Water Content Influence on Properties of Red-Layers in Guangzhou Metro Line, China

In order to reveal water content influence on shear strength, swelling, and creep properties of red-layers in Guangzhou Metro, Southern China, the typical red-layers rock and soil specimens were experimentally studied by direct shear test, UU triaxial test, swelling test, and creep test, and the measured data were analyzed. The results showed that soil internal friction angle exponentially decreased with the water content increase and cohesion in accordance with the Gaussian function firstly increased and then decreased with the increase of water content. Expansion rate significantly decreased with the initial water content increase. The red sandstone had very strong isotropic expansion and disintegration properties. The mechanism of water content effect on red-layers properties was water induced microstructures and mineral compositions change which caused the macro physical and mechanical characteristics degradation. The results should provide the reference for further research for water induced damage mechanism or creep damage control of red-layers in engineering practice

Semianalytical Solution and Parameters Sensitivity Analysis of Shallow Shield Tunneling-Induced Ground Settlement

The influence of boundary soil properties on tunneling-induced ground settlement is generally not considered in current analytic solutions, and the hypothesis of equal initial stress in vertical and horizontal makes the application of the above solutions limited. Based on the homogeneous half-plane hypothesis, by defining the boundary condition according to the ground loss pattern in shallow tunnel, and with the use of Mohr-Coulomb plastic yielding criteria and classic Lame and Kiersch elastic equations by separating the nonuniform stress field to uniform and single-direction stress field, a semiempirical solution for ground settlement induced by single shallow circular tunnel is presented and sensitivity to the ground parameters is analyzed. The methods of settlement control are offered by influence factors analysis of semiempirical solution. A case study in Beijing Metro tunnel shows that the semiempirical solution agrees well with the in situ measured results

Health claims unpacked: a toolkit to enhance the communication of health claims for food

Health claims are sentences on the food product packages to claim the nutrition and the benefits of the nutrition. Consumers in different European contexts often have difficulties understanding health claims, leading to increased confusion about and decreased trust in the food they buy. Focusing on this problem, we develop a toolkit for improving the communication of health claim for consumers. The toolkit provides (1) interactive activities to disseminate knowledge about health claims to the public, and (2) an NLP-based analysis and prediction engine that food manufacturers can use to estimate how consumers like the health claims that the manufacturers created. By using the AI-powered toolkit, consumers, manufacturers, and food safety regulators are engaged in determining the different linguistic and cultural barriers to the effective communication of health claims and formulating solutions that can be implemented on multiple levels, including regulation, enforcement, marketing, and consumer education

UoR at SemEval-2021 task 7: utilizing pre-trained DistilBert model and multi-scale CNN for humor detection

Humor detection is an interesting but difficult task in NLP. Humor might not be obvious in text because it may be embedded into context, hide behind the literal meaning of the phrase and require prior knowledge to understand. We explored different shallow and deep methods to create a humour detection classifier for task 7-1a. Models like Logistic Regression, LSTM, MLP, CNN were used, and pre-trained models like DistilBert were introduced to generate accurate vector representation for textual data. We focused on applying a multi-scale strategy on modelling, and compared different models. Our best model is the DistilBert+MultiScale CNN which used different sizes of CNN kernel to get multiple scales of features. This method achieved 93.7% F1-score and 92.1% accuracy on the test set

Simulation of the radiative effect of haze on the urban hydrological cycle using reanalysis data in Beijing

Although increased aerosol concentration modifies local air temperatures and boundary layer structure in urban areas, little is known about its effects on the urban hydrological cycle. Changes in the hydrological cycle modify surface runoff and flooding. Furthermore, as runoff commonly transports pollutants to soil and water, any changes impact urban soil and aquatic environments. To explore the radiative effect of haze on changes in the urban surface water balance in Beijing, different haze levels are modelled using the Surface Urban Energy and Water Balance Scheme (SUEWS), forced by reanalysis data. The pollution levels are classified using aerosol optical depth observations. The secondary aims are to examine the usability of a global reanalysis dataset in a highly polluted environment and the SUEWS model performance. We show that the reanalysis data do not include the attenuating effect of haze on incoming solar radiation and develop a correction method. Using these corrected data, SUEWS simulates measured eddy covariance heat fluxes well. Both surface runoff and drainage increase with severe haze levels, particularly with low precipitation rates: runoff from 0.06 to 0.18 mm d−1 and drainage from 0.43 to 0.62 mm d−1 during fairly clean to extremely polluted conditions, respectively. Considering all precipitation events, runoff rates are higher during extremely polluted conditions than cleaner conditions, but as the cleanest conditions have high precipitation rates, they induce the largest runoff. Thus, the haze radiative effect is unlikely to modify flash flooding likelihood. However, flushing pollutants from surfaces may increase pollutant loads in urban water bodies.Peer reviewe

Delineating the key virulence factors and intraspecies divergence of Vibrio harveyi via whole-genome sequencing

Vibrio harveyi is one of the major pathogens in aquaculture. To identify the key virulence factors affecting pathogenesis of V. harveyi towards fish, we conducted a field investigation for three representative fish farms infected with V. harveyi. Multilocus sequence typing (MLST) and whole-genome sequencing were conducted to delineate the phylogenetic relationship and genetic divergence of V. harveyi. A total of 25 V. harveyi strains were isolated from the diseased fish and groundwater and were subtyped into 12 sequence types by MLST. Five virulence genes, mshB, pilA, hutR, ureB, and ureG, were variably presented in the sequenced strains. The virulence gene profiles strongly correlated with the distinct pathogenicity of V. harveyi strains, with a strain harboring all five genes exhibiting the highest virulence towards fish. Phenotype assay confirmed that reduced virulence correlated with decreased motility and biofilm formation ability. Additionally, three types of type VI secretion system, namely T6SS1, T6SS2, and T6SS3, were identified in V. harveyi strains, which can be classified into six, four, and 12 subtypes, respectively. In conclusion, the results indicated that the virulence level of V. harveyi is mainly determined by the above virulence genes, which may play vital roles in environmental adaptation for V. harveyi

Comparison between static chamber and tunable diode laser-based eddy covariance techniques for measuring nitrous oxide fluxes from a cotton field

Nitrous oxide (N2O) fluxes from a cotton field in northern China were measured for a year using the static chamber method based on a gas chromatograph (GC) and the eddy covariance (EC) technique based on a tunable diode laser (TDL). The aims were to compare the N2O fluxes obtained from both techniques, assess the uncertainties in the fluxes and evaluate the annual direct emission factors (EFds, i.e. the loss rate of fertilizer nitrogen via N2O emission) using the year-round datasets. During the experimental period, the hourly and daily mean chamber fluxes ranged from 0.6 to 781.8 and from 1.2 to 468.8 g N m−2 h−1, respectively. The simultaneously measured daily mean EC fluxes varied between −10.8 and 912.0 g N m−2 h−1. The EC measurements only provided trustworthy 30-min fluxes during high-emission period (a 20-day period immediately after the irrigation that followed the nitrogen fertilization event). A reliable comparison was confined to the high-emission period and showed that the chamber fluxes were 17–20% lower than the EC fluxes. This difference may implicate the magnitude of systematic underestimation in the fluxes from chamber measurements. The annual emission from the fertilized cotton field was estimated at 1.43 kg N ha−1 yr−1 by the chamber observations and 3.15 kg N ha−1 yr−1 by the EC measurements. The EFds calculated from the chamber and EC data were 1.04% and 1.65%, respectively. The chamber-based estimate was very close to the default value (1.0%) recommended by the Intergovernmental Panel on Climate Change. However, the difference in the EFds based on the two measurement techniques may vary greatly with changing environmental conditions and management practices. Further comparison studies are still needed to elucidate this issue.Peer reviewe

First-principles investigation of aluminum intercalation and diffusion in TiO2 materials: Anatase versus rutile

Aluminum-ion batteries, emerging as a promising post-lithium battery solution, have been a subject of increasing research interest. Yet, most existing aluminum-ion research has focused on electrode materials development and synthesis. There has been a lack of fundamental understanding of the electrode processes and thus theoretical guidelines for electrode materials selection and design. In this study, by using density functional theory, we for the first time report a first-principles investigation on the thermodynamic and kinetic properties of aluminum intercalation into two common TiO 2 polymorphs, i.e., anatase and rutile. After examining the aluminum intercalation sites, intercalation voltages, storage capacities and aluminum diffusion paths in both cases, we demonstrate that the stable aluminum intercalation site locates at the center of the O 6 octahedral for TiO 2 rutile and off center for TiO 2 anatase. The maximum achievable Al/Ti ratios for rutile and anatase are 0.34375 and 0.36111, respectively. Although rutile is found to have an aluminum storage capacity slightly higher than anatase, the theoretical specific energy of rutile can reach 20.90 Wh kg −1 , nearly twice as high as anatase (9.84 Wh kg −1 ). Moreover, the diffusion coefficient of aluminum ions in rutile is 10 −9 cm 2 s −1 , significantly higher than that in anatase (10 −20 cm 2 s −1 ). In this regard, TiO 2 rutile appears to be a better candidate than anatase as an electrode material for aluminum-ion batteries

UoR at SemEval-2020 task 8: Gaussian mixture modelling (GMM) based sampling approach for multi-modal memotion analysis

Memes are widely used on social media. They usually contain multi-modal information such as images and texts, serving as valuable data sources to analyse opinions and sentiment orientations of online communities. The provided memes data often face an imbalanced data problem, that is, some classes or labelled sentiment categories significantly outnumber other classes. This often results in difficulty in applying machine learning techniques where balanced labelled input data are required. In this paper, a Gaussian Mixture Model sampling method is proposed to tackle the problem of class imbalance for the memes sentiment classification task. To utilise both text and image data, a multi-modal CNN-LSTM model is proposed to jointly learn latent features for positive, negative and neutral category predictions. The experiments show that the re-sampling model can slightly improve the accuracy on the trial data of sub-task A of Task 8. The multi-modal CNN-LSTM model can achieve macro F1 score 0.329 on the test set