Is the war entering a new phase? Romania has blamed Russia for a drone strike that sank a cargo ship off Romania's Black Sea coast, killing one crew member and leaving three others missing. It's the latest drone attack targeting commercial shipping off the coasts of NATO members Romania and Bulgaria, with at least seven cargo ships hit and 30 sailors reported killed or missing in the past two weeks, raising fears of an escalation in Russia's war against Ukraine. The shipping data website MarineTraffic showed the Khoryv departed Turkiye on Wednesday and was headed for Romania's Sulina port, which links the Danube River to the Black Sea. The canal has become the primary route for Ukrainian exporters, which rely on ports on the Danube and Romanian territorial waters, as Russia has attacked Ukraine's own Black Sea ports.

'I wasn't thinking straight' says five jobs civil servant Image caption, Kashim Chowdhury wears dark sunglasses, a hat, hoody and gloves as he arrives at court. His face is largely obscured. A civil servant accused of fraudulently juggling multiple public sector jobs has told the court he wasn't thinking straight when he allegedly misled future bosses about his employment status. Kashim Chowdhury said he was in a panic when he applied for a job at the Department of Health (DHSC), failing to declare he was already working at the Department for the Environment (Defra). The prosecution said he already had three full-time jobs at the time, including roles at the London Borough of Tower Hamlets and East London NHS Trust.

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The maps and images show the extent of destruction and give rescue operations a tool to find any remaining survivors. A satellite image from Vantor shows collapsed apartment buildings and widespread damage caused by the earthquake in the Playa Grande neighborhood of La Guaira. Satellite Technology Is being used to streamline rescue efforts in Venezuela following the two earthquakes that struck on June 24. Space agencies have shared images with emergency authorities and the Venezuelan government that not only reveal the magnitude of the disaster but also allow response teams to identify where to focus their efforts--and the challenges on the ground. Following the twin earthquakes in Venezuela, the Copernicus satellite system activated its emergency mapping mode at the request of the European Commission's Directorate-General for Civil Protection and Humanitarian Aid Operations.

In recent years, consumer-grade UAVs have been widely adopted by first responders. In general, they are operated manually, which requires trained pilots, especially in unknown GNSS-denied environments and in the vicinity of structures. Autonomous flight can facilitate the application of UAVs and reduce operator strain. However, autonomous systems usually require special programming interfaces, custom sensor setups, and strong onboard computers, which limits a broader deployment. We present a system for autonomous flight using lightweight consumer-grade DJI drones. They are controlled by an Android app for state estimation and obstacle avoidance directly running on the UAV's remote control. Our ground control station enables a single operator to configure and supervise multiple heterogeneous UAVs at once. Furthermore, it combines the observations of all UAVs into a joint 3D environment model for improved situational awareness.

In the field of medicine and healthcare, the utilization of medical expertise, based on medical knowledge combined with patients' health information is a life-critical challenge for patients and health professionals. The within-laying complexity and variety form the need for a united approach to gather, analyze, and utilize existing knowledge of medical treatments, and medical operations to provide the ability to present knowledge for the means of accurate patient-driven decision-making. One way to achieve this is the fusion of multiple knowledge sources in healthcare. It provides health professionals the opportunity to select from multiple contextual aligned knowledge sources which enables the support for critical decisions. This paper presents multiple conceptual models for knowledge fusion in the field of medicine, based on a knowledge graph structure. It will evaluate, how knowledge fusion can be enabled and presents how to integrate various knowledge sources into the knowledge graph for rescue operations.

Healthcare and Medicine are under constant pressure to provide patient-driven medical expertise to ensure a fast and accurate treatment of the patient. In such scenarios, the diagnosis contains, the family history, long term medical data and a detailed consultation with the patient. In time-critical emergencies, such conversation and time-consuming elaboration are not possible. Rescue services need to provide fast, reliable treatments for the patient in need. With the help of modern technologies, like treatment recommendations, real-time vitals-monitoring, and situation detection through artificial intelligence (AI) a situation can be analyzed and supported in providing fast, accurate patient-data-driven medical treatments. In KIRETT, a wearable device is developed to support in such scenarios and presents a way to provide treatment recommendation in rescue services. The objective of this paper is to present the quantitative results of a two-day KIRETT evaluation (14 participants) to analyze the needs of rescue operators in healthcare.

The integration of vital signs in healthcare has witnessed a steady rise, promising health professionals to assist in their daily tasks to improve patient treatment. In life-threatening situations, like rescue operations, crucial decisions need to be made in the shortest possible amount of time to ensure that excellent treatment is provided during life-saving measurements. The integration of vital signs in the treatment holds the potential to improve time utilization for rescuers in such critical situations. They furthermore serve to support health professionals during the treatment with useful information and suggestions. To achieve such a goal, the KIRETT project serves to provide treatment recommendations and situation detection, combined on a wrist-worn wearable for rescue operations.This paper aims to present the significant role of vital signs in the improvement of decision-making during rescue operations and show their impact on health professionals and patients in need.

This short paper presents first steps in the scientific part of the KIRETT project, which aims to improve first aid during rescue operations using a wearable device. The wearable is used for computer-aided situation recognition by means of artificial intelligence. It provides contextual recommendations for actions and operations to rescue personnel and is intended to minimize damage to patients due to incorrect treatment, as well as increase the probability of survival. The paper describes a first overview of research approaches within the project.