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)

Advancements in science and technology have not only brought hope to humankind to produce disease-free offspring, but also offer possibilities to genetically enhance the next generation’s traits and capacities. Human genetic enhancement, however, raises complex ethical questions, such as to what extent should it be allowed? It has been a great challenge for humankind to develop robust ethical guidelines for human genetic enhancement that address both public concerns and needs. We believe that research about public concerns is necessary prior to (...) developing such guidelines, yet the issues have not been thoroughly investigated in many countries, including Malaysia. Since the novel often functions as a medium for the public to express their concerns, this paper explores ethical concerns about human genetic enhancement expressed in four Malay science fiction novels namely Klon, Leksikon Ledang, Transgenesis Bisikan Rimba and Transgenik Sifar. Religion has a strong influence on the worldview of the Malays therefore some concerns such as playing God are obviously religious. Association of the negative image of scientists as well as the private research companies with the research on human genetic enhancement reflects the authors’ concerns about the main motivations for conducting such research and the extent to which such research will benefit society. (shrink)

This study sheds light on strategies for retaining skilled pharmacists in Pakistan's pharmaceutical sector, offering valuable insights for both academia and industry stakeholders by investigating the impact of human resource management practices, including training and development, compensation and rewards, job performance, and job satisfaction, on employee retention. It also examines the moderating role of career growth in this context. Theoretical foundations are grounded in international migration theories and social exchange theory, providing a comprehensive framework for the study. A cross-sectional survey (...) design was used to collect data from 254 pharmacists in southern Punjab, Pakistan. Structural equation modeling (SEM) was employed for data analysis. Findings reveal that training and development, compensation and rewards, job performance, and job satisfaction all have significant direct effects on employee retention. Additionally, career growth acts as a crucial moderator, strengthening the relationship between training and development and job performance, as well as compensation and rewards and job satisfaction in relation to employee retention. Theoretical implications emphasize the importance of tailored training programs, fair compensation practices, and career growth opportunities. Practical recommendations include creating a positive work environment, rewarding high-performing employees, and fostering career development. Future research directions encompass longitudinal studies, the influence of organizational culture and technology, regional variations, and additional factors affecting retention. (shrink)

The purpose of this research is to highlight the relationship between green product attributes and consumer trust that influence consumers’ decision to purchase green products in the context of Pakistan. This study contributes to determining quantitatively how green product attributes such as physical, perceptual, and reflexive attributes influence consumers’ trust to purchase a green product and investigates the mediating role of green marketing. Data was collected from different industrial sectors through a survey questionnaire. We employed Structural Equation Modeling using the (...) SMART-PLS software to check the reliability and validity of the constructs, and to test the hypotheses. This study reveals variations in terms of shaping the sustainable consumers’ buying behavior by modifying product attributes and green marketing strategies that are in congruence with the proposed hypotheses of this study. In the end, the findings and interpretations of the results are given which can guide the managers to develop effective green marketing campaigns in reshaping the purchase intentions of consumers toward their green products. (shrink)

The role of digitization and globalization have changed consumers’ online buying behaviors, specifically in the times of the COVID-19 pandemic crisis. This seriously influences the online retail industry in developing countries that are already struggling to move toward digital trading through e-business. Pakistan being a developing country is no exception, and it is, therefore, pertinent to examine factors that contribute to digital trading. Employing theories of reasoned action and the technology acceptance model, this study aims to investigate how personal innovativeness (...) and perceived usefulness impact consumers’ online purchase intentions through a serial mediational model. The data were collected through an online survey from 410 respondents. Structural Equation Modeling was used to test the proposed model. This study showed significant results for the direct effect of personal innovativeness and perceived usefulness on online purchase intentions as well as the indirect serial effect via internet browsing and attitude toward online purchasing. The study results have some important practical implications for selling firms, especially in the times of COVID-19. The study suggests that online retailers should be more responsive to the aforementioned factors to facilitate consumers to spend more time browsing, which influences consumers’ interest and intention to make online purchases. As the social distancing and lockdown approaches were implemented in Pakistan and other parts of the world, the trend toward online purchases has increased. Due to this shift in the overall purchasing behavior of consumers and the potential for strong growth in e-commerce, organizations need to consider the post-COVID situation to expand their business in an online platform for addressing the future pandemic crisis. (shrink)

This research aims to identify the investor’s decision-making styles and their impact on entrepreneurial opportunities through the mediation role of entrepreneurial intention and moderation effect of social capital in the healthcare sector of Pakistan. This study applied a structural equation modeling to test the hypotheses on a sample of 400 healthcare investors. Our findings reveal that the conditional indirect relationship of entrepreneurial intention through social capital was significant on opportunity creation and an insignificant influence on opportunity discovery from decision-making styles. (...) This study provides implications for policymakers to enhance entrepreneurial opportunity creation by providing robust social environment investors and encouraging them to create business ventures in the healthcare sector. (shrink)

Energy poverty is a problem that affects developed and developing economies, and its mitigation is of great significance to social welfare. EP affects Latin American countries, and policymakers have recently attempted to address this issue, particularly in the aftermath of the recent economic crisis. It is essential to measure and evaluate EP to implement strategies and policies effectively. Using a panel quantile regression approach, we investigate the heterogeneous impact of green finance, renewable energy, and energy efficiency on EP for 33 (...) Latin American countries from 2000 to 2018. Furthermore, certain associated control variables are incorporated into our model to avoid an omitted variable bias. According to empirical results, the impact of independent variables on EP is heterogeneous. Specifically, green finance is an essential source of alleviating EP, and it has a significant positive effect across all quantiles, but it is especially strong in the middle quantiles. RE and EE significantly mitigate EP, with the strongest effects occurring at higher quantiles. By including green finance, RE, and EE as the main explanatory determinants of EP, the findings urge policymakers in Latin American countries to design a comprehensive energy conservation policy to minimize the effects of massive EP. (shrink)

Climate change and farming malpractices are harmful to the globe's productive soil and biodiversity, thereby posing a hazard to the survival of future generations. Innovative technologies provide continuous smart conservation solutions, such as regenerative farming, to confront the ongoing climate crisis and maintain biodiversity. Albeit, regenerative farming has the potential to conserve climate change by upgrading the soil's organic materials and reinstating biodiversity leading to carbon attenuation. However, a critical problem remains concerning adapting conservation farming practices that can assist low-income (...) farmers. In this scenario, theoretical-driven communication campaigns are critical for addressing individuals' resistance to innovation. Thereby, this research uncovers the moderating influence of the numerous communication tools in determining the adoption of regenerative farming through diminishing farmers' resistance to innovation. The study employed a cross-sectional design vis-à-vis a survey method. A sample of 863 farmers participated by responding to the self-administrated questionnaire. In line with prior theories, the study's results identified that communication campaigns such as public service advertisements and informative scientific documentaries could reduce the resistance to innovation that increases the attitude toward the adoption of regenerative farming with varied intensity. Besides, informational support also remained a significant contributor in determining the intention to adopt regenerative farming. This specifies that implanting habits of conservation farming requires the initiation of communication campaigns using different media content. These results may be advantageous for policymakers to influence farmers' intentions to adopt regenerative farming. (shrink)

Keyword extraction refers to the process of selecting most significant, relevant, and descriptive terms as keywords, which are present inside a single document. Keyword extraction has major applications in the information retrieval domain, such as analysis, summarization, indexing, and search, of documents. In this paper, we present a novel supervised technique for extraction of keywords from medium-sized documents, namely Corpus-based Contextual Semantic Smoothing. CCSS extends the concept of Contextual Semantic Smoothing, which considers term usage patterns in similar texts to improve (...) term relevance information. We introduce four more features beyond CSS as our novel contributions in this work. We systematically compare the performance of CCSS with other techniques, when implemented over INSPEC dataset, where CCSS outperforms all state-of-the-art keyphrase extraction techniques presented in the literature. (shrink)

Irecall vividly my initial excitement at the accomplishments of the Human Genome Project. That excitement was short-lived and diminished steadily over the next decade as I came to realize that the HGP was just another nail to be hit by the metaphoric hammer of genome-sequencing technology. To this day, I see this trend in many other spheres of public health and biomedical science. I take responsibility for using this same approach of "hammer" and "nail" in my own research program, where (...) I use complex systems modeling to address pressing public health issues, such as adverse birth outcomes, food insecurity, and the opioid epidemic. But I am slowly yet surely shifting my ways by explicitly and slowly... (shrink)

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)

Nūr Muḥammad is one of the teachings in Sufism that studies the beginning of the creation of the universe. The Sufis discussed Nūr Muḥammad through God's tajallī (manifestation), and they believed that only Insan Kamil (Perfect Humans) possessed the perfection of His tajallī. This Sufi theory can be comprehended through the dhawqi approach. This research will deal with Nūr Muḥammad's theory of Sufism through the perspective of Tijaniyah Tarekat. The data for this study was obtained through library research utilizing a (...) documentary technique. The collected data will be analyzed using the descriptive analysis method. This study finds that the Tijaniyah Tarekat is a Sufism institution that bases its teachings and practices on the concept of Nūr Muḥammad in the form of ṣalawāt al-fātiḥ and ṣalawāt jawharah al-kamāl. This Tarekat's elucidation of Nūr Muḥammad is also built on and consistent with the explication of authoritative Sufis in Islam's intellectual and spiritual tradition. (shrink)

Over the past couple of decades, research on the perks of corporate social responsibility has reported that it is a source of competitive advantage and can increase the bottom-line performance of the organization. However, a somewhat small proportion of this research is focused on the ‘greenwash’ side, which posits that not all CSR would lead to positive impacts. By extending this line of research, the current study is aimed at investigating the differential impacts of CSR by developing a scale for (...) the three-dimensional model of CSR attributions coined by Ahmad in 2017, that is, Embedded, P-Social, and P-Instrumental CSR, and testing the same with counterproductive sustainability behaviors. The attribution theory was used to explain the relationship between the study variables. Data (N = 311) were collected from the tourism and hospitality sectors. It was found that Embedded and P-Social CSR practices would be attributed to more genuine CSR and would lead to a reduction in counterproductive sustainability behaviors. Furthermore, the P-Instrumental CSR would be attributed to more selfish and instrumental practices and hence would be considered as greenwashing, which will consequently lead to enhancing counterproductive sustainability behaviors. The study further tested the mediating role of employees' organizational trust, which was also supported by the results. Several theoretical and practical implications are discussed. (shrink)

The integration of cellular networks and vehicular networks is complex and heterogeneous. Synchronization among vehicles in heterogeneous vehicular clusters plays an important role in effective data sharing and the stability of the cluster. This synchronization depends on the smooth exchange of information between vehicles and remote servers over the Internet. The remote servers predict road traffic patterns by adopting deep learning methods to help drivers on the roads. At the same time, local data processing at the vehicular cluster level may (...) increase the capabilities of remote servers. However, global positioning system signal interruption, especially in the urban environment, plays a big part in the detritions of synchronization among the vehicles that lead to the instability of the cluster. Instability of connections is a major hurdle in developing cost-effective solutions for deriving assistance and route planning applications. To solve this problem, a self-localization scheme within the vehicular cluster is proposed. The proposed self-localization scheme handles GPS signal interruption to the vehicle within the cluster. A unique clustering criterion and a synchronization mechanism for sharing traffic information system data among multiple vehicles are developed. The developed scheme is simulated and compared with existing known approaches. The results show the better performance of our proposed scheme over others. (shrink)

Muslim communities in the village facing the COVID-19 Pandemic attempts to find refuge from the plague and hope for survival. However, this led to more caution, which may lead to xenophobia. Via ethnography, this study unmasks the xenophobic attitude. This research discusses the root causes of panic in the community so that remedies can be implemented. The research attempts to explain, from a socio-anthropological viewpoint, how people and religious groups in the village perceive the pandemic of COVID-19 based on their (...) belief in their faith and in the science. The research takes place in Cigagak village, an area of approximately 7000 m2 on the outskirts of Bandung of West Java of Indonesia. This study examines the selected respondents from about 190 inhabitants who had close ties to managing places of worship and public places. This study utilises a collaborative self-ethnographic method and qualitative analysis. The influence of COVID-19 has moved to new exclusive and disintegrating practices from the inclusion-cohesive religious tradition. Therefore, this study tries to find out ways on how to reduce exclusive perception and religious practices to a minimum level and how to disappear xenophobia. Amid the COVID-19 Pandemic, inclusive awareness and actions were re-established, and even social cohesiveness was fostered. This study concludes that in its deep conviction nature, theology can change exclusive behaviour to be inclusive if it is based on the religious principles that are raised in response to human events. In this case, the Muslim community in a village can change the fear of COVID-19 pandemic to be a reducer of the panic based on the support of the religious doctrines.Contribution: This article used a collaborative self-ethnography with a religious socio-anthropological viewpoint. This study could help to solve social problems through theological convergence in Islamic milieu, especially that of the government’s formal Islamic organisation and organic Islamic leaders of the society. (shrink)

Data center technology changes the mode of computing. Traditional DCs consist of a single layer and only have Ethernet connections among switches. Those old-fashioned DCs cannot fulfill the high resource demand compared with today’s DCs. The architectural design of the DCs is getting substantial importance and acting as the backbone of the network because of its essential feature of supporting and maintaining the rapidly increasing Internet-based applications which include search engines and social networking applications. Every application has its parameters, like (...) latency and blocking in the DC network. Every data center network has its specialized architecture. It has a specific arrangement of layers and switches, which increase or decrease the DC network’s efficiency. We develop a simulation tool that comprises two different DC architectures: basic tree architecture and c-Through architecture. Using this simulation, we analyze the traffic behavior and the performance of the simulated DCN. Our main purpose is to focus on mean waiting time, load, and blocking with respect to the traffic within the DCN. (shrink)

Bound-constrained optimization has wide applications in science and engineering. In the last two decades, various evolutionary algorithms were developed under the umbrella of evolutionary computation for solving various bound-constrained benchmark functions and various real-world problems. In general, the developed evolutionary algorithms belong to nature-inspired algorithms and swarm intelligence paradigms. Differential evolutionary algorithm is one of the most popular and well-known EAs and has secured top ranks in most of the EA competitions in the special session of the IEEE Congress on (...) Evolutionary Computation. In this paper, a customized differential evolutionary algorithm is suggested and applied on twenty-nine large-scale bound-constrained benchmark functions. The suggested C-DE algorithm has obtained promising numerical results in its 51 independent runs of simulations. Most of the 2013 IEEE-CEC benchmark functions are tackled efficiently in terms of proximity and diversity. (shrink)

With the popularity of location-based social networks, location prediction has become an important task and has gained significant attention in recent years. However, how to use massive trajectory data and spatial-temporal context information effectively to mine the user’s mobility pattern and predict the users’ next location is still unresolved. In this paper, we propose a novel network named STSAN, which can integrate spatial-temporal information with the self-attention for location prediction. In STSAN, we design a trajectory attention module to learn users’ (...) dynamic trajectory representation, which includes three modules: location attention, which captures the location sequential transitions with self-attention; spatial attention, which captures user’s preference for geographic location; and temporal attention, which captures the user temporal activity preference. Finally, extensive experiments on four real-world check-ins datasets are designed to verify the effectiveness of our proposed method. Experimental results show that spatial-temporal information can effectively improve the performance of the model. Our method STSAN gains about 39.8% Acc@1 and 4.4% APR improvements against the strongest baseline on New York City dataset. (shrink)

This research focuses on the employee loyalty aspect of private hospitals in Pakistan during the COVID-19 pandemic, seriously impacted by strict work demand and work-family conflict. To manage this issue, social rewards and psychological rewards played a role as a mediator. The study uses a causal research design with a correlational study design in a non-contrived environment. Minimal researcher interference has been assured. AMOS 24 has been used to deal with the mediation in study design with bootstrap methodology. The study (...) was conducted on 250 nurses of different private hospitals across Punjab province using a proportionate stratified sampling technique. A finding of this study suggests that nurses remain loyal to their organizations despite having uncompromising work demands and facing work-family conflict when they are provided with social and psychological rewards on their job by their organizations. (shrink)

Discussions about politics and human power, including discussions about the concept of the state, have been a discussion that has been going on since Greek times until the time of the growth of Islamic philosophy. The overemphasis on the power of reason led early modern Western societies to reject religion in all political discourse. At this stage, all views of man, power, the constitution, and the state eventually ceased to be associated with God. On the other hand, especially among Muslims, (...) religion is still connected with discussions of politics and human power. This paper will reveal how secularization in political thought grew and developed through principles such as the state of nature and the social contract. Then, based on the thought of one of the influential Muslim scholars, Syed Muhammad Naquib Al-Attas, the author tries to provide a critique of the views of Western thinkers such as Thomas Hobbes, John Locke, and other philosophers, by presenting the concept of the ideal state form derived from the concept of tamaddun formulated by Al-Attas. This research is literature review research using the descriptive method. The findings of this research show that secularization is a product purely born by Western secular thinkers and not taken from any religious teachings, so Western political concepts cannot always be applied, especially in Muslim societies. (shrink)

Includes an introd. of 49 p. by S. G. Abbas.

Integrating artificial intelligence (AI) into healthcare can potentially revolutionize how clinical decisions are made. Advancements in AI-driven Clinical Decision Support Systems (AI_CDSS) are enh...

This study examines the R&D investment behaviour of different types of family-controlled firms with the moderating role of ownership discrepancy between cash-flow rights and excess voting rights by using the sufficiency conditions’ theoretical framework of ability and willingness developed by De Massis. It uses data from family firms that have issued A-shares from 2008 to 2018. They used pooled OLS regression for data analysis and Tobit regression for robustness checks. This study classifies family firm types into two categories, namely, the (...) lone-controller family firms (LCFFs) and the multi-controller family firms (MCFFs), with each being further classified as “excess” or “no excess” voting rights. Both LCFFs without excess voting rights and MCFFs with excess voting rights have the “ability” and “willingness” toward R&D investment. LCFFs with excess voting rights and MCFFs without excess voting rights only have the ability but low willingness to invest in R&D. The study also establishes that Chinese family-controlled firms are heterogeneous toward risky investment. To the best of our knowledge, this study is the first to differentiate Chinese family firms by their unique ownership structure characteristics in investigating the effect of the family firm structure on R&D investment. The study is a novel attempt to test the willingness and ability framework of LCFFs and MCFFs. Previous studies based on agency theory have tacitly assumed that ability and willingness exist in family-controlled firms. However, this study challenges this implicit assumption. (shrink)

Codes of ethics in journalism in the light of Koran and Hadith (Islamic traditions).

Substituted judgment assumes adequate knowledge of patient’s mind-set. However, surrogates’ prediction of individual healthcare decisions is often inadequate and may be based on shared background rather than patient-specific knowledge. It is not known whether surrogate’s prediction of patient’s integrative life-story narrative is better. Respondents in 90 family pairs rank-ordered 47 end-of-life statements as life-story narrative measure and completed instruments on decision-control preference and healthcare-outcomes acceptability as control measures, from respondent’s view and predicted pair’s view. They also scored their confidence in (...) surrogate’s decision-making and familiarity with pair’s healthcare-preferences. Life-story narratives’ prediction was examined by calculating correlation of statements’ ranking scores between respondent-personal and respondent-surrogate Q-sorts and between respondent-surrogate and pair-personal Q-sorts before and after controlling for correlation with respondent-personal scores, and by comparing percentages of respondent-surrogate Q-sorts co-loading with pair-personal vs. respondent-personal Q-sorts. Accuracy in predicting decision-control preference and healthcare-outcomes acceptability was determined by percent concordance. Results were compared among subgroups defined by intra-pair relationship, surrogate’s decision-making confidence, and healthcare-preferences familiarity. Mean age was 35.4 years, 69% were females, and 73 and 80% reported ≥ very good health and life-quality, respectively. Mean surrogate’s decision-making confidence score was 3.35 and 75% were ≥ familiar with pair’s healthcare-preferences. Mean projection, simulation, and adjusted-simulation correlations were 0.68, 0.42, and 0.26, respectively. Out of 180 respondent-surrogate Q-sorts, 24, 9, and 32% co-loaded with respondent-personal, pair-personal, or both Q-sorts, respectively. Accuracy in predicting decision-control preference and healthcare-outcomes acceptability was 47 and 52%, respectively. Surrogate’s decision-making confidence score correlated with adjusted-simulation’s correlation score. There were significant differences among the husband-wife, parent-child, and sibling-sibling subgroups in percentage of respondent-surrogate Q-sorts co-loading with pair-personal Q-sorts and percent agreement on healthcare-outcomes acceptability. Despite high self-reported surrogate’s decision-making confidence and healthcare-preferences familiarity, family surrogates are variably inadequate in simulating life-story narratives. Simulation accuracy may not follow the next-of-kin concept and is 38% based on shared background. (shrink)

Kinds that share historical properties are dubbed “historical kinds” or “etiological kinds,” and they have some distinctive features. I will try to characterize etiological kinds in general terms and briefly survey some previous philosophical discussions of these kinds. Then I will take a closer look at a few case studies involving different types of etiological kinds. Finally, I will try to understand the rationale for classifying on the basis of etiology, putting forward reasons for classifying phenomena on the basis of (...) diachronic features, thereby making a provisional case for considering at least some etiological kinds to be natural kinds. (shrink)

The notion of 'natural kinds' has been central to contemporary discussions of metaphysics and philosophy of science. Although explicitly articulated by nineteenth-century philosophers like Mill, Whewell and Venn, it has a much older history dating back to Plato and Aristotle. In recent years, essentialism has been the dominant account of natural kinds among philosophers, but the essentialist view has encountered resistance, especially among naturalist metaphysicians and philosophers of science. Informed by detailed examination of classification in the natural and social sciences, (...) this book argues against essentialism and for a naturalist account of natural kinds. By looking at case studies drawn from diverse scientific disciplines, from fluid mechanics to virology and polymer science to psychiatry, the author argues that natural kinds are nodes in causal networks. On the basis of this account, he maintains that there can be natural kinds in the social sciences as well as the natural sciences. (shrink)

Features new to the second edition include a foreword by Tynnetta Muhammad, wife and student of Elijah Muhammad; opening comments by world renowned mathematician Dr. Abdulalim Sahabazz; a new chapter co-authored with Dr. Dorothy Blake Fardan; plus guided questions and power point notes to stimulate discourse around Elijah Muhammad's educational ideas.

Data analytics, machine intelligence, and other cognitive algorithms have been employed in predicting various types of diseases in health care. The revolution of artificial neural networks in the medical discipline emerged for data-driven applications, particularly in the healthcare domain. It ranges from diagnosis of various diseases, medical image processing, decision support system, and disease prediction. The intention of conducting the research is to ascertain the impact of parameters on diabetes data to predict whether a particular patient has a disease or (...) not. This paper develops an improved ANN model trained using an artificial backpropagation scaled conjugate gradient neural network algorithm to predict diabetes effectively. For validating the performance of the proposed model, we conduct a large set of experiments on a Pima Indian Diabetes dataset using accuracy and mean squared error as evaluation metrics. We use different number of neurons in the hidden layer, ranging from 5 to 50, to train the ANN models. The experimental results show that the ABP-SCGNN model, containing 20 neurons, attains 93% accuracy on the validation set, which is higher than using the other ANNs models. This result confirms the model’s effectiveness and efficiency in predicting diabetes disease from the required data attributes. (shrink)

With the growing call for private sector actors to address global challenges, it is necessary to first assess whether regions with the greatest needs are accessing corporate philanthropy. In this paper, we ask whether corporate philanthropy is reaching those with the greatest health-care needs. Drawing on economic geography and corporate homophily, we argue that corporate philanthropy tends to exacerbate health inequality as grants are destined for counties with fewer health problems. We test and find support for this hypothesis using data (...) on health grants made by US corporate foundations and county-level health data. Our results that corporate health grants are less likely to go to counties which have a lower proportion of medical service providers and insured citizens suggest that corporate foundations are unwittingly complicit in worsening the resource gap between small, poor, rural counties and large, wealthy, urban counties. From an ethical perspective, we provide some guidance as to how this may be corrected. (shrink)

On the discourse of Islamic ethics and its relation to contemporary modern societies based on the thoughts of Tariq Ramadan, a prominent Muslim scholar.

Synthesizing theories of ethical leadership, psychological climate, pro-environmental behavior, and gender, first, we proposed and tested a model linking supervisors’ ethical leadership and organizational environmental citizenship behavior via green psychological climate. Then we tested the moderating effect of gender on the indirect (via green psychological environment) relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Time-lagged (three waves, two months apart) survey data were collected from 447 employees in various manufacturing and service sector firms operating in China. Data were (...) analyzed using structural equation modeling, bootstrapping, and multi-group technique to test the hypothesized relationships. The results showed a positive relationship between employee ratings of supervisors’ ethical leadership and organizational environmental citizenship behavior. Moreover, green psychological climate mediates the relationship between supervisors’ ethical leadership and organizational environmental citizenship behavior. Importantly, the multi-group analysis revealed that gender moderates the indirect relationship (via green psychological climate) between supervisors’ ethical leadership and organizational environmental citizenship behavior. The study carries useful practical implications for policymakers and managers concerned about environmental sustainability. (shrink)

Firms have traditionally responded to environmental violations by increasing information disclosure and/or communication to manage stakeholder perceptions. As such, these approaches may be symbolic in nature, with no genuine intention to improve the environment. We draw from restorative justice grounded in stakeholder theory and explore a relatively new approach in the form of supplemental environmental projects aimed at restoring the environment, and empirically examine the role of corporate governance in firms’ decisions to undertake reparative actions. Using environmental violations and SEPs (...) data from the US Environmental Protection Agency between 2002 and 2015, we find that firms with smaller boards are more likely to undertake SEPs. We also find that firms with higher board independence and CEO duality undertake SEPs more frequently; however, board gender diversity and the existence of a sustainability committee appear to have no impacts. These results are robust to propensity score matching and an alternative data source. We extend the scope of stakeholder theory by emphasizing a new approach—restorative justice—by which corporations can repair damaged relationships and also improve the environment. We also contribute to corporate governance and environmentalism literature by identifying governance structures that promote environmental restorative justice. Thus, our study will inform different stakeholders, including regulators, shareholders, and boards of directors, and will open new avenues for business ethics scholarship. (shrink)

There is growing interest for implementing tools to monitor cognitive performance in naturalistic work and everyday life settings. The emerging field of research, known as neuroergonomics, promotes the use of wearable and portable brain monitoring sensors such as functional near infrared spectroscopy (fNIRS) to investigate cortical activity in a variety of human tasks out of the laboratory. The objective of this study was to implement an on-line passive fNIRS-based brain computer interface to discriminate two levels of working memory load during (...) highly ecological aircraft piloting tasks. Twenty eight recruited pilots were equally split into two groups (flight simulator vs. real aircraft). In both cases, identical approaches and experimental stimuli were used (serial memorization task, consisting in repeating series of pre-recorded air traffic control instructions, easy vs. hard). The results show pilots in the real flight condition committed more errors and had higher anterior prefrontal cortex activation than pilots in the simulator, when completing cognitively demanding tasks. Nevertheless, evaluation of single trial working memory load classification showed high accuracy (>76%) across both experimental conditions. The contributions here are two-fold. First, we demonstrate the feasibility of passively monitoring cognitive load in a realistic and complex situation (live piloting of an aircraft). In addition, the differences in performance and brain activity between the two experimental conditions underscore the need for ecologically-valid investigations. (shrink)

This article attempts to evaluate emotive meanings across languages and cultures expressed and elicited semiotically from viewers. It investigates the challenges of subtitling emotive feelings in the American filmHomeless to Harvard(2003) into Arabic. It adopts Paul Thibault’s (2000. The multimodal transcription of a television advertisement: Theory and practice. In Anthony Baldry (ed.),Multimodality and multimediality in the distance learning age, 311–385. Campobasso: Palladino Editore) method of multimodal transcription and Feng and O’Halloran’s (2013. The multimodal representation of emotion in film: Integrating cognitive (...) and semiotic approaches.Semiotica197(1/4). 79–100) framework of the multimodal representation of emotion to formulate strategies for subtitling emotion from English into Arabic. Additionally, Feng and O’Halloran’s (2013) framework is adapted to show how stylistic choices (e.g., cinematography, music, soundtracks, etc.) and semiotic expressions can elicit emotion from viewers. The social semiotic model is employed to investigate how emotive representation is realized through verbal and non-verbal items. The findings showed that the filmmakers had properly used stylistic choices and various semiotic techniques to elicit emotion from the viewer derived from the emotion of the film’s heroine. (shrink)