bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cognitive dysfunction in young subjects with periodontal disease
Authors: Hategan Simona I. , Kamer Sabrina A. , Craig Ronald G. , Sinescu Cosmin , de Leon Mony J. , Jianu Dragos C. , Marian Catalin , Bora Bianca I. , Dan Traian-Flavius , Birdac Claudiu D. , Marcu Anca , Kamer Angela R. , Negrutiu Meda Lavinia 
Published: February 2021

Abstract
Background
Periodontal disease is an inflammatory, dysbiotic condition. Studies have shown that in the elderly, periodontal disease was associated with cognitive dysfunction and Alzheimer’s disease.

Objective
To investigate whether young healthy subjects with periodontal disease have lower cognition compared to those without periodontal disease. The salivary cytokines (IL-1β, TNF-α) levels in relation to cognition were also tested.

Methods
In a monocenter, cross-sectional study, forty subjects [mean age (SD) = 34 (5) and 48% female] from western Romania were classified into periodontal disease conditions using radiographic assessment: 10 subjects had aggressive periodontitis (AGG_P), 20 chronic mild-moderate periodontitis (CR_P), and 10 no periodontitis (NL_P). Neuropsychological assessment performed by standardized neurologists and psychologist included Rey Auditory Verbal Learning Test (RAVLT), Montreal Cognitive Assessment test (MOCA), Mini-Mental State Examination (MMSE), and Prague tests. Salivary cytokines levels were determined by ELISA.

Results
RAVLT and MOCA delayed recall scores were lower in AGG_P group compared to NL_P and CR_P. The learning curve was also different with subjects with AGG_P showing reduced learning performance. Contrary to our hypothesis, salivary IL-1β associated with immediate but not delayed cognitive scores.

Conclusions
These results showed for the first time that subjects with AGG_P had cognitive dysfunction and IL-1β may play a role in this process.
Decarbonising road freight: Is truck automation and platooning an opportunity?
Authors: Paddeu Daniela , Denby Jozef 
Published: February 2021

AbstractGovernments, industry and academia are paying high attention to autonomous vehicles and platooning, due to their high potential to transform public and private transport and reduce carbon emissions generated by road transport. The road freight sector is expected to be an early adopter of the autonomous technology due to the potential cost reduction for logistics companies. However, despite the expected fuel savings and polluting emission reductions due to truck platooning, actual benefits would strongly depend on the adopted technology and the operational conditions of the system. This paper investigates the potential for truck platooning to reduce carbon emissions from road freight, presenting a series of scenarios that vary by adoption rates, operational models and platoon size. Scenarios were co-designed with freight stakeholders to build a Truck Platooning Roadmap (2025–2050), considering a specific case study: the UK. Polluting emissions and related external costs are calculated across the different scenarios. Results show that there is high uncertainty for the adoption of truck platooning, with a potential first phase involving a small pool of low-automated trucks, and a second phase with a larger pool of high-automated trucks, reflecting higher economic and environmental benefits. A series of other technological and policy considerations are presented to support policymakers to draw a zero-carbon road freight strategy.
Graphic abstract
Design and Construction of a Tailings Dam over an Ancient Tailings Facility at La Parrilla Mine
Authors: Galera José Miguel , de la Fuente Fernando , García Juan , Calleja Manuel , Pozo Vanesa 
Published: February 2021

AbstractLa Parrilla is a tungsten and tin mine located in western Spain. The tailings facility has a total capacity for 3 Mm3 and will be executed in four different phases. The main constraint for the design and construction of the tailings dam is that it has been constructed over an existing one from the 1980s. The construction activities involved removal and substitution of the old tailings from the southern portion of the facility, ground improvement with gravel columns over an area of about 10,000 m2, and construction of the dyke’s dam. This article describes the main design and construction aspects, including monitoring, until the dam’s completion in June 2019.
Parametric modeling of quantile regression coefficient functions with count data
Authors: Frumento Paolo , Salvati Nicola 
Published: February 2021

AbstractApplying quantile regression to count data presents logical and practical complications which are usually solved by artificially smoothing the discrete response variable through jittering. In this paper, we present an alternative approach in which the quantile regression coefficients are modeled by means of (flexible) parametric functions. The proposed method avoids jittering and presents numerous advantages over standard quantile regression in terms of computation, smoothness, efficiency, and ease of interpretation. Estimation is carried out by minimizing a “simultaneous” version of the loss function of ordinary quantile regression. Simulation results show that the described estimators are similar to those obtained with jittering, but are often preferable in terms of bias and efficiency. To exemplify our approach and provide guidelines for model building, we analyze data from the US National Medical Expenditure Survey. All the necessary software is implemented in the existing R package .
Autonomic cardiovascular alterations as therapeutic targets in chronic kidney disease
Authors: Seravalle Gino , Quarti-Trevano Fosca , Vanoli Jennifer , Lovati Chiara , Grassi Guido 
Published: February 2021

Abstract
Purpose
The present paper will review the impact of different therapeutic interventions on the autonomic dysfunction characterizing chronic renal failure.

Methods
We reviewed the results of the studies carried out in the last few years examining the effects of standard pharmacologic treatment, hemodialysis, kidney transplantation, renal nerve ablation and carotid baroreceptor stimulation on parasympathetic and sympathetic control of the cardiovascular system in patients with renal failure.

Results
Drugs acting on the renin–angiotensin system as well as central sympatholytic agents have been documented to improve autonomic cardiovascular control. This has also been shown for hemodialysis, although with more heterogeneous results related to the type of dialytic procedure adopted. Kidney transplantation, in contrast, particularly when performed together with the surgical removal of the native diseased kidneys, has been shown to cause profound sympathoinhibitory effects. Finally, a small amount of promising data are available on the potential favorable autonomic effects (particularly the sympathetic ones) of renal nerve ablation and carotid baroreceptor stimulation in chronic kidney disease.

Conclusions
Further studies are needed to clarify several aspects of the autonomic responses to therapeutic interventions in chronic renal disease. These include (1) the potential to normalize sympathetic activity in uremic patients by the various therapeutic approaches and (2) the definition of the degree of sympathetic deactivation to be achieved during treatment.
GNSS-to-GNSS time offsets: study on the broadcast of a common reference time
Authors: Sesia Ilaria , Signorile Giovanna , Thai Tung Thanh , Defraigne Pascale , Tavella Patrizia 
Published: February 2021

AbstractWe present two different approaches to broadcasting information to retrieve the GNSS-to-GNSS time offsets needed by users of multi-GNSS signals. Both approaches rely on the broadcast of a single time offset of each GNSS time versus one common time scale instead of broadcasting the time offsets between each of the constellation pairs. The first common time scale is the average of the GNSS time scales, and the second time scale is the prediction of UTC already broadcast by the different systems. We show that the average GNSS time scale allows the estimation of the GNSS-to-GNSS time offset at the user level with the very low uncertainty of a few nanoseconds when the receivers at both the provider and user levels are fully calibrated. The use of broadcast UTC prediction as a common time scale has a slightly larger uncertainty, which depends on the broadcast UTC prediction quality, which could be improved in the future. This study focuses on the evaluation of two different common time scales, not considering the impact of receiver calibration, at the user and provider levels, which can nevertheless have an important impact on GNSS-to-GNSS time offset estimation.
Soft Liver Phantom with a Hollow Biliary System
Authors: Tan Xiangzhou , Li Dandan , Jeong Moonkwang , Yu Tingting , Ma Zhichao , Afat Saif , Grund Karl-Enrst , Qiu Tian 
Published: February 2021

AbstractHepatobiliary interventions are regarded as difficult minimally-invasive procedures that require experience and skills of physicians. To facilitate the surgical training, we develop a soft, high-fidelity and durable liver phantom with detailed morphology. The phantom is anatomically accurate and feasible for the multi-modality medical imaging, including computer tomography (CT), ultrasound, and endoscopy. The CT results show that the phantom resembles the detailed anatomy of real livers including the biliary ducts, with a spatial root mean square error (RMSE) of 1.7 ± 0.7 mm and 0.9 ± 0.2 mm for the biliary duct and the liver outer shape, respectively. The sonographic signals and the endoscopic appearance highly mimic those of the real organ. An electric sensing system was developed for the real-time quantitative tracking of the transhepatic puncturing needle. The fabrication method herein is accurate and reproducible, and the needle tracking system offers a robust and general approach to evaluate the centesis outcome.
Analysis of airborne pollen time series originating from Hirst-type volumetric samplers—comparison between mobile sampling head oriented toward wind direction and fixed sampling head with two-layered inlet
Authors: Mimić Gordan , Šikoparija Branko 
Published: February 2021

AbstractIn this study, we have compared time series of pollen concentration originating from two Hirst-type volumetric samplers that were equipped with different sampling heads. To collect airborne pollen, we have used classic sampler with mobile sampling head including wind vane and adapted sampler with fixed sampling head having two-layered inlet, like in Sigma-2 passive sampler. The devices were placed at the roof level, on the top of the building of the Faculty of Sciences located in Novi Sad, Serbia. The sampling of airborne pollen was performed from February until October 2019. Along with the pollen data, meteorological conditions were recorded with an automated weather station measuring solar radiation, air temperature, relative humidity, wind speed and precipitation. Time series of daily pollen concentrations expressed high correlations, although there were large differences on the hourly basis. Absolute difference between hourly values showed very weak correlation with relevant meteorological parameters: temperature, humidity, precipitation, wind speed and turbulent kinetic energy, leading to the conclusion that sampling with both heads was not affected by meteorological conditions. Counting the pollen grains from the whole sample and not just from 10% of the area, which is the minimum requirement, was done for the six days in the season and proved that error introduced by subsampling during analysis was the main reason for differences in time series. To conclude, replacing mobile sampling head with fixed sampling head having two-layered inlet does not notably affect the quantity of pollen recorded by the Hirst-type volumetric method.
Rotational effects on exchange flows across a submerged sill
Authors: Cuthbertson A. , Berntsen J. , Laanearu J. , Asplin Magdeli 
Published: February 2021

AbstractThis paper presents new laboratory-scale numerical simulations of density-driven exchange flows generated across an idealised, submerged sill obstruction under both non-rotating and rotating frames of reference using the Bergen Ocean Model (BOM), a three-dimensional general ocean circulation model. Initial non-rotating BOM simulations are compared directly with previous laboratory data obtained in a large-scale channel facility incorporating an idealised trapezoidal sill. These laboratory experiments demonstrate that the saline intrusion flux across the sill is initially reduced and then eventually fully blocked under increasing net-barotropic flow conditions imposed in the counterflowing upper freshwater layer, with the saline blockage also more evident for reduced sill submergence depths. These parametric dependences are also demonstrated in the equivalent BOM simulations of the non-rotating sill exchange flows, although the numerical model results tend to overpredict both the interfacial velocity and density gradients across the sill (as indicative of suppressed interfacial mixing), as well as the fresh-saline source flux ratio at which full blockage of the saline intrusion occurs. The BOM simulations are then extended to consider rotating sill exchange flow dynamics. In particular, these additional runs demonstrate that Coriolis forces increase the overall blockage of the saline intrusion layer compared to equivalent non-rotating exchange flows, especially when the Rossby number associated with the saline intrusion flow across the sill is considerably less than unity. This effect is largely attributed to the development of Ekman boundary layer dynamics and associated secondary circulations within the bi-directional exchange flows. These are shown to impose strong control on the transverse distribution and extent of the lower saline intrusion flow across the sill and, hence, the parametric conditions under which full saline intrusion blockage is achieved in rotating sill exchange flows.
Finite element simulation of ductile fracture in polycrystalline materials using a regularized porous crystal plasticity model
Authors: Khadyko Mikhail , Frodal Bjørn Håkon , Hopperstad Odd Sture 
Published: February 2021

AbstractIn the present study, a hypoelastic–plastic formulation of porous crystal plasticity with a regularized version of Schmid’s law is proposed. The equation describing the effect of the voids on plasticity is modified to allow for an explicit analytical solution for the effective resolved shear stress. The regularized porous crystal plasticity model is implemented as a material model in a finite element code using the cutting plane algorithm. Fracture is described by element erosion at a critical porosity. The proposed model is used for two test cases of two- and three-dimensional polycrystals deformed in tension until full fracture is achieved. The simulations demonstrate the capability of the proposed model to account for the interaction between different modes of strain localization, such as shear bands and necking, and the initiation and propagation of ductile fracture in large scale polycrystal models with detailed grain description and realistic boundary conditions.
TORCH: a TOSCA-Based Orchestrator of Multi-Cloud Containerised Applications
Authors: Tomarchio Orazio , Calcaterra Domenico , Di Modica Giuseppe , Mazzaglia Pietro 
Published: February 2021

AbstractThe growth in the number and types of cloud-based services offered to IT customers is supported by the constant entry of new actors in the market and the consolidation of disruptive technologies such as AI, Big Data and Micro-services. From the customer’s perspective, in a market landscape where the cloud offer is highly diversified due to the presence of multiple competing service providers, picking the service that best accommodate their specific needs is a critical challenge. Once the choice is made, so called “cloud orchestration tools” (orchestrators) are required to take care of the customer application’s life-cycle. While big players offer their customers proprietary orchestrators, in the literature quite a number of open-source initiatives have launched multi-cloud orchestrators capable of transparently managing applications on top of the most representative cloud platforms. In this paper, we propose TORCH, a TOSCA-based framework for the deployment and orchestration of cloud applications, both classical and containerised, on multiple cloud providers. The framework assists the cloud customer in defining application requirements by using standard specification models. Unlike other multi-cloud orchestrators, adopts a strategy that separates the provisioning workflow from the actual invocation of proprietary cloud services API. The main benefit is the possibility to add support to any cloud platforms at a very low implementation cost. In the paper, we present a prototypal implementation of TORCH and showcase its interaction with two different container-based cluster platforms. Preliminary performance tests conducted on a small-scale test-bed confirm the potential of TORCH.
Management of RAASi-associated hyperkalemia in patients with cardiovascular disease
Authors: Silva-Cardoso José , Brito Dulce , Frazão João Miguel , Ferreira Aníbal , Bettencourt Paulo , Branco Patrícia , Fonseca Cândida 
Published: February 2021

AbstractRenin–angiotensin–aldosterone system inhibitors (RAASi) reduce morbidity and mortality in heart failure (HF) with reduced ejection fraction in a dose-dependent manner. They also have a positive impact in other cardiovascular diseases (CVDs). However, RAASi may induce hyperkalemia, a potentially life-threatening disorder. This risk is further increased in those with concomitant chronic kidney disease, diabetes mellitus, and/or in patients with hypertension. Current treatment guidelines recommend maximal RAASi dosing to improve clinical outcomes; however, this is often limited by the development of hyperkalemia. When this occurs, current guidelines recommend RAASi down-titration/interruption, which, while improving short-term prognosis, is associated with a negative long-term prognostic impact. At present, the European Society of Cardiology suggests the consideration of novel potassium binders (patiromer and sodium zirconium cyclosilicate) for the management of RAASi-associated hyperkalemia. Both drugs can reduce serum potassium levels and prevent recurrent hyperkalemia. Additionally, patiromer showed enabling of RAASi optimization in high-risk patients. Nevertheless, precise recommendations on the use of these drugs are lacking. Building upon current HF guideline recommendations, a multidisciplinary expert panel convened to design an algorithm providing practical guidance on the use of novel potassium binders/patiromer in patients with HF and/or other CVD. As a result of that effort, we present an evidence-based treatment algorithm for the management of hyperkalemia with novel potassium binders/patiromer in patients with HF and/or other CVD receiving RAASi, including the necessary monitoring to avoid induction of hypokalemia. This algorithm aims to maintain or up-titrate RAASi to optimized doses, while maintaining normokalemia, improved clinical outcomes, and long-term prognosis.
A Cross-Disciplines and Cross-Sector Mixed-Methods Examination of Design Thinking Practices and Outcome
Authors: Lake Danielle , Flannery Kathleen , Kearns Morgan 
Published: February 2021

AbstractThis mixed method study investigated design thinking (DT) practices and outcomes from across disciplinary frameworks within one institution of higher education. Building upon prior DT studies, it examined three interlocking research questions: What DT practices are being implemented across the curriculum? What kinds of outcomes do faculty observe? What are the significant relationships between particular practices and observed outcomes? Thirty-five courses were examined via a faculty survey adapted from Liedtka and Bahr (2019), and a semi-structured interview created by Lake, Ricco, and Whipps (2018). In alignment with liberal arts educational practices, the most frequently utilized DT practices included working in teams that recognize diverse contributions and engaging in active listening in order to find shared meaning. Consistent with expectations for project- and team-based courses, faculty felt such practices yielded valued outcomes, concluding DT practices built trust across teams and increased the quality of solutions. Relationships between practices and outcomes revealed the utilization of more ethnographic tools was associated with a lower frequency of expanding relationships and resources, and that a greater focus on design criteria to find an ideal solution hampered efforts towards trust building. These findings suggest DT requires time and trust which can be constrained by the imposed deadlines of semester-based projects. The survey and interviews pointed to both similarities and differences between disciplines in DT practices. Future research investigating design thinking pedagogy should include faculty, students, and stakeholders with multiple touchpoints for assessment to identify learning experiences that build change-making capacities and yield genuinely valuable and viable real world projects.
Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions
Authors: Rodríguez-Pérez Raquel , Bajorath Jürgen 
Published: February 2021

AbstractMachine learning (ML) enables modeling of quantitative structure–activity relationships (QSAR) and compound potency predictions. Recently, multi-target QSAR models have been gaining increasing attention. Simultaneous compound potency predictions for multiple targets can be carried out using ensembles of independently derived target-based QSAR models or in a more integrated and advanced manner using multi-target deep neural networks (MT-DNNs). Herein, single-target and multi-target ML models were systematically compared on a large scale in compound potency value predictions for 270 human targets. By design, this large-magnitude evaluation has been a special feature of our study. To these ends, MT-DNN, single-target DNN (ST-DNN), support vector regression (SVR), and random forest regression (RFR) models were implemented. Different test systems were defined to benchmark these ML methods under conditions of varying complexity. Source compounds were divided into training and test sets in a compound- or analog series-based manner taking target information into account. Data partitioning approaches used for model training and evaluation were shown to influence the relative performance of ML methods, especially for the most challenging compound data sets. For example, the performance of MT-DNNs with per-target models yielded superior performance compared to single-target models. For a test compound or its analogs, the availability of potency measurements for multiple targets affected model performance, revealing the influence of ML synergies.