The Jet Composition of GRB 230307A: Poynting-Flux-Dominated Outflow?

The jet composition of GRB plays an important role in understanding the energy dissipation and radiation mechanisms in GRB physics, but it is poorly constrained from the observational data. Recently, an interesting long-duration GRB 230307A with redshift $z=$0.065 has attracted great attention. The lack of detected thermal emission and mini-structure of prompt emission lightcurve of this burst suggest that the outflow is Poynting-flux-dominated and point towards the ICMART model. In this paper, we invoke two independent methods to investigate the jet composition of GRB 230307A. The high magnetization parameter ($\sigma>7$ or ever large) for$R_0=10^{10}$ cm that is used to suppress thermal component, strongly suggests that a significant fraction of the outflow energy is likely in a Poynting flux entrained with the baryonic matter. Moreover, it is found that the radiation efficiency of this burst for typical values $\epsilon_e=0.1$ and $\epsilon_B=0.01$ can reach as high as $~50\%$ which disfavors the internal shock model, but is consistent with ICMART model. Finally, a possible unified picture to produce GRB 230307A originated from a compact star merger is also discussed.Comment: 6 pages, 2 figures, 1 table, updated references, and matched with the published veriso

SoftCLIP: Softer Cross-modal Alignment Makes CLIP Stronger

During the preceding biennium, vision-language pre-training has achieved noteworthy success on several downstream tasks. Nevertheless, acquiring high-quality image-text pairs, where the pairs are entirely exclusive of each other, remains a challenging task, and noise exists in the commonly used datasets. To address this issue, we propose SoftCLIP, a novel approach that relaxes the strict one-to-one constraint and achieves a soft cross-modal alignment by introducing a softened target, which is generated from the fine-grained intra-modal self-similarity. The intra-modal guidance is indicative to enable two pairs have some local similarities and model many-to-many relationships between the two modalities. Besides, since the positive still dominates in the softened target distribution, we disentangle the negatives in the distribution to further boost the relation alignment with the negatives in the cross-modal learning. Extensive experiments demonstrate the effectiveness of SoftCLIP. In particular, on ImageNet zero-shot classification task, using CC3M/CC12M as pre-training dataset, SoftCLIP brings a top-1 accuracy improvement of 6.8%/7.2% over the CLIP baseline

TiEV: The Tongji Intelligent Electric Vehicle in the Intelligent Vehicle Future Challenge of China

TiEV is an autonomous driving platform implemented by Tongji University of China. The vehicle is drive-by-wire and is fully powered by electricity. We devised the software system of TiEV from scratch, which is capable of driving the vehicle autonomously in urban paths as well as on fast express roads. We describe our whole system, especially novel modules of probabilistic perception fusion, incremental mapping, the 1st and the 2nd planning and the overall safety concern. TiEV finished 2016 and 2017 Intelligent Vehicle Future Challenge of China held at Changshu. We show our experiences on the development of autonomous vehicles and future trends

One for More: Selecting Generalizable Samples for Generalizable ReID Model

Current training objectives of existing person Re-IDentification (ReID) models only ensure that the loss of the model decreases on selected training batch, with no regards to the performance on samples outside the batch. It will inevitably cause the model to over-fit the data in the dominant position (e.g., head data in imbalanced class, easy samples or noisy samples). %We call the sample that updates the model towards generalizing on more data a generalizable sample. The latest resampling methods address the issue by designing specific criterion to select specific samples that trains the model generalize more on certain type of data (e.g., hard samples, tail data), which is not adaptive to the inconsistent real world ReID data distributions. Therefore, instead of simply presuming on what samples are generalizable, this paper proposes a one-for-more training objective that directly takes the generalization ability of selected samples as a loss function and learn a sampler to automatically select generalizable samples. More importantly, our proposed one-for-more based sampler can be seamlessly integrated into the ReID training framework which is able to simultaneously train ReID models and the sampler in an end-to-end fashion. The experimental results show that our method can effectively improve the ReID model training and boost the performance of ReID models

Prompt-to-afterglow transition of optical emission in a long gamma-ray burst consistent with a fireball

Long gamma-ray bursts (GRBs), which signify the end-life collapsing of very massive stars, are produced by extremely relativistic jets colliding into circumstellar medium. Huge energy is released both in the first few seconds, namely the internal dissipation phase that powers prompt emissions, and in the subsequent self-similar jet-deceleration phase that produces afterglows observed in broad-band electromagnetic spectrum. However, prompt optical emissions of GRBs have been rarely detected, seriously limiting our understanding of the transition between the two phases. Here we report detection of prompt optical emissions from a gamma-ray burst (i.e. GRB 201223A) using a dedicated telescope array with a high temporal resolution and a wide time coverage. The early phase coincident with prompt {\gamma}-ray emissions show a luminosity in great excess with respect to the extrapolation of {\gamma}-rays, while the later luminosity bump is consistent with onset of the afterglow. The clearly detected transition allows us to differentiate physical processes contributing to early optical emissions and to diagnose the composition of the jetComment: Authors' version of article published in Nature Astronomy, see their website for official versio

The effectiveness of collaborative problem solving in promoting students’ critical thinking: A meta-analysis based on empirical literature

Abstract Collaborative problem-solving has been widely embraced in the classroom instruction of critical thinking, which is regarded as the core of curriculum reform based on key competencies in the field of education as well as a key competence for learners in the 21st century. However, the effectiveness of collaborative problem-solving in promoting students’ critical thinking remains uncertain. This current research presents the major findings of a meta-analysis of 36 pieces of the literature revealed in worldwide educational periodicals during the 21st century to identify the effectiveness of collaborative problem-solving in promoting students’ critical thinking and to determine, based on evidence, whether and to what extent collaborative problem solving can result in a rise or decrease in critical thinking. The findings show that (1) collaborative problem solving is an effective teaching approach to foster students’ critical thinking, with a significant overall effect size (ES = 0.82, z = 12.78, P < 0.01, 95% CI [0.69, 0.95]); (2) in respect to the dimensions of critical thinking, collaborative problem solving can significantly and successfully enhance students’ attitudinal tendencies (ES = 1.17, z = 7.62, P < 0.01, 95% CI[0.87, 1.47]); nevertheless, it falls short in terms of improving students’ cognitive skills, having only an upper-middle impact (ES = 0.70, z = 11.55, P < 0.01, 95% CI[0.58, 0.82]); and (3) the teaching type (chi2 = 7.20, P < 0.05), intervention duration (chi2 = 12.18, P < 0.01), subject area (chi2 = 13.36, P < 0.05), group size (chi2 = 8.77, P < 0.05), and learning scaffold (chi2 = 9.03, P < 0.01) all have an impact on critical thinking, and they can be viewed as important moderating factors that affect how critical thinking develops. On the basis of these results, recommendations are made for further study and instruction to better support students’ critical thinking in the context of collaborative problem-solving

An optimization method for vibration suppression and energy dissipation of the axially moving string with hybrid nonclassical boundaries

The axially moving string model is widely used in engineering applications and is of great significance in research. In order to suppress the transverse vibration and facilitate energy dissipation of the axially moving string with nonclassical boundaries, a bi-objective optimization model and methodology are proposed for its boundary parameters’ design. First, an approximate numerical model for an axially moving string with a nonclassical boundary is established, which based on the finite element method (FEM) and Newmark-beta method. Then, a bi-objective model is proposed, including the average transverse vibration and the average system energy in a single traveling wave period, and a particle swarm optimization (BOPSO) algorithm is es-tablished for optimization. Finally, the proposed optimization model is applied in a numerical example, and the results are compared with NSGA-II, a multi-objective cuckoo search algorithm (MOCSA), and multi-objective flower pollination algorithm (MOFPA) to verify the feasibility of the proposed methodology

Solutions for the vibration of an axially moving variable length string system: wave propagation versus space-time finite element predictions

This paper provides numerical and exact solutions for an axially moving stringsystem with variable length by both a space-time finite element and propagating wave model, respectively. Firstly, from the variational form, the dynamic problem for the continuum possessing changing mass is solved by a space-time finite element method. For the problem of a time-varying spatial domain, this finite element method discretizes the spatial and temporal domains simultaneously. Secondly, according to the regularity of propagating wave reflection, an exact solution for a variable-length moving string under uniform motion is derived by a propagating wave method. Subsequently, these two methods proposed are applied to a real-life example, i.e., a high-speed elevator cable. The vibration characteristics of the variable-length moving string with different boundary conditions are analyzed. Compared to the propagating wave method, the space-time finite element method has universality and low computational cost.Keywords: moving string; space-time finite element; changing mass; time-varying spatial domain; propagating wav