AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling

We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images, and music. AnyGPT can be trained stably without any alterations to the current large language model (LLM) architecture or training paradigms. Instead, it relies exclusively on data-level preprocessing, facilitating the seamless integration of new modalities into LLMs, akin to the incorporation of new languages. We build a multimodal text-centric dataset for multimodal alignment pre-training. Utilizing generative models, we synthesize the first large-scale any-to-any multimodal instruction dataset. It consists of 108k samples of multi-turn conversations that intricately interweave various modalities, thus equipping the model to handle arbitrary combinations of multimodal inputs and outputs. Experimental results demonstrate that AnyGPT is capable of facilitating any-to-any multimodal conversation while achieving performance comparable to specialized models across all modalities, proving that discrete representations can effectively and conveniently unify multiple modalities within a language model. Demos are shown in https://junzhan2000.github.io/AnyGPT.github.io/Comment: 28 pages, 16 figures, under review, work in progres

Insight-HXMT observations of Swift J0243.6+6124 during its 2017-2018 outburst

The recently discovered neutron star transient Swift J0243.6+6124 has been monitored by {\it the Hard X-ray Modulation Telescope} ({\it Insight-\rm HXMT). Based on the obtained data, we investigate the broadband spectrum of the source throughout the outburst. We estimate the broadband flux of the source and search for possible cyclotron line in the broadband spectrum. No evidence of line-like features is, however, found up to $\rm 150~keV$. In the absence of any cyclotron line in its energy spectrum, we estimate the magnetic field of the source based on the observed spin evolution of the neutron star by applying two accretion torque models. In both cases, we get consistent results with $B\rm \sim 10^{13}~G$, $D\rm \sim 6~kpc$ and peak luminosity of $\rm >10^{39}~erg~s^{-1}$ which makes the source the first Galactic ultraluminous X-ray source hosting a neutron star.Comment: publishe

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

The large area detector onboard the eXTP mission

The Large Area Detector (LAD) is the high-throughput, spectral-timing instrument onboard the eXTP mission, a flagship mission of the Chinese Academy of Sciences and the China National Space Administration, with a large European participation coordinated by Italy and Spain. The eXTP mission is currently performing its phase B study, with a target launch at the end-2027. The eXTP scientific payload includes four instruments (SFA, PFA, LAD and WFM) offering unprecedented simultaneous wide-band X-ray timing and polarimetry sensitivity. The LAD instrument is based on the design originally proposed for the LOFT mission. It envisages a deployed 3.2 m2 effective area in the 2-30 keV energy range, achieved through the technology of the large-area Silicon Drift Detectors - offering a spectral resolution of up to 200 eV FWHM at 6 keV - and of capillary plate collimators - limiting the field of view to about 1 degree. In this paper we will provide an overview of the LAD instrument design, its current status of development and anticipated performance

Multi-fidelity optimization of a quiet propeller based on deep deterministic policy gradient and transfer learning

PeerReviewe

Autoperforation of two-dimensional materials to generate colloidal state machines capable of locomotion

A central ambition of the robotics field has been to increasingly miniaturize such systems, with perhaps the ultimate achievement being the synthetic microbe or cell sized machine. To this end, we have introduced and demonstrated prototypes of what we call colloidal state machines (CSMs) as particulate devices capable of integrating sensing, memory, and energy harvesting as well as other functions onto a single particle. One technique that we have introduced for creating CSMs based on 2D materials such as graphene or monolayer MoS₂ is “autoperforation”, where the nanometer-scale film is fractured around a designed strain field to produce structured particles upon liftoff. While CSMs have been demonstrated with functions such as memory, sensing, and energy harvesting, the property of locomotion has not yet been demonstrated. In this work, we introduce an inversion moulding technique compatible with autoperforation that allows for the patterning of an external catalytic surface that enables locomotion in an accompanying fuel bath. Optimal processing conditions for electroplating a catalytic Pt layer to one side of an autoperforated CSM are elucidated. The self-driven propulsion of the resulting Janus CSM in H₂O₂ is studied, including the average velocity, as a function of fluid surface tension and H₂O₂ concentration in the bath. Since machines have to encode for a specific task, this work summarizes efforts to create a microfluidic testbed that allows for CSM designs to be evaluated for the ultimate purpose of navigation through complex fluidic networks, such as the human circulatory system. We introduce two CSM designs that mimic aspects of human immunity to solve search and recruitment tasks in such environments. These results advance CSM design concepts closer to promising applications in medicine and other areas

KDM6B Elicits Cell Apoptosis by Promoting Nuclear Translocation of FOXO1 in Non-Small Cell Lung Cancer

Background/Aims: Non-small cell lung carcinoma (NSCLC) is the most common type of lung cancer and the cause of most cancer-related deaths. The molecular mechanisms that are involved in NSCLC development are currently not well understood. Accumulating evidence shows that histone demethylases play important roles in the regulation of pathological developmental processes in many diseases, including various types of cancers. Methods: Mitochondrial membrane potential assays, migration and invasion assays, caspase-3 and caspase-9 activity assays and western blot analysis were used in this research. Results: We found that overexpression of KDM6B, a demethylase that acts on histone H3 at lysine 27 (H3K27), inhibited cell growth by initiating mitochondria-dependent apoptosis and by attenuating the invasion-metastasis cascade in NSCLC cells. Moreover, our results showed that KDM6B directly interacted with FOXO1 and that overexpression of KDM6B promoted nuclear accumulation of FOXO1. The effects of KDM6B on cell apoptosis and metastasis were weakened by knockdown of FOXO1 expression. On the contrary, knocking down expression of KDM6B inhibited cell apoptosis and promoted cell growth by mitigating the nuclear translocation of FOXO1 in NSCLC cells. Conclusions: These findings suggest that KDM6B may act in a pro-apoptotic role in NSCLC by causing the nuclear translocation of FOXO1