Tunable Ka band filters based on graded barium strontium titanate (BST) have been investigated in terms of their associated parasitics, tunability, and temperature dependence of capacitance. The simulation results sho...
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The recent advance in SNP genotyping has made a significant contribution to reduction of the costs for large-scale genotyping. The development also has dramatically increased the size of the SNP genotype data. The inc...
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The recent advance in SNP genotyping has made a significant contribution to reduction of the costs for large-scale genotyping. The development also has dramatically increased the size of the SNP genotype data. The increase of the volume of the data, however, has posed a huge obstacle to the conventional analysis techniques that are typically vulnerable to the high-dimensionality problem. To address the issue, we propose a method that exploits two well-tested models: the document-term model and the transaction analysis model. The proposed method consists of two phases. In the first phase, we reduce the dimensions of the SNP genotype data by extracting significant SNPs through transformation of the data in lieu of the document-term model. In the second phase, we discover the association rules that signify the relations between the SNPs and the traits, through the application of the transactional analysis in the reduced-dimension genotype data. We validated the discovered rules through the literature survey. Experiments were also carried out using the HGDP panel data provided by the Foundation Jean Dausset-CEPH, which prove the validity of our new method for identifying appropriate dimensional reduction and associations of multiple SNPs and traits.
The development of rehabilitation engineering technologies such as the design of smart prosthetics necessitates a deep understanding of brain mechanisms engaged in ecological situations when human interact with new to...
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The development of rehabilitation engineering technologies such as the design of smart prosthetics necessitates a deep understanding of brain mechanisms engaged in ecological situations when human interact with new tools and/or environments. Thus, we aimed to investigate potential hemodynamic signatures reflecting the level of cognitive-motor performance and/or the internal or mental states of individuals when learning a novel tool with unknown properties. These markers were derived from functional Near Infrared Spectroscopy (fNIR) signals. Our results indicate an increased level of oxy-hemoglobin in prefrontal sensors associated with enhanced kinematics during early compared with late learning. This is consistent with previous neuroimaging studies that revealed a higher contribution of prefrontal areas during early compare to late adaptation learning. These non-invasive functional hemodynamic markers may play a role in bioengineering applications such as smart neuroprosthesis and brain monitoring where adaptive behavior is important.
K562 mammalian cells are sorted using a highly integrated microfabricated fluorescence-activated cell sorter (∝FACS). The sample cells are purified with an enrichment factor of 230 at a high throughput (> 1,000 ce...
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Recently, there have been lots of researches on how to provide personalized services to different users according to their personal characters, needs, situations, contexts and so on. Such personalized services are oft...
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Recently, there have been lots of researches on how to provide personalized services to different users according to their personal characters, needs, situations, contexts and so on. Such personalized services are often based on users' profiles provided by the users in the beginning, and users' records or experiences in using corresponding systems in certain periods. However, different systems or terminals collect user information independently and cannot share the user's personal information collected by these different systems/terminals. As a result, each system can only utilize the limited information collected by the system itself to provide services or recommendations, and it thus cannot meet what users' needs in varied situations across the different systems/terminals. Therefore, it is still an open issue on how to gather, share and utilize various kinds of personal information to effective personalized services in right time, right place and right means to users. In this paper, a case study for personalized pervasive learning is discussed as one typical application of the concept of Cyber-I, an individual's counterpart on the cyberspace. The Cyber-I aims to provide a better environment for users to obtain what they may really need on the Web, and it can be considered as an innovated possibility of web usage scenario in the near future. Our case study using pervasive devices (iPad, cell phone, and laptop) for learning issues can be regarded as the best practice to support the proposed Cyber-I.
Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most dea...
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Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most deadly disease that prone to misdiagnose. In general, some practitioners tend to “read” cancer in x-ray rontgen image as tumor this could be fatal. To generate a diagnose, a general practitioner use three kind of examination i.e : patient History, Radio logic examination, phisical examination. In this paper, Gray color for image indexing and retrieval are investigated. The features are derived based on the statistical distribution of Harralick feature from image sample. By utilizing the proposed invariant features, the similarity measure between query and database images provides reliable retrieval results.
The clinical data stored in the health information system can be categorized as two types including structuralized data and non-structuralized ones. In the paper, a data extraction system is developed to assist data r...
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There remains considerable interest in the behavior of acceptors in ZnO, the ultimate goal being the realization of device grade p-type material. Silver is a candidate acceptor, and, in this study, in situ doping of s...
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The use of MEMS to study the effect of mechanical compression on neurogenesis has been demonstrated. Polydimethylsiloxane-(PDMS)-based stretchable platforms were used on neurosphere assay to investigate the role of me...
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The use of MEMS to study the effect of mechanical compression on neurogenesis has been demonstrated. Polydimethylsiloxane-(PDMS)-based stretchable platforms were used on neurosphere assay to investigate the role of mechanical forces on the formation of radial glial processes, neuronal generation and migration. To induce mechanical compression on neurospheres, The PDMS culturing substrate is patterned with micron-sized wells. Neurospheres are cultured on the prestretched device. After 48 hours, when neurospheres are grown to the size of the well's width, the stretched substrate is released. The experimental results showed that applied mechanical compression on neural stem cells cultured as neurospheres could be a factor accelerating the radial glial formation, which is associated to neurogenesis and neuronal migration.
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