Formulation and Evaluation of Bilayer Tablet by Wet Granulation

ABSTRACT: The objective of this present study was to design bilayer tablet of two different drugs for separate release, evaluation of the same and comparison dry granulation formulation with minor changes in components. Both layer of bilayer tablets comprised control release. In wet granulation different type and amount of polymer were used for each layer. The formulated bilayer tablets were evaluated for pre compression as well as post compression parameters including invitro_dissolution_study were carried out. The results showed that wet granulation of formulated bilayer tablet carried out with different polymers viz. Gum acacia, Guar gum, Acrypol -971, HPMC_ K100M, eudragit_RSPO was carried out and based on its release retarding properties. Based on drug release and release kinetics study final formulation was selected that was further analysed for stability study. The accelerated stability study for 6 month showed affirmative result

An unexpected supraclavicular swelling

<p>Abstract</p> <p>Background</p> <p>Colorectal cancer is the third commonest cause of cancer death in UK. It commonly metastasises to the liver but rarely to small bones.</p> <p>Case presentation</p> <p>We describe a case of a patient with adenocarcinoma of the descending colon who presented preoperatively with a right supraclavicular swelling. Subsequent imaging and cytology of the lesion revealed this to be a metastasis to the right clavicle resulting in a pathological fracture.</p> <p>Conclusion</p> <p>This report describes the rare occurrence of a colorectal metastasis to the clavicle. It emphasises that although bone metastases from primary colorectal tumours are rare events, they tend to metastasise to small, non-weight bearing bones. It also discusses the utility of isotope bone scanning and that on certain occasions this imaging method may prove to be equivocal. In such circumstances, biopsy or magnetic resonance imaging is more sensitive for the detection of bone metastases.</p

Design and Application of Distributed Economic Model Predictive Control for Large-Scale Building Temperature Regulation

Although recent research has suggested model predictive control as a promising solution for minimizing energy costs of commercial buildings, advanced control systems have not been widely deployed in practice. Large-scale implementations, including industrial complexes and university campuses, may contain thousands of air handler units each serving a multiplicity of zones. A single centralized control system for these applications is not desirable. In this paper, we propose a distributed control system to economically optimize temperature regulation for large-scale commercial building applications. The decomposition strategy considers the complexities of thermal energy storage, zone interactions, and chiller plant equipment while remaining computationally tractable. One of the primary benefits of the proposed formulation is that the low-level airside problem can be decoupled and solved in a distributed manner; hence, it can be easily extended to handle large applications. Peak demand charges, a major source of coupling, are included. The interactions of the airside system with the waterside system are also considered, including discrete decisions, such as turning chillers on and off. To deploy such a control scheme, a system model is required. Since using physical knowledge about building models can greatly reduce the number of parameters that must be identified, grey-box models are recommended to reduce the length of expensive identification testing. We demonstrate the effectiveness of this control system architecture and identification procedure via simulation studies

An Economic Model Predictive Control Framework for Distributed Embedded Battery Applications

Since building heating, ventilation, and air conditioning (HVAC) systems are significant consumers of primary energy, considerable efforts are being made to improve energy efficiency and decrease energy costs in these applications. Notably, substantial opportunities in the area of HVAC control exist for decreasing energy costs by shifting loads from peak periods to off-peak periods in the presence of time-varying utility prices. This load shifting is also beneficial for power companies since it results in a more constant total load allowing them to operate more efficiently. Economic model predictive control (MPC) has been shown to significantly decrease the energy costs of commercial HVAC systems via load shifting. Typically, thermal energy storage (TES) is used for this purpose by running HVAC equipment at higher rates during periods of low power prices to charge TES and at lower rates during periods of higher prices while discharging TES to meet building demand loads. However, with batteries becoming less expensive to manufacture, electrical energy storage in batteries is becoming a viable option for load shifting. Batteries can be used for both load shifting to decrease costs and revenue generation if the incentives on the electricity market are appropriate. In this work, embedded battery applications are considered. In embedded battery applications, the batteries are directly packaged with airside equipment such as air handler units (AHUs), roof-top units (RTUs), and variable refrigerant flow systems (VRFs). In this arrangement, the batteries are accessible only to the local unit and not to other units. In this paper, we propose a hierarchical control system framework for the economic optimization of distributed embedded battery units. The architecture considers both building mass storage as well as the electrical energy storage of the battery units. A high-level problem performs an economic optimization over the entire system using aggregate models. The low-level layer is broken into subsystems, each optimizing its local decisions with higher fidelity models. Advantages of this framework include no iterative communication required between subsystems, decreased computational complexity in the high-level problem allowing for real-time online implementation, and management of total demand across the entire system to reduce peak demand charges. We conclude with a simulation study demonstrating the benefits of the proposed control architecture

A Case Study of Economic Optimization of HVAC Systems based on the Stanford University Campus Airside and Waterside Systems

Commercial buildings account for $200 billion per year in energy expenditures, with heating, ventilation, and air conditioning (HVAC) systems accounting for most of these costs. In energy markets with time-varying prices and peak demand charges, a significant potential for cost savings is provided by using thermal energy storage to shift energy loads. Since most implementations of HVAC control systems do not optimize energy costs, they have become a primary focus for new strategies aimed at economic optimization. Model predictive control (MPC) has emerged as one popular method to achieve this load shifting, while respecting system constraints. MPC uses a model of the system to make predictions and to solve an optimization problem. Much research has shown the benefits of MPC over alternative strategies for HVAC control [1]. However, some industrial applications, such as large research centers or university campuses, are too large to be solved in a single MPC instance. Decompositions have been proposed in the literature, but it is difficult to evaluate and to compare decompositions against one another when using different systems. In this paper, we present a large-scale relevant case study where solving a single MPC optimization problem is neither desirable nor feasible for real-time implementations. The study is modeled after the Stanford University campus, consisting of both an airside and waterside system [2]. The airside system includes 500 zones spread throughout 25 campus buildings along with the air handler units and regulatory building automation system used for temperature regulation. The waterside system includes the central plant equipment, such as chillers, that is used to meet the load from the buildings. Active thermal energy storage is available to the campus in addition to the passive thermal energy storage present in the form of building mass. The airside models describe the temperature dynamics in each of the 500 zones, and the waterside models describe the power consumption of the central plant equipment. The aim of the control system is to minimize costs in the presence of time-varying electricity prices and a peak demand charge as well as environmental disturbances such as weather while meeting constraints on comfort and equipment. We perform an economic optimization of the entire campus using a hierarchical system with distributed airside controllers to demonstrate the potential savings. The models from this case study are made publicly available for other researchers interested in designing alternative control strategies for managing chilled water production to meet airside loads. The aim of the case study release is to provide a standardized problem for the research community. A benchmark is provided for evaluating performance. References [1] A. Afram and F. Janabi-Sharifi. Theory and applications of HVAC control systems—A review of model predictive control (MPC). Building and Environment, 72:343–355, February 2014. [2] J. B. Rawlings, N. R. Patel, M. J. Risbeck, C. T. Maravelias, M. J. Wenzel, and R. D. Turney. Economic MPC and real-time decision making with application to large-scale HVAC energy systems. Computers & Chemical Engineering, 2017. In Press

Evaluation of Efficacy of Cucumis melo in Gentamycin and CPD Induced Urolithiasis on Rats

Evaluation of the efficacy of methanolic extract of Cucumis melo in urolithiasis induced by gentamycin and calculi producing diet on Wistar rats. Gentamycin (40 mg/kg, subcutaneously) and calculi-producing diet (CPD) was fed to induce urolithiasis on Wistar rats. The effect of oral administration of methanolic extract of Cucumis melo seed on calcium oxalate urolithiasis has been studied and is compared with the effect of oral administration of Cystone as standard on Wistar rats. Gentamycin and CPD feeding resulted in hyperoxaluria and calcium oxalate deposition as well as increased renal excretion of calcium and oxalate. Supplementation with methanolic extract of Cucumis melo seed reduced the elevated urinary oxalate, showing a regulatory action on endogenous oxalate synthesis. The results indicate that the seed of Cucumis melo is endowed with antiurolithiatic activity. Keywords: C. melo, Hyperoxaluria, calcium oxalate deposition, cystone, hyperoxaluria, analysis of varianc