Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models

Recently, growing interest has been aroused in extending the multimodal capability of large language models (LLMs), e.g., vision-language (VL) learning, which is regarded as the next milestone of artificial general intelligence. However, existing solutions are prohibitively expensive, which not only need to optimize excessive parameters, but also require another large-scale pre-training before VL instruction tuning. In this paper, we propose a novel and affordable solution for the effective VL adaption of LLMs, called Mixture-of-Modality Adaptation (MMA). Instead of using large neural networks to connect the image encoder and LLM, MMA adopts lightweight modules, i.e., adapters, to bridge the gap between LLMs and VL tasks, which also enables the joint optimization of the image and language models. Meanwhile, MMA is also equipped with a routing algorithm to help LLMs achieve an automatic shift between single- and multi-modal instructions without compromising their ability of natural language understanding. To validate MMA, we apply it to a recent LLM called LLaMA and term this formed large vision-language instructed model as LaVIN. To validate MMA and LaVIN, we conduct extensive experiments under two setups, namely multimodal science question answering and multimodal dialogue. The experimental results not only demonstrate the competitive performance and the superior training efficiency of LaVIN than existing multimodal LLMs, but also confirm its great potential as a general-purpose chatbot. More importantly, the actual expenditure of LaVIN is extremely cheap, e.g., only 1.4 training hours with 3.8M trainable parameters, greatly confirming the effectiveness of MMA. Our project is released at https://luogen1996.github.io/lavin

Vibration control of a tunnel boring machine using adaptive magnetorheological damper

With a large number of tunnel boring machines (TBM) being used in various tunnel constructions, the vibration problem under complex geological conditions have become increasingly prominent. In order to solve the problem, this article investigates the application of an adaptive magnetorheological (MR) damper on the vibration reduction of a TBM. The MR damper could reduce the horizontal vibration of the TBM system and adjust its dragging force on the propulsive system under different geological conditions. The MR damper can also provide large enough damping force even under a small amplitude vibration, which is required by TBM. In this paper, an MR damper was designed, prototyped and its properties were tested by an MTS system, including its current-dependency, amplitude-dependency and frequency-dependency features. A scaled TBM system incorporated with the MR damper was built to evaluate the vibration reduction effectiveness of the MR damper on the TBM system. The experimental test results demonstrate that the displacement and the acceleration amplitudes of the TMB vibration could be reduced by 52.14% and 53.31%, respectively

Development and evaluation of a versatile semi-active suspension system for high-speed railway vehicles

With the increase in speed of high-speed trains, their vibration will become fiercer and fiercer, especially when the lateral resonance of the car body occurs. This paper develops a versatile semi-active suspension system with variable stiffness (VS) magnetorheological elastomer (MRE) isolators and variable damping (VD) magnetorheological (MR) dampers for high-speed trains, aiming to improve ride comfort by avoiding car body resonance and dissipating vibration energy. As the first step, a multifunction VSVD semi-active suspension system for high-speed railway vehicles was designed and prototyped, including four VS-MRE isolators and two VD-MR dampers. After that, a scaled train model, composing of a car body and a secondary lateral suspension system was designed and built to evaluate the performance of the new VSVD suspension system; a control strategy based on short-time Fourier transform (STFT) and sky-hook was proposed to control the new suspension system. Two different excitations, harmonic excitation and random excitation, were applied to evaluate the train\u27s VSVD suspension. As a comparison, four alternative suspension systems, including passive-off suspension, passive-on suspension, pure VS suspension, and pure VD suspension were also evaluated. The evaluation results verified that the VSVD suspension of the train can avoid lateral resonance of car body and dissipate the vibration energy efficiently. The comparison verified that the VSVD suspension system outperforms the passive-off suspension, passive-on suspension, pure VS suspension, and pure VD suspension

The Effect of Asian Dust Aerosols on Cloud Properties and Radiative Forcing from MODIS and CERES

The effects of dust storms on cloud properties and radiative forcing are analyzed over northwestern China from April 2001 to June 2004 using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) instruments on the Aqua and Terra satellites. On average, ice cloud effective particle diameter, optical depth and ice water path of the cirrus clouds under dust polluted conditions are 11%, 32.8%, and 42% less, respectively, than those derived from ice clouds in dust-free atmospheric environments. The humidity differences are larger in the dusty region than in the dust-free region, and may be caused by removal of moisture by wet dust precipitation. Due to changes in cloud microphysics, the instantaneous net radiative forcing is reduced from -71.2 W/m2 for dust contaminated clouds to -182.7 W/m2 for dust-free clouds. The reduced cooling effects of dusts may lead to a net warming of 1 W/m2, which, if confirmed, would be the strongest aerosol forcing during later winter and early spring dust storm seasons over the studied region

Seasonal Land Fallowing Policy in Response to Groundwater Overdraft in the North China Plain

The Seasonal Land Fallowing Policy (SLFP), designed to mitigate serious groundwater overdraft in the North China Plain, was introduced in Hebei Province in 2014. This paper offers a comprehensive review and assessment of its implementation status, effectiveness and challenges. Based on data at both macro and micro levels, we witnessed the rapid expansion of the SLFP from 2014 to 2019. With a high targeting efficiency, the SLFP reduced groundwater consumption and contributed to real water saving. However, further analysis is needed on the influence of the SLFP on water levels. As a means of payment for ecosystem services, the currentsubsidy offered by the SLFP is not sufficiently flexible to reflect the heterogeneity in farmers’ opportunity cost. Obstacles to the effective and sustainable implementation of the SLFP include unstable and ineligible participants, insufficient incentive for farmers to shift surplus labour to off-farm jobs, and underuse of fallowed land. Based on these challenges, this paper offers policy suggestions to further aid the SLFP’s effective and sustainable implementation in the future

Application and development of Deuterium Metabolic Imaging in tumor glucose metabolism: visualization of different metabolic pathways

Cancer metabolism has emerged as a pivotal area of research recently. The ability to visualize and comprehend the metabolic processes of cancer holds immense clinical value, particularly in the diagnosis of malignant tumors and the assessment of treatment responses. Deuterium Metabolic Imaging (DMI), as a robust, simple, and versatile MR spectroscopic imaging tool, demonstrates promise in tumor diagnosis and treatment efficacy assessment. This review explored the latest developments and applications of DMI in oncology across various tumor metabolic axes, with a specific emphasis on its potential for clinical translation. DMI offers invaluable insights into tumor biology, treatment responses, and prognostic outcomes. Notably, DMI can identify early responses to immunotherapy, a prominent area of current research interest. In conclusion, DMI harbors the potential to evolve into a convenient and efficient imaging technique in clinical practice, thereby advancing precision medicine and improving the diagnosis and evaluation of cancer treatments

Ly49P recognition of cytomegalovirus-infected cells expressing H2-Dk and CMV-encoded m04 correlates with the NK cell antiviral response

Natural killer (NK) cells are crucial in resistance to certain viral infections, but the mechanisms used to recognize infected cells remain largely unknown. Here, we show that the activating Ly49P receptor recognizes cells infected with mouse cytomegalovirus (MCMV) by a process that requires the presence of H2-Dk and the MCMV m04 protein. Using H2 chimeras between H2-Db and -Dk, we demonstrate that the H2-Dk peptide-binding platform is required for Ly49P recognition. We identified m04 as a viral component necessary for recognition using a panel of MCMV-deletion mutant viruses and complementation of m04-deletion mutant (Δm04) virus infection. MA/My mice, which express Ly49P and H2-Dk, are resistant to MCMV; however, infection with Δm04 MCMV abrogates resistance. Depletion of NK cells in MA/My mice abrogates their resistance to wild-type MCMV infection, but does not significantly affect viral titers in mice infected with Δm04 virus, implicating NK cells in host protection through m04-dependent recognition. These findings reveal a novel mechanism of major histocompatability complex class I–restricted recognition of virally infected cells by an activating NK cell receptor

Prediction of earth rotation parameters based on improved weighted least squares and autoregressive model

In this paper, an improved weighted least squares (WLS), together with autoregressive (AR) model, is proposed to improve prediction accuracy of earth rotation parameters(ERP). Four weighting schemes are developed and the optimal power e for determination of the weight elements is studied. The results show that the improved WLS-AR model can improve the ERP prediction accuracy effectively, and for different prediction intervals of ERP, different weight scheme should be chosen