Diagnosis of attention deficit hyperactivity disorder using non‐linear analysis of the EEG signal

Attention deficit hyperactivity disorder (ADHD) is a common behavioural disorder that may be found in 5%–8% of the children. Early diagnosis of ADHD is crucial for treating the disease and reducing its harmful effects on education, employment, relationships, and life quality. On the other hand, non‐linear analysis methods are widely applied in processing the electroencephalogram (EEG) signals. It has been proved that the brain neuronal activity and its related EEG signals have chaotic behaviour. Hence, chaotic indices can be employed to classify the EEG signals. In this study, a new approach is proposed based on the combination of some non‐linear features to distinguish ADHD from normal children. Lyapunov exponent, fractal dimension, correlation dimension and sample, fuzzy and approximate entropies are the non‐linear extracted features. For computing, the chaotic time series of obtained EEG in the brain frontal lobe (FP1, FP2, F3, F4, and Fz) need to be analysed. Experiments on a set of EEG signal obtained from 50 ADHD and 26 normal cases yielded a sensitivity, specificity, and accuracy of 98, 92.31, and 96.05%, respectively. The obtained accuracy provides a significant improvement in comparison to the other similar studies in identifying and classifying children with ADHD.Inspec keywords: feature extraction, time series, fractals, electroencephalography, medical disorders, neurophysiology, medical signal processing, entropy, signal classification, Lyapunov methodsOther keywords: nonlinear extracted features, chaotic time series, identifying classifying children, attention deficit hyperactivity disorder, nonlinear analysis methods, electroencephalogram signals, brain neuronal activity, chaotic behaviour, chaotic indices, EEG signals, nonlinear features, approximate entropies, common behavioural disorder, early diagnosis, life quality, ADHD     

Way forward in meeting energy challenges in Pakistan

In this review the energy potential of Pakistan from hydro, coal, wind, solar and nuclear sources has been discussed. The new projects that are being commissioned on coal, wind, solar, hydel and nuclear-based technologies have also been mentioned. The review has also explored the future prospects of the country’s energy requirements. Pakistan has potential to produce 100,000?MW of electricity from Thar coal for 20 years, 56,000?MW of hydroelectricity, 150,000?MW of wind energy and ～50,000?MW from solar sources. The coal-fired power generation is expected to 11,500?MW in period 2017–2019. The country is moving in the right direction to cater its energy needs. However, there is a need to find local and foreign investment in the country to meet high energy demands in the country in future.     

Comparison of chlorination and chloramination practices on microbial inactivation efficiencies within a scaled‐up water distribution network using central composite design

Disinfection practices reduce the incidence of water‐borne diseases but may result in formation of disinfection byproducts (DBPs) in raw water that are reported to be carcinogenic. Central composite design (CCD) was employed in the present study for optimization of disinfectant dose and contact time with the rationale to evaluate if an optimal balance could be achieved between minimal DBPs formation and effective microbial inactivation with either free or combined chlorine in treated water within a lab‐scale prototype network to simulate real water distribution network conditions. After a series of experimental runs based upon design of experiments (DoE) by CCD, dose was found to be the most significant factor (P < 0.01) in determining DBPs formation in both disinfectant’s applications. Where, contact time significantly (P < 0.01) affected bacterial inactivation in chlorination experiments, in contrast, dose was effective in chloramination experiments. Thus, it was concluded that the optimal balance may be achieved in the water networks with the help of multifactorial optimization when disinfectant dose was maintained near 3 mg/L as applied chlorine dose in both disinfection cases, while contact time was 62 and 155 min for chlorine and chloramine, respectively.     

FeGaB (25 nm)/Al2O3/FeGaB(25 nm)多层薄膜结构：氧化铝(Al2O3)厚度变化对静态与动态磁性能的影响

铁镓(FeGa)薄膜与其它软磁材料相比具有较大的磁致伸缩常数,在设计集成磁性传感器芯片中具有独特的优势,本文通过采用非磁性掺杂和多层膜方法来控制这种合金薄膜的磁学与电学性能参数。我们实验发现在掺杂一定量硼(B)元素后,厚度小于30 nm的FeGa薄膜顽力可以得到显著降低,而对于较厚薄膜在插入超薄Al2 O3中间层后软磁性能可以得到同样程度显著改善,同时饱和磁化(Ms)变化可忽略。对于我们制备的FeGaB (25 nm)/Al2O3(0.5 nm)/FeGaB(25 nm)多层膜,其易轴矫顽力可以小到0.98 Oe,电阻率与50nm单层FeGaB膜相比增加了1.5倍,同时具有吉赫兹高磁导率谱。样品微结构分析表明,磁性颗粒结晶质量和物理尺寸的减小对软磁性改善起到重要作用,另外我们也讨论分析了静磁相互作用和表面形貌对磁畴运动及矫顽力的影响。本文发展的掺杂与多层膜混合方案来来增强电磁性能的方法,也可应用于其他类型的软磁材料系统。     

Bridge condition modelling and prediction using dynamic Bayesian belief networks

The development of a condition-based deterioration modelling methodology at bridge group level using Bayesian belief network (BBN) is presented in this paper. BBN is an efficient tool to handle complex interdependencies within elements of engineering systems, by means of conditional probabilities specified on a fixed model structure. The advantages and limitations of the BBN for such applications are reviewed by analysing a sample group of masonry bridges on the UK railway infrastructure network. The proposed methodology is then extended to develop a time dependent deterioration model using a dynamic Bayesian network. The condition of elements within the selected sample of bridges and a set of conditional probabilities for static and time dependent variables, based on inspection experience, are used as input to the models to yield, in probabilistic terms, overall condition-based deterioration profiles for bridge groups. Sensitivity towards various input parameters, as well as underlying assumptions, on the point-in-time performance and the deterioration profile of the group are investigated. Together with results from ‘what if’ scenarios, the potential of the developed methodology is demonstrated in relation to the specification of structural health monitoring requirements and the prioritisation of maintenance intervention activities.     

Wheat gluten: high molecular weight glutenin subunits--structure, genetics, and relation to dough elasticity

ABSTRACT:  Gluten proteins, representing the major protein fraction of the starchy endosperm, are predominantly responsible for the unique position of wheat amongst cereals. These form a continuous proteinaceous matrix in the cells of the mature dry grain and form a continuous viscoelastic network during the mixing process of dough development. These viscoelastic properties underline the utilization of wheat to prepare bread and other wheat flour based foodstuffs. One group of gluten proteins is glutenin, which consists of high molecular weight (HMW) and low molecular weight (LMW) subunits. The HMW glutenin subunits (HMW-GS) are particularly important for determining dough elasticity. The common wheat possesses 3 to 5 HMW subunits encoded at the Glu-1 loci on the long arms of group 1 chromosomes (1A, 1B, and 1D). The presence of certain HMW subunits is positively correlated with good bread-making quality. Glutamine-rich repetitive sequences that comprise the central part of the HMW subunits are actually responsible for the elastic properties due to extensive arrays of interchain hydrogen bonds. Genetic engineering can be used to manipulate the amount and composition of the HMW subunits, leading to either increased dough strength or more drastic changes in gluten structure and properties.     

Design and testing of varying magnetic field effect in a pulsatility blood flow of viscoelastic material: Flexibility analysis in a curved channel

This paper attempts to investigate the peristaltic mechanism of Williamson fluid in a pipe flow under the influence of variable radial magnetic field along with slip effects and compliant walls. Viscous dissipation and thermophoresis effects are also considered. The solutions of coupled nonlinear ordinary differential equations are obtained using the perturbation technique and results are graphically represented. The effects on heat, mass, velocity, and heat transfer coefficient are studied under various pertinent parameters. The outcomes of the present model can be applied in various fields of biomedical engineering where smart peristaltic pumps can be engineered to transport the biological fluids without any contamination. The scope of the present article is valuable in explaining the blood transport dynamics in small vessels while considering the important wall features with chemical reaction characteristics.     

Quadrature rules for numerical integration based on Haar wavelets and hybrid functions

In this paper Haar wavelets and hybrid functions have been applied for numerical solution of double and triple integrals with variable limits of integration. This approach is the generalization and improvement of the methods (Siraj-ul-Islam et al. (2010) [9]) where the numerical methods are only applicable to the integrals with constant limits. Apart from generalization of the methods [9], the new approach has two major advantages over the classical methods based on quadrature rule: (i) No need of finding optimum weights as the wavelet and hybrid coefficients serve the purpose of optimal weights automatically (ii) Mesh points of the wavelets algorithm are used as nodal values instead of considering the n nodes as unknown roots of polynomial of degree n. The new methods are more efficient. The novel methods are compared with existing methods and applied to a number of benchmark problems. Accuracy of the methods are measured in terms of absolute errors.