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ObjectiveTo identify the common sarcosaprophagous flies in the Yangtze River Delta based on mitochondrial cytochrome c oxidase subunit Ⅰ（COⅠ） gene sequence and verify the reliability of this method.MethodsSeven common genetically stable sarcosaprophagous flies in three families and six genera were collected from large domestic pig carcasses placed in the field and cultured in the laboratory for many generations. The whole genome DNA was extracted and the COⅠ gene fragment was amplified. The forward and reverse sequencing was followed by splicing. The base composition of the amplified fragment and the rate of interspecific evolutionary divergence were analyzed by software such as Mega 7.0.26. The phylogenetic tree of COⅠ gene sequence of common necrophagous flies in the Yangtze River Delta was established by neighbor joining （NJ） method and unweighted pair-group method with arithmetic means （UPGMA） method.ResultsThe average base composition of different flies was A（30.14%）, T（38.23%）, C（15.98%）, G（15.65%）. The rate of interspecific evolutionary divergence ranged from 2.2% to 15.3%, the lowest rate was between Chrysomya megacephala and Chrysomya pinguis, the highest rate was between Muscina stabulans and Boettcherisca peregrina.ConclusionCOⅠ gene can be used to identify the common necrophagous flies in the Yangtze River Delta.

Forensic entomology provides a feasible way to estimate postmortem interval （PMI）, of which the growth and development of sarcosaprophagous insects is the most widely used indicator in forensic practice. Over the years, forensic entomologists have carried out a large number of studies on the development biology of sarcosaprophagous insects. This paper illustrates the main factors that affect the development of sarcosaprophagous insects, including temperature, humidity, light, food types and poisons. The development indicators of sarcosaprophagous insects were reviewed from the perspectives of morphology, differential gene expression and biochemical characteristics. It is emphasized that future research of development biology on sarcosaprophagous insects should fully absorb and integrate the methods of artificial intelligence and omics, and the research object also needs further expansion in order to establish a more objective and more accurate PMI estimation method.

Further promoting the application of lithium iron phosphate (LFP) requires both a high-rate performance and high volumetric energy density. Nanosizing and increased carbon content can improve rate performance but may decrease the volumetric energy density. Therefore, it is challenging to achieve both high volumetric energy density and excellent rate performance simultaneously for LFP. Here, we propose a heterogeneous spray-drying method to synthesize low-carbon-content hierarchical large microspheres filled with small microspheres composed of nanosized primary particles. The material was analyzed using X-ray diffraction, Raman spectroscopy, scanning electron microscopy, transmission electron microscopy, and in situ electrochemical impedance spectroscopy. The material exhibits a high tap density and excellent lithium-ion diffusion kinetics. Benefiting from the hierarchical large microsphere structure, the material maintains a capacity of 130.2 mA h g–1 at a rate of 10C and exhibits no capacity decay after 620 cycles at 1C. This study provides insights for the further promotion of LFP applications. [ABSTRACT FROM AUTHOR]

Postmortem interval （PMI） estimation is a major problem in forensic medicine and a vital indicator of crime investigations. Forensic entomology provides a new way to the PMI estimation, and its superiority has been confirmed through many cases, especially in relation to the cadaver at the stage of advanced decomposition even skeleton. The technologies of forensic entomology have become more mature. This review describes the mechanism of forensic entomology used for PMI estimation, emphasizes the standardized application of technology, and lists the data for the reference of forensic experts in China.

Measurement errors and missing data are often arise in practice. Under this circumstance, we focus on using jackknife empirical likelihood (JEL) and adjust jackknife empirical likelihood (AJEL) methods to construct confidence intervals for the error variance in linear models. Based on residuals of the models, the biased-corrected inverse probability weighted estimator of the error variance is introduced. Furthermore, we propose the jackknife estimator, jackknife and adjust jackknife empirical log-likelihood ratios of the error variance and establish their asymptotic distributions. Simulation studies in terms of coverage probability and average length of confidence intervals are conducted to evaluate the proposed method. A real data set is used to illustrate the proposed JEL and AJEL methods. [ABSTRACT FROM AUTHOR]

In this paper, we consider the weighted composite quantile regression for the linear model when the data are right censored and the censoring indicators are missing at random. The adaptive penalized procedures are proposed to discuss variable selection in the model. Under appropriate assumptions, the asymptotic normality and oracle property of these estimators are also established. The simulation studies are conducted to illustrate the finite sample performance of the proposed methods. [ABSTRACT FROM AUTHOR]

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