Subjectivity and Objectivity in Science and Religion

Subjectivity and objectivity are interdependent in both science and religion. In each discipline, objectivity is based on subjectivity, then structured and communicated within paradigms developed by a community. Non-rational thought is vital to both disciplines, and each relies on non-provable assumptions. Thus, although religion and science investigate reality from different perspectives, their methods are fundamentally similar

When private set intersection meets big data : an efficient and scalable protocol

Large scale data processing brings new challenges to the design of privacy-preserving protocols: how to meet the increasing requirements of speed and throughput of modern applications, and how to scale up smoothly when data being protected is big. Efficiency and scalability become critical criteria for privacy preserving protocols in the age of Big Data. In this paper, we present a new Private Set Intersection (PSI) protocol that is extremely efficient and highly scalable compared with existing protocols. The protocol is based on a novel approach that we call oblivious Bloom intersection. It has linear complexity and relies mostly on efficient symmetric key operations. It has high scalability due to the fact that most operations can be parallelized easily. The protocol has two versions: a basic protocol and an enhanced protocol, the security of the two variants is analyzed and proved in the semi-honest model and the malicious model respectively. A prototype of the basic protocol has been built. We report the result of performance evaluation and compare it against the two previously fastest PSI protocols. Our protocol is orders of magnitude faster than these two protocols. To compute the intersection of two million-element sets, our protocol needs only 41 seconds (80-bit security) and 339 seconds (256-bit security) on moderate hardware in parallel mode

Islet Autoantibody Standardization Program 2018 Workshop : Interlaboratory Comparison of Glutamic Acid Decarboxylase Autoantibody Assay Performance

BACKGROUND: The Islet Autoantibody Standardization Program (IASP) aims to improve the performance of immunoassays measuring type 1 diabetes (T1D)-associated autoantibodies and the concordance of results among laboratories. IASP organizes international interlaboratory assay comparison studies in which blinded serum samples are distributed to participating laboratories, followed by centralized collection and analysis of results, providing participants with an unbiased comparative assessment. In this report, we describe the results of glutamic acid decarboxylase autoantibody (GADA) assays presented in the IASP 2018 workshop. METHODS: In May 2018, IASP distributed to participants uniquely coded sera from 43 new-onset T1D patients, 7 multiple autoantibody-positive nondiabetic individuals, and 90 blood donors. Results were analyzed for the following metrics: sensitivity, specificity, accuracy, area under the ROC curve (ROC-AUC), partial ROC-AUC at 95% specificity (pAUC95), and concordance of qualitative and quantitative results. RESULTS: Thirty-seven laboratories submitted results from a total of 48 different GADA assays adopting 9 different formats. The median ROC-AUC and pAUC95 of all assays were 0.87 [interquartile range (IQR), 0.83-0.89] and 0.036 (IQR, 0.032-0.039), respectively. Large differences in pAUC95 (range, 0.001-0.0411) were observed across assays. Of formats widely adopted, bridge ELISAs showed the best median pAUC95 (0.039; range, 0.036-0.041). CONCLUSIONS: Several novel assay formats submitted to this study showed heterogeneous performance. In 2018, the majority of the best performing GADA immunoassays consisted of novel or established nonradioactive tests that proved on a par or superior to the radiobinding assay, the previous gold standard assay format for GADA measurement. (C) 2019 American Association for Clinical ChemistryPeer reviewe