bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-term outcomes among localized prostate cancer survivors: prospective predictors for return-to-work three years after cancer rehabilitation
Authors: Ullrich Anneke , Rath Hilke Maria , Otto Ullrich , Kerschgens Christa , Raida Martin , Hagen-Aukamp Christa , Bergelt Corinna 
Published: August 2021

AbstractPurposeThis study aimed at (1) investigating the work status of men treated by radical prostatectomy due to diagnosis of localized prostate cancer (LPCa) three years after having attended a cancer rehabilitation program and (2) identifying prospective risk factors for not working at this time point.MethodsIn a longitudinal, questionnaire-based multicenter study, 519 working-age LPCa survivors reported on their work status 12 and 36 months following rehabilitation. Chi-square tests/ttests and multivariable logistic regression analysis were used to identify prospective factors associated with not working at 36 months follow-up.ResultsNearly three quarter of LPCa survivors (N = 377, 73%) worked 3 years after post-acute rehabilitation. Most participants (N = 365, 71%) showed continuous return-to-work (RTW) patterns as they worked both 1 and 3 years following rehabilitation. Multivariable regression analysis revealed older age, low or middle socio-economic status as well as resigned and unambitious work behavior and fatigue at the time of attending the rehabilitation program to be prospective factors for not working at 36 months follow-up. Low socio-economic status [Odds ratio (OR) 4.81, 95% confidence interval (CI) 2.07–11.16] and unambitious work behavior [OR 4.48, 95% CI 2.16–9.31] were the strongest predictors.ConclusionLong-term work retention is a realistic goal among LPCa survivors. The results contribute to the identification of at-risk LPCa survivors early in the RTW process. Special attention should be paid to social inequality. Further, interventions related to the management of fatigue and work-related coping styles could improve long-term RTW, as these were relevant, but potentially modifiable factors impeding work retention.
Geranyl-geraniol addition affects potency of bisphosphonates—a comparison in vitro promising a therapeutic approach for bisphosphonate-associated osteonecrosis of the jaw and oral wound healing
Authors: Otto Marius , Lux Christine , Schlittenbauer Tilo , Halling Frank , Ziebart Thomas 
Published: August 2021

Abstract
Purpose
Analysis of the influence of geranyl-geraniol (GG) addition on four bisphosphonate derivatives regarding their influence on cell viability and migration ability of bone metabolism and endothelial cells in vitro.

Methods
Clodronate, pamidronate, ibandronate, and zoledronate were observed with and without GG addition, for their effect on human osteoblasts (HOB), normal human dermal fibroblasts (NHDF), human endothelial progenitor cells (EPC), and endothelial cells of the human umbilical cord (HUVEC) using migration-, MTT-, and colony-forming cell assays.

Results
Data pointed to a depressing effect of all bisphosphonates on the migration ability of NHDF, EPC, and HOB. MTT assay demonstrated a decreased cell viability of HUVEC of all bisphosphonates in a 50 μM concentration and of NHDF when treated with 50 μM of clodronate, ibandronate, or zoledronate. Tested drugs showed a depressing effect on colony-forming potential of EPC even in a 5 μM concentration. GG addition demonstrated an attenuate impact on bisphosphonate effect on all primary cell cultures, respectively.

Conclusion
In vitro comparison showed that the addition of GG weakens the effect of all bisphosphonates examined. It supports investigations that suggest GG to be able to prevent bisphosphonate-associated osteonecrosis of the jaw (BP-ONJ) in vivo. Future clinical trials may discover the local therapeutic use of GG for the prevention of BP-ONJ.
Nondimensionalization of the Atmospheric Boundary-Layer System: Obukhov Length and Monin–Obukhov Similarity Theory
Authors: Yano Jun–Ichi , Wacławczyk Marta 
Published: August 2021

AbstractThe Obukhov length, although often adopted as a characteristic scale of the atmospheric boundary layer, has been introduced purely based on a dimensional argument without a deductive derivation from the governing equations. Here, its derivation is pursued by the nondimensionalization method in the same manner as for the Rossby deformation radius and the Ekman-layer depth. Physical implications of the Obukhov length are inferred by nondimensionalizing the turbulence-kinetic-energy equation for the horizontally homogeneous boundary layer. A nondimensionalization length scale for a full set of equations for boundary-layer flow formally reduces to the Obukhov length by dividing this scale by a rescaling factor. This rescaling factor increases with increasing stable stratification of the boundary layer, in which flows tend to be more horizontal and gentler; thus the Obukhov length increasingly loses its relevance. A heuristic, but deductive, derivation of Monin–Obukhov similarity theory is also outlined based on the obtained nondimensionalization results.
Temperature and Exports: Evidence from the United States
Authors: Karlsson Jimmy 
Published: August 2021

AbstractThis paper estimates the effect of exogenous short-term temperature changes on the economy of the United States, using high-resolution data on monthly exports which has not been previously exploited in the literature. The detailed disaggregation of U.S. export data into sectors enables a top-down estimation of the net effect of temperature, while also identifying potential mechanisms at the micro level. Using an econometric specification which allows high parametric flexibility, I find significantly negative effects of both high and low temperatures. The magnitude of the effects corresponds to an average reduction of annual U.S. exports by 0.20%, following a uniform 2 $$^{\circ }$$

∘

C temperature increase. Industry heterogeneity in the temperature effect suggests disparate mechanisms behind hot and cold days, which are important to take into account when estimating the future economic damages of climate change in the United States.
Predicting unstable software benchmarks using static source code features
Authors: Laaber Christoph , Basmaci Mikael , Salza Pasquale 
Published: August 2021

AbstractSoftware benchmarks are only as good as the performance measurements they yield. Unstable benchmarks show high variability among repeated measurements, which causes uncertainty about the actual performance and complicates reliable change assessment. However, if a benchmark is stable or unstable only becomes evident after it has been executed and its results are available. In this paper, we introduce a machine-learning-based approach to predict a benchmark’s stability without having to execute it. Our approach relies on 58 statically-computed source code features, extracted for benchmark code and code called by a benchmark, related to (1) meta information, e.g., lines of code (LOC), (2) programming language elements, e.g., conditionals or loops, and (3) potentially performance-impacting standard library calls, e.g., file and network input/output (I/O). To assess our approach’s effectiveness, we perform a large-scale experiment on 4,461 Go benchmarks coming from 230 open-source software (OSS) projects. First, we assess the prediction performance of our machine learning models using 11 binary classification algorithms. We find that Random Forest performs best with good prediction performance from 0.79 to 0.90, and 0.43 to 0.68, in terms of AUC and MCC, respectively. Second, we perform feature importance analyses for individual features and feature categories. We find that 7 features related to meta-information, slice usage, nested loops, and synchronization application programming interfaces (APIs) are individually important for good predictions; and that the combination of all features of the called source code is paramount for our model, while the combination of features of the benchmark itself is less important. Our results show that although benchmark stability is affected by more than just the source code, we can effectively utilize machine learning models to predict whether a benchmark will be stable or not ahead of execution. This enables spending precious testing time on reliable benchmarks, supporting developers to identify unstable benchmarks during development, allowing unstable benchmarks to be repeated more often, estimating stability in scenarios where repeated benchmark execution is infeasible or impossible, and warning developers if new benchmarks or existing benchmarks executed in new environments will be unstable.
Does choice change preferences? An incentivized test of the mere choice effect
Authors: Alós-Ferrer Carlos , Granic Georg D. 
Published: August 2021

AbstractWidespread evidence from psychology and neuroscience documents that previous choices unconditionally increase the later desirability of chosen objects, even if those choices were uninformative. This is problematic for economists who use choice data to estimate latent preferences, demand functions, and social welfare. The evidence on this mere choice effect, however, exhibits serious shortcomings which prevent evaluating its possible relevance for economics. In this paper, we present a novel, parsimonious experimental design to test for the economic validity of the mere choice effect addressing these shortcomings. Our design uses well-defined, monetary lotteries, all decisions are incentivized, and we effectively randomize participants’ initial choices without relying on deception. Results from a large, pre-registered online experiment find no support for the mere choice effect. Our results challenge conventional wisdom outside economics. The mere choice effect does not seem to be a concern for economics, at least in the domain of decision making under risk.
AI for in-line vehicle sequence controlling: development and evaluation of an adaptive machine learning artifact to predict sequence deviations in a mixed-model production line
Authors: Stauder Maximilian , Kühl Niklas 
Published: August 2021

AbstractCustomers in the manufacturing sector, especially in the automotive industry, have a high demand for individualized products at price levels comparable to traditional mass-production. The contrary objectives of providing a variety of products and operating at minimum costs have introduced a high degree of production planning and control mechanisms based on a stable order sequence for mixed-model assembly lines. A major threat to this development is sequence scrambling, triggered by both operational and product-related root causes. Despite the introduction of Just-in-time and fixed production times, the problem of sequence scrambling remains partially unresolved in the automotive industry. Negative downstream effects range from disruptions in the Just-in-sequence supply chain, to a discontinuation of the production process. A precise prediction of sequence deviations at an early stage allows the introduction of counteractions to stabilize the sequence before disorder emerges. While procedural causes are widely addressed in research, the work at hand requires a different perspective involving a product-related view. Built on unique data from a real-world global automotive manufacturer, a supervised classification model is trained and evaluated. This includes all the necessary steps to design, implement, and assess an AI-artifact, as well as data gathering, preprocessing, algorithm selection, and evaluation. To ensure long-term prediction stability, we include a continuous learning module to counter data drifts. We show that up to 50% of the major deviations can be predicted in advance. However, we do not consider any process-related information, such as machine conditions and shift plans, but solely focus on the exploitation of product features like body type, power train, color, and special equipment.
Spatial positional relationship between macular superficial vessel density and ganglion cell-inner plexiform layer thickness in primary angle closure glaucoma
Authors: Lin Yongdong , Ma Di , Wang Hongxi , Chen Shirong , Cai Weihao , Zhang Anlin , Zhang Mingzhi 
Published: August 2021

Abstract
Purpose
To evaluate the spatial relationship between macular superficial vessel density (SVD) and macular ganglion cell-inner plexiform layer (GCIPL) thickness in primary angle closure glaucoma (PACG), and to investigate diagnostic abilities of macular SVD and foveal avascular zone (FAZ) parameters.

Methods
This was a cross-sectional study on 38 PACG patients (38 eyes) and 25 healthy subjects (25 eyes). Macular region was imaged using a 1050-nm-wavelength swept-source optical coherence tomography (OCT) angiography (OCTA) system (DRI OCT Triton, TOPCON). Vessel density of the macular region was quantified by ImageJ software. The peripapillary retinal nerve fiber layer (pRNFL) thicknesses and macular GCIPL thickness were obtained by swept-source OCT. Pearson correlation analysis was used to evaluate the spatial positional relationship between macular SVD and macular GCIPL thickness. At the same time, the correlation between macular SVD and pRNFL thickness was evaluated. Areas under the receiver operating characteristics curves (AUCs) of OCT, OCTA and FAZ measurement metrics were calculated to assess the diagnostic ability for glaucoma.

Results
Macular GCIPL thickness had a moderate correlation with the macular SVD in the inferonasal sector (r = 0.426, P = 0.008). In addition, there was a strong correlation between inferonasal sector of macular vessel density and 5,6,7,8 clock-hour regions of the pRNFL thicknesses (all r > 0.5). Inferoinferior sector of macular SVD and 6,7 clock-hour regions of pRNFL thicknesses also had strong correlation (all r > 0.5). The AUCs of macular SVD ranged between 0.61 (superonasal sector) and 0.76 (inferoinferior sector). The FAZ circularity index showed the highest diagnostic power (AUC = 0.94;95% CI, 0.85–0.99), followed by superotemporal sector of macular GCIPL thicknesses (0.93;95% CI,0.83–0.98).

Conclusions
Sector of macular SVD not only had a spatial positional correlation with corresponding macular GCIPL thickness, but also with clock-hour regional pRNFL thicknesses in PACG eyes. FAZ circulation index might be a useful diagnostic parameter.
Teacher Characteristics, Knowledge and Use of Evidence-Based Practices in Autism Education in Ireland
Authors: Barry Lorna , Holloway Jennifer , Gallagher Stephen , McMahon Jennifer 
Published: August 2021

AbstractAutism evidence-based practices (EBPs) are those with demonstrated improved outcomes for students with autism across a range of skill areas, yet issues persist in adopting these in classroom settings- particularly in general education (GE) settings. This research aimed to identify teacher training, years of experience, access to allied professionals and knowledge and use of autism EBPs in GE settings in Ireland. 369 mainstream primary school teachers reported their characteristics and their knowledge and use of EBPs. Results indicated that the majority of teachers received little initial teacher education training in autism, almost no continuous professional development (CPD) before educating a child with autism, and received little support from allied professionals. Knowledge and use of EBPs differed significantly across teacher characteristics, with findings discussed in relation to teacher training.
Measuring the Impact of Bilingualism on Executive Functioning Via Inhibitory Control Abilities in Autistic Children
Authors: Montgomery Lewis , Chondrogianni Vicky , Fletcher-Watson Sue , Rabagliati Hugh , Sorace Antonella , Davis Rachael 
Published: August 2021

AbstractOne factor that may influence how executive functions develop is exposure to more than one language in childhood. This study explored the impact of bilingualism on inhibitory control in autistic (n = 38) and non-autistic children (n = 51). Bilingualism was measured on a continuum of exposure to investigate the effects of language environment on two facets of inhibitory control. Behavioural control of motor impulses was modulated positively through increased bilingual exposure, irrespective of diagnostic status, but bilingual exposure did not significantly affect inhibition involving visual attention. The results partially support the hypothesis that bilingual exposure differentially affects components of inhibitory control and provides important evidence for families that bilingualism is not detrimental to their development.
Critical parameters in cultivation of experimental biofilms using the example of Pseudomonas fluorescens
Authors: Reddersen Kirsten , Güllmar André , Tonndorf-Martini Silke , Sigusch Bernd W. , Ewald Andrea , Dauben Thomas J. , Martin Karin , Wiegand Cornelia 
Published: August 2021

AbstractFormation and treatment of biofilms present a great challenge for health care and industry. About 80% of human infections are associated with biofilms including biomaterial centered infections, like infections of prosthetic heart valves, central venous catheters, or urinary catheters. Additionally, biofilms can cause food and drinking water contamination. Biofilm research focusses on application of experimental biofilm models to study initial adherence processes, to optimize physico-chemical properties of medical materials for reducing interactions between materials and bacteria, and to investigate biofilm treatment under controlled conditions. Exploring new antimicrobial strategies plays a key role in a variety of scientific disciplines, like medical material research, anti-infectious research, plant engineering, or wastewater treatment. Although a variety of biofilm models exist, there is a lack of standardization for experimental protocols, and designing experimental setups remains a challenge. In this study, a number of experimental parameters critical for material research have been tested that influence formation and stability of an experimental biofilm using the non-pathogenic model strain of Pseudomonas fluorescens. These parameters include experimental time frame, nutrient supply, inoculum concentration, static and dynamic cultivation conditions, material properties, and sample treatment during staining for visualization of the biofilm. It was shown, that all tested parameters critically influence the experimental biofilm formation process. The results obtained in this study shall support material researchers in designing experimental biofilm setups.
Occupational Stress and Catholic Priests: A Scoping Review of the Literature
Authors: Ruiz-Prada Miguel , Fernández-Salinero Samuel , García-Ael Cristina , Topa Gabriela 
Published: August 2021

AbstractThis study offers an exploratory review of the experience of stress and burnout syndrome among Catholic priests. Following Arksey and O’Malley's (Int J Soc Res Methodol 8(1):19–32, 2005, 10.1080/1364557032000119616) protocol, a scoping study was conducted. Given the scarcity of studies found on the subject, a broad selection criterion was used, which included quantitative, qualitative and mixed studies, literature reviews and comparative studies with other professions. The results reveal various risk factors: work overload among younger generations of priests, a sociocultural context that distrusts the clergy, neurotic, introverted, perfectionist and narcissistic personality styles, avoidant and complacent coping styles, living alone, not having sufficient support (especially from the Church authorities), excessive demands and lack of boundaries related to the priestly role and submissive obedience styles, among others. However, the studies reviewed also identified important protection factors: promoting optimism, an approach-based coping style and a collaborative way of resolving conflicts, frequent physical exercise, eating a balanced diet, finding time to rest, strengthening personal identity, social support (from parishioners, collaborators, colleagues, superiors) and leading an active spiritual life. Stress and burnout are associated with certain pathologies linked to smoking, alcoholism, obesity, diabetes, cardiovascular disease, anxiety and depression. Strengthening protective factors and minimizing the impact of risk factors would do much to improve the clergy’s occupational health.
30 years of IRMM-1027 reference materials for fissile material accountancy and control: development, production and characterisation
Authors: Jakopič Rožle , Toth Kalman , Bauwens Jeroen , Buják Renata , Hennessy Carmel , Kehoe Frances , Jacobsson Ulf , Richter Stephan , Aregbe Yetunde 
Published: August 2021

AbstractThe IRMM-1027 Large-sized dried (LSD) spikes are certified reference materials applied to measure the uranium and plutonium content of dissolved fuel solutions using isotope dilution mass spectrometry. High quality starting metals of uranium and plutonium are dissolved to produce a stock solution, which is dispensed into individual vials and dried down. The present spikes are mixtures of typically 50 mg 20% enriched U and 2 mg enriched 239Pu as dried nitrates, conditioned in an organic substance for stability. Each vial of an IRMM-1027 LSD spike comes with certified masses of uranium (235U and 238U) and 239Pu and isotopic composition with associated uncertainty. This article will discuss major developments since the production of the first batch of LSD spikes and will reflect on the current preparation and certification approaches.
Ensemble slice sampling
Authors: Karamanis Minas , Beutler Florian 
Published: August 2021

AbstractSlice sampling has emerged as a powerful Markov Chain Monte Carlo algorithm that adapts to the characteristics of the target distribution with minimal hand-tuning. However, Slice Sampling’s performance is highly sensitive to the user-specified initial length scale hyperparameter and the method generally struggles with poorly scaled or strongly correlated distributions. This paper introduces Ensemble Slice Sampling (ESS), a new class of algorithms that bypasses such difficulties by adaptively tuning the initial length scale and utilising an ensemble of parallel walkers in order to efficiently handle strong correlations between parameters. These affine-invariant algorithms are trivial to construct, require no hand-tuning, and can easily be implemented in parallel computing environments. Empirical tests show that Ensemble Slice Sampling can improve efficiency by more than an order of magnitude compared to conventional MCMC methods on a broad range of highly correlated target distributions. In cases of strongly multimodal target distributions, Ensemble Slice Sampling can sample efficiently even in high dimensions. We argue that the parallel, black-box and gradient-free nature of the method renders it ideal for use in scientific fields such as physics, astrophysics and cosmology which are dominated by a wide variety of computationally expensive and non-differentiable models.