Miracle-dz/UniFAR-FTUs huggingface dataset:
Product Line Optimization for Car-Sharing Platforms in the Sustainable Transportation

As the sharing economy develops in sustainable transportation, car-sharing platforms improve the allocation efficiency of idle cars to customers. However, as the travel demand increases, and the vehicle type becomes various, the sharing market faces a new challenge to satisfy the customers’ diverse needs for quality-differentiated cars. Each customer would like to choose the right car type, while the manufacturing firm and the e-commerce platform should set the right car price for profit maximization. How to match the platform’s product line with the customer’s choice behavior becomes a problem for all the stakeholders in the sharing economy. From the perspective of customer heterogeneity, we establish a game-theoretic framework to study product line optimization in business-to-consumer (B2C) and consumer-to-consumer (C2C) sharing. We solve the optimal quality decision and the optimal pricing strategy for the manufacturing firm and the e-commerce platform in the sharing economy. In numerical experiments, we investigate how the sensitivity of the quality and the cost can jointly influence the profits of sustainable transportation. Our findings show that within the product line, the firm’s selling profit in the C2C sharing is negatively influenced by the sharer’s valuation, while the platform’s sharing profit in the B2C sharing is independent of either buyer’s valuation. We give some policy implications for scholars, practitioners, and policymakers in the sharing economy and point out some limitations and recommendations for the product line design.
Discrete‐time survival trees

Tree‐based methods are frequently used in studies with censored survival time. Their structure and ease of interpretability make them useful to identify prognostic factors and to predict conditional survival probabilities given an individual's covariates. The existing methods are tailor‐made to deal with a survival time variable that is measured continuously. However, survival variables measured on a discrete scale are often encountered in practice. The authors propose a new tree construction method specifically adapted to such discrete‐time survival variables. The splitting procedure can be seen as an extension, to the case of right‐censored data, of the entropy criterion for a categorical outcome. The selection of the final tree is made through a pruning algorithm combined with a bootstrap correction. The authors also present a simple way of potentially improving the predictive performance of a single tree through bagging. A simulation study shows that single trees and bagged‐trees perform well compared to a parametric model. A real data example investigating the usefulness of personality dimensions in predicting early onset of cigarette smoking is presented. The Canadian Journal of Statistics 37: 17‐32; 2009 © 2009 Statistical Society of Canada
Heterogeneous Multi-Behavior Recommendation Based on Graph Convolutional Networks

Traditional recommendation systems usually use single user-item interaction information, which ignore the multiple relationships that exist for other interactions (e.g., likes, clicks). Multi-behavioral recommendation models compensate for the shortcomings of traditional models. The existing multi-behavior recommendation models focus on obtaining behavioral information by distinguishing the interaction differences of multiple user behaviors but ignore the common preferences of items related to user different interactions. In this paper, we propose a Multi-Behavior Heterogeneous Contrastive learning Recommendation (MBHCR) model. Specifically, MBHCR stresses the information fusion between different interaction behaviors and differences in the behavior view. Firstly, we design a unified heterogeneous graph based on the complexity of user multi-behavioral interaction information to distinguish behavioral differences while preserving their complete semantic information. Secondly, we propose a multi-behavior relational aggregator component to model the unified heterogeneous graph only once to capture the potential common representations of users and their different interactions and to mitigate user sparsity. Thirdly, we also design a behavior comparison learning enhancer to complement the interaction differences between the user’s target behavior and auxiliary behaviors on the behavior view and extract valid information. Experiments were conducted on two real-world datasets to demonstrate the validity of MBHCR and designed ablation experiments to verify the contribution of model components.
DERIVATION OF A SCALING LAW IN CLUSTER-CLUSTER AGGREGATIONS FROM A MODIFIED SMOLUCHOWSKI'S COAGULATION EQUATION

We derived a scaling relation in cluster-cluster aggregations from a modified Smoluchowski's coagulation equation and obtained the relation between the scaling exponents and the control parameter. The power laws in cluster-cluster aggregations derived from the scaling relations agreed with those of ferromagnetic colloidal particles obtained by a numerical calculation.
A Chebyshev collocation method for the Navier–Stokes equations with application to double‐diffusive convection

Presentation de la methode de collocation de Tchebyshev pour resoudre les equations bidimensionnelles de Navier-Stokes en variables vorticite-fonction de courant. La discretisation en temps est obtenue a travers une classe de schemas de differences finies semi-implicites
Generalized characteristic interface conditions for high-order multi-block computation

In practical fluid computation with structured grids around complex geometries, singular points with metric discontinuity can frequently be found. Generally, the grid singularities may cause numerical oscillations when some high-order finite difference scheme is applied. Recently, an excellent theory has been proposed which solves the above singular problem by block decomposition along the singular surface and by imposition of the characteristic interface conditions (CIC) on the block interface. However, the original theory has constraints on the mathematical treatment of the block interface, and therefore prevents numerical flexibility from a practical point of view. In this article, in order to extend the functions of the original CIC, we propose the generalized characteristic interface conditions (GCIC). Proper numerical test analysis is conducted to validate the performance of the GCIC, and as a practical application, multi-block computation is performed with the GCIC applied to complex geometry.
Relativistic nonlinear plasma waves in a magnetic field

We study five relativistic plane nonlinear waves: circularly polarized waves and electrostatic plasma oscillations propagating parallel to the magnetic field, relativistic Alfvén waves, linearly polarized transverse waves propagating in zero magnetic field, and finally the relativistic analogue of the extraordinary mode propagating at an arbitrary angle to the magnetic field. When the ions are driven relativistic, they behave like electrons, and the assumption of an ‘electron–positron’ plasma guides us to equations which have the form of a one dimensional potential well. Our solutions indicate that a large-amplitude super luminous wave determines the average plasma properties, and not vice versa. For example, linearly polarized waves impose a plasma number flux equal to the relativistic addition of Nc/β and NVE, where N is the density, c the speed of light, β (>1) the ratio of the phase speed to c and VE the E × B speed measured in the frame moving with speed c/β with respect to the frame in which the phase speed is measured. The implications for cosmic ray acceleration in pulsar magnetospheres are considered.
Approximate optical gain formulas for 1.55-/spl mu/m strained quaternary quantum-well lasers

We have used an efficient analytical model to calculate the optical gain of the strained quantum-well laser of InGaAsP-InP material system. Based on the anisotropic effective mass theory, empirical formulas delineating the relations between optical gain, emission wavelength, well width and material compositions are obtained for 1.55-/spl mu/m In/sub 1-x/Ga/sub x/As/sub y/P/sub 1-y/ quaternary strained quantum-well lasers. Results show a logarithmic relation between the peak optical gain and carrier concentration for all possible material compositions of the quaternary system. We show that the logarithmic relation can be derived algebraically. >
Vision assisted aircraft lateral navigation

Surface operation is currently one of the least technologically equipped phases of aircraft operation. The increased air traffic congestion necessitates more aircraft operations in degraded weather and at night. The traditional surface procedures worked well in most cases as airport surfaces have not been congested and airport layouts were less complex. Despite the best efforts of FAA and other safety agencies, runway incursions continue to occur frequently due to incorrect surface operation. Several studies conducted by FAA suggest that pilot induced error contributes significantly to runway incursions. Further, the report attributes pilot’s lack of situational awareness - local (e.g., minimizing lateral deviation), global (e.g., traffic in the vicinity) and route (e.g., distance to next turn) - to the problem. An Enhanced Vision System (EVS) is one concept that is being considered to resolve these issues. These systems use on-board sensors to provide situational awareness under poor visibility conditions. In this paper, we propose the use of an Image processing based system to estimate the aircraft position and orientation relative to taxiway markings to use as lateral guidance aid. We estimate aircraft yaw angle and lateral offset from slope of the taxiway centerline and horizontal position of vanishing line. Unlike automotive applications, several cues such as aircraft maneuvers along assigned route with minimal deviations, clear ground markings, even taxiway surface, limited aircraft speed are available and enable us to implement significant algorithm optimizations. We present experimental results to show high precision navigation accuracy with sensitivity analysis with respect to camera mount, optics, and image processing error.
Zero Gravity Problems in Space Powerplants: A Status Survey

A review is given of various hydromechanical and heat transfer systems that are adversely affected by zerogravity operation. Methods for experimentally producing zero gravity, including drop tests, aircraft parabolic trajectories, and rockets and satellites, are described and compared. In space power systems, the absence of gravity influences the hydrostatic, hydrodynamic, and lubrication characteristics of components, as well as the convection, boiling, and condensation behavior of heat transfer systems. The design of components to overcome zero-g adversities is discussed. (T.F.H.)
Will Social Distancing in Service Encounters Affect Consumers’ Value Perception During the COVID-19 Pandemic? The Role of Servicescape, Self-Efficacy, and Technological Intervention

This study investigates how physical and psychological distance from one's surroundings may influence one's perception of connectedness with the servicescape and, ultimately, perception of value. It also examines the effect of consumers’ techno-psychological differences and interaction modes on this distance–closeness relationship. The researchers develop and test a conceptual framework of how personal cognitive traits and technological intervention may alter consumers’ perceived connectedness to the servicescape and influence their perceived value in different service settings. Via a quasi-experiment design in three service scenarios, this research shows a synthetical effect of contactless technology in the distancing setting that may work more effectively on high self-efficiency customers to change their perceived closeness to the servicescape and further change their evaluation of the service. The findings reveal the practical implications of social distancing for different types of consumers in service encounters during or after the COVID-19 pandemic.
kNNDD-based One-Class Classification by Nonparametric Density Estimation

, 2001). 분류와 예측은 종속변수에 대한 미래의 값을 예측한다는 점에서 공통된 목적을 가지고 있으나 종속변수가 범주형이면 분류, 연속형이면 예측으로 나눌 수 있다. 군집은 종속변수 없이 독립변수만의 특성을 이용해 비슷한 관측치끼리 그룹화 하는 방법을 말한다. 본 논문에서 다루고자하는 데이터마이닝 기법은 단일 클래스 분류(One-class classification) 기법으로 이는 기존 지도형 분류(Supervised classification) 기법과는 차이가 있다. 지도형 분류기법은 범주형인 종속변수와 이를 설명하는 독립변수들과의 관계를 통해 분류모델을 구축하고 미래 관측치의 독립변수 값이 주어졌을 때 알려지지 않은 해당 종속변수의 값을 예측한다(Khan and Madden, 2010). 반면 단일 클래스 분류 기법은 범주형 종속변수의 미래의 값을 예측한다는 점에서는 기존 지도형 분류 기법과 동일하나 분류모델 생성 시 종속변수를 사용하지 않는다는 점에서 차이가 있다. 최근 단일 클래스 분류기법이 활발히 연구되고 있으며 그 응용분야로 정보검색, 얼굴 인식, 생물정보학, 저자판별 분류, 문서 분류, 제조업체 모니터링 등 다양하게 존재하고 있다(Manevitz and Yousef, 2001; Sanchez-Yanez, 2003; Koppel and Schler, 2004; Kim
Model Search among Multiplicative Models

We propose a non-iterative model search technique to find simple patterns of association for several variables. Our selection procedure is restricted to multiplicative models, therefore all patterns under consideration are interpretable in terms of zero partial associations of variable pairs. Wie illustrate the selection technique on two sets of data, one in a contingency table, one in a covariance matrix.
Double Telegraph Processes and Complete Market Models

The traditional jump-telegraph processes are based on a Poisson process with alternating intensities. We develop a new model based on an alternating doubly stochastic Poisson process with random intensities of jumps. Moreover, in this model the jump-telegraph process performs additional jumps each time when the intensity changes at random. Martingale measures for this type of processes are described by using Girsanov’s transformation. The market model based on the doubly stochastic jump-telegraph process is studied. A class of complete models is also considered.
Packet-Level Throughput Analysis and Energy Efficiency Optimization for UAV-Assisted IAB Heterogeneous Cellular Networks

In this paper, we investigate the packet-level throughput and energy efficiency of millimeter-wave unmanned aerial vehicle (UAV)-assisted integrated access and backhaul (IAB) heterogeneous cellular networks with spatiotemporal traffic. Specifically, we develop a theoretical framework to analyze the mean packet throughput and energy efficiency of the network based on stochastic geometry and queueing theory, whereby the spatial randomness of network deployment and the temporal randomness of network traffic can be appropriately characterized. Different from the traditional network performance metrics emphasizing transmission and resource consumption, the packet-level performance helps to better understand the impact of not only packet transmission but also packet waiting time in a multihop network. Simulation results demonstrate that the assistance of IAB-based UAVs can efficiently relieve the load of terrestrial macro- and small-cell networks, and the appropriate network deployment parameters play pivotal roles in improving both the packet-level throughput and energy efficiency performance. By jointly optimizing the key network parameters, the packet energy efficiency can be significantly improved while ensuring the required mean packet throughput of the network.
Tracking pulsar dispersion measures using the Giant Metrewave Radio Telescope

In this paper, we describe a novel experiment for the accurate estimation of pulsar dispersion measures (DMs) using the Giant Metrewave Radio Telescope. This experiment was carried out for a sample of 12 pulsars, over a period of more than one year (2001 January to 2002 May) with observations about once every fortnight. At each epoch, the pulsar DMs were obtained from simultaneous dual-frequency observations, without requiring any absolute timing information. The DM estimates were obtained from both the single-pulse data streams and from the average profiles. The accuracy of the DM estimates at each epoch is ∼1 part in 104 or better, making the data set useful for many different kinds of studies. The time-series of DMs shows significant variations on time-scales of weeks to months for most of the pulsars. An analysis of the mean DM values from these data shows significant deviations from catalogue values (as well as from other estimates in the literature) for some of the pulsars, with PSR B1642−03 showing the most notable differences. From our analysis results it appears that the constancy of pulsar DMs (at the level of 1 in 103 or better) cannot be taken for granted. For PSR B2217+47, we see evidence of a large-scale DM gradient over a 1-yr period, which is modelled as being due to a blob of enhanced electron density sampled by the line of sight. For some pulsars, including pulsars with fairly simple profiles such as PSR B1642−03, we find evidence for small changes in DM values for different frequency pairs of measurement, a result that needs to be investigated in detail. Another interesting result is that we find significant differences in DM values obtained from average profiles and single-pulse data.
MULTIDIMENSIONAL CHEMICAL MODELING OF YOUNG STELLAR OBJECTS. III. THE INFLUENCE OF GEOMETRY ON THE ABUNDANCE AND EXCITATION OF DIATOMIC HYDRIDES

The Herschel Space Observatory enables observations in the far-infrared at high spectral and spatial resolution. A particular class of molecules will be directly observable: light diatomic hydrides and their ions (CH, OH, SH, NH, CH+, OH+, SH+, NH+). These simple constituents are important both for the chemical evolution of the region and as tracers of high-energy radiation. If outflows of a forming star erode cavities in the envelope, protostellar far-UV (FUV; 6 < Eγ < 13.6 eV) radiation may escape through such low-density regions. Depending on the shape of the cavity, the FUV radiation then irradiates the quiescent envelope in the walls along the outflow. The chemical composition in these outflow walls is altered by photoreactions and heating via FUV photons in a manner similar to photo-dominated regions. In this work, we study the effect of cavity shapes, outflow density, and of a disk with the two-dimensional chemical model of a high-mass young stellar object introduced in the second paper in this series. The model has been extended with a self-consistent calculation of the dust temperature and a multi-zone escape probability method for the calculation of the molecular excitation and the prediction of line fluxes. We find that the shape of the cavity is particularly important in the innermost part of the envelope, where the dust temperatures are high enough (≳100 K) for water ice to evaporate. If the cavity shape allows FUV radiation to penetrate this hot-core region, the abundance of FUV-destroyed species (e.g., water) is decreased. On larger scales, the shape of the cavity is less important for the chemistry in the outflow wall. In particular, diatomic hydrides and their ions CH+, OH+, and NH+ are enhanced by many orders of magnitude in the outflow walls due to the combination of high gas temperatures and rapid photodissociation of more saturated species. The enhancement of these diatomic hydrides is sufficient for a detection using the HIFI and PACS instruments on board Herschel. The effect of X-ray ionization on the chemistry is found to be small, due to the much larger luminosity in FUV bands compared to X-rays.
Increasing the discrimination power of data envelopment analysis

In data envelopment analysis (DEA), to discriminate between efficient units, several ranking methods have been proposed by different authors from various points of views. However, despite of the fact that each technique has some advantages and disadvantages, all of them will face the relatively high computational complexity level. Moreover, different ranking procedures yield to different results. Although there are many ranking approaches in DEA literature, there is a need to provide a complete ranking on efficient units with a lower complexity. The current paper proposes a complete ranking method for fully ranking of all DMUs. Furthermore, this approach makes use of a common set of weights for all DMUs. In the proposed ranking approach, the infeasibility and instability problems of the existing methods have been removed. Moreover, the computational effort of the approach is relatively low in comparison to the existing methods. Sample and real cases will be presented for more illustration.
A Finite-Deformation Shell Theory for Carbon Nanotubes Based on the Interatomic Potential—Part II: Instability Analysis

Based on the finite-deformation shell theory for carbon nanotubes established from the interatomic potential in Part I of this paper, we have studied the instability of carbon nanotubes subjected to different loadings (tension, compression, internal and external pressures, and torsion). Similar to the conventional shells, carbon nanotubes may undergo bifurcation under compression/torsion/external pressure. Our analysis, however, shows that carbon nanotubes may also undergo bifurcation in tension and internal pressure, though the bifurcation modes for tension and compression are very different, and so are the modes for the internal and external pressures. The critical load for instability and bifurcation depends on the interatomic potential used.
Equations of motion for a two-axes gimbal system

Equations of motion for the two-axes yaw-pitch gimbal configuration are discussed on the assumption that the gimbals are rigid bodies and have no mass unbalance. The equations are derived and different terms are brought together into separate groups for the sake of clarity and to facilitate certain interpretations. Different kinds of disturbances and their elimination or reduction are discussed, as is the yaw gain dependence on the pitch angle. Inertia cross couplings are also given. The purpose is twofold: to simplify the picture of the two-axes gimbals and to further illustrate the properties of this configuration.
Optimal trajectory design of a deorbiting electrodynamic tether system

This paper studies the optimal control problem of a nano-satellite deorbiting by a short electrodynamic tether. The optimal control theory is introduced by forming the control problem as a cost index minimisation subjected to several constraints. A direct method based on Hermite-Simpson discretisation is adopted to solve the constraint cost minimisation problem, resulting in an optimal trajectory including the time history of the states and control input, which achieves best deorbiting efficiency and libration stability simultaneously under the given mission requirements. In order to reduce the computation efforts, the continuous deorbiting process of an electrodynamic tether is discretised into a sequential time intervals, where during each interval the slowly varying orbital parameters of the electrodynamic tether are assumed constant. Thus, the whole optimal trajectory is obtained by combining the solutions to the optimal control problems in the intervals. Numerical simulations are performed to test the performance of the optimal trajectory by applying the control input profile to an electrodynamic tether under complex environment perturbations.