Synthesis of plant-based biogenic jarosite nanoparticles using Azadirachta indica and Eucalyptus gunni leaf extracts and its application in Fenton degradation of dicamba

Bio-jarosite,an iron mineral synthesized biologically using bacteria,is a substitute for iron catalysts in the Fenton oxidation of organic pollutants.Iron nanocatalysts have been widely used as Fenton catalysts because they have a larger surface area than ordinary catalysts,are highly recyclable,and can be treated efficiently.This study aimed to explore the catalytic properties of bio-jarosite iron nanoparticles syn-thesized with green methods using two distinct plant species:Azadirachta indica and Eucalyptus gunni.The focus was on the degradation of dicamba via Fenton oxidation.The synthesized nanoparticles exhibited different particle size,shape,surface area,and chemical composition characteristics.Both particles were effective in removing dicamba,with removal efficiencies of 96.8%for A.indica bio-jarosite iron nano-particles(ABFeNPs)and 93.0%for E.gunni bio-jarosite iron nanoparticles(EBFeNPs)within 120 min of treatment.Increasing the catalyst dosage by 0.1 g/L resulted in 7.6%and 43.0%increases in the dicamba removal efficiency for EBFeNPs and ABFeNPs with rate constants of 0.025 min^(-1) and 0.023 min^(-1),respectively,confrming their catalytic roles.Additionally,the high efficiency of both catalysts was demonstrated through five consecutive cycles of linear pseudo-first-order Fenton oxidation reactions.

Seismic behavior of tire waste-sand mixtures for transportation infrastructure in cold regions

Tire wastes have many properties that are valuable from a geotechnical engineering perspective, such as low density, high strength, thermal insulation, energy absorption capacity, permeability, durability, compressibility, resilience, and high frictional strength. Thus, tire wastes offer good thermal characteristics in resisting frost penetration and have good drainage characteristics, being as permeable as coarse granular soil for fill materials. The many advantages of tire wastes make the material suitable for transportation infrastructure construction in cold regions. Also, tire wastes with high damping prop- erty make them a preferable admixture with sand for transportation infrastructures in seismic regions, This study aimed to determine the seismic performance of certain tire waste-sand mixtures in cold regions. A 70% sand-30% tire crumb mixture by weight （TC30） with a very high damping property was selected for analysis as an engineering material for transportation infrastructure. Small-scale shake-table tests were conducted on this material as well as on a sand-only sample under two different temperatures, 0 ℃ and 20 ℃, to simulate cold-region and moderate-temperature performance, respectively. The 1999 lzmit Earthquake Excitation （EW） （Mw = 7.4） was taken as the input motion. Test results showed that the tire waste-sand mixture at 0 ℃ showed better seismic performance than that at room temperature, suggesting that a tire waste-sand mixture in cold regions may reduce seismic hazards to infrastructure.

Enhancement of Workability of Cement-Poor Concrete by Optimizing Paste Content

This study describes the performance of concrete in fresh state, intended for sealing deep bore-holes in the host rock of radioactive repositories. Set of different paste volumes, combinations of water-to-powder ratios and fine aggregate contents have been performed within the frame of this study. The main objective was to search for tendencies, logical connections and phenomena that occur for different combination of materials regarding the fluidity and segregation and mainly the effect from the (paste) or fine aggregate content. It shall be pointed out that this investigation is a suggestion on how concrete can be optimized using two simple test methods based on changing the paste content. The results highlighted the importance of having sufficient amounts of filler and cement paste for separate and carry larger particles, which gives the concrete good workability and fluidity at casting. It was concluded that the slump behaviors can be optimized based on the adjustments of the superplastisizer dosage.

Effects of Incorporating Expanded Polystyrene in Concrete Construction

Polystyrene is a highly popular plastic packaging material. It is essentially non-biodegradable and takes hundreds of years to decompose in case of land filling while other disposal methods or treatments methods create hazardous effects on the environment. However, this material is known to possess properties such as sound insulation, high thermal conductivity, and lightweight, thereby making it a great additive in concrete. Haven incorporated this material into a concrete matrix;in various percentages which served as partial replacement for coarse aggregates, the concretes’ properties were tested and compared with the properties of the conventional concrete. The experimental data was obtained based on the replacement coarse aggregate by EPS volume ratio of 0%, 4%, 8%, 12% and 16%. The concretes’ properties such as its slump, density, compressive strength, flexural strength and split tensile strength were experimentally determined. These results were then used to determine the influence of polystyrene as partial replacement for coarse aggregate was analyzed and the results compared with that of a concrete mix containing no polystyrene. The results obtained from this analysis indicate that the addition of polystyrene in a concrete mix implies smaller densities as the densities of concrete containing 0%, 4%, 8%, 12% and 16% are 2536, 2443, 2363, 2339 and 2316 Kg/m3 respectively. It was also observed that the compressive strength of the concrete decreased with an increase in the percentage of polystyrene incorporated. This is clearly shown using in the 28th day strength of the concrete samples (21.68, 17.25, 15.87, 14.53 and 13.92 mpa for replacements at 0%, 4%, 8%, 12% and 16% respectively). Similarly, the flexural strength of the concrete decreased with an increase in the percentage of polystyrene incorporated. Whereas, the variations in the split tensile strengths were inconsistent as they were notable increments and decrease in the 28th day strength of the various concrete matrixes.

基于统计分析的桥梁坍塌事故原因剖析及预防措施研究

在桥梁设计、施工、运营、维护等环节中,各种潜在不确定因素均可能导致桥梁安全事故的发生。基于对近10年来桥梁坍塌事故的统计分析,在将桥梁坍塌事故归纳为三类因素(先天夭折、人为原因、自然原因)的基础上按事故诱因又细分为水灾害、风灾害、船舶车辆撞击、超载、设计施工失误及年久失修六因素。分别从不同角度对桥梁坍塌事故进行剖析及总结,并结合具体案例针对性地提出预防措施。研究结果表明:导致桥梁坍塌的原因可查、可控、可预防,通过严谨的事前准备、精细的事中控制、完善的事后预防可以有效避免桥梁坍塌事故的发生。

Evaluation of the relationship between two different methods for enumeration fecal indicator bacteria: Colony-forming unit and most probable number

Most probable number （MPN） and colony-forming unit （CFU） estimates of fecal indicator bacteria （FIB） concentration are common measures of water quality in aquatic environments. Thus, FIB intensively monitored in Yeongsan Watershed in an attempt to compare two different methods and to develop a statistical model to convert from CFU to MPN estimates or vice versa. As a result, the significant difference was found in the MPN and CFU estimates. The enumerated Escherichia coli concentrations in MPN are greater than those in CFU, except for the measurement in winter. Especially in fall, E. coli concentrations in MPN are one order of magnitude greater than that in CFU. Contrarily, enterococci bacteria in MPN are lower than those in CFU. However, in general, a strongly positive relationship are found between MPN and CFU estimates. Therefore, the statistical models were developed, and showed the reasonable converting FIB concentrations from CFU estimates to MPN estimates. We expect this study will provide preliminary information towards future research on whether different analysis methods may result in different water quality standard violation frequencies for the same water sample.

Effect of nonionic side chain length of polycarboxylate-ethe卜based high-range water-reducing admixture on properties of cementitious systems

Despite the large variations in the behaviors of water-reducing admixtures upon changes in their structures,most previous reports on the cement-admixture compatibility did not provide suficient information on the structure of the admixture.Hence,the evaluation and generalization of the reports on the cement-admixture compatibility are challenging.In this study,three different polycarboxylate-ether-based water-reducing admixtures with the same free nonionic content,anionic/nonionic molar ratio,and main chain length and different side chain lengths were produced.The compatibility of these admixtures with a CEM I 42.5R-type cement was investigated.In addition,an analysis of variance was performed on the experiment results to evaluate the contributions of the admixture type,admixture/cement ratio,and elapsing time to the Marsh funnel flow time,mini-slump,slump flow,and compressive strength.The water-reducing admixtures having long or short side chains reduced the initial flow characteristics of the cementitious systems.However,the admixture having the shortest side chain was better with regard to flow retention.The side chain length of the admixture did not have significant effects on the compressive strength and water absorption capacity of the mortar mixtures and mini-slump performances of the cement paste mixtures.Regarding the behaviors of the admixtures in the cementitious systems,an optimal admixture side chain molecular weight is proposed.

Simplified theoretical analysis and numerical study on the dynamic behavior of FCP under blast loads

Precast concrete structures have developed rapidly in the last decades due to the advantages of better quality,non-pollution and fast construction with respect to conventional cast-in-place structures.In the present study,a theoretical model and nonlinear 3D model are developed and established to assess the dynamic behavior of precast concrete slabs under blast load.At first,the 3D model is validated by an experiment performed by other researchers.The verified model is adopted to investigate the blast performance of fabricated concrete panels(FCPs)in terms of parameters of the explosive charge,panel thickness,and reinforcement ratio.Finally,a simplified theoretical model of the FCP under blast load is developed to predict the maximum deflection.It is indicated that the theoretical model can precisely predict the maximum displacement of FCP under blast loads.The results show that the failure modes of the panels varied from bending failure to shear failure with the mass of TNT increasing.The thickness of the panel,reinforcement ratio,and explosive charges have significant effects on the anti-blast capacity of the FCPs.

Research and optimization on laminated steel tube column-concrete beam joints with outer stiffening ring

In practical design,the joints with outer stiffening ring were used to connect concrete beams and laminated steel tube columns.The seismic behavior of joints with outer stiffening ring with various types was studied based on experiments.The bearing capacity,rigidity,ductility,energy dissipation capacity,deformation property and strain distribution of the joints with outer stiffening ring with various types were comprehensively evaluated based on the test results of three specimens under quasistatic cyclic loading and finite element analysis.The test results showed that the failure mode,hysteretic behavior,bearing capacity and rigidity degradation of the joints with outer stiffening ring with various types were nearly identical.Furthermore,the strain distribution of the outer stiffening ring of the three joints was nearly the same.The detailing recommendation for the outer strengthening rings was proposed for the concrete beam-laminated steel tube column joints with outer stiffening ring,in order to ensure the good seismic capacity of the joints.

A step forward towards a comprehensive framework for assessing liquefaction land damage vulnerability:Exploration from historical data

The unprecedented liquefaction-related land damage during earthquakes has highlighted the need to develop a model that better interprets the liquefaction land damage vulnerability(LLDV)when determining whether liquefaction is likely to cause damage at the ground's surface.This paper presents the development of a novel comprehensive framework based on select case history records of cone penetration tests using a Bayesian belief network(BBN)methodology to assess seismic soil liquefaction and liquefaction land damage potentials in one model.The BBN-based LLDV model is developed by integrating multi-related factors of seismic soil liquefaction and its induced hazards using a machine learming(ML)algorithm-K2 and domain knowledge(DK)data fusion methodology.Compared with the C4.5 decision tree-J48 model,naive Bayesian(NB)classifier,and BBN-K2 ML prediction methods in terms of overall accuracy and the Cohen's kappa coefficient,the proposed BBN K2 and DK model has a better performance and provides a substitutive novel LLDV framework for characterizing the vulnerability of land to liquefaction-induced damage.The proposed model not only predicts quantitatively the seismic soil liquefaction potential and its ground damage potential probability but can also identify the main reasons and fault-finding state combinations,and the results are likely to assist in decisions on seismic risk mitigation measures for sustainable development.The proposed model is simple to perform in practice and provides a step toward a more sophisticated liquefaction risk assessment modeling.This study also interprets the BBN model sensitivity analysis and most probable explanation of seismic soil liquefed sites based on an engineering point of view.

Identifying mining-induced chromium contamination in soil through visible-near infrared spectroscopy and machine learning

The extraction,purification,and utilization of mineral resources have been among the largest anthropogenic sources of chromium(Cr)in soil.Determining Cr contamination in soil is a key issue prior to its appropriate remediation.Nevertheless,the efficient identification of large-scale soil Cr contamination requires continuous research.The present study proposes a continental-scale method to rapidly identify soil Cr contamination using visible-near infrared spectroscopy(vis-NIR)and machine learning(ML).A large dataset containing 18,675topsoil samples from the Land Use/Land Cover Area Frame Survey 2009 projects across Europe was compiled.Five advanced ML algorithms were compared,and hyperparameter optimization was conducted using the grid search method.Permutation importance was employed to calculate the rank of each spectral wavelength,shedding light on the most sensitive spectral wavelength for Cr contamination.Results indicate that hyperparameter optimization had the most significant performance improvement on support vector machine(SVM),exhibiting an increase in training performance from 0.795 to 0.868.The achieved optimal SVM accuracy,area under the receiver operating feature curve,sensitivity,and specificity of 0.78,0.85,0.85,and 0.66,respectively,indicating excellent predictive performance on the Cr contamination classification.The optimal SVM model revealed that the most important spectral band for classifying Cr contamination was 1430-1433 nm.This finding implies that the adsorption of molecular water was closely related to the classification of Cr contamination.The current study introduces the first continental-scale identification of Cr contamination using visNIR,which has excellent guiding significance for Cr remediation and the identification of other heavy metals using vis-NIR.