Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Llama antibody fragments have good potential for application as HIV-1 topical microbicides

There is an urgent global need for preventative strategies against HIV-1 infections. Llama heavy-chain antibody fragments (VHH) are a class of molecules recently described as potent cross-clade HIV-1 entry inhibitors. We studied the potential of a VHH-based microbicide in an application-oriented fashion. We show that VHH can be inexpensively produced in high amounts in the GRAS organism S. cerevisiae, resulting in very pure, and endotoxin free product. VHH are very stable under conditions they might encounter during transport, storage or use by women. We developed active formulations of VHH in aqueous gel and compressed and lyophilized tablets for controlled release from an intra vaginal device. The release profile of the VHH from e.g. a vaginal ring suggests sufficient bioavailability and protective concentration of the molecule at the mucosal site at the moment of the infection. The ex vivo penetration kinetics through human tissues show that the VHH diffuse into the mucosal layer and open the possibility to create a second defense layer either by blocking the HIV receptor binding sites or by blocking the receptors of immune cells in the mucosa. In conclusion, our data show that VHH have

Application of Nonlinear PCA for Fault Detection in Polymer Extrusion Processes

This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer extrusion processes. Since the processes are complex in nature and nonlinear relationships exist between the recorded variables, an improved nonlinear PCA, which incorporates the radial basis function (RBF) networks and principal curves, is proposed. This algorithm comprises two stages. The first stage involves the use of the serial principal curve to obtain the nonlinear scores and approximated data. The second stage is to construct two RBF networks using a fast recursive algorithm to solve the topology problem in traditional nonlinear PCA. The benefits of this improvement are demonstrated in the practical application to a polymer extrusion process.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Potential hazard to human health from exposure to fragments of lead bullets and shot in the tissues of game animals

Lead is highly toxic to animals. Humans eating game killed using lead ammunition generally avoid swallowing shot or bullets and dietary lead exposure from this source has been considered low. Recent evidence illustrates that lead bullets fragment on impact, leaving small lead particles widely distributed in game tissues. Our paper asks whether lead gunshot pellets also fragment upon impact, and whether lead derived from spent gunshot and bullets in the tissues of game animals could pose a threat to human health.

Detection of Protein-Protein Interactions Using Protein-Fragment Complementation Assays (PCA)

Protein-protein interactions play a central role in many cellular processes. Their characterisation is necessary in order to analyse these processes and for the functional identification of unknown proteins. Existing detection methods such as the yeast two-hybrid (Y2H) and tandem affinity purification (TAP) method provide a means to answer rapidly questions regarding protein-protein interactions, but have limitations which restrict their use to certain interaction networks; furthermore they provide little information regarding interaction localisation at the subcellular level. The development of protein-fragment complementation assays (PCA) employing a fluorescent reporter such as a member of the green fluorescent protein (GFP) family has led to a new method of interaction detection termed Bimolecular Fluorescent Complementation (BiFC). These assays have become important tools for understanding protein interactions and the development of whole genome interaction maps. BiFC assays have the advantages of very low background signal coupled with rapid detection of protein-protein interactions in vivo while also providing information regarding interaction compartmentalisation. Modified forms of the assay such as the use of combinations of spectral variants of GFP have allowed simultaneous visualisation of multiple competing interactions in vivo. Advantages and disadvantages of the method are discussed in the context of other fluorescence-based interaction monitoring techniques.

Long-term mass balance of perennial firn and ice in an Alpine cave (Austria):Constraints from radiocarbon-dated wood fragments

Hundsalm ice cave located at 1520 m altitude in a karst region of western Austria contains up to 7-m-thick deposits of snow, firn and congelation ice. Wood fragments exposed in the lower parts of an ice and firn wall were radiocarbon accelerator mass spectrometry (AMS) dated. Although the local stratigraphy is complex, the 19 individual dates - the largest currently available radiocarbon dataset for an Alpine ice cave - allow to place constraints on the accumulation and ablation history of the cave ice. Most of the cave was either ice free or contained only a small firn and ice body during the 'Roman Warm Period'; dates of three wood fragments mark the onset of firn and ice build-up in the 6th and 7th century ad. In the central part of the cave, the oldest samples date back to the 13th century and record ice growth coeval with the onset of the 'Little Ice Age'. The majority of the ice and firn deposit, albeit compromised by a disturbed stratigraphy, appears to have been formed during the subsequent centuries, supported by wood samples from the 15th to the 17th century. The oldest wood remains found so far inside the ice is from the end of the Bronze Age and implies that local relics of prehistoric ice may be preserved in this cave. The wood record from Hundsalm ice cave shows parallels to the Alpine glacier history of the last three millennia, for example, the lack of preserved wood remains during periods of known glacier minima, and underscores the potential of firn and ice in karst cavities as a long-term palaeoclimate archive, which has been degrading at an alarming rate in recent years. © The Author(s) 2013.

Distinguishing Species of Geoemyclid and Trionychid Turtles from Shell Fragments:Evidence from the Pleistocene at Niah Caves, Sarawak

Fragments of chelonian carapace and plastral dermal plates are well-represented from archaeological sites in the world's dry and wet tropics. However, although these bones are easily identified at an element level, few archaeological reports have explored the potential of using features of form and surface sculpturing as a way to refine that identification to genus or species. The ability to achieve such a refinement would benefit environmental and human subsistence strategy models alike. The objective of the current paper was to isolate recurrent and readily visible surface characteristics on the dermal plates from a selection of commonly occurring Southeast Asian hard- and soft-shelled turtles. Using these criteria, analysis is made of the chelonian assemblage from pre- and post-Last Glacial Maximum (LGM) cultural deposits in the West Mouth of Niah Cave. Copyright (C) 2009 John Wiley & Sons, Ltd.