Suboptimal exchange of information can have tragic consequences to patient's safety and survival. To this end, the Joint Commission lists communication error among the most common attributable causes of sentinel events. The risk management literature further supports this finding, ascribing communication error as a major factor (70%) in adverse events. Despite numerous strategies to improve patient safety, which are rooted in other high reliability industries (e.g., commercial aviation and naval aviation), communication remains an adaptive challenge that has proven difficult to overcome in the sociotechnical landscape that defines healthcare. Attributing a breakdown in information exchange to simply a generic "communication error" without further specification is ineffective and a gross oversimplification of a complex phenomenon. Further dissection of the communication error using root cause analysis, a failure modes and effects analysis, or through an event reporting system is needed. Generalizing rather than categorizing is an oversimplification that clouds clear pattern recognition and thereby prevents focused interventions to improve process reliability. We propose that being more precise when describing communication error is a valid mechanism to learn from these errors. We assert that by deconstructing communication in healthcare into its elemental parts, a more effective organizational learning strategy emerges to enable more focused patient safety improvement efforts. After defining the barriers to effective communication, we then map evidence-based recovery strategies and tools specific to each barrier as a tactic to enhance the reliability and validity of information exchange within healthcare.
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http://dx.doi.org/10.1097/PTS.0000000000000541 | DOI Listing |
Nat Commun
January 2025
Department of Biological Sciences, Dedman College of Humanities and Sciences, Southern Methodist University, Dallas, TX, 75275, USA.
The 40S ribosomal subunit recycling pathway is an integral link in the cellular quality control network, occurring after translational errors have been corrected by the ribosome-associated quality control (RQC) machinery. Despite our understanding of its role, the impact of translation quality control on cellular metabolism remains poorly understood. Here, we reveal a conserved role of the 40S ribosomal subunit recycling (USP10-G3BP1) complex in regulating mitochondrial dynamics and function.
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January 2025
Institute of Telecommunications, Faculty of Computer Science, Electronics and Telecommunications, AGH University of Krakow, Al. Mickiewicza 30, 30-059 Krakow, Poland.
The currently observed development of time-sensitive applications also affects wireless communication with the IoT carried by UAVs. Although research on wireless low-latency networks has matured, there are still issues to solve at the transport layer. Since there is a general agreement that classical transport solutions are not able to achieve end-to-end delays in the single-digit millisecond range, in this paper, the use of WebRTC is proposed as a potential solution to this problem.
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January 2025
Free-Space Optical Communication Technology Research Center, Harbin Institute of Technology, Harbin 150001, China.
To achieve real-time deep learning wavefront sensing (DLWFS) of dynamic random wavefront distortions induced by atmospheric turbulence, this study proposes an enhanced wavefront sensing neural network (WFSNet) based on convolutional neural networks (CNN). We introduce a novel multi-objective neural architecture search (MNAS) method designed to attain Pareto optimality in terms of error and floating-point operations (FLOPs) for the WFSNet. Utilizing EfficientNet-B0 prototypes, we propose a WFSNet with enhanced neural architecture which significantly reduces computational costs by 80% while improving wavefront sensing accuracy by 22%.
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January 2025
Department of Mechanical and Intelligent Systems Engineering, The University of Electro-Communications, Tokyo 1828585, Japan.
Recently, aerial manipulations are becoming more and more important for the practical applications of unmanned aerial vehicles (UAV) to choose, transport, and place objects in global space. In this paper, an aerial manipulation system consisting of a UAV, two onboard cameras, and a multi-fingered robotic hand with proximity sensors is developed. To achieve self-contained autonomous navigation to a targeted object, onboard tracking and depth cameras are used to detect the targeted object and to control the UAV to reach the target object, even in a Global Positioning System-denied environment.
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January 2025
SHCCIG Yubei Coal Industry Co., Ltd., Xi'an 710900, China.
The coal mining industry in Northern Shaanxi is robust, with a prevalent use of the local dialect, known as "Shapu", characterized by a distinct Northern Shaanxi accent. This study addresses the practical need for speech recognition in this dialect. We propose an end-to-end speech recognition model for the North Shaanxi dialect, leveraging the Conformer architecture.
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