bluuebunny/crossref_metadata_2025_split huggingface dataset:
Power of a test for assessing interlaboratory consensus of nominal and ordinal characteristics of a substance, material, or object
Authors: Gadrich Tamar , Marmor Yariv N , Pennecchi Francesca R , Hibbert D Brynn , Semenova Anastasia A , Kuselman Ilya 
Published: June 2024

Abstract
A concept of the consensus among different laboratories participating in an interlaboratory comparison, classifying a substance, material, or object according to its nominal and ordinal (i.e. categorical) characteristics, is devised using decomposition of the total variation of the laboratory responses. One of the components of the total variation is caused by the between-laboratory differences, and the second—by conditions associated with the applied experimental design (for example, temperature of test items, technician experience, etc). This decomposition is based on the recently developed two-way CATANOVA for nominal variables and two-way ORDANOVA for ordinal variables. The consensus is tested as hypotheses about homogeneity, i.e. insignificance of the corresponding components of the total variation. The consensus power is taken to be the power of the homogeneity test. A methodology for evaluation of the consensus power and corresponding risks of false decisions versus the dataset size of categorical characteristics obtained in an interlaboratory comparison is detailed. Examples of evaluation of the power and risks are discussed using previously-published datasets of an interlaboratory comparison of identification of weld imperfections, and an examination of the intensity of the odor of drinking water. An example of computer code in the R programming environment is presented for the power calculations in the case of nominal variables, using a chi-square distribution. A newly developed tool for ordinal variables, an Excel spreadsheet with macros, which is based on Monte Carlo draws from a multinomial distribution, is also available.
Investigations of atomic and molecular processes of NBI-heated discharges in the MAST Upgrade Super-X divertor with implications for reactors
Authors: Verhaegh Kevin , Harrison James , Lipschultz Bruce , Lonigro Nicola , Kobussen Stijn , Moulton David , Osborne Nick , Ryan Peter , Theiler Christian , Wijkamp Tijs , Brida Dominik , Derks Gijs , Doyle Rhys , Federici Fabio , Hakola Antti , Henderson Stuart , Kool Bob , Newton Sarah , Osawa Ryoko , Pope Xander , Reimerdes Holger , Vianello Nicola , Wischmeier Marco ,   the EUROfusion Tokamak Exploitation Team,   the MAST-U Team
Published: June 2024

AbstractThis experimental study presents an in-depth investigation of the performance of the MAST-U Super-X divertor during NBI-heated operation (up to 2.5 MW) focussing on volumetric ion sources and sinks as well as power losses during detachment. The particle balance and power loss analysis revealed the crucial role of Molecular Activated Recombination and Dissociation (MAR and MAD) ion sinks in divertor particle and power balance, which remain pronounced in the change from ohmic to higher power (NBI heated) L-mode conditions. The importance of MAR and MAD remains with double the absorbed NBI heating. MAD results in significant power dissipation (up to∼20%ofPSOL), mostly in the cold (Te<5eV) detached region. Theoretical and experimental evidence is found for the potential contribution ofD−to MAR and MAD, which warrants further study. These results suggest that MAR and MAD can be relevant in higher power conditions than the ohmic conditions studied previously. Post-processing reactor-scale simulations suggests that MAR and MAD can play a significant role in divertor physics and synthetic diagnostic signals of reactor-scale devices, which are currently underestimated in exhaust simulations. This raises implications for the accuracy of reactor-scale divertor simulations of particularly tightly baffled (alternative) divertor configurations.
Compatibility of divertor detachment and ELM suppression in DIII-D high-

β

p

plasmas with ITER-similar shape
Authors: Wu D.G. , Wang L. , Wang H.Q. , Garofalo A.M. , Gong X.Z. , Ding S. , Wang Y.F. , Lan H. , Yan N. , McClenaghan J. , Weisberg D.B. , Hyatt A.W. , Osborne T.H. , Eldon D. , Fenstermacher M.E. , Scotti F. , Yang Q.Q. , Huang J. , Qian J.P. , Li K.D. , Liu J.B. 
Published: June 2024

Abstract
Integration of transient and steady-state divertor heat fluxes control with a high-performance core is necessary for future fusion reactors. In recent DIII-D high-

β

p

experiments, divertor detachment and simultaneous edge localized mode (ELM) suppression are demonstrated while the plasma confinement quality is maintained high in ITER-similar shape. By optimizing the neon injection in high-

β

p

scenario with ITER-similar shape, deep detachment and ELM suppression are achieved with a high-performance core (

β

N

∼ 2.8,

β

p

∼ 2.3) at

q

95

∼ 7.5. Partial divertor detachment and suppression of large ELMs are achieved at

q

95

∼ 6. The stability analyses suggest that with low neon injection, the density pedestal becomes higher and steeper and the

T

i

profile also increases, therefore the increased edge pressure and higher current density destabilize the Peeling-Ballooning mode (PBM), which would lead to a large ELM collapse. With strong neon gas puffing, the significantly reduced pedestal pressure and current density, due to the degraded

T

e

pedestal, lead to the stabilization of PBM and ELMs are suppressed. For both cases, the coupling between the large radius internal transport barrier (ITB) and edge pedestal is the key reason for maintaining high global performance. The formation of large radius ITB compensates for pedestal degradation. Such results could provide an attractive scenario to well control the transient and steady-state heat flux onto the divertor plates while maintaining good plasma performance, which is an important step toward the steady-state operation of future fusion reactors.
Research on Distribution Automation Testing Platform Based on Kubernetes Technology
Authors: Xudong Song , Ya Wu , Yao Yao , Bei Li 
Published: June 2024

Abstract
In this paper, the problems of offline testing, manufacturer collaboration, and inconsistent standardization of existing test platforms are addressed in this study, with a special focus on complex field test scenarios and under-applied test data. To solve this problem, a test platform for distribution automation (DA) equipment based on Kubernetes technology is proposed. First, the composition and testing process of the DA testing system are elaborated in detail, and then a new testing platform is constructed by introducing Kubernetes technology. Finally, the feasibility of the platform is verified by building the new DA test platform based on Kubernetes technology for experiments. This study aims to improve the effectiveness of the test platform, promote the full application of field test scenarios and test data, and provide a more consistent and efficient solution for the testing of distribution automation equipment.
Research on the impact of intelligent battery charging and swapping cabinets on distribution networks: a predictive model based on urban traffic conditions
Authors: Ming Liang , Zhang Zongming , Zhu Feng , Liu Jingwei 
Published: June 2024

Abstract
The ownership of electric bicycles has rapidly increased, which has led to the emergence of intelligent charging and swapping cabinets, eliminating the need for users to charge their electric bicycles at charging cabinets. Instead, they can simply swap the batteries at the charging and swapping cabinets, thereby improving efficiency. However, the charging process within these cabinets also impacts the power distribution grid. Therefore, this paper proposes a charging load prediction model based on urban road conditions and dynamic algorithms. The model combines matrix analysis and dynamic search using the Dijkstra algorithm to simulate electric bicycle driving. The model can navigate around congested roads, reflect the impact of traffic conditions on electric bicycles’ speed and power consumption, and consider the effects of driving, battery consumption, and charging cabinets on the power distribution grid during the charging process. This more accurately reflects the real-time interaction between dynamic driving and traffic conditions. The predicted results also illustrate the regional and temporal variations in the demand for electric bicycle loads, as well as the impact of charging loads on the voltage at different nodes of the power distribution grid.
Hybrid topology and circuit design of power converter based on Si and SiC
Authors: Yang Zaixin , Minfu A , Jian Xusheng 
Published: June 2024

Abstract
The application of a large-capacity power conversion system (PCS) is of great significance for solving the problem of safe energy storage and new energy consumption in new-type power systems. The research and promotion of semiconductor components such as Si and SiC, as well as hybrid topology, have further improved the power density of the converter. In this paper, the topology and circuit design of the converter based on Si and SiC are analyzed by comparison. An SVM modulation method is used for the Three-Level, Two-Stage, Decoupled Active NPC converter (3L-ANPC). Furthermore, a power circuit board (PCB) with Si and SiC is designed. Innovative optimization of the power line and SiC layout in PCB has achieved a good current-sharing effect of the converter. Finally, the effectiveness of current-sharing for a three-level hybrid converter is verified through a double pulse test.
Research on road detection algorithm for power operation safety inspection robots
Authors: Li Luyao , Wang Kai , Fei Zhengming , He Ke 
Published: June 2024

Abstract
The safety of on-site power operations affects the socio-economic development and stable operation, and safety inspection is an important part of power production. To improve work efficiency, intelligent inspection vehicles, inspection robots, and artificial intelligence methods, including image recognition and video recognition technologies, are widely used in power operation safety inspection. Due to the complex environment of power operation sites, inspection vehicles are unable to reach all corners of the operation site. Compact and more flexible quadruped, four-wheeled, or two-wheeled inspection robots mounted on vehicles can cover more operation points, forming a new mode of automated inspection in both air and land with unmanned aerial drones. In the practical application of inspection robots, the primary challenge lies in road recognition and route optimization. To address the difficulty of road detection in the operation of inspection robots, this paper proposes a real-time road detection algorithm based on the Encoder-Decoder structure. It utilizes the idea of binary segmentation to extract semantic information of lane lines in the plane feature map and completes the feature map matching through a road line fitting algorithm, effectively improving the accuracy of road recognition at the operation site and laying a foundation for the automation of on-site inspection by inspection robots. The experimental results on the Tusimple validation set demonstrate that the proposed algorithm achieves an accuracy (acc) of 96.73% and a frame rate of 112.1 FPS, showcasing outstanding detection accuracy and efficient processing speed, providing a reference for future applications of comprehensive automated safety inspection in both air and land.
Exploring the InSAR signature associated with river-sourced recharge in California’s San Joaquin Valley
Authors: Neely Wesley R , Knight Rosemary , Kang Seogi , Goebel Meredith 
Published: June 2024

Abstract
Recharge is a critical component for understanding aquifer systems and the sustainable management of groundwater resources, yet this process is challenging to measure at policy-relevant spatiotemporal scales. Building upon previous research, we tested the hypothesis that InSAR can be used to observe river-sourced recharge if the underlying recharge pathways are associated with sufficient clay content. Our analysis leveraged the decomposition of InSAR time series with interpretations of 3D resistivity models derived from airborne electromagnetic (AEM) surveys. We focused our analysis on two study sites where high density AEM data were available and river-sourced recharge is determined to have occurred during wet years: (1) near Fresno, California and (2) near Visalia, California. Sediment type and hydrogeological structure from AEM supported our hypothesis with the InSAR signature attributed to river-sourced recharge occurring only in the study site with semi-confined to confined conditions and relatively high fraction of interbedded clay within recharge pathways. The timing to peak amplitude, the key feature we wanted to isolate in the InSAR data, near Visalia was interpreted as a pressure pulse front associated with river-sourced recharge propagating into the San Joaquin Valley. This study further validated the potential of InSAR, coupled with AEM data, to map and monitor river-sourced recharge in aquifer systems. As InSAR data become more accessible, this approach holds promise for broader applications in groundwater science and management worldwide.
Quantifying albedo impact and radiative forcing of management practices in European wheat cropping systems
Authors: Yu Ke , Su Yang , Ciais Philippe , Lauerwald Ronny , Ceschia Eric , Makowski David , Xu Yidi , Abbessi Ezzeddine , Bazzi Hassan , Tallec Tiphaine , Brut Aurore , Heinesch Bernard , Brümmer Christian , Schmidt Marius , Acosta Manuel , Buysse Pauline , Gruenwald Thomas , Goll Daniel S 
Published: June 2024

Abstract
Management practices that increase the surface albedo of cultivated land could mitigate climate change, with similar effectiveness to practices that reduce greenhouse gas emissions or favor natural CO2 sequestration. Yet, the efficiency of such practices is barely quantified. In this study, we quantified the impacts of seven different management practices on the surface albedo of winter wheat fields (nitrogen fertilizer, herbicide, fungicide, sowing, harvest, tillage, and crop residues) by analyzing observed daily albedo dynamics from eight European flux-tower sites with interpretable machine learning. We found that management practices have significant influences on surface albedo dynamics compared with climate and soil conditions. The nitrogen fertilizer application has the largest effect among the seven practices as it increases surface albedo by 0.015 ± 0.004 during the first two months after application, corresponding to a radiative forcing of −4.39 ± 1.22 W m−2. Herbicide induces a modest albedo decrease of 0.005 ± 0.002 over 150 d after application by killing weeds in the fallow period only, resulting in a magnitude of radiative forcing of 1.33 ± 1.06 W m−2 which is higher than radiative forcing of other practices in the same period. The substantial temporal evolution of the albedo impacts of management practices increases uncertainties in the estimated albedo-mediated climate impacts of management practices. Although these albedo effects are smaller than published estimates of the greenhouse gas-mediated biogeochemical practices, they are nevertheless significant and should thus be accounted for in climate impact assessments.
Design of photonic topological corner states for electrically pumped terahertz quantum cascade laser
Authors: Li Jixin , Liu Yiying , Zeng Yongquan , Zheng Bin , Chen Hongsheng , Han Song 
Published: June 2024

Abstract
Photonic topological corner states (PTCS) represent discrete zero modes whose frequencies stay in the topological bandgap and wavefunctions exhibit strong spatial localization, which is highly desirable for efficient surface-emitting lasers. While being extensively investigated in optically pumped lasers, the electrically pumped PTCS lasers are merely reported due to the lack of suitable configurations. In this paper, we propose a photonic cavity design based on the PTCSs that can be applied for electrically pumped terahertz quantum cascade lasers (QCLs). The cavity is constructed by following the canonical trivial-nontrivial domain, where the nontrivial domain with expanded and merged four QCL rods is surrounded by the trivial domain with shrunk and merged four QCL rods. Both domains follow the 2D Su–Schrieffer–Heeger (SSH) model. To further construct a fabrication-favorable 3D device, the designed QCL rod array is connected by 2D veins, which functionalize simultaneously as the intermedium for enhanced inter-/intra-cell coupling and the conductive connection to the device. The 3D numerical calculation is finally investigated.
Ab-Initio study of substitution at alkaline earth site on quaternary Heusler alloys LiXNiSb
Authors: Kumar Jagdish , Kumar Manish , Raman D K , Pal Anand 
Published: June 2024

Abstract
In this study, we have studied the quaternary Heusler alloys with the formula LiXNiSb (X = Be, Mg, Ca, Sr, Ba) to investigate the effect of alkaline earth elements at the X site. We explored the structural, lattice dynamics, electronic, and magnetic properties by employing the density functional theory framework in FPLAPW formalism. All the studied alloys are nonmagnetic with no magnetic moment on the Ni atom. LiBeNiSb and LiBaNiSb are dynamically unstable and exhibit imaginary phonon frequencies. The lattice constant of the studied alloys systematically increases with the size of the alkaline earth element, whereas the bulk modulus decreases. Among the stable alloys, LiMgNiSb is metallic, whereas LiCaNiSb and LiSrNiSb are semiconducting with band gap values of 0.43 and 0.34 eV, respectively. The lattice specific heat and optical properties of the semiconducting alloys have also been computed. Our results demonstrate that the studied LiXNiSb alloys can be good candidates for photovoltaic applications.
A strategic approach to sustainable wastewater management and reuse in Saudi Arabia
Authors: Haider Husnain , Ghumman Abdul Razzaq , Al-Salamah Ibrahim Saleh , Alharbi Abdulaziz , EL-Ghoul Yassine , Martuza Muhammad Ali 
Published: June 2024

Abstract
The Kingdom of Saudi Arabia (KSA) faces challenges in protecting its limited natural water resources. The centralized sewage treatment plants (STPs) contribute to conserving natural water resources in various regions of KSA. For sustainable wastewater management strategies in arid environments, the performance of STPs needs to be assessed for various beneficial uses in addition to the existing regulations. The present study used extensive effluent quality data of four STPs to develop a performance assessment approach using multi-criteria and principal component analyses. The performance levels were derived from the compliance rate of effluent standards with different reuses and the efficacy of biosolids management. The proposed approach evaluated the STPs based on the planned applications of treated effluents, considering the land use characteristics of each plant’s disposal point. The factors loadings obtained for the STPs, encompassing total suspended and dissolved solids, and total dissolved solids, oxidizing demanding pollutants (BOD and COD), and nutrients (NO3 and PO4), with 3 to 4 principal components demonstrating above 60% of the effluent monitoring data, established the importance of the effluent quality parameters. The effluent quality index (EQI) was developed for existing and potential reuses, e.g., irrigation, landscaping, fishery, and recreation, during dry (summer) and wet (winter) periods. All STPs showed high EQI for both periods for the present reuse standards of unrestricted irrigation and landscaping. The overall performance index, aggregating EQI and the efficacy of sludge management practices, illustrated declining performance, suggesting staged improvements (tertiary-level treatment, air floatation, sludge digestion, and waste-to-energy) through a periodic assessment process. STPs must enhance their sludge management efficacy to produce Class-A biosolids and waste-to-energy. The proposed approach will help make strategic decisions regarding improvements for STPs and the allocation of financial resources to protect natural resources in various regions across KSA.
A lightweight convolutional neural network for working condition intelligent diagnosis of pumping units
Authors: Pan Shenghu , Ling Qiaomei , Tu Lei 
Published: June 2024

Abstract
Accurate diagnosis of pumping unit working conditions and prompt fault resolution are vital for ensuring safe production in oilfields. In response to the limitations of traditional convolutional neural networks in diagnosing pumping unit working conditions, a lightweight convolutional neural network is proposed. This network addresses the challenges of shallow networks, which cannot effectively extract indicator diagram features, and deep networks, which suffer from excessive parameterization and high redundancy. Firstly, the combination of depthwise separable convolution and dilated convolution efficiently extracts the contour features of the indicator diagram while reducing the model’s parameter count. Additionally, the Attention Embedded Atrous Spatial Pyramid Pooling and the coordinate attention mechanism are incorporated to further capture the shape and position information of indicator diagram lines. The experimental results demonstrate that the proposed lightweight network has 1.26 M parameters and storage size of 4.82 M. Compared to ResNet-50, VGG-16, and MobileNet-V2, its parameter count and storage size are approximately 1/18, 1/11, and 1/2, respectively, making it easily deployable on hardware-limited diagnostic platforms. Moreover, with an average diagnostic accuracy of 98.17%, surpassing existing networks, it enables more effective diagnosis of pumping unit working conditions, thereby enhancing the reliability and accuracy of pumping unit operational monitoring.
Transition metal sulfide nanostructures: synthesis and application in metal-air batteries
Authors: Marimuthu Sundaramoorthy , Kannan Palanisamy , Maduraiveeran Govindhan 
Published: June 2024

Abstract
Owing to great energy density, eco-friendliness, safety and security, and cost-effectiveness, rechargeable metal–air batteries (MABs) have engrossed substantial devotion. The MABs signify one of the most feasible forthcoming alternatives to powering electric vehicles (EVs) and smart-grid energy storage. The progress of MABs has offered a solution benefitting from its much higher theoretical energy density than that of lithium-ion batteries (LIB). However, certain technical difficulties allied with metal–air batteries include sluggish electrochemical oxygen reaction kinetics that has yet to be fixed. The transition single metal and mixed metals sulfides (TMS) nanostructures have validated an advanced electrocatalytic oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) performance, due to their higher electronic conductivity and fast-charge transfer kinetics. The bifunctional electrocatalytic act of the TMSs can be enhanced by altering the electronic configuration, double layer structure and interface, valence state, and vacancies. In this minireview, the preparation, properties, and testing of electrode components of transition metal sulfides (TMS) nanomaterials towards different types of metal–air batteries (aqueous and non-aqueous), the fundamentals, configuration of battery, choice of electrode materials, electrolyte, and separator, current challenges as well as perspectives of the design of high-performance MABs are also discussed based on the existing execution.
Stochastic equations of motion
Authors: Abraham Nitzan 
Published: June 2024

Abstract
This chapter introduces several types of stochastic equation of motion and discusses their solutions. (1) The Langevin equation. (2) Master equations. (3) Counting statistics. (4) Markovian and non-Markovian time evolution. (5) The Chapman–Kolmogorov equation, Fokker–Planck equation and Smoluchowski equation. (6) Passage time distributions and the mean first passage time.