bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative Bio-based Poly(Lactic Acid)/Poly(Alkylene Furanoate)s Fiber Blends for Sustainable Textile Applications
Authors: Perin Davide , Rigotti Daniele , Fredi Giulia , Papageorgiou George Z. , Bikiaris Dimitrios N. , Dorigato Andrea 
Published: May 2021

AbstractThis work aims at producing and investigating, for the first time, the microstructural and thermo-mechanical properties of fibers constituted by poly(lactic acid) (PLA)/poly(alkylene furanoate)s (PAFs) blends for textile applications. Two different PAFs have been investigated, i.e., poly(octylene furanoate) (P8F) and poly(dodecylene furanoate) (P12F), which have been blended with PLA in different concentrations and spun through a lab-made wet spinning device. The microstructural investigation of the fiber cross-section evidenced domains of PAFs homogeneously dispersed within the PLA matrix. The immiscibility of the produced blends was also suggested by the fact that the glass transition temperature of PLA was unaffected by the presence of PAF. The thermal stability of PLA was not substantially influenced by the PAF content, whereas the water absorption tendency decreased with an increase in P12F fraction. The mechanical properties of PLA/P8F blends decreased with the P8F amount, while for PLA/P12F fiber blends the stiffness and the strength were approximatively constant by increasing the P12F content. The drawing process, performed at 70 °C and with two different draw ratios, brought an interesting increase in the mechanical properties of PLA fibers upon P12F introduction. These promising results constitute the basis for future research on these innovative bio-based fibers.
Importance sampling in reinforcement learning with an estimated behavior policy
Authors: Hanna Josiah P. , Niekum Scott , Stone Peter 
Published: May 2021

AbstractIn reinforcement learning, importance sampling is a widely used method for evaluating an expectation under the distribution of data of one policy when the data has in fact been generated by a different policy. Importance sampling requires computing the likelihood ratio between the action probabilities of a target policy and those of the data-producing behavior policy. In this article, we study importance sampling where the behavior policy action probabilities are replaced by their maximum likelihood estimate of these probabilities under the observed data. We show this general technique reduces variance due to sampling error in Monte Carlo style estimators. We introduce two novel estimators that use this technique to estimate expected values that arise in the RL literature. We find that these general estimators reduce the variance of Monte Carlo sampling methods, leading to faster learning for policy gradient algorithms and more accurate off-policy policy evaluation. We also provide theoretical analysis showing that our new estimators are consistent and have asymptotically lower variance than Monte Carlo estimators.
Cross-Dimension Mining Model of Public Opinion Data in Online Education Based on Fuzzy Association Rules
Authors: Li Li-xuan , Huo Ying , Lin Jerry Chun-Wei 
Published: May 2021

AbstractThe multi-dimensional characteristics of public opinion in online education lead to the difficulty of data cross-dimensional mining. To solve this problem, this paper designs a cross-dimensional data mining model of public opinion in online education based on fuzzy association rules. Based on the public opinion subject, object, and ontology to analyze the characteristics of public opinion in online education, Yaahp software is used to calculate the influence factor weight of public opinion in online education. According to the weight analysis results, the relationship between the dimensions of various public opinion data is clarified by using data semantic association. This paper introduces the fuzzy set theory into the database and uses crawlers to obtain public opinion data and stores them in the database, to complete the data preprocessing through distributed text preprocessing, feature selection distributed computing, and text vectorization distributed computing. Taking the cloud computing platform as the core, the cross-dimension mining model of public opinion in online education data is constructed according to the dimension correlation analysis and preprocessing results. The simulation results show that the model has the advantages of wide range, fast speed, and high accuracy, and can provide data support for education reform.
A phase I/II study of bevacizumab, irinotecan and erlotinib in children with progressive diffuse intrinsic pontine glioma
Authors: El-Khouly Fatma E. , Veldhuijzen van Zanten Sophie E. M. , Jansen Marc H. A. , Bakker Dewi P. , Sanchez Aliaga Esther , Hendrikse N. Harry , Vandertop W. Peter , van Vuurden Dannis G. , Kaspers Gertjan J. L. 
Published: May 2021

Abstract
Introduction
This study investigates the safety, tolerability, and preliminary efficacy of combined treatment with VEGF inhibitor bevacizumab, topoisomerase I inhibitor irinotecan, and EGFR inhibitor erlotinib in children with progressive diffuse intrinsic pontine glioma (DIPG).

Methods
Biweekly bevacizumab (10 mg/kg) and irinotecan (125 mg/m2) were combined with daily erlotinib. Two cohorts received increasing doses of erlotinib (65 and 85 mg/m2) following a 3 + 3 dose-escalation schedule, until disease progression with a maximum of one year. Dose-limiting toxicities (DLT) were monitored biweekly. Secondary progression free survival (sPFS) and overall survival (OS) were determined based on clinical and radiological response measurements. Quality of life (QoL) during treatment was also assessed.

Results
Between November 2011 and March 2018, nine patients with disease progression after initial radiotherapy were enrolled. Median PFS at start of the study was 7.3 months (range 3.5–10.0). In the first dose cohort, one patient experienced a DLT (grade III acute diarrhea), resulting in enrollment of three additional patients in this cohort. No additional DLTs were observed in consecutive patients receiving up to a maximum dose of 85 mg/m2. Median sPFS was 3.2 months (range 1.0–10.9), and median OS was 13.8 months (range 9.3–33.0). Overall QoL was stable during treatment.

Conclusions
Daily erlotinib is safe and well tolerated in doses up to 85 mg/m2 when combined with biweekly bevacizumab and irinotecan in children with progressive DIPG. Median OS of the study patients was longer than known form literature.
A Study of Internet Development and Enterprise Financing in China
Authors: Chen Qiang , Zhang Yabin , Chen Lian 
Published: May 2021

AbstractThe development of the Internet has changed many traditional commercial models of enterprises. Therefore, the term Internet development is increasingly drawing attention from scholars. However, we are not certain whether the development of the Internet improves the problem of difficult financing of enterprises and enhances enterprise financing efficiency. This paper analyzes whether Internet development can promote enterprise financing efficiency. First, the Data Envelopment Analysis- Slack Based Measure (DEA-SBM) model is applied to measure the enterprise financing efficiency values of 31 provinces in China. The measurement results indicate that the enterprise financing efficiency in the eastern regions is higher than that of central and western regions. Then, this paper further tests if Internet development can contribute to enterprise financing efficiency based on an econometric model. The analysis results indicate that Internet development has an obvious promoting effect on enterprise financing efficiency. Later, spatial econometric models are adopted in this paper to further analyze if Internet development has a spatial overflow effect on enterprise financing efficiency. The results indicate that Internet development indeed has a spatial overflow effect on enterprise financing efficiency.
A Liposomal Gemcitabine, FF-10832, Improves Plasma Stability, Tumor Targeting, and Antitumor Efficacy of Gemcitabine in Pancreatic Cancer Xenograft Models
Authors: Matsumoto Takeshi , Komori Takashi , Yoshino Yuta , Ioroi Tadaaki , Kitahashi Tsukasa , Kitahara Hiromu , Ono Kohei , Higuchi Tamami , Sakabe Masayo , Kori Hiroshi , Kano Masahiro , Hori Ritsuko , Kato Yukio , Hagiwara Shinji 
Published: May 2021

Abstract
Purpose
The clinical application of gemcitabine (GEM) is limited by its pharmacokinetic properties. The aim of this study was to characterize the stability in circulating plasma, tumor targeting, and payload release of liposome-encapsulated GEM, FF-10832.

Methods
Antitumor activity was assessed in xenograft mouse models of human pancreatic cancer. The pharmacokinetics of GEM and its active metabolite dFdCTP were also evaluated.

Results
In mice with Capan-1 tumors, the dose-normalized areas under the curve (AUCs) after FF-10832 administration in plasma and tumor were 672 and 1047 times higher, respectively, than after using unencapsulated GEM. The tumor-to-bone marrow AUC ratio of dFdCTP was approximately eight times higher after FF-10832 administration than after GEM administration. These results indicated that liposomal encapsulation produced long-term stability in circulating plasma and tumor-selective targeting of GEM. In mice with Capan-1, SUIT-2, and BxPC-3 tumors, FF-10832 had better antitumor activity and tolerability than GEM. Internalization of FF-10832 in tumor-associated macrophages (TAMs) was revealed by flow cytometry and confocal laser scanning microscopy, and GEM was efficiently released from isolated macrophages of mice treated with FF-10832. These results suggest that TAMs are one of the potential reservoirs of GEM in tumors.

Conclusion
This study found that FF-10832 had favorable pharmacokinetic properties. The liposomal formulation was more effective and tolerable than unencapsulated GEM in mouse xenograft tumor models. Hence, FF-10832 is a promising candidate for the treatment of pancreatic cancer.
A robust and efficient algorithm to find profile likelihood confidence intervals
Authors: Fischer Samuel M. , Lewis Mark A. 
Published: May 2021

AbstractProfile likelihood confidence intervals are a robust alternative to Wald’s method if the asymptotic properties of the maximum likelihood estimator are not met. However, the constrained optimization problem defining profile likelihood confidence intervals can be difficult to solve in these situations, because the likelihood function may exhibit unfavorable properties. As a result, existing methods may be inefficient and yield misleading results. In this paper, we address this problem by computing profile likelihood confidence intervals via a trust-region approach, where steps computed based on local approximations are constrained to regions where these approximations are sufficiently precise. As our algorithm also accounts for numerical issues arising if the likelihood function is strongly non-linear or parameters are not estimable, the method is applicable in many scenarios where earlier approaches are shown to be unreliable. To demonstrate its potential in applications, we apply our algorithm to benchmark problems and compare it with 6 existing approaches to compute profile likelihood confidence intervals. Our algorithm consistently achieved higher success rates than any competitor while also being among the quickest methods. As our algorithm can be applied to compute both confidence intervals of parameters and model predictions, it is useful in a wide range of scenarios.
Continuous 3D Multi-Channel Sign Language Production via Progressive Transformers and Mixture Density Networks
Authors: Saunders Ben , Camgoz Necati Cihan , Bowden Richard 
Published: May 2021

AbstractSign languages are multi-channel visual languages, where signers use a continuous 3D space to communicate. Sign language production (SLP), the automatic translation from spoken to sign languages, must embody both the continuous articulation and full morphology of sign to be truly understandable by the Deaf community. Previous deep learning-based SLP works have produced only a concatenation of isolated signs focusing primarily on the manual features, leading to a robotic and non-expressive production. In this work, we propose a novel Progressive Transformer architecture, the first SLP model to translate from spoken language sentences to continuous 3D multi-channel sign pose sequences in an end-to-end manner. Our transformer network architecture introduces a counter decoding that enables variable length continuous sequence generation by tracking the production progress over time and predicting the end of sequence. We present extensive data augmentation techniques to reduce prediction drift, alongside an adversarial training regime and a mixture density network (MDN) formulation to produce realistic and expressive sign pose sequences. We propose a back translation evaluation mechanism for SLP, presenting benchmark quantitative results on the challenging PHOENIX14T dataset and setting baselines for future research. We further provide a user evaluation of our SLP model, to understand the Deaf reception of our sign pose productions.
VPR-Bench: An Open-Source Visual Place Recognition Evaluation Framework with Quantifiable Viewpoint and Appearance Change
Authors: Zaffar Mubariz , Garg Sourav , Milford Michael , Kooij Julian , Flynn David , McDonald-Maier Klaus , Ehsan Shoaib 
Published: May 2021

AbstractVisual place recognition (VPR) is the process of recognising a previously visited place using visual information, often under varying appearance conditions and viewpoint changes and with computational constraints. VPR is related to the concepts of localisation, loop closure, image retrieval and is a critical component of many autonomous navigation systems ranging from autonomous vehicles to drones and computer vision systems. While the concept of place recognition has been around for many years, VPR research has grown rapidly as a field over the past decade due to improving camera hardware and its potential for deep learning-based techniques, and has become a widely studied topic in both the computer vision and robotics communities. This growth however has led to fragmentation and a lack of standardisation in the field, especially concerning performance evaluation. Moreover, the notion of viewpoint and illumination invariance of VPR techniques has largely been assessed qualitatively and hence ambiguously in the past. In this paper, we address these gaps through a new comprehensive open-source framework for assessing the performance of VPR techniques, dubbed “VPR-Bench”. VPR-Bench (Open-sourced at: https://github.com/MubarizZaffar/VPR-Bench) introduces two much-needed capabilities for VPR researchers: firstly, it contains a benchmark of 12 fully-integrated datasets and 10 VPR techniques, and secondly, it integrates a comprehensive variation-quantified dataset for quantifying viewpoint and illumination invariance. We apply and analyse popular evaluation metrics for VPR from both the computer vision and robotics communities, and discuss how these different metrics complement and/or replace each other, depending upon the underlying applications and system requirements. Our analysis reveals that no universal SOTA VPR technique exists, since: (a) state-of-the-art (SOTA) performance is achieved by 8 out of the 10 techniques on at least one dataset, (b) SOTA technique in one community does not necessarily yield SOTA performance in the other given the differences in datasets and metrics. Furthermore, we identify key open challenges since: (c) all 10 techniques suffer greatly in perceptually-aliased and less-structured environments, (d) all techniques suffer from viewpoint variance where lateral change has less effect than 3D change, and (e) directional illumination change has more adverse effects on matching confidence than uniform illumination change. We also present detailed meta-analyses regarding the roles of varying ground-truths, platforms, application requirements and technique parameters. Finally, VPR-Bench provides a unified implementation to deploy these VPR techniques, metrics and datasets, and is extensible through templates.
Who Needs the Experts? The Politics and Practices of Alternative Humanitarianism and Its Relationship to NGOs
Authors: Ishkanian Armine , Shutes Isabel 
Published: May 2021

AbstractDrawing on fieldwork in Greece, we examine the politics and practices of autonomous volunteering in the context of the migration crisis. This involves individuals engaging in activities to support migrants through non-registered, self-organized and self-governed groups that work independent from and in some cases, even in opposition to NGOs. We consider autonomous volunteering as a form of collective action and argue that it constitutes an alternative humanitarianism. While recent literature has sought to identify the rise of emergent practices of alternative humanitarianism in Europe, research has often overlooked how autonomous volunteers distinguish themselves from, relate to and collaborate with NGOs and conversely, how NGOs view and engage with them. We found that despite their critiques of NGOs and their determination to work independently, there were instances of cooperation between autonomous volunteers and NGOs. These interactions did not become substantive alliances, as the work of NGOs and autonomous volunteers continued to be disconnected from each other.
Endothelial dysfunction in obstructive sleep apnea patients
Authors: Harańczyk Michał , Konieczyńska Małgorzata , Płazak Wojciech 
Published: May 2021

AbstractPurposeObstructive sleep apnea syndrome (OSAS) is an independent risk factor for cardiovascular diseases. The aim of the study was to assess the influence of OSAS on endothelial dysfunction and thrombosis biomarkers and to evaluate the effect of treatment with continuous positive airway pressure (CPAP) on biomarker levels.MethodsNT-proBNP, sICAM-1, endothelin-1, von Willebrand factor, D-dimers, and thrombin-antithrombin complex (TAT) were measured in 50 patients diagnosed with moderate-to-severe OSAS. All patients underwent transthoracic echocardiography, and 38 months after the inclusion, 16 CPAP users and 22 non-CPAP users were reassessed.ResultsSleep-related indices of apnea-hypopnea index (AHI) and mean SpO2were associated with higher sICAM-1 levels (AHI < 30: 7.3 ± 4.7 vs. AHI ≥ 30: 19.5 ± 19.4 mg/ml,p = 0.04; SpO2 ≥ 90%: 11.9 ± 9.3 vs. SpO2 < 90%: 23.6 ± 25.8,p = 0.04). sICAM-1 levels were significantly higher in obese patients, particularly with BMI ≥ 40. Plasma levels of TAT were significantly correlated with the increased right ventricular size (right ventricular diameter ≤ 37 mm: 0.86 ± 0.70 vs. > 37 mm: 1.96 ± 1.20 ng/ml,p = 0.04). Endothelin-1 levels were higher in patients with decreased right ventricular function (right ventricle TDI-derived S′ ≥ 12 cm/s: 11.5 ± 10.9 vs. < 12 cm/s: 26.0 ± 13.2 pg/ml,p = 0.04). An increase in NT-proBNP was related to impaired parameters of the right ventricular contractile function. There were no correlations between long-term CPAP therapy and the levels of biomarkers.ConclusionSevere OSAS influences endothelial damage as manifested by an increase in sICAM-1 levels. Changes in right ventricular structure and function, observed mainly in patients with higher TAT and endothelin-1 levels, are also manifested by an increase in NT-proBNP levels. Long-term CPAP treatment does not seem to influence biomarkers in patients with moderate-to-severe OSAS, which may help to explain the lack of influence of CPAP on cardiovascular risk reduction.
Hemodynamic changes of abdominal organs after CT colonography with transrectal administration of CO2: evaluation with early-phase contrast-enhanced dynamic CT
Authors: Ihara Kenichiro , Onoda Hideko , Tanabe Masahiro , Kanki Akihiko , Ito Katsuyoshi 
Published: May 2021

Abstract
Purpose
To evaluate the hemodynamic changes in the liver, pancreas, gastric mucosa and abdominal vessels in early-phase dynamic contrast-enhanced (DCE) CT immediately after CT colonography (CTC) with carbon dioxide expansion.

Materials and methods
This study included 82 patients with DCE-CT after CTC (CTC group) and 77 patients without CTC (control group). Contrast enhancement values of the gastric mucosa, liver, pancreas, portal vein (PV), splenic vein (SpV), superior mesenteric vein (SMV), and inferior mesenteric vein (IMV) in early-phase CT were measured. The presence of hepatic pseudolesions were also recorded.

Results
The mean contrast enhancement values of the gastric mucosa, pancreas and SpV in the CE-CTC group were significantly lower than those in the control group (p < 0.001, p < 0.001, p = 0.014). Conversely, the mean contrast enhancement values of the liver, PV, SMV and IMV in the CE-CTC group were significantly higher than those in the control group (p = 0.003, p = 0.013, p < 0.001, p < 0.001). Hypovascular hepatic pseudolesions were seen in early-phase CT in six patients after CTC, while they were not seen in the control group.

Conclusions
On DCE-CT performed immediately after CTC with carbon dioxide expansion, it is important to be aware of the imaging findings induced by visceral hemodynamic changes.
Role of Exercise as a Modulating Factor in Arrhythmogenic Cardiomyopathy
Authors: Zorzi Alessandro , Cipriani Alberto , Bariani Riccardo , Pilichou Kalliopi , Corrado Domenico , Bauce Barbara 
Published: May 2021

Abstract
Purpose of Review
The review addresses the role of exercise in triggering ventricular arrhythmias and promoting disease progression in arrhythmogenic cardiomyopathy (AC) patients and gene-mutation carriers, the differential diagnosis between AC and athlete’s heart and current recommendations on exercise activity in AC.

Recent Findings
AC is an inherited heart muscle disease caused by genetically defective cell-to-cell adhesion structures (mainly desmosomes). The pathophysiological hallmark of the disease is progressive myocyte loss and replacement by fibro-fatty tissue, which creates the substrates for ventricular arrhythmias. Animal and human studies demonstrated that intense exercise, but not moderate physical activity, may increase disease penetrance, worsen the phenotype, and favor life-threatening ventricular arrhythmias. It has been proposed that in some individuals prolonged endurance sports activity may in itself cause AC (so-called exercise-induced AC).

Summary
The studies agree that intense physical activity should be avoided in patients with AC and healthy gene-mutation carriers. However, low-to-moderate intensity exercise does not appear detrimental and these patients should not be entirely deprived from the many health benefits of physical activity.
Should We Be Using Upstream Beta-Blocker Therapy for Acute Myocardial Infarction?
Authors: Giannakopoulos Georgios , Noble Stephane 
Published: May 2021

Abstract
Purpose of Review
Controversy exists whether beta-blockers should be given before primary percutaneous coronary intervention (PCI) or to defer their administration for up to 24 hours.

Recent Findings
Animal studies, most of them conducted in the 1970s and 1980s, showed evidence that early beta-blocker administration may reduce infarct size. Subsequent human studies had mixed results on infarct size and survival. More specifically, in the current primary PCI era, only four studies evaluated the impact of early intravenous beta-blocker administration after acute myocardial infarction, only two of them before PCI. All studies agree that in hemodynamically stable patients, early intravenous beta-blocker administration is safe and protected against malignant arrhythmias. Nevertheless, results on infarct size and mortality are equivocal.

Summary
Considering the heterogeneity of currently available data, further studies are still needed to assess the benefit of early injection of metoprolol in STEMI patients in a large double-blinded and randomized design versus placebo.