Dancing with the Dragon Heads: Enforcement, Innovations and Efficiency of Contracts between Agricultural Processors and Farmers in China

Contractual breaches are very common in developing countries such as China. In order to prevent breaches of contract, the contractual designs between farmers and agricultural processors (Dragon Head Firms) in China are innovating in two ways: organizational innovations and contractual innovations. Due to contractual innovations, simple price-quantity contracts are evolving into complex cooperation contracts. Using data for over 500 state key processors in 2003 from the Chinese Ministry of Agriculture, we construct econometric models to study contractual choices, contract intensity, and their impacts on sales and profits for agricultural processors in China. The results indicate that capital and the number of contracted farmers are endogenous to contract choices. Processors are more likely to use cooperation contracts compared with price-quantity contracts as the number of contracted farmers increases, because the costs of coordinating, monitoring and enforcing price-quantity contracts may increase dramatically under these circumstances . On the other hand, contract types are not important for the number of contracted farmers, the intensity of contracts, or sales and profits for processors. The results also indicate that the elasticity of profits with respect to capital is 0.52, which implies that the returns to investing in the food processing industry are relatively high in China.Agribusiness,

Protecting the Intellectual Property of Diffusion Models by the Watermark Diffusion Process

Diffusion models have emerged as state-of-the-art deep generative architectures with the increasing demands for generation tasks. Training large diffusion models for good performance requires high resource costs, making them valuable intellectual properties to protect. While most of the existing ownership solutions, including watermarking, mainly focus on discriminative models. This paper proposes WDM, a novel watermarking method for diffusion models, including watermark embedding, extraction, and verification. WDM embeds the watermark data through training or fine-tuning the diffusion model to learn a Watermark Diffusion Process (WDP), different from the standard diffusion process for the task data. The embedded watermark can be extracted by sampling using the shared reverse noise from the learned WDP without degrading performance on the original task. We also provide theoretical foundations and analysis of the proposed method by connecting the WDP to the diffusion process with a modified Gaussian kernel. Extensive experiments are conducted to demonstrate its effectiveness and robustness against various attacks

Free Triiodothyronine Levels Are Associated with Diabetic Nephropathy in Euthyroid Patients with Type 2 Diabetes

Objective. To investigate the association of thyroid function and diabetic nephropathy (DN) in euthyroid patients with type 2 diabetes. Methods. A total of 421 patients were included in this cross-sectional study. The following parameters were assessed: anthropometric measurements, fast plasma glucose, serum creatinine, lipid profile, HbA1c, free triiodothyronine (FT3), free thyroxine, thyroid-stimulating hormone levels, and urinary albumin-to-creatinine ratio (UACR). Patients with UACR of ≥30 mg/g were defined as those suffering from DN. Results. Of the 421 patients, 203 (48.2%) suffered from DN, and no difference was found between males and females. The patients with DN yielded significantly lower FT3 levels than those without DN (P<0.01). The prevalence of DN showed a significantly decreasing trend across the three tertiles based on FT3 levels (59.6%, 46.4%, and 38.6%, P<0.01). After adjustment for gender and age, FT3 levels were found to correlate positively with estimated glomerular filtration rate (P=0.03) and negatively with UACR (P<0.01). Multiple linear regression analysis showed that FT3 level was independently associated with UACR (β=-0.18, t=-3.70, and P<0.01). Conclusion. Serum FT3 levels are inversely associated with DN in euthyroid patients with type 2 diabetes, independent of traditional risk factors

iBILL: Using iBeacon and Inertial Sensors for Accurate Indoor Localization in Large Open Areas

As a key technology that is widely adopted in location-based services (LBS), indoor localization has received considerable attention in both research and industrial areas. Despite the huge efforts made for localization using smartphone inertial sensors, its performance is still unsatisfactory in large open areas, such as halls, supermarkets, and museums, due to accumulated errors arising from the uncertainty of users’ mobility and fluctuations of magnetic field. Regarding that, this paper presents iBILL, an indoor localization approach that jointly uses iBeacon and inertial sensors in large open areas. With users’ real-time locations estimated by inertial sensors through an improved particle filter, we revise the algorithm of augmented particle filter to cope with fluctuations of magnetic field. When users enter vicinity of iBeacon devices clusters, their locations are accurately determined based on received signal strength of iBeacon devices, and accumulated errors can, therefore, be corrected. Proposed by Apple Inc. for developing LBS market, iBeacon is a type of Bluetooth low energy, and we characterize both the advantages and limitations of localization when it is utilized. Moreover, with the help of iBeacon devices, we also provide solutions of two localization problems that have long remained tough due to the increasingly large computational overhead and arbitrarily placed smartphones. Through extensive experiments in the library on our campus, we demonstrate that iBILL exhibits 90% errors within 3.5 m in large open areas