MEASURING THE EFFICIENCY OF INDEX FUNDS: EVIDENCE FROM INDIA

The purpose of this study is to analyse the technical efficiency of Index funds using data envelopment analysis (DEA) and to assess the reasons of inefficiency. Based on secondary data collected from the annual reports of the Association of Mutual Funds in India, this study examined the efficiency performance of the top Index funds available to Indian investors from the year 2018 to 2022 using radial measurers (BCC) of data envelopment analysis. The results show that the average efficiency of Index funds was 83.04 percent during the study period, and the average efficiency of index funds was almost stable during the study period. Only 10 percent of the index funds operated efficiently during the study period. The least amount of slack was found in the input "expense ratio". This reiterates that investment risk is the cause of the funds' inefficiency and not the associated expenses.  This study is first of its kind that has assessed the of Indian index funds and therefore holds important insights for regulators, policy makers and practitioners

Recent Advances in Uncertainty Quantification Methods for Engineering Problems

In the last few decades, uncertainty quantification (UQ) methods have been used widely to ensure the robustness of engineering designs. This chapter aims to detail recent advances in popular uncertainty quantification methods used in engineering applications. This chapter describes the two most popular meta-modeling methods for uncertainty quantification suitable for engineering applications (Polynomial Chaos Method and Gaussian Process). Further, the UQ methods are applied to an engineering test problem under multiple uncertainties. The test problem considered here is a supersonic nozzle under operational uncertainties. For the deterministic solution, an open-source computational fluid dynamics (CFD) solver SU2 is used. The UQ methods are developed in Matlab and are further combined with SU2 for the uncertainty and sensitivity estimates. The results are presented in terms of the mean and standard deviation of the output quantities

Surrogate Modeling-Driven Physics-Informed Multi-fidelity Kriging: Path Forward to Digital Twin Enabling Simulation for Accident Tolerant Fuel

The Gaussian Process (GP)-based surrogate model has the inherent capability of capturing the anomaly arising from limited data, lack of data, missing data, and data inconsistencies (noisy/erroneous data) present in the modeling and simulation component of the digital twin framework, specifically for the accident tolerant fuel (ATF) concepts. However, GP will not be very accurate when we have limited high-fidelity (experimental) data. In addition, it is challenging to apply higher dimensional functions (>20-dimensional function) to approximate predictions with the GP. Furthermore, noisy data or data containing erroneous observations and outliers are major challenges for advanced ATF concepts. Also, the governing differential equation is empirical for longer-term ATF candidates, and data availability is an issue. Physics-informed multi-fidelity Kriging (MFK) can be useful for identifying and predicting the required material properties. MFK is particularly useful with low-fidelity physics (approximating physics) and limited high-fidelity data - which is the case for ATF candidates since there is limited data availability. This chapter explores the method and presents its application to experimental thermal conductivity measurement data for ATF. The MFK method showed its significance for a small number of data that could not be modeled by the conventional Kriging method. Mathematical models constructed with this method can be easily connected to later-stage analysis such as uncertainty quantification and sensitivity analysis and are expected to be applied to fundamental research and a wide range of product development fields. The overarching objective of this chapter is to show the capability of MFK surrogates that can be embedded in a digital twin system for ATF

Data-driven multi-scale modeling and robust optimization of composite structure with uncertainty quantification

It is important to accurately model materials' properties at lower length scales (micro-level) while translating the effects to the components and/or system level (macro-level) can significantly reduce the amount of experimentation required to develop new technologies. Robustness analysis of fuel and structural performance for harsh environments (such as power uprated reactor systems or aerospace applications) using machine learning-based multi-scale modeling and robust optimization under uncertainties are required. The fiber and matrix material characteristics are potential sources of uncertainty at the microscale. The stacking sequence (angles of stacking and thickness of layers) of composite layers causes meso-scale uncertainties. It is also possible for macro-scale uncertainties to arise from system properties, like the load or the initial conditions. This chapter demonstrates advanced data-driven methods and outlines the specific capability that must be developed/added for the multi-scale modeling of advanced composite materials. This chapter proposes a multi-scale modeling method for composite structures based on a finite element method (FEM) simulation driven by surrogate models/emulators based on microstructurally informed meso-scale materials models to study the impact of operational parameters/uncertainties using machine learning approaches. To ensure optimal composite materials, composite properties are optimized with respect to initial materials volume fraction using data-driven numerical algorithms

Experimental Evaluation of the Deadtime Phenomenon for GM Detector: Deadtime Dependence on Operating Voltages

A detailed analysis of Geiger Mueller counter deadtime dependence on operating voltage is presented in the manuscript using four pairs of radiation sources. Based on two-source method, detector deadtime is calculated for a wide range of operating voltages which revealed a peculiar relationship between the operating voltage and the detector deadtime. In the low voltage range, a distinct drop in deadtime was observed where deadtime reached a value as low as a few microseconds (22 µs for 204Tl, 26 µs for 137Cs, 9 µs for 22Na). This sharp drop in the deadtime is possibly due to reduced recombination with increasing voltage. After the lowest point, the deadtime generally increased rapidly to reach a maximum (292 µs for 204Tl, 277 µs for 137Cs, 258 µs for 22Na). This rapid increase in the deadtime is mainly due to the on-set of charge multiplication. After the maximum deadtime values, there was an exponential decrease in the deadtime reaching an asymptotic low where the manufacturer recommended voltage for operation falls. This pattern of deadtime voltage dependence was repeated for all sources tested with the exception of 54Mn. Low count rates leading to a negative deadtime suggested poor statistical nature of the data collected for 54Mn and the data while being presented here is not used for any inference

Enteric coating of ibuprofen tablets (200 mg) using an aqueous dispersion system

Ibuprofen is a propionic acid derivative that belongs to the class NSAIDs. Major adverse reactions associated with Ibuprofen are related to GIT and include peptic and mucosal ulcers, dyspepsia, severe gastric pain and bleeding, that results in excessive treatment failure. The goal of this study was to develop enteric coated ibuprofen tablets in order to avoid gastric mucosal irritation, diffusion of drug across mucosal lining and to let active ingredient be absorbed easily in small intestine. The formulation was developed and manufactured through the direct compression process, the simplest, easiest and most economical method of manufacturing. Enteric coating was done using an Opadry white subcoating and an aqueous coating dispersion of Acryl-Eze. Enteric coated formulation was subjected to disintegration and dissolution tests by placing in 0.1 M hydrochloric acid for 2 h and then 1 h in phosphate buffer with a pH of 6.8. About 0.04% of drug was released in the acidic phase and 99.05% in the basic medium. These results reflect that ibuprofen can be successfully enteric coated in order to prevent its release in the stomach and facilitate rapid release of the drug in the duodenum, due to the presence of superdisintegrant. Formulating this enteric coated tablets could increase patient compliance by decreasing adverse drug reactions (ADR S) associated with Ibuprofen therapy.Ibuprofeno é um derivado do ácido propiônico, que pertence à classe dos fármacos não-esteróides (AINES). As principais reações adversas associadas com o ibuprofeno se referem àquelas do trato gastrintestinal (TGI), como úlceras pépticas e da mucosa, dispepsia, dor gástrica grave e sangramento, que resultam em muitas falhas de tratamento. O objetivo do estudo foi desenvolver comprimidos revestidos de ibuprofeno que impeçam a irritação da mucosa gástrica, difusão do fármaco através da mucosa e permitam, facilmente, a absorção do princípio ativo do intestino delgado. A formulação foi desenvolvida e manufaturada por meio de processo de compressão direta, método mais simples e econômico de preparação. O revestimento entérico foi efetuado utilizando-se subrevestimento com Opadry branco e revestimento por dispersão aquosa de Acryl-Eze. A formulação de revestimento para liberação entérica foi submetida a testes de desintegração e de dissolução, em ácido clorídrico 0,1 M, por 2 h, e, então, a h, em tampão fosfato pH 6,8. Cerca de 0,04% do fármaco foi liberado na fase ácida e 99,05%, no meio básico. Estes resultados refletem o fato de que o ibuprofeno pode ser revestido com sucesso, a fim de impedir sua liberação no estômago e facilitar a rápida liberação do fármaco no duodeno, devido à presença de superdesintegrante. A formulação de tais comprimidos aumentaria a adesão do paciente pela diminuição das reações adversas (RAs), associadas à terapia com ibuprofeno

Simultaneous Experimental Evaluation of Pulse Shape and Deadtime Phenomenon of GM Detector

Analysis of several pulse shape properties generated by a Geiger Mueller (GM) detector and its dependence on applied voltage was performed. The two-source method was utilized to measure deadtime while simultaneously capturing pulse shape parameters on an oscilloscope. A wide range of operating voltages (600-1200 V) beyond the recommended operating voltage of 900 V was investigated using three radioactive sources (204Tl, 137Cs, 22Na). This study investigates the relationship between operating voltage, pulse shape properties, and deadtime of the detector. Based on the data, it is found that deadtime decreases with increasing voltage from 600 to 650 V. At these low voltages (600–650 V), the collection time was long, allowing sufficient time for some recombination to take place. Increasing the voltage in this range decreased the collection time, and hence deadtime decreased. It is also observed that rise and fall time were at their highest at these applied voltages. Increasing the voltage further would result in gas multiplication, where deadtime and pulse width are observed to be increasing. After reaching the maximum point of deadtime (~ 250 µs at ~ 700 V), deadtime started to exponentially decrease until a plateau was reached. In this region, it is observed that detector deadtime and operating voltage show a strong correlation with positive pulse width, rise and fall time, cycle mean, and area. Therefore, this study confirms a correlation between detector deadtime, operating voltage, and pulse shape properties. The results will validate our hypothesis that deadtime phenomena at different operating voltages are phenomenologically different

Big data for treatment planning: pathways and possibilities for smart healthcare systems

Background: Treatment planning is one of the crucial stages of healthcare assessment and delivery. Moreover, it also has a significant impact on patient outcomes and system efficiency. With the evolution of transformative healthcare technologies, most areas of healthcare have started collecting data at different levels, as a result of which there is a splurge in the size and complexity of health data being generated every minute. Introduction: This paper explores the different characteristics of health data with respect to big data. Besides this, it also classifies research efforts in treatment planning on the basis of the informatics domain being used, which includes medical informatics, imaging informatics and translational bioinformatics. Methods: This is a survey paper that reviews existing literature on the use of big data technologies for treatment planning in the healthcare ecosystem. Therefore, a qualitative research methodology was adopted for this work. Results: Review of existing literature has been analyzed to identify potential gaps in research, identifying and providing insights into high prospect areas for potential future research. Conclusion: The use of big data for treatment planning is rapidly evolving, and findings of this research can head start and streamline specific research pathways in the field

CONTROLLED RELEASE OF GABAPENTIN THROUGH RETICULATED CHITOSAN AND HYDROXYETHYL CELLULOSE HYDROGEL MATRIX TABLETS

The aim of the present work was to prepare hydrogel matrix tablets using crosslinked chitosan and hydroxyethyl cellulose (HEC) for controlled release of gabapentin. The chitosan was crosslinked with acetaldehyde and used for the preparation of hydrogel matrix tablets along with hydroxylethyl cellulose by wet granulation method. The samples were characterized by FTIR, DSC, TGA, XRD, SEM and evaluated drug content, swelling pattern and drug release. The matrix tablets were capable of releasing the drug for 24h depending upon the formulation variables. It was observed that as the concentration of HEC increased in the tablets, the drug release was also increased. On the other hand, as the crosslinking of chitosan was increased, the drug release was decreased. Drug release mechanism followed non-Fickian transport. This study demonstrated that the blend hydrogel matrix tablets of crosslinked chitosan and HEC could be a versatile drug delivery system for controlled release of gabapentin

Endovascular embolisation of visceral artery pseudoaneurysms

Objective. To evaluate the technical success, safety, and outcome of endovascular embolization procedure in management of visceral artery pseudoaneurysms. Materials and Methods. 46 patients were treated for 53 visceral pseudoaneurysms at our institution. Preliminary diagnostic workup in all cases was performed by contrast enhanced abdominal CT scan and/or duplex ultrasound. In all patients, embolization was performed as per the standard departmental protocol. For data collection, medical records and radiology reports of all patients were retrospectively reviewed. Technical success, safety, and outcome of the procedure were analyzed. Results. Out of 46 patients, 13 were females and 33 were males. Mean patient age was 44.79 ± 13.9 years and mean pseudoaneurysm size was 35 ± 19.5mm. Technical success rate for endovascular visceral pseudoaneurysm coiling was 93.47% (n = 43). Complication rate was 6.52% (n = 3). Followup was done for a mean duration of 21 ± 1.6 months (0.5-69 months). Complete resolution of symptoms or improvement in clinical condition was seen in 36 patients (80%) out of those 45 in whom procedure was technically successful. Conclusion. Results of embolization of visceral artery pseudoaneurysms with coils at our center showed high success rate and good short term outcome