Pull-Down of Metalloproteins in Their Native States by Using Desthiobiotin-Based Probes

One-third of all proteins are estimated to require metals for structural stability and/or catalytic activity. Desthiobiotin probes containing metal binding groups can be used to capture metalloproteins with exposed active-site metals under mild conditions so as to prevent changes in metallation state. The proof-of-concept was demonstrated with carbonic anhydrase (CA), an open active site, Zn²⁺-containing protein. CA was targeted by using sulfonamide derivatives. Linkers of various lengths and structures were screened to determine the optimal structure for capture of the native protein. The optimized probes could selectively pull down CA from red blood cell lysate and other protein mixtures. Pull-down of differently metallated CAs was also investigated.     

Synchronised carrier-based SVPWM signal generation scheme for the entire modulation range extending up to six-step mode using the sampled amplitudes of reference phase voltages

The issues in synchronised implementation of space vector-based pulse width modulation (SVPWM) signal generation are addressed on a conventional DSP platform. With the present day digital signal processors (DSPs) with clock over 10 MHz, it is possible to include additional tasks for synchronisation in the interrupt service routine (ISR). Also, the task of the synchronisation can be easily accommodated within the same ISR without disturbing the time critical pulse width modulation (PWM) operation. The authors systematically present the additional software requirements to determine the time period proportional to the half carrier switching time interval that is required for the synchronisation. First, the DSP implementation of the conventional multi-level SVPWM based on the sampled amplitudes of reference voltages is presented and then the additional requirements to maintain the PWM in synchronisation are discussed. The simulation results as well as experimental results are presented for a five-level PWM signal generation. A five-level inverter configuration, using a 1.5 kW open-end winding induction motor drive, is used for experimentally verifying the SVPWM     

Electrical conduction in non-metallic rare-earth solids

Schematic energy band diagrams for the genesis of charge carriers in non-metallic rare-earth solids have been presented. It has been shown that positions of 4f bands have significant effect on the genesis and nature of charge carriers, their conduction mechanism and magnitude of electrical conductivity () and Seebeck coefficient (S) of the solid. Relevant relations have been given for both and S in different situations. Experimental data on rare-earth sesquioxides (R₂O₃), rare-earth tungstates [R₂(WO₄)₃] and rare-earth molybdates [R₂(MoO₄)₃] in the intrinsic range have been explained as examples for the validity of energy band diagrams.     

Analytical studies on the temperature distribution in spiral plate heat exchangers: Straightforward design formulae for efficiency and mean temperature difference

The temperature distribution in spiral plate heat exchangers has been calculated numerically to obtain the efficiency and the logarithmic mean temperature difference (LMTD) correction factors F as a function of the number of transfer units N, the number of turns n, and the heat capacity rate ratio C. It has been found that the LMTD correction factors, when plotted against the number of transfer units per turn N/n, fall approximately on a single curve. That curve for balanced countercurrent operation (C = −1) can be very closely represented by the simple formula F = (n/N)tanh(N/n). From that simple analytic representation of our numerical results it was concluded that a simpler physical model might exist to represent the overall behaviour of a spiral plate heat exchanger equally well. In fact, a countercurrent cascade of n cocurrent heat exchangers does result exactly in the above-mentioned formula for the LMTD correction factor. From that model the F-factors for other heat capacity rate ratios C (−1 < C 0) can also be calculated and they are in sufficient agreement with the numerical results.     

Learning Noise-Assisted Robust Image Features for Fine-Grained Image Retrieval

Fine-grained image search is one of the most challenging tasks in computer vision that aims to retrieve similar images at the fine-grained level for a given query image. The key objective is to learn discriminative fine-grained features by training deep models such that similar images are clustered, and dissimilar images are separated in the low embedding space. Previous works primarily focused on defining local structure loss functions like triplet loss, pairwise loss, etc. However, training via these approaches takes a long training time, and they have poor accuracy. Additionally, representations learned through it tend to tighten up in the embedded space and lose generalizability to unseen classes. This paper proposes a noise-assisted representation learning method for fine-grained image retrieval to mitigate these issues. In the proposed work, class manifold learning is performed in which positive pairs are created with noise insertion operation instead of tightening class clusters. And other instances are treated as negatives within the same cluster. Then a loss function is defined to penalize when the distance between instances of the same class becomes too small relative to the noise pair in that class in embedded space. The proposed approach is validated on CARS-196 and CUB-200 datasets and achieved better retrieval results (85.38% recall@1 for CARS-196% and 70.13% recall@1 for CUB-200) compared to other existing methods.     

An efficient algorithm for mass detection and shape analysis of different masses present in digital mammograms

The present study introduces an efficient algorithm for automatic segmentation and detection of mass present in the mammograms. The problem of over and under-segmentation of low-contrast mammographic images has been solved by applying preprocessing on original mammograms. Subtraction operation performed between enhanced and enhanced inverted mammogram significantly highlights the suspicious mass region in mammograms. The segmentation accuracy of suspicious region has been improved by combining wavelet transform and fast fuzzy c-means clustering algorithm. The accuracy of mass segmentation has been quantified by means of Jaccard coefficients. Better sensitivity, specificity, accuracy, and area under the curve (AUC) are observed with support vector machine using radial basis kernel function. The proposed algorithm is validated on Mini-Mammographic Image Analysis Society (MIAS) and Digital Database for Screening Mammography (DDSM) datasets. Highest 91.76% sensitivity, 96.26% specificity, 95.46% accuracy, and 96.29% AUC on DDSM dataset and 94.63% sensitivity, 92.74% specificity, 92.02% accuracy, and 95.33% AUC on MIAS dataset are observed. Also, shape analysis of mass is performed by using moment invariant and Radon transform based features. The best results are obtained with Radon based features and achieved accuracies for round, oval, lobulated, and irregular shape of mass are 100%, 70%, 64%, and 96%, respectively.     

Proteome profiling of exosomes derived from plasma of heifers with divergent genetic merit for fertility

The current study evaluated exosomes isolated from plasma of heifers bred to have high or low fertility through developing extreme diversity in fertility breeding values, however, key animal traits (e.g., body weight, milk production, and percentage of North American genetics) remained similar between the 2 groups. The exosomes were isolated by a combined ultracentrifugation and size exclusion chromatography approach and characterized by their size distribution (nanoparticle tracking analysis), morphology (transmission electron microscopy), and presence of exosomal markers (immunoblotting). In addition, a targeted mass spectrometry approach was used to confirm the presence of 2 exosomal markers, tumor susceptibility gene 101 and flotillin 1. The number of exosomes from plasma of high fertility heifers was greater compared with low fertility heifers. Interestingly, the exosomal proteomic profile, evaluated using mass spectrometry, identified 89 and 116 proteins in the high and low fertility heifers respectively, of which 4 and 31 were unique, respectively. These include proteins associated with specific biological processes and molecular functions of fertility. Most notably, the tetratricopeptide repeat protein 41-related, glycodelin, and kelch-like protein 8 were identified in plasma exosomes unique to the low fertility heifers. These proteins are suggested to play a role in reproduction; however, the role of these proteins in dairy cow reproduction remains to be elucidated. Their identification underscores the potential for proteins within exosomes to provide information on the fertility status and physiological condition of the cow. This may potentially lead to the development of prognostic tools and interventions to improving dairy cow fertility.     

Bootstrapping a weighted linear estimator of the ARCH parameters

Abstract.  A standard assumption while deriving the asymptotic distribution of the quasi maximum likelihood estimator in ARCH models is that all ARCH parameters must be strictly positive. This assumption is also crucial in deriving the limit distribution of appropriate linear estimators (LE). We propose a weighted linear estimator (WLE) of the ARCH parameters in the classical ARCH model and show that its limit distribution is multivariate normal even when some of the ARCH coefficients are zero. The asymptotic dispersion matrix involves unknown quantities. We consider appropriate bootstrapped version of this WLE and prove that it is asymptotically valid in the sense that the bootstrapped distribution (given the data) is a consistent estimate (in probability) of the distribution of the WLE. Although we do not show theoretically that the bootstrap outperforms the normal approximation, our simulations demonstrate that it yields better approximations than the limiting normal.