Resolution-Aware 3D Morphable Model

The 3D Morphable Model (3DMM) is currently receiving considerable attention for human face analysis. Most existing work focuses on fitting a 3DMM to high resolution images. However, in many applications, fitting a 3DMM to low-resolution images is also important. In this paper, we propose a Resolution-Aware 3DMM (RA- 3DMM), which consists of 3 different resolution 3DMMs: High-Resolution 3DMM (HR- 3DMM), Medium-Resolution 3DMM (MR-3DMM) and Low-Resolution 3DMM (LR-3DMM). RA-3DMM can automatically select the best model to fit the input images of different resolutions. The multi-resolution model was evaluated in experiments conducted on PIE and XM2VTS databases. The experimental results verified that HR- 3DMM achieves the best performance for input image of high resolution, and MR- 3DMM and LR-3DMM worked best for medium and low resolution input images, respectively. A model selection strategy incorporated in the RA-3DMM is proposed based on these results. The RA-3DMM model has been applied to pose correction of face images ranging from high to low resolution. The face verification results obtained with the pose-corrected images show considerable performance improvement over the result without pose correction in all resolution

Finding class C GPCR subtype-discriminating n-grams through feature selection

G protein-coupled receptors (GPCRs) are a large and heterogeneous superfamily of receptors that are key cell players for their role as extracellular signal transmitters. Class C GPCRs, in particular, are of great interest in pharmacology. The lack of knowledge about their full 3-D structure prompts the use of their primary amino acid sequences for the construction of robust classifiers, capable of discriminating their different subtypes. In this paper, we describe the use of feature selection techniques to build Support Vector Machine (SVM)-based classification models from selected receptor subsequences described as n-grams. We show that this approach to classification is useful for finding class C GPCR subtype-specific motifs.Peer ReviewedPostprint (author’s final draft

Allele-Specific Down-Regulation of RPTOR Expression Induced by Retinoids Contributes to Climate Adaptations

The mechanistic target of rapamycin (MTOR) pathway regulates cell growth, energy homeostasis, apoptosis, and immune response. The regulatory associated protein of MTOR encoded by the RPTOR gene is a key component of this pathway. A previous survey of candidate genes found that RPTOR contains multiple SNPs with strong correlations between allele frequencies and climate variables, consistent with the action of selective pressures that vary across environments. Using data from a recent genome scan for selection signals, we honed in on a SNP (rs11868112) 26 kb upstream to the transcription start site of RPTOR that exhibits the strongest association with temperature variables. Transcription factor motif scanning and mining of recently mapped transcription factor binding sites identified a binding site for POU class 2 homeobox 1 (POU2F1) spanning the SNP and an adjacent retinoid acid receptor (RAR) binding site. Using expression quantification, chromatin immunoprecipitation (ChIP), and reporter gene assays, we demonstrate that POU2F1 and RARA do bind upstream of the RPTOR gene to regulate its expression in response to retinoids; this regulation is affected by the allele status at rs11868112 with the derived allele resulting in lower expression levels. We propose a model in which the derived allele influences thermogenesis or immune response by altering MTOR pathway activity and thereby increasing fitness in colder climates. Our results show that signatures of genetic adaptations can identify variants with functional effects, consistent with the idea that selection signals may be used for SNP annotation

Allele-Specific Down-Regulation of <i>RPTOR</i> Expression Induced by Retinoids Contributes to Climate Adaptations

The mechanistic target of rapamycin (MTOR) pathway regulates cell growth, energy homeostasis, apoptosis, and immune response. The regulatory associated protein of MTOR encoded by the RPTOR gene is a key component of this pathway. A previous survey of candidate genes found that RPTOR contains multiple SNPs with strong correlations between allele frequencies and climate variables, consistent with the action of selective pressures that vary across environments. Using data from a recent genome scan for selection signals, we honed in on a SNP (rs11868112) 26 kb upstream to the transcription start site of RPTOR that exhibits the strongest association with temperature variables. Transcription factor motif scanning and mining of recently mapped transcription factor binding sites identified a binding site for POU class 2 homeobox 1 (POU2F1) spanning the SNP and an adjacent retinoid acid receptor (RAR) binding site. Using expression quantification, chromatin immunoprecipitation (ChIP), and reporter gene assays, we demonstrate that POU2F1 and RARA do bind upstream of the RPTOR gene to regulate its expression in response to retinoids; this regulation is affected by the allele status at rs11868112 with the derived allele resulting in lower expression levels. We propose a model in which the derived allele influences thermogenesis or immune response by altering MTOR pathway activity and thereby increasing fitness in colder climates. Our results show that signatures of genetic adaptations can identify variants with functional effects, consistent with the idea that selection signals may be used for SNP annotation.</p

Computationally Efficient Implementation of Convolution-based Locally Adaptive Binarization Techniques

One of the most important steps of document image processing is binarization. The computational requirements of locally adaptive binarization techniques make them unsuitable for devices with limited computing facilities. In this paper, we have presented a computationally efficient implementation of convolution based locally adaptive binarization techniques keeping the performance comparable to the original implementation. The computational complexity has been reduced from O(W2N2) to O(WN2) where WxW is the window size and NxN is the image size. Experiments over benchmark datasets show that the computation time has been reduced by 5 to 15 times depending on the window size while memory consumption remains the same with respect to the state-of-the-art algorithmic implementation

Activation of calcineurin underlies altered trafficking of α2 subunit containing GABAA receptors during prolonged epileptiform activity

Fast inhibitory signalling in the mammalian brain is mediated by gamma-aminobutyric acid type A receptors (GABAARs), which are targets for anti-epileptic therapy such as benzodiazepines. GABAARs undergo tightly regulated trafficking processes that are essential for maintenance and physiological modulation of inhibitory strength. The trafficking of GABAARs to and from the membrane is altered during prolonged seizures such as in Status Epilepticus (SE) and has been suggested to contribute to benzodiazepine pharmacoresistance in patients with SE. However, the intracellular signalling mechanisms that cause this modification in GABAAR trafficking remain poorly understood. In this study, we investigate the surface stability of GABAARs during SE utilizing the low Mg2+ model in hippocampal rat neurons. Live-cell imaging of pHluorin (SEP)-tagged α2 subunit containing GABAARs during low Mg2+ conditions reveals that the somatic surface receptor pool undergoes down-regulation dependent on N-methyl-D-aspartate receptor (NMDAR) activity. Analysis of the intracellular Ca2+ signal during low Mg2+ using the Ca2+-indicator Fluo4 shows that this reduction of surface GABAARs correlates well with the timeline of intracellular Ca2+ changes. Furthermore, we show that the activation of the phosphatase calcineurin was required for the decrease in surface GABAARs in neurons undergoing epileptiform activity. These results indicate that somatic modulation of GABAAR trafficking during epileptiform activity in vitro is mediated by calcineurin activation which is linked to changes in intracellular Ca2+ concentrations. These mechanisms could account for benzodiazepine pharmacoresistance and the maintenance of recurrent seizure activity, and reveal potential novel targets for the treatment of SE

Современное состояние и перспективы развития ООПТ Томской области

В работе дана характеристика сети особо охраняемых природных территорий Томской области, ее роли в поддержании эколого-хозяйственного баланса области. Определены этапы формирования сети ООПТ. Дан анализ географического разнообразия сети ООПТ и представленности ее в административных районах области. Определена роль сети ООПТ в сохранении редких и исчезающих видов растений и животных. Разработана и реализована методика комплексной оценки эффективности сети ООПТ. Предложены пути ее развития и оптимизации.In work the characteristic of the network of specially protected natural territories of the Tomsk region, its role in maintaining ecological and economic balance of the region. The stages of forming a network of protected areas. The analysis of the geographic diversity of the PA network and its representation in the administrative districts of the region. Defined the role of the network of protected areas in the conservation of rare and endangered species of plants and animals. Developed and implemented a methodology of comprehensive evaluation of the effectiveness of the PA network. The proposed ways of its development and optimization

Cytokine-facilitated transduction leads to low-level engraftment in nonablated hosts

Using a murine bone marrow transplantation model, we evaluated the long-term engraftment of retrovirally transduced bone marrow cells in nonmyeloablated hosts. Male bone marrow was stimulated in a cocktail of interleukin-3 (IL-3), IL-6, IL-11, and stem cell factor (SCF) for 48 hours, then cocultured on the retroviral producer line MDR18.1 for an additional 24 hours. Functional transduction of hematopoietic progenitors was detected in vitro by reverse transcriptase-polymerase chain reaction (RT-PCR) amplification of multiple drug resistance 1 (MDR1) mRNA from high proliferative potential-colony forming cell (HPP-CFC) colonies. After retroviral transduction, male bone marrow cells were injected into nonablated female mice. Transplant recipients received three TAXOL (Bristol-Myers, Princeton, NJ) injections (10 mg/kg) over a 14-month period. Transplant recipient tissues were analyzed by Southern blot and fluorescence in situ hybridization for Y-chromosome-specific sequences and showed donor cell engraftment of approximately 9%. However, polymerase chain reaction amplification of DNAs from bone marrow, spleen, and peripheral blood showed no evidence of the transduced MDR1 gene. RT-PCR analysis of total bone marrow RNA showed that transcripts from the MDR1 gene were present in a fraction of the engrafted donor cells. These data show functional transfer of the MDR1 gene into nonmyeloablated murine hosts. However, the high rates of in vitro transduction into HPP-CFC, coupled with the low in vivo engraftment rate of donor cells containing the MDR1 gene, suggest that the majority of stem cells that incorporated the retroviral construct did not stably engraft in the host. Based on additional studies that indicate that ex vivo culture of bone marrow induces an engraftment defect concomitantly with progression of cells through S phase, we propose that the cell cycle transit required for proviral integration reduces or impairs the ability of transduced cells to stably engraft

A Multiclassifier Approach for Drill Wear Prediction

Classification methods have been widely used during last years in order to predict patterns and trends of interest in data. In present paper, a multiclassifier approach that combines the output of some of the most popular data mining algorithms is shown. The approach is based on voting criteria, by estimating the confidence distributions of each algorithm individually and combining them according to three different methods: confidence voting, weighted voting and majority voting. To illustrate its applicability in a real problem, the drill wear detection in machine-tool sector is addressed. In this study, the accuracy obtained by each isolated classifier is compared with the performance of the multiclassifier when characterizing the patterns of interest involved in the drilling process and predicting the drill wear. Experimental results show that, in general, false positives obtained by the classifiers can be slightly reduced by using the multiclassifier approach

Impact of dislocations and dangling bond defects on the electrical performance of crystalline silicon thin films

A wide variety of liquid and solid phase crystallized silicon films are investigated in order to determine the performance limiting defect types in crystalline silicon thin-film solar cells. Complementary characterization methods, such as electron spin resonance, photoluminescence, and electron microscopy, yield the densities of dangling bond defects and dislocations which are correlated with the electronic material quality in terms of solar cell open circuit voltage. The results indicate that the strongly differing performance of small-grained solid and large-grain liquid phase crystallized silicon can be explained by intra-grain defects like dislocations rather than grain boundary dangling bonds. A numerical model is developed containing both defect types, dislocations and dangling bonds, describing the experimental results