bluuebunny/crossref_metadata_2025 huggingface dataset:
Observer‐based consensus control of nonlinear multiagent systems under semi‐Markovian switching topologies and cyber attacks
Authors: Xie Xinxin , Yang Zhe , Mu Xiaowu
Published: July 2020

This article investigates the leader‐following consensus of nonlinear multiagent systems under semi‐Markovian switching topologies and cyber attacks. Unlike the related works, the communication channels considered herein are subjected to successful but recoverable attacks, and when the channels work well, the network topology is time‐varying and described by a semi‐Markovian switching topology. Due to the effect of attacks, the communication network is intermittently paralyzed. For the cases that the transition rates of semi‐Markovian switching topologies are completely known and partially unknown, observer‐based control protocols and sufficient conditions are proposed, respectively, to ensure the consensus of the systems in the mean square sense. Finally, simulation examples are given to illustrate the validity of the theoretical results.
Environmental factors controlling phytoplankton dynamics in a large floodplain river with emphasis on cyanobacteria
Authors: Giblin Shawn M. , Gerrish Gretchen A.
Published: July 2020

Harmful algal blooms are occurring in large river ecosystems and at the mouth of large rivers with increasing frequency. In lentic systems, the chemical and physical conditions that promote harmful algal blooms are somewhat predictable but tracking prevalence and conditions that promote harmful algal blooms in lotic systems is much more difficult. We captured two of the most extreme discharge years within the last 20 years occurring in the Upper Mississippi River, allowing a natural experiment that evaluated how major shifts in discharge drive environmental variation and associated shifts in phytoplankton. Statistical models describing significant environmental covariates for phytoplankton assemblages and specific taxa were developed and used to identify management‐relevant numeric breakpoints at which environmental variables may promote the growth of specific phytoplankton and/or cyanobacteria. Our analyses supported that potentially toxin‐producing cyanobacteria dominate under high phosphorus concentration, low nitrogen concentration, low nitrogen‐to‐phosphorus ratio, low turbulence, low flushing, adequate light and warm temperatures. Cyanobacteria dominated in 2009 when low discharge and low flushing likely led to optimal growth environments for Dolichospermum, Aphanizomenon and Microcystis. Rarely will a single factor lead to the dominance, but multiple positive factors working in concert can lead to cyanobacteria proliferation in large rivers. Certain isolated backwaters with high phosphorus, low nitrogen, warm water temperatures and low potential for flushing could benefit from increased connection to channel inputs to reduce cyanobacterial dominance. Numerous examples of this type of habitat currently exist in the Upper Mississippi River and could benefit from reconnection to channel habitats.
Separated traffic grooming for Low Earth Orbit (LEO) optical satellite networks with wavelength dimensioning
Authors: Peng Cong , Zhao Shanghong , Li Ruixin , Li Jun , Wang Weilong , Gao Hanghang
Published: July 2020

Intersatellite laser links have the advantages of high bandwidth, low delay, and low power consumption, which makes wavelength division multiplexing (WDM) with wavelength routing a promising alternative to accommodate the tremendous increasing traffics from terrestrial users. To make better use of the finite wavelengths in optical satellite networks (OSNs), traffic grooming is necessary for the sake of its inherent superiority in partitioning wavelength channel into multiple low‐rate channels to satisfy the traffic requests. However, in most occasions, wavelength dimensioning is taken as a part of traffic grooming, which increases the complexity of application. Therefore, this paper investigates a novel separated traffic grooming method to minimize the number of wavelengths while satisfying the traffic requests, of which the process can be divided into two parts. Firstly, the basic connection requests are bundled to construct aggregation units (AUs). And then, the AUs are groomed onto wavelengths. In the process, an AUs construction method with multihop lightpath bypass grooming (MHLBG) is designed for uniform traffics, and a bandwidth reorganization algorithm (BRA) with MHLBG is customized for nonuniform traffics. Finally, we evaluate performance in simulation, and the results show that the proposed method has realized a good compromise between numbers of wavelengths to be used with the average end‐to‐end delay. Also, the separated traffic grooming method yields better performance than the integrated one.
Co‐sensitized cells from Antarctic resources using Ag nanoparticles
Authors: Cerdá María Fernanda , Botasini Santiago
Published: July 2020

In the present work, we explore in photoanodes of dye‐sensitized solar cell (DSSC) the co‐sensitization of the red protein phycoerythrin extracted from Antarctic algae with spherical silver nanoparticles between 10 and 200 nm and triangular nanoparticles of ~100 nm. We found that the order of addition of the sensitizers matters. Best results achieved for a sequential approach was phycoerythrin used as a dipping solution at the first step and nanoparticles at the second. We found that cell efficiency depends on the protein concentration, although no main differences detected with the nanoparticle shape or size. Our results show an average increase of 25% in the conversion efficiency values in the presence of nanoparticles.
Multinomial logistic regression with missing outcome data: An application to cancer subtypes
Authors: Wang Ching‐Yun , Hsu Li
Published: July 2020

Many diseases such as cancer and heart diseases are heterogeneous and it is of great interest to study the disease risk specific to the subtypes in relation to genetic and environmental risk factors. However, due to logistic and cost reasons, the subtype information for the disease is missing for some subjects. In this article, we investigate methods for multinomial logistic regression with missing outcome data, including a bootstrap hot deck multiple imputation (BHMI), simple inverse probability weighted (SIPW), augmented inverse probability weighted (AIPW), and expected estimating equation (EEE) estimators. These methods are important approaches for missing data regression. The BHMI modifies the standard hot deck multiple imputation method such that it can provide valid confidence interval estimation. Under the situation when the covariates are discrete, the SIPW, AIPW, and EEE estimators are numerically identical. When the covariates are continuous, nonparametric smoothers can be applied to estimate the selection probabilities and the estimating scores. These methods perform similarly. Extensive simulations show that all of these methods yield unbiased estimators while the complete‐case (CC) analysis can be biased if the missingness depends on the observed data. Our simulations also demonstrate that these methods can gain substantial efficiency compared with the CC analysis. The methods are applied to a colorectal cancer study in which cancer subtype data are missing among some study individuals.
Review of Zinc(II) Scaffolds: Efficient Role in Gene Delivery
Authors: Muripiti Venkanna , Gondru Ramesh , Patri Srilakshmi V.
Published: July 2020

Over the past two decades, enormous research has been focused on cationic non‐viral vectors because of their advantages like flexible properties, easy synthesis, robustness, etc. It was also proved that, because of their efficient gene delivery properties, Zinc cationic lipids have received great attention as promising non‐viral gene‐delivery systems. Herewith, the review mainly aimed at the most recent scientific advances of Zinc‐metal coordinative non‐viral gene‐delivery systems. The major progress in the fields of gene‐delivery as well as tissue engineering applications are summarized in the current review.
Determination of diazinon in water and food samples using magnetic solid‐phase extraction coupled with liquid chromatography
Authors: Mohammadnia Maryam , Heydari Rouhollah , Sohrabi Mahmoud Reza , Motiee Fereshteh
Published: July 2020

In the present study, a dispersive micro‐solid phase extraction method using magnetic graphene oxide/vancomycin nanocomposite as sorbent coupled with high‐performance liquid chromatography was developed for determining diazinon in water and food samples. The sorbent was characterized by various techniques such as Fourier‐transform infrared spectroscopy, X‐ray diffraction, scanning electron microscopy–energy dispersive spectroscopy, thermal gravimetric analysis, and Brunauer–Emmett–Teller surface area analysis. Influential parameters on the extraction efficiency of diazinon using dispersive micro‐solid phase extraction such as sorbent and its amount, elution solvent and its volume, adsorption and desorption times, and pH of sample solution were investigated and optimized. Under the optimized conditions, method detection limit and limit of quantitation values were 0.001 and 0.003 µg/mL, respectively. Relative recovery data for several real samples were obtained within the range of 85.0–102.0% with a relative standard deviation <7.5%. Intraday and interday relative standard deviation values were <5.2 and <7.5, respectively. The proposed method was successfully applied to quantitative determination of diazinon in several water and food samples.
Sparse nonparametric regression with regularized tensor product kernel
Authors: Yu Hang , Wang Yuanjia , Zeng Donglin
Published: July 2020

With growing interest to use black‐box machine learning for complex data with many feature variables, it is critical to obtain a prediction model that only depends on a small set of features to maximize generalizability. Therefore, feature selection remains to be an important and challenging problem in modern applications. Most of the existing methods for feature selection are based on either parametric or semiparametric models, so the resulting performance can severely suffer from model misspecification when high‐order nonlinear interactions among the features are present. A very limited number of approaches for nonparametric feature selection were proposed, but they are computationally intensive and may not even converge. In this paper, we propose a novel and computationally efficient approach for nonparametric feature selection in the regression field based on a tensor product kernel function over the feature space. The importance of each feature is governed by a parameter in the kernel function that can be efficiently computed iteratively from a modified alternating direction method of multipliers algorithm. We prove the oracle selection property of the proposed method. Finally, we demonstrate the superior performance of our approach compared with the existing methods via simulation studies and application to the prediction of Alzheimer's disease.
Alternative splicing in mesenchymal stem cell differentiation
Authors: Park Jung Woo , Fu Siyi , Huang Borong , Xu Ren-He
Published: July 2020

The differentiation and maturation of mesenchymal stem cells (MSCs) to mesodermal and other lineages are known to be controlled by various extrinsic and intrinsic signals. The dysregulation of the MSC differentiation balance has been linked to several pathophysiological conditions, including obesity and osteoporosis. Previous research of the molecular mechanisms governing MSC differentiation has mostly focused on transcriptional regulation. However, recent findings are revealing the underrated role of alternative splicing (AS) in MSC differentiation and functions. In this review, we discuss recent progress in elucidating the regulatory roles of AS in MSC differentiation. We catalogue and highlight the key AS events that modulate MSC differentiation to major osteocytes, chondrocytes, and adipocytes, and discuss the regulatory mechanisms by which AS is regulated.
Entrepreneurial ecosystems: Future research trends
Authors: Ratten Vanessa
Published: July 2020

Entrepreneurial ecosystems are gaining ascendancy as one of the most popular topics discussed in the international business literature. This is due to the way they incorporate cultural, economic, social, and political considerations in an evolutionary view of how entities interact in society. Due to an increased emphasis on digitalization and the knowledge economy, it helps to take an ecosystem view when discussing and analyzing entrepreneurship. The aim of this article is to discuss future research trajectories in research, practice, and policy on entrepreneurial ecosystems. Thereby contributing an anthropocosmic view to how entrepreneurship exists and its role in contributing to a more open and inclusive global economy. Specific research and managerial tracks are stated that highlight the importance of investing in an entrepreneurial ecosystem mindset where everything is connected.
The science of belief: A progress report
Authors: Porot Nicolas , Mandelbaum Eric
Published: July 2020

The empirical study of belief is emerging at a rapid clip, uniting work from all corners of cognitive science. Reliance on belief in understanding and predicting behavior is widespread. Examples can be found, inter alia, in the placebo, attribution theory, theory of mind, and comparative psychological literatures. Research on belief also provides evidence for robust generalizations, including about how we fix, store, and change our beliefs. Evidence supports the existence of a Spinozan system of belief fixation: one that is automatic and independent of belief rejection. Independent research supports the existence of a system of fragmented belief storage: one that relies on large numbers of causally isolated, context‐sensitive stores of belief in memory. Finally, empirical and observational data support at least two systems of belief change. One system adheres, mostly, to epistemological norms of updating; the other, the psychological immune system, functions to guard our most centrally held beliefs from potential inconsistency with newly formed beliefs. Refining our understanding of these systems can shed light on pressing real‐world issues, such as how fake news, propaganda, and brainwashing exploit our psychology of belief, and how best to construct our modern informational world.

This article is categorized under:

Psychology > Reasoning and Decision Making

Philosophy > Knowledge and Belief

Philosophy > Foundations of Cognitive Science
Decagon at two loops
Authors: Fleury Thiago , Goncalves Vasco
Published: July 2020

Abstract

We have computed the simplest five point function in $$ \mathcal{N} $$
N
= 4 SYM at two loops using the hexagonalization approach to correlation functions. Along the way we have determined all two-particle mirror contributions at two loops and we have computed all the integrals involved in the final result. As a test of our results we computed a few four-point functions and they agree with the perturbative results computed previously. We have also obtained l loop results for some parts of the two-particle contributions with l arbitrary. We also derive differential equations for a class of integrals that should appear at higher loops in the five point function.
Mimetic black strings
Authors: Sheykhi Ahmad
Published: July 2020

We present two new classes of black string solutions in the context of mimetic gravity. The horizon topology of these solutions can be either a flat T2 torus with topology S1× S1, or a standard cylindrical model with topology R × S1. The first class describes uncharged rotating black string which its asymptotic behavior is a quotient of anti-de Sitter (AdS) space, while the second class represents asymptotically AdS charged rotating black string. We study the casual structure and physical properties of these spacetimes and calculate, the entropy, electric charge, mass and angular momentum per unit length of rotating black strings.
Notes on islands in asymptotically flat 2d dilaton black holes
Authors: Anegawa Takanori , Iizuka Norihiro
Published: July 2020

Abstract

We study the islands and the Page curve in the 1+1-dimensional eternal dilaton black hole models. Without islands, the entanglement entropy of the radiation grows linearly at late time. However with an island, its growth stops at the value of almost twice of the black hole entropy. Therefore an island emerges at the late time, and the entanglement entropy of the radiation shows the Page curve.
Parseval Proximal Neural Networks
Authors: Hasannasab Marzieh , Hertrich Johannes , Neumayer Sebastian , Plonka Gerlind , Setzer Simon , Steidl Gabriele
Published: July 2020

The aim of this paper is twofold. First, we show that a certain concatenation of a proximity operator with an affine operator is again a proximity operator on a suitable Hilbert space. Second, we use our findings to establish so-called proximal neural networks (PNNs) and stable tight frame proximal neural networks. Let$$\mathcal {H}$$Hand$$\mathcal {K}$$Kbe real Hilbert spaces,$$b \in \mathcal {K}$$b∈Kand$$T \in \mathcal {B} (\mathcal {H},\mathcal {K})$$T∈B(H,K)a linear operator with closed range and Moore–Penrose inverse$$T^\dagger $$T†. Based on the well-known characterization of proximity operators by Moreau, we prove that for any proximity operator$$\mathrm {Prox}:\mathcal {K}\rightarrow \mathcal {K}$$Prox:K→Kthe operator$$T^\dagger \, \mathrm {Prox}( T \cdot + b)$$T†Prox(T·+b)is a proximity operator on$$\mathcal {H}$$Hequipped with a suitable norm. In particular, it follows for the frequently applied soft shrinkage operator$$\mathrm {Prox}= S_{\lambda }:\ell _2 \rightarrow \ell _2$$Prox=Sλ:ℓ2→ℓ2and any frame analysis operator$$T:\mathcal {H}\rightarrow \ell _2$$T:H→ℓ2that the frame shrinkage operator$$T^\dagger \, S_\lambda \, T$$T†SλTis a proximity operator on a suitable Hilbert space. The concatenation of proximity operators on$$\mathbb R^d$$Rdequipped with different norms establishes a PNN. If the network arises from tight frame analysis or synthesis operators, then it forms an averaged operator. In particular, it has Lipschitz constant 1 and belongs to the class of so-called Lipschitz networks, which were recently applied to defend against adversarial attacks. Moreover, due to its averaging property, PNNs can be used within so-called Plug-and-Play algorithms with convergence guarantee. In case of Parseval frames, we call the networks Parseval proximal neural networks (PPNNs). Then, the involved linear operators are in a Stiefel manifold and corresponding minimization methods can be applied for training of such networks. Finally, some proof-of-the concept examples demonstrate the performance of PPNNs.
The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods
Authors: Krebs Alice , van Vugt-Lussenburg Barbara M. A. , Waldmann Tanja , Albrecht Wiebke , Boei Jan , ter Braak Bas , Brajnik Maja , Braunbeck Thomas , Brecklinghaus Tim , Busquet Francois , Dinnyes Andras , Dokler Joh , Dolde Xenia , Exner Thomas E. , Fisher Ciarán , Fluri David , Forsby Anna , Hengstler Jan G. , Holzer Anna-Katharina , Janstova Zofia , Jennings Paul , Kisitu Jaffar , Kobolak Julianna , Kumar Manoj , Limonciel Alice , Lundqvist Jessica , Mihalik Balázs , Moritz Wolfgang , Pallocca Giorgia , Ulloa Andrea Paola Cediel , Pastor Manuel , Rovida Costanza , Sarkans Ugis , Schimming Johannes P. , Schmidt Bela Z. , Stöber Regina , Strassfeld Tobias , van de Water Bob , Wilmes Anja , van der Burg Bart , Verfaillie Catherine M. , von Hellfeld Rebecca , Vrieling Harry , Vrijenhoek Nanette G. , Leist Marcel
Published: July 2020

Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes. The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (e.g. rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol). Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans. Moreover, data generation was exemplified by providing results from 25 reporter assays. A complete evaluation of the entire test battery will be described elsewhere. A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity.
MRI features of and factors related to ankle injuries in asymptomatic amateur marathon runners
Authors: Yao Wanzhen , Zhang Yanjing , Zhang Li , Zhou Jing , Zhang Yi , Zheng Xiaozhong , Ding Jianping
Published: July 2020

Objective

To analyze the MRI manifestations of and factors related to ankle injuries in asymptomatic amateur marathon runners.

Materials and methods

A total of 113 amateur marathon runners without any ankle joint symptoms were recruited. Each participant was asked to complete a questionnaire at the beginning of the study and underwent MRI of the ankle. The MRI manifestations of ankle injuries were summarized, and binary logistic regression analysis was applied to analyze the factors related to ankle injuries.

Results

The main MRI features were bone marrow edema-like signal intensity, peritendinous effusion, and partial lateral collateral ligament injury. Others included Achilles tendinopathy, cyst-like lesions, osteochondral lesions, and subcutaneous soft tissue edema. The risk factor for bone marrow edema-like signal intensity in amateur marathon runners was a rearfoot strike pattern (p = 0.028, OR = 1.172); the risk factors for peritendinous effusion were a higher weekly running distance (p = 0.013, OR = 1.685) and increased running years (p = 0.039, OR = 1.113), whereas a rearfoot strike pattern (p = 0.005, OR = 0.831) was a protective factor for peritendinous effusion; the risk factor for Achilles tendinopathy was increased age (p = 0.008, OR = 1.412); the risk factors for anterior talofibular ligament injury were a rearfoot strike pattern (p = 0.017, OR = 1.346) and higher weekly running distance (p = 0.022, OR = 1.171); and the factors for calcaneofibular ligament injury were a higher weekly running distance (p = 0.029, OR = 1.570) and rearfoot strike pattern (p = 0.035, OR = 1.463).

Conclusion

The main MRI features of asymptomatic amateur marathon runners are bone marrow edema-like signal intensity, peritendinous effusion, and partial lateral collateral ligament injury. In addition, increased age, increased running years, higher weekly running distance, and different foot strike patterns are risk factors for ankle injuries.
The Impact of Surgical Boot Camp and Subsequent Repetitive Practice on the Surgical Skills and Confidence of Residents
Authors: Wang Wei , Ma Hucheng , Ren Haozhen , Wang Zhongxia , Mao Liang , He Ningning
Published: July 2020

Background

Boot camp can enable residents to acquire surgical skills and confidence, but they can lose these skills over time if they do not use them. The purpose of this study was to explore whether boot camp and subsequent repetitive practice could strengthen residents’ clinical skills and self‐confidence.

Methods

This is a comparative study of surgical residents who were enrolled in our institution from 2016 to 2017. The residents in the experimental group (enrolled in 2017) received boot camp training and a year of repetitive practice. The control group (enrolled in 2016) only received routine residency training. The rotation assessment pass rates of the two groups during the first year of the residency training were compared. A survey was conducted at different points in time to investigate the influence of boot camp and repetitive practice on the confidence of the residents.

Results

The assessment pass rate of the experimental group was significantly higher than that of the control group (p < 0.05). The residents’ confidence in themselves improved significantly after the boot camp, and it was comparable to that of the residents in the control group after their first year of residency. The level of self‐confidence of the experimental group was further improved after repetitive practice. Finally, residents in the experimental group received better evaluations by their colleagues than the control group received.

Conclusions

This study showed that boot camp can improve the surgical skills and confidence of residents and that repetitive practice can further strengthen them. Residents in the experimental group developed their self‐confidence in boot camp, and it increased after repetitive practice.
Improved Outcome Prediction Across Data Sources Through Robust Parameter Tuning
Authors: Ellenbach Nicole , Boulesteix Anne-Laure , Bischl Bernd , Unger Kristian , Hornung Roman
Published: July 2020

In many application areas, prediction rules trained based on high-dimensional data are subsequently applied to make predictions for observations from other sources, but they do not always perform well in this setting. This is because data sets from different sources can feature (slightly) differing distributions, even if they come from similar populations. In the context of high-dimensional data and beyond, most prediction methods involve one or several tuning parameters. Their values are commonly chosen by maximizing the cross-validated prediction performance on the training data. This procedure, however, implicitly presumes that the data to which the prediction rule will be ultimately applied, follow the same distribution as the training data. If this is not the case, less complex prediction rules that slightly underfit the training data may be preferable. Indeed, a tuning parameter does not only control the degree of adjustment of a prediction rule to the training data, but also, more generally, the degree of adjustment to thedistribution ofthe training data. On the basis of this idea, in this paper we compare various approaches including new procedures for choosing tuning parameter values that lead to better generalizing prediction rules than those obtained based on cross-validation. Most of these approaches use an external validation data set. In our extensive comparison study based on a large collection of 15 transcriptomic data sets, tuning on external data and robust tuning with a tuned robustness parameter are the two approaches leading to better generalizing prediction rules.
Postmortem age estimation via DNA methylation analysis in buccal swabs from corpses in different stages of decomposition—a “proof of principle” study
Authors: Koop Barbara Elisabeth , Mayer Felix , Gündüz Tanju , Blum Jacqueline , Becker Julia , Schaffrath Judith , Wagner Wolfgang , Han Yang , Boehme Petra , Ritz-Timme Stefanie
Published: July 2020

Age estimation based on the analysis of DNA methylation patterns has become a focus of forensic research within the past few years. However, there is little data available regarding postmortem DNA methylation analysis yet, and literature mainly encompasses analysis of blood from corpses without any signs of decomposition. It is not entirely clear yet which other types of specimen are suitable for postmortem epigenetic age estimation, and if advanced decomposition may affect methylation patterns of CpG sites. In living persons, buccal swabs are an easily accessible source of DNA for epigenetic age estimation. In this work, the applicability of this approach (buccal swabs as source of DNA) under different postmortem conditions was tested. Methylation levels of PDE4C were investigated in buccal swab samples collected from 73 corpses (0–90 years old; mean: 51.2) in different stages of decomposition. Moreover, buccal swab samples from 142 living individuals (0–89 years old; mean 41.2) were analysed. As expected, methylation levels exhibited a high correlation with age in living individuals (training set: r2 = 0.87, validation set: r2 = 0.85). This was also the case in postmortem samples (r2 = 0.90), independent of the state of decomposition. Only in advanced putrified cases with extremely low DNA amounts, epigenetic age estimation was not possible. In conclusion, buccal swabs are a suitable and easy to collect source for DNA methylation analysis as long as sufficient amounts of DNA are present.
Ophthalmic Thelazia callipaeda infections: first feline and new canine imported cases in Germany
Authors: L. M. R. Silva , Spoerel S. , Wiesner L. , Klein M. , Pantchev N. , Taubert A. , Hermosilla C.
Published: July 2020

The first case of feline ocular Thelazia callipaeda infection and two new canine imported infections in West Germany are here described. The three animals had a history of recent travel to/from other countries. The young adult cat imported from Spain presented an intermittent unilateral ocular discharge. During in-depth ophthalmic examination, a single alive nematode was removed from the conjunctival compartment of the affected eye. Referring to the canine cases, an adult female dog originated from Kenya presented epiphora and mucous whitish-grey discharge of the right eye. During flushing of the nasolacrimal duct two small, thin and long nematodes were removed. Furthermore, a male Borzoi racing dog with regular visit to racing tracks in different countries presented ocular mucous discharge. At ophthalmologic examination, two transparent-whitish vital nematodes were removed. All nematode specimens of the three cases were morphologically identified as adult T. callipaeda parasites. The animals were treated orally with milbemycin oxime (2.0 mg/kg; cat) or milbemycin oxime/praziquantel (0.5 mg/kg and 5.0 mg/kg; dogs) twice with 1-week interval resulting in complete resolution of symptoms. The repeated introduction of patent T. callipaeda-infected animals, especially from southern and eastern endemic countries, will ease the establishment of ophthalmic thelaziosis in Northern Europe. The male fruit fly, Phortica variegata, an intermediate host of T. callipaeda, is endemic within European countries. Considering the clinical and zoonotic relevance of ophthalmic thelaziosis, enhanced disease awareness of European medical and veterinarian doctors and in-depth eye examination for proper detection of T. callipaeda are crucial for appropriate anthelmintic treatments and to limit spreading of the infection.
On the number of excursion sets of planar Gaussian fields
Authors: Beliaev Dmitry , McAuley Michael , Muirhead Stephen
Published: July 2020

The Nazarov–Sodin constant describes the average number of nodal set components of smooth Gaussian fields on large scales. We generalise this to a functional describing the corresponding number of level set components for arbitrary levels. Using results from Morse theory, we express this functional as an integral over the level densities of different types of critical points, and as a result deduce the absolute continuity of the functional as the level varies. We further give upper and lower bounds showing that the functional is at least bimodal for certain isotropic fields, including the important special case of the random plane wave.
Finnish National Phenological Network 1997–2017: from observations to trend detection
Authors: Helama Samuli , Tolvanen Anne , Karhu Jouni , Poikolainen Jarmo , Kubin Eero
Published: July 2020

Plant phenological dataset collected at 42 sites across the mainland of Finland and covering the years 1997–2017 is presented and analysed for temporal trends. The dataset of n = 16,257 observations represents eleven plant species and fifteen phenological stages and results in forty different variables, i.e. phenophases. Trend analysis was carried out for n = 808 phenological time-series that contained at least 10 observations over the 21-year study period. A clear signal of advancing spring and early-summer phenology was detected, 3.4 days decade−1, demonstrated by a high proportion of negative trends for phenophases occurring in April through June. Latitudinal correlation indicated stronger signal of spring and early-summer phenology towards the northern part of the study region. The autumn signal was less consistent and showed larger within-site variations than those observed in other seasons. More than 60% of the dates based on single tree/monitoring square were exactly the same as the averages from multiple trees/monitoring squares within the site. In particular, the reliability of data on autumn phenology was increased by multiple observations per site. The network is no longer active.
Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware
Authors: Liu Shiwei , Mocanu Decebal Constantin , Matavalam Amarsagar Reddy Ramapuram , Pei Yulong , Pechenizkiy Mykola
Published: July 2020

Artificial neural networks (ANNs) have emerged as hot topics in the research community. Despite the success of ANNs, it is challenging to train and deploy modern ANNs on commodity hardware due to the ever-increasing model size and the unprecedented growth in the data volumes. Particularly for microarray data, the very high dimensionality and the small number of samples make it difficult for machine learning techniques to handle. Furthermore, specialized hardware such as graphics processing unit (GPU) is expensive. Sparse neural networks are the leading approaches to address these challenges. However, off-the-shelf sparsity-inducing techniques either operate from a pretrained model or enforce the sparse structure via binary masks. The training efficiency of sparse neural networks cannot be obtained practically. In this paper, we introduce a technique allowing us to train truly sparse neural networks with fixed parameter count throughout training. Our experimental results demonstrate that our method can be applied directly to handle high-dimensional data, while achieving higher accuracy than the traditional two-phase approaches. Moreover, we have been able to create truly sparse multilayer perceptron models with over one million neurons and to train them on a typical laptop without GPU (https://github.com/dcmocanu/sparse-evolutionary-artificial-neural-networks/tree/master/SET-MLP-Sparse-Python-Data-Structures), this being way beyond what is possible with any state-of-the-art technique.
Towards Massively Parallel Computations in Algebraic Geometry
Authors: Böhm Janko , Decker Wolfram , Frühbis-Krüger Anne , Pfreundt Franz-Josef , Rahn Mirko , Ristau Lukas
Published: July 2020

Introducing parallelism and exploring its use is still a fundamental challenge for the computer algebra community. In high-performance numerical simulation, on the other hand, transparent environments for distributed computing which follow the principle of separating coordination and computation have been a success story for many years. In this paper, we explore the potential of using this principle in the context of computer algebra. More precisely, we combine two well-established systems: The mathematics we are interested in is implemented in the computer algebra system Singular, whose focus is on polynomial computations, while the coordination is left to the workflow management system GPI-Space, which relies on Petri nets as its mathematical modeling language and has been successfully used for coordinating the parallel execution (autoparallelization) of academic codes as well as for commercial software in application areas such as seismic data processing. The result of our efforts is a major step towards a framework for massively parallel computations in the application areas of Singular, specifically in commutative algebra and algebraic geometry. As a first test case for this framework, we have modeled and implemented a hybrid smoothness test for algebraic varieties which combines ideas from Hironaka’s celebrated desingularization proof with the classical Jacobian criterion. Applying our implementation to two examples originating from current research in algebraic geometry, one of which cannot be handled by other means, we illustrate the behavior of the smoothness test within our framework and investigate how the computations scale up to 256 cores.
Moment Identifiability of Homoscedastic Gaussian Mixtures
Authors: Agostini Daniele , Améndola Carlos , Ranestad Kristian
Published: July 2020

We consider the problem of identifying a mixture of Gaussian distributions with the same unknown covariance matrix by their sequence of moments up to certain order. Our approach rests on studying the moment varieties obtained by taking special secants to the Gaussian moment varieties, defined by their natural polynomial parametrization in terms of the model parameters. When the order of the moments is at most three, we prove an analogue of the Alexander–Hirschowitz theorem classifying all cases of homoscedastic Gaussian mixtures that produce defective moment varieties. As a consequence, identifiability is determined when the number of mixed distributions is smaller than the dimension of the space. In the two-component setting, we provide a closed form solution for parameter recovery based on moments up to order four, while in the one-dimensional case we interpret the rank estimation problem in terms of secant varieties of rational normal curves.
Quality is in the eye of the stakeholders: what do professional subtitlers and viewers think about subtitling?
Authors: Szarkowska Agnieszka , Díaz Cintas Jorge , Gerber-Morón Olivia
Published: July 2020

Quality is a rather slippery concept, and its assessment in subtitling can be a challenging task, as its appreciation can easily vary depending on the different stakeholders involved in the production and reception of subtitles. In this paper, we evaluate quality indicators in subtitling as perceived by professional subtitlers and viewers. After exploring the various subtitle parameters that can have an impact on the quality of the end product (such as line breaks, synchronisation, display rates), we present the results of two qualitative studies conducted with professional subtitlers and subtitle viewers with different audiovisual backgrounds. The results yield some similarities and discrepancies, particularly in the way in which the strategy of condensation is perceived by the two groups, and they also help delineate the subtitle parameters that should be taken into consideration in order to improve the creative process as well as the reception of subtitles.
Die Europäische Union in der Corona-Krise
Authors:   ZG Überblick
Published: July 2020

Die Corona-Krise hat alle Mitgliedstaaten der Europäischen Union getroffen — allerdings einige früher und härter als andere. Nun soll ein immens großer Rettungsschirm aufgespannt werden, über dessen Finanzierung, Konditionen und mögliche Auflagen die EU-Mitglieder noch streiten. Auch die Ebenen, auf der die Maßnahmen organisiert werden sollen, sind noch nicht ausbalanciert. Welche Bedeutung kommt dabei der nationalen, welche der supranationalen Ebene zu? Geht es vor allem um die Europäische Währungsunion oder um die gesamte EU? Solidarisches Verhalten gebietet nicht allein die europäische Idee, sondern auch die ökonomische Notwendigkeit, da die Mitgliedstaaten über Lieferketten stark miteinander verflochten sind.
Effekte des Mindestlohns auf die Arbeitszeit
Authors: Pusch Toralf , Seifert Hartmut , Santoro Chiara
Published: July 2020

Zur Evaluation des gesetzlichen Mindestlohns liegen fünf Jahre nach seiner Einführung zahlreiche fundierte Analysen vor. Die Auswirkungen des Mindestlohns auf die Arbeitszeit haben dabei eine besondere Relevanz, da sie die Einkommensentwicklung und das Arbeitsvolumen im Niedriglohnsektor beeinflussen. Vor diesem Hintergrund bietet dieser Beitrag eine aktuelle Analyse mit dem bisher wenig verwendeten und für die Untersuchung des Mindestlohns besonders geeigneten PASS-Datensatz des Instituts für Arbeitsmarkt- und Berufsforschung. Es zeigt sich, dass Arbeitszeitverkürzungen vor allem bei geringfügig Beschäftigten und bei Beziehern von Sozialtransfers aufgetreten sind, was teilweise auf eine Reaktion des Arbeitsangebots zurückzuführen sein dürfte.
Investitionen und Konsum: wirtschaftspolitische Handlungsoptionen zur Jahresmitte 2020
Authors: Hüther Michael
Published: July 2020

Der historisch einmalige Einbruch der gesamtwirtschaftlichen Leistungen in der Corona-Krise macht wirtschaftspolitische Maßnahmen dringend erforderlich. Wenn die Maßnahmen sich auf die Nachfrageseite richten, müssen sie mit dem richtigen Timing, zielgenau und befristet gestaltet sein. Die Lenkungswirkung sollte dabei in den Hintergrund treten. Ein Maßnahmenkatalog, der von Steuersenkungen bis hin zu Direktzahlungen reicht, ist sinnvoll.
Corona-Krise: die transformative Rezession
Authors: Hutter Christian , Weber Enzo
Published: July 2020

Mit der Corona-Krise nimmt die Arbeitslosigkeit trotz aller Gegenmaßnahmen in Deutschland zu. In früheren Rezessionen hat sich gerade die Arbeitslosigkeit Geringqualifizierter verfestigt. Heute zeichnet sich ab, dass der technologische Wandel gerade auch mittlere Qualifikationen betrifft. Um Verfestigung zu vermeiden, ist es wichtig, Neueinstellungen zu fördern, Qualifizierung zu unterstützen und berufliche Umorientierung zu ermöglichen.
Elevated IL-22 in psoriasis plays an anti-apoptotic role in keratinocytes through mediating Bcl-xL/Bax
Authors: Wang Bo , Han Dan , Li Fei , Hou Weikun , Wang Lijuan , Meng Liesu , Mou Kuanhou , Lu Shemin , Zhu Wenhua , Zhou Yan
Published: July 2020

IL-22 is known to mediate inflammation in psoriasis, while IL-22 binding protein (IL-22BP) binds IL-22 to suppress IL-22 signaling. However, the function of IL-22 in regulating apoptosis in psoriasis remains poorly understood. In this study, we found that IL-22/IL-22R1 in lesional skin and IL-22 in serum from psoriatic patients were highly upregulated compared with healthy controls, while IL-22BP was not changed. Correlations between IL-22/IL-22R1 levels and the thickness of psoriatic lesions suggested that IL-22 might positively regulate abnormal hyperplasia in psoriasis. Apoptotic keratinocytes were increased only in stratum corneum, but not in spinous and basal layers of psoriasis. Moreover, IL-22 promoted cell viability in human epidermal keratinocytes (HEKs). The apoptosis induced by TNF-α and IFN-γ was inhibited in HEKs treated with IL-22, since that IL-22 upregulated Bcl-xL and downregulated Bax production in HEKs in the presence of TNF-α and IFN-γ. In addition, IL-22BP could counteract the anti-apoptotic effect of IL-22. Our finding demonstrates that IL-22 might play an anti-apoptosis role on keratinocytes to balance cell proliferation and apoptosis in psoriatic epidermis.
Clinical decision trees support systematic evaluation of multidisciplinary team recommendations
Authors: Hendriks Mathijs P. , Verbeek Xander A. A. M. , van Manen Jeannette G. , van der Heijden Sannah E. , Go Shirley H. L. , Gooiker Gea A. , van Vegchel Thijs , Siesling Sabine , Jager Agnes
Published: July 2020

Purpose

EUSOMA’s recommendation that “each patient has to be fully informed about each step in the diagnostic and therapeutic pathway” could be supported by guideline-based clinical decision trees (CDTs). The Dutch breast cancer guideline has been modeled into CDTs (www.oncoguide.nl). Prerequisites for adequate CDT usage are availability of necessary patient data at the time of decision-making and to consider all possible treatment alternatives provided in the CDT.

Methods

This retrospective single-center study evaluated 394 randomly selected female patients with non-metastatic breast cancer between 2012 and 2015. Four pivotal CDTs were selected. Two researchers analyzed patient records to determine to which degree patient data required per CDT were available at the time of multidisciplinary team (MDT) meeting and how often multiple alternatives were actually reported.

Results

The four selected CDTs were indication for magnetic resonance imaging (MRI) scan, preoperative and adjuvant systemic treatment, and immediate breast reconstruction. For 70%, 13%, 97% and 13% of patients, respectively, all necessary data were available. The two most frequent underreported data-items were “clinical M-stage” (87%) and “assessable mammography” (28%). Treatment alternatives were reported by MDTs in 32% of patients regarding primary treatment and in 28% regarding breast reconstruction.

Conclusion

Both the availability of data in patient records essential for guideline-based recommendations and the reporting of possible treatment alternatives of the investigated CDTs were low. To meet EUSOMA’s requirements, information that is supposed to be implicitly known must be explicated by MDTs. Moreover, MDTs have to adhere to clear definitions of data-items in their reporting.
The unified model of task-specific motivation and teachers’ motivation to learn about teaching and learning supportive modes of ICT use
Authors: de Brabander Cornelis J. , Glastra Folke J.
Published: July 2020

This study explored the readiness of teachers to learn about learning and teaching supportive modes of ICT use with the lens of the Unified Model of Task-specific Motivation (UMTM). According to the UMTM readiness for action is driven by feelings of activities and thoughts about the value of consequences of activities, which both can be positive and negative, and which in turn are influenced by aspects of autonomy and competence, by social relatedness, and by subjective norm. The twofold goal of this study was to test the merits of the model in general and for ICT integration in education in particular. A sample of 282 teachers provided answers about different aspects of their motivation to learn about the two types of ICT use. There were some differences between these two types of learning activities, but for both, thoughts about the value of the consequences of the activities were more important than feelings about them. Furthermore, although sense of competence was relatively more important for leaning about learning supportive ICT use than for learning about teaching supportive ICT use, teachers’ sense of autonomy, a variable that is completely ignored in research on ICT integration, was in general far more important for learning about ICT use than sense of competence.
Experimental investigation and modeling of nonlinear, adaptive dashpot
Authors: Mnich K. , Lazarek M. , Brzeski P. , Perlikowski P.
Published: July 2020

In this paper we determine the characteristics of mechanical components of dynamical systems using a specially designed laboratory rig. We present the details of the experiments performed on the prototype device and provide technical documentation of its crucial elements. We validate the accuracy of measurements using a spring and comparing results with manufacturer data. Then, we examine nonlinear dashpot with variable damping coefficient obtained through the usage of the throttling valve. We perform several tests presenting its force characteristics as a function of velocity and damping coefficient. We derive the mathematical model of the dashpot basing on the experimental data. Finally, we perform transient test in which we change the damping coefficient during operation of the dashpot. The comparison of obtained results with the model gives good accordance.