bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three Amino‐functionalized Alkaline Earth Metal‐Organic Frameworks as Catalysts for Knoevenagel Condensation
Authors: Song Xiuduo , He Yanzhen , Cai Zhe , Li Xiaoyun , Sun Yanmin , Liu Hongguang , Lu Yanfei , Hou Jie , Han Enshan 
Published: October 2020

AbstractThree amino‐functionalized alkaline earth Metal‐Organic Frameworks (MOFs), including Mg‐ABDC [Mg(ABDC)(DMF)], Ca‐ABDC [Ca(ABDC)(DMF)] and Sr‐ABDC [Sr(ABDC)(DMF)]( ABDC=2‐aminobenzene‐1,4‐dicarboxylate anion), were synthesized under solvothermal conditions. The incorporation of alkaline earth metals and N‐containing ligands is an effective way to increase the basicity of MOFs. To explore catalytic activity of three alkaline earth MOFs, they were applied to catalyze the Knoevenagel condensation of benzaldehyde with ethyl cyanoacetate to produce ethyl (E)‐α‐cyanocinnamate. All three alkaline earth MOFs had high catalytic performance, among which Mg‐ABDC showed the best performance. The activity of catalyst was expressed by the conversion rate and selectivity. The conversation rate was up to 94.7 % and the selectivity was nearly 100 % by adding Mg‐ABDC. Mg‐ABDC was proved to be an efficient, stable and heterogeneous catalyst through hot filtration and recycling tests.
Morphology Evolution of a High‐Efficiency PSC by Modulating the Vapor Process
Authors: Yao Zhun , Zhao Wangen , Xu Zhuo , Wen Jialun , Liu Shengzhong (Frank) 
Published: October 2020

AbstractThe morphological quality of the photoactive layer is the key component affecting the performance metrics of a photovoltaic device. Therefore, fine adjustment of the crystallization dynamics is urgently required. By manipulating the amount of dimethyl sulfoxide (DMSO) remaining in the spin‐coated perovskite films during the annealing treatment, an obvious morphological evolution arises. The crystallization kinetics is significantly altered due to the formation of intermediate phases and the variation of DMSO vapor pressure via producing the semienclosed space with a covering. On the one hand, the obviously formed intermediate phase MA2Pb3I8(DMSO)2 retards the crystallization process. On the other hand, the DMSO vapor in the semienclosed space intrigues the recrystallization process and results in Ostwald ripening to produce large‐aspect‐ratio grains with fewer defect states, decreased carrier doping, and longer carrier lifetimes. Thus, nonradiative processes are greatly suppressed. Besides, combined with X‐ray photoelectron spectroscopy measurement and the surface energy of MAI‐ and PbI‐terminated surface model calculated by density functional theory, the defect states are identified and the causes of Pb0 defect states are explained. Using this strategy, a high power conversion efficiency of 20.09% is achieved based on MAPbI3 photovoltaic solar cell, and the long‐term ambient shelf and thermal stability are obviously improved.
Energy‐Saving Multisensor Data Sampling and Fusion with Decision‐Making for Monitoring Health Risk Using WBSNs
Authors: Jaber Alaa Shawqi , Idrees Ali Kadhum 
Published: October 2020

AbstractThe necessity of developing sufficient systems to monitor health conditions has increased due to the aging of the population and the prevalence of chronic diseases, creating a demand for remote health care systems that make use of biosensors. This article proposes an energy‐saving multisensor data sampling and fusion with decision‐making for the monitoring of patient health risk in wireless body sensor networks (WBSNs). The work consists of three steps: energy‐efficient sampling rate adaptation, multisensor data fusion, and decision‐making. The sampling is performed in each biosensor and it adapts its rate based on the local risk and the global risk in which global risk computed at the coordinator, where the data is fused afterward. Finally, decisions are made according to the risk level of the patient. The processing of these functions enables in real‐time the adoption of the biosensor sampling rates based on the dynamic risk level of each biosensor, and a corresponding decision is made whenever an emergency is detected. The performance of the suggested approach is evaluated using actual health datasets, and some of its aspects are put into comparison with an existing approach, such as the data reducing and energy‐consuming rates. The acquired results illustrate a decrease in the volume of gathered data, thus a significant energy saving has been made while preserving data accuracy and integrity. Moreover, presenting a data fusing model at the coordinator level by means of an early warning score system has assessed the health condition of patients and took an appropriate decision when detecting emergencies.
Comparison of the performance of 22 models describing soil water retention curves from saturation to oven dryness
Authors: Du Chaoyang 
Published: October 2020

AbstractSoil water retention curve (SWRC) is key hydraulic property for vadose zone hydrology. Selected 22 SWRC models with different structures were divided into four types: traditional, single‐segment, two‐segment, and three‐segment models. According to the accuracy and model selection criterion, these models were compared and evaluated using water retention data from saturation to oven dryness of 94 soil samples covering almost all soil types. Among the models, the EG model (exponential model combined with the Groenevelt–Grant model) shows the best performance, but the BC (Brooks–Corey) and VG (van Genuchten) models performed the worst. The relationship between model performance and complexity showed that traditional models with residual water content performed worse than segmental models from saturation to oven dryness, and the segmental models performed worse with an increase in the segment number. In general, models with more parameters perform better, but when the parameter number is greater than five, the model performance gradually worsens due to the equifinality of different parameters. The correlation analysis between soil properties on model performance showed that soil texture has a more significant effect on model performance than bulk density and organic matter content, because the models are primarily affected by their mathematical forms rather than the physical significance of the parameters. Each model picks its limitations and may apply to only one or particular group(s) of soil(s). Therefore, the complementarities of different models may be a great choice to improve SWRC fitting and simulation in arid soil.
Confronting grand unification with lepton flavour violation, dark matter and LHC data
Authors: Ellis J. , Gómez M. E. , Lola S. , Ruiz de Austri R. , Shafi Q. 
Published: October 2020

Abstract
We explore possible signatures for charged lepton flavour violation (LFV), sparticle discovery at the LHC and dark matter (DM) searches in grand unified theories (GUTs) based on SU(5), flipped SU(5) (FSU(5)) and SU(4)c×SU(2)L×SU(2)R (4-2-2). We assume that soft supersymmetry-breaking terms preserve the group symmetry at some high input scale, and focus on the non-universal effects on different matter representations generated by gauge interactions at lower scales, as well as the charged LFV induced in Type-1 see-saw models of neutrino masses. We identify the different mechanisms that control the relic DM density in the various GUT models, and contrast their LFV and LHC signatures. The SU(5) and 4-2-2 models offer good detection prospects both at the LHC and in LFV searches, though with different LSP compositions, and the SU(5) and FSU(5) models offer LFV within the current reach. The 4-2-2 model allows chargino and gluino coannihilations with neutralinos, and the former offer good detection prospects for both the LHC and LFV, while gluino coannihilations lead to lower LFV rates. Our results indicate that LFV is a powerful tool that complements LHC and DM searches, providing significant insights into the sparticle spectra and neutrino mass parameters in different models.
Classical and quantum double copy of back-reaction
Authors: Adamo Tim , Ilderton Anton 
Published: October 2020

Abstract
We consider radiation emitted by colour-charged and massive particles crossing strong plane wave backgrounds in gauge theory and gravity. These backgrounds are treated exactly and non-perturbatively throughout. We compute the back-reaction on these fields from the radiation emitted by the probe particles: classically through background-coupled worldline theories, and at tree-level in the quantum theory through three-point amplitudes. Consistency of these two methods is established explicitly. We show that the gauge theory and gravity amplitudes are related by the double copy for amplitudes on plane wave backgrounds. Finally, we demonstrate that in four-dimensions these calculations can be carried out with a background-dressed version of the massive spinor-helicity formalism.
Chaos from massive deformations of Yang-Mills matrix models
Authors: Başkan K. , Kürkçüoğlu S. , Oktay O. , Taşcı C. 
Published: October 2020

AbstractWe focus on an SU(N) Yang-Mills gauge theory in 0 + 1-dimensions with the same matrix content as the bosonic part of the BFSS matrix model, but with mass deformation terms breaking the global SO(9) symmetry of the latter to SO(5)×SO(3)×ℤ2. Introducing an ansatz configuration involving fuzzy four and two spheres with collective time dependence, we examine the chaotic dynamics in a family of effective Lagrangians obtained by tracing over the aforementioned ansatz configurations at the matrix levels$$ N=\frac{1}{6} $$N=16(n+ 1)(n+ 2)(n+ 3), forn= 1,2, · · · ,7. Through numerical work, we determine the Lyapunov spectrum and analyze how the largest Lyapunov exponents(LLE) change as a function of the energy, and discuss how our results can be used to model the temperature dependence of the LLEs and put upper bounds on the temperature above which LLE values comply with the Maldacena-Shenker-Stanford (MSS) bound 2πT, and below which it will eventually be violated.
Bootstrapping conformal four-point correlators with slightly broken higher spin symmetry and 3D bosonization
Authors: Li Zhijin 
Published: October 2020

Abstract
Three-dimensional conformal field theories (CFTs) with slightly broken higher spin symmetry provide an interesting laboratory to study general properties of CFTs and their roles in the AdS/CFT correspondence. In this work we compute the planar four-point functions at arbitrary ’t Hooft coupling λ in the CFTs with slightly broken higher spin symmetry. We use a bootstrap approach based on the approximate higher spin Ward identity. We show that the bootstrap equation is separated into two parts with opposite parity charges, and it leads to a recursion relation for the λ expansions of the correlation functions. The λ expansions terminate at order λ2 and the solutions are exact in λ. Our work generalizes the approach proposed by Maldacena and Zhiboedov to four-point correlators, and it amounts to an on-shell study for the 3D Chern-Simons vector models and their holographic duals in AdS4. Besides, we show that the same results can also be obtained rather simply from bosonization duality of 3D Chern-Simons vector models. The odd term at order O(λ) in the spinning four-point function relates to the free boson correlator through a Legendre transformation. This provides new evidence on the 3D bosonization duality at the spinning four-point function level. We expect this work can be generalized to a complete classification of general four-point functions of single trace currents.
CAAI—a cognitive architecture to introduce artificial intelligence in cyber-physical production systems
Authors: Fischbach Andreas , Strohschein Jan , Bunte Andreas , Stork Jörg , Faeskorn-Woyke Heide , Moriz Natalia , Bartz-Beielstein Thomas 
Published: October 2020

AbstractThis paper introduces CAAI, a novel cognitive architecture for artificial intelligence in cyber-physical production systems. The goal of the architecture is to reduce the implementation effort for the usage of artificial intelligence algorithms. The core of the CAAI is a cognitive module that processes the user’s declarative goals, selects suitable models and algorithms, and creates a configuration for the execution of a processing pipeline on a big data platform. Constant observation and evaluation against performance criteria assess the performance of pipelines for many and different use cases. Based on these evaluations, the pipelines are automatically adapted if necessary. The modular design with well-defined interfaces enables the reusability and extensibility of pipeline components. A big data platform implements this modular design supported by technologies such as Docker, Kubernetes, and Kafka for virtualization and orchestration of the individual components and their communication. The implementation of the architecture is evaluated using a real-world use case. The prototypic implementation is accessible on GitHub and contains a demonstration.
Managerial characteristics and budget use in festival organizations
Authors: Knardal Per Ståle , Bjørnenak Trond 
Published: October 2020

AbstractFestivals are an important part of popular culture and have increased in popularity in recent decades. However, they remain relatively unexplored in the accounting literature, and understanding of the use of management control tools in this context is low. This study aims to investigate the use of budgets in festivals. Informed by upper echelons theory, it investigates how individual and observable characteristics of festival managers are associated with variations in the use of budgets. The study is based on a survey of 61 festival managers from 40 festivals. The findings suggest that festival budgets are particularly important in the planning and coordination process but used less frequently for ex post evaluations. The findings also indicate a positive association between a business educational background and the use of budgets for most purposes, with the exceptions of performance evaluation and reward. This paper contributes to the literature on accounting in popular culture in general and in festivals specifically. Through its application of upper echelons theory, it also contributes to the management accounting and control literature, showing how individual characteristics of managers influence the use of budgets.
A convolutional neural network for fully automated blood SUV determination to facilitate SUR computation in oncological FDG-PET
Authors: Nikulin Pavel , Hofheinz Frank , Maus Jens , Li Yimin , Bütof Rebecca , Lange Catharina , Furth Christian , Zschaeck Sebastian , Kreissl Michael C. , Kotzerke Jörg , van den Hoff Jörg 
Published: October 2020

Abstract
Purpose
The standardized uptake value (SUV) is widely used for quantitative evaluation in oncological FDG-PET but has well-known shortcomings as a measure of the tumor’s glucose consumption. The standard uptake ratio (SUR) of tumor SUV and arterial blood SUV (BSUV) possesses an increased prognostic value but requires image-based BSUV determination, typically in the aortic lumen. However, accurate manual ROI delineation requires care and imposes an additional workload, which makes the SUR approach less attractive for clinical routine. The goal of the present work was the development of a fully automated method for BSUV determination in whole-body PET/CT.

Methods
Automatic delineation of the aortic lumen was performed with a convolutional neural network (CNN), using the U-Net architecture. A total of 946 FDG PET/CT scans from several sites were used for network training (N = 366) and testing (N = 580). For all scans, the aortic lumen was manually delineated, avoiding areas affected by motion-induced attenuation artifacts or potential spillover from adjacent FDG-avid regions. Performance of the network was assessed using the fractional deviations of automatically and manually derived BSUVs in the test data.

Results
The trained U-Net yields BSUVs in close agreement with those obtained from manual delineation. Comparison of manually and automatically derived BSUVs shows excellent concordance: the mean relative BSUV difference was (mean ± SD) = (– 0.5 ± 2.2)% with a 95% confidence interval of [− 5.1,3.8]% and a total range of [− 10.0, 12.0]%. For four test cases, the derived ROIs were unusable (< 1 ml).

Conclusion
CNNs are capable of performing robust automatic image-based BSUV determination. Integrating automatic BSUV derivation into PET data processing workflows will significantly facilitate SUR computation without increasing the workload in the clinical setting.
MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas
Authors: Fuster-Garcia Elies , Lorente Estellés David , Álvarez-Torres María del Mar , Juan-Albarracín Javier , Chelebian Eduard , Rovira Alex , Acosta Cristina Auger , Pineda Jose , Oleaga Laura , Mollá-Olmos Enrique , Filice Silvano , Due-Tønnessen Paulina , Meling Torstein R. , Emblem Kyrre E. , García-Gómez Juan M. 
Published: October 2020

Abstract
Objectives
To assess the combined role of tumor vascularity, estimated from perfusion MRI, and MGMT methylation status on overall survival (OS) in patients with glioblastoma.

Methods
A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships between MGMT and perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored by MGMT methylation in terms of OS.

Results
rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV < 10.73), MGMT methylation was a positive predictive factor for OS (HR = 2.73, p = 0.003, AUC = 0.70). In patients with highly vascularized tumors (rCBV > 10.73), however, there was no significant effect of MGMT methylation (HR = 1.72, p = 0.10, AUC = 0.56).

Conclusions
Our results indicate the existence of complementary prognostic information provided by MGMT methylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most from MGMT methylation. Not considering this information may lead to bias in the interpretation of clinical studies.

Key Points
• MRI perfusion provides complementary prognostic information to MGMT methylation.
• MGMT methylation improves prognosis in glioblastoma patients with moderate vascular profile.
• Failure to consider these relations may lead to bias in the interpretation of clinical studies.
LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid–enhanced MRI for early recurrence risk stratification after curative resection
Authors: Wei Hong , Jiang Hanyu , Zheng Tianying , Zhang Zhen , Yang Caiwei , Ye Zheng , Duan Ting , Song Bin 
Published: October 2020

Abstract
Objectives
To explore the role of preoperative gadoxetic acid–enhanced MRI in stratifying the risk of early recurrence in patients with LR-5 hepatocellular carcinoma (HCC) by LI-RADS v2018 after curative resection.

Methods
Between July 2015 and August 2018, this study evaluated consecutive treatment-naïve at-risk LR-5 HCC patients who underwent gadoxetic acid–enhanced MRI examination within 2 weeks before curative resection. The Cox regression analysis was performed to identify potential predictors of early recurrence. Disease-free survival (DFS) rates were analyzed and compared by using the Kaplan-Meier method and log-rank tests.

Results
Fifty-three of 103 (51.5%) patients experienced early recurrence. Three MRI findings were significantly associated with early recurrence: corona enhancement (hazard ratio [HR]: 2.116; p = 0.013), peritumoral hypointensity on hepatobiliary phase (HBP) (HR: 2.262; p = 0.007), and satellite nodule (HR: 2.777; p = 0.005). An additional risk factor was AFP level > 400 ng/mL (HR: 1.975; p = 0.016). Based on the number of MRI predictors, LR-5 HCC patients were stratified into three subgroups: LR-5a (60/103; no predictor), LR-5b (26/103; one predictor), and LR-5c (17/103; two or three predictors), with low, medium, and high risk of early recurrence, respectively. The 2-year DFS rate of LR-5a, LR-5b, and LR-5c patients was 65.0%, 38.5%, and 5.9%, respectively, while the corresponding median DFS was undefined, 17.1 months, and 5.1 months, respectively (p < 0.001).

Conclusions
In at-risk LR-5 HCC patients, corona enhancement, peritumoral hypointensity on HBP, and satellite nodule could be used to preoperatively stratify the risk of early recurrence after hepatectomy.

Key Points
• Corona enhancement, peritumoral hypointensity on HBP, satellite nodule, and serum AFP level > 400 ng/mL were significant predictors of early recurrence in patients with LR-5 HCC after hepatectomy.
• Based on the number of predictive MRI findings, LR-5 HCC patients could be preoperatively stratified into three subgroups: LR-5a, LR-5b, and LR-5c, with significantly different risk of early recurrence and disease-free survival.
• Preoperative risk stratification is essential for the identification of patients at increased risk of postoperative early recurrence, which may contribute to risk-based personalized management for LR-5 HCC patients.
A flow resistive inspiratory muscle training mask worn during high-intensity interval training does not improve 5 km running time-trial performance
Authors: Faghy Mark A. , Brown Peter I. , Davis Nicola M. , Mayes J. P. , Maden-Wilkinson Tom M. 
Published: October 2020

Abstract
Purpose
There is little evidence of the ergogenic effect of flow-resistive masks worn during exercise. We compared a flow-resistive face mask (MASK) worn during high-intensity interval training (HIIT) against pressure threshold loading inspiratory muscle training (IMT).

Methods
23 participants (13 males) completed a 5 km time trial and six weeks of HIIT (3 sessions weekly). HIIT (n = 8) consisted of repeated work (2 min) at the speed equivalent to 95% $${\dot{\text{V}}}$$

V
˙

O2 peak with equal rest. Repetitions were incremental (six in weeks 1, 2 and 6, eight in weeks 3 and 4 and ten in week 5). Participants were allocated to one of three training groups. MASK (n = 8) wore a flow-resistive mask during all sessions. The IMT group (n = 8) completed 2 × 30 breaths daily at 50% maximum inspiratory pressure (PImax). A control group (CON, n = 7) completed HIIT only. Following HIIT, participants completed two 5 km time trials, the first matched identically to pre-intervention trial (ISO time), and a self-paced effort.

Results
Time trial performance was improved in all groups (MASK 3.1 ± 1.7%, IMT, 5.7 ± 1.5% and CON 2.6 ± 1.0%, p < 0.05). IMT improved greater than MASK and CON (p = 0.004). Post intervention, PImax and diaphragm thickness were improved in IMT only (32% and 9.5%, respectively, p = 0.003 and 0.024).

Conclusion
A flow-resistive mask worn during HIIT provides no benefit to 5 km performance when compared to HIIT only. Supplementing HIIT with IMT improves respiratory muscle strength, morphology and performance greater than HIIT alone.