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Spatially distributed hydrologic models are increasingly being used to study and predict soil moisture flow, groundwater recharge, surface runoff, and river discharge. The usefulness and applicability of such complex models is increasingly held back by the potentially many hundreds (thousands) of parameters that require calibration against some historical record of data. The current generation of search and optimization algorithms is typically not powerful enough to deal with a very large number of variables and summarize parameter and predictive uncertainty. We have previously presented a general‐purpose Markov chain Monte Carlo (MCMC) algorithm for Bayesian inference of the posterior probability density function of hydrologic model parameters. This method, entitled differential evolution adaptive Metropolis (DREAM), runs multiple different Markov chains in parallel and uses a discrete proposal distribution to evolve the sampler to the posterior distribution. The DREAM approach maintains detailed balance and shows excellent performance on complex, multimodal search problems. Here we present our latest algorithmic developments and introduce MT‐DREAM(ZS), which combines the strengths of multiple‐try sampling, snooker updating, and sampling from an archive of past states. This new code is especially designed to solve high‐dimensional search problems and receives particularly spectacular performance improvement over other adaptive MCMC approaches when using distributed computing. Four different case studies with increasing dimensionality up to 241 parameters are used to illustrate the advantages of MT‐DREAM(ZS). Key Points An efficient MCMC method especially designed to solve high‐dimensional problems A parallelization scheme that maintains detailed balance and ergodicity Multi‐try sampling is admirably suited to treat all sources of error explicitly

This review presents a detailed summary of the latest technologies used in flywheel energy storage systems (FESS). This paper covers the types of technologies and systems employed within FESS, the range of materials used in the production of FESS, and the reasons for the use of these materials. Furthermore, this paper provides an overview of the types of uses of FESS, covering vehicles and the transport industry, grid leveling and power storage for domestic and industrial electricity providers, their use in motorsport, and applications for space, satellites, and spacecraft. Different types of machines for flywheel energy storage systems are also discussed. This serves to analyse which implementations reduce the cost of permanent magnet synchronous machines. As well as this, further investigations need to be carried out to determine the ideal temperature range of operation. Induction machines are currently stoutly designed with lower manufacturing cost, making them unsuitable for high-speed operations. Brushless direct current machines, the Homolar machines, and permanent magnet synchronous machines should also be considered for future research activities to improve their performance in a flywheel energy storage system. An active magnetic bearing can also be used alongside mechanical bearings to reduce the control systems’ complications, thereby making the entire system cost-effective.

Gestational diabetes mellitus (GDM) is the fastest growing type of diabetes, affecting between 2 to 38% of pregnancies worldwide, varying considerably depending on diagnostic criteria used and sample population studied. Adverse obstetric outcomes include an increased risk of macrosomia, and higher rates of stillbirth, instrumental delivery, and birth trauma. Metabolomics, which is a platform used to analyse and characterise a large number of metabolites, is increasingly used to explore the pathophysiology of cardiometabolic conditions such as GDM. This review aims to summarise metabolomics studies in GDM (from inception to January 2021) in order to highlight prospective biomarkers for diagnosis, and to better understand the dysfunctional metabolic pathways underlying the condition. We found that the most commonly deranged pathways in GDM include amino acids (glutathione, alanine, valine, and serine), carbohydrates (2-hydroxybutyrate and 1,5-anhydroglucitol), and lipids (phosphatidylcholines and lysophosphatidylcholines). We also highlight the possibility of using certain metabolites as predictive markers for developing GDM, with the use of highly stratified modelling techniques. Limitations for metabolomic research are evaluated, and future directions for the field are suggested to aid in the integration of these findings into clinical practice.

PurposeThe local food tourism in Pakistan is increasing rapidly, and it attracts scholars to determine the factors affecting local food tourists' buying choices. Particularly, the authors aim to investigate the role of food consumption values on predicting domestic tourists' attitude toward local food and its effect on the intention to try local food with the moderating effect of personality traits (neophobia and neophilia).Design/methodology/approachThe authors tested the study model on 250 completed responses from local food tourists. They collected the data from three tourism locations (Islamabad, Rawalpindi and Peshawar) in Pakistan. Their study utilizes the consumption value theory within the limits of Pakistan's local food tourism.FindingsThe empirical findings show that consumption values, such as price, emotion, interaction, epistemic value, location value and variety value, effectively explain the domestic tourists' attitude toward local food. The authors further report that food neophilia strengthens the local tourists' positive reception toward the local food. However, food neophobia weakens the direction between local tourists' attitude toward local food and the intention to try local food.Practical implicationsThis study provides insights pertaining to tourists' local food consumption values (LFCVs) to a local destination owner and marketing manager to strategically work on LFCVs that are crucial for domestic tourists to derive their intention to try local food. Practitioners should work on domestic tourists who possess food neophobia trait and enquire them for their rejection or avoidance of a particular local destination. This will enable practitioners to bring innovation and development in the local destination, which ultimately promote local food tourism.Originality/valueThis study is the first to incorporate the variety and local value in tourists' LFCVs to predict local tourists' attitude toward local food. Additionally, the authors contribute to local food tourism by empirically studying the moderating role of personality traits (food neophilia and food neophobia) to examine the direction between local tourists' attitude and intention to local food.

Many fibrous ingredients incorporated in poultry feed to reduce production costs have low digestibility and cause poor growth in poultry. However, all plant-based fibers are not equal, and thus exert variable physiological effects on the birds, including but not limited to, digestibility, growth performance, and microbial fermentation. Several types of fibers, especially oligosaccharides, when supplemented in poultry diets in isolated form, exhibit prebiotic effects by enhancing beneficial gut microbiota, modulating gut immunity, boosting intestinal mucosal health, and increasing the production of short-chain fatty acids (SCFA) in the gut. Recently, poultry producers are also facing the challenge of limiting the use of antibiotic growth promoters (AGP) in poultry feed. In addition to other alternatives in use, exogenous non-starch polysaccharides digesting enzymes (NSPase) and prebiotics are being used to provide substrates to support the gut microbiome. We also conducted a meta-analysis of different studies conducted in similar experimental conditions to evaluate the variability and conclusiveness in effects of NSPase on growth performance of broilers fed fibrous ingredients. This review presents a holistic approach in discussing the existing challenges of incorporating high-fiber ingredients in poultry feed, as well as strategies to fully utilize the potential of such ingredients in improving feed efficiency and gut health of poultry.

AIM: Functional traits of organisms are key to understanding and predicting biodiversity and ecological change, which motivates continuous collection of traits and their integration into global databases. Such trait matrices are inherently sparse, severely limiting their usefulness for further analyses. On the other hand, traits are characterized by the phylogenetic trait signal, trait–trait correlations and environmental constraints, all of which provide information that could be used to statistically fill gaps. We propose the application of probabilistic models which, for the first time, utilize all three characteristics to fill gaps in trait databases and predict trait values at larger spatial scales. INNOVATION: For this purpose we introduce BHPMF, a hierarchical Bayesian extension of probabilistic matrix factorization (PMF). PMF is a machine learning technique which exploits the correlation structure of sparse matrices to impute missing entries. BHPMF additionally utilizes the taxonomic hierarchy for trait prediction and provides uncertainty estimates for each imputation. In combination with multiple regression against environmental information, BHPMF allows for extrapolation from point measurements to larger spatial scales. We demonstrate the applicability of BHPMF in ecological contexts, using different plant functional trait datasets, also comparing results to taking the species mean and PMF. MAIN CONCLUSIONS: Sensitivity analyses validate the robustness and accuracy of BHPMF: our method captures the correlation structure of the trait matrix as well as the phylogenetic trait signal – also for extremely sparse trait matrices – and provides a robust measure of confidence in prediction accuracy for each missing entry. The combination of BHPMF with environmental constraints provides a promising concept to extrapolate traits beyond sampled regions, accounting for intraspecific trait variability. We conclude that BHPMF and its derivatives have a high potential to support future trait‐based research in macroecology and functional biogeography.

PurposeThis study aims to examine the role of augmented reality (AR) in online impulse behaviour for highbody-involvement products. This study further explores whether flow and spatial presence mediate the link between AR and online impulse behaviour.Design/methodology/approachThe authors collected 255 responses from shopping mall visitors and used SPSS (21.0) (PROCESS macro) and AMOS 21.0 to test the hypothesised model.FindingsThe findings reveal that AR virtual try-on significantly influences online impulse behaviour by providing hedonic value and reducing product risk prior to purchase. Second, flow and spatial presence partially and complementarily mediate the relationship between AR characteristics, hedonic value, and product risk.Originality/valueTheoretically, this study extends the literature on AR and online impulse behaviour from a psychological perspective, and it broadens managers' understanding of how they can use AR as a tool to increase sales.

Purpose Online shopping has continued to grow in popularity, and the advance of internet technology has enhanced customers’ experiences. One technology online retailers have been using to increase sales is virtual try-on (VTO). The purpose of this paper is to investigate how such technology affects online consumers’ purchase decision process towards purchase intention, especially from an integration of utilitarian, hedonic and risk perspectives, by using advanced partial least square (PLS) approaches. Design/methodology/approach This study applied a web-based survey approach for data collection from online apparel retailing websites. The survey instrument was developed by adapting previously validated measurement items. The valid data collected were analysed using PLS with multi-group analyses. Advanced PLS techniques such as examination of discriminant validity using heterotrait-monotrait ratio, tests of out-of-sample prediction performance, and measurement invariance of composite models were applied. Findings The results of examining the proposed model reveal that customers’ attitude towards VTO technology can affect their intention to purchase a garment online, which is affected by perceived usefulness, perceived enjoyment and perceived privacy risk. Perceived ease of use is found to affect perceived usefulness and perceived helpfulness. The results also show no significant differences among age groups and genders in terms of the role of VTO technology in the full decision process towards online purchase intention. Originality/value This study enhances the understanding of the roles that VTO technology plays in consumers’ online purchase intention by providing an integrative view of its utilitarian value, hedonic value and risk. This study demonstrates the feasibility of applying advanced PLS techniques to investigate online consumer behaviour, particularly in the field of VTO application in online retailing. Implications for online retailers and designers of VTO technology are also derived from the findings.

Aim: Despite several recent efforts to map plant traits and to identify their climatic drivers, there are still major gaps. Global trait patterns for major functional groups, in particular, the differences between woody and herbaceous plants, have yet to be identified. Here, we take advantage of big data efforts to compile plant species occurrence and trait data to analyse the spatial patterns of assemblage means and variances of key plant traits. We tested whether these patterns and their climatic drivers are similar for woody and herbaceous plants. Location: New World (North and South America). Methods: Using the largest currently available database of plant occurrences, we provide maps of 200 × 200 km grid-cell trait means and variances for both woody and herbaceous species and identify environmental drivers related to these patterns. We focus on six plant traits: maximum plant height, specific leaf area, seed mass, wood density, leaf nitrogen concentration and leaf phosphorus concentration. Results: For woody assemblages, we found a strong climate signal for both means and variances of most of the studied traits, consistent with strong environmental filtering. In contrast, for herbaceous assemblages, spatial patterns of trait means and variances were more variable, the climate signal on trait means was often different and weaker. Main conclusion: Trait variations for woody versus herbaceous assemblages appear to reflect alternative strategies and differing environmental constraints. Given that most large-scale trait studies are based on woody species, the strikingly different biogeographic patterns of herbaceous traits suggest that a more synthetic framework is needed that addresses how suites of traits within and across broad functional groups respond to climate.

Feeding behaviours are established early in life, with lifelong influences on children's appetite, growth and health, emphasizing the importance of understanding how parent–child feeding interactions relate to children's eating and growth patterns. The objective was to examine reciprocity between parent‐reported feeding practices and children's observed willingness‐to‐try‐new‐foods in childcare settings without parental presence, thereby assessing independence from context and parental influence. The sample included parent–child dyads (n = 436) recruited from 51 childcare centres across 10 counties. Parent‐reported feeding practices, children's observed willingness‐to‐try‐new‐foods and children's height and weight were measured using the Comprehensive Feeding Practices Questionnaire (CFPQ), a food tasting activity and standardized anthropometric protocols, respectively. Logistic and linear regression models assessed associations between parent‐reported feeding practices and children's observed willingness‐to‐try‐new‐foods, as well as body mass index z‐score (BMIz), respectively. All models adjusted for potential confounders, including clustering within childcare centres. Children's observed willingness‐to‐try‐new‐foods was positively associated with parent‐reported restriction for weight control, suggesting independence from context. A child‐driven interpretation suggests parental perceptions of children's high food responsivity or concerns about excess weight gain and a parent‐driven interpretation suggests that children exhibit higher willingness‐to‐try‐new‐foods in response to parental weight‐related restriction. Children's observed willingness‐to‐try‐new‐foods was not related to other parent‐reported feeding practices. Child BMIz was positively associated with parent‐reported restriction for weight and health and negatively associated with pressuring and giving children control over food intake. Future research is needed to determine factors associated with child and parent‐driven interpretations of feeding practices and effective strategies to promote responsive parent feeding practices. Summary Children's observed willingness‐to‐try‐new‐foods in childcare settings without parental presence was positively associated with parent‐reported restriction for weight control. A child‐driven interpretation of the finding suggests parental perceptions of children's high food responsivity or concerns about excess weight gain. A parent‐driven interpretation suggests children exhibit higher willingness‐to‐try‐new‐foods in response to parental weight‐related restrictive feeding practices. Lack of associations between children's observed willingness‐to‐try‐new‐foods and other parent‐reported food practices suggests in the absence of home structure, parent presence and other social factors, children's food‐related decisions may have been guided by extrinsic (e.g. food presentation/peer modelling) or intrinsic (e.g. sensory processing/taste perception/curiosity) factors.