bluuebunny/crossref_metadata_2025 huggingface dataset:
The safe withdrawal rate: evidence from a broad sample of developed markets
Authors: Anarkulova Aizhan , Cederburg Scott , O’Doherty Michael S. , Sias Richard
Published: February 2025

We use a comprehensive new dataset of asset-class returns in 38 developed countries to examine a popular class of retirement spending rules that prescribe annual withdrawals as a constant percentage of the retirement account balance. A 65-year-old couple willing to bear a 5 percent chance of financial ruin can withdraw just 2.31 percent per year, a rate materially lower than conventional advice (e.g., the 4% rule). Our estimates of failure rates under conventional withdrawal policies have important implications for individuals (e.g., savings rates, retirement timing, and retirement consumption), public policy (e.g., participation rates in means-tested programs), and society (e.g., elderly poverty rates).
PyReX: A Recursion Based Crossover Detection Algorithm in Python for Along‐Track Geophysical Measurements
Authors: Vikram K. V. N. G. , Krishna D. V. P. , Sreejith K. M.
Published: February 2025

A crossover point is the location of intersection of any two ground tracks charted by multiple platforms (ships, satellite radar and laser altimeters etc.). Detection of crossovers is of prime importance to estimate the discrepancies in the geophysical measurements at the crossover points. Usual approach of crossover detection considers consecutive data points in tracks as segments and checks for intersections between all combinations of these segments. We present a Recursion based crossover detection algorithm in Python (PyReX) for rapid detection of crossovers by avoiding redundant intersection checks. We test the performance of this algorithm using along‐track sea surface height measurements from satellite altimeters. We observe that the time taken for flagging a crossover between pair of tracks with N segments each varies as vis‐a‐vis the dependency associated with the traditional methods. We further demonstrate that PyReX significantly improves the computation speed for high frequency along‐track measurements from satellite altimeters and ship‐borne gravity data compared to existing algorithms. PyReX is a flexible, open‐source code that could be easily customized for variety of applications involving large‐scale track‐line data sets.
Calibrating Strain Measurements: A Comparative Study of DAS, Strainmeter, and Seismic Data
Authors: Chien Chih‐Chieh , Gerstoft Peter , Hatfield William , Hollberg Leo , Lipovsky Bradley P. , Manos John‐Morgan , Mellors Robert J. , Winebrenner Dale P. , Zumberge Mark A.
Published: February 2025

Significant interest has developed in using optical fibers for seismology through Distributed Acoustic Sensing (DAS). However, converting DAS strain measurements to actual ground motions can result in errors and uncertainties due to imperfect coupling of the fiber to the earth and instrument response functions. To address this, we conducted a comparative analysis of strain data recorded by DAS, Optical Fiber Strainmeters (OFSs), and estimates derived from seismic data. This study used dark fibers in a commercial cable connecting two islands in Puget Sound, Washington, USA. The cable extends from a telecommunication substation on Whidbey Island, through an underground conduit, and across Saratoga Passage to Camano Island. The strain along the cable was recorded using OFS Michelson interferometers and a DAS interrogator, with a broadband seismometer positioned at one end. Comparing a teleseismic earthquake recording showed that summed DAS channels agreed well with OFS recordings. The amplitude discrepancies between the measurements and the seismometer's estimated strain indicated poor coupling between the cable and the earth. We also evaluated DAS amplitude response using a piezoelectric cylinder (PZT) to generate ground truth strain. The findings revealed a notable amplitude decrease in DAS recordings at lower frequencies, highlighting the need for amplitude calibration. Moreover, some underwater signals in the study area were strongly correlated with the velocity of the tidal current. These signals can be localized through coherence calculations between the DAS and OFS recordings.
Cross‐Attractor Transforms: Improving Forecasts by Learning Optimal Maps Between Dynamical Systems and Imperfect Models
Authors: Agarwal N. , Amrhein D. E. , Grooms I.
Published: February 2025

Biased, incomplete numerical models are often used for forecasting states of complex dynamical systems by mapping an estimate of a “true” initial state into model phase space, making a forecast, and then mapping back to the “true” space. While advances have been made to reduce errors associated with model initialization and model forecasts, we lack a general framework for discovering optimal mappings between “true” dynamical systems and model phase spaces. Here, we propose using a data‐driven approach to infer these maps. Our approach consistently reduces errors in the Lorenz‐96 system with an imperfect model constructed to produce significant model errors compared to a reference configuration. Optimal pre‐ and post‐processing transforms leverage “shocks” and “drifts” in the imperfect model to make more skillful forecasts of the reference system. The implemented machine learning architecture using neural networks constructed with a custom analog‐adjoint layer makes the approach generalizable across applications.
Explanation and Optimizing Multi‐Model Blending Algorithm Using Random Variables Theory
Authors: Wang Yu , Cao Yong , Shen Yue , Zhao Ruixia , Zeng Xiaoqing , Yao Li , Dai Kan
Published: February 2025

In this study, we modeled the multi‐model blending process using random variables and explicitly derived the distribution of the blended forecast error under the assumption of normally distributed errors. Utilizing this error distribution, we regained the scalar version of the Best Linear Unbiased Estimator. Notably, the model yielded negative weights, which contradict traditional assumptions that weights should be positive. To address this, we modified the algorithm to set negative weights to zero and compared the performance with the original algorithm. Our findings indicate that setting negative weights to zero results in a slight improvement in blending performance compared to using negative weights directly. This improvement may be attributed to modeling the actual forecast error as a normally distributed unified parameter and applying a consistent correlation coefficient across the annual data set.
PEGSGraph: A Graph Neural Network for Fast Earthquake Characterization Based on Prompt ElastoGravity Signals
Authors: Hourcade Céline , Juhel Kévin , Bletery Quentin
Published: February 2025

State‐of‐the‐art earthquake early warning systems use the early records of seismic waves to estimate the magnitude and location of the seismic source before the shaking and the tsunami strike. Because of the inherent properties of early seismic records, those systems systematically underestimate the magnitude of large events, which results in catastrophic underestimation of the subsequent tsunamis. Prompt elastogravity signals (PEGS) are low‐amplitude, light‐speed signals emitted by earthquakes, which are highly sensitive to both their magnitude and focal mechanism. Detected before traditional seismic waves, PEGS have the potential to produce unsaturated magnitude estimates faster than state‐of‐the‐art systems. Accurate instantaneous tracking of large earthquake magnitude using PEGS has been proven possible through the use of a Convolutional Neural Network (CNN). However, the CNN architecture is sub‐optimal as it does not allow to capture the geometry of the problem. To address this limitation, we design PEGSGraph, a novel deep learning model relying on a Graph Neural Network (GNN) architecture. PEGSGraph accurately estimates the magnitude of synthetic earthquakes down to 7.6–7.7 and determines their focal mechanisms (thrust, strike‐slip or normal faulting) within 70 s of the event's onset, offering crucial information for predicting potential tsunami wave amplitudes. Our comparative analysis on Alaska and Western Canada data shows that PEGSGraph outperforms PEGSNet, providing more reliable rapid magnitude estimates and enhancing tsunami warning reliability.
“QuanTour” illuminates Europe with single photons: celebrating the International Year of Quantum Science and Technology 2025
Authors: Ding Fei
Published: February 2025

Witness the journey of a solid-state quantum light source travelling across Europe and beyond—like an Olympic torch relay in the quantum realm.
Induction chemotherapy followed by camrelizumab plus apatinib and chemotherapy as first-line treatment for extensive-stage small-cell lung cancer: a multicenter, single-arm trial
Authors: Liu Ming , Qiu Guihuan , Guan Wenhui , Xie Xiaohong , Lin Xinqing , Xie Zhanhong , Zhang Jiexia , Qin Yinyin , Du Haijian , Chen Xin , Deng Yu , Li Shiyue , Zhong Nanshan , Zhou Chengzhi
Published: February 2025

Chemo-immunotherapy is the current first-line treatment for patients with extensive-stage small cell lung cancer (ES-SCLC), but survival benefits are modest. We aimed to evaluate the safety, antitumor activity and biomarkers of first-line camrelizumab and apatinib plus chemotherapy in untreated ES-SCLC patients. In this single-arm trial (ClinicalTrials.gov NCT05001412), eligible patients received 2 cycles of etoposide and carboplatin (EC) as induction treatment followed by 2–4 cycles of camrelizumab, apatinib plus EC, then maintenance camrelizumab plus apatinib. Primary endpoint was safety. Secondary endpoints included objective response rate (ORR), duration of response, progression-free survival (PFS), and overall survival (OS). Targeted sequencing and whole transcriptome sequencing were performed to explore biomarkers. All enrolled 40 patients were treated and analyzed for safety. During the entire treatment, treatment-emergent adverse events (TEAEs) occurred in 40 patients (100%), and 30 (75.0%) were grade ≥3. The most common grade ≥3 TEAEs were neutropenia (35.0%), anemia (15.0%) and increased alanine aminotransferase (15.0%). No treatment-related deaths occurred. Among 36 evaluable patients, ORR was 88.9% (95% CI: 73.9%–96.9%), median PFS was 7.3 months (95% CI: 6.6–9.2) and median OS was 17.3 months (11.8-not reached). Mutations in RB1, high levels of tumor mutation burden, natural killer cells, and interferons, and low levels of cancer-associated fibroblasts, correlated with prolonged PFS. Induction chemotherapy followed by camrelizumab, apatinib plus EC demonstrated acceptable safety and promising antitumor activity in untreated ES-SCLC patients. The identified biomarkers need further validation.

Trial Registration ClinicalTrials.gov Identifier: NCT05001412.
Updated MDSGene review on the clinical and genetic spectrum of LRRK2 variants in Parkinson´s disease
Authors: Krüger Clara , Lim Shen-Yang , Buhrmann Alissa , Fahrig Fenja L. , Gabbert Carolin , Bahr Natascha , Madoev Harutyun , Marras Connie , Klein Christine , Lohmann Katja
Published: February 2025

Pathogenic variants in the LRRK2 gene are one of the most commonly identifiable monogenic causes of Parkinson´s disease (PD, PARK-LRRK2). This systematic MDSGene literature review comprehensively summarizes published demographic, clinical, and genetic findings related to LRRK2 variants (https://www.mdsgene.org/). Data on 4660 individuals with 283 different variants were curated. The median age at onset in the PD patients with available information was 56 years, notably, with approximately one-third having PD onset <50 years. Tremor was the most frequently reported initial symptom and more common than reported in other dominantly inherited forms of PD. Of the 211 potentially PD-causing variants, 25 were classified as pathogenic or likely pathogenic, and the remaining 186 (88.2%) were variants of uncertain significance. p.G2019S was the most frequently reported pathogenic variant, followed by p.R1441G and p.R1441C. This systematic review represents the most extensive database on PARK-LRRK2 to date and provides a vital resource to improve precision medicine.
A high-performance X-ray detector based on large-size perovskite MAPbI3 single crystals grown by environmentally friendly solvents and advanced systems
Authors: Li Xiangting , Yang Mengke , Li Zhuoyue , Ma Yundong , Sun Yuanlong , Zhang Min , Zheng Guozong , Hu Ziyu
Published: February 2025

Our work provides a more environmentally friendly method for high-quality PSCs manufacturing, with great potential in large-scale crystal growth and application.
Thermoelectric and thermal properties of molecular junctions: mechanisms, characterization methods and applications
Authors: Fang Chao , Li Yuting , Wang Siwen , Liang Mingchen , Yan Chenshuai , Liu Junyang , Hong Wenjing
Published: February 2025

Thermal and thermoelectric transport in molecular junctions is reviewed, covering quantum mechanisms, characterization methods and applications.
Improving thermal expansion coefficients and mechanical properties of interconnect copper by doping Al2O3 nanoparticles: insights from atomistic simulations
Authors: Zhang Tianyu , Wu Yunwen , Ju Shenghong
Published: February 2025

This study improves the thermal expansion and mechanical properties of interconnect copper by introducing Al2O3 nanoparticles, and investigates different doping configurations to understand the thermal expansion mechanisms in Cu–Al2O3 nanocomposites.
Review on the optical and electrical properties of chalcogenide thin films: challenges and applications
Authors: Abd El-Ghany W. A.
Published: February 2025

A schematic diagram of thin film deposition techniques.
The electrochemical role of the SEI in Li-ion batteries and design principles for electrode surface modification
Authors: Ikeshoji Tamio , Ishino Seiichiro , Kaneko Toshihiro , Itoh Takanori
Published: February 2025

Full solvation in the transition state on the LiF cluster gives lower activation energy for Li transfer at equilibrium potential.
Synthesis, Spectral, and Electrochemical Studies of Electron-Deficient Nitrile Porphyrins and the Utilization in Selective Cyanide Sensing
Authors: Bhardwaj Varusha , Sankar Muniappan
Published: February 2025

Two series of β-cyano-substituted porphyrins, MTPP(CN)X (where M = 2H, Co(II), Ni(II), Cu(II), Zn(II) and X = 1 or 2, were synthesized and thoroughly characterized using a range of spectroscopic...
Recent strategies for controlling the white mould fungal pathogen (Sclerotinia sclerotiorum) using gene silencing, botanical fungicides and nanomaterials
Authors: Ajiboye Timothy O. , Visser H. G. , Erasmus E. , Schutte-Smith M.
Published: February 2025

Sclerotinia sclerotiorum is a fungal pathogen that causes white mould diseases in several plants of economic importance.
Relationships of sarcopenia symptoms and dietary patterns with lung cancer risk: a prospective cohort study
Authors: Zhou Huijun , Liu Fubin , Xu Jingyi , Wang Xixuan , Peng Yu , Wang Peng , Si Changyu , Gong Jianxiao , Gu Jiale , Qin Ailing , Song Fangfang
Published: February 2025

Sarcopenia symptoms may serve as risk factors for lung cancer among the general population. Adopting a dietary pattern rich in whole grains could be a novel approach to improve sarcopenia and adverse lung-cancer related outcomes.
Regulating intermolecular interactions for stable multifunctional organic–inorganic metal halide hybrid glasses
Authors: Jiang Chunyan , Yan Jing , Qiu Jianrong , Wu Mingmei , Xu Beibei
Published: February 2025

A new concept of modulating intramolecular interactions was proposed to achieve high glass-formation ability and tunable crystallization in OIMH glass.
Experimental and computational insights into CuS–Mg composites for high-performance p-type transparent conducting materials
Authors: Lie Stener , Sun Qingde , Mishra Pritish , Li Patrick Wen Feng , Sadhu Anupam , Salim Teddy , Li Shuzhou , Hautier Geoffroy , Wong Lydia Helena
Published: February 2025

Mg incorporation in CuS enhances transparency and conductivity for p-type TCMs. We investigate its optical, electrical, and chemical properties and demonstrate p–n junction diodes, highlighting its potential for semiconductor applications.
An ultra-violet and infrared dual-band photodetector using a Ga2O3 thin film and HgTe colloidal quantum dots
Authors: Zheng Qiqi , Yang Yu , Li Liansheng , Xu Qing-An , Zhang Kenan , Xue Xiaomeng , Ma Lisha , Yu Jianhao , Li Wanjun , Chen Menglu
Published: February 2025

An ultraviolet and infrared dual band photodetector was developed by integrating a solar-blind ultraviolet photoconductive amorphous Ga2O3 film and a short-wave infrared photoconductive HgTe colloidal quantum dot film.
A comparative study of the hot electron energy loss rate in zinc- and cadmium compound quasi-two-dimensional materials
Authors: Phuong Thuy Huynh Thi , Hien Nguyen Dinh
Published: February 2025

The hot electron energy loss rate exhibits the largest value and fastest increase for ZnS, followed by CdS, ZnSe, CdSe, and ZnTe, while it shows the smallest value and slowest increase for CdTe.
Growing and nanomanipulating heterostructures of α-bismuthene in a nearly isolated state
Authors: Martínez-Galera Antonio J. , Gómez-Rodríguez José M.
Published: February 2025

α-Bismuthene heterostructures, which demonstrate one of the weakest couplings between adjacent materials, are grown in situ under ultrahigh vacuum (UHV) conditions and are characterized and nanomanipulated using scanning tunneling microscopy (STM).
Exploring piezoelectric and piezophototronic properties of nanostructured LN-ZnSnS3 for photoresponsive vibrational energy harvesting
Authors: Das Surajit , Paul Swadesh , Datta Anuja
Published: February 2025

Piezoelectric and piezophototronic properties are reported from solution-processed LN-type ZnSnS3 nanocrystals for light-induced self-powered mechanical energy harvesting.
The role of lipid phase and temperature in proton barrier and proton migration on biological membranes
Authors: Ramanthrikkovil Variyam Ambili , Rzycki Mateusz , Nandi Ramesh , Stuchebrukhov Alexei A. , Drabik Dominik , Amdursky Nadav
Published: February 2025

Using a membrane-tethered light-gated transient proton donor probe, we reveal the role of the membrane phase and composition in dictating the membrane's proton transfer efficiency, the proton diffusion dimensionality, and the proton barrier.
Design of thick electrodes for high-performance lithium-ion batteries: a comprehensive perspective under coupled kinetics and thermodynamics
Authors: Fu Kang , Sun Kai , Li Xueyan , Yang Haosong , He Xingmin , Zhai Shoubao , Gong Lili , Tan Peng
Published: February 2025

The latest progress in the field of thick electrodes is comprehensively reviewed considering the coupled kinetics and thermodynamics.
Predicting self-assembly of sequence-controlled copolymers with stochastic sequence variation
Authors: Curtis Kaleigh A. , Statt Antonia , Reinhart Wesley F.
Published: February 2025

Molecular dynamics simulations of ensembles of sequence-controlled copolymers with stochastic sequence variation are performed and analyzed by machine learning.
Demixing of an active-passive binary mixture through a two-dimensional elastic meshwork
Authors: Yadav Ramanand Singh , Chakrabarti Rajarshi
Published: February 2025

A monodisperse mixture of active and passive particles can be separated using an elastic meshwork with a mesh size smaller than the particle size.
Nanowire morphology control in Sb metal-derived antimony selenide photocathodes for solar water splitting
Authors: Wang Zhenbin , Gan Yongping , Service Erin , Adams Pardis , Moehl Thomas , Niu Wenzhe , Tilley S. David
Published: February 2025

Sb2Se3 photocathode performance improves by tuning substrate temperature during Sb metal deposition. Thinner nanorods result in reduced charge recombination, enhancing photocurrent by restricting charge transport in the hk0 direction.
Enhanced P-type conductivity in Sb2Se3 through alkali and alkaline earth metal doping
Authors: Cho Eunkyung , Sung Shi-Joon , Yang Kee-Jeong , Lee Jaebaek , Hoang Van-Quy , Kadiri-English Bashiru , Hwang Dae-Kue , Kang Jin-Kyu , Kim Dae-Hwan
Published: February 2025

Doping of alkaline earth atoms significantly increases p-type conductivity of antimony selenide (Sb2Se3) compared to the undoped system due to the presence of shallow, low-energy, and hole-generating acceptor defects.
Efficient NIR-OLEDs based on color-purity near-infrared (NIR) tris-/bis-heteroleptic iridium(iii) complexes with a single color-responsible ligand
Authors: Chen Youquan , Hou Siyu , Zhang Yan , Tan Mingfeng , Lü Xingqiang , Fu Guorui , Wong Wai-Yeung
Published: February 2025

Based on the [Ir(dpbq)(iqbt)(pbi)] (2), ηMaxEQE = 1.824% (788 nm) and RCMax = 591 mW sr−1 m−2 V−1 for its color-purity NIR-OLED-2 were obtained.
Teaching copolymerization catalysis to metal–organic frameworks by confining molecular catalysts in lattices
Authors: Chiu Chao-Yu , Lin Chia-Her , Wu Pei-Wen , Tegudeer Zhuorigebatu , Tsai Chen-Yen , Gao Wen-Yang
Published: February 2025

Lattice-confinement of catalytically active molecular complexes enables metal–organic frameworks to accomplish new copolymerization reactions that were challenging previously.
Correction: Designing potentially singlet fission materials with an anti-Kasha behaviour
Authors: Pino-Rios Ricardo , Báez-Grez Rodrigo , Szczepanik Dariusz W. , Solà Miquel
Published: February 2025

Correction for ‘Designing potentially singlet fission materials with an anti-Kasha behaviour’ by Ricardo Pino-Rios et al., Phys. Chem. Chem. Phys., 2024, 26, 15386–15392, https://doi.org/10.1039/D4CP01284D.
Efficient hydrosilylation of carbonyls by zinc alkyl complexes supported by flexible amidophosphinochalcogenide ligands
Authors: Bano Kulsum , Ravi Kumar  , Jain Archana , Panda Tarun K.
Published: February 2025

A facile mono- and di-hydrosilylation of various carbonyls is reported under mild reaction conditions to afford silyl ether-protected alcohols in a single step using novel zinc complexes supported by amidophosphinochalcogenide ligand moieties.
Reusable cobalt–copper-catalyzed cross-coupling of (hetero)aryl halides with primary amides under air: investigating a new Co0/CoII-based catalytic cycle
Authors: Saha Anay , Roy Keya , Mondal Sampa , Saha Bijay , Sumar Jayabrata , Sahu Sumanta Kumar , Adak Laksmikanta
Published: February 2025

An efficient ligand-free cobalt–copper-catalyzed cross-coupling reaction of aryl halides with primary amides has been reported under aerobic conditions, and a new Co0/CoII-based catalytic cycle for this transformation is also investigated.
Correction: Enhancing the antibacterial efficacy of vancomycin analogues: targeting metallo-β-lactamases and cell wall biosynthesis
Authors: Sarkar Paramita , Xu Weipan , Vázquez-Hernández Melissa , Dhanda Geetika , Tripathi Shubhandra , Basak Debajyoti , Xie Hexin , Schipp Lea , Dietze Pascal , Bandow Julia E. , Nair Nisanth N. , Haldar Jayanta
Published: February 2025

Correction for ‘Enhancing the antibacterial efficacy of vancomycin analogues: targeting metallo-β-lactamases and cell wall biosynthesis’ by Paramita Sarkar et al., Chem. Sci., 2024, 15, 16307–16320, https://doi.org/10.1039/D4SC03577A.
Contrastive learning for nested Chinese Named Entity Recognition via template words
Authors: Wang Yuke , Liu Qiao , Dai Tingting , Lang Junjie , Lu Ling , Chen Yinong
Published: February 2025

Existing Chinese named entity recognition (NER) research utilises 1D lexicon‐based sequence labelling frameworks, which can only recognise flat entities. While lexicons serve as prior knowledge and enhance semantic information, they also pose completeness and resource requirements limitations. This paper proposes a template‐based classification (TC) model to avoid lexicon issues and to identify nested entities. Template‐based classification provides a template word for each entity type, which utilises contrastive learning to integrate the common characteristics among entities with the same category. Contrastive learning makes template words the centre points of their category in the vector space, thus improving generalisation ability. Additionally, TC presents a 2D table‐filling label scheme that classifies entities based on the attention distribution of template words. The proposed novel decoder algorithm enables TC recognition of both flat and nested entities simultaneously. Experimental results show that TC achieves the state‐of‐the‐art performance on five Chinese datasets.
Co‐simulations of induction machines coupled with a radial ball bearing for mechanical defects analysis
Authors: El Bouharrouti Nada , Sitnikov Maksim , Hemeida Ahmed , Martin Floran , Kudelina Karolina , Naseer Muhammad U. , Belahcen Anouar
Published: February 2025

In this paper, two co‐simulations are introduced to study the behaviour of a 2‐D finite‐element model and a magnetic equivalent model of an induction machine, both coupled with a mechanical radial ball bearing model. This comprehensive approach allows for the generation of synthetic vibration and current signals of a ball bearing mounted on a shaft, taking into account the entire machinery. The study investigates the misalignment effect caused by an inner ring defect in a ball bearing, analysing its impact on the current of the IM models. Likewise, the effects of eccentricity in the induction machine models on rotor vibration are studied through their coupling with the mechanical ball bearing model. This multiphysics co‐simulation provides a novel numerical application to generate data relative to mechanical defects in induction machines. By using this coupled method, an inner ring defect of 1 mm depth and 3 mm length in the bearing model is accurately identified in the frequency spectrum of the stator current, whereas eccentricity faults for levels ranging between 5% and 40% are detected in the vibration spectrum of the ball bearing. The findings are accurately supported by related theory, and further validated through experimental verification for the case of the inner ring fault.
A Stackelberg game‐based model for low‐carbon scheduling of commercial building loads considering lifecycle unit carbon‐emission factors
Authors: Huang Qifeng , Zhuang Zhong , Duan Meimei , Yang Shihai , Sheng Ju , Huang Yixuan
Published: February 2025

The accelerated growth of smart cities and the intensifying impact of climate change have introduced new demands for low‐carbon commercial buildings. The majority of existing low‐carbon scheduling methods for commercial buildings focus on operational carbon emissions embedded in consumed electricity from the electricity network without a lifecycle perspective, resulting in the underestimation of the carbon emissions of consumed electricity. This article proposes a Stackelberg game model for low‐carbon scheduling of commercial building loads. In this model, the lifecycle unit carbon‐emission factors are calculated and then transferred to commercial buildings employing the carbon‐emission flow method. Subsequently, a low‐carbon scheduling model considering the carbon transaction, demand response, and thermal comfort is established for commercial building loads. Finally, the Stackelberg game model is implemented to determine the interaction between commercial buildings and the electricity network. The case study indicates that approximately 23% of indirect carbon emissions from electricity used in commercial buildings originate from the extraction, construction, transportation, demolition, and recycling stage, while approximately 77% occur during the operation stage.
A methodology for estimating radiofrequency signal attenuation from rainfall and atmospheric gases in 5G‐and‐beyond networks
Authors: Batista Andreza P. , Ayub Muhammad S. , Adasme Pablo , Begazo Dante C. , Shad Muhammad R. , Saadi Muhammad , Rosa Renata L. , Rodríguez Demóstenes Z.
Published: February 2025

Industrial applications demand ultra‐reliable and low latency communications, especially in Industrial Internet of Things (IIoT) environments. To meet these expectations, telecommunication network technologies have evolved, culminating in the deployment of fifth‐generation (5G) networks by telecom operators worldwide. However, 5G and beyond networks, operating in millimetre‐wave frequency bands, can suffer signal degradation caused by atmospheric phenomena, such as rainfall and atmospheric gases. This article presents a significant contribution to scientific research by proposing a methodology that leverages ITU‐R recommendations (P.530, P.837, P.838, P.618‐13, P.839‐4, P.1511‐2) for rain‐induced attenuation and incorporates local meteorological data using the Gumbel Distribution. Also, the methodology considers ITU‐R Recommendations (P.676, P.836, P.835) for atmospheric gas‐induced attenuation. A comprehensive flowchart demonstrates the practical application of these recommendations, enabling accurate assessment of signal attenuation for various cities around the world with distinct geographical coordinates. The dataset is obtained from local Meteorological Stations or using digital maps from ITU recommendations. The results obtained with the approximate values of precipitation rates using the proposed method were compared with values from the ITU's study group and verified the effectiveness of the proposed approach, with relative errors not exceeding 1.07%. These analyses indicated the potential impact of atmospheric conditions on 5G network performance, offering valuable insights for optimising network design and improving communication reliability that is relevant to IIoT applications.
Optimizing Data Integrity and Efficiency: Advances and Applications of Pyramid Coding
Authors: Chen Zhenbo
Published: February 2025

The rapid expansion of data in the digital era poses significant challenges in maintaining data integrity and optimizing transmission efficiency. Pyramid codes, an advanced data encoding technique, leverage a multi-level structure to enhance storage efficiency and facilitate efficient data handling. This paper explores pyramid codes as a dynamic solution for data redundancy, detailing their encoding and decoding principles, repair functions, and applications across various sectors including wireless communication, medical imaging, and big data management. Unlike traditional erasure codes, pyramid codes offer superior fault tolerance and recovery capabilities through a hierarchical design that supports minimal overhead in recovering from multiple data failures. The methodology improves upon Reed Solomon codes by offering higher data storage efficiency and the ability to recover after extensive data loss. Additionally, the potential applications of pyramid codes in cloud computing and distributed environments are examined, showcasing their adaptability to complex storage systems and fluctuating data loss scenarios. This study aims to illuminate the role of pyramid codes in advancing data storage and transmission technologies, thus contributing to more robust and efficient data management practices.
Enhancing Data Recovery in RAID6: A Comparative Analysis of Row-Diagonal Parity Codes
Authors: Zhang Wenxu
Published: February 2025

RAID6 systems, known for their robust data protection and redundancy capabilities, encounter challenges in data recovery efficiency and computational complexity. This study investigates the efficacy of Row- Diagonal Parity (RDP) codes within RAID6 frameworks, emphasizing their ability to recover from dual disk failures. The exploration includes a detailed examination of the encoding and decoding processes of RDP codes, employing concrete examples to demonstrate these techniques. Comparative analysis highlights the computational advantages of RDP codes over traditional methods such as Reed-Solomon and EVENODD Codes. Findings reveal that RDP codes not only reduce computational complexity but also enhance data recovery speed significantly. Given these attributes, RDP codes offer a promising solution for large-scale data environments demanding high reliability and swift recovery. This approach markedly improves RAID6's functionality by optimizing recovery processes, thus supporting high-volume storage systems with stringent data integrity requirements. The potential for future enhancements in RAID6 data recovery through further research into hardware acceleration and artificial intelligence is also acknowledged, aiming to refine recovery times and efficiency in large-scale storage applications.
Análisis de errores de estudiantes francófonos en español con fines específicos (EFE)
Authors: Montero Rafael Cuevas
Published: February 2025

En el presente estudio se analizan situaciones comunicativas simuladas en parejas en las que participan estudiantes
francófonos de ELE con sus profesores. Esta actividad pedagógica se ha llevado a cabo a través de llamadas telefónicas con el fin de
evaluar tanto la interacción oral como la capacidad de improvisación y anticipación de los discentes en el contexto profesional turístico.
Nuestro instrumento de investigación es un corpus de lengua oral en el que se han compilado los errores lingüísticos cometidos. Por
tanto, nuestro objetivo principal consiste en clasificar e identificar el origen de dichos errores a partir de su lengua materna, el
francés.
Análisis textual y terminológico del discurso turístico especializado
Authors: Pulgarín Mª Esther Gómez
Published: February 2025

El turismo con mascotas ha experimentado un crecimiento exponencial durante las últimas décadas. En consecuencia, nacen nuevas necesidades lingüísticas y nuevos términos para designar esta modalidad turística en desarrollo. Así, resulta pertinente realizar un análisis de los textos surgidos de esta, así como de su terminología. El presente estudio tiene como objetivo principal estudiar los textos que genera este nuevo discurso turístico especializado y, con ellos y como objetivo secundario, la terminología perteneciente al ámbito de las mascotas que estos contengan. En primer lugar, se propone una exposición y estudio de los tipos de textos con mayor presencia en el turismo con mascotas siguiendo la clasificación de Calvi (2010) y mediante la compilación de un corpus textual. Una vez compilado, se analizarán la estructura de los textos y el lenguaje empleado, además de su terminología especializada relativa a las mascotas, poniendo especial atención en los términos originarios del inglés. Para este propósito, recurriremos a las escritoras Durán y Jiménez, cuyo análisis se enfoca en el turismo de aventuras, dentro de su proyecto DicoAdventure; y De la Cruz et al. Al, que utilizan el estudio de corpora para analizar la incorporación de préstamos ingleses en el sector turístico. Tras ello, se expondrán las conclusiones pertinentes al estudio, entre las que destaca el alto nivel de especialización de los textos.
Textos turísticos en lectura fácil
Authors: Reguera Ana Medina , Márquez Desirée Avilés
Published: February 2025

Este trabajo se encuadra en el proyecto de investigación “Sistemas pictográficos y elementos visuales para comprender el
patrimonio. Traducción intersemiótica a lectura fácil. VISUALECT” del Ministerio de Ciencia e Innovación de España. Concretamente, se
presenta la compilación y composición de un corpus textual de textos turísticos en lectura fácil (LF), concepto que se ubica previamente como una
modalidad de traducción intralingüística para la accesibilidad, que no cuenta aún con un marco teórico sólido en los Estudios de
Traducción. Habida cuenta de lo incipiente que es esta modalidad, se ha elaborado una base de datos de textos origen y meta que sirva
para analizar las estrategias traductoras y el nivel de variabilidad entre diferentes géneros y traductores. Los resultados que se
obtienen entre 250 textos arrojan un repertorio de trece géneros textuales, así como un reparto muy desigual en la distribución
geográfica. Se incluyen reflexiones sobre la dificultad de recuperación de los textos originales y la elevada variabilidad en las
estrategias macrotextuales y en los elementos paratextuales.
Child L2 acquisition of French
Authors: Granfeldt Jonas
Published: February 2025

This paper reviews research on child L2 French (cL2) published since 2000 with a focus on research
areas and methodology in a broad sense. The aim of the review is to identify methodological trends in the research, to
exemplify, and to provide a discussion of prominent features. The review shows that research on cL2 French has mainly
focused on the acquisition of morphosyntax based on oral production data. There are few longitudinal studies while
experimental research focusing on comprehension and online processing is largely lacking. Despite being a world
language, the number of different settings and L1s in cL2 French research is limited. Following trends in bilingualism
research, methods for studying exposure and input have developed from an initial reliance on the Length of Exposure
measure to more sensitive measures of relative exposure, but there are still few studies presenting any absolute
measures of input. In recent years, a focus on the use and development of standardized tests for clinical purposes is
noticeable. The review also shows that reporting practices concerning ethical considerations need to become more
consistent in the future.
Strawberry Green Petal Disease Pathosystem in Québec, Canada
Authors: Santos Abraão Almeida , Molligan Joshua , Plante Nicolas , Peréz-Lopéz Edel
Published: February 2025

The emergence and re-emergence of pathosystems are expected to increase with ongoing climate change. Strawberry green petal disease (SbGP) is caused by phytoplasmas transmitted by two leafhopper species,
Aphrodes bicinctus
and
Macrosteles quadrilineatus
, in strawberry crops. In Québec, SbGP was frequently reported between 1950 and 1970. However, recent surveys (2012–2022) indicate an increased disease incidence in strawberry fields. While it is unclear whether this increase indicates a re-emergence or underreporting, understanding these pathosystem components can help clarify the underlying causes. This case study reviews the SbGP pathosystem, historical reports, and existing control measures, emphasizing the importance of ongoing and future research to address identified gaps. Although SbGP currently poses a limited economic threat, the interactions within the pathosystem could be exacerbated by warming temperatures, potentially leading to increased vector populations, altered phytoplasma development, susceptibility of strawberry plants, and consequently, severe outbreaks and a broader geographic distribution of the disease.

Information

© The Authors 2025
Quantum BPS cosmology
Authors: Kan Nahomi , Shiraishi Kiyoshi , Takeuchi Maki , Yashiki Mai
Published: February 2025

There has been much discussion about the initial conditions of the early Universe in the context of quantum theory. In this paper, we construct the wave function and probability distribution by adopting the quantum version of the BPS equation instead of the usual Wheeler–DeWitt equation in a minisuperspace quantum cosmology with spatially uniform scalar fields. Although the model treated in this study is technically valid for a limited form of scalar potential, we show that it is possible to construct a conserved probability current in our model. We also examine classical and quantum aspects of models with the Dirac–Born–Infeld type scalar fields.
A phase unwrapping algorithm for high dynamic range distributed acoustic sensing with signal fidelity
Authors: Li Zhengying , Wang Changjia , Fu Xuelei , Li Weikai , Gui Xin , Shi Jin
Published: February 2025

In this paper, a differential-unwrapping-integral-regression-extraction (DUIRE) algorithm is proposed. Using the least squares fitting and the empirical mode decomposition (EMD) to replace the polynomial fitting, the cumulative error caused by noise is significantly reduced. While the maximum measurable strain is improved as compared to that of the traditional algorithm, the baseline drift, which occurs in the DUI algorithm, is resolved. In addition, the strain resolution is also improved due to the noise reduction in EMD, thus enhancing the dynamic range and signal fidelity. The dynamic range based on the DUIRE algorithm can reach 97.14 dB@1 kHz. The dynamic range improvement effect is more noticeable when the input signal-to-noise ratio is low. In a fiber Bragg grating based DAS system with 9.80 km sensing distance, only the proposed DUIRE algorithm can correctly restore the applied multi-frequency vibration signal.
Dual-task guided network: hybrid supervised learning for surface defect detection
Authors: Zou Juncheng , Lv Junjie
Published: February 2025

Efficient and accurate surface defect detection is a crucial task for industrial production, where traditional computer vision methods often fail to reliably identify subtle manufacturing defects. This paper proposes a novel hybrid supervised learning-based dual-task guided network (DTGNet) model that combines the strengths of supervised and unsupervised learning techniques to address the limitations of traditional approaches. By integrating partial convolution, scalable convolution and content-guided attention fusion (CGAFusion), our model improves recognition of complex defect features and achieves state-of-the-art performance on benchmark datasets. Experimental validation on the KSDD2 dataset empirically demonstrates DTGNet’s superior performance, with Lite DTGNet achieving a 93.51% accuracy. This innovative approach not only advances industrial quality control technologies but also provides a flexible, data-efficient framework.
Manganese valence modulation in δ-MnO2 via F-doping for enhanced electrocatalytic oxygen evolution reaction
Authors: Shi Xinyu , Deng Libo , Sun Lingna , Zhang Qianling , Ren Xiangzhong , Li Yongliang
Published: February 2025

Manganese dioxide (MnO2) is recognized as a promising candidate for the oxygen evolution reaction (OER); however, its practical application is hindered by limited active sites and low electrical conductivity. Fluorine (F), known for its strong electron affinity and electronegativity, can modulate the surface electronic structure and physicochemical properties of catalysts. In this study, we synthesized MnO2 nanosheets and fluorine-doped MnO2 (F-MnO2) using simple hydrothermal and ion-exchange methods. We then assessed the influence of fluorine doping on the intrinsic OER activity and stability of these catalysts, as well as their underlying catalytic mechanisms. By manipulating the amount of fluorine introduced and the fluorination temperature, we explored the relationship between varying fluorine concentrations and OER performance. The experimental results show that F-MnO2 exhibits higher OER activity than pristine MnO2. At a current density of 10 mA cm–2, the overpotential required for F-MnO2 is merely 320 mV, substantially lower than that of pristine MnO2. This enhanced performance is ascribed to fluorine doping, which leads to an increased quantity of active Mn3+ centers and oxygen vacancies, along with an expanded electrochemically active surface area. Furthermore, F-MnO2 displays improved stability during the testing period. It maintains long-term stability for over 25 h, further corroborating the catalyst’s excellent anti-oxidation and anti-corrosion properties in alkaline water electrolysis.
Extended drift-kinetic full-f turbulent simulation of a linear plasma device using the gyro-moment approach
Authors: Mencke J E , Ricci P
Published: February 2025

Turbulent full-f simulations in a linear plasma device are presented. Extending the work of Frei et al (2024 Phys. Plasmas
31 012301), the simulations are based on a drift-kinetic (DK) model that includes corrections associated with higher-order drifts and finite Larmor radius (FLR) effects, while avoiding the Boussinesq approximation. To solve the DK equation, the ion distribution function is expanded on a Hermite-Laguerre basis and the expansion coefficients, denoted as the gyro-moments (GMs), are evolved. Convergence is demonstrated with a small number of GMs and the ion distribution function is shown to be, approximately, a bi-Maxwellian distribution. The simulations reveal significantly reduced cross-field transport with respect to standard DK simulations. Turbulent structures are observed, predominantly elongated in the parallel direction, and largely unaffected by the number of GMs. Linear investigations of the unstable turbulent modes reveal the presence of a long-wavelength Kelvin–Helmholtz mode and a short-wavelength mode driven unstable by finite FLR corrections. The role of these modes in the nonlinear simulations is discussed.
Theoretical and key technology research on superconducting undulator
Authors: Chen Zilin , Yang Xiangchen , Zhang Xiangzhen , Wei Junhao , Bian Xiaojuan , Gao Yao , Guo Qing , Geng Jieru , Li Yuhui
Published: February 2025

Superconducting undulators (SCUs) are increasingly vital for synchrotron light sources and free-electron lasers in modern particle accelerators due to their ability to surpass the performance limitations of traditional permanent magnet undulators (PMUs). This paper delves into the theoretical framework and key technologies of SCUs, substantiating findings with experimental verifications. The theoretical analysis and numerical simulations of SCU magnetic fields are conducted based on Maxwell’s equations, leading to optimized magnetic field distributions. Advanced manufacturing processes, such as high-precision coil winding and epoxy resin impregnation, are developed and refined. The paper also details the SCU’s cryogenic, power supply, quench protection, vacuum, and magnetic field measurement systems, ensuring safe and stable operations in real-world conditions. Prototypes, including 1.5-meter-long SCUs, undergo rigorous tests at liquid helium temperatures to validate reliability, revealing that while the SCU meets the design goals in both the vertical and horizontal states, gravity effects in the horizontal state deteriorate the quality of the magnetic field and require iterative optimization. The improvement of the magnetic field quality is achieved by locally adjusting the tuning gap and the end correction coils. Despite the advances that have been made, it is essential to further enhance the performance of SCUs by optimizing the end design and adding means to regulate the magnetic field at low temperatures. This study lays a solid theoretical and technical foundation for the application of SCUs in advanced light sources, and is expected to provide a meaningful reference for the development of more SCUs in the future.
Discrete-time systems in quasi-standard form and the h6 coalgebra symmetry
Authors: Drozdov Pavel , Gubbiotti Giorgio
Published: February 2025

In this paper, we characterize all discrete-time systems in quasi-standard form admitting coalgebra symmetry with respect to the Lie–Poisson algebra h6. The outcome of this study is a family of systems depending on an arbitrary function of three variables, playing the rôle of the potential. Moreover, using a direct search approach, we classify discrete-time systems from this family that admit an additional invariant at most quadratic in the physical variables. We discuss the integrability properties of the obtained cases, their relationship with known systems, and their continuum limits.
A Greedy Algorithm-Based Scheme for High-Quality Visually Meaningful Image Encryption
Authors: deng yong , tian xiaomei , Chen Zhong , Xiao Yanting , Xiao Yongquan
Published: February 2025

To address the limitations of existing visually meaningful image encryption algorithms in terms of visual quality and adaptability across different wavelet types, this paper introduces a novel greedy algorithm-based embedding method. Our approach innovatively selects the optimal decomposition basis dynamically by calculating an error value for each candidate basis, tailored to the specific characteristics of both the host and plaintext images. This error-based selection process significantly enhances visual quality across a spectrum of wavelet transformations. Furthermore, we propose a novel two-dimensional hyperchaotic map (2D-RECM), characterized by its hyperchaotic behavior across a broad range of control parameters. The integration of 2D-RECM with our embedding algorithm results in a robust visually meaningful image encryption algorithm (RECM-VMIEA). Extensive simulations and analyses confirm that RECM-VMIEA not only maintains high visual quality but also exhibits exceptional security and robustness, outperforming existing algorithms in these critical aspects.