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Chronic neuroinflammation has been shown to exert adverse influences on the pathology of Alzheimer's disease (AD), associated with the release of abundant proinflammatory mediators by excessively activated microglia, causing synaptic dysfunction, neuronal degeneration, and memory deficits. Thus, the prevention of microglial activation‐associated neuroinflammation is important target for deterring neurodegenerative disorders. Peony seed oil (PSO) is a new food resource, rich in α‐linolenic acid, the precursor of long chain omega‐3 polyunsaturated fatty acids, including docosahexaenoic acid and eicosapentaenoic acid, which exhibit anti‐inflammatory properties by altering cell membrane phospholipid fatty acid compositions, disrupting lipid rafts, and inhibiting the activation of the proinflammatory transcription factor NF‐κB. However, few studies have examined the anti‐neuroinflammatory effects of PSO in AD, and the relevant molecular mechanisms remain unclear. Presenilin1/2 conditional double knockout (PS cDKO) mice display obvious AD‐like phenotypes, such as neuroinflammatory responses, synaptic dysfunction, and cognitive deficits. Here, we assessed the potential neuroprotective effects of PSO against neuroinflammation‐mediated cognitive deficits in PS cDKO using behavioral tests and molecular biologic analyses. Our study demonstrated that PSO suppressed microglial activation and neuroinflammation through the down‐regulation of proinflammatory mediators, such as inducible NOS, COX‐2, IL‐1β, and TNF‐α, in the prefrontal cortex and hippocampus of PS cDKO mice. Further, PSO significantly lessened memory impairment by reversing hyperphosphorylated tau and synaptic proteins deficits in PS cDKO mice. Importantly, PSO's therapeutic effects on cognitive deficits were due to inhibiting neuroinflammatory responses mediated by NF‐κB signaling pathway. Taken together, PSO may represent an effective dietary supplementation to restrain the neurodegenerative processes of AD. Peony seed oil suppressed microglial activation and neuroinflammation through the downregulation of pro‐inflammatory mediators in the prefrontal cortex and hippocampus of PS cDKO mice, and lessened memory impairment by reversing hyperphosphorylated tau and synaptic proteins deficits.

In this letter, a low-complexity receiver (Rx) is proposed for hybrid asymmetrically clipped optical orthogonal frequency division multiplexing (HACO-OFDM). Owing to the special time-domain property of HACO-OFDM, overlaid asymmetrically clipped OFDM (ACO-OFDM) and pulse-amplitude-modulated discrete multitoned (PAM-DMT) signals can be distinguished in the time domain to reduce its computational complexity. Besides, the near-optimal optical power allocation is further applied to optimize the proposed system performance. Theoretical analysis and simulation results demonstrate that, the proposed Rx can achieve nearly the same bit error rate (BER) performance as the BER-optimal iterative Rx but with an effective complexity reduction, thus demonstrating its application potential in high-speed optical communication systems.

Silicon-based complementary metal–oxide–semiconductor (CMOS) has been the mainstream logic style for modern digital integrated circuits (ICs) for decades but will meet its performance limits soon. Extensive investigations have thus been carried out using other semiconductors, especially those with extremely high carrier mobility. However, these materials usually have small or even zero band gap, which leads inevitably to large leakage current or voltage loss in ICs based on these semiconductors. In this work, we propose and demonstrate a strengthened CMOS (SCMOS) logic style using modified field-effect transistors (FETs) to solve this problem, that is, to achieve high performance, utilizing the high carrier mobility in these materials, and to reduce the current leakage resulting from their small band gap. Conventional CMOS FETs are modified to have an asymmetric structure where an additional assistant gate is introduced near the drain to further lower the potential barrier in on-state and to increase the barrier in off-state. SCMOS ICs are constructed using these modified asymmetric CMOS FETs, which demonstrate perfect rail-to-rail output with negligible voltage loss and 3 orders of magnitude suppression of the static power consumption and an operating speed similar to or even higher than that of CMOS ICs. Here, SCMOS is demonstrated using carbon nanotubes, but, in principle, this logic style can be used in ICs based on any small-band-gap semiconductors to provide simultaneously high performance and low power consumption.

Carbon nanotubes (CNTs) have been considered a preferred channel material for constructing high-performance radio frequency (RF) transistors with outstanding current gain cutoff frequency (fT) and power gain cutoff frequency (fmax) but the highest reported fmaxis only 70 GHz. Here, we explore how good RF transistors based on solution-derived randomly oriented semiconducting CNT films, which are the most mature CNT materials for scalable fabrication of transistors and integrated circuits, can be achieved. Owing to the significantly reduced number of CNT/CNT junctions obtained by scaling the channel length down to below 100 nm, we realized RF field-effect transistors (FETs) with maximum transconductance Gmup to 0.38 mS/μm, which is the record among CNT-based RF FETs. After de-embedding the pad-induced capacitances and resistances, the CNT FETs with different gate lengths (Lg) exhibit fTas high as 103 GHz (intrinsically 281 GHz) or fmaxup to 107 GHz (intrinsically 190 GHz), which are the records among CNT-based RF FETs. In particular, the CNT FETs with an Lgof 50 nm present pad de-embedding fTof 86 GHz and fmaxof 85 GHz, and represent the best CNT RF transistor in terms of comprehensive performance to date. To demonstrate the actual high-speed and scalable fabrication of our CNT RF FETs, we fabricated CNT FET-based five-stage ring oscillators with oscillation frequencies above 5 GHz.

An Et3N-catalyzed cascade [3 + 2]-annulation of β-oxo-acrylamides with cyclic N-sulfonyl ketimines or sulfamate-derived imines is developed under mild reaction conditions, which provides a concise and efficient route to access valuable sultam- or sulfamidate-fused imidazolidinone derivatives in good to excellent yields (80–95% yields) with excellent diastereoselectivities (>20:1 drs). The current protocol features atom economy, a transition-metal-free process, and broad functional group tolerance. Moreover, the asymmetric variant of the [3 + 2]-cycloaddition reaction was achieved in the presence of diphenylethanediamine or quinine-based bifunctional squaramide organocatalysts C-1and C-11, giving the corresponding chiral polycyclic imidazolidinones in 68–90% yields with 25–94% ees and >20:1 drs in all cases.

An efficient access to a large array of diarylmethane thioether derivatives is developed through catalyst‐free 1,6‐conjugate addition of 1,4‐dithiane‐2,5‐diols with para‐quinone methides in high to excellent yields. Moreover, this reaction system is also suitable for other sulfur‐based nucleophiles, and the resulting products can be readily converted into other valuable diarylmethane derivatives. An efficient access to a large arrayof diarylmethane thioether derivatives has been developed through catalyst‐free 1,6‐conjugate addition of 1,4‐dithiane‐2,5‐diols with para‐quinone methides in high to excellent yields.

• An asymmetric Laplacian pyramid structure is proposed in which different size features are processed by different network architectures. • The improved dense skip connections and recursive operations are combined to form a deep dense recursive convolutional neural network to properly integrate low-level features and high-level features while expanding the network' s receptive field. • A low-high-medium strategy is adopted to design the number of channels for the convolutional layer of each layer of the pyramid. • Visual assessment and quantitative analysis prove that the proposed network is superior to other classical methods. Large-scale factor image super-resolution whose scale factor is greater than 4 is significant in real-world applications for single image super-resolution. The current image super-resolution techniques for large-scale factor, however, frequently upsample low-resolution images in a single pass, leading to edge artifacts in the reconstructed images. In this article, we provide an improved asymmetric Laplacian pyramid network to further realize large-scale factor image super-resolution and fully utilize various size features. A distinct architecture is applied at each layer of the pyramid for improving feature extraction. We extend the first layer of the pyramid with a lightweight transformer design, which enables the model to efficiently collect the contextual information in the sequence by utilizing the multi-headed attention mechanism. Additionally, we combine improved dense skip connections with recursive operations to form a deep dense recursive convolutional neural network that fuses low-level and high-level features while broadening the network's receptive field. The quantitative and qualitative analysis on benchmark dataset's demonstrate that our method provides superior performance in both PSNR and SSIM and is more in line with human visual perception. [ABSTRACT FROM AUTHOR]