of syphilis infection was found in 6.0% of respondents, while prevalence rates of gonorrhea were 1.7% (Sabin et al. 2003). Though statistics are not available for STDs in the rural areas of Bangladesh and among ethnic or tribal minority groups of the country, the prevalence of traditional medicinal practitioners dispensing medications for such diseases suggests that many in the rural population are also infected by STDs.Major contributing factors for high levels of urinary tract infections (UTIs) in predominantly rural Bangladesh are poor sanitary conditions and lack of proper hygiene. One of the most common UTIs is leucorrhea among women, characterized by a whitish discharge from female genitalia. In one recent study, the most frequently discovered microorganisms found to cause leucorrhea includ- AbstractThe rural population of Bangladesh has traditionally depended on folk medicinal healers for treatment of their ailments. These healers use medicinal plants as their primary source of medicinal formulations. Rural patients are more dependent on traditional or folk medicinal healers for treatment of urinary tract infections (UTIs) and sexually transmitted diseases (STDs) for a number of reasons including lack of access to modern medical facilities, clinging to traditional approaches, and finally hesitancy to relate this form of illnesses in front of unknown doctors. Since the traditional healer usually resides in the same village or in an adjoining area, the patient is more comfortable in seeking them for treatment. We conducted an ethnomedicinal survey among the traditional healers of various ethnic groups and in several regions of the country to obtain information on medicinal plants used to treat UTIs and STDs. Interviews were conducted in the local dialect or language about plant parts used, ailments treated, formulations, and dosages. Thirty-one species were reported by traditional healers as being used for UTIs, including leucorrhea, frequent or infrequent urination, cloudy urination and burning sensations during urination. Ten species were reported to be used against STDs like syphilis and gonorrhea.

Many companies like credit card, insurance, bank, retail industry require direct marketing. Data mining can help those institutes to set marketing goal. Data mining techniques have good prospects in their target audiences and improve the likelihood of response. In this work we have investigated two data mining techniques: the Naïve Bayes and the C4.5 decision tree algorithms. The goal of this work is to predict whether a client will subscribe a term deposit. We also made comparative study of performance of those two algorithms. Publicly available UCI data is used to train and test the performance of the algorithms. Besides, we extract actionable knowledge from decision tree that focuses to take interesting and important decision in business area.

Extracts in organic solvents (namely methanol, ethanol, ethyl acetate and chloroform) of two medicinal plants -Achyranthes aspera and Cassia alata were evaluated for their antibacterial activities against Escherichia coli, Bacillus subtilis, Vibrio cholerae, Salmonella typhi and Staphylococcus aureus. These were carried out by taking the organic extracts of both the leaf and stem parts of the plants at a concentration of 5 mg/ml and their activities were recorded by estimating zones of inhibition as produced by disc-diffusion method on Mueller-Hinton agar media. While neither the leaf nor stem parts of A. aspera in any organic extractions showed antibacterial activity, the methanolic extracts of both the leaf and stem parts of C. alata exhibited antibacterial activity, but only to B. subtilis and S. typhi, and the corresponding MIC values of the leaf extracts were estimated as 1.25 and 1.5 mg/ml respectively. However, the ethanolic extracts of both the stem and leaf parts were found equally effective only to S. aureus (MIC= 1.25 mg/ml). The corresponding MBC values are reported.

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.

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