1,077 research outputs found
A Survey of Methods and Input Data Types for House Price Prediction: Literature list
No full textGeneral file description
This xlsx document contains the literature list that forms the basis of the paper 'A Survey of Methods and Input Data Types for House Price Prediction' by Geerts, M., vanden Broucke, S. and De Weerdt, J. The Excel document contains seven sheets, relating to the phases described in the survey.
Phase3
This sheet contains the literature list for the end of Phase 2 and the start of Phase 3. It has 590 rows and 19 columns. Each row contains the citation information of one article. The columns describe the ID, Authors, Title, Year, Source title, Volume, Issue, DOI, ISSN, ISBN, PubMed, Publisher, Document Type, Language, Keywords, Link, Book DOI, Algorithmic (Title) and Algorithmic (Abstract). The latter two columns are used to indicate whether the articles describe an algorithmic approach to predict house prices based on the title and the abstract respectively. These two columns take the values 'Yes', 'No', and 'Maybe', and were completed during Phase 3.
Phase4
This sheet contains the literature list for the end of Phase 3 and the start of Phase 4. It has 116 rows and 20 columns. Each row contains the citation information of one article. The columns describe the ID, Authors, Title, Year, Source title, Volume, Issue, DOI, ISSN, ISBN, PubMed, Publisher, Document Type, Language, Keywords, Link, Book DOI, Algorithmic (Title), Algorithmic (Abstract) and Reading. All columns are the same as in the first sheet, except for the three last columns. The columns Algorithmic (Title) and Algorithmic (Abstract) now only contain the value 'Yes' as only the articles that describe an algorithm are retained in Phase 3. The column Reading describes the outcome of Phase 4. This columns is empty if the article is retained in this phase and describes the reason if it is not retained.
Phase4(end)
This sheet contains the literature list for the end of Phase 4. It has 94 rows and 20 columns. Each row contains the citation information of one article. The columns describe the ID, Authors, Title, Year, Source title, Volume, Issue, DOI, ISSN, ISBN, PubMed, Publisher, Document Type, Language, Keywords, Link, Book DOI, Algorithmic (Title), Algorithmic (Abstract) and Reading. All columns are the same as in the second sheet. The column Reading is now empty because the articles that were not retained in Phase 4 are removed from the list.
Data table
This sheet contains a table of the literature at the end of Phase 4 with indications of input data types used in the articles, the data novelty score and the cluster that the articles belong to. It has 95 rows, where each row contains the information of one article, except the last 'Total' row. It contains 21 columns :
ID: This is the same identifier as in the previous sheets.
Column1: This is a new identifier, based on an ordering on year and author.
Authors: Same as before.
Title: Same as before.
Year: Same as before.
Structural, Temporal data, Socioeconomic, Environmental, POI, Basic spatial, Location, Eucl Distances, Adv Spatial, Network Distance, Topographical data, Graphs, Images, Text: These are the different input data types. The cell is filled with 'X' if the corresponding article is using the input data type described in the column name.
Score: This column indicates the data novelty score, calculated as explained in the paper based on the sheet 'Rules Data novelty score'.
Cluster: This column indicates the cluster number as explained in the Discussion section of the paper.
Rules Data novelty score
This sheet contains 15 rows, of which the first contains the titles, and two columns. The first columns contains the input data types as in the previous sheet and the second column contains the respective novelty scores.
Model table
This sheet contains a table of the literature at the end of Phase 4 with indications of model types used in the articles, the model novelty score and the cluster that the articles belong to. It has 95 rows, where each row contains the information of one article, except the last 'Total' row. It contains 21 columns :
ID: Same as before.
Column1: Same as before
Authors: Same as before.
Title: Same as before.
Year: Same as before.
MRA, Kriging, SEM, SVC, Time Series, FL, NN, DT, RF, GBT, SVM, ANN, (Other) Ensembles, DL: These are the different model types. The cell is filled with 'X' if the corresponding article is using the model type described in the column name.
Score: This column indicates the model novelty score, calculated as explained in the paper based on the sheet 'Rules Model novelty score'.
Cluster: This column indicates the cluster number as explained in the Discussion section of the paper.
Rules Model novelty score
This sheet contains 15 rows, of which the first contains the titles, and two columns. The first columns contains the model types as in the previous sheet and the second column contains the respective novelty scores
A method for in situ SEM fracture studies of brittle materials using the double torsion technique : application to nuclear graphite
No full textThis work concerned the design and development of a miniature double torsion (DT) testing rig, for use inside the chamber of a scanning electron microscope, to perform in situ loading studies of brittle materials using the DT fracture mechanics specimen. The in situ performance of the system inside the SEM was highly satisfactory, while still providing free rotation of the attached stepper motor. Crack growth rates of down to 19nm/s were directly observed in PMMA specimens. It was concluded that the technique displayed merit in its ability to contribute to the knowledge base of slow cracking and damage development in brittle materials, with the advantage being that the gearing ratios of the current device resulted in slower specimen loading rates, which were more controlled, than reported previously
Modelling tidal sandbank dynamics and impacts of sand extraction in sediment-scarce environments:Literature report
Get PDFU-Sem, a platform for augmented user modelling
No full textWith the increasing popularity of social media, more and more user data is published on the web everyday. As a result, there is a high demand for engineers to devise different algorithms for user modelling based on that data. The U-Sem framework defines an approach for constructing such algorithms and providing them to the customers in the form of user modelling services. The process of building these services, however, requires engineers to perform a lot of manual tasks, many of which are not connected to the core of the engineers’ specialization. These tasks are considered as significant overhead and are reported to cause poor performance of engineers. Therefore, in order to solve that problem, in this thesis we present the design and implementation of the U-Sem platform. It extends the U-Sem idea for building user modelling services by providing a platform that facilitates the work of the engineers. Based on the analysis of the current process for building U-Sem services we solve the two problems which solutions were indicated to be the most beneficial for the engineers. The first one is to enable engineers to add and remove the functional components that build up the services to/from the platform on demand without affecting the work of others using it. While the second problem is to enable engineers to create and process the persistent data required for the services transparently without being aware of where and how it is actually stored.Computer ScienceSoftware and Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc
Heterogeneous and tissue-specific regulation of effector T cell responses by IFN-gamma during Plasmodium berghei ANKA infection.
Get PDFIFN-γ and T cells are both required for the development of experimental cerebral malaria during Plasmodium berghei ANKA infection. Surprisingly, however, the role of IFN-γ in shaping the effector CD4(+) and CD8(+) T cell response during this infection has not been examined in detail. To address this, we have compared the effector T cell responses in wild-type and IFN-γ(-/-) mice during P. berghei ANKA infection. The expansion of splenic CD4(+) and CD8(+) T cells during P. berghei ANKA infection was unaffected by the absence of IFN-γ, but the contraction phase of the T cell response was significantly attenuated. Splenic T cell activation and effector function were essentially normal in IFN-γ(-/-) mice; however, the migration to, and accumulation of, effector CD4(+) and CD8(+) T cells in the lung, liver, and brain was altered in IFN-γ(-/-) mice. Interestingly, activation and accumulation of T cells in various nonlymphoid organs was differently affected by lack of IFN-γ, suggesting that IFN-γ influences T cell effector function to varying levels in different anatomical locations. Importantly, control of splenic T cell numbers during P. berghei ANKA infection depended on active IFN-γ-dependent environmental signals--leading to T cell apoptosis--rather than upon intrinsic alterations in T cell programming. To our knowledge, this is the first study to fully investigate the role of IFN-γ in modulating T cell function during P. berghei ANKA infection and reveals that IFN-γ is required for efficient contraction of the pool of activated T cells
Acute Ethanol Administration Rapidly Increases Phosphorylation of Conventional Protein Kinase C in Specific Mammalian Brain Regions in Vivo
Get PDFBackground
Protein kinase C (PKC) is a family of isoenzymes that regulate a variety of functions in the central nervous system including neurotransmitter release, ion channel activity, and cell differentiation. Growing evidence suggests that specific isoforms of PKC influence a variety of behavioral, biochemical, and physiological effects of ethanol in mammals. The purpose of this study was to determine whether acute ethanol exposure alters phosphorylation of conventional PKC isoforms at a threonine 674 (p-cPKC) site in the hydrophobic domain of the kinase, which is required for its catalytic activity.
Methods
Male rats were administered a dose range of ethanol (0, 0.5, 1, or 2 g/kg, intragastric) and brain tissue was removed 10 minutes later for evaluation of changes in p-cPKC expression using immunohistochemistry and Western blot methods.
Results
Immunohistochemical data show that the highest dose of ethanol (2 g/kg) rapidly increases p-cPKC immunoreactivity specifically in the nucleus accumbens (core and shell), lateral septum, and hippocampus (CA3 and dentate gyrus). Western blot analysis further showed that ethanol (2 g/kg) increased p-cPKC expression in the P2 membrane fraction of tissue from the nucleus accumbens and hippocampus. Although p-cPKC was expressed in numerous other brain regions, including the caudate nucleus, amygdala, and cortex, no changes were observed in response to acute ethanol. Total PKC? immunoreactivity was surveyed throughout the brain and showed no change following acute ethanol injection
Proline-rich tyrosine kinase 2 mediates gonadotropin-releasing hormone signaling to a specific extracellularly regulated kinase-sensitive transcriptional locus in the luteinizing hormone beta-subunit gene
Get PDFG protein-coupled receptor regulation of gene transcription primarily occurs through the phosphorylation of transcription factors by MAPKs. This requires transduction of an activating signal via scaffold proteins that can ultimately determine the outcome by binding signaling kinases and adapter proteins with effects on the target transcription factor and locus of activation. By investigating these mechanisms, we have elucidated how pituitary gonadotrope cells decode an input GnRH signal into coherent transcriptional output from the LH beta-subunit gene promoter. We show that GnRH activates c-Src and multiple members of the MAPK family, c-Jun NH2-terminal kinase 1/2, p38MAPK, and ERK1/2. Using dominant-negative point mutations and chemical inhibitors, we identified that calcium-dependent proline-rich tyrosine kinase 2 specifically acts as a scaffold for a focal adhesion/cytoskeleton-dependent complex comprised of c-Src, Grb2, and mSos that translocates an ERK-activating signal to the nucleus. The locus of action of ERK was specifically mapped to early growth response-1 (Egr-1) DNA binding sites within the LH beta-subunit gene proximal promoter, which was also activated by p38MAPK, but not c-Jun NH2-terminal kinase 1/2. Egr-1 was confirmed as the transcription factor target of ERK and p38MAPK by blockade of protein expression, transcriptional activity, and DNA binding. We have identified a novel GnRH-activated proline-rich tyrosine kinase 2-dependent ERK-mediated signal transduction pathway that specifically regulates Egr-1 activation of the LH beta-subunit proximal gene promoter, and thus provide insight into the molecular mechanisms required for differential regulation of gonadotropin gene expression
Application of BIB–SEM technology to characterize microstructure and pores in mudstone at a range of scales
No full textCharacterization of the microstructure and pores in fine-grained geo-materials like mudstones is challenging because of their heterogeneity and small pore sizes. Combining Broad Ion Beam (BIB) polishing and Scanning Electron Microscopy (SEM) enables the visualization of microstructure and pores from millimetres down to a few nanometres in size. In the SEM, the BIB-polished section is mapped at high magnification with various detectors and the different features are segmented and quantified using image processing algorithms. This technology is applied on undeformed and naturally or experimentally deformed rock samples to analyse the strain behaviour of potential host rock formations of nuclear waste such as the Boom Clay and Callovian-Oxfordian Clay. Application of BIB-SEM in combination with Wood’s Metal Injection allowed imaging the connected pore space in fine-grained rocks like the Boom Clay and Ypresian Clay. The in-situ fluid distribution of saturated rocks can be imaged by applying BIBSEM at cryogenic conditions. These applications aim to increase understanding in deformation mechanisms, sealing capacity and transport properties of fine-grained materials
Methodology for ion neutralization at solid/electrolyte interfaces
No full textPT: J; CR: ADELMAN SA, 1974, J CHEM PHYS, V61, P4242 ADELMAN SA, 1975, J CHEM PHYS, V62, P4908 ADELMAN SA, 1976, J CHEM PHYS, V64, P2375 ANDERSON PW, 1961, PHYS REV, V124, P41 BLANDIN A, 1976, J PHYSIQUE, V37, P369 BLOSS W, 1978, SURF SCI, V72, P277 BOCKRIS JOM, 1963, P ROY SOC LOND A MAT, V274, P55 BRAKO R, 1981, SURF SCI, V108, P253 BRAKO R, 1984, PHYS REV B, V30, P5629 BRAKO R, 1985, PHYS SCR, V32, P451 BRAKO R, 1985, SOLID STATE COMMUN, V55, P633 CHAMBERS LG, 1976, INTEGRAL EQUATIONS S, P114 CIZEK J, 1969, ADV CHEM PHYS, V14, P35 EASA SI, 1985, SURF SCI, V161, P129 GRIMLEY TB, 1983, SURF SCI, V124, P305 MAKOSHI K, 1984, J PHYS SOC JPN, V53, P2441 MCDOWELL HK, 1982, CHEM PHYS, V72, P451 MCDOWELL HK, 1982, J CHEM PHYS, V77, P3263 MCDOWELL HK, 1985, J CHEM PHYS, V83, P772 MORRISON SR, 1980, ELECTROCHEMISTRY SEM, P31 NEWNS DM, 1969, PHYS REV, V178, P1123 NEWNS DM, 1983, PHYS SCRIPTA, V6, P5 PARENT LG, 1984, J ELECTROANAL CH INF, V163, P23 SCHMICKLER W, 1979, J ELECTROANAL CHEM, V100, P533 SCHMICKLER W, 1980, J ELECTROANAL CH INF, V113, P159 SCHUGARD M, 1977, J CHEM PHYS, V66, P2534 SEBASTIAN KL, 1981, SURF SCI, V110, L571 SEBASTIAN KL, 1983, PHYS LETT A, V98, P39 SEBASTIAN KL, 1985, PHYS REV B, V31, P6976 SHANKAR R, 1982, PRINCIPLES QUANTUM M, P482 SROUBEK Z, 1981, SPRINGER SERIES CHEM, V17, P277 TULLY JC, 1980, ANNU REV PHYS CHEM, V31, P319 WATSON GN, 1966, TREATISE THEORY BESS YEAGER E, 1982, SURF SCI, V101, P1; NR: 34; TC: 18; J9: J ELECTROANAL CHEM; PG: 12; GA: C8849Source type: Electronic(1
Statistical Coulomb interactions in multi-beam SEM
No full textStatistical Coulomb interactions in conventional scanning electron microscopy mostly affect the probe size via energy spread and virtual source broadening in the emitter vicinity. However, in a multi-beam probe forming system such as a multi-beam scanning electron microscopes (MBSEM), the trajectory displacement due to interactions in the whole column can give a contribution to the final probe size. For single-beam systems, this can be expressed using approximate formulae for the total trajectory displacement in a beam segment (Jansen's theory) or by integrating contributions of infinitesimally thin beam slices (the slice method). We build on Jansen's theory of statistical Coulomb interactions and develop formulae for the trajectory displacement in a multi-beam system. We also develop a more precise semi-analytical result using the slice method. We compare both approaches with a Monte Carlo simulation and show a good agreement with the results of the slice method. Finally, we discuss the implications of our results for the optical design of multi-beam SEM. In a multi-beam with probe size dominated by Coulomb interactions, an increase in the number of beamlets does not necessarily provide an increase of throughput, because the probe size is limited by the total current. Furthermore, we disprove the notion of "the fewer the crossovers - the less the Coulomb interactions" by showing the quadratic dependence of trajectory displacement on segment length.ImPhys/Charged Particle Optic
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