Abstract Peak ground acceleration (PGA) is frequently used to describe ground motions accurately to defined the zone is critical for structural engineering design. This study developed a novel models for predicting the PGA using Artificial Neural Networks-Gravitational Search Algorithm (ANN-GSA) and Response Surface Methodology (RSM). This paper grants the prediction of PGA for the seismotectonic of Iraq, which is considered the earlier attempt in Iraqi region. The magnitude of the earthquake, the average shear-wave velocity, the focal depth, the distance between the station, and the earthquake source were used in this study. The proposed models are constructed using a database of 187 previous ground motion records, this dataset is also utilized to evaluate the effect of PGA’s parameters. In general, the results demonstrate that the newly proposed models exhibit a high degree of correlation, perfect mean values, a low coefficient of variance, fewer errors, and an acceptable performance index value compared to actual PGA values. However, the composite ANN-GSA model performs better than the RSM model.

RESUMO: Este estudo contribui para a literatura existente sobre o nexo entre a produção de arroz, milho e trigo com produto interno bruto agrícola (AGDP) do Paquistão. Utilizamos dados de séries temporais de 1970 a 2017 e empregamos o modelo NARDL (Non-linear Autoregressive Distributed Lag). Choques de curto e longo prazo entre as variáveis selecionadas e os resultados são verificados por meio do modelo de co-integração e correção não linear de erros. É aplicada uma abordagem de teste de atraso retardado distribuído autorregressivo para co-integração e para encontrar a relação entre variáveis. Nossos resultados confirmam a co-integração; os resultados de choques positivos mostram que a produção de arroz, milho e trigo influencia significativamente na AGDP. Os choques assimétricos positivos de três culturas têm efeito neutro no AGDP. Enquanto nos resultados simétricos mostram o efeito unidirecional entre o arroz, a produção de milho com AGDP e a produção de trigo não têm causalidade de ganger com AGDP. Finalmente, os resultados mostram que a produção de trigo, milho e arroz contribui significativamente para o PIB agrícola no caso do Paquistão.

ABSTRACT: This study contributes to the extant literature on the nexus among rice, maize and wheat production with agriculture gross domestic product (AGDP) of Pakistan. We use time series data from 1970 to 2017 and employ the Non-linear Autoregressive Distributed Lag (NARDL) model. Short run and long run shocks between the selected variables and result’s is checked through the co-integration and nonlinear error correction model.Autoregressive distributed lag bound testing approach for co-integration and to find the relationship between variables Granger causality test is applied.Our results confirm co-integration, positive shocks results show that rice, maize and wheat production have significantly influence on AGDP. The asymmetrically positive shocks of three crops have neutral effect on AGDP. While in symmetric results show the unidirectional effect between rice, maize production with AGDP and wheat production do not have ganger causality with AGDP. Finally, results depict that wheat, maize and rice production significantly contributes to agricultural GDP in the case of Pakistan.

RESUMO: Este estudo contribui para a literatura existente sobre o nexo entre exportação agrícola, taxa de câmbio de importação e crescimento econômico no Paquistão. Utilizamos dados de séries temporais anuais para 1980-2017 e empregamos o modelo Não-linear Autoregressive Distributed Lag (NARDL). Os resultados dos testes NARDL afirmam a co-integração assimétrica entre as variáveis. Os principais resultados do estudo mostram: (i) no teste de co-integração de longo prazo, os choques positivos nas exportações e importações têm uma significância positiva, enquanto a taxa de câmbio afeta positivamente o crescimento econômico; (ii) Teste de co-integração para curto prazo, os choques positivos nas importações são positivos significativos e, enquanto a exportação e a taxa de câmbio têm um efeito negativo significativo no crescimento econômico. Os resultados simétricos mostram: (i) a exportação tem causalidade unidirecional sobre o crescimento ; (ii) a taxa de câmbio tem causalidade bidirecional sobre o crescimento ; (iii) a importação não tem causalidade sobre o crescimento econômico. Além disso, os resultados demonstraram que a relação de causalidade pode ajudar o formulador de políticas a elaborar políticas úteis ao crescimento econômico do Paquistão, o que poderia promover ainda mais o comércio exterior para obter o nível máximo de crescimento econômico.

ABSTRACT: This study contributes to the extant literature on the nexus among agriculture export, import exchange rate and economic growth in Pakistan. We used annual time series data for 1980-2017 and employ the Non-linear Autoregressive Distributed Lag (NARDL) model. The NARDL testing results affirms asymmetric co-integration among the variables. The study main results show: (i) Co-integration test for long run the positive shocks in export and import have positive significant while exchange rate has positive effect the economic growth. (ii) Co-integration test for short run the positive shocks in import has positive significant and while Export and exchange rate have negative significant effect on economic growth. The symmetrical results show: (i) Export has unidirectional granger causality (ii) Exchange rate has bidirectional granger causality (iii) Import has not ganger causality with economic growth. In addition, the results demonstrated that causality relationship can help out policy maker to design such policies which are useful to economic growth of Pakistan, which could further promote foreign trade to gain the maximum level of economic growth.

This work aims to synthesize composite material which combines adequate mechanical properties and high resistance to bacterial adhesion. Such materials are needed in many components in the medical, industrial, and environmental applications. To obtain that combination, high weight percents of anatase nanoparticles, as bacterial adhesion reducer, were incorporated into a matrix of the ABS terpolymer. Pseudomonas aeruginosa, Staphylococcus aureus, and Klebsiella pneumonia were selected for the bacterial adhesion tests. The surface properties of the composites were investigated and correlated to the adhesion behavior using nonlinear regression technique. It has been found that adding anatase nanoparticles improves the stiffness and the compressive strength of the terpolymer with a noticeable reduction in the flexural strength due to the development of minor defects in the structure. Nevertheless, a composite containing 10 wt% of anatase nanoparticles exhibited an interesting and adequate combination of the mechanical properties and the resistance to bacterial adhesion. The regression analysis produced a mathematical formula that excellently fits the experimental data. Such formula can be used to predict the bacterial adhesion to a surface based on its multi-scale features.

ABSTRACT The kinetics of the crystallization of cristobalite in the amorphous silica glass were studied for samples prepared by gel-casting and sintering in air. Avrami and rate equations were used to calculate the rate constants and the activation energy. The results showed that the crystallization obeys the first order and occurs mainly on the surface with activation energy of 543-546kJ/mol. The fewer amounts of OH-groups and the high amount of oxygen vacancies are expected to stand behind the increase in the activation energy as compared with that reported in literatures.