bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dependent plurals and three levels of multiplicity
Authors: Minor Serge 
Published: July 2021

AbstractThe paper focuses on the semantics of distributivity, grammatical number, and cardinality predicates (numerals and modifiers like several). I argue that constructions involving so-called ‘dependent plurals’, i.e. plurals lacking cardinality predicates occurring in the scope of certain quantificational items such as all and most (e.g. All the girls were wearing hats), pose a challenge to familiar semantic frameworks that distinguish between two sources of multiplicity: mereological plurality and distributive quantification. I argue that dependent plural readings should be analysed as distinct both from cumulative readings and distributive readings, in the classical sense. I demonstrate how this can be accomplished in a semantic framework where expressions are evaluated relative to sets of assignments, or plural info states (van den Berg, in Stokhof and Torenvliet (eds) Proceedings of the 7th Amsterdam Colloquium, ILLC, University of Amsterdam, Amsterdam, 1990, in Dekker and Stokhof (eds) Proceedings of the 9th Amsterdam Colloquium, ILLC, University of Amsterdam, Amsterdam, 1994, Some aspects of the Internal Structure of Discourse. The Dynamics of Nominal Anaphora. PhD thesis, University of Amsterdam, 1996). The specific formal implementation is based on a modified version of Brasoveanu’s (Structured nominal and modal reference. PhD thesis, Rutgers, The State University of New Jersey, 2007, Linguist Philos 31(2):129–209. 10.1007/s10988-008-9035-0, 2008) Plural Compositional DRT. In this framework we are able to distinguish between two types of distributivity: weak distributivity across the assignments in a single plural info state and strong distributivity across multiple info states. I argue that both of these types of distributivity play a role in the semantics of natural language, accounting for the contrasting properties of ‘singular quantifiers’, such as each and every, and ‘plural quantifiers’, such as all and most. The contrasting properties of bare plurals and plurals involving cardinality modifiers are analysed in terms of the distinction between state-level and assignment-level (mereological) plurality.
TRU-NET: a deep learning approach to high resolution prediction of rainfall
Authors: Adewoyin Rilwan A. , Dueben Peter , Watson Peter , He Yulan , Dutta Ritabrata 
Published: July 2021

AbstractClimate models (CM) are used to evaluate the impact of climate change on the risk of floods and heavy precipitation events. However, these numerical simulators produce outputs with low spatial resolution that exhibit difficulties representing precipitation events accurately. This is mainly due to computational limitations on the spatial resolution used when simulating multi-scale weather dynamics in the atmosphere. To improve the prediction of high resolution precipitation we apply a Deep Learning (DL) approach using input data from a reanalysis product, that is comparable to a climate model’s output, but can be directly related to precipitation observations at a given time and location. Further, our input excludes local precipitation, but includes model fields (weather variables) that are more predictable and generalizable than local precipitation. To this end, we present TRU-NET (Temporal Recurrent U-Net), an encoder-decoder model featuring a novel 2D cross attention mechanism between contiguous convolutional-recurrent layers to effectively model multi-scale spatio-temporal weather processes. We also propose a non-stochastic variant of the conditional-continuous (CC) loss function to capture the zero-skewed patterns of rainfall. Experiments show that our models, trained with our CC loss, consistently attain lower RMSE and MAE scores than a DL model prevalent in precipitation downscaling and outperform a state-of-the-art dynamical weather model. Moreover, by evaluating the performance of our model under various data formulation strategies, for the training and test sets, we show that there is enough data for our deep learning approach to output robust, high-quality results across seasons and varying regions.
Density-based weighting for imbalanced regression
Authors: Steininger Michael , Kobs Konstantin , Davidson Padraig , Krause Anna , Hotho Andreas 
Published: July 2021

AbstractIn many real world settings,
imbalanced data impedes model performance of learning algorithms, like neural networks, mostly for rare cases. This is especially problematic for tasks focusing on these rare occurrences. For example, when estimating precipitation, extreme rainfall events are scarce but important considering their potential consequences. While there are numerous well studied solutions for classification settings, most of them cannot be applied to regression easily. Of the few solutions for regression tasks, barely any have explored cost-sensitive learning which is known to have advantages compared to sampling-based methods in classification tasks. In this work, we propose a sample weighting approach for imbalanced regression datasets called DenseWeight and a cost-sensitive learning approach for neural network regression with imbalanced data called DenseLoss based on our weighting scheme. DenseWeight weights data points according to their target value rarities through kernel density estimation (KDE). DenseLoss adjusts each data point’s influence on the loss according to DenseWeight, giving rare data points more influence on model
training compared to common data points. We show on multiple differently distributed datasets that DenseLoss significantly improves model performance for rare data points through its density-based weighting scheme. Additionally, we compare DenseLoss to the state-of-the-art method SMOGN, finding that our method mostly yields better performance. Our approach provides more control over model training as it enables us to actively decide on the trade-off between focusing on common or rare cases through a single hyperparameter, allowing the training of better models for rare data points.
Information-theoretic regularization for learning global features by sequential VAE
Authors: Akuzawa Kei , Iwasawa Yusuke , Matsuo Yutaka 
Published: July 2021

AbstractSequential variational autoencoders (VAEs) with a global latent variable z have been studied for disentangling the global features of data, which is useful for several downstream tasks. To further assist the sequential VAEs in obtaining meaningful z, existing approaches introduce a regularization term that maximizes the mutual information (MI) between the observation and z. However, by analyzing the sequential VAEs from the information-theoretic perspective, we claim that simply maximizing the MI encourages the latent variable to have redundant information, thereby preventing the disentanglement of global features. Based on this analysis, we derive a novel regularization method that makes z informative while encouraging disentanglement. Specifically, the proposed method removes redundant information by minimizing the MI between z and the local features by using adversarial training. In the experiments, we trained two sequential VAEs, state-space and autoregressive model variants, using speech and image datasets. The results indicate that the proposed method improves the performance of downstream classification and data generation tasks, thereby supporting our information-theoretic perspective for the learning of global features.
Board behavior’s impact on entrepreneurial orientation in public enterprises
Authors: Tremml Timo , Löbbe Sabine , Kuckertz Andreas 
Published: July 2021

AbstractPublic enterprises find themselves in increasingly competitive markets, a situation that makes having an entrepreneurial orientation (EO) an urgent need, given that EO is an indispensable driver of performance. Research describes politicians delaying the strategic change of public enterprises when serving as board members, but empirical evidence of the impact of board behavior on EO in public enterprises is lacking. We draw on stakeholder-agency theory (SAT) and resource dependence theory (RDT) and use structural equation modeling (SEM) to investigate survey data collected from 110 German energy suppliers that are majority government owned. Results indicate that board strategy control and board networking do not seem to predict EO on first sight. Closer analysis reveals a board networking–EO relationship depending on ownership structure. Remarkably, we find that it is not the usually suspected local municipal owner who hinders EO in our sample organizations but minority shareholders engaging in board networking activities. The results shed light on the intersection of governance and entrepreneurship with special reference to the fine-grained conceptualization of RDT.
Robustness of digital camera identification with convolutional neural networks
Authors: Bernacki Jarosław 
Published: July 2021

AbstractThis paper considers the area of digital forensics (DF). One of the problem in DF is the issue of identification of digital cameras based on images. This aspect has been attractive in recent years due to popularity of social media platforms like Facebook, Twitter etc., where lots of photographs are shared. Although many algorithms and methods for digital camera identification have been proposed, there is lack of research about their robustness. Therefore, in this paper the robustness of digital camera identification with the use of convolutional neural network is discussed. It is assumed that images may be of poor quality, for example, degraded by Poisson noise, Gaussian blur, random noise or removing pixels’ least significant bit. Experimental evaluation conducted on two large image datasets (including Dresden Image Database) confirms usefulness of proposed method, where noised images are recognized with almost the same high accuracy as normal images.
Critical Relations of Crowns in Critical Times of Coronavirus Depression
Authors: Kunos Ádám , Maróti Miklós , Zádori László 
Published: July 2021

AbstractThe critical relations are the building blocks of the relational clone of a relational structure with respect to the relational operations intersection and direct product. In this paper we describe the critical relations of crowns. As a consequence, we obtain that the subpower membership problem for any crown is polynomial-time solvable.
Root anatomy and soil resource capture
Authors: Lynch Jonathan P. , Strock Christopher F. , Schneider Hannah M. , Sidhu Jagdeep Singh , Ajmera Ishan , Galindo-Castañeda Tania , Klein Stephanie P. , Hanlon Meredith T. 
Published: July 2021

Abstract
Background
Suboptimal water and nutrient availability are primary constraints in global agriculture. Root anatomy plays key roles in soil resource acquisition. In this article we summarize evidence that root anatomical phenotypes present opportunities for crop breeding.

Scope
Root anatomical phenotypes influence soil resource acquisition by regulating the metabolic cost of soil exploration, exploitation of the rhizosphere, the penetration of hard soil domains, the axial and radial transport of water, and interactions with soil biota including mycorrhizal fungi, pathogens, insects, and the rhizosphere microbiome. For each of these topics we provide examples of anatomical phenotypes which merit attention as selection targets for crop improvement. Several cross-cutting issues are addressed including the importance of phenotypic plasticity, integrated phenotypes, C sequestration, in silico modeling, and novel methods to phenotype root anatomy including image analysis tools.

Conclusions
An array of anatomical phenes have substantial importance for the acquisition of water and nutrients. Substantial phenotypic variation exists in crop germplasm. New tools and methods are making it easier to phenotype root anatomy, determine its genetic control, and understand its utility for plant fitness. Root anatomical phenotypes are underutilized yet attractive breeding targets for the development of the efficient, resilient crops urgently needed in global agriculture.
Rotational thromboelastometry and conventional coagulation tests in patients undergoing major cardiac or aortic surgery: a retrospective single-center cohort study
Authors: Keyl Cornelius , Bashota Albina , Beyersdorf Friedhelm , Trenk Dietmar 
Published: July 2021

AbstractAlgorithms for treatment of diffuse bleeding in cardiac surgery are based on intervention thresholds of coagulation tests, such as rotational thromboelastometry (ROTEM) or conventional laboratory tests. The relationship between these two approaches is unclear in patients with increased risk of coagulation abnormalities. We retrospectively analyzed the data of 248 patients undergoing major cardiac and/or aortic surgery. ROTEM and conventional laboratory tests were performed simultaneously after termination of cardiopulmonary bypass and protamine administration to investigate the extrinsic and intrinsic system, and to determine deficiencies in platelets and fibrinogen. We evaluated the association between ROTEM and conventional tests by linear regression analysis and compared the frequency of exceeding established thresholds for clinical intervention. Significant linear associations between ROTEM 10 min after the start of coagulation, and plasma fibrinogen concentration or platelet count (FIBTEM A10, R2 = 0.67, p < 0.001; EXTEM A10, R2 = 0.47, p < 0.001) were obtained. However, the 95% prediction intervals exceeded clinically useful ranges (92–233 mg/dL fibrinogen at the intervention threshold of FIBTEM A10 = 10 mm; 14 × 103–122 × 103/µL platelets at the intervention threshold of EXTEM A10 = 40 mm). The association between EXTEM and INR (R2 = 0.23), and INTEM and aPTT (R2 = 0.095) was poor. The frequency of exceeding intervention thresholds and, consequently, of triggering treatment, varied markedly between ROTEM and conventional tests (p < 0.001 for all comparisons). The predictability of conventional coagulation test results by ROTEM is limited, thus hampering the interchangeability of methods in clinical practice.
Antimicrobial and antioxidant activity of Evernia prunastri extracts and their isolates
Authors: Shcherbakova A. , Strömstedt A. A. , Göransson U. , Gnezdilov O. , Turanov A. , Boldbaatar D. , Kochkin D. , Ulrich-Merzenich G. , Koptina A. 
Published: July 2021

AbstractLichens are symbiotic organisms formed by a fungus and one or more photosynthetic partners which are usually alga or cyanobacterium. Their diverse and scarcely studied metabolites facilitate adaptability to extreme living conditions. We investigatedEvernia prunastri(L.) Ach., a widely distributed lichen, for its antimicrobial and antioxidant potential.E. prunastriwas sequentially extracted by hexane (Hex), dichloromethane (DCM) and acetonitrile (ACN) that were screened for their antioxidant and antimicrobial (againstStaphylococcus aureus,Pseudomonas aeruginosa,Escherichia coli and Candida albicans) activities. The Hex extract possessed the highest antioxidant capacity (87 mg ascorbic acid/g extract) corresponding to the highest content of phenols (73 mg gallic acid/g extract). The DCM and Hex extracts were both active againstS. aureus(MICs of 4 and 21 µg/ml, respectively) but were less active against Gram-negative bacteria and yeast. The ACN extract exhibited activity on bothS. aureus(MIC 14 µg/ml) andC. albicans(MIC 38 µg/ml) and was therefore further fractionated by silica gel column chromatography. The active compound of the most potent fraction was subsequently characterized by1H and13C-NMR spectroscopy and identified as evernic acid. Structural similarity analyses were performed between compounds fromE. prunastriand known antibiotics from different classes. The structural similarity was not present. Antioxidant and antimicrobial activities ofE. prunastriextracts originate from multiple chemical compounds; besides usnic acid, most notably evernic acid and derivatives thereof. Evernic acid and its derivatives represent possible candidates for a new class of antibiotics.Graphic abstract
Efficient water treatment achieved in recirculating aquaculture system using woodchip denitrification and slow sand filtration
Authors: Lindholm-Lehto Petra Camilla , Pulkkinen Jani Tapio , Kiuru Tapio , Koskela Juha , Vielma Jouni 
Published: July 2021

AbstractFor a recirculating aquaculture system (RAS), a passive water treatment system was designed for efficient discharge nutrient removal and water reuse in RAS production. Denitrification in a woodchip bioreactor filled with birch wood (Betula pendula) followed by sand filtration was introduced into a side-loop of an experimental RAS rearing rainbow trout (Oncorhynchus mykiss). Denitrification efficiency remained high (96%) throughout the experiment and reached a nitrogen removal rate of 15 g NO3-N m−3 per day. Sand filtration was used to remove dissolved and particulate matter and improve water quality before being returned to water circulation. To ensure the absence of harmful substances in the system, heavy metals were quantified. Additionally, off-flavor-inducing compounds were quantified in the circulating water and in fish flesh. Significantly higher concentrations of geosmin (GSM) (p<0.05) were observed in the controls compared to side-looped systems, but a similar effect was not observed in the case of 2-methylisoborneol (MIB). Among heavy metals, concentrations of Co (30 μg L−1), Ni (40 μg L−1), and Pb (140 μg L−1) decreased to below 10 μg L−1 in the side-loop water after the start-up of the system. Only low concentrations of Cu (5–30 μg L−1) were found in the rearing tank water, in both the side-loop and controls. The results indicated that this type of process design is suitable for safely producing fish of high quality.
A Numerical Study on the Influence of an Axial Magnetic Field (AMF) on Vacuum Arc Remelting (VAR) Process
Authors: Karimi-Sibaki E. , Kharicha A. , Abdi M. , Vakhrushev A. , Wu M. , Ludwig A. , Bohacek J. 
Published: July 2021

Abstract
A comprehensive numerical model is proposed to study the influence of an axial magnetic field (AMF) on the solidification behavior of a Titanium-based (Ti–6Al–4V) vacuum arc remelting (VAR) ingot. Both static and time-varying AMF are examined. The proposed 2D axisymmetric swirl model includes calculating electromagnetic and thermal fields in the entire system composed of the electrode, vacuum plasma, ingot, and mold. A combination of vector potential formulation and induction equation is proposed to model the electromagnetic field accurately. Calculations of the flow in the melt pool and solidification of the ingot are also carried out. All governing equations are presented in cylindrical coordinate. The presence of a weak AMF, such as the earth magnetic field, can dramatically influence the flow pattern in the melt pool. The “Electro-vortex flow” is predicted ignoring AMF or in the presence of a time-varying AMF. However, the flow pattern is “Ekman pumping” in the presence of a static AMF. The amount of side-arcing has no influence on the pool depth in the presence of an AMF. Modeling results are validated against experiments.
Formal self duality
Authors: Kölsch Lukas , Schüler Robert 
Published: July 2021

AbstractWe study the notion of formal self duality in finite abelian groups. Formal duality in finite abelian groups has been proposed by Cohn, Kumar, Reiher and Schürmann. In this paper we give a precise definition of formally self dual sets and discuss results from the literature in this perspective. Also, we discuss the connection to formally dual codes. We prove that formally self dual sets can be reduced to primitive formally self dual sets similar to a previously known result on general formally dual sets. Furthermore, we describe several properties of formally self dual sets. Also, some new examples of formally self dual sets are presented within this paper. Lastly, we study formally self dual sets of the form $\{(x,F(x)) \ : \ x\in {\mathbb {F}}_{2^{n}}\}$
{
(
x
,
F
(
x
)
)

:

x
∈

F

2

n

}
where F is a vectorial Boolean function mapping ${\mathbb {F}}_{2^{n}}$

F

2

n

to ${\mathbb {F}}_{2^{n}}$

F

2

n

.
Decision making in hematology—chronic myeloid leukemia
Authors: Petzer Andreas L. 
Published: July 2021

SummaryChronic myeloid leukemia is nowadays associated with a good prognosis and an excellent life expectancy. However, certain levels of responses have to be achieved with the various available tyrosine kinase inhibitors at certain time points during the treatment otherwise adequate diagnostic and therapeutic actions have to be initiated. This paper will focus on these issues.
Left ventricular false tendons
Authors: Velthuis S. , Senden P. J. 
Published: July 2021

AbstractLeft ventricular false tendons (LVFTs) are fibromuscular structures, connecting the left ventricular free wall or papillary muscle and the ventricular septum.There is some discussion about safety issues during intense exercise in athletes with LVFTs, as these bands have been associated with ventricular arrhythmias and abnormal cardiac remodelling. However, presence of LVFTs appears to be much more common than previously noted as imaging techniques have improved and the association between LVFTs and abnormal remodelling could very well be explained by better visibility in a dilated left ventricular lumen.Although LVFTs may result in electrocardiographic abnormalities and could form a substrate for ventricular arrhythmias, it should be considered as a normal anatomic variant. Persons with LVFTs do not appear to have increased risk for ventricular arrhythmias or sudden cardiac death.
Rapid Consolidation of WC-ZrSiO4 Hard Materials by Spark Plasma Sintering: Microstructure, Densification, and Mechanical Properties
Authors: Lee Jeong-Han , Oh Ik-Hyun , Kim Ju-Hun , Hong Sung-Kil , Park Hyun-Kuk 
Published: July 2021

Abstract
Densely consolidated WC-based hard materials with 5–20 vol% ZrSiO4 was fabricated by spark plasma sintering at 1400 ℃ at a constant heating rate of 70 ℃/min−1. To achieve mechanical alloying of WC-ZrSiO4, planetary ball milling was carried out for 12 h, during which the brittle-brittle components (WC-ZrSiO4) became fragmented and their particles became refined. It was observed that certain, specific, non-isothermal sintering kinetics, such as apparent activation energy, sintering exponents, and densification strain, affected the densification behavior. The evolution of phase structure from powder to compact was found to be related the lattice distortion and micro-strain in the basal planes of WC. By examining the mechanical properties of the samples, it was that the added zircon content leads to enhanced fracture toughness (12.9 MPa m1/2) owing to the presence of WC-ZrSiO4 in the cemented carbide. In fact, the microcrack propagation of the fracture passed through zircon from a transgranular to a ductile component (fcc) where the crack tips could be absorbed.

Graphic Abstract