bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epidemiology, classification and treatment of patella fractures: an observational study of 3194 fractures from the Swedish Fracture Register
Authors: Kruse Mark , Wolf Olof , Mukka Sebastian , Brüggemann Anders 
Published: May 2022

Abstract
Background
Basic epidemiological data on patella fractures derived from large nationwide and multicenter studies are scarce. This observational register study describes patient epidemiology, fracture classification and treatment of patella fractures in adults in a Swedish population.

Methods
We conducted an observational study on data derived from the Swedish Fracture Register (SFR) on all patella fractures classified as non-periprosthetic and non-pathological, registered between 2014 and 2018 in individuals aged ≥ 18years. Epidemiological data on sex, age, side, seasonal variation, trauma mechanism, fracture classification (according to AO/OTA), and treatment were analyzed.

Results
3194 patella fractures were analyzed, occurring at a median age of 67 (range 19–100) years. 64% of all patients were female. Most fractures were caused by low-energy trauma, with 70% due to falling from a standing height. 1796 (56%) of the fractures were transverse compared to 845 (26%) vertical fractures. Most fractures (N=2148, 67%) were treated non-operatively. Operative treatment consisted mainly of Tension Band Wiring (TBW) performed in 774 (24%) patients.

Conclusions
Patella fractures mainly occur in elderly women (> 65 years), commonly caused by low-energy trauma. The main treatment is non-operative (67%), except for transverse (AO/OTA C3) fractures. TBW remains the most used operative treatment of choice. These results may help health care providers, researchers and clinicians better understand the panorama of patella fractures in Sweden.
Gesundheitskompetente Schule: Konzeptentwicklung für organisationale Gesundheitskompetenz in der Schule
Authors: Kirchhoff Sandra , Okan Orkan 
Published: May 2022

ZusammenfassungHintergrundGesundheitskompetenz gilt heute als wichtige Ressource. Schulen sind bedeutsame Wirkstätten im Leben junger Menschen und können maßgeblich zur Stärkung von Gesundheitskompetenz beitragen. Dies auf dem klassischen verhaltensorientierten Weg über Lernangebote, aber auch über einen verhältnisorientierten Ansatz, indem die Schulorganisationgesundheitskompetentoptimiert wird. Der Ansatz geht zurück auf das Konzept der organisationalen Gesundheitskompetenz, das bereits in verschiedenen Settings angekommen ist und dabei hilft, Organisationsbedingungen so zu gestalten, dass die Gesundheitskompetenz der jeweiligen Klientel gestärkt wird. Das Projekt GeKoOrg-Schule (Gesundheitskompetente Organisation Schule) folgt diesem Ansatz und überträgt ihn auf das Schulsetting.Ziel der ArbeitIn GeKoOrg-Schule sollte ein Konzept erarbeitet werden, das Standards zur Entwicklung der organisationalen Gesundheitskompetenz in Schulen bereitstellt und beschreibt, welche Aspekte dabei adressiert werden müssen.Material und MethodenFür die Konzeptentwicklung wurde auf bestehende Konzepte zur organisationalen Gesundheitskompetenz zurückgegriffen. Die Ausarbeitung erfolgte mithilfe von Kommentierungs- und Revisionsschleifen, in welche schulische Akteur:innen einbezogen wurden.ErgebnisseDas GeKoOrg-Schule-Konzept umfasst acht Standards, die verschiedene Bereiche innerhalb der Schulorganisation zur Optimierung und damit zur nachhaltigen Stärkung von Gesundheitskompetenz aufzeigen.DiskussionDie Stärkung von Gesundheitskompetenz in und durch Schule bedarf eines umfassenden verhältnisorientierten Ansatzes. Das Organisationsentwicklungskonzept GeKoOrg-Schule ermöglicht Schulen eine settingbasierte Weiterentwicklung zu gesundheitskompetenten Schulen.
Supervised classification of curves via a combined use of functional data analysis and tree-based methods
Authors: Maturo Fabrizio , Verde Rosanna 
Published: May 2022

AbstractTechnological advancement led to the development of tools to collect vast amounts of data usually recorded at temporal stamps or arriving over time, e.g. data from sensors. Common ways of analysing this kind of data also involve supervised classification techniques; however, despite constant improvements in the literature, learning from high-dimensional data is always a challenging task due to many issues such as, for example, dealing with the curse of dimensionality and looking for a trade-off between complexity and accuracy. Nowadays, research in functional data analysis (FDA) and statistical learning is very lively to address these drawbacks adequately. This study offers a supervised classification strategy that combines FDA and tree-based procedures. Specifically, we introduce functional classification trees, functional bagging, and functional random forest exploiting the functional principal components decomposition as a tool to extract new features and build functional classifiers. In addition, we introduce new tools to support the understanding of the classification rules, such as the functional empirical separation prototype, functional predicted separation prototype, and the leaves’ functional deviance. Furthermore, we suggest some possible solutions for choosing the number of functional principal components and functional classification trees to be implemented in the supervised classification procedure. This research aims to provide an approach to improve the accuracy of the functional classifier, serve the interpretation of the functional classification rules, and overcome the classical drawbacks due to the high-dimensionality of the data. An application on a real dataset regarding daily electrical power demand shows the functioning of the supervised classification proposal. A simulation study with nine scenarios highlights the performance of this approach and compares it with other functional classification methods. The results demonstrate that this line of research is exciting and promising; indeed, in addition to the benefits of the suggested interpretative tools, we exceed the previously established accuracy records on a dataset available online.
Equilibrium existence and expected payoffs in all-pay auctions with constraints
Authors: Pastine Ivan , Pastine Tuvana 
Published: May 2022

AbstractThis paper introduces constraints on player choices in a broad class of all-pay auctions by allowing for upper bounds on players’ strategy sets. It proves the existence of equilibrium and derives simple closed-form formulae for players’ expected payoffs in any equilibrium. These formulae are straightforward to calculate in applications and do not require the derivation of the equilibrium or equilibria. This may be useful because: (i) In some applications players’ expected payoffs are the main item of interest. For example, one may be concerned about the effect of a policy on the market participants. In these cases the results can be used directly, bypassing the need for the full derivation of the equilibrium. (ii) In all-pay auctions, equilibrium is typically in mixed strategies. So in applications where the full characterization of the equilibrium is of interest, finding the players’ expected payoffs is a crucial first step in the derivation of the equilibrium.
Families of pointed toric varieties and degenerations
Authors: Di Rocco Sandra , Schaffler Luca 
Published: May 2022

AbstractThe Losev–Manin moduli space parametrizes pointed chains of projective lines. In this paper we study a possible generalization to families of pointed degenerate toric varieties. Geometric properties of these families, such as flatness and reducedness of the fibers, are explored via a combinatorial characterization. We show that such families are described by a specific type of polytope fibration which generalizes the twisted Cayley sums, originally introduced to characterize elementary extremal contractions of fiber type associated to projective $${\mathbb {Q}}$$
Q
-factorial toric varieties with positive dual defect. The case of a one-dimensional simplex can be viewed as an alternative construction of the permutohedra.
Kinetics, isotherms and thermodynamics of oil spills removal by novel amphiphilic Chitosan-g-Octanal Schiff base polymer developed by click grafting technique
Authors: Eweida Bassant Yousry , Omer Ahmed Mohamed , Tamer Tamer Mahmoud , Soliman Hesham Abd-Elfatah Mohamed , Zaatot Ahmed Amin , Mohy-Eldin Mohamed Samir 
Published: May 2022

AbstractKinetic, isothermal and thermodynamic studies for the oil spills removal process have been conducted by Chitosan and novel amphiphilic Chitosan-g-Octanal Schiff base adsorbents developed by click chemistry and evaluated successfully in the removal of heavy crude oil spills. Chitosan was first prepared from wastes of marine shrimp shells, and then Chitosan and Chitosan-g-Octanal Schiff base adsorbents were synthesized and verified their structures, thermal stability and their morphological changes using FT-IR spectroscopy, TGA and SEM. The oil adsorption percentages (%) using heavy crude oil were 96.41% for the Chitosan-g-Octanal Schiff base adsorbent compared to 64.99% for native Chitosan counterpart. High rate of adsorption was observed where 40% of oil adsorbed within 15 min only using the Chitosan-g-Octanal Schiff base adsorbent compared to 90 min for native Chitosan adsorbent. The adsorption process followed the pseudo-second order model, and the equilibrium data were sufficiently fitted with the Langmuir model with a maximum adsorption capacity 30.30 g/g at 25 °C. Thermodynamic parameters computed from Van’t Hoff plot confirmed the process to be endothermic, favorable and spontaneous.
Benthic assemblages are more predictable than fish assemblages at an island scale
Authors: Sandin Stuart A. , Alcantar Esmeralda , Clark Randy , de León Ramón , Dilrosun Faisal , Edwards Clinton B. , Estep Andrew J. , Eynaud Yoan , French Beverly J. , Fox Michael D. , Grenda Dave , Hamilton Scott L. , Kramp Heather , Marhaver Kristen L. , Miller Scott D. , Roach Ty N. F. , Seferina Gisette , Silveira Cynthia B. , Smith Jennifer E. , Zgliczynski Brian J. , Vermeij Mark J. A. 
Published: May 2022

AbstractDecades of research have revealed relationships between the abundance of coral reef taxa and local conditions, especially at small scales. However, a rigorous test of covariation requires a robust dataset collected across wide environmental or experimental gradients. Here, we surveyed spatial variability in the densities of major coral reef functional groups at 122 sites along a 70 km expanse of the leeward, forereef habitat of Curaçao in the southern Caribbean. These data were used to test the degree to which spatial variability in community composition could be predicted based on assumed functional relationships and site-specific anthropogenic, physical, and ecological conditions. In general, models revealed less power to describe the spatial variability of fish biomass than cover of reef builders (R2 of best-fit models: 0.25 [fish] and 0.64 [reef builders]). The variability in total benthic cover of reef builders was best described by physical (wave exposure and reef relief) and ecological (turf algal height and coral recruit density) predictors. No metric of anthropogenic pressure was related to spatial variation in reef builder cover. In contrast, total fish biomass showed a consistent (albeit weak) association with anthropogenic predictors (fishing and diving pressure). As is typical of most environmental gradients, the spatial patterns of both fish biomass density and reef builder cover were spatially autocorrelated. Residuals from the best-fit model for fish biomass retained a signature of spatial autocorrelation while the best-fit model for reef builder cover removed spatial autocorrelation, thus reinforcing our finding that environmental predictors were better able to describe the spatial variability of reef builders than that of fish biomass. As we seek to understand spatial variability of coral reef communities at the scale of most management units (i.e., at kilometer- to island-scales), distinct and scale-dependent perspectives will be needed when considering different functional groups.
The effect of radiotherapy on fat engraftment for complete breast reconstruction using lipofilling only
Authors: Heine Norbert , Eigenberger Andreas , Brebant Vanessa , Kempa Sally , Seitz Stephan , Prantl Lukas , Kuehlmann Britta 
Published: May 2022

Abstract
Purpose
Lipofilling has been established as a standard technique for contour enhancement following breast reconstruction. However, there is a paucity in current literature regarding the use of this technique for complete reconstruction of the female breast as an alternative to conventional techniques, such as expander or flap-based procedures. In particular, the influence of pre-operative irradiation for successful reconstruction has rarely been examined in published studies. Here, the authors describe their experience with successful fat injection in pre-radiated breasts in comparison with non-pre-radiated patients.

Methods
In this retrospective study, we examined a total of 95 lipofilling treatments on 26 patients (28 breasts). All of them experienced mastectomy following breast cancer; local breast defects after partial resection of the gland were not included in this study. In total, 47 lipofilling procedures in 12 non-irradiated patients (14 breasts) and 48 procedures in 14 irradiated women (also 14 breasts) were performed. Per session, approximately 297 ± 112 cc of adipose tissue was grafted in group A (no radiotherapy) and approximately 259 ± 93 cc was grafted in group B (radiotherapy).

Results
Among the group of women without pre-operative radiation, 71% of breast reconstructions limited to lipofilling only showed constant engraftment of fat tissue with a successful reconstructive result, whereas only 21% of the patients with pre-radiated breasts showed complete reconstruction of the breast with a permanent fat in-growth.

Conclusion
Preoperative radiotherapy significantly impedes successful completion of breast reconstructions planned only by autologous fat transfer. Patients should be selected individually and carefully for complete breast reconstruction using lipofilling only.
BERT’s sentiment score for portfolio optimization: a fine-tuned view in Black and Litterman model
Authors: Colasanto Francesco , Grilli Luca , Santoro Domenico , Villani Giovanni 
Published: May 2022

AbstractIn financial markets, sentiment analysis on natural language sentences can improve forecasting. Many investors rely on information extracted from newspapers or their feelings. Therefore, this information is expressed in their language. Sentiment analysis models classify sentences (or entire texts) with their polarity (positive, negative, or neutral) and derive a sentiment score. In this paper, we use this sentiment (polarity) score to improve the forecasting of stocks and use it as a new “view” in the Black and Litterman model. This score is related to various events (both positive and negative) that have affected some stocks. The sentences used to determine the scores are taken from articles published in Financial Times (an international financial newspaper). To improve the forecast using this average sentiment score, we use a Monte Carlo method to generate a series of possible paths for several trading hours after the article was published to discretize (or approximate) the Wiener measure, which is applied to the paths and returning an exact price as results. Finally, we use the price determined in this way to calculate a yield to be used as views in a new type of “dynamic” portfolio optimization, based on hourly prices. We compare the results by applying the views obtained, disregarding the sentiment and leaving the initial portfolio unchanged.
Near-linear convergence of the Random Osborne algorithm for Matrix Balancing
Authors: Altschuler Jason M. , Parrilo Pablo A. 
Published: May 2022

AbstractWe revisit Matrix Balancing, a pre-conditioning task used ubiquitously for computing eigenvalues and matrix exponentials. Since 1960, Osborne’s algorithm has been the practitioners’ algorithm of choice, and is now implemented in most numerical software packages. However, the theoretical properties of Osborne’s algorithm are not well understood. Here, we show that a simple random variant of Osborne’s algorithm converges in near-linear time in the input sparsity. Specifically, it balances $$K \in {\mathbb {R}}_{\ge 0}^{n \times n}$$

K
∈

R

≥
0

n
×
n

after $$O(m \varepsilon ^{-2} \log \kappa )$$

O
(
m

ε

-
2

log
κ
)

arithmetic operations in expectation and with high probability, where m is the number of nonzeros in K, $$\varepsilon $$
ε
is the $$\ell _1$$

ℓ
1

accuracy, and $$\kappa = \sum _{ij} K_{ij} / ( \min _{ij : K_{ij} \ne 0} K_{ij})$$

κ
=

∑

ij

K

ij

/

(

min

i
j
:

K

ij

≠
0

K

ij

)

measures the conditioning of K. Previous work had established near-linear runtimes either only for $$\ell _2$$

ℓ
2

accuracy (a weaker criterion which is less relevant for applications), or through an entirely different algorithm based on (currently) impractical Laplacian solvers. We further show that if the graph with adjacency matrix K is moderately connected—e.g., if K has at least one positive row/column pair—then Osborne’s algorithm initially converges exponentially fast, yielding an improved runtime $$O(m \varepsilon ^{-1} \log \kappa )$$

O
(
m

ε

-
1

log
κ
)

. We also address numerical precision issues by showing that these runtime bounds still hold when using $$O(\log (n\kappa /\varepsilon ))$$

O
(
log
(
n
κ
/
ε
)
)

-bit numbers. Our results are established through an intuitive potential argument that leverages a convex optimization perspective of Osborne’s algorithm, and relates the per-iteration progress to the current imbalance as measured in Hellinger distance. Unlike previous analyses, we critically exploit log-convexity of the potential. Notably, our analysis extends to other variants of Osborne’s algorithm: along the way, we also establish significantly improved runtime bounds for cyclic, greedy, and parallelized variants of Osborne’s algorithm.
A thermoresponsive valve to control fluid flow in microfluidic paper-based devices
Authors: Iwasaki Wataru , Toda Hiroki , Morita Nobutomo , Motomura Taisei , Fujio Yuki , Takemura Kenshin , Nakanishi Yoshitaka , Nakashima Yuta 
Published: May 2022

AbstractMicrofluidic paper-based analytical devices (μPADs) have recently attracted the attention of researchers and industry owing to their various advantages. However, µPADs lack a way to control fluid flow; therefore, it is difficult to perform complex immunoassays that use multiple reagents and replace the reagents from the analytical area. We developed a controllable thermoresponsive valve for μPADs by functionalizing a polyvinylidene difluoride porous membrane with plasma-induced graft polymerization of poly(N-isopropylacrylamide) (PNIPAAm), which is a thermoresponsive polymer that changes its hydrophilic properties near the lower critical solution temperature (LCST; 32 °C). Surface analysis by attenuated total reflectance Fourier transform infrared spectroscopy confirmed that the fabricated thermoresponsive valves coated with PNIPAAm. The valve performance was evaluated by sandwiching the thermoresponsive valve between two paper microchannels stacked in a T-shaped paper microfluidic device. The thermoresponsive valve fabricated with a monomer concentration ranging from 2.3 to 3.0 wt% and a polymerization time of 5 h or 2.0 wt% and 20–22 h showed good valve performances. These valves were able to stop the flow at room temperature, and allow the flow by opening within 20 s after heating was initiated using a Peltier element located just under the valve. The valve was successfully closed, thereby stopping the flow, and opened by heating. Although a detailed evaluation of the fluid behavior is necessary, we have demonstrated that our thermoresponsive valve can be opened and closed reversibly by temperature control. We believe that this thermoresponsive valve could potentially be used to control the flow of multiple reagents in µPADs.
On the use of commit-relevant mutants
Authors: Ojdanić Miloš , Ma Wei , Laurent Thomas , Chekam Thierry Titcheu , Ventresque Anthony , Papadakis Mike 
Published: May 2022

AbstractApplying mutation testing to test subtle program changes, such as program patches or other small-scale code modifications, requires using mutants that capture the delta of the altered behaviours. To address this issue, we introduce the concept of commit-relevant mutants, which are the mutants that interact with the behaviours of the system affected by a particular commit. Therefore, commit-aware mutation testing, is a test assessment metric tailored to a specific commit. By analysing 83 commits from 25 projects involving 2,253,610 mutants in both C and Java, we identify the commit-relevant mutants and explore their relationship with other categories of mutants. Our results show that commit-relevant mutants represent a small subset of all mutants, which differs from the other classes of mutants (subsuming and hard-to-kill), and that the commit-relevant mutation score is weakly correlated with the traditional mutation score (Kendall/Pearson 0.15-0.4). Moreover, commit-aware mutation analysis provides insights about the testing of a commit, which can be more efficient than the classical mutation analysis; in our experiments, by analysing the same number of mutants, commit-aware mutants have better fault-revelation potential (30% higher chances of revealing commit-introducing faults) than traditional mutants. We also illustrate a possible application of commit-aware mutation testing as a metric to evaluate test case prioritisation.
Solar Radiation and Climate Experiment (SORCE) X-Ray Photometer System (XPS): Final Data-Processing Algorithms
Authors: Woods Thomas N. , Elliott Joshua 
Published: May 2022

AbstractThe X-ray Photometer System (XPS) is one of four instruments onboard NASA’s Solar Radiation and Climate Experiment (SORCE) mission. The SORCE spacecraft operated from 2003 to 2020 to provide key climate-monitoring measurements of total solar irradiance (TSI) and solar spectral irradiance (SSI). The XPS is a set of photometers to measure the solar X-ray ultraviolet (XUV) irradiance shortward of 34 nm and the bright hydrogen emission at 121.6 nm. Each photometer has a spectral bandpass of about 7 nm, and the XPS measurements have an accuracy of about 20%. The updates for the final data-processing algorithms for the XPS solar-irradiance data products are described. These processing updates include improvements for the instrumental corrections for background signal, visible-light signal, and degradation trending. Validation of these updates is primarily with measurements from a very similar XPS instrument onboard NASA’s Thermosphere-Ionosphere-Mesosphere-Energetics-Dynamics (TIMED) mission. In addition, the XPS Level 4 spectral model has been improved with new reference spectra derived with recent XUV observations from NASA’s Solar Dynamics Observatory (SDO) and Miniature X-ray Solar Spectrometer (MinXSS) cubesat.