bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brennstoffzellen der nächsten Generation
Authors: Klose Carolin , Breitwieser Matthias , Koch Susanne , Muenchinger Andreas 
Published: May 2024

ZusammenfassungBrennstoffzellen lassen sich in Hoch‐ und Niedertemperaturtypen aufteilen. Letztere vertragen schnelle Lastwechsel und eignen sich daher für den mobilen Bereich. Ihr Herzstück ist die Membran‐Elektroden‐Einheit. Die Membran muss mehrere anspruchsvolle Anforderungen zugleich erfüllen. Sie muss einerseits die beiden Elektroden und damit Halbreaktionen der „kalten Knallgasreaktion“ gasdicht gegen Wasser‐ und Sauerstoff trennen. Andererseits muss sie als Elektrolyt Protonen leiten können, dazu Wasser als Reaktionsprodukt. Sie muss starken chemischen und mechanischen Belastungen standhalten, ohne schnell zu altern. Etabliert haben sich Membranmaterialien aus Perfluorsulfonsäuren (PFAS). Allerdings ist die Fluorchemie umweltbelastend und wird nur von wenigen Herstellern beherrscht. Der zweite Nachteil: PFAS‐Membranen erlauben nur Betriebstemperaturen unterhalb von 100 °C, was den Wirkungsgrad senkt. Eine vielversprechende Alternative bieten Kohlenwasserstoff‐Membranen. Sie versprechen verbesserte Wirkungsgrade, sind potenziell kostengünstiger und umweltfreundlicher in der Herstellung. Allerdings ist es noch eine Herausforderung, eine ausreichende Lebensdauer zu erreichen. Die aktuellen Fortschritte könnten eine Kommerzialisierung von fluorfreien Membran‐Elektroden‐Einheiten in naher Zukunft ermöglichen.
Intelligent fault diagnosis of machinery based on hybrid deep learning with multi temporal correlation feature fusion
Authors: Lv Yaqiong , Zhang Xiaohu , Cheng Yiwei , Lee Carman K. M. 
Published: May 2024

AbstractWith the advent of intelligent manufacturing era, higher requirements are put forward for the fault diagnosis technology of machinery. The existing data‐driven approaches either rely on specialized empirical knowledge for feature analysis, or adopt single deep neural network topology structure for automatic feature extraction with compromise of certain information loss especially the time‐series information's sacrifice, which both eventually affect the diagnosis accuracy. To address the issue, this paper proposes a novel multi‐temporal correlation feature fusion net (MTCFF‐Net) for intelligent fault diagnosis, which can capture and retain time‐series fault feature information from different dimensions. MTCFF‐Net contains four sub‐networks, which are long and short‐term memory (LSTM) sub‐network, Gramian angular summation field (GASF)‐GhostNet sub‐network and Markov transition field (MTF)‐GhostNet sub‐network and feature fusion sub‐network. Features of different dimensional are extracted through parallel LSTM sub‐network, GASF‐GhostNet sub‐network and MTF‐GhostNet sub‐network, and then fused by feature fusion sub‐network for accurate fault diagnosis. Two fault diagnosis experimental studies on bearings are implemented to validate the effectiveness and generalization of the proposed MTCFF‐Net. Experimental results demonstrate that the proposed model is superior to other comparative approaches.
Deploying a Dipole Electric Field at the CsPbI3 Perovskite/Carbon Interface for Enhancing Hole Extraction and Photovoltaic Performance
Authors: Zhang Qixian , Liu Huicong , Wei Xiaozhen , Song Yongfa , Lv Chunyu , Li Weiping , Zhu Liqun , Lan Yisha , Du Yujiang , Wang Kexiang , Yin Penggang , Lin Changqing , Lin Zedong , Bai Yang , Chen Qi , Yang Shihe , Chen Haining 
Published: May 2024

AbstractCarbon‐based CsPbI3 perovskite solar cells without hole transporter (C‐PSCs) have achieved intense attention due to its simple device structure and high chemical stability. However, the severe interface energy loss at the CsPbI3/carbon interface, attributed to the lower hole selectivity for inefficient charge separation, greatly limits device performance. Hence, dipole electric field (DEF) is deployed at the above interface to address the above issue by using a pole molecule, 4‐trifluoromethyl‐Phenylammonium iodide (CF3‐PAI), in which the ─NH3 group anchors on the perovskite surface and the ─CF3 group extends away from it and connects with carbon electrode. The DEF is proven to align with the built‐in electric field, that is pointing toward carbon electrode, which well enhances hole selectivity and charge separation at the interface. Besides, CF3‐PAI molecules also serve as defect passivator for reducing trap state density, which further suppresses defect‐induced non‐radiative recombination. Consequently, the CsPbI3 C‐PSCs achieve an excellent efficiency of 18.33% with a high VOC of 1.144 V for inorganic C‐PSCs without hole transporter.
Heterogeneous MoS2 Nanosheets on Porous TiO2 Nanofibers toward Fast and Reversible Sodium‐Ion Storage
Authors: Zhu Keping , Gao Songwei , Bai Tonghua , Li Huaike , Zhang Xuefeng , Mu Yue , Guo Wei , Cui Zhiming , Wang Nü , Zhao Yong 
Published: May 2024

Abstract2D layered molybdenum disulfide (MoS2) has garnered considerable attention as an attractive electrode material in sodium‐ion batteries (SIBs), but sluggish mass transfer kinetic and capacity fading make it suffer from inferior cycle capability. Herein, hierarchical MoS2 nanosheets decorated porous TiO2 nanofibers (MoS2 NSs@TiO2 NFs) with rich oxygen vacancies are engineered by microemulsion electrospinning method and subsequent hydrothermal/heat treatment. The MoS2 NSs@TiO2 NFs improves ion/electron transport kinetic and long‐term cycling performance through distinctive porous structure and heterogeneous component. Consequently, the electrode exhibits excellent long‐term Na storage capacity (298.4 mAh g−1 at 5 A g−1 over 1100 cycles and 235.6 mAh g−1 at 10 A g−1 over 7200 cycles). Employing Na3V2(PO4)3 as cathode, the full cell maintains a desirable capacity of 269.6 mAh g−1 over 700 cycles at 1.0 A g−1. The stepwise intercalation‐conversion and insertion/extraction endows outstanding Na+ storage performance, which yields valuable insight into the advancement of fast‐charging and long‐cycle life SIBs anode materials.
Promoting CO Electroreduction to C2+ Oxygenates by Distribution of Water Dissociation Sites
Authors: Yang Chao , Yan Yaqin , Hu Yuncheng , Chen Yangshen , Guan Anxiang , Hu Cejun , Zhang Lijuan , Zheng Gengfeng 
Published: May 2024

AbstractThe electrocatalytic CO2 or CO reduction reaction is a complex proton‐coupled electron transfer reaction, in which protons in the electrolyte have a critical effect on the surface adsorbed *H species and the multi‐carbon oxygenate products such as ethanol. However, the coupling of *H and carbon‐containing intermediates into C2+ oxygenates can be severely hampered by the inappropriate distributions of those species in the catalytic interfaces. In this work, the controlled distribution of highly dispersed CeOx nanoclusters is demonstrated on Cu nanosheets as an efficient CO electroreduction catalyst, with Faradaic efficiencies of ethanol and total oxygenates of 35% and 58%, respectively. The CeOx nanoclusters (2−5 nm) enabled efficient water dissociation and appropriate distribution of adsorbed *H species on the Cu surface with carbon‐containing species, thus facilitating the generation of C2+ oxygenate products. In contrast, pristine Cu without CeOx tended to form ethylene, while the aggregated CeOx nanoparticles promoted the surface density of *H and subsequent H2 evolution.
Machine learning prediction of hypertension and diabetes in twin pregnancies using characteristics at prenatal care entry: a nationwide study
Authors: Mustafa H. J. , Kalafat E. , Prasad S. , Heydari M. ‐H. , Nunge R. N. , Khalil A. 
Published: May 2024

ABSTRACTObjectivesTo develop a prediction model for hypertensive disorders in pregnancy (HDP) and gestational diabetes (GDM) in twin pregnancies utilizing characteristics at the prenatal care entry level.MethodsCross‐sectional study using the US national live birth data between 2016 and 2021. The association of all prenatal candidate variables with HDP and GDM was tested with uni‐ and multi‐variable logistic regression analyses. Prediction models were built with generalized linear models using the logit link function and classification and regression tree approach (XGboost) machine learning (ML) algorithm. Performance was assessed with repeated 2‐fold cross‐validation and performance metrics we considered were area under the curve (AUC). P value <0.001 was considered statistically significant.ResultsA total of 707,198 twin pregnancies were included in the HDP analysis and 723,882 twin pregnancies for the GDM analysis. The incidence of HDP and GDM significantly increased from 12.2% in 2016 to 15.4% in 2021 and from 8.1% in 2016 to 10.7% in 2021, respectively. Factors that increase the risk of HDP in twin gestations are maternal age <20, age≥35, infertility, prepregnancy DM, non‐Hispanic Black population, obesity, and those with Medicaid insurance (p<0.001). Factors that more than doubled the risk are obesity class II and III (p<0.001). Factors that increase the risk of GDM in twin gestations are age <25, age≥30, history of infertility, prepregnancy hypertension, non‐Hispanic Asian population, non‐US nativity, and obesity (p<0.001). Factors that more than doubled the risk are maternal age ≥ 30 years, non‐Hispanic Asian, and class I, II, and III maternal obesity ( p<0.001). For both HDP and GDM, the performance of the ML and logistic regression model was mostly similar with negligible difference in terms of all tested performance domains. The AUC of the final ML model for HDP and GDM were 0.62±0.004, and 0.67±0.004, respectively.ConclusionsThe incidence of HDP and GDM in twin gestations is increasing. The predictive accuracy of the machine learning model for both HDP and GDM in twin gestations is similar to that of the logistic regression model. Both models had modest performance, well‐calibrated, and neither had a poor fit.This article is protected by copyright. All rights reserved.
Gluonic contributions to semi-inclusive DIS in the target fragmentation region
Authors: Chen Kai-Bao , Ma Jian-Ping , Tong Xuan-Bo 
Published: May 2024

Abstract
We study one-loop contributions to semi-inclusive deep inelastic scattering in the target fragmentation region for a polarized lepton beam and nucleon target. Complete one-loop results at leading twist are derived, with a particular focus on the gluonic channel. It shows that four structure functions are generated uniquely by the gluon fracture functions starting at one-loop. Additionally, we obtain two structure functions associated with the longitudinal polarization of the virtual photon, and they are contributed by both gluon and quark channels. By combining existing twist-3 results, all eighteen structure functions for the studied process are predicted in terms of fracture functions convoluted with perturbative coefficient functions.
Improving the five-point bootstrap
Authors: Poland David , Prilepina Valentina , Tadić Petar 
Published: May 2024

Abstract
We present a new algorithm for the numerical evaluation of five-point conformal blocks in d-dimensions, greatly improving the efficiency of their computation. To do this we use an appropriate ansatz for the blocks as a series expansion in radial coordinates, derive a set of recursion relations for the unknown coefficients in the ansatz, and evaluate the series using a Padé approximant to accelerate its convergence. We then study the 〈σσϵσσ〉 correlator in the 3d critical Ising model by truncating the operator product expansion (OPE) and only including operators with conformal dimension below a cutoff ∆ ⩽ ∆cutoff. We approximate the contributions of the operators above the cutoff by the corresponding contributions in a suitable disconnected five-point correlator. Using this approach, we compute a number of OPE coefficients with greater accuracy than previous methods.
An Observational Case Study of a Radiation Fog Event
Authors: Gandhi Arun , Geresdi István , Gyöngyösi András Zénó , Tordai Ágoston Vilmos , Torma Péter , Rehak András , Bíró-Szilágyi Mariann , Horvath Gyula , Ferenczi Zita , Imre Kornélia , Lázár István , Peterka András , Weidinger Tamás 
Published: May 2024

AbstractA micrometeorological fog experiment was carried out in Budapest, Hungary during the winter half year of 2020–2021. The field observation involved (i) standard meteorological and radiosonde measurements; (ii) surface radiation balance and energy budget components, and (iii) ceilometer measurements. 23 fog events occurred during the whole campaign. Foggy events were categorized based on two different methods suggested by Tardif and Rasmussen (2007) and Lin et al. (2022). Using the Present Weather Detector and Visibility sensor (PWD12), duration of foggy periods are approximately shorter (~ 9%) compared to ceilometer measurements. The categorization of fog based on two different methods suggests that duration of radiation fogs is lower compared to that of cloud base lowering (CBL) fogs. The results of analysis of observed data about the longest fog event suggest that (i) it was a radiation fog that developed from the surface upwards with condition of a near neutral temperature profile. Near the surface the turbulent kinetic energy and turbulent momentum fluxes remained smaller than 0.4 m2 s–2 and 0.06 kg m–1 s–2, respectively. In the surface layer the vertical profile of the sensible heat flux was near constant (it changes with height ~ 10%), and during the evolution of the fog, its maximum value was smaller than 25 W m–2, (ii) the dissipation of the fog occurred due to increase of turbulence, (iii) longwave energy budget was close to zero during fog, and a significant increase of virtual potential temperature with height was observed before fog onset. The complete dataset gives an opportunity to quantify local effects, such as tracking the effect of strengthening of wind for modification of stability, surface layer profiles and visibility. Fog formation, development and dissipation are quantified based on the micrometeorological observations performed in suburb area of Budapest, providing a processing algorithm for investigating various fog events for synoptic analysis and for optimization of numerical model parameterizations.
Corticosterone after early adolescent stress prevents social avoidance, aversive behavior, and morphine-conditioned place preference in adulthood
Authors: Vanderhoof Samantha O. , Vincent Carly J. , Beaver Jasmin N. , Latsko Maeson S. , Aguilar-Alvarez Ricardo , Jasnow Aaron M. 
Published: May 2024

Abstract
Rationale
Stress during childhood or adolescence increases vulnerability to psychiatric disorders in adults. In adult rodents, the delayed effects of stress can increase anxiety-like behavior. These effects, however, can be prevented with post-stress administration of corticosterone (CORT). The effectiveness of CORT in preventing adolescent stress-induced emotional behavior alterations in adulthood has yet to be investigated.

Objectives
Here, we investigated the interactions between early adolescent stress and exogenous corticosterone on adult social, aversive, and drug-seeking behavior in mice, which are translationally related to symptoms associated with psychiatric and substance abuse disorders.

Methods and results
A single administration of CORT in drinking water (400ug/mL) for 24 h after social defeat or context fear conditioning prevents defeat-induced social avoidance, alters fear processing, prevents adolescent stress-induced anhedonia, and prevents stress-potentiated morphine place preference in adulthood. Exogenous CORT did not immediately prevent stress-induced potentiation of morphine conditioned-place preference in adolescents but did so in adult mice. However, when administered to adolescent mice, CORT also prevented the incubation of morphine-conditioned place preference into adulthood. Lastly, exogenous CORT administration blunted endogenous corticosterone but was unrelated to freezing behavior during a fear test.

Conclusions
This is the first demonstration of adolescent post-stress CORT promoting socio-emotional resilience and preventing drug-seeking behavior. Our data suggest elevated corticosterone after a stress experience promotes resilience for at least 40 days across the developmental transition from adolescence to adulthood and is effective for socio-emotional and drug-seeking behavior. These results are critical for understanding how adolescent stress impacts emotional and drug-seeking behavior into adulthood.
Marine Fungal Diversity and Dynamics in the Gulf of Trieste (Northern Adriatic Sea)
Authors: Banchi Elisa , Manna Vincenzo , Muggia Lucia , Celussi Mauro 
Published: May 2024

AbstractFungi contribute to different important ecological processes, including decomposition of organic matter and nutrient cycling, but in the marine environment the main factors influencing their diversity and dynamics at the spatial and temporal levels are still largely unclear. In this study, we performed DNA metabarcoding on seawater sampled monthly over a year and a half in the Gulf of Trieste (northern Adriatic Sea), targeting the internal transcribed spacer (ITS) and the 18S rRNA gene regions. The fungal communities were diverse, very dynamic, and belonged predominantly to marine taxa. Samples could be clustered in two groups, mainly based on the high (> 30%) or low relative proportion of the ascomycetes Parengyodontium album, which emerged as a key taxon in this area. Dissolved and particulate organic C:N ratio played important roles in shaping the mycoplankton assemblages, suggesting that differently bioavailable organic matter pools may be utilized by different consortia. The proportion of fungal over total reads was 31% for ITS and 0.7% for 18S. ITS had the highest taxonomic resolution but low power to detect early divergent fungal lineages. Our results on composition, distribution, and environmental drivers extended our knowledge of the structure and function of the mycobiome of coastal waters.
In Vivo Comparison of the Efficacy and Duration of Local Antibiotics on Smooth, Textured and Polyurethane Implant Surfaces
Authors: Karakas Ebubekir , Ayhan M. Suhan , Karasu Oguzhan , Kocak Ceren Ozkul , Yalinay Meltem 
Published: May 2024

Abstract

Background
Capsular contracture is one of the most common complications after breast surgery involving silicone implants. The most likely cause of this condition is biofilm formation. In this study, the efficacy of local antibiotherapy against biofilm formation on implant surfaces was investigated.

Methods
Thirty-six rats were divided into six groups. Three pockets were created on the dorsum of each rat, and 1 × 2 cm implant surface samples from smooth, polyurethane and textured implants were randomly placed into pockets. All samples were inoculated with staphylococcus epidermidis. In groups 1-2-3, inoculated samples were placed into the pockets and removed after 1, 6 and 24 h, respectively. In groups 4-5-6, inoculated samples immersed with rifamycin were placed and removed after 1, 6 and 24 h, respectively. Bacterial load was measured with plate count method.

Results
Bacterial load was lower in groups 4-5-6 than in groups 1-2-3 (p < 0.05). In groups 4-5-6, bacterial load was lower for polyurethane than for textured surfaces at all time points (1, 6 and 24 h; p < 0.05). Again, in groups 4-5-6, bacterial load was lower for smooth than for textured surfaces at 24 h (p < 0.05). In groups 4-5-6, bacterial load was lower for polyurethane than for smooth surfaces at all time points, but difference was not statistically significant (1, 6 and 24 h; p < 0.05).

Conclusion
The results suggest that local antibiotic therapy was effective in reducing the bacterial load on all surfaces. The effectiveness of local rifamycin on the polyurethane surface was higher, and the duration of activity was longer than other surfaces.

No Level Assigned
This journal requires that authors assign a level of evidence to each article. For a full description of these evidence-based medicine ratings, please refer to the Table of contents or the online Instructions to Authors www.springer.com/00266.
Patientenorientierte Optimierung der Versorgungsqualität in der ambulanten spezialfachärztlichen Versorgung (ASV) in einem tertiären rheumatologischen Zentrum
Authors: Ibishi Vlora , Kiltz Uta , Tsiami Styliani , Wessels Michael , Baraliakos Xenofon 
Published: May 2024

Zusammenfassung

Hintergrund
Die Anpassung von Strukturen und Prozessen der Behandlungsabläufe kann zur Steigerung der Patientenzufriedenheit beitragen und steht im Fokus einer patientenorientierten Qualitätssicherung.

Ziel
Es erfolgte die Identifizierung der Patientenzufriedenheit sowie der Bedürfnisse, Erwartungen und Präferenzen hinsichtlich der Versorgung und daraus ableitend die Formulierung von Handlungsempfehlungen zur Optimierung der Versorgungsqualität eines großen tertiären rheumatologischen Zentrums.

Material und Methode
Im Rahmen eines qualitativen Forschungsansatzes wurden halbstrukturierte Patienteninterviews und ein Fokusgruppeninterview bestehend aus Ärzt:innen in rheumatologischer Weiterbildung (ÄiWB) in der ambulanten spezialfachärztlichen Versorgung (ASV) durchgeführt. Es wurden die Qualitätsdimensionen nach Donabedian erfasst. Das Datenmaterial wurde anhand der inhaltlich-strukturierenden qualitativen Inhaltsanalyse (QIA) nach Kuckartz mit der Auswertungssoftware MAXQDA ausgewertet und analysiert.

Ergebnisse
Mittels 12 Patienteninterviews und einer Fokusgruppe aus 3 ÄiWB wurden auf Grundlage der Struktur‑, Prozess- und Ergebnisqualität Handlungsempfehlungen zur Optimierung der Versorgungsqualität abgeleitet. Es erwies sich Optimierungsbedarf im Bereich des Personalmanagements, der internen Praxisabläufe, der Praxisausstattung und der Behandlungsabläufe in der ASV-Ambulanz.

Schlussfolgerungen
Die Ergebnisse aus den Patienteninterviews und der Fokusgruppe zeigten die Aspekte mit Optimierungsbedarf auf. Die Methodik und Ergebnisse dieser Studie können als Anhaltspunkt für Analysen anderer rheumatologischer Kliniken dienen, um im Rahmen des patientenorientierten Qualitätsmanagements und der kontinuierlichen Weiterentwicklung die Versorgungsqualität zu verbessern.
Exposome on skeletal muscle system: a mini-review
Authors: Purcaro Cristina , Marramiero Lorenzo , Santangelo Carmen , Bondi Danilo , Di Filippo Ester Sara 
Published: May 2024

AbstractExposomics is an ever-expanding field which captures the cumulative exposures to chemical, biological, physical, lifestyle, and social factors associated with biological responses. Since skeletal muscle is currently considered as the largest secretory organ and shows substantial plasticity over the life course, this reviews addresses the topic of exposome and skeletal muscle by reviewing the state-of-the-art evidence and the most intriguing perspectives. Muscle stem cells react to stressors via phosphorylated eukaryotic initiation factor 2α and tuberous sclerosis 1, and are sensible to hormetic factors via sirtuin 1. Microplastics can delay muscle regeneration via p38 mitogen-activated protein kinases and induce transdifferentiation to adipocytes via nuclear factor kappa B. Acrolein can inhibit myogenic differentiation and disrupt redox system. Heavy metals have been associated with reduced muscle strength in children. The deep study of pollutants and biological features can shed new light on neuromuscular pathophysiology. The analysis of a time-varying and dynamic exposome risk score from a panel of exposure and phenotypes of interest is promising. The systematization of hormetic factors and the role of the microbiota in modulating the effects of exposure on skeletal muscle responses are also promising. The comprehensive exposure assessment and its interactions with endogenous processes and the resulting biological effects deserve more efforts in the field of muscle health across the lifespan.