A Distributed Block Chebyshev-Davidson Algorithm for Parallel Spectral Clustering

We develop a distributed Block Chebyshev-Davidson algorithm to solve large-scale leading eigenvalue problems for spectral analysis in spectral clustering. First, the efficiency of the Chebyshev-Davidson algorithm relies on the prior knowledge of the eigenvalue spectrum, which could be expensive to estimate. This issue can be lessened by the analytic spectrum estimation of the Laplacian or normalized Laplacian matrices in spectral clustering, making the proposed algorithm very efficient for spectral clustering. Second, to make the proposed algorithm capable of analyzing big data, a distributed and parallel version has been developed with attractive scalability. The speedup by parallel computing is approximately equivalent to $\sqrt{p}$, where $p$ denotes the number of processes. {Numerical results will be provided to demonstrate its efficiency in spectral clustering and scalability advantage over existing eigensolvers used for spectral clustering in parallel computing environments.

Study of cosmogenic activation in 76^{76}Ge enriched germanium detectors during fabrication and transportation above ground

Rare event search experiments using germanium detectors are operated in underground laboratories to minimize the background induced by cosmic rays. However, the cosmogenic activation in germanium crystals on the ground during fabrication and transportation generates long half-life radionuclides and contributes a considerable background. We simulated the production rates of cosmogenic radionuclides in germanium and calculated the specifi c activities of cosmogenic radionuclides according to the scheduled fabrication and transportation processes of $^{76}$Ge enriched germanium detectors. The impact of cosmogenic background in germanium crystals for the next generation CDEX experiment was assessed with the scheduled exposure history above ground

Statistical delay distribution analysis on high-speed railway trains

Published by SpringerOpen, Heidelber

Black holes in Einstein-dilaton-Massive gravity

In this paper, we focus on the Einstein-dilaton-Massive (EdM) gravity including the coupling of dilaton scalar field to massive graviton terms, and then derive static and spherically symmetric solutions of dilatonic black holes in four dimensional spacetime. We discover that the dilatonic black hole could possess two horizons (event and cosmological), extreme (Nariai) and naked singularity black holes for the suitably fixed parameters. Moreover, the dilatonic black hole solutions are neither asymptotic flat nor (A)dS in the appearance of coupling of the dilaton field. In addition, we investigate thermodynamic properties of these dilatonic black holes, and check the corresponding first law of black hole thermodynamics. Extending to the EdM gravity in high dimensions, we further obtain the dilatonic black hole solutions in ($d+1$) dimensional spacetime.Comment: 17 pages, 6 figure

Whole-genome shotgun sequencing unravels the influence of environmental microbial co-infections on the treatment efficacy for severe pediatric infectious diseases

BackgroundThe microbiome plays a pivotal role in mediating immune deviation during the development of early-life viral infections. Recurrent infections in children are considered a risk factor for disease development. This study delves into the metagenomics of the microbiome in children suffering from severe infections, seeking to identify potential sources of these infections.AimsThe aim of this study was to identify the specific microorganisms and factors that significantly influence the treatment duration in patients suffering from severe infections. We sought to understand how these microbial communities and other variables may affect the treatment duration and the use of antibiotics of these patients with severe infections.MethodWhole-genome shotgun sequencing was conducted on samples collected from children aged 0–14 years with severe infections, admitted to the Pediatrics Department of Xiamen First Hospital. The Kraken2 algorithm was used for taxonomic identification from sequence reads, and linear mixed models were employed to identify significant microorganisms influencing treatment duration. Colwellia, Cryptococcus, and Citrobacter were found to significantly correlate with the duration of clinical treatment. Further analysis using propensity score matching (PSM) and rank-sum test identified clinical indicators significantly associated with the presence of these microorganisms.ResultsUsing a linear mixed model after removed the outliers, we identified that the abundance of Colwellia, Cryptococcus, and Citrobacter significantly influences the treatment duration. The presence of these microorganisms is associated with a longer treatment duration for patients. Furthermore, these microorganisms were found to impact various clinical measures. Notably, an increase in hospitalization durations and medication costs was observed in patients with these microorganisms. In patients with Colwellia, Cryptococcus, and Citrobacter, we discover significant differences in platelets levels. We also find that in patients with Cryptococcus, white blood cells, hemoglobin, and neutrophils levels are lower.ConclusionThese findings suggest that Colwellia, Cryptococcus, and Citrobacter, particularly Cryptococcus, could potentially contribute to the severity of infections observed in this cohort, possibly as co-infections. These microorganisms warrant further investigation into their pathogenic roles and mechanisms of action, as their presence in combination with disease-causing organisms may have a synergistic effect on disease severity. Understanding the interplay between these microorganisms and pathogenic agents could provide valuable insights into the complex nature of severe pediatric infections and guide the development of targeted therapeutic strategies

Simulation and economic analysis of an innovative indoor solar cooking system with energy storage

Solar energy technology and energy storage technology are promising to make a contribution to current energy and global climate issue. The energy demand of daily cooking is enormous, and conventional cooking methods use gas or electricity with large carbon emissions. This paper proposes an innovative solar cooking system (SCS) integrated with rock-bed thermocline storage. Thermal oils transfer heat from the collectors to the rocks in the charging process and release heat in cooktop unit for cooking. The energy consumption of a household is first assessed by a reasonable hypothesis. Mathematical models and simulation models are then established to analyze the heat transfer performance of the cooktop unit and the annual running performance of the SCS. The rock-bed thermocline storage, single-tank thermocline storage and two-tank storage are compared. The simulation results indicate that the rock-bed thermocline storage unit employed to SCS will enhance the annual running performance and acquire the minimum initial investment cost. The economic analysis shows that the lowest levelized cost of cooking energy (LCOC) of the SCS is 0.3884 $/kWh, while the corresponding levelized cost of cooking a meal (LCCM) is 0.953$/Meal and the solar fraction (SF) is 71%. Compared to the electrical and natural gas cooker, the SCS saves 1.75 tons and 0.52 tons of carbon emissions annually, respectively