Antimikrobielle Wirkung verschiedener Substanzen auf artifiziell infiziertem Dentin

Die Infektion und die darauffolgende Desinfektion von Dentin in vitro ist die Voraussetzung für in vitro Prüfung von antibakteriell wirkenden Substanzen. Die dazu in der Literatur beschriebenen Verfahren weisen einige Nachteile auf, zum Beispiel, dass es sich bei der in vitro Infektion von Dentin um einen langwierigen Prozess von oft von mehreren Wochen handelt. Außerdem eignet sich nicht jede Bakterie für diese Versuche, die Infektionen gelingen nur im geringen Maße und sehr langsam. Enterococcus faecalis ist ein geeigneter Zielkeim, da er sich leicht identifizieren lässt. Er ist aerob und fakultativ anaerob, leicht zu kultivieren, nicht anspruchsvoll und von allen in den Versuchen verwendeten Bakterien bevölkert er die Dentinkanälchen am schnellsten. In der vorliegenden Arbeit wurde eine Methode entwickelt, um die Infizierung von Dentin zu beschleunigen. 200µm dicke Dentinscheiben wurden in Bottle Top Filtern fixiert. Mit Unterdruck, ausgeübt durch eine Vakuum-Membran-Pumpe, wurde Bakteriensuspension über einen Zeitraum von 4 Stunden durchgesaugt. 48h Stunden Inkubationszeit erschienen ausreichend, um eine Infektion der Dentinscheiben zu erhalten. Auf den so infizierten Dentinscheiben wurde die Wirkung von NaOCl 0,5%, 1,0%, 3,0% und CHX 0,2%. NaCl 0,9% diente als Kontrolle. Die Einwirkzeiten der Materialien betrugen 30sec und 10min. Die jeweilige Testsubstanz und die dazugehörige Kontrolle wurden immer auf der selben Dentinscheibe getestet. Auf diese Weise wurden Trägerobjekt für Test- und Kontrollsubstanz, bis zum Moment der Teilung in zwei Hälften und Auftragen der Substanzen, unter identischen Voraussetzungen behandelt, sie stellten eine Einheit dar. Alle Kontrollkulturen erreichten ungefähr eine optische Dichte von 1,200. Die gewonnenen Ergebnisse zeigten, dass die Wirkung antibakterieller Substanzen sowohl von der Einwirkzeit, als auch von der Höhe der Konzentration abhängig sind. Dies stimmt mit den Ergebnissen anderer Studien überein. Bei 30sec Einwirkzeit konnten die Testsubstanzen das Bakterienwachstum verlangsamen, jedoch nicht aufhalten. Das Bakterienwachstum erreichte letztendlich ähnliche OD-Werte wie die Kontrollkulturen, jedoch mit einer zeitlichen Verzögerung. Nach 10min Einwirkzeit der Testsubstanzen 0,5% NaOCl, 1,0% NaOCl und 0,2% CHX wurde das Bakterienwachstum im Vergleich zu den Ergebnissen nach 30sec Einwirkzeit zeitlich noch mehr verlangsamt. Doch auch nach 10min Desinfektion erreichten die Testkulturen letztendlich eine ähnliche optische Dichte wie die dazugehörigen Kontrollen. Nur die Testkulturen, deren Dentinplättchen mit 3,0% NaOCl über einen Zeitraum von 10 min behandelt wurden, wiesen keinerlei Bakterienwachstum auf. In kurzer Zeit kann eine dichte bakterielle Infektion von Rinderdentin erreicht werden, das mit in der täglichen Praxis verwendeten Agenzien wieder desinfiziert werden kann. Daraus kann geschlossen werden, dass sich die von uns erarbeitete Methode als ein geeignetes System zur artifiziellen Infektion des Dentins erwiesen hat

Intelligent assisted living framework for monitoring elders

Recently, Ambient Intelligence Systems (AmI) in particular Ambient Assisted Living (AAL) are attracting intensive research due to a large variety of application scenarios and an urgent need for elderly in-home assistance. AAL is an emerging multi-disciplinary paradigm aiming at exploiting information and communication technologies in personal healthcare and telehealth systems for countering the effects of growing elderly population. AAL systems are developed to help elderly people living independently by monitoring their health status and providing caregivers with useful information. However, strong contributions are yet to be made on context binding of newly discovered sensors for providing dynamic or/and adaptive UI for caregivers, as the existing solutions (including framework, systems and platforms) are mainly focused on checking user operation history, browser history and applications that are most used by a user for prediction and display of the applications to an individual user. The aim of this paper is to propose a framework for making the adaptive UI from context information (real-time and historical data) that is collected from caregivers (primary user) and elderly people (secondary user). The collected data is processed to produce the contextual information in order to provide assistive services to each individual caregiver. To achieve this, the proposed framework collects the data and it uses a set of techniques (including system learning, decision making) and approaches (including ontology, user profiling) to integrate assistive services at runtime and enable their bindings to specific caregivers, in so doing improving the adaptability parameter of UI for the AAL. © 2017 IEEE

Physics-Based and Retina-Inspired Technique for Image Enhancement

This paper develops a novel image/video enhancement technique that integrates a physics-based image formation model, the dichromatic model, with a retina-inspired computational model, multiscale model of adaptation. In particular, physics-based features (e.g. Power Spectral Distribution of the dominant illuminant in the scene and the Surface Spectral Reflectance of the objects contained in the image are estimated and are used as inputs to the multiscale model for adaptation. The results show that our technique can adapt itself to scene variations such as a change in illumination, scene structure, camera position and shadowing and gives superior performance over the original model

SIMCD: SIMulated crowd data for anomaly detection and prediction

Smart Crowd management (SCM) solutions can mitigate overcrowding disasters by implementing efficient crowd learning models that can anticipate critical crowd conditions and potential catastrophes. Developing an SCM solution involves monitoring crowds and modelling their dynamics. Crowd monitoring produces vast amounts of data, with features such as densities and speeds, which are essential for training and evaluating crowd learning models. By and large, crowd datasets can be classified as real (e.g., real monitoring of crowds) or synthetic (e.g., simulation of crowds). Using real crowd datasets can produce effective and reliable crowd learning models. However, acquiring real crowd data faces several challenges, including the expensive installation of a sensory infrastructure, the data pre-processing costs and the lack of real datasets that cover particular crowd scenarios. Consequently, crowd management literature has adopted simulation tools for generating synthetic datasets to overcome the challenges associated with their real counterparts. The majority of existing datasets, whether real or synthetic, can be used for crowd counting applications or analysing the activities of individuals rather than collective crowd behaviour. Accordingly, this paper demonstrates the process of generating bespoke synthetic crowd datasets that can be used for crowd anomaly detection and prediction, using the MassMotion crowd simulator. The developed datasets present two types of crowd anomalies; namely, high densities and contra-flow walking direction. These datasets are: SIMulated Crowd Data (SIMCD)-Single Anomaly and SIMCD-Multiple Anomalies for anomaly detection tasks, besides two SIMCD-Prediction datasets for crowd prediction tasks. Furthermore, the paper demonstrates the data preparation (pre-processing) process by aggregating the data and proposing new essential features, such as the level of crowdedness and the crowd severity level, that are useful for developing crowd prediction and anomaly detection models

SIMCD: SIMulated crowd data for anomaly detection and prediction

Smart Crowd management (SCM) solutions can mitigate overcrowding disasters by implementing efficient crowd learning models that can anticipate critical crowd conditions and potential catastrophes. Developing an SCM solution involves monitoring crowds and modelling their dynamics. Crowd monitoring produces vast amounts of data, with features such as densities and speeds, which are essential for training and evaluating crowd learning models. By and large, crowd datasets can be classified as real (e.g., real monitoring of crowds) or synthetic (e.g., simulation of crowds). Using real crowd datasets can produce effective and reliable crowd learning models. However, acquiring real crowd data faces several challenges, including the expensive installation of a sensory infrastructure, the data pre-processing costs and the lack of real datasets that cover particular crowd scenarios. Consequently, crowd management literature has adopted simulation tools for generating synthetic datasets to overcome the challenges associated with their real counterparts. The majority of existing datasets, whether real or synthetic, can be used for crowd counting applications or analysing the activities of individuals rather than collective crowd behaviour. Accordingly, this paper demonstrates the process of generating bespoke synthetic crowd datasets that can be used for crowd anomaly detection and prediction, using the MassMotion crowd simulator. The developed datasets present two types of crowd anomalies; namely, high densities and contra-flow walking direction. These datasets are: SIMulated Crowd Data (SIMCD)-Single Anomaly and SIMCD-Multiple Anomalies for anomaly detection tasks, besides two SIMCD-Prediction datasets for crowd prediction tasks. Furthermore, the paper demonstrates the data preparation (pre-processing) process by aggregating the data and proposing new essential features, such as the level of crowdedness and the crowd severity level, that are useful for developing crowd prediction and anomaly detection models

Cloud computing security taxonomy: From an atomistic to a holistic view

Countless discussions around security challenges affecting cloud computing are often large textual accounts, which can be cumbersome to read and prone to misinterpretation. The growing reliance on cloud computing means that not only should we focus on evaluating its security challenges but devote greater attention towards how challenges are viewed and communicated. With many cloud computing implementations in use and a growing evolution of the cloud paradigm (including fog, edge and cloudlets), comprehending, correlating and classifying diverse perspectives to security challenges increasingly becomes critical. Current classifications are only suited for limited use; both as effective tools for research and countermeasures design. The taxonomic approach has been used as a modeling technique towards classifying concepts across many domains. This paper surveys multiple perspectives of cloud security challenges and systematically develops corresponding graphical taxonomy based upon meta-synthesis of important cloud security concepts in literature. The contributions and significance of this work are as follows: (1) a holistic view simplifies visualization for the reader by providing illustrative graphics of existing textual perspectives, highlighting entity relationships among cloud entities/players thereby exposing security areas at every layer of the cloud. (2) a holistic taxonomy that facilitates the design of enforcement or corrective countermeasures based upon the source or origin of a security incident. (3) a holistic taxonomy highlights security boundary and identifies apt areas to implement security countermeasures

Understanding the coexistence of competing raptors by Markov chain analysis enhances conservation of vulnerable species.

Understanding ecological interactions among protected species is crucial for correct management to avoid conflicting outcomes of conservation planning. The occurrence of a superior competitor may drive the exclusion of a subordinate contestant, as in Sicily where the largest European population of the lanner falcon is declining because of potentially competing with the peregrine falcon. We measured the coexistence of these two ecologically equivalent species through null models and randomization algorithms on body sizes and ecological niche traits. Lanners and peregrines are morphologically very similar (Hutchinson ratios <1.3) and show 99% diet overlap, and both of these results predict competitive exclusion. In contrast, their use of diverse cliff substrates for breeding in different times of the season would predict coexistence. To compare these two mutually excluding hypotheses, we examined the pattern of inter-specific transitions in 88 sites that were studied for 14 years (2000-2013) using a Markov chain (MC) occupancy state model, and checked the sensitivity and elasticity of the community structure to changes in transition probabilities. During the study period, 1144 territorial transitions occurred in peregrine and lanner territories, and the MCs were predicted to converge to a stable equilibrium in 2065. Markovian analysis suggested that temporal and spatial segregation of habitat during reproduction might prevail over anatomical specialization for hunting and diet, allowing species coexistence, despite the prediction that peregrines will outnumber the lanners in future projections. Our approach combining niche-overlap analysis and species occupancy modelling led to practical information about conservation options available for the threatened lanner. Lanners are very sensitive to site abandonment, and measures increasing adult persistence in occupied territories could be more rewarding than those encouraging juvenile dispersal and colonization of new sites

Effects of structural environmental enrichment on welfare of juvenile seabream (Sparus aurata)

Current production systems of finfish aquaculture, and in particular intensive farming systems, can cause welfare problems leading not only to poor condition of the fish but also to a decrease in product quality. Adding structural environmental enrichment (EE) to bare rearing environments may improve the welfare of certain cultured fish. In this study we experimentally demonstrate the positive effects of adding structural EE on rearing environments of juvenile seabream (Sparus aurata). Fish maintained for 35 days with EE showed less aggression and interactions with the net pen, and lower erosion of pectoral and caudal fins, compared to fish kept in bare conditions (non-enriched, NE). In addition, EE modified the horizontal distribution of fish in the experimental cage, increasing the use of the inner areas. Non-significant effects of EE were observed on fish body condition and growth, and on brain monoamines levels and mortality. Nevertheless, this work highlights the potential use of structural EE to improve welfare of juvenile seabream, which might be feasible to apply at larger-commercial scale.Agência financiadora Aquicultura Balear S.A.U (Grupo Culmarex) Portuguese Foundation for Science and Technology UID/Multi/04326/2019 Spanish national funds from MINECO (R+D project: PHENOFISH) CTM2015- 69126-C2-1-Rinfo:eu-repo/semantics/publishedVersio

Helminth Communities of Owls (Strigiformes) Indicate Strong Biological and Ecological Differences from Birds of Prey (Accipitriformes and Falconiformes) in Southern Italy

We compared the helminth communities of 5 owl species from Calabria (Italy) and evaluated the effect of phylogenetic and ecological factors on community structure. Two host taxonomic scales were considered, i.e., owl species, and owls vs. birds of prey. The latter scale was dealt with by comparing the data here obtained with that of birds of prey from the same locality and with those published previously on owls and birds of prey from Galicia (Spain). A total of 19 helminth taxa were found in owls from Calabria. Statistical comparison showed only marginal differences between scops owls (Otus scops) and little owls (Athene noctua) and tawny owls (Strix aluco). It would indicate that all owl species are exposed to a common pool of 'owl generalist' helminth taxa, with quantitative differences being determined by differences in diet within a range of prey relatively narrow. In contrast, birds of prey from the same region exhibited strong differences because they feed on different and wider spectra of prey. In Calabria, owls can be separated as a whole from birds of prey with regard to the structure of their helminth communities while in Galicia helminths of owls represent a subset of those of birds of prey. This difference is related to the occurrence in Calabria, but not Galicia, of a pool of 'owl specialist' species. The wide geographical occurrence of these taxa suggest that local conditions may determine fundamental differences in the composition of local communities. Finally, in both Calabria and Galicia, helminth communities from owls were species-poor compared to those from sympatric birds of prey. However, birds of prey appear to share a greater pool of specific helmith taxa derived from cospeciation processes, and a greater potential exchange of parasites between them than with owls because of phylogenetic closeness