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Temperature compensation is the main measure to solve the problem that the detection accuracy of non-dispersive infrared CO2 gas sensor is affected by temperature. As the measurement accuracy of the non-dispersive infrared CO2 gas sensor is easily affected by the ambient temperature, this article analyzes the reasons why the sensor is affected by temperature, and proposes a temperature compensation method that integrates the Whale Algorithm (WOA) and BP neural network. The whale algorithm is used to optimize the weights and thresholds of the BP neural network to build a temperature compensation model for the non-dispersive infrared CO2 gas sensor and compare the superiority with the traditional BP neural network model and particle swarm optimization (PSO) BP neural network model. The experimental results show that the temperature compensation model error of WOA-BP algorithm is lower than 30 ppm, and the average absolute error percentage is 3.86%, which is far better than BP neural network and PSO-BP neural network, and effectively reduces the influence of temperature on the accuracy of the sensor. [ABSTRACT FROM AUTHOR]

Background18F-Flutemetamol (18F-FMM) PET/CT imaging has been widely applied to the diagnosis of mild cognitive impairment and Alzheimer's disease.PurposeThis study aims to explore the distributions of 18F-FMM in different brain regions of mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients and the factors that may affect the combination of 18F-FMM, evaluating the use of 18F-FMM PET/CT imaging in the diagnosis of MCI and AD patients.MethodsFrom July 2020 to April 2021, 24 subjects with MCI (12 males, 12 females, aged of (70.54±9.27) years old), 25 subjects with AD (11 males, 14 females, aged (70.56±7.30) years old) and 9 subjects as normal controls (NC, 2 males, 7 females, aged (57.67±9.00) years old) were recruited from Shanghai. The 18F-FMM PET/CT brain imaging of all subjects were qualitatively and semi-quantitatively analyzed by visual evaluation and standardized uptake value ratio (SUVR), respectively. Student's t-test, one-way analysis of variance and rank sum test were used for the comparison of quantitative variables. Pearson's chi-squared test and Fisher's exact test were used for the comparison of qualitative variables. The diagnostic efficiency was obtained by ROC curve. Multiple linear regression analysis was used to analyze the factors that might affect the combination of 18F-FMM.ResultsThe positive rate of visual assessment was significantly different in NC, MCI and AD groups (χ2=26.85, p < 0.001), and significant differences existed statistically in SUVR of all brain regions among the three groups (H value: 11.54~19.34, F value: 7.43, 11.48, all p < 0.01). The mean values of SUVR in the whole brain of the three groups were statistically different (Z value: -3.87, -2.79, -2.45, all p < 0.016 7). Compared with MCI group, the positive rate in occipital lobe, temporal lobe, parietal lobe and posterior cingulate gyrus was statistically significant (χ2=7.53~10.89, all p < 0.01). With respect to NC, SUVR of all brain regions was lower than that in AD, while SUVR of temporal lobe, frontal lobe and precuneu were lower than that in MCI. Meanwhile, SUVR of occipital lobe, temporal lobe, frontal lobe and parietal lobe in MCI were lower than that in AD. Receiver operating characteristic (ROC) curves showed that the SUVR value of temporal lobe and the mean value of SUVR in the whole brain had the ability to distinguish NC, MCI and AD in sequence. Multiple linear regression analysis showed that cognitive level was significantly negatively correlated with 18F-FMM SUVR in different brain regions.Conclusion18F-FMM PET/CT brain imaging could reflect the cognitive level of middle-aged and elderly people intuitively and has clear diagnostic value for MCI and AD.

BackgroundSubjective cognitive decline (SCD) and mild cognitive impairment (MCI) are a transitional state between normal aging and mild dementia, and most of them have potential Alzheimer's Disease (AD) pathology. Studying the pathophysiological characteristics of SCD and MCI is helpful to the early diagnosis of AD.PurposeThis study aims to investigate the brain perfusion differences among SCD, MCI and AD, and to evaluate the application value of brain perfusion SPECT/CT imaging combined with NeuroGamTM software in these diseases.MethodsFrom July 2020 to April 2021, 15 patients with SCD, 29 patients with MCI and 36 patients with AD were collected from several general hospitals in Shanghai. All subjects underwent neuropsychological test and 99mTc-ECD brain perfusion SPECT/CT imaging. The perfusion levels of Brodmann areas (BA) in the three groups were semi-quantitatively analyzed by NeuroGamTM, and compared with normal database. Student's t-test, one-way analysis of variance and rank sum test were used for the comparison of quantitative variables. Pearson's chi-squared test was used for the comparison of qualitative variables.ResultsThere is no significant difference in BA 4~11, 17~25, 28, 31~32, 36~40 and 44~47 between SCD group and MCI group. The mean perfusion values of BA 8-right(R), 20-left(L), 21R, 23L, 23R, 24L, 31L, 38L, 38R and 45R in SCD group are significantly higher than those in AD group (p

Byline: Juan. Yang, Xiaohui. Zhao, Haijing. Sui, Xueyuan. Liu Background: The prevalence of mild cognitive impairment (MCI), herein China, was without involving the suburban communities, where the awareness of MCI [...]

Aiming at the problem of wind curtailment caused by the lack of system flexibility, an optimal scheduling strategy for improving the flexibility of the electricity-gas- heat interconnection system by the coordinated operation of the gas network management and storage characteristics and the heat storage characteristics of the heat network is proposed. Firstly, the influence of gas network storage and heat network storage on improving flexibility is analyzed respectively. Then, an electricity-gas-heat interconnected system scheduling model considering the dynamic characteristics of gas network management and t the delay characteristics of heat storage in heat network, which greatly improves the imbalance between supply and demand of flexibility in space and time brought by the anti-peak regulation characteristics of wind power to the system. Finally, the IEEE-24 nodes power system, Belgium's 20-node natural gas network and 6- node thermal network are used, for example, analysis. The results show that the proposed scheduling scheme improves the flexibility of the system while its operating cost and wind curtailment cost are the lowest, which promotes the consumption of wind power. [ABSTRACT FROM AUTHOR]

The main reducer is the main component of the whole vehicle, and its main function is to realize deceleration and torque increase. For Baha racing car, in order to improve the dynamic performance of the whole car, the main reducer is designed from the aspects of layout, transmission ratio distribution, shift mode, overall size and shell structure. Calculate the transmission ratio range of reducer according to the performance parameters of transmission parts, and verify the rationality of transmission ratio; Then determine the parameters of gear according to the transmission ratio and related parameters, and finally design the parameters of gear according to the transmission ratio and related parameters, and finally design the parameters of other parts of reducer. Based on the determined parameters, 3D modeling software UG is used to build 3D models of various parts of the reducer, and finite element analysis software ANSYS is used to simulate and analyze the parts to check whether the comprehensive mechanical properties meet the requirements. In this paper, the design of the main reducer realizes the comprehensive design of small size, light weight, reasonable transmission ratio distribution, high reliability, shifting gears during driving, and the comprehensive mechanical properties also meet the requirements.