An enhanced watermarking protocol for electronic copyright management

In Piva et al\u27s watermarking scheme for electronic copyright management system (ECMS), authors were considered trusted potentially, so a dishonest author could authorize more than one distributor to sell her one document, named &quot;One Document to Multi-distributor&quot; problem, which would damage the benefit of the distributors. To resolve the problem, in this paper, we propose an enhanced watermarking protocol based on Piva et al\u27s scheme by introducing document nature code (DNC) and register records table. In addition, our protocol offers the distributor an efficient means to verify his right to an authorized digital document.<br /

Secure buyer - seller watermarking protocol

In the existing watermarking protocols, a trusted third party (TTP) is introduced to guarantee that a protocol is fair to both the seller and buyer in a digital content transaction. However, the TTP decreases the security and affects the protocol implementation. To address this issue, in this article a secure buyer&ndash;seller watermarking protocol without the assistance of a TTP is proposed in which there are only two participants, a seller and a buyer. Based on the idea of sharing a secret, a watermark embedded in digital content to trace piracy is composed of two pieces of secret information, one produced by the seller and one by the buyer. Since neither knows the exact watermark, the buyer cannot remove the watermark from watermarked digital content, and at the same time the seller cannot fabricate piracy to frame an innocent buyer. In other words, the proposed protocol can trace piracy and protect the customer&rsquo;s rights. In addition, because no third party is introduced into the proposed protocol, the problem of a seller (or a buyer) colluding with a third party to cheat the buyer (or the seller), namely, the conspiracy problem, can be avoided.<br /

Hrs Promotes Ubiquitination and Mediates Endosomal Trafficking of Smoothened in Drosophila Hedgehog Signaling

In Hedgehog (Hh) signaling, the seven-transmembrane protein Smoothened (Smo) acts as a signal transducer that is regulated by phosphorylation, ubiquitination, and cell surface accumulation. However, it is not clear how Smo cell surface accumulation and intracellular trafficking are regulated. Here, we demonstrate that inactivation of Hrs by deletion or RNAi accumulates Smo in the late endosome that is marked by late endosome markers. Inactivation of Hrs enhances the wing defects caused by dominant-negative Smo. We show that Hrs promotes Smo ubiquitination, deleting the ubiquitin-interacting-motif (UIM) in Hrs abolishes the ability of Hrs to regulate Smo ubiquitination. However, the UIM domain neither recognizes the ubiquitinated Smo nor directly interacts with Smo. Hrs lacking UIM domain still downregulates Smo activity even though to a less extent. We have characterized that the N-terminus of Hrs directly interacts with the PKA/CK1 phosphorylation clusters to prevent Smo phosphorylation and activation, indicating an ubiquitin-independent regulation of Smo by Hrs. Finally, we found that knockdown of Tsg101 accumulates Smo that is co-localized with Hrs and other late endosome markers. Taken together, our data indicate that Hrs mediates Smo trafficking in the late endosome by not only promoting Smo ubiquitination but also blocking Smo phosphorylation

Watermarking protocol of secure verification

The secure verification is important for watermarking protocols. A malicious arbitrator is able to remove an original watermark from an unauthorized copy of the digital content as a result of a security breach in the phase of arbitration and resell multiple copies of it with impunity. We propose a novel buyer-seller watermarking protocol of secure verification. In this scheme, a seller permutes an original watermark provided by a trusted Watermarking Certification Authority (WCA) and embeds it into digital content in an encrypted domain. In case an unauthorized copy is found, the seller can recover the original watermark from the watermark extracted from the copy and sends it to an arbitrator. Without the knowledge of permutations applied by the seller, the arbitrator is unable to remove the permuted watermark from the digital content. Hence, verification is secured. As an additional advantage of the proposed protocol, arbitration can be conducted without the need for the cooperation of the WCA or the buyer

Inter-individual deep image reconstruction via hierarchical neural code conversion

The sensory cortex is characterized by general organizational principles such as topography and hierarchy. However, measured brain activity given identical input exhibits substantially different patterns across individuals. Although anatomical and functional alignment methods have been proposed in functional magnetic resonance imaging (fMRI) studies, it remains unclear whether and how hierarchical and fine-grained representations can be converted between individuals while preserving the encoded perceptual content. In this study, we trained a method of functional alignment called neural code converter that predicts a target subject’s brain activity pattern from a source subject given the same stimulus, and analyzed the converted patterns by decoding hierarchical visual features and reconstructing perceived images. The converters were trained on fMRI responses to identical sets of natural images presented to pairs of individuals, using the voxels on the visual cortex that covers from V1 through the ventral object areas without explicit labels of the visual areas. We decoded the converted brain activity patterns into the hierarchical visual features of a deep neural network using decoders pre-trained on the target subject and then reconstructed images via the decoded features. Without explicit information about the visual cortical hierarchy, the converters automatically learned the correspondence between visual areas of the same levels. Deep neural network feature decoding at each layer showed higher decoding accuracies from corresponding levels of visual areas, indicating that hierarchical representations were preserved after conversion. The visual images were reconstructed with recognizable silhouettes of objects even with relatively small numbers of data for converter training. The decoders trained on pooled data from multiple individuals through conversions led to a slight improvement over those trained on a single individual. These results demonstrate that the hierarchical and fine-grained representation can be converted by functional alignment, while preserving sufficient visual information to enable inter-individual visual image reconstruction

Efficient Quantum Mixed-State Tomography with Unsupervised Tensor Network Machine Learning

Quantum state tomography (QST) is plagued by the ``curse of dimensionality'' due to the exponentially-scaled complexity in measurement and data post-processing. Efficient QST schemes for large-scale mixed states are currently missing. In this work, we propose an efficient and robust mixed-state tomography scheme based on the locally purified state ansatz. We demonstrate the efficiency and robustness of our scheme on various randomly initiated states with different purities. High tomography fidelity is achieved with much smaller numbers of positive-operator-valued measurement (POVM) bases than the conventional least-square (LS) method. On the superconducting quantum experimental circuit [Phys. Rev. Lett. 119, 180511 (2017)], our scheme accurately reconstructs the Greenberger-Horne-Zeilinger (GHZ) state and exhibits robustness to experimental noises. Specifically, we achieve the fidelity $F \simeq 0.92$ for the 10-qubit GHZ state with just $N_m = 500$ POVM bases, which far outperforms the fidelity $F \simeq 0.85$ by the LS method using the full $N_m = 3^{10} = 59049$ bases. Our work reveals the prospects of applying tensor network state ansatz and the machine learning approaches for efficient QST of many-body states.Comment: 7 pages, 6 figure

An unprecedented 2D covalent organic framework with an htb net topology.

A 2D imine-linked COF with a hitherto unreported htb type topology was synthesized from a linear diamine linker and a judiciously designed tetra-aldehyde building block. This work opens the door to the development of COFs with unprecedented topologies and may broaden the scope of COF functional materials by pore size and pore surface engineering

Dynamics of quantum coherence in many-body localized systems

We demonstrate that the dynamics of quantum coherence serves as an effective probe for identifying dephasing, which is a distinctive signature of many-body localization (MBL). Quantum coherence can be utilized to measure both the local coherence of specific subsystems and the total coherence of the whole system in a consistent manner. Our results reveal that the local coherence of small subsystems decays over time following a power law in the MBL phase, while it reaches a stable value within the same time window in the Anderson localized (AL) phase. In contrast, the total coherence of the whole system exhibits logarithmic growth during the MBL phase and reaches a stable value in the AL phase. Notably, this dynamic characteristic of quantum coherence remains robust even with weak interactions and displays unbounded behavior in infinite systems. Our results provide insights into understanding many-body dephasing phenomena in MBL systems and propose a novel feasible method for identifying and characterizing MBL phases in experiments