A gauge-invariant and current-continuous microscopic ac quantum transport theory

There had been consensus on what the accurate ac quantum transport theory was until some recent works challenged the conventional wisdom. Basing on the non-equilibrium Green's function formalism for time-dependent quantum transport, we derive an expression for the dynamic admittance that satisfies gauge invariance and current continuity, and clarify the key concept in the field. The validity of our now formalism is verified by first-principles calculation of the transient current through a carbon-nanotube-based device under the time-dependent bias voltage. Moreover, the previously well-accepted expression for dynamic admittance is recovered only when the device is a perfect conductor at a specific potential

TRAIL Induces Apoptosis and Autophagy

It is known that tumor necrosis factor‐related apoptosis‐inducing ligand (TRAIL) could induce both apoptosis and autophagy. Here, we summarized the recent findings of the key regulators and the crosstalk pathway that highlights the intricate interplay between TRAIL‐induced apoptosis and autophagy

A Novel Fingerprint Encryption Based on Image and Feature Mosaic

Mobile smart devices in the digital era are enhancing personal information security by adopting fingerprint encryption technology, but due to the small size of mobile smart devices, the area of fingerprint image that can be detected is reduced, resulting in the lack of extractable fingerprint feature information, and traditional fingerprint encryption technology is difficult to apply to small area fingerprint images. To solve the application difficulties of small area fingerprint image encryption, a novel small area fingerprint encryption algorithm based on feature and image mosaic was proposed, and the encryption efficiency of the algorithm was verified using FVC2002 and XDFinger database. Results show that the small area fingerprint recognition algorithm based on feature and image mosaic is significantly improved in encryption efficiency, failure capture rate decreases from 36% to 7%, true acceptance rate increases from 44% to 68%, and the feasibility and reliability of the method is verified. Conclusions can promote the application of small area fingerprint encryption technology in mobile smart devices

Optimized Vectorization Implementation of CRYSTALS-Dilithium

CRYSTALS-Dilithium is a lattice-based signature scheme to be standardized by NIST as the primary post-quantum signature algorithm. In this work, we make a thorough study of optimizing the implementations of Dilithium by utilizing the Advanced Vector Extension (AVX) instructions, specifically AVX2 and the latest AVX512. We first present an improved parallel small polynomial multiplication with tailored early evaluation (PSPM-TEE) to further speed up the signing procedure, which results in a speedup of 5\%-6\% compared with the original PSPM Dilithium implementation. We then present a tailored reduction method that is simpler and faster than Montgomery reduction. Our optimized AVX2 implementation exhibits a speedup of 3\%-8\% compared with the state-of-the-art of Dilithium AVX2 software. Finally, for the first time, we propose a fully and highly vectorized implementation of Dilithium using AVX-512. This is achieved by carefully vectorizing most of Dilithium functions with the AVX512 instructions in order to improve efficiency both for time and for space simultaneously. With all the optimization efforts, our AVX-512 implementation improves the performance by 37.3\%/50.7\%/39.7\% in key generation, 34.1\%/37.1\%/42.7\% in signing, and 38.1\%/38.7\%/40.7\% in verification for the parameter sets of Dilithium2/3/5 respectively. To the best of our knowledge, our AVX512 implementation has the best performance for Dilithium on the Intel x64 CPU platform to date.Comment: 13 pages, 5 figure

Experimental Evaluation of Spectrum Sensing Algorithms for Wireless Microphone Signal

Spectrum congestion has become a critical concern in wireless communication systems due to the limited availability of frequency spectrum. Hence, efficient utilization of spectrum is one of the most important challenges in the evolution of wireless communi-cation systems and radio devices. Cognitive radio (CR) has been introduced as an effec-tive solution for spectrum utilization. Spectrum sensing (SS) is one of the key elements in the implementation of effective and reliable CR systems. SS algorithms are used to obtain awareness about the spectrum usage and existence of primary users in a certain spectrum band. Energy detection (ED) based SS is the most common sensing algorithm due to its low computation and implementation complexity. On the other hand, ED based SS is highly dependent on the precise knowledge of the receiver noise variance. Hence, the performance of the ED algorithm is degraded significantly, when there is uncertainty in the estimation of the noise variance. In this thesis, the wireless microphone (WM) system using the CR concept is intro-duced and the sensing performance of WM signals using three different algorithms are studied. The considered algorithms are based on the ED, namely fast Fourier transform (FFT) based ED, analysis filter bank (AFB) based ED and maximum-minimum ED (Max-Min ED) are studied. Following the analytical models and scenarios of energy detector based SS algorithms, the sensing algorithms are implemented using National Instruments’ (NI) Universal Software Radio Peripheral (USRP) and the NI-LabVIEW software platform, together with the necessary toolboxes. This prototype implementa-tion provides reliable performance evaluation of these spectrum sensing approaches us-ing real world receiver implementation and communication signals from a signal genera-tor, as well as actual WM signals. The results of this study suggest that the performance of Max-Min ED is more robust than FFT & AFB based ED under realistic noise vari-ance uncertainty