Aflatoxin contamination and exposure in processed cereal-based complementary foods for infants and young children in greater Accra,Ghana

In the study, aflatoxin levels were assessed in thirty five (35) cereal-based food products intended for infants and young children. Additionally, the results showed that 71% of the processed foods intended for infants contained AFB₁ (0.18 ± 0.01 to 36.10 ± 0.32 μgkg⁻¹) levels higher than the European Union permissible limits of 0.1 μg kg⁻¹. Aflatoxin intake was estimated using aflatoxin levels in the food products and the estimated individual consumption rates. The study also revealed mixed cereals as having the highest intake of aflatoxin B₁ contaminants (0.005–0.852 μgkg⁻¹bw d⁻¹; 0.004–0.657 μgkg⁻¹bwd⁻¹) with mean estimated daily intake (EDI) of 0.23 ± 0.16 μgkg⁻¹bwd⁻¹ and 0.153 ± 0.13 μgkg⁻¹bwd⁻¹ for infants and young children respectively. The estimated AFT intake recorded for infants and young children for all the cereal-based food ranged from 0.005 to 1.054 μgkg⁻¹bwd⁻¹ and 0.004–0.838 μgkg⁻¹bwd⁻¹ respectively.     

Kernel-based fourth-order diffusion for image noise removal

The fourth-order partial differential equations have good performance on noise smoothing and edge preservation without creating blocky effects on smooth regions. However, for low signal-to-noise ratio images, the discrimination between edges and noise is a challenging problem. A novel kernel-based fourth-order diffusion is proposed in this paper. It introduces a kernelized gradient operator in the fourth-order diffusion process, which leads to more effective noise removal capability. Experiment results show that this method outperforms several previous anisotropic diffusion methods for noise removal and edge preservation.     

Ku波段基片集成波导带通滤波器的设计

设计了一款基于基片集成波导的ku波段卫星通信的带通滤波器。描述了位于SIW内部的金属通孔的等效电路模型,并分析通孔直径、位置等关键参数对滤波器性能的影响。针对基于中心位置的SIW带通滤波器带宽较窄的问题,提出偏置金属通孔SIW带通滤波器的设计方法,从而增大滤波器的带宽。并通过对改进后的基片集成波导带通滤波器的仿真,验证了设计的正确性和方法的有效性。     

Verification of Iron Loss Calculation Method Using a High‐Precision Iron Loss Analyzer

Because of the improved performance of power devices, the volume of the ac filter inductors used in high‐frequency PWM inverters has been reduced. However, the temperature rise in the filter inductor due to this miniaturization has become more pronounced. Therefore, we have proposed an iron loss calculation method for the ac filter inductor. However, the accuracy of the value calculated via the loss map method cannot be verified, because the iron loss arising during each switching period cannot be measured with conventional power measuring instruments. In order to resolve this problem, we developed an inductor loss analyzer (ILA), which allows precise measurement of the iron loss in the inductor during each switching period. The accuracy of the calculation of iron loss in the filter inductor by the loss map method was verified with the ILA. We found that the value calculated by the loss map method differed slightly from the value measured with the ILA. However, these differences can be reduced if we take into account the accurate flux density calculation and the effect of the duty ratio of PWM pulses on the loss. Finally, we verified that the loss map method can provide accurate iron loss calculations.     

Improving oxidation resistance of porous FeAl-based intermetallics with high boron/yttrium alloying

The coalloying with high contents of chromium (Cr), boron (B) and yttrium (Y) for porous B2-structured FeAl intermetallics fabricated through reactive synthesis was conducted. The oxidation behaviors of porous FeAl-based materials were investigated by evaluating the pore-structure evolution, oxidation kinetics and oxide-scale configuration. The results show that with the coalloying of high contents of Cr, B and Y, the oxidation mass gains of porous FeAl materials at 600?800 °C are significantly reduced. The combination of B enriched on the surface of oxide scales and Y located at the scale?metal interface promotes the formation of thin protective nodular α-Al₂O₃ oxide scales. It is indicated that introducing relatively high contents of reactive elements such as B and Y can benefit the selective growth of α-Al₂O₃ scales at relatively low temperatures without pre-treatment.     

Finite-time adaptive fuzzy control for a class of output constrained nonlinear systems with dead-zone

The article investigates the finite-time adaptive fuzzy control for a class of nonlinear systems with output constraint and input dead-zone. First, by skillfully combining the barrier Lyapunov function, backstepping design method, and finite-time control theory, a novel adaptive state-feedback tracking controller is constructed, and the output constraint of the nonlinear system is not violated. Second, the fuzzy logic system is used to approximate unknown function in the nonlinear system. Third, the finite-time command filter is introduced to avoid the problem of “complexity explosion” caused by repeated differentiations of the virtual control signal in conventional backstepping control schemes. Meanwhile, a new saturation function is added in the compensating signal for filter error to improve control accuracy. Finally, based on Lyapunov stability analysis, all the signals of the closed-loop are proved to be semi-globally uniformly ultimately bounded, and the tracking error converges to a small neighborhood region of the origin in a finite time. A simulation example is presented to demonstrate the effectiveness for the proposed control scheme.     

Three-phase four-wire shunt active power filter based on the SOGI filter and Lyapunov function for DC bus control

The three-phase four-wire shunt active power filter (SAPF) was developed to suppress the harmonic currents generated by nonlinear loads, and for the compensation of unbalanced nonlinear load currents, reactive power, and the harmonic neutral current. In this work, we consider instantaneous reactive power theory (PQ theory) for reference current identification based on the following two algorithms: the classic low-pass filter (LPF) and the second-order generalized integrator (SOGI) filter. Furthermore, since an important process in SAPF control is the regulation of the DC bus voltage at the capacitor, a new controller based on the Lyapunov function is also proposed. A complete simulation of the resultant active filtering system confirms its validity, which uses the SOGI filter to extract the reference currents from the distorted line currents, compared with the traditional PQ theory based on LPF. In addition, the simulation performed also demonstrates the superiority of the proposed approach, for DC bus voltage control based on the Lyapunov function, compared with the traditional proportional-integral (PI) controller. Both novel approaches contribute towards an improvement in the overall performance of the system, which consists of a small rise and settling time, a very low or nonexistent overshoot, and the minimization of the total harmonic distortion (THD).     

Two-dimensional temperature distribution estimation for a cross-flow planar solid oxide fuel cell stack

The uniform temperature distribution of a cross-flow planar solid oxide fuel cell (SOFC) stack plays an essential role in stack thermal safety and electrical property. However, because of the strict requirements in stack sealing struture, it is hard to acquire the temperature inside the stack using thermal detection devices within an acceptable cost. Therefore, accurately estimating the two-dimensional (2-D) temperature distribution of the cross-flow stack is crucial for its thermal management. In this paper, Firstly, a 2-D mechanism model of a cross-flow planar SOFC stack is established. The stack is divided into 5*5 nodes along the gas flow directions, which can reflect the stack states with moderate computational burden. Then, experimental test data is utilized to modify and validate the stack model, guaranteeing the model accuracy as well as the reliability of model-based state estimator design. Finally, easily-measured stack inputs and outputs are selected, and a temperature distribution estimator combined with unscented kalman filter (UFK) approach is developed to achieve accurate and fast temperature distribution estimation of a cross-flow SOFC stack. Simulation results demonstrate that the UKF-based temperature distribution estimator can precisely and quickly achieve the temperature distribution estimation of the cross-flow stack under both static state and dynamic state changes and is applicable to cross-flow stacks with different size or cell number as well, the maximum estimated absolute error is less than 0.15 K with an absolute error rate of 0.015%, which indicates the developed estimator has good estimation performances.     

Neural network-based learning and estimation of battery state-of-charge: A comparison study between direct and indirect methodology

Faced with the ever-increasing urban environmental pollution, the electric vehicles (EVs) have received increasing attention in the automotive industry. Lithium-ion batteries, serving as electrochemical power storage, have been extensively used in EVs because of the lightweight, no local pollution and high power density. The increasing awareness on the safe operation and reliability of the battery requires an efficient battery management system (BMS), among the parameters monitored by which, state-of-charge (SOC) is critical in preventing overcharge, deep discharge, and irreversible damage. This article investigates the neural network (NN)-based modeling, learning, and estimation of SOC by comparing two different methodologies, that is, direct structure with SOC as network output and indirect structure with voltage as output. Firstly, the nonlinear autoregressive exogenous neural network (NARX-NN) is introduced, in which SOC is directly deemed as an NN output for learning and estimation. Secondly, a radial basis function (RBF)-based NN with unscented Kalman filter (RBFNN-UKF) is proposed, in which the terminal voltage is used as output. Instead, SOC is deemed as an internal state which would be estimated indirectly based on the feedback error of voltage. Experimental results demonstrate that both estimators can achieve accurate SOC estimation for regular cases, in spite of the inaccurate initial conditions. However, the direct NN structure is revealed as not capable of dealing with the cases with sensor bias, which, however, can be well accommodated in the indirect structure by extending the sensor bias as an augmented state. Benefiting from the uncertainty augmentation and feedback compensation, the indirect RBFNN-UKF shows superiority over the direct estimation in the practical experiments, depicting a promising prospect in the future onboard EV-BMS application.