bluuebunny/crossref_metadata_2025_split huggingface dataset:
Work Ability After Anterior Cervical Decompression and Fusion Followed by a Structured Postoperative Rehabilitation: Secondary Outcomes of a Prospective Randomized Controlled Multi-Centre Trial with a 2-year Follow-up
Authors: Peolsson Anneli , Wibault Johanna , Löfgren Håkan , Dedering Åsa , Öberg Birgitta , Zsigmond Peter , Wåhlin Charlotte 
Published: December 2021

AbstractPurpose Information on work ability after ACDF and postoperative rehabilitation is lacking. The aim of the present study is therefore to investigate the work ability benefits of a structured postoperative treatment (SPT) over a standard care approach (SA) in patients who underwent anterior cervical decompression and fusion (ACDF) for cervical radiculopathy and factors important to the 2-year outcome. Methods Secondary outcome and prediction model of a prospective randomized controlled multi-centre study with a 2-year follow-up (clinicaltrials.gov NCT01547611). The Work Ability Index (WAI) and Work Ability Score (WAS) were measured at baseline and up to 2 years after ACDF in 154 patients of working age who underwent SPT or SA after surgery. Predictive factors for the WAI at 2 years were analysed. Results Both WAI and WAS significantly improved with SPT and SA (p < 0.001), without any between-group differences. Thoughts of being able to work within the next 6 months, Neck Disability Index (NDI), and work-related neck load explained 59% of the variance in WAI at the 2-year follow-up after ACDF. Conclusions Patients improved over time without group differences, suggesting the improvement to be surgery related. Expectation to work within the next 6 months, self-reported neck functioning and work-related neck load were important to work ability and are central factors to ask early after ACDF, to identifying further interventions promoting return to work.
Prediction of thermodynamic properties: centerpiece approach—how do we avoid confusion and get reliable results?
Authors: Verevkin Sergey P. , Andreeva Irina V. , Zherikova Kseniya V. , Pimerzin Aleksey A. 
Published: December 2021

AbstractThe absolute vapor pressures of three amino-alcohols were measured using the transpiration method. The consistent set of standard molar enthalpies of vaporization for eighteen amino-alcohols was evaluated using empirical and structure–property correlations. The averaged values of vaporization enthalpies were recommended as reliable benchmark properties for the heat management of CO2 capture technologies. Centerpiece approach based on the group-additivity principles was developed toward amino-alcohols.
Graphic abstract
Application of calorimetry and other thermal methods in the studies of granulated blast furnace slag from the old storage yards as supplementary cementitious material
Authors: Nocuń-Wczelik W. , Pacierpnik W. , Kapeluszna E. 
Published: December 2021

AbstractThe calorimetric and DTA/TG measurements were applied in testing the effect of granulated blast furnace slag originated from the storage yards of different age, added as a supplementary cementing material to the Portland cement clinker. The studies were performed with aim to evaluate the kinetics of cement hydration and the modification of hydrated paste composition in the presence of additive. The material after 20-year storage, the crushed slag after approximately 2-years storage and the new slag from the current production in the metallurgical plant were used. The slag percentage was 5 ÷ 50%. The addition of granulated blast furnace slag stored for a long time affects the standard properties of cement reducing the compressive strength at longer maturing and with the percentage of additive. This is related mainly to the reduction in the vitreous component. However, at the additive content up to 50% the binder complying with the requirements of the relevant European standards for common cements could be produced. Basing on the results of TG measurements the role of calcium carbonate, being the product resulting from the slag weathering process, acting as a grindability and setting/hardening modifying agent, was highlighted.
Standard-relevant publications: evidence, processes and influencing factors
Authors: Blind Knut , Fenton Alex 
Published: December 2021

AbstractThis paper introduces the concept of standard-relevant publications, complementary to standard-essential patents and framed by the concept of knowledge utilization. By analyzing the reference lists of the around 20,000 standards released by ISO, authors of scientific papers cited in standards who are working at German institutions were identified. The institutions include universities, independent research societies, ministerial research institutes and companies. Almost thirty interviews were conducted with the most-cited of these authors. The interviews addressed the processes by which scientific publications come to be referenced in standards, and the motivations, the barriers and the effects of this. The findings demonstrate opportunities for and challenges to establishing standard-relevant publications as a new performance indicator for researchers, funding agencies, standard-setting organizations and ultimately regulators.
Application of the nonlinear optimisation in regional gravity field modelling using spherical radial base functions
Authors: Mahbuby Hany , Amerian Yazdan , Nikoofard Amirhossein , Eshagh Mehdi 
Published: December 2021

AbstractThe gravity field is a signature of the mass distribution and interior structure of the Earth, in addition to all its geodetic applications especially geoid determination and vertical datum unification. Determination of a regional gravity field model is an important subject and needs to be investigated and developed. Here, the spherical radial basis functions (SBFs) are applied in two scenarios for this purpose: interpolating the gravity anomalies and solving the fundamental equation of physical geodesy for geoid or disturbing potential determination, which has the possibility of being verified by the Global Navigation Satellite Systems (GNSS)/levelling data. Proper selections of the number of SBFs and optimal location of the applied SBFs are important factors to increase the accuracy of estimation. In this study, the gravity anomaly interpolation based on the SBFs is performed by Gauss-Newton optimisation with truncated singular value decomposition, and a Quasi-Newton method based on line search to solve the minimisation problems with a small number of iterations is developed. In order to solve the fundamental equation of physical geodesy by the SBFs, the truncated Newton optimisation is applied as the Hessian matrix of the objective function is not always positive definite. These two scenarios are applied on the terrestrial free-air gravity anomalies over the topographically rough area of Auvergne. The obtained accuracy for the interpolated gravity anomaly model is 1.7 mGal with the number of point-masses about 30% of the number of observations, and 1.5 mGal in the second scenario where the number of used kernels is also 30%. These accuracies are root mean square errors (RMSE) of the differences between predicted and observed gravity anomalies at check points. Moreover, utilising the optimal constructed model from the second scenario, the RMSE of 9 cm is achieved for the differences between the gravimetric height anomalies derived from the model and the geometric height anomalies from GNSS/levelling points.
Neurostimulation Treatment in Chronic Cluster Headache—a Narrative Review
Authors: Evers Stefan , Summ Oliver 
Published: December 2021

AbstractPurpose of ReviewIn this narrative review, the current literature on neurostimulation methods in the treatment of chronic cluster headache is evaluated. These neurostimulation methods include deep brain stimulation, vagus nerve stimulation, greater occipital nerve stimulation, sphenopalatine ganglion stimulation, transcranial magnetic stimulation, transcranial direct current stimulation, supraorbital nerve stimulation, and cervical spinal cord stimulation.Recent FindingsAltogether, only nVNS and SPG stimulation are supported by at least one positive sham-controlled clinical trial for preventive and acute attack (only SPG stimulation) treatment. Other clinical trials either did not control at all or controlled by differences in the stimulation technique itself but not by a sham-control. Case series report higher responder rates.SummaryThe evidence for these neurostimulation methods in the treatment of chronic cluster headache is poor and in part contradictive. However, except deep brain stimulation, tolerability and safety of these methods are good so that in refractory situations application might be justified in individual cases.
Advance artificial time series forecasting model for oil production using neuro fuzzy-based slime mould algorithm
Authors: AlRassas Ayman Mutahar , Al-qaness Mohammed A. A. , Ewees Ahmed A. , Ren Shaoran , Sun Renyuan , Pan Lin , Abd Elaziz Mohamed 
Published: December 2021

AbstractOil production forecasting is an important task to manage petroleum reservoirs operations. In this study, a developed time series forecasting model is proposed for oil production using a new improved version of the adaptive neuro-fuzzy inference system (ANFIS). This model is improved by using an optimization algorithm, the slime mould algorithm (SMA). The SMA is a new algorithm that is applied for solving different optimization tasks. However, its search mechanism suffers from some limitations, for example, trapping at local optima. Thus, we modify the SMA using an intelligence search technique called opposition-based learning (OLB). The developed model, ANFIS-SMAOLB, is evaluated with different real-world oil production data collected from two oilfields in two different countries, Masila oilfield (Yemen) and Tahe oilfield (China). Furthermore, the evaluation of this model is considered with extensive comparisons to several methods, using several evaluation measures. The outcomes assessed the high ability of the developed ANFIS-SMAOLB as an efficient time series forecasting model that showed significant performance.
Matrix metalloproteinase 12 is an independent prognostic factor predicting postoperative relapse of conventional renal cell carcinoma - a short report
Authors: Beres Bence , Yusenko Maria , Peterfi Lehel , Kovacs Gyula , Banyai Daniel 
Published: December 2021

AbstractPurposeApproximately 15% of clinically localised conventional renal cell carcinomas (cRCC) develop metastases within 5 years of follow-up. Sarcomatous cRCC is a highly malignant cancer of the kidney. The aim of our study was to identify biomarkers for estimating the postoperative progression of cRCCs.MethodsGlobal microarray-based gene expression analysis of RCCs with and without sarcomatous changes revealed that a high MMP12 expression was associated with a sarcomatous histology. Additionally, we analysed MMP12 expression using a multi-tissue array comprising 736 cRCC patients without metastasis at the time of surgery. The median follow-up time was 66 ± 29 months.ResultsImmunohistochemistry revealed MMP12 expression in 187 of 736 cRCCs with good follow-up data. Subsequent Kaplan–Meier analysis revealed that patients with MMP12 positive tumours exhibited a significantly shorter tumour-free survival (p < 0.001). In multivariate Cox regression analysis a weak to strong MMP12 expression indicated a 2.4–2.8 times higher risk of postoperative tumour relapse (p < 0.001;p < 0.003, respectively).ConclusionsMMP12 may serve as a biomarker to estimate postoperative cRCC relapse and as a possible target for penfluridol therapy.
Undrained shear strength of Lisbon Miocene clay: a reappraisal based on triaxial and pressuremeter test results
Authors: Lopes Laranjo Mafalda , Matos Fernandes Manuel 
Published: December 2021

Abstract
Undrained shear strength plays a fundamental role on the behaviour of clays. In overconsolidated clays, this parameter is largely influenced by test conditions, namely consolidation stress. “Prazeres Clay” is a Miocene overconsolidated formation, that can be found in a significant part of Lisbon area. Over the last decades a number of very relevant constructions have generated a large database for physical and mechanical properties of Miocene clays. Included in a broader study at the Faculty of Engineering of Porto University about Miocene clay’s physical and mechanical properties, existing data was gathered, treated and critically analysed, in order to establish a useful framework for geotechnical designers. This paper presents the results obtained for undrained shear strength, obtained from triaxial tests and Ménard Pressuremeter tests. It addresses the main difficulties associated with test’s interpretation and presents a discussion on how theoretical values relate to experimental ones. The paper proposes a range of variation for Prazeres Clay’ undrained shear strength based on a significant amount of test results, that is considered to be useful for geotechnical design.

Article Highlights

Undrained Shear strength is a relevant parameter for clays, and is usually derived from triaxial tests

For overconsolidated clays, this parameter is highly dependent on preconsolidation stress, and on its relation to in situ stress.

Based on a significant set of data, the paper presents a simple methodology for estimating this parameter
Regimes of cosmic-ray diffusion in Galactic turbulence
Authors: Reichherzer P. , Merten L. , Dörner J. , Becker Tjus J. , Pueschel M. J. , Zweibel E. G. 
Published: December 2021

AbstractCosmic-ray transport in astrophysical environments is often dominated by the diffusion of particles in a magnetic field composed of both a turbulent and a mean component. This process, which is two-fold turbulent mixing in that the particle motion is stochastic with respect to the field lines, needs to be understood in order to properly model cosmic-ray signatures. One of the most important aspects in the modeling of cosmic-ray diffusion is that fully resonant scattering, the most effective such process, is only possible if the wave spectrum covers the entire range of propagation angles. By taking the wave spectrum boundaries into account, we quantify cosmic-ray diffusion parallel and perpendicular to the guide field direction at turbulence levels above 5% of the total magnetic field. We apply our results of the parallel and perpendicular diffusion coefficient to the Milky Way. We show that simple purely diffusive transport is in conflict with observations of the inner Galaxy, but that just by taking a Galactic wind into account, data can be matched in the central 5 kpc zone. Further comparison shows that the outer Galaxy at $$>5$$

>
5

kpc, on the other hand, should be dominated by perpendicular diffusion, likely changing to parallel diffusion at the outermost radii of the Milky Way.
Utilization of adaptive neuro-fuzzy interference system and functional network in prediction of total organic carbon content
Authors: Siddig Osama , Gamal Hany , Soupios Pantelis , Elkatatny Salaheldin 
Published: December 2021

Abstract
This paper presents the application of two artificial intelligence (AI) approaches in the prediction of total organic carbon content (TOC) in Devonian Duvernay shale. To develop and test the models, around 1250 data points from three wells were used. Each point comprises TOC value with corresponding spectral and conventional well logs. The tested AI techniques are adaptive neuro-fuzzy interference system (ANFIS) and functional network (FN) which their predictions are compared to existing empirical correlations. Out of these two methods, ANFIS yielded the best outcomes with 0.98, 0.90, and 0.95 correlation coefficients (R) in training, testing, and validation respectively, and the average errors ranged between 7 and 18%. In contrast, the empirical correlations resulted in R values less than 0.85 and average errors greater than 20%. Out of eight inputs, gamma ray was found to have the most significant impact on TOC prediction. In comparison to the experimental procedures, AI-based models produces continuous TOC profiles with good prediction accuracy. The intelligent models are developed from preexisting data which saves time and costs.

Article highlights

In contrast to existing empirical correlation, the AI-based models yielded more accurate TOC predictions.

Out of the two AI methods used in this article, ANFIS generated the best estimations in all datasets that have been tested.

The reported outcomes show the reliability of the presented models to determine TOC for Devonian shale.
On the application of the Two-Factor Theory to online employer reviews
Authors: Koncar Philipp , Santos Tiago , Strohmaier Markus , Helic Denis 
Published: December 2021

AbstractMonitoring hygiene and motivation factors from Herzberg’s Two-Factor Theory is a popular way of understanding the influential aspects for employee satisfaction and motivation. The increased availability of employee feedback comprised in online employer reviews yields a promising data source to learn more about these influential factors and the theory itself. However, the application of the Two-Factor Theory to such reviews is yet missing. Thus, this article demonstrates how to apply this theory to more than 2 million online employer reviews. For that, review aspects as well as review ratings are leveraged to study factors that influence employee satisfaction with respect to the theory. Based on the gained insights, a prediction experiment is conducted to forecast employee satisfaction through the textual content of reviews. The presented approach identifies relevant aspects for satisfied and dissatisfied employees working in 43 different industries and 4 different countries. Overall, the results indicate that hygiene factors are most relevant for reviewers, while motivation factors are rather incidental. The prediction experiment achieves a mean balanced accuracy of 0.87, suggesting that review text is predictive for employee satisfaction. Further, the article adds useful input to the discussion of the Two-Factor Theory by providing comparative results across a plethora of different employers, industries and countries.
Multi‐Point Observations of Modulated Whistler‐Mode Waves and Energetic Electron Precipitation
Authors: Qin Murong , Li Wen , Ma Qianli , Woodger Leslie , Millan Robyn , Shen Xiao‐Chen , Capannolo Luisa 
Published: December 2021

AbstractIn this study, we present simultaneous multi‐point observations of whistler‐mode waves detected by RBSP‐B, associated with conjugate electron precipitation observed through enhanced BARREL X‐rays at L ∼ 6 from noon to dusk. Both long period modulation at periods of several to tens of minutes and short period modulation at about tens of seconds are observed in X‐ray measurements. Similar periodicities are also observed for whistler‐mode wave amplitude. We show that the correlation coefficient between whistler‐mode waves and electron precipitation is high in several regions, including plumes and plasma trough. Ultra‐low‐frequency waves (8–30 mHz), which have been suggested to play a potential role in precipitating electrons by modulating whistler‐mode wave intensity or loss cone size, show a weak correlation with whistler‐mode wave amplitudes and the X‐ray counts during the conjunction. We further evaluate whistler‐mode wave driven electron precipitation using a physics‐based technique. The time evolution of the modeled electron precipitation is found to be remarkably consistent with the modulation in the BARREL X‐ray counts both in plumes and plasma trough. By taking advantage of the high‐resolution wave data and close conjunction, we provide strong evidence that whistler‐mode waves are not only directly responsible for the longer modulation (several to tens of minutes), but also the shorter modulation (tens of seconds) of the electron precipitation.
Bayesian Modeling of the Equation of State for Liquid Iron in Earth's Outer Core
Authors: Matsumura T. , Kuwayama Y. , Ueki K. , Kuwatani T. , Ando Y. , Nagata K. , Ito S. , Nagao H. 
Published: December 2021

AbstractWe use Bayesian modeling of the equation of state (EoS) to constrain the density (ρ) and P wave velocity (VP) of liquid iron under conditions of Earth's outer core. Experiments at such high pressures (P) and temperatures (T) are technically challenging, so there are few data available to use in parameter optimization of the EoS. Our Bayesian inference modeling successfully estimates the posterior probability distribution of the parameters and unobserved data by using the Hamiltonian Monte Carlo method. These posterior probability distributions allow calculation of P‐ρ and P‐VP profiles of liquid iron along the adiabatic P‐T profile together with the associated credible intervals. Assuming that the temperature at the core‐mantle boundary (CMB) is 3,500–4,200 K, the P‐ρ and P‐VP profiles show deviations of ρ and VP from the preliminary reference Earth model of about 8–11% and −3% to −5%, respectively. Deviations of the 95% credible intervals of the P‐ρ profile for the CMB and the inner core boundary are 6.9–9.7% and 6.5–9.8%, respectively. Equivalent deviations of the P‐VP profile are −4.8% to −1.5% and −6.0% to −2.3%, respectively. Bayesian modeling of the EoS enables integration of small data sets that include unobserved data and evaluation of uncertainty ranges of physical properties, such as ρ and VP, which are essential for comparison with seismological properties of the core.
Revealing Novel Connections Between Space Weather and the Power Grid: Network Analysis of Ground‐Based Magnetometer and Geomagnetically Induced Currents (GIC) Measurements
Authors: Hughes Joseph , Mcgranaghan Ryan , Kellerman Adam C. , Bortnik Jacob , Arrit Robert F. , Venkataramani Karthik , Perry Charles H. , McCormick Jackson , Ngwira Chigomezyo M. , Cohen Morris 
Published: December 2021

AbstractThe growing depth and breadth of data spanning the solar‐terrestrial environment requires new ways of representing and analyzing the available information. This paper applies one such new data representation—network analysis—to the study of Geomagnetically Induced Currents (GICs) in electric power lines. This work uses newly available electric current data collected by power utilities through the the Electric Power Research Institute (EPRI) SUNBURST project and magnetometer data from the Super Magnetometer Initiative. The magnetometer data are analyzed using wavelet analysis. This new analysis method shows deviations to be more likely for equatorial stations close to water, which may be caused by the coast effect. The deviation likelihood is a complex function of latitude and magnetic local time. The GIC data are analyzed using “Quiet Day Curves” (QDCs) which help isolate geomagnetic disturbances. We find that current deviations are more common in the early morning sector, but this trend differs from station to station. These current and magnetometer data are represented in a network as nodes which are connected when both the current and magnetic measurements have a statistically significant deviation from their baseline behavior. This network is used to study the link between space weather and GICs. To do this, times when a current deviation exists are compared to times when magnetic deviations exist for each magnetometer ‐ current sensor pair. Current deviations are, on average, 1.83 times more likely when there are magnetic deviations. However, some magnetometer deviations are more indicative than others, with the strongest probability multipliers reaching 3.