Enhanced selectivity in the conversion of methanol to 2,2,3-trimethylbutane (triptane) over zinc iodide by added phosphorous or hypophosphorous acid

The yield of triptane from the reaction of methanol with zinc iodide is dramatically increased by addition of phosphorous or hypophosphorous acid, via transfer of hydride from a P–H bond to carbocationic intermediates

Chip-based photonic radar for high-resolution imaging

Radar is the only sensor that can realize target imaging at all time and all weather, which would be a key technical enabler for future intelligent society. Poor resolution and large size are two critical issues for radars to gain ground in civil applications. Conventional electronic radars are difficult to address both issues especially in the relatively low-frequency band. In this work, we propose and experimentally demonstrate, for the first time to the best of our knowledge, a chip-based photonic radar based on silicon photonic platform, which can implement high resolution imaging with very small footprint. Both the wideband signal generator and the de-chirp receiver are integrated on the chip. A broadband photonic imaging radar occupying the full Ku band is experimentally established. A high precision range measurement with a resolution of 2.7 cm and an error of less than 2.75 mm is obtained. Inverse synthetic aperture (ISAR) imaging of multiple targets with complex profiles are also implemented.Comment: 4 pages, 6figure

The Mediatisation of the Chinese Dama in Chinese English-Language Media:A Cognitive Linguistic Approach

The term ‘Chinese dama’ was originally coined by the Wall Street Journal in 2013 to refer to a group of middle-aged and elderly Chinese women who, somewhat frenetically, purchased gold or other items. This study employs a cognitive-linguistic approach to critical discourse analysis to examine how Chinese damas are linguistically mediatised in the Chinese English-language news media. A specialised corpus of 41 news articles with 26661 words, covering the years between 2013 and 2019, was built for this purpose. Informed by Maslow’s ‘hierarchy of needs’ theory, four most recurrent themes of Chinese dama news discourses were identified and coded. The analysis of these discourses suggests that whilst there is divergence in how newspapers construe Chinese damas’ participation in social activities when they are agentive, there is convergence in terms of schematising the conflicts between Chinese damas and the other parties. This seems to fit with the media’s ideological framework, steering ultimately towards the legitimisation of excluding Chinese female seniors from the public realm.</p

Environmental Liabilities and Insolvent Polluters in China: Learning Lessons from the UK and US

Within the context of Enterprises Bankruptcy Law (EBL) in China, this thesis offers an effective means to remedy the issue of how Chinese law ought to ensure that polluters, are held to account for their environmental liabilities. The ‘polluter pays’ principle has been implemented by several pieces of environmental legislation in China, as a means to confront the issue of liability in the case of insolvent polluters. The principle requires those responsible for environmental damage or imminent threats of damage to bear the necessary costs of remediation and prevention. However, in practice, the principle has been rendered relatively ineffective due to current Chinese bankruptcy legislation. Under EBL, an insolvent company externalises its costs associated with its environmental liabilities to society. Firstly, the cost of environmental liability is not specifically mentioned in Chinese EBL and can therefore only be categorised as a general, unsecured liability in the order of distribution during liquidation. Secondly, unsecured liability is difficult to discharge in Chinese bankruptcy cases. This results in environmental liabilities ultimately being borne by the taxpayer, which contradicts with the polluter pays principle. This research references the response of the UK and US to the challenges of environmental liability in insolvency law in order to provide potential solutions for the case of China. The thesis finds that it may be responsible to Chinese law by reducing the externalisation of environmental liability for insolvent polluters and effectively realising the polluter pays principle. It is suggested that this may be achieved by way of EBL reform and the establishment of a financial assurance mechanism

Propensity score regression for causal inference with treatment heterogeneity

Understanding how treatment effects vary on individual characteristics is critical in the contexts of personalized medicine, personalized advertising and policy design. When the characteristics are of practical interest are only a subset of full covariate, non-parametric estimation is often desirable; but few methods are available due to the computational difficult. Existing non-parametric methods such as the inverse probability weighting methods have limitations that hinder their use in many practical settings where the values of propensity scores are close to 0 or 1. We propose the propensity score regression (PSR) that allows the non-parametric estimation of the heterogeneous treatment effects in a wide context. PSR includes two non-parametric regressions in turn, where it first regresses on the propensity scores together with the characteristics of interest, to obtain an intermediate estimate; and then, regress the intermediate estimates on the characteristics of interest only. By including propensity scores as regressors in the non-parametric manner, PSR is capable of substantially easing the computational difficulty while remain (locally) insensitive to any value of propensity scores. We present several appealing properties of PSR, including the consistency and asymptotical normality, and in particular the existence of an explicit variance estimator, from which the analytical behaviour of PSR and its precision can be assessed. Simulation studies indicate that PSR outperform existing methods in varying settings with extreme values of propensity scores. We apply our method to the national 2009 flu survey (NHFS) data to investigate the effects of seasonal influenza vaccination and having paid sick leave across different age groups

Risk Sorting for Enterprise under EC Environments

With the rapid development of internet and emerging of global economic, risk management for enterprise under EC (Electronic Commerce) environments has drawn attentions of many researchers. In this paper, the characteristics of risk for EC enterprise are analyzed. Further, focused on the project organization mode and the uncertain factor of the enterprise under EC, which are main different characteristics from the conventional enterprise, enterprise risk sorting, which is one of the key problems of risk management under EC environments, is studied by using fuzzy ISODATA cluster method based on fuzzy describing of risks. Case study suggests the effectiveness of the method

Synthesis and characterisation of controllably functionalised polyaniline nanofibres

A novel method for functionalising solution based polyaniline (PAni) nanofibres is reported whereby the degree of side-chain attachment can be controllably altered. The covalent attachment of functional side-groups to the surface of PAni nanostructures is achieved by post-polymerisation reflux in the presence of a nucleophile and the functionalised nanomaterial can be purified by simple centrifugation. The technique is therefore easily scalable. We demonstrate that control over the extent of side-chain attachment can be achieved simply by altering the amount of nucleophile added during reflux. We provide evidence that covalently attached carboxlate side-chains influence the doping mechanism of polyaniline and can be used to introduce self-doping behaviour. Acid functionalised nanofibres remain redox active and retain their optical switching capabilities in response to changes in the local chemical environment, thus making them suitable for adaptive sensing applications

Quality assurance plan for China collection 2.0 aerosol datasets

The inversion of atmospheric aerosol optical depth (AOD) using satellite data has always been a challenge topic in atmospheric research. In order to solve the aerosol retrieval problem over bright land surface, the Synergetic Retrieval of Aerosol Properties (SRAP) algorithm has been developed based on the synergetic using of the MODIS data of TERRA and AQUA satellites [1, 2]. In this paper we describe, in details, the quality assessment or quality assurance (QA) plan for AOD products derived using the SRAP algorithm. The pixel-based QA plan is to give a QA flag to every step of the process in the AOD retrieval. The quality assessment procedures include three common aspects: 1) input data resource flags, 2) retrieval processing flags, 3) product quality flags [3]. Besides, all AOD products are assigned a QA ‘confidence’ flag (QAC) that represents the aggregation of all the individual QA flags. This QAC value ranges from 3 to 0, with QA = 3 indicating the retrievals of highest confidence and QA = 2/QA = 1 progressively lower confidence [4], and 0 means ‘bad’ quality. These QA (QAC) flags indicate how the particular retrieval process should be considered. It is also used as a filter for expected quantitative value of the retrieval, or to provide weighting for aggregating/averaging computations [5]. All of the QA flags are stored as a “bit flag” scientific dataset array in which QA flags of each step are stored in particular bit positions

PreConfig: A Pretrained Model for Automating Network Configuration

Manual network configuration automation (NCA) tools face significant challenges in versatility and flexibility due to their reliance on extensive domain expertise and manual design, limiting their adaptability to diverse scenarios and complex application needs. This paper introduces PreConfig, an innovative NCA tool that leverages a pretrained language model for automating network configuration tasks. PreConfig is designed to address the complexity and variety of NCA tasks by framing them as text-to-text transformation problems, thus unifying the tasks of configuration generation, translation, and analysis under a single, versatile model. Our approach overcomes existing tools' limitations by utilizing advances in natural language processing to automatically comprehend and generate network configurations without extensive manual re-engineering. We confront the challenges of integrating domain-specific knowledge into pretrained models and the scarcity of supervision data in the network configuration field. Our solution involves constructing a specialized corpus and further pretraining on network configuration data, coupled with a novel data mining technique for generating task supervision data. The proposed model demonstrates robustness in configuration generation, translation, and analysis, outperforming conventional tools in handling complex networking environments. The experimental results validate the effectiveness of PreConfig, establishing a new direction for automating network configuration tasks with pretrained language models