A CLT for the LSS of large dimensional sample covariance matrices with diverging spikes

In this paper, we establish the central limit theorem (CLT) for linear spectral statistics (LSS) of large-dimensional sample covariance matrix when the population covariance matrices are not uniformly bounded, which is a nontrivial extension of the Bai-Silverstein theorem (BST) (2004). The latter has strongly influenced the development of high-dimensional statistics, especially in applications of random matrix theory to statistics. However, the assumption of uniform boundedness of the population covariance matrices has seriously limited the applications of the BST. The aim of this paper is to remove the barriers for the applications of the BST. The new CLT, allows spiked eigenvalues to exist, which may be bounded or tend to infinity. An important feature of our result is that the roles of either spiked eigenvalues or the bulk eigenvalues predominate in the CLT, depending on which variance is nonnegligible in the summation of the variances. The CLT for LSS is then applied to compare four linear hypothesis tests: The Wilk's likelihood ratio test, the Lawly-Hotelling trace test, the Bartlett-Nanda-Pillai trace test, and Roy's largest root test. We also derive and analyze their power function under particular alternatives.Comment: Comparing with the old manuscript, we modified the title of the paper. arXiv admin note: text overlap with arXiv:2205.07280. arXiv admin note: text overlap with arXiv:2205.0728

Effects of injection rate profile on combustion process and emissions in a diesel engine

When multi-injection is implemented in diesel engine via high pressure common-rail injection system, changed interval between injection pulses can induce variation of injection rate profile for sequential injection pulse, though other control parameters are same. Variations of injection rate shape which influence the air-fuel mixing and combustion process will be important for designing injection strategy. In this research, CFD numerical simulations using KIVA-3V were conducted for examining the effects of injection rate shape on diesel combustion and emissions. After the model was validated by experimental results, five different shapes (including rectangle, slope, triangle, trapezoid and wedge) of injection rate profiles were investigated. Modelling results demonstrate that injection rate shape can have obvious influence on heat release process and heat release traces which cause different combustion process and emissions. It is observed that the baseline - rectangle (flat) shape of injection rate can have better balance between NOx and soot emissions than other investigated shapes. As wedge shape brings about the lowest NOx emissions due to retarded heat release, it produces highest soot emissions among five shapes. Trapezoid shape has the lowest soot emissions, while its NOx is not the highest one. The highest NOx emissions was produced by triangle shape due to higher peak injection rate

A pipeline for improved QSAR analysis of peptides: physiochemical property parameter selection via BMSF, near-neighbor sample selection via semivariogram, and weighted SVR regression and prediction

In this paper, we present a pipeline to perform improved QSAR analysis of peptides. The modeling involves a double selection procedure that first performs feature selection and then conducts sample selection before the final regression analysis. Five hundred and thirty-one physicochemical property parameters of amino acids were used as descriptors to characterize the structure of peptides. These high-dimensional descriptors then go through a feature selection process given by the Binary Matrix Shuffling Filter (BMSF) to obtain a set of important low dimensional features. Each descriptor that passed the BMSF filtering also receives a weight defined through its contribution to reduce the estimation error. These selected features were served as the predictors for subsequent sample selection and modeling. Based on the weighted Euclidean distances between samples, a common range was determined with high-dimensional semivariogram and then used as a threshold to select the near-neighbor samples from the training set. For each sample to be predicted, the QSAR model was established using SVR with the weighted, selected features based on the exclusive set of near-neighbor training samples. Prediction was conducted for each test sample accordingly. The performances of this pipeline are tested with the QSAR analysis of angiotensin-converting enzyme (ACE) inhibitors and HLA-A*0201 data sets. Improved prediction accuracy was obtained in both applications. This pipeline can optimize the QSAR modeling from both the feature selection and sample selection perspectives. This leads to improved accuracy over single selection methods. We expect this pipeline to have extensive application prospect in the field of regression prediction

Food supplementation as a conservation intervention:A framework and a case of helping threatened shorebirds at a refuelling site

Supplemental feeding to mitigate the effects of food shortages may in some cases provide critical help to species conservation. However, supplemental feeding may have both positive and negative effects on wildlife and the environment. A scientifically designed feeding project helps to achieve conservation targets and reduces adverse effects. Here, we summarize a three-step framework for food supplementation that we used in practice: (1) determining whether supplemental feeding is required; (2) designing and implementing a practical feeding scheme; and (3) evaluating the effectiveness of food supplementation. We supplemented food for great knots (Calidris tenuirostris), an endangered migratory shorebird, at a recently impoverished refuelling site (Yalu Jiang estuary) in the Yellow Sea in spring 2018. The abundance of the staple food of great knots (Potamocorbula laevis, which had become very rare after 2012), was insufficient for the birds to refuel before the migratory flight to the breeding grounds. In our practical test, living P. laevis were collected in subtidal areas and transported to the intertidal area where great knots had been foraging in earlier years. The supplemented areas attracted 48% of all the great knots present in the 200 km2 study area. Nearly 90% of the supplemented food was consumed. Most great knots (>80%) foraged in the high-density supplementation zone where the densities of P. laevis were restored to the naturally occurring levels in 2011–2012. Here, food intake rates (mg AFDM/s) were 4.2 times those in the adjacent control zones. The framework and the feeding practice should help guide future supplemental feeding in a wide range of species

Large Eddy Simulation analysis on confined swirling flows in a gas turbine swirl burner

This paper describes a Large Eddy Simulation (LES) investigation into flow fields in a model gas turbine combustor equipped with a swirl burner. A probability density function was used to describe the interaction physics of chemical reaction and turbulent flow as liquid fuel was directly injected into the combustion chamber and rapidly mixed with the swirling air. Simulation results showed that heat release during combustion accelerated the axial velocity motion and made the recirculation zone more compact. As the combustion was taking place under lean burn conditions, NO emissions was less than 10 ppm. Finally, the effects of outlet contraction on swirling flows and combustion instability were investigated. Results suggest that contracted outlet can enhance the generation of a Central Vortex Core (CVC) flow structure. As peak RMS of velocity fluctuation profiles at center-line suggested the turbulent instability can be enhanced by CVC motion, the Power Spectrum Density (PSD) amplitude also explained that the oscillation at CVC position was greater than other places. Both evidences demonstrated that outlet contraction can increase the instability of the central field.  [m1]Is’t right? Yes

Thermal Diffusivity Identification of Distributed Parameter Systems to Sea Ice

A method of optimal control is presented as a numerical tool for solving the sea ice heat transfer problem governed by a parabolic partial differential equation. Taken the deviation between the calculated ice temperature and the measurements as the performance criterion, an optimal control model of distributed parameter systems with specific constraints of thermal properties of sea ice was proposed to determine the thermal diffusivity of sea ice. Based on sea ice physical processes, the parameterization of the thermal diffusivity was derived through field data. The simulation results illustrated that the identified parameterization of the thermal diffusivity is reasonably effective in sea ice thermodynamics. The direct relation between the thermal diffusivity of sea ice and ice porosity is physically significant and can considerably reduce the computational errors. The successful application of this method also explained that the optimal control model of distributed parameter systems in conjunction with the engineering background has great potential in dealing with practical problems

Preliminary results on relationship between thermal diffusivity and porosity of sea ice in the Antarctic

The in situ sea - ice temperature, salinity and density observed from Chinese Antarctic Zhongshan Station have been applied to calculate the vertical profile of sea ice porosity. Based on numerical method, a number of schemes on sea - ice thermal diffusivity versus porosity have been accessed and one optimized scheme is identified by an optimal control model with an advanced distributing parameter system. For simplicity, the internal heating source item was neglected in the heat conduction equation during the identification procedure. In order to illustrate the applicability of this identified scheme, the vertical ice temperature profiles have been simulated and compared with measurements, respectively by using identified scheme and by classical thermodynamic formulae. The comparisons indicated that the scheme describing sea - ice thermal diffusivity and porosity is reasonable. In spite of a minor improvement of accuracy of results against in situ data, the identified scheme has a more physical meaning and could be used potentially in various applications

Aberrant hippocampal subregion networks associated with the classifications of aMCI subjects: a longitudinal resting-state study

Background: Altered hippocampal structure and function is a valuable indicator of possible conversion from amnestic type mild cognitive impairment (aMCI) to Alzheimer’s disease (AD). However, little is known about the disrupted functional connectivity of hippocampus subregional networks in aMCI subjects. Methodology/Principal Findings: aMCI group-1 (n = 26) and controls group-1 (n = 18) underwent baseline and after approximately 20 months follow up resting-state fMRI scans. Integrity of distributed functional connectivity networks incorporating six hippocampal subregions (i.e. cornu ammonis, dentate gyrus and subicular complex, bilaterally) was then explored over time and comparisons made between groups. The ability of these extent longitudinal changes to separate unrelated groups of 30 subjects (aMCI-converters, n = 6; aMCI group-2, n = 12; controls group-2, n = 12) were further assessed. Six longitudinal hippocampus subregional functional connectivity networks showed similar changes in aMCI subjects over time, which were mainly associated with medial frontal gyrus, lateral temporal cortex, insula, posterior cingulate cortex (PCC) and cerebellum. However, the disconnection of hippocampal subregions and PCC may be a key factor of impaired episodic memory in aMCI, and the functional index of these longitudinal changes allowed well classifying independent samples of aMCI converters from non-converters (sensitivity was 83.3%, specificity was 83.3%) and controls (sensitivity was 83.3%, specificity was 91.7%). Conclusions/Significance: It demonstrated that the functional changes in resting-state hippocampus subregional networks could be an important and early indicator for dysfunction that may be particularly relevant to early stage changes and progression of aMCI subjects