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1 Structural, electronic, vibrational, optical and thermodynamic properties of 3-Oxo-3-p-tolylpropylphosphonic acid and 4-Oxo-4-p-tolyl-butyric acid: Density functional theory study 2018-06-18             

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Publication date: 5 November 2018
Source:Journal of Molecular Structure, Volume 1171

Author(s): Abdelkader Hellal, Djebaili Rachida, Samia Zaout, Mouna Elkolli, Salah Chafaa, Lasnouni Touafri, Nadjib Chafai, Mouna Mehri, Khalissa Benbougerra

Two analog acids, once is phosphonic acid, 3-Oxo-3-p-tolylpropylphosphonic acid, and the other is carboxylic acid, 4-Oxo-4-p-tolyl-butyric acid have been studied from a theoretical point of view in order to know their electronic, vibrational and thermodynamic properties by means of Density Functional Theory (DFT) calculations. The stable structures were optimized by using the hybrid B3LYP/6-31G method. The different proprieties for both compounds were analysed by means of the HOMO-LUMO proprieties, atomic charges, dipole moments, molecular electrostatic potentials and thermodynamic parameters. The vibrational spectra of the two acids are calculated and compared with those obtained with experimental FTIR method. The reactivity of molecules using various descriptors such us local softness, electrophilicity, electronegativity, hardness, HOMO-LUMO gap etc. are calculated and discussed.

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2 13C → 1H transfer of light-induced hyperpolarization allows for selective detection of protons in frozen photosynthetic reaction center 2018-06-17             

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Publication date: August 2018
Source:Journal of Magnetic Resonance, Volume 293

Author(s): Pavlo Bielytskyi, Daniel Gräsing, Kaustubh R. Mote, Karthick Babu Sai Sankar Gupta, Shimon Vega, P.K. Madhu, A. Alia, Jörg Matysik

In the present study, we exploit the light-induced hyperpolarization occurring on 13C nuclei due to the solid-state photochemically induced dynamic nuclear polarization (photo-CIDNP) effect to boost the NMR signal intensity of selected protons via inverse cross-polarization. Such hyperpolarization transfer is implemented into 1H-detected two-dimensional 13C–1H correlation magic-angle-spinning (MAS) NMR experiment to study protons in frozen photosynthetic reaction centers (RCs). As a first trial, the performance of such an experiment is tested on selectively 13C labeled RCs from the purple bacteria of Rhodobacter sphaeroides. We observed response from the protons belonging to the photochemically active cofactors in their native protein environment. Such an approach is a potential heteronuclear spin-torch experiment which could be complementary to the classical heteronuclear correlation (HETCOR) experiments for mapping proton chemical shifts of photosynthetic cofactors and to understand the role of the proton pool around the electron donors in the electron transfer process occurring during photosynthesis.

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3 Synthesis of luminescent CePO4:Tb/Au composite for glucose detection 2018-06-17             

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Publication date: December 2018
Source:Dyes and Pigments, Volume 159

Author(s): Guanwen Yan, Yuan Zhang, Weihua Di, Weiping Qin

The glucose oxidase (GOx) is commonly used as targeting molecule for glucose detection since a specific enzymatic reaction can occur, namely, catalytic oxidation of glucose by GOx. However, the intrinsic denaturation of natural enzyme is a problem in the use that leads to the detection inaccuracy and unstability. Here, we designed and prepared the luminescent CePO4:Tb/Au composite for glucose sensing, in which small-sized Au nanoparticles possess GOx-mimicking activity for catalytic oxidation of glucose and the in situ generated H2O2 quenches the luminescence of CePO4:Tb, enabling the fluorescent detection of glucose. The quenching of luminescence in dilute solutions can be well described by the Stern-Volmer relationship in a wide analyte concentration range with the Ksv quenching constant of 13070 M−1. A detection limit of 5.25 μM and a good sensing selectivity were achieved. More importantly, the problem of unstability using natural enzyme in the glucose determination can be efficiently solved by using Au as catalyst instead of GOx due to long-term preserved catalytic activity of Au. Therefore, our developed fluorescent system for glucose detection is potential in the biochemical analysis.

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4 Ambivalence, naturalness and normality in public perceptions of carbon capture and storage in biomass, fossil energy, and industrial applications in the United Kingdom 2018-06-17             

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Publication date: December 2018
Source:Energy Research & Social Science, Volume 46

Author(s): Gareth Thomas, Nick Pidgeon, Erin Roberts

Carbon dioxide capture and storage (CCS) is a promising yet controversial climate change mitigation technology. While numerous studies have addressed perceptions of CCS in fossil energy applications, less attention has been paid to how other applications of the technology may be viewed by lay groups. This article reports on findings from a twoday deliberative focus group held near Drax power station; a coal-biomass co-firing power plant in the north of England. In so doing we adopt a broad, psycho-socially inspired conception of perceived naturalness in order to explore how perceptions of CCS in biomass, fossil fuel, and industrial applications are formed in the context of a range of potential technologies for supporting low carbon energy system transitions. In particular, we explore how perceptions of naturalness and interdependency shaped perceptions of different CCS applications. Our analysis illustrates how perceptions of CCS as threatening, uncanny disruptions to natural systems may shift when re-contextualised to include concerns relating to the intermittency of renewable energy, or be ameliorated through perceptions of industrial and bioenergy applications as supporting natural and economic interdependencies.





5 Deep learning and its applications to machine health monitoring 2018-06-17             

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Publication date: 15 January 2019
Source:Mechanical Systems and Signal Processing, Volume 115

Author(s): Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao, Peng Wang, Robert X. Gao

Since 2006, deep learning (DL) has become a rapidly growing research direction, redefining state-of-the-art performances in a wide range of areas such as object recognition, image segmentation, speech recognition and machine translation. In modern manufacturing systems, data-driven machine health monitoring is gaining in popularity due to the widespread deployment of low-cost sensors and their connection to the Internet. Meanwhile, deep learning provides useful tools for processing and analyzing these big machinery data. The main purpose of this paper is to review and summarize the emerging research work of deep learning on machine health monitoring. After the brief introduction of deep learning techniques, the applications of deep learning in machine health monitoring systems are reviewed mainly from the following aspects: Auto-encoder (AE) and its variants, Restricted Boltzmann Machines and its variants including Deep Belief Network (DBN) and Deep Boltzmann Machines (DBM), Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). In addition, an experimental study on the performances of these approaches has been conducted, in which the data and code have been online. Finally, some new trends of DL-based machine health monitoring methods are discussed.





6 Localization algorithm of energy efficient radio spectrum sensing in cognitive internet of things radio networks 2018-06-17             

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Publication date: December 2018
Source:Cognitive Systems Research, Volume 52

Author(s): Yubao Wu

Spectrum sensing is a key problem of implementing cognitive radio (CR). Some malicious users falsify data, which reduces the performance of spectrum sensing. To this end, trustful cluster-based cooperative compressed spectrum sensing (TCBCSS) algorithm is proposed orienting to malicious user environment. Maximum likelihood (ML) is firstly used for estimating the distance from the cluster to the primary user, and the distance is compared with the preset threshold value so as to seek for the trustful cluster. Then, the channel condition is detected using the compressed spectrum sensing algorithm according to the information provided by the trustful cluster. The simulation result indicates that the proposed TCBCSS algorithm could cope with the malicious user environment effectively, detect the malicious user accurately, and maintain high spectrum detection rate.





7 Basis-updating for data compression of displacement maps from dynamic DIC measurements 2018-06-16             

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Publication date: 15 January 2019
Source:Mechanical Systems and Signal Processing, Volume 115

Author(s): Yen-Hao Chang, Weizhuo Wang, Thorsten Siebert, Jen-Yuan Chang, John E. Mottershead

The extraction of useful information and removal of redundant noise from data has become a major research topic in recent years. Data compression is necessary for all kinds of analysis, and the demand for efficient compression techniques has gained much attention. Digital image correlation is a camera-based measuring system, which has been widely applied in strain analysis because of the convenience of measuring displacement fields by simply selecting a region of interest. Currently, there is interest in applying such methods to engineering structures in dynamics. However, one of the major issues related to the integration of camera-based systems with dynamic measurement is the generation of huge amounts of data, typically extending to many thousands of data points, because of the requirements of high sampling rate, spatial resolution, and long duration of recording. In this paper a new algorithm is presented that addresses the need for efficiency in full-field data processing. By making use of the data itself and combining the concept of sparse representation with Gram-Schmidt orthogonalisation, the number of basis function used to represent the data can be reduced and a concise decomposition established. In both simulated and experimental cases, the compression ratios for data size and number of signals used in operational modal analysis are substantially diminished, thereby demonstrating the effectiveness of the proposed algorithm. A reduced number of new basis functions is determined for the representation of data under the condition that the reconstructed displacement map reproduces the raw measured data to within a chosen threshold on the coefficient of correlation.





8 Numerical aspects of the nonstationary modified linearized Bregman algorithm 2018-06-16             

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Publication date: 15 November 2018
Source:Applied Mathematics and Computation, Volume 337

Author(s): Alessandro Buccini, Yonggi Park, Lothar Reichel

The solution of discrete ill-posed problems has been a subject of research for many years. Among the many methods described in the literature, the Bregman algorithm has attracted a great deal attention and been widely investigated. Recently, a nonstationary preconditioned version of this algorithm, referred to as the nonstationary modified linearized Bregman algorithm, was proposed. The aim of this paper is to discuss numerical aspects of this algorithm and to compare computed results with known theoretical properties. We also discuss the effect of several parameters required by the algorithm on the computed solution.





9 13C→1H transfer of light-induced hyperpolarization allows for selective detection of protons in frozen photosynthetic reaction center 2018-06-09             

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Publication date: Available online 8 June 2018
Source:Journal of Magnetic Resonance

Author(s): Pavlo Bielytskyi, Daniel Gräsing, Kaustubh R. Mote, Karthick Babu Sai Sankar Gupta, Shimon Vega, P.K. Madhu, A. Alia, Jörg Matysik

In the present study, we exploit the light-induced hyperpolarization occurring on 13C nuclei due to the solid-state photochemically induced dynamic nuclear polarization (photo-CIDNP) effect to boost the NMR signal intensity of selected protons via inverse cross-polarization. Such hyperpolarization transfer is implemented into 1H-detected two-dimensional 13C-1H correlation magic-angle-spinning (MAS) NMR experiment to study protons in frozen photosynthetic reaction centers (RCs). As a first trial, the performance of such an experiment is tested on selectively 13C labeled RCs from the purple bacteria of Rhodobacter sphaeroides. We observed response from the protons belonging to the photochemically active cofactors in their native protein environment. Such an approach is a potential heteronuclear spin-torch experiment which could be complementary to the classical heteronuclear correlation (HETCOR) experiments for mapping proton chemical shifts of photosynthetic cofactors and to understand the role of the proton pool around the electron donors in the electron transfer process occurring during photosynthesis.

Graphical abstract

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10 Influenza DNA vaccine purification using pHEMA cryogel support 2018-06-08             

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Publication date: 29 November 2018
Source:Separation and Purification Technology, Volume 206

Author(s): Tiago Santos, Andreia Brito, Renato Boto, Pedro Sousa, Paulo Almeida, Carla Cruz, Cândida Tomaz

Influenza virus is a huge financial and social burden for health care systems over the world. Currently, traditional approaches are not effective in the fight of the epidemy and new alternatives like DNA vaccines have been developed. However, the downstream process of DNA vaccines is a constant challenge in the biotechnology industry. Cryogels has several advantages over traditional supports and have been tested as stationary phase in chromatographic separations. In this work, a method based on poly(2-hydroxyethyl methacrylate) cryogel was used to purify the plasmid NTC7482-41H-VA2 HA, which express the Influenza hemagglutinin gene. For this purpose, the cryogel was synthesized by cryo-polymerization of 2-hydroxyethyl methacrylate and characterized by scanning electron microscopy. The purification of supercoiled isoform of the plasmid NTC7482-41H-VA2 HA from a clarified lysate sample was achieved in a two-step experiment using NaCl and the dynamic binding capacity of pHEMA cryogel was determined. The assessment of DNA vaccine allowed to conclude that the level of contaminants such as proteins, genomic DNA, RNA and endotoxins are in accordance with FDA agency.





 
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