bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recall Bias in Client-Reported Outcomes in Canine Orthopaedic Patients Using Clinical Metrology Instruments
Authors: Pappa Eirini , Maddox Thomas W. , Crystal Edward , Comerford Eithne J. , Tomlinson Andrew W. 
Published: July 2023

Abstract
Objective The aim of this study was to determine the accuracy of client recollection of their dogs' preconsultation status using clinical metrology instruments such as the Liverpool Osteoarthritis in Dogs (LOAD) and Canine Brief Pain Inventory (CBPI) questionnaires in dogs presenting to a referral orthopaedic clinic.
Study Design This is a longitudinal prospective cohort study of client-owned dogs presenting for investigations of lameness (n = 217). LOAD and CBPI questionnaires were completed by the owners at the first consultation (T0). Owners were contacted at 2 (T1), 6 (T2), and 12 (T3) months and asked to recall their dogs' T0 status by completing another LOAD and CBPI questionnaire. The agreement between the T0 and recalled LOAD and CBPI scores was determined using the two-way mixed effects intraclass correlation coefficient (ICC). The Wilcoxon signed-rank test was used to determine the difference between scores.
Results For the LOAD scores, there was moderate agreement between T0 and T1 (ICC: 0.64) and T0 and T2 (ICC: 0.53) scores and poor agreement between T0 and T3 (ICC: 0.496). For the CBPI Pain Severity Scores, there was poor agreement between T0 and all three subsequent time points (ICC < 0.5). For the CBPI Pain Interference Scores, there was moderate agreement between T0 and T1 (ICC: 0.57) and T2 (ICC: 0.56) scores and poor agreement between T0 and T3 (ICC: 0.43).
Conclusion The LOAD and CBPI questionnaires are subject to recall bias. Studies reporting retrospectively acquired CMI data should be interpreted with caution.
The price and income elasticities of natural gas demand in Azerbaijan: Is there room to export more?
Authors: Gurbanov Sarvar , Mikayilov Jeyhun I. , Mukhtarov Shahriyar , Maharramli Shahin 
Published: July 2023

AbstractNatural gas is frequently introduced as a “transitional fuel”. Because burning natural gas emits less carbon dioxide emissions than burning either oil or coal. Additionally, the intermittent nature of low-carbon electricity generation creates imperative for using natural gas for power generation. The role of natural gas is currently under scrutiny as climate change transforms into a climate crisis. Meanwhile, share of natural gas in the primary energy consumption of Azerbaijan is 69%, while 94% of the country’s electricity is currently being generated in natural gas-fired power plants. In this manner, this paper estimates income and price elasticities of natural gas demand for the Azerbaijan case. In this study, various sets of estimation techniques are utilized. By modeling natural gas demand with different estimation methods, including Autoregressive Distributed Lagged Structural Time Series Modeling, Dynamic Ordinary Least Squares Method, Fully Modified Ordinary Least Squares, Canonical Cointegrating Regression, and General to Specific under Autometrics multi-path search machine learning algorithm, we try to find if there is room for the country to export more. All these utilized estimation methods confirmed the long-run income elasticity to be around 0.8, while the long-run price elasticity is around −0.1. Both estimations provide insights in terms of energy security and electricity security for policymakers during the implementation process of climate, energy, and environmental policy. Findings of this study classify natural as a necessity and normal good for the Azerbaijan case. The main policy implication of this study is that policymakers must enable and facilitate the availability of close renewable substitutes for residential and commercial customers. Estimated elasticities suggest that with rising national income, demand for natural gas will keep increasing, and efficient consumption will not be attainable with increasing prices. In the pursuit of export potential, findings suggest that it is more relevant to free up natural gas allocated from power generation by substituting it with renewable energy sources.
Transferability evaluation of the deep potential model for simulating water-graphene confined system
Authors: Liu Dongfei , Wu Jianzhong , Lu Diannan 
Published: July 2023

Machine learning potentials (MLPs) are poised to combine the accuracy of ab initio predictions with the computational efficiency of classical molecular dynamics (MD) simulation. While great progress has been made over the last two decades in developing MLPs, there is still much to be done to evaluate their model transferability and facilitate their development. In this work, we construct two deep potential (DP) models for liquid water near graphene surfaces, Model S and Model F, with the latter having more training data. A concurrent learning algorithm (DP-GEN) is adopted to explore the configurational space beyond the scope of conventional ab initio MD simulation. By examining the performance of Model S, we find that an accurate prediction of atomic force does not imply an accurate prediction of system energy. The deviation from the relative atomic force alone is insufficient to assess the accuracy of the DP models. Based on the performance of Model F, we propose that the relative magnitude of the model deviation and the corresponding root-mean-square error of the original test dataset, including energy and atomic force, can serve as an indicator for evaluating the accuracy of the model prediction for a given structure, which is particularly applicable for large systems where density functional theory calculations are infeasible. In addition to the prediction accuracy of the model described above, we also briefly discuss simulation stability and its relationship to the former. Both are important aspects in assessing the transferability of the MLP model.
Sociocultural approaches to L2 digital collaborative
writing
Authors: Elola Idoia , Oskoz Ana 
Published: July 2023

Whereas collaborative writing is an established
approach to second language (L2) education, the use of this approach
in the L2 classroom has now been bolstered by the ubiquity of
digital tools. Sociocultural theory (SCT) and activity theory (AT),
both frameworks that inform digital collaborative writing,
conceptualize writing as a holistic activity in which several key
elements interact dynamically, including participants, tools, and
outcomes. This chapter explores the value of knowledge sharing,
meaning negotiation, scaffolding, mediation, intersubjectivity, and
action completion – all pivotal tenets in collaborative writing –
through these frameworks. It also illustrates critical issues (e.g.,
knowledge co-construction and interaction) and concludes by
acknowledging unexplored areas of research and instructional
practices that could further advance digital collaborative
writing.
Otolin-1 as a biomarker for the evaluation of the effectiveness of betahistine treatment for benign paroxysmal positional vertigo
Authors: Cakmak Karaer Isil , Urhan Ayca , Akalin Yahya 
Published: July 2023

Objective:
Benign paroxysmal positional vertigo (BPPV) is the most common vertigo disorder. Betahistine is the most commonly used drug in the treatment of vertigo, however its effect on the inner ear is not fully known. Otolin-1 is an inner ear-specific glycoprotein that can be identified in peripheral blood. The aim of the study was to determine the effect of treatment of betahistine for BPPV on serum otolin-1 levels.

Methods:
Thirty (30) patients with BPPV and 30 healthy controls were enrolled in the study. Serum otolin-1 levels were measured before and 14 days after perioral (po) betahistine treatment in the BPPV group, whereas otolin-1 level was examined once in controls. The efficacy of treatment was evaluated with Dizziness Handicap Index (DHI) and Visual Analog Scale (VAS) in the BPPV group.

Results:
Otolin-1 levels were statistically significantly higher in patients with BPPV than controls. In the BPPV group, serum otolin-1 level was found to be statistically significantly lower after betahistine treatment. There was a statistically significantly difference between pre-treatment and posttreatment groups regarding to both DHI and VAS scores.

Conclusion:
Serum otolin-1 can be used as a biomarker in monitoring the effectiveness of treatment of BPPV with betahistine as well as diagnosis of BPPV.
Metasurface modulator of frequency diverse multi-mode OAM beams with equal divergence angle for coincidence imaging
Authors: Zhou Ningning , Tian Chunming , Zhu Shitao , Li Caipin , Zhao Mengran , Chen Xiaoming , Zhang Anxue 
Published: July 2023

Abstract
Traditional multi-mode orbital angular momentum (OAM) beams suffer from low energy efficiency in detection since the divergence angle tends to increase with increasing order of the OAM mode. Thus, OAM beams with equal divergence angle are highly desirable. In this paper, a frequency-diverse multi-mode (FDMM) OAM modulator with approximately equal divergence angle is proposed. The modulator is composed of an OAM modulation metasurface and a spatial filter (SF) with narrow passband. Firstly, the OAM modulation metasurface is designed based on multiple ring-like regions with different radii in the metasurface aperture. Each mode of OAM beam is generated at a corresponding frequency point in one region. Thus, the metasurface aperture can generate different modes of OAM beams at different frequencies (i.e., FDMM OAM beams) simultaneously. Then, the SF with narrow passband is proposed through synthesizing multi-layer frequency selective metasurfaces, aiming to reduce interferences between different modes of OAM beams. Finally, the FDMM OAM modulator is realized by superposing the SF on the OAM modulation metasurface. The FDMM OAM modulator can generate six modes of OAM beams (i.e.,

±
3

,

±
2

and

±
1

modes) at 12.5 GHz, 13.0 GHz and 13.6 GHz, respectively. A multi-mode OAM coincidence imaging model based on the FDMM OAM modulator is established. The simulation and experiment results show that the proposed FDMM OAM modulator can be used for target reconstruction and the coincidence imaging performance can be improved assisted by an optimization algorithm.
Performance benchmarking of an ultra-low vibration laboratory to host a commercial millikelvin scanning tunnelling microscope
Authors: Que Yande , Kumar Amit , Lodge Michael S , Tong Zhengjue , Lai Marcus Kar Fai , Tao Wei , Cui Zhenhao , Shivajirao Ranjith , Jia Junxiang , Lee Siew Eang , Weber Bent 
Published: July 2023

Abstract
Ultra-low temperature scanning tunnelling microscopy and spectroscopy (STM/STS) achieved by dilution refrigeration can provide unrivalled insight into the local electronic structure of quantum materials and atomic-scale quantum systems. Effective isolation from mechanical vibration and acoustic noise is critical in order to achieve ultimate spatial and energy resolution. Here, we report on the design and performance of an ultra-low vibration (ULV) laboratory hosting a customized but otherwise commercially available 40 mK STM. The design of the vibration isolation consists of a T-shaped concrete mass block (∼55t), suspended by actively controlled pneumatic springs, and placed on a foundation separated from the surrounding building in a ‘room-within-a-room’ design. Vibration levels achieved are meeting the VC-M vibration standard at >3 Hz, reached only in a limited number of laboratories worldwide. Measurement of the STM’s junction noise confirms effective vibration isolation on par with custom built STMs in ULV laboratories. In this tailored low-vibration environment, the STM achieves an energy resolution of 43 μeV (144 mK), promising for the investigation and control of quantum matter at atomic length scales.
Cramér distance and discretisations of circle expanding maps I: theory
Authors: Guihéneuf Pierre-Antoine , Monge Maurizio 
Published: July 2023

Abstract
This paper is aimed to study the ergodic short-term behaviour of discretisations of circle expanding maps. More precisely, we prove some asymptotics of the distance between the tth iterate of Lebesgue measure by the dynamics f and the tth iterate of the uniform measure on the grid of order N by the discretisation on this grid, when t is fixed and the order N goes to infinity. This is done under some explicit genericity hypotheses on the dynamics, and the distance between measures is measured by the mean of Cramér distance. The proof is based on a study of the corresponding linearised problem, where the problem is translated into terms of equirepartition on tori of dimension exponential in t. A numerical study associated to this work is presented in Guihéneuf and Monge (2022 arXiv:2206.08000).
Per-fraction planning to enhance optimization degrees of freedom compared to the conventional single-plan approach
Authors: Rossi Linda , Breedveld Sebastiaan , Heijmen Ben 
Published: July 2023

Abstract

Objective. In conventional radiotherapy, a single treatment plan is generated pre-treatment, and delivered in daily fractions. In this study, we propose to generate different treatment plans for all fractions (‘Per-fraction’ planning) to reduce cumulative organs at risk (OAR) doses. Per-fraction planning was compared to the ‘Conventional’ single-plan approach for non-coplanar 4 × 9.5 Gy prostate stereotactic body radiation therapy (SBRT). Approach. An in-house application for fully automated, non-coplanar multi-criterial treatment planning with integrated beam angle and fluence optimization was used for plan generations. For the Conventional approach, a single 12-beam non-coplanar IMRT plan with individualized beam angles was generated for each of the 20 included patients. In Per-fraction planning, four fraction plans were generated for each patient. For each fraction, a different set of patient-specific 12-beam configurations could be automatically selected. Per-fraction plans were sequentially generated by adding dose to already generated fraction plan(s). For each fraction, the cumulative- and fraction dose were simultaneously optimized, allowing some minor constraint violations in fraction doses, but not in cumulative. Main results. In the Per-fraction approach, on average 32.9 ± 3.1 [29;39] unique beams per patient were used. PTV doses in the separate Per-fraction plans were acceptable and highly similar to those in Conventional plans, while also fulfilling all OAR hard constraints. When comparing total cumulative doses, Per-fraction planning showed improved bladder sparing for all patients with reductions in Dmean of 22.6% (p = 0.0001) and in D1cc of 2.0% (p = 0.0001), reductions in patient volumes receiving 30% and 50% of the prescribed dose of 54.7% and 6.3%, respectively, and a 3.1% lower rectum Dmean (p = 0.007). Rectum D1cc was 4.1% higher (p = 0.0001) and Urethra dose was similar. Significance. In this proof-of-concept paper, Per-fraction planning resulted in several dose improvements in healthy tissues compared to the Conventional single-plan approach, for similar PTV dose. By keeping the number of beams per fraction the same as in Conventional planning, reported dosimetric improvements could be obtained without increase in fraction durations. Further research is needed to explore the full potential of the Per-fraction planning approach.
Temperature dependent magnetorelaxometry of magnetic nanoparticle ensembles
Authors: Arsalani Soudabeh , Radon Patricia , Eberbeck Dietmar , Körber Rainer , Jaufenthaler Aaron , Baumgarten Daniel , Wiekhorst Frank 
Published: July 2023

Abstract
Magnetorelaxometry imaging (MRXI) is a non-invasive, quantitative imaging technique for magnetic nanoparticles (MNPs). The image resolution of this technique significantly depends on the relaxation amplitude (ΔB). For this work, we measured the room temperature (299 K) relaxation signals of eight commercial MNP sample systems with different magnetic properties, in both fluid and immobilized states, in order to select the most suitable sample for a particular MRXI setting. Additionally, the effect of elevated temperatures (up to hyperthermia temperature, 335 K) on the relaxation signals of four different MNP systems (Synomag, Perimag, BNF and Nanomag) in both states were investigated. The ΔB values of fluid samples significantly decreased with increasing temperature, and the behaviour for immobilized samples depended on their blocking temperature (T
B). For samples with T
B < 299 K, ΔB also decreased with increasing temperature. Whereas for samples with T
B > 299 K, the opposite behaviour was observed. These results are beneficial for improving the image resolution in MRXI and show, among the investigated systems, and for our setup, Synomag is the best candidate for future in vitro and in vivo studies. This is due to its consistently high ΔB between 299 and 335 K in both states. Our findings demonstrate the feasibility of temperature imaging by MRXI.
Correction of motion tracking errors for PET head rigid motion correction
Authors: Miranda Alan , Kroll Tina , Schweda Vanessa , Staelens Steven , Verhaeghe Jeroen 
Published: July 2023

Abstract

Objective. In positron emission tomography (PET) rigid motion correction, erroneous tracking information translates into reduced quality in motion corrected reconstructions. We aim to improve the accuracy of the motion tracking data, to improve the quality of motion corrected reconstructions. Approach. We developed a method for correction of marker/skin displacement over the skull, for tracking methods which require multiple markers attached on the subject head. Additionally, we correct for small magnitude (∼1–2 mm) residual translation tracking errors that can still be present after other corrections. We performed [18F]FDG scans in awake mice (n = 8) and rats (n = 8), and dynamic [18F]SynVesT-1 scans in awake mice (n = 8). Head tracking was performed with the point source tracking method, attaching 3–4 radioactive fiducial markers on the animals’ heads. List-mode even-by-event motion correction reconstruction was performed using tracking data obtained from the point source tracking method (MC), tracking data corrected for marker displacement (MC-DC), and tracking data with additional correction for residual translation tracking errors (MC-DCT). Image contrast, and the image enhancement metric (IEM, with MC as reference) were calculated in these 3 reconstructions. Main results. In mice [18F]FDG scans, the contrast increased on average 3% from MC to MC-DC (IEM: 1.01), and 5% from MC to MC-DCT (IEM: 1.02). For mice [18F]SynVesT-1 scans the contrast increased 6% from MC to MC-DC (IEM: 1.03), and 7% from MC to MC-DCT (IEM: 1.05). In rat [18F]FDG scans contrast increased 5% (IEM: 1.04), and 9% (IEM: 1.05), respectively. Significance. The methods presented here serve to correct motion tracking errors in PET brain scans, which translates into improved image quality in motion corrected reconstructions.
Combined two-level guided wave structural health monitoring strategy using multifeature integration and machine learning: application to early-age grouted sleeves
Authors: Liu Jiahe , Yi Jun , Li Dongsheng , Cui Xiushi , Zhou Junlong 
Published: July 2023

Abstract
Structural health monitoring of grouted sleeves is one of the assembly industry’s huge challenges. In this study, a combined two-level damage detection was introduced. It comprises defect classification (healthy, rebar eccentricity, and grout leakage) and severity evaluation for early-age grouted sleeves using guided waves. Multiple features (MF) from time-, frequency-, and time-frequency domains were extracted and defined according to the diverse defects and ages of grouted sleeves to represent complex damage characteristics. Moreover, the egret swarm algorithm optimization–extreme learning machine (ESAO-ELM) models were proposed to avoid the influence of subjective experience and judgment from experts. ESAO optimized the initial random parameters (input weights and hidden layer bias) of ELM. Then, two MF-ESAO-ELM models were trained for two-level damage detection on the experimental dataset. The performance of the proposed models was comprehensively evaluated using accuracy, recall, precision, and confusion matrix. MF-ESAO-ELM performs better than ELM and PSO-ELM in accuracy. In this strategy, the defect classification model works in the outer layer to distinguish the state and types of defects of grouted sleeves (healthy, eccentric, or leakage). In comparison, the inner layer starts predicting the severity only if the defect type is leakage. MF-ESAO-ELM offers advantages in terms of accuracy, strategy, and calculation time.
Projection of future carbon benefits by photovoltaic power potential in China using CMIP6 statistical downscaling data
Authors: Niu Jiayun , Wu Jinyang , Qin Wenmin , Wang Lunche , Yang Chao , Zhang Ming , Zhang Yujie , Qi Qinghai 
Published: July 2023

Abstract
Solar photovoltaic (PV) systems is an affordable solution that significantly contribute to climate adaptation and resilience, energy security and greenhouse gas abatement with respect to fossil fuel electricity generation. Currently, available studies on the benefits of PV power generation only consider the electricity consumption and do not account for the possible future benefits from carbon trading under the combined impacts of pollution emissions and socio-economic. In this study, the downscaling and bias correction were applied to the Coupled Model Inter-comparison Project Phase 6 (CMIP6) multi-model mean data based on the historical data from the China Meteorological Administration (CMA) stations. The corrected measurements of meteorology were used to explore the PV power potential and the environmental and economic benefits offset by solar power generation under SSP126, SSP245 and SSP585 in China during 2023–2100. We found that the annual mean PV power potential across mainland China ranged from 1 to 37 Wm−2 and demonstrated a decreasing trend in the Northwest China and an increasing trend in the Southeast China. Compared to thermal power generation, electricity from solar energy will counteract the total emissions of annual mean 139.54 × 105 t CO2, 1702 t SO2, 2562 t NO
X
and 3710 t dust in China in SSP126 scenario. The results of variable importance assessment showed that the West Texas Intermediate crude oil price (47.77%), coal price (41.76%), natural gas price (6.65%) and gross domestic product (2.44%) contribute the most to the carbon emissions allowances (CEAs) price. Against a ‘carbon peak’ background in China, the CEA price will reach 80 CNY/t CO2 by 2030 in China, with the carbon trading value potential ranging from 20 billion to 200 billion CNY of each pixel (10 km × 10 km) by 2030. This study would have important implications for the environmental construction and future investment and construction of PV systems in China.