bluuebunny/crossref_metadata_2025 huggingface dataset:
Functional regulation of von Willebrand factor ameliorates acute ischemia-reperfusion kidney injury in mice
Authors: Ono Shiro , Matsui Hideto , Noda Masashi , Kasuda Shogo , Yada Noritaka , Yoshimoto Kiyomi , Akiyama Masashi , Miyata Toshiyuki , Sugimoto Mitsuhiko , Nishio Kenji
Published: October 2019

Acute kidney injury (AKI), an abrupt loss of renal function, is often seen in clinical settings and may become fatal. In addition to its hemostatic functions, von Willebrand factor (VWF) is known to play a role in cross-talk between inflammation and thrombosis. We hypothesized that VWF may be involved in the pathophysiology of AKI, major causes of which include insufficient renal circulation or inflammatory cell infiltration in the kidney. To test this hypothesis, we studied the role of VWF in AKI using a mouse model of acute ischemia-reperfusion (I/R) kidney injury. We analyzed renal function and blood flow in VWF-gene deleted (knock-out; KO) mice. The functional regulation of VWF by ADAMTS13 or a function-blocking anti-VWF antibody was also evaluated in this pathological condition. Greater renal blood flow and lower serum creatinine were observed after reperfusion in VWF-KO mice compared with wild-type (WT) mice. Histological analysis also revealed a significantly lower degree of tubular damage and neutrophil infiltration in kidney tissues of VWF-KO mice. Both human recombinant ADAMTS13 and a function-blocking anti-VWF antibody significantly improved renal blood flow, renal function and histological findings in WT mice. Our results indicate that VWF plays a role in the pathogenesis of AKI. Proper functional regulation of VWF may improve the microcirculation and vessel function in the kidney, suggesting a novel therapeutic option against AKI.
Modulation of PTH1R signaling by an ECD binding antibody results in inhibition of β-arrestin 2 coupling
Authors: Sarkar Kaushik , Joedicke Lisa , Westwood Marta , Burnley Rebecca , Wright Michael , McMillan David , Byrne Bernadette
Published: October 2019

Parathyroid hormone receptor 1 (PTH1R) belongs to the secretin class of G protein coupled receptors (GPCRs) and natively binds parathyroid hormone (PTH) and parathyroid hormone related peptide (PTHrP). Ligand binding to PTH1R involves binding to the large extracellular domain (ECD) and the orthosteric pocket, inducing conformational changes in the transmembrane domain and receptor activation. PTH1R regulates bone metabolism, signaling mainly through Gs and Gq/11 G-proteins. Here, we used phage display to generate PTH1R ECD-specific antibodies with the aim of modulating receptor functionality. We identified ECD-scFvhFc, which exhibited high affinity binding to both the isolated ECD and to the full-length receptor in styrene-maleic acid (SMA) lipid particles. Epitope mapping using hydrogen-deuterium exchange mass spectrometry (HDX-MS) indicates that the α1 helix of the ECD is ECD-scFvhFc’s epitope which may partially overlap with the known PTH (1–34) binding site. However, PTH (1–34)-mediated Gs activation is Undisturbed by ECD-scFvhFc binding. In contrast, ECD-scFvhFc potently inhibits β-arrestin-2 recruitment after PTH (1–34)-driven receptor activation and thus represents the first monoclonal antibody to selectively inhibit distinct PTH1R signaling pathways. Given the complexity of PTH1R signaling and the emerging importance of biased GPCR activation in drug development, ECD-scFvhFc could be a valuable tool to study PTH1R signaling bias.
HyPer2 imaging reveals temporal and heterogeneous hydrogen peroxide changes in denervated and aged skeletal muscle fibers in vivo
Authors: Staunton C. A. , Owen E. D. , Pollock N. , Vasilaki A. , Barrett-Jolley R. , McArdle A. , Jackson M. J.
Published: October 2019

To determine the role of denervation and motor unit turnover in the age-related increase in skeletal muscle oxidative stress, the hydrogen peroxide (H2O2) specific, genetically-encoded, fluorescentcyto-HyPer2probe was expressed in mouse anterior tibialis (AT) muscle and compared withex vivomeasurements of mitochondrial oxidant generation. Crush of the peroneal nerve induced increased mitochondrial peroxide generation, measured in permeabilised AT fibersex vivoandintra vitalconfocal microscopy ofcyto-HyPer2fluorescence showed increased cytosolic H2O2in a sub-set (~24%) of individual fibers associated with onset of fiber atrophy. In comparison, mitochondrial peroxide generation was also increased in resting muscle from old (26 month) mice compared with adult (6–8 month) mice, but no age effect on fiber cytosolic H2O2in vivowas seen. Thus ageing is associated with an increased ability of muscle fibers to maintain cytosolic redox homeostasis in the presence of denervation-induced increase in mitochondrial peroxide generation.
Autocatalytic amplification of Alzheimer-associated Aβ42 peptide aggregation in human cerebrospinal fluid
Authors: Frankel Rebecca , Törnquist Mattias , Meisl Georg , Hansson Oskar , Andreasson Ulf , Zetterberg Henrik , Blennow Kaj , Frohm Birgitta , Cedervall Tommy , Knowles Tuomas P. J. , Leiding Thom , Linse Sara
Published: October 2019

Alzheimer’s disease is linked to amyloid β (Aβ) peptide aggregation in the brain, and a detailed understanding of the molecular mechanism of Aβ aggregation may lead to improved diagnostics and therapeutics. While previous studies have been performed in pure buffer, we approach the mechanism in vivo using cerebrospinal fluid (CSF). We investigated the aggregation mechanism of Aβ42 in human CSF through kinetic experiments at several Aβ42 monomer concentrations (0.8–10 µM). The data were subjected to global kinetic analysis and found consistent with an aggregation mechanism involving secondary nucleation of monomers on the fibril surface. A mechanism only including primary nucleation was ruled out. We find that the aggregation process is composed of the same microscopic steps in CSF as in pure buffer, but the rate constant of secondary nucleation is decreased. Most importantly, the autocatalytic amplification of aggregate number through catalysis on the fibril surface is prevalent also in CSF.
Marangoni-driven spreading of miscible liquids in the binary pendant drop geometry
Authors: Koldeweij Robin B. J. , van Capelleveen Bram F. , Lohse Detlef , Visser Claas Willem
Published: October 2019

The Marangoni-driven spreading dynamics of binary pendant droplets show a remarkable consistency with other geometries. A single power law describes a large array of Marangoni-driven spreading in binary liquid systems.
Raman spectroscopy for rapid intra-operative margin analysis of surgically excised tumour specimens
Authors: Hubbard Thomas James Eliot , Shore Angela , Stone Nicholas
Published: October 2019

A review of the progress and remaining challenges to the application of Raman spectroscopy for intraoperative margin analysis in cancer.
Substrate stiffness affects the immunosuppressive and trophic function of hMSCs via modulating cytoskeletal polymerization and tension
Authors: Ji Yurong , Li Jing , Wei Yingqi , Gao Wendong , Fu Xiaoling , Wang Yingjun
Published: October 2019

Soft substrates improve the immunosuppressive and trophic function of hMSCs via cytoskeleton inhibition.
Hybrid mesoporous nanorods with deeply grooved lateral faces toward cytosolic drug delivery
Authors: Sun Kaiyao , Ding Tao , Xing Yuxin , Mo Dong , Zhang Jixi , Rosenholm Jessica M.
Published: October 2019

Hybrid mesoporous nanorods with six twisted sharp edges can induce effective penetration of intracellular barriers and cytosolic delivery of membrane-impermeable drugs through curvature effects.
Recent advances in the synthesis and applications of α-(trifluoromethyl)styrenes in organic synthesis
Authors: Tian Feitao , Yan Guobing , Yu Jian
Published: October 2019

α-Trifluoromethylstyrene derivatives are versatile synthetic intermediates for the preparation of more complex fluorinated compounds.
Elemental sulfur-promoted one-pot synthesis of 2-(2,2,2-trifluoroethyl)benzoxazoles and their derivatives
Authors: Li Zhengyu , Dong Jingnan , Wang Junwen , Yang Ding-Yah , Weng Zhiqiang
Published: October 2019

An elemental sulfur promoted one-pot synthesis of 2-(2,2,2-trifluoroethyl)benzoxazole derivatives from the reaction of o-aminophenols, thiols, and anilines with 2-bromo-3,3,3-trifluoropropene is reported.
A symmetry interaction approach to [M2L2]4+ metallocycles and their self-catenation
Authors: Preston Dan , Inglis Amanda R. , Garden Anna L. , Kruger Paul E.
Published: October 2019

A symmetry interaction approach to [M2L2]4+ metallocycles and their self-catenanes.
Enantioselective aryl–aryl coupling facilitated by chiral binuclear gold complexes
Authors: Himmelstrup Jonas , Buendia Mikkel B. , Sun Xing-Wen , Kramer Søren
Published: October 2019

The first example of highly enantioselective aryl–aryl coupling mediated by chiral gold complexes is reported.
Structural phase transitions in VSe2: energetics, electronic structure and magnetism
Authors: Pushkarev Georgy V. , Mazurenko Vladimir G. , Mazurenko Vladimir V. , Boukhvalov Danil W.
Published: October 2019

First principles calculations of the magnetic and electronic properties of VSe2 describing the transition between two structural phases (H,T) were performed.
Effect of atomicity on the oxidation of cationic copper clusters studied using thermal desorption spectrometry
Authors: Wang Haohao , Miyajima Ken , Kudoh Satoshi , Mafuné Fumitaka
Published: October 2019

The resistivity to oxidation of small copper clusters, Cun+ (n ≤ 5), in the gas phase with a precise atomicity at the molecular level was investigated using a combination of thermal desorption spectrometry and mass spectrometry.
Ce/MgAl mixed oxides derived from hydrotalcite LDH precursors as highly efficient catalysts for ketonization of carboxylic acid
Authors: Jiang Binbo , Xi Zhixiang , Lu Feipeng , Huang Zhengliang , Yang Yao , Sun Jingyuan , Liao Zuwei , Wang Jingdai , Yang Yongrong
Published: October 2019

Ketonization of carboxylic acids provides an attractive way for upgrading biomass feedstocks into biofuels.
The consequences of surface heterogeneity of cobalt nanoparticles on the kinetics of CO methanation
Authors: Castillo José , Arteaga-Pérez Luis E. , Karelovic Alejandro , Jiménez Romel
Published: October 2019

The CO hydrogenation reaction was studied under methanation conditions (H2/CO >3, 250–300 °C) on Co/SiO2catalysts with different mean Co nanoparticle size (dp= 4 nm, 13 nm and 33 nm).
Laser induced ion migration in all-inorganic mixed halide perovskite micro-platelets
Authors: Wang Ziming , Wang Yue , Nie Zhonghui , Ren Yinjuan , Zeng Haibo
Published: October 2019

All-inorganic mixed hybrid halide micro-platelet single crystals were fabricated and the photoinduced ion migration mechanism was investigated.
Subnanometer iron clusters confined in a porous carbon matrix for highly efficient zinc–air batteries
Authors: Wu Xin , Dong Juncai , Qiu Mei , Li Yang , Zhang Yongfan , Zhang Huabin , Zhang Jian
Published: October 2019

We describe a facile synthetic protocol to realize the decoration of Fe coordinates at the subnanometer scale into a three-dimensional porous carbon matrix, which great promotes the oxygen reduction reaction compared with isolated Fe atoms.
Reactive nanotemplates for synthesis of highly efficient electrocatalysts: beyond simple morphology transfer
Authors: Kim Jun , Jun Minki , Choi Songa , Jo Jinhyoung , Lee Kwangyeol
Published: October 2019

Template-mediated synthesis using reactive nanotemplates via various chemical conversion reactions to yield highly efficient electrocatalysts.
A unipolar nonvolatile resistive switching behavior in a layered transition metal oxide
Authors: Wang Junjun , Wang Feng , Yin Lei , Sendeku Marshet Getaye , Zhang Yu , Cheng Ruiqing , Wang Zhenxing , Li Ningning , Huang Wenhao , He Jun
Published: October 2019

Nonvolatile resistive random access memories based on synthesized two-dimensional α-MoO3 crystals are demonstrated with high performances.
Co3O4 nanoparticles supported on N-doped electrospinning carbon nanofibers as an efficient and bifunctional oxygen electrocatalyst for rechargeable Zn–air batteries
Authors: Qiu Liuzhe , Han Xiaopeng , Lu Qi , Zhao Jun , Wang Yang , Chen Zelin , Zhong Cheng , Hu Wenbin , Deng Yida
Published: October 2019

This work demonstrates the controllable synthesis of Co3O4 nanoparticles supported on N-doped electrospun carbon nanofibers as an efficient and bifunctional oxygen electrocatalyst for rechargeable zinc–air batteries.
A 2D layer network assembled from an open dendritic silver cluster Cl@Ag11N24and an N-donor ligand
Authors: Li Xiao-Yu , Su Hai-Feng , Xu Jian
Published: October 2019

A 2D layer network was synthesized from an N-donor ligand and a new silver cluster featuring an open dendritic structure with a high coordination ratio of N atom. Both the assembly process and luminescence properties of this complex was studied.
Insights into the interaction of potent antimicrobial chalcone triazole analogs with human serum albumin: spectroscopy and molecular docking approaches
Authors: Yadav Priyanka , Yadav Jitendra Kumar , Agarwal Alka , Awasthi Satish K.
Published: October 2019

Mechanistic insights into the interaction of five previously chemically synthesized triazole-linked chalcone analogs with human serum albumin were analyzed using UV-visible absorption, fluorescence quenching, circular dichroism and molecular docking studies.
Self-assembly and adsorption of cetyltrimethylammonium bromide and didodecyldimethylammonium bromide surfactants at the mica–water interface
Authors: Tsagkaropoulou Georgia , Allen Finian J. , Clarke Stuart M. , Camp Philip J.
Published: October 2019

Molecular-dynamics simulations are used to explore bilayers formed by simple ionic surfactants at the mica–water interface, and to shed light on experimental observations.
Molecular dynamics simulation of microscopic friction mechanisms of amorphous polyethylene
Authors: Zhan Shengpeng , Xu Haiping , Duan Haitao , Pan Lin , Jia Dan , Tu Jiesong , Liu Lian , Li Jian
Published: October 2019

Determining the nature of microscopic mechanism of friction and wear by experimental method is a challenge. Molecular simulation technology is an effective method for exploring microscopic friction mechanisms of polymers.
Rolling friction of elastomers: role of strain softening
Authors: Tiwari A. , Miyashita N. , Persson B. N. J.
Published: October 2019

We study the temperature and velocity dependency of rolling friction.
Influence of sodium diffusion from substrates on performance of SnS/CdS thin-film solar cells
Authors: Cho Jae Yu , Shin Kyeongrok , Lee Hyo Seok , Neerugatti KrishnaRao Eswar , Heo Jaeyeong
Published: October 2019

The influence of Na diffused from substrates on SnS/CdS thin-film solar cells was investigated.
Patch orientation‐specified network for learning‐based image super‐resolution
Authors: Yoo S.B. , Han M.
Published: October 2019

Learning‐based image super‐resolution is considered as a promising solution to reconstruct a high‐resolution image from a low‐resolution image. To improve the super‐resolution performance dramatically, this Letter focuses on the effect of training dataset on the performance and proposes an image super‐resolution scheme based on patch orientation‐specified network. In particular, a deep neural network is trained using patches with a specific orientation and angular transformation is combined with the neural network to cope with various orientations in input patches. Experimental results show the suggested network model is superior to existing state‐of‐the‐art super‐resolution alternatives.
Automatic object model generation for nanoelectronics using C++ meta programming
Authors: Peng Fei , Xiao Zhenjie , Xu Dong , Huang Jianhong , Xie Guangjun
Published: October 2019

Since the development of nanoelectronics is at its early stage, a lot of different devices have been proposed. Accompanying the increasing research interests in nanodevices, developing effective design automation algorithms in different abstraction levels becomes an urgent need. However, the prosperity in the device aspect results a unique difficulty in the algorithm aspect, i.e. it is hard to provide a common object model, data structure used in design automation algorithms, for a specific nanodevice. To freeing algorithm researchers from developing different object models with only minor differences in different algorithms, the authors propose a method of creating object model automatically through C++ template meta programming. A concrete object model for quantum‐dot cellular automata is illustrated as an example.
Fast decoding of binary quadratic residue codes
Authors: Saouter Y.
Published: October 2019

In a recent study, Li et al. proposed an algorithm for the decoding of binary quadratic residue codes with tiny memory requirements. In this Letter, this algorithm is modified in order to dramatically improve the decoding speed. The case of the binary quadratic residue code is used to illustrate the new algorithm.
Efficient active multiplier‐based signal source for >300 GHz system applications
Authors: Hossain M. , Boppel S. , Heinrich W. , Krozer V.
Published: October 2019

This Letter presents a 300 GHz signal source, realised using an 800 nm transferred‐substrate InP double heterojunction bipolar transistor process. The source is based on an active frequency tripler. It delivers −1.6 dBm peak output power at 306 GHz. The DC consumption is only 36 mW, which corresponds to 2% conversion efficiency. The measured tripler achieves more than 30 GHz bandwidth and exhibits very low unwanted harmonics. The chip area of the source is only 0.94 × 0.84 mm2.
Low‐complexity energy‐efficient power allocation scheme for distributed MISO system with beamforming
Authors: Xu Weiye , Yu Xiangbin , Teng Tao
Published: October 2019

This letter investigates the energy efficiency (EE) optimisation of a distributed multiple‐input single‐output (D‐MISO) system, and a suboptimal power allocation (PA) scheme with low complexity is developed for D‐MISO system with beamforming. Different from the existing optimal PA scheme that needs iterative calculation, the developed scheme can provide closed‐form PA and no iteration is required. Using the Cauchy–Schwarz inequality, the upper bound of EE is first obtained, and then the optimised objective function is formulated subject to a set of power budget constraints. By maximising this upper bound, a suboptimal PA scheme for the system is derived, and closed‐form PA coefficients are attained. Interestingly, it is found that the proposed scheme has the same general form of PA as the optimal scheme. Numerical results verify the effectiveness of the proposed scheme, it can achieve the EE performance very close to that of the existing optimal scheme due to better approximation, but it has lower complexity than the latter.
Synchronisation correction‐based colour image watermarking using proximal classifier with consistency and multivariate generalised Gaussian model
Authors: Wang Qian , Wen Taotao , Yang Hongying , Wang Xiangyang
Published: October 2019

In this Letter, a novel synchronisation correction‐based colour image watermarking approach is proposed to resist geometric distortions. The Cb channel of the YCbCr colour host image is first decomposed by a two‐level contourlet transform, and binary watermark image is embedded into the host image by modifying the lowpass coefficients. Then the multivariate generalised Gaussian distribution is used to capture the significant features of colour images, and the proximal classifier with consistency is employed to estimate geometric distortion parameters. Finally, the watermark image is extracted from the corrected watermarked image. Simulation results demonstrate that the presented approach shows excellent robustness against various common image processing attacks and geometric attacks while guaranteeing invisibility.
Mitigation of target distortion in pulse‐agile sensors via Richardson–Lucy deconvolution
Authors: Kirk B.H. , Martone A.F. , Sherbondy K.D. , Narayanan R.M.
Published: October 2019

Pulse‐agile radar systems are becoming more prevalent as the demand for adaptive and cognitive systems increases. This focus is motivated by the need for interference avoidance and spectrum sharing. Pulse agility within a coherent processing interval (CPI) or intra‐CPI adaption has been shown to cause distortion, which will negatively impact the radar's performance. This problem can be framed in the context of image processing such that an ideal range–Doppler image is corrupted by some point spread function. Deconvolution is then applied to remove this distortion and improve radar performance while maintaining the ability to use computationally efficient fast Fourier transform‐based processing.
Sample generation of semi‐automatic pavement crack labelling and robustness in detection of pavement diseases
Authors: Jia Guohui , Song Weidong , Jia Di , Zhu Hong
Published: October 2019

Recent convolutional neural networks have made significant advancements in the detection of road cracks. However, the lack of accurate crack training data reduces the generalisation ability of the deep model. In this Letter, a semi‐automatic pavement crack labelling algorithm is proposed to solve the problem of insufficient training data. First, the modified C–V model is used to obtain the preliminary segmentation results. Second, the direction of the initial segmentation area is calculated by the ellipse fitting method, and the preliminary segmentation results are used as samples for accurate labelling. Finally, a multi‐scale feature extraction module is proposed for learning rich deep convolutional features, which allows the acquired crack features under a complex background to be more discriminant. The experimental results were compared with the manual marking method, and this method can achieve accurate marking of crack images with a low amount of interaction, thereby significantly reducing the cost of ground‐truth making. The results of the validation and comparison experiments on test data sets indicate that the proposed method can not only effectively identify cracks, but also overcome the interference of many factors in the environment.
Differentiation of EMCI in sMR images using segmented brainstem multifractal texture measures
Authors: Palanisamy R. , Swaminathan R. , Sundar S.
Published: October 2019

In this Letter, an attempt has been made to segment the brainstem structure from structural magnetic resonance (sMR) images and differentiate early mild cognitive impairment (EMCI) from normal and Alzheimer's condition using multifractal texture measures. The images considered from public domain database are preprocessed and brainstem is segmented using fuzzy ‘C’ means‐based connected component labelling method. Multifractal spectrum (MS) is evaluated for the segmented brainstem structure using the multifractal detrended moving average technique. Seven MS‐based texture measures are extracted and statistically analysed using one‐way analysis of variance. Classification algorithms namely, naïve Bayes, decision tree and random forest (RF) are employed to distinguish the EMCI condition. Ten‐fold cross‐validation approach is executed and its performance is evaluated using accuracy, precision, recall and area under the curve. The results indicate that the segmented brainstem structures possess multifractal characteristics. Of the extracted MS‐based texture measures, αmax, α0, αR, B and Δα are found to be statistically significant. RF gives the highest accuracy of 92.3% in distinguishing EMCI from other subject groups. Hence, the proposed approach with brainstem MS‐based texture measures in combination with RF can be used as an imaging biomarker for the diagnosis of EMCI.
CSO secret communication
Authors: Yan Senlin
Published: October 2019

A chaos shift parameter synchronisation (CSPS) system based on two different mutually coupled lasers synchronising with another laser is studied while a novel chaos shift orbit (CSO) encoding technique is presented for secret communication. CSPS between the emitter and receiver can still be obtained by shifting the emitter's parameter in real time, where the emitter operates its chaos to vary its orbit or jump across its orbit by using real‐time current changes of one laser. Then, a CSO encoding scheme is implemented successfully. The emitter has numerous real‐time shifting secret keys, so it is highly secure, and the signal is difficult to decipher.
Frequency‐modulated continuous‐wave light detection and ranging with sinusoidal frequency modulation and beat phase detection
Authors: Tsuchida H.
Published: October 2019

The performance of a frequency‐modulated continuous‐wave light detection and ranging is severely limited by the inherent non‐linear chirp when laser diodes with direct frequency modulation are used as light sources. The author proposes and demonstrates a new modulation and detection scheme that is immune to non‐linear chirp. Sinusoidal frequency modulation and beat phase detection are employed for measuring both the velocity and distance of a target. Relative accuracies below ± 2 mm/s and ± 1 mm are confirmed for velocity and distance measurements, respectively, in the proof‐of‐principle experiment.
Optimising earliest deadline first scheduling for parallel real‐time tasks on multiprocessors
Authors: Kim C. , Cho H. , Sung Y.
Published: October 2019

Multiprocessors have become prevalent in real‐time systems owing to their higher throughput. Various types of scheduling algorithms have been proposed for parallel real‐time tasks, which differ from traditional tasks in that their subtasks execute in parallel. A parallel task is frequently modelled as a directed acyclic graph (DAG) that expresses the precedence constraints between its subtasks. In this Letter, the authors propose a decomposition algorithm to improve the Earliest Deadline First schedulability for DAG tasks, based on convex optimisation theory. Their experimental results demonstrate that their algorithm outperforms the two most recently published algorithms.
Engineered gene networks enable non‐genetic drug resistance and enhanced cellular robustness
Authors: Camellato Brendan , Roney Ian J. , Azizi Afnan , Charlebois Daniel , Kaern Mads
Published: October 2019

Drug resistance complicates the treatment of cancer and infectious diseases, and often arises from the elevated expression of a gene that neutralises or reduces drug activity. To investigate this and other expression‐based mechanisms of drug resistance, the authors engineered a set of gene regulatory networks in the eukaryotic model organism Saccharomyces cerevisiae to control a homologue of the cancer‐related human multidrug resistance gene MDR1. Using this system, they explored experimentally how different gene regulatory network features, also called genetic network motifs, contribute to gene expression dynamics and cellular fitness. They observed that coherent feedforward and positive feedback motifs enable rapid and self‐sustained activation of gene expression, and enhance cell survival in the presence of a cytotoxic drug. These observations underscore that genetic network motifs can be critical for drug resistance and that genetic network engineering can be used to enhance cellular tolerance to cytotoxins or other environmental stresses.
Real‐time surgical instrument detection in robot‐assisted surgery using a convolutional neural network cascade
Authors: Zhao Zijian , Cai Tongbiao , Chang Faliang , Cheng Xiaolin
Published: October 2019

Surgical instrument detection in robot‐assisted surgery videos is an import vision component for these systems. Most of the current deep learning methods focus on single‐tool detection and suffer from low detection speed. To address this, the authors propose a novel frame‐by‐frame detection method using a cascading convolutional neural network (CNN) which consists of two different CNNs for real‐time multi‐tool detection. An hourglass network and a modified visual geometry group (VGG) network are applied to jointly predict the localisation. The former CNN outputs detection heatmaps representing the location of tool tip areas, and the latter performs bounding‐box regression for tool tip areas on these heatmaps stacked with input RGB image frames. The authors’ method is tested on the publicly available EndoVis Challenge dataset and the ATLAS Dione dataset. The experimental results show that their method achieves better performance than mainstream detection methods in terms of detection accuracy and speed.
Learning the representation of instrument images in laparoscopy videos
Authors: Kletz Sabrina , Schoeffmann Klaus , Husslein Heinrich
Published: October 2019

Automatic recognition of instruments in laparoscopy videos poses many challenges that need to be addressed, like identifying multiple instruments appearing in various representations and in different lighting conditions, which in turn may be occluded by other instruments, tissue, blood, or smoke. Considering these challenges, it may be beneficial for recognition approaches that instrument frames are first detected in a sequence of video frames for further investigating only these frames. This pre‐recognition step is also relevant for many other classification tasks in laparoscopy videos, such as action recognition or adverse event analysis. In this work, the authors address the task of binary classification to recognise video frames as either instrument or non‐instrument images. They examine convolutional neural network models to learn the representation of instrument frames in videos and take a closer look at learned activation patterns. For this task, GoogLeNet together with batch normalisation is trained and validated using a publicly available dataset for instrument count classifications. They compared transfer learning with learning from scratch and evaluate on datasets from cholecystectomy and gynaecology. The evaluation shows that fine‐tuning a pre‐trained model on the instrument and non‐instrument images is much faster and more stable in learning than training a model from scratch.
Development and face validation of ultrasound‐guided renal biopsy virtual trainer
Authors: Enquobahrie Andinet , Horvath Sam , Arikatla Sreekanth , Rosenberg Avi , Cleary Kevin , Sharma Karun
Published: October 2019

The overall prevalence of chronic kidney disease in the general population is ∼14% with more than 661,000 Americans having a kidney failure. Ultrasound (US)‐guided renal biopsy is a critically important tool in the evaluation and management of renal pathologies. This Letter presents KBVTrainer, a virtual simulator that the authors developed to train clinicians to improve procedural skill competence in US‐guided renal biopsy. The simulator was built using low‐cost hardware components and open source software libraries. They conducted a face validation study with five experts who were either adult/pediatric nephrologists or interventional/diagnostic radiologists. The trainer was rated very highly (>4.4) for the usefulness of the real US images (highest at 4.8), potential usefulness of the trainer in training for needle visualization, tracking, steadiness and hand‐eye coordination, and overall promise of the trainer to be useful for training US‐guided needle biopsies. The lowest score of 2.4 was received for the look and feel of the US probe and needle compared to clinical practice. The force feedback received a moderate score of 3.0. The clinical experts provided abundant verbal and written subjective feedback and were highly enthusiastic about using the trainer as a valuable tool for future trainees.
Influence of chamber structure on arc quenching in multigap system
Authors: Li Zijian , Wang Jufeng , Zhou Xin , Huang Shangshi , Yan Renbao , Xia Zhijian
Published: October 2019

In order to improve the arc quenching ability of the multigap system, it is important to know the principle of arc quenching and how the chamber structure affects the arc development process in the multigap system. In this study, the two‐dimensional geometric model of the multigap system is established based on the magnetohydrodynamics theory in COMSOL multiphysics simulation platform. The principle of arc quenching in the multigap system is explained in detail by analysing the physical characteristics of the arc in the multigap system. The simulation result shows that the arc is compressed at large scales in the semi‐closed chambers of the multigap system, which results in an instantaneous temperature rise of the arc, thus, forming the self‐expanding airflow. The strong self‐expanding airflow cuts off the arc channel and blocks the energy supply of the arc. The influence of the chamber structure on arc quenching in the multigap system is manifested in the fact that proper improvement of the width and depth of the chamber subserves arc cooling, the reduction of the deflection angle and the increment of the number of the chambers are conductive to arc extinction.
Classification of common discharges in outdoor insulation using acoustic signals and artificial neural network
Authors: Polisetty Satish , El‐Hag Ayman , Jayram Shesha
Published: October 2019

Condition monitoring of outdoor insulation systems is crucial to the integrity of distribution and transmission overhead lines and substations. The objective of this study is to use a commercial acoustic sensor along with artificial neural network (ANN), to classify different typical types of discharges in outdoor insulation systems. First, ANN was used to distinguish between five common electrical discharges that were generated under controlled conditions. Next, this approach was extended to include outdoor ceramic insulators. Three types of defects were tested under laboratory conditions, i.e. a crack in the ceramic disc, surface pollution discharge, and corona near the insulator surface. Both a single disc, and three discs connected in an insulator string were tested with respect to these defects. For both controlled samples and full insulators, a recognition rate of more than 85% was achieved.
Platinum modified MoS2 monolayer for adsorption and gas sensing of SF6 decomposition products: a DFT study
Authors: Gui Yingang , Shi Jinzhi , Yang Pingan , Li Tao , Tang Chao , Xu Lingna
Published: October 2019

In the long‐running of sulphur hexafluoride (SF6)‐insulated equipment, SF6 inevitably decomposes to various decomposition products under electric discharge, including SOF2 and SO2F2. In this work, single Pt modified molybdenum disulphide (Pt‐MoS2) monolayer, and double Pt modified molybdenum disulphide (Pt2‐MoS2) monolayer are proposed to analyse its adsorption and sensing properties to SOF2 and SO2F2 with single and double gas molecules adsorption based on density functional theory. The adsorption energy, density of states, and molecular orbit theory are employed to analyse the adsorption and sensing mechanism. It turns out that the Pt‐MoS2 and Pt2‐MoS2 present outstanding adsorption capacity to gas molecules. Specifically, double SOF2 adsorption on Pt2‐MoS2 shows the best adsorption performance, and the conductivity of the adsorption system changes the most in the adsorption process. Overall, both Pt‐MoS2 and Pt2‐MoS2 perform as an excellent gas sensor. This study provides a theoretical basis to develop Pt‐MoS2 and Pt2‐MoS2 based materials for SOF2 and SO2F2 detection in SF6‐insulated equipment.
Potential applications of 5G communication technologies in collaborative intelligent manufacturing
Authors: Shi Yanjun , Han Qiaomei , Shen Weiming , Zhang Hui
Published: October 2019

Nowadays most of the communication technologies used in the manufacturing industry are still wired, including various fieldbuses and dedicated industrial Ethernet technologies, though wireless communication technologies including WiFi and ZigBee are recently being adopted. This study is to investigate the integration of 5G wireless communication technologies with collaborative intelligent manufacturing (CIM) processes and systems. 5G technologies and typical scenarios including enhanced mobile broadband, massive machine type communications, and ultra‐reliable low latency communication are introduced. Various possible applications or business slices of 5G in CIM are analysed, including human–machine interfaces and production IT, process automation, factory automation, logistics and warehousing, monitoring, and maintenance. These applications are analysed by the functions as modules with the extended 5C architecture. A modular collaborative production approach is suggested to combine modules to achieve on‐demand resource allocation and complete flexible tasks in CIM systems. Related research challenges and opportunities are also discussed.
Ultra‐dense LoRaWAN: Reviews and challenges
Authors: Alenezi Mohammed , Chai Kok Keong , Chen Yue , Jimaa Shihab
Published: October 2019

Internet of Things (IoT) is one of the most cited terms within the communication research communities. Next generation wireless networks technologies are expected to have massive‐connections of tens of billions of devices. Such a huge number of devices raised a number of concerns in regards to how much accessible resources are available and what are the best technologies for managing those resources, all in order to avoid shutdowns/collapses in every means. In terms of wireless networks, and in regards to energy being the backbone of IoT devices, Low Power Wide Area Networks (LPWAN) technologies are considered to be a potential solution for IoT applications. In particular, this study reviews Long‐Range (LoRa) technology and advances in the literature of LoRaWAN protocol to date. Furthermore, it discusses the challenges in LoRaWAN and diverts the attention towards applying Ultra‐Dense Network concept on LPWAN.
Secrecy sum rate maximisation in multi‐antenna two‐way relay networks
Authors: Bozorgi Seyedeh Fatemeh , Akhlaghi Soroush
Published: October 2019

This study investigates the achievable secrecy rate of two‐way relay‐assisted networks. It is assumed that there is no direct link between transceiver ends and the communication is carried out in two hops through the use of multi‐antenna relays in the middle of transmission, where the relays employ amplify‐and‐forward strategies. To increase the bandwidth efficiency, intending nodes exchange their confidential messages in two hops. First, both nodes simultaneously send their messages to the relay nodes. Then, throughout the second hop, the relays make use of cooperative beamforming to send their incoming information in such a way that the achievable secrecy sum rate is maximised, considering each node is subject to a minimum secrecy rate constraint. Accordingly, two beamforming strategies, named as null‐space beamforming and information leakage alignment beamforming are proposed, where their achievable secrecy sum rates are investigated and compared to existing works addressed in the literature.
Performance analysis of sub‐optimal transmit and receive antenna selection amplify and forward cooperative communication
Authors: Bouteggui Mokhtar , Merazka Fatiha
Published: October 2019

In this study, the authors consider a multiple‐input–multiple‐output cooperative communication system, based on a single amplify‐and‐forward relay over a Rayleigh fading channel. They investigate the performance of two sub‐optimal transmit receive antenna selection (TRAS) schemes employing M‐ary phase shift keying (M‐PSK). They take the advantages of the moment generating function expression, to avoid the hypergeometric functions commonly used in literature. They derive analytical expressions for the symbol error rate (SER) based on two upper bounds of the instantaneous end‐to‐end signal‐to‐noise ratio (SNR), which are tightly lower bounded for the SER. In addition, an SER upper bound is derived for both TRAS strategies which gets tighter at high SNR. This upper bound is used to determine the system optimal power allocation. Diversity orders for both TRAS strategies are extracted. Their theoretical analysis shows that the SNR upper bound I is tighter compared to the SNR upper bound II especially for sub‐optimal strategy I. At high SNR, the derived SER upper bound approaches the derived SER. Interestingly, it is observed that the optimal power factors lead to a lower SER. Simulation results are presented in comparison with the derived SER for the two upper bounds.
E2‐SR: a novel energy‐efficient secure routing scheme to protect MANET‐IoT
Authors: Ponguwala Maitreyi , Rao Sreenivasa
Published: October 2019

Integration of mobile ad hoc networks (MANETs) and internet of things (IoT) becomes an emerging paradigm to enable opportunistic communication in IoT. However, the lack of infrastructure in MANET increases involvement of adversaries in IoT environment. Thus security provisioning against severe adversaries is still challenging in MANET‐IoT. In this paper, we propose an energy efficient secure routing (E2‐SR) scheme to ensure data security and integrity in MANET‐IoT. We adapt Certificate based authentication in Hash Chain based Certificate Authentication (HCCA) scheme. Cluster formation is involved with secure verification of IoT devices by elliptic curve group law formulations. For cluster formation, secure dual head clustering with elliptic curve verification (SDHC‐EC) algorithm is proposed. Secure routing is enabled by a new Worst Case Particle Swarm Optimization (WC‐PSO) algorithm. The WC‐PSO algorithm is supported by dual state markov chain model (DS‐MCM) for security enhancement. Data security is ensured with data integrity using novel dual XOR‐Rivest Cipher6 Encryption with Fuzzy Evaluation (DXOR‐RC6 with FE) algorithm. The proposed MANET‐IoT network is modeled and tested in ns‐3.26 environment. The evaluation shows that E2‐SR achieves better results in packet delivery ratio, throughput, residual energy, and routing overhead.
Module minimisation based low‐complexity soft decoding of Reed–Solomon codes
Authors: Xing Jiongyue , Chen Li , Bossert Martin
Published: October 2019

The interpolation‐based algebraic decoding for Reed–Solomon (RS) codes can correct errors beyond half of the code's minimum Hamming distance. Using soft information, the algebraic soft decoding (ASD) further improves the decoding performance. This paper presents a unified study of two classical ASD algorithms, the algebraic Chase decoding and the Koetter‐Vardy decoding. Their computationally expensive interpolation is solved by the module minimisation (MM) technique which consists of basis construction and basis reduction. Compared with Koetter's interpolation, the MM interpolation yields a smaller computational cost for the two ASD algorithms. Re‐encoding transform is further applied to reduce the decoding complexity by reducing the degree of module generators. Based on assessing the degree of module seeds, a complexity reducing approach is introduced to further facilitate the two ASD algorithms. Computational cost of the two algorithms as well as their re‐encoding transformed variants will be analysed. Performance of the two ASD algorithms will be compared under decoding expenditure benchmark, providing more practical insights of their applications.
CRB‐based performance analysis of semi‐blind channel estimation for massive MIMO‐OFDM systems with pilot contamination
Authors: Rekik Ouahbi , Ladaycia Abdelhamid , Mokraoui Anissa , Abed‐Meraim Karim
Published: October 2019

Channel estimation, which is a key task in massive multiple‐input multiple‐output orthogonal‐frequency division‐multiplexing systems (MIMO‐OFDM), is severely affected by the problem of pilot contamination during the uplink transmission. Thus, the aim of this study is to investigate, via the Cramér‐Rao Bound tool, the effectiveness of semi‐blind (SB) methods for pilot contamination mitigation. For synchronous cells, these analyses demonstrate the possibility to efficiently solve the pilot contamination problem, with SB approaches, when considering a finite‐alphabet (non‐Gaussian) communications signal. However, considering only the signal's Second Order Statistics is not enough for solving such an issue even if the SB approach is adopted. Moreover, the analyses show that it is possible to get close to the optimal performance with a SB approach even if the pilots are non‐orthogonal as long as they are not fully coherent. For the asynchronous cells case, it has been demonstrated that the pilot contamination still occurs under small inter‐cell delays, but can be strongly mitigated with large inter‐cell delays.
Residual self‐interference suppression guided resource allocation for full‐duplex orthogonal frequency division multiple access system
Authors: Zhang Jianhua , Ma Meng , Ma Jinghuan , Zou Ming , Jiao Bingli
Published: October 2019

In a wideband full‐duplex system, the residual self‐interference (SI) channel exhibits significant frequency selective fading characteristics after radio frequency SI cancellation. Resource allocation using the difference between the signal channel and the residual SI channel is a new method of suppressing residual SI and increasing system capacity. In this work, the residual SI channel and the user uplink channel are modelled as multi‐path frequency selective fading channels that satisfy the Rayleigh distribution. To improve system capacity, the authors propose to allocate the spectrum resource avoiding occupation of subcarriers with high residual SI, while guaranteeing a fair subcarrier assignment (SA) and power allocation (PA). A sum rate of uplink maximisation is formulated, and an algorithmic solution is developed to effectively conduct SA and PA. Numerical results demonstrate the effectiveness of the scheme in increasing system capacity and suppressing residual SI.
Advanced spatial modulation for efficient MIMO‐based B2B communications in sporting activities
Authors: Bhowal Anirban , Sapre Aditi Satsheel , Lalani Ronak , Kshetrimayum Rakhesh Singh
Published: October 2019

In this study, advanced multiple‐input multiple‐output (MIMO) techniques for body‐to‐body (B2B) sensor‐based communication for sporting activities like running and cycling under different scenarios have been proposed. Enhanced spatial modulation and spatial media‐based modulation have been investigated for efficient MIMO‐based B2B communication. Special sensors have been proposed to deploy such techniques. Lognormal (LN) mixture model has been used because it can address the shadowing effects in B2B communication for such activities. Since LN mixture cannot yield closed‐form expressions, it has been approximated using mixture of gamma (MG) distribution to achieve closed‐form expressions for bit error rate (BER) in MIMO‐based B2B communication for the first time. The system performance for the proposed methods has been analysed in terms of BER and theoretical upper bound expressions using MG distribution have been verified by Monte Carlo simulations.
Anomaly detection for cellular networks using big data analytics
Authors: Li Bing , Zhao Shengjie , Zhang Rongqing , Shi Qingjiang , Yang Kai
Published: October 2019

Broadband connectivity and mobile technology have been widely applied in the world. With these advanced technologies, the proliferation of smart devices and their applications by accessing mobile internet have come up with a giant leap forward, leading to the ever‐increasing scale and complexity of cellular networks. This presents imminent challenges to anomaly detection in cellular networks. In this study, the authors discuss challenges and current literature of anomaly detection for cellular networks to embrace the ‘big data’ era. First, they review the state‐of‐the‐art techniques in the area of anomaly detection in cellular networks. Then, the challenges are pinpointed for anomaly detection due to the cellular network big data. Finally, they introduce a big data analytic‐based anomaly detection method for cellular networks.