Biblio

Mid-infrared spectroscopic imaging (MIRSI) is an emerging class of label-free, biochemically quantitative technologies targeting digital histopathology. Conventional histopathology relies on chemical stains that alter tissue color. This approach is qualitative, often making histopathologic examination subjective and difficult to quantify. MIRSI addresses these challenges through quantitative and repeatable imaging that leverages native molecular contrast. Fourier transform infrared (FTIR) imaging, the best-known MIRSI technology, has two challenges that have hindered its widespread adoption: data collection speed and spatial resolution. Recent technological breakthroughs, such as photothermal MIRSI, provide an order of magnitude improvement in spatial resolution. However, this comes at the cost of acquisition speed, which is impractical for clinical tissue samples. This paper introduces an adaptive compressive sampling technique to reduce hyperspectral data acquisition time by an order of magnitude by leveraging spectral and spatial sparsity. This method identifies the most informative spatial and spectral features, integrates a fast tensor completion algorithm to reconstruct megapixel-scale images, and demonstrates speed advantages over FTIR imaging while providing spatial resolutions comparable to new photothermal approaches.

Recently, there has been significant enthusiasms in exploiting physical (PHY-) layer characteristics for secure wireless communication. However, most existing PHY-layer security paradigms are information theoretical methodologies, which are infeasible to real and practical systems. In this paper, we propose a weighted fractional Fourier transform (WFRFT) pre-coding scheme to enhance the security of wireless transmissions against eavesdropping. By leveraging the concept of WFRFT, the proposed scheme can easily change the characteristics of the underlying radio signals to complement and secure upper-layer cryptographic protocols. We demonstrate a running prototype based on the LTE-framework. First, the compatibility between the WFRFT pre-coding scheme and the conversational LTE architecture is presented. Then, the security mechanism of the WFRFT pre-coding scheme is demonstrated. Experimental results validate the practicability and security performance superiority of the proposed scheme.

As a decentralized ledger technology, blockchain is considered to be a potential solution for applications with highly concentrated management mechanism. However, most of the existing blockchain networks are employed with the hash-puzzle-solving consensus protocol, known as proof-of-work. The competition of solving the puzzle introduces high latency, which directly leads to a long transaction-processing time. One solution of this dilemma is to establish a blockchain network with shards. In this paper, we focus on the blockchain network with shards and adopt the security-deposit based consensus protocol, studying the problem of how to balance the security incentive and the economic incentive. Also, the inherent features of the blockchain, i.e., anonymity and decentralization, introduce the information asymmetric issue between the beacon chain and the participants. The contract theory is utilized to formulate the problem between them. As such, the optimal rewards related to the different types of validators can be obtained, as well as the reasonable deposits accordingly. Compared with the fixed deposits, the flexible deposits can provide enough economic incentive for the participants without losing the security incentives. Besides, the simulation results demonstrate that the contract theory approach is capable of maximizing the beacon chain's utility and satisfying the incentive compatibility and individual rationality of the participants.