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For over a decade there have been contradictory claims in the literature about whether the local bulk flow motion of galaxies is consistent or in tension with the ΛCDM model. While it has become evident that systematics affect bulk flow measurements, systematics in the estimators have not been widely investigated. In this work, we thoroughly evaluate the performance of four estimator variants, including the Kaiser maximum likelihood estimator (MLE) and the minimum variance estimator (MVE). We find that these estimators are unbiased, however their precision may be strongly correlated with the survey geometry. Small biases in the estimators can be present leading to underestimated bulk flows, which we suspect are due to the presence of non-linear peculiar velocities. The uncertainty assigned to the bulk flows from these estimators is typically underestimated, which leads to an overestimate of the tension with ΛCDM. We estimate the bulk flow for the CosmicFlows–4 data and use mocks to ensure the uncertainties are appropriately accounted for. Using the MLE we find a bulk flow amplitude of 408 ± 165 kms−1 at a depth of |$49\, \mathrm{Mpc} h^{-1}$|⁠ , in reasonable agreement with ΛCDM. However using the MVE which can probe greater effective depths, we find an amplitude of 428 ± 108 kms−1 at a depth of |$173\, \mathrm{Mpc} h^{-1}$|⁠ , in tension with the model, having only a 0.11 per cent probability of obtaining a larger χ2. These measurements appear directed towards the Great Attractor region where more data may be needed to resolve tensions. [ABSTRACT FROM AUTHOR]

Abstract Many countries use national nutrition surveys (NNSs) to assess their population’s health and nutrition needs. However, NNS aims, approaches, tools, and measurements vary among countries. To date, there has been no review evaluating the NNSs and their practices worldwide to help conduct future NSSs. Therefore, this narrative review was conducted to 1) explore and tabulate current NNSs in five continents (Asia, Europe, Africa, North America, and Australia) and 2) help lay the foundation for establishing clear guidelines for future NNSs. The NNSs were identified using two approaches. First, an electronic database search was conducted with key terms in PubMed database. Second, a general web-based search on the survey webpages of governmental organizations was conducted using the same key terms to identify eligible surveys. The review included general adult population (≥ 18 years) with a cross-sectional design, excluding NNSs related to household-only surveys, specific age groups, or insufficient sample sizes. A total of 41 NNSs were identified in 37 countries across four continents: Asia (n = 15), Europe (n = 21), North America (n = 3), and Australia (n = 2). Broad differences between the surveys were identified, including survey purposes and designs, definitions of geographic areas and target groups, and dietary assessments. Currently, there are 26 ongoing NNSs, while 15 have ended. Among the ongoing NNSs, the cycles of the surveys were either at regular intervals (n = 8) or irregular intervals (n = 8). Of the 41 surveys, 24-h dietary recalls were used in 27 surveys, while only 6 surveys used diet diaries and 8 surveys relied on FFQs. Some surveys (n = 17) utilized multiple tools to assess dietary intake. Most of the surveys that assessed biochemical status (n = 12) focused on blood glucose, haemoglobin A1c (HbA1c), and lipid status, whereas some surveys (n = 6) tested for vitamin and mineral status in blood and/or urine samples. The review identified key characteristics, time frames, sampling methods, and dietary and physical assessment methods obtained from different surveys worldwide. The information organized in this review will be important for researchers, policymakers, and public health programme developers in developing and improving NNS.

The presence of massive neutrinos in the early Universe is expected to have influenced the observed distribution of galaxies and their observed motions. In this work, we explore whether measurements of galaxy peculiar velocities could allow us to improve upon neutrino mass constraints from galaxy redshift surveys alone. Using Fisher matrix forecasts, we show that the galaxy peculiar motions do contain information on the sum of the masses of neutrinos ∑ m ν, and that this information can be used to improve upon constraints that may be obtained from low-redshift galaxy surveys (z < 0.5) combined with Planck measurements of the cosmic microwave background. Compared to the full constraining power offered by Planck and higher redshift DESI data, we find that the benefit of including peculiar velocities only marginally improves neutrino mass constraints. However, when one is limited to modelling only quasi-linear scales, adds additional degrees of freedom via a varying number of effective neutrino species (N eff), or does not include information from Planck , our results show that the inclusion of peculiar velocity measurements can still substantially improve upon the constraints. As such, we demonstrate that it may be possible to achieve upper bounds on ∑ m ν (⁠|$\sigma _{\sum m_{\nu }} = 0.051$| eV; 68 per cent confidence limit) comparable to those from Planck , from spectroscopic galaxy surveys alone, as long as the peculiar velocity data are available. This could allow for an independent comparison between constraints on ∑ m ν from the early- and late-time Universe probes that are particularly timely given current cosmological parameter tensions. [ABSTRACT FROM AUTHOR]

Background: Recognizing the scarcity of data on caffeine consumption among university students in Malaysia, this study was designed to first characterize the habitual caffeine intake within this group. This study further investigated the potential association between these caffeine consumption patterns and sleep quality and mental health status. Methodology: The study employed an online self-administered questionnaire to assess habitual caffeine intake from various products. Sleep quality and mental health were evaluated using the Pittsburgh Sleep Quality Index (PSQI) and the Depression, Anxiety, and Stress Scale-21 (DASS-21), respectively. Results: 78% of the respondents consumed caffeinated products daily within the safe level recommended by the European Food Safety Authority (£400mg/day). Only 2.6% of the students consumed caffeine exceeding the recommended limit. The median total daily caffeine intake was 100mg/day. Most students had poor sleep quality (77.3%), with 43.5%, 49.5%, and 33.0% reporting varying levels of depression, anxiety, and stress, respectively. Odds ratio calculations revealed respondents consuming less than or more than 400 mg/day of caffeine did not show significantly different odds of poor sleep quality, depression, anxiety, or stress compared to non-consumers. Conclusions: This study highlights the need for further localized research on caffeine's effects among Malaysian university students regarding caffeine consumption, sleep, and mental health.

Accurate detection of anomalies in multivariate time series data has attracted much attention due to its importance in a wide range of applications. Since it is difficult to obtain accurately labeled data, many unsupervised anomaly detection algorithms for multivariate time series data have been developed. However, building such a system is challenging since it requires capturing temporal dependencies in each time series and must also encode the inter-correlations between different pairs of time series. To meet this challenge, we propose a Multi Scale Convolutional Variational Autoencoder (MSCVAE) to detect anomalies in multivariate time series data. Firstly, multi scale attribute matrices are constructed from multivariate time series to characterize multiple levels of the system states at different time steps. Then, given the attribute matrices, a convolutional variational autoencoder is employed to generate reconstructed attribute matrices, and also an attention-based ConvLSTM network is used to capture the temporal patterns. In addition, a new ERR-based threshold setting strategy is developed to optimize anomaly detection performance instead of relying on the traditional ROC-based threshold setting strategy with an imbalanced dataset. Finally, the proposed framework is assessed by means of experiments on four datasets. The experimental results show that our proposed framework is superior to competing algorithms in terms of model performance and robustness, demonstrating that our model is effective in detecting anomalies in multivariate time series.

A diet high in polyphenols is associated with a diversified gut microbiome. Tea is the second most consumed beverage in the world, after water. The health benefits of tea might be attributed to the presence of polyphenol compounds such as flavonoids (e.g., catechins and epicatechins), theaflavins, and tannins. Although many studies have been conducted on tea, little is known of its effects on the trillions of gut microbiota. Hence, this review aimed to systematically study the effect of tea polyphenols on the stimulation or suppression of gut microbiota in humans and animals. It was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Articles were retrieved from PubMed and Scopus databases, and data were extracted from 6 human trials and 15 animal studies. Overall, large variations were observed in terms of microbiota composition between humans and animals. A more consistent pattern of diversified microbiota was observed in animal studies. Tea alleviated the gut microbiota imbalance caused by high-fat diet-induced obesity, diabetes, and ultraviolet-induced damage. The overall changes in microbiota composition measured by beta diversity analysis showed that tea had shifted the microbiota from the pattern seen in animals that received tea-free intervention. In humans, a prebiotic-like effect was observed toward the gut microbiota, but these results appeared in lower-quality studies. The beta diversity in human microbiota remains intact despite tea intervention; supplementation with different teas affects different types of bacterial taxa in the gut. These studies suggest that tea polyphenols may have a prebiotic effect in disease-induced animals and in a limited number of human interventions. Further intervention is needed to identify the mechanisms of action underlying the effects of tea on gut microbiota.

This note is intended as a contribution to the study of quantitative measures of graph complexity that use entropy measures based on symmetry. Determining orbit sizes of graph automorphism groups is a key part of such studies. Here we focus on an extreme case where every orbit contains just a single vertex. A permutation of the vertices of a graph G is an automorphism if, and only if, the corresponding permutation matrix commutes with the adjacency matrix of G. This fact establishes a direct connection between the adjacency matrix and the automorphism group. In particular, it is known that if the eigenvalues of the adjacency matrix of G are all distinct, every non-trivial automorphism has order 2. In this note, we add a condition to the case of distinct eigenvalues that makes the graph asymmetric, i.e., reduces the automorphism group to the identity alone. In addition, we prove analogous results for the Google and Laplacian matrices. The condition is used to build an O(n3) algorithm for detecting identity graphs, and examples are given to demonstrate that it is sufficient, but not necessary.

Background Metabolic syndrome (MetS) is defined as a cluster of risk factors for predicting type 2 diabetes mellitus and cardiovascular disease. Objectives This cross-sectional study aimed to develop a cut-off value for fat versus lean mass ratio (FLMR) in predicting MetS and to investigate the association between this indicator with MetS and its components. Methods Subjects comprised 238 Malay adolescents (79% female) aged 18–19 years old. Anthropometric assessment comprised weight, height and waist circumference (WC). Body composition was measured using bioelectrical impedance analysis techniques while blood pressure was measured using a blood pressure monitor. Fasting blood glucose, total cholesterol , triglycerides, high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol were determined from an overnight fasting blood sample. MetS was determined based on International Diabetes Federation (2007) definition for adolescents aged 16-year-old and above. Results The prevalence of MetS was 2.1%. Receiver Operating Characteristics curve analysis revealed that the optimal cut-off value for FLMR was 0.441 with an Area Under the Curve of 0.874 (95% CI: 0.825, 0.913); with sensitivity of 80.0% and specificity of 71.0%. FLMR cut-off of 0.441 was associated with high WC ( p < .001), low HDL-c ( p < .001) and MetS ( p < .05). Binary Logistic Regression analysis revealed that adolescents with high WC, low HDL-c and MetS had higher odds of developing increased FLMR than the cut-off value with an odds ratio (OR) of 43.4 (95% CI: 9.7,193.9), 4.7 (95% CI: 2.3,9.8) and 13.3 (95% CI: 1.5,121.2), respectively. Conclusion FLMR possesses fair discriminatory ability in identifying MetS among adolescents and significant association exists between FLMR and MetS and some of its components.

Research on the structural complexity of networks has produced many useful results in graph theory and applied disciplines such as engineering and data analysis. This paper is intended as a further contribution to this area of research. Here we focus on measures designed to compare graphs with respect to symmetry. We do this by means of a novel characteristic of a graph G, namely an “orbit polynomial.”A typical term of this univariate polynomial is of the form czn, where c is the number of orbits of size n of the automorphism group of G. Subtracting the orbit polynomial from 1 results in another polynomial that has a unique positive root, which can serve as a relative measure of the symmetry of a graph. The magnitude of this root is indicative of symmetry and can thus be used to compare graphs with respect to that property. In what follows, we will prove several inequalities on the unique positive roots of orbit polynomials corresponding to different graphs, thus showing differences in symmetry. In addition, we present numerical results relating to several classes of graphs for the purpose of comparing the new symmetry measure with existing ones. Finally, it is applied to a set of isomers of the chemical compound adamantane C10H16. We believe that the measure can be quite useful for tackling applications in chemistry, bioinformatics, and structure-oriented drug design.

Background and Objectives: Cognitive performance is essential for children, given this is a critical stage of brain growth and development. This systematic review and meta-analysis aimed to ascertain if physical activity or micronutrients impact cognitive performance in children. Materials and Methods: Electronic databases (PubMed and Scopus®) were searched for relevant articles published between 2012 and 2021. We emphasized randomized controlled trials (RCTs) that examined the effect of physical activity and micronutrients on cognitive performance. Data from eligible studies were gathered and evaluated using random-, fixed- or pooled-effects models with 95% confidence intervals (95% CI). Results: Physical activity appeared to improve both Mathematics (d = 1.12, 95% CI: 0.56, 1.67) and attention (d = 0.65, 95% CI: 0.15, 1.14) performances. The micronutrient vitamin B12 had a positive effect on Mathematics (d = 2.39, 95% CI: 0.79, 3.98), English (d = 5.29, 95% CI: 2.76, 7.83), Geography (d = 5.29, 95% CI: 2.76, 7.83), Science (d = 3.39, 95% CI: 2.62, 4.16) and Arts (d = 3.32, 95% CI: 1.84, 4.79). Zinc was found to positively affect English (d = 3.78, 95% CI: 0.44, 7.13), Geography (d = 4.77, 95% CI: 0.56, 8.98) and Arts (d = 2.39, CI: 0.33, 4.45). Iron positively affected Mathematics (d = 1.29, 95% CI: 0.54, 2.06), English (d = 1.29, 95% CI: 0.44, 7.13), Geography (d = 4.77, 95% CI: 0.56, 8.98) and Arts (d = 2.39, 95% CI: 0.33, 4.45). Conclusions: A more comprehensive intervention with a specific dose/level of physical activity, an increased range of cognitive performance, and a well-designed study design that accounts for dietary intake and other health outcomes are required for future studies.