bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effector PHYL1JWB from Candidatus Phytoplasma ziziphi induces abnormal floral development by destabilising flower development proteins
Authors: Xue Chaoling , Zhang Liman , Li Hongtai , Liu Zhiguo , Zhang Yao , Liu Mengjun , Zhao Jin 
Published: August 2024

AbstractPhytoplasmas can induce complex and substantial phenotypic changes in their hosts in ways that favour their colonisation, but the mechanisms underlying these changes remain largely unknown. Jujube witches' broom (JWB) disease is a typical phytoplasma disease causing great economic loss in Chinese jujube (Ziziphus jujuba Mill.). Here, we reported an effector, PHYL1JWB from Candidatus Phytoplasma ziziphi, which implicated in inducing abnormal floral organogenesis. Utilising a combination of in vivo and in vitro methods, we investigated the influence of PHYL1JWB on the proteins associated with floral development. Our findings reveal that PHYL1JWB facilitates the proteasome‐mediated degradation of essential flower morphogenetic regulators, including AP1, SEP1, SEP2, SEP3, SEP4, CAL, and AGL6, through a distinctive pathway that is dependent on the activity of the 26S proteasome, thus obviating the requirement for lysine ubiquitination of the substrates. Further, the Y2H analysis showed that the leucine at position 75th in second α helix of PHYL1JWB is fundamental for the interactions of PHYL1JWB with AP1 and SEP1‐4 in jujube and Arabidopsis. Our research carry profound implications for elucidating the contribution of PHYL1JWB to the aberrant floral development in diseased jujube, and help to establish a robust theoretical underpinning for the prophylaxis and therapy of JWB disease.
Causal relationships between dietary antioxidant vitamin intake and atopic dermatitis: A two‐sample Mendelian randomization study
Authors: Wang Siqing , Dan Wenchao , Wang Zixuan , Sun Yujie , Zhang Guangzhong 
Published: August 2024

AbstractObjectiveOxidative stress is strongly associated with atopic dermatitis (AD), and increased antioxidant intake could potentially reduce the risk of or alleviate its symptoms. However, the argument is disputed. Therefore, we conducted a Mendelian randomization (MR) analysis to explore the causal relationship between dietary antioxidant vitamin intake and AD.MethodsWe applied MR analysis to examine the causative association between dietary antioxidant vitamin intake (vitamin C, vitamin E, carotene, and retinol) and AD. The genome‐wide association study (GWAS) summary data for antioxidant vitamins intake and AD were obtained from the IEU OpenGWAS database and the UK biobank. Our study consisted of two major parts, MR analysis to detect the causal relationship between exposure and outcome, and sensitivity analysis as supplemental evidence to verify the robustness of the results.ResultThe results revealed a suggestive causal relationship between vitamin E intake and AD (p = 0.038, OR 95% CI = 0.745–0.992). However, there was no causal relationship between the other three vitamins (vitamin C, carotene, and retinol) and AD (p = 0.507, OR 95% CI = 0.826–1.099) (p = 0.890, OR 95% CI = 0.864–1.184) (p = 0.492, OR 95% CI = 0.893–1.264). None of the single nucleotide polymorphisms (SNPs) were detected as heterogeneous and pleiotropy in the sensitivity analysis (p > 0.05).ConclusionThe analysis suggested that dietary intake of vitamin E may potentially lower the risk of AD. Conversely, intake of vitamin C, retinol, and carotene is not causally related to AD. Although vitamin E intake could be protective against AD, intake of dietary antioxidant vitamins to prevent or treat AD is not necessary.
Enhance Road Detection Data Processing of LiDAR Point Clouds to Specifically Identify Unmarked Gravel Rural Roads
Authors: Huston Rhett G. , Wilhelm Jay P. 
Published: August 2024

Abstract
Gravel roads lack standardized features such as curbs or painted lines, presenting detection challenges to autonomous vehicles. Global positioning service (GPS) and high resolution maps may not be reliable for navigation of gravel roads, as some roads may only be width of the vehicle and GPS may not be accurate enough. Normal distribution transform (NDT) LiDAR scan matching may be insufficient for navigating on gravel roads as there may not be enough geometrically distinct features for reliable scan matching. This paper examined a method of classifying scanning LiDAR spatial and remission data features for explicit detection of unmarked gravel road surfaces. Exploration of terrain classification using high resolution scanning LiDAR data of specific road surfaces may allow for predicting gravel road boundary locations potentially enabling confident autonomous operations on gravel roads. The principal outcome of this work was a method for gravel road terrain detection using LiDAR data for the purpose of predicting potential road boundary locations. Random decision forests were trained using scanning LiDAR data terrain classification to detect unmarked gravel and asphalt surfaces. It was found that a true-positive accuracy for gravel and asphalt surfaces was 75% and 87%, respectively, at an estimated rate of 13 ms per 360 deg scan. Overlapping results between manually projected and actual road surface areas resulted in 93% intersecting gravel road detection accuracy. Automated post-process examination of classification results yielded an true-positive gravel road detection rate of 72%.
Experimental Study on the Effects of Aquaculture Net Cages on the Motion Responses of a Spar-Type Floating Structure
Authors: Bai Shenyi , Dong Shuchuang , Li Qiao , Zhou Jinxin , Kitazawa Daisuke 
Published: August 2024

Abstract
An innovative concept for a spar-type floating wind turbine that incorporates aquaculture cages not only meets the Sustainable Development Goals (SDGs) but also optimizes the use of offshore ocean space. The integration of floating offshore wind turbines with aquaculture has the potential to bring economic benefits to both industries. In this feasibility study, a 1/56 scale model of a 2MW Spar floating wind turbine is used and the target cage is silver salmon farming cage with dimensions of around 25 m in diameter and 9 m in depth. An experimental investigation was carried out in an experimental tank to examine the surge, heave and pitch dynamic responses of a spar-type floating offshore wind turbine with aquaculture cages. Under regular wave conditions, aquaculture cages of varying quantities and distances were positioned in front of the spar-type floating structure facing the wave direction, with accelerometers recording the spar-type floating structure’s surge, heave, and pitch motion.
The study revealed that cages have a predominantly shadowing influence on the spar’s motion responses, compared to scenarios without cages. This effect is more pronounced when cages are situated nearer to the spar. When wave period was less than 1.0 second, the presence of the cages exerted a more pronounced influence on the movement of the spar. However, when the ratio of incident wavelength to cage diameter is close to 4, the motion responses of the Spar were significantly amplified under the influence of the aquaculture cages. Also, the impact of cages on the spar’s motion is relatively minor, varying from less than 10% for wave periods in excess of 1.2 seconds. Furthermore, the insignificant impact of the number of cages on spar motion attenuation was found but different setting methods will affect the wave field near the cages.
The findings of this study possess significant practical and theoretical implications, as they furnish experimental evidence of the feasibility of integrating renewable energy enterprises with marine aquaculture ventures. In summary, the study determined that the deployment of net cages has an almost negligible impact on the oscillatory movements of spar-type floating platforms in most scenarios but reduces the motion amplitudes under specific wave periods. These discoveries provide crucial guidance for future offshore industry operations, indicating the necessity for further investigations to explore the interplays between floating structures and net cages under diverse conditions.
Numerical Study on the Dynamic Response of Mooring Systems for an Offshore Floating Photovoltaic Platform
Authors: Lian Yushun , Chen Quan , Shen Shutian , Zheng Jinhai , Chen WenXing , Yim Solomon C. 
Published: August 2024

Abstract
Offshore floating photovoltaic (OFPV) platforms have emerged as a new development trend. However, conventional floating photovoltaic platforms designed for inland water areas are not suitable for use directly in ocean environments. Hence, an OFPV platform incorporating three types of mooring systems is proposed. These mooring systems employ various combinations of mooring lines, including all chains, chain-polyester ropes-chain, and chain-nylon ropes-chain, respectively. Dynamic response analysis of the three mooring systems for the offshore floating photovoltaic platform is conducted. The results indicate that the mooring system with nylon ropes shows the lowest tension and the largest displacements of the OFPV platform. However, the mooring systems with all chains show the largest tension under the same environmental load. In addition, the dynamic response of mooring systems with one-line failure is investigated. Results show that the floating platform undergoes significant displacement motion once a mooring line fails. Furthermore, the tension distribution of the remaining mooring lines becomes uneven, potentially leading to overall mooring system failure. This numerical study provides valuable insights into the design of mooring systems incorporating fiber ropes for OFPV platforms.
Identification of Hydrodynamic Coefficients in Nonlinear Maneuvering Model for an ESSO 190000 dwt Tanker by Least-Squares Support Vector Regression With Linear System
Authors: Chua Ming Han , Tam Ivan , Dev Arun , Liu Bin 
Published: August 2024

Abstract
In this article, the least-squares support vector machine (LS-SVM) with linear system of equations is used to identify the hydrodynamic derivatives of a three degree-of-freedom (3-Dofs) maneuvering model for an ESSO 190000 dwt tanker. Instead of identifying the hydrodynamic derivative independently, the highly-correlated hydrodynamic derivatives are identified together by LS-SVM and subsequently distinguished in sets of linear system of equations. The issue of parameter drift is briefly discussed and diminished with the proposed approach. The training data are sampled from the simulated zigzag maneuver. The computational procedures and set up of the support vector machine are discussed in detail. A number of predicted maneuvers are compared with the reference maneuvers. Excellent accuracy and generality of the estimated maneuvering model are achieved based on the proposed system identification technique.
Equivalent Drag Approach for Wave Loads on Slender Structures
Authors: Xia Jinzhu 
Published: August 2024

Abstract
The Morison equation has been widely used to describe flow-induced loads on slender structures in waves and currents. However, as far as the load magnitudes and their probabilistic distributions in irregular seas are concerned, it is more effective to formulate a hydrodynamic load prediction model using an equivalent drag expression because this avoids the necessity to define the added mass and calculate the flow acceleration. Since the inertia effect contributes to the total load, the equivalent drag coefficient is constructed to account for this influence. One obvious advantage of this alternative approach is that the equivalent drag coefficient can be calibrated against the results of total hydrodynamic load measurement or CFD calculations without having to measure or quantify the added mass coefficient and the inertia contribution.
In this paper, the equivalent drag approach is introduced in the regular wave condition as a general method for calculating the amplitude of the total wave loading on any slender structure cross-section. In an irregular sea state, the most probable maximum (MPM) value of the wave load amplitude is expressed in terms of the MPM value of the relative flow velocity and the equivalent drag coefficient which is dependent on a newly defined period number χ. The short-term probability distribution of the wave load magnitudes is represented by a Weibull distribution as a function of the equivalent drag coefficient. The long-term magnitude distribution can be developed by summing the short-term distribution of each sea state weighted by the probability of occurrence. As a special application, the equivalent drag coefficient is determined by fitting a modified hyperbolic relation to the model test results of the measured total wave load on the bilge keel of a floating production vessel (FPSO) in irregular sea states. An example of bilge keel fatigue assessment is presented based on the long-term wave load prediction, while load sensitivity is demonstrated.
Layout Optimization of Wave Energy Park Based on Multi-Objective Optimization Algorithm
Authors: Guo Xinhai , Liu Yao , Zhang Xinshu 
Published: August 2024

Abstract
In this paper, we apply a semi-analytical method and numerical simulation to study the hydrodynamic behavior of large arrays of point-absorber wave energy converters (WECs) and the multi-objective optimization of the arrays layout using particle swam optimization (PSO) algorithm based on surrogate models. To investigate wave interactions among multiple WECs among an array, a semi-analytical model is developed based on the linear potential flow theory and the matched eigen-function expansions method. The fluid domain is divided into two kinds of regions, interior regions underneath the cylinders and an exterior region surrounding all the cylinders. The matched eigen-function expansions method is used to solve the radiation potential problem in each domain, and the hydrodynamic coefficients and motion response of the cylinders in the array are evaluated. To validate the accuracy of our semi-analytical method, the hydrodynamic software WAMIT is adopted to simulate the wave energy park numerically. Results obtained by the semi-analytical method are compared with the numerical simulation results. The hydrodynamic characteristics and power absorption performance of the WECs within the wave energy park are discussed. The power performance of a wave energy park is studied as functions of global geometry, incident wave direction and separating distance between WECs, respectively. Finally, a multi-objective optimization algorithm based on a surrogate model is used to optimize the layout of wave energy array. A surrogate model is established based on radial basis function (RBF) to improve the computing efficiency. With the power output and power smoothing of wave energy array as two optimization objectives, the safety of cylinders and the occupied sea area of wave energy park as constraint conditions, the multi-objective particle swarm optimization (MOPSO) was used to search for the Pareto-optimal solution, and the feasible optimization scheme of wave energy array was given.
Design Challenges of Riser and Lifting System for Ultradeep Sea
Authors: Hou Jing , Yu Chenteh Alan , Cheng Yongming , Zhang Cheng 
Published: August 2024

Abstract
Recent exploration has generated a resurgence of interest in ultradeep sea mining. Deepsea mining industry has revealed many potential fields in the water depth of 4,000 to 6,000 meters. Different from risers used in the oil and gas industry, deepsea mining risers will be towed to cover fields with areas many times of a football field. The bottom end of the riser needs to be freely moved both vertically and horizontally. This paper investigates design challenges of a riser and lift system used for ultradeep sea mining. As application moves to ultra deepsea, design challenges of a Riser and Lifting System (RALS) increase in terms of riser design, analysis, installation, and global performance.
This paper first introduces the state of the art of a typical Riser and Lifting System (RALS) used for ultradeep sea mining. The RALS design issues cover riser wall thickness, tension limits, and high payload. The installation concerns come from hook capacity limit, riser Vortex-Induced Vibration (VIV) when the riser is disconnected, and riser bottom drift caused by vessel motion during installation. This paper further investigates the coupling between the risers and floating platform, riser VIV, and riser dynamic performance. Examples are given to illustrate design challenges of the RALS in ultradeep sea mining. This paper finally summarizes the design challenges of RALS for ultradeep sea mining. In addition, this paper also explores likely solutions to the design challenges.
Forecasting Mooring Tension of Semi-Submersible Oil Production and Storage Platform Using a Novel Transformer Neural Network Model
Authors: Chen Yang , Yuan Lihao 
Published: August 2024

Abstract
This study presents the Transformer framework, which is a top performer in the field of natural language time-series prediction, and suggests an enhanced Transformer neural network model to address the application needs of semi-submersible production platforms for very short-term prediction of mooring tension during operation. Compared with the traditional recurrent neural network, the Transformer neural network has faster computation speed, better generalization ability and scalability, and stronger ability to capture long-range dependencies. In this paper, the proposed Transformer model is used for mooring tension prediction of semi-submersible production platforms, and the proposed neural network model is trained and validated using the actual monitoring data of the first ultra-deepwater semi-submersible production, storage, and offloading platform in the South China Sea during operation. The results show that the proposed method can achieve almost the same prediction results as the current mainstream LSTM model, which has the value of engineering application and promotion.
Maximum Cumulative Fatigue Damage Assessment of Bottom-Fixed Wind Turbine Structures in the Design Phase by AK-MDAmax Approach
Authors: Ren Chao , Xing Yihan 
Published: August 2024

Abstract
Wind energy has become crucial in the worldwide transition towards more sustainable alternatives. Ensuring the reliability of wind turbines is contingent upon the design process. The process of designing structures for wind turbines is iterative and necessitates the examination of design load situations in consideration of fatigue and ultimate limit states. Over the last decade, considerable work has been devoted to determining the ultimate limit states. Yet, efficient methods for estimating fatigue damage in wind turbine structural design are still lacking. Thousands of simulations are often required to estimate the cumulative fatigue damage, and each simulation can be time-consuming. In recent publications, the AK-MDAmax machine-learning methodology has been introduced to estimate the maximum cumulative fatigue damage to wind towers in floating wind turbines. For estimating fatigue damage, the initial works published revealed the excellent efficiency and precision of the AK-MDAmax method. Nevertheless, these initial studies only examined the local locations of the wind turbine tower base of a specific floating wind turbine at a specific location. The applicability of the AK-MDAmax method to bottom-fixed wind turbine systems and the influence of various offshore locations remains uncertain. To estimate the maximum cumulative fatigue damage to a bottom-fixed wind turbine, we implemented the AK-MDAmax method in this study. This article utilises an IEA 15MW wind turbine supported by monopiles at four distinct points inside the turbine structure. To consider the influence of offshore locations, this analysis also considers two distinct offshore metocean conditions. The findings indicate that the AK-MDAmax method can accurately predict the maximum cumulative fatigue damage to wind turbine structures by considering various components. With an error of less than 4 percent, the efficiency may be raised by about 55 times compared to the simulation references, highlighting the benefits of using the AK-MDAmax method for offshore wind turbine design.
Evaluation of Frequency Effects on Corrosion-Fatigue Behaviour of Offshore Steel Pipelines
Authors: Mehmanparast Ali 
Published: August 2024

Abstract
During the operational lifespan, offshore steel pipelines are subject to cyclic loading condition introducing fatigue damage into the material in conjunction with corrosion damage as a result of operation in the marine environment. An important issue that needs to be understood in asset integrity management of offshore pipelines is the cyclic loading frequency effects on corrosion-fatigue cracking behaviour of the material. In this study, a newly proposed approach for corrosion-fatigue analysis of offshore steel structures has been employed to examine its suitability for evaluation of the cracking behaviour in offshore steel pipelines. For this purpose, the experimental corrosion-fatigue data on API 5L X56 steel at different frequencies were collated from the literature and re-analysed using a newly proposed time-dependent fracture mechanics parameter. Moreover, a predictive model was developed to estimate the corrosion-fatigue cracking trends at various frequencies using the high frequency test data in air. The results from this study show that while the frequency effects on corrosion-fatigue cracking behaviour of steels cannot be described using the traditional data analysis method, the new time-dependent approach facilitates accurate characterisation of corrosion-fatigue data at a wide range of frequencies. Also, knowing that corrosion-fatigue testing at low frequencies is time-consuming and costly, it has been shown in this study that the long-term cracking behaviour of the material can be predicted using much faster tests at higher frequencies in air. This study showcases the potential of the newly proposed corrosion-fatigue life prediction approach using a time-dependent fracture mechanics parameter for structural integrity assessment of steel pipelines. Last but not least, the results from this study highlight the need for employment of innovative approaches for long-term structural integrity assessment of offshore steel structures and pipelines.
A Progressive Screening Approach for Mooring Configuration Selection: A Case Study of the Arven Offshore Wind Farm
Authors: Glasspool Jonathan , Tao Longbin , Venugopal Vengatesan , Pillai Ajit C. 
Published: August 2024

Abstract
The mooring system of a floating offshore wind turbine (FOWT) impacts both the capital and operational expenses. The future success of floating offshore wind is, therefore, dependent on finding optimum mooring system designs from the wide field of possibilities.
This paper introduces a methodology to identify appropriate mooring systems with the lowest cost using Arven Offshore Wind Farm as a case study. The methodology employs a systematic screening pipeline, utilizing short-duration time domain simulations in OrcaFlex to assess mooring line systems’ suitability based on DNV-ST-0437 and DNV-ST-0119 compliant load cases. Through progressively more detailed simulations, the pipeline efficiently narrows down the field of mooring configurations, assessing design parameters in one tenth of the time of a full enumeration.
This approach allows for the identification of a lowest-cost mooring system, highlighting the design trade-offs between cost and key design parameters. For the Arven case study, the methodology has identified a semi-taut three-line nylon system with 225 m anchor radius, 1200 kN pretension and a 192 mm line diameter as being the most efficient system. The outlined methodology provides a broadly applicable and efficient means to identify optimum mooring systems for diverse development sites worldwide.