bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rethinking Integration of Epistemic Strategies in Social Understanding: Examining the Central Role of Mindreading in Pluralist Accounts
Authors: Wolf Julia , Coninx Sabrina , Newen Albert 
Published: November 2021

AbstractIn recent years, theories of social understanding have moved away from arguing that just one epistemic strategy, such as theory-based inference or simulation constitutes our ability of social understanding. Empirical observations speak against any monistic view and have given rise to pluralistic accounts arguing that humans rely on a large variety of epistemic strategies in social understanding. We agree with this promising pluralist approach, but highlight two open questions: what is the residual role of mindreading, i.e. the indirect attribution of mental states to others within this framework, and how do different strategies of social understanding relate to each other? In a first step, we aim to clarify the arguments that might be considered in evaluating the role that epistemic strategies play in a pluralistic framework. On this basis, we argue that mindreading constitutes a core epiststrategy in human social life that opens new central spheres of social understanding. In a second step, we provide an account of the relation between different epistemic strategies which integrates and demarks the important role of mindreading for social understanding.
Quadrotor Path Following and Reactive Obstacle Avoidance with Deep Reinforcement Learning
Authors: Rubí Bartomeu , Morcego Bernardo , Pérez Ramon 
Published: November 2021

AbstractA deep reinforcement learning approach for solving the quadrotor path following and obstacle avoidance problem is proposed in this paper. The problem is solved with two agents: one for the path following task and another one for the obstacle avoidance task. A novel structure is proposed, where the action computed by the obstacle avoidance agent becomes the state of the path following agent. Compared to traditional deep reinforcement learning approaches, the proposed method allows to interpret the training process outcomes, is faster and can be safely trained on the real quadrotor. Both agents implement the Deep Deterministic Policy Gradient algorithm. The path following agent was developed in a previous work. The obstacle avoidance agent uses the information provided by a low-cost LIDAR to detect obstacles around the vehicle. Since LIDAR has a narrow field-of-view, an approach for providing the agent with a memory of the previously seen obstacles is developed. A detailed description of the process of defining the state vector, the reward function and the action of this agent is given. The agents are programmed in python/tensorflow and are trained and tested in the RotorS/gazebo platform. Simulations results prove the validity of the proposed approach.
The CombiConsultation: a new concept of sequential consultation with the pharmacist and practice nurse/general practitioner for patients with a chronic condition.
Authors: Meijvis Valérie A. M. , Heringa Mette , Kwint Henk-Frans , de Wit Niek J. , Bouvy Marcel L. 
Published: November 2021

AbstractThe primary health care system is generally well organized for dealing with chronic diseases, but comprehensive medication management is still a challenge. Studies suggest that pharmacists can contribute to effective and safe drug therapy by providing services like a clinical medication review (CMR). However, several factors limit the potential impact of a CMR. Therefore, we propose a new pharmaceutical care service for patients with a chronic condition: the CombiConsultation. The CombiConsultation is a medication evaluation service conducted by the (community) pharmacist and either the practice nurse or general practitioner. It consists of 3 steps: medication check, implementation and follow-up. The pharmacist primarily focusses on setting treatment goals for 1 or 2 drug-related problems in relation to a specific chronic condition. In this manuscript we describe the process and characteristics of the CombiConsultation. We compare the CombiConsultation with the CMR and explain the choices made and the implications for implementation.
A novel definition and treatment of hyperinflammation in COVID-19 based on purinergic signalling
Authors: Hasan Djo , Shono Atsuko , van Kalken Coenraad K. , van der Spek Peter J. , Krenning Eric P. , Kotani Toru 
Published: November 2021

AbstractHyperinflammation plays an important role in severe and critical COVID-19. Using inconsistent criteria, many researchers define hyperinflammation as a form of very severe inflammation with cytokine storm. Therefore, COVID-19 patients are treated with anti-inflammatory drugs. These drugs appear to be less efficacious than expected and are sometimes accompanied by serious adverse effects. SARS-CoV-2 promotes cellular ATP release. Increased levels of extracellular ATP activate the purinergic receptors of the immune cells initiating the physiologic pro-inflammatory immune response. Persisting viral infection drives the ATP release even further leading to the activation of the P2X7 purinergic receptors (P2X7Rs) and a severe yet physiologic inflammation. Disease progression promotes prolonged vigorous activation of the P2X7R causing cell death and uncontrolled ATP release leading to cytokine storm and desensitisation of all other purinergic receptors of the immune cells. This results in immune paralysis with co-infections or secondary infections. We refer to this pathologic condition as hyperinflammation. The readily available and affordable P2X7R antagonist lidocaine can abrogate hyperinflammation and restore the normal immune function. The issue is that the half-maximal effective concentration for P2X7R inhibition of lidocaine is much higher than the maximal tolerable plasma concentration where adverse effects start to develop. To overcome this, we selectively inhibit the P2X7Rs of the immune cells of the lymphatic system inducing clonal expansion of Tregs in local lymph nodes. Subsequently, these Tregs migrate throughout the body exerting anti-inflammatory activities suppressing systemic and (distant) local hyperinflammation. We illustrate this with six critically ill COVID-19 patients treated with lidocaine.
Take a deep breath… The evolution of the respiratory system of symphytognathoid spiders (Araneae, Araneoidea)
Authors: Lopardo Lara , Michalik Peter , Hormiga Gustavo 
Published: November 2021

AbstractSpiders are unique in having a dual respiratory system with book lungs and tracheae, and most araneomorph spiders breathe simultaneously via book lungs and tracheae, or tracheae alone. The respiratory organs of spiders are diverse but relatively conserved within families. The small araneoid spiders of the symphytognathoid clade exhibit a remarkably high diversity of respiratory organs and arrangements, unparalleled by any other group of ecribellate orb weavers. In the present study, we explore and review the diversity of symphytognathoid respiratory organs. Using a phylogenetic comparative approach, we reconstruct the evolution of the respiratory system of symphytognathoids based on the most comprehensive phylogenetic frameworks to date. There are no less than 22 different respiratory system configurations in symphytognathoids. The phylogenetic reconstructions suggest that the anterior tracheal system evolved from fully developed book lungs and, conversely, reduced book lungs have originated independently at least twice from its homologous tracheal conformation. Our hypothesis suggests that structurally similar book lungs might have originated through different processes of tracheal transformation in different families. In symphytognathoids, the posterior tracheal system has either evolved into a highly branched and complex system or it is completely lost. No evident morphological or behavioral features satisfactorily explains the exceptional variation of the symphytognathoid respiratory organs.
Polynomial Response Surface based on basis function selection by multitask optimization and ensemble modeling
Authors: Zhao Yong , Ye Siyu , Chen Xianqi , Xia Yufeng , Zheng Xiaohu 
Published: November 2021

AbstractPolynomial Regression Surface (PRS) is a commonly used surrogate model for its simplicity, good interpretability, and computational efficiency. The performance of PRS is largely dependent on its basis functions. With limited samples, how to correctly select basis functions remains a challenging problem. To improve prediction accuracy, a PRS modeling approach based on multitask optimization and ensemble modeling (PRS-MOEM) is proposed for rational basis function selection with robustness. First, the training set is partitioned into multiple subsets by the cross validation method, and for each subset a sub-model is independently constructed by optimization. To effectively solve these multiple optimization tasks, an improved evolutionary algorithm with transfer migration is developed, which can enhance the optimization efficiency and robustness by useful information exchange between these similar optimization tasks. Second, a novel ensemble method is proposed to integrate the multiple sub-models into the final model. The significance of each basis function is scored according to the error estimation of the sub-models and the occurrence frequency of the basis functions in all the sub-models. Then the basis functions are ranked and selected based on the bias-corrected Akaike’s information criterion. PRS-MOEM can effectively mitigate the negative influence from the sub-models with large prediction error, and alleviate the uncertain impact resulting from the randomness of training subsets. Thus the basis function selection accuracy and robustness can be enhanced. Seven numerical examples and an engineering problem are utilized to test and verify the effectiveness of PRS-MOEM.
Electric vehicle charging station planning with dynamic prediction of elastic charging demand: a hybrid particle swarm optimization algorithm
Authors: Bai Xingzhen , Wang Zidong , Zou Lei , Liu Hongjian , Sun Qiao , Alsaadi Fuad E. 
Published: November 2021

AbstractThis paper is concerned with the electric vehicle (EV) charging station planning problem based on the dynamic charging demand. Considering the dynamic charging behavior of EV users, a dynamic prediction method of EV charging demand is proposed by analyzing EV users’ travel law via the trip chain approach. In addition, a multi-objective charging station planing problem is formulated to achieve three objectives: (1) maximize the captured charging demands; (2) minimize the total cost of electricity and the time consumed for charging; and (3) minimize the load variance of the power grid. To solve such a problem, a novel method is proposed by combining the hybrid particle swarm optimization (HPSO) algorithm with the entropy-based technique for order preference by similarity to ideal solution (ETOPSIS) method. Specifically, the HPSO algorithm is used to obtain the Pareto solutions, and the ETOPSIS method is employed to determine the optimal scheme. Based on the proposed method, the siting and sizing of the EV charging station can be planned in an optimal way. Finally, the effectiveness of the proposed method is verified via the case study based on a test system composed of an IEEE 33-node distribution system and a 33-node traffic network system.
Clinical and translational research workforce education survey identifies needs of faculty and staff
Authors: Loucks Tammy L. , Harvey Jillian , Lee-Chavarria Diana , Paranal Rechelle , Lenert Kathleen A. , Bonilha Heather S. , Feghali-Bostwick Carol 
Published: November 2021

Abstract
Developing the translational research workforce is a goal established by the National Center for Advancing Translational Science for its network of Clinical and Translational Science Award Program hubs. We surveyed faculty and research staff at our institution about their needs and preferences, utilization of existing trainings, and barriers and facilitators to research training. A total of 545 (21.9%) faculty and staff responded to the survey and rated grant development, research project development, and professional development among their top areas for further training. Faculty prioritized statistical methods and dissemination and implementation, while staff prioritized research compliance and research administration. Faculty (73.9%; n = 119) and staff (87.3%; n = 165) reported that additional training would give them more confidence in completing their job responsibilities. Time and lack of awareness were the most common barriers to training. Our results indicate the value of training across a range of topics with unique needs for faculty and staff. This pre-COVID survey identified time, awareness, and access to training opportunities as key barriers for faculty and staff. The shift to remote work spurred by the pandemic has further heightened the need for effective and readily accessible online trainings to enable continuous development of the clinical and translational research workforce.
Gluten contamination in labelled gluten-free, naturally gluten-free and meals in food services in low-, middle- and high-income countries: a systematic review and meta-analysis
Authors: Guennouni Morad , Admou Brahim , El khoudri Noureddine , Bourrhouat Aicha , Zogaam Loubna Gharbi , Elmoumou Lahcen , Hilali Abderraouaf 
Published: November 2021

AbstractThe gluten-free diet is based on the consumption of foods without gluten, which aims to manage celiac disease. The concern of celiac patients is that these foods should be safe. However, gluten contamination can affect these foods. The objectives of this review and meta-analysis were first, to identify articles that detected gluten contamination in gluten-free foods using validated methods. Second, to quantify the overall prevalence of gluten contamination of naturally gluten-free foods, labelled gluten-free products, and meals prepared in food services. Third, to highlight the influence of the country’s income and the period of study on this prevalence. The studies were identified in Scopus, Science Direct, Web of Science, PubMed, and Google Scholar. Forty articles were included according to PRISMA guidelines. The statistical meta-analysis was performed using MedCalc 19 software. The results show that in the gluten-free foods analysed, the overall prevalence of gluten contamination was estimated at 15.12% (95% CI: 9.56%–21.70%), with more than 20 mg/kg of gluten. Naturally gluten-free foods were significantly more contaminated than labelled gluten-free products and than meals in food services (28.32%; 9.52%; 4.66% respectively; p < 0.001). Moreover, it was noticed that oats were the most contaminated food. In addition, the prevalence of gluten contamination has significantly decreased over time. The majority of the studies were carried out in upper-middle-income and high-income countries, while only one study was conducted in lower-middle income countries. Therefore, it is necessary to implement preventive actions to reduce gluten contamination, ensuring safe gluten-free foods for celiac patients, including low-income countries.
Linear PDE with constant coefficients
Authors: Ait El Manssour Rida , Härkönen Marc , Sturmfels Bernd 
Published: November 2021

AbstractWe discuss practical methods for computing the space of solutions to an arbitrary homogeneous linear system of partial differential equations with constant coefficients. These rest on the Fundamental Principle of Ehrenpreis–Palamodov from the 1960s. We develop this further using recent advances in computational commutative algebra.
Infection of Diplostomum spp. in invasive round gobies in the St Lawrence River, Canada
Authors: Marcogliese D.J. , Locke S.A. 
Published: November 2021

Abstract
The round goby (Neogobius melanostomus) is a successful invader of the Great Lakes–St Lawrence River basin that harbours a number of local parasites. The most common are metacercariae of the genus Diplostomum. Species of Diplostomum are morphologically difficult to distinguish but can be separated using molecular techniques. While a few species have been sequenced from invasive round gobies in this study system, their relative abundance has not been documented. The purpose of this study was to determine the species composition of Diplostomum spp. and their relative abundance in round gobies in the St Lawrence River by sequencing the barcode region of cytochrome c oxidase I. In 2007–2011, Diplostomum huronense (=Diplostomum sp. 1) was the most common, followed in order by Diplostomum indistinctum (=Diplostomum sp. 4) and Diplostomum indistinctum sensu Galazzo, Dayanandan, Marcogliese & McLaughlin (2002). In 2012, the most common species infecting the round goby in the St Lawrence River was D. huronense, followed by D. indistinctum and Diplostomum gavium (=Diplostomum sp. 3). The invasion of the round goby in the St Lawrence River was followed by a decline of Diplostomum spp. in native fishes to low levels, leading to the previously published hypothesis that the presence of the round goby has led to a dilution effect. Herein, it is suggested that despite the low infection levels in the round goby, infections still may lead to spillback, helping to maintain Diplostomum spp. in native fishes, albeit at low levels.
Classification of pseudocalcium visual responses from mouse retinal ganglion cells
Authors: Shabani H. , Sadeghi Mahdi , Zrenner E. , Rathbun D.L. , Hosseinzadeh Z. 
Published: November 2021

Abstract
Recently, a detailed catalog of 32 retinal ganglion cell (RGC) visual response patterns in mouse has emerged. However, the 10,000 samples required for this catalog—based on fluorescent signals from a calcium indicator dye—are much harder to acquire from the extracellular spike train recordings underlying our bionic vision research. Therefore, we sought to convert spike trains into pseudocalcium signals so that our data could be directly matched to the 32 predefined, calcium signal-based groups. A microelectrode array (MEA) was used to record spike trains from mouse RGCs of 29 retinas. Visual stimuli were adapted from the Baden et al. study; including moving bars, full-field contrast and temporal frequency chirps, and black–white and UV-green color flashes. Spike train histograms were converted into pseudocalcium traces with an OGB-1 convolution kernel. Response features were extracted using sparse principal components analysis to match each RGC to one of the 32 RGC groups. These responses mapped onto of the 32 previously described groups; however, some of the groups remained unmatched. Thus, adaptation of the Baden et al. methodology for MEA recordings of spike trains instead of calcium recordings was partially successful. Different classification methods, however, will be needed to define clear RGC groups from MEA data for our bionic vision research. Nevertheless, others may pursue a pseudocalcium approach to reconcile spike trains with calcium signals. This work will help to guide them on the limitations and potential pitfalls of such an approach.
Evaluating Simulated Raindrop Size Distributions and Ice Microphysical Processes With Polarimetric Radar Observations in a Meiyu Front Event Over Eastern China
Authors: Chen Gang , Zhao Kun , Huang Hao , Yang Zhengwei , Lu Yinghui , Yang Ji 
Published: November 2021

AbstractTo better understand the characteristics of simulated raindrop size distributions (DSDs) and ice microphysical processes for convective systems in the East Asia monsoon region, a typical Meiyu event is simulated with the Weather Research and Forecasting (WRF) model using three two‐moment bulk microphysics schemes in this study. The simulated microphysical characteristics are then evaluated using polarimetric radar observations and retrievals. Although the observed linear storm structures are well simulated in terms of their location, there are significant deviations regarding simulated polarimetric radar variables and DSD parameters when compared to the observations. Compared to radar retrievals, all the simulated low‐level raindrops are found to have lower number concentration and larger mean sizes. To investigate the sources of the simulated DSD biases, vertical distributions of radar reflectivity and specific ice hydrometers (snow, graupel), as well as profiles of liquid/ice water contents from radar retrievals and simulations are further compared. In addition, variations about the occurrence frequency and transfer rate for four categories of ice processes (deposition, aggregation, riming, and melting) among the three schemes are analyzed. Results indicate that the overprediction of snow and graupel from riming processes is likely to be responsible for the production of extremely large raindrops at low levels.
Policy Representation Learning for Multiobjective Reservoir Policy Design With Different Objective Dynamics
Authors: Zaniolo Marta , Giuliani Matteo , Castelletti Andrea 
Published: November 2021

AbstractMost water reservoir operators make use of forecasts to inform their decisions and enhance water systems flexibility and resilience by anticipating hydrological extremes. Yet, despite numerous candidate hydro‐meteorological variables and forecast horizons may potentially be beneficial to operations, the best information set for a given problem is often not evident. Additionally, in multipurpose systems characterized by multiple demands with varying vulnerabilities and temporal scales, this information set might change according to the objective tradeoff. In this work, we contribute a novel method to learn the optimal policy representation (i.e., policy input set) by combining a feature selection routine with a multiobjective Direct Policy Search framework in order to retrieve the best policy input set online (i.e., while learning the policy) and dynamically with the objective trade‐off. The selected policy search routine is the Neuro‐Evolutionary Multi‐Objective Direct Policy Search (NEMODPS) which generates flexible policy shapes adaptive to online changes in the input set. This approach is demonstrated on the case study of Lake Como (Italy), where the operating objectives are highly heterogeneous in their dynamics (fast and slow) and vulnerabilities (wet and dry extremes). We show how varying objectives, and tradeoffs therein, benefit from a different policy representation, ultimately yielding remarkable results in terms of conflict mitigation between different users. More informed policies, moreover, show higher robustness when re‐evaluated across a suite of different hydrological conditions.