Solar cycle variation of real CME latitudes

With the assumption of radial motion and uniform longitudinal distribution of coronal mass ejections (CMEs), we propose a method to eliminate projection effects from the apparent observed CME latitude distribution. This method has been applied to SOHO LASCO data from 1996 January to 2006 December. As a result, we find that the real CME latitude distribution had the following characteristics: (1) High-latitude CMEs ($\theta>60^{\circ}$ where $\theta$ is the latitude) constituted 3% of all CMEs and mainly occurred during the time when the polar magnetic fields reversed sign. The latitudinal drift of the high-latitude CMEs was correlated with that of the heliospheric current sheet. (2) 4% of all CMEs occurred in the range $45^{\circ}\leq\theta\leq60^{\circ}$. These mid-latitude CMEs occurred primarily in 2000, near the middle of 2002 and in 2005, respectively, forming a prominent three-peak structure; (3) The highest occurrence probability of low-latitude ($\theta< 45^{\circ}$) CMEs was at the minimum and during the declining phase of the solar cycle. However, the highest occurrence rate of low-latitude CMEs was at the maximum and during the declining phase of the solar cycle. The latitudinal evolution of low-latitude CMEs did not follow the Sp\"{o}rer sunspot law, which suggests that many CMEs originated outside of active regions.Comment: 4 pages, 4 figures, accepted by ApJ Lette

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios

Multi-object tracking in traffic videos is a crucial research area, offering immense potential for enhancing traffic monitoring accuracy and promoting road safety measures through the utilisation of advanced machine learning algorithms. However, existing datasets for multi-object tracking in traffic videos often feature limited instances or focus on single classes, which cannot well simulate the challenges encountered in complex traffic scenarios. To address this gap, we introduce TrafficMOT, an extensive dataset designed to encompass diverse traffic situations with complex scenarios. To validate the complexity and challenges presented by TrafficMOT, we conducted comprehensive empirical studies using three different settings: fully-supervised, semi-supervised, and a recent powerful zero-shot foundation model Tracking Anything Model (TAM). The experimental results highlight the inherent complexity of this dataset, emphasising its value in driving advancements in the field of traffic monitoring and multi-object tracking.Comment: 17 pages, 7 figure

Periplasmic biomineralization for semi-artificial photosynthesis

Semiconductor-based biointerfaces are typically established either on the surface of the plasma membrane or within the cytoplasm. In Gram-negative bacteria, the periplasmic space, characterized by its confinement and the presence of numerous enzymes and peptidoglycans, offers additional opportunities for biomineralization, allowing for nongenetic modulation interfaces. We demonstrate semiconductor nanocluster precipitation containing single- and multiple-metal elements within the periplasm, as observed through various electron- and x-ray-based imaging techniques. The periplasmic semiconductors are metastable and display defect-dominant fluorescent properties. Unexpectedly, the defect-rich (i.e., the low-grade) semiconductor nanoclusters produced in situ can still increase adenosine triphosphate levels and malate production when coupled with photosensitization. We expand the sustainability levels of the biohybrid system to include reducing heavy metals at the primary level, building living bioreactors at the secondary level, and creating semi-artificial photosynthesis at the tertiary level. The biomineralization-enabled periplasmic biohybrids have the potential to serve as defect-tolerant platforms for diverse sustainable applications

Skywork: A More Open Bilingual Foundation Model

In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3.2 trillion tokens drawn from both English and Chinese texts. This bilingual foundation model is the most extensively trained and openly published LLMs of comparable size to date. We introduce a two-stage training methodology using a segmented corpus, targeting general purpose training and then domain-specific enhancement training, respectively. We show that our model not only excels on popular benchmarks, but also achieves \emph{state of the art} performance in Chinese language modeling on diverse domains. Furthermore, we propose a novel leakage detection method, demonstrating that test data contamination is a pressing issue warranting further investigation by the LLM community. To spur future research, we release Skywork-13B along with checkpoints obtained during intermediate stages of the training process. We are also releasing part of our SkyPile corpus, a collection of over 150 billion tokens of web text, which is the largest high quality open Chinese pre-training corpus to date. We hope Skywork-13B and our open corpus will serve as a valuable open-source resource to democratize access to high-quality LLMs

Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level.Comment: 24 pages, 5 figure

Impact Resistance Study of Three-Dimensional Orthogonal Carbon Fibers/BMI Resin Woven Composites

Three-dimensional woven composites have been reported to have superior fracture toughness, fatigue life and damage tolerance compared with laminated composites due to through-thickness reinforcement. These properties make them lighter replacements for traditional high-strength metals and laminated composites. This paper will present impact resistance research on three-dimensional orthogonal woven composites consisting of carbon fibers/bismaleimide resin (BMI). A series of impact tests were conducted using the gas gun technique with the impacted target of 150 mm &times; 150 mm &times; 8 mm (length &times; width &times; thickness) and the cylindrical titanium projectile. The projectile velocity ranged from 180 m/s to 280 m/s, generating different results from rebound to perforation. This paper also presents a multiscale modeling strategy to investigate the damage and failure behavior of three-dimensional woven composites. The microscale and mesoscale are identified to consider the fiber/matrix scale and the tow architecture scale respectively. The macroscale model was effective with homogenized feature. Then a combined meso-macroscale model was developed with the interface definitions for component analysis in the explicit dynamic software LS-DYNA. The presented results showed reliable interface connection and can be used to study localized composites damage at a relatively high efficiency