bluuebunny/crossref_metadata_2025 huggingface dataset:
Simply structured controllers for vibration suppression in long rotors
Authors: Aleyaasin Majid
Published: April 2021

In this paper suppression of the transient flexural vibrational disturbances in long rotors, with fluid film bearings, is investigated. The rotor is described by a series of distributed shafts connected by the lumped discs, and the system is mounted on lumped fluid film bearings. Upon determination of the dynamic stiffness matrix of the system, the best approximate transfer function matrix description of the rotor, is determined. Initially vibration suppression by simple diagonal Proportional + Integral (PI) controllers is studied and via direct search optimisation techniques the PI parameters which exhibit fast vibration suppression is found. The resulted high integration rate, and low proportional gain PI controller, theoretically provided fast suppression time. However, it is shown that due to the strong coupling effect in the rotor system, and high rate of integration, the closed loop relative stability is weak, and feasibility of controller is questionable. Therefore, an alternative simple first order controller without integration action, that is named “attenuation filter “is suggested that can produce stronger stability and produces significant (not full) vibration suppression. The closed loop multivariable control of the rotor system comprising two vibration sensors and two magnetic actuators using such attenuation filter, is then simulated. The response to step disturbances, has provided 95% suppression with significantly fast response. It is concluded that although the attenuation filter may not provide 100% suppression, but it more reliable since the integration of the error, that results weak stability is avoided.
Assessing the long-term potential of fiber reinforced polymer composites for sustainable marine construction
Authors: Kappenthuler Steve , Seeger Stefan
Published: April 2021

Fiber reinforced polymer composites (FRPC) have gain rapid interest as light-weight and corrosion-resistant materials for various applications in marine infrastructure. Despite their advantages, FRPCs are still susceptible to other environmental factors present in the marine environment and manufactured mostly from non-renewable materials. This greatly affects the overall economic and environmental sustainability of such components. To determine the long-term suitability of various FRPCs for use in marine environments, this paper provides a holistic comparison of the performance of 16 FRPCs (four fiber types: glass, carbon, natural, basalt; and four polymer resins: epoxy, polyester, vinylester, thermoplastic) not only from a technical, but also from an economic, environmental and resource perspective. The resulting ranking not only assesses each material’s long-term potential, but also provides a detailed overview of individual strengths and weaknesses. Although ranked the lowest of all materials, the partial renewability of the natural fiber composites makes them an interesting material in the longer term. Therefore, we use the framework to evaluate a number of approaches aimed at improving the overall performance of these composites.
What Impact Will the New-Built Metro Bring to the Transportation of Second-Tier Cities? From the Perspective of a Multilayer Complex Network
Authors: Zhao Fang , Cao Hongmei , Lu Tianwei
Published: April 2021

Metro is being developed rapidly in second-tier cities. There is a need to understand the impact it brings as it relates to the planning and management of the whole urban transportation system. In this paper, we applied the multilayer complex network theory to study this problem by contrasting the characteristics of transportation networks before and after the metro is built. We focused on transportation networks in second-tier cities and (1) proposed edge functions of the road subnetwork and rail transit subnetwork with impedance as weight; (2) established an interlayer function based on the transfer behavior to couple the above subnetworks into the multilayer weighted transportation network; and (3) redefined statistical parameters, such as node strength, chessboard coefficient, and average least pass cost. At last, Hohhot, China, a typical second-tier city, was taken as a case study. Calculations show that the new-built metro network in the second-tier city increases convenience and reduces travel cost, whereas, the vulnerability of the whole network increases, and the distribution of key nodes in the road network is reconstructed. For the sustainable development of urban transportation, more attention should be paid to the new-built metro in second-tier cities.
Biometric characteristics of the wild population of sea urchin Paracentrotus lividus (Lamarck, 1816) on the Tunisian coast
Authors: Sellem F. , Bouhaouala-Zahar B.
Published: April 2021

The present study was conducted to provide biometric data of the edible sea urchin Paracentrotus lividus along the Tunisian coastline where thirteen marine localities were selected randomly. A total of 653 individuals were collected and their metric and weight measurements were recorded. The size distribution of the different samples was determined and relative growth expressions were deduced. Data analysis showed that all localities’ samples of the wild population were dominated by one-size class, except Port Prince and Haouaria. Interestingly, only diameter-height relationships (D-H) were different between the geographical localities. Diameter-weight relationships (D-TW and D-TWTE) revealed a significant negative growth for all the localities, with the exception of Gammarth which showed positive growth for total weight (D-TW). Moreover, the multivariable analysis revealed divergences and/or similarities between metric and weight variables. Altogether, data highlights the inter-population discrimination with respect to geographic localization and clear segregation between the northern and the eastern localities demonstrated the plasticity of the species.
The selective cytotoxicity of silver thiosulfate, a silver complex, on MCF-7 breast cancer cells through ROS-induced cell death
Authors: Ota Akira , Tajima Masataka , Mori Kazunori , Sugiyama Erika , Sato Vilasinee Hirunpanich , Sato Hitoshi
Published: April 2021

Background

Silver is a transition metal that is known to be less toxic than platinum. However, only few studies have reported the anticancer effects of some silver complexes and their possibility as an alternative to platinum complex. This study investigated the anticancer effects of the silver thiosulfate complex (STS), [Ag(S2O3)2]3−, consisting of silver and sodium thiosulfate.

Methods

In vitro cytotoxic activity of STS was investigated comparatively in human cancer cell lines (K562 and MCF-7) and normal human cells (mesenchymal stem cells and mammary epithelial cells). For its anticancer effects, cell cycle, mode of cell death, morphological changes, and accumulation of intracellular ROS and GSH were evaluated in MCF-7 to provide mechanistic insights.

Results

STS showed a concentration-dependent cytotoxicity in MCF-7 cell, which was abolished by pretreatment with N-acetylcysteine, suggesting ROS accumulation by STS. Moreover, STS caused cell cycle arrest at the G1 phase, decrease in the GSH levels, and morphological changes in MCF-7. Direct measurement of ROS demonstrated the elevation of intracellular ROS accumulation in cancer cells treated with STS; however, neither cytotoxicity nor ROS accumulation was observed in normal human cells.

Conclusion

The results obtained here are the first evidence to show that STS exhibited an anticancer activity through ROS-induced mechanisms, and that its cytotoxicity is highly selective to cancer cells. The results of the present study warrant further investigation on the detailed mechanism of STS actions, as well as its in vivo effectiveness and safety for clinical application.
Low-carbon cast microalloyed steel intercritically heat-treated at different temperatures: microstructure and mechanical properties
Authors: Torkamani Hadi , Raygan Shahram , Garcia Mateo Carlos , Palizdar Yahya , Rassizadehghani Jafar , Vivas Javier , San-Martin David
Published: April 2021

In this study, dual-phase (DP, ferrite + martensite) microstructures were obtained by performing intercritical heat treatments (IHT) at 750 and 800 °C followed by quenching. Decreasing the IHT temperature from 800 to 750 °C leads to: (i) a decrease in the volume fraction of austenite (martensite after quenching) from 0.68 to 0.36; (ii) ~ 100 °C decrease in martensite start temperature (Ms), mainly due to the higher carbon content of austenite and its smaller grains at 750 °C; (iii) a reduction in the block size of martensite from 1.9 to 1.2 μm as measured by EBSD. Having a higher carbon content and a finer block size, the localized microhardness of martensite islands increases from 380 HV (800 °C) to 504 HV (750 °C). Moreover, despite the different volume fractions of martensite obtained in DP microstructures, the hardness of the steels remained unchanged by changing the IHT temperature (~ 234 to 238 HV). Applying lower IHT temperature (lower fraction of martensite), the impact energy even decreased from 12 to 9 J due to the brittleness of the martensite phase. The results of the tensile tests indicate that by increasing the IHT temperature, the yield and ultimate tensile strengths of the DP steel increase from 493 to 770 MPa, and from 908 to 1080 MPa, respectively, while the total elongation decreases from 9.8 to 4.5%. In contrast to the normalized sample, formation of martensite in the DP steels could eliminate the yield point phenomenon in the tensile curves, as it generates free dislocations in adjacent ferrite.
Serving Athena
Authors: Shear Julia L.
Published: April 2021

In ancient Athens, the Panathenaia was the most important festival and was celebrated in honour of Athena from the middle of the sixth century BC until the end of the fourth century AD. This in-depth study examines how this all-Athenian celebration was an occasion for constructing identities and how it affected those identities. Since not everyone took part in the same way, this differential participation articulated individuals' relationships both to the goddess and to the city so that the festival played an important role in negotiating what it meant to be Athenian (and non-Athenian). Julia Shear applies theories of identity formation which were developed in the social sciences to the ancient Greek material and brings together historical, epigraphical, and archaeological evidence to provide a better understanding both of this important occasion and of Athenian identities over the festival's long history.
Rule of Law Intermediaries
Authors: Simion Kristina
Published: April 2021

Scholars puzzle over the conditions that make rule of law development in authoritarian settings successful. In this significant contribution, focusing on the decade of Myanmar's political transformation, Kristina Simion explores rule of law assistance through the practice and experience of intermediaries, their capital, strategies and challenges. How do intermediaries influence the field, and the ways in which the rule of law is brokered transnationally? And why do they matter? Simion relates her research to law and sociology to bring to light these neglected players, focusing on who they are, the influence they have, their double agency and their crucial importance in establishing trust and translating rule of law. Relying on rich empirical data collected in Myanmar, the book shares the voices of the individuals that help to steer societal change within authoritarian confines. This socio-legal work offers some insights into why rule of law change in authoritarian settings often does not go expected ways, one of the development field's long unresolved issues.
Privileged Precariat
Authors: van Zyl-Hermann Danelle
Published: April 2021

White workers occupied a unique social position in apartheid-era South Africa. Shielded from black labour competition in exchange for support for the white minority regime, their race-based status effectively concealed their class-based vulnerability. Centred on this entanglement of race and class, Privileged Precariat examines how South Africa's white workers experienced the dismantling of the racial state and the establishment of black majority rule. Starting from the 1970s, it shows how apartheid reforms constituted the withdrawal of state support for working-class whiteness, sending workers in search of new ways to safeguard their interests in a rapidly changing world. Danelle van Zyl-Hermann tracks the shifting strategies of the blue-collar Mineworkers' Union, culminating in its reinvention, by the 2010s, as the Solidarity Movement, a social movement appealing to cultural nationalism. Integrating unique historical and ethnographic evidence with global debates, Privileged Precariat offers a chronological and interpretative rethinking of South Africa's recent past and contributes new insights from the Global South to debates on race and class in the era of neoliberalism.
In the Mirror of Persian Kings
Authors: Auer Blain
Published: April 2021

For a period of nearly eight hundred years, Perso-Islamic kingship was the source for the dominant social and cultural paradigms organising Indian political life. In the medieval world of South Asia, Persian kingship took the form of a hybridized and adaptive political expression. The Persian king embodied the values of justice, military heroics, and honor, ideals valorized historically and transculturally, yet the influence of the pre-Islamic Persian past and Persian forms of kingship has not yet been fully recognised. In this book, Blain Auer demonstrates how Persian kingship was a transcultural phenomenon. Describing the contributions made by kings, poets, historians, political and moral philosophers, he reveals how and why the image of the Persian king played such a prominent role in the political history of Islamicate societies, in general, and in India, in particular. By tracing the historical thread of this influence from Samanid, Ghaznavid, and Ghurid empires, Auer demonstrates how that legacy had an impact on the establishment of Delhi as a capital of Muslim rulers who made claims to a broad symbolic and ideological inheritance from the Persian kings of legend.
Deep Learning in Science
Authors: Baldi Pierre
Published: April 2021

This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking.
Affect and the Rise of Right-Wing Populism
Authors: Zembylas Michalinos
Published: April 2021

This book uses affect theory to analyze the rise of right-wing populism in recent years and discusses the pedagogical implications for democratic education. It provides examples of how affect and emotion play a crucial role in the rise and reproduction of current right-wing populism. The author suggests ideas about affective pedagogies for educators to use (along with recognizing the risks involved) to renew democratic education. The chapters lay out the importance of harnessing the power of affective experiences and adopting strategic pedagogical approaches to provide affirmative practices that move beyond simply criticizing right-wing populism. The book consequently undermines the power of fascist and right-wing tendencies in public life and educational settings without stooping to methods of indoctrination. This volume is a valuable resource for researchers and policy-makers in education, political science and other related fields, who can utilize the affective complexities involved in combatting right-wing populism to their advantage.
Characteristics of Atmospheric Aerosols Over the UAE Inferred From CALIPSO and Sun Photometer Aerosol Optical Depth
Authors: Nelli Narendra , Fissehaye Samson , Francis Diana , Fonseca Ricardo , Temimi Marouane , Weston Michael , Abida Rachid , Nesterov Oleksandr
Published: April 2021

This study provides insights on the composition and variability of atmospheric aerosols over the United Arab Emirates (UAE) by analyzing the atmospheric conditions together with 14 years (2006–2019) of aerosol optical depth (AOD) retrieved from CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellite, and 7 years of AOD measured from the ground‐based Aerosol Robotic Network (AERONET).

We found that mineral dust is the most prevailing aerosol subtype. In addition, polluted dust and polluted continental aerosols are observed mostly in the cold season. The AOD is higher in spring and summer, when the atmospheric conditions are more favorable to the occurrence of dust events. Moreover, there is another peak in winter associated with dust storms triggered by mid‐latitude baroclinic systems. In summer’s daytime, extinction coefficients in excess of 0.2 km−1 are observed up to 3–4 km above the surface, as a result of the warmer and windier conditions. In the cold season and at night, the dust layers are confined to the lower atmosphere below 2 km. On a climatological time scale, we found that the AOD over the UAE has been decreasing since 2009, possibly due to the increasing trend in precipitation and changes in land use.

This study highlights the large contribution of dust aerosols to the total aerosol load over the UAE and stresses on the need to account for mineral dust aerosols in climate‐air pollution related studies as well as weather and air quality forecasts.
Performance of the Ionospheric Kappa‐Correction of Radio Occultation Profiles Under Diverse Ionization and Solar Activity Conditions
Authors: Danzer J. , Haas S. J. , Schwaerz M. , Kirchengast G.
Published: April 2021

The kappa‐correction is an easy‐to‐use method to correct for residual ionospheric errors in radio occultation (RO) data. It is a simple empirical model term that only depends on readily available data. While its basic utility was well proven in previous studies, including a recent predecessor study on RO climatologies under solar cycle variations, its performance for individual RO profile correction under diverse and extreme ionization conditions is unclear so far. Here we tackle this gap and focus on investigating (extremely) low and high solar activity and ionization conditions of individual RO events, including inspection of ionospheric symmetry between inbound and outbound raypaths. Using a global multi‐year ensemble of MetOp‐A and GRACE‐A RO events over 2008–2015 as basis, we applied a sampling approach leading to six characteristic condition cases. These cases also relate to day and night time variations and geographic variations from the equatorial to the high latitude region. We inspected the kappa‐correction and its performance relative to the standard bending angle correction for RO‐retrieved stratospheric profiles and found mean deviations in temperature of near −0.3 K in the upper stratosphere (40–45 km) for high ionization conditions, with extreme deviations exceeding −2 K for strong inbound/outbound asymmetry. The kappa‐correction term itself reaches a mean value near 0.05 μrad under these high conditions. Low solar activity and ionization conditions lead to a mean correction smaller than 0.005 μrad and mean temperature deviations smaller than 0.02 K. An intercomparison to other quality datasets, predominantly showed a decrease in mean temperature difference when applying the kappa‐correction.
Evidence of Alfvenic Poynting Flux as the Primary Driver of Auroral Motion During a Geomagnetic Substorm
Authors: Tian S. , Colpitts C. A. , Wygant J. R. , Cattell C. A. , Ferradas C. P. , Igl A. B. , Larsen B. A. , Reeves G. D. , Donovan E. F.
Published: April 2021

Geomagnetic substorms are major energy transfer events where energy stored in the Earth's magnetotail is released into the ionosphere. Substorm phenomena, including auroral activities, earthward Poynting flux, magnetic field dipolarization, etc, have been extensively studied. However, the complex interplay among them is not fully understood. In a fortuitous event on June 7, 2013, the twin Van Allen Probes (separated by 0.4 h in local time) observed bursts of earthward Alfvenic Poynting flux in the vicinity of the plasma sheet boundary layer (PSBL). The Poynting flux bursts correlate with enhancements of auroral brightness around the footpoints of both spacecraft. This indicates a temporal and spatial correlation between the auroral brightening and Poynting flux bursts, and that the auroral motion is directly linked to the perpendicular expansion of the Alfven wave. These observations suggest that the Alfvenic Poynting flux is a primary driver for the auroral electron acceleration. Around the time of auroral brightening, a dipolarization was seen to propagate more than 4 h in local time during a 20 min period. The azimuthal phase speed of this dipolarization (2 deg/min) is too small to explain the azimuthal motion of the aurora (13.6 deg/min), but the dipolarization could be related to the generation of the Alfvenic Poynting flux through phase mixing at strong density gradients like those in the PSBL.
Toward a Next Generation Particle Precipitation Model: Mesoscale Prediction Through Machine Learning (a Case Study and Framework for Progress)
Authors: McGranaghan Ryan M. , Ziegler Jack , Bloch Téo , Hatch Spencer , Camporeale Enrico , Lynch Kristina , Owens Mathew , Gjerloev Jesper , Zhang Binzheng , Skone Susan
Published: April 2021

We advance the modeling capability of electron particle precipitation from the magnetosphere to the ionosphere through a new database and use of machine learning (ML) tools to gain utility from those data. We have compiled, curated, analyzed, and made available a new and more capable database of particle precipitation data that includes 51 satellite years of Defense Meteorological Satellite Program (DMSP) observations temporally aligned with solar wind and geomagnetic activity data. The new total electron energy flux particle precipitation nowcast model, a neural network called PrecipNet, takes advantage of increased expressive power afforded by ML approaches to appropriately utilize diverse information from the solar wind and geomagnetic activity and, importantly, their time histories. With a more capable representation of the organizing parameters and the target electron energy flux observations, PrecipNet achieves a >50% reduction in errors from a current state‐of‐the‐art model oval variation, assessment, tracking, intensity, and online nowcasting (OVATION Prime), better captures the dynamic changes of the auroral flux, and provides evidence that it can capably reconstruct mesoscale phenomena. We create and apply a new framework for space weather model evaluation that culminates previous guidance from across the solar‐terrestrial research community. The research approach and results are representative of the “new frontier” of space weather research at the intersection of traditional and data science‐driven discovery and provides a foundation for future efforts.
Using Principal Component Analysis to Characterize the Variability of VLF Wave Intensities Measured by a Low‐Altitude Spacecraft and Caused by Interplanetary Shocks
Authors: Bezděková B. , Němec F. , Parrot M. , Kruparova O. , Krupar V.
Published: April 2021

Very low frequency wave intensity measurements provided by the French low‐altitude DEMETER spacecraft are studied using the principal component analysis (PCA). We focus on both the physical interpretation of the first two principal components and their application to real physical problems. Variations of the first principal component (PC1) coefficients due to the geomagnetic activity and seasonal/longitudinal changes are studied. It is shown that their distribution corresponds to the wave intensity dependences obtained in previous studies. Moreover, the variations of PC1 coefficients around interplanetary shock arrivals are analyzed. The study is performed for fast forward (FF), fast reverse, slow forward, and slow reverse shocks separately. It shows that the most significant effect on the wave intensity is displayed in the FF case. Furthermore, it turns out that the wave intensity variations depend on the wave intensity detected before the shock arrival. Finally, the shock strength and interplanetary magnetic field orientation are also important. The performed analysis shows that PCA can be successfully applied to characterize large data sets of spacecraft measurements by limited sets of numbers—principal component coefficients (typically first one or two are enough), which still maintain a sufficient amount of information.
Data Assimilation Retrieval of Electron Density Profiles From Ionosonde Virtual Height Data
Authors: Forsythe Victoriya V. , Azeem Irfan , Blay Ryan , Crowley Geoff , Makarevich Roman A. , Wu Wanli
Published: April 2021

A new method is developed to retrieve electron density profiles from a raw virtual height ionosonde traces. A Kalman filter is used for the assimilative inversion scheme together with the newly developed data‐driven vertical covariance model. The detailed mathematical formalism for the derivation of the Jacobian that takes into account the effect of the magnetic field is presented. The incoherent scatter radar measurements from Arecibo observatory are employed as the known truth to simulate the virtual height data. The results show that the data assimilative inversion technique accurately retrieves the vertical structure of the ionospheric density at the bottom side of the profile and reconstructs the vertical and temporal small‐scale density variations. A comparison with the results obtained by the POLynomial ANalysis (POLAN) inversion algorithm is presented. The assimilative inversion systematically outperforms the accuracy of the POLAN algorithm, on average reducing the percent errors in the electron density by half. Additionally, the simultaneous data ingestion is compared to the sequential assimilation of the virtual height data.
Layer-by-layer assembled magnetic molecularly imprinted nanoparticles for the highly specific recovery of luteolin from honeysuckle leaves
Authors: Tian Xuemeng , Gao Ruixia , Wang Yue , He Yulian , Hussain Sameer , Heinlein Jake , Tian Jiahao , Pfefferle Lisa D. , Tang Xiaoshuang , Tang Yuhai
Published: April 2021

Eco-friendly layer-by-layer assembled magnetic molecularly imprinted nanomaterials were designed for the specific recovery of luteolin from bio-waste honeysuckle leaves.
Carbon quantum dots as a dual platform for the inhibition and light-based destruction of collagen fibers: implications for the treatment of eye floaters
Authors: Barras Alexandre , Sauvage Félix , de Hoon Inès , Braeckmans Kevin , Hua Dawei , Buvat Gaëtan , Fraire Juan C. , Lethien Christophe , Sebag J. , Harrington Michael , Abderrahmani Amar , Boukherroub Rabah , De Smedt Stefaan , Szunerits Sabine
Published: April 2021

Fibrillation of collagen I is prevented most strongly by positively charged CQDs and pulsed-laser illumination destroys collagen aggregates and vitreous opacities.
An unnatural tripeptide structure containing intramolecular double H-bonds mimics a turn hairpin conformation
Authors: Liu Jin-Yu , Sun Xue-Yi , Tang Quan , Song Jun-Jie , Li Xiao-Qi , Gong Bing , Liu Rui , Lu Zhong-Lin
Published: April 2021

A series of unnatural tripeptides, each consisting of two aromatic γ-amino acid residues and an ϖ-amino acid residue, are designed to probe their folding into hairpin conformations.
Improving thermal diffusivity of supported Fe-based Fischer–Tropsch catalysts to enhance long-chain hydrocarbon production
Authors: Xing Chuang , Li Mingquan , Fu Yajie , Chen Xiaobing , Lu Peng , Li Xiaotian , Amoo Cederick Cyril
Published: April 2021

Fischer Tropsch synthesis (FTS) is highly exothermic so heat removal remains crucial. In this study, a rational procedure is examined to remove heat in the FTS by improving the thermal diffusivity on a series of Fe-based catalysts.
The complex, bidirectional role of extracellular vesicles in infection
Authors: White Joni Renee , Dauros-Singorenko Priscila , Hong Jiwon , Vanholsbeeck Frédérique , Phillips Anthony , Swift Simon
Published: April 2021

Cells from all domains of life release extracellular vesicles (EVs), packages that carry a cargo of molecules that participate in communication, co-ordination of population behaviours, virulence and immune response mechanisms. Mammalian EVs play an increasingly recognised role to fight infection, yet may also be commandeered to disseminate pathogens and enhance infection. EVs released by bacterial pathogens may deliver toxins to host cells, signalling molecules and new DNA to other bacteria, and act as decoys, protecting infecting bacteria from immune killing. In this review, we explore the role of EVs in infection from the perspective of both the pathogen and host, and highlight their importance in the host/pathogen relationship. We highlight proposed strategies for EVs in therapeutics, and call attention to areas where existing knowledge and evidence is lacking.
Transcription factors regulated by cAMP in smooth muscle of the myometrium at human parturition
Authors: Li Jonathan K.H. , Lai Pei F. , Tribe Rachel M. , Johnson Mark R.
Published: April 2021

Cyclic adenosine monophosphate (cAMP) contributes to maintenance of a quiescent (relaxed) state in the myometrium (i.e. uterine smooth muscle) during pregnancy, which most commonly has been attributed to activation of protein kinase A (PKA). PKA-mediated phosphorylation of cytosolic contractile apparatus components in myometrial smooth muscle cells (mSMCs) are known to promote relaxation. Additionally, PKA also regulates nuclear transcription factor (TF) activity to control expression of genes important to the labour process; these are mostly involved in actin-myosin interactions, cell-to-cell connectivity and inflammation, all of which influence mSMC transition from a quiescent to a contractile (pro-labour) phenotype. This review focuses on the evidence that cAMP modulates the activity of TFs linked to pro-labour gene expression, predominantly cAMP response element (CRE) binding TFs, nuclear factor κB (NF-κB), activator protein 1 (AP-1) family and progesterone receptors (PRs). This review also considers the more recently described exchange protein directly activated by cAMP (EPAC) that may oppose the pro-quiescent effects of PKA, as well as explores findings from other cell types that have the potential to be of novel relevance to cAMP action on TF function in the myometrium.
Fluorescence resonance energy transfer in revealing protein–protein interactions in living cells
Authors: Bhaumik Sukesh R.
Published: April 2021

Genes are expressed to proteins for a wide variety of fundamental biological processes at the cellular and organismal levels. However, a protein rarely functions alone, but rather acts through interactions with other proteins to maintain normal cellular and organismal functions. Therefore, it is important to analyze the protein–protein interactions to determine functional mechanisms of proteins, which can also guide to develop therapeutic targets for treatment of diseases caused by altered protein–protein interactions leading to cellular/organismal dysfunctions. There is a large number of methodologies to study protein interactions in vitro, in vivo and in silico, which led to the development of many protein interaction databases, and thus, have enriched our knowledge about protein–protein interactions and functions. However, many of these interactions were identified in vitro, but need to be verified/validated in living cells. Furthermore, it is unclear whether these interactions are direct or mediated via other proteins. Moreover, these interactions are representative of cell- and time-average, but not a single cell in real time. Therefore, it is crucial to detect direct protein–protein interactions in a single cell during biological processes in vivo, towards understanding the functional mechanisms of proteins in living cells. Importantly, a fluorescence resonance energy transfer (FRET)-based methodology has emerged as a powerful technique to decipher direct protein–protein interactions at a single cell resolution in living cells, which is briefly described in a limited available space in this mini-review.
Deep learning techniques‐based perfection of multi‐sensor fusion oriented human‐robot interaction system for identification of dense organisms
Authors: Li Haiju , Zhang Chuntang , Bo Jingwen , Ding Zhongjun
Published: April 2021

For detection of dense small‐target organisms with indistinct features in complex background, the efficiency and accuracy of traditional target detection methods are low. Multi‐sensor fusion oriented human‐robot interaction (HRI) system has facilitated biologists to process and analyse data. For this, several deep learning models based on convolutional neural network (CNN) are improved and compared to study the species and density of dense organisms in deep‐sea hydrothermal vent, which are fused it with related environmental information given by position sensors and conductivity‐temperature‐depth (CTD) sensors, so as to perfect multi‐sensor fusion oriented HRI system. Firstly, the authors combined different meta‐architectures and different feature extractors, and obtained five object identification algorithms based on CNN. Then, they compared computational cost of feature extractors and weighed the pros and cons of each algorithm from mean detection speed, correlation coefficient and mean class‐specific confidence score to confirm that Faster Region‐based CNN (R‐CNN)_InceptionNet is the best algorithm applicable to hydrothermal vent biological dataset. Finally, they calculated the cognitive accuracy of rimicaris exoculata in dense and sparse areas, which were 88.3% and 95.9% respectively, to analyse the performance of the Faster R‐CNN_InceptionNet. Results show that the proposed method can be used in the multi‐sensor fusion oriented HRI system for the statistics of dense organisms in complex environments.
Research on intelligent service of customer service system
Authors: Nie Jinji , Wang Qi , Xiong Jianbin
Published: April 2021

With the development of the wireless network, from 4G network to 5G network, people's communication quality has improved significantly and the processing requirements of operators' customer service systems will ameliorate, whereas the business undertaken by the intelligent network becomes more difficult. Customer service system, which can convey files and video, has evolved from manual to intelligent. At the same time, this system establishes a knowledge base based on the process of solving problems with customers. The customer service system can also undertake the task of process control within the enterprise. The ultimate goal is to understand the needs of customers through the knowledge base and develop corporate products based on customer data. Furthermore, this study proposes a network architecture of an intelligent customer service system to provide a reference for the construction.
Joint spectrum sensing, power and bandwidth allocation for multiband cognitive radio systems
Authors: Karimi Mohammad , Ahmadi Shadi
Published: April 2021

Multiband cognitive radio (CR) signaling allows CR networks to efficiently take advantage of the unused frequency bands. Joint spectrum sensing and power allocation in CR systems has been shown to provide higher opportunities for CR transmission. In this work, joint spectrum sensing and resource allocation (power and bandwidth) are performed in a multiband CR system. This is achieved by defining an optimization problem which is formulated with the aim of minimizing CR network outage probability. It is shown that minimizing the outage probability of CR network is equivalent to maximizing the CR network achievable data rate. Hence, the related optimization problem converts to maximizing the average opportunistic CR data rate under constraints on interference, power budget and total available bandwidth leading to a non‐convex optimization problem. As the original formulated optimization problem is inherently non‐convex, it is converted into a convex problem where the optimal solution is obtained using the Lagrange multipliers method and linear programming. For performance comparison, the classical method based on equal bandwidth allocation for each subchannel is considered. Several numerical results are provided to contrast the performance of the proposed method compared to the classical method, in terms of the average achievable CR data rate.
A data‐driven method to predict service level for call centers
Authors: Hou Chenyu , Cao Bin , Fan Jing
Published: April 2021

In call centers, the service level is an important metric to measure the reasonability of the staffing schedule. Traditional service level calculation methods are based on the queue theory, which has very strict restrictions and is not suitable for real scenarios. Therefore, in this paper, a data‐driven method to solve the service level prediction problem is proposed to be used. To this end, the relationship between service level and other factors, such as number of calls, number of agents, time, is explored. Then some features are extracted based on empirical analyses and propose to use decision tree based ensemble methods, like random forest and GBDT, to model the relationship between service level and input features. Finally, extensive experimental results show that the proposed method outperforms other baselines significantly. Especially compared with the traditional queue theory methods, our method improves the performance by 6% and 9% in terms of MAE and MAPE.
Robust static output feedback Nash strategy for uncertain Markov jump linear stochastic systems
Authors: Mukaidani Hiroaki , Xu Hua , Zhuang Weihua
Published: April 2021

In this article, robust static output feedback (SOF) Nash games for a class of uncertain Markovian jump linear stochastic systems (UMJLSSs) are investigated, in which each player may have access to local/private SOF information. It is proved that the robust SOF Nash strategy set can be obtained by minimizing the upper bounds of the cost functions based on a guaranteed cost control mechanism. By using the Karush–Kuhn–Tucker (KKT) condition, the necessary conditions for the existence of the robust SOF Nash strategy set are established in terms of the solvability conditions of nonlinear simultaneous algebraic equations (NSAEs). A heuristic algorithm is developed to solve the NSAEs. Particularly, it is shown that the robust convergence of the heuristic algorithm is guaranteed by combining the Krasnoselskii–Mann (KM) iterative algorithm with a new convergence condition. Finally, a simple practical example is presented to show the reliability and usefulness of the proposed algorithm.
Model identification and parametric adaptive control of hydraulic manipulator with neighborhood field optimization
Authors: Guo Qing , Chen Zhenlei , Shi Yan , Liu Gan
Published: April 2021

The model identification and uncertain parameters estimation are common control problems in multi‐DOF manipulator system, since both model parametric uncertainties and unknown external disturbance often degrade the output performance and the close‐loop system stability. In this study, by using the joint angle and the torque information, a neighborhood field optimization is adopted to identify the Lagrange model parameters of two‐DOF hydraulic manipulator. The fitness function of the neighborhood field optimization is designed to optimize the minimal squared error of the torque estimation and to obtain the lumped estimated parameters with high accuracy. Then based on the identification model, a parametric adaptive controller is designed to address uncertain electro‐hydraulic parameters and external disturbances. Furthermore, a new stable control variable is redesigned to avoid the redundant input saturation of electro‐hydraulic actuator. The effectiveness of the proposed controller is verified by the comparative experimental results with the general backstepping controller.
Quasi‐bipartite synchronisation of multiple inertial signed delayed neural networks under distributed event‐triggered impulsive control strategy
Authors: Udhayakumar K. , Rihan Fathalla A. , Li Xiaodi , Rakkiyappan R.
Published: April 2021

The central concern of this paper is to study leader‐following quasi‐bipartite synchronisation of a multiple inertial signed neural networks with varying time‐delay by utilising distributed event‐triggered impulsive control scheme, where connections between adjacent nodes of the neural networks either positive or negative. The second‐order neural networks, called inertial neural networks, can be transformed into differential equations of first‐order by implementing suitable variable substitution. Under certain hypothesis about the node dynamics, signed graph theory and balanced topology of networks, some conditions are derived in terms of lower‐dimensional linear matrix inequalities (LMIs) to achieve leader‐following quasi‐bipartite synchronisation. In addition, a basic algebraic condition is derived to estimate the theoretical upper bound for the error node. Finally, some numerical simulations are provided to illustrate the correctness of the theoretical results.
Exponential stability of discrete‐time delayed neural networks with saturated impulsive control
Authors: He Zhilong , Li Chuandong , Cao Zhengran , Li Hongfei
Published: April 2021

This paper examines the problem of the locally exponentially stability for impulsive discrete‐time delayed neural networks (IDDNNs) with actuator saturation. By fully considering the delay information of the state of the considered system, a new delay‐dependent polytopic representation within a discrete‐time framework is obtained. Based on the delay‐independent polytopic representation approach, the saturation term is expressed as a delay‐dependent convex combination. In order to obtain some less conservative stability conditions and estimate a larger of the domain of attraction, a novel type of Lyapunov–Krasovskii function (LKF) dependent on the delay information and the impulses instant is proposed, which is called time‐dependent LKF. Then, by combining with the proposed LKF, a discrete Wirtinger‐based inequality, an extended reciprocally convex matrix inequality and some novel analysis techniques, several new exponential stability criteria dependent on the bounds of the delay are presented. Moreover, when saturation constraints are not considered in the impulsive controller, the stability of the system is also discussed. Finally, two examples are given to confirm the applicability of the proposed results.
The effect of standing waves on the attenuation constant for a low‐loss rectangular waveguide
Authors: Collier Richard J. , Ridler Nick M. , Young Paul R.
Published: April 2021

When standing waves are present in a rectangular waveguide, the resistive losses in the walls are not uniformly distributed. This affects the measurement of the attenuation constant. Here the phenomenon for the TE10 mode in air‐filled waveguide, where the deviation from the normal travelling wave attenuation constant is only about ±1% over the conventional bandwidth, is discussed. However, the paper also shows that nearer the cut‐off frequency for the waveguide, the deviation could be as high as ±100%.
Complex permittivity control of SiCf/SiC composite through thermal oxidation
Authors: Lee Hyun Seok , Lee Won Jun
Published: April 2021

In this letter, we propose a process for fabricating a Silicon Carbide fiber (SiCf)/Silicon Carbide (SiC) composite radar‐absorbing structure (RAS); the process can precisely control the complex permittivity of the composite in high‐temperature environments. During the manufacturing of the SiCf/SiC composite, sufficient carbon is supplied to the SiC fibre to ensure conductive properties. Thereafter, thermal oxidation is performed to remove carbon, which transformed the conductive property of the composite material into the dielectric property. The duration of thermal oxidation was controlled because of which the complex permittivity of the composite material approached the optimal complex permittivity for impedance matching. A specimen of the SiCf/SiC composite radar‐absorbing structure was produced, and the reflection loss of the specimen was measured. The results indicated that the specimen could absorb more than 99% of the incident electromagnetic waves in the frequency range from 9.02 to 9.84 GHz.
Compact 4 × 4 butler matrix with non‐standard phase differences for IoT applications
Authors: Bekasiewicz Adrian , Koziel Slawomir
Published: April 2021

Butler matrices represent a popular class of feeding networks for antenna arrays. Large dimensions and the lack of flexibility in terms of achievable output phase difference make conventional Butler structures of limited use for modern communication devices. In this work, a compact planar 4 × 4 matrix with non‐standard relative phase shifts of –30, 150, –120, and 60° has been proposed. The structure is designed to operate at the centre frequency of 2.45 GHz. Small dimensions of 31.3 × 22.9 mm make it useful for Internet of Things applications. The structure operates from 2.35 to 2.55 GHz, which covers the industrial, scientific and medical bandwidth. At the centre frequency, the measured amplitude and phase imbalance are 1.65 dB and ±4.3°, respectively. The proposed circuit has been compared to the state‐of‐the‐art structures from the literature.
On outage performance of IRS‐assisted wireless communication with user mobility following RWP model
Authors: Zhao Xiang , Sun Jinyong
Published: April 2021

An intelligent reflecting surface (IRS)‐assisted wireless communication system with user mobility following random waypoint (RWP) model is investigated, where the user receives the reflection signal from the IRS controlled by the access point (AP) via a programmable controller, and the IRS is mounted on an unmanned aerial vehicle which is only an auxiliary device to enable IRS reflection communication at a certain altitude. As user moves, the AP makes the reflected beamforming of the IRS following with the user through coding the unit‐element of the IRS. To investigate the effect of joint IRS feature and user mobility on the outage performance, the cumulative distribution function of the received signal‐to‐noise ratio of the mobile user is first derived and then the close‐form expression for the outage probability is obtained. Numerical simulations are performed to validate the accuracy of the analytical results. The solutions are also compared with that for conventional amplify‐and‐forward relay system. Insights are drawn related to the number of meta‐surface elements, and the maximum activity radius of mobile user.
Experimental study on the practical mitigation of passive intermodulation for time and temperature in cavity duplexer
Authors: Choi Byungchang
Published: April 2021

Practical methods to mitigate level and variation of passive intermodulation with respect to time and temperature of coaxial cavity type duplexer are proposed through a variety of experimental results. From the findings derived in this study, a stable passive intermodulation response with less than 1 dB variation was shown in the environment temperature range of −10–85 °C. The duplexer with time‐stable PIM response at room temperature had a stable PIM value even in the environment temperature range.