CKG: Dynamic Representation Based on Context and Knowledge Graph

Recently, neural language representation models pre-trained on large corpus can capture rich co-occurrence information and be fine-tuned in downstream tasks to improve the performance. As a result, they have achieved state-of-the-art results in a large range of language tasks. However, there exists other valuable semantic information such as similar, opposite, or other possible meanings in external knowledge graphs (KGs). We argue that entities in KGs could be used to enhance the correct semantic meaning of language sentences. In this paper, we propose a new method CKG: Dynamic Representation Based on \textbf{C}ontext and \textbf{K}nowledge \textbf{G}raph. On the one side, CKG can extract rich semantic information of large corpus. On the other side, it can make full use of inside information such as co-occurrence in large corpus and outside information such as similar entities in KGs. We conduct extensive experiments on a wide range of tasks, including QQP, MRPC, SST-5, SQuAD, CoNLL 2003, and SNLI. The experiment results show that CKG achieves SOTA 89.2 on SQuAD compared with SAN (84.4), ELMo (85.8), and BERT$_{Base}$ (88.5)

Does Faith Has Impact on Investment Return: Evidence From REITs

This paper investigates whether faith has impact on investment returns. Specifically, we choose the Shariah compliance and REITs investment for the purpose of investigation. Synthetic Shariah compliant portfolios are constructed with various interpretation of compliance. We compare the performance of Shariah compliant portfolios with US Equity REIT portfolio during 1993-2017 by examining the abnormal returns using CAPM and Carhart four-factor model. We find no evidence of underperformance or outperformance of the Shariah compliant investments. This is also true during the financial crisis periods which is confirmed by the sub-sample analysis. Our findings suggest that Shariah compliant REIT investor faces no cost or gain in his investments as a result of his faith

Can rainmakers justify their pay? The role of investment banks in REIT M&As

This study explicitly rejects the prima facie proposition that the top-tier investment banks are capable of delivering supernormal value creation to the shareholders of a REIT acquirer in a corporate acquisition. Using the event study method, we find that REIT acquirers advised by market-leading investment banks suffer an average cumulative abnormal return of −4.41% following the M&A announcement, whereas REIT acquirers advised by non-top-tier investment banks only suffer an average cumulative abnormal return of −1.49%. The evidence shows that the contemporary practice of employing investment banks based on the prestige of the advisory firms could potentially result in value-destroying M&As for the REIT acquirers

Does faith has impact on investment return: evidence from REITs

TThis paper investigates whether faith has impact on investment returns. Specifically, we choose the Shariah compliance and REITs investment for the purpose of investigation. Synthetic Shariah compliant portfolios are constructed with various interpretation of compliance. We compare the performance of Shariah compliant portfolios with US Equity REIT portfolio during 1993–2017 by examining the abnormal returns using CAPM and Carhart four-factor model. We find no evidence of underperformance or outperformance of the Shariah compliant investments. This is also true during the financial crisis periods which is confirmed by the sub-sample analysis. Our findings suggest that Shariah compliant REIT investor faces no cost or gain in his investments as a result of his faith

Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving

Vehicle Specific Power (VSP) has been increasingly used as a good indicator for the instantaneous power demand on engines for real world driving in the field of vehicle emission and fuel consumption modeling. A fixed vehicle mass is normally used in VSP calculations. However, the influence of passenger load was always been neglected. The major objective of this paper is to quantify the influence of passenger load on diesel bus emissions and fuel consumption based on the real-world on-road emission data measured by the Portable Emission Measurement System (PEMS) on urban diesel buses in Nanjing, China. Meanwhile, analyses are conducted to investigate whether passenger load affected the accuracy of emission and fuel consumption estimations based on VSP. The results show that the influence of passenger load on emission and fuel consumption rates were related to vehicle's speed and acceleration. As for the distance-based factors, the influence of passenger load was not obvious when the buses were driving at a relative high speed. However the effects of passenger load were significant when the per-passenger factor was used. Per-passenger emission and fuel consumption factors decreased as the passenger load increased. It was also found that the influence of passenger load can be omitted in the emission and fuel consumption rate models at low and medium speed bins but has to be considered in the models for high speed and VSP bins. Otherwise it could lead to an error of up to 49%. The results from this research will improve the accuracy of urban bus emission and fuel consumption modeling and can be used to improve planning and management of city buses and thus achieve energy saving and emission reduction

Challenges of developing a power system with a high renewable energy proportion under China’s carbon targets

For China, one of its most important commitments is to realize its “3060” targets of achieving a CO2 emission peak by 2030 and carbon neutrality by 2060. However, for a developing country with heavy carbon utilization, achieving carbon neutrality in a short period necessitates tough changes. This paper briefly introduces energy and electricity scenarios and analyzes the challenges based on the current power system in China. Moreover, it summarizes the six characteristics of China’s future power grid and highlights some partially representative projects in the country

Emergence of Fatal PRRSV Variants: Unparalleled Outbreaks of Atypical PRRS in China and Molecular Dissection of the Unique Hallmark

Porcine reproductive and respiratory syndrome (PRRS) is a severe viral disease in pigs, causing great economic losses worldwide each year. The causative agent of the disease, PRRS virus (PRRSV), is a member of the family Arteriviridae. Here we report our investigation of the unparalleled large-scale outbreaks of an originally unknown, but so-called “high fever” disease in China in 2006 with the essence of PRRS, which spread to more than 10 provinces (autonomous cities or regions) and affected over 2,000,000 pigs with about 400,000 fatal cases. Different from the typical PRRS, numerous adult sows were also infected by the “high fever” disease. This atypical PRRS pandemic was initially identified as a hog cholera-like disease manifesting neurological symptoms (e.g., shivering), high fever (40–42°C), erythematous blanching rash, etc. Autopsies combined with immunological analyses clearly showed that multiple organs were infected by highly pathogenic PRRSVs with severe pathological changes observed. Whole-genome analysis of the isolated viruses revealed that these PRRSV isolates are grouped into Type II and are highly homologous to HB-1, a Chinese strain of PRRSV (96.5% nucleotide identity). More importantly, we observed a unique molecular hallmark in these viral isolates, namely a discontinuous deletion of 30 amino acids in nonstructural protein 2 (NSP2). Taken together, this is the first comprehensive report documenting the 2006 epidemic of atypical PRRS outbreak in China and identifying the 30 amino-acid deletion in NSP2, a novel determining factor for virulence which may be implicated in the high pathogenicity of PRRSV, and will stimulate further study by using the infectious cDNA clone technique

Electromagnetic transient modelling and simulation of power converters based on a piecewise generalised state–space averaging method

Common averaging methods are studied for modelling a grid-connected converter in renewable energy domain to balance accuracy and efficiency of electromagnetic transient simulation. A piecewise generalised state–space averaging (P-GSSA) method is proposed for converters with large-scale renewable energy connected to the grid. The piecewise technique is applied to the GSSA model of converters, which combine time segment with similar operating characteristics. In addition, multi-time scale modelling is successfully achieved for the grid-connected converters in the renewable energy domain. An example is simulated according to the P-GSSA model proposed in this paper, and simulation results show that the proposed model can provide an efficient simulation of power converters connected to the grid in the domain of large-scale renewable energy