Search

Virtual reality, as an excellent supportive instructional technology, has gained increasing attention from educators and professionals, where desktop-based virtual reality (DVR) is broadly adopted due to its affordability and accessibility. However, when evaluating students' learning experiences such as flow experiences in DVR environments, most studies adopt a single construct (the total score of flow experience) rather than multiple constructs (enjoyment, engagement, concentration, presence and time distortion). This study implemented desktop-based virtual reality for a STEM bridge designing program with a total of 254 undergraduates to investigate the relationship between self-regulation skills, five dimensions of flow experience, learning satisfaction and continuous intention when engaging in a DVR learning environment. The results revealed that self-regulated learning exerted a dominant impact on students' learning attitudes in DVR learning, in which students' flow experience had a significant mediating effect. Notably, although DVR exhibited poor time distortion, higher satisfaction and continuous intention were still predicted by the mentality of flow experience (ie, enjoyment, engagement, concentration and presence). The findings of this study contribute to the consideration of learning experiences and attitudes, which has insights for the future design of desktop-based virtual reality environments and related instructional activities.

Designing reflective activities for online video learning could enhance learning outcomes and, to some extent, influence learning processes (ie, attentional processes and emotional experiences). It is necessary to select different levels of reflective activities in online video learning according to learning processes and outcomes. This study examined to what extent different levels of reflection may affect the learning outcomes, and further explored the impact of reflection on learning processes. Participants, comprising 60 undergraduates, were randomly and equally assigned to two different groups: a reflection group and a critical reflection group, and each group member completed specific learning tasks. The results of the learning outcomes showed that critical reflection led to better transfer performance than reflection, but retention performance was the same in both conditions. Regarding process measures, eye-tracking data indicated that the embedding of critical reflection strategies facilitated learners' visual attention, and controlled the difficulty of processing. Meanwhile, physiological data showed that the learners' reflection was accompanied by stress, and there was no significant difference between the two levels of reflection.

We study the many-body dynamics of weakly interacting Bose gases with two-particle losses. We show that both the two-body interactions and losses in atomic gases may be tuned by controlling the inelastic scattering process between atoms by an optical Feshbach resonance. Interestingly, the low-energy behavior of the scattering amplitude is governed by a single parameter, i.e. the complex $s$-wave scattering length $a_c$. The many-body dynamics are thus described by a Lindblad master equation with complex scattering length. We solve this equation by applying the Bogoliubov approximation in analogy to the closed systems. Various peculiar dynamical properties are discovered, some of them may be regarded as the dissipative counterparts of the celebrated results in closed Bose gases. For example, we show that the next-order correction to the mean-field particle decay rate is to the order of $|n a_c^{3}|^{1/2}$, which is an analogy of the Lee-Huang-Yang correction of Bose gases. It is also found that there exists a dynamical symmetry of symplectic group Sp$(4,\mathbb{C})$ in the quadratic Bogoliubov master equation, which is an analogy of the SU(1,1) dynamical symmetry of the corresponding closed system. We further confirmed the validity of the Bogoliubov approximation by comparing its results with a full numerical calculation in a double-well toy model. Generalizations of other alternative approaches such as the dissipative version of the Gross-Pitaevskii equation and hydrodynamic theory are also discussed in the last.

The Bohai oilfield is characterized by severe heterogeneity and high average permeability, leading to a low water flooding recovery efficiency. Polymer flooding only works for a certain heterogeneous reservoir. Therefore, supplementary technologies for further enlarging the swept volume are still necessary. Based on the concept of discontinuous chemical flooding with multi slugs, three chemical systems, which were polymer gel (PG), hydrophobically associating polymer (polymer A), and conventional polymer (polymer B), were selected as the profile control and displacing agents. The optimization design of the discontinuous chemical flooding was investigated by core flooding experiments and displacement equilibrium degree calculation. The gel, polymer A, and polymer B were classified into three levels based on their profile control performance. The degree of displacement equilibrium was defined by considering the sweep conditions and oil displacement efficiency of each layer. The effectiveness of displacement equilibrium degree was validated through a three-core parallel displacement experiment. Additionally, the parallel core displacement experiment optimized the slug size, combination method, and shift timing of chemicals. Finally, a five-core parallel displacement experiment verified the enhanced oil recovery (EOR) performance of discontinuous chemical flooding. The results show that the displacement equilibrium curve exhibited a stepwise change. The efficiency of discontinuous chemical flooding became more significant with the number of layers increasing and heterogeneity intensifying. Under the combination of permeability of 5000/2000/500 mD, the optimal chemical dosage for the chemical discontinuous flooding was a 0.7 pore volume (PV). The optimal combination pattern was the alternation injection in the form of "medium-strong-weak-strong-weak", achieving a displacement equilibrium degree of 82.3%. The optimal shift timing of chemicals occurred at a water cut of 70%, yielding a displacement equilibrium degree of 87.7%. The five-core parallel displacement experiment demonstrated that discontinuous chemical flooding could get a higher incremental oil recovery of 24.5% compared to continuous chemical flooding, which presented a significantly enhanced oil recovery potential. [ABSTRACT FROM AUTHOR]

Intelligent manufacturing technology is revolutionizing the production processes in the automotive industry through enhanced efficiency, flexibility, and intelligence. This review examines the current applications and future trends of intelligent manufacturing in the automotive sector, aiming to inform technological innovation and strategic planning. The paper begins by outlining the development and significance of intelligent manufacturing in the context of the automotive industry. Key technologies such as the industrial Internet, mechatronics, industrial robots, and digital factories are then highlighted, with an analysis of their roles in improving manufacturing efficiency and product quality. Through a comprehensive literature review and case analysis, the integrated application of these technologies is explored, particularly their innovations in production line design and impact on new energy vehicles. The paper concludes by summarizing how intelligent manufacturing technology is driving the automotive industry’s transformation towards greener and smarter production, and it proposes future research directions and addresses technical challenges.

Logistic regression models are widely used in case‐control data analysis, and testing the goodness‐of‐fit of their parametric model assumption is a fundamental research problem. In this article, we propose to enhance the power of the goodness‐of‐fit test by exploiting a monotonic density ratio model, in which the ratio of case and control densities is assumed to be a monotone function. We show that such a monotonic density ratio model is naturally induced by the retrospective case‐control sampling design under the alternative hypothesis. The pool‐adjacent‐violator algorithm is adapted to solve for the constrained nonparametric maximum likelihood estimator under the alternative hypothesis. By measuring the discrepancy between this estimator and the semiparametric maximum likelihood estimator under the null hypothesis, we develop a new Kolmogorov‐Smirnov‐type statistic to test the goodness‐of‐fit for logistic regression models with case‐control data. A bootstrap resampling procedure is suggested to approximate the p$$ p $$‐value of the proposed test. Simulation results show that the type I error of the proposed test is well controlled and the power improvement is substantial in many cases. Three real data applications are also included for illustration. [ABSTRACT FROM AUTHOR]