SPACE-TIME ESTIMATION AND PREDICTION UNDER FIXED-DOMAIN ASYMPTOTICS WITH COMPACTLY SUPPORTED COVARIANCE FUNCTIONS

We study the estimation and prediction of Gaussian processes with spacetime covariance models belonging to the dynamical generalized Wendland (DGW) family, under fixed-domain asymptotics. Such a class is nonseparable, has dynamical compact supports, and parameterizes differentiability at the origin similarly to the space-time Matern class.Our results are presented in two parts. First, we establish the strong consistency and asymptotic normality for the maximum likelihood estimator of the microergodic parameter associated with the DGW covariance model, under fixed-domain asymptotics. The second part focuses on optimal kriging prediction under the DGW model and an asymptotically correct estimation of the mean squared error using a misspecified model. Our theoretical results are, in turn, based on the equivalence of Gaussian measures under some given families of space-time covariance functions, where both space or time are compact. The technical results are provided in the online Supplementary material

Estimation and prediction using generalized wendland covariance functions under fixed domain asymptotics

We study estimation and prediction of Gaussian random fields with covariance models belonging to the generalized Wendland (GW) class, under fixed domain asymptotics. As for the Matérn case, this class allows for a continuous parameterization of smoothness of the underlying Gaussian random field, being additionally compactly supported. The paper is divided into three parts: first, we characterize the equivalence of two Gaussian measures with GW covariance function, and we provide sufficient conditions for the equivalence of two Gaussian measures with Matérn and GW covariance functions. In the second part, we establish strong consistency and asymptotic distribution of the maximum likelihood estimator of the microergodic parameter associated to GW covariance model, under fixed domain asymptotics. The third part elucidates the consequences of our results in terms of (misspecified) best linear unbiased predictor, under fixed domain asymptotics. Our findings are illustrated through a simulation study: the former compares the finite sample behavior of the maximum likelihood estimation of the microergodic parameter with the given asymptotic distribution. The latter compares the finite-sample behavior of the prediction and its associated mean square error when using two equivalent Gaussian measures with Matérn and GW covariance models, using covariance tapering as benchmark

Extreme Peripheral Blood Plasmacytosis Mimicking Plasma Cell Leukemia as a Presenting Feature of Angioimmunoblastic T-Cell Lymphoma (AITL).

Angioimmunoblastic T-cell lymphoma (AITL) is one of four major subtypes of nodal peripheral T cell lymphoma, characterized by its cell of origin, the follicular helper T-cell (TFH). Patients typically present with prominent constitutional (B) symptoms, generalized lymphadenopathy, hepatosplenomegaly, cytopenias, and rash. Here we present a case of a 62-year-old male with progressive cervical adenopathy, fevers and weight loss presenting with extreme polyclonal plasmacytosis and high plasma EBV viral load. While the initial presentation appeared to mimic plasma cell leukemia or severe infection, lymph node biopsy and bone marrow biopsy confirmed a diagnosis of AITL. This case highlights the heterogeneity of the clinical presentation of AITL to enable physicians to more promptly recognize, diagnose and initiate treatment

The impact of customer personality and online brand community engagement on intention to forward company and users generated content: palestinian banking industry a case

Personality five characteristics are playing crucial role on intention to forward Online Company Generated Content and user generated content mediated by online brand community engagement. This paper is applied on a case of banking industry in order to perceive a long run relationship between banks operating in Palestine and their customers. The total of 685 valid questionnaires were collected from online banking sector in Palestine, who is member of online brand community in Facebook. Moreover, the data were analysed and processed by structural equation model. The results reveal that personality traits (extraversion, conscientiousness, and openness) have positive influence on online brand community engagement. It also found that online brand community engagement plays vital role in inducing clients to forward CGC and UGC. Simultaneously, the results provide banks with a valuable implication on how banking industry can attract more customers in online brand community website and perceived trust of banks services and product

Asymptotically equivalent prediction in multivariate geostatistics

Cokriging is the common method of spatial interpolation (best linear unbiased prediction) in multivariate geo-statistics. While best linear prediction has been well understood in univariate spatial statistics, the literature for the multivariate case has been elusive so far. The new challenges provided by modern spatial datasets, being typ-ically multivariate, call for a deeper study of cokriging. In particular, we deal with the problem of misspecified cokriging prediction within the framework of fixed domain asymptotics. Specifically, we provide conditions for equivalence of measures associated with multivariate Gaussian random fields, with index set in a compact set of a d-dimensional Euclidean space. Such conditions have been elusive for over about 50 years of spatial statistics. We then focus on the multivariate Matern and Generalized Wendland classes of matrix valued covariance functions, that have been very popular for having parameters that are crucial to spatial interpolation, and that control the mean square differentiability of the associated Gaussian process. We provide sufficient conditions, for equivalence of Gaussian measures, relying on the covariance parameters of these two classes. This enables to identify the parameters that are crucial to asymptotically equivalent interpolation in multivariate geostatistics. Our findings are then illustrated through simulation studies

Exploiting the mediating role of the metabolome to unravel transcript-to-phenotype associations.

Despite the success of genome-wide association studies (GWASs) in identifying genetic variants associated with complex traits, understanding the mechanisms behind these statistical associations remains challenging. Several methods that integrate methylation, gene expression, and protein quantitative trait loci (QTLs) with GWAS data to determine their causal role in the path from genotype to phenotype have been proposed. Here, we developed and applied a multi-omics Mendelian randomization (MR) framework to study how metabolites mediate the effect of gene expression on complex traits. We identified 216 transcript-metabolite-trait causal triplets involving 26 medically relevant phenotypes. Among these associations, 58% were missed by classical transcriptome-wide MR, which only uses gene expression and GWAS data. This allowed the identification of biologically relevant pathways, such as between ANKH and calcium levels mediated by citrate levels and SLC6A12 and serum creatinine through modulation of the levels of the renal osmolyte betaine. We show that the signals missed by transcriptome-wide MR are found, thanks to the increase in power conferred by integrating multiple omics layer. Simulation analyses show that with larger molecular QTL studies and in case of mediated effects, our multi-omics MR framework outperforms classical MR approaches designed to detect causal relationships between single molecular traits and complex phenotypes

Study of macular and optic disk blood flow by angio‐OCT in Glucose‐6‐Phosphate Dehydrogenase (G6PD) deficient men and age‐related G6PD‐normal subjects

Purpose: The reported prevalence of Glucose‐6‐Phosphate Dehydrogenase (G6PD) deficiency in Sardina, Italy, ranges from 8% to 15%. Hemizygous males have totally deficient erythrocytes. Evidence indicates that patients with G6PD deficiency are protected against ischemic heart and cerebrovascular disease, colorectal cancer, retinal vein occlusion, and nonarteritic anterior ischemic optic neuropathy. The purpose of this study was to study the macular and optic disk blood flow by angio‐OCT in G6PD‐deficient men and age‐related G6PD‐normal subjects and ascertain whether, or not, there are statistically significant differences between the two groups Methods: 22 G6PD‐deficient men and 22 perfectly age‐matched G6PD‐normal controls were examined at the Ophthalmology Unit, University of Sassari, Sassari, Italy. A complete review of the medical history and a complete ophthalmological examination, including ETDRS best corrected visual acuity, slit‐lamp biomicroscopy of the anterior segment, applanation tonometry, and fundus examination, was carried out. An HD 6‐mm Angio‐Retina and a 4.5‐mm Angio Disk (RT‐Vue, Optovue XR‐100 with Angio Vue, CA) examination were also performed Results: Only 1 eye per patients was included in the analysis, for a total of 22 eyes in each group. All the exported parameters about retinal and disk flow were evaluated. No statistical differences between the two groups were found, even after controlling for the effects of age, hypertension and hypercholesterolemia (p = 0.9). Conclusions: Results suggest that G6PD‐deficient and G6PD‐normal men have similar macular and optic disk blood flow. Larger scale studies are necessary to confirm these findings