Effect of Caparis spinosa root extract on promastigotes and amastigotes of Leishmania major

This study was carried out to identify the efficacy of Caparis spinosa root extract on promastigotes and amastigotes of Leishmania major. Caparis spinosa extracts were prepared. Promastogotes of  L.major (1×106 parasites/ml)were incubated at 26 ºC for 24,48 and 72hours in fresh medium(NNN), in absence or presence of different concentrations (0.1,0.3,0.5,0.7,0.9 mg/ml) of Caparis spinosa methanolic root extract. It was determined that anti-protozoal activity of Caparis extract (0.9 mg/ml) was similar to glucantime as a gold standard drug (p<0.05) and both were able to kill 97.8 % of promastigotes after72 hours. Microscopic observation showed that mainly complete lyses of promastigotes after treating with0.9 mg/ml of Caparis spinosa for72hours. Higher extract concentrations had more effect on promastigote population (p<0.05). It was demonstrated that Caparis sponosa root extract has positive effect on amastigotes of leishmania major. It was determined 0.7 mg/ml and 0.9 mg/ml Caparis root extract concentrations were more effective than other concentrations on amastigots of Leishmania in ulcers. The mean of ulcer size of the mice that received 50 µl of 0.7 mg/ml and 0.9 mg/ml Caparis root extract were less than mice receiving 0.1, 0.3 and 0.5. The mean of ulcer size of the mice that received 50 µl of 0.9 mg/ml Caparis spinosa root extract were significantly smaller than control group after six weeks(p<0.05) ,but the mean of ulcer size in mice which had been received glucantime (150 mg/ml)and Caparis root extract were not  significantly different (p>0.05). The results were suggestive that Caparis root extract had significantly similar effect in reduction of ulcer size as compared to glucantime (p<0.05).

Application of synthetic polymers as adsorbents for the removal of cadmium from aqueous solutions: batch experimental studies

In the present study seven synthetic polymers were used as adsorbents for the removal of Cd(II) from aqueous solution. The equilibrium studies were systematically carried out in a batch process, covering various process parameters that include agitation time, adsorbent dosage, and pH of the aqueous solution.The analyzing system was an atomic absorption spectrometer (Perkin-Analyst 100). It was observed in adsorption and desorption tests that synthetic polymers showed significant pH dependence, which affected the removal efficiency, robustly. Adsorption behavior was found to follow Freundlich and Longmuir isotherms. A regeneration study was also carried out

CEIoT: A Framework for Interlinking Smart Things in the Internet of Things

In the emerging Internet of Things (IoT) environment, things are interconnected but not interlinked. Interlinking relevant things offers great opportunities to discover implicit relationships and enable potential interactions among things. To achieve this goal, implicit correlations between things need to be discovered. However, little work has been done on this important direction and the lack of correlation discovery has inevitably limited the power of interlinking things in IoT. With the rapidly growing number of things that are connected to the Internet, there are increasing needs for correlations formation and discovery so as to support interlinking relevant things together effectively. In this paper, we propose a novel approach based on Multi-Agent Systems (MAS) architecture to extract correlations between smart things. Our MAS system is able to identify correlations on demand due to the autonomous behaviors of object agents. Specifically, we introduce a novel open-sourced framework, namely CEIoT, to extract correlations in the context of IoT. Based on the attributes of things our IoT dataset, we identify three types of correlations in our system and propose a new approach to extract and represent the correlations between things. We implement our architecture using Java Agent Development Framework (JADE) and conduct experimental studies on both synthetic and real-world datasets. The results demonstrate that our approach can extract the correlations at a much higher speed than the naive pairwise computation method

Batch matching of conjunctive triple patterns over linked data streams in the internet of things

The Internet of Things (IoT) envisions smart objects col lecting and sharing data at a global scale via the Internet. One challenging issue is how to disseminate data to relevant consumers efficiently. This paper leverages semantic technologies, such as Linked Data, which can facilitate machine- to-machine (M2M) communications to build an efficient information dissemination system for semantic IoT. The system integrates Linked Data streams generated from various data collectors and disseminates matched data to relevant data consumers based on conjunctive triple pattern queries registered in the system by the consumers. We also design a new data structure, CTP-automata, to meet the high performance needs of Linked Data dissemination. We evaluate our system using a real-world dataset generated from a Smart Building Project. With CTP-automata, the proposed system can disseminate Linked Data at a speed of an order of magnitude faster than the existing approach with thousands of registered conjunctive queries.Yongrui Qin, Quan Z. Sheng, Nickolas J.G. Falkner, Ali Shemshadi, Edward Curr

SECF: Improving SPARQL Querying Performance with Proactive Fetching and Caching

Querying on SPARQL endpoints may be unsatisfactory due to high latency of connections to the endpoints. Caching is an important way to accelerate the query response speed. In this paper, we propose SPARQL Endpoint Caching Framework (SECF), a client-side caching framework for this purpose. In particular, we prefetch and cache the results of similar queries to recently cached query aiming to improve the overall querying performance. The similarity between queries are calculated via an improved Graph Edit Distance (GED) function. We also adapt a smoothing method to implement the cache replacement. The empirical evaluations on real world queries show that our approach has great potential to enhance the cache hit rate and accelerate the querying speed on SPARQL endpoints

Epidemiological Aspects of Canine Dirofilariasis in the North of Iran

Background: Dirofilaria immitis is an important parasite in dog and other carnivores. Our objec­tive was study on incidence and periodicity of heartworm in north of Iran and using other meth­ods for its diagnosis in addition to Parasitology exam.Methods: This survey spanned two years, between 2006 and 2008. Blood samples were collected from 431 stray dogs distributed along north of Iran, the coastal areas of the Caspian Sea. The Knott's modified test was used for diagnosis of D. immitis and other filariae. Meanwhile, the periodic­ity of microfilaria in peripheral blood circulation was calculated and the imaging diagno­sis techniques of four dogs that had positive results were done.Result: Diagnostic parasitology results indicated that 16.01% of stray dogs were microfilaremic. Two different microfilariae were diagnosed: D. immitis in 13.69%, Dipetalonema reconditum in 1.86% and in 0.46% both of them. There was no statistically significant between infection to fiariae with sex and age of dogs. Also study on the periodicity of the presence of microfilaria in peripheral circulation showed that the highest rate of those was at 1 am and the lowest rate at 12 pm. Radiographic study showed distinctive signs with varied degrees of severity included: Tortu­ous and enlargement of main and lobar pulmonary artery, pulmonary parenchymal lesions and Right side heart enlargement that confirmed in electrocardiography. Also in echocardiographic images observed short parallel-sided images with the appearance of equal signs that indicated the pres­ence of the heartworm.Conclusion: These results showed that to obtain a reliable diagnosis of heartworm infection, imag­ing tests could support parasitological exams

A Learning Based Framework for Improving Querying on Web Interfaces of Curated Knowledge Bases

Knowledge Bases (KBs) are widely used as one of the fundamental components in Semantic Web applications as they provide facts and relationships that can be automatically understood by machines. Curated knowledge bases usually use Resource Description Framework (RDF) as the data representation model. To query the RDF-presented knowledge in curated KBs, Web interfaces are built via SPARQL Endpoints. Currently, querying SPARQL Endpoints has problems like network instability and latency, which affect the query efficiency. To address these issues, we propose a client-side caching framework, SPARQL Endpoint Caching Framework (SECF), aiming at accelerating the overall querying speed over SPARQL Endpoints. SECF identifies the potential issued queries by leveraging the querying patterns learned from clients’ historical queries and prefecthes/caches these queries. In particular, we develop a distance function based on graph edit distance to measure the similarity of SPARQL queries. We propose a feature modelling method to transform SPARQL queries to vector representation that are fed into machine-learning algorithms. A time-aware smoothing-based method, Modified Simple Exponential Smoothing (MSES), is developed for cache replacement. Extensive experiments performed on real-world queries showcase the effectiveness of our approach, which outperforms the state-of-the-art work in terms of the overall querying speed