Introduction : a divided discipline -- A genealogy of agency -- Reforming a paradigm : constructivism to rational constructivism -- A rational constructivist theory of identity and strategy -- Jerusalem : the unsubstitutable core value -- Jihad for Jerusalem : Israel the tiger 1967-1997 -- Jihad for Jerusalem : Iran the cub 1967-1997 -- Jihad for Jerusalem : Saudi Arabia the paper tiger 1967-1997 -- Jihad for Jerusalem : Jordan the mouse 1967-1997 -- Conclusion : the future of Jerusalem.

This book analyses the state of development of Muslims at the regional level. It explains the linkages between the findings of global, national, and state-level studies with regard to the current status of Muslims and broadens understanding of Muslims and their participation in virtually all major sectors, including the economy, housing, demography, health, migration, state policy, and affirmative action. The book presents the challenges faced by the community and reflects upon the socio-economic and educational conditions of Muslims in Telangana State. (...) It presents a comparative analysis of mortality data, maternal health, delivery care, and child immunization, as well as reproductive health aspects and children’s nutritional status. It shares valuable insights into the impacts of emigration and internal migration on health among local Muslims and presents a detailed analysis of data from the Census of India, NSSO, and Commission of Inquiry on Socio-Economic and Educational Status of Muslims regarding the social, economic, and demographic situation of Muslims in Telangana, as well as their opportunities for development under the newly formed state government. The book would be of great interest to scholars and researchers in development economics, sociology, politics, history, cultural studies, minority studies, Islamic studies, and policy studies, as well as policymakers, civil society activists, and those working in media and journalism. (shrink)

This paper examines incorrect use of oral contraceptives (OCs) in rural Bangladesh by using data from an OC compliance survey. Of the 1031 current users of OCs interviewed, about 13% took their pills out of sequence, while 17% left incorrect intervals between pill packs. Forty per cent of the women reported missing one active pill during the 6 months prior to the survey, and 74% of them took correct action with the missed pill. Of the women who missed two active (...) pills (16%), only 9% took correct action. Multivariate analyses revealed that women's education and their husbands' support helped protect against taking incorrect action with a missed pill. The fieldworker's contact was found to protect against leaving an incorrect interval between pill packs. Women who had membership of non-government organizations were less likely to interrupt their pill use, and more likely to take their pill out of sequence. The present study underscores the need for providing women with more support in their pill use, and advocates that service providers should be the focal point of efforts. Husbands' support is essential to improve the pill-taking behaviour of Bangladeshi women. (shrink)

Clinicians have an obligation to ensure that patients with adequate capacity can make autonomous decisions. Thus, patients who choose to forego treatment and leave hospitals “against medical advice” are typically allowed to do so. But what happens when they require clinicians’ assistance to physically leave? Is it incumbent upon clinicians to not only respect and fulfill patients’ requests with which they disagree, but to physically assist in their fulfillment? We attempt to develop an ethical framework wherein clinicians can honor patients’ (...) wishes without necessarily sacrificing their own moral position. (shrink)

Errors have been the concern of providers and consumers of health care services. However, consumers' perception of medical errors in developing countries is rarely explored. The aim of this study is to assess community members' perceptions about medical errors and to analyse the factors affecting this perception in one Middle East country, Oman.

Volume 20, Issue 7, July 2020, Page 150-152.

In this paper, DSEK model with fractional derivatives of the Atangana-Baleanu Caputo is proposed. This paper gives a brief overview of the ABC fractional derivative and its attributes. Fixed point theory has been used to establish the uniqueness and existence of solutions for the fractional DSEK model. According to this theory, we will define two operators based on Lipschitzian and prove that they are contraction mapping and relatively compact. Ulam-Hyers stability theorem is implemented to prove the fractional DSEK model’s stability (...) in Banach space. Also, fractional Euler’s numerical method is derived for initial value problems with ABC fractional derivative and implemented on fractional DSEK model. The symmetric properties contribute to determining the appropriate method for finding the correct solution to fractional differential equations. The numerical solutions generated using fractional Euler’s method have been plotted for different values of α where α ∈ 0,1 and different step sizes h. Result discussion will be given, describing the changes that occur due to the step size h. (shrink)

Clinical responses to dopamine replacement therapy for individuals with Parkinson’s disease are often difficult to predict. We characterized changes in MDS-UPDRS motor factor scores resulting from a short-duration L-Dopa response, and investigated how the inter-subject clinical differences could be predicted from motor cortical magnetoencephalography. MDS-UPDRS motor factor scores and resting-state MEG recordings were collected during SDR from twenty individuals with a PD diagnosis. We used a novel subject-specific strategy based on linear support vector machines to quantify motor cortical oscillatory frequency (...) profiles that best predicted medication state. Motor cortical profiles differed substantially across individuals and showed consistency across multiple data folds. There was a linear relationship between classification accuracy and SDR of lower limb bradykinesia, although this relationship did not persist after multiple comparison correction, suggesting that combinations of spectral power features alone are insufficient to predict clinical state. Factor score analysis of therapeutic response and novel subject-specific machine learning approaches based on subject-specific neuroimaging provide tools to predict outcomes of therapies for PD. (shrink)

Drawing on the scholarship of Critical Religion, this article shows how the modern category “religion” operates through a gender code which upholds its discursive power and enables the production of religious—and therefore racial—hierarchies. Specifically, it argues that mentioning religion automatically makes gender present in discourse. Acknowledging religion as an inherently gendered category in this way gives further insight into the discursive power and functioning of the religious label. With the example of the Westphalian production of the “myth of religious violence” (...) and the employment of “religion” in colonial contexts, I demonstrate how a gender code upholds and enables the discursive power of religion. Religion is both gendered and gendering. Acknowledging the multiple ways in which religion is gendered and gendering, then, has important bearings on the analysis of religion’s racializing function which is upheld and aided by the gender code through which religion is spoken. (shrink)

The 3D Prandtl fluid flow through a bidirectional extending surface is analytically investigated. Cattaneo–Christov fluid model is employed to govern the heat and mass flux during fluid motion. The Prandtl fluid motion is mathematically modeled using the law of conservations of mass, momentum, and energy. The set of coupled nonlinear PDEs is converted to ODEs by employing appropriate similarity relations. The system of coupled ODEs is analytically solved using the well-established mathematical technique of HAM. The impacts of various physical parameters (...) over the fluid state variables are investigated by displaying their corresponding plots. The augmenting Prandtl parameter enhances the fluid velocity and reduces the temperature and concentration of the fluid. The momentum boundary layer boosts while the thermal boundary layer mitigates with the rising elastic parameter strength. Furthermore, the enhancing thermal relaxation parameter ) reduces the temperature distribution, whereas the augmenting concentration parameter drops the strength of the concentration profile. The increasing Prandtl parameter declines the fluid temperature while the augmenting Schmidt number drops the fluid concentration. The comparison of the HAM technique with the numerical solution shows an excellent agreement and hence ascertains the accuracy of the applied analytical technique. This work finds applications in numerous fields involving the flow of non-Newtonian fluids. (shrink)

This paper examines incorrect use of oral contraceptives (OCs) in rural Bangladesh by using data from an OC compliance survey. Of the 1031 current users of OCs interviewed, about 13% took their pills out of sequence, while 17% left incorrect intervals between pill packs. Forty per cent of the women reported missing one active pill during the 6 months prior to the survey, and 74% of them took correct action with the missed pill. Of the women who missed two active (...) pills (16%), only 9% took correct action. Multivariate analyses revealed that women support helped protect against taking incorrect action with a missed pill. The fieldworker support is essential to improve the pill-taking behaviour of Bangladeshi women. (shrink)

The current study investigates whether tournament incentives motivate chief executive officer to be socially responsible. Furthermore, it explores the role of sub-national institutional contingencies [i.e., state-owned enterprises vs. non-SOEs, foreign-owned entities vs. non-FOEs, cross-listed vs. non-cross-listed, developed region] in CEO tournament incentives and the corporate social responsibility performance relationship. Data were collected from all A-shared companies listed in the stock exchanges of China from 2014 to 2019. The study uses the baseline methodology of ordinary least squares and cluster OLS regression. (...) Moreover, firm-fixed effects regression, two-stage least squares regression, and propensity score matching deal with the endogeneity problem and check the robustness of the results. The results provide reliable evidence that tournament incentives motivate CEOs to be more socially responsible. On the other hand, sub-national institutional contingencies positively affect the association between CEO tournament incentives and CSRP. The findings have important implications for companies and regulators who wish to enhance CSP by providing incentives to top managers. (shrink)

Nowadays, online product reviews have been at the heart of the product assessment process for a company and its customers. They give feedback to a company on improving product quality, planning, and monitoring its business schemes in order to increase sale and gain more profit. They are also helpful for customers to select the right products in less effort and time. Most companies make spam reviews of products in order to increase the products sales and gain more profit. Detecting spam (...) product reviews is a challenging issue in NLP. Numerous machine learning approaches have attempted to detect and classify the product reviews as spam or nonspam. However, in order to improve the classification accuracy, this study has introduced an ensemble machine learning model that combines predictions from multilayer perceptron, K-Nearest Neighbour, and Random Forest and predicts the outcome of the review as spam or real, based on the majority vote of the contributing models. In order to accomplish the task of spam review classification, the proposed ensemble and other benchmark boosting approaches are tested with 25 statistical features extracted from mobile application reviews of Yelp Dataset. Then, three different selection techniques are exploited to diminish the feature space and filter out the top 10 optimal features. The effectiveness of the proposed ensemble, the individual models, and other benchmark boosting approaches is again evaluated with 10 optimal features in terms of classification accuracy. Experimental outcomes illustrate that the proposed ensemble model outperformed the individual classifiers and state-of-the-art boosting approaches like Generalized Boost Regression Model, Extreme Gradient Boost, and AdaBoost Regression Model in terms of classification accuracy. (shrink)

We investigate and analyze the dynamics of hepatitis B with various infection phases and multiple routes of transmission. We formulate the model and then fractionalize it using the concept of fractional calculus. For the purpose of fractionalizing, we use the Caputo–Fabrizio operator. Once we develop the model under consideration, existence and uniqueness analysis will be discussed. We use fixed point theory for the existence and uniqueness analysis. We also prove that the model under consideration possesses a bounded and positive solution. (...) We then find the basic reproductive number to perform the steady-state analysis and to show that the fractional-order epidemiological model is locally and globally asymptotically stable under certain conditions. For the local and global analysis, we use linearization, mean value theorem, and fractional Barbalat’s lemma, respectively. Finally, we perform some numerical findings to support the analytical work with the help of graphical representations. (shrink)

This study has examined the problems’ related to communicativeecology of pilgrim sojourners in Saudi Arabia and its impact on the levelsof their satisfaction with the services provided in a probability sample of439 Pakistani pilgrims. The sojourners’ communication ecology in problemsituations comprises eleven communication sources. Of these, contactswith family/friends and co-pilgrims made top of the list followed by suchcommunity organization sources like information counters, tour operators, andthe Pakistani Hajj mission officials. The mediated sources of contacts with theethnic newspaper, and the mainstream (...) Saudimass media ranked the 3rd and the 4th. The Internet and the digital billboardswere each cited in less than 10 percent of the responses. Stepwise multipleregressions revealed that the most important sources of impact on satisfactionwere: contact with community organizations, family/friends and co-pilgrims,the ethnic newspaper, and the digital screens. Implications of the impact onsatisfaction are discussed for communicating with the pilgrims. (shrink)

Acute Myeloid Leukemia is a kind of fatal blood cancer with a high death rate caused by abnormal cells’ rapid growth in the human body. The usual method to detect AML is the manual microscopic examination of the blood sample, which is tedious and time-consuming and requires a skilled medical operator for accurate detection. In this work, we proposed an AlexNet-based classification model to detect Acute Myeloid Leukemia in microscopic blood images and compared its performance with LeNet-5-based model in Precision, (...) Recall, Accuracy, and Quadratic Loss. The experiments are conducted on a dataset of four thousand blood smear samples. The results show that AlexNet was able to identify 88.9% of images correctly with 87.4% precision and 98.58% accuracy, whereas LeNet-5 correctly identified 85.3% of images with 83.6% precision and 96.25% accuracy. (shrink)

On taking the common distinction between the legal and the ethical as a point of departure, and in an effort to understand Marshall's approach to self-interest, and thereby to his conception of an ethics of commerce, I read three of his essays in the light of some non-technical writings of Frank Hahn and three other Cambridge intellectuals. My larger project connects self-interest and self-deception to a possible ethics of theorizing in economics, and thereby to the ethics of the relationship between (...) the theorist and the theorized, the analyst and the analyzed. (shrink)

Online forums have become the main source of knowledge over the Internet as data are constantly flooded into them. In most cases, a question in a web forum receives several responses, making it impossible for the question poster to obtain the most suitable answer. Thus, an important problem is how to automatically extract the most appropriate and high-quality answers in a thread. Prior studies have used different combinations of both lexical and nonlexical features to retrieve the most relevant answers from (...) discussion forums, and hence, there is no standard/general set of features that could be effectively used for relevant answer/reply post classification. However, this study proposed an answer detection model that is exclusively relying on lexical features and employs a random forest classifier for classification of answers in discussion boards. Experimental results showed that the proposed answer detection model outperformed the baseline technique and other state-of-the-art machine learning algorithms in terms of classification accuracy on benchmark forum datasets. (shrink)

Background. Imposter syndrome, associated with self-doubt and fear despite clear accomplishments and competencies, is frequently detected in medical students and has a negative impact on their well-being. This study aimed to predict the students’ IS using the machine learning ensemble approach. Methods. This study was a cross-sectional design among medical students in Bangladesh. Data were collected from February to July 2020 through snowball sampling technique across medical colleges in Bangladesh. In this study, we employed three different machine learning techniques such (...) as neural network, random forest, and ensemble learning to compare the accuracy of prediction of the IS. Results. In total, 500 students completed the questionnaire. We used the YIS scale to determine the presence of IS among medical students. The ensemble model has the highest accuracy of this predictive model, with 96.4%, while the individual accuracy of random forest and neural network is 93.5% and 96.3%, respectively. We used different performance matrices to compare the results of the models. Finally, we compared feature importance scores between neural network and random forest model. The top feature of the neural network model is Y7, and the top feature of the random forest model is Y2, which is second among the top features of the neural network model. Conclusions. Imposter syndrome is an emerging mental illness in Bangladesh and requires the immediate attention of researchers. For instance, in order to reduce the impact of IS, identifying key factors responsible for IS is an important step. Machine learning methods can be employed to identify the potential sources responsible for IS. Similarly, determining how each factor contributes to the IS condition among medical students could be a potential future direction. (shrink)

With the development of wireless technology, two basic wireless network models that are commonly used, known as infrastructure and wireless ad hoc networks, have been developed. In the literature, it has been observed that channel contention is one of the main reasons for packet drop in WANETs. To handle this problem, this paper presents a routing protocol named CCBR. CCBR tries to determine a least contended path between the endpoints to increase packet delivery ratio and to reduce packet delay and (...) normalized routing overhead. Moreover, throughout the active data section, each intermediate node computes its channel contention value. If an intermediate node detects an increase in channel contention, it notifies the source node. Then the source node determines another least contended route for transmission. The advantages of CCBR are verified in our NS2-based performance study, and the results show that CCBR outperforms ad hoc on-demand distance vector in terms of packet delivery ratio, end-to-end delay, and routing overhead by 4% to 9%. (shrink)

BackgroundThe complexities of the workplace environment in the downstream oil and gas industry contain several safety-risk factors. In particular, instituting stringent safety standards and management procedures are considered insufficient to address workplace safety risks. Most accident cases attribute to unsafe actions and human behaviors on the job, which raises serious concerns for safety professionals from physical to psychological particularly when the world is facing a life-threatening Pandemic situation, i.e., COVID-19. It is imperative to re-examine the safety management of facilities and (...) employees’ well-being in the downstream oil and gas production sector to establish a sustainable governance system. Understanding the inherent factors better that contribute to safety behavior management could significantly improve workplace safety features.ObjectiveThis study investigates employees’ safety behavior management model for the downstream oil and gas industry to consolidate the safety, health and wellbeing of employees in times of COVID-19.MethodsNominal Group Technique was first employed to screen primary behavioral factors from 10 workplace health and safety experts from Malaysia’s downstream oil and gas industry. Consequently, 18 significant factors were identified for further inquiry. Next, the interpretive structural modeling technique was used to ascertain the complex interrelationships between these factors and proposed a Safety Behavioral Management Model for cleaner production.ResultsThis model shows that management commitment, employee knowledge and training, leadership, and regulations contribute significantly to several latent factors. Our findings support the Social Cognitive Theory, where employees, their environment, and their behaviors are related reciprocally.ConclusionIt is postulated that identifying safety factors and utilizing the proposed model guides various stakeholder groups in this industry, including practitioners and policymakers, for achieving long-term sustainability. (shrink)

Responding to a major pandemic and planning for allocation of scarce resources under crisis standards of care requires coordination and cooperation across federal, state and local governments in tandem with the larger societal infrastructure. Maryland remains one of the few states with no state-endorsed ASR plan, despite having a plan published in 2017 that was informed by public forums across the state. In this article, we review strengths and weaknesses of Maryland’s response to COVID-19 and the role of the Maryland (...) Healthcare Ethics Committee Network in bridging gaps in the state’s response to prepare health care facilities for potential implementation of ASR plans. Identified “lessons learned” include: Deliberative Democracy Provided a Strong Foundation for Maryland’s ASR Framework; Community Consensus is Informative, Not Normative; Hearing Community Voices Has Inherent Value; Lack of Transparency & Political Leadership Gaps Generate a Fragmented Response; Pandemic Politics Requires Diplomacy & Persistence; Strong Leadership is Needed to Avoid Implementing ASR … And to Plan for ASR; An Effective Pandemic Response Requires Coordination and Information-Sharing Beyond the Acute Care Hospital; and The Ability to Correct Course is Crucial: Reconsidering No-visitor Policies. (shrink)

A passive brain–computer interface based upon functional near-infrared spectroscopy brain signals is used for earlier detection of human drowsiness during driving tasks. This BCI modality acquired hemodynamic signals of 13 healthy subjects from the right dorsolateral prefrontal cortex of the brain. Drowsiness activity is recorded using a continuous-wave fNIRS system and eight channels over the right DPFC. During the experiment, sleep-deprived subjects drove a vehicle in a driving simulator while their cerebral oxygen regulation state was continuously measured. Vector phase analysis (...) was used as a classifier to detect drowsiness state along with sleep stage-based threshold criteria. Extensive training and testing with various feature sets and classifiers are done to justify the adaptation of threshold criteria for any subject without requiring recalibration. Three statistical features along with six VPA features were used. The average accuracies for the five classifiers are 90.9% for discriminant analysis, 92.5% for support vector machines, 92.3% for nearest neighbors, 92.4% for both decision trees, and ensembles over all subjects’ data. Trajectory slopes of CORE vector magnitude and angle: m and m are the best-performing features, along with ensemble classifier with the highest accuracy of 95.3% and minimum computation time of 40 ms. The statistical significance of the results is validated with a p-value of less than 0.05. The proposed passive BCI scheme demonstrates a promising technique for online drowsiness detection using VPA along with sleep stage classification. (shrink)

In this paper, an intelligent neural network-based controller is designed and implemented to control the speed of a permanent magnet synchronous motor. First, the exact mathematical model of PMSM is presented, and then, by designing a controller, we apply the wind turbine emulation challenges. The designed controller for the first time is implemented on a Arm Cortex-M microcontroller and tested on a laboratory PMSM. Since online learning neural network on a chip requires a strong processor, high memory, and convergence guarantee, (...) this article uses the offline method. In this method, first, for different work points, the neural network is trained by local controllers, and then, the trained network is implemented on the chip and used. Uncertainty in the parameters and the effect of load torque as challenges of control systems are applied in the proposed method, and a comparison with other methods is performed in the implementation results section. (shrink)