Clinical Comparison of Outcomes of Early versus Delayed Carotid Artery Stenting for Symptomatic Cerebral Watershed Infarction due to Stenosis of the Proximal Internal Carotid Artery

The aim of this study was to compare the clinical outcomes of early versus delayed carotid artery stenting (CAS) for symptomatic cerebral watershed infarction (sCWI) patients due to stenosis of the proximal internal carotid artery. We retrospectively collected clinical data of those who underwent early or delayed CAS from March 2011 to April 2014. The time of early CAS and delayed CAS was within a week of symptom onset and after four weeks from symptom onset. Clinical data such as second stroke, the National Institutes of Health Stroke Scale (NHISS) score, and modified Rankin Scale (mRS) score and periprocedural complications were collected. The rate of second stroke in early CAS group is lower when compared to that of delayed CAS group. There was no significant difference regarding periprocedural complications in both groups. There was a significant difference regarding mean NHISS score 90 days after CAS in two groups. Early CAS group had a significant better good outcome (mRS score ≤ 2) than delayed CAS group. We suggest early CAS for sCWI due to severe proximal internal carotid artery stenosis as it provides lower rate of second stroke, comparable periprocedural complications, and better functional outcomes compared to that of delayed CAS

Realizing In-Memory Baseband Processing for Ultra-Fast and Energy-Efficient 6G

To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors. Traditional complementary metal-oxide-semiconductor (CMOS)-based baseband processors face two challenges in transistor scaling and the von Neumann bottleneck. To address these challenges, in-memory computing-based baseband processors using resistive random-access memory (RRAM) present an attractive solution. In this paper, we propose and demonstrate RRAM-implemented in-memory baseband processing for the widely adopted multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) air interface. Its key feature is to execute the key operations, including discrete Fourier transform (DFT) and MIMO detection using linear minimum mean square error (L-MMSE) and zero forcing (ZF), in one-step. In addition, RRAM-based channel estimation module is proposed and discussed. By prototyping and simulations, we demonstrate the feasibility of RRAM-based full-fledged communication system in hardware, and reveal it can outperform state-of-the-art baseband processors with a gain of 91.2$\times$ in latency and 671$\times$ in energy efficiency by large-scale simulations. Our results pave a potential pathway for RRAM-based in-memory computing to be implemented in the era of the sixth generation (6G) mobile communications.Comment: arXiv admin note: text overlap with arXiv:2205.0356

Production of human blood group B antigen epitope conjugated protein in Escherichia coli and utilization of the adsorption blood group B antibody

Additional file 1: Table S1. List of constructed plasmids, strains and primers used in the study. Figure S1. MALDI-TOF detection of MBPmut (a) and MBPmut-OPS (b)

A perception-based emotion contagion model in crowd emergent evacuation simulation

With the increasing number of emergencies, the crowd simulation technology has attracted wide attention in recent years. Existing emergencies have shown that individuals are easy to be influenced by other’s emotion during the evacuation. This will make it easier for people to aggregate together and increase security risks. Some of the existing evacuation models without considering emotion are therefore not suitable for describing crowd behaviors in emergencies. We propose a perception-based emotion contagion model and use multi-agent technology to simulate the crowd behaviors. Navigation points are introduced to guide the movement of the agents. Based on the proposed model, a prototype simulation system for crowd emotion contagion is developed. The comparative simulation experiments verify that the model can effectively deduct the evacuation time and crowd emotion contagion. The proposed model could be an assistant analysis method for crowd management in emergencies