TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT

Tables are prevalent in real-world databases, requiring significant time and effort for humans to analyze and manipulate. The advancements in large language models (LLMs) have made it possible to interact with tables using natural language input, bringing this capability closer to reality. In this paper, we present TableGPT, a unified fine-tuned framework that enables LLMs to understand and operate on tables using external functional commands. It introduces the capability to seamlessly interact with tables, enabling a wide range of functionalities such as question answering, data manipulation (e.g., insert, delete, query, and modify operations), data visualization, analysis report generation, and automated prediction. TableGPT aims to provide convenience and accessibility to users by empowering them to effortlessly leverage tabular data. At the core of TableGPT lies the novel concept of global tabular representations, which empowers LLMs to gain a comprehensive understanding of the entire table beyond meta-information. By jointly training LLMs on both table and text modalities, TableGPT achieves a deep understanding of tabular data and the ability to perform complex operations on tables through chain-of-command instructions. Importantly, TableGPT offers the advantage of being a self-contained system rather than relying on external API interfaces. Moreover, it supports efficient data process flow, query rejection (when appropriate) and private deployment, enabling faster domain data fine-tuning and ensuring data privacy, which enhances the framework's adaptability to specific use cases.Comment: Technical Repor

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Phase-Sensitive Surface Plasmon Resonance Sensors: Recent Progress and Future Prospects

Surface plasmon resonance (SPR) is an optical sensing technique that is capable of performing real-time, label-free and high-sensitivity monitoring of molecular interactions. SPR biosensors can be divided according to their operating principles into angle-, wavelength-, intensity- and phase-interrogated devices. With their complex optical configurations, phase-interrogated SPR sensors generally provide higher sensitivity and throughput, and have thus recently emerged as prominent biosensing devices. To date, several methods have been developed for SPR phase interrogation, including heterodyne detection, polarimetry, shear interferometry, spatial phase modulation interferometry and temporal phase modulation interferometry. This paper summarizes the fundamentals of phase-sensitive SPR sensing, reviews the available methods for phase interrogation of these sensors, and discusses the future prospects for and trends in the development of this technology

Disturbance Identification and Adaptive Compensation Method in Optical Target Tracking System

External disturbance suppression is critical in high-precision optical target tracking systems. Although the traditional disturbance observation compensator (DOBC) method can improve anti-disturbance performance, its fixed structure limits its ability to handle variable disturbances. To improve the suppression ability of time-varying narrowband disturbances, we propose a disturbance identification and adaptive compensation method based on DOBC (DIAC-DOBC). The peak frequency of the observed disturbance can be obtained with high precision using AR parameter model identification. To design the Q filter, an improved notch filter structure is proposed, with parameters that can be adjusted automatically and a stronger suppression ability. Furthermore, the conditions for closed-loop stability and robust stability are detailed. Finally, the method's effectiveness is demonstrated through simulation and actual experimentation on an optical target tracking system with disturbances

Magnetorheological Damper Working in Squeeze Mode

This research is focused on evaluation of the magnetorheological fluids (MRFs) based damper which works in squeeze mode. The operation direction of this damper is parallel to the direction of the external magnetic field. Before testing, commercial software ANSYS was used to analyze the magnetic field distribution inside the damper generated by charging current in the coil. The performance of the damper was tested by using the MTS809 (produced by MTS Systems Corporation, USA). For simulation of this damper, a mathematical model was set up. Experimental results showed that the small squeezed MR damper could produce large damping force; for example, the maximum damping force is nearly 6 kN, while the amplitude is 1.2 mm, the frequency is 1.0 Hz, and the current is 2.0 A, and the damping force was controllable by changing the current in the coil. The damping force versus displacement curves are complex. We divide them into four regions for simulation. The maximum damper force increased quickly with the increasing of the current in coil. This kind of damper can be used in vibration isolation for precise equipment

Dual-modulus 3D printing technology for magnetorheological Metamaterials-Part II: Negative regulation theory and application

Metamaterials are artificially structured periodic materials that have remarkable property of wave attenuation in bandgaps. However, metamaterials with adjustable and low-frequency bandgap are still challenge in traditional method. In this work, a novel magnetorheological metamaterial (MRM) with negative regulation and low -frequency bandgaps was fabricated by dual-modulus 3D printing technology. The bandgaps of negative regulation MRM were analyzed theoretically by using the mass-spring model. As a result, the starting frequency of bandgap reduced by 37.6% and ending frequency increased by 47.8% under external magnetic field. Moreover, the propagation characteristics of longitudinal wave in negative regulation MRM were also studied and the results indicated that the stiffnesses were magnetic-related, and the bandgap can be tuned substantially under external magnetic field. This work presented a negative regulation MRM that the bandgap was broadened and moved to lower frequency under the external magnetic field, showing a great potential in the field of vibration isolation

A Novel Microfluidic Flow Rate Detection Method Based on Surface Plasmon Resonance Temperature Imaging

A novel microfluidic flow rate detection method based on surface plasmon resonance (SPR) temperature imaging is proposed. The measurement is performed by space-resolved SPR imaging of the flow induced temperature variations. Theoretical simulations and analysis were performed to demonstrate a proof of concept using this approach. Experiments were implemented and results showed that water flow rates within a wide range of tens to hundreds of μL/min could be detected. The flow rate sensor is resistant to disturbances and can be easily integrated into microfluidic lab-on-chip systems