Exploring the supply chain management of fair trade business:Case study of a fair trade craft company in China

For two decades, fair trade has served as an alternative approach of trading that encourages minimal returns, sustainability, and ethics, by offering producers in developing countries better trading conditions and secured rights. This movement has emerged recently in China, with companies involving domestic trading between richer and poorer regions. However, lack of third-party certification, standardization, process control, public awareness, and brand recognition continue to be challenges. To understand the current fair trade business in China, this paper investigates important decision-making areas from a supply chain management perspective. With the nature of empirical studies, an in-depth case analysis of a fair trade craft company has been conducted along with the purchasing and supplier relationship management, internal operations, and marketing and customer relationship management. This company currently combines the role of fair trade organization and retailer, by implementing an in-house certification system and vertically integrating the supply chain. Findings also highlight risk at each stage of supply chain. Compared with the western society, the unique features of Chinese fair trade business are captured with prioritized areas for improvement. This research contributes to the fair trade literature by providing exploratory study into emerging issues in the supply chain, particularly inside developing countries. The recommendations also create value for policy-makers and practitioners of fair trade companies

Excess free volume and structural properties of inert gas condensation synthesized nanoparticles based CuZr nanoglasses

Nanoglass (NG) as a new structure-tunable material has been investigated using both experiments and computational modeling. Experimentally, inert gas condensation (IGC) is commonly employed to prepare metallic glass (MG) nanoparticles that are consolidated using cold compression to generate an NG. In computational modeling, various methods have been used to generate NGs. However, due to the high computational cost involved, heretofore modeling investigations have not followed the experimental synthesis route. In this work, we use molecular dynamics simulations to generate an NG model by consolidating IGC-prepared Cu(64)Zr(36) nanoparticles following a workflow similar to that of experiments. The resulting structure is compared with those of NGs produced following two alternative procedures previously used: direct generation employing Voronoi tessellation and consolidation of spherical nanoparticles carved from an MG sample. We focus on the characterization of the excess free volume and the Voronoi polyhedral statistics in order to identify and quantify contrasting features of the glass-glass interfaces in the three NG samples prepared using distinct methods. Results indicate that glass-glass interfaces in IGC-based NGs are thicker and display higher structural contrast with their parent MG structure. Nanoparticle-based methods display excess free volume exceeding 4%, in agreement with experiments. IGC-prepared nanoparticles, which display Cu segregation to their surfaces, generate the highest glass-glass interface excess free volume levels and the largest relative interface volume with excess free volume higher than 3%. Voronoi polyhedral analysis indicates a sharp drop in the full icosahedral motif fraction in the glass-glass interfaces in nanoparticle-based NG as compared to their parent MG

PartDiff: Image Super-resolution with Partial Diffusion Models

Denoising diffusion probabilistic models (DDPMs) have achieved impressive performance on various image generation tasks, including image super-resolution. By learning to reverse the process of gradually diffusing the data distribution into Gaussian noise, DDPMs generate new data by iteratively denoising from random noise. Despite their impressive performance, diffusion-based generative models suffer from high computational costs due to the large number of denoising steps.In this paper, we first observed that the intermediate latent states gradually converge and become indistinguishable when diffusing a pair of low- and high-resolution images. This observation inspired us to propose the Partial Diffusion Model (PartDiff), which diffuses the image to an intermediate latent state instead of pure random noise, where the intermediate latent state is approximated by the latent of diffusing the low-resolution image. During generation, Partial Diffusion Models start denoising from the intermediate distribution and perform only a part of the denoising steps. Additionally, to mitigate the error caused by the approximation, we introduce "latent alignment", which aligns the latent between low- and high-resolution images during training. Experiments on both magnetic resonance imaging (MRI) and natural images show that, compared to plain diffusion-based super-resolution methods, Partial Diffusion Models significantly reduce the number of denoising steps without sacrificing the quality of generation

A Microalbuminuria Threshold to Predict the Risk for the Development of Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients

OBJECTIVE: To test the hypothesis that a microalbuminuria (MA) threshold can help predict the risk for the development of diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM)_ patients. DESIGN: We conducted a cross-sectional study of 4739 subjects with T2DM and a prospective study of 297 subjects with T2DM in China respectively. METHODS: Clinical and laboratory data were collected and biologic risk factors associated with any DR were analysed. RESULTS: In the cross-sectional study, we found that MA was an independent risk factor for DR development; further, when the patients were divided into MA deciles, odds ratio (ORs) of DR for the patients in the sixth MA decile (10.7 mg/24 h) was 1.579-fold (1.161-2.147) compared to that for patients in the first MA decile. Furthermore, the OR of DR increased with a gradual increase in MA levels. Similarly, in the prospective study, during a mean follow-up of 4.5 years, we found that 51 patients (29.0%) of the 176 subjects with high MA level (10.7-30 mg/24 h) developed DR, while 17 patients (14.1%) of the 121 subjects with lower MA (<10.7 mg/24 h) developed DR, and the relative risk ratio of the development of DR is 2.13(95% CI, 1.58-3.62, P<0.001). CONCLUSION: These data suggest that an MA threshold can predict the risk for the development of DR in type 2 diabetes mellitus, although it is still within the traditionally established normal range

Does tax enforcement reduce corporate environmental investment? evidence from a quasi-natural experiment

The transition to a green, sustainable economy is largely reliant on corporate investment in the realm of environmental protection. Utilizing the adoption of the third phase of the Golden Tax Project (GTPIII) in China as a quasi-natural experiment, this paper examines how corporate environmental investment changes in response to greater tax enforcement. Our results reveal that tougher tax enforcement significantly lowers corporate environmental investment. Such an effect is stronger for firms faced by high financial constraints and those operating in non-heavy-polluting industries. Moreover, the mechanism analysis indicates that the higher tax burden induced by greater tax enforcement is the potential channel. Overall, this paper shows that stricter tax enforcement could potentially result in adverse spillover effects on corporate environmental investment, which warrants attention in tax collection practices

CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation

A large portion of volumetric medical data, especially magnetic resonance imaging (MRI) data, is anisotropic, as the through-plane resolution is typically much lower than the in-plane resolution. Both 3D and purely 2D deep learning-based segmentation methods are deficient in dealing with such volumetric data since the performance of 3D methods suffers when confronting anisotropic data, and 2D methods disregard crucial volumetric information. Insufficient work has been done on 2.5D methods, in which 2D convolution is mainly used in concert with volumetric information. These models focus on learning the relationship across slices, but typically have many parameters to train. We offer a Cross-Slice Attention Module (CSAM) with minimal trainable parameters, which captures information across all the slices in the volume by applying semantic, positional, and slice attention on deep feature maps at different scales. Our extensive experiments using different network architectures and tasks demonstrate the usefulness and generalizability of CSAM. Associated code is available at https://github.com/aL3x-O-o-Hung/CSAM

Mutations in the Human naked cuticle Homolog NKD1 Found in Colorectal Cancer Alter Wnt/Dvl/β-Catenin Signaling

BACKGROUND:Mutation of Wnt signal antagonists Apc or Axin activates beta-catenin signaling in many cancers including the majority of human colorectal adenocarcinomas. The phenotype of apc or axin mutation in the fruit fly Drosophila melanogaster is strikingly similar to that caused by mutation in the segment-polarity gene, naked cuticle (nkd). Nkd inhibits Wnt signaling by binding to the Dishevelled (Dsh/Dvl) family of scaffold proteins that link Wnt receptor activation to beta-catenin accumulation and TCF-dependent transcription, but human NKD genes have yet to be directly implicated in cancer. METHODOLOGY/PRINCIPAL FINDINGS:We identify for the first time mutations in NKD1--one of two human nkd homologs--in a subset of DNA mismatch repair-deficient colorectal tumors that are not known to harbor mutations in other Wnt-pathway genes. The mutant Nkd1 proteins are defective at inhibiting Wnt signaling; in addition, the mutant Nkd1 proteins stabilize beta-catenin and promote cell proliferation, in part due to a reduced ability of each mutant Nkd1 protein to bind and destabilize Dvl proteins. CONCLUSIONS/SIGNIFICANCE:Our data raise the hypothesis that specific NKD1 mutations promote Wnt-dependent tumorigenesis in a subset of DNA mismatch-repair-deficient colorectal adenocarcinomas and possibly other Wnt-signal driven human cancers