bluuebunny/crossref_metadata_2025_split huggingface dataset:
Krebsregister in Deutschland: Was bringt die Zukunft für die Urologie?
Authors: Kraywinkel Klaus , Flegar Luka , Huber Johannes , Groeben Christer 
Published: April 2023

Zusammenfassung
Als Krebsregister werden systematisch gesammelte Informationen in Form einer Datenbank zu Tumorerkrankungen bezeichnet. Sie können Auskunft über die Qualität der onkologischen Versorgung oder Fortschritte in der Therapie der einzelnen Krebsarten über die Zeit liefern. Seit 1995 sind alle Deutschen Bundesländer gesetzlich verpflichtet ein Krebsregister aufzubauen und zu führen. Das Zentrum für Krebsregisterdaten (ZfKD) am Robert Koch-Institut sammelt diese bundesweiten Daten seit dem Jahre 2009 und führt diese in einen jährlich geprüften Datensatz zusammen, welcher für Forschungszwecke verfügbar ist. Im Rahmen des Krebsfrüherkennungs- und registergesetzes (KFRG) welches 2013 verabschiedet wurde, bekamen die Krebsregister eine neue Ausrichtung. So leisten sie seither einen zentralen Beitrag zur Qualitätssicherung der onkologischen Versorgung in Deutschland. Die Finanzierung der Krebsregister wird im Wesentlichen durch die Krankenkassen getragen. Eine anstehende Erweiterung des Datensatzes um klinische Variablen und die frühere Bereitstellung durch das ZfKD ab dem kommenden Jahr bietet neue Möglichkeiten für die wissenschaftliche Nutzung der Krebsregister-Daten. Dabei wird insbesondere der Krankheitsverlauf nun deutlich detaillierter abgebildet werden. Neben den Krebsregistern bestehen in Deutschland nur wenige sinnvolle Ergänzungen zur Beurteilung der flächendeckenden Versorgungssituation und Behandlungsrealität auf nationaler Ebene. Die fallpauschalbezogene Krankenhausstatistik (DRG-Datenbank) des Statistischen Bundesamtes erfasst sämtliche Abrechnungsdaten aller deutschen Krankenhäuser mit wenigen Ausnahmen. Eine weitere interessante Ergänzung zu den Krebsregisterdaten bieten die Datensätze der strukturierten Qualitätsberichte, welche seit 2003 für deutsche Krankenhäuser verpflichtend sind. Zukünftig soll durch das in 2021 beschlossene Gesetz zur Zusammenführung von Krebsregisterdaten die wissenschaftliche Rolle der Krebsregister weiter aufgewertet werden.
Visible-Light-Responsive Nano CuO/ZnO Photocatalyst for Chan–Lam Coupling Reaction and Aerobic C(sp3)–H Bond Oxidation
Authors: Hosseini-Sarvari Mona , Daneshvar Mohammad Reza , Tavakolian Mina 
Published: April 2023

AbstractWhen it comes to heterogeneous photocatalysts, semiconductors are the best candidate with a high potential to respond in visible-light regions. In this study, semiconductor p-n heterojunction, nano CuO/ZnO, was synthesized via a simple, sustainable, and low-cost approach. Photocatalytic activity of the synthesized material with a 2.02 eV band gap was investigated in the Chan–Lam coupling reaction and C(sp3)–H bond oxidation of alkyl aromatic compounds under visible-light irradiation in aqueous solution. In the case of the Chan–Lam coupling reaction, various derivatives of aniline and arylboronic acid successfully took part in the reaction, delivering the desired products in 57–89% yields. In addition, nano CuO/ZnO photocatalyst showed high efficiency in the C(sp3)–H bond oxidation of alkyl aromatic compounds under air as a green oxidant. Noticeably, the photocatalyst showed high performance in the large-scale synthesis of desired products and maintained activity after several uses.
Prevalence of Cardiovascular Risk Factors and Associated Estimated Risk of Atherosclerotic Cardiovascular Disease in Adult Volunteers in Jeddah, Saudi Arabia
Authors: Ismaeil Nabeel H. , Chaudhary Ammar G. , Mahdi Nasser A. , Al-Hyari Adel M. , Aljohani Naji 
Published: April 2023

Abstract
Background The prevalence of cardiovascular disease and its risk factors are rising globally, including in the Kingdom of Saudi Arabia (KSA). The majority of epidemiologic data, however, was obtained from primary care centers or tertiary hospitals, and disease epidemiology in the general population needs to be better defined.
Objective: This study aims to determine the prevalence of cardiometabolic risk factors in a random sample of adult volunteers in Jeddah, Saudi Arabia, and their risk for atherosclerotic cardiovascular disease (ASCVD).
Materials and Methods This cross-sectional study was based on data from volunteers participating in the “My Heart, My Health” community campaign conducted in a large-scale commercial center in Jeddah, KSA. Participants 20 years of age and above answered a questionnaire containing several risk factors of ASCVD. Anthropometric measurements and blood samples were collected for lipid profile and hemoglobin A1c. Ten-year and lifelong ASCVD risk scores were calculated.
Results Eight-hundred seven volunteers participated (390 men and 417 women). The most common risk factor for men was low-high-density lipoprotein cholesterol, which was more prevalent than in women (77.9 vs. 30.3%, p < 0.01). The most common risk factor for women was obesity that was more prevalent than for men (42.6 vs. 36.8%, p = 0.30). The mean ASCVD risk score in 10 years was 8.1% (standard deviation [SD]: 10.5), and the mean ASCVD risk factor optimization % was 2.0% (SD: 2.5). The mean lifelong risk score was 39.5% (SD: 13.9), and the mean ASCVD lifelong risk factor optimization was 6.6% (SD: 2.6).
Conclusion This study identified a high prevalence of cardiometabolic risk factors in the Saudi general public visiting a large commercial center in Jeddah, Saudi Arabia. The leading cardiometabolic risk factor is dyslipidemia in men and obesity in women. The 10-year ASCVD risk factor score is modest.
The EU and its paradoxes: enforcing stability not promoting democracy
Authors: Dana Tariq 
Published: April 2023

AbstractThis critical analysis explores the contradictions between the European Union's (EU) democracy promotion rhetoric and the underlying motivations behind these efforts, specifically in the context of the 2006 Palestinian elections. Contrary to the traditional perception that EU democracy promotion aims to establish and strengthen democratic institutions and practices, this review argues that the primary goal is often to enforce stability under the expansive settler-colonial structure. The Palestinian elections of 2006 serve as a pertinent case study to illustrate this paradox. The EU's response to the victory of Hamas was marked by inconsistencies and contradictions, revealing the tension between its democracy promotion rhetoric and the prioritization of a kind of stability based on Israeli terms.
Spectra and characteristics of somatic mutations induced by ionizing radiation in hematopoietic stem cells
Authors: Matsuda Yukiko , Uchimura Arikuni , Satoh Yasunari , Kato Naohiro , Toshishige Masaaki , Kajimura Junko , Hamasaki Kanya , Yoshida Kengo , Hayashi Tomonori , Noda Asao , Tanabe Osamu 
Published: April 2023

Spectra and frequencies of spontaneous and X-ray-induced somatic mutations were revealed with mouse long-term hematopoietic stem cells (LT-HSCs) by whole-genome sequencing of clonal cell populations propagated in vitro from single isolated LT-HSCs. SNVs and small indels were the most common types of somatic mutations, and increased up to twofold to threefold by whole-body X-irradiation. Base substitution patterns in the SNVs suggested a role of reactive oxygen species in radiation mutagenesis, and signature analysis of single base substitutions (SBS) revealed a dose-dependent increase of SBS40. Most of spontaneous small deletions were shrinkage of tandem repeats, and X-irradiation specifically induced small deletions out of tandem repeats (non-repeat deletions). Presence of microhomology sequences in non-repeat deletions suggested involvement of microhomology mediated end-joining repair mechanisms as well as nonhomologous end-joining in radiation-induced DNA damages. We also identified multisite mutations and structural variants (SV), i.e., large indels, inversions, reciprocal translocations, and complex variants. The radiation-specificity of each mutation type was evaluated from the spontaneous mutation rate and the per-Gy mutation rate estimated by linear regression, and was highest with non-repeat deletions without microhomology, followed by those with microhomology, SV except retroelement insertions, and multisite mutations; these types were thus revealed as mutational signatures of ionizing radiation. Further analysis of somatic mutations in multiple LT-HSCs indicated that large fractions of postirradiation LT-HSCs originated from single LT-HSCs that survived the irradiation and then expanded in vivo to confer marked clonality to the entire hematopoietic system, with varying clonal expansion and dynamics depending on radiation dose and fractionation.
Dynamic Fourier ptychography with deep spatiotemporal priors
Authors: Bohra Pakshal , Pham Thanh-an , Long Yuxuan , Yoo Jaejun , Unser Michael 
Published: April 2023

Abstract
Fourier ptychography (FP) involves the acquisition of several low-resolution intensity images of a sample under varying illumination angles. They are then combined into a high-resolution complex-valued image by solving a phase-retrieval problem. The objective in dynamic FP is to obtain a sequence of high-resolution images of a moving sample. There, the application of standard frame-by-frame reconstruction methods limits the temporal resolution due to the large number of measurements that must be acquired for each frame. In this work instead, we propose a neural-network-based reconstruction framework for dynamic FP. Specifically, each reconstructed image in the sequence is the output of a shared deep convolutional network fed with an input vector that lies on a one-dimensional manifold that encodes time. We then optimize the parameters of the network to fit the acquired measurements. The architecture of the network and the constraints on the input vectors impose a spatiotemporal regularization on the sequence of images. This enables our method to achieve high temporal resolution without compromising the spatial resolution. The proposed framework does not require training data. It also recovers the pupil function of the microscope. Through numerical experiments, we show that our framework paves the way for high-quality ultrafast FP.
Breakdown characteristics in dielectric-confined microcavity discharge of plate electrodes
Authors: Wang Wenjing , Zhang Tianliang , Han Ruoyu , He Feng , Ouyang Jiting 
Published: April 2023

Abstract
Breakdown characteristics in dielectric-confined microcavity discharge of plate-to-plate electrodes under DC voltage are investigated in this paper. Experimental and particle-in-cell/Monte Carlo code simulated results show that the breakdown characteristic curve (the relation between the breakdown voltage V
br and the product pd of gas pressure p and electrode gap d or the V
br–pd curve) with a microcavity effect will deviate from the traditional Paschen curve, and seed electron adsorption by the dielectric wall is considered as the deviation mechanism. A smaller microcavity height will enhance this deviation. Based on the extent of deviation, there exist two critical microcavity heights, h
cr1 and h
cr2, for the breakdown characteristic curve. When the cavity height h is larger than h
cr1, the V
br–pd curve conforms to Paschen’s law due to the minor adsorbed electrons. When h < h
cr1, the V
br values in the V
br–pd curve begin to increase overall, compared to those in the Paschen curve. Specifically, when h
cr2 < h < h
cr1, the V
br–1/h curve exhibits a positive linear relation; when h < h
cr2, V
br increases sharply with 1/h as a nonlinear relationship due to the massive adsorbed electrons. Additionally, the type of dielectric material used to construct the microcavity also has a significant impact on V
br, which is related to the different electron adsorbility η of various dielectric walls. For deeper insight, a ‘microcavity effect’ analysis model was developed to discuss the modified V
br–pd curve and provide the explanation for the critical values of microcavity heights and the influence of the dielectric material. Significant adsorption of charged particles (especially the seed electrons) by the dielectric wall will reduce the electron multiplication and further improve the breakdown voltage when the cavity height h is comparable to the product ηλ
e (the dielectric electron adsorbility and electron mean free path). On this basis, the modified breakdown criterion considering the microcavity effect was derived. The analytical expressions of the two critical height values h
cr1 and h
cr2 (h
cr1 = 100ηλ
e, h
cr2 = 10ηλ
e) and the linear relation of V
br–1/h curve in h
cr2 < h< h
cr1 are presented quantitatively.
Bearing remaining useful life prediction using spatial-temporal multiscale graph convolutional neural network
Authors: Yang Xiaoyu , Li Xinye , Zheng Ying , Zhang Yong , Wong David Shan-Hill 
Published: April 2023

Abstract
Remaining useful life (RUL) prediction of bearings is important to guarantee their reliability and formulate a maintenance strategy. Recently, deep graph neural networks (GNNs) have been applied to predict the RUL of bearings. However, they usuallylack dynamic features, use manual stage identification, and experience the over-smoothing problem, which will have a negative effect on the prediction accuracy. This paper proposes a new framework for bearing RUL prediction based on spatial-temporal multi-scale graph convolutional neural network (STMSGCN), which can improve the accuracy of prediction by solving the above-mentioned problems. Specifically, different to the most-used static feature of bearings, a dynamic feature that can capture the time-varying change of vibration energy is proposed. A sliding window alarm method is proposed to detect the fault occurrence time (FOT), which can offer an accurate healthy stage rather than human-defined methods. Then, the STMSGCN is proposed to predict the RUL of bearings, which solves the over-smoothing problem of the deep GNN model. The PRONOSTIA platform is adopted to verify the proposed method. The results verify that the sliding window alarm method can detect the FOT faster for slowly degrading bearings, and the proposed STMSGCN structure gives higher prediction accuracy compared to the existing methods.
Index theorems for graph-parametrized optimal control problems
Authors: Agrachev Andrei , Baranzini Stefano , Beschastnyi Ivan 
Published: April 2023

Abstract
In this paper we prove Morse index theorems for a big class of constrained variational problems on graphs. Such theorems are useful in various physical and geometric applications. Our formulas compute the difference of Morse indices of two Hessians related to two different graphs or two different sets of boundary conditions. Some applications such as the iteration formulas and lower bounds for the index are proved.
Design development and control of a shape memory alloy linear actuation based XYθ motion stage
Authors: Choudhury Rutupurna , Singh Yogesh 
Published: April 2023

Abstract
This article addresses the development and trajectory tracking analysis of the three degrees of freedom Shape memory alloy (SMA) actuation-based 4-
P
PR

XY
θ

motion stage. The developed motion stage is of four legs of the PPR (Prismatic-Prismatic-Revolute) configuration, having the first prismatic joint as the active joint. SMA spring is incorporated as the linear actuator of the motion stage. The three degrees of freedom motion of the end-effector is achieved based on a new type of SMA-driven PPR joint configuration to provide two translations and one rotational motion. The advantages of the SMA as an actuator is such as lightweight, higher accuracy, and micron-level movement to establish linear motion and silent actuation. The kinematic and jacobian relations are derived for the developed motion stage. The actuation of the SMA (Nitinol) spring actuator is accomplished by the use of a programmable power supply. In addition, the close loop PID control scheme to the SMA linear actuator is investigated. The mechanism has some inherent errors, as geometric errors (kinematic error), friction between the elements of the mechanism, etc, are significant issues in tracking the trajectory of the motion stage. Thus, to address the above issues, this study incorporates the dual-loop control scheme for better trajectory tracking and error compensation of the proposed motion stage. The control method employs a redundant feedback approach, in which discrete joint space displacements and mobile platform coordinates, and task space coordinates are determined as feedback signal using suitable sensors. In this control scheme, the actual joint displacement errors are computed using the redundant feedback data and corrected the desired joint displacement trajectory to obtain the desired task space trajectory. To measure the effectiveness of the used control scheme, a real-time prototype of the proposed motion stage (4-
P
PR) is developed and investigated the performance of the control method using some simple geometric trajectories. It is observed from the experiments that the motion stage using SMA linear actuation technique has good tracking performance using the control scheme. The developed motion stage can be implemented in the micro-stereolithography process and micron-level positioning application.
Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification
Authors: Gruich Cameron J , Madhavan Varun , Wang Yixin , Goldsmith Bryan R 
Published: April 2023

AbstractIt is critical that machine learning (ML) model predictions be trustworthy for high-throughput catalyst discovery approaches. Uncertainty quantification (UQ) methods allow estimation of the trustworthiness of an ML model, but these methods have not been well explored in the field of heterogeneous catalysis. Herein, we investigate different UQ methods applied to a crystal graph convolutional neural network to predict adsorption energies of molecules on alloys from the Open Catalyst 2020 dataset, the largest existing heterogeneous catalyst dataset. We apply three UQ methods to the adsorption energy predictions, namelyk-fold ensembling, Monte Carlo dropout, and evidential regression. The effectiveness of each UQ method is assessed based on accuracy, sharpness, dispersion, calibration, and tightness. Evidential regression is demonstrated to be a powerful approach for rapidly obtaining tunable, competitively trustworthy UQ estimates for heterogeneous catalysis applications when using neural networks. Recalibration of model uncertainties is shown to be essential in practical screening applications of catalysts using uncertainties.
Respondent-Driven Sampling for Estimation of the Cumulative Lifetime Incidence of Abortion in Soweto, Johannesburg, South Africa: A Methodological Assessment
Authors: Jayaweera Ruvani T , Gerdts Caitlin , Wesson Paul , Motana Relebohile , Muñoz Isabel , Bessenaar Tshegofatso , McFarland Willi , Ahern Jennifer 
Published: April 2023

Abstract
Respondent-driven sampling (RDS) is a potential strategy for addressing challenges in accurate estimation of abortion incidence, but it relies on often untested assumptions. We conducted an RDS study to estimate the cumulative lifetime incidence of abortion in Soweto, Johannesburg, South Africa (April–December 2018), to evaluate whether RDS assumptions were met, and to compare RDS estimates of incidence with estimates adjusted for employment and age based on census data. A total of 849 participants were recruited from 11 seed participants between April and December 2018. The assumption that individuals can identify target population members and the assumption of approximation of sampling with replacement was met. There were minor violations of the assumptions of seed independence from the final sample and reciprocity of ties. Assumptions of accurate degree reporting and random recruitment were not met. Failure to meet assumptions yielded a study sample with different employment characteristics than those of the target population; this could not be resolved by standard RDS methods. The RDS estimate of cumulative lifetime abortion incidence was 12.1% (95% confidence interval: 9.8, 14.3), and the employment-adjusted estimate was 16.9% (95% confidence interval: 12.8, 22.1). We caution researchers in using RDS for representative estimates of abortion incidence. Use of postsurvey weights to adjust for differences in characteristics between the sample and the target population may yield more representative results.
Phosphatidylglycerol-specific phospholipase C from Amycolatopsis sp. NT115 strain: purification, characterization, and gene cloning
Authors: Kajiyama Kiyoto , Sugimori Daisuke 
Published: April 2023

ABSTRACT
Recently, phosphatidylglycerol (PG) focused on its important role in chloroplast photosynthesis, mitochondrial function of the sperm, an inhibitory effect on SARS-CoV-2 ability to infect naïve cells, and reducing lung inflammation caused by coronavirus disease 2019. To develop an enzymatic PG determination method as the high-throughput analysis of PG, a PG-specific phospholipase C (PG-PLC) was found in the culture supernatant of Amycolatopsis sp. NT115. PG-PLC (54 kDa by SDS-PAGE) achieved the maximal activity at pH 6.0 and 55 °C and was inhibited by detergents, such as Briji35, Tween 80, and sodium cholate, but not by EDTA and metal ions, except for Zn2+. The open reading frame of the PG-PLC gene consisted of 1620 bp encoding 515-amino-acid residues containing the preceding 25-amino-acid residues (Tat signal peptide sequence). The putative amino acid sequence of PG-PLC was highly similar to those of metallophosphoesterases; however, its substrate specificity was completely different from those of known PLCs.
K-RET: knowledgeable biomedical relation extraction system
Authors: Sousa Diana F , Couto Francisco M 
Published: April 2023

Abstract

Motivation
Relation extraction (RE) is a crucial process to deal with the amount of text published daily, e.g. to find missing associations in a database. RE is a text mining task for which the state-of-the-art approaches use bidirectional encoders, namely, BERT. However, state-of-the-art performance may be limited by the lack of efficient external knowledge injection approaches, with a larger impact in the biomedical area given the widespread usage and high quality of biomedical ontologies. This knowledge can propel these systems forward by aiding them in predicting more explainable biomedical associations. With this in mind, we developed K-RET, a novel, knowledgeable biomedical RE system that, for the first time, injects knowledge by handling different types of associations, multiple sources and where to apply it, and multi-token entities.

Results
We tested K-RET on three independent and open-access corpora (DDI, BC5CDR, and PGR) using four biomedical ontologies handling different entities. K-RET improved state-of-the-art results by 2.68% on average, with the DDI Corpus yielding the most significant boost in performance, from 79.30% to 87.19% in F-measure, representing a P-value of 2.91×10−12.

Availability and implementation
https://github.com/lasigeBioTM/K-RET.