bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative genomics in the search for conserved long noncoding RNAs
Authors: Szcześniak Michał Wojciech , Kubiak Magdalena Regina , Wanowska Elżbieta , Makałowska Izabela 
Published: April 2021

Abstract
Long noncoding RNAs (lncRNAs) have emerged as prominent regulators of gene expression in eukaryotes. The identification of lncRNA orthologs is essential in efforts to decipher their roles across model organisms, as homologous genes tend to have similar molecular and biological functions. The relatively high sequence plasticity of lncRNA genes compared with protein-coding genes, makes the identification of their orthologs a challenging task. This is why comparative genomics of lncRNAs requires the development of specific and, sometimes, complex approaches. Here, we briefly review current advancements and challenges associated with four levels of lncRNA conservation: genomic sequences, splicing signals, secondary structures and syntenic transcription.
Multi‐modal broad learning for material recognition
Authors: Wang Zhaoxin , Liu Huaping , Xu Xinying , Sun Fuchun 
Published: April 2021

AbstractMaterial recognition plays an important role in the interaction between robots and the external environment. For example, household service robots need to replace humans in the home environment to complete housework, so they need to interact with daily necessities and obtain their material performance. Images provide rich visual information about objects; however, it is often difficult to apply when objects are not visually distinct. In addition, tactile signals can be used to capture multiple characteristics of objects, such as texture, roughness, softness, and friction, which provides another crucial way for perception. How to effectively integrate multi‐modal information is an urgent problem to be addressed. Therefore, a multi‐modal material recognition framework CFBRL‐KCCA for target recognition tasks is proposed in the paper. The preliminary features of each model are extracted by cascading broad learning, which is combined with the kernel canonical correlation learning, considering the differences among different models of heterogeneous data. Finally, the open dataset of household objects is evaluated. The results demonstrate that the proposed fusion algorithm provides an effective strategy for material recognition.
Unstructured road parameter cognition for ICVs using multi‐frame 3D point clouds
Authors: Xie Guotao , Yan Kangjian , Wang Dongsheng , Sun Ning , Gao Hongbo 
Published: April 2021

AbstractRoad parameter cognition is essential for intelligent and connected vehicles (ICVs) operating on unstructured roads because it can influence their path planning and motion control. A method is presented for the extraction of longitudinal slopes and lateral slopes and the roughness of unstructured roads using multi‐frame three‐dimensional point clouds. First, a segmentation method based on the multiple features is proposed to extract and divide the regions of interest into blocks with different slopes, which is valuable for further study on ground segmentation. Second, a parameter cognition method is proposed to estimate the slope and roughness of unstructured roads. Last but not least, a multi‐frame fusion method is proposed to improve cognition accuracy. Experimental tests on unstructured roads demonstrate that the proposed algorithm has satisfactory performance in terms of the accuracy of recognizing road slopes and roughness.
Compact empty substrate integrated waveguide with high performance and its application in microwave
Authors: Qiang Jingxia , Xu Feng , Yang Ling , Zhan Junlin 
Published: April 2021

AbstractA compact slow‐wave empty substrate integrated waveguide (SW‐ESIW) structure is proposed in this article. This structure is composed of an empty substrate with a bottom layer including several rows of internal metallised via holes. In order to decrease both the lateral and longitudinal dimensions, the slow wave effect, caused by physical separation of electric and magnetic fields, is introduced while retaining the advantages of ESIW, such as high quality factor, small insertion loss, and the advantages of SIW, such as low cost and easy processing. Compared to the classical ESIW, the proposed SW‐ESIW structure achieves a size reduction of 37% and retains the triple‐layer structure. At the same time, in contrast with general SW‐SIW structure, which needs double layer with dielectric material, the novel waveguide obtains a significant performance improvement in insertion loss and quality factor. In the article, a fourth‐order filter is designed to verify the idea that the SW‐ESIW technology provides the low loss, high quality factor and compact structure. By combining the advantages of SW‐SIW and ESIW technology, the proposed SW‐ESIW structure can be widely applied to the microwave integrated circuits with miniaturisation and high quality factor.
Resistance switching and conduction mechanism on ferroelectric copolymer thin film device
Authors: Qin Xue , Xiao Xia , Qin Shu‐Chao , Dong Rui‐Xin , Yan Xun‐Ling 
Published: April 2021

AbstractThe memristor of sandwich structure is prepared by employing the ferroelectric copolymer poly (vinylidene fluoride/trifluoroethylene) (P(VDF‐TrFE)). The device exhibits great bipolar resistance switching characteristics. The low on–off voltage (3/−2.7 V) and high Ion/Ioff ratio (≈103) as well as fast switching speed are obtained in this device. Based on the intrinsic spontaneous polarization characteristics of ferroelectric materials, the conduction mechanism model of ferroelectric film conductive channel is established and the linear relationship between conductivity and average polarization intensity is given. The calculated results of conductance–voltage (G–V) curve show an obvious hysteresis phenomenon and the distinguishable high/low conductivity states. This physical model is consistent with the experimental results, indicating a reasonable conduction mechanism of the device.
Complementary frequency modulated radar waveforms and optimised receive processing
Authors: Jones Christian C. , Mohr Charles A. , McCormick Patrick M. , Blunt Shannon D. 
Published: April 2021

AbstractDesign methodologies are developed for complementary frequency modulated (FM) waveforms and for optimised complementary mismatched filtering (MMF) of arbitrary non‐repeating waveforms. The former is a sub‐class of random FM waveforms denoted as complementary FM (Comp‐FM) while the latter extends a practical instantiation of least‐squares mismatched filtering yielding the mismatched complementary‐on‐receive filtering (MiCRFt) scheme. Both of these approaches have an emphasis on the non‐ideal physical effects of the radar transmitter and receiver, thereby permitting high‐fidelity simulation analysis and subsequent experimental demonstration of their efficacy using open‐air measurements.
Modelling radio luminosity functions of radio-loud AGN by the cosmological evolution of supermassive black holes
Authors: Tucci Marco , Toffolatti Luigi 
Published: April 2021

Aims. We develop a formalism to model the luminosity functions (LFs) of radio-loud active galactic nuclei (AGN) at GHz frequencies by the cosmological evolution of the supermassive black hole (SMBH) hosted in their nuclei. The mass function and Eddington ratio distributions of SMBHs computed in a previous work published by one of the authors have been taken as the starting point for this analysis.
Methods. Our approach is based on physical and phenomenological relations that allow us to statistically calculate the radio luminosity of AGN cores, corrected for beaming effects, by linking it with the SMBH at their centre, through the fundamental plane of black hole activity. Moreover, radio luminosity from extended jets and lobes is also computed through a power-law relationship that reflects the expected correlation between the inner radio core and the extended jets and lobes. By following a classification scheme well established in the field, radio-loud AGN are further divided into two classes, characterized by different accretion modes onto the central BH. If the Eddington ratio, λ, is ≤0.01 they are called low-kinetic (LK) mode AGN; if λ ≥ 0.01, they are called high-kinetic (HK) mode AGN, this critical value roughly corresponding to the transition between radiatively inefficient and efficient accretion flows. The few free parameters used in the present model are determined by fitting two different types of observational data sets: local (or low-redshift) LFs of radio-loud AGN at 1.4 GHz and differential number counts of extragalactic radio sources at 1.4 and 5 GHz.
Results. Our present model fits well almost all published data on LFs of LK mode AGN and of the total AGN population up to redshifts z ≤ 1.5 and also in the full range of luminosities currently probed by data. On the other hand, it tends to underestimate some recent measures of the LF of HK mode AGN at low redshifts, but only at low radio luminosities. All in all, the good performance of our model in this redshift range is remarkable, considering that all the free parameters used but the fraction of HK mode AGN are redshift independent. The present model is also able to provide a very good fit to almost all data on number counts of radio-loud sources at 1.4 and 5 GHz.
Vulnerability and mutual insurance
Authors: Eisen Roland 
Published: April 2021

AbstractVulnerability comes, according to Orio Giarini, with two risks: human-made risks, also called entrepreneurial risks, and natural or pure risks such as accidents and earthquakes. Both types of risk are growing in dimension and are increasingly interrelated. To control the vulnerability, sophisticated insurance products are called for. Here, mutual insurance is relevant, in particular when risks are large, probabilities uncertain or unknown, and events interrelated or correlated. In this paper the following three examples are discussed and the advantages of mutual insurance are shown: unknown probabilities connected with unforeseeable events, correlated risks and macroeconomic or demographic risks.
Changes in mobility and socioeconomic conditions during the COVID-19 outbreak
Authors: Dueñas Marco , Campi Mercedes , Olmos Luis E. 
Published: April 2021

AbstractSince the outbreak of the 2019 novel coronavirus (COVID-19) pandemic, governments have been implementing containment measures aimed at mitigating the spread of the virus, including restrictions to human mobility. The ability to adapt to the pandemic and respond to containment measures can be bound by socioeconomic conditions, which are heterogeneous in large urban areas of low-income and middle-income countries. In this paper, we analyse mobility changes following the implementation of containment measures in Bogotá, Colombia. We characterise the mobility network before and during the pandemic and analyse its evolution and changes between January and July 2020. We observe a general reduction in mobility trends, but the overall connectivity between different areas of the city remains after the lockdown, reflecting the resilience of the mobility network. Then, we estimate a gravity model to assess the effect of socioeconomic conditions on mobility flows. We find that the responses to lockdown policies depend on the socioeconomic conditions of the population. Before the pandemic, the population with better socioeconomic conditions shows higher mobility flows. Since the lockdown, mobility presents a general decrease, but the population with worse socioeconomic conditions shows lower reductions in mobility flows. We conclude by deriving policy implications.
Deletion mutation within the goat
Authors: Bai Yangyang , Li Jie , Zhu Haijing , Liu Jinwang , Dong Shuwei , Li Longping , Qu Lei , Chen Hong , Song Xiaoyue , Lan Xianyong 
Published: April 2021

The protein phosphatase 3 catalytic subunit α (PPP3CA) gene is a high reproduction traits candidate gene for goats as revealed by a genome-wide association study. The aim of this work was to explore the genetic variations of the goat PPP3CA as well as to evaluate the genetic effects on litter size. Three novel insertions/deletions (indels) within the goat PPP3CA were found and their minor allelic frequencies (MAF) were 0.105, 0.066, and 0.042, respectively. The results showed that only the 20 bp indel polymorphism was significantly associated with litter size in Shaanbei white cashmere goats (P < 0.05) and individuals with deletion/deletion (DD) genotypes demonstrated the junior phenotypes when compared with those with other genotypes. These findings suggested that the 20 bp indel is a potential DNA marker for selecting superior individuals in marker-assisted selection for breeding concerning fecundity in goats.
Scalable deep learning to identify brick kilns and aid regulatory capacity
Authors: Lee Jihyeon , Brooks Nina R. , Tajwar Fahim , Burke Marshall , Ermon Stefano , Lobell David B. , Biswas Debashish , Luby Stephen P. 
Published: April 2021

Significance
Monitoring compliance with environmental regulations is a global challenge. It is particularly difficult for governments in low-income countries, where informal industry is responsible for a large amount of pollution, because the governments lack the ability to locate and monitor large numbers of dispersed polluters. This study demonstrates an accurate, scalable machine-learning approach for identifying brick kilns, a highly polluting informal industry in Bangladesh, in satellite imagery. Our data reveal widespread violations of the national regulations governing brick manufacturing, which has implications for the health and well-being of the country. Our approach offers a low-cost, replicable method for regulatory agencies to generate information on key pollution sources.
Communication-efficient federated learning
Authors: Chen Mingzhe , Shlezinger Nir , Poor H. Vincent , Eldar Yonina C. , Cui Shuguang 
Published: April 2021

Significance
Federated learning (FL) is an emerging paradigm that enables multiple devices to collaborate in training machine learning (ML) models without having to share their possibly private data. FL requires a multitude of devices to frequently exchange their learned model updates, thus introducing significant communication overhead, which imposes a major challenge in FL over realistic networks that are limited in computational and communication resources. In this article, we propose a communication-efficient FL framework that enables edge devices to efficiently train and transmit model parameters, thus significantly improving FL performance and convergence speed. Our proposed FL framework paves the way to collaborative ML in large-scale networking systems such as Internet of Things networks.
Impact of land use and land cover changes on carbon storage in rubber dominated tropical Xishuangbanna, South West China
Authors: Sarathchandra Chaya , Alemu Abebe Yirga , Worthy Fiona Ruth , Lakmali Wijerathne Iresha , Ma Huaixia , Yingfeng Bi , Jiayu Guo , Chen Huafang , Yan Qiaoshun , Geng Yanfei , Weragoda Dayani S. , Li Li-Li , Fengchun Yang , Wickramasinghe Sriyani , Xu Jianchu 
Published: April 2021

ABSTRACT

Land use and land cover (LULC) play a significant role in carbon regulation. South-China accounts for ~65% of China’s carbon sink. In Xishuangbanna (South-China), rubber is expanding rapidly creating an urgent need to understand and monitor LULC change and how spatial variation affects carbon storage (CS). This is vital for the formation and implementation of better land use management practices. We studied LULC changes of 22-year period; addressing how these changes have affected the CS. We quantified LULC changes between1988 and 2010 using remote sensing methods and calculated CS changes using InvEST. Results showed that between 1988 and 2010, the rate of deforestation accelerated to 203.2 km
2
y
−1
and ~23% of forest were lost. Conversion of natural forest to rubber was responsible for 78% of this deforestation. Rubber expansion rate was 153.4 km
2
y
−1
. Changes to LULC drove a temporal CS reduction 0.223 Tg C/km
2
. Local stakeholders have strong economic interest in converting land to more profitable plantations. Government efforts is required to control land conversion through new policies and incentives to retain natural forest. Assessment of specific potential land use change will be required to avoid promoting the conversion of high carbon storage land uses to low carbon storage land uses.
Distance sensor with a tunable aperture actuated by thermal expansion of silicon chevron beams
Authors: Hong Chong Ho , Kim Hyeon Cheol , Jatmiko Wisnu , Kurnianingsih  , Chun Kukjin , Park Byung-Gook 
Published: April 2021

Abstract
To measure the distance of an object, we propose a distance sensor that combines a tunable aperture operated by the thermal expansion of silicon chevron beams with a commercial camera similar to the automotive black box. The distance sensor is composed of a tunable aperture, a lens with an 8 mm focal length, and a 1/4-inch full high definition image sensor, where a tunable aperture is attached to the camera lens. To estimate the distance to the object, the blur difference is expressed in the form of a depth map using the depth from defocus algorithm. The mean error of distance estimation was 0.29 m. The area of the tunable aperture in the distance sensor is 1.18 mm2 at OFF state and 2.79 mm2 when the voltage is applied. The distance sensor can display an image and a distance simultaneously and can be applied to autonomous vehicles, drones, and robots.
Operando SAXS study of a Pt/C fuel cell catalyst with an X-ray laboratory source
Authors: Schröder Johanna , Quinson Jonathan , Kirkensgaard Jacob J K , Arenz Matthias 
Published: April 2021

Abstract
Small-angle X-ray scattering (SAXS) is a powerful technique to investigate the degradation of catalyst materials. Ideally such investigations are performed operando, i.e. during a catalytic reaction. An example of operando measurements is to observe the degradation of fuel cell catalysts during an accelerated stress test (AST). Fuel cell catalysts consist of Pt or Pt alloy nanoparticles (NPs) supported on a high surface area carbon. A key challenge of operando SAXS measurements is a proper background subtraction of the carbon support to extract the information of the size distribution of the Pt NPs as a function of the AST treatment. Typically, such operando studies require the use of synchrotron facilities. The background measurement can then be performed by anomalous SAXS or in a grazing incidence configuration. In this work we present a proof-of-concept study demonstrating the use of a laboratory X-ray diffractometer for operando SAXS. Data acquisition of operando SAXS with a laboratory X-ray diffractometer is desirable due to the general challenging and limited accessibility of synchrotron facilities. They become even more crucial under the ongoing and foreseen restrictions related to the COVID-19 pandemic. Although, it is not the aim to completely replace synchrotron-based studies, it is shown that the background subtraction can be achieved by a simple experimental consideration in the setup that can ultimately facilitate operando SAXS measurements at a synchrotron facility.
Obtaining impact ionization-induced hole current by electrical measurements in gallium nitride metal–insulator–semiconductor high electron mobility transistors
Authors: Yeh Yu-Hsuan , Chang Ting-Chang , Huang Wei-Chen , Zheng Hao-Xuan , Tsao Yu-Ching , Ciou Fong-Min , Lin Yu-Shan , Tan Yung-Fang , Sun Li-Chuan , Zhou Kuan-Ju , Chen Kuan-Hsu , Huang Jen-Wei 
Published: April 2021

Abstract
In this paper, an extraction method for measuring impact ionization-induced hole current in gallium nitride (GaN) metal–insulator–semiconductor high electron mobility transistors (MIS-HEMTs) is proposed. The results show that the non-monotonic impact ionization current characteristic can be easily acquired by the extraction method. Further, different hot-carrier stress (HCS) conditions can be obtained based on the I
G–V
G curve, and the reliability tests can act as verification of the impact-ionization curve. In addition, electrical reliability tests indicate that the threshold voltage (V
TH) shift and on-state current (I
on) degradation in the MIS-HEMTs have a positive correlation to impact ionization-generated hole current. During HCS operation, the V
TH will shift positively and I
on decreases due to hot electrons trapping into the GaN layer. This model is validated by TCAD simulation.
Morphology-dependent catalytic activity of tungsten trioxide (WO3) nanostructures for hydrogenation of furfural to furfuryl alcohol
Authors: Ali Wesam A , Bharath G , Morajkar Pranay P , Salkar Akshay V , Haija Mohammad Abu , Banat Fawzi 
Published: April 2021

Abstract
The development of effective and low-cost catalysts for the hydrogenation and stabilization of bio-oils is still a challenge that needs to be overcome. Several nanostructured WO3 catalysts were synthesized in this study to investigate the effect of their morphology on their catalytic activity and selectivity for the hydrogenation of biomass-derived compounds such as furfural (FF). The morphology of the catalysts was tuned via a surfactant-assisted hydrothermal process. Nanorod and nanoprism WO3 catalysts were produced using dodecyl dimethylammonium bromide (DAB) and poly (ethylene-alt-maleic anhydride), respectively, while WO3 nanocubes were produced without the use of surfactants. Various analytical techniques were used to characterize the morphology of the synthesized WO3 catalyst. Furthermore, the hydrogenation of FF was used as a probe reaction to evaluate the catalytic performance of the WO3 nanostructures. Notably, DAB-assisted WO3 nanorods (D-WO3) exhibited a relatively high furfuryl alcohol (FFA) selectivity of 85% with an FF conversion of 52% at 100 °C, under 10 bar of H2 pressure over a reaction time of 120 min. A plausible route for the hydrogenation of FF into FFA and other products over D-WO3 nanocatalyst was illustrated. The D-OW3 nanocatalyst’s promising results indicate that it could be a viable, low-cost, and efficient alternative catalyst for hydrogenating FF into FFA.
Recent development in friction of 2D materials: from mechanisms to applications
Authors: Guo Yanbao , Zhou Xuanli , Lee Kyungjun , Yoon Hyun Chul , Xu Quan , Wang Deguo 
Published: April 2021

Abstract
Two-dimensional (2D) materials with a layered structure are excellent candidates in the field of lubrication due to their unique physical and chemical properties, including weak interlayer interaction and large specific surface area. For the last few decades, graphene has received lots of attention due to its excellent properties. Besides graphene, various new 2D materials (including MoS2, WS2, WSe2, NbSe2, NbTe2, ReS2, TaS2 and h-BN etc.) are found to exhibit a low coefficient of friction at the macro- and even micro-scales, which may lead to widespread application in the field of lubrication and anti-wear. This article focuses on the latest development trend in 2D materials in the field of tribology. The review begins with a summary of widely accepted nano-scale friction mechanisms contain surface friction mechanism and interlayer friction mechanism. The following sections report the applications of 2D materials in lubrication and anti-wear as lubricant additives, solid lubricants, and composite lubricating materials. Finally, the research prospects of 2D materials in tribology are presented.