The International Classification of Functioning, Disability and Health provides a classification of human bodily functions, which, while exhibiting non-conformance to many formal ontological principles, provides an insight into which basic functions such a classification should include. Its evaluation is an important first step towards such an adequate ontology of this domain. Presented at the 13th Annual North American WHO Collaborating Center Conference on the ICF, 2007.

Sign Language Recognition (SLR) aims to translate sign language into text or speech in order to improve communication between deaf-mute people and the general public. This task has a large social impact, but it is still difficult due to the complexity and wide range of hand actions. We present a novel 3D convolutional neural network (CNN) that extracts discriminative spatial-temporal features from photo datasets. This article is about classification of sign languages are not universal and are usually not mutually (...) intelligible although there are also similarities among different sign languages. They are the foundation of local Deaf cultures and have evolved into effective means of communication. Although signing is primarily used by the deaf and hard of hearing, hearing people also use it when they are unable to speak, when they have difficulty speaking due to a health condition or disability (augmentative and alternative communication), or when they have deaf family members, such as children of deaf adults. In this article we use the 43500 image in the dataset in size 64*64 pixel by use CNN Architecture and achieved 100% accuracy. (shrink)

Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques (...) have been proposed by diverse research groups in the recent past. However, yet effective and comprehensive deep ensemble neural network-based classification model with high accuracy classification results is not available in the literature. In this thesis, we review ways and mechanisms to use deep learning techniques to research on multi-disease computer-aided detection about gastrointestinal and identify these images. We re-trained five state-of-the-art neural network architectures, VGG16, ResNet, MobileNet, Inception-v3, and Xception on the Kvasir dataset to classify eight categories that include an anatomical landmark (pylorus, z-line, cecum), a diseased state (esophagitis, ulcerative colitis, polyps), or a medical procedure (dyed lifted polyps, dyed resection margins) in the Gastrointestinal Tract. Our models have showed results with a promising accuracy which is a remarkable performance with respect to the state-of-the-art approaches. The resulting accuracies achieved using VGG, ResNet, MobileNet, Inception-v3, and Xception were 98.3%, 92.3%, 97.6%, 90% and 98.2%, respectively. As it appears, the most accurate result has been achieved when retraining VGG16 and Xception neural networks with accuracy reache to 98% due to its high performance on training on ImageNet dataset and internal structure that support classification problems. (shrink)

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties (...) of potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach. (shrink)

Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper we try (...) to fill this gap. By trying to translate sign language using artificial intelligence algorithms, we focused in this paper using transfer learning technique based on deep learning by utilizing a MobileNet algorithm and compared it with the previous paper results[10a], where we get in the Mobilenet algorithm on the degree of Accuracy 93,48% but the VGG16 the accuracy was 100% For the same number of images (43500 in the dataset in size 64*64 pixel ) and the same data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch . (shrink)

Abstract: Alzheimer's disease (AD) is one of the most common types of dementia. Symptoms appear gradually and end with severe brain damage. People with Alzheimer's disease lose the abilities of knowledge, memory, language and learning. Recently, the classification and diagnosis of diseases using deep learning has emerged as an active topic covering a wide range of applications. This paper proposes examining abnormalities in brain structures and detecting cases of Alzheimer's disease especially in the early stages, using features derived from (...) medical images. The entire brain image was passed on through the transmission of Xception learning architectures. The Convolutional Neural Network (CNN) was constructed with the help of separable convolution layers that It can automatically learn general features from imaging data for classification. (shrink)

New biotechnologies have the potential to both dramatically improve human well-being and dramatically widen inequalities in well-being. This paper addresses a question that lies squarely on the fault line of these two claims: When as a matter of justice are societies obligated to include a new biotechnology in a national healthcare system? This question is approached from the standpoint of a twin aim theory of justice, in which social structures, including nation-states, have double-barreled theoretical objectives with regard to human well-being. (...) The first aim is to achieve a sufficient level of well-being in each of six core dimensions. In the special case of healthcare systems, this aim is focally but not exclusively attentive to achieving health sufficiency as one of the core dimensions. The second aim is to combat the emergence and persistence of densely woven patterns of systematic disadvantage that tend to undermine the achievement of a sufficient level of health and the other core elements of well-being of some persons and groups. Judgments about entitlements to health related resources, including new biotechnologies, are made in light of a threshold notion of health sufficiency. What is enough or sufficient health? The answer that is defended here is that sufficient health is enough health for a decent human life, understood as enough health to live a full life course without preventable, significant functional disability or decrement in health, or treatable pain or suffering. When a state must include a new biotechnology in its national healthcare system is also influenced by ancillary concerns about the connection between health and other core dimensions of well-being. What counts as a significant functional impairment or health decrement is thus explicated, in part, in relation to the theory’s sufficiency aim for the other essential dimensions of well-being, and thus for a decent life, overall. Those elements of health that play a critical role in the experience of sufficient reasoning, affiliation, security, respect and self determination are especially important; any loss of health function or capacity that threatens the individual’s prospects for sufficiency in these other dimensions, including the relational egalitiarian concerns they entail, constitutes a significant functional impairment. Within national borders, individuals are thus entitled to those health-related goods and services that are essential for a sufficiency of each of the dimensions of well-being; with regard to self determination and respect, what is sufficient by way of guaranteed access to specific goods and services is going to depend on the implications of such access for where an individual stands in relation to her co-nationals. The content of any entitlement to health-related goods and services is also necessarily dynamic. What can be done for health and the other core dimensions of well-being as a function of technological innovation and diffusion is in constant flux. The paper concludes by considering the implications of this analysis for the conditions under which states are obligated to include access in their healthcare systems to one biotechnology, deep brain stimulation. (shrink)

On January 30, 2020, the World Health Organization declared a Public Health Emergency of International Concern (PHEIC) over what would quickly become known as SARS-CoV- 2 or COVID- 19. This emergency status was officially ended in the United States in May 2023 amidst much dissent and debate. Although emergency conditions resulting from COVID- 19 will likely wax and wane over the coming years, there is good reason to think that the incidence of severe global pandemics will increase (...) over the next century, as will declarations of emergency. The declaration of an emergency calls for urgent action, but it just as urgently demands careful reflection. Official “emergency” status licenses unparalleled executive intervention, completely reorganizing the lives of those who live under its decree. Such official recognition, however, is heavily dependent on the social context in and from which the emergency arises. Highlighting which circumstances rise to the level of an official emergency clarifies our reigning assumptions about what threshold of active harm—and in relation to which groups of people—demands immediate intervention. (shrink)

Recent years have illustrated how the reproductive realm is continuously drawing the attention of medical and legal experts worldwide. The availability of technological services to facilitate reproduction has led to serious concerns over the right to reproduce, which no longer is determined as a private/personal matter. The growing technological options do implicate fundamental questions about human dignity and social welfare. There has been an increased demand for determining (a) the rights of prisoners, unmarried and homosexuals to such services, (b) concerns (...) over child’s information and health needs, (c) claims for wrongful birth and wrongful life, (d) the role of donors and physicians, (e) posthumous reproduction etc. In addition, the role of national and international law has been emphasized for an efficient system of functioning and delivery. This paper is an attempt to explore the pressing claims to reproductive choices, coupled with a marked increase in demand for legislative intervention in India. (shrink)

A large part of the controversy surrounding the publication of DSM-5 stems from the possibility of replacing the purely descriptive approach to classification favored by the DSM since 1980. This paper examines the question of how mental disorders should be classified, focusing on the issue of whether the DSM should adopt a purely descriptive or theoretical approach. I argue that the DSM should replace its purely descriptive approach with a theoretical approach that integrates causal information into the DSM’s descriptive (...) diagnostic categories. The paper proceeds in three sections. In the first section, I examine the goals (viz., guiding treatment, facilitating research, and improving communication) associated with the DSM’s purely descriptive approach. In the second section, I suggest that the DSM’s purely descriptive approach is best suited for improving communication among mental health professionals; however, theoretical approaches would be superior for purposes of treatment and research. In the third section, I outline steps required to move the DSM towards a hybrid system of classification that can accommodate the benefits of descriptive and theoretical approaches, and I discuss how the DSM’s descriptive categories could be revised to incorporate theoretical information regarding the causes of disorders. I argue that the DSM should reconceive of its goals more narrowly such that it functions primarily as an epistemic hub that mediates among various contexts of use in which definitions of mental disorders appear. My analysis emphasizes the importance of pluralism as a methodological means for avoiding theoretical dogmatism and ensuring that the DSM is a reflexive and self-correcting manual. (shrink)

Kant’s conception of mental illness is unlikely to satisfy contemporary readers. His classifications of mental illness are often fluid and ambiguous, and he seems to attribute to human beings at least some responsibility for preventing mental illness. In spite of these apparent disadvantages, I argue that Kant’s account of mental illness can be illuminating to his views about the normative dimensions of human cognition. In contrast to current understandings of mental illness, Kant’s account is what I refer to as “non-pathological.” (...) That is, most mental illnesses are for Kant continuous with normally functioning cognition. Someone with a healthy reason can easily fall into mental illness and someone with mental illness can (perhaps not as easily) re-establish healthy reason. By accepting a non-pathological definition of mental illness, it follows for Kant that humans have more agency and responsibility regarding their mental health than current views allow, which explains why several of his writings aim to prescribe a “diet of the mind” (2:271). Contrary to popular readings of Kant as a champion of reason’s power, Kant’s conception of mental illness shows that he recognizes how fragile human reason can be. (shrink)

Much academic work (in philosophy, economics, law, etc.), as well as common sense, assumes that ill health reduces well-being. It is bad for a person to become sick, injured, disabled, etc. Empirical research, however, shows that people living with health problems report surprisingly high levels of well-being - in some cases as high as the self-reported well-being of healthy people. In this chapter, I explore the relationship between health and well-being. I argue that although we have good (...) reason to believe that health problems causing pain and death typically do reduce well-being, health problems that limit capabilities probably don't reduce well-being nearly as much as most people suppose. I then briefly explore the consequences of this conclusion for political philosophy and ethics. If many health problems don't significantly reduce well-being, why should governments go to great expense to prevent or treat them? Why should parents be obliged to ensure the health of their children? (shrink)

Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...) is a technique used to generate face detection and recognize it for real or fake by using profile images and determine the differences between them. In this study, we used deep learning techniques to generate models for Real and Fake face detection. The goal is determining a suitable way to detect real and fake faces. The model was designed and implemented, including both Dataset of images: Real and Fake faces detection through the use of Deep learning algorithms based on neural networks. We have trained dataset which consists of 9,000 images for total in 150 epochs, and got the ResNet50 model to be the best model of network architectures used with 100% training accuracy, 99.18% validation accuracy, training loss 0.0003, validation loss 0.0265, and testing accuracy 99%. (shrink)

The Axis II Work Group of the Task Force on Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) has expressed concern that antisocial personality disorder (APD) criteria are too long and cumbersome and that they focus on antisocial behaviors rather than personality traits central to traditional conceptions of psychopathy and to international criteria. R. D. Hare et al describe an alternative to the approach taken in the DSM-III—Revised (DSM-III—R; American Psychiatric Association, 1987), namely, the revised Psychopathy Checklist. The authors (...) also discuss the multisite APD field trials designed to evaluate and compare 4 criteria sets: the DSM-III—R criteria, a shortened list of these criteria, the criteria for dyssocial personality disorder from the 10th edition of the International Classification of Diseases (World Health Organization, 1990), and a 10-item criteria set for psychopathic personality disorder derived from the revised Psychopathy Checklist. (PsycINFO Database Record (c) 2015 APA, all rights reserved). (shrink)

Age and gender classification has become relevant to an increasing amount of applications, particularly since the rise of social platforms and social media. Even Nevertheless, contrast to the large performance improvements recently reported for the closely related task of audio. In this research, we show that performance on these tasks can be significantly improved by learning representations using deep convolutional neural networks (CNN). where we get in the ResNet the training accuracy was 98% ,validation accuracy 95%, testing accuracy 96% (...) .Testing dataset organized into one folder (age-gender-test) and contains 1676 audio files related to 39 of age and gender categories and 40 epoch. (shrink)

The major objective of this study was to investigate whether visual impairments (VI) impact mental health literacy among first-generation university students (FGUS). A descriptive survey research method was used to examine the mental health literacy of 132 purposive sample of FGUS with and without VI from three federal universities in Southern Nigeria. A 35-item MHL Scale (MHLS) for university students (Crobach’s α=0.83) with 5-point response was used for data collection. Questionnaire distribution was achieved through the help of two (...) research assistants. Means, standard deviations, analysis of variance and regression plot were employed to analyze the research data. Participants’ mean age was 24.96±3.86 years. Results showed a higher level of mental health literacy across seven domains of the MHL Scale among students with VI compared to those without this disability. The students identified mental health literacy they possess including the ability to recognize specific disorders, the ability to seek mental health information, the ability to identify risk factors and causes, the ability to understand self-treatment options, the ability to access professional assistance, and positive behaviors that promote awareness and help-seeking. VI did not significantly impact the mental health literacy of FGUS with VI. VI explained only 6.31% of the variation in MHL among FGUS with VI. Accordingly, mental health literacy is an essential skill that should be acquired by everyone, including those who suffer from specific disorders and professionals who care for them. Further effort is required in order to improve the mental literacy of FGUS without VI in Nigerian universities. (shrink)

Abstract: Vegetables are an essential component of a healthy diet and play a critical role in promoting overall health and well- being. Vegetables are rich in important vitamins and minerals, including vitamin C, folate, potassium, and iron. They also provide fiber, which helps maintain digestive health and prevent chronic diseases. We are proposing a deep learning model for the classification of vegetables. A dataset was collected from Kaggle depository for Vegetable with 15000 images for 15 different classes. (...) The data was preprocessed, normalized and split into three sets (train, valid, test). The proposed model was trained and validated using the train and valid sets and accuracy of both training and validation was very high. For the evaluation of the proposed model we utilized these metrics: accuracy, F1-score, precision, Recall and time required for testing. We then tested the proposed model using the test set. The result of the testing was accuracy (99.95%), F1-score (99.95%), precision (99.95%), Recall (99.95%) and time required for testing the test set was 1.38 seconds. (shrink)

Local participation is always beneficial for sustainable action and environmental problems resulting from urban implementation due to the failure of social and institutional change necessary for a successful transformation of rural life to urban life ahead of the rapid movement of the population. Despite good legal practice and comprehensive guidelines, evidence suggests that Environmental Impact Assessment (EIA) or more broadly Environmental, Social and Health Impact Assessment (ESHIA) have not yet been found satisfactory in Nigeria, as the current system amounts (...) to duplication of efforts and cost. However, ESHIA has been developed and integrated to help manage project activities, facilities, and operations sustainably, so that both economic and ecological profits are accrued (sustainable development) or ensure that any development project does not result in excessive deterioration of and/or the irreversible adverse effect on any component of the environment – a recite for sustainable development. A literature review was done by using a variety of search engines including Research Gate, Google Scholar, Academia, Mendeley, SSRN search strategy to retrieve research publications, “grey literature” and expert working group reports. The thrust of this study is to evaluate the potential benefits of ESHIA as a tool for sustainable environmental development. The evaluation and implementation of EIA are one of the strengths of these tools. Indeed, EIA is the first and foremost management tool employed to help mitigate adverse, potential, and associated impacts of proposed major developments in our environment. EIA is a regulatory requirement that is efficiently used to improve performance, project design, enhancing decision-making, and facilitating policy programs in a sustainable environment. An evaluation of the EIA systems reveals several weaknesses of the EIA system. These include the inadequate capacity of EIA approval authorities, deficiencies in screening and scoping, poor EIA quality, insufficient public participation, and weak monitoring, and erratic government policies. Overall, most EIA study rarely meets the objectives of being a project planning tool to contribute to achieving sustainable development and mitigate the impact of the development project. The study recommends some directions for the future to ensure that entire content of the EIA are religiously implemented, review the existing EIA act, increase the expertise of EIA consultants, create a liaison office with an international organisation and with sister agency, ESHIA must enjoy Improved budgetary provision, time latitude, spatial contexts and methodological improvements for outcome measures to achieve results that are relevant to sustainable development by improving project design, enhancing decision making and facilitating policy programs. (shrink)

Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it is important (...) to classify memory loss and to know the patient at what level and his assessment of Alzheimer's disease through CT scans of the brain. In this thesis, we review ways and techniques to use deep learning classification to classifying the Alzheimer's Disease The proposed method used to improve patient care, reduce costs, and allow fast and reliable analysis in large studies. The model will be designed using Python language for implementing the system, which is very useful for doctors, classifying the Alzheimer's Disease, was used. The model used 70% from image for training and 30% from image for validation, our trained model achieved an accuracy of 100% on a held-out test set. (shrink)

Abstract: This research employs a Random Forest classification model to predict and assess obesity and cardiovascular disease (CVD) risk based on a comprehensive dataset collected from individuals in Mexico, Peru, and Colombia. The dataset comprises 17 attributes, including information on eating habits, physical condition, gender, age, height, and weight. The study focuses on classifying individuals into different health risk categories using machine learning algorithms. Our Random Forest model achieved remarkable performance with an accuracy, F1-score, recall, and precision all (...) reaching 97.23%. The model's success is attributed to its ability to effectively leverage attributes related to eating habits, physical condition, and demographic factors. Feature importance analysis reveals key factors contributing to accurate predictions. This paper contributes to the field of health analytics by demonstrating the effectiveness of Random Forest in predicting and categorizing health risks. The insights gained from this research have the potential to inform personalized health interventions and contribute to the advancement of precision health strategies. Furthermore, the study highlights the importance of leveraging machine learning techniques for health risk assessment in diverse populations. (shrink)

Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether (...) a certain type of fruit meets their nutritional requirement. In this paper, machine learning based approach is presented for classifying and identifying 10 different fruit with a dataset that contains 6847 images use 4793 images for training, 1027 images for validation and 1027 images for testing. A deep learning technique that extensively applied to image recognition was used. We used 70% from image for training and 15% from image for validation 15% for testing. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

Liminal Bodies, Reproductive Health, and Feminist Rhetoric presents composition professor Lydia McDermott's "sonogram" methodology of rhetorical listening, an exercise that discloses feminine voices muted or unjustly disciplined within texts ostensibly written on women's behalf. The texts examined by McDermott range from eighteenth-century pregnancy manuals to speeches by Favorinus, the ancient sophist, who is described from antiquity as a hermaphrodite. Part of McDermott's purpose in sonogramming is to critique modern and contemporary feminists. She objects to the feminist trend of perpetuating (...) and answering a "disability" rhetoric about women, or of demonstrating that women can overcome a... (shrink)

there is a communication gap between hearing-impaired people and those with normal hearing, sign language is the main means of communication in the hearing-impaired population. Continuous sign language recognition, which can close the communication gap, is a difficult task since the ordered annotations are weakly supervised and there is no frame-level label. To solve this issue, we compare the accuracy of each model using two deep learning models, Inception and Xception . To that end, the purpose of this paper is (...) By attempting to translate sign language using deep learning models, we focused in this paper a comparing between Inception and Xception ¬¬¬¬¬ algorithm and compared it to previous papers in which we used VGG19[1], mobileNet [2], where we get in the Inception and Xception algorithm on the degree of Accuracy 99.32%, 99,43% respectively. number of images (29000 in the dataset in size 75*75 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...) a vital role in supporting human well-being and the health of our planet. . Fishes have a lots of types such that: Red Mullet, Sea Bass, Striped Red Mullet and Shrimp. Each of them has its own shape and characteristics that differ from other types. We proposed a system that recognize nine types of fishes using deep learning. We trained the model with a dataset that contain 9000 images that were slit into 6300 images for training, 1350 for validation and 1350 for testing. The proposed model achieved accuracy (99.68%), precision (99.69%), recall (99.68%), and f1-score (99.68%). This indicates that our proposed model can effectively predicate and classify different types of fish with very high accuracy. (shrink)

Students do not necessarily use the definitions presented to them when determining examples or non-examples of given mathematical ideas. Instead, they utilize the concept image they carry with them as a result of experiences with such examples and nonexamples. Hence, teachers should try exploring students‟ images of various mathematical concepts in order to improve communication between students and teachers. This suggestion can be addressed through error analysis. This study therefore is a descriptive-qualitative type that looked into the errors committed by (...) senior high school students in dealing with mathematical functions, explored the underlying reasons for such errors, and provided recommendations on how students could learn to manage their errors and how teachers could realize how to manage students‟ errors. Initial findings showed that the students generally demonstrated mathematical, logical and strategic errors. Mathematical error was generally exhibited in their inability to use properties and operations properly. Logical error was exhibited in their false arguments, rearranging concepts, improper classifications, arguing cyclically, and using equivalent transforms. Strategic error was manifested in their not being able to distinguish patterns, lack of integral concept, and not being able to transform a word problem into symbols. Errors prevailed despite the students‟ positive view and confidence in mathematics not only because of poor image concepts but because of lack of exposure to certain important mathematical tasks. Further investigation on the other sources of these errors is therefore necessary. (shrink)

Integrating medical imaging with computing technologies, such as Artificial Intelligence (AI) and its subsets: Machine learning (ML) and Deep Learning (DL) has advanced into an essential facet of present-day medicine, signaling a pivotal role in diagnostic decision-making and treatment plans (Huang et al., 2023). The significance of medical imaging is escalated by its sustained growth within the realm of modern healthcare (Varoquaux and Cheplygina, 2022). Nevertheless, the ever-increasing volume of medical images compared to the availability of imaging experts. Biomedical experts (...) and radiologists have resulted in a widening disparity, causing an excess and overwhelming workload on these healthcare professionals (Chen et al., 2021). Several studies indicate that the present-day biomedical radiologist is now saddled with the daunting task of interpreting an image almost every 10 seconds to keep pace with the burgeoning clinical demands (McDonald et al., 2015; Hosny et al., 2018; Lantsman et al., 2022). This cognitive drain has invariably led to inevitable consequences such as delays in diagnosis and an amplified risk of diagnostic errors – thus, the biomedical imaging aspect is in dire need of methods that would aid accurate diagnostics and analytics for improved decision making. In this review, the importance of AI-related technologies such as ML and/or DL methods are reviewed in relation to the processing of medical or biomedical images along with their potentials, challenges, and possible suggestions for future studies in the health landscape. The focus will be on machine learning methods associated with the medical field of image classification. (shrink)

The aim of the article is to identify the impact of cognitive style of management on the development of tourism and hospitality companies. The article discusses some approaches to the definition of “cognitive style”, presents the author’s understanding in the organizational context, namely, the cognitive style should be understood as the features of awareness, interpretation and dissemination of external and internal information by the staff in order to improve the efficiency and competitiveness of the products manufactured. The table “The attitude (...) of employees of different cognitive styles to work according to the classification by Cool E., Holland J., Myers Briggs I.” was developed, which allows determining the relationships between correspondence of the employee cognitive style to his duties and attitude to work. The trends of choosing tourist services by the consumer depending on his individual cognitive style have been analyzed. The necessity of taking into account the cognitive features both of the staff (in order to increase productivity, loyalty, improve health and self-esteem) and the consumer (to increase the level of his satisfaction of the services) has been proved. (shrink)

The Global Forum on Bioethics in Research (GFBR) served as a global platform for debate on ethical issues in international health research between 1999 and 2008, bringing together research ethics experts, researchers, policy makers and community members from developing and developed countries. In total, nine GFBR meetings were held on six continents. Work is currently underway to revive the GFBR. This paper describes the purpose and history of the GFBR and presents key elements for its reinstatement, future functioning (...) and sustainability. Potential participants and sponsors are encouraged to contribute actively to the future of this unique international research ethics event. (shrink)

Attention Deficit Hyperactivity Disorder (ADHD) continues to be controversial with arguments for and against its veracity being waged by individuals representing a variety of disciplines from behavioral scientists to philosophers. Our perspective focuses on the epistemological underpinnings of what is now commonly known as ADHD. Its ignominious history and current disputes may stem from a "pessimistic" epistemology, meaning that truth is only the province of persons in authority and power. The authoritative organizations that govern the diagnostic labels and criteria are (...) the American Psychiatric Association and their Diagnostic and Statistical Manual and the World Health Organization that sponsors the International Classification of Disease. We contrast the pessimistic epistemology with criteria for truth from the scientific method. Although scientific scrutiny has been and is being applied subsequent to "authoritarian edicts" of the disorder, we opine that ADHD currently does not have status beyond that of the "hypothetical construct." Moreover, current brain-based causal models have failed to provide rigorous supporting data that comes from testing falsifiable hypotheses. (shrink)

It is widely known that Black people are significantly more likely to be killed by the police in the United States of America than white people. What is less widely known is that nearly half of all people killed by the police are disabled people. The aim of this paper is to better understand the intersection of racism and ableism in the USA. Contributing to the growing literature at the intersection of philosophy of disability and critical philosophy of race, (...) I argue that theories concerning white supremacy should take more seriously the ways in which it functions as a process and apparatus of making abled and disabled. I conclude by discussing how understanding white supremacy in this manner is a valuable coalitional tool in fights for social justice. (shrink)

Nietzsche assesses values, moralities, religions, cultures, and persons in terms of health. He argues that we should reject those that are unhealthy and develop healthier alternatives. But what is Nietzsche’s conception of health, and why should it carry such normative force? In this paper I argue for reading Nietzsche’s concept of health as the overall ability to meet the demands of one’s motivational landscape. I show that, unlike other interpretations, this reading accounts for his rejection of particular (...) features of a prevailing, then as now, model of health; for his association of health with strength and with psychic unity; and for his claim that health is compatible with, and can even be enhanced by, functional impairments such as those from which he personally suffered. Throughout I draw connections to recent literature on health and disability. (shrink)

Abstract: Public procurement is the acquisition of right goods, works and services required to satisfy certain needs at the right time, from the right supplier, in the right quantities, in the right quality, and at the right price. Worldwide it accounts 10% – 30 % of GNP while in Tanzania it accounts for about more 45% of the total budget. Appropriate procurement system in the public sector is a tool for achieving political, economic and social goals. The research examined the (...) impact of the capacity building on the performance of LGAs procurement function, was conducted in Tanzania to the four regions in 2018, comprised a sample size of 224 respondents from eight Local Government Authorities (LGAs). Qualitative and quantitative data were collected, employed the case study method intended to the Evaluate Assessment of Capacity Building Programme on the Performance of LGAs procurement functions. The study revealed that procurement functions have improved because of the intervention of capacity building such as the improvement of the; Use and application of PPA and PPR, use and application of Procurement Planning, use and application of Contract Management and Administration, use procurement record keeping and reporting, use and application of PMIS & Other Procurement Systems, appropriate Tendering Process. Also, the researchers have revealed challenges hindering LGAs procurement system such as; lack training, unpredictable funds flow and political interference. Moreover, based on the contributions attributed by the capacity building further research can be undertaking to measure the impact of capacity building in the other areas apart from procurement field such as; health, agriculture, good governance and so on. In addition to that, another research can be undertaken to assess the factors hindering the performance of LGAs procurement system. (shrink)

Summary Background Self-binding directives instruct clinicians to overrule treatment refusal during future severe episodes of illness. These directives are promoted as having potential to increase autonomy for individuals with severe episodic mental illness. Although lived experience is central to their creation, service users’ views on self-binding directives have not been investigated substantially. This study aimed to explore whether reasons for endorsement, ambivalence, or rejection given by service users with bipolar disorder can address concerns regarding self-binding directives, decision-making capacity, and human (...) rights. Methods This study used qualitative data from an internet-based survey distributed to the mailing list of the UK charity Bipolar UK, which contained multiple closed and open questions on advance decision-making in bipolar disorder. Quantitative analysis of a closed question about self-binding directives had already demonstrated endorsement amongst a very high proportion of participants with bipolar disorder who completed the survey. We conducted thematic analysis of responses from those participants who answered a subsequent open question about reasons for their view. Research was co-produced within a multi-disciplinary team, with clinical, legal, and ethical expertise, and lived experience of bipolar disorder. Ideas and methodologies associated with all these areas of expertise were used in the analysis of these reasons and to gain insight into the thoughts of individuals with bipolar disorder about self-binding directives and associated issues. Findings Between Oct 23 and Dec 5, 2017, 932 individuals with a self-reported clinical diagnosis of bipolar disorder completed the internet survey, with 565 (154 men; 400 women; 11 transgender or other) providing free text answers to the open question. A large majority of respondents endorsed self-binding directives, nearly all describing a determinate shift to types of distorted thinking and decision-making when unwell as their key justification. Responses indicating ambivalence were dominated by logistical concerns about the drafting and implementation of self-binding directives, while those who rejected self-binding directives also cited logistical concerns, validity of their thinking when unwell, and potential contravention of human rights. Interpretation This study is, to our knowledge, the first large study of reasons why mental health service users might endorse or reject the use of self-binding directives. The findings provide empirical support for introducing self-binding directives into mental health advance decision-making practice and policy and may help to address enduring ethical concerns surrounding possible implementation of the directive while a person retains decision-making capacity. The opinions expressed here in responses given by multiple service users with bipolar disorder challenge a prominent view within international disability rights debates that involuntary treatment and recognition of impaired mental capacity constitute inherent human rights violations. Funding The Wellcome Trust . (shrink)

Can we identify potential long-term consequences of digitalisation on public health? Environmental studies, metabolic research, and state of the art research in neurobiology point towards the reduced amount of natural day and sunlight exposure of the developing child, as a consequence of increasingly long hours spent indoors online, as the single unifying source of a whole set of health risks identified worldwide, as is made clear in this review of currently available literature. Over exposure to digital environments, from (...) abuse to addiction, now concerns even the youngest (ages 0 to 2) and triggers, as argued on the basis of clear examples herein, a chain of interdependent negative and potentially long-term metabolic changes. This leads to a deregulation of the serotonin and dopamine neurotransmitter pathways in the developing brain, currently associated with online activity abuse and/or internet addiction, and akin to that found in severe substance abuse syndromes. A general functional working model is proposed under the light of evidence brought to the forefront in this review. (shrink)

The volume provides an updated perspective on international aspects of various developments in media and culture. It includes discussions on how the digital environment contributes to the transformation and re-interpretation of existing phenomena, such as violence-on-demand in online movies, the internet appeal of virtual gangsta rappers, or the revived battle rap tradition, which operates outside the commercial limitations of the music industry and generates more views on social media than most recording artists. -/- The book offers a new consideration (...) of long-term trends and developments, and demonstrates in various examples how formerly marginal practices like gaming or the previously shunned Turkish movie industry have turned into influential tools of social change. In addition, the reciprocity of media content and political settings is underlined in a focus on the Arab world and the reconstruction of impulses from transnational media outlets to recent forms of citizen journalism, as well as in the case of governments’ approaches to media policy in response to the COVID-19 pandemic. The book places the spotlight on pressing issues, such as the ongoing enforcement of information control in the name of public health or the local politics and practices that hinder the process of democratization in authoritarian systems. -/- . (shrink)

Numerous research groups are now utilizing Basic Formal Ontology as an upper-level framework to assist in the organization and integration of biomedical information. This paper provides elucidation of the three existing BFO subcategories of realizable entity, namely function, role, and disposition. It proposes one further sub-category of tendency, and considers the merits of recognizing two sub-categories of function for domain ontologies, namely, artifactual and biological function. The motivation is to help advance the coherent ontological treatment of functions, roles, and dispositions, (...) to help provide the potential for more detailed classification, and to shed light on BFO’s general make-up and use. (shrink)

Measurement of ability or inability to perform activities of daily living is important to in describing the functional status of a person and then implementing an intervention. Evaluations of ADLs are mainly used in nursing and in rehabilitation of people with disabilities and the elderly. Measuring ability to perform ADLs is crucial for the management of healthcare in aging societies. It is important to understand differences between categories of ADLs and challenges in their evaluation that are connected to the roles (...) of family members. (shrink)

Mental health is a global priority, and states and stakeholders are taking steps toward advancing a human right to mental health for all (APA, 2018). This is evidenced by international studies, initiatives, declarations, and domestic policy interventions. From a right-based perspective, mental health is not the mere absence of a psychiatric condition or psychosocial disability (WHO, 2022). It speaks of an environment in which individuals live a life of dignity. The application of human rights principles (...) to mental health allows us to incorporate novel ideas about the role of all stakeholders in fostering the security, freedom, justice, and dignity of individuals. With this point of view in mind, many states are revisiting their mental health laws and governance practices. (shrink)

„Errors are the greatest obstacles to the progress of science; to correct such errors is of more practical value than to achieve new knowledge,“ asserted Eugen Bleuler. Basic error of several prevailing classification schemes of pathological conditions, as for example ICD-10, lies in confusing and mixing symptoms with diseases, what makes them unscientific. Considering the need to bring order into the chaos and light into terminological obscureness, I introduce the Causal classification of diseases originating from the notion of (...) bodily wholeness and causality of its loss. (shrink)

Much disease and disability is the result of lifestyle behaviours. For example, the contribution of imprudence in the form of smoking, poor diet, sedentary lifestyle, and drug and alcohol abuse to ill-health is now well established. More importantly, some of the greatest challenges facing humanity as a whole – climate change, terrorism, global poverty, depletion of resources, abuse of children, overpopulation – are the result of human behaviour. In this chapter, we will explore the possibility of using advances (...) in the cognitive sciences to develop strategies to intentionally manipulate human motivation and behaviour. While our arguments apply also to improving prudential motivation and behaviour in relation to health, we will focus on the more controversial instance: the deliberate targeted use of biomedicine to improve moral motivation and behaviour. We do this because the challenge of improving human morality is arguably the most important issue facing humankind (Persson and Savulescu, forthcoming). We will ask whether using the knowledge from the biological and cognitive sciences to influence motivation and behaviour erodes autonomy and, if so, whether this makes it wrong. (shrink)

How can researchers use race, as they do now, to conduct health-care studies when its very definition is in question? The belief that race is a social construct without “biological authenticity” though widely shared across disciplines in social science is not subscribed to by traditional science. Yet with an interdisciplinary approach, the two horns of the social construct/genetics dilemma of race are not mutually exclusive. We can use traditional science to provide a rigorous framework and use a social-science approach (...) so that “invisible” factors are used to adjust the design of studies on an as-needed basis. One approach is to first observe health-care outcomes and then categorize the outcomes, thus removing genetic differences as racial proxies from the design of the study. From the outcomes, we can then determine if there is a pattern of conceivable racial categories. If needed, we can apply dynamic notions of race to acknowledge bias without prejudice. We can use them constructively to improve outcomes and reduce racial disparities. Another approach is nearly identical but considers race not at all: While analyzing outcomes, we can determine if there are biological differences significant enough to identify classifications of humans. That is, we look for genetic patterns in the outcomes and classify only those patterns. There is no attempt to link those patterns to race. (shrink)

Abstract: Rice is one of the most important staple crops in the world and serves as a staple food for more than half of the global population. It is a critical source of nutrition, providing carbohydrates, vitamins, and minerals to millions of people, particularly in Asia and Africa. This paper presents a study on using deep learning for the classification of different types of rice. The study focuses on five specific types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. (...) A dataset of 75,000 images was collected and annotated, consisting of 15,000 images for each of the five types of rice. The deep learning system uses convolutional neural networks (CNNs) to classify images of rice grains based on their physical characteristics. The performance of the deep learning system was evaluated using metrics such as accuracy, precision, recall, and F1-score. The results show that the proposed deep learning system was able to achieve high accuracy in classifying the different types of rice, outperforming traditional image processing techniques. This study provides valuable insights into the potential of deep learning for classifying different types of rice and can be useful for applications such as quality control in rice processing industries and research in crop science. The large size of the dataset, 15,000 images for each type of rice, helped the deep learning system to learn the features of each type of rice, and increase the performance of the classifier. The attained overall accuracy of the proposed model (99.96%), Precision (99.96%), Recall (99.96%) and F1-score (99.96%). Thus, the proposed model proved that it leaned the five categories of rice and it can generalize these categories and it is effective. (shrink)

Abstract: As Nigeria’s Central Bank marks its 60th anniversary, it has become necessary to assess its performance. Consequently in this paper, we provide a comprehensive, unbiased review of the Central bank of Nigeria (CBN). The paper starts with a discussion on the role and activities of the West African Currency Board, which was the precursor of the CBN and subsequently analyzes how the Board led to the emergence of the CBN. We look at the functions, mandate and organizational structure of (...) the CBN. Second, we assess how the CBN has responded to the changing financial landscape over the years. Third, noting that the CBN has over time promoted financial reforms and played a key regulatory role, we discuss the sufficiency of the financial reforms it has promoted as well as the regulatory tools that it has deployed over the years. In this regard, we specifically highlight the role of the CBN in the global financial crises of 2007-2009 as well as the European debt crises of 2010 to 2013. Fourth, given that the primary mandate of the CBN revolves around price and exchange rate stability, we analyze its performance thus far noting the numerous challenges it has faced. Summarily, we find that the CBN has operated a multi-pronged approach by utilizing a combination of policy instruments including price-based, quantity-based and administrative policy measures. Going forward, we recommend that the CBN needs to continue to adopt avant garde mechanisms to further strengthen the Nigerian banking industry with a view to maintaining the stability and health of the economy. (shrink)

Innovation is progressively needed in responding to global challenges. Moreover, the increasing complexity of challenges implies demand for the usage of multisectoral and policy mix approaches. Wicked problems can be tackled by "integrated innovation" that combines the coordinated implementation of social, technological, and health innovation co-created by entities of the public sector, the private sector, the non-governmental sector, and the informal sector. This Research Topic focuses on filling the knowledge gaps about the selected types of innovation. First, regarding social (...) innovation that can be understood as new strategies, concepts, products, services, and organizational forms that allow the satisfaction of human needs. Second, a technological innovation that refers to new or remarkably improved products, goods, or services in terms of their technical specifications, components, materials, software, design, or other functional features. Third, health innovation that focuses on novel or enhanced health policies, systems, products, technologies, services, and care delivery schemes to improve people’s health. Finally, this Research Topic highlights attempts to develop integrated innovation that can add value to social policy, health policy, and environmental policy by improving efficiency, effectiveness, quality, sustainability, safety, and affordability. (shrink)

A pineapple is a tropical plant with eatable leafy foods most monetarily critical plant in the family Bromeliaceous. The pineapple is native to South America, where it has been developed for a long time. The acquaintance of the pineapple with Europe in the seventeenth century made it a critical social symbol of extravagance. Since the 1820s, pineapple has been industrially filled in nurseries and numerous tropical manors. Further, it is the third most significant tropical natural product in world creation. In (...) the twentieth century, Hawaii was a prevailing maker of pineapples, particularly for the US, be that as it may, by 2016, Costa Rica, Brazil, and the Philippines represented almost 33% of the world's creation of pineapples. In this paper, machine learning based approach is presented for identifying type pineapple with a dataset that contains 1,311images use 946 images for training, 197 images for validation and 168 images for testing. A deep learning technique that extensively applied to image recognition was used. use 70% from image for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a heldout test set. (shrink)

American Sign Language, or ASL as its acronym is commonly known, is a fascinating language, and many people outside of the Deaf community have begun to recognize its value and purpose. It is a visual language consisting of coordinated hand gestures, body movements, and facial expressions. Sign language is not a universal language; it varies by country and is heavily influenced by the native language and culture. The American Sign Language alphabet and the British Sign Language alphabet are completely contrary. (...) Fingerspelling is one-handed in ASL and two-handed in BSL, with the exception of the letter C. AI technologies, particularly deep learning, can play an important role in breaking down communication barriers between deaf or hearing-impaired people and other communities, significantly contributing to their social inclusion. Recent advances in sensing technologies and AI algorithms have paved the way for the development of a wide range of applications aimed at meeting the needs of the deaf and hearing-impaired communities. To that end, the purpose of this paper is By attempting to translate sign language using artificial intelligence algorithms, we focused in this paper on a transfer learning technique based on deep learning using a ResNet algorithm and compared it to previous papers in which we used VGG19[1]and mobileNet [2], where we get in the ResNet algorithm on the degree of Accuracy 93,48% e number of images (43500 in the dataset in size 64*64 pixel ) and the data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch. (shrink)

This entry discusses the relationship between disability and well‐being. Disabilities are commonly thought to be unfortunate, but whether this is true is unclear, and, if it is true, it is unclear why it is true. The entry first explains the disability paradox, which is the apparent discrepancy between the level of well‐being that disabled people self‐report, and the level of well‐being that nondisabled people predict disabled people to have. It then turns to an argument that says that disabilities (...) must be bad, because it is wrong to cause them in others. Later sections discuss whether disabilities might be intrinsically bad or even bad by definition. The final section addresses the claim that disabilities are bad only because society discriminates against people with disabilities. (shrink)

Introduction: Multiple sclerosis (MS) is an autoimmune disease that causes scar tissue in the nervous system and seriously affects the quality of life of people. Muscle weakness, spasticity and coordination problems are seen primarily in the lower extremities. Strengthening exercises improve muscle strength in people with multiple sclerosis, but there is no consensus on their effect on walking capacity. -/- Methods: To determine the relationship between gluteus maximus muscle strength, ataxia, balance and walking capacity in Multiple Sclerosis. An experimental study (...) design was applied. Gluteus maximus muscle strength was measured using a dynamometer. Walking capacity was determined by the 6-minute walk test (6MWT) and dynamic gait index (DGI). Balance was evaluated with the one-leg standing test (SLS). The severity of ataxia was measured with the International Ataxia Rating Scale (ICARS). Fatigue was evaluated with VAS and quality of life of all patients with SF36 short form. -/- Results: EDSS mean of the study = 3.39 ± 1.4; 2 men and 16 women with mean age = 37.17 ± 9.16 years were included. 6MWT, DGI, ALS, ICARS, VAS were different before and after treatment (p<0.05). There was no significant difference other than physical function and general health among the sub-parameters of SF36 (p>0.05). Correlation of muscle strength with ataxia, gait and balance was not significant (p>0.05) -/- Conclusion: In individuals with MS, the fact that the treatment program consists of modalities that include balance and sensory exercises as well as muscle strengthening exercises increases the success of rehabilitation. (shrink)

Defining Ecosophy (ecological wisdom) like a contemporary philosophy of survival, security and a sustainable Human Development, terrestrial nature and society, the author of this article approaches the correlation between it and the digital version of security in the context of new technologies. Human survival is in connection with the protection, optimal functioning of the natural environment and the development of human society. Human evolution, physical and psychological (the issues of Anthropoecology, a medical-biological science, deals with them), depends on the natural (...) and social environment, on the development of new techniques and technologies. New technologies (nano-, bio-, info-, socio-technologies) can ensure the security and the increasing development of the human being, but they can threaten it too. The author does not deny behaviours, the possibility that human intellect could be non-biological. Moreover, the author believes if it comes to it, that we will not be able to speak about the human species. New technologies like the traditional and less new, are intended to help in solving various problems related to health, society interactions with nature, human society and diverse cultures, societies and states. The philosophy of security and the digital one, like the components of Ecosophy, along with philosophical aspects of Anthropoecology, General Ecology and Social Ecology, needs like any other science or philosophy to elaborate systems of concepts, principles and laws. (shrink)