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Abstract-Cloud computing economically enables customers with limited computational resources to outsource large-scale computations to the cloud. However, how to protect customers' confidential data involved in the computations then becomes a major security concern. In this paper, we present a secure outsourcing mechanism for solving large-scale systems of linear equations (LE) in cloud. Because applying traditional approaches like Gaussian elimination or LU decomposition (aka. direct method) to such large-scale LE problems would be prohibitively expensive, we build the secure LE outsourcing mechanism via a completely different approach -iterative method, which is much easier to implement in practice and only demands relatively simpler matrix-vector operations. Specifically, our mechanism enables a customer to securely harness the cloud for iteratively finding successive approximations to the LE solution, while keeping both the sensitive input and output of the computation private. For robust cheating detection, we further explore the algebraic property of matrix-vector operations and propose an efficient result verification mechanism, which allows the customer to verify all answers received from previous iterative approximations in one batch with high probability. Thorough security analysis and prototype experiments on Amazon EC2 demonstrate the validity and practicality of our proposed design.

Phosphatidylinositol 3-phosphate (PI3P) plays essential roles in vesicular trafficking, organelle biogenesis and autophagy. Two class III phosphatidylinositol 3-kinase (PI3KC3) complexes have been identified in mammals, the ATG14L complex (PI3KC3-C1) and the UVRAG complex (PI3KC3-C2). PI3KC3-C1 is crucial for autophagosome biogenesis, and PI3KC3-C2 is involved in various membrane trafficking events. Here we report the cryo-EM structures of human PI3KC3-C1 and PI3KC3-C2 at sub-nanometer resolution. The two structures share a common L-shaped overall architecture with distinct features. EM examination revealed that PI3KC3-C1 "stands up" on lipid monolayers, with the ATG14L BATs domain and the VPS34 C-terminal domain (CTD) directly contacting the membrane. Biochemical dissection indicated that the ATG14L BATs domain is responsible for membrane anchoring, whereas the CTD of VPS34 determines the orientation. Furthermore, PI3KC3-C2 binds much more weakly than PI3KC3-C1 to both PI-containing liposomes and purified endoplasmic reticulum (ER) vesicles, a property that is specifically determined by the ATG14L BATs domain. The in vivo ER localization analysis indicated that the BATs domain was required for ER localization of PI3KC3. We propose that the different lipid binding capacity is the key factor that differentiates the functions of PI3KC3-C1 and PI3KC3-C2 in autophagy.

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The development and application of a deep near-infrared (NIR) emitting star-shaped diketopyrrolopyrrole−Zn-porphyrin compound, ZnP(TDPP) 4 , is reported. The structure, conjugation, and planarity of the porphyrin compound were carefully tuned by molecular design, which resulted in a low-energy photoluminescence peak at 872 nm. The ZnP(TDPP) 4 compound was employed as the emissive guest in light-emitting electrochemical cells (LECs), which also comprised the conjugated polymer poly[1,3-bis(2-ethylhexyl)-5-(5-(6-methyl-4,8-bis(5-(tributylsilyl)thiophen-2yl)benzo[1,2-b:4,5-b′]dithiophen-2-yl)thiophen-2-yl)-7-(5-methylthiophen-2-yl)-4H,8H-benzo[1,2-c:4,5-c′]dithiophene-4,8-dione] (PBDTSi-BDD) as the majority host, an ionic liquid as the electrolyte, and two air-stabile electrodes. These systematically optimized host−guest LECs featured a peak electroluminescence at 900 nm, which was delivered at a significant radiance of 36 μW/cm 2 and at a low drive voltage of 3.8 V. It is notable that this is the most redshifted NIR emission attained from an LEC device to date, and as such, this work introduces Zn porphyrins as a sustainable and tunable option for emerging emissive NIR applications.

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