A note on the stability of Toeplitz matrix inversion formulas

AbstractIn this paper, we consider the stability of the algorithms emerging from Toeplitz matrix inversion formulas. We show that if the Toeplitz matrix is nonsingular and well-conditioned, then they are numerically forward stable

Modification of 1D TiO2 nanowires with GaOxNy by atomic layer deposition for TiO2@GaOxNy core-shell nanowires with enhanced photoelectrochemical performance

As a well-known semiconductor that can catalyse the oxygen evolution reaction, TiO2 has been extensively investigated for its solar photoelectrochemical water properties. Unmodified TiO2 shows some issues, particularly with respect to its photoelectrochemical performance. In this paper, we present a strategy for the controlled deposition of controlled amounts of GaOxNy cocatalysts on TiO2 1D nanowires (TiO2@GaOxNy core-shell) using atomic layer deposition. We show that this modification significantly enhances the photoelectrochemical performance compared to pure TiO2 NW photoanodes. For our most active TiO2@GaOxNy core-shell nanowires with a GaOxNy thickness of 20 nm, a photocurrent density up to 1.10 mA cm-2 (at 1.23 V vs RHE) under AM 1.5 G irradiation (100 mW cm-2) has been achieved, which is 14 times higher than that of unmodified TiO2 NWs. Furthermore, the band gap matching with TiO2 enhances absorption of visible light over unmodified TiO2 and the facile oxygen vacancy formation after deposition of GaOxNy also provides active sites for water activation. Density functional theory studies of model systems of GaOxNy-modified TiO2 confirm the band gap reduction, high reducibility and ability to activate water. The highly efficient and stable systems of TiO2@GaOxNy core-shell nanowires with ALD deposited GaOxNy demonstrates a good strategy for fabrication of core-shell structures that enhances the photoelectrochemical performance of readily available photoanodes

Parallelization of adaptive Bayesian cubature using multimodal optimization algorithms

PurposeBayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.Design/methodology/approachBy theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.FindingsThe superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.Originality/valueMultimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.</jats:sec

Quantifying Nonradiative Recombination and Resistive Losses in Perovskite Photovoltaics: A Modified Diode Model Approach

Pinpointing the origin of inefficiency can expedite the process of optimizing the efficiency of perovskite photovoltaics. However, it is challenging to discern and quantify the different loss pathways in a complete perovskite photovoltaic device under operational conditions. To address this challenge, we propose a modified diode model that can quantify bulk/interface defect-assisted recombination and series/shunt resistive losses. By adopting drift-diffusion simulation as the benchmark, we explore the physical meanings of the modified diode model parameters and evaluate the performance of the model for simulation parameters spanning many orders of magnitude. Our evaluation shows that, in most practical cases, the proposed model can accurately quantify all the aforementioned losses, and in some special cases, it is possible to identify the predominant loss pathway. Moreover, we apply the modified diode model to our lab-produced devices (based on Cs0.05FA0.95PbI3 perovskites), demonstrating its effectiveness in quantifying entangled losses in practice. Finally, we provide a set of guidelines for applying the modified diode model and interpreting the results. Source code available at https://github.com/WPT-Lab124/Modified-Diode-Model.Comment: 26 pages, 6 figures, published in Solar RR

A sequential sampling-based Bayesian numerical method for reliability-based design optimization

For efficiently solving the Reliability-Based Design Optimization (RBDO) problem with multi-modal, highly nonlinear and expensive-to-evaluate limit state functions (LSFs), a sequential sampling-based Bayesian active learning method is developed in this work. The penalty function method is embedded to transform the constrained optimization problem into a non-constrained one to reduce the model complexity. The proposed method for solving RBDO problems starts by training a Gaussian process (GP) model, in the augmented space of random and design variables. It is then based on an efficient sampling scheme for simulating the GP model, the adaptive Bayesian optimization (BO) and Bayesian reliability analysis (BRA) procedures are combined in a collaborative way for sequentially producing the joint training points. BO driven by expected improvement (EI) function is used for inferring the global optimum in the design space with global convergence, and the BRA equipped with U function is implemented for inferring the failure probabilities at the identified design points with the desired accuracy. The superiority of the proposed method is demonstrated with two numerical and two real-world engineering examples

Hyaluronan Signaling during Ozone-Induced Lung Injury Requires TLR4, MyD88, and TIRAP

Ozone exposure is associated with exacerbation of reactive airways disease. We have previously reported that the damage-associated molecular pattern, hyaluronan, is required for the complete biological response to ambient ozone and that hyaluronan fragments signal through toll-like receptor 4 (TLR4). In this study, we further investigated the role of TLR4 adaptors in ozone–induced airway hyperresponsiveness (AHR) and the direct response to hyaluronan fragments (HA). Using a murine model of AHR, C57BL/6J, TLR4−/−, MyD88−/−, and TIRAP−/− mice were characterized for AHR after exposure to either ozone (1 ppm×3 h) or HA fragments. Animals were characterized for AHR with methacholine challenge, cellular inflammation, lung injury, and production of pro-inflammatory cytokines. Ozone-exposed C57BL/6J mice developed cellular inflammation, lung injury, pro-inflammatory cytokines, and AHR, while mice deficient in TLR4, MyD88 or TIRAP demonstrated both reduced AHR and reduced levels of pro-inflammatory cytokines including TNFα, IL-1β, MCP-1, IL-6 and KC. The level of hyaluronan was increased after inhalation of ozone in each strain of mice. Direct challenge of mice to hyaluronan resulted in AHR in C57BL/6J mice, but not in TLR4−/−, MyD88−/−, or TIRAP−/− mice. HA-induced cytokine production in wild-type mice was significantly reduced in TLR4−/−, MyD88−/−, or TIRAP−/− mice. In conclusion, our findings support that ozone-induced airway hyperresponsiveness is dependent on the HA-TLR4-MyD88-TIRAP signaling pathway

SETDB2 Links E2A-PBX1 to Cell-Cycle Dysregulation in Acute Leukemia through CDKN2C Repression

Acute lymphoblastic leukemia (ALL) is associated with significant morbidity and mortality, necessitating further improvements in diagnosis and therapy. Targeted therapies directed against chromatin regulators are emerging as promising approaches in preclinical studies and early clinical trials. Here, we demonstrate an oncogenic role for the protein lysine methyltransferase SETDB2 in leukemia pathogenesis. It is overexpressed in pre-BCR+ ALL and required for their maintenance in vitro and in vivo. SETDB2 expression is maintained as a direct target gene of the chimeric transcription factor E2A-PBX1 in a subset of ALL and suppresses expression of the cell-cycle inhibitor CDKN2C through histone H3K9 tri-methylation, thus establishing an oncogenic pathway subordinate to E2A-PBX1 that silences a major tumor suppressor in ALL. In contrast, SETDB2 was relatively dispensable for normal hematopoietic stem and progenitor cell proliferation. SETDB2 knockdown enhances sensitivity to kinase and chromatin inhibitors, providing a mechanistic rationale for targeting SETDB2 therapeutically in ALL

Rheumatoid Arthritis Naive T Cells Share Hypermethylation Sites With Synoviocytes.

ObjectiveTo determine whether differentially methylated CpGs in synovium-derived fibroblast-like synoviocytes (FLS) of patients with rheumatoid arthritis (RA) were also differentially methylated in RA peripheral blood (PB) samples.MethodsFor this study, 371 genome-wide DNA methylation profiles were measured using Illumina HumanMethylation450 BeadChips in PB samples from 63 patients with RA and 31 unaffected control subjects, specifically in the cell subsets of CD14+ monocytes, CD19+ B cells, CD4+ memory T cells, and CD4+ naive T cells.ResultsOf 5,532 hypermethylated FLS candidate CpGs, 1,056 were hypermethylated in CD4+ naive T cells from RA PB compared to control PB. In analyses of a second set of CpG candidates based on single-nucleotide polymorphisms from a genome-wide association study of RA, 1 significantly hypermethylated CpG in CD4+ memory T cells and 18 significant CpGs (6 hypomethylated, 12 hypermethylated) in CD4+ naive T cells were found. A prediction score based on the hypermethylated FLS candidates had an area under the curve of 0.73 for association with RA case status, which compared favorably to the association of RA with the HLA-DRB1 shared epitope risk allele and with a validated RA genetic risk score.ConclusionFLS-representative DNA methylation signatures derived from the PB may prove to be valuable biomarkers for the risk of RA or for disease status