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PDF file - 101K, KSHV infection converts BOEC cells into spindle shape, and upregulates the expression of lymphatic endothelial markers

The oral cavity is a primary site of initial contact and entry for many viruses. Viral replication in the oral epithelium promotes viral shedding in saliva, allowing interpersonal transmission, as well as spread to other cell types, where chronic infection can be established.

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In the last couple of years, the rapid advances and decreasing costs of sequencing technologies have revolutionized transcriptomic research. Long-read sequencing (LRS) techniques are able to detect full-length RNA molecules in a single run without the need for additional assembly steps. LRS studies have revealed an unexpected transcriptomic complexity in a variety of organisms, including viruses. A number of transcripts with proven or putative regulatory role, mapping close to or overlapping the replication origins (Oris) and the nearby transcription activator genes, have been described in herpesviruses. In this study, we applied both newly generated and previously published LRS and short-read sequencing datasets to discover additional Ori-proximal transcripts in nine herpesviruses belonging to all of the three subfamilies (alpha, beta and gamma). We identified novel long non-coding RNAs (lncRNAs), as well as splice and length isoforms of mRNAs and lncRNAs. Furthermore, our analysis disclosed an intricate meshwork of transcriptional overlaps at the examined genomic regions. Our results suggest the existence of a ‘super regulatory center’, which controls both the replication and the global transcription through multilevel interactions between the molecular machineries.

Application of multiwall carbon nanotubes (MWCNT) as a filler component in composite materials can lead to remarkable increase in mechanical strength. It is a challenging application to form a living bone tissue biocomposite that is reinforced with MWCNTs at a dental implant—bone interface. The successful biointegration of MWCNT and the implant material depends on the processes of osseointegration, namely surface interactions at the molecular and cellular level. In this work the compatibility of MWCNT with main osseointegration processes has been overviewed with special attention to the toxicity of MWCNT for interacting human cells, and In Vitro experiments were performed with primary human osteoblast cells. The cells were isolated from oral bone fragments and grown in cell culture conditions. Plate wells were covered with MWCNT layers of three different densities. Osteoblast cell suspensions were placed onto the MWCNT layers and into empty plate wells. 24 and 72 hours after seeding the attachment and proliferation of cells was evaluated using Thiazolyl Blue Tetrazolium Bromide (MTT) colorimetric assay. The extent of cell death was characterized by Lactate Dehydrogenase (LDH) assay. The osteoblast cell viability tests show that cells were attached to all investigated surfaces, but with lower rate to higher density MWCNTs. A low level of cell death was observed in each sample type. Phase contrast and fluorescent microscopic observations show that although MWCNTs are not toxic for human primary osteoblast cells, an intense interaction of the cells with MWCNTs reduces their proliferation and markedly affects their morphology.

The immediate early viral protein replication and transcription activator (RTA) of Kaposi’s sarcoma-associated herpesvirus (KSHV) is essential for activating the lytic cycle of KSHV. RTA induces the KSHV lytic cycle by several mechanisms, acting as a viral transcription factor that directly induces viral and host genes and acting as a viral E3 ubiquitin ligase by degrading host proteins that block viral lytic replication. Recently, we have characterized the global gene expression changes in primary effusion lymphoma (PEL) upon lytic reactivation of KSHV, which also led to the identification of rapidly downregulated genes such as ID2, an inhibitor of basic helix-loop-helix transcription factors. Here, we demonstrate that ID2 overexpression in PEL ablates KSHV lytic reactivation, indicating that ID2 inhibits the KSHV lytic cycle. Furthermore, we show that while ID2 is highly expressed during latency, its protein level is rapidly reduced by 4 h postinduction during lytic reactivation. Our results indicate that RTA binds to ID2 and induces its degradation during the KSHV lytic cycle by N-terminal ubiquitination through the ubiquitin-proteasome pathway. Importantly, we found that not only KSHV RTA but also its Epstein-Barr virus (EBV) and murine gammaherpesvirus 68 (MHV68) homologs interact with ID2, and they can induce the degradation of all four members of the ID protein family, suggesting an evolutionarily conserved interplay between gammaherpesvirus RTAs and ID proteins. Taken together, we propose that ID2 acts as a repressor of the KSHV lytic cycle, which is counteracted by its RTA-mediated degradation. We also predict that ID proteins may act as restriction factors of the lytic phase of the other gammaherpesviruses as well. IMPORTANCE In addition to its transcription regulatory role, RTA is also known to have an E3 ubiquitin ligase activity, which RTA utilizes for inducing protein degradation. However, it is still largely unknown what host factors are downregulated during KSHV lytic reactivation by RTA-mediated protein degradation and what the biological significance of the degradation of these host factors is. In this study, we discovered that RTA employs N-terminal ubiquitination to induce degradation of ID2, a potent transcription repressor of host genes, via the ubiquitin-proteasome pathway to promote KSHV lytic reactivation in PEL cells. Furthermore, we found that not only KSHV RTA but also RTA of EBV and MHV68 gammaherpesviruses can induce the degradation of all four human ID proteins, indicating that the interplay between gammaherpesvirus RTAs and ID proteins is evolutionarily conserved.

The dysregulation of host signaling pathways plays a critical role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and viral pathogenesis. While a number of viral proteins that can block type I IFN signaling have been identified, a comprehensive analysis of SARS-CoV-2 proteins in the regulation of other signaling pathways that can be critical for viral infection and its pathophysiology is still lacking. Here, we screened the effect of 21 SARS-CoV-2 proteins on 10 different host signaling pathways, namely, Wnt, p53, TGFβ, c-Myc, Hypoxia, Hippo, AP-1, Notch, Oct4/Sox2, and NF-κB, using a luciferase reporter assay. As a result, we identified several SARS-CoV-2 proteins that could act as activators or inhibitors for distinct signaling pathways in the context of overexpression in HEK293T cells. We also provided evidence for p53 being an intrinsic host restriction factor of SARS-CoV-2. We found that the overexpression of p53 is capable of reducing virus production, while the main viral protease nsp5 can repress the transcriptional activity of p53, which depends on the protease function of nsp5. Taken together, our results provide a foundation for future studies, which can explore how the dysregulation of specific signaling pathways by SARS-CoV-2 proteins can control viral infection and pathogenesis.

Smart factories require location aware services such as asset tracking. These location aware services should be based on indoor positioning systems. Symbolic indoor positioning is considered as a classification task, where each category denotes a well-defined part of the building, such as a room or corridor. Hence, standard classifiers can be applied to symbolic indoor positioning. A topology-based classification evaluation method is presented that calculates the classification error based on the gravitational force between the symbolic positions denoted by categories. Three variants of the proposed topology-based method is evaluated and compared to the CRISP approach. The comparison was performed over a dataset recorded in a three-storey building whose topology is given in Indoor Geographic Markup Language format. Experimental results showed that the topology-based method gives a more detailed comparison of classifiers for indoor positioning than CRISP.

The biology of primary lytic Kaposi's sarcoma-associated herpesvirus (KSHV) infection is still not well understood, which is largely attributed to the lack of cell lines permissive to robust lytic KSHV infection in vitro. Our study demonstrates that primary human dermal lymphatic microvascular endothelial cells (HDLMEC) support lytic KSHV replication following de novo infection, resulting in robust KSHV production, indicating that HDLMECs are suitable for studying the regulation of primary lytic KSHV infection. Importantly, by utilizing lytically infected HDLMECs, we show for the first time that the KSHV latent genes LANA and viral cyclin are required for lytic replication during de novo lytic infection, a function of these latent genes that has not yet been recognized. Since Kaposi's sarcoma is considered to be originated from infected lymphatic endothelial cells, HDLMECs represent a valuable in vitro cell culture model for investigating lytic KSHV infection, which has been understudied in KSHV pathogenesis.

Prediction of economical growth is a complex task which is essential for planning sustainable economy. The economy has a wide range of indicators that are monitored and recorded by governments and international organizations. Agriculture is one of the most essential factors to modern day economical sustainability. The Food and Agriculture Organization keeps essential agricultural data sets which consist of records on production of crops and other agricultural products whose production strongly relates to the Gross Domestic Product of many countries. Assuming that total crop production and agricultural economy growth are highly related, the production of crops and total value of income from agriculture can be learnt by machine learning models. As data is recorded along an axis of time, it can be interpreted as a time series of various factors. Recurrent Neural Network excel in learning time series and sequential data. This paper presents experimental results on training various recurrent neural networks for modeling the changes of Agricultural and Gross Domestic Products. The paper details the data transformation, model building and model validation steps. Our experimental results showed that the models could achieve 85% accuracy.

Prediction and modeling of stock market changes attract not only economists and other scientific professionals, but the general public as well. With the rise of blockchain, and cryptocurrencies, the interest in stock trading has surged. Stock prices are precisely recorded in frequent fixed intervals, and this data is publicly available. Due to the outstanding performance of recurrent neural networks in sequential data modeling, recurrent networks can be applied to model the stock market. Although accurate prediction of the changes is not possible due to the stock market’s highly stochastic stochastic nature, a recurrent neural network could give a good approximation of trends. National Association of Securities Dealers Automated Quotations publishes stock values every few minutes, which data stream was used to model and predict changes. This paper presents a proof of concept implementation of a stock market price prediction system using recurrent neural networks and a continuous data stream.

The importance of proper hygienical behaivour is essential in today’s word especially during an ongoing pandemic. Wearing mask became mandatory in many countries during the COVID-19 Pandemic. Recognizing whether people are wearing masks is complicated image recognition task which could be facilitated and automated with machine learning techniques. Camera streams are widely available in indoor environments which can be used for object detection and image processing. Convolutional Neural Networks have been successfully applied in image classification and object recognition task in various application areas. There are already trained and openly available general purpose convolutional neural networks which can be used as an initial version for specific applications. A number of different image datasets are also available for research and industrial purposes. The InceptionV3 Neural Network architecture was used to tailored to determine whether a mask is being worn or not using transfer learning techniques, and convolutional neural networks. A variational autoencoder has also been trained to normalize the dataset with respect to skin colour, angle of the head and among other parameters. This paper describes the implementation of a mask recognition software using transfer learning, a convolutional neural network and a variational autoencoder.

It is still largely unknown what host factors are involved in controlling the expression of the lytic viral gene RTA during primary infection, which determines if Kaposi's sarcoma-associated herpesvirus (KSHV) establishes latent or lytic infection. We have recently identified the histone demethylase KDM2B as a repressor of RTA expression during both de novo KSHV infection and latency based on an epigenetic factor siRNA screen. Here, we report that surprisingly, KDM2B overexpression can promote lytic de novo infection by using a mechanism that differs from what is needed for its repressor function. Our study revealed that while the DNA-binding and demethylase activities of KDM2B linked to its transcription repressive function are dispensable, its C-terminal F-box and LRR domains are required for the lytic infection-inducing function of KDM2B. We found that overexpressed KDM2B increases the half-life of the AP-1 subunit c-Jun protein and induces the AP-1 signaling pathway. This effect is dependent upon the binding of KDM2B to the SKP1-CUL1-F-box (SCF) E3 ubiquitin ligase complex via its F-box domain. Importantly, the inhibition of AP-1 reduces KDM2B-mediated lytic de novo KSHV infection. Overall, our findings indicate that KDM2B may induce the degradation of some host factors by using the SCF complex resulting in the enrichment of c-Jun. This leads to increased AP-1 transcriptional activity, which facilitates lytic gene expression following de novo infection interfering with the establishment of viral latency.SignificanceThe expression of epigenetic factors is often dysregulated in cancers or upon specific stress signals, which often results in a display of non-canonical functions of the epigenetic factors that are independent from their chromatin-modifying roles. We have previously demonstrated that KDM2B normally inhibits KSHV lytic cycle using its histone demethylase activity. Surprisingly, we found that KDM2B overexpression can promote lytic de novo infection, which does not require its histone demethylase or DNA-binding functions. Instead, KDM2B uses the SKP1-CUL1-F-box (SCF) E3 ubiquitin ligase complex to induce AP-1 transcriptional activity, which promotes lytic gene expression. This is the first report that demonstrates a functional link between SFCKDM2B and AP-1 in the regulation of KSHV lytic cycle.

Background In this research the biomechanical properties of a bone model was examined. Porcine ribs are used as experimental model. The objective of this research was to investigate and compare the biomechanical properties of the bone model before and after implant placement. Methods The bone samples were divided in three groups, Group 1 where ALL-ON-FOUR protocol was used during pre-drilling and placing the implants, Group 2 where ALL-ON-FOUR protocol was used during pre-drilling, and implants were not placed, and Group 3 consisting of intact bones served as a control group. Static and dynamic loading was applied for examining the model samples. Kruskal–Wallis statistical test and as a post-hoc test Mann–Whitney U test was performed to analyze experimental results. Results According to the results of the static loading, there was no significant difference between the implanted and original ribs, however, the toughness values of the bones decreased largely on account of predrilling the bones. The analysis of dynamic fatigue measurements by Kruskal–Wallis test showed significant differences between the intact and predrilled bones. Conclusion The pre-drilled bone was much weaker in both static and dynamic tests than the natural or implanted specimens. According to the results of the dynamic tests and after a certain loading cycle the implanted samples behaved the same way as the control samples, which suggests that implantation have stabilized the skeletal bone structure.

Ion implantation has been a key technology in microelectronics and generally, for the controlled surface modification of materials for tribology, biocompatibility, corrosion resistance and many more. In this work in-situ spectroscopic ellipsometry was used for accurately tracking and on-line evaluating the accumulation of voids and damage in crystalline Ge during implantation of 200-keV Sb+ ions at a total fluence of 1016 cm− 2 using an ion flux of 2.1 × 1012 cm− 2s− 1. The phases of damage accumulation were identified using unique optical multi-layer models describing the layer structure and composition. The formation of initial partial disorder was followed by complete amorphization and void formation occurring at the fluence of 1 × 1015 cm− 2, reaching a high volume fraction of voids and a layer thickness of ≈ 200 nm by the end of the process. This agrees with numerical simulations and results of complementary measurements including ion beam analysis and electron microscopy. The developed in-situ method for controlling the dynamics of structural damage accumulation is a versatile ion-implantation tool for avoiding adverse void formation and for controlled evolution of subsurface nanocavities or cellular surface texture alike.

The development of machine learning over the years has facilitated the joint upsurge of complex cognitive infocommunication systems. Machine Learning methods are vital elements of modern cognitive infocommunications systems because they can be used in various ways such as behavior modeling or sentiment analysis. Machine Learning algorithms requires a reliable infrastructure and vast amount of data. Therefore building data warehouse systems is one of the essential steps of of building reliable cognitive infocommunication systems. Finding and preprocessing data streams of different origins are the first steps during the creation of a data warehouse. Unfortunately, online data streams are most often formatted uniquely. Therefore, the obtained data sets must be transformed into a unified data model. The modelling and conversion of data sources serves as a key step during the unification of heterogeneous data. Storage should be persistent, and optimized for the analytical processing of data. These requirements raise technological challenges that are not common during the design of data sources. This paper gives an overview of current data warehouse technologies and suggests an infrastructure implementation. Hive is used for accessing, modifying, and running complex analytics on the stored data sets. Economical data can often be unique to the product, or the industry it covers. Different data sources used unique data formats which were tailored for their application area or needs. Moreover, some of these data sources may change their format in time. Therefore, a flexible data transformation step is required which can be configured easily. The ETL processes of the data sources are implemented in Python, and Hive. The data is loaded in a Hive data warehouse which stores data in the distributed Hadoop File System.

Software development infrastructure allows communication between developers and it consists of a wide range of interconnected application specific tools which react events and communicate with themselves. These tools and their automation capabilities realize an intelligent system for software engineers which may be overlooked. Therefore, this infrastructure can be considered as a cognitive info-communication system. Teaching good communication practices and efficient usage of these tools is exceptionally important in higher education. Hence, software engineering capstone courses are essential part of education which are usually focused on methodologies, programming, communication or project management. Infrastructure is often assumed to be already established. On the other hand, development infrastructure is vital for many projects, evolve with time and contribute to the long term goals of software companies. Deployment of an efficient development infrastructure requires the integration of wide range of systems so it may not be available for recently started projects. Virtualization and cloud providers facilitates the deployment of complex software systems. This paper presents a virtual software development infrastructure that can be used in a classroom environment for mimic real development infrastructures.

Digital transformation is slow process in education which became an urgent topic in the spring of 2020 due to COVID-19. In mid March, the Hungarian Government closed the schools and universities and the classes were held in online form. This faced both students and teachers with unexpected challenges. Survey was conducted among the Computer Science and Information Technologist students of the Eszterhazy Karoly University at the end of the semester. Our survey was focused on the experience, feelings and overall expression of the students regarding to digital education and recent changes. Moreover, the survey contains questions about technical preparation and infrastructure. The responses are processed by well-known statistical data analysis tools. Based on the results, the students enjoyed the digital education and half of them are willing to continue it in the future. In addition, students would prefer to use their own devices during on tutorials which allow some changes in the labor environments. Unfortunately, some students had technical issues which may be caused by the heterogeneous software environment and can be solved with support material. Digital transformation was considered successful and the feedback will be integrated into our online classes.

The potential mechanical impact of different rotary systems used for root canal preparation has been a matter of debate for long. The aim of this study was to explore the incidence of dentinal cracks after root canal instrumentation with various rotary systems, in vitro. One hundred and eighty intact lower central incisors were selected and randomly divided into fourteen treatment groups (n = 12/group) and a control group (n = 12). After decoronation, the root canals were instrumented with fourteen different rotary systems (E3, E3 azure, NT2, Hyflex CM, Hyflex EDM, 2Shape, OneCurve, ProTaper Next, ProTaper Gold, WaveOne Gold, Mtwo, Reciproc Blue, TF adaptive, K3XF). All roots were horizontally sectioned at 3, 6, and 9 mm from the apex with a low-speed saw under water-cooling. The slices were then examined under stereomicroscope for dentinal cracks. No cracks were found in the control group. Cracks were found in all treatment groups, predominantly in the 3 mm slices. There was no statistically significant difference in the number of cracks when comparing the different systems to each other at any section level. At 3 mm, however, five of the studied systems, namely K3XF (p = 0.004), Protaper Next (p = 0.001), Reciproc Blue (p

In urban landscapes, humans are the most significant factor determining belowground diversity, including earthworms. Within the framework of the Global Urban Soil Ecology and Education Network (GLUSEEN), a multi-city comparison was carried out to assess the effects of soil disturbance on earthworms. In each of five cities (Baltimore, USA; Budapest, Hungary; Helsinki and Lahti, Finland; Potchefstroom, South Africa), covering four climatic and biogeographical regions, four habitat types (ruderal, turf/lawn, remnant and reference) were sampled. The survey resulted in 19 species belonging to 9 genera and 4 families. The highest total species richness was recorded in Baltimore (16), while Budapest and the Finnish cities had relatively low (5–6) species numbers. Remnant forests and lawns supported the highest earthworm biomass. Soil properties (i.e. pH and organic matter content) explained neither earthworm community composition nor abundance. Evaluating all cities together, earthworm communities were significantly structured by habitat type. Communities in the two adjacent cities, Helsinki and Lahti were very similar, but Budapest clearly separated from the Finnish cities. Earthworm community structure in Baltimore overlapped with that of the other cities. Despite differences in climate, soils and biogeography among the cities, earthworm communities were highly similar within the urban habitat types. This indicates that human-mediated dispersal is an important factor shaping the urban fauna, both at local and regional scales.

A formulation of linearized gravity in flat background, based on the Fierz tensor as a counterpart of the electromagnetic field strength, is discussed in detail and used to study fundamental properties of the linearized gravitational field. In particular, the linearized Einstein equations are written as first order partial differential equations in terms of the Fierz tensor, in analogy with the first order Maxwell equations. An energy-momentum tensor ($T_{\mathrm{lg}}^{ab}$) with favourable properties and exhibiting remarkable similarity to the standard energy-momentum tensor of the electromagnetic field is found for the linearized gravitational field. $T_{\mathrm{lg}}^{ab}$ is quadratic in the Fierz tensor (which is constructed from the first derivatives of the linearized metric), traceless, and satisfies the dominant energy condition in a gauge that contains the transverse traceless gauge. It is further shown that in suitable gauges, including the transverse traceless gauge, linearized gravity in the absence of matter has a duality symmetry that maps the Fierz tensor, which is antisymmetric in its first two indices, into its dual. Conserved currents associated with the gauge and duality symmetries of linearized gravity are also determined. These currents show good analogy with the corresponding currents in electrodynamics., Comment: 45 pages, revised manuscript, title change

In an increasingly urbanized world scientific research has shifted towards the understanding of cities as unique ecosystems. Urban land use change results in rapid and drastic changes in physical and biological properties, including that of biodiversity and community composition. Soil biodiversity research often lags behind the more charismatic groups such as vertebrates and plants. This paper attempts to fill this gap and provides an overview on urban isopod research. First, a brief overview on urban land use change is given, specifically on the major alterations on surface soils. Historical studies on urban isopods is summarized, followed by the status of current knowledge on diversity, distribution, and function of urban isopod species and communities. A review of more than 100 publications revealed that worldwide 50 cities and towns have some record of terrestrial isopod species, but only a few of those are city-scale explorations of urban fauna. A total of 110 isopod species has been recorded although the majority of them only once. The ten most frequently occurring isopods are widely distributed synanthropic species. Knowledge gaps and future research needs call for a better global dataset, long term monitoring of urban populations, multi-scale analyses of landscape properties as potential drivers of isopod diversity, and molecular studies to detect evolutionary changes.

Compositional changes in natural communities associated with anthropogenic influence often lead to localised extinctions and biodiversity loss. Soil invertebrates are also threatened by urbanisation due to habitat fragmentation, vegetation changes and management, soil alteration, degradation, and disappearing shelter sites. The aim was to assess terrestrial isopod (Oniscidea) assemblages in differently degraded urban forest patches of a metropolitan area (Budapest, Hungary). Study sites were compared by their species richness, composition and the relevant background factors (soil properties, dead wood, litter characteristics, and canopy closure). The degree of urban disturbance was expressed using an urbanisation index (UI) based on built-up density and vegetation cover. The isopods were identified to species level, and were qualified by their habitat preference and naturalness index (TINI). Average Rarity Index (ARI), derived from TINIs provided information on the degree of naturalness/disturbance of each habitat. Altogether 14 isopod species were collected from 23 sample sites. Urbanisation indirectly affected on the composition of isopod assemblages through the quantity of dead wood and soil plasticity. ARIs and UIs of sample sites were negatively correlated. Urban patches harboured habitat generalist, synanthropic and established introduced species with low naturalness value of assemblages. Areas with no or low anthropogenic disturbance maintained stable native, autochthonous assemblages that were characteristic of rural sites in the region. Transitional zones between rural and urban habitats usually maintained a mixed isopod fauna consisting of both urban and rural elements.

Failure of dental implants is caused mainly by peri-implant infections resulting in loss of supporting bone. Since there is no ideal therapy of peri-implantitis, the focus of research has been shifted toward better prevention and the development of antibacterial surfaces. In our study we examined the attachment and proliferation of primary epithelial and MG-63 osteosarcoma cells on Ti dental implants coated with photocatalytic nanohybrid films. Two polyacrylate resin based layers were investigated on commercially pure (CP4) Ti discs: 60 wt% TiO2/40 wt% copolymer and 60 wt% Ag-TiO2/40 wt% copolymer ([Ag] = 0,001 wt%). Surface properties were examined by scanning electron microscopy (SEM) and profilometry. Cell responses were investigated via dimethylthiazol-diphenyl tetrazolium bromide (MTT) and visualized with fluorescence microscopy. Profilometry revealed significant changes in surface roughness of TiO2 (Ra = 1.79 μm) and Ag-TiO2 layers (Ra = 5.76 μm) compared to the polished (Ra(P) = 0.13 μm) and sandblasted, acid-etched control surfaces (Ra(SA) = 1.26 μm). MTT results demonstrated that the attachment (24 h) of epithelial cells was significantly higher on the Ag-TiO2 coated samples (OD540 = 0.079) than on the polished control surfaces (OD540 = 0.046), whereas MG-63 cells did not show any difference in attachment between the groups. After one week, epithelial cells showed slightly increased survival as compared to MG-63 cells. The results suggest that the tested coatings are cytocompatible with epithelial cells, which means that they are not only antibacterial, but they also appear to be promising candidates for implantological use.

Implementation of Energy Performance Certificates (EPCs) varies significantly across EU Member States in terms of scope and available information, resulting in limited reliability, compliance, market penetration or user acceptance. This paper, therefore, investigates the end-user perspectives towards future development of EPCs to support EPC schemes in the EU. Without a full insight into what end-user's demand and need, it is impossible to make accurate assessments of how EPCs will become key drivers for deep renovation, environmental impact reduction and healthy buildings. A survey with 2563 end-users of EPCs was conducted on ten innovative EPC features in five EU countries (Denmark, Greece, Portugal, Poland, and Romania), including building owners and occupants to learn about their needs and expectations. The results highlight that the features are viewed most positively if homeowners or tenants are energy conscious and energy performance is an important aspect when buying or renting property. Furthermore, the insights gathered through the analysis of the survey provide suggestions for public authorities on how EPC methodologies could be customised to support the advancement of EPC schemes. Further work includes testing and validation of methodologies that are being developed in different EU Member States as a part of the H2020 X-tendo project.

Determination of indoor position is vital for the creation of smart environments. Symbolic indoor positioning algorithms determine the location as a well-defined part of the building, such as a roo...

An ontology based way finding algorithm is presented in this paper that allows route generation between two separate parts of an indoor environment. The presented ontology provides a flexible way to describe and model the indoor environment, in addition it fits and extends the existing model of the ILONA System. Ontology reasoners provide an efficient way to perform complex queries over the knowledge base. The instances, that are queried by the reasoner, are used to initialize the graph which represents an indoor environment. Due to parameterization of the reasoner, different graphs can be generated from the ontology which makes the way finding algorithm flexible. Thus, the task of indoor way finding was converted into a well-known graph search problem. Dijkstra’s shortest path algorithm is used for route generation in the graph yielded. The algorithm was implemented and tested in the ILONA System and its functioning is demonstrated by real-life scenarios.

Syntheses of highly ordered carbon nanotube (CNT) forests were studied from the aspect of the quality of CNTs and the properties of Fe-Co catalyst. CNT forests were grown by catalytic chemical vapor deposition. The amount of catalyst was varied in two ways: (1) catalyst layers with different nanostructure were produced with pulsed laser deposition by applying different argon pressures in the deposition chamber, and (2) compact catalyst layers were deposited with different thickness in 1–5 nm range. Our results show that both the nanostructure of the catalyst layer and the layer thickness have a significant role in the formation of catalytic particles, therefore also on the character of CNT growth.