Thin-layer heap bioleaching of copper flotation tailings containing high levels of fine grains and microbial community succession analysis

Thin-layer heap bioleaching of copper flotation tailings containing high levels of fine grains was carried out by mixed cultures on a small scale over a period of 210 d. Lump ores as a framework were loaded at the bottom of the ore heap. The overall copper leaching rates of tailings and lump ores were 57.10wt% and 65.52wt%, respectively. The dynamic shifts of microbial community structures about attached microorganisms were determined using the Illumina MiSeq sequencing platform based on 16S rRNA amplification strategy. The results indicated that chemolithotrophic genera Acidithiobacillus and Leptospirillum were always detected and dominated the microbial community in the initial and middle stages of the heap bioleaching process; both genera might be responsible for improving the copper extraction. However, Thermogymnomonas and Ferroplasma increased gradually in the final stage. Moreover, the effects of various physicochemical parameters and microbial community shifts on the leaching efficiency were further investigated and these associations provided some important clues for facilitating the effective application of bioleaching.     

Synthesis of BiOCl photocatalyst by a low-cost,simple hydrolytic technique and its excellent photocatalytic activity

A novel photocatalyst, bismuth oxychloride (BiOCl) micro-nano particles with a fine ferrite plate structure, was prepared by a low-cost, simple hydrolytic method. The as-prepared BiOCl was characterized by scanning electron microscopy (SEM), thermogravimetric analysis-differential thermal analysis (TGA-DTA), X-ray diffraction (XRD), and UV-vis diffuse reflectance spectra (DRS). The effects of preparation conditions such as sodium dodecyl benzene sulfonate (SDBS) dispersant, HCl concentration, and heat treatment temperature on BiOCl performances were investigated. Moreover, its photocatalytic activity was evaluated on the degradation of methylene orange (MO) and was compared with that of TiO₂ (P25). The experimental results confirmed that BiOCl micro-nano particles prepared with SDBS, the HCl concentration of 1.5 mol/L, and the heat treatment temperature of 80℃ exhibited the best performance for the photodegradation of MO solution, and they showed good stability and better photocatalytic activity than P25 photocatalyst.     

A novel method for solving the multiple traveling salesmen problem with multiple depots

Multi-traveling salesman problem(MTSP) is an extension of traveling salesman problem,which is a famous NP hard problem,and can be used to solve many real world problems,such as railway transportation,routing and pipeline laying.In this paper,we analyze the general properties of MTSP,and find that the multiple depots and closed paths in the graph is a big issue for MTSP.Thus,a novel method is presented to solve it.We transform a complicated graph into a simplified one firstly,then an effective algorithm is proposed to solve the MTSP based on the simplified results.In addition,we also propose a method to optimize the general results by using 2-OPT.Simulation results show that our method can find the global solution for MTSP efficiently.     

Variable diffusion boundary layer and diffusion flux at sediment-water interface in response to dynamic forcing over an intertidal mudflat

The diffusion boundary layer (DBL) significantly limits the exchange between sediment and overlying water and therefore becomes a bottleneck of diffusive vertical flux at the sediment-water interface (SWI). Variable DBL thickness and diffusion flux in response to dynamic forcing may influence replenishment of nutrients and secondary pollution in coastal waters. In situ measurements of velocity in the bottom boundary layer (BBL) and oxygen concentration in the DBL were made over an intertidal mudflat, using an acoustic Doppler current and mini profiler. A linear distributed zone in the oxygen profile, the profile slope discontinuity and variance of concentration can be used to derive accurate DBL thickness. Diffusion fluxes calculated from the water column and sediment are identical, and their bias is less than 6%. A numerical model PROFILE is used to simulate the in situ dissolved oxygen profile, and layered dissolved oxygen consumption rates in the sediment are calculated. The DBL thickness (0.10-0.35 mm) and diffusion flux (15.4-53.6 mmol m 2 d 1) vary with a factor of 3.5 during a tidal period. Over an intertidal mudflat, DBL thickness is controlled by flow speed U in the BBL, according to δDBL=1686.1DU 1+0.1 (D is the molecular diffusion coefficient). That is, the DBL thickness δDBL increases with decreasing flow speed U. Changes of diffusion flux at the SWI are caused by variations in the water above the sediment and the turbulent mixing intensity. The diffusion flux is positively related to the turbulent dissipation rate, friction velocity and turbulent energy. Under the influence of dynamics in the BBL, DBL thickness and flux vary significantly.     

Characterization of a Y-type hexagonal ferrite-based frequency tunable microwave absorber

A Y-type hexaferrite rod with the composition of Ba₂Co_1.8Cu_0.2Fe₁₂O₂₂ was presented as an absorbing material with high absorbance. Its high absorbance and wide absorption band result from ferromagnetic resonance (FMR) that is self-biased by strong shape and magnetocrystalline anisotropy fields. Around the FMR frequency the specimen of the ferrite rods exhibits very high absorbance and the FMR frequency can be tuned by the rod dimension. In addition to the high absorbance and the wide tunable absorption band, the microwave absorber has another advantage of light weight due to the use of the ferrite rods instead of ferrite slabs.     

Effect of MWCNT reinforcement on the precipitation-hardening behavior of AA2219

Aluminum alloy matrix composites have found a predominant place in research, and their applications are explored in almost all industries. The aerospace industry has been using precipitation-hardenable alloys in structural applications. However, insufficient literature is available on the influence of multiwalled carbon nanotubes (MWCNTs) on precipitation-hardenable alloy composite materials; thus, this work was designed to elucidate the effect on MWCNT reinforcement on AA2219 with and without precipitation hardening. Reinforcement with MWCNTs has been reported to accelerate precipitation and to achieve greater hardness within a much shorter time. The addition of 0.75wt% MWCNTs resulted in maximal hardness at 90 min, which is approximately 27% of improvement over the maximum hardness achieved by the corresponding monolithic alloy after 10 h of aging. The sample reinforced with 0.75wt% MWCNTs showed an improvement of 82% in hardness by solutionizing and aging compared to that achieved by sintering.     

Effects of Zn content on the microstructure and the mechanical and corrosion properties of as-cast low-alloyed Mg–Zn–Ca alloys

The effects of Zn content on the microstructure and the mechanical and corrosion properties of as-cast low-alloyed Mg–xZn–0.2Ca alloys (x=0.6wt%, 2.0wt%, 2.5wt%, hereafter denoted as 0.6Zn, 2.0Zn, and 2.5Zn alloys, respectively) are investigated. The results show that the Zn content not only influences grain refinement but also induces different phase precipitation behaviors. The as-cast microstructure of the 0.6Zn alloy is composed of α-Mg, Mg₂Ca, and Ca₂Mg₆Zn₃ phases, whereas 2.0Zn and 2.5Zn alloys only contain α-Mg and Ca₂Mg₆Zn₃ phases, as revealed by X-ray diffraction (XRD) and transmission electron microscopy (TEM) analyses. Moreover, with increasing Zn content, both the ultimate tensile strength (UTS) and the elongation to fracture first increase and then decrease. Among the three investigated alloys, the largest UTS (178 MPa) and the highest elongation to fracture (6.5%) are obtained for the 2.0Zn alloy. In addition, the corrosion rate increases with increasing Zn content. This paper provides an updated investigation of the alloy composition–microstructure–property relationships of different Zn-containing Mg–Zn–Ca alloys.     

Improvement of microstructure and corrosion properties of friction stir welded AA5754 by adding Zn interlayer

This study investigated the effect of Zn foil layers on the microstructure and corrosion characteristics of friction stir welded aluminum alloy 5754. Samples of various joints were prepared by applying different rotational and welding speeds, and their microstructures were evaluated via a metallographic technique and scanning electron microscopy equipped with energy-dispersive X-ray spectroscopy elemental analysis. The anticorrosion behavior of joints in the absence and presence of a Zn interlayer was studied by cyclic potentiodynamic polarization test in 3.5wt% NaCl aqueous solution, and sound welds were obtained in the presence of the Zn interlayer foil. The results revealed that the joint made at a rotational speed of 800 r/min and traveling speed of 15 mm/min achieved a chemical composition identical to that of aluminum alloy 7xxx series, and as such, it showed the best resistance to corrosion.     

Software Module Clustering Algorithm Using Probability Selection

Software module clustering problem is an important and challenging problem in software reverse engineering whose main goal is to obtain a good modular structure of the software system. The large complex software system can be divided into some subsystems that are easy to understand and maintain through the software module clustering. Aiming at solving the problem of slow convergence speed, the poor clustering result, and the complex algorithm, a software module clustering algorithm using probability selection is proposed. Firstly, we convert the software system into complex network diagram, and then we use the operation of merger, adjustment and optimization to get the software module clustering scheme. To evaluate the effectiveness of the algorithm, a set of experiments was performed on 5 real-world module clustering problems. The comparison of the experimental results proves the simplicity of the algorithm as well as the low time complexity and fast convergence speed. This algorithm provides a simple and effective engineering method for software module clustering problem.     

Quantitative Analysis of Multi-Recovery-Based Intrusion Tolerance Model

Quantitative analysis has always been a difficult problem in security analysis of intrusion tolerance systems. An intrusion tolerance model based on multiple recovery mechanisms is introduced in this paper and how to quantify the security attributes of the model is proposed. A state transition model with recovery states more accurately describes the dynamic behavior of the system. Considering that recovery mechanisms have a great impact on the security performance of the system, we set up the cost models corresponding to different recovery mechanisms. We propose a feasible security measure based on mean cost to security failure in order to evaluate the system cost during the recovery phase. The experimental results confirmed the feasibility of the proposed methods.