This study aims at investigating the impact of globalization on CO₂ emission in Vietnam. Empirical analysis is performed by employing autoregressed distributed lag approach on time series data for the period of 1990 to 2016. The paper tested the stationary, cointegration of time series data and utilized autoregressed distributed lag modeling technique to determine the short run and long run relationship among CO2 emission, globalization, foreign direct investment, exports, coal consumption per capita and fossil fuels electricity generation. The results show that globalization increases CO₂ emission in Vietnam and thus globalization is not beneficial for the long-term environmental health. Exports lowers CO₂ emissions in both short run and long run whereas coal consumption per capita and fossil fuels electricity generation raise CO₂ emissions. The study further shows that foreign direct investment did not affect CO₂ emissions directly in short run as well as in long run.

Construction emissions have become a major concern that has risen extensively in the last few decades. This paper introduces a building information modeling (BIM)-based model to evaluate the environmental and economic consequences of different project alternatives. The model calculates direct, indirect emissions and primary energy for the overall project life cycle. A hybrid fuzzy multi-objective non-dominated sorting genetic algorithm II (NSGA-II) problem is designed to model the uncertainties associated with the quantification of the judging attributes, and consequently to find the most sustainable materials by minimizing the objective functions; project duration, project life cycle cost, project overall emissions and total project primary energy. Finally, TOPSIS is applied to select the most sustainable material for each construction component among the set of Pareto optimal solutions. A case study of an academic building in Saudi Arabia is presented in order to exemplify the practical features of the proposed model.

A series of novel 10-phenylsulfonyl-2-substituted-4,10 dihydrobenzo[4,5]imidazo[1,2-a]pyrimidin-4-one derivatives obtained from N-sulfonation of 2-substituted-pyrimido[1,2-a]benzimidazol-4(10H)-ones and screened for for their in vitro anti-tuberculosis activities against Mycobacterium tuberculosis H37Rv by Microplate Alamar Blue Assay (MABA) method. The structures were established on the basis of their IR, ¹H-NMR, ¹³C-NMR, ESI-MS data and also the compound with 3f were crystallized and analysed by single crystal X-ray diffraction studies.

In this work, the Fe₃O₄@SiO₂@AMBI/Cu nanocatalyst was synthesized and used as a well-organized magnetic nanocatalyst for the click reaction. This nanocatalyst has effectively catalyzed the cyclization of terminal alkynes and sodium azide with aryl iodide/benzyl halide for the formation of 1,4-disubstituted 1,2,3-triazoles under mild reaction conditions with good to high yields in low reaction time.

Two heterocyclic Schiff bases namely (E)-2-(1-(2-phenylhydrazono)ethyl)pyridine (or 2-acetyl pyridine phenyl hydrazone) (2APPH) and (E)-2-(1-triazylidineethyl)pyridine (or 2-acetyl pyridine semicarbazone) (2APSC) were synthesized, characterized and their corrosion inhibition behaviour as well as mechanism of inhibition were investigated by different techniques. Structural characterization includes NMR, Mass, IR and UV-visible spectroscopy and elemental analysis. Corrosion inhibition behaviour of aforesaid compounds on mild steel in 1M hydrochloric acid was examined by electrochemical methods including potentiodynamic polarization analysis and electrochemical impedance spectroscopic techniques. The mechanism of corrosion inhibition was explored and supplemented by adsorption and surface morphological studies. Quantum mechanical investigations on corrosion behaviour of compounds were also conducted and satisfying correlation was noticed between the results of corrosion measurement methods and quantum mechanical evaluations.

Deciding conceptual stage of engineering design to identify an optimal design concept from a set of alternatives is a task of great interest for manufacturers because it has an impact on profitability of the manufacturing firms in terms of extending product demand life cycle and gaining more market share. To achieve this task, design concepts encompassing all required attributes are developed and the decision is made on the optimal design concept. This article proposes the modeling of decision making in the conceptual design stage of a product as a multi-criteria decision making analysis. The proposition is based on the fact that the design concepts can be decided based on considering the available design features and various sub-features under each design feature. Pairwise comparison matrix of fuzzy analytic hierarchy process is applied to determine the weights for all design features and their sub-features depending on the importance to the design features to the optimal design and contributions of the sub-features to the performance of the main design features. Fuzzified Pugh matrices are developed for assessing the availability of the sub-features in the design concept. The cumulative from the Pugh matrices produced a pairwise comparison matrix for the design features from which the design concepts are ranked using a minimum degree of possibility. The result obtained show that the decision process did not arbitrarily apportion weights to the design concepts because of the moderate differences in the final weights.

Indolylimidazole compounds that contain both indole and imidazole rings have shown various biological and pharmacological activities. These indolylimidazole compounds have been synthesized and extracted from the plants. In this paper, we have reviewed biological activities of natural and synthesized indolylimidazoles and their various synthetic methods. In recent time, the substituted indolylimidazole derivatives have synthesized and reported in the presence of different kind of the catalysts such as strong protic acid HNO₃@nano SiO₂, Zn²⁺@KSF and acetic acid and Amberlyst A-15. This review paper is divided into two categories bases on bioactivities of natural and synthesized indolylimidazole derivatives.

The rule based categorization approaches such as associative classification have the capability to produce classifiers rival to those learned by traditional categorization approaches such as Naïve Bayes and K-nearest Neighbor. However, the lack of useful discovery and usage of categorization rules are the major challenges of rule based approaches and their performance is declined with large set of rules. Genetic Algorithm (GA) is effective to reduce the high dimensionality and improve categorization performance. However, the usage of GA in most researches is limited in the categorization preprocessing stage and its results is used to simplify the categorization process performed by other categorization algorithms. This paper proposed a hybrid GA rule based categorization method, named genetic algorithm rule based categorization (GARC), to enhance the accuracy of categorization rules and to produce accurate classifier for text mining. The GARC consists of three main stages; namely, search space determination, rule discovery with validation (rule generation), and categorization. The experimental results are carried out on three Arabic text datasets with multiple categories to evaluate the efficiency of GARC. The results show that a promising performance was achieved by using GARC for Arabic text categorization. The GARC achieves the best performance with small feature space in most situations.

Clustering is one of the most common unsupervised data mining classification techniques for splitting objects into a set of meaningful groups. However, the traditional k-means algorithm is not applicable to retrieve useful information / clusters, particularly when there is an overwhelming growth of multidimensional data. Therefore, it is necessary to introduce a new strategy to determine the optimal number of clusters. To improve the clustering task on high dimensional data sets, the distance based k-means algorithm is proposed. The proposed algorithm is tested using eighteen sets of normal and non-normal multivariate simulation data under various combinations. Evidence gathered from the simulation reveal that the proposed algorithm is capable of identifying the exact number of clusters.

O-Acyl substituted derivatives of 3-benzyl-5-(2-hydroxyethyl)-4-methyl-1,3-thiazolium chloride which is a structural analog of vitamin B₁ were synthesized and evaluated towards acetylcholinesterase and butyrylcholinesterase in vitro. The inhibition properties of the O-substituted compounds depend on nature of substituents at position 3 and 5 of the thiazolium ring. Some of the thiazolium salts showed high potency in the inhibition of only one of the two enzymes. The selective effects of these inhibitors are governed by substituent at position 5. Kinetic studies and molecular docking simulation were performed for elucidating mechanisms of enzyme-inhibitor complex formation.