bluuebunny/crossref_metadata_2025 huggingface dataset:
Supramolecular assemblies involving salt bridges: DFT and X-ray evidence of bipolarity
Authors: Tripathi Suparna , Islam Samiul , Seth Saikat Kumar , Bauzá Antonio , Frontera Antonio , Mukhopadhyay Subrata
Published: October 2020

Three new aminopyridinium/4,4′-oxydibenzoate salts have been synthesized and structurally characterized. A common feature of these compounds is the formation of antiparallel π-stacked salt bridges.
From zero- to three-dimensional heterobimetallic coordination polymers with the [Pt{SSC-N(CH2COO)2}2]4− metalloligand
Authors: Liebing Phil , Oehler Florian , Witzorke Juliane , Schmeide Marten
Published: October 2020

A series of novel, structurally manifold heterobimetallic dithiocabamato-carboxylates (DTCCs) were efficiently prepared by a metalloligand approach.
Near-infrared-emitting AIE multinuclear cationic Ir(iii) complex-assembled nanoparticles for photodynamic therapy
Authors: Li Lijuan , Zhang Liping , Tong Xiaofan , Li Yite , Yang Zhiyu , Zhu Dongxia , Su Zhongmin , Xie Zhigang
Published: October 2020

The first pure NIR-emitting AIE multinuclear Ir(iii) complex NPs obtained by self-assembly exhibit excellent cell imaging and PDT performance.
High-throughput wastewater analysis for substance use assessment in central New York during the COVID-19 pandemic
Authors: Wang Shiru , Green Hyatt C. , Wilder Maxwell L. , Du Qian , Kmush Brittany L. , Collins Mary B. , Larsen David A. , Zeng Teng
Published: October 2020

Wastewater analysis provides insights into population lifestyle and health status during the coronavirus pandemic.
Investigating the background and local contribution of the oxidants in London and Bangkok
Authors: Khan M. Anwar H. , Holland Rayne , Foulds Amy , Matthews James C. , Panditharatne Sanjee , Jenkin Michael E. , Lowe Douglas , Navasumrit Panida , Percival Carl J. , Shallcross Dudley E.
Published: October 2020

Trends of oxidant levels in London and Bangkok roadside sites.
Delineating the enhanced efficiency of carbon nanomaterials including the hierarchical architecture of the photoanode of dye-sensitized solar cells
Authors: Srinivasan Venkatesan , Sivanadanam Jagadeeswari , Ramanujam Kothandaraman , Asha Jhonsi Mariadoss
Published: October 2020

The inclusion of CNMs together with TiO2enhanced the short circuit current density by 31% and power conversion efficiency (PCE) by 46% compared to the CNM-free DSSCs.
Recent advances in synthetic and medicinal chemistry of phosphotyrosine and phosphonate-based phosphotyrosine analogues
Authors: Makukhin Nikolai , Ciulli Alessio
Published: October 2020

This review summarizes advances over the last decade in the design of phosphotyrosine and its phosphonate-based derivatives, focusing on their synthesis and medicinal chemistry applications.
Accelerating solar desalination in brine through ion activated hierarchically porous polyion complex hydrogels
Authors: Zhu Fengbo , Wang Liqian , Demir Baris , An Meng , Wu Zi Liang , Yin Jun , Xiao Rui , Zheng Qiang , Qian Jin
Published: October 2020

A hierarchically porous hydrogel (HPH) mediated by a polyion complex enables accelerated solar desalination performance in brine than in pure water.
Effect of reduction temperature on the structure and catalytic performance of mesoporous Ni–Fe–Al2O3 in oxidative dehydrogenation of ethane
Authors: Xu Xia , Kumar Megarajan Suresh , Xia Xuefa , Toghan Arafat , Feldhoff Armin , Zhang Yan , Jiang Heqing
Published: October 2020

The effects of reduction temperature on the structure and catalytic performance of mesoporous Ni–Fe–Al2O3 are investigated for the first time.
Depolymerization of proanthocyanidins and application exploration in the field of preparation of flexible materials
Authors: Zhu Hongfei , Chen Siqi , Song Jie , Ren Shixue , Fang Guizhen , Li Shujun
Published: October 2020

A heat-induced flexible shape memory material was prepared.
Polyketide β-branching: diversity, mechanism and selectivity
Authors: Walker P. D. , Weir A. N. M. , Willis C. L. , Crump M. P.
Published: October 2020

The structural diversity of newly discovered polyketides continues to grow. This review summarises the range of structures with single and multiple β-branches and the mechanistic details of each catalytic step, covering literature from 2008 to August 2020.
Controlling palladium morphology in electrodeposition from nanoparticles to dendritesviathe use of mixed solvents
Authors: Hussein Haytham E. M. , Amari Houari , Breeze Ben G. , Beanland Richard , Macpherson Julie V.
Published: October 2020

By changing the mole fraction of water (χwater) in the solvent acetonitrile (MeCN), we report a simple procedure to control nanostructure morphology during electrodeposition.
Transition metal-free synthesis of alkyl pinacol boronates
Authors: Das Kanak Kanti , Paul Swagata , Panda Santanu
Published: October 2020

This review systematically outlined the research in the area of transition metal free synthesis of alkyl pinacol boronates, which are versatile and important scaffolds to construct diverse organic compounds.
Advances in fluorescent sensors for β-galactosidase
Authors: Li Meng , Yang Mengqing , Zhu Wei-Hong
Published: October 2020

This minireview summarizes advances in the molecular design strategy and biological applications of fluorescent probes for β-galactosidase (β-Gal), focusing on detection accuracy enhancement and aggregation-induced emission for background minimization.
Elodeoidins A–H, acylphloroglucinol meroterpenoids possessing diverse rearranged skeletons from Hypericum elodeoides
Authors: Li Qi-Ji , Tang Peng-Fei , Zhou Xin , Lu Wei-Jia , Xu Wen-Jun , Luo Jun , Kong Ling-Yi
Published: October 2020

Inspired by the biosynthetic fragment (9), the first example of rearranged dimethylated acylphloroglucinol and monoterpene adducts, elodeoidins A–H (1–8) representing four skeletons and two rearranged pathways were authenticated from H. elodeoides.
Error or exemption to the rule? Development of a diagnostic check for thermochemistry of metal–organic compounds
Authors: Zherikova Kseniya V. , Verevkin Sergey P.
Published: October 2020

A diagnostic tool for checking the consistency of thermochemical data of tris(beta-diketonato)metal complexes is developed.
Ex situ upgrading of pyrolysis vapors over PtTiO2: extraction of apparent kinetics via hierarchical transport modeling
Authors: Pecha M. Brennan , Iisa Kristiina , Griffin Michael , Mukarakate Calvin , French Richard , Adkins Bruce , Bharadwaj Vivek S. , Crowley Meagan , Foust Thomas D. , Schaidle Joshua A. , Ciesielski Peter N.
Published: October 2020

Chemical reaction kinetics enable predictive scaling studies and process sensitivity analyses that can substantially accelerate commercial deployment of new catalytic transformation technologies.
Photoresponsive molecular tools for emerging applications of light in medicine
Authors: Welleman Ilse M. , Hoorens Mark W. H. , Feringa Ben L. , Boersma Hendrikus H. , Szymański Wiktor
Published: October 2020

This perspective article explores the current state of light-controlled molecular tools for medical therapy and imaging and offers an outlook on clinical application scenarios and optimisation strategies.
Mechanical properties of temperature-responsive gels containing ethylene glycol in their side chains
Authors: Kureha Takuma , Hayashi Kyohei , Li Xiang , Shibayama Mitsuhiro
Published: October 2020

The mechanical properties of temperature-responsive poly(oligo-ethylene glycol methyl ether methacrylate)-based gels were investigated using dynamic viscoelasticity measurements to find applications in tissue and biomedical engineering.
Core–satellite assemblies of Au@polydopamine@Ag nanoparticles for photothermal-mediated catalytic reaction
Authors: Zakia Maulida , Yoo Seong Il
Published: October 2020

The synergistic effect of plasmonic and catalytic functions in Au@PDA@Ag to enhance the plasmon-promoted catalytic reaction.
A chemically and mechanically stable dual-phase membrane with high oxygen permeation flux
Authors: Nam Gyeong Duk , Lee Gahyeon , Choi Soomin , Lee Jinsil , Song Sun-Ju , Joo Jong Hoon
Published: October 2020

This contribution details our comprehensive efforts to design a chemically and mechanically stable dual-phase membrane with a high oxygen permeation flux.
Atomically dispersed M–N–C catalysts for the oxygen reduction reaction
Authors: Xu Hao , Wang Dan , Yang Peixia , Liu Anmin , Li Ruopeng , Li Yun , Xiao Lihui , Ren Xuefeng , Zhang Jinqiu , An Maozhong
Published: October 2020

The systematic summarization of synthesis–structure–property–mechanism correlations provides guidance for the rational design of an atomically dispersed M–N–C catalyst for the ORR.
Noble-metal-free electrocatalysts toward H2O2production
Authors: Dong Kai , Lei Ying , Zhao Haitao , Liang Jie , Ding Peng , Liu Qian , Xu Zhaoquan , Lu Siyu , Li Quan , Sun Xuping
Published: October 2020

This review summaries recent progress of noble-metal-free electrocatalysts toward H2O2production including carbon-based materials, metal compounds, single atom catalysts and metal complexes.
A non-toxic triboelectric nanogenerator for baby care applications
Authors: Yan Kang , Li Xiao , Wang Xiao-Xiong , Yu Miao , Fan Zhiyong , Ramakrishna Seeram , Hu Han , Long Yun-Ze
Published: October 2020

Herein, we report a non-toxic triboelectric nanogenerator for baby care applications.
Injectable zwitterionic thermosensitive hydrogels with low-protein adsorption and combined effect of photothermal-chemotherapy
Authors: Zheng Anbi , Wu Di , Fan Man , Wang Hong , Liao Yonggui , Wang Qin , Yang Yajiang
Published: October 2020

Low-biofouling injectable hydrogels were constructed based on thermosensitive nanogels to co-load a photothermal agent and chemotherapeutics to improve anti-tumor efficiency.
Intermolecular B–N coordination and multi-interaction synergism induced selective glycoprotein adsorption by phenylboronic acid-functionalized magnetic composites under acidic and neutral conditions
Authors: Li Zhiyu , Bin Luo  , Yu Lingzhu , Lan Fang , Wu Yao
Published: October 2020

An unorthodox mechanism of glycoprotein specific separation using magnetic nanoparticles armed with intermolecular B–N coordination and multi-interaction synergism.
Structure-induced optoelectronic properties of phenothiazine-based materials
Authors: Revoju Srikanth , Matuhina Anastasia , Canil Laura , Salonen Henri , Hiltunen Arto , Abate Antonio , Vivo Paola
Published: October 2020

Phenothiazine (PTZ)-based materials have recently received considerable interest owing to their intriguing optoelectronic properties, low-cost, versatility of functionalization, and commercial availability.
Niobium diselenide nanosheets for a vector soliton fiber laser
Authors: Yang Huiran
Published: October 2020

Niobium diselenide (NbSe2), an emerging group VB transition metal dichalcogenide, has been widely used in materials science, chemistry, and physics, while the applications of NbSe2 in ultrafast photonics are still rare.
Hierarchical growth of Au nanograss with intense built-in hotspots for plasmonic applications
Authors: Shi Yali , Li Qian , Zhang Yao , Wang Guoqing , Matsuo Yasutaka , Liang Xingguo , Takarada Tohru , Ijiro Kuniharu , Maeda Mizuo
Published: October 2020

“Au nanograsses” displaying intertwined nanowires produced by hierarchical growth indicate superior electromagnetic enhancement effect in both simulations and single-particle SERS.
Some assembly required: building the fly eye for motion detection and colour discrimination
Authors: Walther Rhian F. , Pichaud Franck
Published: October 2020

Among the many eyes that have evolved on Earth, the insect compound eye is the most abundant. Its crystal-like lattice structure is a feat of engineering that has evolved over millions of years, and is exquisitely adapted to detect moving objects and discriminate colours. This enables many behaviours, including foraging for food, finding a mate and avoiding predators. Our understanding of how the compound eye is built and works has been greatly expanded by studying the humble fruit fly, Drosophila melanogaster. The simple outward appearance of the fly eye belies a host of sophisticated features. Through the precise arrangement of photosensitive cells in the retina and their connections to the brain, the fly eye packs an astonishing amount of hardware into a very tiny volume. In this primer, we introduce the molecular pathways that underpin the building and inner workings of the fly eye.
Prognostic performance of the FACED score and bronchiectasis severity index in bronchiectasis: a systematic review and meta-analysis
Authors: He Min , Zhu Min , Wang Chengdi , Wu Zuohong , Xiong Xiaofeng , Wu Hongxia , Cheng Deyun , Ji Yulin
Published: October 2020

Background: Bronchiectasis is a multidimensional lung disease characterized by bronchial dilation, chronic inflammation, and infection. The FACED (Forced expiratory volume in 1 s (FEV1), Age, Chronic colonization, Extension, and Dyspnea) score and Bronchiectasis Severity Index (BSI) are used to stratify disease risk and guide clinical practice. This meta-analysis aimed to quantify the accuracy of these two systems for predicting bronchiectasis outcomes.

Methods: PubMed, Embase, and the Cochrane Database of Systematic Reviews were searched for relevant studies. Quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) criteria. Pooled summary estimates, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated. Summary receiver operating characteristic curves were constructed, and the area under the curve (AUC) was used to evaluate prognostic performance.

Results: We analyzed 17 unique cohorts (6525 participants) from ten studies. FACED scores with a cut-off value ≥ 5 predicted all-cause mortality better than BSI with a cut-off value ≥ 9, based on pooled sensitivity (0.34 vs 0.7), specificity (0.94 vs 0.66), PLR (4.76 vs 2.05), NLR (0.74 vs 0.48), DOR (6.67 vs 5.01), and AUC (0.87 vs 0.75). Both FACED scores with a cut-off value ≥ 5 (AUC = 0.82) and BSI scores with a cut-off value ≥ 5 or 9 (both AUC = 0.80) help to predict hospitalization.

Conclusions: At a cut-off value ≥ 5, FACED scores can reliably predict all-cause mortality and hospitalization, while BSI scores can reliably predict hospitalization with a cut-off of ≥5 or ≥9. Further studies are essential to validate the prognostic performance of these two scores.
Efficient beam selection and resource allocation scheme for WiFi and 5G coexistence at unlicensed millimetre‐wave bands
Authors: Li Pengru , Liu Danpu
Published: October 2020

To alleviate the spectrum scarcity, the unlicensed 60 GHz band has raised increasing concerns due to its continuous large bandwidth. Considering IEEE 802.11ad/ay has already been deployed in this millimetre‐wave band, the coexistence issues with new radio‐based access to unlicensed spectrum should be weighed when deploying fifth generation (5G) network. Fortunately, the directional transmission on beams is able to reduce interference significantly, so beam selection can be combined with power control. To maximise spectrum efficiency (SE) of the 5G network while ensuring a friendly coexistence, the authors formulate an optimisation problem by jointly considering beam selection and resource allocation. More specifically, they design a spectrum planning mechanism to reduce the interference between 5G and WiFi, and then a block coordinate descent method is used to determine the user association, beam selection and power control for 5G users, while limiting the interferences to WiFi devices. Simulation results verify the effectiveness of the proposed algorithm in terms of complexity, convergence and SE.
Performance of non‐orthogonal multiple access: analysis using compute‐and‐forward cooperative relaying in 5G networks
Authors: Ntiamoah‐Sarpong Kwadwo , Huang Zhong , Wen Guangjun , Ampoma Affum Emmanuel
Published: October 2020

With the increasing demand for high‐speed mobile transmissions for 5G networks, the cooperative relay‐aided non‐orthogonal multiple access (CR‐NOMA) has been highly considered. An efficient and reliable CR‐NOMA not only depends on the network mechanism but on the network coding strategy at the relay. Even though conventional strategies have broadly been studied, they suffer from noise accumulation and interference. Lately, the compute‐and‐forward (CpF) strategy has been identified as a potential technique to mitigate interference and enhance outage probability. In this study, the authors present a mathematical formulation to examine the performance of CpF on downlink CR‐NOMA. In the proposed formulation, a two‐stage downlink cooperative relay network is considered to obtain analytical closed‐form expressions of outage probability and bit error rate. The outage probabilities and bit error rates of existing relaying strategies are compared regarding the network model. The theoretical analysis shows that CpF requires half the number of relays desirable in amplify‐and‐forward and decode‐and‐forward strategies to achieve a proportionate outage probability in CR‐NOMA. Finally, we present results to show that at a lower signal‐to‐noise ratio, the integration of CpF and NOMA enhances error performance irrespective of the number of users.
Ergodic spectral efficiency of massive MIMO with correlated Rician channel and MRC detection based on LS and MMSE channel estimation
Authors: Sadraei Mohammad Hadi , Fazel Mohammad Sadegh , Doost‐Hoseini Ali Mohamad
Published: October 2020

The authors study the spectral efficiency (SE) of a multi‐cell massive multiple‐input multiple‐output (MIMO) system with a spatially correlated Rician channel. The correlation between least squares (LS) estimator and its error complicates SE analysis, since signal and interference components become cross‐correlated, too. Minimum mean square error (MMSE) estimators do not suffer from this burden. In some previous works, a proper part of the signal is referred to interference, which makes them cross‐uncorrelated, and leads to a SE lower bound. In their modified approach, the authors extract and refer the cross‐correlated part of interference to the signal to attain this objective. Here, they use this approach for calculating the instantaneous SE of maximum ratio combining (MRC) detector under LS and MMSE estimation methods. They further derive closed‐form approximations of their ergodic SE. This approach is also applicable to other linear channel estimators or data detectors. Numerical results show that achievable SE surpasses that of the previous approach. Moreover, they show that their approximation is close enough to Monte Carlo simulation results, especially at the high number of the base station antennas.
Hybrid mapped optical‐OFDM using non‐linear companding technique for indoor visible light communication application
Authors: Sahoo Pritam Keshari , Prajapati Yogendra Kumar , Tripathi Rajeev
Published: October 2020

In this study, the authors have developed an analytical model for reducing the peak‐to‐average‐power ratio (PAPR) using non‐linear companding transform (NCT) based on inverse hyperbolic sine function. As a consequence of non‐linear transform, this study compensates the system bit error rate (BER) degradation with the help of an error efficient hybrid modulation. By means of an inflexion point and companding parameter, more design flexibility is achieved; as a result, a trade‐off between PAPR and BER has reasonably been more precise. To the best of the authors’ awareness, no findings have yet been reported on the performance evaluation of the optical orthogonal frequency division multiplexing (OOFDM) system using a hybrid modulation technique. To find out the advantages of hybrid modulation with NCT, the authors inspect the nature of PAPR reduction, and BER improvement through numerical simulations. The numerical BER results exhibit roughly 3 dBm decay in the power efficiency of hybrid modulation with NCT over discrete Fourier transform (DFT) precoding technique. On the other hand, the NCT technique with hybrid modulation has 6 dB less PAPR than the DFT precoding technique.
Safeguarding unmanned aerial systems: an approach for identifying malicious aerial nodes
Authors: Sayeed Mohd Abuzar , Kumar Rajesh , Sharma Vishal
Published: October 2020

The coordination between aerial and ground nodes has enhanced the versatility and quality of the traditional networks. The application of aerial systems in mission‐critical operations, as well as civilian applications, brings in the context of safeguarding unmanned aerial systems (UAS) from malicious attackers. This study discusses the threats and attacks mounted on UAS, alongside the challenges introduced by the unmanned aerial vehicle (UAV) network structure itself. A framework for safeguarding UAS against malicious attackers and recovering the rogue UAVs is proposed in the study. The proposed framework enforces a dynamic conceptual grid‐based layout over the actual geographical deployment. The dynamically shuffling grid ascertains the security of transmission channels, as every time the grid is shuffled periodically or based on abnormal behaviour, the safety paradigm is reinitiated. Public key cryptographic algorithms are deployed for securing the communication links. Neural networks‐based predictions are used for detecting abnormality in behavioural, statistical, and mobility patterns. Principal component analysis based on multivariate statistical analysis is used for detecting outliers in the aerial network environment. The behaviour prediction and outlier detection algorithms significantly improve the overall performance of the network and provide immunity against the intruders with reduced false positives, high accuracy, and better detection rate.
Healing of large‐scale failures in WSN by the effectual placement of relay nodes
Authors: Rajeswari Gopinathan , Murugan Krishnan
Published: October 2020

The lightening growth inInternet of Things (IoT), forced the deployment of various types of applications. Due to the likelihood of sensor failures, the applications of IoT cannot be benefited. These node failures can transform the fully‐connected network into multiple disjoint sub‐networks, named network partitioning problem where the nodes fail to perform intended services. The federation of these isolated network segments is essential. In this study, a distributed approach FRTP (Failure Recovery using Relay Nodes at Torricelli points ()) is proposed, where the restoration of the disconnected network is initiated using the relay nodes (RNs). The performance of FRTP is evaluated using network simulator tool NS‐2 and the experimental results show that it achieves better performance than the existing approaches. The main goal of the proposed approach is to minimise the number of HRNs (Healing Relay Nodes), APL (Average path length), recovery time of the network and to maximise the average node degree. The average improvement in minimisation of number of HRN, APL, and recovery time of the network for radio range of 100 m are 21.57, 13.23, and 9.96%, respectively, and the maximisation of average node degree is 9.83%.
Distributed resource allocation optimisation algorithm based on particle swarm optimisation in wireless sensor network
Authors: Hao Xiaochen , Yao Ning , Wang Jiaojiao , Wang Liyuan
Published: October 2020

This study concentrates on the optimal resource allocation problem in a wireless sensor network with rare spectrum resources and improper topology structure. To explore the interdependence of various resources and achieve better anti‐interference property, the authors analyse the problem of joint power control and channel allocation based on bit error rate (BER) model and energy consumption model. Specifically, low‐energy consumption and BER are both crucial design objectives for a number of multi‐hop wireless network applications with constrained network resources and battery‐powered sensors. As these two objectives that influenced by power control and channel allocation are conflicting with each other, it becomes important to achieve the trade‐off between them. Aiming at the aforementioned problem, this study formulates a multi‐objective optimisation model to minimise BER and energy consumption under the constraints of link interference, link capacity, and network connectivity. On the basis of this model, they propose a distributed resource allocation optimisation algorithm based on particle swarm optimisation (DRAPSO) to achieve Pareto optimal solutions. Furthermore, the information complexity and time complexity of DRAPSO are theoretically analysed. The simulation results show that DRAPSO can effectively increase network capacity, decrease energy consumption, and BER. Besides, the trade‐off of multi‐performances can be significantly achieved.
Design and implementation of reinforcement learning‐based intelligent jamming system
Authors: Zhang Shuangyi , Tian Hua , Chen Xueqiang , Du Zhiyong , Huang Luying , Gong Yuping , Xu Yuhua
Published: October 2020

Here the intelligent jammer issue is studied. With the rapid development of cognitive radio technology, current cognitive terminals can adaptively or intelligently switch channel by spectrum sensing and decision‐making. Most of the traditional jamming methods, such as swept jamming and comb jamming, generally work in a relatively fixed pattern, which are not able to effectively jam the terminals empowered with cognition and spectrum decision‐making capability. In view of this problem, the authors propose an intelligent jamming decision‐making system based on reinforcement learning. First, in order to jam a pair of transmitter and receiver with adaptive frequency hopping capability, a jammer with spectrum sensing, offline training and learning scheme is proposed. Second, a reinforcement learning‐based algorithm for jamming decision‐making is proposed and simulated. A special feature of the proposed scheme is that considering the reward is difficult to obtain in the actual communication system, a virtual jamming decision‐making method is used to enable the jammer to learn and jam efficiently without the user's prior information. Finally, the proposed jamming model and algorithm are implemented and verified on Universal software radio peripheral testbed.
Performance of maximal ratio transmission over generalised‐K fading channels
Authors: Aslan Kardes , Gucluoglu Tansal
Published: October 2020

Mathematical analyses of wireless systems mostly consider fading and exclude the effect of shadowing since the derivation of performance metrics usually becomes extremely difficult. However, shadowing has to be studied to get better insights about the practical realisations. Therefore, generalised‐K distribution has been widely used recently to model the impact of both fading and shadowing. In this study, the performance of popular maximal ratio transmission, which is a practical multiple antenna technique, is obtained for generalised‐K fading channels. Particularly, outage probability, average channel capacity and symbol error rate expressions are derived and verified by computer simulations.
Generic wavelet‐based image decomposition and reconstruction framework for multi‐modal data analysis in smart camera applications
Authors: Yan Yijun , Liu Yiguang , Yang Mingqiang , Zhao Huimin , Chai Yanmei , Ren Jinchang
Published: October 2020

Effective acquisition, analysis and reconstruction of multi‐modal data such as colour and multi‐/hyper‐spectral imagery is crucial in smart camera applications, where wavelet‐based coding and compression of images are highly demanded. Many existing discrete wavelet filtering banks have fixed coefficients hence their performance is highly dependent on the signal/image being processed. To tackle this problem, a unified framework is proposed in this study, which can produce a series of discrete wavelet filtering banks, where many existing discrete wavelet filtering banks become special cases of the framework. For each generated filtering bank, it consists of two decomposition filters and two reconstruction filters through an optimisation process. The efficacy of the filtering banks produced by the framework has been validated in two case studies, including colour image decomposition and reconstruction, and hyperspectral image classification. Comprehensive experiments have demonstrated the superior performance of the proposed framework, which will benefit the efficacy of smart camera and camera network applications.
Analysis of coil pitch in induction machines for electric vehicle applications
Authors: Gundogdu Tayfun , Zhu Zi‐Qiang , Mipo Jean‐Claude
Published: October 2020

This study investigates the influence of stator coil pitch on the electromagnetic performance of squirrel‐cage induction machine (IM) with emphasis on the flux‐weakening (FW) capability for electric vehicle applications. Three different winding topologies, obtained by changing the coil pitch, namely integer‐slot distributed winding (ISDW), integer‐slot concentrated winding, and fractional‐slot concentrated winding (FSCW), are studied. Their merits and demerits are revealed by comparing their performances characteristics, including winding harmonic index, total axial length, average torque, torque ripple, power losses, efficiency, and FW capability. It is revealed that due to the very high Magnetomotive force (MMF) harmonics induced in the bar current, the bar copper loss of the IM with FSCW is significant. It is also revealed that the parasitic effects of the double‐layer winding configurations are lower than those of the single‐layer (SL) winding configurations. It is also demonstrated that for the slot/pole/phase combinations lower than two , the higher the coil pitch, the lower the parasitic effects and the higher the efficiency. Moreover, it is found that the combinations , especially those having longer coil pitch and higher stator slot number, and the SL combinations offer better FW capability. Finally, the Finite‐element analysis (FEA) results of IM with long‐pitch ISDWs are validated by experimental measurements.
Using and enhancing the cogging torque of PM machines in valve positioning applications
Authors: Taghipour Boroujeni Samad , Takorabet Noureddine , Mezani Smail , Lubin Thierry , Haghgooie Peyman
Published: October 2020

In this study, it is aimed to use the cogging torque of permanent magnet (PM) machines for providing the load torque in the valve positioning applications. The policy is to use the machine cogging torque to overcome the load torque at the steady‐state condition (fixed valve position). Therefore, there is no excitation, and no armature Joule losses at the steady‐state condition and consequently lower thermal stress for the machine. To have a more compact actuator, it is tried to increase the machine cogging torque. Two well‐known types of PM machines, i.e. surface‐mounted PM (SPM) and flux‐switching PM (FSPM) machines are studied to be applied in this application. Some techniques such as applying auxiliary slots and PM segmentation (for the SPM machine) and two‐part rotor topology (for both SPM and FSPM machines) are proposed to increase the machine cogging torque. The impact of each technique on the developed cogging torque is studied by means of finite element analysis. Finally, the SPM and FSPM machines are compared together in the terms of the torque density. The validity of the proposed concept of providing the load torque by the cogging torque is investigated by experimental tests.
Alternative model for computing transformer tank induced losses in the time domain
Authors: de Oliveira Luiz F. , Sadowski Nelson , Cabral Sergio Henrique Lopes
Published: October 2020

In the performance evaluation of power transformers, the occurrence of eddy currents and their effects on the transformer tank have been widely modelled and studied for the cases of power frequency in the steady state. Nonetheless, for the cases when harmonic components are present (zero‐sequence flux) or for transient conditions (inrush or geomagnetically induced current (GIC) events) there is much to do. With this aim, this work presents the proposal in using temporal modelling for evaluating eddy currents in transformer tank walls in practical cases of sinusoidal, harmonic and transient excitations. Obtained results are compared with consolidated commercially available software based on finite elements for showing how good this proposition is.
Dynamic robust generation–transmission expansion planning in the presence of wind farms under long‐ and short‐term uncertainties
Authors: Ahmadi Saeid , Mavalizadeh Hani , Ghadimi Ali Asghar , Miveh Mohammad Reza , Ahmadi Abdollah
Published: October 2020

The main goal of generation expansion planning (GEP) and transmission expansion planning (TEP) is to expand the power system to satisfy the increasing demand of electricity while maintaining efficient operation of the system. The major objective of this study is to propose a dynamic, robust GEP–TEP expansion planning in the presence of wind farms considering both long‐ and short‐term uncertainties. The suggested model allows implementing information‐gap decision theory on multi‐year long‐term uncertainties, such as demand growth and future increase in production capacity to decrease the risk in long‐term decisions. Additionally, a scenario‐based approach is employed for short‐term uncertainties in demand and wind power production in a 1‐year time horizon. The main advantage of the proposed model is to enhance the power system robustness against the uncertainties corresponding to forecast errors. To verify the robustness of the suggested expansion planning model, it is applied to the Garver 6‐bus and IEEE 24‐bus test systems.
Correlation scan matching algorithm based on multi‐resolution auxiliary historical point cloud and lidar simultaneous localisation and mapping positioning application
Authors: Liu Haiqiao , Luo Shibin , Lu Jiazhen
Published: October 2020

The matching algorithm is an important part of simultaneous location and mapping. Aiming at the problem of large computation and poor real‐time performance of two‐dimensional lidar traditional correlation scan matching (CSM) algorithm, a multi‐resolution auxiliary historical point cloud matching algorithm is proposed, which combines high and low resolution and adopts a single‐frame to multi‐frame step‐by‐step matching scheme. The algorithm was carried out on the sweeping robot. Compared with the traditional CSM algorithm and iterative closest points algorithm, the single position accuracy of the method in this study is improved. In the indoor space of ∼10 m × 10 m, the cumulative error is reduced by 16.24 and 33.96%, respectively. Consequently, our algorithm can still manage to process in real‐time.
Grain segmentation of sandstone images based on convolutional neural networks and weighted fuzzy clustering
Authors: Jiang Feng , Li Na , Zhou Lili
Published: October 2020

Grain segmentation of sandstone images is to partition the images into non‐overlapping regions, each of which is an independent mineral grain. However, a sandstone image usually contains hundreds of mineral grains and complicated micro‐structures, which makes current segmentation methods inefficient. In this study, the authors propose a three‐stage framework for the automatic segmentation of sandstone images. In the first stage, the input sandstone images are pre‐segmented into over‐segmented mineral superpixels. In the second stage, the instance‐independent features are extracted by a specially designed convolutional neural network, and the instance‐aware features are extracted by computing histogram statistics and Gabor responses of mineral superpixels. In the third stage, a novel weighted fuzzy clustering algorithm is proposed to cluster the mineral superpixels into different classes, afterwards the adjacent mineral superpixels are merged to yield the complete minerals according to their classes. The experimental results conducted on the sandstone image datasets demonstrate the effectiveness of the proposed method, which evidently outperform the state‐of‐the‐art segmentation methods.
Corner detection using the point‐to‐centroid distance technique
Authors: Zhang Shizheng , Huangfu Luwen , Zhang Zhifeng , Huang Sheng , Li Pu , Wang Heng
Published: October 2020

Corners, highly important local features of images and corner finding, play a crucial role in computer vision and image processing, such as object tracking and vehicle detection. Proposing effective and efficient corner detectors is the aim of corner detection. In this study, the authors first present a new measure of corner sharpness termed as the point‐to‐centroid distance (PCD) and then examine its behaviours, which display beneficial characteristics that help distinguish corners from non‐corners. Based on PCD behaviours, the authors propose a novel corner detector. Extensive experimental results demonstrate that the PCD technique is effective and simultaneously efficient for corner detection compared with six other contour‐based corner detectors in terms of two commonly used evaluation metrics – average repeatability and localisation error.
Volumetric lung nodule segmentation in thoracic CT scan using freehand sketch
Authors: Pramod Kumar S. , Latte Mrityunjaya V. , Siri Sangeeta K.
Published: October 2020

The authors presented a novel computerised scheme to segment pulmonary nodules using freehand sketch. Here, freehand sketching is considered to identify the location of a nodule and it serves as a natural way and also it provides inferring adaptive information i.e. size, density, texture and mass centre etc. The proposed scheme includes two phases. In first phase using the freehand sketch analysis the multi seed points to select RoI. In the second phase nodule volumetric extraction is done using geometric modelling and implicit surface reconstruction for volumetric analysis. Spherical bins are used for ray triangle intersections and then local implicit surface fitting and blending method for surface reconstruction and depiction. The performance of the proposed scheme is assessed by accuracy and consistency using 112 CT examinations from LIDC. The IoU and ASD were used to assess the discrepancy between proposed method and inter observer agreement in the proposed approach. In estimating the reproducibility, the discrepancy in proposed scheme and the manual contouring by the expert is observed to be on an average of 0.13 ± 0.07 mm and 3.04 ± 1.7 mm respectively. The experiment shows that, the proposed scheme performs reasonably well and demonstrate merit of freehand sketch.
Gain‐enhancement technique for wearable patch antenna using grounded metamaterial
Authors: Das Goutam Kumar , Basu Subhadeep , Mandal Bappaditya , Mitra Debasis , Augustine Robin , Mitra Monojit
Published: October 2020

In this study, a metamaterial (MTM)‐based high‐gain compact‐wearable antenna for 2.45 GHz industrial, scientific and medical radio band application has been proposed. To achieve the flexibility of the antenna, textile material felt fabric has been chosen as the substrate of the antenna as well as MTM. An omega (Ω) like structure has been taken as MTM unit cell design. High value of permeability is utilised for the gain enhancement of the antenna. In addition, very low specific absorption rate (SAR) is obtained using the MTM which makes the proposed antenna suitable for the biomedical application. The proposed antenna has achieved about 3 dB gain enhancement along with SAR value of 0.405 W/kg (1 g tissue). The design has been optimised and the prototype with the optimised parameter has been fabricated and tested over the semi‐solid phantom and human body. Further, the proposed antenna over different type of textile material has also been validated.
Virtual machines migration game approach for multi‐tier application in infrastructure as a service cloud computing
Authors: Thanh Bui Khiet , Dac Ho Hung , Pham Tran Vu , Tran Hung Cong
Published: October 2020

Virtual machines migration is an essential feature of virtualisation technology which brings many advantages in cloud computing management process such as proactive fault tolerance, load balancing, and power management. There have been many virtual migration algorithms that have been developed but it is hard to find one that best suits all applications as well as ensures the desire of all stakeholders. The optimal virtual machines migration of cloud computing is usually NP‐hard or NP‐complete. In addition, determining when virtual machines migrate is a challenge because of the difficulty of fault detection in cloud computing. In this study, the authors propose a virtual machines migration game approach for multi‐tier application in infrastructure‐as‐a‐service cloud computing where they first proposed fault detection model based on Takagi–Sugeno fuzzy system with metric's physical machines and then optimal or near optimal migration solution is approximated based on Nash equilibrium. The results of experiment demonstrate the efficiency of their proposal. The proposed virtual machines migration algorithm has been benchmarked in order to highlight their strength and feasibility.
Rough‐set and machine learning‐based approach for optimised virtual machine utilisation in cloud computing
Authors: Shylaja B.S. , Bhaskar R.
Published: October 2020

To meet rising demands for computing resources, information technology service providers need to select cloud‐based services for their vitality and elasticity. Enormous numbers of data centres are designed to meet customer needs. Burning up energy by data centre is very high with the large‐scale deployment of cloud data centres. Virtual machine consolidation strategy implementation reduces the data centre energy consumption and guarantees service level agreements. This study proposes a machine learning‐based method in cloud computing for the automated use of virtual machines. Machine learning‐based virtual machine selection approach integrates the migration control mechanism that enhances selection strategy efficiency. The experiment is performed with various real machine workload circumstances to provide proof and effectiveness of the proposed method. The exploratory outcome shows that the proposed approach streamlines the utilisation of the virtual machine and diminishes the consumption of energy and improves infringement of service level agreements to accomplish better performance.
Power spectrum of turbulent convection in the solar photosphere
Authors: Yelles Chaouche L. , Cameron R. H. , Solanki S. K. , Riethmüller T. L. , Anusha L. S. , Witzke V. , Shapiro A. I. , Barthol P. , Gandorfer A. , Gizon L. , Hirzberger J. , van Noort M. , Blanco Rodríguez J. , Del Toro Iniesta J. C. , Orozco Suárez D. , Schmidt W. , Martínez Pillet V. , Knölker M.
Published: October 2020

The solar photosphere provides us with a laboratory for understanding turbulence in a layer where the fundamental processes of transport vary rapidly and a strongly superadiabatic region lies very closely to a subadiabatic layer. Our tools for probing the turbulence are high-resolution spectropolarimetric observations such as have recently been obtained with the two balloon-borne SUNRISE missions, and numerical simulations. Our aim is to study photospheric turbulence with the help of Fourier power spectra that we compute from observations and simulations. We also attempt to explain some properties of the photospheric overshooting flow with the help of its governing equations and simulations. We find that quiet-Sun observations and smeared simulations are consistent with each other and exhibit a power-law behavior in the subgranular range of their Doppler velocity power spectra with a power-law index of ≈ − 2. The unsmeared simulations exhibit a power law that extends over the full range between the integral and Taylor scales with a power-law index of ≈ − 2.25. The smearing, reminiscent of observational conditions, considerably reduces the extent of the power-law-like portion of the power spectra. This suggests that the limited spatial resolution in some observations might eventually result in larger uncertainties in the estimation of the power-law indices. The simulated vertical velocity power spectra as a function of height show a rapid change in the power-law index (at the subgranular range) from roughly the optical depth unity layer, that is, the solar surface, to 300 km above it. We propose that the cause of the steepening of the power-law index is the transition from a super- to a subadiabatic region, in which the dominant source of motions is overshooting convection. A scale-dependent transport of the vertical momentum occurs. At smaller scales, the vertical momentum is more efficiently transported sideways than at larger scales. This results in less vertical velocity power transported upward at small scales than at larger scales and produces a progressively steeper vertical velocity power law below 180 km. Above this height, the gravity work progressively gains importance at all relevant scales, making the atmosphere progressively more hydrostatic and resulting in a gradually less steep power law. Radiative heating and cooling of the plasma is shown to play a dominant role in the plasma energetics in this region, which is important in terms of nonadiabatic damping of the convective motions.
Inference of the chromospheric magnetic field configuration of solar plage using the Ca II 8542 Å line
Authors: Pietrow A. G. M. , Kiselman D. , de la Cruz Rodríguez J. , Díaz Baso C. J. , Pastor Yabar A. , Yadav R.
Published: October 2020

Context.It has so far proven impossible to reproduce all aspects of the solar plage chromosphere in quasi-realistic numerical models. The magnetic field configuration in the lower atmosphere is one of the few free parameters in such simulations. The literature only offers proxy-based estimates of the field strength, as it is difficult to obtain observational constraints in this region. Sufficiently sensitive spectro-polarimetric measurements require a high signal-to-noise ratio, spectral resolution, and cadence, which are at the limit of current capabilities.

Aims.We use critically sampled spectro-polarimetric observations of the Ca II8542 Å line obtained with the CRISP instrument of the Swedish 1-m Solar Telescope to study the strength and inclination of the chromospheric magnetic field of a plage region. This will provide direct physics-based estimates of these values, which could aid modelers to put constraints on plage models.

Methods.We increased the signal-to-noise ratio of the data by applying several methods including deep learning and PCA. We estimated the noise level to be 1 × 10−3Ic. We then used STiC, a non-local thermodynamic equilibrium inversion code to infer the atmospheric structure and magnetic field pixel by pixel.

Results.We are able to infer the magnetic field strength and inclination for a plage region and for fibrils in the surrounding canopy. In the plage we report an absolute field strength of |B| = 440 ± 90 G, with an inclination of 10° ±16° with respect to the local vertical. This value for |B| is roughly double of what was reported previously, while the inclination matches previous studies done in the photosphere. In the fibrillar region we found |B| = 300 ± 50 G, with an inclination of 50° ±13°.
Design of temperature control system for crystal silicon velvet
Authors: Wang Qing , Zhou Lili
Published: October 2020

With the rapid development of automation control technology, the majority of enterprises have begun to introduce automation equipment, but in some photovoltaic cell production in the enterprise, for the crystal silicon pile of temperature control in the process is still in the traditional way of manual control, this way of temperature control for the employee’s personal safety demand is higher, there is a certain risk. Aimed at this problem, this paper designed a crystal silicon velvet temperature control system based on MCU, the system consists of DS18B20 temperature sensor, 51 single chip microcomputer, sound and light alarm system, LCD1602 display module and motor drive module, the implementation of the system of velvet groove temperature monitoring, to ensure that the quality of the crystal silicon cell, through the simulation test system is stable, reliable and has certain practical application and popularization value.