The Allusions of Behavioral Finance

The deliberation in theoretical finance among the Efficient Market Hypothesis (EMH) and the subject of the behavioral finance is of immense interest. from the time when its emerge, the EMH has been the most significant theory which describes the behavior of the diverse agents in the financial markets and overlooks more or less any prospective impact of human behavior in the investment method. From the end of 1970s and the commencement of 1980s, a rising number of researchers and scholars showed the irregularity of this theory. The anomalies of the recent portfolio models and theories have provoked the development of behavioral finance. Behavioral finance assimilates psychology and economics in finance theory and has its heredity in theground-breaking work of great psychologists Tversky and Daniel Kahneman (1979). The rationale of this study is to present a synthesis of the behavioral finance literature over the last two decades. Keywords: Efficient Market Hypothesis, Financial Market, arbitrage, Cognitive dissonance, Regret avoidance Type: Literature Revie

Establishing Reference Intervals for HBA1C in all three Trimesters of Pregnancy; A Cross-Sectional Study on Healthy Pregnant Women of Quetta, Baluchistan

Objective: To establish the reference intervals in healthy pregnant females of Quetta, Baluchistan, for Glycosylated Hemoglobin (HbA1c) in all three trimesters of pregnancy. Study Design: Cross-sectional study. Place and Duration of Study: Pathology Department Combined Military Hospital, Quetta Pakistan, from Jun 2018 to Jun 2019. Methodology: Blood samples of healthy pregnant females were drawn for Glycosylated haemoglobin (HbA1c). Fasting plasma glucose and haemoglobin were also measured to rule out hyperglycemia and anaemia. Samples for Glycated haemoglobin(HbA1c) were analyzed by Turbidimetric Immuno-inhibition (TINIA) method. For all the trimesters, 5th and 95th percentiles were taken as reference intervals for Glycosylated haemoglobin (HbA1c) and compared for each trimester. Results: A total of 388 samples were taken, of which 136(35.05%) females were from the first trimester, 128(32.98%) and 124(31.97%) from the second and third trimesters, respectively. The mean age of the study population was 25.1±3.7 years in the first trimester, 26.7±4.5 years in the second-trimester while and the third trimester it was 26.8±4.8 years. In the first, second,and third trimesters, the reference intervals for Glycosylated haemoglobin (HbA1c) were 3.8-5.2%, 4.1-5.4%, and 4.2-5.7%,respectively. Conclusion: For the exact diagnosis of hyperglycemia in pregnancy, each laboratory should establish its reference intervals of Glycated haemoglobin (HbA1c) for each trimester as it varies from trimester to trimester

Financial hazard assessment for electricity suppliers due to power outages: the revenue loss perspective

The electrical power infrastructure of the modern world is advanced, efficient, and robust, yet power outages still occur. In addition to affecting millions of people around the world, these outage events cost billions of dollars to the global economy. In this paper, the revenue loss borne by electricity-supplying companies in the United States due to power outage events is estimated and predicted. Various factors responsible for power outages are considered in order to present an exploratory data analysis at the U.S. level, followed by the top ten affected states, which bear over 85% of the total revenue loss. The loss is computed using historic observational data of electricity usage patterns and the tariff offered by the energy suppliers. The study is supplemented with reliable and publicly available records, including electricity usage patterns, the consumer category distribution, climatological annotations, population density, socio-economic indicators and land area. Machine learning techniques are used to predict the revenue loss for future outage events, as well as to characterize the key parameters for efficient prediction and their partial dependence. The results show that the revenue loss is a function of several parameters, including residential sales, percentage of industrial customer, time-period of the year, and economic indicators. This study may help energy suppliers make risk-informed decisions, while developing revenue generation strategies as well as identifying safer investment avenues for long-term returns

Global genetic diversity and evolutionary patterns among Potato leafroll virus populations

Potato leafroll virus (PLRV) is a widespread and one of the most damaging viral pathogens causing significant quantitative and qualitative losses in potato worldwide. The current knowledge of the geographical distribution, standing genetic diversity and the evolutionary patterns existing among global PLRV populations is limited. Here, we employed several bioinformatics tools and comprehensively analyzed the diversity, genomic variability, and the dynamics of key evolutionary factors governing the global spread of this viral pathogen. To date, a total of 84 full-genomic sequences of PLRV isolates have been reported from 22 countries with most genomes documented from Kenya. Among all PLRV-encoded major proteins, RTD and P0 displayed the highest level of nucleotide variability. The highest percentage of mutations were associated with RTD (38.81%) and P1 (31.66%) in the coding sequences. We detected a total of 10 significantly supported recombination events while the most frequently detected ones were associated with PLRV genome sequences reported from Kenya. Notably, the distribution patterns of recombination breakpoints across different genomic regions of PLRV isolates remained variable. Further analysis revealed that with exception of a few positively selected codons, a major part of the PLRV genome is evolving under strong purifying selection. Protein disorder prediction analysis revealed that CP-RTD had the highest percentage (48%) of disordered amino acids and the majority (27%) of disordered residues were positioned at the C-terminus. These findings will extend our current knowledge of the PLRV geographical prevalence, genetic diversity, and evolutionary factors that are presumably shaping the global spread and successful adaptation of PLRV as a destructive potato pathogen to geographically isolated regions of the world

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Sars-Cov-2 Infection with Polymyositis- A Case Report

Among the most prevalent and least addressed symptoms of SARS-CoV-2 infection are myalgia, muscle weakness, and body aches. Only a few studies have reported polymyositis in patients with Covid-19 infection. At least one-third of patients with Covid-19 syndrome had elevated CPK levels. The cause of elevated CPK can be a cytokine storm or viral infection of the muscles. We present a case in which our patient developed features of myositis following the resolution of an acute viral prodrome caused by SARS-CoV-2. Our patient had both radiological and biopsy-proven neuromuscular manifestations of SARS-CoV-2 associated with polymyositis. Proximal muscle weakness began shortly after the resolution of the initial infection and progressed gradually over weeks or months, resulting in immobility. In the aftermath of investigations, the patient was diagnosed with polymyositis, appropriate treatment was started, and he showed signs of improvement

Deploying Viruses against Phytobacteria: Potential Use of Phage Cocktails as a Multifaceted Approach to Combat Resistant Bacterial Plant Pathogens

Plants in nature are under the persistent intimidation of severe microbial diseases, threatening a sustainable food production system. Plant-bacterial pathogens are a major concern in the contemporary era, resulting in reduced plant growth and productivity. Plant antibiotics and chemical-based bactericides have been extensively used to evade plant bacterial diseases. To counteract this pressure, bacteria have evolved an array of resistance mechanisms, including innate and adaptive immune systems. The emergence of resistant bacteria and detrimental consequences of antimicrobial compounds on the environment and human health, accentuates the development of an alternative disease evacuation strategy. The phage cocktail therapy is a multidimensional approach effectively employed for the biocontrol of diverse resistant bacterial infections without affecting the fauna and flora. Phages engage a diverse set of counter defense strategies to undermine wide-ranging anti-phage defense mechanisms of bacterial pathogens. Microbial ecology, evolution, and dynamics of the interactions between phage and plant-bacterial pathogens lead to the engineering of robust phage cocktail therapeutics for the mitigation of devastating phytobacterial diseases. In this review, we highlight the concrete and fundamental determinants in the development and application of phage cocktails and their underlying mechanism, combating resistant plant-bacterial pathogens. Additionally, we provide recent advances in the use of phage cocktail therapy against phytobacteria for the biocontrol of devastating plant diseases

Data_Sheet_2_Global genetic diversity and evolutionary patterns among Potato leafroll virus populations.docx

Potato leafroll virus (PLRV) is a widespread and one of the most damaging viral pathogens causing significant quantitative and qualitative losses in potato worldwide. The current knowledge of the geographical distribution, standing genetic diversity and the evolutionary patterns existing among global PLRV populations is limited. Here, we employed several bioinformatics tools and comprehensively analyzed the diversity, genomic variability, and the dynamics of key evolutionary factors governing the global spread of this viral pathogen. To date, a total of 84 full-genomic sequences of PLRV isolates have been reported from 22 countries with most genomes documented from Kenya. Among all PLRV-encoded major proteins, RTD and P0 displayed the highest level of nucleotide variability. The highest percentage of mutations were associated with RTD (38.81%) and P1 (31.66%) in the coding sequences. We detected a total of 10 significantly supported recombination events while the most frequently detected ones were associated with PLRV genome sequences reported from Kenya. Notably, the distribution patterns of recombination breakpoints across different genomic regions of PLRV isolates remained variable. Further analysis revealed that with exception of a few positively selected codons, a major part of the PLRV genome is evolving under strong purifying selection. Protein disorder prediction analysis revealed that CP-RTD had the highest percentage (48%) of disordered amino acids and the majority (27%) of disordered residues were positioned at the C-terminus. These findings will extend our current knowledge of the PLRV geographical prevalence, genetic diversity, and evolutionary factors that are presumably shaping the global spread and successful adaptation of PLRV as a destructive potato pathogen to geographically isolated regions of the world.</p

Data_Sheet_1_Global genetic diversity and evolutionary patterns among Potato leafroll virus populations.CSV

Potato leafroll virus (PLRV) is a widespread and one of the most damaging viral pathogens causing significant quantitative and qualitative losses in potato worldwide. The current knowledge of the geographical distribution, standing genetic diversity and the evolutionary patterns existing among global PLRV populations is limited. Here, we employed several bioinformatics tools and comprehensively analyzed the diversity, genomic variability, and the dynamics of key evolutionary factors governing the global spread of this viral pathogen. To date, a total of 84 full-genomic sequences of PLRV isolates have been reported from 22 countries with most genomes documented from Kenya. Among all PLRV-encoded major proteins, RTD and P0 displayed the highest level of nucleotide variability. The highest percentage of mutations were associated with RTD (38.81%) and P1 (31.66%) in the coding sequences. We detected a total of 10 significantly supported recombination events while the most frequently detected ones were associated with PLRV genome sequences reported from Kenya. Notably, the distribution patterns of recombination breakpoints across different genomic regions of PLRV isolates remained variable. Further analysis revealed that with exception of a few positively selected codons, a major part of the PLRV genome is evolving under strong purifying selection. Protein disorder prediction analysis revealed that CP-RTD had the highest percentage (48%) of disordered amino acids and the majority (27%) of disordered residues were positioned at the C-terminus. These findings will extend our current knowledge of the PLRV geographical prevalence, genetic diversity, and evolutionary factors that are presumably shaping the global spread and successful adaptation of PLRV as a destructive potato pathogen to geographically isolated regions of the world.</p

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundEstimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.Methods22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.FindingsGlobal all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.InterpretationGlobal adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic