This research looked at the effects of COVID-19 on a number of the world’s most important stock exchanges, as well as the empirical relation between the COVID-19 wave and stock market volatility. In order to plan proper portfolio diversification in international financial markets, researchers must examine COVID-19 anxiety in relation to stock market volatility. The stock market volatility connected with the COVID-19 pandemic was measured using AR(1)-GARCH(1,1). COVID-19 fear, according to our research, is the ultimate driver of public attention and stock market volatility. The findings show that throughout the pandemic, stock market performance and GDP growth both declined significantly due to average increases. Furthermore, a 1% increase in COVID-19 causes a 0.8% and 0.56% decline in stock return and GDP, respectively. The stock market, on the other hand, showed a slight movement in GDP growth. Furthermore, the COVID-19 pandemic reported cases index, death index, and global panic index all influenced public perceptions of purchasing and selling. As a result, rather than investing in stocks, it is recommended that you invest in gold. The research also makes policy recommendations for important stakeholders. We look to examine how stock returns respond dynamically to unanticipated changes in the COVID-19 scenarios, as well as the uncertainty that comes with a pandemic. Using daily data from Canada and the USA, we conclude that a spike in COVID-19 instances has a negative impact on the stock market in general. Furthermore, in both the increase and decline scenarios in Canada, the stock return reactions are asymmetric. The disparity is due to the unfavorable impact of the pandemic’s unpredictability. We also discovered that uncertainty had a negative impact on the US stock market. The magnitude, however, is insignificant.

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Glaucoma is one of the prevalent causes of blindness in the modern world. It is a salient chronic eye disease that leads to irreversible vision loss. The impediments of glaucoma can be restricted if it is identified at primary stages. In this paper, a novel two-phase Optic Disk localization and Glaucoma Diagnosis Network (ODGNet) has been proposed. In the first phase, a visual saliency map incorporated with shallow CNN is used for effective OD localization from the fundus images. In the second phase, the transfer learning-based pre-trained models are used for glaucoma diagnosis. The transfer learning-based models such as AlexNet, ResNet, and VGGNet incorporated with saliency maps are evaluated on five public retinal datasets (ORIGA, HRF, DRIONS-DB, DR-HAGIS, and RIM-ONE) to differentiate between normal and glaucomatous images. This study’s experimental results demonstrate that the proposed ODGNet evaluated on ORIGA for glaucoma diagnosis is the most predictive model and achieve 95.75, 94.90, 94.75, and 97.85% of accuracy, specificity, sensitivity, and area under the curve, respectively. These results indicate that the proposed OD localization method based on the saliency map and shallow CNN is robust, accurate and saves the computational cost.

This study described an empirical link between COVID-19 fear and stock market volatility. Studying COVID-19 fear with stock market volatility is crucial for planning adequate portfolio diversification in international financial markets. The study used AR (1) – GARCH (1,1) to measure stock market volatility associated with the COVID-19 pandemic. Our findings suggest that COVID-19 fear is the ultimate cause driving public attention and is a stock market volatility. The results demonstrate that stock market performance and GDP growth decreased significantly through average increases during the pandemic. Further, a 1% increase in COVID-19 cases the stock return and GDP decrease with a 0.8%, 0.56%, respectively. However, GDP growth demonstrated a slight movement with stock exchange. Moreover, public attention to the attitude of buying or selling was highly dependent on the COVID-19 pandemic reported cases index, death index, and global fear index. Consequently, investment in the gold market, rather than in the stock market, is recommended. The study also suggests policy implications for key stakeholders.

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Objectives: Uterine fibroids are frequently associated with symptoms like subfertility, heavy menstrual bleeding etc. When symptomatic they need to be treated medically or surgically. We assessed the efficacy and safety of laparoscopy assisted mini-laparotomy for fibroids causing a big uterine size (>12 weeks). Study Design: Observational study. Setting: At Hameed Latif Hospital Lahore, Pakistan. Period: From Feb 2018 to Jan 2019. Material & Methods: Forty six patients were selected by non-probability convenience sampling. Size of uterus, number of fibroids were recorded. All patients underwent hysteroscopy followed by laparoscopy assisted mini-laparotomy for myomectomy. A small 5cm incision was used extending its length only where needed. Length of incision, time for procedure, volume of blood loss were recorded. Data was analyzed with MS Excel 2013. Results: All participants were sub fertile women with uterine fibroids and size of uterus more than 12 weeks. Menorrhagia was a common symptom seen in 36.9% patients. Hysteroscopy revealed uterine deformities in 43% patients. Laparoscopy showed bilateral tubal blockage in 23 % participants. Average size of uterus per-operatively was 19.4 weeks. Mean duration of surgery was 54.13 min (SD ±18.05) and average blood loss was 650 ml (SD±238.28). No procedure was converted into conventional laparotomy and average length of incision was 4.9 cm (SD±0.91). Conclusion: LA MLT is a safe and effective approach to remove big fibroids. Hysteroscopy in the same sitting allows detection & correction of uterine abnormalities. Additional advantage of laparoscopy is ability to check tubal patency in the same sitting in sub fertile women.