One Question,Multiple Answers: Biochemical and Biophysical Screening Methods Retrieve Deviating Fragment Hit Lists

Fragment‐based lead discovery is gaining momentum in drug development. Typically, a hierarchical cascade of several screening techniques is consulted to identify fragment hits which are then analyzed by crystallography. Because crystal structures with bound fragments are essential for the subsequent hit‐to‐lead‐to‐drug optimization, the screening process should distinguish reliably between binders and non‐binders. We therefore investigated whether different screening methods would reveal similar collections of putative binders. First we used a biochemical assay to identify fragments that bind to endothiapepsin, a surrogate for disease‐relevant aspartic proteases. In a comprehensive screening approach, we then evaluated our 361‐entry library by using a reporter‐displacement assay, saturation‐transfer difference NMR, native mass spectrometry, thermophoresis, and a thermal shift assay. While the combined results of these screening methods retrieve 10 of the 11 crystal structures originally predicted by the biochemical assay, the mutual overlap of individual hit lists is surprisingly low, highlighting that each technique operates on different biophysical principles and conditions.     

Distributed fiber optic monitoring of a CFA pile with a central reinforcement bar bundle

In this paper, we present an application of distributed fiber optic sensor (DFOS) technology to measure the strain of a continuous flight auger (CFA) test pile with a central reinforcement bar bundle, during a static load test carried out in London. Being distributed in nature, DFOS gives much more information about the pile performance as compared to traditional point sensors, such as identifying cross-sectional irregularities or other anomalies. The strain profiles recorded along the depth of the piles from the DFOS were used to calculate pile deformation (contraction), shaft friction, and tip resistance under various loads. Based on this pile load test, a finite element (FE) analysis was performed using a one-dimensional nonlinear load-transfer model. Calibrated by the shaft friction and tip resistance derived from the monitored data, the FE model was able to simulate the pile and soil performance during the load testing with good accuracy. The effect of the reinforcement cage and central reinforcement bar bundle were investigated, and it was found that the addition of a reinforcement cage would reduce the pile settlement by up to 20%.     

Monitoring process variation using modified EWMA

A new control chart, namely, modified exponentially weighted moving average (EWMA) control chart, for monitoring the process variance is introduced in this work by following the recommendations of Khan et al.¹⁵ The proposed control chart deduces the existing charts to be its special cases. The necessary coefficients, which are required for the construction of modified EWMA chart, are determined for various choices of sample sizes and smoothing constants. The performance of the proposed modified EWMA is evaluated in terms of its run length (RL) characteristics such as average RL and standard deviation of RL. The efficiency of the modified EWMA chart is investigated and compared with some existing control charts. The comparison reveals the superiority of proposal as compared with other control charts in terms of early detection of shift in process variation. The application of the proposal is also demonstrated using a real-life dataset.     

Transferrin-Decorated Niosomes with Integrated InP/ZnS Quantum Dots and Magnetic Iron Oxide Nanoparticles: Dual Targeting and Imaging of Glioma

The development of multifunctional nanoscale systems that can mediate efficient tumor targeting, together with high cellular internalization, is crucial for the diagnosis of glioma. The combination of imaging agents into one platform provides dual imaging and allows further surface modification with targeting ligands for specific glioma detection. Herein, transferrin (Tf)-decorated niosomes with integrated magnetic iron oxide nanoparticles (MIONs) and quantum dots (QDs) were formulated (PEGNIO/QDs/MIONs/Tf) for efficient imaging of glioma, supported by magnetic and active targeting. Transmission electron microscopy confirmed the complete co-encapsulation of MIONs and QDs in the niosomes. Flow cytometry analysis demonstrated enhanced cellular uptake of the niosomal formulation by glioma cells. In vitro imaging studies showed that PEGNIO/QDs/MIONs/Tf produces an obvious negative-contrast enhancement effect on glioma cells by magnetic resonance imaging (MRI) and also improved fluorescence intensity under fluorescence microscopy. This novel platform represents the first niosome-based system which combines magnetic nanoparticles and QDs, and has application potential in dual-targeted imaging of glioma.     

Efficient document image binarization using heterogeneous computing and parameter tuning

In the context of historical document analysis, image binarization is a first important step, which separates foreground from background, despite common image degradations, such as faded ink, stains, or bleed-through. Fast binarization has great significance when analyzing vast archives of document images, since even small inefficiencies can quickly accumulate to years of wasted execution time. Therefore, efficient binarization is especially relevant to companies and government institutions, who want to analyze their large collections of document images. The main challenge with this is to speed up the execution performance without affecting the binarization performance. We modify a state-of-the-art binarization algorithm and achieve on average a 3.5 times faster execution performance by correctly mapping this algorithm to a heterogeneous platform, consisting of a CPU and a GPU. Our proposed parameter tuning algorithm additionally improves the execution time for parameter tuning by a factor of 1.7, compared to previous parameter tuning algorithms. We see that for the chosen algorithm, machine learning-based parameter tuning improves the execution performance more than heterogeneous computing, when comparing absolute execution times.

     

Steam reforming of methanol over ruthenium impregnated ceria,alumina and ceria–alumina catalysts

The wet impregnation method was used to prepare different ruthenium promoted Ce–Al catalysts. These catalysts were used in the steam reforming of methanol reaction (SRM). The effects of the reaction temperature (200–400 C) and the catalyst composition were studied for optimization reasons. The steam to methanol molar ratio was kept constant (S/M = 2). The promotion of cerium/aluminum oxides with Ru enhanced their catalytic activity. The catalytic test results showed that the Ru/Ce combination was the most beneficial. The synergy between Ru and cerium oxide led to the formation of active sites with excellent redox properties. For high active phase content, the 5 RuCe catalyst exhibited the highest hydrogen production amount with no CO formation. This catalyst was kept under stream for 5 days at 400 C, and no significant deactivation was observed. Copyright © 2016 John Wiley & Sons, Ltd.     

Enhancement of the liquid feed distribution in gas‐solid fluidized beds by nozzle pulsations (induced by solenoid valve)

In this work, it was found that spray nozzles pulsations greatly improved the liquid feed spray distribution on fluidized bed particles. Pulsating a spray nozzle doubled its nozzle performance index at various operating conditions. The objective of this study was to impose fluctuations of well‐defined frequency and amplitude on the liquid spray to investigate potentially beneficial effects of fluctuations on the liquid feed distribution on the particles in the fluidized bed. Three sets of experiments were conducted to study the quality of the spray jet‐bed interaction using a conductance probe method. The jet penetration for each experiment was calculated theoretically. © 2011 American Institute of Chemical Engineers AIChE J, 2011     

Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models

The analysis of many physical and engineering problems involves running complex computational models (simulation models, computer codes). With problems of this type, it is important to understand the relationships between the input variables (whose values are often imprecisely known) and the output. The goal of sensitivity analysis (SA) is to study this relationship and identify the most significant factors or variables affecting the results of the model. In this presentation, an improvement on existing methods for SA of complex computer models is described for use when the model is too computationally expensive for a standard Monte-Carlo analysis. In these situations, a meta-model or surrogate model can be used to estimate the necessary sensitivity index for each input. A sensitivity index is a measure of the variance in the response that is due to the uncertainty in an input. Most existing approaches to this problem either do not work well with a large number of input variables and/or they ignore the error involved in estimating a sensitivity index. Here, a new approach to sensitivity index estimation using meta-models and bootstrap confidence intervals is described that provides solutions to these drawbacks. Further, an efficient yet effective approach to incorporate this methodology into an actual SA is presented. Several simulated and real examples illustrate the utility of this approach. This framework can be extended to uncertainty analysis as well.     

A novel DCT domain CRT-based watermarking scheme for image authentication surviving JPEG compression

Digital watermarking techniques have been proposed for copyright protection and authentication of multimedia data. In this paper, we propose a novel Chinese Remainder Theorem (CRT)-based technique for digital watermarking in the Discrete Cosine Transform (DCT) domain that is robust to several common attacks. We compared the performance of the proposed technique with recently proposed Singular Value Decomposition (SVD)-based and spatial CRT-based watermarking schemes. Experimental results have shown that the proposed technique successfully makes the watermark perceptually invisible and has better robustness to common image manipulation techniques such as JPEG compression, brightening and sharpening effects compared to the spatial domain-based CRT scheme. The proposed scheme is able to achieve a Tamper Assessment Function (TAF) value of less than 10% when the watermarked image undergoes JPEG compression between a range of 50 to 70%, where as, the spatial CRT-based scheme produce TAF value of more than 35% and the SVD-based scheme produces TAF value between 10 to 40% depending on the host image, for the same range of compression. When the watermark capacity is doubled, the proposed technique is still able to maintain imperceptibility and low TAF values, for most of the attacks.