Suchergebnisse

On March 6, 2018, the Court of Justice of the European Union (CJEU) found in Slowakische Republik (Slovak Republic) v. Achmea B.V. that the arbitration agreement contained in the 1991 Agreement on Encouragement and Reciprocal Protection of Investments between the Kingdom of the Netherlands and the Czech and Slovak Federative Republic (BIT) had an adverse effect on the autonomy of EU law and, thus, was incompatible with EU law. This important decision has ignited a debate on the compatibility of other arbitration agreements in both intra-EU bilateral investment treaties (intra-EU BITs) and in the Energy Charter Treaty (ECT) with EU law.

Tsang Lau, Jawad AhmadDivision of Liver Diseases, Mount Sinai School of Medicine, New York, USAAbstract: The Model for End-Stage Liver Disease (MELD) score incorporates serum bilirubin, creatinine, and the international normalized ratio (INR) into a formula that provides a continuous variable that is a very accurate predictor of 90-day mortality in patients with cirrhosis. It is currently utilized in the United States to prioritize deceased donor organ allocation for patients listed for liver transplantation. The MELD score is superior to other prognostic models in patients with end-stage liver disease, such as the Child–Turcotte–Pugh score, since it uses only objective criteria, and its implementation in 2002 led to a sharp reduction in the number of people waiting for liver transplant and reduced mortality on the waiting list without affecting posttransplant survival. Although mainly adopted for use in patients waiting for liver transplant, the MELD score has also proved to be an effective predictor of outcome in other situations, such as patients with cirrhosis going for surgery and patients with fulminant hepatic failure or alcoholic hepatitis. Several variations of the original MELD score, involving the addition of serum sodium or looking at the change in MELD over time, have been examined, and these may slightly improve its accuracy. The MELD score does have limitations in situations where the INR or creatinine may be elevated due to reasons other than liver disease, and its implementation for organ allocation purposes does not take into consideration several conditions that benefit from liver transplantation. The application of the MELD score in prioritizing patients for liver transplantation has been successful, but further studies and legislation are required to ensure a fair and equitable system.Keywords: MELD score, liver transplantation

Due to COVID-19, the government of Pakistan had to take measures to bring about changes in almost all infrastructures, including that of education and decided to switch to a virtual learning environment and urged all educational institutes to adopt virtual learning strategies to facilitate student learning process. In an attempting to contain the virus instructed educational institutes to explore virtual space to continue learning process. The University of Lahore was one of the few universities in Pakistan that took the lead and decided to serve the learning purpose. However, due to cultural differences and dependency on traditional learning, most universities found it difficult to follow suit. The University of Lahore has crossed a milestone and emerged as a model for other universities across country. The virtual learning strategies that have been adopted by the University are no less than international standards and the administration have been working tirelessly to ensure the smooth running of this digital education system. Based on the student survey and faculty interviews, this study recommends regular virtual trainings by educational institutes and to overcome the issues of internet connectivity and electricity in the country as a whole to better deal with the challenges that lie ahead.

Satellite images have drawn increasing interest from a wide variety of users, including business and government, ever since their increased usage in important fields ranging from weather, forestry and agriculture to surface changes and biodiversity monitoring. Recent updates in the field have also introduced various deep learning (DL) architectures to satellite imagery as a means of extracting useful information. However, this new approach comes with its own issues, including the fact that many users utilize ready-made cloud services (both public and private) in order to take advantage of built-in DL algorithms and thus avoid the complexity of developing their own DL architectures. However, this presents new challenges to protecting data against unauthorized access, mining and usage of sensitive information extracted from that data. Therefore, new privacy concerns regarding sensitive data in satellite images have arisen. This research proposes an efficient approach that takes advantage of privacy-preserving deep learning (PPDL)-based techniques to address privacy concerns regarding data from satellite images when applying public DL models. In this paper, we proposed a partially homomorphic encryption scheme (a Paillier scheme), which enables processing of confidential information without exposure of the underlying data. Our method achieves robust results when applied to a custom convolutional neural network (CNN) as well as to existing transfer learning methods. The proposed encryption scheme also allows for training CNN models on encrypted data directly, which requires lower computational overhead. Our experiments have been performed on a real-world dataset covering several regions across Saudi Arabia. The results demonstrate that our CNN-based models were able to retain data utility while maintaining data privacy. Security parameters such as correlation coefficient (−0.004), entropy (7.95), energy (0.01), contrast (10.57), number of pixel change rate (4.86), unified average change intensity (33.66), and more ...

To avoid chaos and disconnect with learning activities, governments decided to switch to virtual learning environment and urged all educational institutes to adopt virtual learning strategies to facilitate student learning process during COVID-19. The government of Pakistan, in the attempt to contain the virus instructed educational institutes to explore virtual space to continue learning process. The University of Lahore was one of the few universities in Pakistan that took the lead and decided to serve the learning purpose. It is, however, difficult in Pakistan to switch to online learning easily because of cultural differences as education system in Pakistan is mainly based on traditional learning but the University of Lahore has crossed a milestone and emerged as a model for other universities across country. The virtual learning strategies that have been adopted by the University are no less than international standards and the administration have been working tirelessly to ensure the smooth running of this digital education system. Based on the student survey and faculty interviews, this study recommends regular virtual trainings by educational institutes and to overcome the issues of internet connectivity and electricity to better deal with the challenges lie ahead.

Internet of Things Overview: Architecture, Technologies, Application, and Challenges -- IoMT Applications Perspectives: from Opportunities and Security Challenges to Cyber-Risk Management -- Cybersecurity Challenges and Implications for the Adoption of Cloud Computing and IoT: DDoS Attacks as an Example -- Implementation of the C4.5 Algorithm in the Internet of Things Applications -- Intrusion Detection Systems using Machine Learning -- Multivariate Procedure for Modeling and Prediction of Temperature in Punjab, Pakistan -- New Proposed Model for the Influence of Climate Change on the Tension Anticipation in Hospital Emergencies -- Statistical Downscaling Modeling for Temperature Prediction -- UAV-based IoT applications for action recognition -- Federated Learning for Market Surveillance -- Fake News in Social Media: Fake News Themes and Intentional Deception in the News and on Social Media.