Jinyuan Liu

We derive a geometric mechanism for magnetic interaction within anisotropic spatial dynamics (ASD). The transverse length vector effect identifies the physical interaction distance of two charges moving with a common transverse velocity as r_T=γr, where r is the reference separation and γ is the Lorentz factor. Applying Coulomb’s inverse-square law to this distance gives F_T=(1-β² ) F₀ and the magnetic interaction difference ΔF_m=-β² F₀, with β=v/c. These relations are exact throughout the subluminal interval for this configuration. Magnetism is thus represented as the motion-induced geometric reduction of a single Coulomb interaction. A virtual-work analysis distinguishes the physical force conjugate to r_T from the generalized force Q_r=F₀/γ conjugate to r. This supplies an ASD interpretation of the inverse-Lorentz-factor scaling while preserving the different physical roles of the two force variables. We further prove that rotational and reflection covariance, separate linearity in the source and test velocities, and zero magnetic power determine a unique bilinear quasistatic kernel once its normalization is fixed by the transverse result. Superposition recovers the Biot–Savart representation and the Ampère force between parallel steady currents. Comparison with conventional electrodynamics identifies differences in spatial interpretation, force decomposition, and exact velocity dependence.

Measuring the emissivity of an infrared radiant sample with high accuracy is important. Previous studies reported on the multi- or two-temperature calibration methods, which used a reference blackbody (or blackbodies) to eliminate the background radiation, and assumed that the background radiation was independent of temperature. However, in practical measurements, this assumption does not hold. To solve the above problems, this study proposes a modified two-temperature calibration method and facility. The two temperature points are set in a certain small interval based on the proposed calculation method; based on the indication of the approximation that the emissivities of the sample and the background radiations remain the same at these two temperatures, the emissivities can be calculated with measurement signals at these two temperatures, and a reference blackbody is not needed. An experimental facility was built up and three samples with emissivities around 0.100, 0.500, and 0.900 were measured in (8~14) μm. The relative expanded uncertainties were 9.6%, 4.0%, and 1.5% at 60 °C, respectively, and 8.8%, 5.8%, and 1.2% at 85 °C (k = 2), respectively. The experimental results showed consistency with the results obtained using other methods, indicating the effectiveness of the developed method. The developed method might be suitable for samples whose emissivities are temperature insensitive.

Background and Objectives: Depth perception of the human visual system in three-dimensional (3D) space plays an important role in human–computer interaction and artificial intelligence (AI) areas. It mainly employs binocular disparity and motion parallax cues. This study aims to systemically summarize the related studies about depth perception specified by these two cues. Materials and Methods: We conducted a literature investigation on related studies and summarized them from aspects like motivations, research trends, mechanisms, and interaction models of depth perception specified by these two cues. Results: Development trends show that depth perception research has gradually evolved from early studies based on a single cue to quantitative studies based on the interaction between these two cues. Mechanisms of these two cues reveal that depth perception specified by the binocular disparity cue is mainly influenced by factors like spatial variation in disparity, viewing distance, the position of visual field (or retinal image) used, and interaction with other cues; whereas that specified by the motion parallax cue is affected by head movement and retinal image motion, interaction with other cues, and the observer’s age. By integrating these two cues, several types of models for depth perception are summarized: the weak fusion (WF) model, the modified weak fusion (MWF) model, the strong fusion (SF) model, and the intrinsic constraint (IC) model. The merits and limitations of each model are analyzed and compared. Conclusions: Based on this review, a clear picture of the study on depth perception specified by binocular disparity and motion parallax cues can be seen. Open research challenges and future directions are presented. In the future, it is necessary to explore methods for easier manipulating of depth cue signals in stereoscopic images and adopting deep learning-related methods to construct models and predict depths, to meet the increasing demand of human–computer interaction in complex 3D scenarios.