bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transfer Deep Learning Network for Rolling Bearing Fault Diagnosis of Wind Turbines
Authors: Cheng Zhiwei , Li Xuejiao , Peng Guangbin , Deng Yongsheng , Xie Zhihong , Liu Lian 
Published: May 2023

Abstract
Fault diagnosis of rolling bearings has become a critical measure to ensure the security, efficiency, and availability of wind turbine systems. In this work, an approach called a transfer deep learning network is reported to resolve the drawbacks of existing rolling bearing fault algorithms on the basis of deep learning, such as large training parameters, long training time, and insufficient training samples. The reported approach mainly consists of two steps: feature transfer using transfer component analysis and network transfer using the pre-trained convolutional neural network. One dataset of rolling bearings with four fault types is gathered to estimate the classification performance, and the peer model is employed for a comparison study. The derived research results show that the reported algorithm based on the feature transfer and the network transfer can yield outstanding results in the rolling bearing fault diagnosis.
Research on Finite Element Analysis and Torque Ripple Suppression of the Switched Reluctance Motor
Authors: You XiaoXiao , Chu ChunLin , Zhang TianYuan , Sun BaoJiang 
Published: May 2023

Abstract
To repress the torque ripple of the switched reluctance motor, this study takes a three-phase 12/8-pole switched reluctance motor as an instance and simulates the electromagnetic field of the motor using Maxwell finite element software to analyze the influence of electromagnetic characteristics and pole arc parameters on the torque ripple of the motor. In conjunction with the Workbench platform, the response surface method and multi-objective genetic algorithm are used to optimize the pole arc coefficients so the average torque of the optimized motor meets the operating requirements while the torque ripple is suppressed. The findings demonstrate that various structural parameters have diverse impacts on motor torque and that multi-objective optimization can significantly diminish the torque ripple of the motor.
Redox-responsive self-assembled podophyllotoxin twin drug nanoparticles for enhanced intracellular drug delivery
Authors: Ma Yingyu , Chen Lei , Deng Lian , Li Xuebing , Zhao Xiu , Jiang Daobing , Liu Jiabao , Song Yang , Liu Junda , Cui Nan , Qiu Neng 
Published: May 2023

Abstract
Podophyllotoxin (PPT) is an active natural pharmaceutical component with potent anticancer activity. However, due to its poor water solubility and serious side effects, its medical applications are limited. In this work, we synthesized a series of PPT dimers, which can be self-assembled into stable nanoparticles of 124–152 nm in aqueous solution and can significantly increase the solubility of PPT in aqueous solution. In addition, PPT dimer nanoparticles exhibited high drug loading capacity (>80%) and could store at 4 °C in aqueous state with good stability for at least 30 d. In vitro release studies showed that nanoparticles with disulfide bonds (SS NPs) can quickly release (about 96.5% drug released within 24 h) the conjugated drug in PBS buffer (pH = 7.4) in the presence of DTT. Cell endocytosis experiments showed that SS NPs enhanced cell uptake (18.56 times higher than PPT for Molm-13, 10.29 times for A2780S and 9.81 times for A2780T) and maintained antitumor effect against human ovarian tumor cells (A2780S and resistant A2780T) and human breast cancer cells (MCF-7). In addition, the endocytosis mechanism of SS NPs was revealed that these nanoparticles were mainly up-taken by macropinocytosis-mediated endocytosis. We believe that these PPT dimer-based nanoparticles will become an alternative formula for PPT, moreover the assembly behavior of PPT dimer can be extended to other therapeutic drugs.
Exploring rainfall variabilities using statistical functional data analysis
Authors: Mazelan N A , Suhaila J 
Published: May 2023

Abstract
Functional data analysis (FDA) has been widely applied in various scientific fields, including climatological, hydrological, environmental, and biomedical. The flexibility of the FDA in incorporating temporal elements into the statistical analysis makes the method highly demanded compared to the conventional statistical approach. This study introduces FDA methods to investigate the variations and patterns of rainfall throughout Peninsular Malaysia, which includes 16 rain gauge stations in Peninsular Malaysia from 1999 to 2019. A descriptive statistic of the functional data depicted the mean and variation of the rainfall curve over time, while the functional principal component analysis measured the temporal variability of the rainfall curve. According to the findings, the first and second principal components accounted for 87.4% of all variations. The first principal component was highly characterised by the stations over the eastern region during the northeast monsoon since the highest variability was observed from November to January. On the other hand, the stations impacted by the inter-monsoon season were best described by the second principal component. Based on the factor scores derived from the functional principal component, those rain gauge stations with comparable features were then clustered. Overall, the results showed that the rainfall pattern is strongly influenced by their geographical and topographical features and the seasonal monsoon effect.
A brief overview of the issues faced by Harmful Algal Blooms along Johor straits
Authors: Noor N M , Hazri M I N M , Boo W H , Cob Z C 
Published: May 2023

Abstract
Urbanization of coastal areas worldwide has increased due to an increase in the global population. The production of sustainable aquaculture is greatly impacted by a surge of this urbanization. In certain countries, particularly for individuals with more limited space in metropolitan areas, such as along Johor’s coastal area, aquaculture might well be a good strategy to maintain food availability (continuous production plus high-quality meals). Consequently, the adoption of aquaculture along the Johor’s coastal area has lead to Harmful Algal Blooms (HAB). This paper examines the evolution of the aquaculture industry of Malaysian Johor coastal areas in relation to HABs. In addition to HABs, the aforementioned metropolitan regions confront diverse economic and geographical obstacles when attempting to increase their aquaculture production sustainably. Those problems are therefore addressed using a variety of operations as well as surveillance techniques in this brief overview. Lockdowns and border prohibitions caused by the continuous COVID-19 infection have had a global impact. These logistical difficulties in the seafood industry have increased dependency on imported supplies. It is suggested that international decision- making, supervision, and knowledge exchange can successfully solve the challenges urbanized areas have in ensuring sustainable food security through the evolution within the aquaculture sector.
A systematic review of Climate Change related Coral Reef research trend in Malaysia
Authors: Yu HP , Wee HB 
Published: May 2023

Abstract
Climate change related coral reef research has been receiving great interest globally as the world continues to experience worsening catastrophic climate change events, which causes the degradation of the ecosystem. While Malaysia is known for its extensive coral reef coverage, little is known about its coral reef research trajectory, especially related to climate change. Hence, this study aims to address the state of Malaysian coral reef research trend using the Web of Science (WoS; 1987–2022) database with comparison made within four areas in the country (East Coast of Peninsular Malaysia, West Coast of Peninsular Malaysia, Sarawak and Sabah), and explicitly looking into the aspect of climate change using three search strings respectively; (1) Bleach*, (2) Acid*, (3) Climate Change*. The results found the number of such publications in the WoS database is low (total of 31 publications in 36 years), with substantial research location bias dominated at the East Coast of Peninsular Malaysia. Generally, the study subjects of the publications focus on mixed organisms (Coral Reef) and Cnidaria as well as non-biological category ‘Environment’. Overall, the ecological assessment of the study trend shows notable climate change research gap in Malaysian coral reef research (lack of important organism studies; Pisces, Echinodermata, Mollusca). Thus, there is a need for climate change inclusive research direction in Malaysian coral reef research for the understanding, adaptation, prediction, and management of our coral reef ecosystem in an era of accelerated climate change circumstances.
Application of integrated LCA-GIS model in the agricultural sector: A brief overview
Authors: Kaita M S , Harun S N 
Published: May 2023

Abstract
Life Cycle Assessment (LCA) and Geographic Information System (GIS) are two different and complementary tools. LCA is used to evaluate only environmental consequences and cannot be employed to assess spatial environmental impacts, while GIS is a decision-making spatial tool capable of restoring, retrieving, analyzing, modelling, and mapping large areas with a huge volume of spatial data. The Integrated LCA-GIS model is a framework that aims at addressing the unsuitable match in spatial firmness/resolution of LCA. This paper conducted a brief overview of the application of the LCA-GIS model in the agricultural sector to investigate and clarify the current situation of the technique, especially in the areas of environmental assessment, sustainability assessment, energy-environment assessment, and qualitative assessment in terms of system boundaries, functional unit and impact categories in the agricultural sector. Cradle-to-gate system boundary was used in all the studies reviewed and this shows that there was a lack of depth analysis in evaluating the environmental impacts of the whole agricultural process. It is also observed in this paper that, few impact categories were assessed and no single damage category was evaluated, it further revealed that the LCA-GIS methodology for sustainability assessment does not evaluate socio-economic factors thus leading to the establishment of Regional Sustainability Assessment Methodology (RSAM). This paper recommends the use of a cradle-to-grave system boundary thus will help in an in-depth analysis of evaluating the environmental impacts of any agricultural product; evaluation of all the impact and damage categories and development of a single software that integrates LCA with GIS that applies to any research field.
Bivariate copula for flood frequency analysis in Johor river basin
Authors: Jafry N A , Suhaila J , Yusof F , Nor S R M , Alias N E 
Published: May 2023

Abstract
Flooding is a multi-attribute event that is described by many factors such as peak flow and flood volume. It is extremely vital to consider both the flood volume and the flood peak while studying the flood frequency analysis as the univariate analysis cannot accurately portray the flood issue and suffers from an underestimation and an overestimation problem. Traditional univariate and multivariate modeling techniques have several mathematical shortcomings including the inability to distinguish between the marginal and joint behavior of the variables under study. Therefore, the copula function was introduced to tackle the above restriction. Six copula models will be applied in this study to find the best bivariate distribution between the flood variables in Johor River Basin, Malaysia, including Gaussian, Student-t, Clayton, Gumbel, Frank, and Joe. Before that, several marginal distributions were fitted to select the most appropriate distribution for flood variables. It was found that the Pearson Type-III fits both the flood peak flow and the flood volume best. The evaluation of the best univariate marginal distribution and the copula model will be based on Akaike Information Criterion (AIC). Our findings suggested that Frank Copula is more suited to represent the relationship between peak flow and flood volume as it portrays the lowest AIC values of -69.41 and highest log-likelihood values of 35.7, where both values outperform the other proposed copula models. However, future research which considers all three flood variables which are peak flow, volume, and duration should be conducted to attain a more reliable result.
Assessment of water availability in the Sekampung Argoguruh Sub-Watershed for sustainable water management
Authors: Fitri A , Ariyanto L , Pratiwi D , Maulud K N A , Susarman  , Sari R O 
Published: May 2023

Abstract
In the Sekampung watershed, the Sekampung Argoguruh sub-watershed has been planned to be developed into one of the food barn regions, acting as a buffer for the nearby areas. This region is going to be converted from uncultivated to cultivated land in almost all parts. Given the recent developments in that area, it is necessary to determine if the water supply can fulfil the water demand for irrigation. Therefore, this study aims to evaluate the water supply-demand in the Sekampung Argoguruh sub-watershed in order to check the condition of long-term water resources for sustainable water management. In this study, the water supply was estimated by using National Rural Electric Cooperative Association (NRECA) method, while the amount of water required for agriculture and other uses in Sekampung Argoguruh sub-watershed were observed and calculated. The data analysis shows that the average water supply in the Sekampung Argoguruh sub-watershed is around 19.62 m3/s, whereas the average water demand for all activities in that region is roughly 11.65 m3/s. The situation of the water balance can be classified as excess based on the estimation findings, allowing water allocation to be done to satisfy demand.
UAVs for monitoring responses of regenerating forests under increasing climate change-driven droughts - a review
Authors: Luber A , Ramachandran V , Jaafar W S W M , Bajaj S , de-Miguel S , Cardil A , Doaemo W , Mohan M 
Published: May 2023

Abstract
The impact of climate change-driven droughts on regenerating forests is poorly understood due to the complexities involved in regeneration processes and the difficulties in measuring the relevant parameters with sufficient spatial and temporal resolution in a timely manner. Drought increases tree mortality in both undisturbed and disturbed forests and may influence forest regeneration dynamics from seed germination to the recruitment, growth, and survival of tree seedlings. Seedlings and small saplings may be more susceptible to changes in water availability than larger individuals due to their shallower roots that may be unable to reach the deeper, moist soil layers, and due to uneven competition with adult trees for soil moisture. The potential range shifts and local extinction of drought-sensitive species can also result in changes in forest species community composition and diversity loss at different scales. There is a need for precise and low-cost monitoring systems that facilitate better capturing of the complexities of such processes for restoration measures. The objective of this paper is to study the use of UAVs (Unmanned Aerial Vehicles) for monitoring responses of regenerating forests under increasing climate change-driven droughts. UAVs have several advantages over traditional field-based monitoring techniques and flexibility in selecting the required spatiotemporal resolution over other remote sensing methods, making them a promising tool for monitoring forest recovery. Although further research is required to ensure the accuracy and effectiveness of UAV-facilitated measures for monitoring forest regeneration, UAVs possess great potential in forest management in the event of increasing occurrences of climate-change driven droughts.
Estimating of Photovoltaic Energy Saving Potential and Investment Energy Value in Malaysia based on GIS Technology
Authors: Aldhshan S R S , Maulud K N A , Karim O A , Bahri M A S , Rahman M A 
Published: May 2023

Abstract
Creating environmentally friendly energy schemes that are sustainable is critical as a solution to the economic, ecological, and societal influences related to the energy sector. It should be noted that buildings utilize up to forty percent of global energy consumption. Furthermore, by 2030, it is anticipated to reach fifty percent. As a result, the world faces a significant dilemma in overcoming such worldwide energy generation issues. Concerning primary energy consumption, Malaysia is among Asia’s largest consumers. Malaysia’s immediate energy use in 2018 was 3.79 quadrillion Btu, growing at a 4.58% annualized rate. This article thoroughly reviewed past studies of global energy usage, particularly in Malaysia, and how the geographical information system (GIS) methodologies were employed for spatial evaluation of energy efficacy. Undoubtedly, effective energy strategies are critical in energy policy, and they can be developed through the application of a variety of methods for energy conservation in building structures. The findings of this study indicate that some GIS methods, such as machine learning, deep learning and multiple criteria decision analysis, are mainly employed for calculating energy consumption, researching renewable energy sources, and analyzing solar radiation. The results also show that the fuzzy_AHP and fuzzy_DS techniques have a higher capability and reliability in identifying the most suitable sites for photovoltaic (PV) farms. Due to the generation of a 3D model exportable to software tools through this technique, the 3D models are deemed efficient for calculating solar radiation. Furthermore, GIS and 3D can assist with various tasks, including access to sunlight in built structures and environments in urban areas, urban growth prediction models, and the habitability of public spaces analysis.
Analysis of a tuneable NZRI metamaterial unit cell for satellite applications
Authors: Al-Bawri S S , Islam M T , Singh M J. 
Published: May 2023

Abstract
In this paper, a new single negative metamaterial (MTM) unit cell structure with low profile of 6.2 × 6.2 m2 is proposed. The unit cell shows near zero refractive index (NZRI) characteristics in C, X and Ku bands whereas epsilon negative index (ENG) in Ku-Band frequency. The properties of the proposed MTM unit cell are analysed with the Rogers 5880 substrate which displays low permittivity. To verify the effectiveness of the split ring resonators (SRR) as a metamaterial, a comparison of the unit cell properties in 2 × 3 array structures is created. Besides low profile, tunability performance is shown in the proposed design by adjust the central strip line width of the proposed metamaterial whereas the frequency resonance can be shifted and controlled accordingly. Using commercially available CST software, the reflection (S11) and transmission (S12) parameters of the unit cell are determined. The proposed MTM unit cell can be potentially used in many applications including satellite communication systems.
Parametric analysis of epsilon-negative (ENG) and near zero refractive index (NZRI) characteristics of extraordinary metamaterial for 5g millimetre-wave applications
Authors: Musaed A A , Al-Bawri S S , Islam M T , Alkadri W M A 
Published: May 2023

Abstract
A tuneable single layer metamaterial (MTM) unit cell comprised of symmetric H-shaped resonators for 5G applications is proposed with epsilon negative (ENG) between 28 - 32 GHz, near zero permeability along the entire frequency range, and near zero refractive index between 28 - 32 GHz. The constructed design offers wide operational frequency range of 24.6 - 31.8 GHz with transmission coefficient resonances (S21) at 28 GHz. The symmetric resonating patch is partitioned into four comparable and equal quartiles, with an H-shaped resonator in each quartile. The metamaterial copper metallic layer is constructed on a Rogers (RT-5880) substrate and has dimensions of 9 × 9 mm2. The scattering parameter for the interaction with the electromagnetic wave is introduced the interesting properties of the effective parameter. The compactness of the subwavelength based metal-dielectric based resonator is related to the tailored metallic design. Numerical simulation of the proposed design is executed in CST microwave studio.
The production of hydrogen through microwave-initiated catalytic dehydrogenation of model hydrocarbon compounds on Fe/AC catalyst without significant CO2 emissions
Authors: Aldrees S , González-Cortés S , Al-Shihri S , Dilworth J R , Edwards P P 
Published: May 2023

Abstract
The utilization of hydrogen as a fuel source through the microwave-initiated catalytic deep-dehydrogenation (MICDD) of Saudi Arabian light crude oil (LCO) using Fe metal supported on activated carbon has been proposed for this study to achieve the current target of limiting global warming to 1.5 °C above pre-industrial levels. Should renewable technologies, for example, wind and solar, be not able to decarbonise the energy industry sufficiently in the near future, other approaches are needed to generate energy without the emission of massive amounts of aerial carbon (CO2). The composition of crude oil varies depending on its source; however, it is mainly composed of three families of hydrocarbons (paraffins, naphthenes, and aromatics). The aim of this work is to gain an understanding into the contribution of a single hydrocarbon model compound and combinations of these model compounds in proportions close to their real proportions in the LCO preparing a “synthetic crude oil”. In this work, hexadecane, cyclohexane, and benzene, toluene, and xylene (BTX) were selected to closely represent paraffins, naphthenes, and aromatics respectively. It was found that this as a facile route to produce both high concentrations of hydrogen from hexadecane (~90 vol. selectivity) and significant amounts of carbon multiwalled nanotubes over 30 wt. % Fe/AC catalyst at 1000 W input power. The results highlighted the effect of the composition of crude oils on the efficiency of H2 production and showed that paraffinic feedstock was relatively better for producing H2 among other hydrocarbons, and the presence of cyclic hydrocarbons, particularly aromatics, may inhibit H2 production. Importantly, this process creates solid carbon as a by-product of the process instead of CO2 and therefore does not contribute to climate change. The approach also has the potential to synthesise other high-value hydrocarbons as by-products.