A comprehensive three-phase load flow method for integrated MV and LV distribution networks

In the smart grid era, significant penetrations of distributed renewables not only directly impact the secondary low-voltage (LV) distribution network where they are connected, but also indirectly affect the primary medium-voltage (MV) distribution network. Therefore, load flow algorithms are expected to cover both MV and LV levels within a distribution network for more accurate and reasonable analyses. In this study, based on the Direct Load Flow approach and detailed modeling of common Dyn11 distribution transformers, a comprehensive three-phase load flow method which can effectively and efficiently solve the integrated MV and LV distribution networks is proposed. The feasibility and effectiveness as well as superior computational performance in terms of accuracy, efficiency and robustness are verified by simulations on the typical IEEE 4-bus test feeder and a real Australian distribution network over 24 hours

RecKGC: Integrating recommendation with knowledge graph completion

Both recommender systems and knowledge graphs can provide overall and detailed views on datasets, and each of them has been a hot research domain by itself. However, recommending items with a pre-constructed knowledge graph or without one often limits the recommendation performance. Similarly, constructing and completing a knowledge graph without a target is insufficient for applications, such as recommendation. In this paper, we address the problems of recommendation together with knowledge graph completion by a novel model named RecKGC that generates a completed knowledge graph and recommends items for users simultaneously. Comprehensive representations of users, items and interactions/relations are learned in each respective domain, such as our attentive embeddings that integrate tuples in a knowledge graph for recommendation and our high-level interaction representations of entities and relations for knowledge graph completion. We join the tasks of recommendation and knowledge graph completion by sharing the comprehensive representations. As a result, the performance of recommendation and knowledge graph completion are mutually enhanced, which means that the recommendation is getting more effective while the knowledge graph is getting more informative. Experiments validate the effectiveness of the proposed model on both tasks. © 2019, Springer Nature Switzerland AG

Understanding attitudes towards intellectual property from the perspective of design professionals

Intellectual Property Rights (IPR) are meant to protect and promote creativity and innovation. Regardless of the increasing role of IPR in advancing innovations, the corresponding IPR system in the creative industries is still underdeveloped and facing many challenges, especially in developing countries such as China. For example, designers may wittingly or unwittingly violate IP in their design activities, and piracy is a grave concern for the creative industries in China, which may lead to severe revenue drains. To facilitate the development of an IPR system in the creative industries in China, it is essential first to understand what factors may determine the attitudes of design professionals towards IPR in China. A qualitative contextual interview study, conducted with 49 Chinese designers and design managers, revealed different levels of IPR awareness (e.g. what constitutes IPR and how IPR can be protected), and the perceived effectiveness of IPR law enforcement (i.e. weak law enforcement vs vigorous law enforcement), and how different ethical beliefs and ethical climates can have a distinctive impact on attitudes towards IPR. Moreover, our study found that Chinese design professionals exhibit different motivations for their design work. Such motives in design can stimulate different levels of IPR awareness, and these could have an indirect impact on attitudes towards IPR. Based on these findings, a theoretical model is proposed, which incorporates several factors identified from the contextual interview study. Our theoretical model can serve as a baseline model and provide theoretical foundations for future empirical studies on people’s attitudes towards IPR

Reconstruction of time series leaf area index for improving wheat yield estimates at field scales by fusion of Sentinel-2, -3 and MODIS imagery

Continuous time series crop growth monitoring during the main crop growth and development period at field scales is very important for crop management and yield estimation. For more than a decade, the time series leaf area index (LAI) products obtained from high temporal resolution satellites have been widely used in global crop growth monitoring. However, the spatial resolutions (250–1000 m) of these satellite sensors are too coarse for areas with complex and diverse land-use types, especially in China, which causes great uncertainties in crop growth monitoring and yield estimation results. In addition, due to the influence of clouds, optical remote sensing satellites cannot obtain continuous time series data at a given time step over the main crop growth and development period. In this paper, a method based on spatiotemporal data fusion and singular vector decomposition (SVD) is proposed to reconstruct field-scale time series LAI imagery over the main growth and development period of winter wheat. In this method, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) is used to fuse the reflectance imagery of Sentinel-2 and Sentinel-3, and a linear regression model between the LAI data retrieved from the fused reflectance data and the singular vectors derived from the 4-day interval Moderate Resolution Imaging Spectroradiometer (MODIS) LAI data is established to reconstruct the continuous time series field-scale LAI imagery at a given time step. The accuracy of the reconstructed LAI and its capability for winter wheat yield estimation were tested on the Guanzhong Plain of China. The results indicate that (1) the ESTARFM model can fuse the reflectance bands from visible to shortwave infrared of Sentinel-2 and Sentinel-3 on the Guanzhong Plain accurately within a 20-day interval of the winter wheat growth and development period; (2) the 4-day interval field-scale LAI imagery over the main winter wheat growth and development period can be accurately reconstructed based on the linear regression models between the fused LAI data and the singular vectors derived from the 4-day interval MODIS LAI data; and (3) the yield map estimated from the reconstructed field-scale LAI shows more yield distribution details than MODIS yield estimation results. This study shows the feasibility of reconstructing continuous time series field-scale LAI data over the main winter wheat growth and development period on the Guanzhong Plain by combining the spatiotemporal data fusion model with SVD and the potential for estimating the winter wheat yield at field scales

Prediction of job characteristics for intelligent resource allocation in HPC systems: A survey and future directions

Nowadays, high-performance computing (HPC) clusters are increasingly popular. Large volumes of job logs recording many years of operation traces have been accumulated. In the same time, the HPC cloud makes it possible to access HPC services remotely. For executing applications, both HPC end-users and cloud users need to request specific resources for different workloads by themselves. As users are usually not familiar with the hardware details and software layers, as well as the performance behavior of the underlying HPC systems. It is hard for them to select optimal resource configurations in terms of performance, cost, and energy efficiency. Hence, how to provide on-demand services with intelligent resource allocation is a critical issue in the HPC community. Prediction of job characteristics plays a key role for intelligent resource allocation. This paper presents a survey of the existing work and future directions for prediction of job characteristics for intelligent resource allocation in HPC systems. We first review the existing techniques in obtaining performance and energy consumption data of jobs. Then we survey the techniques for single-objective oriented predictions on runtime, queue time, power and energy consumption, cost and optimal resource configuration for input jobs, as well as multi-objective oriented predictions. We conclude after discussing future trends, research challenges and possible solutions towards intelligent resource allocation in HPC systems

The influence of split sleep-wake schedules and daytime sleep strategies on neurobehavioural performance

Introduction: Consumer demands for 24‐h services have led to an increase in employees engaged in shiftwork. However, since these schedules often restrict sleep to biologically inopportune times, the risk of fatigue‐related accidents is a significant concern. As such, two studies were conducted to evaluate alternative sleep‐scheduling options that might optimise performance in situations where long nocturnal sleep episodes are not feasible. Methods: Study 1 considered the effectiveness of short sleep‐wake cycles at sustaining performance around the clock. Twenty‐nine males participated in a 13‐day, 28 h forced desynchrony (FD) protocol in one of two conditions. All obtained the same total time in bed, allocated as one 9.3 h episode per 28 h in the “standard sleep” condition or 4.7 h per 14 h in the “split sleep” condition. Circadian time was estimated from body temperature. Study 2 assessed different daytime sleep strategies between two simulated 12‐h night shifts. Twelve males each participated in three conditions, which differed only in the timing of sleep. The strategies included an immediate sleep, a delayed sleep, and two short sleeps. Performance in both studies was assessed regularly in terms of lapses on the PVT. Results: For the first study, mixed‐models ANOVAs revealed no overall difference between consolidated and split schedules [F(1,30)=2.20, p > .05]. However, there was a significant interaction between schedules and circadian phase such that fewer response lapses occurred at night in the split schedule than the consolidated schedule [F(5,795)=3.8, p > .05]. For Study 2, repeated measures ANOVA showed no differences between the three sleep strategies in night‐time mean lapse count [F(2,183)=0.79, p > .05]. Discussion: The results from both studies indicate that splitting sleep episodes is not inherently harmful to performance provided the total duration is sufficient. Study 1 suggests split work‐rest schedules may be preferable to traditional night shifts for sustaining performance in some industries. Study 2 suggests the timing and arrangement of daytime sleep between long 12 h nights shifts is not critical for nocturnal function

Developing a fused vegetation temperature condition index for drought monitoring at field scales using Sentinel-2 and MODIS imagery

Time-series high spatial resolution drought monitoring is essential for effective agricultural management. For more than a decade, the multiyear vegetation temperature condition index (VTCI) based on the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) has been applied to regional drought monitoring. However, the spatial resolutions of AVHRR and MODIS (1 km) often represent mixtures of built-up areas and different vegetation or crop types. In this paper, a framework is proposed to obtain a ten-day interval multiyear VTCI at field scales, which is fused from Sentinel-2 data with a fine spatial resolution (20 m) and ten-day interval Terra MODIS data with a coarse spatial resolution using the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). This framework includes the disaggregation of the Terra MODIS land surface temperature (LST) using Sentinel-2 data and digital elevation model (DEM) data, the spatiotemporal fusion of normalized difference vegetation index (NDVI) and LST, and drought monitoring by the fused VTCI. The accuracy of this framework for regional drought monitoring was tested in the Guanzhong Plain of China. The results indicate that 1) the Sentinel-2 biophysical products combined with DEM data based on support vector regression can accurately disaggregate the Terra MODIS LST; 2) the ESTARFM has good capability to fuse the NDVI and LST derived from Sentinel-2 and Terra MODIS; 3) the multiyear spatiotemporally fused VTCI, a quantitative drought monitoring index at field scales, can be calculated by using the linear regression between the single-year fused VTCI based on the data in 2018 and the multiyear Terra MODIS VTCI based on an 18-year data record; and 4) the spatiotemporal fusion of the multiyear VTCI can significantly improve the drought monitoring accuracy in the winter wheat and woodland area of the Guanzhong Plain. From mid-March to early May, the multiyear spatiotemporally fused VTCIs have better correlation with the cumulative precipitation over the past 20 days (R2 is 0.83 in the entire study area) than the multiyear Terra MODIS VTCIs (R2 is 0.80 in the entire study area). The results of this study demonstrate the potential of using the spatiotemporal fusion algorithm to obtain the multiyear VTCI at field scales and provide an effective method for improving the accuracy of drought monitoring

Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: A meta-analysis

Livestock grazing activities potentially alter ecosystem carbon (C) and nitrogen (N) cycles in grassland ecosystems. Despite the fact that numerous individual studies and a few meta-analyses had been conducted, how grazing, especially its intensity, affects belowground C and N cycling in grasslands remains unclear. In this study, we performed a comprehensive meta-analysis of 115 published studies to examine the responses of 19 variables associated with belowground C and N cycling to livestock grazing in global grasslands. Our results showed that, on average, grazing significantly decreased belowground C and N pools in grassland ecosystems, with the largest decreases in microbial biomass C and N (21.62% and 24.40%, respectively). In contrast, belowground fluxes, including soil respiration, soil net N mineralization and soil N nitrification increased by 4.25%, 34.67% and 25.87%, respectively, in grazed grasslands compared to ungrazed ones. More importantly, grazing intensity significantly affected the magnitude (even direction) of changes in the majority of the assessed belowground C and N pools and fluxes, and C : N ratio as well as soil moisture. Specifically,light grazing contributed to soil C and N sequestration whereas moderate and heavy grazing significantly increased C and N losses. In addition, soil depth, livestock type and climatic conditions influenced the responses of selected variables to livestock grazing to some degree. Our findings highlight the importance of the effects of grazing intensity on belowground C and N cycling, which may need to be incorporated into regional and global models for predicting effects of human disturbance on global grasslands and assessing the climate-biosphere feedbacks. © 2016 John Wiley & Sons Lt

The repetitive DNA landscape in Avena (Poaceae): chromosome and genome evolution defined by major repeat classes in whole-genome sequence reads.

BACKGROUND: Repetitive DNA motifs - not coding genetic information and repeated millions to hundreds of times - make up the majority of many genomes. Here, we identify the nature, abundance and organization of all the repetitive DNA families in oats (Avena sativa, 2n = 6x = 42, AACCDD), a recognized health-food, and its wild relatives. RESULTS: Whole-genome sequencing followed by k-mer and RepeatExplorer graph-based clustering analyses enabled assessment of repetitive DNA composition in common oat and its wild relatives' genomes. Fluorescence in situ hybridization (FISH)-based karyotypes are developed to understand chromosome and repetitive sequence evolution of common oat. We show that some 200 repeated DNA motifs make up 70% of the Avena genome, with less than 20 families making up 20% of the total. Retroelements represent the major component, with Ty3/Gypsy elements representing more than 40% of all the DNA, nearly three times more abundant than Ty1/Copia elements. DNA transposons are about 5% of the total, while tandemly repeated, satellite DNA sequences fit into 55 families and represent about 2% of the genome. The Avena species are monophyletic, but both bioinformatic comparisons of repeats in the different genomes, and in situ hybridization to metaphase chromosomes from the hexaploid species, shows that some repeat families are specific to individual genomes, or the A and D genomes together. Notably, there are terminal regions of many chromosomes showing different repeat families from the rest of the chromosome, suggesting presence of translocations between the genomes. CONCLUSIONS: The relatively small number of repeat families shows there are evolutionary constraints on their nature and amplification, with mechanisms leading to homogenization, while repeat characterization is useful in providing genome markers and to assist with future assemblies of this large genome (c. 4100 Mb in the diploid). The frequency of inter-genomic translocations suggests optimum strategies to exploit genetic variation from diploid oats for improvement of the hexaploid may differ from those used widely in bread wheat

Antagonistic effects of nitrification inhibitor 3,4-dimethylpyrazole phosphate and fungicide iprodione on net nitrification in an agricultural soil

This study evaluated the effects of nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP) and fungicide iprodione on net nitrification rates and abundances of functional genes related to nitrification and denitrification in an agricultural soil. Single DMPP application or repeated iprodione applications decreased net nitrification rates in the test soil. However, when the DMPP and iprodione were applied together, they could generate antagonistic effects on the inhibitions of net nitrification rates. Repeated iprodione applications reduced ammonia-oxidizing archaea and bacteria (AOA and AOB) amoA gene abundances, while DMPP application decreased AOB amoA gene abundances only. The abundances of narG and nirK genes were negatively affected by repeated iprodione applications. Our results demonstrated that combined applications of DMPP and iprodione could generate antagonistic effects on the inhibitions of net nitrification rates and discrepant impacts on the abundances of functional genes related to soil denitrification. © 201