Combined loose piece pattern for a complex job

Casting is one of the earliest metal-shaping methods known to human being. It generally means pouring molten metal into a refractory mold with a cavity of the shape to be made, and allowing it to solidify. When solidified , the desired metal object is taken out from the refractory mold either by breaking the mold or by taking mold apart. This process is also called founding. A pattern is a replica of the object to be made by the casting process, with some modifications. The main modifications are addition of pattern allowances like shrinkage allowance, machining allowance, draft allowance etc., the provision of core prints and elimination of fine details. Loose piece pattern is used when the contour of the part is such that withdrawing the pattern from the mold is not possible. Hence during molding, the obstructing part of the contour is held as a loos piece by a wire. After molding is over, first the main pattern is removed and then the loose pieces are recovered through the gap generated by the main pattern. A safety valve which is generally manufactured by complex forging method , can be easily manufactured by sand casting method which is more economical the forging method. In the sand casting method, the two wedge shaped portions of the safety valve create problem during removal of pattern, so these two portions are taken as loose pieces and held as loose pieces by a wire or pin. Once the main pattern body is removed, these loose pieces are recovered through the space vacated by main pattern body. So this project work deals with manufacturing of safety valve using sand casting with split pattern which consists of multi loose pieces (combined loose piece) and its advantages over complex forging metho

Effect of various cardiovascular risk factors on oxidative stress markers in post menopausal women

Background: The objectives was to study the association between oxidative stress and various cardiovascular risk factors individually and also there cumulative effect in post-menopausal women.Methods: 50 postmenopausal women with cardiovascular risk factors like hyperglycemia, hypertension, high Body Mass Index and Hyperlipidaemia were selected and burden of various cardiovascular risk factors in them is noted and also compared with 50 age matched apparently healthy post menopausal controls. Malon-di-aldehyde (MDA), vitaminE and vitamin C were taken to assess oxidative stress status. ANOVA was applied to find the effect of individual risk factor on oxidative stress and Student’s t-test was applied to compare between cases with single risk factors and multiple risk factors.Results: It was found that though all cardiovascular risk factors increase oxidative stress significantly but none of them has significant association in comparison to others (F value 0.37, 0.88 and 0.62 for MDA, vitamin E and C respectively). However, MDA value found in cases with multiple risk factors when compared with that of cases with single risk factor was found to be statistically significant (P <0.001). Similarly, the decrease in vitamin E in cases with multiple risk factors when compared with single risk factor cases was found to be significant. (P <0.01) and vitamin C in women with multiple risk factors was decreased in comparison to women with a single risk factor and was significant (P <0.001).Conclusions: The study shows that all the risk factors are equally responsible for increase in oxidative stress and multiple risk factors increase the oxidative stress significantly in comparison to any single risk factor

Empirical Forecasting Analysis of Bitcoin Prices: A Comparison of Machine learning, Deep learning, and Ensemble learning Models

Bitcoin has drawn a lot of interest recently as a possible high-earning investment. There are significant financial risks associated with its erratic price volatility. Therefore, investors and decision-makers place great significance on being able to precisely foresee and capture shifting patterns in the Bitcoin market. However, empirical studies on the systems that support Bitcoin trading and forecasting are still in their infancy. The suggested method will predict the prices of all key cryptocurrencies with accuracy. A number of factors are going to be taken into account in order to precisely predict the pricing. By leveraging encryption technology, cryptocurrencies may serve as an online accounting framework and a medium of exchange. The main goal of this work is to predict Bitcoin price. To address the drawbacks of traditional forecasting techniques, we use a variety of machine learning, deep learning, and ensemble learning algorithms. We conduct a performance analysis of Auto-Regressive Integrated Moving Averages (ARIMA), Long-Short-Term Memory (LSTM), FB-Prophet, XGBoost, and a pair of hybrid formulations, LSTM-GRU and LSTM-1D_CNN. Utilizing historical Bitcoin data from 2012 to 2020, we compared the models with their Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The hybrid LSTM-GRU model outperforms the rest with a Mean Absolute Error (MAE) of 0.464 and a Root Mean Squared Error (RMSE) of 0.323. The finding has significant ramifications for market analysts and investors in digital currencies

Minimal hepatic encephalopathy: consensus statement of a working party of the Indian National Association for study of the liver

Hepatic encephalopathy (HE) is a major complication that develops in some form and at some stage in a majority of patients with liver cirrhosis. Overt HE occurs in approximately 30-45% of cirrhotic patients. Minimal HE (MHE), the mildest form of HE, is characterized by subtle motor and cognitive deficits and impairs health-related quality of life. The Indian National Association for Study of the Liver (INASL) set up a Working Party on MHE in 2008 with a mandate to develop consensus guidelines on various aspects of MHE relevant to clinical practice. Questions related to the definition of MHE, its prevalence, diagnosis, clinical characteristics, pathogenesis, natural history and treatment were addressed by the members of the Working Party

Incorporating uncertainty and risk in transportation investment decision-making

This paper presents a framework for addressing uncertainty and risk for large-scale transportation investments involving public–private participation. Demand, fare/toll and demand responsive costs are considered in the uncertainty analysis. Uncertainty analysis provides information on economic feasibility of the project. A set of relaxation policies is proposed to form various Ownership, Tenure and Governance (OTG) strategies reflecting the nature and level of participation by the public and private entity. A Monte Carlo Simulation-based Value at Risk is used to quantify risk. Finally, a methodology is proposed to integrate uncertainty and risk. The framework is tested on the proposed multibillion dollar Detroit River International Crossing connecting the cities of Detroit in the USA with Windsor in Canada. The analysis provides insights to probable outcomes for this transportation infrastructure investment under different OTG scenarios

Multi-entity perspective transportation infrastructure investment decision making

Investment in new large transportation infrastructure is capital-intensive and irreversible in nature. Private sector participation in infrastructure investment has gained popularity in recent times because of scarcity of resources at the public sector, and because of the ability of the private sector to build, operate, maintain such facilities, and share future uncertainties. In such cases, there are multiple entities each with different objectives in the project. Traditional techniques used to determine feasibility of such projects and do not consider two critical elements. These are the need (1) to identify major entities involved in these projects and their individual objectives, and (2) the importance of analyzing measures of effectiveness of each entity in a multi-objective context. A framework is proposed to address these issues along with a set of relaxation policies to reflect the nature and level of participation by the entities.First, the feasibility of each single entity perspective is determined and next, a multi-objective optimization (MOO) is proposed reflecting the perspectives of all entities. The MOO results in pareto-optimal solutions to serve as tradeoff between the participation levels of the multiple entities. The Analytic Hierarchy Process (AHP) is used as a tool to narrow down number of options for decision makers for further consideration. AHP and MOO are integrated to determine the feasibility of strategies from multi-entity perspectives. The framework is examined on the proposed multibillion dollar international river crossing connecting the city of Detroit in the U.S. and the city of Windsor in Canada. This methodology provides a decision making process tool for large-scale transportation infrastructure investment consisting of multiple entities. © 2013

TID and I-TD controller design for magnetic levitation system using genetic algorithm

This article is about the design of controllers for magnetic levitation (Maglev) system in both simulation and real time. Local linearization around the equilibrium point has been done for the nonlinear Maglev system to obtain a linearized model transfer function. In this study, the design of integral-tilted-derivative (I-TD) controller has been proposed for the Maglev system and its performance is compared with conventional tilted-integral-derivative (TID) controller. In this study, TID controller parameters have been optimized through genetic algorithm (GA) and those set of values have been employed for the design of I-TD controller. A performance comparison between TID and I-TD controller is then investigated. The analysis shows the superiority of I-TD controller over TID controller in terms of maximum overshoot, gain margin and phase margin. The settling time remains almost same in both the cases. In future, a detailed study of robustness in presence of model uncertainties will be incorporated as a scope of further research

A Critical Analysis of Modeling Aspects of D-STATCOMs for Optimal Reactive Power Compensation in Power Distribution Networks

Distribution static compensators (D-STATCOMs) can enhance the technical performance of the power distribution network by providing rapid and continuous reactive power support to the connected bus. Accurate modeling and efficient utilization of D-STATCOMs can maximize their utility. In this regard, this article offers a novel current-injection-based D-STATCOM model under the power control mode of operation for the reactive power compensation of the power distribution network. The versatility of the proposed D-STATCOM model is demonstrated by combining it with two of the most established distribution load flow techniques, viz., the forward–backward sweep load flow and the BIBC–BCBV-matrix-based direct load flow. Further, the allocation of the proposed D-STATCOM model is carried out under a multiobjective mathematical formulation consisting of various technical and economic indices such as the active power loss reduction index, voltage variation minimization index, voltage stability improvement index and annual expenditure index. A novel parameter-free metaheuristic algorithm, namely a student-psychology-based optimization algorithm, is proposed to determine the optimal assignment of the different number of D-STATCOM units under the multiobjective framework. The proposed allocation scheme is implemented on a standard 33-bus test system and on a practical 51-bus rural distribution feeder. The obtained results demonstrate that the proposed D-STATCOM model can be efficiently integrated into the distribution load flow algorithms. The student-psychology-based optimization algorithm is found to be robust and efficient in solving the optimal allocation of D-STATCOMs as it yields minimum power loss compared to other established approaches for 33-bus PDNs. Further, the economic analysis carried out in this work can guide network operators in deciding on the number of D-STATCOMs to be augmented depending on the investment costs and the resulting savings

<span style="font-size:15.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-GB;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-GB">First record of <i>Halophila ovalis</i> in the Haripur creek, East Coast of India</span>

1939-1941<span style="font-size:9.0pt;font-family: " times="" new="" roman";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;color:black;mso-ansi-language:en-gb;mso-fareast-language:en-us;="" mso-bidi-language:hi"="" lang="EN-GB">Present study reports the first record of occurrence of a seagrass Halophila ovalis, family- Hydrocharitaceae and class-Liliopsida in the Haripur creek of the southern coast of Odisha.  It was suggested that the shallow water region of this tidal creek provided a conducive environment for colonization of this particular sea grass species. This study also describes the morphological and habitat characteristics of the sea grass.</span