An artificial intelligence and NLP based Islamic FinTech model combining Zakat and Qardh-Al-Hasan for countering the adverse impact of COVID 19 on SMEs and individuals

Pursose: The ongoing Corona virus (COVID 19) pandemic has already impacted almost everyone across the globe. The focus has now shifted from spread of the disease to the economic consequences it will bring to the society. The shortage of production will result into the shortage of supply and consequently will end as loss of jobs and employment for millions of people around the world. Two of the most important section of our society i.e., daily wage laborers and Small and Medium Enterprises (SMEs) will have to bear the major burnt of this crisis. The proposed integrated Artificial Intelligence and NLP based Islamic FinTech Model combining Zakat (Islamic tax) and Qardh-Al-Hasan (benevolent loan) can help the economy to minimize the adverse impact of COVID 19 on individuals and SMEs. Design/Methodology/Approach: The present study explores the possibility of Zakat and Qardh-Al-Hasan as a financing method to fight the adverse impact of Corona virus on poor individuls and SMEs. It provides the solution by proposing an Artificial Intelligence and NLP based Islamic FinTech Model combining Zakat and Qardh-Al-Hasan. Findings: The findings of the study reveals that Islamic finance has immense potential to fight any kind of situation/pandemic. Zakat and Qardh-Al-Hasan, if combined together can prove to be a deadly combination to fight the adverse effect of COVID 19. Practical Implications: To be used as an effective way to support individuals and SMEs in the period during and after the pandemic of COVID 19. Originality/value: There is no study combining Zakat and Qardh Al-Hasan to fight the adverse effect of poor individuals and SMEs. The study will contribute massively to the existing literature and will help the government and civil societies in fighting the economic impact of COVID 19 on individuals and SMEs.peer-reviewe

Unexplained Gaps and Oaxaca-Blinder Decompositions

We analyze four methods to measure unexplained gaps in mean outcomes: three decompositions based on the seminal work of Oaxaca (1973) and Blinder (1973) and an approach involving a seemingly naïve regression that includes a group indicator variable. Our analysis yields two principal findings. We show that the coefficient on a group indicator variable from an OLS regression is an attractive approach for obtaining a single measure of the unexplained gap. We also show that a commonly-used pooling decomposition systematically overstates the contribution of observable characteristics to mean outcome differences when compared to OLS regression, therefore understating unexplained differences. We then provide three empirical examples that explore the practical importance of our analytic results.discrimination, decompositions

Age at quitting smoking as a predictor of risk of cardiovascular disease incidence independent of smoking status, time since quitting and pack-years

BACKGROUND Risk prediction for CVD events has been shown to vary according to current smoking status, pack-years smoked over a lifetime, time since quitting and age at quitting. The latter two are closely and inversely related. It is not known whether the age at which one quits smoking is an additional important predictor of CVD events. The aim of this study was to determine whether the risk of CVD events varied according to age at quitting after taking into account current smoking status, lifetime pack-years smoked and time since quitting. FINDINGS We used the Cox proportional hazards model to evaluate the risk of developing a first CVD event for a cohort of participants in the Framingham Offspring Heart Study who attended the fourth examination between ages 30 and 74 years and were free of CVD. Those who quit before the median age of 37 years had a risk of CVD incidence similar to those who were never smokers. The incorporation of age at quitting in the smoking variable resulted in better prediction than the model which had a simple current smoker/non-smoker measure and the one that incorporated both time since quitting and pack-years. These models demonstrated good discrimination, calibration and global fit. The risk among those quitting more than 5 years prior to the baseline exam and those whose age at quitting was prior to 44 years was similar to the risk among never smokers. However, the risk among those quitting less than 5 years prior to the baseline exam and those who continued to smoke until 44 years of age (or beyond) was two and a half times higher than that of never smokers. CONCLUSIONS Age at quitting improves the prediction of risk of CVD incidence even after other smoking measures are taken into account. The clinical benefit of adding age at quitting to the model with other smoking measures may be greater than the associated costs. Thus, age at quitting should be considered in addition to smoking status, time since quitting and pack-years when counselling individuals about their cardiovascular risk.This research was supported by an NHMRC health services research grant (no. 465130), an NHMRC/NHF PhD scholarship and a Vichealth Fellowship

Relationship between empathy and personality traits in students of a Public Sector Medical University

Introduction: Empathy among medical students and doctors, is rather unexplored part of medical flora and fauna which may vary with each personality. Objective: to determine the correlation between empathy and personality traits of final year medical students. Materials and Methods: This cross-sectional study was conducted at Rawalpindi Medical University, Pakistan. A total of 144 medical students were included in the study. For personality traits assessment and empathy assessment, Big Five Inventory and Interpersonal Reactivity Index were used. All the data was analyzed using SPSS version 20. Results: The mean score for empathy scale was found to be 61.25 ± 10.0. Females were more empathetic than males in all subscales but pointedly so in empathetic concern scale. Overall empathy scale was strongly correlated with Agreeableness and Neuroticism (P<0.001). Perspective taking scale was positively related with Agreeableness and openness, Empathy concern scale was positively related with Agreeableness, and Personal Distress was positively related with Conscientiousness and Neuroticism. The demographic factors of age and gender explained only 1.7%, 6.8%, 2.4% and 2.0% of the variance in the four scales of empathy. After adjustment for age and gender, perspective taking was positively associated with Agreeableness and Openness and Personal distress was associated with Agreeableness, Neuroticism and Openness. Conclusion: We conclude that personality traits have a substantial correlation with empathy and its subscales. So we need to evaluate the personality of a medical student and tailor a set of rules for each individual consistent with their persona to develop empathy in them. Keywords: Big Five; Personality; Empathy; Medical students; Pakista

Relationship between empathy and personality traits in students of a Public Sector Medical University

Introduction: Empathy among medical students and doctors, is rather unexplored part of medical flora and fauna which may vary with each personality. Objective: to determine the correlation between empathy and personality traits of final year medical students. Materials and Methods: This cross-sectional study was conducted at Rawalpindi Medical University, Pakistan. A total of 144 medical students were included in the study. For personality traits assessment and empathy assessment, Big Five Inventory and Interpersonal Reactivity Index were used. All the data was analyzed using SPSS version 20. Results: The mean score for empathy scale was found to be 61.25 ± 10.0. Females were more empathetic than males in all subscales but pointedly so in empathetic concern scale. Overall empathy scale was strongly correlated with Agreeableness and Neuroticism (P<0.001). Perspective taking scale was positively related with Agreeableness and openness, Empathy concern scale was positively related with Agreeableness, and Personal Distress was positively related with Conscientiousness and Neuroticism. The demographic factors of age and gender explained only 1.7%, 6.8%, 2.4% and 2.0% of the variance in the four scales of empathy. After adjustment for age and gender, perspective taking was positively associated with Agreeableness and Openness and Personal distress was associated with Agreeableness, Neuroticism and Openness. Conclusion: We conclude that personality traits have a substantial correlation with empathy and its subscales. So we need to evaluate the personality of a medical student and tailor a set of rules for each individual consistent with their persona to develop empathy in them. Keywords: Big Five; Personality; Empathy; Medical students; Pakista

The Role of Intersectional Stereotypes on Evaluations of Gay and Lesbian Political Candidates

This is the publisher's version, which is also available electronically from: http://dx.doi.org/10.1017/S1743923X09990511Social scientists are increasingly taking a more complex theoretical approach to the role of stereotyping in the electorate’s evaluation of political candidates.Within this literature, most studies investigate the impact of one stereotype on the public’s evaluation of candidates from an underrepresented group. We build on and extend this literature by exploring what we term “intersectional stereotyping”: The role of stereotypes in shaping the electorate’s evaluation of political candidates who share dual membership in stigmatized groups — women and sexual minorities. We empirically examine the impact of intersectional stereotyping in a unique 2003 survey of national adults. Our results indicate that gender, both of the respondent and the candidate, plays a key role in shaping attitudes toward gay and lesbian political candidates. These findings suggest that intersectional stereotyping plays a nuanced role in evaluations of candidates; in certain contexts gender stereotypes are more significant, and at other times stereotypes about sexual minorities appear to be driving evaluations of candidates

Enhancing properties of iron and manganese ores as oxygen carriers for chemical looping processes by dry impregnation

The use of naturally occurring ores as oxygen carriers in CLC processes is attractive because of their relative abundance and low cost. Unfortunately, they typically exhibit lower reactivity and lack the mechanical robustness required, when compared to synthetically produced carriers. Impregnation is a suitable method for enhancing both the reactivity and durability of natural ores when used as oxygen carriers for CLC systems. This investigation uses impregnation to improve the chemical and mechanical properties of a Brazilian manganese ore and a Canadian iron ore. The manganese ore was impregnated with Fe2O3 and the iron ore was impregnated with Mn2O3 with the goal of forming a combined Fe/Mn oxygen carrier. The impregnated ore’s physical characteristics were assessed by SEM, BET and XRD analysis. Measurements of the attrition resistance and crushing strength were used to investigate the mechanical robustness of the oxygen carriers. The impregnated ore’s mechanical and physical properties were clearly enhanced by the impregnation method, with boosts in crushing strength of 11–26% and attrition resistance of 37–31% for the impregnated iron and manganese ores, respectively. Both the unmodified and impregnated ore’s reactivity, for the conversion of gaseous fuel (CH4 and syngas) and gaseous oxygen release (CLOU potential) were investigated using a bench-scale quartz fluidised-bed reactor. The impregnated iron ore exhibited a greater degree of syngas conversion compared to the other samples examined. Iron ore based oxygen carrier’s syngas conversion increases with the number of oxidation and reduction cycles performed. The impregnated iron ore exhibited gaseous oxygen release over extended periods in an inert atmosphere and remained at a constant 0.2% O2 concentration by volume at the end of this inert period. This oxygen release would help ensure the efficient use of solid fuels. The impregnated iron ore’s reactivity for CH4 conversion was similar to the reactivity of its unmodified counterpart. The unmodified manganese ore converted CH4 to the greatest extent of all the samples tested here, while the impregnated manganese ore exhibited a decrease in reactivity with respect to syngas and CH4 conversion.EPSR

Performance Analysis of Full Duplex D2D in Opportunistic Spectrum Access

© 2018 IEEE. Opportunistic Spectrum Access (OSA) allows an efficient use of spectrum based on share-it or use-it principle and can be a viable solution for the challenging problem of spectrum scarcity. Emerging systems have been proposed for OSA, where primary users (PU) have guaranteed interference protection from secondary users (SU). The potential of Full Duplex (FD) and Device-To-device (D2D) technologies in 5G has proven to be promising for increasing data rates and network capacity. In this article using stochastic geometry and random graphs, we model and assess the D2D operations in full Duplex/half Duplex mode for SUs, while protecting the PU's transmission by defining the exclusion zone (EZ). Depending on the location and transmit power of D2D users, the induced aggregate interference should not violate the interference threshold for EZ of PUs. For this, we characterize the interference from D2D links and derive the probability for successful D2D users for half-duplex and full duplex modes. Analyses is further supported by extensive simulations results

Characterization of Laser-Generated Aluminum Plasma Using Ion Time-of-Flight and Optical Emission Spectroscopy

Laser plasma generated by ablation of an Al target in vacuum is characterized by ion time-of-flight combined with optical emission spectroscopy. A Q-switched Nd:YAG laser (wavelength λ = 1064 nm, pulse width τ ∼ 7 ns, and fluence F ≤ 38 J/cm2) is used to ablate the Al target. Ion yield and energy distribution of each charge state are measured. Ions are accelerated according to their charge state by the double-layer potential developed at the plasma-vacuum interface. The ion energy distribution follows a shifted Coulomb-Boltzmann distribution. Optical emission spectroscopy of the Al plasma gives significantly lower plasma temperature than the ion temperature obtained from the ion time-of-flight, due to the difference in the temporal and spatial regions of the plasma plume probed by the two methods. Applying an external electric field in the plasma expansion region in a direction parallel to the plume expansion increases the line emission intensity. However, the plasma temperature and density, as measured by optical emission spectroscopy, remain unchanged