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The present study was designed to evaluate the hepatoprotective activity of ethanol extract of Punica granatum L. leaf in association with gallic acid in high-fat diet-induced animal model. Total 30 rats were used. These were divided into 5 groups of 6 animals each. Group 1 was given normal diet and was treated as the control. Group 2 was given a high-fat diet and was considered as a induced group. Groups 3, 4 and 5 were given high-fat diet along with ethanol extract of Punica granatum L. leaf (200 mg/kg), ethanol extract of Punica granatum L. leaf+gallic acid (100+10 mg/kg) and orlistat (22 mg/kg), which constituted the treatment groups. The total period of the study was 8 w. At the end of the study, activities of alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, total protein, albumin, globulin and albumin/globulin ratio were measured. The antioxidant defense activities like superoxide dismutase, catalase and reduced glutathione were analyzed together with lipid peroxidation in the liver tissue. In addition, histology of liver was examined. The high-fat diet caused alternation in the activities of markers of liver function along with changes in histology of the liver. The high-fat diet increased lipid peroxidation and decreased antioxidant defense system. The alterations induced by the high-fat diet were restored more effectively by the ethanol extract of Punica granatum L. leaf+gallic acid than the ethanol extract of Punica granatum L. leaf alone or orlistat.

The present communication attempts to study the antimicrobial activity of successive extraction using n-hexane, chloroform, ethyl acetate, alcohol and separate aqueous extract from whole plant of Ruellia tuberosa L. against different bacterial and fungal organisms (ATCC , MTC) using disc diffusion method. The chloroform, ethyl acetate, alcohol and aqueous extracts were active against all the bacteria tested and showed significant antibacterial properties. The aqueous extract exhibited less activity against fungal organisms. Thus it may be informed that Ruellia tuberosa L. extract may be used to treat oral bacterial diseases.

Ruellia tuberoa L. of Acanthaceae family is a Minnie root medicinal, tropical plant widely distributed in south East Asia. In folk medicine, it has been used as diuretic, antidiabetic, antipyretic, analgesic, anti-hypersensitive, thirst-quenching, and antidotal agent. Recently this plant has been incorporated as a component in an herbal drink in Taiwan. However a very few chemical constituents and pharmacological activities have been reported for this species. As there is no pharmacognostic work reported on whole plant, the present investigation attempts to undertake to study the pharmacognostical and preliminary phytochemical studies along with HPTLC, fingerprinting analysis for whole plant of Ruellia tuberosa L. Preliminary organic analysis revealed the presence of tannin, flavonoid, steroid, triterpnoid and phenol in different extracts respectively. Physiochemical studies revealed that total ash is 13.53%, acid insoluble ash is 2.36%, alcohol soluble extractive value is 7.67%, water soluble extractive value is 24.78% and loss on drying at 105°C is 11.29%. These specific identities will be useful in identification and authentication of the raw drug.

In this paper we consider workforce management in repair/maintenance environments in which repairmen are cross-trained to attend more than one type of machine. In this context, we study the machine-repairman problem with heterogeneous machines but with partially cross-trained repairmen. We introduce simple repairman-assignment rules as well as machine-priority rules that are effective in minimizing the machine downtime costs, or balancing the percentage of working machines of different types. We show that static machine priority rules are effective in minimizing systems downtime costs, while a generalized version of the longest queue policy is effective in balancing the percentage of working machines. We also introduce the concept of hidden symmetry in repair environments, and show that the well-known chain repairman skill set structure performs very well in repair environments with hidden symmetry. Finally, we provide insights into the design and control issues of repair/maintenance systems with cross-trained repairmen.

We consider a finite-population queueing system with heterogeneous classes of customers and a single server. For the case of nonpreemptive service, we fully characterize the structure of the server's optimal service policy that minimizes the total average customer waiting costs. We show that the optimal service policy may never serve some classes of customers. For those classes that are served, we show that the optimal service policy is a simple static priority policy. We also derive sufficient conditions that determine the optimal priority sequence.

Chemical process plant decision making is ongoing during operation based upon availability both of components and of the entire system. These decisions include repair policies, maintenance strategies, and inspection routines. The industry state-of-the-art in availability analysis is a Petri Net simulation. It produces confidence intervals on availabilities. In this paper, we present an alternative – generic Markov models. Our models produce exact results in the case of exponential failure and repair times, are at least as easy to use during model building, and reduce computational effort by orders of magnitude. A case study of a reactor regenerator system in a Fluid Catalytic Cracking Unit in a petroleum refinery is presented. Scope and purpose We needed to estimate the availability of a complex system of machinery in an oil refinery in India. Availability is defined as the fraction of time a system performs its specified functions under stated conditions of use and maintenance, and is not easy to calculate. Currently, the best methodology in the field for modeling this type of problem is called Petri nets. As we began the study, we saw similar types of failure modes occurring in many different system components. Further, we found that Petri nets, for our problem, took a lot of computer time yet generated only a subset of the numbers that we needed. We therefore invented a methodology of our own, which we call generic Markov chains, that can be used like building blocks to build precisely the models that industry needs. The models run orders of magnitude faster, are easier to build, and give us a fuller range of performance measures.