bluuebunny/crossref_metadata_2025_split huggingface dataset:
Schwingungsbasierte Lastrekonstruktion an Gründungsstrukturen von Offshore‐Windenergieanlagen
Authors: Tsiapoki Stavroula , Colomer Segura Carles , Ebert Carsten 
Published: May 2022

AbstractDie Zustandsüberwachung (SHM) der Turm‐ und Fundamentstrukturen von Offshore‐Windenergieanlagen hat sich als anerkannte Regel der Technik in der Praxis etabliert. Ein wichtiger Aspekt dabei ist die Erfassung, Bewertung und Analyse der einwirkenden Ermüdungsbeanspruchungen, um die Anlagen für einen ermüdungsarmen Betrieb zu optimieren und Potenzial für Lebensdauerverlängerungen vorzuhalten. Ermüdungsbeanspruchungen können entweder direkt mittels Dehnungsmessstreifen gemessen oder indirekt aus der Messung von Turmverformungen in Verbindung mit einem mechanischen Modell (z. B. Finite‐Elemente‐Modell) rekonstruiert werden. Die indirekte Rekonstruktion kann auch mit den Begriffen „virtuelle Sensoren“ bzw. „Digital Twin“ beschrieben werden. In diesem Beitrag wird vorgestellt, wie Ermüdungseinwirkungen an relevanten Bereichen von Offshore‐Gründungsstrukturen, wie z. B. der Turm‐Transition‐Piece‐Verbindung, aus Beschleunigungs‐ und Neigungsmessungen rekonstruiert werden können. Der Ansatz verwendet die am Turm erfassten strukturellen Antworten sowie ein FE‐Modell, um interne Kräfte bzw. Momente in der Struktur zu bestimmen. Es wird anhand realer Beispiele von deutschen Offshore‐Projekten gezeigt, wie die Genauigkeit in Abhängigkeit von den zur Verfügung stehenden Messinformationen und berücksichtigten Lastannahmen beeinflusst wird. Die Auswirkungen von Unsicherheiten aus Messung und Modellannahmen (z. B. Kalibrierfehler, Baugrundsteifigkeiten) werden ebenfalls dargestellt.
A novel deep learning prognostic system improves survival predictions for stage III non‐small cell lung cancer
Authors: Yang Linlin , Fan Xinyu , Qin Wenru , Xu Yiyue , Zou Bing , Fan Bingjie , Wang Shijiang , Dong Taotao , Wang Linlin 
Published: May 2022

AbstractBackgroundAccurate prognostic prediction plays a crucial role in the clinical setting. However, the TNM staging system fails to provide satisfactory individual survival prediction for stage III non‐small cell lung cancer (NSCLC). The performance of the deep learning network for survival prediction in stage III NSCLC has not been explored.ObjectivesThis study aimed to develop a deep learning‐based prognostic system that could achieve better predictive performance than the existing staging system for stage III NSCLC.MethodsIn this study, a deep survival learning model (DSLM) for stage III NSCLC was developed based on the Surveillance, Epidemiology, and End Results (SEER) database and was independently tested with another external cohort from our institute. DSLM was compared with the Cox proportional hazard (CPH) and random survival forest (RSF) models. A new prognostic system for stage III NSCLC was also proposed based on the established deep learning model.ResultsThe study included 16,613 patients with stage III NSCLC from the SEER database. DSLM showed the best performance in survival prediction, with a C‐index of 0.725 in the validation set, followed by RSF (0.688) and CPH (0.683). DSLM also showed C‐indices of 0.719 and 0.665 in the internal and real‐world external testing datasets, respectively. In addition, the new prognostic system based on DSLM (AUROC = 0.744) showed better performance than the TNM staging system (AUROC = 0.561).ConclusionIn this study, a new, integrated deep learning‐based prognostic model was developed and evaluated for stage III NSCLC. This novel approach may be valuable in improving patient stratification and potentially provide meaningful prognostic information that contributes to personalized therapy.
Impact of proton pump inhibitors on efficacy of antiplatelet strategies with ticagrelor or aspirin after percutaneous coronary intervention: Insights from the GLOBAL LEADERS trial
Authors: Ono Masafumi , Onuma Yoshinobu , Kawashima Hideyuki , Hara Hironori , Gao Chao , Wang Rutao , O'Leary Neil , Benit Edouard , Janssens Luc , Ferrario Maurizio , Żurakowski Aleksander , Dominici Marcello , Huber Kurt , Buszman Paweł , Garg Scot , Wykrzykowska Joanna J. , Piek Jan J. , Jüni Peter , Hamm Christian , Windecker Stephan , Vranckx Pascal , Deliargyris Efthymios N. , Bhatt Deepak L. , Storey Robert F. , Valgimigli Marco , Serruys Patrick W. ,   The GLOBAL LEADERS trial investigators
Published: May 2022

AbstractBackgroundSeveral studies have suggested that proton pump inhibitors (PPIs) may reduce the antiplatelet effects of clopidogrel and/or aspirin, possibly leading to cardiovascular events.AimsWe aimed to investigate the association between PPI and clinical outcomes in patients treated with ticagrelor monotherapy or conventional antiplatelet therapy after percutaneous coronary intervention (PCI).MethodsThis is a subanalysis of the randomized GLOBAL LEADERS trial, comparing the experimental antiplatelet arm (23‐month ticagrelor monotherapy following 1‐month dual antiplatelet therapy [DAPT]) with the reference arm (12‐month aspirin monotherapy following 12‐month DAPT) after PCI. Patient‐oriented composite endpoints (POCEs: all‐cause mortality, myocardial infarction, stroke, or repeat revascularization) and its components were assessed stratified by PPI use as a time‐dependent covariate in patients with the experiment or reference antiplatelet arm.ResultsAmong 15,839 patients, 2115 patients (13.5%) experienced POCE at 2 years. In the reference arm, the use of PPIs was independently associated with POCE (hazard ratio [HR]: 1.27; 95% confidence interval [CI]: 1.12–1.44) and its individual components, whereas it was not in the experimental arm (HR: 1.04; 95% CI: 0.92–1.19; pinteraction = 0.035). During the second‐year follow‐up, patients taking aspirin with PPIs had a significantly higher risk of POCE compared to those on aspirin without PPIs (HR: 1.57; 95% CI: 1.27–1.94), whereas the risk did not differ significantly irrespective of PPI in ticagrelor monotherapy group (HR: 1.03; 95% CI: 0.83–1.28; pinteraction = 0.008).ConclusionsIn contrast to conventional antiplatelet strategy, there were no evidence suggesting the interaction between ticagrelor monotherapy and PPIs on increased cardiovascular events, which should be confirmed in further studies.Clinical Trial RegistrationURL: https://clinicaltrials.gov
Insight into the Synergistic Collaboration of g‐C3N4/SnO2 Composites for Photoelectrocatalytic CO2 Reduction
Authors: Zhang Erhui , Tang Jing , Li Zirong , Zhou Yongsheng 
Published: May 2022

AbstractA novel method for constructing a g‐C3N4/SnO2 heterostructure for CO2 reduction reaction (CO2RR) is presented. In the heterostructure, the introduction of g‐C3N4 makes for restraining the recombination of photo‐induced electrons and holes while the existence of SnO2 plays a vital role in selective catalytic reduction of CO2 into HCOOH, thus their cooperative interaction makes the photoelectric property of g‐C3N4/SnO2 towards CO2RR improved greatly. The so‐fabricated g‐C3N4/SnO2 shows an exclusive HCOOH selectivity and a high faradic efficiency of 58 %, which is about 8 times higher than that of single SnO2. The photocurrent reaches 7.5 μA cm−2 under 0.5 V. Besides, the overpotential is as low as 300 mV (vs. RHE). Moreover, the PL emission decreases obviously after the introduction of g‐C3N4. Given these performance advantages of g‐C3N4/SnO2, the solution‐processed strategy with post‐annealing treatment offers a facile, efficient, yet scalable approach reference to construct CO2RR heterostructure catalysts, which shows higher potential in CO2RR electrocatalysis.
Piezo‐elasticity and stability limits of monocrystal methane gas hydrates: Atomistic‐continuum characterization
Authors: Zhu Xiaodan , Rey Alejandro D. , Servio Phillip 
Published: May 2022

AbstractGas hydrates are guest‐host crystalline materials formed by water cages and guest gases such as methane and carbon dioxide under simultaneously relative high‐pressure and low‐temperature conditions. With this unique guest‐host structural feature, gas hydrates can be used for gas storage and carbon dioxide (CO2) sequestration, creating challenges such as flow assurance and geological stability. Some of these challenges are related to material instabilities caused by changing external conditions. Thus, this paper aims to determine the theoretical pressure stability limits of monocrystal defect‐free sI methane gas hydrates at 0 K using accurate density functional theory to simulate the hydrate's thermodynamic and elastic responses under varying pressures. The pressure stability limits are determined by Born stability criteria and piezo sensitivity factors. The important brittle‐to‐ductile transitions of gas hydrates are established. Also, polycrystalline mechanical properties, including the Poisson ratio and Young modulus, are calculated from the second‐order elastic constants obtained from the monocrystal sI methane hydrates, which provide the upper bounds. Taken together, the piezo‐sensitivity of a complete set of elastic properties of sI methane gas hydrates and material stability limits determined by atomistic calculations provide new data and fundamental understanding for technological applications.
Velocity‐resolved Laser‐induced Desorption for Kinetics on Surface Adsorbates
Authors: Pappendorf Kim , Golibrzuch Kai , Zhong Tian‐Li , Schwabe Sven , Kitsopoulos Theofanis , Wodtke Alec M. 
Published: May 2022

AbstractInvited for this month's cover are the groups of Alec M. Wodtke at the Georg‐August University in Göttigen (Germany) and at the University of Crete (Greece). The cover picture shows ammonia (NH3) molecules adsorbed on an atomically flat platinum surface. An ultra‐short laser pulse hits the surface and heats up the metal electron rapidly to several thousand Kelvin within a few 100 fs. This high electronic temperature causes a fraction of the ammonia molecules to desorb with hyperthermal velocity from the surface. Depended on the laser intensity, the number of desorbing molecules is proportional to the surface coverage. Read the full text of their Research Article at 10.1002/cmtd.202200017.
Mandelic Acid as an Interfacial Modifier for High Performance NiOx‐based Inverted Perovskite Solar Cells
Authors: Fu Yu , Liu Xingchong , Zhao Shuangshuang 
Published: May 2022

AbstractNickel oxide (NiOx) inverted perovskite solar cells have been witnessed as promising solar cells because of the low cast, easy fabrication and negligible hysteresis. However, the inferior interface feature of the link NiOx and perovskite layer often causes poor device property and repeatability. Here, Mandelic acid (MAD) is introduced to form a modified layer, which could improve the poor interface properties between perovskite layer and NiOx layer. The contact angel images revels MAD could increase the hydrophobicity and facilitate the growth of perovskite crystal. The X‐ray diffraction pattern and Fourier transform infrared spectroscopy have confirmed that the MAD small molecule could interact with residual PbI2 crystal, leading to better interface contact and high crystallinity. This is further demonstrated by the scanning electron microscopy test of NiOx/MAD/MAPbI3 film that average grain size is increased from 201.85 nm to 315.17 nm. The space‐charge limited current measurement proves the introduction of MAD molecule that result in the decreased trap state density from 3.58×1015 cm−3 to 2.721015 cm−3. As a consequence, The power conversion efficiency is significantly improved from 14.9% to 18.42% of MAPbI3‐based devices that retained nearly 80% initial PCE after 50 days in N2 without encapsulation.
Detection of brain tumor size using modified deep learning and multilevel thresholding utilizing modified dragonfly optimization algorithm
Authors: Ramesh Kumar Aarthi , Kuttiappan Helenprabha 
Published: May 2022

AbstractNowadays, brain tumor (BT), which is the abnormal growth of the mass of tissues in the human brain, is the main cause of death among kids and adults. The existing methodologies concentrate only on the BT classification and could not detect the BT size. This work proposes to detect the BT size utilizing Modified Deep Learning (MDNN) and multilevel thresholding (MT) utilizing modified dragonfly optimization (MD‐MT) algorithm. Afterward, the Histogram Clipping (HC)‐based Contrast Limited Adaptive Histogram Equalization (CLAHE) approach is implemented for enhancing the contrast of the inputted image, and certain features are extracted as of those contrast‐enhanced images. Next, the image is classified as (i) tumor image and (ii) nontumor image with the aid of MDNN. The tumor part is segmented as the classified tumor affected image utilizing MD‐MT. Here, the proposed HC‐CLAHE attains a 99.74% Spearman Rank Correlation, which is greater among other methods while the proposed MD‐MT attains a higher accuracy (99.73%). For classification, the proposed MDNN and the existing Artificial Neural Network, K‐Nearest Neighbor, Support Vector Machine, and Naïve Bayes are contrasted grounded on their performance in respect of precision, f‐measure, and recall. The proposed work shows excellent performance during the experimental evaluation.
Generation of Piezo1‐CreER transgenic mice for visualization and lineage tracing of mechanical force responsive cells in vivo
Authors: Li Xufeng , Zhang Zhenqian , Han Maoying , Li Yang , He Lingjuan , Zhou Bin 
Published: May 2022

SummaryCells and tissues are exposed to a wide range of mechanical stimuli during development, tissue homeostasis, repair, and regeneration. Over the past few decades, mechanosensitive ion channels (MSCs), as force‐sensing integral membrane proteins, have attracted great attention with regard to their structural dynamics and mechanics at the molecular level and functions in various cells. Piezo‐type MSC component 1 (Piezo1) is a newly discovered MSC; it is inherently mechanosensitive. However, which type of cells express Piezo1 in vivo remains unclear. To detect and trace Piezo1‐expressing cells, we generated and characterized a novel tamoxifen‐inducible Cre knock‐in mouse line, Piezo1‐CreER, which expresses CreER recombinase under the control of the endogenous Piezo1 promoter. Using this genetic tool, we detected the expression of Piezo1 in various cell types at the embryonic, neonatal, and adult stages. Our data showed that Piezo1 was highly expressed in endothelial cells in all the three stages, while the Piezo1 expression in epithelial cells was dynamic during development and growth. In summary, we established a new genetic tool, Piezo1‐CreER, to study Piezo1‐expressing cells in vivo during development, injury response, and tissue repair and regeneration.
Inference for epidemic models with time‐varying infection rates: Tracking the dynamics of oak processionary moth in the UK
Authors: Wadkin Laura E. , Branson Julia , Hoppit Andrew , Parker Nicholas G. , Golightly Andrew , Baggaley Andrew W. 
Published: May 2022

Abstract

Invasive pests pose a great threat to forest, woodland, and urban tree ecosystems. The oak processionary moth (OPM) is a destructive pest of oak trees, first reported in the UK in 2006. Despite great efforts to contain the outbreak within the original infested area of South‐East England, OPM continues to spread.

Here, we analyze data consisting of the numbers of OPM nests removed each year from two parks in London between 2013 and 2020. Using a state‐of‐the‐art Bayesian inference scheme, we estimate the parameters for a stochastic compartmental SIR (susceptible, infested, and removed) model with a time‐varying infestation rate to describe the spread of OPM.

We find that the infestation rate and subsequent basic reproduction number have remained constant since 2013 (with between one and two). This shows further controls must be taken to reduce below one and stop the advance of OPM into other areas of England.

Synthesis. Our findings demonstrate the applicability of the SIR model to describing OPM spread and show that further controls are needed to reduce the infestation rate. The proposed statistical methodology is a powerful tool to explore the nature of a time‐varying infestation rate, applicable to other partially observed time series epidemic data.
Ambivalent sexism and violence toward women: A meta‐analysis
Authors: Agadullina Elena , Lovakov Andrey , Balezina Maryana , Gulevich Olga A. 
Published: May 2022

AbstractThe Ambivalent Sexism Theory suggests that there are two complementary types of sexism: hostile (subjectively negative attitude towards gender groups) and benevolent (subjectively positive attitude towards gender groups). In this meta‐analysis we analysed the relationship between ambivalent sexism and attitudes toward male‐to‐female violence or violent behaviour. Violence type, the context of violence, respondents’ gender, the countries’ level of gender inequality, and sample type were tested as moderators. The results showed that both hostile and benevolent sexism independently impact on attitudes toward violence and violent behaviour albeit to a different degree. Specifically, the relationship between hostile sexism and attitudes and behaviour is stronger than for the benevolent sexism. The type and context of violence moderate the relationship between hostile sexism and attitudes toward violence and violent behaviour. Only the country's gender inequality levels showed a moderation effect for benevolent sexism. Theoretical and practical implications of the results are discussed.
The impact of organizational statements of support for the black community in the wake of a racial mega‐threat on organizational attraction and revenue
Authors: Corrington Abby , Fa‐Kaji Naomi M. , Hebl Mikki R. , King Eden B. , Stewart Dillon , Alao Temi 
Published: May 2022

AbstractWhen race‐related injustices occur in society, organizations can respond by sending supportive signals to prospective and current employees. Using signaling theory (Spence, 1973), the current study examines the outcomes associated with organizations' public declarations of support for the Black community following race‐related mega‐threats (Leigh & Melwani, 2019). In Study 1, prospective employees evaluated a specific organization (Ben & Jerry's) that publicly supported the Black community following race‐related mega‐threats. Those who perceived higher levels of organizational support for diversity and inclusion (POSDI) reported higher organizational attraction (OA). Study 2 described a fictitious organization that responded to race‐related mega‐threats by messaging support for either Black Lives Matter (BLM), Blue Lives Matter, All Lives Matter, or no social movement. Prospective employees perceived higher levels of POSDI when the company issued a statement in support of BLM (relative to the other movements), which in turn was associated with higher OA. Study 3 focused on current employees and examined how POSDI influences financial outcomes in real Fortune 500 companies. Organizations that issued statements publicly supporting the Black community following a race‐related mega‐threat received higher POSDI ratings by employees, which predicted increased organizational revenue, even after controlling for revenue prior to making the statements. In sum, organizations that signal public support for the Black community in the wake of a race‐related mega‐threat not only increase prospective employees' POSDI, but may also boost OA and, ultimately, financial revenue.
Body mass index trajectories and associations with cognitive decline in people with Lewy body dementia and Alzheimer's disease
Authors: Borda Miguel G. , Jaramillo‐Jimenez Alberto , Giil Lasse M. , Tovar‐Rios Diego A. , Soennesyn Hogne , Aarsland Dag 
Published: May 2022

AbstractBackground and AimsIn older adults with dementia, low body mass index (BMI) is associated with higher mortality and other adverse health outcomes. BMI or nutritional status trajectories from diagnosis have not yet been well described in dementia, especially in people with Lewy body dementia (LBD); a group that has a poorer prognosis. With this study, we aimed to evaluate the BMI trajectory in people diagnosed with mild LBD and Alzheimer's disease (AD).MethodsThe Dementia Study of Western Norway is a cohort study with annual assessments. Five‐year measurements of BMI from 196 patients (LBD = 85 and AD = 111) diagnosed with mild dementia were analyzed using adjusted linear mixed‐effects models.ResultsThere were no differences between LBD and AD in baseline BMI, age, or mini‐mental status examination (MMSE). During the follow‐up, we observed a significant decrease in BMI in the LBD group across the study period (estimation [Est.]: −0.63, SE: 0.14; p < 0.001). By contrast, there was no significant change in BMI trajectory associated with AD diagnosis (Est.: 0.05, SE: 0.15; p = 0.730). Further, the introduction of an interaction term between diagnosis and time in the study showed that this difference (BMI trajectories) was significant (Est.: −0.63, SE: 0.14; p < 0.001). In addition, there was a significant interaction between MMSE total score and the follow‐up time; the lower the MMSE, the lower the BMI (Est.: 0.01, SE: 0.01; p = 0.044).ConclusionIn LBD, BMI significantly decreased with disease progression. In addition, low cognitive performance was associated with a reduction in BMI. These results highlight the importance of BMI evaluation in people with dementia, particularly patients diagnosed with LBD, and suggest that patients with LBD could be targeted for dietary intervention to maintain body weight.
CD8 agonism functionally activates memory T cells and enhances antitumor immunity
Authors: Madi Alaa , Weisshaar Nina , Buettner Michael , Poschet Gernot , Ma Sicong , Wu Jingxia , Mieg Alessa , Hering Marvin , Ming Yanan , Mohr Kerstin , ten Bosch Nora , Cui Guoliang 
Published: May 2022

AbstractMemory CD8+ T cells mature after antigen clearance and ultimately express CD8 protein at levels higher than those detected in effector CD8+ T cells. However, it is not clear whether engagement of CD8 in the absence of antigenic stimulation will result in the functional activation of T cells. Here, we found that CD8 antibody‐mediated activation of memory CD8+ T cells triggered T cell receptor (TCR) downstream signaling, enhanced T cell‐mediated cytotoxicity and promoted effector cytokine production in a glucose‐ and glutamine‐dependent manner. Furthermore, pretreatment of memory CD8+ T cells with an agonistic anti‐CD8 antibody enhanced their tumoricidal activity in vitro and in vivo. From these studies, we conclude that CD8 agonism activates glucose and glutamine metabolism in memory T cells and enhances the efficacy of memory T cell‐based cancer immunotherapy.
Revisiting credit risk and banks performance of China's commercial banks before and after Covid 19 pandemic
Authors: Twum Angelina Kissiwaa , Agyemang Andrew Osei , Sare Yakubu Awudu 
Published: May 2022

AbstractThe effectiveness of the financial market is reflected in the financial crisis which mostly results in credit risk. The impact of credit risk in China is likely to affect the global economy since China is the fastest‐growing economy as well as the second‐best economy in the world in terms of gross domestic product. Using panel data for twenty‐eight listed commercial banks in China from 1990 to 2020, the study explored the relationship between credit risk and business performance. The authors utilized the Generalized Methods of Moments (GMM) as the primary estimator while the Pooled Mean Group (PMG) was used as a robust estimator. A negative and statistically significant relationship was found between non‐performing loan and return on equity, as well as loan loss provision and profitability of the bank. On the contrary, capital adequacy ratio revealed a positive and statistically significant relationship with bank performance. Credit growth on the other hand recorded positive but insignificant relationship with performance of banks. The findings will add up to existing literature on credit risk and business performance of commercial banks.