An Analysis of the Approaches to Building Learning Party Organizations in Colleges and Universities

The Fourth Plenary Session of the Seventeenth Central Committee of the Chinese Communist Party assigned the strategic task of building a learning Marxist Party, which is a major initiative made from the overall perspective of promoting the cause of socialism with Chinese characteristics and of improving the building of Party. So the Party organizations at all levels should make joint efforts to implement the task of building a learning Party from all aspects and in all areas. Higher education plays an overall, fundamental, leading and humanistic role in the socialist construction in China, and the Party building is an important part of the Communist Party of China itself. In this sense, it is particularly important to promote the building of learning Party organizations in colleges and universities so as to build a comprehensive learning Party. And the writer is firmly convinced that it is of great significance to actively explore the approaches to building learning Party organizations in colleges and universities.

Towards Target-Driven Visual Navigation in Indoor Scenes via Generative Imitation Learning

We present a target-driven navigation system to improve mapless visual navigation in indoor scenes. Our method takes a multi-view observation of a robot and a target as inputs at each time step to provide a sequence of actions that move the robot to the target without relying on odometry or GPS at runtime. The system is learned by optimizing a combinational objective encompassing three key designs. First, we propose that an agent conceives the next observation before making an action decision. This is achieved by learning a variational generative module from expert demonstrations. We then propose predicting static collision in advance, as an auxiliary task to improve safety during navigation. Moreover, to alleviate the training data imbalance problem of termination action prediction, we also introduce a target checking module to differentiate from augmenting navigation policy with a termination action. The three proposed designs all contribute to the improved training data efficiency, static collision avoidance, and navigation generalization performance, resulting in a novel target-driven mapless navigation system. Through experiments on a TurtleBot, we provide evidence that our model can be integrated into a robotic system and navigate in the real world. Videos and models can be found in the supplementary material.Comment: 11 pages, accepted by IEEE Robotics and Automation Letter

Mixed-Signal Parallel Compressive Spectrum Sensing for Cognitive Radios

Wideband spectrum sensing for cognitive radios requires very demanding analog-to-digital conversion (ADC) speed and dynamic range. In this paper, a mixed-signal parallel compressive sensing architecture is developed to realize wideband spectrum sensing for cognitive radios at sub-Nqyuist rates by exploiting the sparsity in current frequency usage. Overlapping windowed integrators are used for analog basis expansion, that provides flexible filter nulls for clock leakage spur rejection. A low-speed experimental system, built with off-the-shelf components, is presented. The impact of circuit nonidealities is considered in detail, providing insight for a future integrated circuit implementation

Construction of Trusted Routing Based on Trust Computation

In the field of applied IoT, a large number of wireless sensor devices are tasked with data production and collection, providing IoT subjects with a large amount of basic data to support top-level IoT applications. However, there is a considerable risk of being attacked on such sensor networks that are organized in a wireless form. These relatively independent network devices have extremely limited performance and lifetime, a problem that can be supplemented in a centralized network with base stations by relying on the performance of the core nodes of the network, but in a decentralized self-organizing network, they can have a serious adverse impact on the implementation of security solutions. Considering the fundamental nature of the data generated by such end devices in IoT application services, the protection of their security is also directly related to the quality of upper layer services provided. The main research result of this paper is the design of a trust routing scheme for self-organizing networks. The scheme is based on a comprehensive evaluation of data transmission rate, transmission delay, and other factors related to the operation status of the self-organized network and improves the efficiency of the overall work of the self-organized network by reducing the performance consumption of individual nodes of the self-organized network and balancing the network load

Sodium Butyrate Protects N2a Cells against Aβ Toxicity In Vitro

Alzheimer’s disease (AD) is a common neurodegenerative disease. Aβ plays an important role in the pathogenesis of AD. Sodium butyrate (NaB) is a short-chain fatty acid salt that exerts neuroprotective effects such as anti-inflammatory, antioxidant, antiapoptotic, and cognitive improvement in central nervous system diseases. The aim of this study is to research the protective effects of NaB on neurons against Aβ toxicity and to uncover the underlying mechanisms. The results showed that 2 mM NaB had a significant improvement effect on Aβ-induced N2a cell injury, by increasing cell viability and reducing ROS to reduce injury. In addition, by acting on the GPR109A receptor, NaB regulates the expression of AD-related genes such as APP, NEP, and BDNF. Therefore, NaB protects N2a cells from Aβ-induced cell damage through activating GPR109A, which provides an innovative idea for the treatment of AD

The heterogeneity of mesenchymal stem cells: an important issue to be addressed in cell therapy

Abstract With the continuous improvement of human technology, the medical field has gradually moved from molecular therapy to cellular therapy. As a safe and effective therapeutic tool, cell therapy has successfully created a research boom in the modern medical field. Mesenchymal stem cells (MSCs) are derived from early mesoderm and have high self-renewal and multidirectional differentiation ability, and have become one of the important cores of cell therapy research by virtue of their immunomodulatory and tissue repair capabilities. In recent years, the application of MSCs in various diseases has received widespread attention, but there are still various problems in the treatment of MSCs, among which the heterogeneity of MSCs may be one of the causes of the problem. In this paper, we review the correlation of MSCs heterogeneity to provide a basis for further reduction of MSCs heterogeneity and standardization of MSCs and hope to provide a reference for cell therapy

The Lancet Countdown on PM2·5 pollution-related health impacts of China's projected carbon dioxide mitigation in the electric power generation sector under the Paris Agreement: a modelling study

Summary: Background: Except for comparing the implementation costs of the Paris Agreement with potential health benefits at the national levels, previous studies have not explored the health impacts of the nationally determined contributions (NDCs) by countries and in regional details. In this Lancet Countdown study, we aimed to estimate and monetise the health benefits of China's NDCs in the electric power generation sector, and then compare them with the implementation costs, both at the national and regional levels. Methods: In this modelling study, we linked the Multi-regional model for Energy Supply system and their Environmental ImpaCts, the Multi-resolution Emission Inventory for China model, the offline-coupled Weather Research and Forecasting model, the Community Multiscale Air Quality model, and the Integrated Health Impact Assessment model with a time scope from 2010 to 2050. We calculated the PM2·5 concentrations and compared the health impacts and implementation costs between two scenarios that reflect CO2 and air pollutant emissions—the reference (REF) scenario (no climate policy) and the NDC scenario (100% realisation of NDC targets: CO2 emission intensity needs to be about 40% below 2010 emissions by 2030 [roughly 35% below 2030 emissions in REF], and about 90% below 2010 emissions by 2050 [roughly 96% below 2050 emissions in REF]). Findings: Under a comparatively optimistic health benefits valuation condition, at the national level, 18–62% of implementation costs could be covered by the health benefits in 2030. In 2050, the overall health benefits would substantially increase to 3–9 times of the implementation costs. However, northwest China would require the highest implementation costs and will also have more premature deaths because of a more carbon-intensive energy structure than business as usual. By 2030, people in northwest China (especially in Gansu, Shaanxi, and Xinjiang provinces) would need to bear worse air quality, and 10 083 (95% CI 3419–16 138) more premature deaths annually. This undesirable situation would diminish by about 2050. A solution that assumes no growth in air pollutant emissions in 2030 at the regional level is technically feasible, but would not be cost-effective. Interpretation: Our results suggest that cost–benefit analysis of climate policy that omits regional air pollution could greatly underestimate benefits. A compensation mechanism for inter-regional interests (including financial, technological, and knowledge support) should be established for regions that give up their human health benefits for the sake of the whole nation to realise the climate change targets. Funding: National Natural Science Foundation of China and Cyrus Tang Foundation