bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simultaneous slope design optimisation and stability assessment using a genetic algorithm and a fully automatic image‐based analysis
Authors: Wijesinghe Dakshith Ruvin , Dyson Ashley , You Greg , Khandelwal Manoj , Song Chongmin , Ooi Ean Tat 
Published: August 2022

AbstractMine slope design is a complex task that requires consideration of geotechnical analysis, structural stability, economics and the environment. Economic factors usually drive mine slope design, particularly in the case of open‐pit designs, where the process of steepening slope walls by several degrees can have profound financial implications. Due to the risks associated with catastrophic slope collapse, slope stability analysis is an integral component of open‐pit engineering projects. However, initial design concepts and geotechnical assessments are often considered separately. In this study, a technique is developed that combines the scaled boundary finite element method (SBFEM) with genetic algorithms (GAs) to simultaneously perform slope stability analysis and optimise the slope profile. The iterative design approach optimises characteristics of the slope profile such as the slope height, width, angle and number of benches while ensuring the factor of safety (FoS) remains above a threshold value. A salient feature of the technique is the ability to automatically address the modifications to the geometry of the slope by updating the digital images used in the analysis to assess the stability of each instance in the optimisation process and determine the optimum slope geometry. The results highlight the application of the developed technique to determine appropriate slope excavation designs as well as slope backfilling scenarios. The method is exemplified in several cases where complex stratigraphies and spatially variable materials are considered. As such, the GA‐driven slope design process conveys an optimised, automated tool, combining mine slope design and slope stability analysis.
Statistical quality control using image intelligence: A sparse learning approach
Authors: Kang Yicheng 
Published: August 2022

AbstractAdvances in image acquisition technology have made it convenient and economic to collect large amounts of image data. In manufacturing and service industries, images are increasingly used for quality control purposes because of their ability to quickly provide information about product geometry, surface defects, and nonconforming patterns. In production line monitoring, image data often take the form of image streams in the sense that images from the process are being collected over time. In such applications, a fundamental task is to properly analyze image data streams. This image monitoring problem is challenging for several reasons. First, images often have complicated structures such as edges and singularities, which render many traditional smoothing methods inapplicable. Second, a typical grayscale image contains tens of thousands of pixels, so the data is high‐dimensional. It has been shown in the statistical process control (SPC) literature that conventional multivariate control charts have limited power of detecting process shifts when the data dimension is high. In this article, we propose to transform images using a two‐dimensional wavelet basis and monitor the wavelet coefficients by sparse learning‐based multivariate control charts. By adapting the sparse learning algorithm to our quality control problem, the proposed method is able to detect shifts in the wavelet coefficients in a timely fashion and simultaneously identify those shifted coefficients. Combining this feature with the localization property of the wavelet basis, our method also enables accurate diagnosis of faulty image regions. In addition, the proposed charting statistics have explicit formulas, so they are easy to compute. Theoretical justifications and numerical comparisons with an existing method show that our method works well in applications.
A 0–1 mixed‐integer program‐based group‐and‐release strategy for solving the integrated runway scheduling and taxiway routing problem
Authors: Desai Jitamitra , Srivathsan Sandeep , Yu Chuhang , Zhang Dong 
Published: August 2022

AbstractWith growing air traffic demand and the required airport infrastructure lagging behind by at least a decade, it has become imperative for air traffic controllers to efficiently squeeze the available capacity at an airport in order to minimize aircraft delays. It has been well documented that the two major bottlenecks affecting the smooth functioning of air traffic operations at an airport are runways and taxiways. The key problem involving these resources includes the scheduling of flights on the runway, and the determination of the taxiway paths to be traversed by flights from their assigned gates to the runway. We address this problem by modeling an integrated runway scheduling and taxiway routing problem as a 0–1 mixed‐integer program (MIP) in a free‐path setting where any feasible taxiway route can potentially be assigned to a flight. As a direct application of this MIP model is not suitable for solving large‐scale instances, we develop a three‐step group‐and‐release strategy that first segregates the flights based on their allocated gates and associated ramps, and then solves the MIP model for each ramp to determine the taxiway path for each flight. In the final step, the path for each flight is fixed, and a sequencing problem over all flights is solved to determine high quality, feasible solutions. The performance of the proposed methodology is benchmarked against three algorithms, namely: (i) constraint‐generation; (ii) sequential two‐stage algorithm; and (iii) FCFS algorithm. Our numerical experiments, based on actual flight data from Changi airport (Singapore), show that, on average, the optimality gap as well as the computational time is considerably reduced for our strategy as compared to existing methods, thereby highlighting the efficacy of the proposed approach in solving realistic instances.
3D printing of glass fiber reinforced acrylonitrile butadiene styrene and investigation of tensile, flexural, warpage and roughness properties
Authors: Amiri Aria , Zolfaghari Abbas , Shakeri Mohsen 
Published: August 2022

AbstractThree‐dimensional (3D) printing or additive manufacturing (AM) enables to fabricate, complex parts in low quantities without expensive molds or tools in short time. While several 3D printing methods are available, printing with the method of fused deposition modeling (FDM) is particularly widespread because of the simplicity and potential applicability. The applications of FDM to obtain strong components used in aerospace and automotive industries are widely being explored. This study investigates mechanical properties of 3D printed parts with composite filaments made by acrylonitrile butadiene styrene (ABS)/short glass fibers (SGFs). At first, composite filaments with varying GF contents 5, 10, and 15 wt% were manufactured. In addition, maleic anhydride grafted ABS (ABS‐g‐MA) as coupling agent, nozzle temperature and raster angle orientation were considered as other parameters. Results showed that with 15 wt% of GF, means of tensile and flexural strengths were increased 33% and 36%, respectively. Meanwhile, tensile and flexural moduli were improved 57% and 62%. Among the different raster angle, 0° had the best mechanical properties. Maximum ultimate tensile strength was obtained 61 MPa. Warpage and surface roughness were measured in this study. Generally, nozzle temperature and coupling agent did not have any significant effects on all the results in this study.
Separation of memory span and learning rate: Evidence from behavior and spontaneous brain activity in older adults
Authors: Chen Shuyuan , Li Rui , Wang Pengyun , Li Juan 
Published: August 2022

AbstractIt is unclear how the ability to initially acquire information in a first learning trial relates to learning rate in subsequent repeated trials. The separation of memory span and learning rate is an important psychological dilemma that remains unaddressed. Given the potential effects of aging on memory and learning, this study investigated the separation of memory span and learning rate from behavior and spontaneous brain activity in older adults. We enrolled a total of 758 participants, including 707 healthy older adults and 51 mild cognitive impairment (MCI) patients. Sixty‐five participants out of 707 completed resting‐state functional magnetic resonance imaging (fMRI) scanning. Behaviorally, memory span and learning rate were not correlated with each other in the paired‐associative learning test (PALT) but were negatively correlated in the auditory verbal learning test (AVLT). This indicated that the relationship between memory span and learning rate for item memory might be differentially affected by aging. Interaction analysis confirmed that these two capacities were differentially affected by test type (associative memory vs. item memory). Additionally, at three progressive brain activity indexes (ALFF, ReHo, and DC), the right brain regions (right inferior temporal gyrus and right middle frontal gyrus) were more negatively correlated with memory span, whereas, the left precuneus was more positively correlated with learning rate. Regarding pathological aging, none of the correlations between memory span and learning rate were significant in either PALT or AVLT in MCI. This study provides novel evidence for the dissociation of memory span and learning rate at behavioral and brain activity levels, which may have useful applications in detecting cognitive deficits or conducting cognitive interventions.
The effect of immersive virtual reality‐based attentional bias modification on anxiety mitigation in healthy population
Authors: Wang Yamin , Zhang Xiaoxiang , Gao Jidong , Zhang Leran , Jiang Jinhang 
Published: August 2022

AbstractThe present study compared an immersive virtual reality‐based attentional bias modification (immersive VR‐ABM) with the desktop version of the VR‐ABM and an immersive virtual reality‐based game (immersive VR‐game) to examine the possible effect of the immersive presence on self‐reported emotional reactions to a stressful task. One hundred and twenty participants were randomly assigned into three groups, and each group received a three‐turn induction–intervention training. Anxiety symptoms were assessed at pre‐induction, post‐induction, and post‐training. Results showed that virtual reality‐based anxiety was induced and alleviated successfully in all three groups, but only the immersive VR‐ABM group showed an accumulated effect on self‐reported anxiety across sessions. The attentional bias based on probe latencies indicated no significant change in either the immersive or desktop VR‐ABM groups. The present findings support the hypothesized VR‐ABM's effect on self‐reported anxiety at the immersive presence. The practical implications of using immersive VR‐ABM are discussed for obtaining ecological validity.
Development of multiple reaction monitoring (MRM) assays to identify Brucella abortus proteins in the serum of humans and livestock
Authors: Husain Aliabbas A. , Pinto Sneha M. , Subbannayya Yashwanth , Kapoor Saketh , Khulkhule Payal , Bhartiya Nidhi , Prasad T. S. Keshava , Daginawala Hatim F. , Singh Lokendra R. , Kashyap Rajpal Singh 
Published: August 2022

AbstractIn the present study, a targeted multiple reaction monitoring‐mass spectrometry (MRM‐MS) approach was developed to screen and identify protein biomarkers for brucellosis in humans and livestock. The selection of proteotypic peptides was carried out by generating in silico tryptic peptides of the Brucella proteome. Using bioinformatics analysis, 30 synthetic peptides corresponding to 10 immunodominant Brucella abortus proteins were generated. MRM‐MS assays for the accurate detection of these peptides were optimized using 117 serum samples of human and livestock stratified as clinically confirmed (45), suspected (62), and control (10). Using high throughput MRM assays, transitions for four peptides were identified in several clinically confirmed and suspected human and livestock serum samples. Of these, peptide NAIYDVVTR corresponding to B. abortus proteins: BruAb2_0537 was consistently detected in the clinically confirmed serum samples of both humans and livestock with 100% specificity. To conclude, a high throughput MRM‐MS‐based protocol for detecting endogenous B. abortus peptides in serum samples of humans and livestock was developed. The developed protocol will help design sensitive assays to accurately diagnose brucellosis in humans and livestock. The data associated with this study are deposited in Panorama Public (https://panoramaweb.org/rNOZCy.url with ProteomeXchange ID: PXD034407).
Plastic structures for diverse substrates: A revisit of human ABC transporters
Authors: Hou Wen‐Tao , Xu Da , Wang Liang , Chen Yu , Chen Zhi‐Peng , Zhou Cong‐Zhao , Chen Yuxing 
Published: August 2022

AbstractATP‐binding cassette (ABC) superfamily is one of the largest groups of primary active transporters that could be found in all kingdoms of life from bacteria to humans. In humans, ABC transporters can selectively transport a wide spectrum of substrates across membranes, thus playing a pivotal role in multiple physiological processes. In addition, due to the ability of exporting clinic therapeutics, some ABC transporters were originally termed multidrug resistance proteins. Increasing investigations of human ABC transporters in recent years have provided abundant information for elucidating their structural features, based on the structures at distinct states in a transport cycle. This review focuses on the recent progress in human ABC structural analyses, substrate binding specificities, and translocation mechanisms. We dedicate to summarize the common features of human ABC transporters in different subfamilies, and to discuss the possibility to apply the fast‐developing techniques, such as cryogenic electron microscopy, and artificial intelligence‐assisted structure prediction, for future studies.
Thermodynamically consistent versions of approximations used in modelling moist air
Authors: Eldred Christopher , Taylor Mark , Guba Oksana 
Published: August 2022

AbstractSome existing approaches to modelling the thermodynamics of moist air make approximations that breakthermodynamic consistency, such that the resulting thermodynamics does not obey the first and second laws or has other inconsistencies. Recently, an approach to avoid such inconsistency has been suggested: the use ofthermodynamic potentialsin terms of theirnatural variables, from which all thermodynamic quantities and relationships (equations of state) are derived. In this article, we develop this approach forunapproximatedmoist‐air thermodynamics and two widely used approximations: the constant‐ approximation and the dry heat capacities approximation. The (consistent) constant‐ approximation is particularly attractive because it leads to, with the appropriate choice of thermodynamic variable, adiabatic dynamics that depend only on total mass and are independent of the breakdown between water forms. Additionally, a wide variety of material from different sources in the literature on thermodynamics in atmospheric modelling is brought together. It is hoped that this article provides a comprehensive reference for the use of thermodynamic potentials in atmospheric modelling, especially for the three systems considered here.
Free‐Space Quantum Key Distribution with Single Photons from Defects in Hexagonal Boron Nitride
Authors: Samaner Çağlar , Paçal Serkan , Mutlu Görkem , Uyanık Kıvanç , Ateş Serkan 
Published: August 2022

AbstractEfficient single photon generation is an important requirement for several practical applications in quantum technologies, including quantum cryptography. A proof‐of‐concept demonstration of free‐space quantum key distribution (QKD) is presented with single photons generated from an isolated defect in hexagonal boron nitride (hBN). The bright source operating at room temperature is integrated into a QKD system based on B92 protocol and a sifted key rate of 238 bps with a quantum bit error rate of 8.95% are achieved at 1 MHz clock rate. The effect of temporal filtering of detected photons on the performance of QKD parameters is also studied. It is believed that these results will stimulate the research on optically active defects in hBN as well as other 2D‐based quantum emitters and their applications within quantum information technologies including practical QKD systems.
Guidewire simulation of endovascular intervention: A systematic review
Authors: Qiu Jianpeng , Ming Jianzhong , Qian Cheng , Chen Yang , Gao Dazhi , Zhou Shoujun , zhao Gang , Tang Shujun , Xing Liudong 
Published: August 2022

AbstractBackgroundEndovascular intervention is an important minimally invasive surgery that requires professional skills to operate surgical instruments. Such skills are mainly gained through the traditional training paradigm of “see one, do one, teach one”, rather than the guidewire simulation system.MethodsTo identify limitations of existing guidewire simulation research and suggest further research orientations, a comprehensive search on literature published from 2007 to 2021 is performed in 11 selected electronic databases. Through our scrutiny and filtration, 34 articles are selected as major studies for careful examinations.ResultsWe identify challenges faced in the field of endovascular intervention guidewire simulation. We examine and classify guidewire simulation techniques (including guidewire models, collision detection methods and collision response methods), accuracy evaluation methods, error sources, and performance optimization methods.ConclusionsGuidewire simulation can satisfy the urgent need to train surgeons, thus more efforts should be dedicated enabling its wide application in clinical environment.
Radially varying delay‐compensated distributed control of reaction‐diffusion PDEs on n‐ball under revolution symmetry conditions
Authors: Guan Dandan , Qi Jie 
Published: August 2022

AbstractIn this article, a distributed control design is developed via partial differential equation (PDE) backstepping for a class of reaction‐diffusion PDEs on ‐ball under revolution symmetry conditions in the presence of radial spatially varying actuator delay. The actuator delay is modeled by a two‐dimensional (2D) first‐order hyperbolic PDE with spatially varying boundary, resulting in a cascaded transport‐diffusion PDE system. Two‐step backstepping transformation is introduced for the control design. First, a new Volterra transformation for the ‐ball under revolution symmetry is proposed that allows the kernel function to be solvable. Different from the kernel in the 1D domain, which is expressed by the classical Fourier series, the kernel of the ‐ball under revolution symmetry conditions is based on the Fourier–Bessel series. The resulting Volterra transformation is an implicit one that contains the state of the target system on both sides of the definition. Based on the implicit transformation, we employ the successive approximations approach to derive the second‐step transformation, namely, an explicit transformation, and arrive at a stable target system. The inverse transformation is also derived, to prove exponential stability of the closed‐loop system. The stability analysis requires more technical skills that are not needed in solving the spatially varying delay compensation problem when the domain is 1D. Numerical simulation examples of 3D and 4D revolution‐symmetrical systems illustrate the effectiveness of the controller.
LQ‐optimal 2‐rate control of a class of single‐input single‐output discrete‐time plants
Authors: Bhattacharya Sragdhara , Ghosh Arun , Das Sarit K. 
Published: August 2022

AbstractUse of 2‐rate controllers for robust control via zero‐placement is a topic of interest in current literature. This paper proposes a 2‐degree‐of‐freedom, 2‐rate, dynamic, output feedback controller to compensate single‐input single‐output (SISO), unstable, non‐minimum phase (NMP), discrete, linear time‐invariant (LTI) plants of relative degree unity; and achieves exactly the same loop and input‐output properties as can be achieved by a linear quadratic regulator (LQR) for the equivalent lifted LTI plant using state feedback. Such LQR‐like loop and input‐output properties, it may be noted, cannot be attained by LTI or even the existing 2‐rate output feedback controllers for plants with NMP zeros. Examples presented illustrate the efficacy of the proposed controller with respect to the existing ones.
Design of a joint adaptive high‐gain observer for a class of nonlinear sampled‐output system with unknown states and parameters
Authors: Zhuang Xincheng , Wang Haoping , Ahmed‐Ali Sofiane , Tian Yang 
Published: August 2022

AbstractIn this article, a joint adaptive high‐gain observer design method is proposed for a class of nonlinear systems subject to sampled output data measurements. The considered class of system is characterized by a nonlinear term coupled with an unknown parameter that enters the system in both the outputs and the states equations. The fact that the considered system involves an output sampling process and an unknown parameter renders the design of the nonlinear adaptive observer more difficult. To overcome this difficulty, a novel closed‐loop output predictor is proposed. Based on the well‐known decoupling method between the state and unknown parameters, a joint adaptive high‐gain observer which can simultaneously guarantee the exponential convergence of the estimation of the unknown state and the unknown parameter is proposed in this article. The structure of the designed observer has been extended to the case of sampled and delayed data measurements. The effectiveness of our proposed observer is demonstrated through numerical simulations and performance comparison with another observer structure proposed in the literature.
Perceptions of the impacts of invasive alien plants in the riparian zone of the Ganga River: Insights from Varanasi, India
Authors: Singh Rinku , Tiwari Amit Kumar , Singh Gopal Shankar 
Published: August 2022

AbstractRiparian zones are among the most threatened habitats due to invasive species. Traditionally, studies on invasive alien plants (IAPs) of riparian zones have focused on their ecological implications. Studies assessing the impacts of IAPs on ecosystem services (ES) and ecosystem disservices (EDS) through people's perceptions are lacking in this habitat. This study was conducted in the riparian zone of the Ganga River in Varanasi, India. We used a questionnaire‐based survey to assess people's perceptions of IAPs and their potential to provide ES and EDS. Results indicated that residents were aware of IAPs and perceived these both positively (providing ES) and negatively (providing EDS). Soil stabilization and loss of native plant diversity were the most commonly perceived ES and EDS respectively. Socio‐demographic variables such as age and education shape people's perceptions of IAPs. Younger and educated respondents were more likely to perceive IAPs negatively. Respondents most commonly used fire as a practice to manage IAPs. They placedParthenium hysterophorusL. as the highest priority based on its impacts and management needs. This study highlights the need to incorporate public perceptions into the policy, planning, and management of IAPs, particularly in the riparian zone.