bluuebunny/crossref_metadata_2025_split huggingface dataset:
Molecular Identification of Endophytic Fungi from Javanese Ginseng (Talinum paniculatum Gaertn.) and their Potential against Phytopathogens
Authors: Tinta Manik Visi , Nurcahya Intan , Setiaramdani Susi , Yulianto Yanto , Undang  
Published: December 2023

Abstract
Endophytes from medicinal plants have been demonstrated to produce bioactive chemicals with antibacterial capabilities. Previous research found many endophytes in Javanese ginseng roots. Identifying and comprehending the benefits of endophyte microorganisms is critical for boosting plant growth and defense. The aim of this study was to identify endophytic microbes from Javanese ginseng with antifungal activity. In this present study, two isolates the GJ-9 and FN-1, were analyzed using NL1/NL4 and ITS1/4 primers. The amplification and sequencing of the ITS and the D1-D2 LSU rRNA gene were performed. The D1-D2 LSU rRNA sequence analysis results showed that GJ-9 has similarities with Candida Spencermartinsiae with 99.82% percentage identity, while FN-1 has been identified as Aspergillus flavus according to the ITS sequence analysis result with 99.83% percentage identity. Antagonistic assays showed both isolates displayed considerable antagonistic ability against Rhizopus stolonifera, Pythium sp., Botrytis sp., and Fusarium sp, with overall inhibition rate were over 50%. The Aspergillus flavus showed the better ability to inhibit the growth of Phytium sp. (74.90 %) and Rhizopus stolonifera (60 %), while the Candida Spencermartinsiae is better for controlling Botrytis sp. (55.68%) and Fusarium sp. (60.39 %). The result suggests the endophyte from Javanese ginseng can be used as an agent for controlling various plant diseases; furthermore, it could lead to a reduction of agrochemical inputs.
The elusive bio-stimulatory function of Cladophialophora chaetospira SK51 to alleviate Fusarium wilt of strawberry
Authors: Harsonowati W , Triasih U. , Narisawa K 
Published: December 2023

Abstract
The highly virulent Fusarium oxysporum formae speciales (f.sp.) fragaria causes Fusarium wilt and significant losses in the strawberry agroindustry. The effective control strategies for this phytopathogen have yet to be developed. We aimed to evaluate the bioefficacy of root-colonizer dark septate endophytic fungi (DSEs) in controlling Fusarium wilt in simultaneous with biostimulation activities. Three out of nineteen tested isolates were selected because of their superior bioefficacy in regulating disease suppression and growth promotion. Notably, the highest level of disease suppression was marked at 90.48%, followed by 85.71% and 61.90% with the inoculation of these three selected isolates i.e., SK51, SK47, and SK48, respectively. The fungal isolates were identified based on partial SSU, LSU, and ITS as DSE fungus Cladophialophora chaetospira strain SK51, Exophiala sp. strain SK47, and E. pisciphila strain SK48. Our findings showed that C. chaetospira SK51 exhibited significant potential in promoting plant growth and suppressing diseases. It significantly enhanced various plant growth factors, such as the total plant biomass, the content of chlorophyll (SPAD), the formation of flower buds, and the development of fruits compared to both non-inoculated control and the other two DSE-inoculated plants. Our study provides new findings and perspectives on the use of the DSE, particularly C. chaetospira SK51 as a bioprotectant and biostimulant for enhancing the development, flower bud formation, and fruit development in strawberry plants.
Active damage mitigation of the blade leading edge erosion for a wind turbine during rainfall events
Authors: Ripoll Á Ú , Jiang Z , Verma A , Zhou J 
Published: December 2023

Abstract
Leading edge erosion (LEE) of wind turbine blades is a major concern for the wind turbine industry. LEE leads to increased blade surface roughness and incurs significant repair and maintenance costs. To address this issue, the present paper proposes an active LEE mitigation method by operating wind turbines in an erosion-safe mode with reduced rotor speed during precipitation. The proposed method involves first numerically modelling the NREL 5-MW reference wind turbine in openFAST. Then, during a regular operation in the presence of rainfall, the erosion-safe mode is designed, implemented and initiated with a modified blade pitch controller in Matlab-Simulink. To evaluate the effectiveness of this mode, the long-term rainfall distribution of the De Kooy site in the Netherlands is examined. The analysis considers a comparison of power output, erosion lifetime, and levelized cost of energy (LCOE) with and without the proposed safe modes. The study shows that the erosion-safe mode can significantly extend the erosion lifetime at the cost of reduced power generation. The controller settings affect the wind turbine performance, and a reduced rotor speed of 11 revolutions per minute is recommended considering the LCOE (308.64€/MWh). While the proposed mitigation method shows promise, it requires further refinement for real-life implementation in wind turbines.
Life cycle cost analysis of a floating wind farm in the Norwegian Sea
Authors: Bjørni F A , Lien S , Midtgarden T Aa , Santos L C , Jiang Z 
Published: December 2023

Abstract
The offshore wind energy industry has witnessed rapid growth in the past decade. Still, there is a lack of commercial floating wind projects due to the relatively high development costs and other factors. To facilitate the holistic evaluation of floating wind farms in Norway, this article investigates the levelized cost of energy of a floating offshore wind farm and its economic feasibility. The Troll field west of Bergen, Norway, is assumed to be the target offshore site, and a farm size of 50 wind turbines with a lifespan of 25 years are considered. Each floating wind turbine has a 15-megawatt turbine mounted on a semi-submersible floater. Based on detailed analysis, the levelized cost of energy of the wind farm is estimated to be approximately 100.7 $/MWh. The capital expenditure is the most prominent cost and constitutes 63.1% of the total cost, and the operational expenditure constitutes the remaining 36.9%. Further, sensitivity analyses show the influence of the lifespan, capacity factor, and project discount rate on the levelized cost of energy. The present study contributes to techno-economic evaluation of floating wind projects at an early phase.
Two-body dynamic simulations of a combined semi-submersible floating offshore wind turbine and torus wave energy converter
Authors: Lee C F , De Santis Tavares V , Ong M C 
Published: December 2023

Abstract
Dynamic responses of a combined wind and wave energy system which consist of a 5MW semi-submersible floating offshore wind turbine (FOWT) and a torus-shaped wave energy converter (WEC) are investigated. In the investigated configuration, the torus WEC is constrained to move only in the heave direction with respect to the FOWT. This results in a two-body dynamic system that allows for the extraction of wave energy through the relative heave motion. A Modelica-based multi-body system (MBS) code is used to perform fully coupled dynamic analyses of the combined system. The wind turbine loads are calculated using the state-of-the-art Blade Element Momentum (BEM) method, while the wave power take-off (PTO) system is modelled as a linear spring and a viscous damper. A case study is presented where the mass of the torus is varied to investigate the impact on the two-body dynamics of the combined system. The system performance is assessed in terms of the maximum wave power absorption and the quality of wind power production.
Calculation and prediction of suspended span caused by erosion of deep water submarine pipelines
Authors: Jia X , Ni K , Li Y , Jia L 
Published: December 2023

Abstract
Submarine pipelines can be divided into three types based on their laying status: pipelines laid flat on the seabed, pipelines without buried, and pipelines buried in shallow trenches. In addition, there is also a suspended span state caused by waves and currents erosion. The four laying states of submarine pipelines indicate that the seabed, as the foundation supporting the pipeline, must provide sufficient support to ensure the stability of the pipeline. This article studies the erosion span data of existing pipelines, evaluates and predicts the pipeline span state through theoretical calculation and analysis, and then uses numerical simulation calculation methods to predict the pipeline span depth, and compares and verifies it with measured data.
Dynamic response of a single point mooring submersible fish cages in waves and current
Authors: Wen X , Cheng H , Ong M C 
Published: December 2023

Abstract
Submersible fish cages are designed for installing in the open sea sites that are subjected to violent sea conditions to reduce the hydrodynamic forces acting on the fish cages. To assess the dynamic responses of a single point mooring submersible fish cage under the rough sea conditions, a numerical model including hydrodynamic and structural methods is proposed. The waves and current are modelled using the airy wave theory. For the floating collars and sinker tube, the Morison model is adopted to calculate the hydrodynamic force and the modal superposition method is proposed to calculate the structural responses. For the aquaculture net, the screen model is adopted to calculate the hydrodynamic force and the extended position-based dynamics (XPBD) method is proposed to obtain the structural deformations. The hydrodynamic dynamic forces and the deformations of the fish cages are compared between the fish cages on water surface and in deep water. Results show that when the fish cage is submerged 20m from the water surface, the average horizontal force is reduced by 30% and the variation of the horizontal force is reduced by 81%. Significant reductions in the deformation of the floating collars are observed. Therefore, using submersible fish cage can help reduce physical stress and avoid structural damage for the fish cage system. In addition, the coupling of XPBD and MS can provide a quick solution for the structural modelling of the fish farm system, which can be utilized at the initial stage of fish farm design.
Dynamic response of a floating dock under corrosion-induced accidents
Authors: Zahi T , Wen X , Ong M C 
Published: December 2023

Abstract
Dynamic responses of a floating dock under corrosion-induced accidents are studied using a numerical method. The numerical model is proposed to calculate the dynamic responses of the floating dock during operations. It includes a six-degree-of-freedom (6-DOF) model, a hydrostatic force model, a hydrodynamic force model, and a hydraulic model. The effects of the corrosion-induced holes on the stability of the floating dock are investigated and the results show that the maximum pitch and roll angles are 0.18° and 0.69° respectively when there is one hole located at one tank. The maximum pitch and roll angles become 0.42° and 2.04° respectively when there are two holes located at different tanks. The results indicate that situations involving more than one corroded hole result in large roll and pitch angles, which ultimately increase the risk of the vessel capsizing. This analysis not only emphasizes potential hazards but also presents an opportunity for the maritime sector to enhance safety, operational efficiency, and environmental responsibility.
Combining machine learning methods and data augmentation for misaligned journal bearings design
Authors: Arvanitis K , Nikolakopoulos P G 
Published: December 2023

Abstract
Shaft misalignment is one of the most common defects observed in rotating systems and has a substantial effect on dynamic behaviour, stability, and lifetime. Aim of this study is the binary identification of misalignment using five Machine Learning techniques: Logistic Regression, K-Nearest Neighbours, Support Vector Machines, Decision Tree and Random Forest. Nevertheless, the limited quantity of provided data points coupled with the substantial imbalance between the aligned and misaligned cases necessitated the implementation of oversampling and data augmentation methods. The utilization of SMOTE-LOF for oversampling the minority class, alongside the adoption of a Conditional Tabular GAN for the generation of synthetic data points yielded substantial outcomes. The application of SMOTE with the Local Outlier Factor on the original dataset achieves the oversampling of the minority class by using additional synthetic data, while the LOF factor overcome the noise problem. After the SMOTE-LOF implementation, new synthetic samples of the minority class are added to the dataset, eliminating the imbalance, however the ‘cleaned’ dataset’s small number of samples could lead to poor performance of the Machine Learning techniques. Hence, using a Generative Adversarial Network to expand the dataset is requisite, and since the experimental data is tabular, utilizing a Conditional Tabular Generative Adversarial Network is ideal for this case of study. The results of the current study elucidate the dataset that, among the augmented datasets, exhibits the best quality score when contrasted with the original dataset. Furthermore, the dataset that performs the best on the Machine Learning algorithms is determined.
Reuse of decommissioned offshore steel components for new buildings: A case study
Authors: Valen L V , Siriwardane S C , Bjørheim F , Røland S 
Published: December 2023

Abstract
Reuse process of structural steel members, which are extracted from decommissioned offshore platform, for new apartment building is presented in this paper. An index is introduced to assess the technical feasibility of the reuse process of offshore steel components to steel buildings. The applicability and significance of the reuse process is demonstrated by a real case study. Steel columns of a new four-storey apartment building are replaced by selected members from recently decommissioned offshore platform in this case study and hence feasibility, cost benefits and environmental advantages are investigated. Utilization ratios of selected pre-used columns shows that those columns have more than sufficient capacities to withstand the loads. This indicates that considered decommissioned module of offshore topside is applicable for similar size of new buildings. The results indicate significant environmental benefits such as reduction of the CO2 emission, low global worming potentiality, and etc. The reusability index of the considered case study is 51.5%, which shows marginal feasibility of reuse, and this can be increased, if the reuse process is industrialized and streamlined by the offshore decommisioning companies. Three ways are proposed to industrialize and streamline the reuse process in the latter part of this paper.
Transitioning towards renewable energy and sustainable storage solutions at remote communities in the Arctic, Case study of Flatey, Iceland
Authors: Hjallar M R A , Víðisdóttir E D , Gudmestad O T 
Published: December 2023

Abstract
The need for transitioning towards renwable energy and sustainable storage solutions is particularly challenging for remote communities in the Arctic, located far away from the electricity grid. This paper explores the potential for use of renewable energy on the remote island of Flatey, Iceland, which currently relies on two diesel aggregates for power. The primary goal is to assess the feasibility of transitioning from fossil fuels to renewable energy sources, such as solar or wind power, to meet the island’s variable energy demand while reducing its environmental impact. With a year-around population of 5 and with a considerably increased energy consumption during vacation times, due to more population, Flatey’s annual energy consumption is ~ 209.000 kWh, peaking in July at ~ 25.000 kWh. This fluctuation requires an adaptable and resilient energy infrastructure. The paper examines the viability of Flatey as a self-sufficient renewable energy provider. The study considers the island’s energy requirements, consumption patterns, and geographical constraints, while also evaluating technical, economic, and social factors that may influence renewable energy adaption. This paper, thereafter, investigates the feasibility of achieving energy self-sufficiency on the small island of Flatey. Different energy storage options is considered, focusing on battery storage, underground solar power/energy storage, and hydrogen storage.
Assessment of awareness levels towards additive manufacturing best practices in transforming traditional manufacturing: A case study in Ethiopian context
Authors: Lemma T , Lemu H G , Gutema E M 
Published: December 2023

Abstract
The main objective of this study is to assess the awarness levels of acadamic staffs and industry experts towards the best practices of additive manufacturing (AM) in transforming traditional manufacturing (TM) in local context. The study used closed ended questionnaires with 1-5 liker scales to collect secondary data from the respondents. The collected data were analyzed using descriptive statistics (frequency and percentage) by using SPSS v20 software. The findings of this paper identified ten (10) AM best practice benefit factors (Resource consumption benefit factor, Waste management benefit factor, Pollution control benefit factor Material utilization benefit factors, Design optimization benefit factor, Manufacturing flexibility best practice factors, SC flexibility benefit factors, SC network improvement benefit factor, Cost reduction benefit factors, Ability of changing customer demand benefit factors) in transforming traditional manufacturing in local context. Among the eight AM best practices both academic staffs and industry experts have common awareness level on five factors. In addition, the findings of the study showed that 49% of academic staffs and 37% of industry experts have good awarness levels towards the identified AM best practices in transfornig traditional manufacturing. Based on the findings of this study conceptual framework was developed for future research work to quantitatively investigate the effects of AM best practices on traditional manufacturing performmance.
Additive manufacturing best practices and its impact on supply chain performance through structural equation modelling: A case study in Ethiopian footwear industry
Authors: Lemma T , Gutema E M , Lemu H G 
Published: December 2023

Abstract
The aim of this study is to analyze the effects of additive manufacturing (AM) best practices on supply chain (SC) performance. The study developed conceptual framework with four AM best practice as independent variables and five SC performance measuring factors as dependent variables. To test the developed model and hypothesis, data’s has been collected from 129 respondents from 29 footwear industries in Ethiopia. AMOS v.23 is used to test model fit with confirmatory factor analysis (CFA) (χ2/df, RMSEA, CFI, GFI, RMR, Tucker-Lewis index (TLI)). Reliability analysis was carried out to test the reliability and stability of the research questionnaires. Correlation analysis was performed to test the strength and association between dependent and independent variables. And to test the developed hypothesis structural equation modelling (SEM) or paths analysis was used. The findings of the CFA result indicated that data fit the model reasonably well. The finds of correlation analysis indicated that, AM best practices have positive, strong and significant relationship with cost, time and reliability related factors of SC performance. But it has very weak and insignificant relationship with customer related factors. In addition, the findings revelled that AM best practices have negative and insignificant relationship with supplier related factors. On the other hands, the findings of SEM confirmed that the identified four AM best practices positively and significantly improve SC performance. And this study concludes that manufacturing flexibility, material utilization, environmental control and product design optimization of AM plays a vital role in improving SC performance.
Hydrogen safety considerations: Mitigating risks and securing operations in enclosed spaces
Authors: Kleszcz S , Assadi M 
Published: December 2023

Abstract
The increased interest in hydrogen as a versatile and environmentally friendly energy carrier has led to its recognition as a potential solution for addressing environmental concerns and challenges associated with transitioning to alternative energy sources. However, working with hydrogen requires careful consideration of safety measures to ensure the safe handling, storage, and utilization of this highly flammable gas. This article focuses on the important safety considerations related to working with hydrogen in enclosed spaces and emphasizes the steps taken to minimize risks. Essential calculations were conducted to determine the concentration of hydrogen within a container during a leak. The findings revealed that, without proper ventilation and safety precautions, the concentration of hydrogen in the container can quickly reach explosive levels. To ensure safe operation, a secure system has been designed and described, which includes the implementation of various detection devices. Additionally, the article discusses the recommended course of action in the event of an explosion. In summary, this study offers a safety analysis of hydrogen leakage in a container. The suggested security system, incorporating detection devices and a safety valve, guarantees the safe functioning of the hydrogen supply system.
Development of a surrogate model of a trans-critical CO2 heat pump for use in operations optimization using an artificial neural network
Authors: Sazon T A S , Zhang Q , Nikpey H 
Published: December 2023

Abstract
Conventional physics-based models can demand substantial computational resources when employed for operational optimization. To allow faster system simulations that can be employed for operational optimization, a surrogate model of the CO2 heat pump has been developed using an artificial neural network (ANN). The ANN model takes in six (6) inputs: evaporator water-side mass flow, its temperature, gas cooler water-side mass flow, its temperature, set-point output temperature, and high-side heat pump pressure. The model’s outputs comprise the electrical energy needed to run the heat pump, the heat from the gas coolers, the temperature of the heat pump-heated fluid, and the outlet temperature of the heat pump’s evaporator. Data used for training, validating, and testing the ANN model were generated by running a calibrated Modelica model of the CO2 heat pump for various combinations of input parameters obtained from Latin hypercube sampling. The ANN model developed includes an input layer with 6 inputs, 2 hidden dense layers, each with 30 neurons, and an output layer for 4 outputs (6-30-30-3). The ReLU activation function was implemented on each hidden layer and no regularizations were imposed. The Adam optimizer was used with a learning rate of 0.001 specified. Early stopping (patience = 2000) was implemented to ensure that the training data was not overfitted. A maximum of 30000 epochs was specified. The resulting Mean Square Error (MSE) obtained for the training, validation, and testing data sets were 1.38x10−5, 2.05x10−5, and 3.65x10−5, respectively. When tested against one-week operational runs generated by Modelica, the Root Mean Square Errors (RMSEs) for coefficient of performance (COP)s for spring, summer, autumn, and winter operations obtained were 0.232, 0.346, 0.089 and 0.076, respectively. The resulting surrogate ANN model can be integrated into the system model as a functional mock-up unit within Modelica to facilitate faster simulations for operational optimization.