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The demand for processing vast volumes of data has surged dramatically due to the advancement of machine learning technology. Large-scale data processing necessitates substantial computational resources, prompting individuals and enterprises to turn to cloud services. Accompanying this trend is a growing concern regarding data leakage and misuse. Homomorphic encryption (HE) is one solution for safeguarding data privacy, enabling encrypted data to be processed securely in the cloud. However, the encryption and decryption routines of some HE schemes require considerable computational resources, presenting non-trivial work for clients. In this paper, we propose an outsourced decryption protocol for the prevailing RLWE-based fully homomorphic encryption schemes. The protocol splits the original decryption into two routines, with the computationally intensive part executed remotely by the cloud. Its security relies on an invariant of the NTRU-search problem with a newly designed blinding key distribution. Cryptographic analyses are conducted to configure protocol parameters across varying security levels. Our experiments demonstrate that the proposed protocol achieves up to a $67\%$ acceleration in the client's local decryption, accompanied by a $50\%$ reduction in space usage., Comment: content and title updated

Previous mechanical meta-structures used for mechanical memory storage, computing and information processing are severely constrained by low information density and/or non-robust structural stiffness to stably protect the maintained information. To address these challenges, we proposed a novel reprogrammable multifunctional mechanical metastructure made by an unprecedented building block based on kinematic mechanism. The proposed meta-structure can achieve all abovementioned functionalities accompanying with high information density and promising structural stability. We attribute all these merits to the intrinsic kinematic bifurcations of structural units, which enable the periodic meta-structure with additional and independently deformable bi-stable structural segments, and multi-layered deformed configurations to significantly enlarge the available information bits. We validate the stable information storage are originated from the compatible deformations of local structural segments before and after bifurcations. We illustrated the stored information can be feasibly reprogrammed by magnetic poles. Our design strategy paves new way for creating novel functional mechanical metastuctures.

Some bi or multi-stable Mechanical meta-structures have been implemented as mechanical memory devices which however are with limits such as complex structural forms, low information storage capability and/or fragile structural stability to maintain the stored information bits robustly under external interferences. To address these issues, we refer to the structural intelligence by constructing a simple 3D-printable multi-layered cylindrical kirigami module with gradient structural parameters and propose a mechanical memory device that can robustly store information bits exponentially larger than previous designs. We demonstrate the promising enhancement of information storage capability of our proposed mechanical memory device relies on two mechanisms 1 the deformation sequences of the kirigami module enabled by the gradient structural parameter, which brings the extra dimensional degree of freedom to break the traditional mechanical memory unit with only planar form and merits information bits with spatially combinatorical programmability, and 2 the combinatorics of the deformation independences among the cylindrical kiriagmi unit arrays in the constructed mechanical memory device. Particularly, we achieve both the structural stabilities and the desired structural robustness in the mechanical memory devices by additively introducing magnetic N-S poles in units, which can protect the stored information from interferences like mechanical crushing, impacting and or shaking.

In this paper, a flexible tether-net system is applied to capture the space debris and a numerical framework is established to explore its nonlinear dynamic behaviors, which comprises four principal phases: folding, spreading, contacting, and closing. Based on the discretization of the whole structure into multiple nodes and connected edges, elastic force vectors and associated Jacobian matrix are derived analytically to solve a series of equations of motion. With a fully implicit method applied to analyze the nonlinear dynamics of a slender rod network, the involved mechanical responses are investigated numerically accounting for the interactions. Contact between the deformable net and a rigid body is handled implicitly through a cost-effective modified mass algorithm while the catenary theory is utilized to guide the folding process (from planar configuration to origami-like pattern). The dragging and spreading actions for the folded hexagon net could be realized by shooting six corner mass toward a specific direction; next, the six corners would be controlled to move along a prescribed path producing a closing gesture, when touch between the flying net and the target body is detected, so that for the space debris could be captured and removed successfully. We think the established discrete model could provide a novel insight in the design of active debris removal (ADR) techniques, and promote further development of the model-based control of tether tugging systems., Comment: 19 pages, 18 figures

Natural selection has tuned many flying and swimming animals across different species to share the same narrow design space for optimal high-efficient and energy-saving locomotion, e.g., their dimensionless Strouhal numbers St that relate flapping frequency and amplitude and forward speed fall within the range of 0.2 < St < 0.4 for peak propulsive efficiency. It is rather challenging to achieve both fast and high-efficient soft-bodied swimming robots with high performances that are comparable to marine animals, due to the observed narrow optimal design space in nature and the compliance of soft body. Here, bioinspired by the wing or fin flapping motion in flying and swimming animals, we report leveraging the generic principle of snapping instabilities in the bistable and multistable flexible pre-curved wings for high-performance, butterfly swimming-like, soft-bodied flapping-wing robots. The soft swimming robot is lightweight (2.8 grams) and demonstrates a record-high speed of 3.74 body length/s (4.8 times faster than the reported fastest soft swimmer), high-efficient (0.2 < St = 0.25 < 0.4), low energy consumption cost, and high maneuverability (a high turning speed of 157o /s). Its high performances largely outperform the state-of-the-art soft swimming robots and are even comparable to its biological counterparts.

A lateral Josephson junction in which the surface of a 3D topological insulator serves as the weak link should support topologically protected excitations related to Majorana fermions. The resulting $4\pi$-periodic current-phase relationship could be detected under high-frequency excitation by the suppression of odd Shapiro steps. Here, we demonstrate such devices through the self-formation of a Pd-Te superconducting layer from a telluride topological insulator, and observe suppressed first and third Shapiro steps. Other devices, including those where the Pd-Te layer is bolstered by an additional Al layer, show no suppression of Shapiro steps, a difference supported by simulations. Though we rule out the known trivial causes of suppressed Shapiro steps in our devices, we nevertheless argue that corroborating measurements and disorder-aware theoretical descriptions of these systems are needed before confidently claiming the observation of Majorana states., Comment: 10 pages, 5 figures, plus Supplemental Material