The Study of Owl's Silent Flight and Noise Reduction on Fan Vane with Bionic Structure

In light of the bionics engineering point of view, we use the biological non-smooth surface in the surface design of the fan blade in order to reduce the fan noise and improve air flow and efficiency .We design several kinds of Sawtooth-shaped distribution, and apply the non-smooth form on the fan model. We analyzed the acoustic performance of various non-smooth fan blades that was reflected when the fan was rotating. Through the wind tunnel test, we obtained the spectrum map, wind comparison chart, efficiency curve and other important parameters that came from the comparison between smooth and non-smooth models and the noise of the fan. This paper will reveal that the non-smooth shape practically is good for preventing formation of off-body vortex, which is caused by turbulent boundary layer on the vane surface, and it will have reference significance for exploring the mechanism of noise reduction on fan vane. Key words: Owl; Bionic; Noise Reduction; Optimization Tes

A Peptide That Binds Specifically to the β-Amyloid of Alzheimer's Disease: Selection and Assessment of Anti-β-Amyloid Neurotoxic Effects

The accumulation of the amyloid-β peptide (Aβ) into amyloid plaques, an essential event in Alzheimer's disease (AD) pathogenesis, has caused researchers to seek compounds that physiologically bind Aβ and modulate its aggregation and neurotoxicity. In order to develop new Aβ-specific peptides for AD, a randomized 12-mer peptide library with Aβ1-10 as the target was used to identify peptides in the present study. After three rounds of selection, specific phages were screened, and their binding affinities to Aβ1-10 were found to be highly specific. Finally, a special peptide was synthesized according to the sequences of the selected phages. In addition, the effects of the special peptide on Aβ aggregation and Aβ-mediated neurotoxicity in vitro and in vivo were assessed. The results show that the special peptide not only inhibited the aggregation of Aβ into plaques, but it also alleviated Aβ-induced PC12 cell viability and apoptosis at appropriate concentrations as assessed by the cell counting kit-8 assay and propidium iodide staining. Moreover, the special peptide exhibited a protective effect against Aβ-induced learning and memory deficits in rats, as determined by the Morris water maze task. In conclusion, we selected a peptide that specifically binds Aβ1-10 and can modulate Aβ aggregation and Aβ-induced neuronal damage. This opens up possibilities for the development of a novel therapeutic approach for the treatment of AD

A parameter optimization method for stress simulation of double horse head pumping unit dynamics model with cable

Some components in Double horse head (DHH) pumping unit may occur cracking failure due to high cycle alternating stress, and this makes the research on dynamic stress simulation for them more interesting topic in its maintenance operation. This paper aims to improve the accuracy of dynamic stress simulation model through a parameter optimization method for the cable joints in DHH pumping unit. A series of cylinders was employed to model the steel cable, and the back horse head was also transformed to flexible body, then a rigid-flexible multibody dynamics model with cable was constructed to simulate the dynamic stress of components in DHH pumping unit. Stiffness and damping coefficient in cable joints have a significant effect on the model performance, and an unreasonable value may cause a strong vibrational and undesirable model response, therefore, a Memetic Algorithms based method was proposed to optimize them for improving the simulation accuracy using tested stress as objective function. Results show that the dynamic stress simulated from improved model is much closer to the experimental test compared with the original model, and these optimized parameters are also valid for the model in other working condition

An improved local mean decomposition method and its application for fault diagnosis of reciprocating compressor

Local mean decomposition (LMD) is a new time–frequency analysis method which can decompose a signal adaptively into a set of product function (PF) components, and the construction of local mean function and envelope function plays an important role in the accuracy of its PF components. Aiming at the strong nonstationarity, nonlinearity and multi-component coupling characteristics of reciprocating compressor vibration signals, an improved LMD was proposed by a novel construction method of local mean function and envelope function. By introducing an extreme symmetrical point between two extreme points and using the Monotone Piecewise Cubic Hermite Interpolation (MPCHI) instead of Cubic Spline Interpolation (CSI) to construct the envelopes, a novel construction method of local mean function and envelope function was proposed, and then the improved LMD algorithm was given based on this novel construction method. The improved LMD was applied to decompose the vibration signals of reciprocating compressor fault states, and the comparison of details between different LMD decomposition results verified the superiority of this improved method. The envelope frequency spectrum of PF component gives a more significant peak of fault frequency than that of original signal, which further indicates that this proposed method is competent for the diagnosis of reciprocating compressor oversized bearing clearance fault

CPSAA: Accelerating Sparse Attention using Crossbar-based Processing-In-Memory Architecture

The attention mechanism requires huge computational efforts to process unnecessary calculations, significantly limiting the system's performance. Researchers propose sparse attention to convert some DDMM operations to SDDMM and SpMM operations. However, current sparse attention solutions introduce massive off-chip random memory access. We propose CPSAA, a novel crossbar-based PIM-featured sparse attention accelerator. First, we present a novel attention calculation mode. Second, we design a novel PIM-based sparsity pruning architecture. Finally, we present novel crossbar-based methods. Experimental results show that CPSAA has an average of 89.6X, 32.2X, 17.8X, 3.39X, and 3.84X performance improvement and 755.6X, 55.3X, 21.3X, 5.7X, and 4.9X energy-saving when compare with GPU, FPGA, SANGER, ReBERT, and ReTransformer.Comment: 14 pages, 19 figure

Impaired Spatial Learning and Memory is Linked to Neurochemical Indicators of Brain Aging in the Middle-Aged CD-1 Mice with Maternal Exposure to LPS

Aim: Prenatal exposure to a disadvantageous circumstance may produce accelerated brain aging. Previously, our middle-aged model of CD-1 mice with maternal exposure to low-dose lipopolysaccharide (LPS) showed accelerated memory aging at a behavioral level. Here we investigated whether there was a corresponding pathophysiological alteration in the brain.Materials and Methods: The mothers in the LPS group were administered a low dose (i.p. 50μg/kg) of LPS daily for 3 days during late gestation to simulate an inflammatory condition in maternal infection.Results: The treatment accelerated the age-related decline of spatial learning and memory in the Morris water maze in the middle-aged offspring. Compared to control mice (n = 12), these mice (n = 12) exhibited elevated malondialdehyde contents (P = 0.042), decreased activities of superoxide dismutase (P < 0.001) and glutathione peroxidase (P = 0.010) in the brain, and elevated levels of amyloid beta (Ps < 0.005) and synaptotagmin-1 (Ps < 0.037) in several hippocampal layers. These age-related indicators correlated with a decline in spatial learning and memory (Ps < 0.05).Conclusions: During gestation, maternal illness in mice might be an initiator of accelerated brain aging in offspring, as indicated by behavioral-cognitive and neurochemical measures