bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mediterranean diet and associations with the gut microbiota and pediatric-onset multiple sclerosis using trivariate analysis
Authors: Mirza Ali I. , Zhu Feng , Knox Natalie , Black Lucinda J. , Daly Alison , Bonner Christine , Van Domselaar Gary , Bernstein Charles N. , Marrie Ruth Ann , Hart Janace , Yeh E. Ann , Bar-Or Amit , O’Mahony Julia , Zhao Yinshan , Hsiao William , Banwell Brenda , Waubant Emmanuelle , Tremlett Helen 
Published: July 2024

Abstract
Background
The interplay between diet and the gut microbiota in multiple sclerosis (MS) is poorly understood. We aimed to assess the interrelationship between diet, the gut microbiota, and MS.

Methods
We conducted a case-control study including 95 participants (44 pediatric-onset MS cases, 51 unaffected controls) enrolled from the Canadian Pediatric Demyelinating Disease Network study. All had completed a food frequency questionnaire ≤21-years of age, and 59 also provided a stool sample.

Results
Here we show that a 1-point increase in a Mediterranean diet score is associated with 37% reduced MS odds (95%CI: 10%–53%). Higher fiber and iron intakes are also associated with reduced MS odds. Diet, not MS, explains inter-individual gut microbiota variation. Several gut microbes abundances are associated with both the Mediterranean diet score and having MS, and these microbes are potential mediators of the protective associations of a healthier diet.

Conclusions
Our findings suggest that the potential interaction between diet and the gut microbiota is relevant in MS.
Research on transaction privacy protection solutions for cross‐border commerce
Authors: Ma JinCheng , Li Fei 
Published: July 2024

AbstractIn response to the dual privacy protection challenges concerning the confidentiality of transaction amounts and identities in cross‐border trade, a transaction scheme that combines +HomEIG Zero Knowledge Proof (+HomEIG‐ZKProof) and the national encryption algorithm SM2 is proposed. While ensuring transaction traceability and verifiability, this scheme achieves privacy protection for both payers’ and recipients’ identities, specifically tailored for cross‐border trade scenarios. Additionally, customs authorities play the role of supervisory nodes to verify the identities of transaction parties and the zero‐knowledge proofs for transaction information. The RAFT consensus algorithm is employed to construct a secure authentication application, demonstrating how zero‐knowledge proofs, combined with homomorphic encryption, can be verified through a consensus process. In this scenario, the legitimacy of transaction amounts is subject to zero‐knowledge verification during consensus interactions. Merchant identity verification is accomplished using SM2 ring signatures. The analysis indicates that this scheme offers strong security features such as resistance to tampering attacks, public key replacement attacks, impersonation attacks, and anonymity. Testing results demonstrate that this scheme can effectively provide dual privacy protection for transaction amounts and identities in cross‐border trade, meeting the practical requirements of privacy protection in cross‐border trade transactions.
Ultrasonic localization method based on Chan‐WLS algorithm for detecting power transformer partial discharge faults by fibre optic F‐P sensing array
Authors: Liu Hong , Yang Tianhe , Zhang Zhixian , Tian Haoyuan , Song Yuxuan , Sun Qiuxia , Wang Wei , Geng Yunjun , Chen Weigen 
Published: July 2024

AbstractFibre optic F‐P sensor has become one of the mainstream detection methods for partial discharge faults due to their advantages of good insulation, high sensitivity, resistance to electromagnetic interference, simple structure and inexpensive pricing. The first‐order resonant frequency of the acoustically sensitive diaphragm of the F‐P sensor is given based on the theory of plate and shell vibration, and the fibre optic F‐P sensing array is designed based on the Fabry–Perot interference principle. A sensor installation method is also proposed for introducing a fibre optic F‐P probe into the power transformer interior using a fibre optic penetrator through flange at the power transformer oil change valve. A system of non‐linear equations is developed by utilising the time difference of arrival (TDOA) of the partial discharge ultrasound signal propagation to the F‐P sensing array. The Chan‐WLS algorithm is used to convert the non‐linear equations in the TDOA localisation method into a non‐linear optimisation problem to be solved and experimentally verified on the 220 kV real power transformer. The experimental results show that the error in the partial discharge fault localisation is solved based on the Chan‐WLS algorithm and the actual location is 20.27 cm, which is within the acceptable error.
Nonmonotonic load‐dependence of friction during nanoparticle manipulation
Authors: Luo Chunsheng , Chen Lei , Tang Chuan , Liu Yangqin , Jiang Yilong , Qian Linmao 
Published: July 2024

AbstractThe tribological behaviors of nanoparticles (NPs) have attracted widespread attention in the fields of nano‐lubrication and ultra‐precision manufacturing. The frictional and dynamic behaviors of SiO2 NPs acting with the single asperity were studied on silicon surface utilizing atomic force microscope. The friction forces of NPs, both static and kinetic, exhibit an initial decrease followed by an increase as the normal load increases (0–300 nN). The nonmonotonic load‐dependence of friction behavior corresponds to the dynamic transformation of “sliding‐rolling‐sliding” motion state of the manipulated NPs, which can be predicted by a Double‐Hertz model and further confirmed by nanoindentation‐marked NPs. This research has a significant implication for regulating dynamic behaviors of NPs in contemporary three‐body abrasive tribology.
DRU‐HVDC for offshore wind power transmission: A review
Authors: Yu Lujie , Fu Ziyu , Li Rui , Zhu Jiebei 
Published: July 2024

AbstractThe rapid development of offshore wind farms (OWFs) calls for economical and reliable power transmission technology. This review paper focuses on the diode‐rectifier‐unit based high voltage direct current (DRU‐HVDC) transmission systems. The main technical features of DRU‐HVDC are highlighted and the comparisons with MMC‐HVDC and LCC‐HVDC are conducted. Considering the uncontrollability of DRU and the necessity of offshore wind turbines (WTs) to establish offshore network, the existing decentralized and centralized control strategies are reviewed in detail. For the fully‐grid‐forming converter, the operation principle of the P–V and Q–f power control is explained from the OWF‐DRU level and the WT level, respectively. For the partial‐grid‐forming converter, why the voltage control loop can be eliminated is analysed. Focusing on the start‐up issue caused by the unidirectional‐power‐flow characteristic of DRU, several start‐up solutions are reviewed, including medium voltage alternative current (MVAC) umbilical cable, auxiliary MMC, energy storage for WTs, auxiliary low voltage DC cable. Then considering different fault locations, the fault characteristic and protection of the DRU‐HVDC system is presented, including the offshore AC faults, DRU faults, HVDC faults and onshore AC faults. Finally, the future research topics worth exploring for DRU‐HVDC system are identified.
A dual pathway for understanding the relation between wellbeing and resilience
Authors: Riasnugrahani Missiliana , Setiawan Tery , de Jong Edwin , Takwin Bagus 
Published: July 2024

AbstractThis study investigates the intricate connections between relational wellbeing and individual resilience, through family and community protective factors. As such, we aim to bridge an existing gap in resilience literature by examining the elements that contribute to individual resilience from a relational perspective through a random sample of slum dwellers in Indonesia. To address this research gap, we adopted White’s conceptualisation of relational wellbeing and integrated Benard’s perspective on individual resilience and applied them using established measures to assess the general population living in slum areas across three Indonesian cities: Bima, Manado and Pontianak. Rigorous confirmatory factor analysis were conducted to establish the validity and reliability of all employed measures. The results of the mediated-path analysis underscore the significance of family protective factors in most relationships between dimensions of relational wellbeing and individual resilience. Notably, the two mediators exhibited distinct effects: the former positively mediated the relation, while the latter demonstrated an inverted mediation effect. These findings significantly enhance our understanding of the nuanced interplay between wellbeing and resilience, particularly regarding the impact of familial and community support on individuals’ ability to cope with daily life challenges, especially in disaster-prone areas.
Enhancing supercapacitor energy density by TiN–ZnS composites unveiled as a promising electrode
Authors: Arif Muhammad , Riaz Junaid , Bibi Amina , Yang Hongran , Zhu Ting 
Published: July 2024

This work describes a low-cost wet chemical synthesis technique to produce TiN–ZnS nanocomposites suitable for high energy density supercapacitors. Ti, Zn, N, and S elements in the synthesized materials were verified using comprehensive morphological, structural, and surface chemical investigations. Due to improved electric conductivity and electroactivity, this TiN–ZnS nanocomposite electrode exhibited excellent capacitance and charge transport kinetics, outperforming individual TiN and ZnS electrodes in electrochemical performance. The TiN–ZnS || MnO2 electrode configuration in an asymmetric supercapacitor system exhibited a high energy density of 74.13 Wh kg−1 and an exceptional power density of 7648 W kg−1 at a current density of 9 A g−1. The TiN–ZnS electrode also showed a remarkable retention rate of 96.8% even after 10 000 cycles. This work highlights the potential of the TiN–ZnS composite as a high-performance electrode for supercapacitors.
Reception zones of translated Nigerian literature in France
Authors: Madueke Sylvia Ijeoma 
Published: July 2024

Abstract
French translations of Nigerian literature have evolved since its introduction in France in 1953. Previous research documented periodic gaps and accounted for an ongoing translation of Nigerian literary texts in France. Since Nigerian literature has emerged as one of France’s most translated Anglophone African works, this study pursues this field by investigating how the French target culture receives and legitimizes this new literature. Consequently, it discusses several zones for the reception of Nigerian literature translated in France. Through a case study of the translation of a Nigerian writer, a general analysis of a mainstream French magazine and review platforms, and information garnered from interviews and fieldwork in France, this study shows that the prestige of a publisher, an author’s literary status, and thematic and political leanings contribute to successful reception and visibility in the target literary system. Critical and popular reception analyses from this study indicate progress in the domain of translated Nigerian literature, such as that translated Nigerian literature is featured in a mainstream French magazine. However, they show a lack of more comprehensive and systematic representation crucial for literary legitimization and visibility of translated Nigerian literature.
Eikonal approximation for Floquet scattering
Authors: Liu Yaru , Zhang Peng 
Published: July 2024

Abstract
The eikonal approximation (EA) is widely used in various high-energy scattering problems. In this work we generalize this approximation from the scattering problems with time-independent Hamiltonian to the ones with periodical Hamiltonians, i.e., the Floquet scattering problems. We further illustrate the applicability of our generalized EA via the scattering problem with respect to a shaking spherical square-well potential, by comparing the results given by this approximation and the exact ones. The generalized EA we developed is helpful for the research of manipulation of high-energy scattering processes with external field, e.g. the manipulation of atom, molecule or nuclear collisions or reactions via strong laser fields.
High-dimensional nonlinear variable separation solutions and novel wave excitations for the (4 + 1)-dimensional Boiti–Leon–Manna–Pempinelli equation
Authors: Liang Zu-feng , Tang Xiao-yan , Ding Wei 
Published: July 2024

Abstract
Considering the importance of higher-dimensional equations that are widely applied to real nonlinear problems, many (4 + 1)-dimensional integrable systems have been established by uplifting the dimensions of their corresponding lower-dimensional integrable equations. Recently, an integrable (4 + 1)-dimensional extension of the Boiti–Leon–Manna–Pempinelli (4DBLMP) equation has been proposed, which can also be considered as an extension of the famous Korteweg–de Vries equation that is applicable in fluids, plasma physics and so on. It is shown that new higher-dimensional variable separation solutions with several arbitrary lower-dimensional functions can also be obtained using the multilinear variable separation approach for the 4DBLMP equation. In addition, by taking advantage of the explicit expressions of the new solutions, versatile (4 + 1)-dimensional nonlinear wave excitations can be designed. As an illustration, periodic breathing lumps, multi-dromion-ring-type instantons, and hybrid waves on a doubly periodic wave background are discovered to reveal abundant nonlinear structures and dynamics in higher dimensions.
Charge self-consistent dynamical mean field theory calculations in combination with linear combination of numerical atomic orbitals framework based density functional theory
Authors: Qu 瞿 Xin 鑫 , Xu 许 Peng 鹏 , Liu 刘 Zhiyong 志勇 , Wang 王 Jintao 金涛 , Wang 王 Fei 飞 , Huang 黄 Wei 威 , Li 李 Zhongxin 忠星 , Xu 徐 Weichang 卫昌 , Ren 任 Xinguo 新国 
Published: July 2024

Abstract
We present a formalism of charge self-consistent dynamical mean field theory (DMFT) in combination with density functional theory (DFT) within the linear combination of numerical atomic orbitals (LCNAO) framework. We implemented the charge self-consistent DFT+DMFT formalism by interfacing a full-potential all-electron DFT code with three hybridization expansion-based continuous-time quantum Monte Carlo impurity solvers. The benchmarks on several 3d, 4f and 5f strongly correlated electron systems validated our formalism and implementation. Furthermore, within the LCANO framework, our formalism is general and the code architecture is extensible, so it can work as a bridge merging different LCNAO DFT packages and impurity solvers to do charge self-consistent DFT+DMFT calculations.
Classifying Rice Leaf Diseases through CNN for the Sustainable Agriculture
Authors: Krishnaveni R , Tamilselvan S , Prakash N , Haridass K , Harish S M , Lalith Kumar U 
Published: July 2024

Abstract
A major source of revenue and a means of sustenance in India is agriculture. Rice is a staple meal that is farmed in the major areas of India. It has been discovered that diseases significantly harm rice harvests, causing considerable costs for the agricultural sector. Plant pathologists are searching for an accurate and reliable method of identifying the illness afflicting rice plants. One effective use of machine learning in crop remote sensing is the categorization of agricultural illnesses. A major area of research right now for detecting agricultural diseases is deep learning. In this study, an effective Convolution Neural Network (CNN) based technique for detecting leaf disease in rice plants was developed. The major subjects of this study are the three well-known rice illnesses brown spot, hispa and leaf blast. This approach for diagnosing and recognising rice plant disease is based on the size, shape, and colour of lesions in the leaf picture. In Otsu’s global thresholding, the background noise is removed from the picture by binarizing it. The Histogram of gradient image edges and features are then displayed to see whether the image contains vectors that can identify sick regions. This model is used to learn the features after the vectors have been validated. It then divides the rice leaf images into four categories: healthy, brown spot, hispa, and leaf blast. The necessary deep learning toolkit is constructed in MATLAB to use the CNN based rice leaf detection algorithm. The Support Vector Machine (SVM) based classifier is also examined for comparison.
Catalysts and Constraints: A Comprehensive Review of G20 Countries’ Performance in Financial Stability, Climate Change Mitigation, and Sustainable Development (2023)
Authors: Mores Geddam Samuel , Amudhan S , Nethravathi N 
Published: July 2024

Abstract
This article presents a comprehensive review of the 2023 performance of G20 countries in the critical areas of Financial Stability, Climate Change Mitigation, and Sustainable Development. The G20, now expanded to include 21 nations with the inclusion of the African Union, plays a pivotal role in addressing global challenges. The study analyses financial stability using the 2023 Index of Economic Freedom, climate change mitigation through the Climate Change Performance Index (CCPI), and sustainable development based on the Sustainable Development Report 2023. The findings reveal notable variations in the performance of G20 nations, highlighting strengths and weaknesses in each area. Key insights include the financial stability leadership of Germany and the United Kingdom, India’s forefront position in climate change mitigation, and the sustainable development achievements of Germany, France, the United Kingdom, Japan, Italy, and Canada. The study underscores the interconnectedness of these three dimensions and emphasizes the need for holistic approaches to global challenges.
A Review towards Sustainable Heart Rate-Based Disease Detection: Prioritizing Environmental Impact, Access, and Health Outcomes
Authors: Raja Dinesh , Fateen Mohammed , Teja Talluri Mahi , Karthikeyan V 
Published: July 2024

Abstract
Sustainability in heart rate-based disease detection goes beyond diagnostics, embracing innovation that considers environmental impact, access, and health outcomes. Prioritizing energy efficiency and eco-friendly materials reduces the devices’ carbon footprint. Secure data management ensures privacy while optimizing resource use. Equitable access bridges gaps, reaching all communities for better health outcomes. Long-term benefits arise from preventive measures and healthier lifestyles. Adherence to regulations ensures safety and environmental responsibility. Education fosters informed choices, empowering individuals for sustainable healthcare decisions. In essence, sustainability in heart rate-based disease detection embodies a commitment to holistic well-being, paving the way for a more equitable and environmentally responsible future in healthcare. The heart rate based early identification of diseases are very popular owing to the advantages of just measuring and analysing rather than sending the samples for the laboratory test. Hence, in this paper the heart rate based early detection of diseases are done a detailed review. The various disease identification and the detection methods are studied meticulously and presented in this paper.
Renewable Energy based Automatic Water Level Monitoring for an Overhead Water Tank – A Prototype System
Authors: Ramu B , Kalyan Sagar K , Siva A , Palleswari Y T R 
Published: July 2024

Abstract
Resources provide enough energy to meet our needs to heat our houses, power our cities, and run our cars. Renewable resources also produce clean energy and greenhouse gas emissions, contributing to climate change. Nowadays, every one of us depends on using machine-based or other kinds of work to fulfil our day-to-day requirements, which include working with electricity. However, renewable energy sources such as solar and wind energy-based electricity must be increased to meet their daily requirements. In this paper, we come across the concept of a solar energy-based household water pump system to mitigate the AC supply usage for this purpose. In this, we used a solar panel to extract the solar energy to charge the battery up to 12V DC supply, and also, a rectifier circuit was used to charge the battery in the absence of solar energy through a step-down center-tapped transformer. The battery was charging in hybrid mode. Utilizing a driver circuit, the battery’s output is connected to an inverter circuit to boost the AC supply up to 230V. As a result, this arrangement gives us an uninterrupted AC supply used to test AC load, such as a bulb operating on a 230V AC supply. This idea is verified with a proteus software tool to drive for an application of automated switching ON/OFF water pumping 1-Φ induction motor to an overhead tank was performed using a relay circuit and also tested with a prototype hardware kit by connecting a bulb as the load at the output side.
Characteristics and Ash-Related Problem Prediction of Refused Derived Fuel from River Waste
Authors: Ruhiyat A S , Putra H P , Adelia Nesha , Prayoga M Z E , Suyatno  , Samudera H E , Noerhidayat A , Goeritno A 
Published: July 2024

Abstract
Environmental pollution, especially in rivers, increases every year, especially due to waste being dumped directly into rivers. Municipal solid waste can be processed into refused derived fuel to be used as a coal fuel mixture in CFPP. This research aims to analyse the risk of burning RDF originating from river waste as a single fuel and RDF as a mixed fuel for coal up to 30%. Solid fuel standard tests were used to determine sample characteristics and properties. To determine the initial risk of the ash deposition problem of RDF from river waste (RDF-R), the theoretical prediction indices are used. As a single fuel, RDF-R exhibits a high risk of slagging due to its high composition of Fe2O3 and CaO in the ash. Adding RDF-R to coal leads to increase of the slagging and fouling risk. However, addition up to 30% RDF-R to coal has insignificant effect in corrosion because the sulfur content in the coal can reduce the corrosive effects of chlorine.
Influence of humidity on the performance of floating photovoltaic systems over ponds in a tropical urban environment
Authors: Hendarti R , Linggarjati J , Kurnia JC , Arkan Hanan H R 
Published: July 2024

Abstract
Floating solar photovoltaics (FPV) are increasingly favored for solar energy harnessing, necessitating a thorough grasp of performance-influencing factors, notably weather conditions. This study delves into the statistical scrutiny of humidity’s impact on FPV performance within tropical settings, focusing on Jakarta’s urban context. While humidity’s effect on solar cell performance, particularly voltage output, is acknowledged, its influence in urban pond settings remains underexplored. Thus, an experiment was conducted, placing a floating PV system over a 24 m2 pond to directly assess humidity’s impact. Additionally, ambient temperature and irradiance levels were analyzed to comprehensively understand their interconnected effects on system efficiency. Moreover, the study investigated airflow’s role in humidity variation and overall environmental dynamics. The experimental setup comprised two strategically positioned solar panels over a 1.5-meter-deep pond. Regression and analysis of variance (ANOVA) techniques were employed to scrutinize humidity’s impact on the FPV system. Results revealed an inverse relationship between humidity and voltage, with humidity also contributing to ambient temperature reduction, thereby enhancing the microclimate. These findings underscore the intricate interplay of factors, where humidity, driven by evaporation, negatively influences irradiance levels while indirectly benefiting PV cell temperature by lowering ambient temperature. This research provides crucial insights for optimizing FPV performance in tropical urban settings, emphasizing the importance of nuanced approaches that account for humidity’s impact on floating photovoltaic systems.