas-condensate formation fluid compositional simulation in accordance with gas and condensate sample composition as well as gas-condensate study. Simplified geologic model of studied reservoir has been built and hydrodynamic simulation of its condition has been performed for different recovery mechanisms. Comparative analysis of gas condensate reservoir development parameters (condensate recovery factor, С2-С4 recovery factor, and condensate-gas factor) at different recovery mechanisms proved that application of cycling results in increase of extraction of hydrocarbon group С5+ component and allows solving a number of economic and environmental problems. It is possible to adapt the model to the required geologic conditions to use the given technology in the territory of Eastern Siberia and other petroleum provinces.

Cowpea (Vigna unguiculata) is a legume that is cultivated throughout Africa and contributes a significant amount of plant-based protein to human diets. There are many varieties of cowpeas, and these have varying seed characteristics such as shape, size, colour and nutritional properties. The compositional, physico-mechanical, and functional properties of two new cowpea seed varieties were investigated in order to determine their full food-use potentials as well as key parameters for their postharvest machinery for processing, handling, and storage. The proximate composition of the two cowpea cultivars was determined using standard methods. Physico-mechanical analyses carried out were the hundred-seed weight and volume, bulk density, true density, size, aspect ratio, surface area, equivalent diameter, porosity and angle of repose. Functional properties determined were cooking time and water uptake of the grain as well as water and oil absorption, foam capacity and stability, and emulsion capacity and stability of the flour. The Padi-Tuya variety was longer, broader and thicker than WangKae. The results showed both varieties to be useful sources of macronutrients. The moisture, fat and fibre in WangKae were significantly higher (p<0.05) than Padi-Tuya. However, both cowpea varieties had comparable protein levels of 17.7 g/100 g. The cooking time, hydration capacities and indices of the two varieties were also significantly different (p<0.05), but their swelling capacities, swelling and water uptake indices were comparable. Cooking times were 40 and 62 min for Padi-Tuya and WangKae. respectively. The water and oil absorption capacities, as well as the swelling indices, were similar, but their emulsion capacities and stabilities were significantly different (p<0.05) for the flour. Padi-Tuya had a higher foam capacity, but was less stable, than WangKae. The physico-mechanical properties determined would aid in the design of cleaning, handling and other processing machinery as well as storage facilities for the new cowpeas. The functional and the compositional parameters would assist in the food formulations. [ABSTRACT FROM AUTHOR]

Porcelain wares containing calcined bone ash and gypsum in their pastes were some of the most commercially successful high-fired wares produced in Britain and America during the third quarter of the 18th century. They were produced by the two earliest porcelain manufactories in America (the Bartlam and the Bonnin & Morris factories) and by several British manufactories, including the largest such enterprise (Bow) and another London factory (Isleworth). Owing to the influence that London manufacturers had on contemporary and later porcelain producers elsewhere in Britain and in America, major, minor, and high-precision trace-element data were determined for pastes and glazes of potsherds from the sites of these factories so that compositional commonalities and differences could be ascertained. Multidimensional scaling of major- and minor-element data for 34 samples of these wares generates diagrams on which the products of the four factories under consideration cluster relatively tightly as compared with diagrams created using only trace elements and all analytical data (major, minor, and trace elements). The coupling of geochemically unaffiliated components (or ratios thereof), including trace elements, however, tends to generate the best field separation on discrimination diagrams for these wares. The American and British phosphatic porcelains described here can readily be distinguished based on the concentrations of various paste components; rubidium vs. arsenic and tin, for example, best distinguishes Bartlam from Bonnin & Morris and their London counterparts. [ABSTRACT FROM AUTHOR]

Magazines are the origin of disport and proficiency from decennium; primarily embarked on 1789. This is a research on V.shine kids magazines and uses Leech and Short's framework (2007) of stylistic analysis on linguistic level to encompass figure of speech, syntactical configuration and morphological shoreline and Linda Mcloughlin (2002) theoretical frame on compositional level. Interconnected topic unzipped magazine from all perspective; how cover page is starting point of magnetism for the reader, how content of the magazine committed to diversification for bibliophile. The study also discussed concerning material like cover page, content page, columns, poetry, fictions, caption, chromaticity, tint and layout of V.shine magazine. This research has manipulated methodology on both quantitative and qualitative level. Systematic random sampling of different items from V.shine magazine was effectuated to propound a stylistic analysis of kids literary language, through non-probability systematic random sampling text was selected from V.shine magazine November 2018, volume 8, issue: 11 and V.shine magazine March 2019, volume 9 issue: 3 and for compositional stylistic analysis both magazines were extracted to reconsider design, lay out and cover pages. Research findings indicated that magazines in history were not much inviting. V. shine magazines dominance with entire properties of proficiency and distraction with multipurpose items on linguistic and compositional levels is trustworthy; notwithstanding supplementary periodicals behavior with one theme and approach that is monotonous. [ABSTRACT FROM AUTHOR]

Background: Sedentary behaviour is potentially a modifiable risk factor for depression and anxiety disorders, but findings have been inconsistent. To assess the associations of sedentary behaviour with depression and anxiety symptoms and estimate the impact of replacing daily time spent in sedentary behaviours with sleep, light, or moderate to vigorous physical activity, using compositional data analysis methods.Methods: We conducted a prospective cohort study in 60,235 UK Biobank participants (mean age: 56; 56% female). Exposure was baseline daily movement behaviours (accelerometer-assessed sedentary behaviour and physical activity, and self-reported total sleep). Outcomes were depression and anxiety symptoms (Patient Health Questionnaire-9 and Generalised Anxiety Disorders-7) at follow-up.Results: Replacing 60 min of sedentary behaviour with light activity, moderate-to-vigorous activity, and sleep was associated with lower depression symptom scores by 1.3% (95% CI, 0.4-2.1%), 12.5% (95% CI, 11.4-13.5%), and 7.6% (95% CI, 6.9-8.4%), and lower odds of possible depression by 0.95 (95% CI, 0.94-0.96), 0.75 (95% CI, 0.74-0.76), and 0.90 (95% CI, 0.90-0.91) at follow-up. Replacing 60 min of sedentary behaviour with moderate-to-vigorous activity and sleep was associated with lower anxiety symptom scores by 6.6% (95% CI, 5.5-7.6%) and 4.5% (95% CI, 3.7-5.2%), and lower odds of meeting the threshold for a possible anxiety disorder by 0.90 (95% CI, 0.89-0.90) and 0.97 (95%CI, 0.96-0.97) at follow-up. However, replacing 60 min of sedentary behaviour with light activity was associated with higher anxiety symptom scores by 4.5% (95% CI, 3.7-5.3%) and higher odds of a possible anxiety disorder by 1.07 (95% CI, 1.06-1.08).Conclusions: Sedentary behaviour is a risk factor for increased depression and anxiety symptoms in adults. Replacing sedentary behaviour with moderate-to-vigorous activity may reduce mental health risks, but more work is necessary to clarify the role of light activity. [ABSTRACT FROM AUTHOR]

Petrological features of carbonate rocks that exert control on their mechanical and physical properties are examined in the study presented here. Ninety-four representative rock block samples were collected at outcrops and were tested for uniaxial compressive strength (UCS), point load index (PLI), indirect tensile strength (ITS), sonic velocity (SV; Vp and Vs), Schmidt hardness value (SHV), slake durability index (SDI), porosity (n), water absorption (WA), unit weight (UW), and specific gravity (SG), according to the standards. The carbonate rock samples were classified into four groups, according to their compositional and textural characteristics, using XRD, XRF, polarized-light microscope, and SEM. Different types of regression analyses were performed to find the most applicable relationship between measured mechanical/physical properties and mineralogical/textural features of these carbonate rocks. The results suggest that rocks with pure calcite (no dolomite component) and abundant iron oxide cement are more sensitive to mechanical failure than the other carbonate rocks tested here. High silica content appears to reduce the UCS and Id2 values probably due to the presence of silica as separate chert nodules and detrital quartz grains. The results also suggest impact of the arid environmental conditions in the study area. The correlation data indicated wide range of variability and cover ranges reported in published literature on carbonate rocks from other regions. The derived correlation equations of the rock strength parameters may be specific within the arid environment of the investigated rocks, but the results may still provide comparative guidelines for rock testing in the region and regions of other carbonate rocks. [ABSTRACT FROM AUTHOR]

Objectives The aim of the study is to study the effect of vacuum treatment, heating temperature, mixing time and load force on the strength of heat-resistant expanded clay concrete for lining thermal units.Method The study is based on the vacuum processing technology of heat-resistant concrete based on a composite binder for lining the hearth of a trolley of a brick kiln, vacuum-packed concrete mix.Result The effect of vacuum processing of the mixture on the technological properties of heat-resistant expanded clay concrete on a composite binder made from Portland cement and finely ground expanded clay activated in a planetary mill (Activator-4M) is investigated. Compositions have been developed and the technological properties of expanded clay concrete have been investigated depending on the heating temperature and the amount of finely ground additives.Conclusion The results of the analysis of the dependence of the strength of expanded clay concrete on the heating temperature, the mixing time and the load strength confirm that the concrete strength indicators during evacuation are higher than for concrete without vacuum treatment; the increase in concrete strength after vacuum treatment under various technological exposure conditions is explained by an increase in workability indicators, which is characterized by the mobility and stiffness of the concrete mixture, denser packing of aggregate in the concrete structure, and also the large effect of vacuum compaction associated with the suction of water and air as well as static sealing due to the difference in atmospheric pressure and vacuum cavity pressure. The magnitude of the effective force reaches 70-75 kN / m2 with the removal of water and air from the vacuum surface; the pressure transmitted to the concrete is reduced, since part of the load is spent on determining the forces of internal friction and the development of contact stresses in the solid phase.

Seaweeds or macroalgae are attractive candidates for carbon capture, while also supplying a sustainable photosynthetic bioenergy feedstock, thanks to their cultivation potential in offshore marine farms. Seaweed cultivation requires minimal external nutrient requirements and allows for year-round production of biomass. Despite this potential, there remain significant challenges associated with realizing large-scale, sustainable agronomics, as well as in the development of an efficient biomass deconstruction and conversion platform to fuels and products. Recent biotechnology progress in the identification of enzymatic deconstruction pathways, tailored to complex polymers in seaweeds, opens up opportunities for more complete utilization of seaweed biomass components. Effective, scalable, and economically viable conversion processes tailored to seaweed are discussed and gaps are identified for yield and efficiency improvements. A realistic framework around seaweed carbon capture potential and seaweed biomass conversion is needed to guide future bioenergy production. Maximizing carbon storage in the biomass based on marine agronomy in the underutilized exclusive economic zone of the oceans represents significant untapped resources. Using biotechnological applications for deconstruction of the famously complex polysaccharides provides a route towards the discovery of new enzymatic cascades present in microbial communities. Seaweed-based industrial biotechnology allows for exploitation of the intrinsic biomass value based on its biochemical composition. It is necessary to place the seaweed biorefinery discussion in the context of the large-scale, offshore farms that are envisioned for bioenergy production to create market opportunities commensurate with the volumes produced. [ABSTRACT FROM AUTHOR]

Ordered categorical data occur in many applied fields, such as geochemistry, econometrics, sociology and demography or even transportation research, for example, in the form of results from various questionnaires. There are different possibilities for modelling proportions of individual categories. Generalised linear models (GLMs) are traditionally used for this purpose, but also methods of compositional data analysis (CoDa) can be considered. Here, both approaches are compared in depth. Particularly, different assumptions of the models on variability are highlighted. Advantages and disadvantages of individual models are pointed out. While the CoDa model may be inappropriate when the variability of the compositional coordinates depends on the regressors, for example, due to different total counts on which the coordinates are based, the GLM may underestimate the uncertainty of the predictions considerably in case of large-scale data. [ABSTRACT FROM AUTHOR]

The fluid injection in sedimentary formations may generate geochemical interactions between the fluids and the rock minerals, e.g., CO2 storage in a depleted reservoir or a saline aquifer. To simulate such reactive transfer processes, geochemical equations (equilibrium and kinetics equations) are coupled with compositional flows in porous media in order to represent, for example, precipitation/dissolution phenomena. The aim of the decoupled approach proposed consists in replacing the geochemical equilibrium solver with a substitute method to bypass the huge consuming time required to balance the geochemical system while keeping an accurate equilibrium calculation. This paper focuses on the use of artificial neural networks (ANN) to determine the geochemical equilibrium instead of solving geochemical equations system. To illustrate the proposed workflow, a 3D case study of CO2 storage in geological formation is presented. [ABSTRACT FROM AUTHOR]

Background: Studies have seldom used Compositional Data Analysis (CoDA) to map the effects of sleep, sedentary behaviour, and physical activity on older adults' cardio-metabolic profiles. This study therefore aimed to illustrate how sleep, sedentary behaviour, and physical activity profiles differ between older adult groups (60–89 years), with 'low' compared to those with 'high' concentrations of endocrine cardio-metabolic disease risk markers, using CoDA. Method: Ninety-three participants (55% female) wore a thigh-mounted triaxial accelerometer for seven consecutive free-living days. Accelerometer estimates of daily average hours of engagement in sedentary behaviour (SB), standing, light-intensity physical activity (LIPA), sporadic moderate-vigorous physical activity (sMVPA, accumulated with bouts between 1 and 10 min), 10-min moderate-vigorous physical activity (10MVPA, accumulated with bouts ≥10 min), in addition to self-reported sleeping hours were reported. Fasted whole blood concentrations of total cholesterol, triglyceride, glucose, and glycated haemoglobin, and serum lipoprotein lipase (LPL), interleukin-6 (IL-6), and procollagen III N-terminal propeptide were determined. Results: Triglyceride concentration appeared to be highly dependent on 10MVPA engagement as the 'low' and 'high' concentration groups engaged in 48% more and 32% less 10MVPA, respectively, relative to the geometric mean of the entire study sample. Time-use composition of the 'low' LPL group's engagement in 10MVPA was 26% less, while the 'high' LPL group was 7.9% more, than the entire study sample. Time-use composition of the 'high' glucose and glycated haemoglobin groups appeared to be similar as both engaged in more Sleep and SB, and less 10MVPA compared to the study sample. Participants with a 'low' IL-6 concentration engaged in 4.8% more Sleep and 2.7% less 10MVPA than the entire study sample. Time-use composition of the Total Cholesterol groups was mixed with the 'low' concentration group engaging in more Standing and 10MVPA but less Sleep, SB, LIPA, and sMVPA than the entire study sample. Conclusion: Older adults should aim to increase 10MVPA engagement to improve lipid profile and decrease SB engagement to improve glucose profile. [ABSTRACT FROM AUTHOR]

ABSTRACT The central aims of many host or environmental microbiome studies are to elucidate factors associated with microbial community compositions and to relate microbial features to outcomes. However, these aims are often complicated by difficulties stemming from high-dimensionality, non-normality, sparsity, and the compositional nature of microbiome data sets. A key tool in microbiome analysis is beta diversity, defined by the distances between microbial samples. Many different distance metrics have been proposed, all with varying discriminatory power on data with differing characteristics. Here, we propose a compositional beta diversity metric rooted in a centered log-ratio transformation and matrix completion called robust Aitchison PCA. We demonstrate the benefits of compositional transformations upstream of beta diversity calculations through simulations. Additionally, we demonstrate improved effect size, classification accuracy, and robustness to sequencing depth over the current methods on several decreased sample subsets of real microbiome data sets. Finally, we highlight the ability of this new beta diversity metric to retain the feature loadings linked to sample ordinations revealing salient intercommunity niche feature importance. IMPORTANCE By accounting for the sparse compositional nature of microbiome data sets, robust Aitchison PCA can yield high discriminatory power and salient feature ranking between microbial niches. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/DEICODE; additionally, a QIIME 2 plugin is provided to perform this analysis at https://library.qiime2.org/plugins/deicode/.

In this paper, flow of multi-component two-phase fluids in highly heterogeneous anisotropic two-dimensional porous media is studied using computational methods suitable for unstructured triangular and/or quadrilateral grids. The physical model accounts for miscibility and compressibility of fluids while gravity and capillary effects are neglected. The governing equations consist of a pressure equation together with a system of mass conservation equations. For solving pressure equation, a new method called Control Volume Distributed Finite Element Method (CVDFEM) is introduced which uses Control Volume Distributed (CVD) vertex-centered grids. It is shown that the proposed method is able to approximate the pressure field in highly anisotropic and heterogeneous porous media fairly accurately. Moreover the system of mass conservation equations is solved using various upwind and central schemes. These schemes are extended from one-dimensional to two-dimensional unstructured grids. Using a series of numerical test cases, comparison is made between different approaches for approximation of the hyperbolic flux function. Semi one-dimensional high-order data reconstruction procedures are employed to decrease stream-wise numerical diffusion. The results suggest that the Modified Dominant Wave (MDW) scheme outperforms other hyperbolic schemes studied in this paper from both accuracy and computational cost points of view. [ABSTRACT FROM AUTHOR]

• A cell-centred finite-volume CVD-MPFA based numerical framework has been presented for compositional gas-water phase flow in discrete-fracture matrix systems using unstructured grids. • An advance "fugacity-activity" type model of CO 2 dissolution into water phase has been incorporated in the framework and applied for flow simulations in reservoirs with discrete-fractures. • A comparison of equi-dimensional fracture model and the lower-dimensional fracture model has been presented for compositional gas-water phase flow using unstructured grids for the reservoirs with intersecting fractures. A novel numerical framework is presented for simulation of compositional compressible gas-water phase flow in fractured porous media based on a fully-implicit cell-centred finite-volume method on unstructured grids. We employ a discrete-fracture model where fractures are modelled lower-dimensionally, within a rock matrix. A mass balance equation is solved over the rock-matrix while a lower-dimensional flow equation is solved over the lower-dimensional fractures, with coupling terms to account for the flux transfer from the surrounding rock-matrix. The discretisation of the Darcy-fluxes is based on the control-volume distributed multi-point flux approximation (CVD-MPFA) coupled with a lower-dimensional fracture model. We solve a non-linear system for the primary variables that are the phase pressure and the component molar densities while the secondary variables are updated depending on the updated values of the primary variables at each iteration of the non-linear solver. We use the cubic type equation-of-state (EOS) to model the physical properties of gas components, e.g. CO 2. The water phase is multi-component as we allow solubility of gas components in the water phase. Solubility of H 2 O in the gaseous phase is also included in the developed method. We compare compositional simulation results, using unstructured grids, obtained via the lower-dimensional fracture model and the results obtained by the equi-dimensional fracture model for a case of CO 2 injection into a water saturated reservoir with intersecting fractures. The results show good agreement between the two models while the lower-dimensional fracture model is also computationally cost effective. Results are also presented for the evolution of injected CO 2 under gravity through a water saturated reservoir with and without fractures that demonstrate the profound effects of discrete-fractures that can lead to CO 2 leakage. The presented method is also applied to a 3D simulation of injection of a multi-component gas with CO 2 and CH 4 into a saline water saturated reservoir with a surface 2D fracture network. [ABSTRACT FROM AUTHOR]

Functional safety standards such as IEC 61508 and ISO 26262 advocate a particularly stringent requirements engineering where safety requirements must be structured in a hierarchical manner and specified in accordance with the system architecture. In contrast to the stringent requirements engineering in functional safety standards, according to previous studies, requirements engineering in industry is in general of poor quality. Contracts theory has been previously shown to be suitable for supporting such a stringent requirements engineering effort; this support has also been implemented in tools. However, to use these contract-based tools, requirements must be formalized, which is a major challenge in industry. Therefore, to support current industrial requirements engineering practice and the stringent requirements engineering in functional safety standards, it is shown how tool support can be provided even when requirements, and also architectures, are not formalized. This is achieved by enforcing syntactic, yet formal, conditions in contracts theory. Despite the need for further validation, initial findings in an industrial case study indicate high potential in realizing the proposed support in an industrial setting. [ABSTRACT FROM AUTHOR]

Abstract WO 3 thin films are prepared by electron beam evaporation (EBE) technique under the base pressure of 2 × 10-5 mbar at various substrate temperature (T s) ranging from room temperature (RT) to 450 °C. The deposited films were characterized systematically to analyse the influence of substrate temperature on structural, morphological, compositional, vibrational, electrical, optical and electrochromic properties. The EDS data of deposited films confirm the presence of tungsten (W) and Oxygen (O) elements. XRD spectra reveal that films deposited at T s < 250 °C are found to be amorphous and turns to crystalline as the substrate temperature raised to 450 °C. The morphological studies reveal that, beyond 250 °C of substrate temperature the material structure slowly changes to well crystallined structure with grain size about 70-80 nm. W = O and O-W-O bonds were present in the films which were confirmed by Raman spectra. The optical data represents the indirect allowed transitions and the band gap values are observed to be decreased from 3.24 to 2.93 eV with rise of substrate temperature from RT to 450 °C. It is also found that the RT electrical conductivity is increased with increase of T s. Finally it is found that the coloration efficiency (CE) of the films deposited at RT is 30.63 cm2/C at the wavelength of 550 nm. [ABSTRACT FROM AUTHOR]

Miscible gas injection is one of the most effective enhanced oil recovery techniques. There are several challenges in accurately modeling this process, which occurs in the near-miscible region. The adjustment of relative permeability for near-miscible processes is the main focus of this work. The dependence of relative permeability on phase identification can lead to significant complications while simulating near-miscible displacements. We present an analysis of how existing methods incorporate compositional dependence in relative permeability functions. The sensitivity of the different methods to the choice of reference points is presented with guidelines to limit the modification of the relative permeabilities to physically reasonable values. We distinguish between the two objectives of reflecting near-miscible behavior and ensuring smooth transitions across phase changes. We highlight an important link that combines the two objectives in a more general framework. We make use of Gibbs free energy as a compositional indicator in the generalized framework. The new approach was implemented in an automatic differentiation general purpose research simulator and tested on a set of near-miscible gas-injection problems. We show that including compositional dependencies in the relative permeability near the critical point impacts the simulation results with significant improvements in nonlinear convergence. [ABSTRACT FROM AUTHOR]

Numerical simulation of fluid flow coupled with chemical reactions has been an active field in the hydrogeology community and many formulations have been programmed into different software. In recent years, this subject has attracted increasing interest in the reservoir simulation community, partly for the application of chemical methods for hydrocarbon extraction but also for research on the geological sequestration of CO. In this paper, an extension to the concept of dual mesh for reactive transport modeling is presented. This approach involves two meshes, a low-resolution mesh to resolve the pressure equation and a high-resolution mesh to transport the species and to calculate the geochemical equilibrium. The main objective is to preserve the fine scale heterogeneities to reach a more accurate field behavior simulation than conventional approach which consist in performing simulations on a coarser mesh. The method is applied to a simulation of CO storage in the SPE10 model that keep a high resolution of the heterogeneities. [ABSTRACT FROM AUTHOR]

A new discretization approach for coupled free and porous-medium flows is introduced, which uses a finite-volume staggered-grid method for the discretization of the Navier-Stokes equations in the free-flow subdomain, while a vertex-centered finite-volume method is employed in the porous medium. The latter allows for the use of unstructured grids to discretize the porous medium, and the presented method is capable of handling non-matching grids at the interface. Moreover, the basis functions of the vertex-centered finite-volume method, with their degrees of freedom located at the interface, allow for an accurate evaluation of the coupling terms and of additional nonlinear velocity-dependent terms in the porous medium. The available advantages of this coupling method are investigated in a series of tests: a convergence test for various grid types, an evaluation of the implementation of the coupling conditions, and an example using the velocity-dependent Forchheimer term in the porous-medium subdomain. • Novel discretization approach for coupling free- and porous-medium flow. • Efficient and accurate reconstruction of interface quantities. • Capable of handling non-matching grids at the interface. • Physically complex exchange processes are accurately described. • Detailed comparative study with existing methods. [ABSTRACT FROM AUTHOR]