bluuebunny/crossref_metadata_2025_split huggingface dataset:
An improved, less erroneous protocol for the classical “cuen”, “cuoxam” or “cadoxen” viscosity measurements of pulps
Authors: Zaccaron Sara , Ahn Kyujin , Henniges Ute , Potthast Antje , Rosenau Thomas 
Published: March 2022

AbstractCorrectness and reliability of molar mass data by viscometry in organometallic solvents (cuen, cuoxam, cadoxen) are compromised by the alkalinity of these solvents which causes immediate depolymerization especially in the case of pulps with higher carbonyl content (oxidative damage). The viscosity values thus correspond to the molar mass after the beta-elimination reactions that underly these degradative processes, which is sometimes significantly smaller than the molar mass determined by gel permeation chromatography (GPC) in the non-degrading solvent system DMAc/LiCl. Despite this well-known drawback, viscosity measurements have become a standard approach for molar mass measurements due to their ease and fastness, especially in the pulp and paper industries. A potential way to reduce the inherent error of these molar mass determinations via viscosity measurements is a reductive treatment prior to dissolution of the pulp in the organometallic solvents, which converts the labile, alkali-sensitive carbonyl structures back to the respective alcohols. Using sodium borohydride (NaBH4) on different types of cellulosic pulps, we demonstrate the beneficial effects of such a reduction step on the determined degree of polymerization (DP) for all three common solvents: cuen, cuoxam and cadoxen. Molar mass distributions and profiles of carbonyl groups were determined by GPC and by carbonyl selective fluorescence labeling (“CCOA method”). Such a reductive treatment was especially valuable for hemicellulose-containing pulps. While the decreased measurement error according to the new protocol is beyond doubt, an immediate acceptance in the pulp and paper industries is at least questionable, because the new, more correct data would not agree with the old – wrong, but consistent – numbers accumulated over years and decades. In the long run, however, the new, improved protocol will prevail here as well due to its lower error rate.
Statin use is associated with lower risk of dementia in stroke patients: a community-based cohort study with inverse probability weighted marginal structural model analysis
Authors: Yang Zhirong , Toh Sengwee , Li Xiaojuan , Edwards Duncan , Brayne Carol , Mant Jonathan 
Published: March 2022

AbstractCurrent evidence is inconclusive on cognitive benefits or harms of statins among stroke patients, who have high risk of dementia. This observational cohort study investigated the association between statin use and post-stroke dementia using data from the Clinical Practice Research Datalink. Patients without prior dementia who had an incident stroke but received no statins in the preceding year were followed for up to 10 years. We used inverse probability weighted marginal structural models to estimate observational analogues of intention-to-treat (ITT, statin initiation vs. no initiation) and per-protocol (PP, sustained statin use vs. no use) effects on the risk of dementia. To explore potential impact of unmeasured confounding, we examined the risks of coronary heart disease (CHD, positive control outcome), fracture and peptic ulcer (negative control outcomes). In 18,577 statin initiators and 14,613 non-initiators (mean follow-up of 4.2 years), the adjusted hazard ratio (aHR) for dementia was 0.70 (95% confidence interval [CI] 0.64–0.75) in ITT analysis and 0.55 (95% CI 0.50–0.62) in PP analysis. The corresponding aHRITT and aHRPP were 0.87 (95% CI 0.79–0.95) and 0.70 (95% CI 0.62–0.80) for CHD, 1.03 (95% CI 0.82–1.29) and 1.09 (95% CI 0.77–1.54) for peptic ulcer, and 0.88 (95% CI 0.80–0.96) and 0.86 (95% CI 0.75–0.98) for fracture. Statin initiation after stroke was associated with lower risk of dementia, with a potentially greater benefit in patients who persisted with statins over time. The observed association of statin use with post-stroke dementia may in part be overestimated due to unmeasured confounding shared with the association between statin use and fracture.
Update of the Xylella fastidiosa outbreak in France: two new variants detected and a new region affected
Authors: Cunty Amandine , Legendre Bruno , de Jerphanion Pauline , Dousset Christèle , Forveille Aurélie , Paillard Sandrine , Olivier Valérie 
Published: March 2022

AbstractXylella fastidiosa is a xylem-limited bacterium native to America and classified as a priority pest for EU regulation. Since 2013, X. fastidiosa has been identified in European countries with a Mediterranean climate, such as Italy, France, Spain and Portugal, with different subspecies and sequence types (ST) detected. Since 2015 X. fastidiosa subsp. multiplex ST6 and/or ST7 has been detected in Corsica and the Provence-Alpes-Côte d’Azur in almost 70 plant species, whereas X. fastidiosa subsp. pauca ST53 has been found in only two host plants. In this study, we report two new variants, recently detected in two separated areas of the PACA region, genetically related to the subspecies multiplex and assigned to (i) ST88 detected on Polygala myrtifolia, Hebe sp., Osteospermum ecklonis, Lavandula x intermedia, Coronilla glauca and Euryops chrysanthemoides and (ii) ST89: detected on Myoporum sp. and Viburnum tinus. Both variant strains were isolated in vitro. Moreover, we report here the identification of X. fastidiosa subsp. multiplex ST6 in a new region of the South of France, Occitanie (Aude), in plants from natural and urban settings and from a nursery.
Visualizing the customization endeavor in product-based-evolving software product lines: a case of action design research
Authors: Díaz Oscar , Montalvillo Leticia , Medeiros Raul , Azanza Maider , Fogdal Thomas 
Published: March 2022

AbstractSoftware Product Lines (SPLs) aim at systematically reusing software assets, and deriving products (a.k.a., variants) out of those assets. However, it is not always possible to handle SPL evolution directly through these reusable assets. Time-to-market pressure, expedited bug fixes, or product specifics lead to the evolution to first happen at the product level, and to be later merged back into the SPL platform where the core assets reside. This is referred to as product-based evolution. In this scenario, deciding when and what should go into the next SPL release is far from trivial. Distinct questions arise. How much effort are developers spending on product customization? Which are the most customized core assets? To which extent is the core asset code being reused for a given product? We refer to this endeavor as Customization Analysis, i.e., understanding the functional increments in adjusting products from the last SPL platform release. The scale of the SPLs’ code-base calls for customization analysis to be conducted through Visual Analytics tools. This work addresses the design principles for such tools through a joint effort between academia and industry, specifically, Danfoss Drives, a company division in charge of the P400 SPL. Accordingly, we adopt an Action Design Research approach where answers are sought by interacting with the practitioners in the studied situations. We contribute by providing informed goals for customization analysis as well as an intervention in terms of a visual analytics tool. We conclude by discussing to what extent this experience can be generalized to product-based evolving SPL organizations other than Danfoss Drives.
Hope for the Evolutionary Debunker: How Evolutionary Debunking Arguments and Arguments from Moral Disagreement Can Join Forces
Authors: Tersman Folke , Risberg Olle 
Published: March 2022

AbstractFacts about moral disagreement and human evolution have both been said to exclude the possibility of moral knowledge, but the question of how these challenges interact has largely gone unaddressed. The paper aims to present and defend a novel version of the evolutionary “debunking” argument for moral skepticism that appeals to both types of considerations. This argument has several advantages compared to more familiar versions. The standard debunking strategy is to argue that evolutionary accounts of moral beliefs generate skeptical implications because they attribute those beliefs to factors that are unrelated to their truth. That strategy is vulnerable to “third-factor” responses, which invoke first-order moral claims to challenge the assumption that Darwinian factors and the moral truths are really unrelated in that way. In contrast, our version is immune to those responses, as it does not proceed via assumptions about how Darwinian factors relate to the moral facts. Instead, it focuses on what evolutionary accounts of moral beliefs have to say about the fact that people often reach divergent moral beliefs. The argument thereby illustrates how the debunking strategy can join forces with the argument from moral disagreement. The combination of those strategies presents, we think, a challenge that is more formidable than when they are considered separately.
Accurate Detection of Occluded Wildfire Boundary
Authors: Feng Licheng , Katupitiya Jay 
Published: March 2022

AbstractInaccurate localization of wildfire boundary will adversely affect the efficiency of fire fighting, especially in the case of limited water for aerial dumping. This paper formulates the detection of occluded wildfire boundary as a shape completion problem and introduces a new solution. Different from traditional shape completion algorithms which only consider the contour geometry, the proposed algorithm takes partially visible fire surface geometry into consideration, and generates extrapolated feature points to detect the invisible section. The proposed solution involves two processes: firstly, fire surfaces above the occluded segments are extrapolated to the ground level with a Hurwitz–Radon operator based algorithm to obtain feature points in the invisible segments of the wildfire boundary; secondly, interpolating extra control points with a Bezier curve to reduce uncertainty and improve the accuracy of fire boundary detection. To demonstrate the effectiveness and efficiency of the proposed algorithm, a series of numerical simulations were performed. Simulated results show that the proposed algorithm in this study can detect the occluded wildfire boundary that conforms with the ground truth of the invisible fire boundary.
Connected components of Isom($$\varvec{\pmb {\mathbb {H}}^3}$$)-representations of non-orientable surfaces
Authors: Durán Batalla Juan Luis 
Published: March 2022

AbstractLet $$N_k$$

N
k

denote the closed non-orientable surface of genus k. In this paper we study the behaviour of the ‘square map’ from the group of isometries of hyperbolic 3-space to the subgroup of orientation preserving isometries. The properties of the ‘square map’ and other related maps serve as a technical step towards the counting of the connected components of the variety of representations of $$\pi _1(N_k)$$

π
1

(

N
k

)

in Isom$$(\mathbb {H}^3)$$

(

H

3

)

. We show that the variety of representations hom($$\pi _1(N_k),\mathrm {Isom}(\mathbb {H}^3)$$

π
1

(

N
k

)

,
Isom

(

H

3

)

) has $$2^{k+1}$$

2

k
+
1

connected components, which are distinguished by the Stiefel-Whitney classes of the associated flat bundle.
Assessing learning processes rather than outcomes: using critical incidents to explore student learning abroad
Authors: Davis Kirsten A. , Knight David B. 
Published: March 2022

AbstractThere is an increasing emphasis on assessing student learning outcomes from study abroad experiences, but this assessment often focuses on a limited range of outcomes and assessment methods. We argue for shifting to assessing student learning processes in study abroad and present the critical incident technique as one approach to achieve this goal. We demonstrate this approach in interviews with 79 students across a range of global engineering programs, through which we identified 173 incidents which were analyzed to identify common themes. This analysis revealed that students described a wide range of experiences and outcomes from their time abroad. Students’ experiences were messy and complex, making them challenging to understand through typical assessment approaches. Our findings emphasize the importance of using a range of assessment approaches and suggest that exploring students’ learning processes in addition to learning outcomes could provide new insights to inform the design of study abroad programs.
Curcumin attenuates inflammation of Macrophage-derived foam cells treated with Poly-L-lactic acid degradation via PPARγ signaling pathway
Authors: Chen Dongping , Xi Yangbo , Zhang Suzhen , Weng Linsheng , Dong Zhihui , Chen Can , Wu Tim , Xiao Jianmin 
Published: March 2022

AbstractPoly-L-lactic acid (PLLA) is considered to be a promising candidate material for biodegradable vascular scaffolds (BVS) in percutaneous coronary intervention (PCI). But, PLLA-BVS also faces the challenge of thrombosis (ST) and in-stent restenosis (ISR) caused by in-stent neo-atherosclerosis (ISNA) associated with inflammatory reactions in macrophage-derived foam cells. Our previous studies have confirmed that curcumin alleviates PLLA-induced injury and inflammation in vascular endothelial cells, but it remains unclear whether curcumin can alleviate the effect of inflammatory reactions in macrophage-derived foam cells while treated with degraded product of PLLA. In this study, PLLA-BVS was implanted in the porcine coronary artery to examine increased macrophages and inflammatory cytokines such as NF-κb and TNF-α by histology and immunohistochemistry. In vitro, macrophage-derived foam cells were induced by Ox-LDL and observed by Oil Red Staining. Foam cells were treated with pre-degraded PLLA powder, curcumin and PPARγ inhibitor GW9662, and the expression of IL-6, IL-10, TNF-α, NF-κb, PLA2 and PPARγ were investigated by ELISA or RT-qPCR. This study demonstrated that the macrophages and inflammatory factors increased after PLLA-BVS implantation in vivo, and foam cells derived from macrophages promoted inflammation by products of PLLA degradation in vitro. This present study was found that the inflammation of foam cells at the microenvironment of PLLA degraded products were significantly increased, and curcumin can attenuate the inflammation caused by the PLLA degradation via PPARγ signal pathway. In addition, curcumin should be further studied experimentally in vivo experiments on animal models as a potential therapeutic to reduce ISNA of PLLA-BVS.
Optimization and validation of multi-state NMR protein structures using structural correlations
Authors: Ashkinadze Dzmitry , Kadavath Harindranath , Riek Roland , Güntert Peter 
Published: March 2022

AbstractRecent advances in the field of protein structure determination using liquid-state NMR enable the elucidation of multi-state protein conformations that can provide insight into correlated and non-correlated protein dynamics at atomic resolution. So far, NMR-derived multi-state structures were typically evaluated by means of visual inspection of structure superpositions, target function values that quantify the violation of experimented restraints and root-mean-square deviations that quantify similarity between conformers. As an alternative or complementary approach, we present here the use of a recently introduced structural correlation measure, PDBcor, that quantifies the clustering of protein states as an additional measure for multi-state protein structure analysis. It can be used for various assays including the validation of experimental distance restraints, optimization of the number of protein states, estimation of protein state populations, identification of key distance restraints, NOE network analysis and semiquantitative analysis of the protein correlation network. We present applications for the final quality analysis stages of typical multi-state protein structure calculations.
On the Moments of the Partition Function of the C$$\beta $$E Field
Authors: Assiotis Theodoros 
Published: March 2022

AbstractWe obtain a combinatorial formula for the positive integer moments of the partition function of the$$C\beta E_{N}$$CβENfield, or equivalently the moments of the moments of the characteristic polynomial of the$$C\beta E_{N}$$CβENensemble. We then use this formula to establish the largeNasymptotics of these moments in the “moment-supercritical” regime. A key role is played by Jack polynomials.
The effect of technological relatedness on firm sales evolution through external knowledge sourcing
Authors: Guerrero Alex J. , Heijs Joost , Huergo Elena 
Published: March 2022

AbstractThis paper analyzes the impact of knowledge spillovers on firm performance measured through total sales, the percentage of innovative sales and a categorical variable that classifies firms into three different groups depending on the stage of their sales growth evolution: upturn, downturn, or transition. We specifically focus on whether there are asymmetric spillover effects depending on the intermediary role of firms’ technological relatedness, which we proxy by the use of external sources of knowledge. Using data on 5900 Spanish firms for the period 2004–2016, we find that spillover effects from intra-sector and upstream knowledge pools are—in general—positive, although with some differences depending on the measure of firm performance and on the moderating role of technological networking. Our results also suggest the presence of a “business stealing effect” in environments with a high proportion of knowledge-based gross added value. Furthermore, we find that spillover effects are asymmetric depending on the firm’s size and intensity of R&D employment. Knowledge spillovers seem to play a more significant role in the case of SMEs than in large companies, and firms with high intensities of R&D employment benefit more from upstream spillovers and less from horizontal spillovers than firms with low intensities.
S-Adenosylmethionine affects ERK1/2 and STAT3 pathway in androgen-independent prostate cancer cells
Authors: Schmidt Thomas 
Published: March 2022

Abstract
Background
The most critical point in the treatment of prostate cancer is the progression towards a hormone-refractory tumour, making research on alternative therapies necessary. This study focused on the methyl donor S-adenosylmethionine (SAM), which is known to act as an antitumourigenic in several cancer cell lines. Though a genome-wide downregulation of proto-oncogenes in prostate cancer cell lines treated with SAM is obvious, the anticancer effects remain elusive. Thus, in this study, the impact of SAM treatment on the cell cycle, apoptosis and cancer-related pathways was investigated.

Methods and results
After performing SAM treatment on prostate cancer cell lines (PC-3 and DU145), a cell-cycle arrest during the S-phase, a downregulation of cyclin A protein levels and an upregulation of p21 cell cycle inhibitor were observed. The proapoptotic Bax/Bcl-2 ratio and the caspase-3 activity were elevated; additionally, the apoptosis rate of SAM treated cells increased significantly in a time-dependent manner. Moreover, immunoblots displayed a downregulation of Erk1/2 and STAT3 phosphorylation accompanied by a reduced expression of the STAT3 protein.

Conclusion
SAM caused changes in cancer-related pathways, probably leading to the effects on the cell cycle and apoptosis rate. These results provide deeper insights into the anticancer effects of SAM on prostate cancer cells.
Robust color image watermarking using multiple fractional-order moments and chaotic map
Authors: Hosny Khalid M. , Darwish Mohamed M. 
Published: March 2022

AbstractRobust watermarking is an effective method and a promising solution for securing and protecting the copyright of digital images. Moments and moment invariants have become popular tools for robust watermarking due to their geometric invariance and favorable capability of image description. Many moments-based robust watermarking schemes have been proposed. However, there is a challenging problem of these schemes that should be addressed. One of these problems is to improve both imperceptibility and robustness. In contrast, the other problem, most of these schemes used inefficient, traditional computation methods of the moments, resulting in an inaccurate and inefficient performance of the watermarking schemes. To overcome these challenges, in this paper, we propose a novel robust color image-watermarking algorithm based on new multiple fractional multi-channel orthogonal moments, fractional-order exponent moments (MFrEMs), fractional-order polar harmonic transforms (MFrPHTs), and fractional-order radial harmonic Fourier moments (MFrRHFMs). Firstly, highly accurate fractional new multi-channel orthogonal moments are computed for the host color images. Then, more stable and accurate coefficients of fractional new multi-channel orthogonal moments are selected. Finally, a robust color image watermarking approach for multiple watermarks images is proposed based on MFrEMs, MFrPHTs, and MFrRHFMs using a 1D Sine chaotic map. The experimental results demonstrate that the proposed approach provides robustness against various attacks and better imperceptibility than the existing methods.
Deep Distributional Sequence Embeddings Based on a Wasserstein Loss
Authors: Abdelwahab Ahmed , Landwehr Niels 
Published: March 2022

AbstractDeep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions.