bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated deep brain stimulation programming with safety constraints for tremor suppression in patients with Parkinson’s disease and essential tremor
Authors: Sarikhani Parisa , Ferleger Benjamin , Mitchell Kyle , Ostrem Jill , Herron Jeffrey , Mahmoudi Babak , Miocinovic Svjetlana 
Published: August 2022

Abstract

Objective. Deep brain stimulation (DBS) programming for movement disorders requires systematic fine tuning of stimulation parameters to ameliorate tremor and other symptoms while avoiding side effects. DBS programming can be a time-consuming process and requires clinical expertise to assess response to DBS to optimize therapy for each patient. In this study, we describe and evaluate an automated, closed-loop, and patient-specific framework for DBS programming that measures tremor using a smartwatch and automatically changes DBS parameters based on the recommendations from a closed-loop optimization algorithm thus eliminating the need for an expert clinician. Approach. Bayesian optimization which is a sample-efficient global optimization method was used as the core of this DBS programming framework to adaptively learn each patient’s response to DBS and suggest the next best settings to be evaluated. Input from a clinician was used initially to define a maximum safe amplitude, but we also implemented ‘safe Bayesian optimization’ to automatically discover tolerable exploration boundaries. Main results. We tested the system in 15 patients (nine with Parkinson’s disease and six with essential tremor). Tremor suppression at best automated settings was statistically comparable to previously established clinical settings. The optimization algorithm converged after testing

15.1
±
0.7

settings when maximum safe exploration boundaries were predefined, and

17.7
±
4.9

when the algorithm itself determined safe exploration boundaries. Significance. We demonstrate that fully automated DBS programming framework for treatment of tremor is efficient and safe while providing outcomes comparable to that achieved by expert clinicians.
Influence of the number of trials on evoked motor cortical activity in EEG recordings
Authors: Borràs Marta , Romero Sergio , Alonso Joan F , Bachiller Alejandro , Serna Leidy Y , Migliorelli Carolina , Mañanas Miguel A 
Published: August 2022

Abstract

Objective. Improvements in electroencephalography enable the study of the localization of active brain regions during motor tasks. Movement-related cortical potentials (MRCPs), and event-related desynchronization (ERD) and synchronization are the main motor-related cortical phenomena/neural correlates observed when a movement is elicited. When assessing neurological diseases, averaging techniques are commonly applied to characterize motor related processes better. In this case, a large number of trials is required to obtain a motor potential that is representative enough of the subject’s condition. This study aimed to assess the effect of a limited number of trials on motor-related activity corresponding to different upper limb movements (elbow flexion/extension, pronation/supination and hand open/close). Approach. An open dataset consisting on 15 healthy subjects was used for the analysis. A Monte Carlo simulation approach was applied to analyse, in a robust way, different typical time- and frequency-domain features, topography, and low-resolution electromagnetic tomography. Main results. Grand average potentials, and topographic and tomographic maps showed few differences when using fewer trials, but shifts in the localization of motor-related activity were found for several individuals. MRCP and beta ERD features were more robust to a limited number of trials, yielding differences lower than 20% for cases with 50 trials or more. Strong correlations between features were obtained for subsets above 50 trials. However, the inter-subject variability increased as the number of trials decreased. The elbow flexion/extension movement showed a more robust performance for a limited number of trials, both in population and in individual-based analysis. Significance. Our findings suggested that 50 trials can be an appropriate number to obtain stable motor-related features in terms of differences in the averaged motor features, correlation, and changes in topography and tomography.
Containerized immutable maritime data sharing utilizing Distributed Ledger Technologies
Authors: Knutsen Knut Erik , Liang Qin , Karandikar Nikita , Ibrahim Imran Halimi Bin , Tong Xiao Gang Tony , Tam Jacob Jun Hui 
Published: August 2022

Abstract
In recent years, distributed ledger technologies (DLTs), especially blockchain technology, has become a popular topic and is being implemented in different industries. Ships are expected to be equipped with more advanced equipment and less crew onboard. The communication and information sharing between different maritime stakeholders such as business partners, port authorities, tax authorities, class societies, flag states, IMO and EU become more important than ever. Trust and authenticity are key properties when utilizing data for safety or business critical applications, and will only increase in importance as automation levels increase towards fully autonomous ships and trading systems. The implementation of DLTs as close as possible to the data source helps provide a reliable, trustworthy way to share, process and verify the data. The objective of this paper is to explore how tamperfree maritime data sharing can enable automated transactions between vessels and shore-based entities. Singapores TradeTrust platform has shown that digitalization of international trade has great potential. In this paper we explore how further enhancements may be implemented and how the distributed ledger VeChain, as compared to Ethereum, have some distinct advantages that may be beneficial for continued automation and efficiency gains. The electronic Bill of Lading was taken as an example to demonstrate the concept. Reporting requirements from the other maritime data sharing scenarios are also expected to require a way of ensuring tamperfree data.
Exploring navigator roles and tasks in transitioning towards supervisory control of autonomous collision avoidance systems
Authors: van de Merwe G K , Mallam S C , Engelhardtsen Ø , Nazir S 
Published: August 2022

Abstract
This study aims to systematically map and assess performance requirements for collision avoidance manoeuvring for two cases. A case where the navigator performs collision avoidance, and a case where collision avoidance is performed by collision avoidance system where the navigator acts as its supervisor. An appraisal of collision avoidance manoeuvring was performed based on three data sources: the collision avoidance regulations, a ferry operator’s procedures, and interviews with navigators including in situ observations. A framework was established in which the gathered data was structured and analysed using a cognitive task analysis approach. Based on the results, performance requirements and information needs were established. Further work will focus on detailing the navigator’s information needs and the corresponding system’s transparency requirements to support effective human performance.
Evaluation of effectiveness of the STAMP / STPA in risk analysis of autonomous ship systems
Authors: Yamada Tomoaki , Sato Makoto , Kuranobu Rikiya , Watanabe Ryo , Itoh Hiroko , Shiokari Megumi , Yuzui Tomohiro 
Published: August 2022

Abstract
To ensure safety of Maritime Autonomous Surface Ships (MASS), the importance of risk assessment is emphasized in classification societies, but the assessment method is not specified, and standardization of the method is expected. In the risk analysis of conventional ship, we focus on equipment failure mainly on hardware, but in MASS, it is necessary to analyze not only hardware but also large-scale and complicated systems including software and human beings. STAMP / STPA is an analysis method for large-scale and complicated systems, and it may be applicable to MASS risk analysis. In this paper, we will verify the effectiveness of STAMP / STPA in the initial stage of MASS design and consider it from a certification point of view.
Prediction of tidal-driven currents using convolutional neural network
Authors: Choo Jian Feng , Chow Jeng Hei , Tkalich Pavel 
Published: August 2022

Abstract
Efficient forecasting models of coastal currents are required for the predictive control of smart vessels with autonomous or remote operating capabilities. Accurate physics-based numerical models demand computational resources that often are unavailable onboard ships; moreover, internet bandwidth at remote locations might not be sufficient to exchange the large computational files with onshore servers. In this case, light and efficient Data-Driven Models (DDM) may be developed to be used as a surrogate for a physics-based model.
Currents and surface elevation are hydrodynamic variables driven by astronomic tide potential, allowing for harmonic analysis and synthesis of otherwise irregular solutions of Navier-Stokes equations. Once numerical solutions are obtained and analysed in the Fourier domain, the identified harmonics (tide constituents) can be used as a dataset to train the DDM. One approach to building a DDM is by utilizing a Convolutional Neural Network (CNN).
CNN is mainly applied in image recognition processes, where it learns the spatial features of image matrices of pixels arranged in columns and rows and uses the learned features to predict an output. This approach can be applied to 2D or 3D fields of predominantly tidal-driven coastal currents. This paper extends the CNN framework to approximate and predict coastal hydrodynamic state variables in space and time. The depth-averaged Navier-Stokes equations were used to create the dataset necessary to train the adopted CNN autoencoder architecture.
Two methods of CNN model development are explored. The first method assesses CNN’s capabilities for time forward prediction, using 2D time series of hydrodynamic variables. The second method investigates CNN’s parameter (using Manning number) prediction ability using 2D spatial plots formed by the top 20 most energetic tidal constituents that were obtained from the numerical solution. The hyperparameters of the CNN model for both methods were carefully optimized and tuned using the loss function, Root Mean Square Error (RMSE). The coefficient of determination, the relative error of the time series, and its amplitude and phase were used to gauge the performance of the CNN model for both methods at the final testing stage.
Once accurate solutions are achieved, the trained DDM is almost instantaneous and uses negligible computational resources as compared to traditional fluid solvers. Therefore, trained DDM can be deployed onboard ships where global forecast information (e.g., from Global Forecast System) can be used to provide an accurate prediction of the current forcing. To generate the instantaneous current predictions for navigation and smart ship control, the global data can be pulled or pushed to the ship before the mission.
Maritime Autonomous Surface Ships: Automation Transparency for Nearby Vessels
Authors: Alsos Ole Andreas , Hodne Philip , Skåden Oskar Kristoffer , Porathe Thomas 
Published: August 2022

AbstractIn the future, maritime autonomous surface ships (MASS) will become more advanced, and mariners will move from the bridge to remote operation centres. To avoid dangerous situations and frequent intervention from the operators, a MASS needs to perceive the environment and calculate the current state and future intention of nearby ships. Another challenge for a MASS is to explain the decisions of its algorithms and make the artificial intelligence’s decisions transparent to not only the operators, but also external stakeholders, such as passengers, vessel traffic services, and nearby ships. This is calledautomation transparency. In this paper we focus on how MASS, through various means of maritime communication, can (1)expresstheir own state and intention to other ships and (2)perceiveother ships’ state and intention. Towards that, we first analyse current maritime communication methods in terms of how well they can be expressed and perceived by today’s MASS in comparison to traditional ships. Next, we analyse which gaps in their communication should be focused on to maximise safety at sea. Finally, we present multiple design recommendations for naval architects, human factors engineers, and interaction designers who are designing and building the next generation of MASS.
milliAmpere: An Autonomous Ferry Prototype
Authors: Brekke Edmund F , Eide Egil , Eriksen Bjørn-Olav H , Wilthil Erik F , Breivik Morten , Skjellaug Even , Helgesen Øystein K , Lekkas Anastasios M. , Martinsen Andreas B , Thyri Emil H. , Torben Tobias , Veitch Erik , Alsos Ole A , Johansen Tor Arne 
Published: August 2022

AbstractIn this paper, we summarize the experiences with the autonomous passenger ferry development prototype milliAmpere, which has been used as a test platform in several research projects at the Norwegian University of Science and Technology (NTNU) since 2017. New algorithms for motion planning, motion control, collision avoidance, docking, multi-target tracking and localization have been developed and verified in full-scale experiments with milliAmpere. The infrastructure surrounding milliAmpere includes several sensor rigs supporting research on multi-sensor fusion and situational awareness, and a shore control lab which can be used to study the interaction between human operators and the autonomous ferry. Building upon the experiences with milliAmpere, the full-scale autonomous ferry milliAmpere2 was recently launched.
On the implementation of a rule-based system to perform assessment of COLREGs onboard maritime autonomous surface ships
Authors: Constapel M , Koch P , Burmeister H-C 
Published: August 2022

Abstract
Complying to the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) is one of the key challenges for Maritime Autonomous Surface Ships (MASS) to perform autonomous navigation. We propose a rule-based approach utilizing operationalized situation statements to assess vessel encounters with regards to COLREGs. The statements contain basic informational pieces to describe the relation between two vessels. For processing with a rule-based inference system, the statements are grouped into rule sets to determine applicable COLREGs rules for an encounter situation. Implementation results are shown in the context of the B ZERO project, outlining how the approach can be utilized onboard a seagoing ship.
Biofuel Adoption Pathways for Cargo Vessels under Carbon Tax
Authors: Xiao Zengqi , Lam Jasmine Siu Lee , Thepsithar Prapisala , Milla Kevin 
Published: August 2022

Abstract
According to the International Maritime Organization (IMO) Greenhouse Gas (GHG) Strategy, the shipping industry by 2050 aims to reduce by at least 50% of GHG emission level in 2008. Among various alternative energy sources, biofuels illustrate potential as a drop-in fuel using existing shipboard technologies, bunkering infrastructure, and a new fuel replacing conventional fossil-based fuels. However, the decision to adopt biofuel in vessels depends on various factors. Biofuels may be derived from different feedstock and production routes and thus demonstrate different economic and environmental performances. The compatible type of engines also differs across biofuels, implying differences in capital cost. In addition, a high carbon tax may push the usage of a more expensive biofuel, while a low carbon tax may not drive the switch from fossil fuel. This study aims to analyse biofuel adoption pathways under carbon tax to achieve a net 50% GHG emission reduction for cargo vessels, including bulk carriers, container vessels and tankers. The study focuses on the following types of fuels: low sulphur fuel oil (LSFO), marine gas oil (MGO), Liquefied natural gas (LNG), biodiesel in the form of palm methyl ester (PME), hydrotreated vegetable oil (HVO), and bio-LNG.
A quick surface heat flux estimation method for typical structures of high-speed aircrafts
Authors: Wu Long , Wang Feng , Wang Qi , Han Yiyu , Li Zhengzhou 
Published: August 2022

Abstract
Surface heat flux estimation of high-speed aircrafts is an inverse problem and high system ill-posedness usually leading to instability and low accuracy. In this study, an efficient method is proposed to solve it stably. The heat flux identification equation is established based on the superposition principle. Tikhonov regularization method with the parameter determined by generalized cross validation is applied to reduce the sensitivity to measurement error. A calibration method is presented to correct the pulse sensitivity coefficient matrix so that the estimation method can be used for complex three-dimensional structures. Numerical studies demonstrate the efficiency and accuracy.
Uncertainty analysis and visualization for a coupled thermohydraulics-neutronics simulation by deterministic sampling
Authors: Yang Wen , Huang Jun , Tian Zhaofei , Chen Guangliang 
Published: August 2022

Abstract
Uncertainty quantification and sensitivity analysis by deterministic sampling is performed on a thermohydraulics-neutronics coupling simulation of a 5×5 rod bundle in pressurized water reactor. Thermohydraulics calculation is conducted by a CFD simulation and neutronics calculation is conducted by method of characteristic (MOC). The coupling simulation of CFD and MOC, together with large number of calculations needed by random sampling in uncertainty quantification, leads to high computational cost. Therefore, deterministic sampling is introduced in this study and proves its efficiency. Moreover, the calculated results usually have some distribution pattern on the selected section, using mass average value as output is unable to reflect the distribution feature. Therefore, a method realized by Python program is introduced to perform uncertainty quantification and sensitivity analysis of the outputs on the outlet section in fine-mesh level. It is found that the uncertainty of outputs and the inputs’ impact on outputs vary in different areas at the outlet section.
Development of a single-scale initial flow field into steady homogeneous turbulence with validating a constructed Fourier spectral analysis
Authors: Suzuki Hiroki , Kouchi Toshinori 
Published: August 2022

Abstract
This study presents the development of a single-scale initial velocity field into steady homogeneous isotropic turbulence. Here, we verify a constructed Fourier spectral analysis, which is then used to approach the present issue. The present homogeneous isotropic turbulence is maintained steady by using a linear forcing scheme of Lundgren (2003). Here, two values of the primary coefficient are set here for this scheme. The initial velocity field is also set to maintain the flow globally isotropic. Temporal developments of turbulence statistics, visualization results and structure functions are examined in this study. As shown in a previous study, Rosales and Meneveau (2005), the turbulence length scale at a steady-state could remain independent of a value used for the linear forcing coefficient. The turbulence fields needed 10 to 15 times longer than the turbulence time scale to achieve this steady-state. A larger amount of time was needed for the structure functions to reach their steady-state profiles than for the turbulence statistics.
Flow structure of pitched and skewed microjet vortex generator array
Authors: Da Xingya , Yi Yuan , Zhang Yue , Guo Longkai , Tao Yang 
Published: August 2022

Abstract
To understand the micro-vortex structure of Microjet Vortex Generators, a plate with pitched and skewed jet holes was established. Simulations using SST-DDES method based on WENO scheme were conducted to analyse the effect of jet pressure, hole interval and incoming boundary layer thickness on the flow structure. The pitch angle and skew angle are 55 degrees and 45 degrees respectively. The total pressure of microjets ranges from 2.5 to 3.5 times the mainstream pressure. The interval of microjets ranges from 6.75 to 13.5 diameters of the hole, and the thickness of incoming boundary layer ranges from 2 to 4 diameters of the hole. The flow field is dominated by three vortices, including a main vortex and two secondary vortices which are significantly influenced by jet pressure and interval. The interaction between secondary vortices and main vortex plays an important role in the process of boundary layer mixing.
Improved theory of the elastic-plastic response of spherical containment vessels subjected to internal blast loading and its application
Authors: He Zeng , Wang Zhihuan , Zhang Baihua , Jia Leiming , Tian Zhou 
Published: August 2022

Abstract
Baker built the displacement equations of motion for a thin spherical shell to spherically symmetric internal blast loading, and further provided the analytical solution of the elastic-plastic response under a triangular decaying pressure, neglecting shell thinning and radius variation [1], which was widely used in the fields of analysis and design of explosion containment vessels. However, it appears that some improvements and corrections are needed when we revisit this classic problem. In this paper, the elastic-plastic response of thin spherical shells is investigated mathematically. The complete equations of motion for three models are developed. Then the main ideas of the analytical and numerical methods are presented, as well as some important procedures and results by using Laplace transform techniques, which are convenient to use and generalize. Three typical examples are solved to exhibit differences between our improved theory and Baker’s [1]. Furthermore, our models are employed to gain some insights into response regularities, including the effect of various degrees of strain-hardening on maximum displacements under impulsive loading, and the effect of loading duration on the shell displacement for a perfectly plastic material.
The dominant mechanism of gold film damage induced by near-threshold femtosecond laser: non-thermal deformation or thermal ablation
Authors: Zhang Ke , Sun Jingya 
Published: August 2022

Abstract
Near-threshold femtosecond laser produces nanostructures on the gold film, which has received much attention in applications. However, the theoretical researches on the early stage of gold film excitation induced by the femtosecond laser are scarce, because of the ultrafast and non-equilibrium characteristics. In this study, stress and temperature distributions in different thicknesses of gold film induced by the near-threshold fluences were calculated. At the fluence below the melting threshold, we found that only the 30 nm gold films might be damaged by the non-thermal deformation. At the fluence of the melting threshold, the dominant damage mechanism shifted from non-thermal deformation to thermal melting as the gold film thickness increased. Our study provided a way to distinguish the dominant damage mechanism of gold film and it was valuable for the theoretical study of near-threshold processing.
Quaternionic Dirac oscillator
Authors: Sadovskií D A , Zhilinskií B I 
Published: August 2022

Abstract
We construct an elementary quaternionic slow–fast Hamiltonian dynamical system with one formal control parameter and two slow degrees of freedom as half-integer spin in resonance 1:1:2 with two slow oscillators. Invariant under spin reversal and having a codimension-5 crossing of its fast Kramers-degenerate semi-quantum eigenvalues, our system is the dynamical equivalent of the spin-quadrupole model by Avron et al (1989 Commun. Math. Phys.
124 595–627), exhibiting non-Abelian geometric phases. The equivalence is uncovered through the equality of the spectral flow between quantum superbands and Chern numbers c
2 computed by Avron et al.