Oilfield development aiming at crude oil production is an extremely complex process, which involves many uncertain risk factors affecting oil output. Thus, risk prediction and early warning about oilfield development may insure operating and managing oilfields efficiently to meet the oil production plan of the country and sustainable development of oilfields. However, scholars and practitioners in the all world are seldom concerned with the risk problem of oilfield block development. The early warning index system of blocks development which includes the monitoring index and planning index was refined and formulated on the basis of researching and analyzing the theory of risk forecasting and early warning as well as the oilfield development. Based on the indexes of warning situation predicted by neural network, the method dividing the interval of warning degrees was presented by “3σ” rule; and a new method about forecasting and early warning of risk was proposed by introducing neural network to Bayesian networks. Case study shows that the results obtained in this paper are right and helpful to the management of oilfield development risk.

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Skin is the body’s largest organ, and the main function of skin is to protect underlying organs from possible external damage. Melanocytes play an important role in skin pigmentation. The Bama pig has a “two-end-black” phenotype with different coat colors across skin regions, e.g., white skin (without melanocytes) and black skin (with melanocytes), which could be a model to investigate skin-related disorders, specifically loss of melanocytes. Here, we generated expression profiles of mRNAs and long noncoding RNAs in Bama pig skins with different coat colors. In total, 14,900 mRNAs and 7549 lncRNAs were expressed. Overall, 2338 mRNAs/113 lncRNAs with FDR-adjusted p-value ≤ 0.05 were considered to be differentially expressed (DE) mRNAs/lncRNAs, with 1305 down-regulated mRNAs and 1033 up-regulated mRNAs in white skin with|log2(fold change)| > 1. The genes down-regulated in white skin were associated with pigmentation, melanocyte–keratinocyte interaction, and keratin, while up-regulated ones were mainly associated with cellular energy metabolisms. Furthermore, those DE lncRNAs were predicted to be implicated in pigmentation, keratin synthesis and cellular energy metabolism. In general, this study provides insight into the transcriptional difference involved in melanocyte-loss-induced keratinocyte changes and promotes the Bama pig as a biomedical model in skin research.

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Background: The microbiota of the digestive and reproductive systems has a prominent role in animal health and performance, but the extent of its contribution is difficult to determine. In chickens, the effect of host genetics on the reproductive and digestive tract microbiota is unclear, and the means by which digestive/reproductive microbiomes help improve egg production in chicken are unknown. Results: To gain insight into this, we examined genomes from 128 chickens reared under identical conditions and described their digestive (crop, gizzard and small intestine) and reproductive tract (vagina, uterus and isthmus) microbiota. Although the diversity, composition and predicted function of the digestive and reproductive tract microbiota exhibited notable microbiota variation substantially between different parts, host genetics had limited effects on the reproductive and digestive tract microbial community. The digestive and reproductive tract microbiota had a significant effect on egg production (accounting for 52.31% - 98.86% of the variance), after correcting for host genetic effects; in particular, the uterus and isthmus microbiota accounted for an average of 93.59% and 98.86%, respectively, of variance in egg production. We further identified four reproductive tract microbial species which were related to immune system, Bacteroides fragilis , Bacteroides salanitronis , Bacteroides barnesiae and Clostridium leptum , that were significantly positively correlated with egg production. Chickens with a lower abundance of these species had produced significantly fewer eggs at 300 days of age (37.13 vs. 113.75) than those with a higher abundance of these microorganisms. We speculated that these microorganisms regulate chicken reproductive activity by mediating its immune system. Conclusions: Host genetics has limited effect on digestive/reproductive microbiome composition. The distinct site-associated chicken microbiome may be determined by the differences of their physical function. These findings may help design strategies for controlling and altering the digestive/reproductive tract microbiota in chickens to improve egg production.