Background Integrating artificial intelligence (AI) into healthcare has raised significant ethical concerns. In pharmacy practice, AI offers promising advances but also poses ethical challenges. Methods A cross-sectional study was conducted in countries from the Middle East and North Africa (MENA) region on 501 pharmacy professionals. A 12-item online questionnaire assessed ethical concerns related to the adoption of AI in pharmacy practice. Demographic factors associated with ethical concerns were analyzed via SPSS v.27 software using appropriate statistical tests. Results Participants expressed concerns (...) about patient data privacy (58.9%), cybersecurity threats (58.9%), potential job displacement (62.9%), and lack of legal regulation (67.0%). Tech-savviness and basic AI understanding were correlated with higher concern scores (p < 0.001). Ethical implications include the need for informed consent, beneficence, justice, and transparency in the use of AI. Conclusion The findings emphasize the importance of ethical guidelines, education, and patient autonomy in adopting AI. Collaboration, data privacy, and equitable access are crucial to the responsible use of AI in pharmacy practice. (shrink)

In their report for the Swiss government onthe notion of the dignity of creatures, PhilippBalzer, Klaus-Peter Rippe, and Peter Schaber analyzethe relationship between human dignity and the dignityof creatures, taking them as two categoricallydifferent concepts. Human dignity is defined as the``moral right not to be humiliated,'' whereas thedignity of creatures is taken to be ``the inherentvalue of nonhuman living beings.'' To my mind there isno need to draw a categorical distinction between thetwo concepts. Both notions could be brought togetherunder an (...) all-encompassing concept of the inherentvalue of living beings, humans and non-humans alike,a concept one could name ``the dignity of livingbeings.'' Indeed, this very notion underlies theposition taken in the report, although this is notmade explicit by the authors themselves.As the aim of the paper is only to clarify theconcepts used, I do not go beyond this ``internal''critique of their position, i.e., I don't assess howthe claims articulated via these concepts – theclaim that humans and/or creatures have an inherentvalue consisting in a supposed intrinsic good – areto be justified, although I myself would be ratherskeptical that this might be successfully done. (shrink)

Radiography images are widely utilized in the health sector to recognize the patient health condition. The noise and irrelevant region information minimize the entire disease detection accuracy and computation complexity. Therefore, in this study, statistical Kolmogorov–Smirnov test has been integrated with wavelet transform to overcome the de-noising issues. Then the cat swarm-optimized deep belief network is applied to extract the features from the affected region. The optimized deep learning model reduces the feature training cost and time and improves the overall (...) disease detection accuracy. The network learning process is enhanced according to the AdaDelta learning process, which replaces the learning parameter with a delta value. This process minimizes the error rate while recognizing the disease. The efficiency of the system evaluated using image retrieval in medical application dataset. This process helps to determine the various diseases such as breast, lung, and pediatric studies. (shrink)

The Self We Live By confronts the serious challenges facing the self in postmodern times. Taking issue with contemporary trivializations of the self, the book traces a course of development from the early pragmatists who formulated what they called the 'empirical self', to contemporary constructionist views of the storied self. Presenting an institutional context for the increasing complexity and ubiquity of narrative identity, the authors illustrate the 'everyday technology of self construction' and idscuss the resulting moral climate. The book is (...) suitable for advanced undergraduates and graduate students in courses such as Individual in Society, Contemporary American Society, Social Psychology, Social Interaction and Culture & Personality. (shrink)

Dass die Würde des Menschen unantastbar sei, stellt eine der populärsten, aber auch eine der umstrittensten Aussagen des Grundgesetzes dar. Dabei wird eine sachorientierte Diskussion oft durch mehr oder minder unausgewiesene semantische und historische Annahmen blockiert. Aus dieser Beobachtung heraus wird zum einen überlegt, wie sich unterschiedliche Bedeutungen des Ausdrucks "Menschenwürde" unterscheiden und ethischen Fragestellungen resp. Positionen zuordnen ließen. Zum anderen wird die Einführung des Ausdrucks in das Verfassungsrecht nachgezeichnet. Das Hauptaugenmerk gilt dabei Art.1 Abs. 1 Grundgesetz, dessen Gehalt in (...) Auseinandersetzung mit der bisherigen Rechtsprechung rekonstruiert wird. (shrink)

Content-based image retrieval (CBIR) is a technique used to retrieve image from an image database. However, the CBIR process suffers from less accuracy to retrieve many images from an extensive image database and prove the privacy of images. The aim of this article is to address the issues of accuracy utilizing deep learning techniques such as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon–Kim–Kim–Song (CKKS). The system has been proposed, namely (...) RCNN_CKKS, which includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a new dataset. In the second part (online processing), the client sends the encrypted image to the server, which depends on the CNN model trained to extract features of the sent image. Next, the extracted features are compared with the stored features using a Hamming distance method to retrieve all similar images. Finally, the server encrypts all retrieved images and sends them to the client. Deep-learning results on plain images were 97.87% for classification and 98.94% for retriever images. At the same time, the NIST test was used to check the security of CKKS when applied to Canadian Institute for Advanced Research (CIFAR-10) dataset. Through these results, researchers conclude that deep learning is an effective method for image retrieval and that a CKKS method is appropriate for image privacy protection. (shrink)

We prove that in a nilpotent-by-finite stable group an equation that holds generically holds everywhere. Combining this result with results of Wagner and Bryant, we conclude that a soluble-by-finite stable group of generic exponent n has exponent n.

RésuméOn prouve que dans un groupe stable, nilpotent par fini, une équation générìquement satisfaite y est partout satisfaite. En combinant ce résultat avec des résultats de Wagner et Bryant, on déduit qu'un groupe stable résoluble-par-fini d'exposant généríquenest d'exposantn.

Internet-of-Things (IoT) creates a significant impact in spectrum sensing, information retrieval, medical analysis, traffic management, etc. These applications require continuous information to perform a specific task. At the time, various intermediate attacks such as jamming, priority violation attacks, and spectrum poisoning attacks affect communication because of the open nature of wireless communication. These attacks create security and privacy issues while making data communication. Therefore, a new method autoencoder deep neural network (AENN) is developed by considering exploratory, evasion, causative, and priority (...) violation attack. The created method classifies the transmission outcomes used to predict the transmission state, whether it is jam data transmission or sensing data. After that, the sensing data is applied for network training that predicts the intermediate attacks. In addition to this, the channel access algorithm is used to validate the channel for every access that minimizes unauthorized access. After validating the channel according to the neural network, data have been transmitted over the network. The defined process is implemented, and the system minimizes different attacks on various levels of energy consumption. The effectiveness of the system is implemented using TensorFlow, and the system ensures the 99.02% of detection rate when compared with other techniques. (shrink)

In this paper, we present an intensive investigation of the finite volume method compared to the finite difference methods. In order to show the main difference in the way of approaching the solution, we take the Burgers equation and the Buckley–Leverett equation as examples to simulate the previously mentioned methods. On the one hand, we simulate the results of the finite difference methods using the schemes of Lax–Friedrichs and Lax–Wendroff. On the other hand, we apply Godunov’s scheme to simulate the (...) results of the finite volume method. Moreover, we show how starting with a variational formulation of the problem, the finite element technique provides piecewise formulations of functions defined by a collection of grid data points, while the finite difference technique begins with a differential formulation of the problem and continues to discretize the derivatives. Finally, some graphical and numerical comparisons are provided to illustrate and corroborate the differences between these two main methods. (shrink)

IntroductionFew studies have examined psychological distress in healthcare workers across the care continuum. This study describes distress levels reported by HCWs across care settings and factors associated with distress.MethodsA cross-sectional survey of HCWs from Windsor, Ontario, was conducted between May 30th, 2020, and June 30th, 2020. The survey included the Kessler Psychological Distress Scale, sociodemographic, frontline status, perceptions of training, protection, support, respect among teams, and professional and personal stressors. Univariate analyses were used to compare across settings and multivariate logistic (...) regression assessed factors associated with distress.ResultsFour hundred and three HCWs from the hospital, community health and social service, first responder, primary care, home, and long-term care participated in the survey. Common concerns included fear of transmitting COVID-19 to family, safety on the job, and balancing personal care with work demands. LTC and home-care HCWs reported greater concern about workload and staffing levels, whereas community health workers were more anxious about their financial security. Overall, 228 HCWs who completed the K10 reported high distress, with greater rates among hospital and LTC HCWs. Distress was more likely in HCWs who identified as female, younger than 55, perceived lower respect among team, and experienced greater worry about physical and mental health and managing high workloads.ConclusionResults showed a high degree of distress experienced by HCWs across care settings and the impact of the COVID-19 pandemic on personal and work-related stress. Promoting self-care and supportive and collaborative healthcare teams are promising avenues for mitigating symptoms of distress. (shrink)

Nowadays, lung cancer is one of the most dangerous diseases that require early diagnosis. Artificial intelligence has played an essential role in the medical field in general and in analyzing medical images and diagnosing diseases in particular, as it can reduce human errors that can occur with the medical expert when analyzing medical image. In this research study, we have done a systematic survey of the research published during the last 5 years in the diagnosis of lung cancer classification of (...) lung nodules in 4 reliable databases, and we selected 50 research paper using systematic literature review. The goal of this review work is to provide a concise overview of recent advancements in lung cancer diagnosis issues by machine learning and deep learning algorithms. This article summarizes the present state of knowledge on the subject. Addressing the findings offered in recent research publications gives the researchers a better grasp of the topic. We checked all the characteristics, such as challenges, recommendations for future work were analyzed in detail, and the published datasets and their source were presented to facilitate the researchers’ access to them and use it to develop the results achieved previously. (shrink)

Early adversity and trauma can have profound effects on children’s affective development and mental health outcomes. Interventions that improve mental health and socioemotional development are essential to mitigate these effects. We conducted a pilot study examining whether a reading-based program improves emotion recognition and mental health through socialization in Syrian refugee and Jordanian non-refugee children aged 7–12 years old living in Jordan. To measure emotion recognition, children classified the expression in faces morphed between two emotions, while mental health was assessed (...) using survey measures of optimism, depression, anxiety, distress, and insecurity. Prior to the intervention, both groups of children were significantly biased to interpret ambiguous facial expressions as sad, while there was no clear bias on the fear–anger spectrum. Following the intervention, we found changes in Syrian refugee children’s bias in emotion recognition away from sad facial expressions, although this returned to pre-intervention levels 2 months after the end of the program. This shift in the bias away from sad facial expressions was not associated with changes in self-reported mental health symptoms. These results suggest a potential positive role of the reading intervention on affective development, but further research is required to determine the longer-term impacts of the program. (shrink)

A patient with a history of bipolar II disorder and endstage renal disease who required hemodialysis for five years abruptly wished to withdraw from dialysis on day seven of her hospital admission for a urinary tract infection. She had never discussed wishing to withdraw from dialysis prior to this hospital admission. She had experienced several symptoms of depression during her stay. Her desire to withdraw from dialysis treatment was discordant with her previously expressed desires, and the psychiatry team determined that (...) her judgment was likely altered by her depressive episode. Given her previous positive response to electroconvulsive therapy (ECT), the psychiatry team recommended that she receive ECT before she choose to withdraw from dialysis. (shrink)