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.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A steelmaking-continuous casting (SCC) scheduling problem is an example of complex hybrid flow shop scheduling problem (HFSSP) with a strong industrial background. This paper investigates the SCC scheduling problem that involves controllable processing times (CPT) with multiple objectives concerning the total waiting time, earliness/tardiness and adjusting cost. The SCC scheduling problem with CPT is seldom discussed in the existing literature. This study is motivated by the practical situation of a large integrated steel company in which the just-in-time (JIT) and cost-cutting production strategy have become a significant concern. To address this complex HFSSP, the scheduling problem is decomposed into two subproblems: a parallel machine scheduling problem (PMSP) in the last stage and an HFSSP in the upstream stages. First, a hybrid differential evolution (HDE) algorithm combined with a variable neighborhood decomposition search (VNDS) is proposed for the former subproblem. Second, an iterative backward list scheduling (IBLS) algorithm is presented to solve the latter subproblem. The effectiveness of this bi-layer optimization approach is verified by computational experiments on well-designed and real-world scheduling instances. This study provides a new perspective on modeling and solving practical SCC scheduling problems.     

Food packages and communication through typeface design: The exoticism of exotypes

Although widely used by brands to communicate an exotic origin, exotypes have never been studied in the marketing literature. This research presents the exotype family of typefaces and then uses semiotic models to examine its power to evoke foreign cultures. One experiment is conducted among 1718 questionnaire respondents in order to study consumer perceptions of six exotypes. The results show that exotypes are able to communicate a specific exotic origin, especially when the connoted meaning of the typeface is congruent with the denoted meaning of the text.     

Rapid crystallization of poly(ethylene 2,6-naphthalate) via aryl amide derivatives

ABSTRACT

A very small amount of aryl amide derivative (TMB-5) was used for nucleating Poly(ethylene 2,6-naphathalate) (PEN) by melt blending. The crystalline temperature, crystallinity, and nucleation efficiency of the composites were increased as a result of the addition of TMB-5. The half-time of crystallization decreased upon the addition of TMB-5 and the work required in folding polymer chains were reduced simultaneously in the polymer mixtures. The crystal size of the PEN/TMB-5 blends became smaller due to the increase of nucleation sites. The TMB-5 had no effect on the PEN crystal type. TMB-5 slightly increased the impact strength of PEN.     

An experimental approach to produce hydrogen and methane from food waste using catalyst

Anaerobic co-digestion of food waste, cow dung, and sludge solution is experimented in the presence of calcium peroxide (CaO₂) as the catalyst to produce hydrogen and methane as a source of renewable energy. The substrate to inoculum ratios (v/v) of 1:1(S1), 1:2(S2), 1:3(S3), 1:4(S4) and 1:5(S5) are investigated in separate fermentative and methanogenic reactors. The result from the fermentative reactors indicate maximum hydrogen concentration of 26.34% with cumulative yield of 114.1 mL/g total solid (TS) in S3 compared to the other samples. Methanogenic reaction shows the highest methane concentration of 54.13% in S3. The highest daily (average) and cumulative biogas yield of 5.36 mL/g TS and 201.9 mL/g TS respectively are identified in S3. A maximum carbon dioxide concentration of 63.11% is found in S1. Overall, the substrate to inoculum ratio of 1:3 is spotted to be optimal for effective hydrogen and methane production during the anaerobic co-digestion process.     

Enhanced bioactivity of Zanthoxylum schinifolium fermented extract: Anti-inflammatory,anti-bacterial,and anti-melanogenic activity

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Framework to manage multiple goals in community-based energy sharing network in smart grid

Smart grid has opened up a new role of “prosumer” in an energy value network, transforming many conventional energy consumers into prosumers, who not only generate green energy but also share the surplus with utilities and other consumers. The concept of a goal-oriented prosumer community group (PCG) has emerged recently as an effective way to fulfill sustainable energy exchange. Such community-based energy sharing networks comprise multiple irreconcilable objectives such as demand constraints, cost constraints, and income maximization. In many cases, one goal may be achievable only at the expense of other goals. This necessitates the development of an effective framework to manage the multiple goals and reduce the gap with their achievement levels. Therefore, in this research paper, an effective framework is developed to negotiate among the multiple goals and thus to define optimal mutual goals for each PCG in a more sustainable manner using multiple-criteria goal programming techniques. Simulation results are presented to illustrate how the methods work in practical situations, where each of the objective measure is given a target value and the unwanted deviations from this set are minimized in an achievement function.     

Multi-objective optimization of shield construction parameters based on random forests and NSGA-II

Metro shield construction will inevitably cause changes in the stress and strain state of the surrounding soil, resulting in stratum deformation and surface settlement (SS), which will seriously endanger the safety of nearby buildings, roads and underground pipe networks. Therefore, in the design and construction stage, optimizing the shield construction parameters (SCP) is the key to reducing the SS rate and increasing the safe driving speed (DS). However, optimization of existing SCP are challenged by the need to construct a unified multiobjective model for optimization that are efficient, convenient, and widely applicable. This paper innovatively proposes a hybrid intelligence framework that combines random forest (RF) and non-dominant classification genetic algorithm II (NSGA-II), which overcomes the shortcomings of time-consuming and high cost for the establishment and verification of traditional prediction models. First, RF is used to rank the importance of 10 influencing factors, and the nonlinear mapping relationship between the main SCP and the two objectives is constructed as the fitness function of the NSGA-II algorithm. Second, a multiobjective optimization framework for RF-NSGA-II is established, based on which the optimal Pareto front is calculated, and reasonable optimized control ranges for the SCP are obtained. Finally, a case study in the Wuhan Rail Transit Line 6 project is examined. The results show that the SS is reduced by 12.5% and the DS is increased by 2.5% with the proposed framework. Meanwhile, the prediction results are compared with the back-propagation neural network (BPNN), support vector machine (SVM), and gradient boosting decision tree (GBDT). The findings indicate that the RF-NSGA-II framework can not only meet the requirements of SS and DS calculation, but also used as a support tool for real-time optimization and control of SCP.     

AHP-based procedure for optimization of microwave-assisted blackberry sugar osmotic process

Due to the limitations of single index analysis, the merits and demerits of microwave-assisted permeation process cannot be comprehensively evaluated. However, the analytical hierarchy process (AHP) was applied to optimize the conditions of microwave-assisted diffusion of sugar in blackberry. In this paper, the results of a single-factor experiment were compared with blackberry preserved after the treatment of microwave. An orthogonal rotation test procedure was designed to calculate the composite score of preserved blackberry fruit using AHP, and to determine the optimum processing conditions based on sugar osmosis characteristics. The results showed that the sugar content, vitamin C (VC) content, and color difference of treated blackberry increased with the increase of microwave power, the residence time, and the resulting sugar concentration. The composite grade points are listed to show that the optimum results were as follows: power level, the residence time, and the sugar concentration were, respectively, 210?W, 12?min, and 35%.