Heteroscedasticity effects as component to future stock market predictions using RNN-based models.

Heteroscedasticity effects are useful for forecasting future stock return volatility. Stock volatility forecasting provides business insight into the stock market, making it valuable information for investors and traders. Predicting stock volatility is a crucial task and challenging. This study proposes a hybrid model that predicts future stock volatility values by considering the heteroscedasticity element of the stock price. The proposed model is a combination of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and a well-known Recurrent Neural Network (RNN) algorithm Long Short-Term Memory (LSTM). This proposed model is referred to as GARCH-LSTM model. The proposed model is expected to improve prediction accuracy by considering heteroscedasticity elements. First, the GARCH model is employed to estimate the model parameters. After that, the ARCH effect test is used to test the residuals obtained from the model. Any untrained heteroscedasticity element must be found using this step. The hypothesis of the ARCH test yielded a p-value less than 0.05 indicating there is valuable information remaining in the residual, known as heteroscedasticity element. Next, the dataset with heteroscedasticity is then modelled using an LSTM-based RNN algorithm. Experimental results revealed that hybrid GARCH-LSTM had the lowest MAE (7.961), RMSE (10.466), MAPE (0.516) and HMAE (0.005) values compared with a single LSTM. The accuracy of forecasting was also significantly improved by 15% and 13% with hybrid GARCH-LSTM in comparison to single LSTMs. Furthermore, the results reveal that hybrid GARCH-LSTM fully exploits the heteroscedasticity element, which is not captured by the GARCH model estimation, outperforming GARCH models on their own. This finding from this study confirmed that hybrid GARCH-LSTM models are effective forecasting tools for predicting stock price movements. In addition, the proposed model can assist investors in making informed decisions regarding stock prices since it is capable of closely predicting and imitating the observed pattern and trend of KLSE stock prices.

Disparities in patient-resident physician communication and counseling: A multi-perspective exploratory qualitative study.

Effective communication between physicians and patients plays an integral role in clinical care. Gaps in a physician's ability to ensure effective communication, especially with patients from diverse backgrounds, are known causes of medical errors. This study explores the potential biases and disparities in patient-resident communication, which may influence a patient's quality of care. This exploratory qualitative study was conducted at the largest academic medical center in Pakistan. Purposive sampling was used to approach participants from surgery, medicine, obstetrics and gynecology, pediatrics and family medicine. Faculty, fellows and residents working in these departments and medical students in their fourth and fifth years of undergraduate education with prior experience of at least one month in these specialties during their clinical rotations were included. Focus group discussions (FGDs) lasting 45-60 minutes were conducted with each cohort of healthcare professionals separately, using a semi-structured interview guide. Sixty participants (19 males and 41 females, mean age: 32.9, SD: 10.9) took part in the study. Thematic analysis revealed five major themes. Four themes focused on residents' biases and patient disparities hindering patient-resident communication: (1) patient-resident gender discordance (2) ethnicity and language barriers, (3) differing social class of the patient, and (4) challenging patient-resident interactions (patients resistant to treatment, exceedingly inquisitive and those with multiple attendants, etc.). The fifth theme identified the need for a communication skills curriculum in postgraduate medical education. Opposite gender and discordant socioeconomic/cultural backgrounds of patients pose a challenge to effective patient-physician communication. Self-identification and awareness of residents' biases when interacting with patients can ensure their active elimination and improve their communication skills. Integrating these components in a standardized curriculum within postgraduate programs can enable resident-physicians to provide the same level of care and communicate more efficiently with patients of all backgrounds.

Impact of the China-Pakistan Economic Corridor on the China-Europe and China-Middle East trading route selection.

This research examines the potential impact of the China-Pakistan Economic Corridor (CPEC) on the selection of trading routes between China, the Middle East, and Europe, with a specific focus on the transportation of a 40-foot standard container carrying general commodities. The study compares traditional routes with the new CPEC routes in terms of time, distance, and cost. The findings indicate that the new CPEC routes offer reduced travel time and distance when compared to the traditional routes across all provinces involved. The research reveals that the cost of road transportation along the new CPEC route is lower for Xinjiang province, but higher for the other provinces. By utilizing the new CPEC routes, the time required for goods to travel from China to the Middle East and Europe will be reduced by 10 to 20 days. Furthermore, the distance covered in this trade route will be shortened by 3,000 to 10,000 kilometres. Specifically, the province of Xinjiang in western China stands to benefit significantly from the new CPEC routes, saving approximately $2,000 on trade with the Middle East and Europe. These findings highlight the potential advantages and economic benefits that can be realized by leveraging the CPEC for trade between China, the Middle East, and Europe, particularly in terms of reduced transportation time and distance.

Nutritional Assessment in Cancer Patients.

Malnutrition in cancer patients is highly prevalent. The metabolic and physiologic changes associated with the disease and the side effects of treatment regimens all combine together to produce a detrimental effect on the patient's nutritional status. A poor nutritional status significantly reduces the efficacy of treatment methods and the patient's overall chances of survival. Therefore, an individualized nutrition care plan is essential to counter malnutrition in cancer. Nutritional assessment is the first step of this process which sets the foundation for developing an effective intervention plan. Currently, there is no single standard method for nutritional assessment in cancer. Hence, to get a true picture of the patient's nutritional state, a comprehensive analysis of all aspects of the patient's nutritional status is the only reliable strategy. The assessment includes anthropometric measurements and evaluation of body protein status, body fat, inflammation markers, and immune markers. A thorough clinical examination which factors in the medical history and physical signs, along with the dietary intake patterns of the patient, is also important components of nutritional assessment of cancer patients. To facilitate with the process, various nutritional screening tools like patient-generated subjective global assessment (PGSGA), nutrition risk screening (NRS), and malnutrition screening tool (MST) have been developed. While these tools have their own benefits, they only give a glimpse of the nutritional problems and do not bypass the need for a complete assessment employing various methods. This chapter covers all four of the elements of nutritional assessment for cancer patients in detail.

Green Synthesis of Zinc Oxide (ZnO) Nanoparticles from Green Algae and Their Assessment in Various Biological Applications.

The biosynthesis of algal-based zinc oxide (ZnO) nanoparticles has shown several advantages over traditional physico-chemical methods, such as lower cost, less toxicity, and greater sustainability. In the current study, bioactive molecules present in Spirogyra hyalina extract were exploited for the biofabrication and capping of ZnO NPs, using zinc acetate dihydrate and zinc nitrate hexahydrate as precursors. The newly biosynthesized ZnO NPs were characterized for structural and optical changes through UV-Vis spectroscopy, Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDX). A color change in the reaction mixture from light yellow to white indicated the successful biofabrication of ZnO NPs. The UV-Vis absorption spectrum peaks at 358 nm (from zinc acetate) and 363 nm (from zinc nitrate) of ZnO NPs confirmed that optical changes were caused by a blue shift near the band edges. The extremely crystalline and hexagonal Wurtzite structure of ZnO NPs was confirmed by XRD. The involvement of bioactive metabolites from algae in the bioreduction and capping of NPs was demonstrated by FTIR investigation. The SEM results revealed spherical-shaped ZnO NPs. In addition to this, the antibacterial and antioxidant activity of the ZnO NPs was investigated. ZnO NPs showed remarkable antibacterial efficacy against both Gram-positive and Gram-negative bacteria. The DPPH test revealed the strong antioxidant activity of ZnO NPs.

The symmetric and asymmetric impacts of green energy, eco-innovation, and urbanization in explaining low-carbon economy for Pakistan.

Over the past three decades, global economic development patterns have considerably affected the natural environment, and economies have endured a plethora of environmental concerns as a result of the negative effects of climate change. Among them, Pakistan is the fifth most vulnerable country, and climate change has harmfully affected the ecological and socio-economic conditions of the country. In this regard, this study aimed to investigate the role of green energy consumption, eco-innovation, and urbanization while explaining the dream of low-carbon economy and environmental sustainability in the context of Pakistan using annual time series dataset spanning from 1990 to 2020. The short-run and long-run associations among explained and explanatory variables were investigated using the symmetric, asymmetric, and quantile autoregressive distributed lag models. The findings of the study demonstrated that low-carbon economy, green energy consumption, ecological innovation, urbanization, GDP per capita, and labor force are cointegrated for the long-term association in symmetric, asymmetric, and quantile autoregressive distributed lag models. Furthermore, green energy consumption and effective eco-innovation are the most important paths to ensure environmental sustainability, while urbanization, GDP per capita, and labor force contribute negatively to the low-carbon economy. The findings of the study provide a policy framework for the development of a comprehensive strategy to promote environmental sustainability in Pakistan by emphasizing green energy consumption, ecological innovation, and controlled urbanization, as well as the incorporation of environment friendly policies into economic development policies.

Economic analysis of different throughput scenarios and implementation strategies of computer-aided detection software as a screening and triage test for pulmonary TB.

BACKGROUND: Artificial Intelligence (AI) systems have demonstrated potential in detecting tuberculosis (TB) associated abnormalities from chest X-ray (CXR) images. Thus, they might provide a solution to radiologist shortages in high TB burden countries. However, the cost of implementing computer-aided detection (CAD) software has thus far been understudied. In this study, we performed a costing analysis of CAD software when used as a screening or triage test for pulmonary TB, estimated the incremental cost compared to a radiologist reading of different throughput scenarios, and predicted the cost for the national scale-up plan in Pakistan. METHODS: For the study, we focused on CAD software reviewed by the World Health Organization (CAD4TB, Lunit INSIGHT CXR, qXR) or listed in the Global Drug Facility diagnostics catalogue (CAD4TB, InferRead). Costing information was obtained from the CAD software developers. CAD4TB and InferRead use a perpetual license pricing model, while Lunit and qXR are priced per license for restricted number of scans. A major implementer in Pakistan provided costing information for human resource and software training. The per-screen cost was estimated for each CAD software and for radiologist for 1) active case finding, and 2) facility based CXR testing scenarios with throughputs ranging from 50,000-100,000 scans. Moreover, we estimated the scale-up cost for CAD or radiologist CXR reading in Pakistan based on the National Strategic Plan, considering that to reach 80% diagnostic coverage, 50% of TB patients would need to be found through facility-based triage and 30% through active case finding (ACF). RESULTS: The per-screen cost for CAD4TB (0.25 USD- 2.33 USD) and InferRead (0.19 USD- 2.78 USD) was lower than that of a radiologist (0.70 USD- 0.93 USD) for high throughput scenarios studied. In comparison, the per-screen cost for Lunit (0.94 USD- 1.69 USD) and qXR (0.95 USD-1.9 USD) were only comparable with that of the radiologists in the highest throughput scenario in ACF. To achieve 80 percent diagnostic coverage at scale in Pakistan, the projected additional cost of deploying CAD software to complement the current infrastructure over a four-year period were estimated at 2.65-19.23 million USD, whereas Human readers, would cost an additional 23.97 million USD. CONCLUSIONS: Our findings suggest that using CAD software could enable large-scale screening programs in high TB-burden countries and be less costly than radiologist. To achieve minimum cost, the target number of screens in a specific screening strategy should be carefully considered when selecting CAD software, along with the offered pricing structure and other aspects such as performance and operational features. Integrating CAD software in implementation strategies for case finding could be an economical way to attain the intended programmatic goals.

Realized Heritability, Risk Assessment, and Inheritance Pattern in Earias vittella (Lepidoptera: Noctuidae) Resistant to Dipel (Bacillus thuringiensis Kurstaki).

Earias vittella Fabricius is a potential cotton and okra pest in South Asia. The realized heritability, risk assessment, and inheritance mode of Bacillus thuringiensis Kurstaki (Btk) resistance were determined in the Dipel-selected (DIPEL-SEL) E. vittella. The DIPEL-SEL strain had a 127.56-fold rise in Dipel resistance after nine generations compared to the laboratory reference strain (LAB-PK). The overlapping of 95% fiducial limits in the median lethal concentrations (LC50s) of the F1 (DIPEL-SEL♂ × LAB-PK♀) and F1ǂ (DIPEL-SEL♀ × LAB-PK♂) suggested a lack of sex linkage and an autosomal Dipel resistance. The dominance (DLC) values for the F1 (0.86) and F1ǂ (0.94) indicated incompletely dominant resistance to Dipel. Backcrossing of the F1♀ × Lab-PK♂ revealed a polygenic response of resistance to Dipel. The realized heritability estimation (h2) of resistance to Dipel was 0.19. With 20% to 90% selection mortality, the generations required for a tenfold increase in LC50 of Dipel were 4.7-22.8, 3.1-14.9, and 2.3-11.1 at h2 of 0.19, 0.29, and 0.39, respectively, and a constant slope of 1.56. At slope values of 2.56 and 3.56 with a constant h2 = 0.19, 7.7-37.4 and 10.6-52.0 generations were needed to increase the tenfold LC50 of Dipel in the DIPEL-SEL E. vittella. It is concluded that the DIPEL-SEL E. vittella has an autosomal, incompletely dominant, and polygenic nature of resistance. The h2 of 0.19 suggested that a high proportion of phenotypic variation for the Dipel resistance in E. vittella was heritable genetic variation. The present results will support the creation of an effective and suitable resistance management plan for better control of E. vittella.

Are globalization, urbanization, and energy consumption cause carbon emissions in SAARC region? New evidence from CS-ARDL approach.

This study examines the impact of energy consumption, urbanization, and globalization on environmental degradation proxied by carbon emissions (CO2) in the South Asian Association for Regional Cooperation (SAARC) countries, namely Sri Lanka, Pakistan, Maldives, Nepal, Bhutan, Bangladesh, and India using data over the period 1990-2018. The cross-sectional autoregressive distributed lag (CS-ARDL), pooled mean group (PMG), and Dumitrescu and Hurlin (D-H) Granger causality techniques are employed for the empirical analysis. First and second-generation panel unit root tests are used to determine the stationary level of all data series which reveals mixed order of integration. The empirical findings show that urbanization, gross domestic product (GDP) per capita income, energy consumption, industrial growth, globalization, and financial development cause CO2 emissions, while the other variables, namely arable land and innovation, put negative effects on CO2 emissions. Moreover, the D-H heterogeneous test results exhibit that bi-directional relationship exists between CO2 and arable land, urbanization, industrial growth, and financial development, while a unidirectional causality exists between CO2 emissions and GDP per head income. These findings suggest that planned urbanization, investment in renewable energy sources, and effective strategies regarding the economic and financial integration with the global economies are required for a clean and green environment.

Implementing work place based assessment: The modified direct observation of procedural skills (DOPS) across medical specialties - An experience from a developing country.

OBJECTIVE: To assess the skill level of residents regarding central venous catheterisation insertion, and to assess the reliability of scores in a simulated situation. METHODS: The quasi-experimental study with pre- and post-test design was conducted from February to June 2013 at the Aga Khan University, Karachi, and comprised four workshops attended by residents. The workshops were video-recorded for feedback and self-assessment. At the end of the workshops, knowledge and procedural skills were assessed using a self-generated 38-item, task-specific instrument after ensuring its content validity. Data was analysed using SPSS 19. RESULTS: There were 40 residents in the sample. The self-generated instrument was reliable with Cronbach's alpha value 0.83 and inter-rater coefficient 0.79. There was significant improvement in the skills level post-intervention compared to the baselines mean values (p=0.001). The subjects were satisfied with the workshops, as indicated by a mean score of 8.83±1.367. CONCLUSIONS: The workshops appeared to improve the central venous catheterisation insertion skills of the residents.

Heterogeneous effect of GHG emissions and fossil energy on well-being and income in emerging economies: a critical appraisal of the role of environmental stringency and green energy.

The new Agenda 2030 for sustainable development call for initiatives to bridge the gap between environmental protection and socio-economic development. To provide insight on the relationship between socio-economics, and ecology, the current study examines the effectiveness of environmental stringency and green energy to mitigate the effects of fossil energy and greenhouse gas emissions on human well-being and income for 12 emerging economies. The outcomes from dynamic heterogeneous panel estimators of cross-sectional-based auto regressive distributed lag and cross-sectional-augmented distributed lag indicate that: (i) green energy consumption and electricity consumption have a substantial positive effect on well-being and per capita income. (ii) The stringent environmental policy is found to decrease per capita income, but it increases well-being, while the square of environmental stringency is found to increase per capita income. (iii) Fossil energy consumption and greenhouse gas emissions have a negative effect on well-being but a positive impact on income. The outcome of U-test confirmed the presence of a U-shaped curve with a turning point (0.433) between per capita income and environmental policy stringency. This study yielded consistent results from the panel Granger causality test. Based on our findings, we may argue that it is necessary to prioritize human well-being over economic growth, and suggest several policy implications to achieve sustainable development goals.

Re-examining the nexuses of communicable diseases, environmental performance, and dynamics of sustainable Development in OECD countries.

We investigate the determinants of communicable diseases (CDs) and nexus of financial development, economic development, and renewable energy consumption to address the issues of ecological footprint level, the impacts of communicable diseases (CDs), and economic growth of the OECD countries throughout 2000-2019. The results from FMOLS and DOLS reveal that the levels of financial development, energy consumption, and trade volume significantly contribute to overcoming the death toll occurring due to CDs. As regards the growth function, the level of trade in the economy is significantly associated with economic growth. The findings reveal that the improvements and developments in the financial sectors and trading activities cause a reduction in the infection cases represented by COVID-19. In contrast, economic growth does have a negative but insignificant impact upon COVID-19. We conclude that sound financial development combined with economic and environmental regulations could be strategically helpful to cope with CDs.

Globalization toward environmental sustainability and electricity consumption to environmental degradation: does EKC inverted U-shaped hypothesis exist between squared economic growth and CO2 emissions in top globalized economies.

The study inspects the inverted U shape of the environmental Kuznets curve (EKC) hypothesis following the influence of economic growth on CO2 emissions and the reaction of electricity consumption and globalization toward CO2 emissions in top globalized economies. This study has taken the data of the top 9 globalized countries from 1990 to 2019 while adopting fully modified ordinary least squares and dynamic ordinary least squares panel cointegration approaches to determine the long run effects and Dumitrescu and Hurlin panel causality for the directions of the causality among the variables. According to the long-term findings of the research, economic growth and electricity consumption substantially contribute to CO2 secretions. On the other hand, the squared growth and globalization mitigate CO2 emissions and contribute to environmental sustainability. However, the inverse influence of squared growth on CO2 emissions shows the presence of the inverted U shape of the EKC hypothesis. Furthermore, Dumitrescu and Hurlin causality measures have shown the bi-directional causality of electricity consumption and economic growth with CO2 emissions and globalization with economic growth. At the same time, unidirectional causality exists from globalization to CO2 emissions, economic growth to electricity consumption, and electricity consumption to globalization. The study recommends long-term globalization and sustainable development projects to ensure environmental sustainability in these globalized economies.

Competition, capital growth and risk-taking in emerging markets: Policy implications for banking sector stability during COVID-19 pandemic.

This paper investigates how banking competition and capital level impact on the risk-taking behavior of banking institutions in the Middle East and North Africa (MENA) region. The topic is perceived to be of significant importance during the COVID-19 pandemic. We use data for more than 225 banks in 18 countries in the MENA region to test whether increased competition causes banks to hold higher capital ratios. Employing panel data techniques, and distinguishing between Islamic and conventional banks, we show that banks tend to hold higher capital ratios when operating in a more competitive environment. We also provide evidence that banks in the MENA region increase their capitalization levels in response to a higher risk and vice versa. Further, banking concentration (measured by the HH-index) and credit risk have a significant and positive impact on capital ratios of IBs, whereas competition does play a restrictive role in determining the level of their capital. The results hold when controlling for ownership structure, regulatory and institutional environment, bank-specific and macroeconomic characteristics. Our findings inform regulatory authorities concerned with improving the financial stability of banking sector in the MENA region to strengthen their policies in order to force banks to better align with capital requirements and risk during the COVID-19 pandemic.

The discrepancy between admission and discharge diagnoses: Underlying factors and potential clinical outcomes in a low socioeconomic country.

OBJECTIVE: The discrepancy between admission and discharge diagnosis can lead to possible adverse patient outcomes. There are gaps in integrated studies, and less is understood about its characteristics and effects. Therefore, this study was conducted to determine the frequency, characteristics, and outcomes of diagnostic discrepancies at admission and discharge. DESIGN AND DATA SOURCES: This retrospective study reviewed the admitting and discharge diagnoses of adult patients admitted at Aga Khan University Hospital (AKUH), Internal Medicine Department between October 2018 and February 2019. The frequency and outcomes of discrepancies in patient diagnoses were noted among Emergency Department (ED) physician versus admitting physician, admitting physician versus discharge physician, and ED physician versus discharge physician for the full match, partial match, and mismatch diagnoses. The studied outcomes included interdepartmental transfer, Intensive Care Unit (ICU) transfer, in-hospital mortality, readmission within 30 days, and the length of stay. For simplicity, we only analyzed the factors for the discrepancy among ED physicians and discharge physicians. RESULTS: Out of 537 admissions, there were 25.3-27.2% admissions with full match diagnoses while 18.6-19.4% and 45.3-47.9% had mismatch and partial match diagnoses respectively. The discrepancy resulted in an increased number of interdepartmental transfers (5-5.8%), ICU transfers (5.6-8.7%), in-hospital mortality (8-11%), and readmissions within 30 days in ED (14.4%-16.7%). A statistically significant difference was observed for the ward's length of stay with the most prolonged stay in partially matched diagnoses (6.3 ± 5.4 days). Among all the factors that were evaluated for the diagnostic discrepancy, older age, multi-morbidities, level of trainee clerking the patient, review by ED faculty, incomplete history, and delay in investigations at ED were associated with significant discrepant diagnoses. CONCLUSIONS: Diagnostic discrepancies are a relevant and significant healthcare problem. Fixed patient or physician characteristics do not readily predict diagnostic discrepancies. To reduce the diagnostic discrepancy, emphasis should be given to good history taking and thorough physical examination. Patients with older age and multi-morbidity should receive significant consideration.

Concordance Between Clinical and Pathological Response Assessment After Neo-Adjuvant Chemotherapy in Patients With Invasive Lobular Carcinoma.

Background Neo-adjuvant chemotherapy (NAC) is frequently administered in breast carcinoma patients. The clinical response to NAC guides further treatment. The pathological response is not only an independent prognostic factor, but it also guides further treatment and prognosis. Objectives The aim of our study was to find the degree of concordance between clinical and pathological response assessments after NAC in Invasive lobular Carcinoma (ILC) cases by using World Health Organization (WHO) criteria and different pathological systems, respectively. We also tried to identify any useful parameter of clinical assessment that could better correlate with pathologic assessment and provide a better estimation of residual tumor. Methods This retrospective study was conducted on 26 ILC tumors diagnosed in 24 patients who were treated with NAC followed by surgical resection between January 2009 and December 2020. Medical records and microscopy glass slides were reviewed for clinical and pathological response assessments, respectively. Results The pre-treatment tumor area ranged from 1.8-255 cm2 and the mean±SD was 52.2±66.8 cm2. After NAC, complete clinical response was observed in four (15.3%) cases. The clinically assessed mean tumor area significantly reduced from 52.2±66.8 cm2 to 17.2±22.6 cm2 (p-value<0.001). The pathologically assessed mean tumor area (27.4±24.1 cm2) didn't differ significantly from the clinically assessed mean tumor area (17.2±22.6 cm2) (p-value=0.114). Pathologically, the majority of the cases showed partial response, and a complete pathological response was achieved in only two (7.7%) cases. The concordance rates between clinical assessment by the WHO method and pathological assessment of the breast using the Sataloff method, Miller-Payne (MP) system, Residual Cancer Burden system, and Chevallier method were 26.7%, 15.8%, 9%, and 3.5%, respectively, with insignificant p-values. Percentage reduction in clinical size and percentage reduction in tumor cellularity differed significantly (p-value=0.038). Conclusion Clinical response assessment provides a less accurate estimation of residual disease, as it shows poor concordance with pathological assessment using different assessment systems/methods.

n-polynomial exponential type p-convex function with some related inequalities and their applications.

In this paper, the idea and its algebraic properties of n-polynomial exponential type p-convex function have been investigated. Authors prove new trapezium type inequality for this new class of functions. We also obtain some refinements of the trapezium type inequality for functions whose first derivative in absolute value at certain power are n-polynomial exponential type p-convex. At the end, some new bounds for special means of different positive real numbers are provided as well. These new results yield us some generalizations of the prior results. Our idea and technique may stimulate further research in different areas of pure and applied sciences.