Efficient stabilization of dredged sludge with high water content using an improved bio-carbonation of reactive magnesia cement method

This study proposed an improved bio-carbonation of reactive magnesia cement(RMC)method for dredged sludge stabilization using the urea pre-hydrolysis strategy.Based on unconfined compression strength(UCS),pickling-drainage,and scanning electron microscopy(SEM)tests,the effects of prehydrolysis duration(T),urease activity(UA)and curing age(CA)on the mechanical properties and microstructural characteristics of bio-carbonized samples were systematically investigated and analyzed.The results demonstrated that the proposed method could significantly enhance urea hydrolysis and RMC bio-carbonation to achieve efficient stabilization of dredged sludge with 80%high water content.A significant strength increment of up to about 1063.36 kPa was obtained for the bio-carbonized samples after just 7 d of curing,which was 2.64 times higher than that of the 28-day cured ordinary Portland cement-reinforced samples.Both elevated T and UA could notably increase urea utilization ratio and carbonate ion yield,but the resulting surge in supersaturation also affected the precipitation patterns of hydrated magnesia carbonates(HMCs),which weakened the cementation effect of HMCs on soil particles and further inhibited strength enhancement of bio-carbonized samples.The optimum formula was determined to be the case of T?24 h and UA?10 U/mL for dredged sludge stabilization.A 7-day CA was enough for bio-carbonized samples to obtain stable strength,albeit slightly affected by UA.The benefits of high efficiency and water stability presented the potential of this method in achieving dredged sludge stabilization and resource utilization.This investigation provides informative ideas and valuable insights on implementing advanced bio-geotechnical techniques to achieve efficient stabilization of soft soil,such as dredged sludge.

Effect of discrete fibre reinforcement on soil tensile strength

The tensile behaviour of soil plays a significantly important role in various engineering applications. Compacted soils used in geotechnical constructions such as dams and clayey liners in waste containment facilities can suffer from cracking due to tensile failure. In order to increase soil tensile strength, discrete fibre reinforcement technique was proposed. An innovative tensile apparatus was developed to deter- mine the tensile strength characteristics of fibre reinforced soil. The effects of fibre content, dry density and water content on the tensile strength were studied. The results indicate that the developed test apparatus was applicable in determining tensile strength of soils. Fibre inclusion can significantly in- crease soil tensile strength and soil tensile failure ductility. The tensile strength basically increases with increasing fibre content. As the fibre content increases from 0% to 0.2%, the tensile strength increases by 65.7%. The tensile strength of fibre reinforced soil increases with increasing dry density and decreases with decreasing water content. For instance, the tensile strength at a dry density of 1.7 Mg/m^3 is 2.8 times higher than that at 1.4 Mg/m^3. It decreases by 30% as the water content increases from 14.5% to 20.5%. Furthermore, it is observed that the tensile strength of fibre reinforced soil is dominated by fibre pull-out resistance, depending on the interracial mechanical interaction between fibre surface and soil matrix.

BEVGGC:Biogeography-Based Optimization Expert-VGG for Diagnosis COVID-19 via Chest X-ray Images

Purpose:As to January 11,2021,coronavirus disease(COVID-19)has caused more than 2 million deaths worldwide.Mainly diagnostic methods of COVID-19 are:(i)nucleic acid testing.This method requires high requirements on the sample testing environment.When collecting samples,staff are in a susceptible environment,which increases the risk of infection.(ii)chest computed tomography.The cost of it is high and some radiation in the scan process.(iii)chest X-ray images.It has the advantages of fast imaging,higher spatial recognition than chest computed tomography.Therefore,our team chose the chest X-ray images as the experimental dataset in this paper.Methods:We proposed a novel framework—BEVGG and three methods(BEVGGC-I,BEVGGC-II,and BEVGGC-III)to diagnose COVID-19 via chest X-ray images.Besides,we used biogeography-based optimization to optimize the values of hyperparameters of the convolutional neural network.Results:The experimental results show that the OA of our proposed three methods are 97.65%±0.65%,94.49%±0.22%and 94.81%±0.52%.BEVGGC-I has the best performance of all methods.Conclusions:The OA of BEVGGC-I is 9.59%±1.04%higher than that of state-of-the-art methods.

Least-Square Support Vector Machine and Wavelet Selection for Hearing Loss Identification

Hearing loss(HL)is a kind of common illness,which can significantly reduce the quality of life.For example,HL often results in mishearing,misunderstanding,and communication problems.Therefore,it is necessary to provide early diagnosis and timely treatment for HL.This study investigated the advantages and disadvantages of three classical machine learning methods:multilayer perceptron(MLP),support vector machine(SVM),and least-square support vector machine(LS-SVM)approach andmade a further optimization of the LS-SVM model via wavelet entropy.The investigation illustrated that themultilayer perceptron is a shallowneural network,while the least square support vector machine uses hinge loss function and least-square optimizationmethod.Besides,a wavelet selection method was proposed,and we found db4 can achieve the best results.The experiments showed that the LS-SVM method can identify the hearing loss disease with an overall accuracy of three classes as 84.89±1.77,which is superior to SVM andMLP.The results show that the least-square support vector machine is effective in hearing loss identification.

The coupled hydro-mechanical behaviours of compacted crushed Callovo-Oxfordian argillite

Callovo-Oxfordian （COx） argillite obtained from the excavation of high-level radioactive waste geological disposal has been evaluated as an alternative sealing/backfill material in France. This paper presents an experimental investigation into the hydro-mechanical behaviour of compacted crushed COx argillite. A series of oedorneter compressive tests including various loading-unloading cycles were conducted on COx argillite powders at different initial water contents. After reaching the desired dry density （2.0 Mg/m^3）, the vertical stress was reduced to different levels （7.0 and 0.5 MPa） and the compacted sample was then flooded under constant volume conditions while measuring the changes in the vertical stress. It was found that the initial water content significantly affects the compressive behaviour. The measured saturated hydraulic conductivity is less than 1×10^-10m/s.

Evaluation Model of Farmer Training Effect Based on AHP–A Case Study of Hainan Province

On the basis of studying the influencing factors of training effect evaluation,this paper constructs an AHP-fuzzy comprehensive evaluation model for farmers’vocational training activities in Hainan Province to evaluate farmers’training effect,which overcomes the limitations of traditional methods.Firstly,the content and index system of farmer training effect evaluation are established by analytic hierarchy process,and the weight value of each index is determined.Then,the fuzzy comprehensive evaluation(FCE)of farmer training effect is carried out by using multi-level FCE.The joint use of AHP and FCE improves the reliability and effectiveness of the evaluation process and results.The overall comprehensive evaluation result of the farmer training effect evaluation is“good”.