bluuebunny/crossref_metadata_2025_split huggingface dataset:
Additivity Coefficients for all Classes in the Algebra of Darboux-Like Maps on $$\mathbb {R}$$
Authors: Ciesielski K. C. , Natkaniec T. , Rodríguez-Vidanes D. L. , Seoane-Sepúlveda J. B. 
Published: December 2020

AbstractThe class $$\mathbb D$$
D
of generalized continuous functions on $$\mathbb {R}$$
R
known under the common name of Darboux-like functions is usually described as consisting of eight families of maps: Darboux, connectivity, almost continuous, extendable, peripherally continuous, those having perfect road, and having either the Cantor Intermediate Value Property or the Strong Cantor Intermediate Value Property. The algebra $$\mathcal {A}(\mathbb D)$$

A
(
D
)

of classes of functions generated by these families contains 17 atoms. In this work we will calculate the values of the additivity coefficient $${{\,\mathrm{A}\,}}(\mathcal {F})$$

A

(
F
)

for all atoms $$\mathcal {F}$$
F
in the algebra $$\mathcal {A}(\mathbb D)$$

A
(
D
)

. We also determine the values $${{\,\mathrm{A}\,}}(\mathcal {F})$$

A

(
F
)

for a lot of other families $$\mathcal {F}\in \mathcal {A}(\mathbb D)$$

F
∈
A
(
D
)

. Open questions and new directions of research shall also be provided.
Higher stand densities can promote soil carbon storage after conversion of temperate mixed natural forests to larch plantations
Authors: Na Meng , Sun Xiaoyang , Zhang Yandong , Sun Zhihu , Rousk Johannes 
Published: December 2020

AbstractSoil carbon (C) reservoirs held in forests play a significant role in the global C cycle. However, harvesting natural forests tend to lead to soil C loss, which can be countered by the establishment of plantations after clear cutting. Therefore, there is a need to determine how forest management can affect soil C sequestration. The management of stand density could provide an effective tool to control soil C sequestration, yet how stand density influences soil C remains an open question. To address this question, we investigated soil C storage in 8-year pure hybrid larch (Larix spp.) plantations with three densities (2000 trees ha−1, 3300 trees ha−1 and 4400 trees ha−1), established following the harvesting of secondary mixed natural forest. We found that soil C storage increased with higher tree density, which mainly correlated with increases of dissolved organic C as well as litter and root C input. In addition, soil respiration decreased with higher tree density during the most productive periods of warm and moist conditions. The reduced SOM decomposition suggested by lowered respiration was also corroborated with reduced levels of plant litter decomposition. The stimulated inputs and reduced exports of C from the forest floor resulted in a 40% higher soil C stock in high- compared to low-density forests within 8 years after plantation, providing effective advice for forest management to promote soil C sequestration in ecosystems.
Assisting humans in privacy management: an agent-based approach
Authors: Kurtan A. Can , Yolum Pınar 
Published: December 2020

AbstractImage sharing is a service offered by many online social networks. In order to preserve privacy of images, users need to think through and specify a privacy setting for each image that they upload. This is difficult for two main reasons: first, research shows that many times users do not know their own privacy preferences, but only become aware of them over time. Second, even when users know their privacy preferences, editing these privacy settings is cumbersome and requires too much effort, interfering with the quick sharing behavior expected on an online social network. Accordingly, this paper proposes a privacy recommendation model for images using tags and an agent that implements this, namely pelte. Each user agent makes use of the privacy settings that its user have set for previous images to predict automatically the privacy setting for an image that is uploaded to be shared. When in doubt, the agent analyzes the sharing behavior of other users in the user’s network to be able to recommend to its user about what should be considered as private. Contrary to existing approaches that assume all the images are available to a centralized model, pelte is compatible to distributed environments since each agent accesses only the privacy settings of the images that the agent owner has shared or those that have been shared with the user. Our simulations on a real-life dataset shows that pelte can accurately predict privacy settings even when a user has shared a few images with others, the images have only a few tags or the user’s friends have varying privacy preferences.
Decidability in robot manipulation planning
Authors: Vendittelli Marilena , Cristofaro Andrea , Laumond Jean-Paul , Mishra Bud 
Published: December 2020

AbstractConsider the problem of planning collision-free motion of n objects movable through contact with a robot that can autonomously translate in the plane and that can move a maximum of $$m \le n$$

m
≤
n

objects simultaneously. This represents the abstract formulation of a general class of manipulation planning problems that are proven to be decidable in this paper. The tools used for proving decidability of this simplified manipulation planning problem are, in fact, general enough to handle the decidability problem for the wider class of systems characterized by a stratified configuration space. These include, e.g., problems of legged and multi-contact locomotion, bi-manual manipulation. In addition, the approach described does not restrict the dynamics of the manipulation system modeled.
Seizure triggered by flicker electroretinogram in a patient with no history of epilepsy
Authors: Heinrich Sven P. , Agostini Hansjürgen 
Published: December 2020

Abstract
Purpose
It is well known that repetitive flash stimulation may trigger seizures in susceptible individuals. Nevertheless, reports of such incidents occurring during recording of a flash electroretinogram (ERG) are extremely rare. Here, we describe the case of a photic-induced seizure triggered during an ERG recording in the absence of a history of epilepsy or other paroxysmal events.

Methods
A 14-year-old male patient presented with reduced visual acuity and impaired mesopic vision. Ophthalmological exams confirmed the patient’s complaints but were inconclusive as to the underlying pathophysiology. An ERG recording was performed, during which the 30-Hz flicker stimulus triggered a seizure.

Results
The ERG was essentially normal, with the exception of a 7-Hz rhythm superimposed onto the flicker ERG response that was recorded when the seizure developed.

Conclusions
The present case highlights the possibility that the 30-Hz ERG flash stimulus triggers a seizure in patients with no previous paroxysmal events. Literature evidence suggests that the likelihood of such an incident could be reduced by stimulating monocularly.
Development of a Field Deployable Firebrand Flux and Condition Measurement System
Authors: Zen Simone , Thomas Jan C. , Mueller Eric V. , Dhurandher Bhisham , Gallagher Michael , Skowronski Nicholas , Hadden Rory M. 
Published: December 2020

AbstractA new instrument to quantify firebrand dynamics during fires with particular focus on those associated with the Wildland-Urban Interface (WUI) has been developed. During WUI fires, firebrands can ignite spot fires, which can rapidly increase the rate of spread (ROS) of the fire, provide a mechanism by which the fire can pass over firebreaks and are the leading cause of structure ignitions. Despite this key role in driving wildfire dynamics and hazards, difficulties in collecting firebrands in the field and preserving their physical condition (e.g. dimensions and temperature) have limited the development of knowledge of firebrand dynamics. In this work we present a new, field-deployable diagnostic tool, an emberometer, designed to provide measurement of firebrand fluxes and information on both the geometry and the thermal conditions of firebrands immediately before deposition by combining a visual and infrared camera. A series of laboratory experiments were conducted to calibrate and validate the developed imaging techniques. The emberometer was then deployed in the field to explore firebrand fluxes and particle conditions for a range of fire intensities in natural pine forest environments. In addition to firebrand particle characterization, field observations with the emberometer enabled detailed time history of deposition (i.e. firebrand flux) relative to concurrent in situ fire behaviour observations. We highlight that deposition was characterised by intense, short duration “showers” that can be reasonably associated to spikes in the average fire line intensity. The results presented illustrate the potential use of an emberometer in studying firebrand and spot fire dynamics.
A Novel Modeling Approach to Stochastically Evaluate the Impact of Pore Network Geometry, Chemistry and Topology on Fluid Transport
Authors: Apostolopoulou Maria , Stamatakis Michail , Striolo Alberto , Dusterhoft Ron , Hull Rob , Day Richard 
Published: December 2020

AbstractFine-grained sandstones, siltstones, and shales have become increasingly important to satisfy the ever-growing global energy demands. Of particular current interest are shale rocks, which are mudstones made up of organic and inorganic constituents of varying pore sizes. These materials exhibit high heterogeneity, low porosity, varying chemical composition and low pore connectivity. Due to the complexity and the importance of such materials, many experimental, theoretical and computational efforts have attempted to quantify the impact of rock features on fluids diffusivity and ultimately on permeability. In this study, we introduce a stochastic kinetic Monte Carlo approach developed to simulate fluid transport. The features of this approach allow us to discuss the applicability of 2D vs 3D models for the calculation of transport properties. It is found that a successful model should consider realistic 3D pore networks consisting of pore bodies that communicate via pore throats, which however requires a prohibitive amount of computational resources. To overcome current limitations, we present a rigorous protocol to stochastically generate synthetic 3D pore networks in which pore features can be isolated and varied systematically and individually. These synthetic networks do not correspond to real sample scenarios but are crucial to achieve a systematic evaluation of the pore features on the transport properties. Using this protocol, we quantify the contribution of the pore network’s connectivity, porosity, mineralogy, and pore throat width distribution on the diffusivity of supercritical methane. A sensitivity analysis is conducted to rank the significance of the various network features on methane diffusivity. Connectivity is found to be the most important descriptor, followed by pore throat width distribution and porosity. Based on such insights, recommendations are provided on possible technological approaches to enhance fluid transport through shale rocks and equally complex pore networks. The purpose of this work is to identify the significance of various pore network characteristics using a stochastic KMC algorithm to simulate the transport of fluids. Our findings could be relevant for applications that make use of porous media, ranging from catalysis to radioactive waste management, and from environmental remediation to shale gas production.
Reference Pose Generation for Long-term Visual Localization via Learned Features and View Synthesis
Authors: Zhang Zichao , Sattler Torsten , Scaramuzza Davide 
Published: December 2020

AbstractVisual Localization is one of the key enabling technologies for autonomous driving and augmented reality. High quality datasets with accurate 6 Degree-of-Freedom (DoF) reference poses are the foundation for benchmarking and improving existing methods. Traditionally, reference poses have been obtained via Structure-from-Motion (SfM). However, SfM itself relies on local features which are prone to fail when images were taken under different conditions, e.g., day/night changes. At the same time, manually annotating feature correspondences is not scalable and potentially inaccurate. In this work, we propose a semi-automated approach to generate reference poses based on feature matching between renderings of a 3D model and real images via learned features. Given an initial pose estimate, our approach iteratively refines the pose based on feature matches against a rendering of the model from the current pose estimate. We significantly improve the nighttime reference poses of the popular Aachen Day–Night dataset, showing that state-of-the-art visual localization methods perform better (up to 47%) than predicted by the original reference poses. We extend the dataset with new nighttime test images, provide uncertainty estimates for our new reference poses, and introduce a new evaluation criterion. We will make our reference poses and our framework publicly available upon publication.
On sharpness of error bounds for multivariate neural network approximation
Authors: Goebbels Steffen 
Published: December 2020

AbstractSingle hidden layer feedforward neural networks can represent multivariate functions that are sums of ridge functions. These ridge functions are defined via an activation function and customizable weights. The paper deals with best non-linear approximation by such sums of ridge functions. Error bounds are presented in terms of moduli of smoothness. The main focus, however, is to prove that the bounds are best possible. To this end, counterexamples are constructed with a non-linear, quantitative extension of the uniform boundedness principle. They show sharpness with respect to Lipschitz classes for the logistic activation function and for certain piecewise polynomial activation functions. The paper is based on univariate results in Goebbels (Res Math 75(3):1–35, 2020.https://rdcu.be/b5mKH)
Adverse drug reactions in SARS-CoV-2 hospitalised patients: a case-series with a focus on drug–drug interactions
Authors: Crescioli Giada , Brilli Valentina , Lanzi Cecilia , Burgalassi Andrea , Ieri Alessandra , Bonaiuti Roberto , Romano Elias , Innocenti Rinaldo , Mannaioni Guido , Vannacci Alfredo , Lombardi Niccolò 
Published: December 2020

AbstractDue to the need of early and emergency effective treatments for COVID-19, less attention may have been paid to their safety during the global emergency. In addition, characteristics of drug–drug interaction (DDI)-related adverse drug reactions (ADRs) in COVID-19 patients have not yet been studied in depth. The aim of the present case-series study is to describe clinical and pharmacological characteristics of SARS-CoV-2 hospitalised patients, focusing on ADRs, particularly those related to DDIs. We evaluated all reports of COVID-19 medication-related ADRs collected within the COVID-19 Units of Careggi University Hospital, Florence (Italy), between January 1st and 31st May 2020. Information regarding COVID-19 medications, patients’ demographic and clinical characteristics, concomitant drugs, ADRs description and outcome, were collected. Each case was evaluated for the causality assessment and to identify the presence of DDIs. During the study period, 23 Caucasian patients (56.5% males, mean age 76.1 years) experienced one or more ADRs. The majority of them were exposed to polypharmacy and 17.4% presented comorbidities. ADRs were referred to cardiovascular, psychiatric and gastrointestinal disorders. The most frequently reported preferred term was QT prolongation (mean QT interval 496.1 ms). ADRs improved or resolved completely in 60.8% of cases. For all patients, a case-by-case evaluation revealed the presence of one or more DDIs, especially those related to pharmacokinetic interactions. Despite the small number of patients, our evidence underline the clinical burden of DDIs in SARS-CoV-2 hospitalised patients and the risk of unexpected and uncommon psychiatric ADRs.
Simulation of utilization for LPBF manufacturing systems
Authors: Stittgen Tobias , Schleifenbaum Johannes Henrich 
Published: December 2020

AbstractDue to resolving major technological challenges Additive Manufacturing (AM) is on the brink of industrialization. In order to operate capital-intensive AM equipment in an economically viable manner, service providers must configure their production environment in a way which enables high capacity utilization and short throughput times while minimizing work in process. The interrelation of those three mentioned production-related key performance indicators, also known as the scheduling dilemma, must be addressed with due consideration of the technology’s characteristics. Within the framework of this paper the authors describe the impact of a service provider’s facility configuration regarding machine pool, operator availability and distribution of work content on the production system’s utilization. The evaluations rely on a simulation model developed in Matlab®, which allows for modification and execution of production schedules within AM facilities of different configurations. The validation of the proposed model is based on empirical data gathered on the shopfloor of GKN Additive, a global AM service provider.
Efficient joint identification and fluted segment modelling of shrink-fit tool assemblies by updating extended tool models
Authors: Brecher Christian , Chavan Prateek , Fey Marcel 
Published: December 2020

AbstractIn milling, the dynamic behavior of the tool center point is crucial for estimating surface quality of the workpiece as well as the process stability behavior. Experimental-analytical receptance coupling can be used for predicting the tool tip dynamics but requires accurate analytical modelling of the holder-tool assembly. This includes the reliable identification of the holder-tool joint properties as well as the correct modelling of the fluted segment of end mills. However, the modelling effort associated with accurately representing the dynamic behavior of the fluted segment is significant. In addition, the joint identification requires a reference tool tip frequency response function of the tool assembly clamped in the machine spindle. This is inefficient and can also lead to incorrect estimation of joint properties. This paper provides an efficient method for joint identification and fluted section modelling using an offline, free–free excitation approach. The objective of this paper is to enable a direct comparison of the dynamic behavior of the freely constrained analytical tool assembly model with that of the real freely constrained tool assembly. The comparison of displacement to force frequency response at certain points on the tool assembly allows for the identification of tool model parameters such as the joint properties and effective diameter of the fluted segment. The comparability is realized by extending the analytical holder-tool beam model to include the receptance model of the standard spindle-holder interface. In this study, as an example, a thermal shrink-fit holder-tool beam model is extended to include an HSK-A63 interface. Subsequently, frequency response functions at two points on the real freely constrained tool assembly are measured in order to identify the joint stiffness and effective diameter of the fluted segment using the corresponding proposed formulations. The updated holder-tool model is then coupled with a 4-axis milling machine and validated. Despite the reduced modelling effort, a good prediction accuracy could be achieved for different holder-tool combinations.
A mathematical model-based approach to optimize loading schemes of isometric resistance training sessions
Authors: Herold Johannes L. , Sommer Andreas 
Published: December 2020

AbstractIndividualized resistance training is necessary to optimize training results. A model-based optimization of loading schemes could provide valuable impulses for practitioners and complement the predominant manual program design by customizing the loading schemes to the trainee and the training goals. We compile a literature overview of model-based approaches used to simulate or optimize the response to single resistance training sessions or to long-term resistance training plans in terms of strength, power, muscle mass, or local muscular endurance by varying the loading scheme. To the best of our knowledge, contributions employing a predictive model to algorithmically optimize loading schemes for different training goals are nonexistent in the literature. Thus, we propose to set up optimal control problems as follows. For the underlying dynamics, we use a phenomenological model of the time course of maximum voluntary isometric contraction force. Then, we provide mathematical formulations of key performance indicators for loading schemes identified in sport science and use those as objective functionals or constraints. We then solve those optimal control problems using previously obtained parameter estimates for the elbow flexors. We discuss our choice of training goals, analyze the structure of the computed solutions, and give evidence of their real-life feasibility. The proposed optimization methodology is independent from the underlying model and can be transferred to more elaborate physiological models once suitable ones become available.
Synthesis, microstructure, and properties of high purity Mo2TiAlC2 ceramics fabricated by spark plasma sintering
Authors: Niu Yunhui , Fu Shuai , Zhang Kuibao , Dai Bo , Zhang Haibin , Grasso Salvatore , Hu Chunfeng 
Published: December 2020

AbstractThe synthesis, microstructure, and properties of high purity dense bulk Mo2TiAlC2ceramics were studied. High purity Mo2TiAlC2powder was synthesized at 1873 K starting from Mo, Ti, Al, and graphite powders with a molar ratio of 2:1:1.25:2. The synthesis mechanism of Mo2TiAlC2was explored by analyzing the compositions of samples sintered at different temperatures. It was found that the Mo2TiAlC2phase was formed from the reaction among Mo3Al2C, Mo2C, TiC, and C. Dense Mo2TiAlC2bulk sample was prepared by spark plasma sintering (SPS) at 1673 K under a pressure of 40 MPa. The relative density of the dense sample was 98.3%. The mean grain size was 3.5 μm in length and 1.5 μm in width. The typical layered structure could be clearly observed. The electrical conductivity of Mo2TiAlC2ceramic measured at the temperature range of 2–300 K decreased from 0.95 × 106to 0.77 × 106Ω–1·m–1. Thermal conductivity measured at the temperature range of 300–1273 K decreased from 8.0 to 6.4 W·(m·K)–1. The thermal expansion coefficient (TEC) of Mo2TiAlC2measured at the temperature of 350–1100 K was calculated as 9.0 × 10–6K–1. Additionally, the layered structure and fine grain size benefited for excellent mechanical properties of low intrinsic Vickers hardness of 5.2 GPa, high flexural strength of 407.9 MPa, high fracture toughness of 6.5 MPa·m1/2, and high compressive strength of 1079 MPa. Even at the indentation load of 300 N, the residual flexural strength could hold 84% of the value of undamaged one, indicating remarkable damage tolerance. Furthermore, it was confirmed that Mo2TiAlC2ceramic had a good oxidation resistance below 1200 K in the air.