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Backgroundβ-decay half-life is one of the fundamental physical properties of unstable nuclei and plays an important role in nuclear physics and astrophysics.PurposeThis study aimed to provide accurate nuclear β-decay half-life predictions and reasonable uncertainties associated with the predictions.MethodsNuclear β-decay half-lives were studied based on the Bayesian neural network (BNN) approach. Three types of neural networks with x = (Z, N), x = (Z, N, Qβ), and x = (Z, N, δ, Qβ) were constructed as inputs to explore the influence of the input on the prediction. The posterior distributions were sampled using the Markov chain Monte Carlo algorithm. The mathematical expectations and standard deviations of the neural network predictions on the posterior distributions were used as the predicted values and errors of the BNN approach.ResultsThe learning accuracy can be significantly improved by incorporating the β-decay energy and physical quantity related to the nuclear pair effect into the neural network input layer and then using the logarithm of β-decay half-life as the network output. For nuclei with half-lives of less than 1 s, the prediction accuracy is approximately 0.2 orders of magnitude, which is similar to that afforded by the BNN method by learning the differences between the logarithms of the experimental half-lives and theoretical results.ConclusionsThe Bayesian neural network can accurately predict β-decay half-lives. When extrapolated to the unknown nuclear region, the predicted β-decay half-lives agree with the results of other theoretical models within errors, especially for nuclei with Z ≳ 50.

Cloud computing is the mainstream information system technology, however, privacy protection of user and privacy violation tracking and forensics in the cloud computing environment have always been a challenge. The current mainstream cloud computing forensics system and standard are not mature and complete, and are far from the target of computer forensics. With the focus on privacy violation and forensics in the cloud environment, status and challenges of cloud forensics and cloud privacy violation were reported firstly. Then, the research content and technical route of privacy forensics in the cloud environments were analyzed. Finally, a specific privacy violation forensics system for cloud environments was presented.

There are strong heterogeneous characteristics of reservoir property between the core and limbs of the Kela-2 anticline, although they are in the same structure. The reservoir heterogeneity mode of “small-scale and east-west” cannot be explained by the distribution mode of compressional stress “large-scale and south-north” proposed by previous scholars. Statistical result of petrographic composition and diagenetic characteristics shows that the differentiation of reservoir compaction between the core and limbs of the Kela-2 anticline is clear. The differentiation is controlled by the difference of tensile stress suffered by strata above the neutral plane during folding deformation. The tensile stress suffered by strata in the anticlinal core is stronger than that in the anticlinal limbs. In the Kela-2 anticline, the difference of tensile stress between the anticlinal core (Kela-201) and limbs (Kela-203 & Kela-204) is obvious. The tensile stress offsets the compaction effect caused by vertical and lateral (south-north) stress, and it is constructive to reservoir quality. It is the major factor controlling the differentiation of reservoir compaction. Key words: Tarim Basin, Kuqa depression, Kela-2 gas field, reservoir quality, structural position, compaction