Functionalisation of MWCNTs with poly(lauryl acrylate) polymerised by Cu(0)-mediated and RAFT methods

Poly(lauryl acrylate) P[LA] of various molar masses were prepared via reversible addition–fragmentation chain transfer (RAFT) polymerisation and Cu(0)-mediated radical polymerisation, for the purpose of improving the dispersion and interfacial adhesion of MWCNTs with polymers such as isotactic poly(propylene) (iPP). Lauryl acrylate (LA) was polymerised via RAFT to high conversion (95%), furnished polymers in good agreement with theoretical Mn with dispersity increasing with increasing Mn. LA polymerised via the Cu(0)-mediated method to full conversion (>98%), gave polymers in good agreement with theoretical Mn and low dispersity (Đ ≈ 1.2) for lower molar mass polymers. Low molar mass tailing was also observed for P[LA] via Cu(0)-mediated polymerisation for higher molar mass polymers. Thermogravimetric analysis (TGA) of P[LA] via RAFT showed an onset of degradation occurred at ≈340–350 °C, however, this decreased to ≈250–260 °C for lower molar mass polymers. TGA of the RAFT agent revealed an onset of degradation of ≈200–250 °C. Free radicals generated from thermal degradation of end groups did not influence the thermal stability of the P[LA] backbone and ‘unzipping’ commonly seen with methacrylates was not observed. TGA analysis of P[LA] via the Cu(0)-mediated method revealed a similar degradation profile to that of P[LA] via RAFT. The thermal stability of P[LA] is sufficient to allow for melt processing with iPP. P[LA] via RAFT mixed with MWCNTs showed an adsorption of ≈10–25 wt% P[LA] on to the MWCNTs. The onset of thermal degradation of the P[LA] remained unchanged after adsorption on to the MWCNTs. P[LA] via the Cu(0)-mediated method adsorbed up to 85 wt% and an increase in thermal stability of ≈50 °C was recorded. Increasing P[LA] and MWCNT concentration independently also resulted in an increase in the level of adsorption, possibility due to increased CH–π interaction. The difference in thermal stability could possibly be due to heat transfer from the P[LA] to the MWCNTs, resulting in delayed pyrolysis of P[LA]. Size exclusion chromatography (SEC) and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) of P[LA] after heating to 200 °C for 30 min in air showed loss of end groups but, the P[LA] backbone remained preserved for both polymer types. Evidence from transmission electron micrographs (TEM) shows the P[LA] adsorbing onto the MWCNT surface. Melt processing composites of P[LA] via Cu(0)-mediated with MWCNTs and iPP was possible as the P[LA] was thermally stable during the both extrusion and in the TGA when studied post melt mixing

Robots in machining

Robotic machining centers offer diverse advantages: large operation reach with large reorientation capability, and a low cost, to name a few. Many challenges have slowed down the adoption or sometimes inhibited the use of robots for machining tasks. This paper deals with the current usage and status of robots in machining, as well as the necessary modelling and identification for enabling optimization, process planning and process control. Recent research addressing deburring, milling, incremental forming, polishing or thin wall machining is presented. We discuss various processes in which robots need to deal with significant process forces while fulfilling their machining task

A vrtual sensor for online fault detection of multitooth-tools

The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases.Red de Supervision y Diagnosis de Sistemas Complejos (DPI2009-06124-E) of the Spanish Ministry of Science and Innovatio

The modification in measles vaccination age as a consequence of the earlier decline of transplacentally transferred antimeasles antibodies in Turkish infants

WOS: A1996VY85900014PubMed ID: 8982627The maternal antibodies are gradually decreased at 9 to 12 months in infants. We determined the elimination period of maternal measles antibodies in 34 infants whose mothers had had a history of natural measles previously. Seropositivity rates at sixth and nine months of age were found to be 61.8% and 3.4%, respectively. The very low passive antibody at nine months of age may suggest the measles vaccination could be carried out earlier than just before the critical age of antibody level

Effect on serum ECP, NO and MCP-1 level of specific immunotherapy in ashmatic children monosensitized to mite

62nd Annual Meeting of the American-Academy-of-Allergy-Asthma-and-Immunology -- MAR 03-07, 2006 -- Miami Beach, FLWOS: 000236263100046…Amer Acad Allergy, Asthma & Immuno

Enabling Pervasive Federated Learning using Vehicular Virtual Edge Servers

Recent works have proposed various distributed federated learning (FL) systems for the edge computing paradigm. These FL algorithms can assist pervasive applications in various aspects, e.g., decision making, pattern recognition, and behavior prediction. Existing solutions do not efficiently support the training based on the real-time location-specific data, because fundamentally, the \u27data collection\u27 problem is rarely studied in the context of FL systems. To address this problem, we present a novel system, VC-SGD (Vehicular Clouds-Stochastic Gradient Descent), which seamlessly integrates the emerging concept of vehicular clouds with an edge-based FL. We show that by using vehicular clouds as virtual edge servers, VC-SGD is able to effectively support FL algorithms that use real-time location-specific data. We develop a general simulator that uses SUMO to simulate vehicle mobility and MXNet to perform real training. We use our simulator to verify the efficacy of VC-SGD. The experimental results demonstrate that VC-SGD improves over existing solutions