Pentaerythritol-zinc (penzinc) was prepared by a solid-phase reaction technique. The principal volatile products of the reaction between pentaerythritol and ZnO were analyzed with a coupled thermogravimetry-mass spectrometery system. The results indicated that a large amount of water was formed at the reaction temperature. Scanning electron microscopy (SEM) results showed the appearance of penzinc as flaky particles. Accordingly, the penzinc obtained through the dehydration between pentaerythritol and ZnO is likely to be a monopentaerythritol complex, such as zinc monoglycerolate. The thermal stability of poly(vinyl chloride) (PVC) with penzinc as a thermal stabilizer was investigated by a Congo Red test, Oven aging test and thermal gravimetric analysis (TGA). The Congo Red test showed the thermal stability time of PVC with penzinc was 38 min, longer than those with commercial thermal stabilizers. TGA indicated that the penzinc had little impact on the thermal degradation of PVC, but could increase the mass of residues. Oven aging test showed that the penzinc could significantly retard the discoloration during the long-term decomposition of PVC. Meanwhile, no ''zinc burning'' was observed in the PVC with penzinc. These results indicate that the penzinc is an excellent thermal stabilizer for rigid PVC.

Pentaerythritol-zinc (called Penzinc), which is a novel thermal stabilizer for PVC, was synthesized, and its performance was characterized during the thermal processing of PVC. The stabilization effects of this new stabilizer combined with calcium stearate (CaSt 2 ) and stearoyl benzoyl methane (b-diketone) were investigated using conductivity tests, thermal aging tests, and torque rheometry tests. The results revealed that the addition of Penzinc can improve the color and thermal stability of PVC in both static and dynamic tests. There are no obvious synergistic effects between Penzinc and CaSt 2 . However, the synergistic action between Penzinc and b-diketone is excellent. The thermal stability mechanisms of Penzinc and b-diketone are also discussed with the help of quantum chemical calculations.

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Acetonedicarboxylic acid diethyl ester (AADE) is obtained by the interaction of ethanol with acetonedicarboxylic acid that is prepared from anhydrous citric acid. The thermal stabilizing effect of calcium and zinc stearates (CaSt2/ZnSt2) combined with AADE on poly (vinyl chloride) (PVC) is evaluated by the Congo red test, conductivity test, thermal aging test, and thermogravimetric analysis. The results of thermal stability tests show that the addition of AADE can improve not only the thermal stability but also the color stability of PVC. The improvement in stabilizing effectiveness is ascribed to the synergistic effect between CaSt2/ZnSt2 and AADE. The thermal stability mechanism of AADE is also under discussion with the help of quantum chemical calculations. The results of quantum chemical calculations indicate that, besides having the ability to form complexes with zinc ion, AADE has an evident tendency to replace the allyl chloride of the PVC. The results of the thermal aging test and quantum chemical calculations show that the thermal stabilizing effectiveness of AADE is higher than that of stearoyl benzoyl methane (β‐Diketones). J. VINYL ADDIT. TECHNOL., 21:228–234, 2015. © 2014 Society of Plastics Engineers

Abstract-In this paper, we propose a novel computer vision based fall detection system for monitoring an elderly person in a home care, assistive living application. Initially, a single camera covering the full view of the room environment is used for the video recording of an elderly person's daily activities for a certain time period. The recorded video is then manually segmented into short video clips containing normal postures, which are used to compose the normal dataset. We use the codebook background subtraction technique to extract the human body silhouettes from the video clips in the normal dataset and information from ellipse fitting and shape description, together with position information, is used to provide features to describe the extracted posture silhouettes. The features are collected and an online one class support vector machine (OCSVM) method is applied to find the region in feature space to distinguish normal daily postures and abnormal postures such as falls. The resultant OCSVM model can also be updated by using the online scheme to adapt to new emerging normal postures and certain rules are added to reduce false alarm rate and thereby improve fall detection performance. From the comprehensive experimental evaluations on data sets for 12 people, we confirm that our proposed personspecific fall detection system can achieve excellent fall detection performance with 100% fall detection rate and only 3% false detection rate with the optimally tuned parameters. This work is a semi-unsupervised fall detection system from a system perspective because although an unsupervised type algorithm (OCSVM) is applied, human intervention is needed for segmenting and selecting of video clips containing normal postures. As such, our research represents a step towards a complete unsupervised fall detection system. Index Terms-Health care, assistive living, fall detecMiao Yu, Adel Rhuma, Syed Mohsen Naqvi and Jonathon Chambers are with School of Electronic, Electrical and Systems Engineering, Loughborough University, UK, e-mails: (m.yu, a.rhuma, s.m.r.naqvi, j.a.chambers)@lboro.ac.uk.+ Yuanzhang Yu is with the Shandong