bluuebunny/crossref_metadata_2025_split huggingface dataset:
A marginalised particle filter with variational inference for non‐linear state‐space models with Gaussian mixture noise
Authors: Cheng Cheng , Tourneret Jean‐Yves , Lu Xiaodong 
Published: October 2021

AbstractThis work proposes a marginalised particle filter with variational inference for non‐linear state‐space models (SSMs) with Gaussian mixture noise. A latent variable indicating the component of the Gaussian mixture considered at each time instant is introduced to specify the measurement mode of the SSM. The resulting joint posterior distribution of the state vector, the mode variable and the parameters of the Gaussian mixture noise is marginalised with respect to the noise variables. The marginalised posterior distribution of the state and mode is then approximated by using an appropriate marginalised particle filter. The noise parameters conditionally on each particle system of the state and mode variable are finally updated by using variational Bayesian inference. A simulation study is conducted to compare the proposed method with state‐of‐the‐art approaches in the context of positioning in urban canyons using global navigation satellite systems.
Construction and characterization of rectal cancer‐related lncRNA‐mRNA ceRNA network reveals prognostic biomarkers in rectal cancer
Authors: Cai Guoying , Sun Meifei , Li Xinrong , Zhu Junquan 
Published: October 2021

AbstractRectal cancer is an important cause of cancer‐related deaths worldwide. In this study, the differentially expressed (DE) lncRNAs/mRNAs were first identified and the correlation level between DE lncRNAs and mRNAs were calculated. The results showed that genes of highly correlated lncRNA‐mRNA pairs presented strong prognosis effects, such as GPM6A, METTL24, SCN7A, HAND2‐AS1 and PDZRN4. Then, the rectal cancer‐related lncRNA‐mRNA network was constructed based on the ceRNA theory. Topological analysis of the network revealed that the network was maintained by hub nodes and a hub subnetwork was constructed, including the hub lncRNA MIR143HG and MBNL1‐SA1. Further analysis indicated that the hub subnetwork was highly related to cancer pathways, such as ‘Focal adhesion’ and ‘Wnt signalling pathway’. Hub subnetwork also had significant prognosis capability. A closed lncRNA‐mRNA module was identified by bilateral network clustering. Genes in modules also showed high prognosis effects. Finally, a core lncRNA‐TF crosstalk network was identified to uncover the crosstalk and regulatory mechanisms of lncRNAs and TFs by integrating ceRNA crosstalks and TF binding affinities. Some core genes, such as MEIS1, GLI3 and HAND2‐AS1 were considered as the key regulators in tumourigenesis. Based on the authors’ comprehensive analysis, all these lncRNA‐mRNA crosstalks provided promising clues for biological prognosis of rectal cancer.
How many Mel‐frequency cepstral coefficients to be utilized in speech recognition? A study with the Bengali language
Authors: Hasan Md. Rakibul , Hasan Md. Mahbub , Hossain Md Zakir 
Published: October 2021

AbstractSpeech‐related research has a wide range of applications. Most speech‐related researches employ Mel‐frequency cepstral coefficients (MFCCs) as acoustic features. However, finding the optimum number of MFCCs is an active research question. MFCC‐based speech classification was performed for both vowels and words in the Bengali language. As for the classification model, deep neural network (DNN) with Adam optimizer was used. The performances were measured with five different performance metrics, namely confusion matrix, classification accuracy, area under curve of receiver operating characteristic (AUC‐ROC), F score, and Cohen's Kappa with four‐fold cross‐validations at different number of MFCCs. All performance metrics gave the best score for 24/25 MFCCs; hence it is suggested that the optimum number of MFCCs should be 25, although many existing studies use only 13 MFCCs. Furthermore, it is verified that increasing the number of MFCCs yields better classification metrics with lower computational burden than the increment of hidden layers. Lastly, the optimum number of MFCCs obtained from this study was used in a more improved DNN model, from which 99% and 90% accuracies were achieved for vowel and word classification, respectively, and the vowel classification score outperformed state‐of‐the‐art results.
Ternary VS2/ZnS/CdS hybrids as efficient electrocatalyst for hydrogen evolution reaction: Experimental and theoretical insights
Authors: Shinde Pratik V. , Gavali Deepak S. , Thapa Ranjit , Singh Manoj Kumar , Rout Chandra Sekhar 
Published: October 2021

Widely used precious metal (i.e., Pt, or Pd) electrocatalysts need to be replaced with other cost-effective and earth-abundant materials for economical water splitting applications. Recently, two-dimensional (2D) transition metal dichalcogenides (MoS2, VS2, WS2, etc.) have emerged as ideal electrocatalysts for the hydrogen evolution reaction (HER) due to their tunable physicochemical properties and rich catalytic active sites. In this regard, we propose a strategy to achieve improved HER performance of VS2 by fabricating a hybrid material with transition metal (Zn and Cd)-based sulfides. A facile hydrothermal approach is employed to prepare a VS2/ZnS/CdS hybrid catalyst that exhibits remarkable electrocatalytic performance for the HER in acidic media with a small overpotential of 86 mV at 10 mA/cm2 and a Tafel slope of 74.4 mV/dec. This inferred the Volmer–Heyrovsky mechanism with electrochemical desorption of hydrogen as the rate-limiting step. High performance is attributed to the abundance of catalytically active sites and the synergistic interactions between the materials. Theoretical calculations reveal that the VS2/ZnS/CdS hybrid shows favorable HER activity owing to its low hydrogen adsorption free energy of about 0.35 eV. We believe that this work on designing 2D VS2/ZnS/CdS will offer a new pathway to discover an efficient H2 generation electrocatalyst.
A cure for woundless pain
Authors: She Yasheng 
Published: October 2021

AbstractAs a cultural construct, the idol is a consumer product created to “heal” in the age of exhaustion. Layering a “guardian” aspect onto Laura Mulvey’s “male gaze,” this paper contextualizes the commodification and consumption of innocence. This paper brings the documentary,Tokyo Idols(2017), and the animated film,Perfect Blue(1997), into a conversation to theorize how femininity is constructed and commodified in Japan’s pop idol industry. The idol culture consumes innocence only to create more trauma for women by stressing the arbitrary importance of innocence and sacrificing female agency in the process.
Romance N Prep N constructions in visual word recognition
Authors: Hennecke Inga , Baayen Harald 
Published: October 2021

Abstract
N Prep N constructions such as Sp. bicicleta de montaña ‘mountain bike’ are very productive and
frequent in Romance languages. They commonly have been classified as syntagmatic compounds that show no
orthographic union and exhibit an internal structure that resembles free syntactic structures, such as Sp. libro para
niños ‘book for children’. There is no consensus on how to best distinguish lexical from syntactic N Prep N
constructions. The present paper presents an explorative eye-tracking study on N Prep N constructions, varying both lexical type
(lexical vs. syntactic) and preposition across three languages, French, Spanish and Portuguese. The task of the eye-tracking study
was a reading aloud paradigm of the constructions in sentence context. Constructions were fixated on less when more frequent,
independent of lexical status. There was also modest evidence that a higher construction frequency afforded shorter total fixation
durations, but only for lower deciles of the response distribution. The (construction-initial) head noun also received fewer
fixations as construction frequency increased, and also when the head noun was more frequent. The second fixation durations on the
head noun also revealed an effect of lexical status, with syntactic constructions receiving shorter fixations at the 5th and 7th
deciles. The probability of a fixation on the preposition decreased with preposition frequency, but first fixations on the
preposition increased with preposition frequency. The prepositions of Portuguese, the language with the richest inventory of
prepositions, received more fixations than the prepositions of French and Spanish. The observed pattern of results is consistent
with models of lexical processing in which reading is guided by knowledge of both higher-level constructions and knowledge of key
constituents such as the head noun and the preposition.
Metaphor and metonymy in Chinese and American political cartoons (2018–2019) about the Sino-US trade conflict
Authors: Zhang Cun , Forceville Charles 
Published: October 2021

AbstractPolitical cartoons make meaning by drawing on scenarios that must be immediately recognizable by their intended audience. Crucial meaning-making mechanisms in these scenarios are verbo-visual ensembles of metaphors and metonymies. In this paper we investigate 69 Chinese and 60 American political cartoons published in 2018 and 2019 that pertain to the two nations’ trade conflict. By examining the cross-cultural similarities and differences between metaphors and metonymies, we chart how Chinese and American cartoonists portray this trade conflict. We end by showing how a complete interpretation of the cartoons requires enrichment with insights provided by yet other analytical instruments.
ASMADA—A tool for automatic analysis of shape memory alloy thermal cycling data under constant stress
Authors: Kuner Matthew C , Karakalas Anargyros A , Lagoudas Dimitris C 
Published: October 2021

Abstract
The authors present the automatic shape memory alloy data analyzer (ASMADA). ASMADA is capable of rapid, robust, and consistent processing of shape memory alloy thermal cycling data acquired under constant stress. This seeks to address two primary issues: the lack of unified analysis procedures in relevant standards and the near-universal manual analysis of such data. ASMADA is compliant with the definitions provided in ASTM standards and calculates up to twenty-three (23) material properties/parameters at speeds ranging from 5 to 35 cycles s−1. These parameters include the four transformation start/finish temperature thresholds, which are calculated using the tangent line method; the transformation region tangent lines are determined using a modified sigmoid function, whereas the single-phase region tangent lines are determined based on the geometry of the cycle data. Additionally, a graphical user interface is provided to make the tool readily accessible and easy to navigate. The capabilities of ASMADA have been tested on experimental data from four different research groups; results from five of these tests are presented to demonstrate the tool’s robustness. This tool was developed in Python and is publicly available at https://github.com/matthewkuner/ASMADA
Magnetorheological damper temperature characteristics and control-oriented temperature-revised model
Authors: Liang Guanqun , Zhao Tong , Li Ningfei , Wei Yintao , Savaresi Sergio Matteo 
Published: October 2021

Abstract
Accurate control of the magnetorheological damper (MRD) damping force and current is necessary to realize the effective semi-active suspension control. However, the temperature sensitivity of the magnetorheological fluid makes the MRD force strongly dependent on temperature changes, leading to the problem of the model mismatch and degradation of control effect. In this paper, the experimental study of MRD at different currents and velocities from −40 °C to 80 °C was implemented. It reveals the characteristic of MRD damping loss at low temperatures and viscous damping reduction at high temperatures. On this basis, a new parametrized hyperbolic hysteresis model with temperature as an independent variable is proposed, providing an accurate description of the viscosity, stiffness, and hysteresis characteristics of the MRD. A simplified temperature-revised inverse model is proposed to calculate the driving current with demanding force. It could improve the accuracy of driving current by 12.79% and demanding force by 18.67%. A process in the loop simulation is implemented to validate the inverse model with a modified non-chattering algorithm. Together with the inverse model, the proposed algorithm could realize continuous current change, reducing the RMS of acceleration by 14% on road of class B. Furthermore, the temperature compensation could improve the control effect by 19.78%.
Lamb wave damage severity estimation using ensemble-based machine learning method with separate model network
Authors: Rizvi Syed Haider M , Abbas Muntazir 
Published: October 2021

AbstractLamb wave-based damage estimation have great potential for structural health monitoring. However, designing a generalizable model that predicts accurate and reliable damage quantification result is still a practice challenge due to complex behavior of waves with different damage severities. In the recent years, machine learning (ML) algorithms have been proven to be an efficient tool to analyze damage-modulated Lamb wave signals. In this study, ensemble-based ML algorithms are employed to develop a generalizable crack quantification model for thin metallic plates. For this, the scattering of Lamb wave signals due to different configuration of crack dimension and orientation is extensively studied. Various finite element simulations signals, representing distinct crack severities in term of crack length, penetration and orientation are acquired. Realizing that both temporal and spectral information of signal is extremely important to damage quantification, three time-frequency (TF) based damage sensitive indices namely energy concentration, TF flux and coefficient of energy variance are proposed. These damage features are extracted by employing smoothed-pseudo Wigner–Ville distribution. After that data augmentation technique based on the spline-based interpolation is applied to enhance the size of the dataset. Eventually, these fully developed damage dataset is deployed to train ensemble-based models. Here we propose separate model network, in which different models are trained and then link together to predict new and unseen datasets. The performance of the proposed model is demonstrated by two cases: first simulated data incorporated with high artificial noises are employed to test the model and in the second scenario, experimental data in raw form are used. Results indicate that the proposed model has the potential to develop a general model that yields reliable answer for crack quantification.
Stranded land constrains public land management and contributes to larger fires
Authors: Leonard Bryan , Plantinga Andrew J , Wibbenmeyer Matthew 
Published: October 2021

Abstract
Wildfire activity in the western United States has been increasing since the 1970s, with many fires occurring on land managed by government agencies. Over six million acres of public lands are surrounded by private land and lack road access, making them legally inaccessible to federal and state agencies and potentially constraining management and suppression of wildfires. In this paper, we assemble data on all fires that started on public lands in the western US over the period 1992–2015 and estimate the effect of legal accessibility on fire size. We find that ignitions are 14%–23% more likely to become large (greater than one acre) if they occur on inaccessible land. We provide evidence that this effect may be driven in part by agencies’ inability to conduct fuels management and in part by slower suppression responses on legally inaccessible land. Our results suggest that wildfire prevention and suppression could be bolstered by improved access to public lands and underscore the need for ongoing research on the relationship between land ownership and wildfire.
Guaranteeing completely positive quantum evolution
Authors: Dilley Daniel , Gonzales Alvin , Byrd Mark 
Published: October 2021

Abstract
In open quantum systems, it is known that if the system and environment are in a product state, the evolution of the system is given by a linear completely positive (CP) Hermitian map. CP maps are a subset of general linear Hermitian maps, which also include non completely positive (NCP) maps. NCP maps can arise in evolutions such as non-Markovian evolution, where the CP divisibility of the map (writing the overall evolution as a composition of CP maps) usually fails. Positive but NCP maps are also useful as entanglement witnesses. In this paper, we focus on transforming an initial NCP map to a CP map through composition with the asymmetric depolarizing map. We use separate asymmetric depolarizing maps acting on the individual subsystems. Previous work have looked at structural physical approximation (SPA), which is a CP approximation of an NCP map using a mixture of the NCP map with a completely depolarizing map. We prove that the composition can always be made CP without completely depolarizing in any direction. It is possible to depolarize less in some directions. We give the general proof by using the Choi matrix and an isomorphism from a maximally entangled two qudit state to a set of qubits. We also give measures that describe the amount of disturbance the depolarization introduces to the original map. Given our measures, we show that asymmetric depolarization has many advantages over SPA in preserving the structure of the original NCP map. Finally, we give some examples. For some measures and examples, completely depolarizing (while not necessary) in some directions can give a better approximation than keeping the depolarizing parameters bounded by the required depolarization if symmetric depolarization is used.
First-order nonlinear eigenvalue problems involving functions of a general oscillatory behavior
Authors: Komijani Javad 
Published: October 2021

Abstract
Eigenvalue problems arise in many areas of physics, from solving a classical electromagnetic problem to calculating the quantum bound states of the hydrogen atom. In textbooks, eigenvalue problems are defined for linear problems, particularly linear differential equations such as time-independent Schrödinger equations. Eigenfunctions of such problems exhibit several standard features independent of the form of the underlying equations. As discussed in Bender et al (2014 J. Phys. A: Math. Theor. 47 235204), separatrices of nonlinear differential equations share some of these features. In this sense, they can be considered eigenfunctions of nonlinear differential equations, and the quantized initial conditions that give rise to the separatrices can be interpreted as eigenvalues. We introduce a first-order nonlinear eigenvalue problem involving a general class of functions and obtain the large-eigenvalue limit by reducing it to a random walk problem on a half-line. The introduced general class of functions covers many special functions such as the Bessel and Airy functions, which are themselves solutions of second-order differential equations. For instance, in a special case involving the Bessel functions of the first kind, i.e. for y′(x) = J

ν
(xy), we show that the eigenvalues asymptotically grow as 241/42
n
1/4. We also introduce and discuss nonlinear eigenvalue problems involving the reciprocal gamma and the Riemann zeta functions, which are not solutions to simple differential equations. With the reciprocal gamma function, i.e. for y′(x) = 1/Γ(−xy), we show that the nth eigenvalue grows factorially fast as

(

1
−
2
n

)

/
Γ

(

r

2
n
−
1

)

, where r

k
is the kth root of the digamma function.
Analysis of the influence of sheath positions, flight parameters and incident wave parameters on the wave propagation in plasma sheath
Authors: ZHANG Qifan , HAN Yiping , DONG Qinlu , DONG Chang 
Published: October 2021

Abstract
The plasma sheath covering hypersonic vehicles has a significant effect on the propagation of electromagnetic waves. Based on the calculation of the flow field of a conical cylindrical, this work studies the propagation of electromagnetic waves in plasma sheath at L-band and Ku-band, and discusses the propagation characteristics in the head, side and tail of the sheath. The dielectric properties of plasma sheath are related to flight speed and altitude. A flight condition corresponds to a unique distribution of dielectric properties. For the conical cylindrical, the results show that flight speed is generally negatively correlated with the transmissivity of the plasma sheath. The reflection characteristics of electromagnetic waves at the L-band and Ku-band when obliquely incident to the plasma sheath show a downward trend. When the frequency is increased to Ku-band, the propagation characteristics of electromagnetic waves in the plasma sheath are related to the position of the sheath.
Defect passivation of perovskites in high efficiency solar cells
Authors: Tan Shaun , Huang Tianyi , Yang Yang 
Published: October 2021

Abstract
Metal halide perovskite solar cells (PSCs) have enormous potential as the next-generation photovoltaic technology. Being solution-processed at relatively low temperatures, it is inevitable that crystallographic defects are formed in abundance during fabrication. Such defects may cause undesirable energy losses by non-radiative recombination to limit the performance of PSCs. More importantly, it has become apparent that defect activity is fundamentally responsible for the operational instability issues hindering the commercialization readiness of PSCs. It is therefore necessary to develop strategies to minimize defect formation and to passivate formed defects. Here, we discuss recent advances on such defect mitigation and passivation strategies. We especially emphasize on methodologies that are incorporated into state-of-the-art PSCs that have demonstrated world record efficiencies and long-term stability.
Machinability analysis in high speed turning of Ti–6Al–4V alloy and investigation of wear mechanism in AlTiN PVD coated tungsten carbide tool
Authors: Muthuswamy Padmakumar , Murugesan Vijaya Ganesa Velan 
Published: October 2021

Abstract
Titanium alloys are one of the most critical and prominently used materials in automotive, aerospace, and biomedical application due to their superior strength to weight ratio. The very property that makes it a suitable material for such applications also makes it challenging to machine. In this study, an attempt has been made to understand the machinability of Ti–6Al–4V titanium alloy at high cutting speeds in turning. A full factorial method and Analysis of Variance (ANOVA) technique were used to conduct 18 different experimental runs and determine the significance of variables that are responsible for the variation in average surface roughness (Ra) and forces. The results show that feed rate is the single most significant factor for Ra, whereas the contribution of feed and depth of cut are more for the forces, followed by cutting speed. Tool life tests were conducted with AlTiN PVD coated tools at three different cutting speeds, and SEM analysis to evaluate the wear mechanism revealed that abrasive wear, notching, and diffusion were predominant which accelerated the wear rate. Although machining studies on Ti6Al4V at low cutting speeds are well established, the novelty of the study is to perform a comprehensive analysis to evaluate the machinability and study wear mechanism using AlTiN coated tungsten carbide tool at high cutting speeds.