A Statistical Study of GRB X-ray Flares: Evidence of Ubiquitous Bulk Acceleration in the Emission Region

When emission in a conical relativistic jet ceases abruptly (or decays sharply), the observed decay light curve is controlled by the high-latitude "curvature effect". Recently, Uhm & Zhang found that the decay slopes of three GRB X-ray flares are steeper than what the standard model predicts. This requires bulk acceleration of the emission region, which is consistent with a Poynting-flux-dominated outflow. In this paper, we systematically analyze a sample of 85 bright X-ray flares detected in 63 Swift GRBs, and investigate the relationship between the temporal decay index $\alpha$ and spectral index $\beta$ during the steep decay phase of these flares. The $\alpha$ value depends on the choice of the zero time point $t_0$. We adopt two methods. "Method I" takes $t_0^I$ as the first rising data point of each flare, and is the most conservative approach. We find that at 99.9% condifence level 56/85 flares have decay slopes steeper than the simplest curvature effect prediction, and therefore, are in the acceleration regime. "Method II" extrapolates the rising light curve of each flare backwards until the flux density is three orders of magnitude lower than the peak flux density, and defines the corresponding time as the time zero point (t_0^II). We find that 74/85 flares fall into the acceleration regime at 99.9% condifence level. This suggests that bulk acceleration is common, may be even ubiquitous among X-ray flares, pointing towards a Poynting-flux-dominated jet composition for these events.Comment: 68 pages, 6 figures, 2 tables, ApJS, in pres

Parameter estimation of fractional uncertain differential equations via Adams method

Parameter estimation of uncertain differential equations becomes popular very recently. This paper suggests a new method based on fractional uncertain differential equations for the first time, which hold more parameter freedom degrees. The Adams numerical method and Adam algorithm are adopted for the optimization problems. The estimation results are compared to show a better forecast. Finally, the predictor–corrector method is adopted to solve the fractional uncertain differential equations. Numerical solutions are demonstrated with varied α-paths

Single-layer behavior and slow carrier density dynamic of twisted graphene bilayer

We report scanning tunneling microscopy (STM) and spectroscopy (STS) of twisted graphene bilayer on SiC substrate. For twist angle ~ 4.5o the Dirac point ED is located about 0.40 eV below the Fermi level EF due to the electron doping at the graphene/SiC interface. We observed an unexpected result that the local Dirac point around a nanoscaled defect shifts towards the Fermi energy during the STS measurements (with a time scale about 100 seconds). This behavior was attributed to the decoupling between the twisted graphene and the substrate during the measurements, which lowers the carrier density of graphene simultaneously

RETRACTED: NEAT1 Overexpression Indicates a Poor Prognosis and Induces Chemotherapy Resistance via the miR-491-5p/SOX3 Signaling Pathway in Ovarian Cancer

BackgroundAccumulated studies have reported that dysregulated long non-coding RNAs (lncRNAs) are crucial in ovarian cancer (OC) initiation and development. However, detailed biological functions of lncRNA NEAT1 during the progression of OC remains to be uncovered.PurposeOur aim was to identify the role of NEAT1 in cisplatin resistance of ovarian cancer and the underlying mechanisms.MethodsThe expression patterns of NEAT1 in OC cell lines and tissue samples were identified by qRT-PCR. The cisplatin (DDP) sensitivity of OC cells was detected by MTT and CCK8 assay, while OC cell apoptosis and cell cycle were detected using flow cytometer assays. In addition, effects of NEAT1 on tumor growth were determined by xenograft tumor model. Luciferase reporter assay was conducted to prove the regulatory relation of miR-491-5p, NEAT1, and SOX3. Importantly, the expression of NEAT1 in exosomes from cisplatin-resistant patients was also determined by using qRT-PCR.ResultsIn this study, upregulated NEAT1 was detected in OC cell lines and tissues. Meanwhile, NEAT1 was also increased in cisplatin-resistant OC cell lines and tissues. Upregulation of NEAT1 inhibited cisplatin-induced OC cell apoptosis and promoted cell proliferation, while knockdown of NEAT1 played the opposite role. These effects were also observed in vivo. Furthermore, direct interaction was observed between NEAT1 and miR-491-5p. NEAT1 led to the upregulation of miR-491-5p-targeted SOX3 mRNA. Importantly, this study also showed upregulated NEAT1 expression in serum exosomes derived from cisplatin-resistant patients.ConclusionNEAT1 is vital in the chemoresistance of ovarian cancer through regulating miR-491-5p/SOX3 pathway, showing that NEAT1 might be a potential target for OC resistance treatment

A GA-Based Approach to Hide Sensitive High Utility Itemsets

A GA-based privacy preserving utility mining method is proposed to find appropriate transactions to be inserted into the database for hiding sensitive high utility itemsets. It maintains the low information loss while providing information to the data demanders and protects the high-risk information in the database. A flexible evaluation function with three factors is designed in the proposed approach to evaluate whether the processed transactions are required to be inserted. Three different weights are, respectively, assigned to the three factors according to users. Moreover, the downward closure property and the prelarge concept are adopted in the proposed approach to reduce the cost of rescanning database, thus speeding up the evaluation process of chromosomes

2-Methyl-4-trifluoro­meth­yl-1,3-thia­zole-5-carboxylic acid

In crystal of the title compound, C6H4F3NO2S, mol­ecules are linked by O—H⋯N and C—H⋯O hydrogen bonds, forming chains

The physical origin of the periodic activity for FRB 20180916B

Fast radio bursts (FRBs) are transient radio signals with millisecond-duration, large dispersion measure (DM) and extremely high brightness temperature. Among them, FRB 20180916B has been found to have a 16-day periodic activity. However, the physical origin of the periodicity is still a mystery. Here, we utilize the comprehensive observational data to diagnose the periodic models. We find that the ultra-long rotation model is the most probable one for the periodic activity. However, this model cannot reproduce the observed rotation measure (RM) variations. We propose a self-consistent model, i.e., a massive binary containing a slowly rotational neutron star and a massive star with large mass loss, which can naturally accommodate the wealth of observational features for FRB 20180916B. In this model, the RM variation is periodic, which can be tested by future observations.Comment: 12 pages, 8 figure

Event-Guided Procedure Planning from Instructional Videos with Text Supervision

In this work, we focus on the task of procedure planning from instructional videos with text supervision, where a model aims to predict an action sequence to transform the initial visual state into the goal visual state. A critical challenge of this task is the large semantic gap between observed visual states and unobserved intermediate actions, which is ignored by previous works. Specifically, this semantic gap refers to that the contents in the observed visual states are semantically different from the elements of some action text labels in a procedure. To bridge this semantic gap, we propose a novel event-guided paradigm, which first infers events from the observed states and then plans out actions based on both the states and predicted events. Our inspiration comes from that planning a procedure from an instructional video is to complete a specific event and a specific event usually involves specific actions. Based on the proposed paradigm, we contribute an Event-guided Prompting-based Procedure Planning (E3P) model, which encodes event information into the sequential modeling process to support procedure planning. To further consider the strong action associations within each event, our E3P adopts a mask-and-predict approach for relation mining, incorporating a probabilistic masking scheme for regularization. Extensive experiments on three datasets demonstrate the effectiveness of our proposed model.Comment: Accepted to ICCV 202