Over the past several years, the study of self-related cognition has garnered increasing interest amongst psychologists and cognitive neuroscientists. Concomitantly, lesion and neuroimaging studies have demonstrated the importance of intact cortico-cortical and cortico-subcortical connections for supporting high-level cognitive functions. Commissurotomy or “split-brain” patients provide unique insights into the role of the cerebral commissures in maintaining an individual’s sense of self, as well as into the unique self-representation capabilities of each cerebral hemisphere. Here we review empirical work examining the integrity of (...) self-related processes in patients with various disconnection syndromes, focusing on studies of self-recognition, ownership, and agency. Taken together, this body of work suggests that an intact corpus callosum enabling interhemispheric transfer is necessary for some, but not all types of self-representations. (shrink)

To assess the ability of the disconnected cerebral hemispheres to recognize images of the self, a split-brain patient was tested using morphed self-face images presented to one visual hemifield at a time while making “self/other” judgments. The performance of the right and left hemispheres of this patient as assessed by a signal detection method was not significantly different, though a measure of bias did reveal hemispheric differences. The right and left hemispheres of this patient independently and equally possessed the ability (...) to self-recognize, but only the right hemisphere could successfully recognize familiar others. This supports a modular concept of self-recognition and other-recognition, separately present in each cerebral hemisphere. (shrink)

The disability viewpoint is the fundamental for understanding social justice in a given population. Disability rights need to be obeyed in the inclusive preparedness and response to all the disasters or during the crisis period including COVID-19 pandemic. COVID-19 pandemic jeopardized the health and rehabilitation services globally. The impact is much more in low resource developing countries like Bangladesh. In general, people with disability (PWD) suffer from multiple medical and rehabilitation complications and they need frequent rehabilitation consultations or hospital admissions (...) in comparison to people without disability. As a developing country, Bangladesh has poor ratios of doctors, nurses and technologists of 1:0.4:0.24 (WHO: 1:3:5) to face the COVID-19 challenge. Rehabilitation services have been disrupted in almost two-thirds (63%) of countries of the world. Even though rehabilitation is the key to recovery following severe illness from COVID-19. There are many concerns and debates about the preparedness, response and mitigation the process of COVID-19 on the part of the national government. According to recent study reports, the lives of about 100% of PWD have been impacted by the COVID-19 pandemic. COVID-19 National Technical Advisory Committee is working for strategic planning, response and mitigation process but omission of a representative of PWD or a rehabilitation physician in the committee has created much dissatisfaction. The difficult COVID-19 testing process due to country wide shutdown of rehabilitation essential services and central pulling of rehabilitation physicians have side lined the PWD inclusiveness. It is expected that the rehabilitation preparedness, response and mitigation of the pandemic should be based on an ethics driven process. (shrink)

This paper demonstrates the political perspective of corporate social responsibility disclosures and, drawing on Weber’s notion of traditionalism, seeks to explain what motivates companies to make such disclosures in a traditional setting. Annual reports of 23 banking companies in Bangladesh are analysed over the period 2009–2012. This is supplemented by a review of documentary evidence on the political and social activities of corporations and reports published in national and international newspapers. We found that, in the banking companies over the period (...) of study, apparently neutral, corporate, philanthropic activities disclosed and promoted in CSR reports are inextricably linked to powerful leaders’ personal projects and the ruling party’s agendas. We have demonstrated elements of traditional societies, including personal loyalty and the public display of loyalty, the master–servant relationship, and obedience to personal rather than formal authority, provide an understanding of why banks have employed politically charged CSR disclosure strategies. The paper contributes to disclosure studies where political motivations of corporate disclosure rarely discussed. The paper extends the debate on political CSR by demonstrating that the role of family and familial values at the organisational and national levels may be much more important when it comes to CSR disclosure and activities. (shrink)

The Sustainable Development Goal of the United Nations related to reduced inequalities calls for greater economic inclusion of the poor. Yet, how business leaders grant economic opportunities and development to the poor is significantly under-researched. Extending burgeoning responsible leadership theory that promotes paradox-savvy leadership for building inclusive ventures through various actors, this study introduces new concepts of inclusive leadership that foster the economic inclusion of the poor from Amartya Sen’s capability approach perspective. By studying how leaders include the poor in (...) social businesses, we provide a fresh perspective of inclusive leadership as a personalized empowering cycle of economic–social–economic inclusion to close the gaps between the rich and poor in business and society. This perspective provides new territories of diversity and inclusion research for reduced inequality. (shrink)

Despite the fact that Islam is one of the major religions, the frameworks of this faith are yet to be fully understood. As a consequence, it is being confused with activities contrary to its teachings. Islam has an elaborate treatment for almost every aspect of life including the affairs of business. Business is an acceptable and dignified occupation, which has to be conducted within the given frameworks. Islam encourages the creation, acquisition and consumption of wealth, and the fulfilling of certain (...) conditions in so doing. Wealth is held in trust as a gift from God. The terms of reference of this trust are to be complied with. Ethical principles do play a major role in shaping the behavior of a Muslim, in or out of business. In an era of globalization, the need for a better understanding of the premises of Islamic faith cannot be overemphasized. (shrink)

This study adapts the theory of reasoned action (Ajzen and Fishbein, 1980) to the behavior of fraudulent reporting on financial statements so as to examine the effects of moral reasoning and self-monitoring on intention to report fraudulently, using structural equation modeling. The paper seeks to investigate two of the red flags for financial statement fraud identified in Loebbecke et al.'s (1989) paper: client management displays a significant lack of moral fiber and client personnel exhibit strong personality anomalies. As expected, high (...) moral reasoners are more influenced than low moral reasoners by their own attitude towards the behavior. Contrary to prior research, low self-monitors are found to be more influenced than high self-monitors by subjective norms. Future research is recommended to investigate the counter-intuitive results for self-monitors, to consider the implications of group decision making as regards the promulgation of fraudulent financial statements, and to examine additional red flags for financial statement fraud. (shrink)

Despite the fact that Islam is one of the major religions, the frameworks of this faith are yet to be fully understood. As a consequence, it is being confused with activities contrary to its teachings. Islam has an elaborate treatment for almost every aspect of life including the affairs of business. Business is an acceptable and dignified occupation, which has to be conducted within the given frameworks. Islam encourages the creation, acquisition and consumption of wealth, and the fulfilling of certain (...) conditions in so doing. Wealth is held in trust as a gift from God. The terms of reference of this trust are to be complied with. Ethical principles do play a major role in shaping the behavior of a Muslim, in or out of business. In an era of globalization, the need for a better understanding of the premises of Islamic faith cannot be overemphasized. (shrink)

This paper aims to introduce a robust framework for forecasting demand, including data preprocessing, data transformation and standardization, feature selection, cross-validation, and regression ensemble framework. Bagging ), boosting and extreme gradient boosting regression ), and stacking are employed as ensemble models. Different machine learning approaches, including support vector regression, extreme learning machine, and multilayer perceptron neural network, are adopted as reference models. In order to maximize the determination coefficient value and reduce the root mean square error, hyperparameters are set using (...) the grid search method. Using a steel industry dataset, all tests are carried out under identical experimental conditions. In this context, STACK1 and STACK2 models provided better performance than other models. The highest accuracies of R2 of 0.97 and 0.97 are obtained using STACK1 and STACK2, respectively. Moreover, the rank according to performances is STACK1, STACK2, XGBR, GBR, RFR, MLP, ELM, and SVR. As it improves the performance of models and reduces the risk of decision-making, the ensemble method can be used to forecast the demand in a steel industry one month ahead. (shrink)

The number of scientific publications is growing exponentially. Research articles cite other work for various reasons and, therefore, have been studied extensively to associate documents. It is argued that not all references carry the same level of importance. It is essential to understand the reason for citation, called citation intent or function. Text information can contribute well if new natural language processing techniques are applied to capture the context of text data. In this paper, we have used contextualized word embedding (...) to find the numerical representation of text features. We further investigated the performance of various machine-learning techniques on the numerical representation of text. The performance of each of the classifiers was evaluated on two state-of-the-art datasets containing the text features. In the case of the unbalanced dataset, we observed that the linear Support Vector Machine achieved 86% accuracy for the “background” class, where the training was extensive. For the rest of the classes, including “motivation,” “extension,” and “future,” the machine was trained on less than 100 records; therefore, the accuracy was only 57 to 64%. In the case of a balanced dataset, each of the classes has the same accuracy as trained on the same size of training data. Overall, SVM performed best on both of the datasets, followed by the stochastic gradient descent classifier; therefore, SVM can produce good results as text classification on top of contextual word embedding. (shrink)

Crop cultivation is one of the oldest activities of civilization. For a long time, crop production was carried out based on knowledge passed from generation to generation. However, due to the rapid growth in the human population of the world, human knowledge-based cultivation is not enough to meet the demanding need. To address this issue, the usage of machine learning-based tools has been studied in this paper. An experiment has been carried out over 0.3 million data. This dataset identifies 46 (...) prominent parameters for cultivation, which is collected from the Department of Agriculture Extension, Bangladesh. Comparison between neural networks and numbers of machine learning algorithms has been carried out in this research. It is observed that the neural network outperforms the other methods by maintaining an average prediction accuracy of 96.06% for six different crops. Other contemporary machine learning algorithms, namely, support vector machine, random forest, and logistic regression, have average prediction accuracy of around 68.9%, 91.2%, and 62.39%, respectively. (shrink)

This study aims to identify artificial intelligence (AI) technologies that are applied in climate-smart agricultural practices and address ethical concerns of deploying those technologies from legal perspectives. As climate-smart agricultural AI, the study considers those AI-based technologies that are used for precision agriculture, monitoring peat lands, deforestation tracking, and improved forest management. The study utilized a systematic literature review approach to identify and analyze AI technologies employed in climate-smart agriculture and associated ethical and legal concerns. The study findings indicate several (...) ethical concerns for deploying AI in climate-smart agricultural practices pertaining to data inaccuracy, other technical errors based on wrong recommendations or wrongful acts, data ownership and intellectual property issues, and economic issues resulting in digital division and privacy and security related issues. In this study, the ethical concerns were further examined based on criminal law, tort law, privacy and data protection law, and intellectual property law. In this regard, the study finds that the current tort law pattern is more suitable than the criminal law pattern to address some major ethical concerns, such as data inaccuracy and other technical errors based on wrong recommendations or wrongful acts. Finally, the study recommends that at the global level, all countries need to fill up the current gap of international law on climate-smart agriculture through agreeing on a standard set of legal provisions and enhancing collaboration in innovation and deployment of climate-smart agricultural AI. It further recommends that at the local level, countries need to adopt suitable regulations addressing multi-stakeholders’ interests associated with the deployment of climate-smart agricultural AIs. (shrink)

The means by which social environmental exposures influence risk of mental disorders is a persistent and still open question. A key candidate mechanism for the biologic mediation of environmental effects involves epigenetic factors, which regulate gene function without altering underlying DNA sequence. Recent work has shown that environmental exposures such as childhood abuse, family history of mental disorder, and low socioeconomic status (SES) associate with differential DNA methylation (5mC) – a relatively stable, but modifiable, epigenetic factor. However, the longitudinal relation (...) among SES, 5mC, brain function, and risk of depression remains to be elucidated. Here, we briefly review literature relevant to these associations and discuss recent findings that, for the first time, prospectively demonstrate sequential links between low SES, changes in 5mC, changes in brain function, and risk of depression in a cohort of adolescents. (shrink)

In the area of machine learning, different techniques are used to train machines and perform different tasks like computer vision, data analysis, natural language processing, and speech recognition. Computer vision is one of the main branches where machine learning and deep learning techniques are being applied. Optical character recognition is the ability of a machine to recognize the character of a language. Pashto is one of the most ancient and historical languages of the world, spoken in Afghanistan and Pakistan. OCR (...) application has been developed for various cursive languages like Urdu, Chinese, and Japanese, but very little work is done for the recognition of the Pashto language. When it comes to handwritten character recognition, it becomes more difficult for OCR to recognize the characters as every handwritten character’s shape is influenced by the writer’s hand motion dynamics. The reason for the lack of research in Pashto handwritten character data as compared to other languages is because there is no benchmark dataset available for experimental purposes. This study focuses on the creation of such a dataset, and then for the evaluation purpose, a machine is trained to correctly recognize unseen Pashto handwritten characters. To achieve this objective, a dataset of 43000 images was created. Three Feed Forward Neural Network models with backpropagation algorithm using different Rectified Linear Unit layer configurations were trained and tested with this dataset. The simulation shows that Model 1 achieved accuracy up to 87.6% on unseen data while Model 2 achieved an accuracy of 81.60% and 3% accuracy, respectively. Similarly, loss was the lowest for Model 1 with 0.15 and 3.17 for training and testing, followed by Model 2 with 0.7 and 4.2 for training and testing, while Model 3 was the last with loss values of 6.4 and 3.69. The precision, recall, and f-measure values of Model 1 were better than those of both Model 2 and Model 3. Based on results, Model 1 is found to be the most efficient as compared to the other two models in terms of accuracy to recognize Pashto handwritten characters. (shrink)

This paper is about human rights and policing in Bangladesh, with special focus on the role of National Human Rights Commission. The protection and promotion of human rights in Bangladesh has become difficult as the law enforcement agencies, particularly the police and the Rapid Action Battalion, are involved in human rights violations. An overall culture of impunity for human rights violations exists in Bangladesh. The National Human Rights Commission appears to have failed to break the culture of impunity in Bangladeshi (...) politics. This paper explains the reasons why the National Human Rights Commission in Bangladesh largely fails to make the political system in particular law enforcement agencies accountable. (shrink)

This paper is about human rights and policing in Bangladesh, with special focus on the role of National Human Rights Commission. The protection and promotion of human rights in Bangladesh has become difficult as the law enforcement agencies, particularly the police and the Rapid Action Battalion, are involved in human rights violations. An overall culture of impunity for human rights violations exists in Bangladesh. The National Human Rights Commission appears to have failed to break the culture of impunity in Bangladeshi (...) politics. This paper explains the reasons why the National Human Rights Commission in Bangladesh largely fails to make the political system in particular law enforcement agencies accountable. (shrink)

Three inevitable realities instigate this study. Primarily, the goal of security in the region will most likely be accomplished just if as a minimum some level of cooperation is achieved between the major countries of the region. Second, Afghanistan cannot advance economically or enhance its security and administration independently without some cooperation from India and Pakistan. Third, although many strategists view the idea of Pak-India cooperation with distrust, there are many common grounds where both can gain considerable security, governance, and (...) economic advantages. Most of the existing studies are focused on the assumptions that how peace in the region will come. First view is about involvement of USA and European countries on one side and stake holders in Afghanistan on the other. Some believe in a trilateral pattern i.e. Western World, Afghan stake holders and Pakistan. Many also highlight the importance of support from neighboring countries like Iran, the Central Asian Republics, and China. This study highlights the significance of a trilateral solution in Afghanistan and the steps forward from this particular aspect. The possible answer to security dilemma of Pakistan in the context of Afghanistan is a solution within the region. (shrink)

The article extends the critique of structuration theory from a critical realist perspective, in particular by demonstrating how its theoretical shortcomings are manifest in management accounting research. Examining of one of the most cited structuration-based accounting studies and other more recent structuration-based accounting studies, the article highlights what accounting researchers who have embraced a structuration lens may have ignored. It also demonstrates why accounting researchers could not get a better theoretical purchase out of structuration. We find that a critical realist (...) account provides a far more in-depth account of budgeting changes and is likely to avoid the problems encountered in using a structuration theoretical lens. The article has important implications for accounting researchers as it demonstrates that analytical dualism instead of duality has much better potential to offer deeper understanding of accounting changes. (shrink)

Seasonal outbreaks have several different periods that occur primarily during winter in temperate regions, while influenza may occur throughout the year in tropical regions, triggering outbreaks more irregularly. Similarly, dengue occurs in the star of the rainy season in early May and reaches its peak in late June. Dengue and flu brought an impact on various countries in the years 2017–2019 and streaming Twitter data reveals the status of dengue and flu outbreaks in the most affected regions. This research work (...) presents that Social Media Analysis can be used as a detector of the epidemic outbreak and to understand the sentiment of social media users regarding various diseases. Providing awareness about seasonal outbreaks through SMA is an effective approach for researchers and healthcare responders to detect the early outbreaks. The proposed model aims to find the sentiment about the disease in tweets, and the seasonal outbreaks-related tweets are classified into two classes as disease positive and disease negative. This work proposes a machine-learning-based approach to detect dengue and flu outbreaks in social media platform Twitter, using four machine learning algorithms: Random Forest, K-Nearest Neighbor, Support Vector Machine, and Decision Tree, with the help of Term Frequency and Inverse Document Frequency. For experimental analysis, two datasets are analyzed individually. The experimental results show that the RF classifier has outperformed the comparison models in terms of improved accuracy, precision, recall, F1-measure, and Receiver Operating Characteristic curve. The proposed work offers favorable performance with total precision, accuracy, recall, and F1-measure ranging from 84% to 88% for conventional machine learning techniques. (shrink)

A recent initiative at Muffakham Jah College of Engineering and Technology, Hyderabad, India, has resulted in setting up a program called Centre for Environment Studies and Socioresponsive Engineering which seeks to involve undergraduate students in studying and solving environmental problems in and around the city of Hyderabad, India. Two pilot projects have been undertaken — one focusing on design and construction of an eco-friendly house, The Natural House, and another directed at improving environmental and general living conditions in a slum (...) area. The paper describes our attempts and experience of motivating our students to take interest in such projects. In an interesting development we invited a member of a student-faculty team at Massachusetts Institute of Technology (M.I.T.) that is doing a project in Nepal on safe drinking water. We report in our paper how the presentation by the guest from M.I.T. served as a catalyst for generating interest among civil and mechanical engineering students in our own projects. The paper includes contributions from one of our students and the M.I.T. staff member, reporting on their experiences related to the slum development project. (shrink)