The Chloranthus sessilifolius genome provides insight into early diversification of angiosperms

Most extant angiosperms belong to Mesangiospermae, which comprises eudicots, monocots, magnoliids, Chloranthales and Ceratophyllales. However, phylogenetic relationships between these five lineages remain unclear. Here, we report the high-quality genome of a member of the Chloranthales lineage (Chloranthus sessilifolius). We detect only one whole genome duplication within this species and find that polyploidization events in different Mesangiospermae lineage are mutually independent. We also find that the members of all floral development-related gene lineages are present in C. sessilifolius despite its extremely simplified flower. The AP1 and PI genes, however, show a weak floral tissue-specialized expression. Our phylogenomic analyses suggest that Chloranthales and magnoliids are sister groups, and both are together sister to the clade comprising Ceratophyllales and eudicots, while the monocot lineage is sister to all other Mesangiospermae. Our findings suggest that in addition to hybridization, incomplete lineage sorting may largely account for phylogenetic inconsistencies between the observed gene trees.

Arithmetic Operations and Expected Values of Regular Interval Type-2 Fuzzy Variables

High computation complexity restricts the application prospects of the interval type-2 fuzzy variable (IT2-FV), despite its high degree of freedom in representing uncertainty. Thus, this paper studies the fuzzy operations for the regular symmetric triangular IT2-FVs (RSTIT2-FVs)—the simplest IT2-FVs having the greatest membership degrees of 1. Firstly, by defining the medium of an RSTIT2-FV, its membership function, credibility distribution, and inverse distribution are analytically and explicitly expressed. Secondly, an operational law for fuzzy arithmetic operations regarding mutually independent RSTIT2-FVs is proposed, which can simplify the calculations and directly output the inverse credibility of the functions. Afterwards, the operational law is applied to define the expected value operator of the IT2-FV and prove the linearity of the operator. Finally, some comparative examples are provided to verify the efficiency of the proposed operational law.

Type 2 diabetes and the risk of cardiovascular events in peripheral artery disease versus coronary artery disease

IntroductionThe prevalence of type 2 diabetes mellitus (T2DM) is higher in peripheral artery disease (PAD) than in coronary artery disease (CAD) patients, and PAD overall confers higher cardiovascular risk than CAD. How cardiovascular risk compares between PAD and CAD patients when analyses are stratified by the presence of type 2 diabetes is unclear and is addressed in the present study.Research design and methodsWe prospectively recorded major cardiovascular events (MACE; ie, cardiovascular death, myocardial infarction or stroke) over 10.0±4.7 years in 923 patients with stable CAD, of whom 26.7% had T2DM and in 292 patients with PAD, of whom 42.1% had T2DM. Four groups were analyzed: CAD patients without diabetes (CAD/T2DM−; n=677), CAD patients with T2DM (CAD/T2DM+; n=246), PAD patients without diabetes (PAD/T2DM−; n=169) and PAD patients with T2DM (PAD/T2DM+; n=123).ResultsThe event rate for MACE increased over our four investigated groups: it was lowest in CAD/T2DM− patients (2.52 events per 100 person-years). It was significantly higher in CAD/T2DM+ patients (3.96 events per 100 person-years; p<0.001), in PAD/T2DM− patients (3.68 events per 100 person-years; p=0.022), and in PAD/T2DM+ patients (7.10 events per 100 person-years; p<0.001), who in turn were at a higher risk than CAD/T2DM+ or PAD/T2DM− patients (p=0.001 and p<0.001, respectively). Cox regression analysis after multivariate adjustment showed that the presence of T2DM (HR=1.44 (95% CI 1.09 to 1.92); p=0.012) and the presence of PAD versus CAD (HR=1.48 (95% CI 1.15 to 1.91); p=0.002) were mutually independent predictors of cardiovascular events.ConclusionsIn conclusion, our data show that T2DM as well as the presence of PAD versus CAD are mutually independent predictors of MACE. Patients with both PAD and T2DM are at an exceedingly high risk of cardiovascular events.

Estimation of An Optimum Spatial Autocorrelation in Linear Mixed Models Containing Spatial Effects

Fay-Herriot model assumes that the random effects between regions (areas) are independent of each other. This allows the regions to be mutually independent so that the estimators obtained are unbiased estimators. In cases where the regions are not mutually independent, it can develop a model in which the assumptions are violated (not fulfilled) or allow the regions to be dependent. The development of this model is known as small area estimation (SAE) with spatial effects. In small area estimation with spatial effects, one of the important parameters is the spatial autocorrelation parameter. In various small area estimation with spatial effects, it is still very rare to generate estimators of the spatial autocorrelation parameter. Most of the parameter values used are known, that is by trying to enter several spatial autocorrelation parameter values to show that the addition of regional aspects can increase the accuracy of the small area estimation. In addition, they have also tried a restricted maximum likelihood approach in estimating the spatial autocorrelation and component variance but they still assume that the sampling variance is known (assigned). Therefore, this research proposes a concentrated log-likelihood function by means of numerical procedure to find an optimum estimate value for spatial autocorrelation coefficient where both a sampling variance and a component variance are unknown. Parameters estimators obtained in the models, fixed and random effects parameters, are proved to be consistent.

Discrete Convolution-Based Energy Spectrum Configuring Method for the Analysis of the Intrinsic Radiation of 176Lu

There has been considerable interest in inorganic scintillators based on lutetium due to their favorable physical properties. Despite their advantages, lutetium-based scintillators could face issues because of the natural occurring radioisotope of 176Lu that is contained in natural lutetium. In order to mitigate its potential shortcomings, previous works have studied to understand the energy spectrum of the intrinsic radiation of 176Lu (IRL). However, few studies have focused on the various principal types of photon interactions with matter; in other words, only the full-energy peak according to the photoelectric effect or internal conversion have been considered for understanding the energy spectrum of IRL. Thus, the approach we have used in this study considers other principal types of photon interactions by convoluting each energy spectrum with combinations for generating the spectrum of the intrinsic radiation of 176Lu. From the results, we confirm that the method provides good agreement with the experiment. A significant contribution of this study is the provision of a new approach to process energy spectra induced by mutually independent radiation interactions as a single spectrum.

On the asymptotic behavior of the eigenvalue distribution of block correlation matrices of high-dimensional time series

We consider linear spectral statistics built from the block-normalized correlation matrix of a set of [Formula: see text] mutually independent scalar time series. This matrix is composed of [Formula: see text] blocks. Each block has size [Formula: see text] and contains the sample cross-correlation measured at [Formula: see text] consecutive time lags between each pair of time series. Let [Formula: see text] denote the total number of consecutively observed windows that are used to estimate these correlation matrices. We analyze the asymptotic regime where [Formula: see text] while [Formula: see text], [Formula: see text]. We study the behavior of linear statistics of the eigenvalues of this block correlation matrix under these asymptotic conditions and show that the empirical eigenvalue distribution converges to a Marcenko–Pastur distribution. Our results are potentially useful in order to address the problem of testing whether a large number of time series are uncorrelated or not.

Grandparents childhood exposures and religious belief in their granddaughters: possible transgenerational associations

The prevalence of religious belief has fallen dramatically. A possible reason is that environmental exposures to previous generations are involved, e.g., evidence of an association between childhood exposures of grandparents and outcomes in their grandchildren including obesity, autistic traits, and survival have been reported. Generally, the associations between the grandparent’s exposure and grandchild’s outcome varied with sex of grandparent, his/her age at exposure and sex of the grandchild.Using data collected by the Avon Longitudinal Study of Parents and Children (ALSPAC) we investigate whether exposures such as smoking and/or traumatic events experienced by any of the grandparents are associated with the likelihood that their adult grandchildren have a religious belief. We show that the granddaughters (but not the grandsons) were more likely to have reported such a belief if one of their maternal grandparents had experienced traumatic events pre-puberty (age 6-11), or their paternal grandmother had experienced such events in adolescence. Conversely if their maternal grandfather had started smoking regularly during childhood or their paternal grandmother had smoked prenatally, the granddaughter was substantially less likely to be a believer. These associations were mutually independent and not explained by demographic factors. They may account for a small proportion of the fall in prevalence of religious belief over time, but the association needs confirming in other studies.

Sequential Model for Long-Term Planning of Building Renewal and Capital Improvement

The paper puts forward a mixed integer linear programming model to support the long-term planning and budgeting for renewal and capital improvements of residential buildings, i.e., to select the optimal sequence of repair and improvement actions over a predefined planning horizon. The input is provided by the evaluation of the building performance according to a set of criteria. Then a set of possible repairs, replacements and improvements needs to be proposed together with the estimates of their cost and benefits; the latter are expressed by increments of building performance ratings according to predefined criteria. The renewal and modernization measures are not mutually independent: at least some of them are complementary and should be carried out in a specific order. The optimization problem was to define the order of renewal/improvement measures resulting with the highest benefits available within the budget, or to achieve the required levels of building performance at the lowest cost. A unique feature of the model is the approach to the constraints on sequential relationships between the measures and to their selection. The model can be used to construct long-term renewal and capital improvement plans.