1,750,149 research outputs found
Distributed human computation framework for linked data co-reference resolution
Full text linkDistributed Human Computation (DHC) is a technique used to solve computational problems by incorporating the collaborative effort of a large number of humans. It is also a solution to AI-complete problems such as natural language processing. The Semantic Web with its root in AI is envisioned to be a decentralised world-wide information space for sharing machine-readable data with minimal integration costs. There are many research problems in the Semantic Web that are considered as AI-complete problems. An example is co-reference resolution, which involves determining whether different URIs refer to the same entity. This is considered to be a significant hurdle to overcome in the realisation of large-scale Semantic Web applications. In this paper, we propose a framework for building a DHC system on top of the Linked Data Cloud to solve various computational problems. To demonstrate the concept, we are focusing on handling the co-reference resolution in the Semantic Web when integrating distributed datasets. The traditional way to solve this problem is to design machine-learning algorithms. However, they are often computationally expensive, error-prone and do not scale. We designed a DHC system named iamResearcher, which solves the scientific publication author identity co-reference problem when integrating distributed bibliographic datasets. In our system, we aggregated 6 million bibliographic data from various publication repositories. Users can sign up to the system to audit and align their own publications, thus solving the co-reference problem in a distributed manner. The aggregated results are published to the Linked Data Cloud
PONE-D-15-54606R2 / 10.1371/journal.pone.0155092
No full textThe included dataset was used to achieve conclusions in the paper entitled "Task and Resting-State fMRI Reveal Altered Salience Responses to Positive Stimuli in Patients with Major Depressive Disorder"
PONE-D-15-54606R2 / 10.1371/journal.pone.0155092
No full textThe included dataset was used to achieve conclusions in the paper entitled "Task and Resting-State fMRI Reveal Altered Salience Responses to Positive Stimuli in Patients with Major Depressive Disorder"
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Device architecture and characterization of organic and hybrid perovskite photovoltaic
Full text linkPhotovoltaic (PV), which converts sunlight into electricity, is a promising solution to the energy and environmental crisis we are facing right now. In this dissertation, we are focusing on next generation semiconductors as the photoactive materials, i.e. organic and orgainic/inorganic hybrid perovskite semiconductors, to achieve cost effective and energy efficient solar cell technology. Organic semiconductor always shows narrow absorption compared with the conventional inorganic semiconductors, which is one of the limiting factors of the organic photovoltaic (OPV). In the second chapter, we solve this problem by employing the multi-absorber bulk heterojunction (BHJ) device architecture, in which different polymer absorbers are blended together to cover panchromatic absorption. A comparison study reveals the working mechanism of this novel device, and the material selection rule is summarized. Eventually, the 8.7% power conversion efficiency is realized in ternary BHJ solar cell. Besides the narrow absorption, the organic BHJ layer is usually very thin (~100 nm) due to its limited carrier mobility, hence the absorption is insufficient in the photoactive layer. In the third chapter, we utilize the plasmonic effect of the metal nanoparticle to enhance the absorption of the OPVs. The addition of spectrally tuned SiO2-Au nanorods leads to improved photocurrent and device efficiency. On the other hand, the narrow absorption of organic materials also creates new device possibility that traditional semiconductor can't deliver. One of the good examples is the visibly semitransparent solar cells. In the fourth chapter, we develop this idea by engineering transparent top electrode and incorporate photonic distributed bragg reflector to further improve the device efficiency without compromising the visible transparency. Organic/inorganic hybrid perovskite semiconductor attracts incredible attentions in the past few years. It originates from the excitonic semiconductor family but delivers superior photovoltaic device performance than the typical excitonic solar cell e.g. dye sensitized solar cells and organic solar cells. However, the photophysics of this type of material is still mysterious in many aspects. In the fifth chapter, we try to understand its photophysical property by some basic characterization methods. We discover that the photo excitations in this materials varies with different crystal size. Besides, we observe the photoluminescence lifetime and intensity improve dramatically after exposing to the moisture. The improved photophysical property eventually results in greatly enhanced photovoltaic device performance. In addition to the solar cell, we successfully demonstrates the ultral high photodetectivity based on the perovskite materials, the results are included in sixth chapter
Micropattern technology applied to the in vitro study of the early embryonic development
No full textMicropattern technology, which enables control of cell and tissue architecture in vitro has been demonstrated as a useful and efficient tool for modeling the microenvironments at different scales and complexities. In the last 20 years, scientists have benefited a lot in revealing and dissecting the mechanism of communication between cells and the surrounding tissues and leading to the function from the breakthroughs in micropattern technology. Moreover, micropattern technology allows users to culture cells under well-defined geometric confinement by controlling cell shape, size, position, or multi-layered architecture. From the study of cell biology and developmental biology, we know that both geometric and mechanical cues present in the microenvironment affect cell behavior a lot. However, there is no possibility that we can test both these cues under standard tissue culture. Nowadays, many micropattern methods are available to address this problem at various scales. Generally speaking, these new methods provide a powerful platform for asking fundamental and mechanism questions in cell biology and tissue engineering, including cell survival, proliferation, differentiation, cell migration, cytokinesis, and cell polarity.
Human pluripotent stem cells (hPSCs), including embryonic stem cells (hESCs) and induced pluripotent stem cells (hiPSCs), are widely used in regenerative medicine as well as experimental model of normal and diseased organogenesis because of their nearly pluripotent differentiation potential into all cell lineages of all the three germ layers: endoderm, ectoderm and mesoderm germ layers. As we know, the differentiation fates of hPSCs are highly sensitive to local environmental factors that can modulate autocrine or paracrine signaling as well as mechanotransduction processes mediated by physical cues. Cell micropatterning encompasses a set of technical strategies that have been developed to spatially organize the geometry and location of a cell population with the purpose to control the local cellular microenvironment, such as cell-cell and cell-matrix interactions. In the context of hPSCs, cell micropattern has been employed to gain significant insights into how geometric and chemical cues modulate cell fates decision and cell organization into early embryonic differentiation patterns. At the same time, 2D and 3D micropatterned hPSCs have been used to control the colony size of multicellular patterns, which in turn will influence differentiation decisions into three germ layers. In recent years, numerous cell micropattern methods have been established and developed, but only very few, such as microcontact printing, micro-well culture, photo-patterning, and micro-stencil, have been successfully applied to micropatterned hPSCs. The challenge with micropatterned hPSCs lies in their fragility and a most stringent requirement of the microenvironment which include the specific extracellular matrix (ECM) and growth conditions for cell adhesion and survival.
To date, the use of micropattern has shown that the self-organization of hESCs can be influenced by both geometric and chemical cues and generate several ring-like cell populations of different cell-fates, similar to those observed at gastrulation. These self-organizing patterns emerge as a consequence of the interaction between receptor localization and the production of the BMP-inhibitor NOGGIN. This system represents an in vitro model ideally suited to reveal the complex interaction between signaling, fate, and shape, as well as explore symmetric-breaking events and the self-organization properties of pluripotent stem cells. In response to specific factors, for example, dual-Smad inhibitor and WNT inhibitor, the micropatterned hESCs can be differentiated into neural progenitors and primitive streak-like populations respectively. Interestingly, micropattern technology can also be applied to regenerative medicine, for example, the micropatterned organizer cells can be transplanted into the chicken embryo and subsequently induces a secondary axis which later initiates a neural fate in the host. As a conclusion, micropattern technology applied to the in vitro study can help us understand and reveal the secret of human embryonic development in various ways. In the meantime, more and more tissue engineering methods, include both 2-dimensional and 3-dimensional, will be established and combined with micropattern technology to develop a well-defined microenvironment, which will help people to generate more complex in vitro model.
Here in this thesis, we have established our micropattern technique by applying a fast and convenient surface functionalization procedure. By using different photomasks, we can make the micropatterns in various shapes, and sizes ranged from 50μm to 1000μm. Then a two-steps of surface Poly-L-lysine and ECM coating is necessary to generate the cell culture substrate. For the micropatterned cell culture, we tested and modified the protocol, and now we can harvest stable and well-formed cell colonies in culture for more than 8 days. With the purpose to investigate how the neural induction will be affected when under geometric confinement, we performed a micropatterned neural induction experiment by using a dual-Smad inhibitor neural induction protocol we have developed previously. In standard cell culture, it has been reported and demonstrated that the dual inhibitions of Smad signaling is highly efficient in the neural conversion of both hESCs and hiPSCs. The synergistic action of two inhibitors, SB431542 and NOGGIN, is sufficient to induce rapid (~6days) and complete (>80%) neural conversion under adherent culture conditions. Also in the same work, the future date suggested that the cell density, which means the initial seeding density, influences the outcome of cell fates of neural induction significantly: High seeding density promoted cell fate presents central nervous system while low seeding density promoted neural crest cell fate. So, we hypothesis that, our micropatterned neural induction platform could be useful to generate different cell fates located individually along the colony axis, and this different allocation could be an in vitro model to mimic the patterning of ectoderm. As we expected, we found that in the micropatterned neural induction colony, cells self-organized themselves into 3 main populations from inner to outer. In the center of the colony, cells showed a relatively low density and expressed both AP-2α and P75 (neural crest markers). On the contrary, cells outside expressed NESTIN, SOX1, and PAX6 (neural progenitor markers) and distributed as a ring structure between the center and border. This population presents a central nervous system cell fate. By comparing the cell density distributed form the center to the border, we found that the low density promotes neural crest cell fate in the center while high density promotes central nervous system cell fate outside, and the cells at the border had a more compact morphology and highly expressed only NESTIN, this cell population presents the surface ectoderm cell fate. General speaking, our micropatterned neural induction model can be used as an in vitro platform to mimic the human ectodermal patterning.
Later on, we extended our experimental model to establish an in vitro co-culture system with the purpose to investigate how the 3 germ layers communicate with each other during embryogenesis. During this period, a new hESCs-GFP cell line was established by Lentivirus infection, and it was used in the co-culture system to mark the cells of pre/sub seeded. To mimic the co-cultured mesodermal and endodermal cells, we developed a meso-endoderm differentiation protocol under standard cell culture condition, and this meso-endoderm population can be seeded on top of the neuroectoderm cell population to simulate the in vivo architecture. Interestingly, we found that the vast majority subsequently seeded meso-endoderm cells can only adhere to the border of neuroectoderm fate, and they arranged into a ring-like structure close to PAX6+ cells. This adhesion property may be determined by the intrinsic differences between specific cell fates of ectoderm. Moreover, we also found that when the meso-endoderm cells were co-cultured with neuroectoderm, a new cell population can be generated from sub-seeded cells, and they all co-expressed PAX6 but are not exist in meso-endoderm cell culture. Additionally, with 3 days’ co-culture, we surprisingly found some cells located above the PAX6+ neuroectoderm cells, and they showed a totally different cell morphology form other cell populations. It seems these cells were self-organized into a linear morphology and became the connecting cross-structure in this co-culture system. At all events, this co-culture system we developed has been demonstrated a robust platform in the study of interaction and communication between different germ layers.
To investigate the self-organization ability of subsequently seeded meso-endoderm, we next performed a micropatterned meso-endoderm cell culture. Briefly, we initiated meso-endoderm induction by applying the same protocol with 24 hours and then seeded this mixed population on the same micropatterns. To simulate the same condition, we repeated all the same seeding density, medium, and medium change for 3 days. Unexpectedly, the micropatterned meso-endoderm cells differentiated into distinct different cell populations with diverse morphologies. Generally, cells in the colony center showed a compact and multi-layered structure while cells at the border differentiated into many linear structures. As a conclusion, it is evident that the meso-endoderm cell fate has intrinsic self-organization property under geometric confinement, but how the organization is affected when co-cultured with neuroectoderm are still not clear. From this perspective, we are facing the opportunity and challenging at the same time, and more research activities are necessary for the coming future
Link services for linked data
No full textThis thesis investigated the concept of building link services as an extension of Linked Data to improve its navigability (thus improving the linking of the Web of Linked Data). The study first considered the Semantic Web URI and how an agent understands what a URI refers to when dereferencing it. As a result, a generic URI dereferencing algorithm was designed which can be used by any agent to consume Linked Data. The navigability of the Web of Linked Data was then defined - how an agent can follow the links to discover more data. To understand how the Web of Linked Data is connected, this study found 425 million across-datasets URIs (URIs link two different datasets and enable discoverability between datasets) on the Linked Data cloud and only 7.5% of resources are linked to non-local datasets. To improve the navigability of the Web of Linked Data, a list of link services was built. These link services are RESTful services, and takes a link as input and provides a RDF document as output with linking information of the requested URIs. They are: resolution service (retrieves the RDF description of the requested URI for agents), Link extraction service (extracts URIs from a RDF), Linkbase service (third party hosting link relations between datasets, especially for those data which were not originally linked), Reasoning service (applies rules of reasoning to generate a new RDF), Composition service (compose multiple RDF documents into one documents), and Link injection service (inject extra links relations into the client requested RDF document). To use link services, it is almost always requires multiple requests from the clients. Thus, to make the service transparent to the clients and to enable clients to orchestrate link services easily, a link service proxy was built that can be used from the client side with any Linked Data application. When clients request a URI via HTTP, the proxy injects link relations to the requested RDF documents on the fly, hence augmenting Linked Data. The link service proxy was evaluated using four services we built during the enAKTing project: PSI backlink service, sameAs co-reference service, geo-reasoning services, and a link injection service. This work showed that these services alone added 373 million across datasets foreign URIs, which almost doubles the previously mentioned 7.5% across-datasets foreign URIs coverage to the 14%. We also demonstrated how the linked service proxy works dynamically with the Web browser to enrich the Web of Linked Data. As all link services can be easily reused, and programmed to navigate theWeb of Linked Data as well as generating new link services, we believe this provides a basis for agents to consume Linked Data. Following this trend, the Linked Data consumers will only need to orchestrate or create the link services to consume the Web of Linked Data. Any other Web-based Linked Data applications can be understood as specialised services to be built on top of the link services
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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