bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis, Crystal Structure and Luminescent Properties of a 3D Mg(II)−Sm(III) Heterometallic Coordination Polymer Containing 20‐member Water Clusters
Authors: Chen Yanmei , Liu Shanshan , Lin Junqi , Liu Siyu , Ruan Zhijun 
Published: December 2020

AbstractA new Mg(II)−Sm(III) heterometallic coordination polymer (Cp) with the formula [Sm2(pydc)6Mg3(H2O)6] ⋅ 11H2O (1) (H2pydc=pyridine‐2,6‐dicarbolylic acid) has been solvothermal synthesized by reacting pyridine‐2,6‐dicarbolylic acid, Sm(NO3)3 ⋅ 6H2O, MgCl2 ⋅ 6H2O and imidazole at 393 K for 48 h. It was characterized by single‐crystal X‐ray diffraction, elemental analysis, IR and TGA. The results show that coordination polymer 1 exhibits a three‐dimensional network structure and crystallizes in hexagonal crystal system, space group P6/mcc, with crystallographic data of a=15.4203(6) Å, b=15.4203(6) Å, c=15.2563(6) Å, α=β=90°, γ=120°, V=3141.7(3) Å3, and Z=2. The twenty‐member water cluster structure and topological structure of compound 1 were analyzed, and its luminescent properties were studied. It presents the characteristic emission spectra of Sm(III) ions.
Aufnahmediagnose Prellung: Ätiologie, Epidemiologie und Kostenfaktoren
Authors: Woschek Mathias , Schindler Cora R. , Sterz Jasmina , Störmann Philipp , Willems Laurent , Marzi Ingo , Verboket René D. 
Published: December 2020

Zusammenfassung
Hintergrund
Die stationäre Aufnahme von Patienten mit Prellungen wird in Kliniken der Akutversorgung regelhaft praktiziert. Dabei stehen die pathophysiologischen Unfallfolgen oft im Hintergrund. Ziel dieser retrospektiven monozentrischen Untersuchung war die Untersuchung der Ätiologie sowie der kostenverursachenden Faktoren und Refinanzierung bei Aufnahmen durch Prellungen.

Methodik
Es erfolgte die Abfrage der Patienten entsprechend den Entlassdiagnosen aus dem krankenhausinternen Informationssystem (KIS). Eingeschlossen wurden 117 Patienten in einem Zeitraum von 2 Jahren. Es erfolgten hier die Klassifizierung nach Unfallmechanismus sowie die Einteilung in Altersgruppen. Des Weiteren erfolgte die Kostenkalkulation anhand von abteilungs- und klinikspezifischen Tagessätzen.

Ergebnisse
Bezüglich der Ätiologie war der häusliche Sturz die häufigste Ursache (48,7 %), gefolgt von dem Hochrasanztrauma (22,8 %). Innerhalb der Gruppe des häuslichen Sturzes lag das Durchschnittsalter im Mittel bei 77,8 Jahre. Diese Gruppe zeigte die längste Verweildauer (VWD) mit 5,2 Tagen. Im Rahmen der kalkulierten Kosten zeigte die Gruppe nach häuslichem Sturz die höchsten Kosten mit 2596,24 € bei einem mittleren DRG-Erlös von 1464,51 €.

Diskussion
Die Auswertung der klinikinternen Daten bestätigte die subjektive Wahrnehmung, dass ein Großteil der nach Prellung aufgenommenen Patienten aus der Altersgruppe >65 Jahre stammt. Die Aufnahme erfolgt hier vor dem Hintergrund der in dieser Altersgruppe zunehmenden Komorbiditäten sowie zur Abwendung von Folgeerkrankungen und Folgen der Immobilisierung. Ebenfalls konnte gezeigt werden, dass die Versorgungskosten gesundheitsökomisch relevant sind und die Behandlung in diesen Fällen nicht kostendeckend ist.
The faster the better? Time to first CT scan after admission in moderate-to-severe traumatic brain injury and its association with mortality
Authors: Mader Marius Marc-Daniel , Rotermund Roman , Lefering Rolf , Westphal Manfred , Maegele Marc , Czorlich Patrick ,   the TraumaRegister DGU
Published: December 2020

AbstractFast acquisition of a first computed tomography (CT) scan after traumatic brain injury (TBI) is recommended. This study is aimed at investigating whether the length of the period preceding initial CT scan influences mortality in patients with leading TBI. A retrospective cohort analysis of patients registered in the TraumaRegister DGU® was conducted including adult patients with TBI, defined as Abbreviated Injury ScaleHead ≥ 3 and GCS ≤ 13 who had been treated in level 1 or 2 trauma centers from 2007–2016. Patients were grouped according to time intervals either from trauma or from admission to CT. A total of 6904 patients met the inclusion criteria. Mean time period from trauma to hospital admission was 68.8 min. From admission to first CT, a mean of 19.0 min elapsed. Trauma severity was higher in groups with a longer duration from trauma to CT as represented by a mean (± standard deviation) Injury Severity Score (ISS) of 19.8 ± 9.0, 20.7 ± 9.3, and 21.4 ± 7.5 and similar distribution of mortality of 24.9%, 29.9%, and 36.3% in the ≤ 60-min, 61–120-min, and ≥ 121-min groups, respectively. An adjusted multivariable logistic regression model showed a significant influence of the level of the trauma center (p = 0.037) but not for interval from admission to CT (p = 0.528). TBI patients with a longer time span from trauma to first CT were more severely injured and demonstrated a worse prognosis, but received a CT scan faster when duration from admission is observed. The duration until the CT scan was obtained showed no significant impact on the mortality.
A Numerical Investigation of the Effects of Fuel Composition on the Minimum Ignition Energy for Homogeneous Biogas-Air Mixtures
Authors: Papapostolou Vassilios , Turquand d’Auzay Charles , Chakraborty Nilanjan 
Published: December 2020

AbstractThe minimum ignition energy (MIE) requirements for ensuring successful thermal runaway and self-sustained flame propagation have been analysed for forced ignition of homogeneous stoichiometric biogas-air mixtures for a wide range of initial turbulence intensities and CO2 dilutions using three-dimensional Direct Numerical Simulations under decaying turbulence. The biogas is represented by a CH4 + CO2 mixture and a two-step chemical mechanism involving incomplete oxidation of CH4 to CO and H2O and an equilibrium between the CO oxidation and the CO2 dissociation has been used for simulating biogas-air combustion. It has been found that the MIE increases with increasing CO2 content in the biogas due to the detrimental effect of the CO2 dilution on the burning and heat release rates. The MIE for ensuring self-sustained flame propagation has been found to be greater than the MIE for ensuring only thermal runaway irrespective of its outcome for large root-mean-square (rms) values of turbulent velocity fluctuation, and the MIE values increase with increasing rms turbulent velocity for both cases. It has been found that the MIE values increase more steeply with increasing rms turbulent velocity beyond a critical turbulence intensity than in the case of smaller turbulence intensities. The variations of the normalised MIE (MIE normalised by the value for the quiescent laminar condition) with normalised turbulence intensity for biogas-air mixtures are found to be qualitatively similar to those obtained for the undiluted mixture. However, the critical turbulence intensity has been found to decrease with increasing CO2 dilution. It has been found that the normalised MIE for self-sustained flame propagation increases with increasing rms turbulent velocity following a power-law and the power-law exponent has been found not to vary much with the level of CO2 dilution. This behaviour has been explained using a scaling analysis and flame wrinkling statistics. The stochasticity of the ignition event has been analysed by using different realisations of statistically similar turbulent flow fields for the energy inputs corresponding to the MIE and it has been demonstrated that successful outcomes are obtained in most of the instances, justifying the accuracy of the MIE values identified by this analysis.
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
Authors: Ruiz Alejandro Pasos , Flynn Michael , Large James , Middlehurst Matthew , Bagnall Anthony 
Published: December 2020

AbstractTime Series Classification (TSC) involves building predictive models for a discrete target variable from ordered, real valued, attributes. Over recent years, a new set of TSC algorithms have been developed which have made significant improvement over the previous state of the art. The main focus has been on univariate TSC, i.e. the problem where each case has a single series and a class label. In reality, it is more common to encounter multivariate TSC (MTSC) problems where the time series for a single case has multiple dimensions. Despite this, much less consideration has been given to MTSC than the univariate case. The UCR archive has provided a valuable resource for univariate TSC, and the lack of a standard set of test problems may explain why there has been less focus on MTSC. The UEA archive of 30 MTSC problems released in 2018 has made comparison of algorithms easier. We review recently proposed bespoke MTSC algorithms based on deep learning, shapelets and bag of words approaches. If an algorithm cannot naturally handle multivariate data, the simplest approach to adapt a univariate classifier to MTSC is to ensemble it over the multivariate dimensions. We compare the bespoke algorithms to these dimension independent approaches on the 26 of the 30 MTSC archive problems where the data are all of equal length. We demonstrate that four classifiers are significantly more accurate than the benchmark dynamic time warping algorithm and that one of these recently proposed classifiers, ROCKET, achieves significant improvement on the archive datasets in at least an order of magnitude less time than the other three.
Nonlinear interaction between self- and parametrically excited wind-induced vibrations
Authors: Di Nino Simona , Luongo Angelo 
Published: December 2020

AbstractThe aeroelastic behavior of a planar prismatic visco-elastic structure, subject to a turbulent wind, flowing orthogonally to its plane, is studied in the nonlinear field. The steady component of wind is responsible for a Hopf bifurcation occurring at a threshold critical value; the turbulent component, which is assumed to be a small harmonic perturbation of the former, is responsible for parametric excitation. The interaction between the two bifurcations is studied in a three-dimensional parameter space, made of the two wind amplitudes and the frequency of the turbulence. Aeroelastic forces are computed by the quasi-static theory. A one-D.O.F dynamical system, drawn by a Galerkin projection of the continuous model, is adopted. The multiple scale method is applied, to get a two-dimensional bifurcation equation. A linear stability analysis is carried out to determine the loci of periodic and quasi-periodic bifurcations. Limit cycles and tori are computed by exact, asymptotic, and numerical solutions of the bifurcation equations. Numerical results are obtained for a sample structure, and compared with finite-difference solutions of the original partial differential equation of motion.
Generation and robustness of quantum entanglement in spin graphs
Authors: Riegelmeyer Jan , Wignall Dan , Estarellas Marta P. , D’Amico Irene , Spiller Timothy P. 
Published: December 2020

AbstractEntanglement is a crucial resource for quantum information processing, and so protocols to generate high-fidelity entangled states on various hardware platforms are in demand. While spin chains have been extensively studied to generate entanglement, graph structures also have such potential; however, only a few classes of graphs have been explored for this specific task. In this paper, we apply a particular coupling scheme involving two different coupling strengths to a graph of two interconnected $$3\times 3$$

3
×
3

square graphs such that it effectively contains three defects. We show how this structure allows generation of a Bell state whose fidelity depends on the chosen coupling ratio. We apply partitioned graph theory in order to reduce the dimension of the graph and show that, using a reduced graph or a reduced chain, we can still simulate the same protocol with identical dynamics. Finally, we investigate how fabrication errors affect the entanglement generation protocol and how the different equivalent structures are affected, finding that for some specific coupling ratios they are extremely robust.
Out-of-hospital cardiac arrest in dialysis patients
Authors: Obremska Marta , Madziarska Katarzyna , Zyśko Dorota , Ładny Jerzy R. , Gałązkowski Robert , Gąsior Mariusz , Nadolny Klaudiusz 
Published: December 2020

AbstractPurposeThe aim of the study was to assess whether a history of dialysis is related to cardiopulmonary resuscitation (CPR) attempts and survival to hospital admission in patients with out-of-hospital cardiac arrest (OHCA).MethodsThe databases of the POL-OHCA registry and of emergency medical calls in the Command Support System of the State of Emergency Medicine (CSS) were searched to identify patients with OHCA and a history of dialysis. A total of 264 dialysis patient with OHCA were found: 126 were dead on arrival of emergency medical services (EMS), and 138 had OHCA with CPR attempts. Data from the POL-OHCA registry for patients with CPR attempts, including age, sex, place of residence, first recorded rhythm, defibrillation during CPR, and priority dispatch codes, were collected and compared between patients with and without dialysis.ResultsCPR attempts by EMS were undertaken in 138 dialyzed patients (52.3%). The analysis of POL-OHCA data revealed no differences in age, sex, place of residence, first recorded rhythm, and priority dispatch codes between patients with and without dialysis. Defibrillation was less frequent in dialysis patients (P = 0.04). A stepwise logistic regression analysis revealed no association between survival to hospital admission and a history of hemodialysis (odds ratio = 1.12; 95% CI 0.74–1.70,P = 0.60).ConclusionsA history of dialysis in patients with OHCA does not affect the rate of CPR attempts by EMS or a short-term outcome in comparison with patients without dialysis. Defibrillation during CPR is less common in patients on dialysis than in those without.
Self-Compassion and Instagram Use Is Explained by the Relation to Anxiety, Depression, and Stress
Authors: Keyte Rebecca , Mullis Lauren , Egan Helen , Hussain Misba , Cook Amy , Mantzios Michail 
Published: December 2020

AbstractPrevious research acknowledges that prolonged social media use is associated with several negative psychological consequences, including higher levels of depression, anxiety, and stress. In order to protect individuals from social stressors, research illustrates the role that self-compassion can play, with individuals high in self-compassion reporting greater emotional wellbeing; hence, proposing self-compassion could be a trait that is positively related to social media use. This research aimed to investigate the relationship between Instagram use and self-compassion, and whether this relationship can be explained through the relation to psychological wellbeing (depression, anxiety, and stress). A cross-sectional study was conducted to investigate this relationship amongst young adults (n = 173), utilizing a revised version of The Multidimensional Facebook Intensity Scale to explore Instagram, The Self-Compassion Scale, and the Depression, Anxiety, and Stress Scale. Instagram intensity appeared to influence psychological wellbeing, with participants who spent more time on Instagram reporting poorer psychological wellbeing. Whilst higher levels of self-compassion were associated with lower levels of reported depression, anxiety, and stress, the relationship between Instagram intensity and self-compassion was not mediated to the extent as expected by wellbeing. Possible explanations and future directions are discussed as to what could explain the positive relationship between self-compassion and Instagram use.
Denoising Autoencoder, A Deep Learning Algorithm, Aids the Identification of A Novel Molecular Signature of Lung Adenocarcinoma
Authors: Wang Jun , Xie Xueying , Shi Junchao , He Wenjun , Chen Qi , Chen Liang , Gu Wanjun , Zhou Tong 
Published: December 2020

Abstract
Precise biomarker development is a key step in disease management. However, most of the published biomarkers were derived from a relatively small number of samples with supervised approaches. Recent advances in unsupervised machine learning promise to leverage very large datasets for making better predictions of disease biomarkers. Denoising autoencoder (DA) is one of the unsupervised deep learning algorithms, which is a stochastic version of autoencoder techniques. The principle of DA is to force the hidden layer of autoencoder to capture more robust features by reconstructing a clean input from a corrupted one. Here, a DA model was applied to analyze integrated transcriptomic data from 13 published lung cancer studies, which consisted of 1916 human lung tissue samples. Using DA, we discovered a molecular signature composed of multiple genes for lung adenocarcinoma (ADC). In independent validation cohorts, the proposed molecular signature is proved to be an effective classifier for lung cancer histological subtypes. Also, this signature successfully predicts clinical outcome in lung ADC, which is independent of traditional prognostic factors. More importantly, this signature exhibits a superior prognostic power compared with the other published prognostic genes. Our study suggests that unsupervised learning is helpful for biomarker development in the era of precision medicine.
Exploring Potential Signals of Selection for Disordered Residues in Prokaryotic and Eukaryotic Proteins
Authors: Panda Arup , Tuller Tamir 
Published: December 2020

Abstract
Intrinsically disordered proteins (IDPs) are an important class of proteins in all domains of life for their functional importance. However, how nature has shaped the disorder potential of prokaryotic and eukaryotic proteins is still not clearly known. Randomly generated sequences are free of any selective constraints, thus these sequences are commonly used as null models. Considering different types of random protein models, here we seek to understand how the disorder potential of natural eukaryotic and prokaryotic proteins differs from random sequences. Comparing proteome-wide disorder content between real and random sequences of 12 model organisms, we noticed that eukaryotic proteins are enriched in disordered regions compared to random sequences, but in prokaryotes such regions are depleted. By analyzing the position-wise disorder profile, we show that there is a generally higher disorder near the N- and C-terminal regions of eukaryotic proteins as compared to the random models; however, either no or a weak such trend was found in prokaryotic proteins. Moreover, here we show that this preference is not caused by the amino acid or nucleotide composition at the respective sites. Instead, these regions were found to be endowed with a higher fraction of protein–protein binding sites, suggesting their functional importance. We discuss several possible explanations for this pattern, such as improving the efficiency of protein–protein interaction, ribosome movement during translation, and post-translational modification. However, further studies are needed to clearly understand the biophysical mechanisms causing the trend.
Impact of Cavity Shave Margins on Margin Status in Patients with Pure Ductal Carcinoma In Situ
Authors: Howard-McNatt Marissa , Dupont Elisabeth , Tsangaris Theodore , Garcia-Cantu Carlos , Chiba Akiko , Berger Adam C. , Levine Edward A. , Gass Jennifer S. , Ollila David W. , Chagpar Anees B. , Gallagher Kristalyn , Lum Sharon S. , Martinez Ricardo D. , Willis Alliric I. , Pandya Sonali V. , Brown Eric A. , Fenton Andrew , Mendiola Amanda , Murray Mary , Haddad Victor , Solomon Naveenraj L. , Senthil Maheswari , Bansil Hannah , Snyder Samuel K. , Edmonson David , Lazar Melissa , Namm Jukes P. , Li Fangyong , Butler Meghan , McGowan Noreen E. , Herrera Maria E. , Avitan Yoana P. , Yoder Brian , McPartland Tara , Chagpar Anees B. 
Published: December 2020

BACKGROUND:
We examined the impact of cavity shave margins (CSMs) on margin status in patients with pure ductal carcinoma in situ (DCIS) undergoing partial mastectomy (PM).

METHODS:
One hundred and nine patients from 2 multicenter, randomized controlled trials were identified with pure DCIS (no invasive cancer). Surgeons performed their best PM, with specimen radiography and resection of selective margins per surgeon discretion. Patients were then randomized to have CSM resected or not. A positive margin was defined as <2 mm from ink.

RESULTS:
Median patient age was 63 years; median size of DCIS was 1.20 cm; 43.6% of patients had high-grade DCIS; and 58 (53.2%) patients were randomized to take CSM. The “shave” and “no-shave” groups were well-matched for age, race, ethnicity, palpability, grade, and size of DCIS. Although 33 (56.9%) of the patients in the shave group had a positive margin before randomization, only 12 (20.7%) had a positive margin after randomization to CSM (p < 0.001). In the no-shave group, 17 patients (33.3%) had a positive margin. Controlling for size and grade of DCIS, taking CSM resulted in a nearly 65% reduction in the positive-margin rate (odds ratio 0.366; 95% CI, 0.136 to 0.981; p = 0.046). Size of DCIS remained an independent predictor of positive margins in the model (odds ratio 1.646; 95% CI, 1.227 to 2.209; p = 0.001).

CONCLUSIONS:
CSM reduces positive-margin rates in patients with pure DCIS, and can be a practical solution for DCIS patients who tend to have a high rate of margin positivity.
BRIDGING THE GAP EBIII-IBA: EARLY INTERMEDIATE BRONZE RADIOCARBON DATES FROM KHIRBAT EL-’ALYA NORTHEAST, ISRAEL
Authors: Lev Ron , Shalev Omer , Regev Johanna , Paz Yitzhak , Boaretto Elisabetta 
Published: December 2020

ABSTRACTRecent radiocarbon (14C) research demonstrates that the urban culture of Early-Bronze III in the southern Levant ends around 2500 BC, and not around 2300 BC as was widely assumed. This should extend the Intermediate Bronze Age by 200 years. Charred olive pits from Intermediate Bronze Age contexts in the site of Khirbat el-‘Alya Northeast in the Judean Shephelah region (Israel) were14C dated, resulting in calibrated dates around 2500 BC. The date range of Khirbat el-‘Alya Northeast samples is an indication that in the Mediterranean parts of the southern Levant, the Intermediate Bronze Age material culture appeared around the time of the decline of the preceding culture of Early-Bronze III—around 2500 BC or somewhat earlier. Possible Intermediate Bronze settlement pattern and the site’s relation to the nearby Early-Bronze city of Tel Yarmuth are discussed based on previous Intermediate Bronze and Early-Bronze related research in the surrounding area.