Nielsen Busch and Mjaaland (2023) raise important considerations, but confuse certain critical issues and overlook others, and questions emerge about how these decisions should be made in our socie...

Tuberculosis is caused by bacillus Mycobacterium tuberculosis. In this study, a mathematical model of tuberculosis is analyzed. The numerical behaviour of the considered model is analyzed including basic reproduction number and stability. We applied three numerical techniques to this model, i.e., nonstandard finite difference scheme, Runge–Kutta method of order 4, and forward Euler scheme. NSFD scheme preserves all the essential properties of the model. Acquired results corroborate that NSFD scheme converges for each step size. While the other two schemes failed (...) to preserve some properties of the model such as positivity and convergence. A graphical comparison presented in this study confirms the numerical stability of the NSFD technique shown here is maintained over a large area. (shrink)

If one thing that the failed coup by a small but some of the top hierarchy of Turkish armed forces on that fateful July 15, 2016 day made clear, it was: the ordinary civilians, unarmed as they were poured into the streets to defend the government whatever way they can. This massive public sympathy and support for Turkish resident Erdogan and his government would be hard, if not impossible to understand, without knowing the historical intellectual, academic, and moral combat between (...) the modernists and Islamist groups working within the country. Mustafa Kamal had turned Turkey, mostly by force, from Ottoman Empire into the secular mode using military power. Various Islamic revolutionary outfits struggled for the revival of Ottoman Empire. Among them Bedi-uz-Zaman Said Nursi managed to cast a strong influence. A little slow but steadfast effort influenced by Nursi movement. Islam-shy Western powers managed alternate power structure against sitting President Tayyep Erdogan. They, however, failed due to result oriented social work delivered by his regime as Mayor and Prime Minister. It is a lesson for other revolutionaries and Governments especially for Islamic revolutionaries that if politicians deliver no power can oust them like a bee from butter. (shrink)

Based on the Lotka–Volterra system, a pest-natural enemy model with nonlinear feedback control as well as nonlinear action threshold is introduced. The model characterizes the implementation of comprehensive prevention and control measures when the pest density reaches the nonlinear action threshold level depending on the pest density and its change rate. The mortality rate of the pest is a saturation function that strictly depends on their density while the release of natural enemies is also a nonlinear pulse term depending on (...) the density of real-time natural enemies. The exact impulsive and phase sets are given. The definition and properties of the Poincaré map corresponding to the pulse points on the phase set are provided. We investigate the existence and stability of boundary and interior order-1 periodic solution. The theoretical analysis developed in the present paper combined with nonlinear controlling measures as well as nonlinear action threshold methods and techniques laid the foundation for the establishment and analysis of other state-dependent feedback control models. (shrink)

This study uncovers a new finding on the impact of CEO tenure on corporate social and environmental performance (CS&EP) in coastal and non-coastal areas of China using fixed-effect panel data regression models. The Two-Stage Least Squares instrumental panel regression is used to validate the veracity of the empirical results. To this end, we extract data from all non-financial Chinese listed firms for the period of 2009 to 2015. By applying the multivariant framework, the findings of the study exhibit a negative (...) and significant effect of CEO tenure on CS&EP. Moreover, this study shows that firms with head offices in coastal areas of China tend to weaken the negative impact of CEO tenure on CS&EP, indicating that CS&EP is more focused in coastal areas of China than non-coastal ones. The findings suggest that the increase in CEOs’ CS&EP in the early years of their service tenure tends to increase their compensation packages. This study is useful for policymakers to link CS&EP with firm economic practices to attain sustainable development objectives. (shrink)

Our objective is to examine the effects of Big Five personality traits on ethical ideologies using a time-lagged design of 406 employees of higher education institutions in Pakistan. Based on low/high idealism versus relativism, we investigate the conceptual linkage between each of the personality traits and moral philosophy. The results illustrate that extraversion and openness to experience believed on subjectivism moral philosophy, agreeableness believed on situationism, and neuroticism believed on absolutism moral philosophies. In addition, contentiousness believed on exceptionism moral philosophy. (...) Furthermore, managerial implications and future research directions are suggested. (shrink)

As COVID-19 pandemic continued to propagate, millions of lives are currently at risk especially elderly, people with chronic conditions and pregnant women. Iraq is one of the countries affected by the COVID-19 pandemic. Currently, in Iraq, there is a need for a self-assessment tool to be available in hand for people with COVID-19 concerns. Such a tool would guide people, after an automated assessment, to the right decision such as seeking medical advice, self-isolate, or testing for COVID-19. This study proposes (...) an online COVID-19 self-assessment tool supported by the internet of medical things (IoMT) technology as a means to fight this pandemic and mitigate the burden on our nation’s healthcare system. Advances in IoMT technology allow us to connect all medical tools, medical databases, and devices via the internet in one collaborative network, which conveys real-time data integration and analysis. Our IoMT framework-driven COVID-19 self-assessment tool will capture signs and symptoms through multiple probing questions, storing the data to our COVID-19 patient database, then analyze the data to determine whether a person needs to be tested for COVID-19 or other actions may require to be taken. Further to this, collected data can be integrated and analyzed collaboratively for developing a national health policy and help to manage healthcare resources more efficiently. The IoMT framework-driven online COVID-19 self-assessment tool has a big potential to prevent our healthcare system from being overwhelmed using real-time data collection, COVID-19 databases, analysis, and management of people with COVID-19 concerns, plus providing proper guidance and course of action. (shrink)

During the COVID-19 outbreak, educational institutions were closed, and students worldwide were confined to their homes. In an educational environment, students depend on collaborative learning to improve their learning performance. This study aimed to increase the understanding of social media adoption among students during the COVID-19 pandemic for the purpose of CL. Social media provides a learning platform that enables students to easily communicate with their peers and subject specialists, and is conducive to students' CL. This study addresses the key (...) concept of CL during the COVID-19 pandemic by assessing social media use among students in higher education. The relationship between social media use and students' performance is crucial to understanding the role of social media during a pandemic. This study is based on constructivism theory and the technology acceptance model. Structural equation modeling was used to analyze the conceptual model using SmartPLS. The research findings indicate that social media plays an important role during the pandemic because it provides opportunities for students to enhance CL under the aforementioned situations. This study makes noteworthy theoretical and practical contributions. (shrink)

In developing countries, the patriarchal social construct, unsatisfactory legal protection, and underlying cultural bias against women have resulted in increasing intimate partner violence, which largely goes unaddressed, undocumented, and unreported in healthcare settings. This case study presents a common scenario of intimate partner violence and carefully analyzes its ethical implications in an emergency case at a tertiary care hospital in Karachi, Pakistan. In this study, basic ethical principles are used to discuss important ethical challenges faced daily by healthcare workers in (...) the medical, social, and legal context. It further highlights the dire need of patient education, safety, and a solid framework for addressing, documenting, and reporting intimate partner violence for healthcare workers. (shrink)

The food security of more than half of the world’s population depends on rice production which is one of the key objectives of precision agriculture. The traditional rice almanac used astronomical and climate factors to estimate yield response. However, this research integrated meteorological, agro-chemical, and soil physiographic factors for yield response prediction. Besides, the impact of those factors on the production of three major rice ecotypes has also been studied in this research. Moreover, this study found a different set of (...) those factors with respect to the yield response of different rice ecotypes. Machine learning algorithms named Extreme Gradient Boosting and Support Vector Regression have been used for predicting the yield response. The SVR shows better results than XGBoost for predicting the yield of the Aus rice ecotype, whereas XGBoost performs better for forecasting the yield of the Aman and Boro rice ecotypes. The result shows that the root mean squared error of three different ecotypes are in between 9.38% and 24.37% and that of R-squared values are between 89.74% and 99.13% on two different machine learning algorithms. Moreover, the explainability of the models is also shown in this study with the help of the explainable artificial intelligence model called Local Interpretable Model-Agnostic Explanations. (shrink)

On November 2019, the world commemorated the 30th anniversary of the United Nations’ Convention on the Rights of the Child. The UNCRC noted that “the press and other media have essential fu...

Present era can be categorized due to its speed of changes. Pakistani society got affected by worst kind of terrorism and extremism in last fifteen years. The root causes of prevailing security environment in Pakistan are multifaceted, complex and are derived from structural, as well as micro-level conditions. Objective of this research is to highlight the gaps in security doctrine of Pakistan. Both qualitative and quantitative methodology in the format of Knowledge Attitude and Practice is selected. Primary question of this (...) research was to find the gaps in national internal security policy of Pakistan. This primary question is further sub divided into ten sub questions. Implementation modalities and the impediments of National Internal Security Policy 2014 are also discussed. This research finds out that national internal security policy 2014 was a vibrant document and right step in the domain of policy formulation but demanded non-pragmatic results from security operators. Majority of its drawbacks are removed in in its later version of 2018-23. Survey and questionnaire based analysis is also made part of this article along with recommendations as submitted by respondents. (shrink)

Unmanned aerial vehicles, particularly quadcopters, have several medical, agriculture, surveillance, and security applications. However, the use of this innovative technology for civilian applications is still very limited in low-income countries due to the high cost, whereas low-cost controllers available in the market are often tuned using the hit and trial approach and are limited for specific applications. This paper addresses this issue and presents a novel proof of concept low-cost quadcopter UAV design approach using a systematic Model-Based Design method for (...) mathematical modeling, simulation, real-time testing, and prototyping. The quadcopter dynamic model is developed, and controllers are designed using Proportional Integral, and Derivative, Pole Placement, and Linear Quadratic Regulator control strategies. The stability of the controllers is also checked using Lyapunov stability analysis. For verification and validation of the design, Software-in-the-Loop, Processor-in-the-Loop, Hardware-in-the-loop testing, and Rapid Control Prototyping have been performed. The V&V methods of the MBD approach showed practically valid results with a stable flight of the quadcopter prototype. The proposed low-cost POC quadcopter design approach can be easily modified to have enhanced features, and quadcopters with different design parameters can be assembled using this approach for a diverse range of applications. (shrink)

The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron, recurrent neural network, and autoregressive integrated moving average on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA-MLP and ARIMA-RNN. Because of the complicated and noisy nature of financial data, we combine novel machine-learning techniques such as MLP and RNN with ARIMA model to predict the three stock (...) market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA-MLP and ARIMA-RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root-mean-square error and mean absolute error. Apart from this, ARIMA-MLP outperformed the ARIMA-RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA-RNN beat the ARIMA-MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time-series forecasting. (shrink)

On correct method of understanding various Buddhist philosophical concepts according to sutras and tantras. (Dus gsum gyi rgyal ba sras dang bcas paʹi bstan pa mthaʼ dag dang kyad par Rdo-rje-ʼchang Karma-paʼi dgong pa gsal bar byed paʼi bstan bcos thar paʼi lam chen bgrod paʼi shing rta zhes bya ba ʼdi yin no).

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.

AI-driven journalism refers to various methods and tools for gathering, verifying, producing, and distributing news information. Their potential is to extend human capabilities and create new forms of augmented journalism. Although scholars agreed on the necessity to embed journalistic values in these systems to make AI systems accountable, less attention was paid to data quality, while the results’ accuracy and efficiency depend on high-quality data in any machine learning task. Assessing data quality in the context of AI-driven journalism requires a (...) broader and interdisciplinary approach, relying on the challenges of data quality in machine learning and the ethical challenges of using machine learning in journalism. To better identify these, we propose a data quality assessment framework to support the collection and pre-processing stages in machine learning. It relies on three of the core principles of ethical journalism—accuracy, fairness, and transparency—and participates in the shift from model-centric to data-centric AI, by focusing on data quality to reduce reliance on large datasets with errors, making data labelling consistent, and better integrating journalistic knowledge. (shrink)

Background and ObjectivesThe purpose of this study was to draw the attention toward the implications of COVID-19 and the related restrictions imposed worldwide especially in Pakistan. The primary objective was to highlight the levels of psychological distress, anxiety, family violence, suicidality, and well-being due to COVID-19 and the secondary objective was to associate it to social demographic factors.Materials and MethodsIt is designed as a cross-sectional study by employing an online questionnaire in the English language and obtaining responses using a snowball (...) sampling technique. We used three validated measures including Kessler Psychological Distress Scale (K10), Generalized Anxiety Disorder (GAD-7) index and World Health Organization Well-Being Index (WHO-5).ResultsA sample of 420 participants was recruited from across Pakistan, with most participants were females (79%), students (89.8%) and belonging to Punjab (54%). Nearly one-fourth of the participants (23.8%) scored above the minimum value set for moderate or high psychological distress (K10 > 12). There was a higher prevalence of distress among females and resident of province Punjab. The majority of individuals reported that they were living with their family (94.5%) and more than half (52.6%) were neutral regarding their satisfaction with their living conditions. 40.5% believed that the lockdown has had a negative impact on their mental health. 31.4% have reported that they themselves have experienced abuse from a family member. 48.6% scored high on the GAD-7 scale and low wellbeing score was found among 80.2%. Students were found to be more vulnerable to mental illness and anxiety.ConclusionWith the lockdown restrictions, psychosocial distress has become prevalent in Pakistan. (shrink)

In order to reduce the dimensionality of parameter space and enhance out-of-sample forecasting performance, this research compares regularization techniques with Autometrics in time-series modeling. We mainly focus on comparing weighted lag adaptive LASSO with Autometrics, but as a benchmark, we estimate other popular regularization methods LASSO, AdaLASSO, SCAD, and MCP. For analytical comparison, we implement Monte Carlo simulation and assess the performance of these techniques in terms of out-of-sample Root Mean Square Error, Gauge, and Potency. The comparison is assessed with (...) varying autocorrelation coefficients and sample sizes. The simulation experiment indicates that, compared to Autometrics and other regularization approaches, the WLAdaLASSO outperforms the others in covariate selection and forecasting, especially when there is a greater linear dependency between predictors. In contrast, the computational efficiency of Autometrics decreases with a strong linear dependency between predictors. However, under the large sample and weak linear dependency between predictors, the Autometrics potency ⟶ 1 and gauge ⟶ α. In contrast, LASSO, AdaLASSO, SCAD, and MCP select more covariates and possess higher RMSE than Autometrics and WLAdaLASSO. To compare the considered techniques, we made the Generalized Unidentified Model for covariate selection and out-of-sample forecasting for the trade balance of Pakistan. We train the model on 1985–2015 observations and 2016–2020 observations as test data for the out-of-sample forecast. (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 personalized recommender system is broadly accepted as a helpful tool to handle the information overload issue while recommending a related piece of information. This work proposes a hybrid personalized recommender system based on affinity propagation, namely, APHPRS. Affinity propagation is a semisupervised machine learning algorithm used to cluster items based on similarities among them. In our approach, we first calculate the cluster quality and density and then combine their outputs to generate a new ranking score among clusters for the (...) personalized recommendation. In the first phase, user preferences are collected and normalized as items rating matrix. This generated matrix is then clustered offline using affinity propagation and kept in a database for future recommendations. In the second phase, online recommendations are generated by applying the offline model. Negative Euclidian similarity and the quality of clusters are used together to select the best clusters for recommendations. The proposed APHPRS system alleviates problems such as sparsity and cold-start problems. The use of affinity propagation and the hybrid recommendation technique used in the proposed approach helps in improving results against sparsity. Experiments reveal that the proposed APHPRS performs better than most of the existing recommender systems. (shrink)

Mining social network data and developing user profile from unstructured and informal data are a challenging task. The proposed research builds user profile using Twitter data which is later helpful to provide the user with personalized recommendations. Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets. Semantic and syntactic analysis on tweets is performed to minimize information loss during the process of tweets classification. After (...) precise classification and sentiment analysis, the system builds user interest-based profile by analyzing user’s post on Twitter to know about user interests. The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately. (shrink)

Aesthetics of art and literature; articles.

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 provides a critical review of economic outcome metrics used in healthcare value assessment, emphasizing the evolving landscape of resource allocation, patient-centered approaches, and standardization efforts. With healthcare costs rising globally, the efficient allocation of limited resources is essential. Metrics like Quality-Adjusted Life Years (QALYs), Disability-Adjusted Life Years (DALYs), Incremental Cost-Effectiveness Ratios (ICERs), and Cost-Benefit Analysis (CBA) are central to guiding funding decisions, influencing insurance coverage, and shaping treatment prioritization. Emerging trends, such as the integration of artificial intelligence (AI) (...) and big data, are enhancing the precision of these assessments, while patient-centered metrics underscore the importance of patient satisfaction and quality of life. Additionally, there is a growing push for the standardization of these metrics to create consistent frameworks across diverse health systems. This paper explores case studies, practical applications, and future directions to provide insights into how healthcare systems can adopt more effective, globally aligned economic assessments. (shrink)

On Western philosophy from the point of view of Burmese philosophers.

Mostly consists of works composed in Tibetan, with translations into Mongolian, on the Soyombo script.

Résumé L’histoire récente montre que les deuxièmes générations rencontrent aussi un problème d’intégration. Les immigrations post-coloniales sont maintenant mondialisées, et les quartiers dortoirs d’immigration sont devenus des places de commerce cosmopolites. L’espace public dans lequel se meut l’immigration s’est différencié. L’émigré devient l’immigré, la famille se regroupe. La nouvelle génération veut incarner la tradition et n’a plus peur de marquer l’espace public des signes ostentatoires d’une présence singulière.

Fix 2 < n < ω. Let CA n denote the class of cylindric algebras of dimension n, and let RCA n denote the variety of representable CA n ’s. Let L n denote first-order logic restricted to the first n variables. Roughly, CA n, an instance of Boolean algebras with operators, is the algebraic counterpart of the syntax of L n, namely, its proof theory, while RCA n algebraically and geometrically represents the Tarskian semantics of L n. Unlike Boolean (...) algebras having a Stone representation theorem, RCA n ⊊ CA n. Using combinatorial game theory, we show that the existence of certain finite relation algebras RA, which are algebras whose domain consists of binary relations, implies that the celebrated Henkin omitting types theorem fails in a very strong sense for L n. Using special cases of such finite RA ’s, we recover the classical nonfinite axiomatizability results of Monk, Maddux, and Biro on RCA n and we re-prove Hirsch and Hodkinson’s result that the class of completely representable CA n ’s is not first-order definable. We show that if T is an L n countable theory that admits elimination of quantifiers, λ is a cardinal < 2 ℵ 0, and F = 〈 Γ i : i < λ 〉 is a family of complete nonprincipal types, then F can be omitted in an ordinary countable model of T. (shrink)