Chinese Dairy Farm Performance and Policy Implications in the New Millennium

China has significantly expanded its dairy cow numbers and increased its dairy processing capacity over the last five year in an attempt to meet increased demand for dairy products. China’s net imports of dairy products, however, has expanded at a growth rate in excess of 30% during the same period. To consider why China is still struggling to meet rising dairy product demand in China in the new millennium, this paper employs a new set of farm-level survey data and stochastic input distance functions to empirically estimate Total factor Productivity (TFP) on China’s dairy farms. The results show that the TFP growth has been positive on and this rise in productivity has been mostly driven by technological change. However, the new results show that on average, the same farms have been behind the advancing technical frontier. We also find one of the drivers of the dairy farms’ productivity advances is the relatively robust rate of technological change. The results suggest that efforts to achieve increased adoption of new technologies and better advice on how to use the technologies and manage production and marketing within the dairy farm sector, will likely further increase TFP growth in China.Distance Function; Total Factor Productivity; Technical Inefficiency; Dairy Farms

Topological Dirac states beyond π\pi orbitals for silicene on SiC(0001) surface

The discovery of intriguing properties related to the Dirac states in graphene has spurred huge interest in exploring its two-dimensional group-IV counterparts, such as silicene, germanene, and stanene. However, these materials have to be obtained via synthesizing on substrates with strong interfacial interactions, which usually destroy their intrinsic $\pi$($p_z$)-orbital Dirac states. Here we report a theoretical study on the existence of Dirac states arising from the $p_{x,y}$ orbitals instead of $p_z$ orbitals in silicene on 4H-SiC(0001), which survive in spite of the strong interfacial interactions. We also show that the exchange field together with the spin-orbital coupling give rise to a detectable band gap of 1.3 meV. Berry curvature calculations demonstrate the nontrivial topological nature of such Dirac states with a Chern number $C = 2$, presenting the potential of realizing quantum anomalous Hall effect for silicene on SiC(0001). Finally, we construct a minimal effective model to capture the low-energy physics of this system. This finding is expected to be also applicable to germanene and stanene, and imply great application potentials in nanoelectronics.Comment: 6 Figures , Accepted by Nano Letter

Reliable Generation of EHR Time Series via Diffusion Models

Electronic Health Records (EHRs) are rich sources of patient-level data, including laboratory tests, medications, and diagnoses, offering valuable resources for medical data analysis. However, concerns about privacy often restrict access to EHRs, hindering downstream analysis. Researchers have explored various methods for generating privacy-preserving EHR data. In this study, we introduce a new method for generating diverse and realistic synthetic EHR time series data using Denoising Diffusion Probabilistic Models (DDPM). We conducted experiments on six datasets, comparing our proposed method with eight existing methods. Our results demonstrate that our approach significantly outperforms all existing methods in terms of data utility while requiring less training effort. Our approach also enhances downstream medical data analysis by providing diverse and realistic synthetic EHR data

The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing

We present a unified probabilistic formulation for diffusion-based image editing, where a latent variable is edited in a task-specific manner and generally deviates from the corresponding marginal distribution induced by the original stochastic or ordinary differential equation (SDE or ODE). Instead, it defines a corresponding SDE or ODE for editing. In the formulation, we prove that the Kullback-Leibler divergence between the marginal distributions of the two SDEs gradually decreases while that for the ODEs remains as the time approaches zero, which shows the promise of SDE in image editing. Inspired by it, we provide the SDE counterparts for widely used ODE baselines in various tasks including inpainting and image-to-image translation, where SDE shows a consistent and substantial improvement. Moreover, we propose SDE-Drag -- a simple yet effective method built upon the SDE formulation for point-based content dragging. We build a challenging benchmark (termed DragBench) with open-set natural, art, and AI-generated images for evaluation. A user study on DragBench indicates that SDE-Drag significantly outperforms our ODE baseline, existing diffusion-based methods, and the renowned DragGAN. Our results demonstrate the superiority and versatility of SDE in image editing and push the boundary of diffusion-based editing methods

(1S,3R)-3-Ammonio­cyclo­hexa­necarboxyl­ate

The title γ-amino­butyric acid, C7H13NO2, exists as a zwitterion. The crystal structure is stabilized by a network of inter­molecular N—H⋯O hydrogen bonds, forming a two-dimensional bilayer. An inter­molecular C—H⋯O hydrogen bond is also observed