Identifying sequence regions undergoing conformational change via predicted continuum secondary structure

Motivation: Conformational flexibility is essential to the function of many proteins, e.g. catalytic activity. To assist efforts in determining and exploring the functional properties of a protein, it is desirable to automatically identify regions that are prone to undergo conformational changes. It was recently shown that a probabilistic predictor of continuum secondary structure is more accurate than categorical predictors for structurally ambivalent sequence regions, suggesting that such models are suited to characterize protein flexibility. Results: We develop a computational method for identifying regions that are prone to conformational change directly from the amino acid sequence. The method uses the entropy of the probabilistic output of an 8-class continuum secondary structure predictor. Results for 171 unique amino acid sequences with well-characterized variable structure (identified in the 'Macromolecular movements database') indicate that the method is highly sensitive at identifying flexible protein regions, but false positives remain a problem. The method can be used to explore conformational flexibility of proteins (including hypothetical or synthetic ones) whose structure is yet to be determined experimentally.

Building user commitment to implementing a knowledge management strategy

In the IS literature, commitment is typically considered to involve organizational or managerial support for a system and not that of its users. This paper however reports on a field study involving 16 organizations that attempted to build user involvement in developing a knowledge management strategy by having them design it. Twenty-two IT-supported group workshops (involving 183 users) were run to develop action plans for better knowledge management that users would like to see implemented. Each workshop adopted the same problem structuring technique to assist group members develop a politically feasible action plan to which they were psychologically and emotionally dedicated. In addition to reviewing the problem structuring method, this paper provides qualitative insight into the factors a knowledge management strategy should have to encourage user commitment. © 2004 Elsevier B.V. All rights reserved.

Journey making group workshops as a research tool

Problem-structuring group workshops can be used in organizations as a consulting tool and as a research tool. One example of the latter is using a problem-structuring method (PSM) to help a group tackle an organizational issue; meanwhile, researchers collect the participants' initial views, discussion of divergent views, the negotiated agreement, and the reasoning for outcomes emerging. Technology can help by supporting participants in freely sharing their opinions and by logging data for post-workshop analyses. For example, computers let participants share views anonymously and without being influenced by others (as well as logging those views), and video-cameras can record discussions and intra-group dynamics. This paper evaluates whether technology-supported Journey Making workshops can be effective research tools that can capture quality research data when compared against theoretical performance benchmarks and other qualitative research tools. © 2006 Operational Research Society Ltd. All rights reserved.

Mass transfer coefficient for drying of moist particulate in a bubbling fluidized bed

Experiments on drying of moist particles by ambient air were carried out to measure the mass transfer coefficient in a bubbling fluidized bed. Fine glass beads of mean diameter 125?µm were used as the bed material. Throughout the drying process, the dynamic material distribution was recorded by electrical capacitance tomography (ECT) and the exit air condition was recorded by a temperature/humidity probe. The ECT data were used to obtain qualitative and quantitative information on the bubble characteristics. The exit air moisture content was used to determine the water content in the bed. The measured overall mass transfer coefficient was in the range of 0.0145–0.021?m/s. A simple model based on the available correlations for bubble-cloud and cloud-dense interchange (two-region model) was used to predict the overall mass transfer coefficient. Comparison between the measured and predicted mass transfer coefficient have shown reasonable agreement. The results were also used to determine the relative importance of the two transfer regions.

Palette-colouring: a belief propagation approach

We consider a variation of the prototype combinatorial optimization problem known as graph colouring. Our optimization goal is to colour the vertices of a graph with a fixed number of colours, in a way to maximize the number of different colours present in the set of nearest neighbours of each given vertex. This problem, which we pictorially call palette-colouring, has been recently addressed as a basic example of a problem arising in the context of distributed data storage. Even though it has not been proved to be NP-complete, random search algorithms find the problem hard to solve. Heuristics based on a naive belief propagation algorithm are observed to work quite well in certain conditions. In this paper, we build upon the mentioned result, working out the correct belief propagation algorithm, which needs to take into account the many-body nature of the constraints present in this problem. This method improves the naive belief propagation approach at the cost of increased computational effort. We also investigate the emergence of a satisfiable-to-unsatisfiable 'phase transition' as a function of the vertex mean degree, for different ensembles of sparse random graphs in the large size ('thermodynamic') limit.

Decision Trees for Applicability of Evolution Rules in Transition P Systems

Transition P Systems are a parallel and distributed computational model based on the notion of the cellular membrane structure. Each membrane determines a region that encloses a multiset of objects and evolution rules. Transition P Systems evolve through transitions between two consecutive configurations that are determined by the membrane structure and multisets present inside membranes. Moreover, transitions between two consecutive configurations are provided by an exhaustive non-deterministic and parallel application of active evolution rules subset inside each membrane of the P system. But, to establish the active evolution rules subset, it is required the previous calculation of useful and applicable rules. Hence, computation of applicable evolution rules subset is critical for the whole evolution process efficiency, because it is performed in parallel inside each membrane in every evolution step. The work presented here shows advantages of incorporating decision trees in the evolution rules applicability algorithm. In order to it, necessary formalizations will be presented to consider this as a classification problem, the method to obtain the necessary decision tree automatically generated and the new algorithm for applicability based on it.

Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

Real-time biosensor for the assessment of nanotoxicity and cancer electrotherapy

Knowledge of cell electronics has led to their integration to medicine either by physically interfacing electronic devices with biological systems or by using electronics for both detection and characterization of biological materials. In this dissertation, an electrical impedance sensor (EIS) was used to measure the electrode surface impedance changes from cell samples of human and environmental toxicity of nanoscale materials in 2D and 3D cell culture models. The impedimetric response of human lung fibroblasts and rainbow trout gill epithelial cells when exposed to various nanomaterials was tested to determine their kinetic effects towards the cells and to demonstrate the biosensor's ability to monitor nanotoxicity in real-time. Further, the EIS allowed rapid, real-time and multi-sample analysis creating a versatile, noninvasive tool that is able to provide quantitative information with respect to alteration in cellular function. We then extended the application of the unique capabilities of the EIS to do real-time analysis of cancer cell response to externally applied alternating electric fields at different intermediate frequencies and low-intensity. Decreases in the growth profiles of the ovarian and breast cancer cells were observed with the application of 200 and 100 kHz, respectively, indicating specific inhibitory effects on dividing cells in culture in contrast to the non-cancerous HUVECs and mammary epithelial cells. We then sought to enhance the effects of the electric field by altering the cancer cell's electronegative membrane properties with HER2 antibody functionalized nanoparticles. An Annexin V/EthD-III assay and zeta potential were performed to determine the cell death mechanism indicating apoptosis and a decrease in zeta potential with the incorporation of the nanoparticles. With more negatively charged HER2-AuNPs attached to the cancer cell membrane, the decrease in membrane potential would thus leave the cells more vulnerable to the detrimental effects of the applied electric field due to the decrease in surface charge. Therefore, by altering the cell membrane potential, one could possibly control the fate of the cell. This whole cell-based biosensor will enhance our understanding of the responsiveness of cancer cells to electric field therapy and demonstrate potential therapeutic opportunities for electric field therapy in the treatment of cancer.

Using geophysical surveys to test tracer-based storage estimates in headwater catchments

Acknowledgements The authors are grateful to Stian Bradford, Chris Gabrielli, and Julie Timms for practical and logistical assistance. The provision of transport by Iain Malcolm and Ross Glover of Marine Scotland Science was greatly appreciated. We also thank the European Research Council ERC (project GA 335910 VEWA) for funding through the VeWa project and the Leverhulme Trust for funding through PLATO (RPG-2014-016).

Real-time Biosensor for the Assessment of Nanotoxicity and Cancer Electrotherapy

Knowledge of cell electronics has led to their integration to medicine either by physically interfacing electronic devices with biological systems or by using electronics for both detection and characterization of biological materials. In this dissertation, an electrical impedance sensor (EIS) was used to measure the electrode surface impedance changes from cell samples of human and environmental toxicity of nanoscale materials in 2D and 3D cell culture models. The impedimetric response of human lung fibroblasts and rainbow trout gill epithelial cells when exposed to various nanomaterials was tested to determine their kinetic effects towards the cells and to demonstrate the biosensor’s ability to monitor nanotoxicity in real-time. Further, the EIS allowed rapid, real-time and multi-sample analysis creating a versatile, noninvasive tool that is able to provide quantitative information with respect to alteration in cellular function. We then extended the application of the unique capabilities of the EIS to do real-time analysis of cancer cell response to externally applied alternating electric fields at different intermediate frequencies and low-intensity. Decreases in the growth profiles of the ovarian and breast cancer cells were observed with the application of 200 and 100 kHz, respectively, indicating specific inhibitory effects on dividing cells in culture in contrast to the non-cancerous HUVECs and mammary epithelial cells. We then sought to enhance the effects of the electric field by altering the cancer cell’s electronegative membrane properties with HER2 antibody functionalized nanoparticles. An Annexin V/EthD-III assay and zeta potential were performed to determine the cell death mechanism indicating apoptosis and a decrease in zeta potential with the incorporation of the nanoparticles. With more negatively charged HER2-AuNPs attached to the cancer cell membrane, the decrease in membrane potential would thus leave the cells more vulnerable to the detrimental effects of the applied electric field due to the decrease in surface charge. Therefore, by altering the cell membrane potential, one could possibly control the fate of the cell. This whole cell-based biosensor will enhance our understanding of the responsiveness of cancer cells to electric field therapy and demonstrate potential therapeutic opportunities for electric field therapy in the treatment of cancer.

Evaluation of frozen ground conditions along a coastal topographic gradient at Byers Peninsula (Livingston Island, Antarctica) by geophysical and geoecological methods

Geophysical surveying and geoelectricalmethods are effective to study permafrost distribution and conditions in polar environments. Geoelectrical methods are particularly suited to study the spatial distribution of permafrost because of its high electrical resistivity in comparison with that of soil or rock above 0 °C. In the South Shetland Islands permafrost is considered to be discontinuous up to elevations of 20–40ma.s.l., changing to continuous at higher altitudes. There are no specific data about the distribution of permafrost in Byers Peninsula, in Livingston Island, which is the largest ice-free area in the South Shetland Islands. With the purpose of better understanding the occurrence of permanent frozen conditions in this area, a geophysical survey using an electrical resistivity tomography (ERT)methodologywas conducted during the January 2015 field season, combined with geomorphological and ecological studies. Three overlapping electrical resistivity tomographies of 78meach were done along the same profile which ran from the coast to the highest raised beaches. The three electrical resistivity tomographies are combined in an electrical resistivitymodel which represents the distribution of the electrical resistivity of the ground to depths of about 13malong 158m. Several patches of high electrical resistivity were found, and interpreted as patches of sporadic permafrost. The lower limits of sporadic to discontinuous permafrost in the area are confirmed by the presence of permafrost-related landforms nearby. There is a close correspondence between moss patches and permafrost patches along the geoelectrical transect.

Solving the problem of diffraction of an optical-band electromagnetic wave by metal nanostructured aperture arrays with the use of the method of impedance boundary conditions

The problem of diffraction of an optical wave by a 2D periodic metal aperture array with square, circular, and ring apertures is solved with allowance for the finite permittivity of a metal in the optical band. The correctness of the obtained results is verified through comparison with experimental data. It is shown that the transmission coefficient can be substantially greater than the corresponding value reached in the case of diffraction by a grating in a perfectly conducting screen.

An ontology-based method for sparsity problem in tag recommendation

Tags or personal metadata for annotating web resources have been widely adopted in Web 2.0 sites. However, as tags are freely chosen by users, the vocabularies are diverse, ambiguous and sometimes only meaningful to individuals. Tag recommenders may assist users during tagging process. Its objective is to suggest relevant tags to use as well as to help consolidating vocabulary in the systems. In this paper we discuss our approach for providing personalized tag recommendation by making use of existing domain ontology generated from folksonomy. Specifically we evaluated the approach in sparse situation. The evaluation shows that the proposed ontology-based method has improved the accuracy of tag recommendation in this situation.

A combined method for mitigating sparsity problem in tag recommendation

Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

Reconstruction from incomplete data in cone-beam tomography

A method for reconstruction of an object f(x) x=(x,y,z) from a limited set of cone-beam projection data has been developed. This method uses a modified form of convolution back-projection and projection onto convex sets (POCS) for handling the limited (or incomplete) data problem. In cone-beam tomography, one needs to have a complete geometry to completely reconstruct the original three-dimensional object. While complete geometries do exist, they are of little use in practical implementations. The most common trajectory used in practical scanners is circular, which is incomplete. It is, however, possible to recover some of the information of the original signal f(x) based on a priori knowledge of the nature of f(x). If this knowledge can be posed in a convex set framework, then POCS can be utilized. In this report, we utilize this a priori knowledge as convex set constraints to reconstruct f(x) using POCS. While we demonstrate the effectiveness of our algorithm for circular trajectories, it is essentially geometry independent and will be useful in any limited-view cone-beam reconstruction.