Multivariate statistical analysis of Raman images of a pharmaceutical tablet

This paper describes the application of principal component analysis (PCA) and independent component analysis (ICA) to identify the reference spectra of a pharmaceutical tablet's constituent compounds from Raman spectroscopic data. The analysis shows, first with a simulated data set and then with data collected from a pharmaceutical tablet, that both PCA and ICA are able to identify most of the features present in the reference spectra of the constituent compounds. However, the results suggest that the ICA method may be more appropriate when attempting to identify unknown reference spectra from a sample. The resulting PCA and ICA models are subsequently used to estimate the relative concentrations of the constituent compounds and to produce spatial distribution images of the analyzed tablet. These images provide a visual representation of the spatial distribution of the constituent compounds throughout the tablet. Images associated with the ICA scores are found to be more informative and not as affected by measurement noise as the PCA based score images. The paper concludes with a discussion of the future work that needs to be undertaken for ICA to gain wider acceptance in the applied spectroscopy community.     

Computationally efficient application of the generic shape-illumination invariant to face recognition from video

As a problem of high practical appeal but many outstanding challenges, computer-based face recognition remains a topic of extensive research attention. In this paper we are specifically interested in the task of identifying a person using multiple images both in training and as a query. Thus, a novel method is proposed which advances the state-of-the-art in set-based face recognition. The introduced approach is based on a previously described invariant in the form of generic shape-illumination effects. The contributions include (i) an analysis of the computational demands of the original method and a demonstration of its practical limitations, (ii) a novel representation of personal appearance in the form of linked mixture models in image and pose-signature spaces, and (iii) an efficient (in terms of storage needs and matching time) manifold re-illumination algorithm based on the aforementioned representation. An evaluation and comparison of the proposed method with the original generic shape-illumination algorithm shows that comparably high recognition rates are achieved on a large data set (1.5% error on 700 face sets containing 100 individuals and extreme illumination variation) with a dramatic improvement in matching speed (over 700 times for sets containing 1600 faces) and storage requirements (independent of the number of training images). Theoretical and empirical findings of the present work are used to identify and discuss avenues for future research.     

Gene Mutation Profiles in Primary Diffuse Large B Cell Lymphoma of Central Nervous System: Next Generation Sequencing Analyses

The existence of a potential primary central nervous system lymphoma-specific genomic signature that differs from the systemic form of diffuse large B cell lymphoma (DLBCL) has been suggested, but is still controversial. We investigated 19 patients with primary DLBCL of central nervous system (DLBCL CNS) using the TruSeq Amplicon Cancer Panel (TSACP) for 48 cancer-related genes. Next generation sequencing (NGS) analyses have revealed that over 80% of potentially protein-changing mutations were located in eight genes (CTNNB1, PIK3CA, PTEN, ATM, KRAS, PTPN11, TP53 and JAK3), pointing to the potential role of these genes in lymphomagenesis. TP53 was the only gene harboring mutations in all 19 patients. In addition, the presence of mutated TP53 and ATM genes correlated with a higher total number of mutations in other analyzed genes. Furthermore, the presence of mutated ATM correlated with poorer event-free survival (EFS) (p = 0.036). The presence of the mutated SMO gene correlated with earlier disease relapse (p = 0.023), inferior event-free survival (p = 0.011) and overall survival (OS) (p = 0.017), while mutations in the PTEN gene were associated with inferior OS (p = 0.048). Our findings suggest that the TP53 and ATM genes could be involved in the molecular pathophysiology of primary DLBCL CNS, whereas mutations in the PTEN and SMO genes could affect survival regardless of the initial treatment approach.     

Isogeometric bending analysis of composite plates based on a higher-order shear deformation theory

This research paper presents an isogeometric plate finite element formulation for analysis of thick composite plates. Isogeometric finite element method which is based on non-uniform rational B-splines (NURBS) basis functions, is a novel numerical procedure developed to bridge the gap between CAD and FEM modeling of structures. In order to investigate the behavior of isogeometric plate elements under static loading, plate kinematics is based on third order shear deformation theory (TSDT) of Reddy, which is free from transverse shear locking. This paper discusses accurate transverse stress recovery procedures for TSDT isogeometric finite elements. Numerical experiments with quadratic, cubic and quartic elements are presented and obtained results are compared to other available ones.     

Effects of dams and reservoirs on the hydrological characteristics of the lower drava river

During the last 20 years numerous water supply, hydroelectric and other large structures have been built along the Drava River and in its catchment area in Slovenia, Croatia, Hungary and Austria. Their construction has greatly influenced the water regime of the Drava River, especially during low water periods. The changes in the low flow regime along the stretch from Varazdin (285 km) to its confluence with the Danube (0 km) are examined. The analysis includes changes in the water levels, discharges and the amounts of suspended sediment and bed load. The intensity of changes, the time of their occurrence and their trends are examined.     

Discovering topic structures of a temporally evolving document corpus

In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimension. In contrast to previous work our model does not impose a prior on the rate at which documents are added to the corpus nor does it adopt the Markovian assumption which overly restricts the type of changes that the model can capture. Our key technical contribution is a framework based on (i) discretization of time into epochs, (ii) epoch-wise topic discovery using a hierarchical Dirichlet process-based model, and (iii) a temporal similarity graph which allows for the modelling of complex topic changes: emergence and disappearance, evolution, splitting, and merging. The power of the proposed framework is demonstrated on two medical literature corpora concerned with the autism spectrum disorder (ASD) and the metabolic syndrome (MetS)—both increasingly important research subjects with significant social and healthcare consequences. In addition to the collected ASD and metabolic syndrome literature corpora which we made freely available, our contribution also includes an extensive empirical analysis of the proposed framework. We describe a detailed and careful examination of the effects that our algorithms’s free parameters have on its output and discuss the significance of the findings both in the context of the practical application of our algorithm as well as in the context of the existing body of work on temporal topic analysis. Our quantitative analysis is followed by several qualitative case studies highly relevant to the current research on ASD and MetS, on which our algorithm is shown to capture well the actual developments in these fields.     

TiO2–CeO2 composite coatings for photocatalytic degradation of chloropesticide and organic dye

Journal of Materials Science: Materials in Electronics - Spray pyrolysis was used to deposit CeO2–TiO2 coatings on stainless steel substrates. The addition of CeO2 to TiO2 changes morphology...     

Uneven batch data alignment with application to the control of batch end-product quality

Batch processes are commonly characterized by uneven trajectories due to the existence of batch-to-batch variations. The batch end-product quality is usually measured at the end of these uneven trajectories. It is necessary to align the time differences for both the measured trajectories and the batch end-product quality in order to implement statistical process monitoring and control schemes. Apart from synchronizing trajectories with variable lengths using an indicator variable or dynamic time warping, this paper proposes a novel approach to align uneven batch data by identifying short-window PCA&PLS models at first and then applying these identified models to extend shorter trajectories and predict future batch end-product quality. Furthermore, uneven batch data can also be aligned to be a specified batch length using moving window estimation. The proposed approach and its application to the control of batch end-product quality are demonstrated with a simulated example of fed-batch fermentation for penicillin production.     

Insights into proteolytic processing of the major peanut allergen Ara h 2 by endogenous peanut proteases

BACKGROUND: The major peanut allergens are Ara h 1, Ara h 2 and Ara h 6. Proteolytic processing has been shown to be required for the maturation process of Ara h 6. The aim of this study was to examine whether Ara h 2 undergoes proteolytic processing and, if so, whether proteolytic processing influences its ability to bind human immunoglobulin E (IgE). RESULTS: Ara h 2 isolated from peanut extract under conditions of protease inhibition revealed a single additional peak for its two known isoforms (Ara h 2.01 and Ara h 2.02), corresponding to a C‐terminally truncated form lacking a dipeptide (RY). Ara h 2 isolated in the absence of protease inhibition, however, yielded two additional peaks, identified as C‐terminally truncated forms lacking either a dipeptide (RY) or a single tyrosine residue. The IgE‐binding capacity of the Ara h 2 truncated forms was not altered. CONCLUSION: Ara h 2 undergoes proteolytic processing by peanut proteases that involves C‐terminal removal of a dipeptide. Hence Ara h 2 isolated from peanut extract is a complex mixture of two isoforms expressed by different genes, Ara h 2.01 and Ara h 2.02, as well as truncated forms generated by the proteolytic processing of these isoforms. Copyright © 2010 Society of Chemical Industry     

Real-time monitoring of an industrial batch process

This paper describes the development of a real-time monitoring system for a batch process operated by Aroma and Fine Chemicals Limited. The process shares many similarities with other batch processes in that cycle times can vary considerably, instrumentation is limited and inefficient laboratory assays are required to determine the end-point of each batch. The aim of the work conducted in this study was to develop a data driven system to accurately identify the end-point of the batch. This information can then be used to reduce the overall cycle time of the process. Novel approaches based upon multivariate statistical techniques are shown to provide a soft sensor that can estimate the product quality throughout the batch and provide a long-term estimate of the likely cycle time. This system has been implemented on-line and initial results indicate that it offers potential to significantly reduce operating costs.