bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accuracy assessment of offshore wind measurements partially compensated by MCP method considering data availability
Authors: Enoki K , Ishihara T 
Published: November 2024

Abstract
In Japan, most offshore promotion areas for bottom-fixed wind turbines are in near-shore areas, where offshore wind speeds are not uniform. The dual-scanning LiDAR system (DSL), which is a remote-sensing technology, is widely used to measure the mean wind speed, wind direction, and turbulence for resource and site assessments. However, the availability of DSL data tends to be lower than the key performance indicators proposed in the Carbon Trust in Offshore Wind Accelerator project owing to the characteristics of DSL. Missing observed data can be predicted using the measure–correlate–predict (MCP) method, and the uncertainty of the MCP method can be examined using a prediction function. However, a method to evaluate the accuracy of the final dataset comprising observed data and data predicted by the MCP method is yet to be devised. In this study, a set of formulas is proposed to evaluate the accuracy of indices, such as the coefficient of determination, slope, and offset of linear regression, for a partially complemented dataset using the MCP method. The proposed formulas are validated against on-site measurements.
Calibration and implementation of a design tool for drag anchors in clay
Authors: Nielsen S D , Sørensen S P H , Ø Nielsen C , Jensen C L 
Published: November 2024

Abstract
Drag anchors are considered as one of the most applicable anchor solutions for floating offshore wind as they can be used for a wide range of soil conditions. For feasibility studies of floating offshore wind farms different anchor concepts needs to be compared in order to select the most proper anchor solution. To do so, the level of details in the analysis for the various anchor types must be similar. Currently design charts are adopted as a simple design method for drag anchors. However, design charts are developed for specific soil conditions, and do not account for site specific soil conditions. To have similar precision, as analytical solutions for suction anchors, a simple design methodology that can account for site specific soil conditions for drag anchors must be adopted. This paper presents an example for how a simple analytical solution can be calibrated against design charts, which makes it possible to account for site specific soil conditions, resulting in a better basis for comparing early stage drag anchor design to other anchor solutions.
Research on the new control strategy of the three-phase VIENNA rectifier
Authors: Ma Xingrui , Lu Jianning 
Published: November 2024

Abstract
The VIENNA rectifier has long been used in applications such as charging piles, and the theoretical research on its control strategy is enumerated. Compared with other circuit components, the VIENNA rectifier has fewer power components and a higher power factor, so it is applied to more application scenarios. The traditional PI control has a long start-up response time and a high overshoot, while the sliding mode control (SMC) has excellent control performance for nonlinear systems. In my article, the control mode of the VIENNA rectifier is analyzed mathematically, SMC takes controls of the current inner loop, and a new exponential reaching rate is put forward the at first improve the control process. Finally, a complete system simulation model is built to prove the superiority of the VIENNA rectifier based on an optimized SMC control strategy for each control target and the corresponding control strategy. The results show that the control effect is obviously optimized by using this method.
A multi-time scale grid scheduling optimization method considering demand-side resources
Authors: Jiang Chi , Wang Chaoliang , Lu Chunguang , Yan Huajiang 
Published: November 2024

Abstract
This research introduces a pioneering strategy for optimizing power grid scheduling across various time scales, addressing a previously unmet need in the field of energy regulation. Initially, we amassed and categorized tunable resources on the demand side into three distinct temporal categories—long-term, short-term, and immediate—reflecting their respective response attributes. This taxonomy informed the development of a cohesive scheduling framework, encompassing pre-emptive, daily, and instantaneous sub-models, designed to facilitate precise control over grid operations. The deployment of this framework has led to marked enhancements in both the efficiency and dependability of power grid management. The merits of this methodology were exemplified through its application to the IEEE33 network model, showcasing its proficiency in the acquisition of optimized scheduling parameters. This multi-tiered modeling and optimization technique offers an innovative pathway for the dynamic and effective management of smart grids.
A clustering method for charging behaviors of electric vehicle users based on an improved k-means algorithm
Authors: Li Chenggang , Zhang Jiajun , Zhang Haifeng , Wang Jiarui 
Published: November 2024

Abstract
The uncertainty of Electric vehicle users’ (EVUs) charging behaviors affect the power grid safety. Therefore, mining the charging behavior characteristics of EVUs can help the power grid to make optimal operation plans previously to smooth the load curve and improve stability. In this regard, a clustering strategy for EVUs is proposed, using an improved K-means algorithm based on the minimum variance theory(MVT). Additionally, the Monte Carlo algorithm is utilized to obtain the simulation results of EVUs. Finally, a numerical simulation based on actual data in China is established to validate the effectiveness and reliability of the proposed cluster algorithm. The results indicate that the proposed cluster algorithm can accurately extract the characteristics of EVUs’ off-on grid behaviors and obtain the accurate daily charging demand representing the main charging rules among EVUs. The proposed algorithm results in a reduction of 69.2% of solution time compared to the traditional K-means algorithm.
Monitoring of insulator pollution discharge in overhead distribution network based on acoustic emission technology
Authors: Luo Busheng , Luo Zishun , Yang Shihao 
Published: November 2024

Abstract
During the continuous operation of the distribution network, dirt often accumulates on the surface of insulators. Once encountering a humid climate environment, it may cause accidental discharge, leading to the occurrence of flashover pollution accidents. In order to effectively monitor this issue, this study adopted a monitoring method based on acoustic emission technology. This article introduces the discharge process and acoustic emission phenomenon of insulators in overhead distribution networks under pollution conditions. By using emission signal detection devices, acoustic signals generated during insulator discharge are captured. And the wavelet denoising algorithm was used to process its signal, based on which the discharge characteristics of insulator pollution in the overhead distribution network were extracted. The emission amount of insulator pollution in the overhead distribution network was determined according to the set threshold, achieving monitoring of pollution emissions. The results indicate that the proposed method can accurately monitor the discharge of insulators in overhead distribution networks, provide scientific basis for timely maintenance measures, and improve the operational safety and reliability of distribution networks.
Power flow distribution identification via machine learning algorithm and distributed resource clearing method
Authors: Wang Su , Fu Chen , Lan Li , Chen Peng , Guo Mingxing , Tang Mingxi 
Published: November 2024

Abstract
Under the background of dual carbon, a large number of distributed new energy sources are connected to the demand side, which leads to great risks in the operation of the power system. As an effective solution, distributed power transaction still has problems, such as high clearing time, unknown low-voltage distribution network structure, and resource scheduling ignoring user needs. Therefore, this paper proposes an optimal regulation method of demand-side resources based on distributed transactions. Based on the historical operation data of the distribution network, the eXtreme Gradient Boosting (XGBoost) algorithm is used to study the relationship between node injection power, node voltage, and node-side line power flow. It is also used to check the results of distributed transactions and design a market mechanism for rapid clearing and settlement of distributed transactions. The results of an example show that the identification of power flow distribution in a distribution network based on reinforcement learning can meet the security check requirements of distributed transaction results.
Exact results on the dynamics of the stochastic Floquet-East model*
Authors: De Fazio Cecilia , Garrahan Juan P , Klobas Katja 
Published: November 2024

Abstract
We introduce a stochastic generalisation of the classical deterministic Floquet-East model, a discrete circuit with the same kinetic constraint as the East model of glasses. We prove exactly that, in the limit of long time and large size, this model has a large deviation phase transition between active and inactive dynamical phases. We also compute the finite time and size scaling of general space-time fluctuations, which for the case of inactive regions gives rise to dynamical hydrophobicity. We also discuss how, through the Trotter limit, these exact results also hold for the continuous-time East model, thus proving long-standing observations in kinetically constrained models. Our results here illustrate the applicability of exact tensor network methods for solving problems in many-body stochastic systems.
Lie–Hamilton systems on Riemannian and Lorentzian spaces from conformal transformations and some of their applications
Authors: Campoamor-Stursberg Rutwig , Carballal Oscar , Herranz Francisco J 
Published: November 2024

AbstractWe propose a generalization of two classes of Lie–Hamilton systems on the Euclidean plane to two-dimensional curved spaces, leading to novel Lie–Hamilton systems on Riemannian spaces (flat 2-torus, product of hyperbolic lines, sphere and hyperbolic plane), pseudo-Riemannian spaces (anti-de Sitter, de Sitter, and Minkowski spacetimes), as well as to semi-Riemannian spaces (Newtonian or non-relativistic spacetimes). The vector fields, Hamiltonian functions, symplectic form and constants of the motion of the Euclidean classes are recovered by a contraction process. The construction is based on the structure of certain subalgebras of the so-called conformal algebras of the two-dimensional Cayley–Klein spaces. These curved Lie–Hamilton classes allow us to generalize naturally the Riccati, Kummer–Schwarz and Ermakov equations on the Euclidean plane to curved spaces, covering both the Riemannian and Lorentzian possibilities, and where the curvature can be considered as an integrable deformation parameter of the initial Euclidean system.
Antioxidant and antidiabetic potential of Cystoseira myrica-mediated green metallic zinc nanoparticles using the algal extract: synthesis and characterization
Authors: Diab Amira S , Alqhtani Haifa A , Bin-Jumah May , Rudayni Hassan A , Elsayed Khaled N M , Al Zoubi Wail , Allam Ahmed A , Abukhadra Mostafa R 
Published: November 2024

Abstract

Cystoseira myrica marine macroalgae (CSR) were used to produce metallic zinc nanoparticle composites by utilizing the phytochemicals naturally found in the algae. This involves homogenizing the residuals of CSR (10 g), zinc nitrate solution (5 M; 100 ml), and methanol liquid extract (100 ml) at 30 °C for 24 h of sonication and stirring, followed by filtration and drying. This resulted in a hybrid bio-composite (Zn/CSR), which demonstrated strong antioxidant and antidiabetic properties when compared to zinc oxide (ZnO) and CSR used separately. The Zn/CSR hybrid showed excellent antioxidant activity against common radicals such as DPPH (91.5 ± 1.66%), nitric oxide (90.4 ± 1.2%), ABTS (92.2 ± 1.9%), and O2
·− (27.8 ± 1.12%) (p < 0.05), performing better than the standard antioxidant, ascorbic acid. Regarding its antidiabetic properties, the Zn/CSR composite significantly inhibited key enzymes involved in diabetes, including both commercial enzyme forms (α-amylase (80.3 ± 1.65%), α-glucosidase (96.6 ± 1.11%), amyloglucosidase (95.8 ± 1.3%)) and their crude intestinal forms (α-amylase (72.3 ± 1.5%), α-glucosidase (94.2 ± 1.7%)) (p < 0.05). This improvement increases the impact of the green CSR extract in reducing the agglomeration behaviors of the loaded metal and the formation of a capping layer from the phytochemicals on its surface, in addition to the beneficial effects of the CSR as substrate, which enhances the biological functions of the loaded metal and its interaction interfaces. The Zn/CSR composite also outperformed commercial miglitol drugs and slightly surpassed acarbose in effectiveness. Given the high cost and potential side effects of current medications, the Zn/CSR composite could be a cost-effective alternative for antioxidant and antidiabetic treatments. These findings also emphasize the role of CSR-derived phytochemicals and algae residues in enhancing the biological activity of the metal nanoparticles.
Investigation of the microstructure, electrical and mechanical properties of Al-CNTs-B4C composite prepared by double-step stir casting for power transmission conductor
Authors: Malobi Uchenna Ifeanyi , Ezema Ikechukwu Ike-Eze C , Ujah Chika Oliver 
Published: November 2024

Abstract
Monolithic aluminium alloy is a modern engineering material that is in high demand owing to its excellent performance and versatility. It has a high electrical conductivity, low density, high strength- to- weight ratio, and high resistance to corrosion. However, it lacks adequate resistance to creep, fatigue, stable microstructure, and strength at elevated temperatures. To overcome these deficiencies, aluminium matrix composites are developed. This work focuses on an experimental investigation of the microstructure, mechanical strength, and electrical conductivity of Al-CNTs-B4C composite consolidated by a double-step stir casting technique. An x-ray diffractometer, transmission electron microscopy, and a field-emission scanning electron microscope fitted with energy dispersive x-ray spectroscopy were used to characterize the start-up powders and the cast samples. A Brinell tester was used to measure the microhardness of the cast samples. A four-point probe meter was used to determine the electrical conductivity. The microstructural results revealed formation of Al4C3 and Al3BC intermetallics, B4C phase and amorphous carbon precipitate. Marginally improved electrical conductivity of 33.33 × 107 S m−1 (65.1% IACS) was obtained with Al-5CNTs-15B4C, together with high microhardness of 725.72 MPa. The microhardness improved by 94.7% over monolithic pure Al. The double-step stir casting enhanced the homogenous dispersion of the reinforcements. The improvements in the mechanical properties and electrical conductivity were attributed to the synergy between B4C and CNTs which induced Orowan looping, load transfer effect, plastic deformation and dislocation pinning in the composite. It is recommended that this composite will perform creditably in power transmission.
Enhancement of the photocatalytic efficiency of ZnO utilizing luminescent Y2O3 particles
Authors: Gültekin Serdar , Birlik Isil , Oguzlar Sibel , Ertekin Kadriye 
Published: November 2024

Abstract
This study explored the superior photocatalytic performance of the nanoscale zinc oxide-yttrium oxide (ZnO-Y2O3) based composite over ZnO nanoparticles (NPs). We investigated this by following the photocatalytic degradation efficiency of methylene blue (MB). The sol–gel synthesized Y2O3 and ZnO NPs were characterized by x-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The spectral behaviour and photocatalytic efficiency of the proposed composite were investigated by UV–vis spectrophotometry, steady-state and time-resolved photoluminescence (PL) measurements, respectively. The results indicated the successful formation of Y2O3 and ZnO nanoparticles with desirable structural properties. The photocatalytic degradation efficiency of the MB solution was evaluated for different concentrations of the counterparts of the ZnO-Y2O3 composite. In particular, the ZnO-5Y2O3-based composite showed superior photocatalytic activity after 150 min of UV irradiation, achieving 98.4% degradation of the MB solution compared to the 77% degradation achieved by pure ZnO. Although Y2O3 alone does not exhibit photocatalytic activity, its combination with ZnO significantly enhances the photocatalytic performance of ZnO. This improvement was attributed to the luminescence properties of Y2O3. By elucidating this unique mechanism, the performance of photocatalytic materials can be significantly enhanced. In our study, the improvement of the photodegradation rate constant (kapp) of ZnO from 0.009 min−1 to 0.0242 min−1 demonstrated the promising photocatalytic efficiency of the ZnO-5Y2O3 based composite, opening up exciting possibilities for further applications in environmental remediation and other fields.
Assessing the fiscal implications of flood disasters in India: insights for general and special category states
Authors: Mohanty Ranjan Kumar , Behera Deepak Kumar , Agarwal Priti , Sahoo Dibakar , Parida Yashobanta 
Published: November 2024

Abstract
This study provides a comprehensive analysis of the fiscal consequences arising from flood disasters in India, with a specific focus on the challenges encountered by General Category States (GCS) and Special Category States (SCS). Recognizing India’s vulnerability to floods due to its diverse geographical and climatic landscape, the research emphasizes the need for a coordinated disaster response framework involving both central and state governments. Utilizing a panel vector autoregression (VAR) methodology alongside impulse response functions (IRFs), the study finds that flood disasters significantly impact fiscal variables over a medium-term horizon of 3–5 years. Our findings indicate that fiscal deficits widen for up to three years post-disaster, while expenditures on flood control surge in the following years. Notably, SCS face a disproportionate fiscal strain, exacerbated by their geographical disadvantages and heightened susceptibility to disasters, leading to a decline in non-tax revenue after flood shocks. The study advocates for tailored fiscal policies that enhance the resilience and recovery capacity of both GCS and SCS in addressing flood-induced fiscal challenges.
Evaluating process parameters of SLS part of polyamide-12 recycled powder using RSM
Authors: Rahman Irfan Ur , Ab Wahab Norfariza Binti , Raja Abdullah Raja Izamshah Bin , Rosley Mohd Idain Fahmy Bin , Abu Zaki Muhammad Syafiq Syazwan , Taib Mohd Taufik 
Published: November 2024

Abstract
Selective laser sintering (SLS) is a highly flexible rapid prototyping (RP) technology which can use a wide range of powdered materials to generate high quality complex geometries directly from digital models. The SLS process uses a laser to sinter selected areas of powdered materials to produce solid objects layer by layer, according to the 2D data obtained from CT scan or MRI imaging techniques. This paper presents research work for evaluating the effect of process parameters on impact toughness and surface roughness of the part manufactured on Farsoon SS402P SLS from recycled ageing FS 3300PA which is PA-12 based powder and standard operating parameters using Response Surface Methodology (RSM) design of experiments. Impact tests have been performed as per the ASTM D6110 standard using recommendations from ISO 179-2. According to the results, effect of process parameters are successfully analyzed by employing impact toughness and surface roughness tests. Based on the results of the ANOVA analysis, impact toughness increases with increasing laser power (4.467 J cm−2 at 72.5 watts). Similarly, it is also clear from the results that the region with the lowest laser power, high layer thickness, and 90-degree orientation had the lowest surface roughness (3.46 μm).
Intracapillary monoclonal IgM deposits disease with massive pseudothrombi: A clinicopathologic study of 4 cases and literature review
Authors: Ma Lei , Liang Dandan , Yao Xinchen , Yang Xiaoqing , Li Suhua , Adelibieke Yelixiati· , Xu Feng , Liang Shaoshan , Chen Dacheng , Yang Fan , Wang Xiaoyu , Tang Yujie , Jia Ruoyu , Zeng Caihong 
Published: November 2024

Abstract

Objectives
Intracapillary monoclonal IgM deposits disease (ICMDD) has long been considered a hallmark of Waldenström macroglobulinemia (WM) nephropathy. Intracapillary immunoglobulin thrombi are the characteristic features of cryoglobulinemic glomerulonephritis. Here, we reported 4 cases of ICMDD with massive pseudothrombi but without WM or cryoglobulinemia.

Methods
We retrospectively analyzed the clinical and pathologic features of patients diagnosed with ICMDD with massive pseudothrombi.

Results
A total of 4 patients (2 men and 2 women) aged 62 to 73 years were enrolled in this study. Microscopic hematuria, edema, and renal insufficiency were present in all patients, along with low serum C3 and C4 in 2 patients. Hematologic examination showed abnormal serum free light chain ratios in all patients and high levels of serum IgM in 3 patients. IgM-κ monoclonal band was identified by serum immunofixation electrophoresis in 3 patients. One patient was diagnosed with small B-cell lymphoma by bone marrow aspiration. Renal biopsy specimen showed massive periodic acid-Schiff–positive hyaline thrombi in the glomerular capillary lumens and also less mesangial, subendothelial, and subepithelial deposits on light microscopy. Immunofluorescence indicated positive staining for IgM (++) and κ light chain staining in the glomerular capillary lumens, capillary walls, and mesangium in all patients. By electron microscopy, the glomerular capillary lumens were filled with homogeneous high-electron-dense deposits without substructure. Two patients were treated with prednisone combined with cyclophosphamide, and 2 received plasma cell–targeted chemotherapy. One patient achieved partial renal remission.

Conclusions
Intracapillary monoclonal IgM deposits disease is a rare disease and not always related to WM. Most patients have IgM monoclonal immunoglobulinemia; renal biopsy specimens mainly show a large number of pseudothrombi in the glomerular capillary lumens. Cyclophosphamide is effective in some patients.
English language and employability in locally produced ELT textbooks: Clashes between neoliberal ideals and social class structures in the pedagogical space
Authors: Ali M Maksud , Hamid M Obaidul 
Published: November 2024

Abstract
While a growing body of literature has illustrated how neoliberal discourses of English and employment have come to shape English language teaching (ELT) textbooks in a globalized world, little is known about how the translation of these discourses into pedagogical practices is mediated by the social class structures in postcolonial societies. In this article, we draw on a larger qualitative case study to address this gap in the Bangladesh secondary schooling context. We utilize Bourdieu’s conceptual resources and analyze interview and classroom observation data to illustrate how discourses of English and employment introduced into the secondary education-level ELT textbook are enacted in a high socio-economic status school. As our findings illustrate, the students from this school rejected how English was linked to low-profile jobs in the textbook, as this representation contradicted their social class and career aspirations. These findings contribute to the political economy in applied linguistics literature by illustrating how the enactment of the neoliberal discourses of English and employment constructed in the locally produced ELT textbooks is mediated by social class.