Role of sulfide and ligand strength in controlling nanosilver toxicity

Nanosilver has been used broadly in nanotechnology enhanced consumer products because of its strong antimicrobial properties. Silver nanoparticles (AgNPs) released from these products will likely enter wastewater collection and treatment systems. This research evaluated the role of sulfide and ligand strength in controlling nanosilver toxicity to nitrifying bacteria that are important in wastewater treatment. The nanosilver toxicity in the absence and presence of ligands (SO₄²⁻, S²⁻, Cl⁻, PO₄³⁻, and EDTA⁻) commonly present in wastewater was determined from the oxygen uptake rate measurements. Sulfide appeared to be the only ligand to effectively reduce nanosilver toxicity. By adding a small aliquot of sulfide that was stoichiometrically complexed with AgNPs, the nanosilver toxicity to nitrifying organisms was reduced by up to 80%. Scanning electron microscopy coupled with energy dispersive X-ray analysis indicated that AgNPs were highly reactive with sulfide to form new Ag_xS_y complexes or precipitates. These complexes were not oxidized after a prolonged period of aeration (18 h). This information is useful for wastewater treatment design and operation to reduce nanosilver toxicity via sulfide complexation. While the biotic ligand model was successful in predicting the toxicity of Ag⁺ ions, it could not accurately predict the toxicity of AgNPs. Nevertheless, it could be one of the many tools useful in predicting and controlling nanosilver toxicity to wastewater microorganisms.     

Posture optimization for a humanoid robot using a simple genetic algorithm

This study proposes a method of real-time posture optimization of humanoid robots using a genetic algorithm and neural network. Here, the motion of a humanoid robot pushing an object is considered. When the robot starts pushing the object, the palms of its hands and the soles of its feet are assumed to be fixed on the object and on the ground, respectively, and they sense the reaction force from those surfaces. The reaction force results in changes of torques in the joints. This study determines an optimized posture using a genetic algorithm such that either the torques are evenly distributed over all joints or the torque of the weakest joint is rapidly reduced. Several different optimized postures are then generated by varying the reaction forces at the palms and the soles. The data is used as training patterns for a multilayer perceptron neural network with a back-propagation learning algorithm. Using the trained neural network, the humanoid robot can find the optimal posture for different reaction forces in real time. Several simulations were conducted to confirm the effectiveness of the proposed method. The simulation results showed that the proposed method can be used for real-time posture optimization of humanoid robots.     

Numerical and experimental studies on characteristic surface temperature variations of aluminum plates facing different directions

This paper is a part of the work in developing a software that predicts IR signatures from objects in the scene by considering the direct and diffuse solar irradiations, the atmospheric convection and the conduction within objects. The thermal information of the objects and their background is essential for understanding the IR signature characteristics from the scene. The thermal contrast between the objects and the background is then used to obtain their infrared radiation contrast which is the important signal in identifying the objects. We considered the composite heat transfer modes including conduction, convection and spectral solar irradiation on the objects within a scene to calculate the surface temperature distribution. The radiative energy components included in the thermal analyses are consisted of the direct and diffuse solar irradiances and sky thermal irradiation, while the thermal conduction within the object is approximated as one-dimensional heat transfer into the depth. The measured diurnal surface temperature variations on the three different test plates facing east, south and west respectively are fairly well compared with the modeled results obtained from the software developed in this study and a commercial software. A complete set of measured data including the plate temperature together with the detailed weather information and the irradiation data can be valuable reference for future study.     

A joint normalcy index to evaluate patients with gait pathologies in the functional aspects of joint mobility

Gait analysis using 3D motion capture systems provides joint kinematic and kinetic analysis results such as joint relative angles and moments that can be use used to evaluate the degrees of pathological gait patterns. However, the complex data produced using these 3D motion capture systems can only analyzed by experts, because the gait analysis is highly coupled to the kinematics of each joint. Therefore, several Several previous studies using gait analysis have relied on the data compression technique to represent gait deviation from the average normal profiles as a single value. Even though it is important to evaluate gait pathologies at the joint level, all these previous studies have just used a single value to evaluate the pathological gait pattern. Using just one variable for evaluation of a gait is limited in terms of determining which joint movement patterns are getting better during rehabilitation. Therefore, in this study, a method suitable for evaluating gait deviation during a gait was developed to provide three indices for the hip, knee and ankle joints. In addition, to validate the proposed method in clinical cases, experimental tests were conducted on thirty thirty-six normal walkers and six patients with cerebral palsy. Furthermore, to validate the proposed method in regards to rehabilitation, experimental tests were conducted on three classified walking groups with imposed ankle equinus constraints. The JNI for the hip joint, knee joint and ankle were 8.78 (±3.70), 2.92 (±3.25) and 8.79 (±4.38), respectively, in the normal walking group. However, these values were significantly different for the pathological walking group with cerebral palsy. The JNI of the hip joint, knee joint and ankle joint were 203.73 (±171.59), 81.23 (±52.13) and 248.39 (±149.99), respectively, for this group. There were also differences between any two of the three classified groups with imposed ankle equinus constraints. In particular, the JNI of the ankle joint was statistically different at the p<0.01 level, and this parameter clearly increased as the degree of the imposed ankle equinus was increased. These results demonstrate that the proposed JNI can be used as a scalar factor to evaluate the angular deviation of each joint in normal and patient groups. In addition, this approach can be adapted to evaluate rehabilitation and pre/post surgery.     

Fabrication and characterization of PMN-PT single crystal cantilever array for cochlear-like acoustic sensor

We have successfully fabricated piezoelectric PMN-PT single crystal cantilever array. Each PMN-PT cantilever has a different length to achieve different resonance frequencies. The width and thickness of PMN-PT cantilever array are 200 μm and 10 μm, respectively. Resonance frequencies of PMN-PT cantilevers were measured with laser interferometer, and charge sensitivity was measured with charge-measuring device. PMN-PT cantilever array was installed in a noise-shield case. The array was then exposed to sound pressure frequency corresponding to resonance frequency to measure its sensitivity. The experimental results show that the PMN-PT cantilever array has high sensitivity to the sound pressure. This implies that the single crystal PMN-PT cantilever array is a potential candidate for a cochlear-like acoustic sensor.     

A performance study on a direct drive hydro turbine for wave energy converter

Clean and renewable energy technologies using ocean energy give us non-polluting alternatives to fossil-fueled power plants as a countermeasure against global warming and growing demand for electrical energy. Among the ocean energy resources, wave power takes a growing interest because of its enormous amount of potential energy in the world. Therefore, various types of wave power systems to capture the energy of ocean waves have been developed. However, a suitable turbine type is not yet normalized because of relatively low efficiency of the turbine systems. The purpose of this study is to investigate the performance of a newly developed direct drive hydro turbine (DDT), which will be built in a caisson for a wave power plant. Experiment and CFD analysis are conducted to clarify the turbine performance and internal flow characteristics. The results show that the DDT obtains fairly good turbine efficiency in cases with and without wave conditions. Most of the output power is generated at the runner passage of Stage 2. Relatively larger amount of the decreased tangential velocity at Stage 2 produces more angular momentum than that at Stage 1 and thus, the larger angular momentum at the Stage 2 makes a greater contribution to the generation of total output power in comparison with that at Stage 1. Large vortex existing in the upper-left region of the runner passage forms a large recirculation region in the runner passage, and the recirculating flow consumes the output power at Region 2.     

Lumped parameter modeling and analysis of hybrid magnet engine valve actuator

The hybrid magnet engine valve actuator (HMEVA) composed of two types of magnets (permanent magnet and electromagnet) and two balanced springs is a promising tool for implementing innovative engine management strategies for variable valve timing. Finite Element Method (FEM), a favored actuator design tool due to its high accuracy, was utilized to analyze the electromagnetic actuator, but it consumes a lot of time especially in computation iterations for optimization. Accordingly, the magnetic equivalent circuit analysis can be an alternative tool to FEM because of its computation iteration capability with fair accuracy. In this paper, an equivalent magnetic circuit model of an HMEVA is developed considering the reluctances, external magnetic forces and so on, and the simulation results are presented. In addition, the result of lumped parameter analysis (LA) is compared with those obtained from finite element analysis for verification.     

Three-dimensional model of spray forming by fringe element reconstruction method

A three-dimensional spray forming process model was developed to predict the general transient shape of deposited material. The distribution of the spatial droplet flow rate was modeled by an axisymmetrical Gaussian function, and the shadowing effect was utilized for accurate prediction of the deposited shape. In order to construct the three-dimensional meshes applicable to various numerical analyses, the fringe element reconstruction method was employed to calculate the shape of deposited material. In order to verify the developed method, the simulation results were compared with the available experimental data in the literature. Good agreement was obtained between the numerical and experimental results. Finally, the effect of the withdrawal velocity of the substrate was investigated.