Pharmaceutical-instigated pollution is a major concern, especially in relation to aquatic environments and drugs such as meropenem antibiotics. Adsorbents, such as multi-walled carbon nanotubes, offer potential as means of removing polluting meropenem antibiotics and other similar compounds from water. In order to evaluate the effectiveness of multi-walled carbon nanotubes in this capacity, various experimental parameters, including contact time, initial concentration, pH, temperature and the dose of adsorbent have been investigated. The Langmuir and the Freundlich isotherm models have been used. The data obtained using a modified Langmuir model have been consistent with the experimental ones; the best pH value has been obtained to have the maximum uptake capacity with the hights coefficient of determination. The adsorption kinetics data is in accordance with pseudo-second order model for adsorption processes, which is in line with the measured data. The results of this thermodynamic research indicate that the reaction that removes meropenem antibiotics from water by adsorption is exothermic. A combination of mechanisms is responsible for meropenem antibiotics adsorption to adsorbent, including electrostatic and π–π EDA interactions, hydrophobic interaction, functional groups and molecule substitution. According to the research findings, multi-walled carbon nanotubes offer a potential method that can be quickly deployed in order to address pharmaceutical contamination of water.
Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
... Show MoreResearchers dream of developing autonomous humanoid robots which behave/walk like a human being. Biped robots, although complex, have the greatest potential for use in human-centred environments such as the home or office. Studying biped robots is also important for understanding human locomotion and improving control strategies for prosthetic and orthotic limbs. Control systems of humans walking in cluttered environments are complex, however, and may involve multiple local controllers and commands from the cerebellum. Although biped robots have been of interest over the last four decades, no unified stability/balance criterion adopted for stabilization of miscellaneous walking/running modes of biped
The federal state is usually based on a number of regions because it is based on the multiplicity of political entities. The federal experiments were based on the existence of two or more regions and each federal system has its own peculiarities. Administrative authority between the federal government and local elected bodies of local people of absolute relative independence does not threaten the entity of the state according to the Constitution and the law and on a regional or reformer basis and exercise its powers within the legal scope prescribed The relationship between the federal authority and the Kurdistan region is the first level of the relationship on the real level, especially since no other region in Iraq has been formed exce
... Show MoreThis paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.
... Show MoreIt is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the
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