Study on tax burden calculation and risk allocation for industries in free trade zones

The existence of tax burden outlier of industries will hinder the sustainable development of the regional economy. By calculating the tax burden of 3,585 enterprises in 11 industries in China (Zhejiang) Pilot Free Trade Zone, we find that there are six industries with abnormal tax burden, namely, the construction industry, transportation, the warehousing and postal industry, information transmission, software and the information technology service industry, the financial industry, the real estate industry, and the leasing and business service industry. Based on the semi-parametric time-varying model, we changed the time variable into the industry variable, and studied the mutual influence of the tax burden of each industry under the control variables of actual tax burden and employment number respectively and jointly driven. Considering the control variable as the formulation of tax policy, we can calculate the interaction and fluctuation range of each industry tax burden under different tax policies. According to this result, the tax burden risk of six industries with tax burden outlier is allocated

Ketones Improves Apolipoprotein E4-Related Memory Deficiency Via Sirtuin 3

Background: Apolipoprotein E4 (ApoE4) is the major genetic risk factor of Alzheimer\u27s disease (AD). ApoE4 carriers have cerebral hypometabolism which is thought as a harbinger of AD. Our previous studies indicated ketones improved mitochondria energy metabolism via sirtuin 3 (Sirt3). However, it is unclear whether ketones upregulate Sirt3 and improve ApoE4-related learning and memory deficits. Results: Ketones improved learning and memory abilities of ApoE4 mice but not ApoE3 mice. Sirt3, synaptic proteins, the NAD+/ NADH ratio, and ATP production were significantly increased in the hippocampus and the cortex from ketone treatment. Methods: Human ApoE3 and ApoE4 transgenic mice (9-month-old) were treated with either ketones or normal saline by daily subcutaneous injections for 3 months (ketones, beta-hydroxybutyrate (BHB): 600 mg/kg/day; acetoacetate (ACA): 150 mg/kg/day). Learning and memory ability of these mice were assessed. Sirt3 protein, synaptic proteins (PSD95, Synaptophysin), the NAD+/ NADH ratio, and ATP levels were measured in the hippocampus and the cortex. Conclusion: Our current studies suggest that ketones improve learning and memory abilities of ApoE4 transgenic mice. Sirt3 may mediate the neuroprotection of ketones by increasing neuronal energy metabolism in ApoE4 transgenic mice. This provides the foundation for Sirt3\u27s potential role in the prevention and treatment of AD

Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?

Accurately monitoring global vegetation dynamics with modern remote sensing is critical for understanding the functions and processes of the biosphere and its interactions with the planetary climate. The MODerate resolution Imaging Spectroradiometer (MODIS) vegetation index (VI) product has been a primary data source for this purpose. To date, the MODIS team had released several versions of VI products that have widely used in global change studies and practical applications. In this study, we re-examined the global vegetation activity by comparing the recent MODIS Collection 6 (C6) VIs with Collection 5 (C5) VIs including Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from Terra (2001â2015) and Aqua Satellites (2003â2015). We found substantial differences in global vegetation trends betweenTerra-C5 and -C6 VIs, especially EVI. From 2001 to 2015, global vegetation showed a remarkable greening trend in annual EVI from the Terra-C6 (0.28% yearâ1; P<0.001), in contrast to the decreasing EVI trend from the Terra-C5 (â0.14% yearâ1, P<0.01). Spatially, large portions of the browning areas in tropical regions identified by Terra-C5 VIs were not evident in Terra-C6 VIs. In contrast, the widespread greening areas in Terra-C6 VIs were consistent with Aqua-C6 VIs and GIMMS3g NDVI. Our finding of a greening Earth supports the recent studies suggesting an enhanced land carbon sink. Our study suggests that most of the vegeta

Diagnostic accuracy of tumor necrosis factor-alpha, interferon-gamma, interlukine-10 and adenosine deaminase 2 in differential diagnosis between tuberculous pleural effusion and malignant pleural effusion

BACKGROUND: The current study was performed to investigate the potential biomarkers for the differential diagnosis of tuberculous pleural effusion (TPE) and malignant pleural effusions (MPE). METHODS: Among ninety patients (n = 90) involved in the study, 47 with tuberculous pleural effusion aged from 18 to 70 and 43 with secondary malignant pleural effusion aged from 34 to 78. We tested the pleural levels of TNF-α, IFN-γ and IL-10 as well as the enzyme activity of ADA(2), and then we compared the differential diagnostic efficiencies of those biochemical parameters with ADA between the two groups. RESULTS: Our results show that, the concentrations of pleural TNF-α (45.55 ± 15.85 ng/L), IFN-γ (114.97 ± 27.85 ng/L) as well as activities of ADA(2) (35.71 ± 10.00 U/L) and ADA (39.39 ± 10.60 U/L) in tuberculous group were significantly higher compared to malignant group. Furthermore, according to the ROC curve analysis the thresholds of TNF-α, IFN-γ, ADA(2) and ADA were found to be 30.3 ng/L, 103.65 ng/L, 29.45 U/L, and 39.00 U/L, respectively. TNF-α, IFN-γ and ADA(2) yielded better sensitivity, specificity, and accuracy of the diagnosis than ADA. Our investigation further revealed that the combinations of TNF-α and ADA(2) further increased the specificity and accuracy for the differential diagnosis. CONCLUSION: In conclusion, we found that TNF-α, IFN-γ, ADA and ADA(2) all increased in TPE. Combinations of the TNF-α and ADA(2) yielded the best specificity and accuracy for the differential diagnosis of TPE from MPE. Our investigation suggests that the applications of TNF-α together with ADA(2) may contribute to more efficient diagnosis strategies in the management of discrimination between tuberculous and malignant pleural effusions

Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN

Generative Adversarial Networks (GAN) have many potential medical imaging applications, including data augmentation, domain adaptation, and model explanation. Due to the limited embedded memory of Graphical Processing Units (GPUs), most current 3D GAN models are trained on low-resolution medical images. In this work, we propose a novel end-to-end GAN architecture that can generate high-resolution 3D images. We achieve this goal by separating training and inference. During training, we adopt a hierarchical structure that simultaneously generates a low-resolution version of the image and a randomly selected sub-volume of the high-resolution image. The hierarchical design has two advantages: First, the memory demand for training on high-resolution images is amortized among subvolumes. Furthermore, anchoring the high-resolution subvolumes to a single low-resolution image ensures anatomical consistency between subvolumes. During inference, our model can directly generate full high-resolution images. We also incorporate an encoder with a similar hierarchical structure into the model to extract features from the images. Experiments on 3D thorax CT and brain MRI demonstrate that our approach outperforms state of the art in image generation and clinical-relevant feature extraction.Comment: 12 pages, 9 figures. Under revie

Weight-based Channel-model Matrix Framework provides a reasonable solution for EEG-based cross-dataset emotion recognition

Cross-dataset emotion recognition as an extremely challenging task in the field of EEG-based affective computing is influenced by many factors, which makes the universal models yield unsatisfactory results. Facing the situation that lacks EEG information decoding research, we first analyzed the impact of different EEG information(individual, session, emotion and trial) for emotion recognition by sample space visualization, sample aggregation phenomena quantification, and energy pattern analysis on five public datasets. Based on these phenomena and patterns, we provided the processing methods and interpretable work of various EEG differences. Through the analysis of emotional feature distribution patterns, the Individual Emotional Feature Distribution Difference(IEFDD) was found, which was also considered as the main factor of the stability for emotion recognition. After analyzing the limitations of traditional modeling approach suffering from IEFDD, the Weight-based Channel-model Matrix Framework(WCMF) was proposed. To reasonably characterize emotional feature distribution patterns, four weight extraction methods were designed, and the optimal was the correction T-test(CT) weight extraction method. Finally, the performance of WCMF was validated on cross-dataset tasks in two kinds of experiments that simulated different practical scenarios, and the results showed that WCMF had more stable and better emotion recognition ability.Comment: 18 pages, 12 figures, 8 table

Sirtuin 3 Attenuates Amyloid-Beta Induced Neuronal Hypometabolism

Alzheimer\u27s disease (AD) is manifested by regional cerebral hypometabolism. Sirtuin 3 (Sirt3) is localized in mitochondria and regulates cellular metabolism, but the role of Sirt3 in AD-related hypometabolism remains elusive. We used expression profiling and weighted gene co-expression network analysis (WGCNA) to analyze cortical neurons from a transgenic mouse model of AD (APPSwInd). Based on WGCNA results, we measured NAD+ level, NAD+/ NADH ratio, Sirt3 protein level and its deacetylation activity, and ATP production across both in vivo and in vitro models. To investigate the effect of Sirt3 on amyloid-β (Aβ)-induced mitochondria damage, we knocked down and over-expressed Sirt3 in hippocampal cells. WGCNA revealed Sirt3 as a key player in Aβ-related hypometabolism. In APP mice, the NAD+ level, NAD+/ NADH ratio, Sirt3 protein level and activity, and ATP production were all reduced compared to the control. As a result, learning and memory performance were impaired in 9-month-old APP mice compared to wild type controls. Using hippocampal HT22 cells model, Sirt3 overexpression increased Sirt3 deacetylation activity, rescued mitochondria function, and salvaged ATP production, which were damaged by Aβ. Sirt3 plays an important role in regulating Aβ-induced cerebral hypometabolism. This study suggests a potential direction for AD therapy