Efficiency of Farmer Organisations in Supplying Supermarkets with Quality Food in Vietnam

The development of supermarkets in Vietnam, as in other emerging countries, goes along with an increasing concern on the part of purchasers for food quality. The paper investigates whether farmer organisations are able to help small-scale farmers get access to supermarkets, and the role that supermarkets and public support play in their emergence and development. It is based on case studies involving a number of stakeholders marketing vegetables, flavoured rice and litchi fruit in Vietnam. The interviews investigated patterns of horizontal and vertical coordination that link farmers to supermarkets, the distribution of costs and benefits between farmers and traders along the chains in relation to the strategy of quality differentiation. Eight farmer associations that work in the form of private commercial organisations are regular supermarket suppliers for the selected products. Their ability to supply supermarkets is related to the combination of functions they make available to their members, especially as regards training to improve quality (appearance, taste, safety), quality promotion and control, for which they receive public support, as well as their participation in flexible contracts with supermarkets, shops and schools. Supermarket supply through farmer associations increases farmer incomes when compared with traditional chains, yet the situation is reported to change with the increase in supermarket competition. The paper argues that changes in farmer organisation are not only due to supplying supermarkets, but also to public and international support to food quality improvement, which have been of benefit to supermarkets.Agribusiness, Industrial Organization,

XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection

With the advancement of deep learning (DL) in various fields, there are many attempts to reveal software vulnerabilities by data-driven approach. Nonetheless, such existing works lack the effective representation that can retain the non-sequential semantic characteristics and contextual relationship of source code attributes. Hence, in this work, we propose XGV-BERT, a framework that combines the pre-trained CodeBERT model and Graph Neural Network (GCN) to detect software vulnerabilities. By jointly training the CodeBERT and GCN modules within XGV-BERT, the proposed model leverages the advantages of large-scale pre-training, harnessing vast raw data, and transfer learning by learning representations for training data through graph convolution. The research results demonstrate that the XGV-BERT method significantly improves vulnerability detection accuracy compared to two existing methods such as VulDeePecker and SySeVR. For the VulDeePecker dataset, XGV-BERT achieves an impressive F1-score of 97.5%, significantly outperforming VulDeePecker, which achieved an F1-score of 78.3%. Again, with the SySeVR dataset, XGV-BERT achieves an F1-score of 95.5%, surpassing the results of SySeVR with an F1-score of 83.5%

Preparation of Ti/TiO2-PANi electrodes by combining method of thermal treatment with polymerization processing and their electrochemical property

Ti/TiO2-PANi-electrodes were synthesized by combining method of thermal treatment of titanium substrate with chemical polymerization processing of aniline on which. Their morphological structure was observed by scanning electron microscopy. The presence of PANi and TiO2 were indicated by infrared spectra and X-ray diffraction, respectively. Their electrochemical properties were characterized by cyclic voltammetry and impedance spectroscopy. The results showed that their photoelectrochemical property with light on in 0.5 M H2SO4 indicating a n-conductor that depended on PANi thickness covered TiO2-layer among them the best one obtained by oxidative temperature of 500 oC for 30 minutes during thermal treatment of titanium substrate connected with an immersing into acidic aniline solution for only 8 min during polymerization

Assessment of aflatoxin B1 contamination in rice and maize

Introduction: Aflatoxins B1 are among the most common poisonous mycotoxins produced by certain fungi that harm animals and crops. Mycotoxins can cause a variety of adverse health effects and pose a serious health threat to humans. The Maximum Residue Limits of aflatoxin B1 in processed cereals and ingredients are 2 parts per billion (ppb) and 5 ppb, respectively. Objectives: To evaluate the status of aflatoxin B 1 contamination in rice, corn and staple food produced in Ha Giang province compared with the maximum permitted levels. Methods: A total of 210 rice and maize samples were analyzed to quantify the level of aflatoxin B1. Analysis of mycotoxins was conducted by High Performance Liquid Chromatography using a fluorescence detector. Results: It was found that rice, rice products, maize, and maize products had a mean aflatoxin B1 content of 1.79 ppb, 2.55 ppb, 2.19 ppb, and 6.35 ppb, respectively. The results also showed that 71.9% of samples were contaminated with mycotoxins, and 14.28% of samples exceeded the maximum allowable limit. Conclusion: The concentration of aflatoxin B1 in 14.28% of the samples are over permissible limits by nationwide regulations

Simulation for Optimizing the Design of Cryogenic Stopping Cell for the IGISOL Facility at ELI-NP

The production of the exotic neutron-rich ion beams from photofission of the actinide targets in an IGISOL facility will be studied via an experimental program that will take place at the Extreme Light Infrastructure - Nuclear Physics (ELI-NP) facility. Geant4 simulation toolkit was used for optimizing the target configuration in order to maximize the rate of released photofission fragments from targets placed in a cell filled with He gas