Power induced by bubbles of different sizes and frequencies on to hollow fibers in submerged membrane systems

To shed light onto the relationship between sparging conditions and fouling control in submerged hollow fiber membranes, the effects of bubble size and frequency on the hydrodynamic conditions induced in membrane system were studied. Two general classes of bubbles were considered: coarse (0.75–2.5 mL) and pulse (100–500 mL). The power transferred (P_trans) onto membranes could be used to characterise the multiple effects induced under different sparging conditions. P_trans is proportional to root mean square of shear stress (τ_rms), the area of zone of influence (i.e. the fraction in the system where high velocity and high vorticity (turbulence) are induced by the bubble) and their rise velocity. At a given sparging rate, the power transferred onto membranes was less with coarse bubble sparging than pulse bubble sparging and increased with the size of pulse bubbles. For all cases, the power transfer efficiency was consistently higher for pulse bubble sparging than for coarse bubble sparging. The power transfer efficiency to the system was greatest for the small pulse bubbles considered when a small amount of power is required for fouling control. However, when fouling is extensive, large pulse bubbles may be required to generate the required amount of power for fouling control.     

Estimation of Lightning Current and Return Stroke Velocity Profile Using Measured Electromagnetic Fields

To evaluate lightning current using measured electromagnetic fields, an inverse procedure algorithm is proposed in this article, where the variation of return velocity stroke velocity is considered as opposed to previous methods where the velocity is set at a constant value. The proposed algorithm considers all electromagnetic fields components directly in the time domain without needing to apply any extra conversions. Moreover, it can support the wide range of current models based on the general form of engineering current models. The proposed method is validated using a sample of triggered lightning data and measured electromagnetic fields at two stations with different distances from the lightning channel. The results illustrate that the proposed method could estimate the behavior of current along the channel and can thus be used for preparing a data bank to record lightning current parameters of a wide range of lightning occurrences based on measured fields.     

Experimental evaluation of a vibration-based leak detection technique for water pipelines

Conventional water pipeline leak detection surveys employ labour-intensive acoustic techniques, which are usually expensive and not amenable for continuous monitoring of distribution systems. Many previous studies attempted to address these limitations by proposing and evaluating a myriad of continuous, long-term monitoring techniques. However, these techniques have difficulty to identify leaks in the presence of pipeline system complexities (e.g. T-joints), offered limited compatibility with popular pipe materials (e.g. PVC), and were in some cases intrusive in nature. Recently, a non-intrusive pipeline surface vibration-based leak detection technique has been proposed to address some of the limitations of the previous studies. This new technique involves continuous monitoring of the change in the cross-spectral density of surface vibration measured at discrete locations along the pipeline. Previously, the capabilities of this technique have been demonstrated through an experimental campaign carried out on a simple pipeline set-up. This paper presents a follow-up evaluation of the new technique in a real-size experimental looped pipeline system located in a laboratory with complexities, such as junctions, bends and varying pipeline sizes. The results revealed the potential feasibility of the proposed technique to detect and assess the onset of single or multiple leaks in a complex system.     

Seismic bearing capacity of shallow strip foundations in the vicinity of slopes using the lower bound finite element method

The seismic bearing capacity of shallow strip foundations in the vicinity of slopes was investigated by the use of the lower bound limit analysis in conjunction with the finite element method and the linear programming technique. The combination of the most probable failure modes including slope instability and ultimate bearing capacity makes the problem difficult to solve by conventional approximate methods such as the limit equilibrium, the bound theorems of the limit analysis, and the slip line methods since these are based on assumptions about either kinematically admissible failure mechanisms or statically admissible stress fields. The pseudo-static seismic loading scheme was adopted in the presence of both horizontal and vertical acceleration fields, and the soil-foundation interface was assumed perfectly rough. Parametric analyses were conducted to evaluate the most effective factors in the form of the dimensionless strength and geometry parameters. The results of the current study were found comparable with those in the literature, and the consistency of the results confirmed the robustness of the extended finite element lower bound formulation. It was shown that the normalized limit pressure is dramatically reduced as the earthquake acceleration coefficients increases, and that it increases with higher the soil strength parameters. Moreover, the threshold distance at which the influence of the slope diminishes was found to be a function of the soil strength parameters and the slope geometry.     

Friction stir welding of co-cast aluminium clad sheet

The effects of welding parameters on material consolidation are examined during friction stir butt welding of 2 mm Al 5083 alloy aluminium sheet with a surface cladding of Al 3025 alloy, which was co-cast from the melt. The influence of welding parameters on joint consolidation is investigated when tool revolutions per minute, travel speed and penetration depth were varied. It was found that modifying the pin of the welding tool to have a two-flat profile improves material consolidation and avoids defect formation during welding, and optimum welding parameters involve a combination of high tool rotation speed and travel speed. Optical and electron microscopy revealed that the integrity of the surface cladding layer could be maintained during friction stir welding while avoiding defect formation within the stir zone of the weld. The tensile strength of the joint was ～58% of the base material due to softening within the stir zone.     

Kinetics of methane decomposition to COx-free hydrogen and carbon nanofiber over Ni–Cu/MgO catalyst

Kinetic modeling of methane decomposition to CO_x-free hydrogen and carbon nanofiber has been carried out in the temperature range 550–650 °C over Ni–Cu/MgO catalyst from CH₄–H₂ mixtures at atmospheric pressure. Assuming the different mechanisms of the reaction, several kinetic models were derived based on Langmuir–Hinshelwood type. The optimum value of kinetic parameters has been obtained by Genetic Algorithm and statistical analysis has been used for the model discrimination. The suggested kinetic model relates to the mechanism when the dissociative adsorption of methane molecule is the rate-determining stage and the estimated activation energy is 50.4 kJ/mol in agreement with the literature. The catalyst deactivation was found to be dependent on the time, reaction temperature, and partial pressures of methane and hydrogen. Inspection of the behavior of the catalyst activity in relation to time, led to a model of second order for catalyst deactivation.     

Numerical study of developing laminar forced convection of a nanofluid in an annulus

Laminar forced convection of a nanofluid consisting of Al₂O₃ and water has been studied numerically. Two dimensional elliptical governing equations have been solved to investigate the hydrodynamics and thermal behaviors of the fluid flow throughout an annulus. Single phase approach is used for the nanofluid modeling. The velocity and temperature profiles are presented in the fully developed region. The axial evolution of temperature, convective heat transfer coefficient and the friction coefficient at the inner and outer walls' region are shown and discussed. It is shown that the dimensionless axial velocity profile does not significantly change with the nanoparticle volume fraction. But, the temperature profiles are affected by the nanoparticle concentration. In general convective heat transfer coefficient increases with nanoparticle concentration. However, when the order of magnitude of heating energy is much higher than the momentum energy the friction coefficient depends on the nanoparticle concentration. At higher Reynolds numbers for which the momentum energy increases, this dependency on the nanoparticle volume fraction decreases.     

Arachidin-1, a Prenylated Stilbenoid from Peanut,Induces Apoptosis in Triple-Negative Breast Cancer Cells

Triple-negative breast cancer (TNBC) is unresponsive to typical hormonal treatments, causing it to be one of the deadliest forms of breast cancer. Investigating alternative therapies to increase survival rates for this disease is essential. The goal of this study was to assess cytotoxicity and apoptosis mechanisms of prenylated stilbenoids in TNBC cells. The prenylated stilbenoids arachidin-1 (A-1) and arachidin-3 (A-3) are analogs of resveratrol (RES) produced in peanut upon biotic stress. The anticancer activity of A-1 and A-3 isolated from peanut hairy root cultures was determined in TNBC cell lines MDA-MB-231 and MDA-MB-436. After 24 h of treatment, A-1 exhibited higher cytotoxicity than A-3 and RES with approximately 11-fold and six-fold lower IC₅₀, respectively, in MDA-MB-231 cells, and nine-fold and eight-fold lower IC₅₀, respectively, in MDA-MB-436 cells. A-1 did not show significant cytotoxicity in the non-cancerous cell line MCF-10A. While A-1 blocked cell division in G2-M phases in the TNBC cells, it did not affect cell division in MCF-10A cells. Furthermore, A-1 induced caspase-dependent apoptosis through the intrinsic pathway by activating caspase-9 and PARP cleavage, and inhibiting survivin. In conclusion, A-1 merits further research as a potential lead molecule for the treatment of TNBC.     

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.     

Immunogenicity of MultiTEP-Platform-Based Recombinant Protein Vaccine,PV-1950R,Targeting Three B-Cell Antigenic Determinants of Pathological α-Synuclein

Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) are characterized by the aberrant accumulation of intracytoplasmic misfolded and aggregated α-synuclein (α-Syn), resulting in neurodegeneration associated with inflammation. The propagation of α-Syn aggregates from cell to cell is implicated in the spreading of pathological α-Syn in the brain and disease progression. We and others demonstrated that antibodies generated after active and passive vaccinations could inhibit the propagation of pathological α-Syn in the extracellular space and prevent/inhibit disease/s in the relevant animal models. We recently tested the immunogenicity and efficacy of four DNA vaccines on the basis of the universal MultiTEP platform technology in the DLB/PD mouse model. The antibodies generated by these vaccines efficiently reduced/inhibited the accumulation of pathological α-Syn in the different brain regions and improved the motor deficit of immunized female mice. The most immunogenic and preclinically effective vaccine, PV-1950D, targeting three B-cell epitopes of pathological α-Syn simultaneously, has been selected for future IND-enabling studies. However, to ensure therapeutically potent concentrations of α-Syn antibodies in the periphery of the vaccinated elderly, we developed a recombinant protein-based MultiTEP vaccine, PV-1950R/A, and tested its immunogenicity in young and aged D-line mice. Antibody responses induced by immunizations with the PV-1950R/A vaccine and its homologous DNA counterpart, PV-1950D, in a mouse model of PD/DLB have been compared.