Chemical Recycling of PET by Glycolysis: Polymerization and Characterization of the Dimethacrylated Glycolysate

Summary: In the framework of chemical recycling of polymers, leading to the generation of secondary value‐added products, PET flakes taken from post‐consumer soft drink bottles, were glycolyzed with DEG. The oligomers obtained were analyzed for their molecular weight and characterized by FT‐IR and POM. Subsequently, dimethacrylated oligoesters of PET glycolysate (PET‐GLY‐DMA) were synthesized by methacrylation of the glycolyzed PET product. The resulted monomer PET‐GLY‐DMA was studied by FT‐IR, POM and DSC. Thermal polymerization of this monomer was carried out at 80 °C in the presence of benzoyl peroxide as initiator. A UV‐curable formulation was also prepared on the basis of neat PET‐GLY‐DMA, as well as by mixing PET‐GLY‐DMA with styrene, using DMPA as photoinitiator. Nanoparticles of SiO₂ were dispersed into PET‐GLY‐DMA/styrene copolymers as reinforcing agents and the mechanical properties of resins formed were studied.

Preparation of methacrylated PET glycolysate.     

Analysis of the receiver response for a noncoaxial lidar system with fiber-optic output

The return signal of a noncoaxial lidar system with fiber-optic output is examined. The dependence of the overlap regions and the overlap factor of the system on the fiber diameter is calculated for several inclination angles between the laser beam and the optical receiver axes. The effect of central obstruction is included and both cases of Gaussian and quasi-Gaussian laser beam profiles are treated. The irradiance spatial distribution on the focal plane of the system is calculated and experimentally determined. Finally, an alignment procedure of the lidar system is described based on the comparison between the range-corrected lidar signal and the range-corrected exponentially attenuated Rayleigh backscattered coefficient.     

Late‐onset Pompe's disease in a hemodialysis patient: A first case report

A 37‐year‐old hemodialysis patient appeared with unusual somnolence during 2 successive hemodialysis sessions. Blood gas analysis revealed hypercapnic respiratory failure and spirometry restrictive lung disease. After exclusion of other causes of restrictive lung disease with chest CT‐scan and cerebrum MRI, electrophysiological study revealed myopathy. Because besides lordosis and limb‐girdle gait the patient was ambulant the possibility of late‐onset Pompe's disease was set and confirmed with evaluation of α‐glucosidase activity and genetic analysis. Enzyme replacement therapy (ERT) with aglucosidase alfa was started. Due to inaccessibility of veins in the arm without the arteriovenous fistula, during the last 1 year, the patient received the ERT through the venous line of the hemodialysis circuit. Three years later the patient remains ambulant without the need of any assistant device and preserved his pulmonary function. This is the first described case of late‐onset Pompe's disease in a hemodialysis patient treated with ERT.     

Search personalization through query and page topical analysis

Thousands of users issue keyword queries to the Web search engines to find information on a number of topics. Since the users may have diverse backgrounds and may have different expectations for a given query, some search engines try to personalize their results to better match the overall interests of an individual user. This task involves two great challenges. First the search engines need to be able to effectively identify the user interests and build a profile for every individual user. Second, once such a profile is available, the search engines need to rank the results in a way that matches the interests of a given user. In this article, we present our work towards a personalized Web search engine and we discuss how we addressed each of these challenges. Since users are typically not willing to provide information on their personal preferences, for the first challenge, we attempt to determine such preferences by examining the click history of each user. In particular, we leverage a topical ontology for estimating a user’s topic preferences based on her past searches, i.e. previously issued queries and pages visited for those queries. We then explore the semantic similarity between the user’s current query and the query-matching pages, in order to identify the user’s current topic preference. For the second challenge, we have developed a ranking function that uses the learned past and current topic preferences in order to rank the search results to better match the preferences of a given user. Our experimental evaluation on the Google query-stream of human subjects over a period of 1 month shows that user preferences can be learned accurately through the use of our topical ontology and that our ranking function which takes into account the learned user preferences yields significant improvements in the quality of the search results.     

Collaborative reputation mechanisms for electronic marketplaces

Members of electronic communities are often unrelated to each other, they may have never met and have no information on each other's reputation. This kind of information is vital in Electronic Commerce interactions, where the potential counterpart's reputation can be a significant factor in the negotiation strategy. Collaborative reputation mechanisms can provide personalized evaluations of the various ratings assigned to each user to predict their reliabilities. While these reputation mechanisms are developed in the context of electronic commerce, they are applicable in other types of electronic communities such as chatrooms, newsgroups, mailing lists, etc.     

Architecture and algorithms of the Xphone multimedia communication system

We describe the architecture and the algorithms used in Columbia University'sXphone multimedia communication system. The system assumes a best-effort operating system and network and provides facilities for call management, intra-application scheduling for the support of continuous data flow and integration with the windowing system, and synchronized video/audio acquisition/playback (locally or across a network) with minimized and bounded end-to-end delay. An algorithm based on time-stamps and device-state information is used for synchronization. The effects of jitter (delay variation) are mitigated with silence detection; the end-to-end delay is kept bounded by a restart mechanism. Finally, for live video sources, we describe a source bit-rate adaptation algorithm that maximizes the video image quality to the available network bandwidth and video display window size.     

Model-based segmentation and tracking of head-and-shoulder video objects for real time multimedia services

A statistical model-based video segmentation algorithm is presented for head-and-shoulder type video. This algorithm uses domain knowledge by abstracting the head-and-shoulder object with a blob-based statistical region model and a shape model. The object segmentation problem is then converted into a model detection and tracking problem. At the system level, a hierarchical structure is designed and spatial and temporal filters are used to improve segmentation quality. This algorithm runs in real time over a QCIF size video, and segments it into background, head and shoulder three video objects on average Pentium PC platforms. Due to its real time feature, this algorithm is appropriate for real time multimedia services such as videophone and web chat. Simulation results are offered to compare MPEG-4 performance with H.263 on segmented video objects with respects to compression efficiency, bit rate adaptation and functionality.