An alternative to Kim and Warde's mixed randomized response model

When open or direct surveys are about sensitive matters (e.g. gambling habits, addiction to drug and others intoxicants, alcoholism, proneness to tax invasion, induced abortions, drunken driving, history of past involvement in crimes, and homosexuality), non-response bias and response bias become serious problems because people oftentimes do not wish to give correct information. To reduce non-response and response bias, various alternative approaches have been proposed, for example a randomized response survey technique, or a mixed randomized response model using simple random sampling with a replacement sampling scheme that improves the privacy of respondents, proposed by authors Kim and Warde. In this paper we have suggested an alternative to Kim and Warde's mixed randomized response model to estimate the proportion of qualitative sensitive variable under the conditions presented in both the cases of completely truthful reporting and less than completely truthful reporting by the respondents. Properties of the proposed randomized response model have been studied along with recommendations. We have also extended the proposed model to stratified random sampling. Numerical illustrations and graphs are also given in support of the present study

Role of Artificial Intelligence in Identifying Financial Fraud

This thesis explores the role of Artificial Intelligence (AI) in identifying and preventing financial fraud in the age where the world continues to digitalize. Focus being the protection offered by financial institutions to their consumers. Frauds such as phishing scams, identity theft, and online shopping fraud are explored. The thesis examines the different AI-driven tools used to enhance protection, such as real-time transaction monitoring, predictive analytics, Know Your Customer (KYC) processes, and social media and dark web monitoring. These methods are compared to the traditional rule-based ones to accentuate the capabilities of AI-driven methods. The results highlight AI’s superiority in scalability, adaptability, and accuracy when compared to the previous methods in place. However, there are still challenges ahead, such as data integrity and quality, ethical concerns, regulatory inconsistencies, and algorithmic biases. The findings emphasize the improvement AI-driven tools have made in securing consumers from financial fraud. Yet emphasis is put on being cautious, and especially the need for consumer education, explainable AI, and improved data integrity. The thesis aims to provide a holistic understanding of AI’s role in the safety and security of consumers and the future direction of where AI-enabled fraud prevention strategies are headed

Mechanical Characterization Of Composite Repairs For Fiber-Glass Wind Turbine Blades

While in service, wind turbine blades experience various modes of loading. An example is impact loading in the form of hail or bird strikes, which might lead to localized damage or formation of cracks a few plies deep on the blade surface. One of the methods to conduct repairs on wind turbine blades that are damaged while in service is hand lay-up of the repair part after grinding out the damaged portion and some of its surrounding area. The resin used for such repairs usually differs from the parent plate resin in composition and properties such as gel time, viscosity, etc. As a result the properties of the repaired parts are not the same as that of the undamaged blades. Subsequent repetitive loading can be detrimental to weak repairs to such an extent so as to cause delamination at the parent-repair bondline causing the repairs to eventually fall off the blade. Thus the strength and toughness of the repair are of critical importance. Initial part of this work consists of an effort to increase repair strength by identifying an optimum hand layup repair resin for fiberglass wind turbine blades currently being manufactured by a global company. As delamination of the repair from the parent blade is a major concern and unidirectional glass fibers along with a polymer resin are used to manufacture blades under consideration, testing method detailed in ASTM D 5528 (Test Method for Mode I Interlaminar Fracture Toughness of Unidirectional Fiber-Reinforced Polymer Matrix Composites) was followed to determine propagation fracture toughness values of the prospective vinyl ester repair resin candidates. These values were compared to those for a base polyester repair resin used by the company. Experimental procedure and results obtained from the above mentioned testing using double cantilever beam (DCB) specimens are detailed. Three new repair resins were shortlisted through mode I testing. It was also found that variation in the depth of the ground top ply of the parent part affects the propagation fracture toughness values of the repair. Repairs conducted on surfaces with partially ground top plies possess higher fracture toughness values than those conducted on surfaces with complete top plies ground off. The three top repair resin candidates were then evaluated against the base repair resin under fatigue loading. The specimen configuration and testing method were chosen so as to be able to test hand layup repairs under tension - tension cyclic loading. It was observed that all three new repair resins perform better than the base repair resin. The selection of the optimum repair resin was based on results from mode I and fatigue testing. Global manufacturing regulations and standards were also of prime concern. The final new repair resin is being used by the company in all of its plants over the globe. The balance of this work involves study of the effect of mixed mode I - mode II loading on the strength of repairs conducted on fiber reinforced composite parts using hand lay-up technique. The specimens for this part were similar to those manufactured for mode I testing but with different dimensions and layup. They were made and tested in accordance with ASTM D 6671 (Standard Test Method for Mixed Mode I - Mode II Interlaminar Fracture Toughness of Unidirectional Fiber Reinforced Polymer Matrix Composites). Comparison was made between the fracture toughness of the above chosen optimum repair resin and the base repair resin. At least two levels of mode mixture GII/G (Mode II fracture toughness / Mode I and II fracture toughness) were examined. Also, two levels of grinding were considered (complete ply vs. partial ply ground off) in order to establish the influence of varying top-ply grinding depths on the strength of hand layup repairs conducted on fiberglass composite structures. The results of this work have the potential to improve the repair process for current fiberglass wind turbine blades

Characterization of Actinomycetes and Trichoderma spp. for cellulase production utilizing crude substrates by response surface methodology

Laboratory bench scaling was done and an average of 1.85 fold increase by Response Surface Methodology (RSM) optimization was obtained. It was found that the predicted value (4.96 IU/ml) obtained by RSM is in close accordance with observed activity 5.14 IU/ml. Endoglucanases are mainly induced by CMC while Wheat bran (natural substrate) exoglucanase is more active when induced by avicel and cellulose. Addition of substrate beyond a level caused inhibition of cellulase production. The molecular weight of protein as determined by SDS-PAGE is very similar to molecular weight of cellulase of Trichoderma viride (T. viride) cellulase and Trichoderma reesei (T. reesei) endoglucanase. T. reesei β-glucosidase has high enzymatic activity on CMC substrate when compared with T. viride β-glucosidase. Secondary structure analysed by using Circular Dichroism confirmed that composition of celluase system is very similar to other analysed species. The cellulase was found to be active in pH range of 4.8-5.5; while temperature range varied from 50°C to 70°C. Although the enzymatic activity produced by mutants were lesser than the parent, but in one case mutants of Trichoderma reesei’s BGL has shown higher activity on cellulose

Phytochemical Analysis, Total Phenolic Content, Antioxidant and Antidiabetic Activity of Sansevieria cylindrica Leaves Extract

Background: Genus “Sansevieria” has been traditionally used for the treatment of various ailments in African countries since a long time. In particular, Sansevieria trifasciata is used for the treatment of inflammatory conditions and sold as a crude drug in the market to treat victims of snakebite in South Africa and tropical America. Therefore, the present study aimed to investigate the presence of phytochemicals, total phenolic content, antioxidant as well as antidiabetic activity of ethanol extract and fractions of Sansevieria cylindrica leaves. Methods and findings: Phytochemical analysis of hexane, chloroform, methanol and aqueous fractions Sansevieria cylindrica leaves confirmed the presence of steroids, flavonoids, saponins, tannins, and phenolic acids. Methanol fraction was found to show maximum phenolic content. Ethanol extract and its methanol fraction showed significant antioxidant and antidiabetic activity. They inhibited 80.5% and 83.6% respectively DPPH free radical at 100 μg/ml concentration. In addition, methanol fraction exhibited 57.9% inhibition of glucose-6- phosphatase enzyme at 100 μM concentration. Conclusion: Our study confirmed the traditional uses of Sansevieria cylindrica plants for the treatment of various diseases

A Proficient Two-Stage Stratified Randomized Response Strategy

A stratified randomized response model based on R. Singh, Singh, Mangat, and Tracy (1995) improved two-stage randomized response strategy is proposed. It has an optimal allocation and large gain in precision. Conditions are obtained under which the proposed model is more efficient than R. Singh et al. (1995) and H. P. Singh and Tarray (2015) models. Numerical illustrations are also given in support of the present study

New Procedures of Estimating Proportion and Sensitivity Using Randomized Response in a Dichotomous Finite Population

The problem of estimating the population proportion possessing a sensitive attribute using simple random sampling with replacement (SRSWR) is advocated. Two new procedures are proposed. The suggested models are more efficient than the Huang (2004) randomized response technique under some realistic conditions. Numerical and graphic illustrations are given

Risk adjustment is crucial in comparing outcomes of various surgical modalities in patients with ileal perforation

<p>Abstract</p> <p>Background</p> <p>Using crude mortality and morbidity rates for comparing outcomes can be misleading. The aim of the present study was to compare the outcome of various surgical modalities without and with risk adjustment using Physiologic and Operative Severity Scoring for the enUmeration of Mortality and morbidity (POSSUM) score in cases of ileal perforations.</p> <p>Methods</p> <p>Prospective study on 125 patients of ileal perforations. Resection anastamosis (Group I) was done in 38 patients, primary repair (Group II) in 42 patients and 45 patients had an ileostomy (Group III). The disease severity was assessed in all patients using POSSUM score. The odds of death without and with risk adjustment using POSSUM mortality score were calculated for all groups</p> <p>Results</p> <p>Seventeen patients (14%) patients died and 99 (79%) developed postoperative complications. Using crude mortality rates Group I appeared to be the best treatment option with only 2 (5%) deaths followed by Group II with 5 (12%) deaths where as Group III had the worst outcome with 10 deaths (22%). However, Group III (ileostomy) patients had higher mean POSSUM mortality and morbidity score (55.55%, 91.33%) than Group I (28%, 75.26%) and Group II (27%, 73.59%). Taking Group I as the reference (odds ratio, OR1) odds of death were greatest in Group III (OR 5.14, p = 0.043) followed by Group II (OR 2.43, p = 0.306). With risk adjustment using POSSUM mortality score the odds of death decreased in Group III (OR 1.16 p = 0.875). For the whole group, there was a significant association between the POSSUM score and postoperative complications and deaths. Mean POSSUM mortality and morbidity score of those who died (63.40 vs.33.68, p = 0.001) and developed complications (66.32 vs.84.20, p = 0.001) was significantly higher. For every percent increase in severity score the risk of postoperative complications and death increased by 1.10 (p = 0.001) and1.06 (p = 0.001) respectively.</p> <p>Conclusion</p> <p>Despite ileostomy patients having highest crude mortality and complication rates, after risk adjustment it was equally safe. Severity of the disease rather than the surgical option had a significant impact on the outcome in patients with ileal perforations.</p

Nephroprotective action of Peucedanum grande against cadmium chloride induced renal toxicity in Wistar rats

Cadmium is a known industrial pollutant which accumulates in the kidney and its exposure leads to the production of reactive oxygen species (ROS). The present study was carried out to evaluate the protective effects of Peucedanum grande against CdCl2 induced renal toxicity in Wistar rats. Wistar rats were subjected to oral pretreatment of P. grande (60 and 120 mg/kg b.wt) against the renal toxicity induced by administration of CdCl2 (3mg/kg b.wt). Efficacy of P. grande against the renal toxicity was evaluated in terms of biochemical estimation of antioxidant enzyme activities and histopathological changes. P. grande pretreatment prevented deteriorative effects induced by CdCl2 through a protective mechanism that involved reduction of increased oxidative stress as well as by restoration of histopathological changes against CdCl2 administration

On the impact of the galaxy window function on cosmological parameter estimation

One important source of systematics in galaxy redshift surveys comes from the estimation of the galaxy window function. Up until now, the impact of the uncertainty in estimating the galaxy window function on parameter inference has not been properly studied. In this paper, we show that the uncertainty and the bias in estimating the galaxy window function will be salient for ongoing and next-generation galaxy surveys using a simulation-based approach. With a specific case study of cross-correlating Emission-line galaxies from the DESI Legacy Imaging Surveys and the Planck CMB lensing map, we show that neural network-based regression approaches to modelling the window function are superior in comparison to linear regression-based models. We additionally show that the definition of the galaxy overdensity estimator can impact the overall signal-to-noise of observed power spectra. Finally, we show that the additive biases coming from the window functions can significantly bias the modes of the inferred parameters and also degrade their precision. Thus, a careful understanding of the window functions will be essential to conduct cosmological experiments.Comment: 13 pages, 12 figures, complementary paper to an upcoming paper on Cross-Correlation of ELGs and Planck CMB lensing, accepted for publication in MNRA