Numerical simulation of pressures in a radical system

The time-space location of an advancing front has been described in such a manner as to permit the calculation of frontal pressures when a heterogeneous (in permeability) radial system is subjected to water encroachment. A finite difference application has been developed to calculate these pressures at specified radial distances from the injection or production wellbore. These pressure have been further utilized to predict the pressures at the advancing front for different time intervals --Abstract, page iii

QUALITATIVE CHARACTERIZATION OF PHYTOCHEMICALS AND IN VITRO ANTIMICROBIAL EVALUATION OF LEAF EXTRACT OF COUROUPITA GUIANENSIS AUBL. - A THREATENED MEDICINAL TREE

Objective: Screening of phytochemicals present in aqueous extract and evaluation of the antibacterial and antifungal activities from different organic extracts of leaf of C. guianensis Aubl.Methods: Antimicrobial activity of different extracts was evaluated by using the disc diffusion assay. Methanolic, ethanolic and chloroform extracts of leaf were tested against fungus and representatives of Gram-positive and Gram-negative bacteria.Results: Presence of alkaloids, flavonoids, glycosides, phlobatannins, steroids, tannins and terpenoids was observed in aqueous extract of leaf. Chloroform extract showed better activity against Gram-positive bacteria in comparison to Gram-negative bacteria. Methanolic extract was more effective on Gram negative bacteria. Leaf extract was also effective against Candida species. Minimum inhibitory concentration was 25 mg/ml for ethanolic, 50 mg/ml for methanolic and 100 mg/ml for chloroform extracts against S. aureus. Conclusion: Present study of C. guianensis seems to be promising for pharmaceutical industries for making an antimicrobial drug or cream especially against S. aureus and provides details of pharmacological investigation, identification, isolation and characterization of novel bioactive compounds

IT Infusion and its Performance Impacts: An Empirical Analysis of eProcurement in the Service Industry

This paper examines the infusion of e-procurement applications along two dimensions of usage – intensity and organizational acceptance – and tests the relationship between use and procurement performance. Drawing upon the resource-based view of the firm, this paper tests the relationship between select organizational resources and e-procurement infusion in the context of procurement of indirect materials and services. The research model is estimated with survey data obtained on 193 organizations from the service sector. Data are analyzed using structural equation modeling. The results suggest that while organizational integration and business knowledge of IT managers are significantly related to only organizational acceptance of e-procurement, procurement process readiness and organizational slack resources are related to both the dimensions of e-procurement infusion. Our results also show that both dimensions of e-procurement infusion are positively related to procurement performance while their interaction effect on performance is negative. Theoretical and practical implications of these results are discussed

Anti-mycobacterial activity of Piper longum L. fruit extracts against multi drug resistant Mycobacterium Spp

A long tradition of using pepper as to fight against several ailments by the local tribal people is still in the practice, in many parts of the rural India. So utilizing this tribal knowledge base for this highly medicinal plant, an attempt was made to isolate some novel natural bioactive compounds with potential activity against multidrug resistant (MDR) Mycobacterium. A bioassay guided fractionation of Pippali (Piper longum L.) was performed in five different organic solvents and their activities were monitored against different pathogenic bacteria including MDR Mycobacterium. Different fractions were screened for the bioactivity against Mycobacterium, and the structure of bioactive compound was characterized with H1 and C13 NMR. An ethyl acetate fraction of Pippali extract was found active against M. smegmatis (3000µg ml-1) and M. tuberculosis (39 µg ml-1). It also shows very significant activity against other bacterial strains like E.coli (152 µg ml-1), Staphylococcus aureus (14 µg ml-1), Salmonella typhi (180 µg ml-1), Enterococcus faecalis (15 µg ml-1), and Pseudomonas aeruginosa (52 µg ml-1). This fraction of ethyl acetate was then purified and characterized as piperine [5-(1, 3-benzodioxol-5-yl)-1-piperidin-1-ylpenta-2,4-dien-1-one], a well known alkaloid from this plant. Bioactivity guided fractionation concludes that Piperine is the only active ingredients in various fractions of fruit extract evaluated for antibacterial activity. Fraction having piperine has significant activity against multi drug resistant strains of Mycobacterium spp. than other purified fractions of fruit extract. The current finding encourages us to develop new alternative medicine that includes piperine alone and/or in combination with other drugs to fight against the drug resistance among Mycobacterial strains.   

Incorporating a Machine Learning Model into a Web-Based Administrative Decision Support Tool for Predicting Workplace Absenteeism

Productivity losses caused by absenteeism at work cost U.S. employers billions of dollars each year. In addition, employers typically spend a considerable amount of time managing employees who perform poorly. By using predictive analytics and machine learning algorithms, organizations can make better decisions, thereby increasing organizational productivity, reducing costs, and im-proving efficiency. Thus, in this paper we propose hybrid optimization methods in order to find the most parsimonious model for absenteeism classification. We utilized data from a Brazilian courier company. In order to categorize absenteeism classes, we preprocessed the data, selected the attributes via multiple methods, balanced the dataset using the synthetic minority over-sampling method, and then employed four methods of machine learning classification: Support Vector Machine (SVM), Multinomial Logistic Regression (MLR), Artificial Neural Network (ANN), and Random Forest (RF). We selected the best model based on several validation scores, and compared its performance against the existing model. Furthermore, project managers may lack experience in machine learning, or may not have the time to spend developing machine learning algorithms. Thus, we propose a web-based interactive tool supported by cognitive analytics management (CAM) theory. The web-based decision tool enables managers to make more informed decisions, and can be used without any prior knowledge of machine learning. Understanding absenteeism patterns can assist managers in revising policies or creating new arrangements to reduce absences in the workplace, financial losses, and the probability of economic insolvency

In-vitro scolicidal activity of Mallotus philippinensis (Lam.) Muell Arg. fruit glandular hair extract against hydatid cyst Echinococcus granulosus

AbstractObjectiveTo investigate new scolicidal agent from natural resources to cope with the side effects associated with synthetic drugs in Echinococcosis.MethodsThe scolicidal potential of methanolic fruit powder extract (10 and 20 mg/mL) of Mallotus philippinensis (M. philippinensis) was investigated. Viability of protoscoleces was confirmed by trypan blue exclusion method, where mortality was observed at concentration of 10 and 20 mg/mL in 60 min treatment against Echinococcus granulosus (E. granulosus), under in-vitro conditions with reference to the known standard drug Praziquantel®.ResultsAt concentration 10 and 20 mg/mL, the mortality rate was observed 97% and 99% respectively for 60 min treatment; while up to 93% mortality was observed with 20 mg/mL for only 10 min treatment. The concentration above 20 mg/mL for above 2 h showed 100% mortality, irrespective of further incubation.ConclusionsAs compared with the standard anti-parasitic drug Praziquantel our extract has significant scolicidal activity with almost no associated side effects

Incidence and predation rate of hornet (Vespa spp.) on European honeybee (Apis mellifera L.) apiary at mid-hill areas of Lalitpur district, Nepal

Predatory hornets are considered as one of the major constraints to beekeeping industry. Therefore, its incidence and predation rate was studied throughout the year at two locations- rural and forest areas of mid-hill in Laliptur district during 2016/017 to 2017/018. Observation was made on the number of hornet and honey bee captured by hornet in three different times of the day for three continuous minutes every fortnightly on five honeybee colonies. During the study period, major hornet species captured around the honeybee apiary at both locations were, Vespa velutina Lepeletier, Vespa basalis Smith, Vespa tropica (Linnaeus) and Vespa mandarina Smith. The hornet incidence varied significantly between the years and locations along with different observation dates. Their incidence and predation rates were low in early spring and summer that gradually increased with the highest peak in October and November in both locations. The maximum predation was on mid-November (62.07%) and early-November (53.49%) at rural and forest locations, respectively during 2016/017. In 2017/018, the highest predation was on early-November (70.27%) at rural area while it was in mid-November (58.62%) in the apiaries near the forest area. The population of hornet was considerably higher at forest areas and their incidence around the honeybee apiaries were negatively correlated with rainfall. Hence, assessment of the temporal and spatial population variations and predation rates along with weather parameters is helpful in to develop sustainable management plans of the hornet in apiary