bluuebunny/crossref_metadata_2025_split huggingface dataset:
A System for Continuous Assurance and Certifications of Data Quality for Digital Twins
Authors: Hansen Ove H. , Jaiswal Vivek , Stang Jørgen 
Published: August 2024

Abstract
A digital twin is a digital representation of a physical asset and is critically dependent on data collection and transmission. The physical and digital parts need to communicate and exchange data with each other for the digital twin to perform its function and deliver value over time. Increasingly, the data utilized for digital twin solutions may be hosted in multiple locations such as third-party cloud services, in-house servers, other digital twins, or other sources. The different sources of data enable operations at scale and multiple new business opportunities. However, it also brings with it challenges related to data quality and cyber security. The capabilities of digital twins need interoperable solutions, which means that digital twins can connect, communicate, and exchange qualified data or services without requiring extra effort or adaptation. A formal certification of data products used for digital twins will improve trust and reduce risk.
Data values and quality are changing and need to be fit for use within acceptable risk. Bad data, lack of data and security breaches can and will jeopardize business critical operations and need to be governed by strategies, and management of change processes and tools. There is a need for a system for continuous assurance and certifications of data quality and cyber security.
The described system is currently under development for quality assurance and certification of data products for the maritime and the energy industry. The result could be a game-changer when it comes to trust and reliability for digital twins.
Examples and reference cases of the independent and automated digital quality assurance and certification system for digital twins will cover management of changes, cyber security, data quality, or automated compliance assessments and statements. The use cases present technical and practical solutions and the system to meet the continuous assurance and certification requirements as well as learnings from ongoing projects.
Theoretical Analysis on Mechanically Lined Pipe Fabrication
Authors: Wei Rongzhi , Vaz Murilo Augusto , Hu Xuefeng 
Published: August 2024

Abstract
Mechanically Lined Pipe (MLP) is a double-walled pipe comprising a carbon steel outer pipe internally coated with a thin layer of Corrosion Resistance Alloy (CRA). This CRA layer serves to safeguard the outer pipe against corrosive substances presented in the production fluid from offshore O&G fields, while the high strength low carbon steel outer pipe bears majority of external loads. The process of hydroforming expansion represents the predominant technique employed in affixing the liner into the carrier pipe. Precise and dependable theoretical models have been consistently sought for enhancing the fabrication efficiency and serving as a benchmark for subsequent failure analysis. The Tresca criterion has been adopted in stress-strain analysis of MLP due to its mathematical simplicity. Nevertheless, it is worth noting that the Tresca criterion is widely acknowledged for its conservative approach in predicting the yielding of metallic material. Consequently, the accuracy of employing the Tresca criterion in analyzing the fabrication of MLP is arguable. To further enhance accuracy, the infinitesimal strain theory and von Mises yield criterion are applied in conducting theoretical analysis for the MLP processing. The stress state within liner after being fully-plastified and loaded with external interfacial contact pressure is derived with radial displacement compatibility. And residual contact pressure is derived analytically through the circumferential strain compatibility method. The interfacial contact pressure, residual contact pressure and hydraulic expansion pressure working range of one set MLP liner and carrier pipe is predicted using the improved model with von Mises criterion.
On the Potential Impact of Climate Change on Design of Offshore Wind Turbines
Authors: Amlashi Hadi 
Published: August 2024

Abstract
A reliability-based approach for offshore wind turbine design is proposed to account for climate change of metocean conditions and uncertainty related to the estimates of future extreme weather and other metocean parameters. The impact of expected wave and wind climate change on OWT design is demonstrated for monopile-supported OWTs with site-specific metocean conditions. The presented examples show consequences of climate change for the fore-aft bending failure probability of bottom-fixed support structure. To maintain the safety level in the current IEC-61400 based-design, the safety factors should be increased by 30–35 % if the fore-aft total bending moment increases by 35%, due to climate change-related extreme weather. However, it should be noted that the ability to adopt climate change adaptation strategies may imply that the current practice of designing of OWTs may require less rigorous changes in the future. The impact of this adaptation and uncertainty associated with it should be accounted for.
Causal Convolution LengthNet Model for Slender Marine Structures
Authors: Machado Vinicius , Sagrilo Luis 
Published: August 2024

Abstract
Finite element modeling (FEM) is the standard way to evaluate structural responses based on the physics of the application. They are often used for time-domain analysis, simulating a set of stochastic loading cases on slender marine structures, and carrying out different types of nonlinearities. While the irregular wave approach offers a closer approximation to structural responses due to environmental loadings’ stochastic nature, it is more demanding computationally. To reduce simulation time while ensuring accuracy, this study introduces strategies to design artificial neural network (ANN) frameworks using deep learning algorithms. The LengthNet class type can predict responses at multiple structural nodes simultaneously, both temporally and spatially, cutting down training time, especially when dealing with a high number of nodes. This work introduces the LengthNet model based on causal convolutional neural networks, which outperforms the state-of-the-art LengthNet based on Recurrent Neural Networks and the NodeNet model. A significant improvement in the PAC (Percentage of Accurate Cases) metric was observed for the Lazy-Wave configuration. Different fatigue regions are processed at the same time, going from the upper regions down to the touchdown zone (TDZ), passing through local analysis and fatigue quantification via the S-N curve. Predicted damage values versus the ground truth ones are also presented.
Investigation of VIV Responses of Slender Structures Under Waves and Currents
Authors: Wu Jie , Yin Decao , Lie Halvor , Grytøyr Guttorm , Hogg Brendan Francis 
Published: August 2024

Abstract
The slender marine structures, such as marine risers and dynamic power cables, etc. are exposed to waves and currents. Vibrations due to periodic vortex shedding around the structure can lead to fast accumulation of fatigue damage and amplified drag loads. Vortex Induced Vibrations (VIV) often represent a safety risk and a major design consideration adding notable costs to all stages of the system development. It is known that the presence of waves may disrupt organized vortex shedding and affect structures’ dynamic responses and resulting drag loads. However, the present frequency domain VIV prediction tools can only consider constant current. The fatigue damages due to VIV and waves have to be calculated independently, and then combined afterwards. In addition, the influences on the drag loads are neglected. These have been some of the major uncertainties in the present design practice, which is more pronounced for shallow water applications, e.g., power cables to floating wind turbines. There are both lack of understanding of the wave-VIV interactions and reliable prediction tools.
In present study, a model test of a steel catenary riser (SCR) subjected to wave and VIV loads carried out at SINTEF Ocean were studied. Relevant test cases were selected and analysed to understand the influences of wave loads on VIV responses. Nonlinear time domain VIV simulation using VIVANA-TD were also carried out, which showed good agreement between prediction and model test results. Other relevant studies were also examined and parameters that may affect structure responses under wave and VIV loads were discussed.
Nylon Ropes for Mooring of Floating Offshore Wind Turbines: The NYMOOR Project
Authors: Fonseca Nuno , Føre Heidi Moe , Sørum Stian Høegh , Gaarder Rune , Leira Bernt Johan , Faria Rui Pedro , Kent Michael 
Published: August 2024

Abstract
Effective mooring of floating offshore wind turbines (FOWTs) is challenging, and conventional mooring designs often require line components with quite large diameters. This is mainly a consequence of large mean environmental loads from wind, namely the wind thrust force, combined with a relatively stiff mooring system. Nylon ropes have the potential to reduce stresses in mooring lines due to their flexible and elastic behaviour. However, there is very little experience with use of nylon for permanent mooring of floating structures. Of particular concern is the long-term endurance and behaviour of nylon ropes in the ocean environment. Furthermore, new material models are required to simulate mechanical properties of nylon ropes, and design analysis tools must be further developed to accommodate these new models.
The paper starts by presenting state-of-the-art in the topic of nylon ropes with focus on mooring applications. It reviews and documents advantages of nylon ropes in mooring of FOWTs with results from two case studies, and identifies knowledge gaps. Then it describes the NYMOOR research project, which addresses some of the knowledge and technological gaps. We start with the project objectives. The assumed hypotheses are formulated based on the best knowledge in the topic. Then the project methodology and the research activities are described in detail.
Study on the Collision Probability of Tandem Top-Tensioned Risers Based on the Extremes Statistical Methodology
Authors: Gu Honglu , Guo Haiyan , Meng Fanshun , Li Xiaomin , Li Fuheng 
Published: August 2024

Abstract
This paper aims to develop an integrated model for predicting the probability of riser collisions. This model can fully utilize the limited time series samples and dramatically reduce the computational time consumption required to accumulate enough data samples. First, a global mechanical model for the dual-riser system, which considers the current, random wave, top motion, and hydrodynamic interference effects, is constructed based on the vector form intrinsic finite element. Then, an analytical geometry-based procedure is coded, and a three-stage sieving strategy is proposed to efficiently obtain a random time series sample of the minimum distance, Cmin (t). The distribution parameters of this sample for various extreme value distributions are determined by the maximum likelihood estimation. The χ2 test, histograms, and quantile plots are used together to further assess the fitting quality of each theoretical model to the sample, and determine the optimal probability distribution form. Based on this optimal extreme value distribution model, the crossing rate of the sample is extrapolated to the failure threshold to predict the collision probability. Moreover, the probability prediction results are verified by Monte Carlo simulation and compared with the Gumbel probability paper method.
A Neural Operator for the Estimation of Wave Heights From Wind Data
Authors: Mathias Marlon S. , S. Thiersch Carlos H. , R. Patitucci Luca , R. de Barros Marcel , M. Moreno Felipe , Jordão Artur , Dottori Marcelo , R. Costa Anna H. , Gomi Edson S. , Tannuri Eduardo A. 
Published: August 2024

Abstract
This paper presents a Neural Operator (NOp) for estimating wave height from wind data. The NOp is a machine learning model to approximate functions from one function space to another. It is trained to map wind data to wave height. Each function is represented as a graph, with vertices corresponding to physical locations and edges carrying geographical distribution information. The model uses a convolutional kernel, allowing nodes to exchange information based on relative positions. After several convolutions, the latent values are decoded into target variables. The model is agnostic to the absolute position of each node, simplifying training and enabling application to various domains. Although a precise wave height reconstruction is impossible, as it depends on multiple other variables and on past data, we demonstrate that such a model is able to approximate previously unavailable variables from available data, including the capability of inferring it in grids and resolutions different than those used during training.
Evaluating the Impact of Seated Pilates on Functional Outcomes Among Those With Mild, Moderate, and Severe Multiple Sclerosis Impairment: A Pilot Feasibility Trial
Authors: Adamson Brynn , Lindsay Keston G. , Almasri Layla , Koppele Duffy Meghann , Kirkpatrick Stacy , Hernandez Manuel E. 
Published: August 2024

This pilot study assessed the feasibility and functional benefits of a twice-weekly, 12-week, virtual, seated, group-based Pilates program in persons with mild to severe multiple sclerosis (MS). Participants were randomized into either a Pilates-only group or a Pilates group, which also incorporated hip and shoulder-cuff activation exercises. Process, management, and scientific-feasibility metrics were analyzed descriptively. Functional outcomes, physical activity, and MS-related outcomes (impact, fatigue, and quality of life) were measured pre- and postintervention and analyzed using mixed-effects models, analysis of variance, and cluster analysis. Twenty-two participants completed baseline testing. Sixteen completed the intervention and postintervention testing. Collapsed across groups, analyses demonstrated improvements in the Timed 25-Foot Walk (36%), Timed Up-and-Go (13%), and the Berg Balance Scale (10%, statistically significant). Neither between-groups differences nor physical activity or MS outcome changes were significant. Participants reported high satisfaction. Findings suggest that virtual, seated Pilates is feasible and may confer balance benefits to individuals with MS.
Response of
Staphylococcus aureus
physiology and Agr quorum sensing to low-shear modeled microgravity
Authors: Hauserman Matthew R. , Sullivan Leia E. , James Kimberly L. , Ferraro Mariola J. , Rice Kelly C. 
Published: August 2024

ABSTRACT

Staphylococcus aureus
is commonly isolated from astronauts returning from spaceflight. Previous analysis of omics data from
S. aureus
low Earth orbit cultures indicated significantly increased expression of the Agr quorum sensing system and its downstream targets in spaceflight samples compared to ground controls. In this current study, the rotary cell culture system (RCCS) was used to investigate the effect of low-shear modeled microgravity (LSMMG) on
S. aureus
physiology and Agr activity. When cultured in the same growth medium and temperature as the previous spaceflight experiment,
S. aureus
LSMMG cultures exhibited decreased
agr
expression and altered growth compared to normal gravity control cultures, which are typically oriented with oxygenation membrane on the bottom of the high aspect rotating vessel (HARV). When
S. aureus
was grown in an inverted gravity control orientation (oxygenation membrane on top of the HARV), reduced Agr activity was observed relative to both traditional control and LSMMG cultures, signifying that oxygen availability may affect the observed differences in Agr activity. Metabolite assays revealed increased lactate and decreased acetate excretion in both LSMMG and inverted control cultures. Secretomics analysis of LSMMG, control, and inverted control HARV culture supernatants corroborated these results, with inverted and LSMMG cultures exhibiting a decreased abundance of Agr-regulated virulence factors and an increased abundance of proteins expressed in low-oxygen conditions. Collectively, these studies suggest that the orientation of the HARV oxygenation membrane can affect
S. aureus
physiology and Agr quorum sensing in the RCCS, a variable that should be considered when interpreting data using this ground-based microgravity model.

IMPORTANCE

S. aureus
is commonly isolated from astronauts returning from spaceflight and from surfaces within human-inhabited closed environments such as spacecraft. Astronaut health and immune function are significantly altered in spaceflight. Therefore, elucidating the effects of microgravity on
S. aureus
physiology is critical for assessing its pathogenic potential during long-term human space habitation. These results also highlight the necessity of eliminating potential confounding factors when comparing simulated microgravity model data with actual spaceflight experiments.
SARS-CoV-2 papain-like protease inhibits ISGylation of the viral nucleocapsid protein to evade host anti-viral immunity
Authors: Rhamadianti Aulia Fitri , Abe Takayuki , Tanaka Tomohisa , Ono Chikako , Katayama Hisashi , Makino Yoshiteru , Deng Lin , Matsui Chieko , Moriishi Kohji , Shima Fumi , Matsuura Yoshiharu , Shoji Ikuo 
Published: August 2024

ABSTRACT

A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes mild-to-severe respiratory symptoms, including acute respiratory distress. Despite remarkable efforts to investigate the virological and pathological impacts of SARS-CoV-2, many of the characteristics of SARS-CoV-2 infection still remain unknown. The interferon-inducible ubiquitin-like protein ISG15 is covalently conjugated to several viral proteins to suppress their functions. It was reported that SARS-CoV-2 utilizes its papain-like protease (PLpro) to impede ISG15 conjugation, ISGylation. However, the role of ISGylation in SARS-CoV-2 infection remains unclear. We aimed to elucidate the role of ISGylation in SARS-CoV-2 replication. We observed that the SARS-CoV-2 nucleocapsid protein is a target protein for the HERC5 E3 ligase-mediated ISGylation in cultured cells. Site-directed mutagenesis reveals that the residue K374 within the C-terminal spacer B-N3 (SB/N3) domain is required for nucleocapsid-ISGylation, alongside conserved lysine residue in MERS-CoV (K372) and SARS-CoV (K375). We also observed that the nucleocapsid-ISGylation results in the disruption of nucleocapsid oligomerization, thereby inhibiting viral replication. Knockdown of ISG15 mRNA enhanced SARS-CoV-2 replication in the SARS-CoV-2 reporter replicon cells, while exogenous expression of ISGylation components partially hampered SARS-CoV-2 replication. Taken together, these results suggest that SARS-CoV-2 PLpro inhibits ISGylation of the nucleocapsid protein to promote viral replication by evading ISGylation-mediated disruption of the nucleocapsid oligomerization.

IMPORTANCE
ISG15 is an interferon-inducible ubiquitin-like protein that is covalently conjugated to the viral protein via specific Lys residues and suppresses viral functions and viral propagation in many viruses. However, the role of ISGylation in SARS-CoV-2 infection remains largely unclear. Here, we demonstrated that the SARS-CoV-2 nucleocapsid protein is a target protein for the HERC5 E3 ligase-mediated ISGylation. We also found that the residue K374 within the C-terminal spacer B-N3 (SB/N3) domain is required for nucleocapsid-ISGylation. We obtained evidence suggesting that nucleocapsid-ISGylation results in the disruption of nucleocapsid-oligomerization, thereby suppressing SARS-CoV-2 replication. We discovered that SARS-CoV-2 papain-like protease inhibits ISG15 conjugation of nucleocapsid protein via its de-conjugating enzyme activity. The present study may contribute to gaining new insight into the roles of ISGylation-mediated anti-viral function in SARS-CoV-2 infection and may lead to the development of more potent and selective inhibitors targeted to SARS-CoV-2 nucleocapsid protein.
High-throughput genetics enables identification of nutrient utilization and accessory energy metabolism genes in a model methanogen
Authors: Day Leslie A. , Carlson Hans K. , Fonseca Dallas R. , Arkin Adam P. , Price Morgan N. , Deutschbauer Adam M. , Costa Kyle C. 
Published: August 2024

ABSTRACT

Archaea are widespread in the environment and play fundamental roles in diverse ecosystems; however, characterization of their unique biology requires advanced tools. This is particularly challenging when characterizing gene function. Here, we generate randomly barcoded transposon libraries in the model methanogenic archaeon
Methanococcus maripaludis
and use high-throughput growth methods to conduct fitness assays (RB-TnSeq) across over 100 unique growth conditions. Using our approach, we identified new genes involved in nutrient utilization and response to oxidative stress. We identified novel genes for the usage of diverse nitrogen sources in
M. maripaludis
including a putative regulator of alanine deamination and molybdate transporters important for nitrogen fixation. Furthermore, leveraging the fitness data, we inferred that
M. maripaludi
s can utilize additional nitrogen sources including ʟ-glutamine, ᴅ-glucuronamide, and adenosine. Under autotrophic growth conditions, we identified a gene encoding a domain of unknown function (DUF166) that is important for fitness and hypothesize that it has an accessory role in carbon dioxide assimilation. Finally, comparing fitness costs of oxygen versus sulfite stress, we identified a previously uncharacterized class of dissimilatory sulfite reductase-like proteins (Dsr-LP; group IIId) that is important during growth in the presence of sulfite. When overexpressed, Dsr-LP conferred sulfite resistance and enabled use of sulfite as the sole sulfur source. The high-throughput approach employed here allowed for generation of a large-scale data set that can be used as a resource to further understand gene function and metabolism in the archaeal domain.

IMPORTANCE

Archaea are widespread in the environment, yet basic aspects of their biology remain underexplored. To address this, we apply randomly barcoded transposon libraries (RB-TnSeq) to the model archaeon
Methanococcus maripaludis
. RB-TnSeq coupled with high-throughput growth assays across over 100 unique conditions identified roles for previously uncharacterized genes, including several encoding proteins with domains of unknown function (DUFs). We also expand on our understanding of carbon and nitrogen metabolism and characterize a group IIId dissimilatory sulfite reductase-like protein as a functional sulfite reductase. This data set encompasses a wide range of additional conditions including stress, nitrogen fixation, amino acid supplementation, and autotrophy, thus providing an extensive data set for the archaeal community to mine for characterizing additional genes of unknown function.
The complete genomic sequencing of a
Klebsiella pneumoniae
isolate derived from the blood of a patient suffering from severe neurological problems in Zhengzhou, China
Authors: Yang Huishuang , Zhang Jun , Salman Sayyed , Zhu Weidong 
Published: August 2024

ABSTRACT

This study presents the comprehensive analysis of the genomic sequence of
Klebsiella pneumoniae
strain FAHZZU7042hy, having a 5,690,191 bp chromosome size. This strain was obtained from a blood sample of a patient suffering from severe neurological problems in Zhengzhou, China, 2023.