Synthesis and characterisation of fluorescent pyrene‐end‐capped polylactide fibres

Fluorescent markers are critical for tracking the position and movement of molecules both in vivo and in vitro. Conventionally, synthetic dyes are non‐covalently added to polymers for fluorescent tracking, but often diffuse away. Here we demonstrate, for the first time, a facile method for the synthesis of fluorescent poly(lactic acid) nano‐/microfibres for biomedical applications using solution spin blowing. Pyrene‐end‐capped poly(l ‐lactide) (PLLA) derivatives were synthesised using the ring‐opening polymerisation of l ‐lactide and they were characterised using spectroscopic and thermal analyses. Submicrometre‐sized fluorescent fibres were produced from these PLLA derivatives using solution blow spinning techniques generating polymer blends and core–shell fibres. Such system could be further exploited to incorporate electrically conductive carbon allotropes via the pyrene aromaticity, producing fluorescent and electrically active fibres for in vitro monitoring and electrical stimulation. © 2018 Society of Chemical Industry     

Porous shell/dense core structures prepared in tungsten phosphate glass through template-free route

The preparation of the 11.7Li₂O–39.7WO₃–10.9CaO–37.7P₂O₅ glass (pgLWCP) was based on a one-step heat treatment of the 6Li₂O–18WO₃–43CaO–33P₂O₅ (gLWCP) glass followed by leaching of the β-Ca₂P₂O₇ phase formed during the crystallization process. The porous structure was formed in the region formerly occupied by the β-Ca₂P₂O₇ phase. The gLWCP undergoes devitrification through surface crystallization. This process occurs after a thermal treatment in lower temperature and in a shorter period of time than that required for the complete crystallization. After acid leaching treatment, we obtained a core-/shell-like structure with a very well-defined dense glass (gLWCP)/porous glass (pgLWCP) interface. The pgLWCP exhibits reversible coloration–decoloration reactions.     

Experimental campaign,modeling, and sensitivity analysis for the molecular distillation of petroleum residues 673.15 K+

This research activity proposes a sensitivity analysis of the molecular distillation process by focusing the attention on the response of the overall distillate flow rate under several conditions of distillation temperature and feed flow rate. Specific equations to characterize physicochemical properties of petroleum residues have been formulated by means of ASTM-based experimental campaigns combined with specific optimization techniques.     

Text entry for the Blind on Smartwatches

Universal Access in the Information Society - The interaction challenges presented by touch-screen enabled devices for blind and visually impaired people has been addressed extensively in the...     

An adaptive potential for robust shape estimation

This paper describes an algorithm for shape estimation in cluttered scenes. A new image potential is defined based on strokes detected in the image. The motivation is simple. Feature detectors (e.g. edge points detectors) produce many outliers, which hamper the performance of boundary extraction algorithms. To overcome this difficulty we organize edges in strokes and assign a confidence degree (weight) to each stroke. The confidence degrees depend on the distance of the stroke points to the boundary estimates and they are updated during the estimation process. A deformable model is used to estimate the object boundary, based on the minimization of an adaptive potential function which depends on the confidence degree assigned to each stroke. Therefore, the image potential changes during the estimation process. Both steps (weight update, energy minimization) are derived as the solution of a maximum likelihood estimation problem using the EM algorithm.Experimental tests are provided to illustrate the performance of the proposed algorithm.     

Applying machine learning techniques for scaling out data quality algorithms in cloud computing environments

Deduplication is the task of identifying the entities in a data set which refer to the same real world object. Over the last decades, this problem has been largely investigated and many techniques have been proposed to improve the efficiency and effectiveness of the deduplication algorithms. As data sets become larger, such algorithms may generate critical bottlenecks regarding memory usage and execution time. In this context, cloud computing environments have been used for scaling out data quality algorithms. In this paper, we investigate the efficacy of different machine learning techniques for scaling out virtual clusters for the execution of deduplication algorithms under predefined time restrictions. We also propose specific heuristics (Best Performing Allocation, Probabilistic Best Performing Allocation, Tunable Allocation, Adaptive Allocation and Sliced Training Data) which, together with the machine learning techniques, are able to tune the virtual cluster estimations as demands fluctuate over time. The experiments we have carried out using multiple scale data sets have provided many insights regarding the adequacy of the considered machine learning algorithms and proposed heuristics for tackling cloud computing provisioning.     

A fuzzy queue-aware routing approach for wireless mesh networks

Recent advances in Wireless Mesh Networks (WMNs) have overcome the drawbacks of traditional wired and ad-hoc networks and now they are seen as a means of allowing last mile communications with quality level assurance in Future Multimedia Systems. However, new routing schemes are needed to provide end-to-end Quality of Service (QoS) and Quality of Experience (QoE) support for delay/loss/jitter-sensitive multimedia applications. The well-known OLSR (Optimized Link State Routing) protocol with ETX (Expected Transmission Count) metric brings many benefits to the path selection process, but has a drawback with regard to queue availability management, which reduces the system performance. This problem is caused when OLSR-EXT control messages are exchanged and the queues of mesh routers along the end-to-end communication path are overloaded. As a result, multimedia-related packets will suffer from loss/delay/jitter and the overall system performance will decrease. This paper proposes the Optimized Link State Routing-Fuzzy ETX Queue (OLSR-FEQ) protocol to overcome the limitations of OLSR-ETX regarding queue availability, QoS and QoE assurance. OLSR-FEQ optimizes network and user-based parameters by coordinating queue availability, QoS and fuzzy issues in the routing decision process as a way of allocating the best paths for multimedia applications. Performance evaluations were carried out with the Network Simulator (NS-2.34) to show the benefits of the proposed solution when compared with existing routing schemes, namely OLSR-ETX, OLSR-FLC, OLSR-MD and HWMP (IEEE 802.11s standard), regarding QoS (unsuccessful packet delivery and throughput) and QoE (PSNR, SSIM, VQM and MOS) parameters.     

A neural network with asymmetric basis functions for feature extraction of ECG P waves.

In this work a simple neural network with asymmetric basis functions is proposed as a feature extractor for P waves in electrocardiographic signals (ECG). The neural network is trained using the classical backward-error-propagation algorithm. The performance of the proposed network was tested using actual ECG signals and compared with other types of neural feature extractors.     

Amygdaloid lesion increases the toxicity of intrahippocampal kainic acid injection and reduces the late occurrence of spontaneous recurrent seizures in rats

Spontaneous recurrent seizures (SRS) following intrahippocampal kainic acid (KA) injection have been described in a previous paper from our laboratory. The SRSs are clinically similar to the seizures induced by kindling the amygdala and we suggested that the amygdala plays a role in initiating the SRSs. Accordingly, the present paper examines the effect of amygdaloid lesions on intrahippocampal KA-treated rats. There were short- and long-term effects. (1) Short-term: the toxicity of KA was increased in lesioned animals. Status epilepticus followed by death of the animals was evoked with half of the dose required to cause the same effect in intact rats. Moreover, a gross haematuria was encountered 6-12 h after KA injection. This was not observed in non-lesioned rats even following the highest KA doses. (2) Long-term: amygdaloid lesions delayed the occurrence of the SRSs, reduced their incidence and modified their expression. In lesioned animals seizures began with a period of tonic immobility with no sign of the masticatory movements seen in intact animals. Histological examination of the KA-induced lesions did not show any major differences between lesioned and intact animals. It is suggested that the short-term effects are due to an unspecific effect on homeostatic mechanisms, whereas the long-term ones reflect a specific involvement of the amygdala in the late appearing seizures.