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• Using Geospatial Technologies to understand Mixed Reality better. • Utilizing the Internet of Things to communicate between Mixed Reality Environments and the Real Worlds. • Defining a novel Virtual-to-Real interaction method for Mixed Reality Interactions. • Demonstrating a case study with an application prototype, where a virtual man executes a physical task. As Mixed Reality applications penetrate people's daily activities, strong synergies with Geospatial technologies and the Internet of Things are revealed. The first is due to the significance of the spatial reference of all involved actors of a Mixed Reality environment: the end-user, the real and the virtual objects. The second is due to the ever-increasing participation of sensors controlling devices and machines always and everywhere. This paper highlights these synergies and proposes a case proving they crucially empower a Mixed Reality experience. Through this synergy, a novel interaction method for Mixed Reality Environments emerges, the "physical task execution" interaction method. An open-source application prototype was developed to support the case study where we assign a physical task to a virtual man to execute, utilising the Internet of Things in a Mixed Reality Environment. [ABSTRACT FROM AUTHOR]

Abstract Staphylococcus aureus is an important cause of food intoxication, whereas methicillin-resistant S. aureus (MRSA) constitutes a serious public-health concern due to its ability to colonize and infect humans and animals. S. aureus and MRSA have often been isolated from milk and dairy products. The objectives of this study were to estimate the prevalence and the antimicrobial resistance of S. aureus and MRSA in four Greek dairy industries, to identify virulence factors of MRSA isolates and to describe their genetic diversity, in order to identify possible epidemiological links and evaluate the risk of MRSA dissemination to the community. S. aureus was isolated from 67 out of 305 (22.0%) dairy industry samples (bulk-tank milk, dairy products, employee nasal swabs and equipment/surface swabs). Almost all (99%) of the 227 corresponding S. aureus isolates (approximately 4 isolates per positive sample) were resistant to at least one antimicrobial and 22% were multi-drug resistant (MDR). MRSA were isolated from 11 different samples (3.6%) originating from three of the dairy plants. All MRSA isolates were capable of forming biofilms, while staphylococcal enterotoxin (SE) genes were detected in 91% of the MRSA isolates, with sec being the most frequent. All of the MRSA isolates harbored the mec A gene but the mec C and Pandon-Valentine leucocidin (PVL) genes were not detected. Pulse-Field Gel Electrophoresis (PFGE) analysis showed genetic diversity among the MRSA isolates and indicated clonal circulation in one of the dairy plants. Seven spa types were identified among the MRSA isolates with the most prevalent (t065) isolated only in one dairy plant. Certain spa types (t065, t337 and t3536) were isolated for the first time in Greece. The presence of MDR, biofilm-forming and enterotoxigenic MRSA strains in dairy plant facilities may lead to their dissemination to the community, but also to staphylococcal food poisoning, when conditions are favorable. The study's findings highlight the need for continuous monitoring of the dairy production chain, the need for re-evaluating the implemented cleaning and sanitizing processes and the adoption of preventive strategies in order to minimize public-health risks. Highlights • Of 305 samples tested, 22.0% were S. aureus -positive & 3.6% were MRSA-positive. • Most MRSA isolates belonged to spa type t065. • spa types t065, t337 and t3536 were isolated for the first time in Greece. • Almost all MRSA isolates harbored SE-genes; sec being most frequent. • All MRSA isolates were capable to form biofilm. [ABSTRACT FROM AUTHOR]

Mode identification from post-disturbance “ringdown” responses can provide vital information concerning the dynamic performance and the stability margins of power systems. Therefore, several measurement-based identification techniques have been proposed in the literature to analyze ringdown responses of transmission systems and provide close to real-time estimation of the modal content. However, the applicability of these methods has not been thoroughly investigated for the analysis of active distribution networks (ADNs). Scope of this paper is to evaluate the applicability and the performance of eight measurement-based system identification techniques for the modal analysis of ADNs. The examined methods are used to identify the dominant oscillatory modes contained in ringdown responses of different types of signals. The Monte Carlo method is applied to investigate the influence of several parameters on the accuracy and efficiency of the identification procedure, while laboratory measurements are used to further demonstrate the accuracy of the examined methods. Practical issues encountered in the application of the identification techniques for the analysis of ADNs are discussed and potential solutions are proposed. Results reveal that although most of the examined techniques perform satisfactorily enough and thus can be readily employed for the modal analysis of ADNs, the Vector Fitting and the Hybrid FD/TD seem to be the most effective methods in terms of accuracy, robustness and computational efficiency. [ABSTRACT FROM AUTHOR]

Digital Elevation Models (DEMs), in combination with high quality raster graphics provide realistic three-dimensional (3D) representations of the globe (virtual globe) and amazing navigation experience over the terrain through earth browsers. In addition, the adoption of interoperable geospatial mark-up languages (e.g. KML) and open programming libraries (Javascript) makes it also possible to create 3D spatial objects and convey on them the sensation of any type of texture by utilizing open 3D representation models (e.g. Collada). One step beyond, by employing WebGL frameworks (e.g. Cesium.js, three.js) animation and motion effects are attributed on 3D models. However, major GIS-based functionalities in combination with all the above mentioned visualization capabilities such as for example animation effects on selected areas of the terrain texture (e.g. sea waves) as well as motion effects on 3D objects moving in dynamically defined georeferenced terrain paths (e.g. the motion of an animal over a hill, or of a big fish in an ocean etc.) are not widely supported at least by open geospatial applications or development frameworks. Towards this we developed and made available to the research community, an open geospatial software application prototype that provides high level capabilities for dynamically creating user defined virtual geospatial worlds populated by selected animated and moving 3D models on user specified locations, paths and areas. At the same time, the generated code may enhance existing open visualization frameworks and programming libraries dealing with 3D simulations, with the geospatial aspect of a virtual world. [ABSTRACT FROM AUTHOR]

While the postsynaptic density of excitatory synapses is known to encompass a highly complex molecular machinery, the equivalent organizational structure of inhibitory synapses has long remained largely undefined. In recent years, however, substantial progress has been made towards identifying the full complement of organizational proteins present at inhibitory synapses, including submembranous scaffolds, intracellular signaling proteins, transsynaptic adhesion proteins, and secreted factors. Here, we summarize these findings and discuss future challenges in assigning synapse-specific functions to the newly discovered catalog of proteins, an endeavor that will depend heavily on newly developed technologies such as proximity biotinylation. Further advances are made all the more essential by growing evidence that links inhibitory synapses to psychiatric and neurological disorders. [ABSTRACT FROM AUTHOR]

All the Salmonella enterica ser. Infantis strains isolated under official control programs in Greece during a four year period were studied, 23 of human origin, 16 from food animals and one from food. Molecular analyses (PFGE) in combination with antimicrobial susceptibility testing were used to study whether the occurrence S. Infantis in Greece resulted from different biotypes or a successful spread of one clone. Low rates of antimicrobial resistance were observed, except for streptomycin among human isolates (48%), indicating that selective pressure due to consumption of antimicrobials has not resulted the spread of dominant clones. Pulsed Field Gel Electrophoresis revealed 31 Xba I distinct pulsotypes among the 40 strains with 60% overall similarity reflecting diversity. Four main clusters were constructed, using an 85% cut off value, clusters A, B, C and D consisting of 14, 6, 8 and 8 isolates respectively. Point source of transmission was not hypothesized as multiple reservoirs of the serovar seem to be present in Greece during the study period. [ABSTRACT FROM AUTHOR]

The formation of neuronal synapses and the dynamic regulation of their efficacy depend on the proper assembly of the postsynaptic neurotransmitter receptor apparatus. Receptor recruitment to inhibitory GABAergic postsynapses requires the scaffold protein gephyrin and the guanine nucleotide exchange factor collybistin (Cb). In vitro, the pleckstrin homology domain of Cb binds phosphoinositides, specifically phosphatidylinositol 3-phosphate (PI3P). However, whether PI3P is required for inhibitory postsynapse formation is currently unknown. Here, we investigated the role of PI3P at developing GABAergic postsynapses by using a membrane-permeant PI3P derivative, timelapse confocal imaging, electrophysiology, as well as knockdown and overexpression of PI3P-metabolizing enzymes. Our results provide the first in cellula evidence that PI3P located at early/sorting endosomes regulates the postsynaptic clustering of gephyrin and GABAA receptors and the strength of inhibitory, but not excitatory, postsynapses in cultured hippocampal neurons. In human embryonic kidney 293 cells, stimulation of gephyrin cluster formation by PI3P depends on Cb. We therefore conclude that the endosomal pool of PI3P, generated by the class III phosphatidylinositol 3-kinase, is important for the Cbmediated recruitment of gephyrin and GABAA receptors to developing inhibitory postsynapses and thus the formation of postsynaptic membrane specializations. [ABSTRACT FROM AUTHOR]

Signaling at nerve cell synapses is a key determinant of proper brain function, and synaptic defects-or synaptopathies-are at the basis of many neurological and psychiatric disorders. In key areas of the mammalian brain, such as the hippocampus or the basolateral amygdala, the clustering of the scaffolding protein Gephyrin and of γ-aminobutyric acid type A receptors at inhibitory neuronal synapses is critically dependent upon the brainspecific guanine nucleotide exchange factor Collybistin (Cb). Accordingly, it was discovered recently that an R290H missense mutation in the diffuse B-cell lymphoma homology domain of Cb, which carries the guanine nucleotide exchange factor activity, leads to epilepsy and intellectual disability in human patients. In the present study, we determined the mechanism by which the CbR290H mutation perturbs inhibitory synapse formation and causes brain dysfunction. Based on a combination of biochemical, cell biological, and molecular dynamics simulation approaches, we demonstrate that the R290H mutation alters the strength of intramolecular interactions between the diffuse B-cell lymphoma homology domain and the pleckstrin homology domain of Cb. This defect reduces the phosphatidylinositol 3-phosphate binding affinity of Cb, which limits its normal synaptogenic activity. Our data indicate that impairment of the membrane lipid binding activity of Cb and a consequent defect in inhibitory synapse maturation represent a likely molecular pathomechanism of epilepsy and mental retardation in humans. [ABSTRACT FROM AUTHOR]

Abstract: The electromagnetic interference of power lines to nearby metallic pipelines has been a subject of research for many decades. Usually attention was given to gas or oil pipelines that shared the same rights-off-way with a power line for large distances. However, the recent advancement of renewable energy sources and specifically Photovoltaic (PV) power, due to generous incentives provided in many countries, has resulted in installations of large PV power stations even in agricultural areas. This brought up cases where such power stations in the MWp level, typically connected in medium voltage through buried cables, are located in the vicinity of metallic irrigation pipelines. Under certain conditions, these situations may result in induced voltages and currents on the pipeline that can pose threats to operating personnel. This work presents an analysis of the problems through a quasi-real case study adapted from a real case of a PV power station. The calculation methodology involves a hybrid method that is used in a way to reduced computational time. Results are presented both for normal operating conditions and faults in the power station and may be useful for both agriculture professionals and engineers. [Copyright &y& Elsevier]

Abstract: A general formulation for the determination of the influence of imperfect earth on overhead transmission line impedances and admittances is presented in this paper. The resulting model can be used in the simulation of electromagnetic transients in cases of two-layer earth over a wide frequency range, covering most fast transient phenomena of power engineering interest. The propagation characteristics of an overhead transmission line over homogeneous and two-layer earth are investigated using the proposed model. A systematic comparison of the proposed model with other approaches is also presented and the differences due to earth stratification are reported. Finally, the transmission line parameters calculated by the proposed formulation are used in the simulation of fast transient surges in a transmission line excited by double exponential sources. [Copyright &y& Elsevier]

This paper presents the development of a novel data-driven fault detection and classification scheme for DC faults in multi-terminal HVDC transmission system which incorporates superconducting cables and modular multi-level converters. As the deployment of superconducting cables for bulk power transmission from remote renewable generation is progressively increasing in the future energy grids, many fault-related challenges have been raised (i.e., fault detection, protection sensitivity/stability). In this context, the applications of Artificial Intelligence techniques have started to be considered as a powerful tool for the development of robust fault management solutions. The proposed artificial intelligence-based method utilizes local current and voltage measurements to detect and classify all types of faults on the DC cables and DC buses, without the requirement of measurements exchange among different DC substations. The performance of the proposed scheme has been assessed through detailed transient simulation analysis and the results confirmed its effectiveness against a wide range of fault conditions (i.e., various fault types, fault locations and fault resistances). Furthermore, the feasibility of the developed scheme for real-time implementation has been validated using real-time software in the loop testing. The results revealed that the proposed algorithm can correctly, and within a very short period of time (i.e. less than 2 ms) detect and classify the faults within the protected zone and concurrently remain stable during external faults. Additionally, the generalization capability of the algorithm has been verified against influencing factors such as the addition of noise, highlighting the robustness of the presented scheme. • The deployment of DC Superconducting Cables in HVDC systems has started to be considered a promising solution for bulk power transmission from remote renewable generation units. • The inherent fault current limiting capability and the unique electro-thermal properties of the SCs have introduced many fault management issues in power systems. • For the protection of SCs in meshed HVDC systems, schemes with increased sensitivity, discrimination capability and high operational speed are required. • Artificial-Intelligence-based protection schemes overcome the limitations of existing protection methods in the data-rich power systems, providing fast, and accurate fault detection and classification. • XGBoost-based fault detection and classification algorithm performs effectively under various faults occurred on SCs and DC busbars, providing a reliable protection solution and accelerating the uptake of superconducting technology. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of fault localization in power grids which incorporate Superconducting Cables (SCs) and presence of inverter-connected generation, by proposing a novel data-driven fault location scheme. The developed fault location algorithm utilizes the transformation of time domain fault current and voltage signatures, to time–frequency domain and exploits the advantages of a Convolutional Neural Network (CNN) to estimate the fault position along SCs. The proposed algorithm has been tested using a verified model of SC, and the results revealed that it can provide precise fault localization for a wide range of fault scenarios, including different fault types, fault resistance values and fault inception angles. Furthermore, the proposed scheme robustness has been verified against different influencing factors accounting for very small increments of fault location, additive noise and different value of sampling frequency. For validation purposes, the effectiveness of the CNN-based algorithm has been compared with other data-driven algorithms and the relevant advantages have been highlighted. • The deployment of Superconducting Cables in power systems has introduced many fault related challenges, accounting for fault detection and location. • The identification of accurate fault position on Superconducting Cables is a very important task for the wider adoption of such technology, due to their complex configuration and the lack of standardization in the repair procedure. • The limitations of the conventional fault locations schemes, resulting from quenching of Superconducting Cables, renders the utilization of AI-based techniques a very promising solution. • Time to time-frequency domain transformations are utilized as powerful feature extraction tools in fault location applications. • CNN-based algorithms provide accurate fault location estimation on Superconducting Cables, remaining unaffected by quenching phenomenon. [ABSTRACT FROM AUTHOR]

• A dynamic equivalent modelling approach for the representation and analysis of the dynamic performance of distribution networks with high penetration of Electric Vehicles (EVs) is developed. • The influence of EV charger control parameters on the resulting dynamic responses and modelling needs is investigated. • The impact of EV penetration level on the dynamic behavior of distribution networks is analysed. • The variability of model parameters under different EV penetration levels is presented. During the last few years, there is a worldwide drive for the electrification of the transportation sector to achieve reduced carbon emissions. In this context, the global fleet of electric vehicles (EVs) is steadily increasing. Consequently, in the near future, EVs will become a significant part of the overall power demand. Therefore, the distinct characteristics of the power converters, used in EV charging stations, will have a clear impact on power system dynamics. Therefore, new methods and models are required to simulate and analyse the dynamic performance of distribution networks (DNs) hosting EVs as well as to represent their aggregated dynamic behaviour for transmission level dynamic studies. Towards this objective, in this paper, an equivalent model, based on variable order transfer functions, is proposed to analyse the dynamic properties of EVs as well as to simulate the dynamic behavior of EV-rich DNs. Initially, a sensitivity analysis is performed to quantify the influence of the different control settings of the EV chargers on the resulting dynamics. The analysis reveals that control settings affect considerably the underlying dynamics. Nevertheless, in all cases the proposed equivalent model provides very accurate estimates. Moreover, the impact of EV penetration level on DN dynamics is quantified using a set of metrics. Additionally, a parametric analysis is conducted to verify the applicability of the proposed equivalent model for the dynamic analysis of DNs under specific EV penetration levels. Finally, guidelines for the derivation of generic parameters for the developed equivalent model are proposed. [ABSTRACT FROM AUTHOR]

Originally, ancillary services (ASs) were provided by large-scale power plants to ensure the secure and reliable operation of power systems. However, with the advent of renewable energy sources either in large-scale or as smaller distributed generation units, there is a strong need to revisit the structure and aim of traditional ASs and reconsider them under two main concepts; ASs provided to distribution networks (DNs), aiming to solve local issues at the distribution level, and ASs offered to transmission system (TS), targeting to solve issues having a wider impact on the power system. The former can be considered as DN-oriented ASs, while the latter as TS-oriented ASs. In this changing environment, the increasing installation of measuring infrastructure has created new sources of data, providing the opportunity to improve the performance of several ASs by applying measurement-based analysis. This review paper gives an insight into the most important DN- and TS-oriented ASs foreseen to apply in future power systems. Additionally, state-of-the-art on measurement-based analysis techniques that can be used to facilitate the provision of several ASs by providing in real-time critical information regarding system dynamic performance is presented. • Detailed review on future ancillary services (ASs) in transmission systems. • Detailed review on future ASs in distribution systems. • Overview of measurement-based techniques to facilitate the provision of ASs. • Discussion on future research areas regarding ASs provision. [ABSTRACT FROM AUTHOR]

Signaling at nerve cell synapses is a key determinant of proper brain function, and synaptic defects--or synaptopathies--are at the basis of many neurological and psychiatric disorders. Collybistin (CB), a brain-specific guanine nucleotide exchange factor, is essential for the formation of γ-aminobutyric acidergic (GABAergic) postsynapses in defined regions of the mammalian forebrain, including the hippocampus and basolateral amygdala. This process depends on a direct interaction of CB with the scaffolding protein gephyrin, which leads to the redistribution of gephyrin into submembranous clusters at nascent inhibitory synapses. Strikingly, synaptic clustering of gephyrin and GABAA type A receptors (GABAARs) in several brain regions, including the cerebral cortex and certain thalamic areas, is unperturbed in CB-deficient mice, indicating that the formation of a substantial subset of inhibitory postsynapses must be controlled by gephyrin-interacting proteins other than CB. Previous studies indicated that the α3 subunit of GABAARs (GABAAR-α3) binds directly and with high affinity to gephyrin. Here, we provide evidence (i) that a homooligomeric GABAAR-α3A343W mutant induces the formation of submembranous gephyrin clusters independently of CB in COS-7 cells, (ii) that gephyrin clustering is unaltered in the neuronal subpopulations endogenously expressing the GABAAR-α3 in CB-deficient brains, and (iii) that exogenous expression of GABAAR-α3 partially rescues impaired gephyrin clustering in CB-deficient hippocampal neurons. Our results identify an important role of GABAAR-α3 in promoting gephyrin-mediated and CB-independent formation of inhibitory postsynapses. [ABSTRACT FROM AUTHOR]

The assembly of the postsynaptic transmitter sensing machinery at inhibitory nerve cell synapses requires the intimate interplay between cell adhesion proteins, scaffold and adaptor proteins, and g-aminobutyric acid (GABA) or glycine receptors. We developed an in vitro membrane system to reconstitute this process, to identify the essential protein components, and to define their mechanism of action, with a specific focus on the mechanism by which the cytosolic C terminus of the synaptic cell adhesion protein Neuroligin-2 alters the conformation of the adaptor protein Collybistin-2 and thereby controls Collybistin- 2-interactions with phosphoinositides (PtdInsPs) in the plasma membrane. Supported hybrid membranes doped with different PtdInsPs and 1,2-dioleoyl-sn-glycero-3-{[N-(5-amino- 1-carboxypentyl)iminodiacetic acid]succinyl} nickel salt (DGSNTA(Ni)) to allow for the specific adsorption of the His6-tagged intracellular domain of Neuroligin-2 (His-cytNL2) were prepared on hydrophobically functionalized silicon dioxide substrates via vesicle spreading. Two different collybistin variants, the WT protein (CB2SH3) and a mutant that adopts an intrinsically 'open' and activated conformation (CB2SH3/W24A-E262A), were bound to supportedmembranes in the absence or presence of His-cytNL2. The corresponding binding data, obtained by reflectometric interference spectroscopy, show that the interaction of the C terminus of Neuroligin-2 with Collybistin-2 induces a conformational change in Collybistin-2 that promotes its interaction with distinct membrane PtdInsPs. [ABSTRACT FROM AUTHOR]

Gephyrin is a central scaffold protein that mediates development, function, and plasticity of mammalian inhibitory synapses by interacting with various inhibitory synaptic proteins. Here, we showthat IQSEC3, a guanine nucleotide exchange factor for ARF6, directly interacts with gephyrin, an interaction that is critical for the inhibitory synapse localization of IQSEC3. Overexpression of IQSEC3 increases inhibitory, but not excitatory, synapse density in a guanine nucleotide exchange factor activity-dependent manner. Conversely, knock down of IQSEC3 decreases size of gephyrin cluster without altering gephyrin puncta density. Collectively, these data reveal that IQSEC3 acts together with gephyrin to regulate inhibitory synapse development. [ABSTRACT FROM AUTHOR]

The regulatory protein collybistin (CB) recruits the receptor-scaffolding protein gephyrin to mammalian inhibitory glycinergic and GABAergic postsynaptic membranes in nerve cells. CB is tethered to the membrane via phosphoinositides. We developed an in vitro assay based on solid-supported 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine membranes doped with different phosphoinositides on silicon/silicon dioxide substrates to quantify the binding of various CB2 constructs using reflectometric interference spectroscopy. Based on adsorption isotherms, we obtained dissociation constants and binding capacities of the membranes. Our results show that full-length CB2 harboring the N-terminal Src homology 3 (SH3) domain (CB2SH3+) adopts a closed and autoinhibited conformation that largely prevents membrane binding. This autoinhibition is relieved upon introduction of the W24A/E262A mutation, which conformationally "opens" CB2SH3+ and allows the pleckstrin homology domain to properly bind lipids depending on the phosphoinositide species with a preference for phosphatidyl-inositol 3-monophosphate and phosphatidylinositol 4-monophosphate. This type of membrane tethering under the control of the release of the SH3 domain of CB is essential for regulating gephyrin clustering. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cells (PEMFCs) are devices that attract the interest for a variety of applications including portable devices, transportation and stationary power. Several models are available in the literature concerning PEMFCs with different modelling approaches. In this paper, two representative dynamic models are examined, one using an electrical equivalent and one based on semi-empirical equations. Moreover, an enhanced model based on semi – empirical equations and a simplified transfer function representation for the dynamic response is proposed. All models can be easily incorporated in power system simulation software. Scope of this paper is to present a parametric analysis method in order to determine the ability of each model to represent accurately the steady – state as well as the slow and fast dynamics of a PEMFC. The influence of each specific parameter is investigated and the tuning procedure is described. Finally, simulation results are presented and the adaptability of all models is evaluated. [ABSTRACT FROM AUTHOR]