There is a lack of appropriate classification criteria for the determination of atretic follicles in guinea pigs. In the present study, new criteria were established based on the latest morphologic criteria for cell death proposed by the Nomenclature Committee on Cell Death (NCCD) in 2009. Ovaries of guinea pigs were sampled on different stages of estrous cycle, and the morphologic observations of atretic follicles were investigated in serial sections. The results showed that the process of follicular atresia could be classified into four continuous stages: (1) the granulosa layer became loose, and some apoptotic bodies began to appear; (2) the granulosa cells were massively eliminated; (3) the theca interna cells differentiated; and (4) the residual follicular cells degenerated. In addition, the examination revealed that these morphologic criteria were accurate and feasible. In conclusion, this study provides new criteria for the classification of atretic follicles in guinea pigs, and this knowledge can inform future research in the area.

Albumen quality is a leading economic trait in the chicken industry. Major studies have paid attention to genetic architecture underlying albumen quality. However, the putative quantitative trait locus (QTL) for this trait is still unclear. In this genome-wide association study, we used an F₂ resource population to study longitudinal albumen quality. Seven single-nucleotide polymorphism (SNP) loci were found to be significantly ($p\mathit{<}\mathrm{8.43}\times {\mathrm{10}}^{-\mathrm{7}}$ ) related to albumen quality by univariate analysis, while 11 SNPs were significantly ($p\mathit{<}\mathrm{8.43}\times {\mathrm{10}}^{-\mathrm{7}}$ ) associated with albumen quality by multivariate analysis. A QTL on GGA4 had a pervasive function on albumen quality, including a SNP at the missense of NCAPG, and a SNP at the intergenic region of FGFPB1. It was further found that the putative QTLs at GGA1, GGA2, and GGA7 had the strongest effects on albumen height (AH) at 32 weeks, Haugh units (HU) at 44 weeks, and AH at 55 weeks. Moreover, novel SNPs on GGA5 and GGA3 were associated with AH and HU at 32, 44, and 48 weeks of age. These results confirmed the regions for egg weight that were detected in a previous study and were similar with QTL for albumen quality. These results showed that GGA4 had the strongest effect on albumen quality. Only a few significant loci were detected for most characteristics probably reflecting the attributes of a pleiotropic gene and a minor-polygene in quantitative traits.

Both of the coalbed methane (CBM) and shale gas reservoirs are dominated by nanometer‐scale pores with their nanopore structures controlling the occurrence, enrichment, and accumulation of natural gas. Low‐pressure nitrogen gas adsorption (LP‐N₂GA), low‐pressure carbon dioxide gas adsorption (LP‐CO₂GA), high‐pressure methane adsorption (HPMA), and field emission scanning electron microscope (FE‐SEM) experiments were conducted on 14 different‐rank coal samples and nine Longmaxi shale samples collected from various basins in China to compare their nanopore characteristics. The FE‐SEM results indicate that the pore structures of both the coal and shale samples consist of nanometer‐sized pores that primarily developed in the organic matter. The types of their isothermal adsorption curves are similar. However, the coal and shale samples possess various hysteresis loops, which suggest that the nanopores in shale are open‐plated, whereas those in coal are semi‐open. Furthermore, the specific surface area (SSA) and pore volume (PV) of the micropores in coal are much larger than those of the mesopores, with the micropore SSAs accounting for 99% of the total SSA in the coal samples. However, the micropore SSAs in the shale samples only account 42.24% of the total SSA. These different nanopore structures reflect their different methane adsorption mechanisms. The methane adsorption of coal is primarily controlled by the micropore SSA, whereas that of shale is primarily controlled by the mesopore SSA. If we use mesopore SSA to analyze its impact on methane adsorption capacity of coal and shale, it will be mismatched. However, no mismatching relationship exists between the total SSAs and adsorption capacities of coal and shale. This study highlights the controlling effect of total SSA on methane adsorption capacity.

Previous studies have shown that shale oil mobility depends on the relative content of free oil and adsorbed oil. However, the research on how to establish a shale oil mobility evaluation is relatively insufficient. This study aims to use pyrolysis data before and after extraction to accurately identify the content of free oil and adsorbed oil, analyze the influencing factors of shale oil mobility, characterize the hydrocarbon generation and expulsion process, and evaluate shale oil mobility. We utilized an integrated mineralogical and geochemical dataset from the PS18-1 well in the Liutun Sag, Dongpu Depression, Bohai Bay Basin. The results show that the adsorption capacity of type I organic matter (OM) on shale oil is greater than that of type II OM, the OM abundance is of great significance to shale oil mobility, and that quartz and feldspar can promote shale oil mobility. The T_max corresponding to the threshold of hydrocarbon expulsion is 438~440 °C, and the oil saturation index (OSI) is about 158 mg/g TOC. There are four small intervals: a (3257 m~3260 m), b (3262 m~3267 m), c (3273 m~3278 m), and d (3281 m~3282 m) meeting the conditions of hydrocarbon expulsion. Large-scale hydrocarbon expulsion occurred in interval a, a small amount of hydrocarbon expulsion in interval b, a large amount of hydrocarbon expulsion in interval c, and almost no hydrocarbon expulsion in interval d. Based on the crossplot of S₁ and TOC, combined with other parameters such as OSI, hydrocarbon generation potential (HGP), and free and adsorbed oil, we established an evaluation chart of shale oil mobility and divided it into five categories: A, B, C, D, and E. While categories A and C have good mobility and great resource potential, categories B and D have relatively poor mobility and medium resource potential, and category E has little mobility and is an invalid resource.

Face recognition has recently become ubiquitous in many scenes for authentication or security purposes. Meanwhile, there are increasing concerns about the privacy of face images, which are sensitive biometric data that should be carefully protected. Software-based cryptosystems are widely adopted nowadays to encrypt face images, but the security level is limited by insufficient digital secret key length or computing power. Hardware-based optical cryptosystems can generate enormously longer secret keys and enable encryption at light speed, but most reported optical methods, such as double random phase encryption, are less compatible with other systems due to system complexity. In this study, a plain yet high-efficient speckle-based optical cryptosystem is proposed and implemented. A scattering ground glass is exploited to generate physical secret keys of gigabit length and encrypt face images via seemingly random optical speckles at light speed. Face images can then be decrypted from the random speckles by a well-trained decryption neural network, such that face recognition can be realized with up to 98% accuracy. The proposed cryptosystem has wide applicability, and it may open a new avenue for high-security complex information encryption and decryption by utilizing optical speckles.