VLSI Architecture for Polar Codes Using Fast Fourier Transform-Like Design

Polar code is a novel and high-performance communication algorithm with the ability to theoretically achieving the Shannon limit, which has attracted increasing attention recently due to its low encoding and decoding complexity. Hardware optimization further reduces the cost and achieves better timing performance enabling real-time applications on resource-constrained devices. This thesis presents an area-efficient architecture for a successive cancellation (SC) polar decoder. Our design applies high-level transformations to reduce the number of Processing Elements (PEs), i.e., only log2 N pre-computed PEs are required in our architecture for an N-bit code. We also propose a customized loop-based shifting register to reduce the consumption of the delay elements further. Our experimental results demonstrate that our architecture reduces 98.90% and 93.38% in the area and area-time product, respectively, compared to prior works

High-Performance VLSI Architectures for Lattice-Based Cryptography

Lattice-based cryptography is a cryptographic primitive built upon the hard problems on point lattices. Cryptosystems relying on lattice-based cryptography have attracted huge attention in the last decade since they have post-quantum-resistant security and the remarkable construction of the algorithm. In particular, homomorphic encryption (HE) and post-quantum cryptography (PQC) are the two main applications of lattice-based cryptography. Meanwhile, the efficient hardware implementations for these advanced cryptography schemes are demanding to achieve a high-performance implementation. This dissertation aims to investigate the novel and high-performance very large-scale integration (VLSI) architectures for lattice-based cryptography, including the HE and PQC schemes. This dissertation first presents different architectures for the number-theoretic transform (NTT)-based polynomial multiplication, one of the crucial parts of the fundamental arithmetic for lattice-based HE and PQC schemes. Then a high-speed modular integer multiplier is proposed, particularly for lattice-based cryptography. In addition, a novel modular polynomial multiplier is presented to exploit the fast finite impulse response (FIR) filter architecture to reduce the computational complexity of the schoolbook modular polynomial multiplication for lattice-based PQC scheme. Afterward, an NTT and Chinese remainder theorem (CRT)-based high-speed modular polynomial multiplier is presented for HE schemes whose moduli are large integers

PaReNTT: Low-Latency Parallel Residue Number System and NTT-Based Long Polynomial Modular Multiplication for Homomorphic Encryption

High-speed long polynomial multiplication is important for applications in homomorphic encryption (HE) and lattice-based cryptosystems. This paper addresses low-latency hardware architectures for long polynomial modular multiplication using the number-theoretic transform (NTT) and inverse NTT (iNTT). Chinese remainder theorem (CRT) is used to decompose the modulus into multiple smaller moduli. Our proposed architecture, namely PaReNTT, makes four novel contributions. First, parallel NTT and iNTT architectures are proposed to reduce the number of clock cycles to process the polynomials. This can enable real-time processing for HE applications, as the number of clock cycles to process the polynomial is inversely proportional to the level of parallelism. Second, the proposed architecture eliminates the need for permuting the NTT outputs before their product is input to the iNTT. This reduces latency by n/4 clock cycles, where n is the length of the polynomial, and reduces buffer requirement by one delay-switch-delay circuit of size n. Third, an approach to select special moduli is presented where the moduli can be expressed in terms of a few signed power-of-two terms. Fourth, novel architectures for pre-processing for computing residual polynomials using the CRT and post-processing for combining the residual polynomials are proposed. These architectures significantly reduce the area consumption of the pre-processing and post-processing steps. The proposed long modular polynomial multiplications are ideal for applications that require low latency and high sample rate as these feed-forward architectures can be pipelined at arbitrary levels

Hierarchical Intention Tracking for Robust Human-Robot Collaboration in Industrial Assembly Tasks

Collaborative robots require effective human intention estimation to safely and smoothly work with humans in less structured tasks such as industrial assembly, where human intention continuously changes. We propose the concept of intention tracking and introduce a collaborative robot system that concurrently tracks intentions at hierarchical levels. The high-level intention is tracked to estimate human\u27s interaction pattern and enable robot to (1) avoid collision with human to minimize interruption and (2) assist human to correct failure. The low-level intention estimate provides robot with task-related information. We implement the system on a UR5e robot and demonstrate robust, seamless and ergonomic human-robot collaboration in an ablative pilot study of an assembly use case

Scalp mechanical stimulation alleviates cerebral hypoperfusion in rats with 2-VO by controlling cerebral edema

Objective: To illustrate the cerebral protective effect of scalp mechanical stimulation (SMS), similar to scalp acupuncture in basic mechanism, on cerebral edema in rats with cerebral hypoperfusion. Methods: First, we screened the strength of SMS by measuring skin temperature and blood perfusion using laser speckle contrast imaging. Next, we observed the cerebral protective effects on cerebral blood perfusion, cerebral edema, and pathological changes in rats with modified two-vessel carotid artery occlusion (2-VO). Furthermore, the apoptosis-related proteins (caspase-3, cleaved-caspase-3) and cerebral edema related proteins [antiglial fibrillary acidic protein (GFAP) and antiaquaporin-4 (AQP4)] were measured via immunohistochemistry and Western blot analysis. Additionally, the correlation between neural apoptosis and AQP4 protein levels was analyzed. Results: We found that 0.5 N was the best SMS intensity suitable for our study. Compared with the control group, 0.5, 1, and 2 N maintained the scalp temperature and improved scalp blood flow (all P < .05). SMS intervention significantly increased cerebral blood flow and reduced the brain water content in rats with 2-VO (P < .001 and P = .0449, respectively). Compared to the rats with 2-VO, SMS treatment significantly reduced the number of caspase-3-positive cells (P = .0086) and cleaved caspase-3-positive cells (P = .036) in the hippocampal CA1, which was similar to the protein level of caspase-3 (P = .019). Compared to the sham group, the expression of GFAP and AQP4 was higher in the 2-VO group (P = .0369 and P = .0142), which was significantly decreased by SMS (P = .0484 and P = .0229). The expression of AQP4 was positively correlated with the expression of caspase-3 or cleaved caspase-3 (R2 = 0.6071/R2 = 0.8500). Conclusion: This study demonstrated the optimum SMS intensity for ameliorating cerebral hypoperfusion and its possible mechanism of action. Therefore, SMS is a promising and straightforward method for preventing ischemic stroke and cognitive impairment

Spin-resolved purcell effect in a quantum dot microcavity system

We demonstrate the spin selective coupling of the exciton state with cavity mode in a single quantum dot (QD)-micropillar cavity system. By tuning an external magnetic field, each spin polarized exciton state can be selectively coupled with the cavity mode due to the Zeeman effect. A significant enhancement of spontaneous emission rate of each spin state is achieved, giving rise to a tunable circular polarization degree from -90% to 93%. A four-level rate equation model is developed, and it agrees well with our experimental data. In addition, the coupling between photon mode and each exciton spin state is also achieved by varying temperature, demonstrating the full manipulation over the spin states in the QD-cavity system. Our results pave the way for the realization of future quantum light sources and the quantum information processing applications

Preclinical Studies of Chiauranib Show It Inhibits Transformed Follicular Lymphoma through the VEGFR2/ERK/STAT3 Signaling Pathway

Transformed follicular lymphoma (t-FL), for which there is no efficient treatment strategy, has a rapid progression, treatment resistance, and poor prognosis, which are the main reasons for FL treatment failure. In this study, we identified a promising therapeutic approach with chiauranib, a novel orally developed multitarget inhibitor targeting VEGFR/Aurora B/CSF-1R. We first determined the cytotoxicity of chiauranib in t-FL cell lines through CCK-8, EdU staining, flow cytometry, and transwell assays. We also determined the killing effect of chiauranib in a xenograft model. More importantly, we identified the underlying mechanism of chiauranib in t-FL tumorigenesis by immunofluorescence and Western blotting. Treatment with chiauranib significantly inhibited cell growth and migration, promoted apoptosis, induced cell cycle arrest in G2/M phase, and resulted in significant killing in vivo. Mechanistically, chiauranib suppresses the phosphorylation level of VEGFR2, which has an anti-t-FL effect by inhibiting the downstream MEK/ERK/STAT3 signaling cascade. In conclusion, chiauranib may be a potential therapy to treat t-FL, since it inhibits tumor growth and migration and induces apoptosis by altering the VEGFR2/ERK/STAT3 signaling pathway