Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning

The recent surge of generative AI has been fueled by the generative power of diffusion probabilistic models and the scalable capabilities of large language models. Despite their potential, it remains elusive whether diffusion language models can solve general language tasks comparable to their autoregressive counterparts. This paper demonstrates that scaling diffusion models w.r.t. data, sizes, and tasks can effectively make them strong language learners. We build competent diffusion language models at scale by first acquiring knowledge from massive data via masked language modeling pretraining thanks to their intrinsic connections. We then reprogram pretrained masked language models into diffusion language models via diffusive adaptation, wherein task-specific finetuning and instruction finetuning are explored to unlock their versatility in solving general language tasks. Experiments show that scaling diffusion language models consistently improves performance across downstream language tasks. We further discover that instruction finetuning can elicit zero-shot and few-shot in-context learning abilities that help tackle many unseen tasks by following natural language instructions, and show promise in advanced and challenging abilities such as reasoning.Comment: added reference

Shear response behavior of STF/kevlar composite fabric in picture frame test

The picture frame test was applied to compare Kevlar neat and STF/Kevlar composite fabrics. The digital image correlation markers method was applied to measure the shear deformation behavior of the fabric in real-time under three loading rates: 100, 500, and 1000 mm/min. A theoretical model was applied to evaluate the effect of STF on the shear deformation stiffness of the fabric and cells and on the energy absorption during shear deformation. The results show that the STF/Kevlar composite fabric has a larger load-carrying capacity than the neat fabric in the picture frame test, and has obvious loading rate dependence. The yarn cell of the fabric undergoes slip deformation and reaches a shear-locked state; the shear modulus and the cell spring torsion coefficient of the STF/Kevlar composite fabric are significantly higher than those of neat fabric. The shear thickening behavior of STF occurs at higher loading rates, and the composite fabric has the highest shear deformation stiffness and shear energy absorption level

Magnesium Alleviates Adverse Effects of Lead on Growth, Photosynthesis, and Ultrastructural Alterations of Torreya grandis Seedlings

Magnesium (Mg2+) has been shown to reduce the physiological and biochemical stress in plants caused by heavy metals. To date our understanding of how Mg2+ ameliorates the adverse effects of heavy metals in plants is scarce. The potential effect of Mg2+ on lead (Pb2+) toxicity in plants has not yet been studied. This study was designed to clarify the mechanism of Mg2+-induced alleviation of lead (Pb2+) toxicity. Torreya grandis (T. grandis) seedlings were grown in substrate contaminated with 0, 700 and 1400 mg Pb2+ per kg-1 and with or without the addition of 1040 mg kg-1 Mg2+. Growth parameters, concentrations of Pb2+ and Mg2+ in the plants’ shoots and roots, photosynthetic pigment, gas exchange parameters, the maximum quantum efficiency (Fv/Fm), root oxidative activity, ultrastructure of chloroplasts and root growth were determined to analyze the effect of different Pb2+ concentrations in the seedlings as well as the potential ameliorating effect of Mg2+ on the Pb2+ induced toxicity. The growth of T. grandis seedlings cultivated in soils treated with 1400 mg kg-1 Pb2+ was significantly reduced compared with that of plants cultivated in soils treated with 0 or 700 mg kg-1 Pb2+. The addition of 1040 mg kg-1 Mg2+ improved the growth of the Pb2+-stressed seedlings, which was accompanied by increased chlorophyll content, the net photosynthetic rate and Fv/Fm, and enhanced chloroplasts development. In addition, the application of Mg2+ induced plants to accumulate five times higher concentrations of Pb2+ in the roots and to absorb and translocate four times higher concentrations of Mg2+ to the shoots than those without Mg2+ application. Furthermore, Mg2+ addition increased root growth and oxidative activity, and protected the root ultrastructure. To the best of our knowledge, our study is the first report on the mechanism of Mg2+-induced alleviation of Pb2+ toxicity. The gener¬ated results may have important implications for understanding the physiological interactions between heavy metals and plants, and for successful management of T. grandis plantations grown on soils contaminated with Pb2+

Complex Locomotion Skill Learning via Differentiable Physics

Differentiable physics enables efficient gradient-based optimizations of neural network (NN) controllers. However, existing work typically only delivers NN controllers with limited capability and generalizability. We present a practical learning framework that outputs unified NN controllers capable of tasks with significantly improved complexity and diversity. To systematically improve training robustness and efficiency, we investigated a suite of improvements over the baseline approach, including periodic activation functions, and tailored loss functions. In addition, we find our adoption of batching and an Adam optimizer effective in training complex locomotion tasks. We evaluate our framework on differentiable mass-spring and material point method (MPM) simulations, with challenging locomotion tasks and multiple robot designs. Experiments show that our learning framework, based on differentiable physics, delivers better results than reinforcement learning and converges much faster. We demonstrate that users can interactively control soft robot locomotion and switch among multiple goals with specified velocity, height, and direction instructions using a unified NN controller trained in our system. Code is available at https://github.com/erizmr/Complex-locomotion-skill-learning-via-differentiable-physics

Three-Dimensional Simulation of the Shrinkage Behavior of Injection-Molded Poly Lactic Acid (PLA): Effects of Temperature, Shear Rate and Part Thickness

The effects of injection temperature, shear and part thickness on the linear shrinkage of injection-molded poly (lactic acid) (PLA) were intensively analyzed using the Autodesk Moldflow software. The obtained results showed that both melt temperature and shear rate had obvious effects on the linear shrinkage of PLA, i.e., the linear shrinkage of PLA increases significantly with the increase of melt temperature and shear rate. In addition, the shrinkage of high-crystallinity PLA was remarkably larger than that of low-crystallinity PLA, and thin-walled parts was larger than thick-walled ones in shrinkage

Autonomous stabilization of Fock states in an oscillator against multi-photon losses

Fock states with a well-defined number of photons in an oscillator have shown a wide range of applications in quantum information science. Nonetheless, their usefulness has been marred by single and multiple photon losses due to unavoidable environment-induced dissipation. Though several dissipation engineering methods have been developed to counteract the leading single-photon loss error, averting multiple photon losses remains elusive. Here, we experimentally demonstrate a dissipation engineering method that autonomously stabilizes multi-photon Fock states against losses of multiple photons using a cascaded selective photon-addition operation in a superconducting quantum circuit. Through measuring the photon-number populations and Wigner tomography of the oscillator states, we observe a prolonged preservation of quantum coherence properties for the stabilized Fock states $\vert N\rangle$ with $N=1,2,3$ for a duration of about $10$~ms, far surpassing their intrinsic lifetimes of less than $50~\mu$s. Furthermore, the dissipation engineering method demonstrated here also facilitates the implementation of a non-unitary operation for resetting a binomially-encoded logical qubit. These results highlight the potential application in error-correctable quantum information processing against multi-photon-loss errors.Comment: Main text: 6 pages, 4 figures; Supplementary material: 6 pages, 4 figures, 4 table

Heisenberg-limited quantum metrology using 100-photon Fock states

Quantum metrology has emerged as a promising avenue for surpassing the limitations of classical mechanics in high-precision measurements. However, the practical implementation of quantum metrology is hindered by the challenges of manipulating exotic quantum states in large systems. Here, we propose and demonstrate a hardware-efficient approach to achieve Heisenberg-limited quantum metrology using large photon-number Fock states. We have developed a programmable photon number filter that efficiently generates Fock states with up to 100 photons in a high-quality superconducting microwave cavity. Using these highly nontrivial states in displacement and phase measurements, we demonstrate a precision scaling close to the Heisenberg limit and achieve a maximum metrological gain of up to 14.8 dB. Our hardware-efficient quantum metrology can be extended to mechanical and optical systems and provides a practical solution for high metrological gain in bosonic quantum systems, promising potential applications in radiometry and the search for new particles.Comment: Main text: 10 pages, 4 figures; Supplement: 16 pages, 9 figures, 1 tabl

ALMA Imaging of the CO(7-6) Line Emission in the Submillimeter Galaxy LESS 073 at redshift 4.755⋆^\star

In this paper we present our imaging observations on the CO(7-6) line and its underlying continuum emission of the young submillimeter galaxy LESS 073 at redshift 4.755, using the Atacama Large Millimeter/submillimeter Array (ALMA). At the achieved resolution of $\sim$$1^{\prime\prime}.2\times0^{\prime\prime}.9$ ($8\times6$~kpc$^2$), the CO(7-6) emission is largely unresolved (with a deconvolved size of $1^{\prime\prime}.1(\pm0^{\prime\prime}.5) \times 0^{\prime\prime}.9(\pm0^{\prime\prime}.8)$), and the continuum emission is totally unresolved. The CO(7-6) line emission has an integrated flux of $0.86\pm0.08$~Jy km/s, and a line width of $343\pm40$ km/s. The continuum emission has a flux density of 0.51 mJy. By fitting the observed far-infrared (FIR) spectral energy distribution of LESS 073 with a single-temperature modified blackbody function, we obtained a dust temperature $T_{\rm dust}=57.6\pm3.5$ K, 60-to-100 $\mu$m flux density ratio $f_{60}/f_{100}=0.86\pm0.08$, and total infrared luminosity $L_{\rm IR}=(5.8\pm0.9) \times 10^{12}~L_\odot$. The SED-fit-based $f_{60}/f_{100}$ is consistent with those estimated from various line ratios as advocated by our earlier work, indicating that those proposed line-ratio-based method can be used to practically derive $f_{60}/f_{100}$ for high-$z$ sources. The total molecular gas mass of LESS 073 is $(3.3\pm1.7) \times10^{10}~M_\odot$, and the inferred gas depletion time is about 43 Myr.Comment: 8 pages, 6 figures, accepted for publication in Ap