bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of osteoporosis and osteopenia in elderly patients scheduled for total knee arthroplasty
Authors: Delsmann Maximilian M. , Schmidt Constantin , Mühlenfeld Moritz , Jandl Nico Maximilian , Boese Christoph Kolja , Beil Frank Timo , Rolvien Tim , Ries Christian 
Published: December 2021

Abstract
Introduction
Osteoporosis is a common comorbidity in elderly patients with osteoarthritis (OA) and may increase perioperative complications in orthopedic surgery (e.g., component migration, periprosthetic fractures). As there is no investigation of bone mineral density (BMD) in elderly patients prior to total knee arthroplasty (TKA) in Europe, we investigated this issue with a particular focus on a potential treatment gap.

Materials and methods
We assessed the BMD by dual-energy X-ray absorptiometry (DXA) in 109 consecutive elderly patients (age ≥ 70 years) scheduled for TKA. In addition to a detailed assessment of osteoporosis and osteopenia, the influence of clinical risk factors and radiological OA severity on BMD was evaluated using group comparisons and linear regression models. In addition, we analyzed differences in BMD between patients scheduled for TKA vs. total hip arthroplasty (THA).

Results
Of the included 109 patients, 19 patients (17.4%) were diagnosed with osteoporosis and 50 (45.9%) with osteopenia. In the osteoporotic patients, a clinically relevant underdiagnosis concomitant with a serious treatment gap was observed in 95.0% of the patients. Body mass index, OA grade, and glucocorticoid use were identified as independent factors associated with BMD. No differences in BMD were found between the patients scheduled for TKA vs. THA.

Conclusions
Considering the high prevalence of osteoporosis and osteopenia in elderly patients, DXA screening should be recommended for patients ≥ 70 years indicated for TKA.
Grundprobleme und Perspektiven des Gentechnikrechts
Authors: Kloepfer Michael , Doerenbach Stella 
Published: December 2021

ZusammenfassungDer vorliegende Beitrag zielt darauf ab, einen Überblick über aktuelle Entwicklungen des
Gentechnikrechts zu verschaffen. Neben einigen (immer noch bestehenden) Grundproblematiken im Spannungsfeld
zwischen Vorsorgeprinzip und Innovationsbestreben, gibt es sowohl Neuerungen in der europäischen Rechtsprechung,
als auch in der technischen und gesellschaftlichen Entwicklung, die vorgestellt und in Kontext gesetzt werden.
Einer engeren Untersuchung werden dabei u.a. das Mutagenese-Urteil des EuGH aus dem Jahr 2018 und sogenannte
“Gene-Drives” unterzogen.
Constitutivity in Flavour Perception
Authors: Skrzypulec Błażej 
Published: December 2021

AbstractWithin contemporary philosophy of perception, it is commonly claimed that flavour experiences are paradigmatic examples of multimodal perceptual experiences. In fact, virtually any sensory system, including vision and audition, is believed to influence how we experience flavours. However, there is a strong intuition, often expressed in these works, that not all of these sensory systems make an equal contribution to the phenomenology of flavour experiences. More specifically, it seems that the activities of some sensory systems are constitutive for flavour perception while others merely influence how we experience flavours. This paper aims to answer the question regarding the constitutive factors of flavour perception in a twofold way. First, a theoretical framework is developed, relying on debates regarding constitutivity in analytic metaphysics and philosophy of science, which defines the stronger and weaker senses in which the activities of sensory systems may be constitutive for flavour perception. Second, relying on empirical results in flavour science, the constitutive status of activities related to distinct sensory systems in the context of flavour perception is investigated.
Competition and physician-induced demand in a healthcare market with regulated price: evidence from Ghana
Authors: Dzampe Adolf Kwadzo , Takahashi Shingo 
Published: December 2021

AbstractUsing panel data of administrative claims spanning 36 months (2017–2019) and an instrumental variable method, this study examines whether physician-induced demand for hypertension disease care exists in Ghana’s healthcare system where price is regulated, and there is no co-payment. We find that an increase in competition—measured as a high doctor-to-population ratio at the district level—leads to an increase in the number of physician visits, suggesting physician-induced demand exists, and that effects are greater for large hospitals and public health providers. This result is further supported by alternative measures and specifications showing that physicians’ revenue from medication and gross revenue increase as the physician density increases. These pattern suggest that physicians in high density areas, faced with a decrease in number of patients per physician, make up for the decline in income by inducing more patient visits.
On the Efficient Computation of Large Scale Singular Sums with Applications to Long-Range Forces in Crystal Lattices
Authors: Buchheit Andreas A. , Keßler Torsten 
Published: December 2021

AbstractWe develop a new expansion for representing singular sums in terms of integrals and vice versa. This method provides a powerful tool for the efficient computation of large singular sums that appear in long-range interacting systems in condensed matter and quantum physics. It also offers a generalised trapezoidal rule for the precise computation of singular integrals. In both cases, the difference between sum and integral is approximated by derivatives of the non-singular factor of the summand function, where the coefficients in turn depend on the singularity. We show that for a physically meaningful set of functions, the error decays exponentially with the expansion order. For a fixed expansion order, the error decays algebraically both with the grid size, if the method is used for quadrature, or the characteristic length scale of the summand function in case the sum over a fixed grid is approximated by an integral. In absence of a singularity, the method reduces to the Euler–Maclaurin summation formula. We demonstrate the numerical performance of our new expansion by applying it to the computation of the full nonlinear long-range forces inside a domain wall in a macroscopic one-dimensional crystal with $$2\times 10^{10}$$

2
×

10
10

particles. The code of our implementation in Mathematica is provided online. For particles that interact via the Coulomb repulsion, we demonstrate that finite size effects remain relevant even in the thermodynamic limit of macroscopic particle numbers. Our results show that widely-used continuum limits in condensed matter physics are not applicable for quantitative predictions in this case.
An Arbitrary High Order Well-Balanced ADER-DG Numerical Scheme for the Multilayer Shallow-Water Model with Variable Density
Authors: Fernández E. Guerrero , Díaz M. J. Castro , Dumbser M. , de Luna T. Morales 
Published: December 2021

AbstractIn this work, we present a novel numerical discretization of a variable pressure multilayer shallow water model. The model can be written as a hyperbolic PDE system and allows the simulation of density driven gravity currents in a shallow water framework. The proposed discretization consists in an unlimited arbitrary high order accurate (ADER) Discontinuous Galerkin (DG) method, which is then limited with the MOOD paradigm using an a posteriori subcell finite volume limiter. The resulting numerical scheme is arbitrary high order accurate in space and time for smooth solutions and does not destroy the natural subcell resolution inherent in the DG methods in the presence of strong gradients or discontinuities. A numerical strategy to preserve non-trivial stationary solutions is also discussed. The final method is very accurate in smooth regions even using coarse or very coarse meshes, as shown in the numerical simulations presented here. Finally, a comparison with a laboratory test, where empirical data are available, is also performed.
Feasibility of an Assessment Tool as a Data-Driven Approach to Reducing Racial Bias in Biomedical Publications
Authors: Wescott Siobhan , Johnson Ronn , Lamba Sangeeta , Olson Devon , Haywood Yolanda , Meltzer Carolyn C , Correa Ricardo 
Published: December 2021

AbstractThe editorial independence of biomedical journals allows flexibility to meet a wide range of research interests. However, it also is a barrier for coordination between journals to solve challenging issues such as racial bias in the scientific literature. A standardized tool to screen for racial bias could prevent the publication of racially biased papers. Biomedical journals would maintain editorial autonomy while still allowing comparable data to be collected and analyzed across journals. A racially diverse research team carried out a three-phase study to generate and test a racial bias assessment tool for biomedical research. Phase 1, an in-depth, structured literature search to identify recommendations, found near complete agreement in the literature on addressing race in biomedical research. Phase 2, construction of a framework from those recommendations, provides the major innovation of this paper. The framework includes three dimensions of race: 1) context, 2) tone and terminology, and 3) analysis, which are the basis for the Race Equity Vetting Instrument for Editorial Workflow (REVIEW) tool. Phase 3, pilot testing the assessment tool, showed that the REVIEW tool was effective at flagging multiple concerns in widely criticized articles. This study demonstrates the feasibility of the proposed REVIEW tool to reduce racial bias in research. Next steps include testing this tool on a broader sample of biomedical research to determine how the tool performs on more subtle examples of racial bias.
Quantification of Fracture Roughness by Change Probabilities and Hurst Exponents
Authors: Gutjahr Tim , Hale Sina , Keller Karsten , Blum Philipp , Winter Steffen 
Published: December 2021

AbstractThe objective of the current study is to utilize an innovative method called “change probabilities” for describing fracture roughness. In order to detect and visualize anisotropy of rock joint surfaces, the roughness of one-dimensional profiles taken in different directions is quantified. The central quantifiers, change probabilities, are based on counting monotonic changes in discretizations of a profile. These probabilities, which usually vary with the scale, can be reinterpreted as scale-dependent Hurst exponents. For a large class of Gaussian stochastic processes, change probabilities are shown to be directly related to the classical Hurst exponent, which generalizes a relationship known for fractional Brownian motion. While related to this classical roughness measure, the proposed method is more generally applicable, therefore increasing the flexibility of modeling and investigating surface profiles. In particular, it allows a quick and efficient visualization and detection of roughness anisotropy and scale dependence of roughness.
A Riemannian Newton trust-region method for fitting Gaussian mixture models
Authors: Sembach Lena , Burgard Jan Pablo , Schulz Volker 
Published: December 2021

AbstractGaussian Mixture Models are a powerful tool in Data Science and Statistics that are mainly used for clustering and density approximation. The task of estimating the model parameters is in practice often solved by the expectation maximization (EM) algorithm which has its benefits in its simplicity and low per-iteration costs. However, the EM converges slowly if there is a large share of hidden information or overlapping clusters. Recent advances in Manifold Optimization for Gaussian Mixture Models have gained increasing interest. We introduce an explicit formula for the Riemannian Hessian for Gaussian Mixture Models. On top, we propose a new Riemannian Newton Trust-Region method which outperforms current approaches both in terms of runtime and number of iterations. We apply our method on clustering problems and density approximation tasks. Our method is very powerful for data with a large share of hidden information compared to existing methods.
Delivering Urgent Care Using Telemedicine: Insights from Experienced Clinicians at Academic Medical Centers
Authors: Laub Natalie , Agarwal Anish K. , Shi Catherine , Sjamsu Arianna , Chaiyachati Krisda 
Published: December 2021

Abstract
Background
Care delivered using telemedicine has been steadily growing in the USA but represented a small fraction of overall visits before the COVID-19 pandemic as few clinicians had been providing care using telemedicine. Understanding how experienced clinicians have practiced telemedicine can help guide today’s exponential adoption of telemedicine.

Objective
The objective of this study was to explore barriers and facilitators to providing effective, high-quality urgent care using telemedicine (“tele-urgent care”) from the perspective of clinicians experienced in telemedicine.

Approach
We conducted semi-structured interviews between July 2018 and March 2019 of clinicians who had been providing tele-urgent care services to patients as a part of their routine clinical practice. Themes were identified using content analysis with a constant comparative coding approach.

Key Results
Among the 20 clinicians interviewed, the majority were female (90%) and nurse practitioners (65%). We identified four themes related to barriers and facilitators to providing effective, high-quality tele-urgent care. Workplace factors such as a strong information technology (IT) infrastructure, real-time IT support, an electronic health record, and a collegial work environment, often virtual, were necessary standards. Communication and exam techniques from in-person encounters were adapted to tele-urgent care including active listening skills and teaching patients to conduct specific exam maneuvers virtually. The convenience of tele-urgent care should be preserved to support improvements in access to care. Finally, patients and clinicians occasionally had mismatched expectations about what could or would be provided during a tele-urgent care encounter. Managing the added tension that can occur during a telemedicine encounter was important.

Conclusion
As telemedicine becomes an integral part of the care continuum, incorporating and accounting for these key insights when we train and support clinicians will be necessary to provide effective, high-quality care to patients in the future.
Attitudes of administrative decision-makers towards nature-based solutions for flood risk management in Germany
Authors: Tafel Leopold , Ott Edward , Brillinger Mario , Schulze Christoph , Schröter Barbara 
Published: December 2021

AbstractOver the last two decades, alternative and holistic concepts, such as Nature-based Solutions (NbS) were introduced and adopted by policy-makers, including to the field of flood protection, thereby causing a paradigm shift towards flood risk management. The inclusion of natural water retention measures (NWRM) such as dike relocation and floodplain restoration into the German guidelines for flood protection institutionalized the new concepts in Germany. Whereas small scale NbS and the affected population have already been subject to thorough scientific research, large-scale NbS and the decision-makers assigned with the measure’s implementation have yet to be studied. How do administrative decision-makers perceive the new approach and measures? Are there particular attitudes among the decision-makers regarding NbS? Which aspects of implementing large-scale NbS influence possible attitudes? Which hurdles do decision-makers concern for the implementation of the new concepts? This paper investigates these questions on the example of dike relocation and floodplain restoration using Q-methodology with administrative decision-makers of flood protection authorities in the German state of Saxony-Anhalt. The consecutive statistical analysis unveiled three significant viewpoints among the decision-makers. The viewpoints/attitudes were classified as 1. The Convinced, 2. The Concerned and, 3. The Evaluators, defined by varying and individual concerns on the implementation of dike relocation and floodplain restoration. Hereby, this study delivers insights on large-scale NbS as well as on the issues of their implementation.
Deep learning-based automated characterization of crosscut tests for coatings via image segmentation
Authors: Zhang Gaoyuan , Schmitz Christian , Fimmers Matthias , Quix Christoph , Hoseini Sayed 
Published: December 2021

AbstractA manual scratch test to measure the scratch resistance of coatings applied to a certain substrate is usually used to test the adhesion of a coating. Despite its significant amount of subjectivity, the crosscut test is widely considered to be the most practical measuring method for adhesion strength with a good reliability. Intelligent software tools help to improve and optimize systems combining chemistry, engineering based on high-throughput formulation screening (HTFS) technologies and machine learning algorithms to open up novel solutions in material sciences. Nevertheless, automated testing often misses the link to quality control by the human eye that is sensitive in spotting and evaluating defects as it is the case in the crosscut test. In this paper, we present a method for the automated and objective characterization of coatings to drive and support Chemistry 4.0 solutions via semantic image segmentation using deep convolutional networks. The algorithm evaluated the adhesion strength based on the images of the crosscuts recognizing the delaminated area and the results were compared with the traditional classification rated by the human expert.
Robot-Fish Interaction Helps to Trigger Social Buffering in Neon Tetras: The Potential Role of Social Robotics in Treating Anxiety
Authors: Romano Donato , Stefanini Cesare 
Published: December 2021

AbstractThe emerging field of social robotics comprises several multidisciplinary applications. Anxiety and stress therapies can greatly benefit by socio-emotional support provided by robots, although the intervention of social robots as effective treatment needs to be fully understood. Herein,Paracheirodon innesi, a social fish species, was used to interact with a robotic fish to understand intrinsic and extrinsic mechanisms causing anxiety, and how social robots can be effectively used as anxiety treatments. In the first experiment we tested the effects of a conspecific-mimicking robot on the fish tendency to swim in the bottom when transferred in a new tank. Here,P. innesispent a significantly longer time in the upper section of the test tank when the robotic fish was present, clearly indicating a reduction of their state of anxiety due to social stimuli. The second experiment was based on a modification of the dark/light preference test, since many teleost fish are scototactic, preferring dark environments. However, when the robotic fish was placed in the white half of the test tank,P. innesiindividuals swam longer in this section otherwise aversive. Social support provided by the robotic fish in both experiments produced a better recovery from anxiety due to social buffering, a phenomenon regulated by specific neural mechanisms. This study provides new insights on the evolution and mechanisms of social buffering to reduce anxiety, as well as on the use of social robots as an alternative to traditional approaches in treating anxiety symptoms.
Prognostic and predictive value of radiomics features at MRI in nasopharyngeal carcinoma
Authors: Bao Dan , Zhao Yanfeng , Liu Zhou , Zhong Hongxia , Geng Yayuan , Lin Meng , Li Lin , Zhao Xinming , Luo Dehong 
Published: December 2021

Abstract
Purpose
To explore the value of MRI-based radiomics features in predicting risk in disease progression for nasopharyngeal carcinoma (NPC).

Methods
199 patients confirmed with NPC were retrospectively included and then divided into training and validation set using a hold-out validation (159: 40). Discriminative radiomic features were selected with a Wilcoxon signed-rank test from tumors and normal masticatory muscles of 37 NPC patients. LASSO Cox regression and Pearson correlation analysis were applied to further confirm the differential expression of the radiomic features in the training set. Using the multiple Cox regression model, we built a radiomic feature-based classifier, Rad-Score. The prognostic and predictive performance of Rad-Score was validated in the validation cohort and illustrated in all included 199 patients.

Results
We identified 1832 differentially expressed radiomic features between tumors and normal tissue. Rad-Score was built based on one radiomic feature: CET1-w_wavelet.LLH_GLDM_Dependence-Entropy. Rad-Score showed a satisfactory performance to predict disease progression in NPC with an area under the curve (AUC) of 0.604, 0.732, 0.626 in the training, validation, and the combined cohort (all 199 patients included) respectively. Rad-Score improved risk stratification, and disease progression-free survival was significantly different between these groups in every cohort of patients (p = 0.044 or p < 0.01). Combining radiomics and clinical features, higher AUC was achieved of the prediction of 3-year disease progression-free survival (PFS) (AUC, 0.78) and 5-year disease PFS (AUC, 0.73), although there was no statistical difference.

Conclusion
The radiomics classifier, Rad-Score, was proven useful for pretreatment prognosis prediction and showed potential in risk stratification for NPC.
An evolutionary optimization approach to prevent electronics burnout in subsea oil and gas equipment
Authors: Somassoundirame Ramechecandane , Nithiyananthan Eswari 
Published: December 2021

AbstractThe electronics burnout in subsea engineering equipment caused by the excessive heating of electronics due to improper cooling mechanism is an area of major concern in subsea oil and gas fields. Very often the electronic canisters are encapsulated by insulation to prevent hydrate formation in the subsea completion equipment. The electronic equipment with a set of sensors is usually deployed subsea for live monitoring of data and to regulate the functioning of the equipment. This study presents a numerical methodology to predict and prevent electronics burnout in a pressure/temperature transmitter (PT/TT) that is truly representative of a wide class of PT/TT deployed subsea. An optimization study of the insulation system around the PT/TT sensors that encompasses the various contradicting constraints that are routinely encountered in subsea engineering has been presented for the benefit of the readers. In the present study, the optimal design of the insulation system around the electronics equipment is generated using a combination of thermal finite element analysis and evolutionary optimization algorithms. The results obtained show that the proposed methodology can yield results which could be a tremendous improvement in the traditional means of designing the insulation systems for such electronics equipment. It is also shown that locating the electronic housing far from the production fluid in the PT/TT sensors can lead to proper cooling and thereby avoid the burnout to a significant extent.