Biological characteristics and outcomes of gliosarcoma

Gliosarcoma is a highly aggressive primary brain tumour. It is a relatively rare tumour and comprises of two histological components, glial and sarcomatous. Gliosarcomas carry a poorer prognosis than that of Glioblastoma Multiforme (GBM). The current review highlights important histological and radiological features of gliosarcoma in the light of recent literature, and also touches upon the treatment options and outcomes of various types of gliosarcoma

Extended Health Services of Pharmacists: Role in COVID-19 Management

COVID-19 is creating a chaotic scenario all over the world. Due to the unavailability of approved therapy, the number of affected cases is escalating day by day. Different components of the healthcare system have been consistently working in different settings for its containment. Pharmacists are one of the healthcare experts, who are working on the front-line. In this review, we aimed to evaluate the activities of pharmacists as a healthcare professional in disasters such as; COVID-19 management. The focus on services offered by pharmacists has shifted from traditional dispensing and compounding to patient-specific over a period contributing to the quality use of medicine and primary care. Pharmacists are thus, considered essentially one of the main pillars of the healthcare team for the provision of extended health services (EHS), for instance, the effective management of COVID-19. They are working from community to clinical setting. Practicing tele-pharmacy health services, they can reach out to remote places as well. Utilizing their expertise on clinical as well as managerial aspects, they have proved to be dynamic professionals in such a global health crises. Adequate training, inclusion of disaster management in the curriculum of pharmacy, support from the legislative body, and inter- as well as intra-professional collaboration are the key factors for professional development and recognition

Extending SATPLAN to Multiple Agents

Abstract Multi-agent planning is a core issue in the multi-agent systems field. In this work we focus on the coordination of multiple agents in a setting where agents are able to achieve individual goals that may be either independent, or necessary for the achievement of a global common goal. The agents are able to generate individual plans in order to achieve their own goals, but, as they share the same environment, they need to find a coordinated course of action that avoids harmful (or negative) interactions, and benefits from positive interactions, whenever this is possible. Moreover, agents are interested in finding plans with optimal length where preference is given to the length of the joint plan. We formalize these problems in a more general way with respect to previous works and present a coordination algorithm which provides the optimal solution in the case of two agents. In this algorithm, agents use µ-SATPLAN as the underlying planner for generating individual and joint consistent plans. This planner is an extension of the well known classical planner SATPLAN, aiming to deal with negative and positive interactions and, therefore, with multi-agent planning problem. Finally we present the experimental results using the multi-agent planning problems from the domains proposed and used in classical planning, which demonstrate the effectiveness of µ-SATPLAN and the coordination algorithm.

Un langage de programmation agent intégrant la planification temporelle et les mécanismes de coordination de plans

PARIS-BIUSJ-Mathématiques rech (751052111) / SudocSudocFranceF

Pre-Christ Wisdom and Civilization in Aag Ka Darya

Qurratulain Hayder is a renowned fiction writer of the twentieth century. Her novel Aag ka Darya (also translated as River of Fire) is considered to be a classic in the tradition of Urdu fiction writing. This novel deals with Indian civilization and wisdom emanating from there in pre-Christ era. She has presented various constituting elements of Indian civilization through this narrative. Besides that, the thoughts and the teachings of the wise of that age, namely, Gautam Buddha, Mahavir, Kapil, Panini and Chankya have also been interwoven in the story. This article explores these themes and civilzational details in the novel.</p

Black Cohosh and Liver Toxicity: Is There a Relationship?

Herbal supplements are commonly used by patients for various problems. It is a well-known fact that most patients do not tell their physicians about the use of herbal supplements unless they are specifically asked. As a result, sometimes important information regarding drug side effects is missed in history taking. During our literature search, we found several retrospective studies and other meta-analyses that claim a lacking or weak link between black cohosh use and hepatotoxicity. We present a case of a 44-year-old female who developed subacute liver injury demonstrated on a CT scan and liver biopsy within a month of using the drug to resolve her hot flashes and discuss a possible temporal and causal association between black cohosh use and liver disease. Since the patient was not taking any other drugs, we concluded that the acute liver injury was caused by the use of black cohosh. We agree with the United States Pharmacopeia recommendations that a cautionary warning about hepatotoxicity should be labeled on the drug package

Smart Scheduling of EVs Through Intelligent Home Energy Management Using Deep Reinforcement Learning

This article presents the deep reinforcement learning (DRL) based smart scheduling in intelligent home energy management system (SSIHEMS) for electric vehicles (EVs) scheduling by utilizing the photovoltaic (PV) on the rooftop for economic dispatch problems. Therefore, optimizing home appliances to minimize consumption cost is challenging because of the randomness of electricity prices and poses a challenge for efficient scheduling. The data-driven model-free DRL-based SSIHEMS is utilized to optimize the decision by managing different home appliances and offering appropriate scheduling EVs to overcome the shortcomings. The decision includes the proper scheduling of battery charging, discharging, and EV to reduce the dependency on the electric grid through a collaborative approach. In addition, the proposed work covers designing a gym-based environment that incorporates the states fed to an agent and receives the reward based on the action taken for scheduling. Hence, the case study is performed to validate the proposed approach. It is verified that the decisions for battery charging, discharging, and EV scheduling are managed well through PV generation with respect to time. Furthermore, to verify the robustness and effectiveness, a comparison of different algorithms such as deep Q-network (DQN), double DQN, and dueling DQN

Current Status and Performance Analysis of Table Recognition in Document Images With Deep Neural Networks

The first phase of table recognition is to detect the tabular area in a document. Subsequently, the tabular structures are recognized in the second phase in order to extract information from the respective cells. Table detection and structural recognition are pivotal problems in the domain of table understanding. However, table analysis is a perplexing task due to the colossal amount of diversity and asymmetry in tables. Therefore, it is an active area of research in document image analysis. Recent advances in the computing capabilities of graphical processing units have enabled the deep neural networks to outperform traditional state-of-the-art machine learning methods. Table understanding has substantially benefited from the recent breakthroughs in deep neural networks. However, there has not been a consolidated description of the deep learning methods for table detection and table structure recognition. This review paper provides a thorough analysis of the modern methodologies that utilize deep neural networks. Moreover, it presents a comprehensive understanding of the current state-of-the-art and related challenges of table understanding in document images. The leading datasets and their intricacies have been elaborated along with the quantitative results. Furthermore, a brief overview is given regarding the promising directions that can further improve table analysis in document images

A Hierarchical Control Methodology for Renewable DC Microgrids Supporting a Variable Communication Network Health

The monitoring and control of renewable energy sources (RESs) based on DC (Direct Current) microgrids (DC MG) are gaining much consideration at this time. In comparison with the isolated individual control of converters in a microgrid, DC microgrids provide better voltage regulation and harmonized energy generation/consumption. To address the inherent vulnerability of communication links, robust methods have been proposed that improve the resilience of communication-based control. However, the failure of the communication links in microgrid control layers remains a considerable issue that may lead to one or more nodes being disconnected and operating as a communication island. Such types of communication islanding may cause the unpredictable behavior of the system and further destabilization may lead to a cascaded failure. This paper proposes a fast algorithm to detect and evaluate network connectivity based on the information stored at every node in the form of a look-up table. The control structure has been modified under communication islanding, and a communication connectivity observer is used at every node to detect and address power flow issues under communication islanding. The proposed method has been verified through mathematical analysis, simulation, and experimental results