bluuebunny/crossref_metadata_2025_split huggingface dataset:
The challenge of demonstrating contemporary natural selection on polygenic quantitative traits in the wild
Authors: Buggs Richard J. A. 
Published: November 2022

In a From the Cover article in this issue of Molecular Ecology, Ashraf et al. (2022) apply genomic prediction methods, devised by breeders to inform artificial selection, to understand the genetic component of variation in highly polygenic quantitative traits in Soay sheep (Figure 1). These methods have allowed them to investigate the effects of contemporary natural selection on genetic variation underlying these traits in the wild (Hunter et al., 2022). Genomic prediction approaches promise to enhance our understanding of the evolution of highly polygenic quantitative traits in the wild and may allow us to document concrete examples of their natural selection in real time in systems that would otherwise be intractable.
Salivary levels of NLRC4 inflammasome in different periodontal clinical status
Authors: Toraman Ayşe , Sağlam Ebru , Savran Levent , Sağlam Mehmet , Köseoğlu Serhat 
Published: November 2022

AbstractObjectiveNucleotide‐binding and oligomerization domain (NOD)‐like receptor family CARD domain‐containing protein 4 (NLRC4) has a critical role in the regulation of interleukin‐1β (IL‐1β), an important cytokine in the pathogenesis of the periodontal diseases. In this study, we aimed to evaluate levels of salivary NLRC4 inflammasomes in different periodontal clinical statuses.MethodsThe individuals with 20 periodontally healthy (healthy), 20 gingivitis, and 20 periodontitis were periodontally examined. Saliva samples were collected, after the clinical measurements (plaque index, gingival index, gingival bleeding index, probing depth, and clinical attachment level). The levels of salivary NLRC4, IL‐1β, and interleukin 10 (IL‐10) were examined by enzyme‐linked immunosorbent assay.ResultsThe results demonstrated that levels of salivary NLRC4 (p < 0.01), and IL‐1β (p < 0.001) were significantly higher in gingivitis and periodontitis than in the healthy group. No significant difference was salivary IL‐10 levels between the groups (p > 0.05). Positive significant correlations among NLRC4 and IL‐1β salivary levels and clinical parameters were detected (p < 0.05).ConclusionThe findings of this study suggest that the NLRC4 is elevated in periodontal disease. Larger randomized controlled clinical studies are needed to use salivary NLRC4 levels as a potential marker for detecting the presence and/or severity of the periodontal disease.
Management and behavior‐modifying recommendation effects in childhood headache
Authors: Gungor Mesut , Guler Muhammet Akif , Karagoz Yuksel Sumeyra 
Published: November 2022

AbstractBackgroundHeadaches are common in childhood. Recently, there has been an increasing trend toward pharmacological treatment.MethodsSecondary causes were excluded first in patients who attended our clinic with headache. Those without a secondary cause were evaluated as primary headache and classified into subgroups. Behavior‐modifying recommendations (adequate and regular sleep, adequate and regular nutrition, adequate fluid intake, and restriction of screen exposure) were given to all patients. Patients were re‐evaluated at 1, 3, and 6 months. Pharmacologic treatment was started at the end of the first month with follow‐up at the third and sixth months for those who did not benefit from the behavior‐modifying recommendations.ResultsA total of 875 patients presented with headache complaints, of which 30.6% were evaluated as primary headache. Behavior‐modifying recommendations were beneficial for 23.1% with migraine with aura; 20.3% with migraine without aura, and 36.8% with tension‐type headache.ConclusionSecondary causes should be excluded first in patients who present to the pediatric neurology clinic with headache. Behavioral modifications to change the lifestyle of patients diagnosed with primary headache should be tried before giving pharmacologic treatment.
Genetic structure of Plasmopara halstedii populations across Europe and South Russia
Authors: Kitner Miloslav , Thines Marco , Sedlářová Michaela , Vaculná Lucie , Bán Rita , Körösi Katalin , Iwebor Maria , Antonova Tatiana , Ali Tahir , Nádvorník Petr , Lebeda Aleš , Spring Otmar 
Published: November 2022

AbstractPlasmopara halstedii is a biotrophic parasite of sunflower (Helianthus annuus). We genetically analysed 162 P. halstedii samples collected between 1982 and 2018, representing a 3500 km west–east transect across Europe, from France to the Krasnodar region in southern Russia. To assess the population genetic structure among P. halstedii isolates, we sequenced two mitochondrial regions (cox1 and cox2), in addition to analysing eight polymorphic simple sequence repeat (SSR, microsatellite) markers. Sequencing of cox2 enabled comparison of our data with recent SSR‐based studies to provide further evidence for differences among P. halstedii strains infecting different hosts (H. annuus, H. × laetiflorus, Rudbeckia spp.). There are two different lineages infecting H. annuus that we resolved on a neighbour‐joining tree, which also corresponded to a discriminant analysis of principal components. This suggests at least two independent introductions of P. halstedii on sunflower. We observed no relationship between the phylogenetic placement of the individual samples and virulence characteristics, indicating independent evolution of virulence phenotypes. Both genetic markers clearly separated P. halstedii samples originating from H. annuus and H. × laetiflorus, suggesting these might represent distinct species.
The effect of inherently threatening contexts on visuocortical engagement to conditioned threat
Authors: Stegmann Yannik , Andreatta Marta , Wieser Matthias J. 
Published: November 2022

AbstractFear and anxiety are crucial for adaptive responding in life‐threatening situations. Whereas fear is a phasic response to an acute threat accompanied by selective attention, anxiety is characterized by a sustained feeling of apprehension and hypervigilance during situations of potential threat. In the current literature, fear and anxiety are usually considered mutually exclusive, with partially separated neural underpinnings. However, there is accumulating evidence that challenges this distinction between fear and anxiety, and simultaneous activation of fear and anxiety networks has been reported. Therefore, the current study experimentally tested potential interactions between fear and anxiety. Fifty‐two healthy participants completed a differential fear conditioning paradigm followed by a test phase in which the conditioned stimuli were presented in front of threatening or neutral contextual images. To capture defense system activation, we recorded subjective (threat, US‐expectancy), physiological (skin conductance, heart rate) and visuocortical (steady‐state visual evoked potentials) responses to the conditioned stimuli as a function of contextual threat. Results demonstrated successful fear conditioning in all measures. In addition, threat and US‐expectancy ratings, cardiac deceleration, and visuocortical activity were enhanced for fear cues presented in threatening compared with neutral contexts. These results are in line with an additive or interactive rather than an exclusive model of fear and anxiety, indicating facilitated defensive behavior to imminent danger in situations of potential threat.
A spatial data model for accessibility with indoor temporal changes
Authors: Liu Liu , Zlatanova Sisi 
Published: November 2022

AbstractIndoor accessibility is often evaluated with the networks extracted from buildings. For instance, circulation networks with depth cost are applied to floor design. A group of data models supports the extraction of indoor networks from buildings, and these networks are widely used to evaluate the accessibility of users. However, the existing cases are mostly devised for static environments, that is, without consideration of dynamic obstacles. This assumption may contradict the fact of daily changes such as pedestrian flow and temporal blockage. Except emergency scenarios, these daily temporal changes can interrupt the continuous movement of a user, and they shall be considered for data modeling of indoor networks. Thus, this article proposes a concise data model which can manage daily temporal changes of accessibility and support related accessibility queries. In the data model, we consider indoor accessibility on two levels of detail, that is, the room and sub‐room levels. On the room level, we revise a gravity model to measure the accessibility variation of rooms influenced by temporal obstacles. On the sub‐room level, we continuously update obstacle‐avoiding networks adapted to temporal obstacles. In this case, the accessibility of a user at any location can be assessed and time‐dependent accurate routes can be planned at different moments. We implemented this spatial data model in the DBMS PostgreSQL and its feasibility was demonstrated with the test in a campus building. The data model can be applied to daily checks of user accessibility and can be further incorporated with indoor sensor systems and simulation models to predict accessibility variation.
Equivariant quadratic forms in characteristic 2
Authors: Nebe Gabriele , Parker Richard 
Published: November 2022

AbstractLet be a finite group and a finite field of characteristic . Denote by the ‐rank of the commutator factor group and by the number of isomorphism classes of self‐dual simple ‐modules. Then the Witt group of equivariant quadratic forms is isomorphic to an elementary abelian ‐group of rank .
Mechanisms of Hebbian‐like plasticity in the ventral premotor – primary motor network
Authors: Casarotto Andrea , Dolfini Elisa , Cardellicchio Pasquale , Fadiga Luciano , D'Ausilio Alessandro , Koch Giacomo 
Published: November 2022

AbstractThe functional connection between ventral premotor cortex (PMv) and primary motor cortex (M1) is critical for the organization of goal‐directed actions. Repeated activation of this connection by means of cortico‐cortical paired associative stimulation (cc‐PAS), a transcranial magnetic stimulation (TMS) protocol, may induce Hebbian‐like plasticity. However, the physiological modifications produced by Hebbian‐like plasticity in the PMv‐M1 network are poorly understood. To fill this gap, we investigated the effects of cc‐PAS on PMv‐M1 circuits. We hypothesized that specific interactions would occur with I2‐wave interneurons as measured by the short intracortical facilitation protocol (SICF). We used different paired‐pulse TMS protocols to examine the effects of PMv‐M1 cc‐PAS on SICF, on GABAergic circuits as measured by short (SICI) and long (LICI) intracortical inhibition protocols, and varied the current direction in M1 to target different M1 neuronal populations. Finally, we examined the effects of cc‐PAS on PMv‐M1 connectivity using a dual coil approach. We found that PMv‐M1 cc‐PAS induces both a long‐term potentiation (LTP)‐ or long‐term depression (LTD)‐like after‐effect in M1 neuronal activity that is strongly associated with a bidirectional‐specific change in I2‐wave activity (SICF = 2.5 ms ISI). Moreover, cc‐PAS induces a specific modulation of the LICI circuit and separately modulates PMv‐M1 connectivity. We suggest that plasticity within the PMv‐M1 circuit is mediated by a selective mechanism exerted by PMv on M1 by targeting I2‐wave interneurons. These results provide new mechanistic insights into how PMv modulates M1 activity that are relevant for the design of brain stimulation protocols in health and disease.
imageKey points
The I2‐wave is specifically modulated by the induction of ventral premotor cortex – primary motor cortex (PMv‐M1) plasticity.
After PMv‐M1 cortico‐cortical paired associative stimulation (cc‐PAS), corticospinal excitability correlates negatively with I2‐wave amplitude.
Different cc‐PAS coil orientations can lead to a long‐term potentiation‐ or long‐term depression‐like after‐effect in M1.
Virtual Centrifugal Pump Test Rig for Laboratory Classes Based on IoT Technology
Authors: Roclawski Harald , Sterle Laura , Böhle Martin 
Published: November 2022

Abstract
In the project IoT for Supervision and Control of Water Systems (IoT.H2O) the potential of the Internet of Things concept for operating pump systems is investigated. As a result of the project, a pump test rig which can be controlled by an open source IoT platform was developed. Because of COVID 19 students are currently not able to access the test rig in their laboratory class. In the paper, a virtual pump test rig is presented. The model of the test rig is based on the physical IoT pump test rig and consists of models for pump, control valve, piping system and electric motor. By modeling the electric motor, the operating behavior of the pump becomes much more realistic since effects of inertia can be included. The communication of the IoT platform with the model is based on the MQTT protocol and is identical to the real rig. The test rig can be operated with any web browser through a dashboard. On the dashboard, the operating frequency of the electric motor, the control valve position, the static head of the system and the tank pressure before the pump can be set with predefined control widgets which are already available in the IoT platform. Also, through buttons, measurements of speed, static pressure and torque are possible. The data can be downloaded after the measurements are taken.
In different assignments, the students, can measure the head and efficiency curves and system curves and compare speed control and throttle control. Also, different types of pumps can be assessed easily by exchanging the pump curves in the model.
A big advantage of the virtual lab tests is that the students can run the tests by themselves and obtain their own data. Before, the tests were only run in groups because of time constraints. Based on the laboratory class, they are able to assess the behavior of pumps in systems and to design pump systems efficiently. Also, they are introduced to the concept of IoT.
Numerical Investigation of Bladeless Compressor on Different Disk Spaces and Diffuser Configurations
Authors: Tiwari Ravi Nath , Eleftheriou Konstantinos , Ferrari Mario Luigi , Efstathiadis Theofilos , Traverso Alberto , Kalfas Anestis 
Published: November 2022

Abstract
The cost-effectiveness of turbomachinery is a key aspect within the small-size compressor market. For this reason, Tesla turbomachinery, invented by Nikola Tesla in 1913, could be a good solution, particularly for low volumetric flow applications, where volumetric compressors are usually used. It consists of a bladeless rotor which stands out for its ease of construction and its ability to maintain almost the same performance as size decreases. One of its advantages is that it can run either as a turbine or as a compressor with minor modifications at the stator. The objective of this paper is to investigate a 3kW Tesla compressor, which design was derived from an analogous Tesla expander prototype (59% isentropic efficiency from the numerical study), by conducting a computational fluid dynamic analysis for different disk gaps and diffuser configurations.
The potential of the Tesla compressor is shown to be quite promising, with a peak isentropic efficiency estimated at 53%. Although bladeless compressor is a simple turbomachinery device, different parts i.e., diffuser, tip clearance, and volute need to be optimized. Utilizing computational fluid dynamics algorithms, different disk gaps and different diffusers are simulated in order to increase the overall performance of the compressor and understand the flow dynamic behavior behind this technology. The dimensionless Ekman number is used to express the optimum disk space of the compressor rotor. Thus, the overall performance of the Tesla compressor is improved by 5–10% points compared to the initial model. Simultaneously, diffuser optimization strategies are applied and proved that there is a direct impact on the optimum design conditions, improving the pressure ratio at high mass flow rates.
Liquid Air Combined Cycle
Authors: Conlon William M. , Venetos Milton , Rimpel Aaron 
Published: November 2022

Abstract
Hybrid integration of thermal energy storage with gas turbines can provide compact, cost-effective, long-duration energy storage while reducing the fuel consumption of dispatchable resources needed for the reliability of renewable dominant electric grids. The Liquid Air Combined Cycle™ (LACC) is a hybrid energy storage system using cryogenic liquid air as an energy storage medium and gas turbine exhaust heat to extract stored energy.
The storage tank is charged using liquefaction processes employing electric motor-driven compressors to pressurize the air, heat exchangers to reject heat of compression, and expanders to reduce the temperature and liquefy the air. Proven cryogenic refrigeration processes can be selected based on capital cost (per kg/s of liquid air produced), efficiency (kJ per kg of air produced), and operating factors including startup speed and load following capability.
This paper presents results of studies undertaken for the U.S. Department of Energy to evaluate cost and performance tradeoffs for charge and discharge cycle components, optimize charge and discharge cycles, and assess the techno-economic potential of LACC technology.
The Application of an Artificial Neural Network As a Baseline Model For Condition Monitoring of Innovative Humidified Micro Gas Turbine Cycles
Authors: Colquhoun Kathryn , Nikpey Somehsaraei Homam , De Paepe Ward 
Published: November 2022

Abstract
Due to high penetration of renewables, the EU energy system is undergoing a transition from large-scale centralized generation towards small-scale distributed generation. The increasing share of intermittent renewables such as solar and wind has become the main driver for dispatchable distributed energy generation technologies to maintain the grid flexibility and stability. In this context, micro gas turbines (MGTs) with high fuel and operation flexibility could play a crucial role to guarantee the grid stability, enabling deeper penetration of the intermittent renewable energy sources.
Despite this, the MGT market is still considered to be niche and there are R&D&I challenges that need to be addressed to further promote this technology in distributed generation applications. Innovative MGT cycles based on a cycle humidification concept, can be considered to obtain higher system performance. However, given the fact that MGTs are installed close to the consumption points, where they are operated by non-technical prosumers with very limited access to maintenance services, they should also offer high availability and reliability to avoid unexpected outages and secure the supply. Therefore, intelligent monitoring systems are needed that can support non-expert end-users to detect degradation and plan maintenance before a breakdown occurs.
In this study we investigated and developed advanced methods based on artificial neural networks (ANNs) for condition monitoring of a humidified MGT cycle under real-life operational conditions. To create a high-performing model, extensive data preprocessing has been conducted to remove data outliers and select optimum model features, which provide best results. Additionally, the model hyperparameters such as learning rate, momentum and number of hidden nodes have been altered to achieve the most accurate predictions. The results of this study have provided a baseline ANN model capable of conducting condition monitoring of a micro-Humid Air Turbine (mHAT) system, which will be applied to additional studies in the future.
Optimal Design and Operation Planning of VPPs Based on Hydrogen Storage and Hydrogen Combined Cycle
Authors: Castelli Alessandro Francesco , Pilotti Lorenzo , Martelli Emanuele 
Published: November 2022

Abstract
Virtual Power Plants (VPPs) and Multi-Energy Systems (MESs) are aggregated energy systems comprising renewable energy sources, energy storage systems and dispatchable units. The presence of such diverse systems unlocks the possibility of a near-zero carbon emission energy generation while overtaking the main drawback of renewables sources that is their lack of control. Among the different energy storage systems, large scale (seasonal) H2 storages (e.g. salt cavern or depleted oil field) would allow shifting the excess solar energy from the hot to the cold season. High round-trip efficiency (electricity to electricity) and unpaired operational flexibility could be achieved using H2 in state-of-the-art combined cycles.
This work investigates the optimal design and operation of a fully renewable VPPs integrating PV panels, batteries for short-term storage, electrolyzers, H2 seasonal storage and H2-fired combined cycles. The optimal design and optimal yearly operation of such complex VPP are formulated as Mixed Integer Linear Programs (MILP) and solved to global optimality imposing to meet the highest possible fraction of the electricity demand profile. Results indicate that the optimal VPP design features a 490 MWhel of battery, 687 MWel of PV panels, 392 MWel of electrolyzer and requires a minimum H2 storage size of 168 GWhH2,LHV to power a combined cycle of 58 MWel. In case of a geological H2 seasonal storage availability, the resulting cost of generated electricity is above 430 $/MWhel, considerably higher with respect to the average electricity prices in Italy (in the range 50–80 $/MWhel) underlining the need of achieving better power-to-gas efficiencies and lower specific investment costs of conversion technologies in the next years. Furthermore, if the H2 storage needs to be built on purpose, the resulting cost of electricity would be even higher.
Interactive Learning Platform for the Preliminary Design of Axial Turbines and Its Use for Graduate Courses
Authors: Silva George Patton de Oliveira , Tomita Jesuino Takachi , Bringhenti Cleverson , Whitacker Luiz Henrique Lindquist , Tonon Daniel da Silva 
Published: November 2022

Abstract
The gas turbine industry requires extensive knowledge in several areas of engineering, and since both industry and academy continuously develop new approaches, technologies, and models, usually, there is not enough time to cover all the relevant subjects in one or two-semester courses for undergraduate or graduate students. In previous work, the authors have presented an interactive platform for the preliminary design of single-stage axial turbines with uncooled blades, for use at the undergraduate courses offered by the Turbomachine Department at Aeronautics Institute of Technology to accelerate the learning process. The present work aims to present an expansion of this interactive learning platform, with the inclusion of a module for the thermodynamic cycle study, a module for off-design calculations, and the generation of a PDF file containing the step-by-step solution memorial with all the equations and values used in the design. The work also presents a structure for the conduction of a graduate course in turbomachines focused on the design of axial turbines. It comprehends theory and exercise classes, oriented study with the interactive learning platform, and a project in which the students have to implement some of the modules and run test cases. The authors observed more interest of the students and higher quality questions in the classes while using the interactive platform or programming, developing a better understanding of the design process until the end of the course. Also, while, in previous semesters, the preliminary design occupied almost half of the 48-hour course, it took only 12-hour to cover the same subject, granting time to more advanced topics, such as blade cooling, off-design performance and computational fluid dynamics simulations.