57 research outputs found

    A complex networks based analysis of jump risk in equity returns:An evidence using intraday movements from Pakistan stock market

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    International audienceWe employ a multi-stage methodology combining complex network analytics and financial risk modelling to unveil the correlation structures amongst the price jump risks of companies forming the KSE-100 index in Pakistan. We identify the most influential companies in terms of jump risk, and identify communities — clusters of companies with similar price movement characteristics or with highly correlated price jumps. We find that equities in Pakistan stock market experience jumps in different time periods that are correlated to varying degrees within and across industries resulting in 19 different communities, four of which are strongly connected. While Oil & Gas, Cement and Banking sectors exhibit a significant representation of firms in communities, the automobile industry, however, seems to play an important role in risk propagation. These results provide an interesting insight to investors and other stakeholders from an emerging market viewpoint identifying the major sectors driving the volatility of KSE-100 index

    A Robust Deep Model for Classification of Peptic Ulcer and Other Digestive Tract Disorders Using Endoscopic Images

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    Accurate patient disease classification and detection through deep-learning (DL) models are increasingly contributing to the area of biomedical imaging. The most frequent gastrointestinal (GI) tract ailments are peptic ulcers and stomach cancer. Conventional endoscopy is a painful and hectic procedure for the patient while Wireless Capsule Endoscopy (WCE) is a useful technology for diagnosing GI problems and doing painless gut imaging. However, there is still a challenge to investigate thousands of images captured during the WCE procedure accurately and efficiently because existing deep models are not scored with significant accuracy on WCE image analysis. So, to prevent emergency conditions among patients, we need an efficient and accurate DL model for real-time analysis. In this study, we propose a reliable and efficient approach for classifying GI tract abnormalities using WCE images by applying a deep Convolutional Neural Network (CNN). For this purpose, we propose a custom CNN architecture named GI Disease-Detection Network (GIDD-Net) that is designed from scratch with relatively few parameters to detect GI tract disorders more accurately and efficiently at a low computational cost. Moreover, our model successfully distinguishes GI disorders by visualizing class activation patterns in the stomach bowls as a heat map. The Kvasir-Capsule image dataset has a significant class imbalance problem, we exploited a synthetic oversampling technique BORDERLINE SMOTE (BL-SMOTE) to evenly distribute the image among the classes to prevent the problem of class imbalance. The proposed model is evaluated against various metrics and achieved the following values for evaluation metrics: 98.9%, 99.8%, 98.9%, 98.9%, 98.8%, and 0.0474 for accuracy, AUC, F1-score, precision, recall, and loss, respectively. From the simulation results, it is noted that the proposed model outperforms other state-of-the-art models in all the evaluation metrics

    Zinc nutrition application augments morpho-physiological attributes, productivity and grain zinc bioavailability of Paddy Rice

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    Zinc (Zn) deficiency is the most important micronutrient disorders affecting plants and human health. Present study evaluated the potential of various Zn application methods in improving the performance of selected rice genotypes and Zn bioavailability in grains. Pre-selected Zn application methods through pot experiments were validated in the field. Harvested grains were fed to albino rats for Zn bioavailability. Results revealed that soil + foliar application of Zn was effective in improving the seedling growth of rice genotypes by modulating the agronomic, water related and biochemical attributes. The rats gained more body weight fed with rice genotype Accession-164 (high Zn accumulator) compared with the minimum for Super Basmati (low Zn accumulator) feed. In crux, soil application of Zn at 15 kg ha-1 followed by foliar application of 0.25% ZnSO4.7H2O solution at tillering and heading stages produced the highest grain yield (26.25%, 29.11%) with maximum bioavailable Zn (21.02%, 22.50%) during both years, respectively, in the grains for combating malnutrition in the tested rats

    On the Efficiency of Foreign Exchange Markets in times of the COVID-19 Pandemic

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    We employ multifractal detrended fluctuation analysis (MF-DFA) to provide the first look at the efficiency of forex markets during the initial period of ongoing COVID-19 pandemic, which has disrupted the financial markets globally. We use high frequency (5-min interval) data of six major currencies traded in the forex market for the period from 01 October 2019 to 31 March 2020. Prior to the application of MF-DFA, we examine the inner dynamics of multifractality using seasonal-trend decompositions using loess (STL) method. Overall, the results confirm the presence of multifractality in forex markets, which demonstrates, in particular: (i) a decline in the efficiency of forex markets during the period of COVID-19 outbreak, and (ii) the heterogeneity in the effects on the strength of multifractality of exchange rate returns under investigation. The largest effect is observed in the case of AUD as it shows the highest (lowest) efficiency before (during) COVID-19 assessed in terms of low (high) multifractality. During COVID-19 period, CAD and CHF exhibit the highest efficiency. Our findings may help policymakers in shaping a comprehensive response to improve the forex market efficiency during such a black swan event

    Impact of Brand Loyalty in Assessing Purchase Intentions of a Customer: A Study of Automobile Industry in South Asian Perspective

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    In this modern age, brands are more concentrating on consumers’ quality of life style as these reflect their status symbol or social class through the company’s products. The current study is aimed to check the effect of brand name, awareness, and price and brand quality on the brand loyalty of the product of automobiles, after that brand loyalty effect is examined on the product purchase intention specifically in South Asian context. For checking the effect of the variables brand name, brand awareness, brand price and brand quality were considered as independent variables and brand loyalty was considered as a dependent variable. The study was correlational as it shows the relationship of different dependent and independent variables. This study has been conducted through a survey design. The population was considered as the citizens of Bahawalpur, one of the oldest stateS in South Asian region and for the data collection random sampling technique was used. A total number of 300 questionnaires were distributed randomly to the users of automobile in the Bahawalpur out of which 287 responses were received after deducting the omission and errors. Different hypotheses were tested in this research for relationships of variables, out of which five were accepted and the one which was about the effect of brand price on brand loyalty was rejected. The collected data were analyzed after using different statistical techniques and it shows that brand awareness, name, quality has a direct and positive impact on the brand loyalty of the product and on the other hand there is also a positive effect of brand loyalty on the purchase intention of the product

    Time to endoscopy for acute upper gastrointestinal bleeding: results from a prospective multicentre trainee-led audit

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    Background: Endoscopy within 24 hours of admission (early endoscopy) is a quality standard in acute upper gastrointestinal bleeding (AUGIB). We aimed to audit time to endoscopy outcomes and identify factors affecting delayed endoscopy (>24h of admission).Methods: This prospective multicentre audit enrolled patients admitted with AUGIB who underwent inpatient endoscopy between Nov-Dec 2017. Analyses were performed to identify factorsassociated with delayed endoscopy, and to compare patient outcomes, including length of stay and mortality rates, between early and delayed endoscopy groups.Results: Across 348 patients from 20 centres, the median time to endoscopy was 21.2h (IQR 12.0- 35.7), comprising median admission to referral and referral to endoscopy times of 8.1h (IQR 3.7- 18.1) and 6.7h (IQR 3.0-23.1) respectively. Early endoscopy was achieved in 58.9%, although this varied by centre (range: 31.0% - 87.5%, p=0.002). On multivariable analysis, lower Glasgow-Blatchford score, delayed referral, admissions between 7am-7pm or via the Emergency Department were independent predictors of delayed endoscopy. Early endoscopy was associated with reduced length of stay (median difference 1d; p= 0.004), but not 30-day mortality (p=0.344).Conclusions: The majority of centres did not meet national standards for time to endoscopy. Strategic initiatives involving acute care services may be necessary to improve this outcome

    Online routing of bandwidth guaranteed paths with local restoration using optimized aggregate usage information

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    We investigate the problem of distributed online routing of bandwidth guaranteed paths with local restoration. A unified model is proposed that captures the bandwidth sharing characteristic of backup paths that provision local restoration, corresponding to different fault models. We apply the model to describe bandwidth sharing on backup paths for varying degrees of network state information. The extent of backup bandwidth sharing depends on the amount of network state information made available through routing protocols. A key design criterion for traffic engineering schemes is to maximize the sharing between backup paths, while minimizing this protocol overhead. Kodialam et al. demonstrated in [3] that propagating a constant amount of aggregated information per link leads to cost effective bandwidth sharing. We propose a new optimized aggregate information scenario (oAIS), in which we judiciously select the propagated information, such that the protocol overhead is identical to that in [3]. Simulations show that oAIS outperforms other information scenarios with comparable protocol overhead

    Corpus-Based Analysis of Career Services Language in the UK and Pakistani University Websites

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    This study investigates the language of career services webpages in the top seven UK and the top seven PK (Pakistani) QS-ranked universities. Career services webpages of universities address career-related issues of students and serve as a remedy to the social problem of unemployment. These platforms train their students according to the requirements of employers by strengthening them with employability skills. Therefore, this research aims to highlight the notion of ‘career’ and ‘job’ in career services webpages of the UK and PK universities. The methodology used is corpus-based critical discourse analysis and the data is analyzed with Antconc 3.5.8 version. The sample size consisting of 353473 words of PK corpus and 323234 words of UK corpus is selected by using the judgmental sampling technique and the corpus is built by using Sketch Engine. The results show the inclination of PK universities towards the ‘academic career’ of their students because whenever they talk about the career and jobs of students, they show their concern about not having third division or D grade in their academic career to get a degree. This preference of PK universities is promoting rot culture of defining capabilities of students through their degrees that needs to be addressed. Whereas, UK universities show their concern about the skills and employability of their students by providing them knowledgeable and conceptual tasks to get an ideal job. The analysis concludes that the language of both UK and PK universities put emphasis on career development and employability skills, but their approach seems to be different in making their graduates employable. The findings of this research can be beneficial in creating awareness among students and academicians regarding the outcomes of language that is used by university websites and its influence on their professional choices
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