Event-based Compositional Reasoning of Information-Flow Security for Concurrent Systems

High assurance of information-flow security (IFS) for concurrent systems is challenging. A promising way for formal verification of concurrent systems is the rely-guarantee method. However, existing compositional reasoning approaches for IFS concentrate on language-based IFS. It is often not applicable for system-level security, such as multicore operating system kernels, in which secrecy of actions should also be considered. On the other hand, existing studies on the rely-guarantee method are basically built on concurrent programming languages, by which semantics of concurrent systems cannot be completely captured in a straightforward way. In order to formally verify state-action based IFS for concurrent systems, we propose a rely-guarantee-based compositional reasoning approach for IFS in this paper. We first design a language by incorporating ``Event'' into concurrent languages and give the IFS semantics of the language. As a primitive element, events offer an extremely neat framework for modeling system and are not necessarily atomic in our language. For compositional reasoning of IFS, we use rely-guarantee specification to define new forms of unwinding conditions (UCs) on events, i.e., event UCs. By a rely-guarantee proof system of the language and the soundness of event UCs, we have that event UCs imply IFS of concurrent systems. In such a way, we relax the atomicity constraint of actions in traditional UCs and provide a compositional reasoning way for IFS in which security proof of systems can be discharged by independent security proof on individual events. Finally, we mechanize the approach in Isabelle/HOL and develop a formal specification and its IFS proof for multicore separation kernels as a study case according to an industrial standard -- ARINC 653

Diagnostic performance of microRNA-133a in acute myocardial infarction: A meta-analysis

   Background: The aim of this study was to evaluate the diagnostic performance of microRNA-133a in the diagnosis of acute myocardial infarction (AMI). Methods: Major databases including PubMed, Embase and the Cochrane Library were searched for case-controlled studies comparing AMI and non-AMI patients. The outcome was evaluated by the relative expression of microRNA-133a in plasma or serum. The Mantel-Haenszel odds ratio (OR) was calculated using a fixed-effects model meta-analysis for the outcome. The primary outcomes of interest were pooled sensitivity, specificity and diagnostic accuracy of microRNA-133a for AMI. Results: Out of 137 identified related articles, 10 were found to conform with the inclusion and ex­clusion criteria of the study. The 10 case-controlled studies contained complete data for 1,074 patients (with no restrictions of race, age or sex), and a database containing 137 patients from the registry of each study. In addition to low heterogeneity, a statistically significant increase was found in overall microRNA-133a expression between AMI vs. non-AMI; the pooled OR was 22.84 (95% confidence interval [CI] 13.87–37.63), sensitivity was 0.84 (95% CI 0.75–0.90), specificity was 0.82 (95% CI 0.74–0.89) and area under curve (AUC) was 0.90 (95% CI 0.87–0.92). Conclusions: Based on the meta-analysis of ten case-controlled studies including 1,074 patients,it was found that the level of microRNA-133a in blood serum or plasma maybe used as a diagnostic biomarker of AMI

Explicit Feature Interaction-aware Uplift Network for Online Marketing

As a key component in online marketing, uplift modeling aims to accurately capture the degree to which different treatments motivate different users, such as coupons or discounts, also known as the estimation of individual treatment effect (ITE). In an actual business scenario, the options for treatment may be numerous and complex, and there may be correlations between different treatments. In addition, each marketing instance may also have rich user and contextual features. However, existing methods still fall short in both fully exploiting treatment information and mining features that are sensitive to a particular treatment. In this paper, we propose an explicit feature interaction-aware uplift network (EFIN) to address these two problems. Our EFIN includes four customized modules: 1) a feature encoding module encodes not only the user and contextual features, but also the treatment features; 2) a self-interaction module aims to accurately model the user's natural response with all but the treatment features; 3) a treatment-aware interaction module accurately models the degree to which a particular treatment motivates a user through interactions between the treatment features and other features, i.e., ITE; and 4) an intervention constraint module is used to balance the ITE distribution of users between the control and treatment groups so that the model would still achieve a accurate uplift ranking on data collected from a non-random intervention marketing scenario. We conduct extensive experiments on two public datasets and one product dataset to verify the effectiveness of our EFIN. In addition, our EFIN has been deployed in a credit card bill payment scenario of a large online financial platform with a significant improvement.Comment: Accepted by SIGKDD 2023 Applied Data Science Trac

Metasomatized lithospheric mantle for Mesozoic giant gold deposits in the North China craton

The origin of giant lode gold deposits of Mesozoic age in the North China craton (NCC) is enigmatic because high-grade metamorphic ancient crust would be highly depleted in gold. Instead, lithospheric mantle beneath the crust is the likely source of the gold, which may have been anomalously enriched by metasomatic processes. However, the role of gold enrichment and metasomatism in the lithospheric mantle remains unclear. Here, we present comprehensive data on gold and platinum group element contents of mantle xenoliths (n = 28) and basalts (n = 47) representing the temporal evolution of the eastern NCC. The results indicate that extensive mantle metasomatism and hydration introduced some gold (<1–2 ppb) but did not lead to a gold-enriched mantle. However, volatile-rich basalts formed mainly from the metasomatized lithospheric mantle display noticeably elevated gold contents as compared to those from the asthenosphere. Combined with the significant inheritance of mantle-derived volatiles in auriferous fluids of ore bodies, the new data reveal that the mechanism for the formation of the lode gold deposits was related to the volatile-rich components that accumulated during metasomatism and facilitated the release of gold during extensional craton destruction and mantle melting. Gold-bearing, hydrous magmas ascended rapidly along translithospheric fault zones and evolved auriferous fluids to form the giant deposits in the crust