HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph Embedding

We consider a contrastive learning approach to knowledge graph embedding (KGE) via InfoNCE. For KGE, efficient learning relies on augmenting the training data with negative triples. However, most KGE works overlook the bias from generating the negative triples-false negative triples (factual triples missing from the knowledge graph). We argue that the generation of high-quality (i.e., hard) negative triples might lead to an increase in false negative triples. To mitigate the impact of false negative triples during the generation of hard negative triples, we propose the Hardness and Structure-aware (\textbf{HaSa}) contrastive KGE method, which alleviates the effect of false negative triples while generating the hard negative triples. Experiments show that HaSa improves the performance of InfoNCE-based KGE approaches and achieves state-of-the-art results in several metrics for WN18RR datasets and competitive results for FB15k-237 datasets compared to both classic and pre-trained LM-based KGE methods

Politics of memories: Identity construction in museums

This paper adopts collective memory theory to reveal processes through which heritage tourism stakeholders (re)construct contested national identity. Theoretically sensitised to identity crisis, the study analyses how Hong Kong and Macao heritage managers utilise complex transnational memories to (re)construct an identity aligned with, yet distinct from, that of China. Through a critical discourse analysis of interviews and discursive exhibition and museum texts, the article reveals that museum managers formulate heritage imaginings and a sense of belonging(s) through defining the collective memory for “Self” and “Other”. The article concludes that, by collective memory-building, museum professionals make tangible statements of national identities through legitimating negotiations and resistance in heritage tourism discourse. Implications for heritage tourism studies and museum management are also discussed

Mesoporous High‐Surface‐Area Copper–Tin Mixed‐Oxide Nanorods: Remarkable for Carbon Monoxide Oxidation

Mesoporous, high‐surface‐area Cu–Sn mixed‐oxide nanorods were fabricated for the first time by nanocasting with the use of mesoporous KIT‐6 silica as the hard template. The Cu–Sn nanorods are significantly more active than 1 % Pd/SnO2 for the oxidation of CO and possesses long‐term durability and potent water resistance; they thus have the potential to replace noble metal catalysts for emission‐control processes.In rod we trust: Mesoporous, high‐surface‐area Cu–Sn nanorods are successfully fabricated for the first time by nanocasting with the use of KIT‐6 silica as the hard template; these nanomaterials are significantly more active than 1 % Pd/SnO2 for the oxidation of CO, and furthermore, they have the potential to replace noble metal catalysts for emission control.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137536/1/cctc201600221.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137536/2/cctc201600221-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137536/3/cctc201600221_am.pd

Evaluating how lodging affects maize yield estimation based on UAV observations

Timely and accurate pre-harvest estimates of maize yield are vital for agricultural management. Although many remote sensing approaches have been developed to estimate maize yields, few have been tested under lodging conditions. Thus, the feasibility of existing approaches under lodging conditions and the influence of lodging on maize yield estimates both remain unclear. To address this situation, this study develops a lodging index to quantify the degree of lodging. The index is based on RGB and multispectral images obtained from a low-altitude unmanned aerial vehicle and proves to be an important predictor variable in a random forest regression (RFR) model for accurately estimating maize yield after lodging. The results show that (1) the lodging index accurately describes the degree of lodging of each maize plot, (2) the yield-estimation model that incorporates the lodging index provides slightly more accurate yield estimates than without the lodging index at three important growth stages of maize (tasseling, milking, denting), and (3) the RFR model with lodging index applied at the denting (R5) stage yields the best performance of the three growth stages, with R2 = 0.859, a root mean square error (RMSE) of 1086.412 kg/ha, and a relative RMSE of 13.1%. This study thus provides valuable insight into the precise estimation of crop yield and demonstra\tes that incorporating a lodging stress-related variable into the model leads to accurate and robust estimates of crop grain yield

Path Planning for Unmanned Aerial Vehicle Using a Mix-Strategy-Based Gravitational Search Algorithm

Path planning is a global optimization problem aims to program the optimal flight path for Unmanned Aerial Vehicle (UAV) that has short length and suffers from low threat. In this paper, we present a Mixed-Strategy based Gravitational Search Algorithm (MSGSA) for the path planning. In MSGSA, an adaptive adjustment strategy for the gravitational constant attenuation factor alpha ( α) is presented firstly, in which the value of α is adjusted based on the evolutionary state of the particles. This helps to adaptively balance the exploration and exploitation of the algorithm. In addition, to further alleviate the premature convergence problem, a Cauchy mutation strategy is developed for MSGSA. In this strategy, only when the global best particle cannot be further improved for several times the mutation is executed. In the MSGSA based path planning procedure, we construct an objective function using the flight length cost, threat area cost, and turning angle constraint to decrease the flight risk and obtain the smoother path. For performance evaluation, the MSGSA is applied to two typical simulated flight missions with complex flight environments, including user-defined forbidden flying areas, Radar, missile, artillery and anti-aircraft gun. The obtained flight paths are compared with that of the standard Gravitational Search Algorithm (GSA) and two improved variants of GSA, i.e. gbest-guided GSA (GGSA), and hybrid Particle Swarm Optimization and GSA (PSOGSA). The experimental results demonstrate the superiority of the MSGSA based method in terms of the solution quality, robustness, as well as the constraint-handling ability

Simultaneous determination of kolliphor HS15 and miglyol 812 in microemulsion formulation by ultra-high performance liquid chromatography coupled with nano quantity analyte detector

A novel method for simultaneous determination of kolliphor HS15 and miglyol 812 in microemulsion formulation was developed using ultra-high performance liquid chromatography coupled with a nano quantitation analytical detector (UHPLC–NQAD). All components in kolliphor HS15 and miglyol 812 were well separated on an Acquity BEH C18 column. Mobile phase A was 0.1% trifluoroacetic acid (TFA) in water and mobile phase B was acetonitrile. A gradient elution sequence was programed initially with 60% organic solvent, slowly increased to 100% within 8 min. The flow rate was 0.7 mL/min. Good linearity (r>0.95) was obtained in the range of 27.6–1381.1 μg/mL for polyoxyl 15 hydroxystearate in kolliphor HS15, 0.8–202.0 μg/mL for caprylic acid triglyceride and 2.7–221.9 μg/mL for capric acid triglyceride in miglyol 812. The relative standard deviations (RSD) ranged from 0.6% to 1.7% for intra-day precision and from 0.4% to 2.7% for inter-day precision. The overall recoveries (accuracy) were 99.7%–101.4% for polyoxyl 15 hydroxystearate in kolliphor HS15, 96.7%–99.6% for caprylic acid triglyceride, and 94.1%–103.3% for capric acid triglyceride in miglyol 812. Quantification limits (QL) were determined as 27.6 μg/mL for polyoxyl 15 hydroxystearate in kolliphor HS15, 0.8 μg/mL for caprylic acid triglyceride, and 2.7 μg/mL for capric acid triglyceride in miglyol 812. No interferences were observed in the retention time ranges of kolliphor HS15 and miglyol 812. The method was validated in terms of specificity, linearity, precision, accuracy, QL, and robustness. The proposed method has been applied to microemulsion formulation analyses with good recoveries (82.2%–103.4%)

Development and validation of a GCâFID method for quantitative analysis of oleic acid and related fatty acids

Oleic acid is a common pharmaceutical excipient that has been widely used in various dosage forms. Gas chromatography (GC) has often been used as the quantitation method for fatty acids normally requiring a derivatization step. The aim of this study was to develop a simple, robust, and derivatization-free GC method that is suitable for routine analysis of all the major components in oleic acid USP-NF (United States Pharmacopeia-National Formulary) material. A gas chromatographyâflame ionization detection (GCâFID) method was developed for direct quantitative analysis of oleic acid and related fatty acids in oleic acid USP-NF material. Fifteen fatty acids were separated using a DB-FFAP (nitroterephthalic acid modified polyethylene glycol) capillary GC column (30 mÃ0.32 mm i.d.) with a total run time of 20 min. The method was validated in terms of specificity, linearity, precision, accuracy, sensitivity, and robustness. The method can be routinely used for the purpose of oleic acid USP-NF material analysis. Keywords: Oleic acid, Fatty acids, Gas chromatography, Method development, Derivatization-fre

Study on the Influence of Tourists’ Value on Sustainable Development of Huizhou Traditional Villages-- A Case of Hongcun and Xidi

The tourists’ value of traditional village representing personal values, influences the tourists’ behavior deeply. This paper, with the soft ladder method of MEC theory from the perspective of the tourist, studies the value of tourists born in the 60s, 70s, 80s, and 90s of the traditional villages in Hongcun and Xidi, which indicates 39 MEC value chains, and reveals 11 important attributes of Huizhou traditional villages, 16 tourism results, and 9 types of tourists’ values. With constructing a sustainable development model of Huizhou traditional villages based on tourists’ value, it shows an inherent interaction between tourists’ value and traditional village attributes subdividing the tourism products and marketing channels of Huizhou traditional villages, which is of great significance to the sustainable development of traditional villages in Huizhou

Assessment Method of Wind Farm Harmonic Emission Value Based on Improved Complex Linear Regression Model

Wind turbine filter and reactive power compensation devices lead to the harmonic impedance of wind farm is not much larger than that of the utility, so the influence by the wind farm harmonic impedance can not be neglected while assessing the harmonic emission value of wind farm A method based on improved complex linear regression is proposed in this paper for assessing the harmonic emission value of wind farm. The linear regression model is established by using the harmonic current at PCC point as the explanatory variable and the harmonic voltage of the wind farm as the explanatory variable. The utility harmonic impedance is calculated by complex least squares method. For various of the topology of wind farm feeder network, an equivalent method of feeder network is proposed to calculate the wind farm harmonic impedance. Errors are analyzed by using the error marginal effect of the dispersion parameter. Simulation and measured data verify the effectiveness of the proposed metho