Purinergic receptors in ocular inflammation

Inflammation is a complex process that implies the interaction between cells and molecular mediators, which, when not properly 'tuned,' can lead to disease. When inflammation affects the eye, it can produce severe disorders affecting the superficial and internal parts of the visual organ. The nucleoside adenosine and nucleotides including adenine mononucleotides like ADP and ATP and dinucleotides such as P(1),P(4)-diadenosine tetraphosphate (Ap4A), and P(1),P(5)-diadenosine pentaphosphate (Ap5A) are present in different ocular locations and therefore they may contribute/modulate inflammatory processes. Adenosine receptors, in particular A2A adenosine receptors, present anti-inflammatory action in acute and chronic retinal inflammation. Regarding the A3 receptor, selective agonists like N(6)-(3-iodobenzyl)-5'-N-methylcarboxamidoadenosine (CF101) have been used for the treatment of inflammatory ophthalmic diseases such as dry eye and uveoretinitis. Sideways, diverse stimuli (sensory stimulation, large intraocular pressure increases) can produce a release of ATP from ocular sensory innervation or after injury to ocular tissues. Then, ATP will activate purinergic P2 receptors present in sensory nerve endings, the iris, the ciliary body, or other tissues surrounding the anterior chamber of the eye to produce uveitis/endophthalmitis. In summary, adenosine and nucleotides can activate receptors in ocular structures susceptible to suffer from inflammatory processes. This involvement suggests the possible use of purinergic agonists and antagonists as therapeutic targets for ocular inflammation.

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.

Dynamic patterns of flow in the workplace: characterizing within-individual variability using a complexity science approach

As a result of the growing interest in studying employee well-being as a complex process that portrays high levels of within-individual variability and evolves over time, this present study considers the experience of flow in the workplace from a nonlinear dynamical systems approach. Our goal is to offer new ways to move the study of employee well-being beyond linear approaches. With nonlinear dynamical systems theory as the backdrop, we conducted a longitudinal study using the experience sampling method and qualitative semi-structured interviews for data collection; 6981 registers of data were collected from a sample of 60 employees. The obtained time series were analyzed using various techniques derived from the nonlinear dynamical systems theory (i.e., recurrence analysis and surrogate data) and multiple correspondence analyses. The results revealed the following: 1) flow in the workplace presents a high degree of within-individual variability; this variability is characterized as chaotic for most of the cases (75%); 2) high levels of flow are associated with chaos; and 3) different dimensions of the flow experience (e.g., merging of action and awareness) as well as individual (e.g., age) and job characteristics (e.g., job tenure) are associated with the emergence of different dynamic patterns (chaotic, linear and random).

A dynamic analysis of asymmetric shocks in EU manufacturing

Available empirical evidence regarding the degree of symmetry between European economies in the context of Monetary Unification is not conclusive. This paper offers new empirical evidence concerning this issue related to the manufacturing sector. Instead of using a static approach as most empirical studies do, we analyse the dynamic evolution of shock symmetry using a state-space model. The results show a clear reduction of asymmetries in terms of demand shocks between 1975 and 1996, with an increase in terms of supply shocks at the end of the period.

Dynamic electrostatic force microscopy in liquid media

We present the implementation of dynamic electrostatic force microscopy in liquid media. This implementation enables the quantitative imaging of local dielectric properties of materials in electrolyte solutions with nanoscale spatial resolution. Local imaging capabilities are obtained by probing the frequency-dependent and ionic concentration-dependent electrostatic forces at high frequency (>1 MHz), while quantification of the interaction forces is obtained with finite-element numerical calculations. The results presented open a wide range of possibilities in a number of fields where the dielectric properties of materials need to be probed at the nanoscale and in a liquid environment.

Dynamic electrostatic force microscopy in liquid media

We present the implementation of dynamic electrostatic force microscopy in liquid media. This implementation enables the quantitative imaging of local dielectric properties of materials in electrolyte solutions with nanoscale spatial resolution. Local imaging capabilities are obtained by probing the frequency-dependent and ionic concentration-dependent electrostatic forces at high frequency (>1 MHz), while quantification of the interaction forces is obtained with finite-element numerical calculations. The results presented open a wide range of possibilities in a number of fields where the dielectric properties of materials need to be probed at the nanoscale and in a liquid environment.