Radiative diffusivity factors in cirrus and stratocumulus clouds: Application to two-stream models

A diffusion-like description of radiative transfer in clouds and the free atmosphere is often used. The two stream model is probably the best known example of such a description. The main idea behind the approach is that only the first few moments of radiance are needed to describe the radiative field correctly. Integration smooths details of the angular distribution of specific intensity and it is assumed that the closure parameters of the theory (diffusivity factors) are only weakly dependent on the distribution. The diffusivity factors are investigated using the results obtained from both Stratocumulus and Cirrus phases of FIRE experiment. A new theoretical framework is described in which two (upwards and downwards) diffusivity factors are used and a detailed multistream model is used to provide further insight about both the diffusivity factors and their dependence on scattering properties of clouds

MCAD: Multi-teacher Cross-modal Alignment Distillation for efficient image-text retrieval

With the success of large-scale visual-language pretraining models and the wide application of image-text retrieval in industry areas, reducing the model size and streamlining their terminal-device deployment have become urgently necessary. The mainstream model structures for image-text retrieval are single-stream and dual-stream, both aiming to close the semantic gap between visual and textual modalities. Dual-stream models excel at offline indexing and fast inference, while single-stream models achieve more accurate cross-model alignment by employing adequate feature fusion. We propose a multi-teacher cross-modality alignment distillation (MCAD) technique to integrate the advantages of single-stream and dual-stream models. By incorporating the fused single-stream features into the image and text features of the dual-stream model, we formulate new modified teacher features and logits. Then, we conduct both logit and feature distillation to boost the capability of the student dual-stream model, achieving high retrieval performance without increasing inference complexity. Extensive experiments demonstrate the remarkable performance and high efficiency of MCAD on image-text retrieval tasks. Furthermore, we implement a mobile CLIP model on Snapdragon clips with only 93M running memory and 30ms search latency, without apparent performance degradation of the original large CLIP

Data Stream Models for Predicting Adverse Events in a War Theater

Predicting adverse events in a war theater has been an active area of research. Recent studies used machine learning methods to predict adverse events utilizing infrastructure development spending data as input variables. The goals of these studies were to find correlation and disclose the main factors between adverse events and human-social-infrastructure development projects, and reduce the occurrence of the adverse events. The predictions still have large errors compared with the real values using the existing methods. The reason could be that some significant variables are removed to comply with constraints in a soft computing model such as neural networks, fuzzy inference systems (FIS) and adaptive neuro-fuzzy inference systems (ANFIS) that work well with a smaller number of variables. In this paper, a data stream approach using three data stream regression algorithms, AMRules, TargetMean and FIMTDD, is proposed to predict the adverse events so that much more input variables could be included. The results show that the data stream methods generate better results than machine learning methods used in the previous studies, thus helping us better understand the relationship between infrastructure development and adverse events. In addition the data stream methods also outperform the traditional linear regression model. An important advantage in using data stream methods is the ability to create and apply predictive models with a relatively small amount of memory and time. Finally, the use of data stream methods provides an additional advantage by allowing the user to observe error distribution over time for more accurate assessment of the performance of the resulting models

Connecting the Milky Way potential profile to the orbital timescales and spatial structure of the Sagittarius Stream

Recent maps of the halo using RR Lyrae from Pan-STARRS1 have clearly depicted the spatial structure of the Sagittarius stream. These maps show the leading and trailing stream apocenters differ in galactocentric radius by a factor of two, and also resolve substructure in the stream at these apocenters. Here we present dynamical models that reproduce these features of the stream in simple Galactic potentials. We find that debris at the apocenters must be dynamically young, in the sense of being stripped off in the last two pericentric passages, while the Sagittarius dwarf is currently experiencing a third passage. The ratio of apocenters is sensitive to both dynamical friction and the outer slope of the Galactic rotation curve. These dependences can be understood with simple regularities connecting the apocentric radii, circular velocities, and orbital period of the progenitor. The effect of dynamical friction on the stream can be constrained using substructure within the leading apocenter. Our ensembles of models are not intended as statistically proper fits to the stream. Nevertheless, out of the range of models we consider, we consistently find the mass within 100 kpc to be $\sim 7 \times 10^{11} \, M_{\odot}$, with a nearly flat rotation curve between 50 and 100 kpc. This points to a more extended Galactic halo than assumed in some current models. As in previous work, we find prolate or triaxial halos ease agreement with the track of the leading stream. We display the behavior of our models in various observational spaces and characterize the substructure expected within the stream. In particular, the young trailing stream visible near trailing apocenter should exhibit a tight trend of velocity with distance separate from the older debris, and we suggest that this will serve as an especially useful probe of the outer Galactic potential.Comment: Submitted to MNRA