bluuebunny/crossref_metadata_2025_split huggingface dataset:
From Headache to Handled: Advanced In-Basket Management System in Primary Care Clinics Reduces Provider Workload Burden and Self-Reported Burnout
Authors: Smith LaPortia , Kirk Wendy , Bennett Monica M. , Youens Kenneth , Ramm Jason 
Published: October 2024

Abstract
Background The electronic health record (EHR) has been associated with provider burnout, exacerbated by increasing In-Basket burden.
Objectives We sought to study the impact of implementing a team-based approach to In-Basket management on a series of primary care ambulatory sites.
Methods We performed a workflow analysis of the transition to the Advanced In-Basket Management (AIM) nurse team triage for six family medicine clinic locations in a large health system. We abstracted and analyzed associated provider workflow metrics from our EHR. We conducted a postintervention provider survey on satisfaction with the AIM project and provider burnout.
Results The AIM project was implemented in six family medicine clinics after provider townhalls and workgroup development. A nurse team curriculum was created using the principles of “maturing the message” before sending it to a provider and “only handle it once” to improve response efficiency. Provider workload metrics abstracted from the EHR demonstrated 12.2 fewer In-Basket messages per provider per day (p < 0.05), 6.3 fewer minutes per provider per day worked outside scheduled hours (p < 0.05), 3.5 fewer minutes spent in the In-Basket per provider per day (p < 0.05), but 13.7 more seconds spent per completed message per provider (p = 0.017), likely attributable to increased message complexity. Sixty-four percent of providers reported no burnout symptoms in a postintervention survey, 56% agreed that the AIM project reduced their burnout, and approximately 70% of providers agreed that the AIM project was acceptable and appropriate for their clinic.
Conclusion The AIM project demonstrates team-based nurse In-Basket triage is possible to implement across multiple primary care sites, is an acceptable intervention for providers, can reduce provider workload burden and self-reported provider burnout.
Disseminating fraud awareness and prevention advice to older adults: perspectives on the most effective means of delivery
Authors: Button Mark , Shepherd David , Hawkins Chloe , Tapley Jacki 
Published: October 2024

AbstractRaising awareness to combat scams has become a central strategy of fraud/scam prevention. Using data from a wider evaluation of a targeted campaign to improve fraud prevention and awareness for older adults predominantly over 75, this paper offers findings on the most effective means of dissemination of anti-scam communications to this group. The paper draws upon almost 1000 questionnaire responses and qualitative data from older adults, as well as volunteers and workers involved in the project. The research finds many older adults have not received any fraud prevention or awareness communications in the prior six months, illustrating a gap in fraud prevention messaging reaching this group. The paper also shows that the preferred method of dissemination is one-to-one through friends and family and that is also the case for the most isolated. The paper offers some potential solutions to address these gaps, particularly for lonely older adults.
Time-dependent rovibronic wave function of H

2
+

by multiconfiguration theory
Authors: Lötstedt Erik , Kato Tsuyoshi , Yamanouchi Kaoru 
Published: October 2024

Abstract
We simulate the time-dependent rovibronic wave function of H

2
+

in an intense, few-cycle 400 nm laser field using a time-dependent multiconfiguration method. By calculating the expectation value of the total angular momentum squared, the time-dependent expectation value of the internuclear distance, the induced dipole moment, and the probability of electron ejection, we show that rotational, vibrational and electronic excitation as well as ionization can be simulated. We compare the results obtained using the time-dependent multiconfiguration method with the results obtained using the standard two-state Born-Oppenheimer approximation and the close-coupling expansion. We find that the multiconfiguration results for a wave function constructed using 21 time-dependent orbitals are in good agreement with the close-coupling results, but that the two-state Born-Oppenheimer approximation leads to an underestimation of the induced dipole moment by a factor of two and an overestimation the expectation value of the total angular momentum squared by a factor of 2.3.
A bearing fault diagnosis model with convolutional cross transformer and ResNet18
Authors: Ma Xurui , Wang Yanyan , Qin Jinning , Wang Zefeng , Liu Zhengyang 
Published: October 2024

Abstract
In the industrial field, malfunction of rotating machinery, especially bearings, can cause significant economic losses to enterprises. Addressing the limitations of traditional fault diagnosis methods, such as poor generalization performance and low noise resistance, this paper introduces a fault diagnosis model that parallels the cross convolutional transformer and ResNet18 (CCTAR). The proposed CCTAR utilizes two feature extraction channels, aimed at balancing the extraction of local and global features, and the specially designed convolutional cross-decoding layer has excellent noise resistance, surpassing traditional multi-layer Transformer encoding layers with a single-layer structure. CCTAR achieves commendable recognition accuracy across multiple datasets and maintains high accuracy in noisy environments. Furthermore, transfer learning experiments have demonstrated the proposed model’s capability to achieve superior fault diagnosis performance across different working conditions with a limited number of samples, highlighting its practical significance.
Measurement of plasma electron energy distribution functions by Langmuir probe using a modified AC modulation method
Authors: Xu L F , Zhao J , Jian Y , Kang H J 
Published: October 2024

Abstract
In the diagnosis of vacuum discharge plasma using the Langmuir probe, the electron energy distribution function (EEDF) is closely related to the second derivative of current to voltage (d
2
I/dV
2) on the Langmuir probe. While d
2
I/dV
2 is very sensitive to probe noise, its accuracy directly affects the measurement results of the EEDF. In this paper, a modified AC modulation method is proposed to improve the measurement accuracy of the EEDF. First, two small AC signals of different amplitudes are modulated on the measured DC scanning voltage of the Langmuir probe, and the probe current signal is measured. Then, the fundamental amplitudes of the two AC signals are corrected by spectral analysis and using the all-phase fast Fourier transformation—fast Fourier transformation amplitude correction algorithm. Then the accurate first-order derivative of the probe current to voltage (dI/dV) is obtained using the AC modulation derivative correction algorithm, and finally the EEDF is obtained by numerically differentiating dI/dV to obtain d
2
I/dV
2. The method of this paper is compared with the traditional data processing method through experiments, and the results show the superiority and effectiveness of the method.
Effect of different injection strategies considering intravenous injection on combination therapy of magnetic hyperthermia and thermosensitive liposomes
Authors: Zhu 朱 Jiajia 佳佳 , Tang 汤 Yundong 云东 , Flesch 弗 Rodolfo C. C. 莱施C. C. 鲁道夫 , Jin 金 Tao 涛 
Published: October 2024

Abstract
The combination therapy of magnetic hyperthermia and thermosensitive liposomes (TSL) is an emerging and effective cancer treatment method. The heat generation of magnetic nanoparticles (MNPs) due to an external alternating magnetic field can not only directly damage tumor cells, but also serves as a triggering factor for the release of doxorubicin from TSL. The aim of this study is to investigate the effects in the degree of tumor cell damage of two proposed injection strategies that consider intravenous administration. Since both MNPs and TSL enter the tumor region intravenously, this study establishes a biological geometric model based on an experiment-based vascular distribution. Furthermore, this study derives the flow velocity of interstitial fluid after coupling the pressure distribution inside blood vessels and the pressure distribution of interstitial fluid, which then provides the convective velocity for the calculation of subsequent nanoparticle concentration. Different injection strategies for the proposed approach are evaluated by drug delivery result, temperature distribution, and tumor cell damage. Simulation results demonstrate that the proposed delayed injection strategy after optimization can not only result in a wider distribution for MNPs and TSL due to the sufficient diffusion time, but also improves the distribution of the temperature and drug concentration fields for the overall efficacy of combination therapy.
Multi-Horizon Model Predictive Control for Energy Management in Zero-Emission High-Speed Passenger Vessels
Authors: Najjaran Samieh , Skjetne Roger 
Published: October 2024

Abstract
High-speed passenger vessels (HSPVs) play an important role in coastal regions due to their high energy consumption and emissions. This study develops an optimal energy management system (EMS) for a zero-emission hybrid power system, powered by a fuel cell (FC) and a battery energy storage system (BESS). The global optimal solution for loading the FC and operating the BESS is computed using a linear programming (LP) approach, assuming a priori knowledge of the complete operational profile. Since the global solution is not realizable in an onboard EMS, the main objective of this paper is to develop an algorithm for real-time application. A multi-horizon model predictive control (MH-MPC) algorithm is applied to a model of the power system to solve the optimization problem with a prediction mechanism over the entire route. This approach is benchmarked against the global LP solution to evaluate the effectiveness of the proposed EMS. The results highlight the potential of the MH-MPC approach for achieving a near-optimal EMS in a zero-emission HSPV.
Just-in-Time Port Call Optimization: Challenges and IT-Systems
Authors: Pahl Julia 
Published: October 2024

Abstract
Many ports serve ships on a first-come-first-serve (FCFS) basis leading to negative environmental impacts due to ships “hurrying up to wait” if berths are not ready forcing them to idle at anchorage. Besides the fuel consumption used at elevated speed to be in good time in the port area, average anchorage times can account for 5 − 10% of ship voyage durations during which ships still emit carbon dioxide (CO2) while running auxiliary engines consuming ca. 15% of the voyage’s marine fuel. Ships deciding to skip or reshuffle port calls due to this might enforce this practice which can result into overall uncertainty, unbalanced port resource utilization including congestion and logjams rippling entire industries. Congested port areas complicate traffic management of arriving and leaving ships. The need to establish a comprehensive system for managing arrivals and departures becomes even more pressing in the case of damaged ships or accidents. Besides, early communicating terminal and port readiness notices allows ships to adjust their speed and save fuel of up to 21% of the overall voyage. Information technological advances made great progress by optimizing individual ship voyages. However, the optimization of cargo transport within a system which can also take into account real-time safety levels of ships, is still unsolved. In this paper, we review past research on just-in-time (JIT) port call optimization (PCO), its challenges, and its way forward through digitalization efforts to achieve desperately needed greenhouse gas (GHG) emissions reductions.
Design of sustainable integrated energy systems for green ports – selection and sizing
Authors: Polić Dražen , Melloh Tobias , Malhotra Avichal , Zadeh Mehdi , Dunger Torsten 
Published: October 2024

Abstract
Design of sustainable and integrated energy systems for marine port is a complex problem, involving multiple conflicting objectives like energy efficiency and minimum losses, cost-effectiveness, and avoiding excessive cycling and degradation. This paper addresses the sizing of integrated and sustainable port energy systems with renewable energy sources and energy storage systems based on two different methods. Both developed methods start by selecting design sets representing the gradual expansion of renewable sources and storage to the maximum size, limited by various constraints. Each design variant is evaluated based on the energy demands of the port, historical prices, and site energy production capacity. The first method, developed by ITK Engineering GmbH, uses a conventional deterministic forecasting approach with detailed annual data. The latter, developed by NTNU, employs several 24-hour data sets to capture annual energy dynamics. Key performance indicators for both methods are defined based on the total cost, with the benchmark cost obtained using the first (deterministic) method with 100% grid-supplied energy. Two virtual ports of different sizes (Port A and B) are established in two electric markets (1 and 2) for verification and benchmarking. The paper then discusses the influence of uncertainty in 24-hour data sets, used by the second (stochastic) method, for all cases.
Envisioning a decision support system for the planning of alternative fuel bunkering operations in Singapore
Authors: Low Kai Sheng Bryan , Tkalich Pavel , Hei Chow Jeng , Sasmal Kaushik 
Published: October 2024

Abstract
In the coming decades, the global maritime industry will face a most formidable technological and societal challenge set by climate change – achieving net zero carbon emissions by 2050. To meet this target, ships are shifting towards the use of low-carbon alternative fuels such as ammonia and methanol. While this paradigm shift to the bunkering of greener fuels is encouraging, it also introduces a new and unique type of environmental risk in the unfortunate scenario of a spill. In the past decades numerous environmental studies have been conducted and mitigation techniques for petroleum oil spills have been developed. However, ammonia and methanol spills are comparatively less understood globally and in the region. There is a significant knowledge gap regarding how the complex atmosphere, hydrodynamic and environmental conditions of the Singapore Straits may influence the dispersion and assimilation of hypothetical ammonia or methanol plumes. Together with other emerging alternative fuels such as electricity and hydrogen, ammonia and methanol have different physical and chemical properties in ambient water compared to conventional LNG or petroleum oil which makes modelling the risk they pose to the environment more challenging. In view of these challenges, the key objective of our research is to develop an operationally running decision support system (DSS) that combines physics-based atmospheric and coastal hydrodynamic models that can forecast the marine and atmospheric plume dispersion of alternative fuels. This forecasting capability will be supplemented with data-driven and rule-based optimisation algorithms that can be used to determine the optimal mitigation scenarios which minimises the potential environmental impacts. Overall, the DSS will integrate observation data, models, mitigation scenarios, and decision-making tools pertaining to efficient and safe bunkering operations within Singapore’s ports. This is essential as the use of alternative fuels in maritime industry becomes more common in Singapore and around the world. Such a system will aid relevant authorities to better calculate risk and plan mitigation measures at designated bunkering locations and periods having optimal atmospheric, hydraulics, and environmental conditions. In this paper, we describe the potential consequences of alternative fuel spills, mitigation measures and a plan for assessing their environmental impact within the context of Singapore. We will review the limited current efforts to model ammonia spills in the literature and propose for a more integrated modelling approach through the DSS.
A novel method for evaluating ship concept performance in transport systems
Authors: Nordahl H , Tangstad E J , Specht P , Podimatas V C , Dæhlen J S , Wennersberg L A L 
Published: October 2024

Abstract
Transport carries significant external costs such as climate change, accidents, pollution, and road congestion, driving national and international strategies for the development of new transport concepts. This includes shifting larger cargo volumes away from roads to more sustainable transport modes such as waterborne. The SEAMLESS project was launched in 2023 to answer to these needs by developing technology for autonomous waterborne zero-emission feeder-loop services. The realisation of such services depends on their modal competitiveness. Autonomous ships are expected to reduce transport costs and emissions, and ultimately improve logistical performance. There are, however, few published studies that quantify these impacts of autonomy. Furthermore, commercial waterborne autonomous transport services do not exist yet, limiting the possibilities for empirical analysis. Hence, research is needed to address exactly how and to what extent, autonomy improves competitiveness in different applications. This paper addresses the need for more empirical analyses of innovative waterborne transport performance, by presenting a novel method for evaluating ship concept performance in transport systems. The impacts of design choices are captured through hydrodynamic and logistical simulations. The method can be applied to transport systems consisting of both conventional and novel ship designs, operating on one or more routes including transhipments. It is implemented in the software SIMPACT and applied to a case study which establishes a shortsea feeder-loop service in the Bergen area in Norway. The Bergen municipality has decided that the container terminal is to be moved out of the city centre to reduce local traffic and emissions. However, in the absence of a competitive waterborne transport service in this region, the relocation will have the unfortunate consequence of an estimated annual net increase in regional truck traffic of 40,000 additional truck trips over 25km. By means of the proposed methodology, this paper investigates the feeder-loop concept and compare its quantified performance to truck transport and finds that competition is feasible.
Bridge Detection in Autonomous Shipping: A YOLOv8 Approach with Autodistill and GroundedSAM
Authors: Schlonsak Ruben , Schreiter Jan-Philipp , Hellbrück Horst 
Published: October 2024

Abstract
Inland waterway transportation remains a crucial and cost-effective mode of global transport despite challenges such as skilled personnel shortages, increasing competition, and ecological impacts. Autonomous technology enhances vessel navigation, scheduling, safety, and efficiency, making it a viable solution for smart ship and port operations. Reliable object detection is essential for autonomous ships to navigate safely and avoid collisions with static structures like bridges, piers, bollards, and locks.
This paper presents an innovative approach for training a network using the Autodistill pipeline for bridge detection and segmentation. We generate a labeled bridge dataset using GroundedSAM, which integrates Grounding DINO and the Segment Anything Model (SAM) to detect and segment regions based on text input. The system focuses on identifying ‘bridge’ and ‘water’ classes, producing high-quality labeled data. Manual filtering improves label quality, enhancing the training of the YOLOv8 model, known for its superior object detection capabilities.
Our approach demonstrates high performance in accurately detecting bridges, confirmed through evaluations with and without manual filtering. To validate our solution’s feasibility in real-world applications, we deployed the model on a NVIDIA Jetson AGX Orin for performance evaluation. Future work will extend this approach to additional static and mobile objects relevant to smart ship and port operations, such as ship locks and various ship types.
Lidar-Based Obstacle Detection and Path Prediction for Unmanned Surface Vehicles
Authors: Zantopp Nico , Budak Akif , Delea Cosmin , Werner Herberto , Nok Au Ching , Oeffner Johannes 
Published: October 2024

Abstract
Unmanned Surface Vehicles (USVs) represent an advanced technology with a wide range of applications in maritime contexts, and they offer a promising alternative to manned systems, particularly for the provision of services such as riverbed mapping. Furthermore, the use of USVs in combination with other robotic systems, such as flying drones, remotely operated underwater vehicles (ROVs) and autonomous underwater vehicles (AUVs), opens up innovative ways to inspect and monitor maritime infrastructure. However, the use of these systems in dynamic environments, such as ports or shipping lanes, requires a high degree of adaptability and precision in navigation to manoeuvre safely between other traffic participants and obstacles to prevent collisions. To address this problem, USVs require sophisticated perception systems for the precise detection and classification of nearby objects. Leveraging Light Detection and Ranging (LiDAR) technology, which is renowned for its efficacy in obstacle avoidance in robotics, this paper outlines the adaptation of a LiDAR sensor for USVs. The proposed pipeline enables the detection of other moving vessels and the accurate determination of their positions and trajectories up to 150 m from the USV. This paper introduces an obstacle detection system and validates it within a port setting. A methodical approach to LiDAR data preprocessing, clustering, and point cloud extraction will be outlined. Furthermore, it explores the application of an Unscented Kalman Filter (UKF) for the projection of motion paths of identified entities. This advanced form of data analysis provides the ability to predict the future position and path of potential obstacles, optimize decision-making for autonomous navigation algorithms and significantly improve the safety of USV operations. The pipeline is tested experimentally in sea trials by enacting five different scenarios that USV may encounter in a port setting. The results of the pipeline’s tracking capabilities are compared to the ground truth data collected by the tracked vessel and plotted to visualize the error.
A Simple and Forgiving Automatic Docking System for Under-Actuated USVs
Authors: Maximilian Odenwald Jakob , Alexander Christensen Kim , Didriksen Endre , Hagen Helgesen Håkon , Steinert Martin 
Published: October 2024

Abstract
This article presents the development and testing of an automatic docking system, tailored to smaller, under-actuated, and uncrewed vessels. The system integrates a vessel control system for safe and repeatable dock approaches, and a mooring system capable of handling significant trajectory and pose offsets. The developed system features a shore-focused, floating structure with vertically mounted flat funnels for mooring. Testing involved various on-water experiments, validating the system’s reliability in correcting yaw and lateral offsets under challenging conditions. Later development and testing included the integration of automatic mooring control, a vessel charging concept, as well as a capable vessel approach controller. The final test demonstrated the system’s ability to achieve automatic docking in 33 out of 36 attempts despite varying wind conditions. The system’s performance highlights its potential to enhance docking safety and efficiency for under-actuated vessels. Combining automatic approach and automatic mooring, the presented system has the potential to enable routine under-actuated USV operations with minimal human effort.