Numerical simulation for machining S-tube by abrasive flow with various particle volume fractions

Abrasive flow machining has become an economical and efficient ultra-precision process for machining complex-shaped pipe parts, and processing effect is exceedingly subject to particle volume fraction. In this paper, aiming at uncovering the influence of various particle volume fractions on the machining result of abrasive flow finishing, based on fluid mechanics theory, mixed phase model and discrete phase model were conducted, FLUENT software was resorted to simulate the numerical characteristics of the solid-liquid two-phase flow field in the inner channel of S-tube with different-particle-volume-fraction abrasive flows, the mechanism of erosion and wear of particles was uncovered, which provides a theoretical basis for abrasive flow machining S-tube structured components

Effect of Acorus tatarinowii extract on hyperprolactinemia in rats

Purpose: To determine the mechanism underlying the anti-hyperprolactinemia effect of Acorus tatarinowii extract (ATE) in rats. Methods: Rats were divided into six groups (n =10 each group), viz, healthy control, untreated hyperprolactinemic rats, hyperprolactinemic rats treated with bromocriptine (0.6 mg/kg), and hyperprolactinemic rats treated with ATE (3.2, 6.4, or 12.8 g/kg). After 30 days, the hypothalamic protein levels of dopamine D2 receptor, protein kinase A (PKA), and cyclic adenosine monophosphate (cAMP) were determined. Results: Dopamine D2 receptor levels were lower in untreated hyperprolactinemic rats than in healthy control (p < 0.01), but this decrease was attenuated by ATE (p < 0.05). Elevated PKA levels in untreated hyperprolactinemic rats (0.78 ± 0.03µg/mL, p < 0.01) were decreased by ATE (3.2 g/kg, 0.51 ± 0.02 µg/mL, p < 0.05; 6.4 g/kg, 0.39 ± 0.03 µg/mL, p < 0.01; 12.8 g/kg, 0.24 ± 0.04 µg/mL, p < 0.01). Similarly, elevated cAMP levels in hyperprolactinemic rats (3.1 ± 0.3 ng/mL) were lowered by ATE (3.2 g/kg, 2.2 ± 0.4 ng/mL, p < 0.05; 6.4 g/kg, 1.8 ± 0.3 ng/mL, p < 0.01; 12.8 g/kg, 1.4 ± 0.3 ng/mL, p < 0.01). Conclusion: ATE anti-hyperprolactinemia activity is mediated by dopamine D2 receptor signaling via cAMP/PKA pathway

The influence of local officials' promotion incentives on carbon emission in Yangtze River Delta, China

China's carbon emissions is heavily influenced by economic growth, which can be largely related to the local officials' promotion incentives. The current study was conducted to test the hypothesis that the influence of local officials' individual characteristics on carbon emissions was driven by the promotion incentives. Yangtze River Delta where carbon emissions accounted for around 13.95% of China's total emissions was selected as the research area. The multiple linear regression model was applied to determine the relationship between local officials' characteristics and total carbon emissions and carbon emissions from different sectors. The results indicated that local officials' promotion source, tenure and age significantly influenced the total carbon emission. Despite insignificance influence of officials' academic level on carbon emissions, the professional background in economics and management had a significant influence on carbon reduction. Our results indicated the importance of local officials' promotion incentives for carbon emission in China. Therefore, low carbon development should be included as an important part of official promotion system

One Fits All: A Unified Synchrotron Model Explains GRBs with FRED-Shaped Pulses

The analysis of gamma-ray burst (GRB) spectra often relies on empirical models like the Band function, which lacks a distinct physical explanation. Previous attempts to couple physical models with observed data have been confined to individual burst studies, where the model is fitted to segmented spectra with independent physical parameters. These approaches frequently fail to explain the spectral evolution, which should be governed by a consistent set of physical conditions. In this study, we propose a novel approach by incorporating the synchrotron radiation model to provide a self-consistent explanation for a selection of single-pulse GRBs. Our sample is carefully chosen to minimize contamination from overlapping pulses, allowing for a comprehensive test of the synchrotron model under a unified physical condition, such as a single injection event of electrons. By tracing the evolution of cooling electrons in a decaying magnetic field, our model predicts a series of time-dependent observed spectra that align well with the observed data. Remarkably, using a single set of physical parameters, our model successfully fits all time-resolved spectra within each burst. Additionally, our model accurately predicts the evolution of some key features of GRBs such as the spectral peak $E_{\rm p}$ and light curve shapes, all of which are consistent with observations. Our findings strongly support the notion that the spectral and temporal evolution in GRB pulses originates from the expansion of the GRB emission region with an initial radius of approximately $10^{15}$ cm, with synchrotron radiation being the underlying emission mechanism.Comment: 25 pages, 18 figures, 4 table

13-Ethoxy­carbonyl-16-(1-methyl­ethyl)-17,19-dinoratis-15-ene-4,14-dicarboxylic acid monohydrate: a new derivative of maleopimaric acid

The title compound, C26H38O6·H2O, is a mono-ester of a derivative of maleopimaric acid, an abietic-type acid. The two fused and unbridged cyclo­hexane rings adopt approximate chair conformations while the three other three six-membered rings have boat conformations

Towards the AlexNet Moment for Homomorphic Encryption: HCNN, theFirst Homomorphic CNN on Encrypted Data with GPUs

Deep Learning as a Service (DLaaS) stands as a promising solution for cloud-based inference applications. In this setting, the cloud has a pre-learned model whereas the user has samples on which she wants to run the model. The biggest concern with DLaaS is user privacy if the input samples are sensitive data. We provide here an efficient privacy-preserving system by employing high-end technologies such as Fully Homomorphic Encryption (FHE), Convolutional Neural Networks (CNNs) and Graphics Processing Units (GPUs). FHE, with its widely-known feature of computing on encrypted data, empowers a wide range of privacy-concerned applications. This comes at high cost as it requires enormous computing power. In this paper, we show how to accelerate the performance of running CNNs on encrypted data with GPUs. We evaluated two CNNs to classify homomorphically the MNIST and CIFAR-10 datasets. Our solution achieved a sufficient security level (> 80 bit) and reasonable classification accuracy (99%) and (77.55%) for MNIST and CIFAR-10, respectively. In terms of latency, we could classify an image in 5.16 seconds and 304.43 seconds for MNIST and CIFAR-10, respectively. Our system can also classify a batch of images (> 8,000) without extra overhead

Opportunities and challenges for Chinese elderly care industry in smart environment based on occupants' needs and preferences

New developments in intelligent devices for assisting elderly people can provide elders with friendly, mutual, and personalized interactions. Since the intelligent devices should continually make an important contribution to the smart elderly care industry, smart services or policies for the elders are recently provided by a large number of government programs in China. At present, the smart elderly care industry in China has attracted numerous investors’ attention, but the smart elderly care industry in China is still at the beginning stage. Though there are great opportunities in the market, many challenges and limitations still need to be solved. This study analyzes 198 news reports about opportunities and challenges in the smart elderly care industry from six major Chinese portals. The analysis is mainly based on needs assessment for elderly people, service providers, and the Chinese government. It is concluded that smart elderly care services satisfy the elders’ mental wants and that needs for improving modernization services are the most frequently mentioned opportunities. Also, the frequently mentioned challenges behind opportunities are intelligent products not being able to solve the just-needed, user-consumption concept and the ability to pay, which is the most frequently mentioned challenge. The results of this study will enable stakeholders in the smart elderly care industry to clarify the opportunities and challenges faced by smart elderly care services in China’s development process and provide a theoretical basis for better decision making