In-Orbit Instrument Performance Study and Calibration for POLAR Polarization Measurements

POLAR is a compact space-borne detector designed to perform reliable measurements of the polarization for transient sources like Gamma-Ray Bursts in the energy range 50-500keV. The instrument works based on the Compton Scattering principle with the plastic scintillators as the main detection material along with the multi-anode photomultiplier tube. POLAR has been launched successfully onboard the Chinese space laboratory TG-2 on 15th September, 2016. In order to reliably reconstruct the polarization information a highly detailed understanding of the instrument is required for both data analysis and Monte Carlo studies. For this purpose a full study of the in-orbit performance was performed in order to obtain the instrument calibration parameters such as noise, pedestal, gain nonlinearity of the electronics, threshold, crosstalk and gain, as well as the effect of temperature on the above parameters. Furthermore the relationship between gain and high voltage of the multi-anode photomultiplier tube has been studied and the errors on all measurement values are presented. Finally the typical systematic error on polarization measurements of Gamma-Ray Bursts due to the measurement error of the calibration parameters are estimated using Monte Carlo simulations.Comment: 43 pages, 30 figures, 1 table; Preprint accepted by NIM

Influence of the Earth on the background and the sensitivity of the GRM and ECLAIRs instruments aboard the Chinese-French mission SVOM

SVOM (Space-based multi-band astronomical Variable Object Monitor) is a future Chinese-French satellite mission which is dedicated to Gamma-Ray Burst (GRB) studies. Its anti-solar pointing strategy makes the Earth cross the field of view of its payload every orbit. In this paper, we present the variations of the gamma-ray background of the two high energy instruments aboard SVOM, the Gamma-Ray Monitor (GRM) and ECLAIRs, as a function of the Earth position. We conclude with an estimate of the Earth influence on their sensitivity and their GRB detection capability.Comment: 24 pages, 15 figures, accepted for publication in Experimental Astronom

Learning Domain-Aware Detection Head with Prompt Tuning

Domain adaptive object detection (DAOD) aims to generalize detectors trained on an annotated source domain to an unlabelled target domain. However, existing methods focus on reducing the domain bias of the detection backbone by inferring a discriminative visual encoder, while ignoring the domain bias in the detection head. Inspired by the high generalization of vision-language models (VLMs), applying a VLM as the robust detection backbone following a domain-aware detection head is a reasonable way to learn the discriminative detector for each domain, rather than reducing the domain bias in traditional methods. To achieve the above issue, we thus propose a novel DAOD framework named Domain-Aware detection head with Prompt tuning (DA-Pro), which applies the learnable domain-adaptive prompt to generate the dynamic detection head for each domain. Formally, the domain-adaptive prompt consists of the domain-invariant tokens, domain-specific tokens, and the domain-related textual description along with the class label. Furthermore, two constraints between the source and target domains are applied to ensure that the domain-adaptive prompt can capture the domains-shared and domain-specific knowledge. A prompt ensemble strategy is also proposed to reduce the effect of prompt disturbance. Comprehensive experiments over multiple cross-domain adaptation tasks demonstrate that using the domain-adaptive prompt can produce an effectively domain-related detection head for boosting domain-adaptive object detection

Baseline blood pressure does not modify the effect of intravenous thrombolysis in successfully revascularized patients

Background: Studies indicate a trajectory relationship between baseline blood pressure (BP) and outcome in patients with acute ischemic stroke (AIS) eligible for both intravenous thrombolysis (IVT) with alteplase and endovascular treatment (EVT). We determined whether baseline BP modified the effect of IVT in successfully revascularized AIS patients who participated in the Direct Intra-Arterial Thrombectomy to Revascularize AIS Patients With Large Vessel Occlusion Efficiently in Chinese Tertiary Hospitals (DIECT-MT) trial. Methods: The association of baseline systolic BP, trichotomized as high (141–185 mmHg), middle (121–140 mmHg), and low (91–120 mmHg), and the outcomes of any intracerebral hemorrhage (ICH), symptomatic ICH (sICH), and mortality and functional outcome on the modified Rankin scale at 90 days were explored. Logistic regression models determined the interaction between clinical outcomes and baseline systolic and diastolic BP, and mean arterial pressure (MAP), at 10 mmHg intervals. Data are reported as odds ratios (OR) and 95% CI. Results: A post-hoc analysis of DIRECT-MT, in 510 of the 656 randomized participants with successful revascularization underwent MT. The overall adjusted common OR of IVT and baseline BP on any ICH, sICH, and 90-day mortality and functional outcome were 0.884 (95%CI 0.613–1.274), 0.643 (95%CI 0.283–1.458), 0.842 (95%CI 0.566–1.252), and 1.286 (95%CI 0.772–2.142), respectively. No significant interaction between baseline blood pressure and intravenous thrombolysis with clinical outcome was observed. Conclusions: In patients with baseline SBP under 185 mmHg, baseline blood pressure does not alter the risk of hemorrhagic transformation and clinical outcome in successfully revascularized patients, regardless of intravenous alteplase usage. Future studies are needed to confirm our findings. Registration: URL: http://www.clinicaltrials.gov, Identifier: NCT03469206

Cambricon-LLM: A Chiplet-Based Hybrid Architecture for On-Device Inference of 70B LLM

Deploying advanced large language models on edge devices, such as smartphones and robotics, is a growing trend that enhances user data privacy and network connectivity resilience while preserving intelligent capabilities. However, such a task exhibits single-batch computing with incredibly low arithmetic intensity, which poses the significant challenges of huge memory footprint and bandwidth demands on limited edge resources. To address these issues, we introduce Cambricon-LLM, a chiplet-based hybrid architecture with NPU and a dedicated NAND flash chip to enable efficient on-device inference of 70B LLMs. Such a hybrid architecture utilizes both the high computing capability of NPU and the data capacity of the NAND flash chip, with the proposed hardware-tiling strategy that minimizes the data movement overhead between NPU and NAND flash chip. Specifically, the NAND flash chip, enhanced by our innovative in-flash computing and on-die ECC techniques, excels at performing precise lightweight on-die processing. Simultaneously, the NPU collaborates with the flash chip for matrix operations and handles special function computations beyond the flash\u27s on-die processing capabilities. Overall, Cambricon-LLM enables the on-device inference of 70B LLMs at a speed of 3.44 token/s, and 7B LLMs at a speed of 36.34 token/s, which is over 22X to 45X faster than existing flash-offloading technologies, showing the potentiality of deploying powerful LLMs in edge devices.15 pages, 16 figure

DocGenome: An Open Large-scale Scientific Document Benchmark for Training and Testing Multi-modal Large Language Models

Scientific documents record research findings and valuable human knowledge, comprising a vast corpus of high-quality data. Leveraging multi-modality data extracted from these documents and assessing large models\u27 abilities to handle scientific document-oriented tasks is therefore meaningful. Despite promising advancements, large models still perform poorly on multi-page scientific document extraction and understanding tasks, and their capacity to process within-document data formats such as charts and equations remains under-explored. To address these issues, we present DocGenome, a structured document benchmark constructed by annotating 500K scientific documents from 153 disciplines in the arXiv open-access community, using our custom auto-labeling pipeline. DocGenome features four key characteristics: 1) Completeness: It is the first dataset to structure data from all modalities including 13 layout attributes along with their LaTeX source codes. 2) Logicality: It provides 6 logical relationships between different entities within each scientific document. 3) Diversity: It covers various document-oriented tasks, including document classification, visual grounding, document layout detection, document transformation, open-ended single-page QA and multi-page QA. 4) Correctness: It undergoes rigorous quality control checks conducted by a specialized team. We conduct extensive experiments to demonstrate the advantages of DocGenome and objectively evaluate the performance of large models on our benchmark.Homepage of DocGenome: https://unimodal4reasoning.github.io/DocGenome_page 22 pages, 11 figure

Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite

As China's first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band (1-250 keV) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 MeV. It was designed to perform pointing, scanning and gamma-ray burst (GRB) observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed. Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results.Comment: 29 pages, 40 figures, 6 tables, to appear in Sci. China-Phys. Mech. Astron. arXiv admin note: text overlap with arXiv:1910.0443