Reactivity of a Carene-Derived Hydroxynitrate in Mixed Organic/Aqueous Matrices: Applying Synthetic Chemistry to Product Identification and Mechanistic Implications

β-hydroxynitrates (HN) are a major class of products formed during OH and NO3 initiated oxidation of terpenes. Their production contributes significantly to secondary organic aerosol (SOA) formation and NOx sequestration. However, studying the condensed phase reactions of this important class of molecules has been hindered by the lack of commercially available authentic standards. The goal of this work was to examine the influence of water concentration and solvent identity on product yields of a tertiary HN derived from 3-carene prepared in house. To assess the role of water on conversion chemistry, bulk-phase reactions were conducted in DMSO-d6, a non-nucleophilic solvent, with a gradient of water concentrations, and analyzed with 1H NMR. Product identifications were made by comparison with authentic standards prepared in house. Four major products were identified, including an unexpected diol produced from carbocation rearrangement, diol diastereomers, and trans-3-carene oxide, with varying yields as a function of water concentration. Product yields were also measured in two protic, nucleophilic solvents, MeOD-d4 and EtOD-d6. Finally, reactions with added chloride formed alkyl chloride products in yields approaching 30%. These results are among the first to highlight the complexities of nucleophilic reactions of hydroxynitrates in bulk, mixed aqueous/organic media and to identify new, unexpected products.

Traceability of Fruits and Vegetables Supply Chain towards Efficient Management: A Case Study from Sri Lanka

The necessity for food traceability has been increased over the years with the expansion of food supply chains globally over these years due to stringent of food safety regulations. Enhancing the access to quality food safely is one of the essential requirements of food supply chain traceability. Conversely, significant percentages of postharvest losses available especially in developing countries due to poor supply chain and logistics practices thereby threatening food security. Unless there is a possibility to trace the Supply chain, it is difficult to take remedial actions. When it comes to Sri Lanka, currently it is harder to have the traceability in most of the foods supply chains commonly on most of the elementary supply chains such as fruits and vegetables. This has led to postharvest losses since it is harder to identify when and where damages occur, who are accountable, harvested and transient times, supply demand mismatch too. Therefore, this paper aims to investigate the feasibility of tracing of fruit and vegetable supply chain in Sri Lanka and contribute theoretically to facilitate authorities and decision makers for future traceability improvement. Availability of secondary information on fruits and vegetables traceability was examined referring to government agencies. Basic structure of supply chain was identified based on secondary data and a case study was conducted based on supply chains linked to Thambuththegama and Keppetipola Dedicated Economic Centers to gather primary data. To quantify the feasibility of tracing, a feasibility index was developed. Developed index was used to assess the feasibility towards improved traceability of selected chains where it can be applied for other food and non-food supply chains as well. The feasibility index can be used for other fruits and vegetables supply chains too to assess the feasibility prior to implementation of a traceability system. Furthermore, it can be used for non-food supply chains with some modifications. Analysis revealed that poor feasibility of wholesalers compared to farmers and retailers. Product identification technologies, awareness and willingness for traceability improvement were ranged low to fair for all the entity categories. Hence, enhancement of record-keeping and information sharing, adopting product identification and quality measurement technologies, and strengthening of legislation were identified as key improvements for enhanced fruits and vegetable traceability and efficient postharvest management of studied supply chains

Transfer learning-based Fashion Image Classification using Hybrid 2D-CNN and ImageNet Neural Network

Many algorithms have been developed as a result of recent advances in machine learning to handle a variety of challenges. In recent years, the most popular transfer learning method has allowed researchers and engineers to run experiments with minimal computing and time resources. To tackle the challenges of classification, product identification, product suggestion, and picture-based search, this research proposed a transfer learning strategy for Fashion image classification based on hybrid 2D-CNN pretrained by VGG-16 and AlexNet. Pre-processing, feature extraction, and classification are the three parts of the proposed system's implementation. We used the Fashion MNIST dataset, which consists of 50,000 fashion photos that have been classified. Training and validation datasets have been separated. In comparison to other conventional methodologies, the suggested transfer learning approach has higher training and validation accuracy and reduced loss. Keywords: Machine Learning, Transfer Learning, Convolutional Neural Network, Image Classification, VGG16, AlexNet, 2D CNN.

Development Of Production-Based Learning Models For Optimizing The Technopreneurship Spirit In Higher Education

Development of production-based learning models carried out to seek validity, practicality and effectiveness in the application of technopreneur courses in universities. Production-based learning model is an alternative to develop students' skills, attitudes and knowledge that are relevant today. Research and development is used to test the validity of experts through Focus Group Discussions (FGD), then limited trials are carried out in the development of this production-based learning model. From the processes carried out, a new syntax development is produced which refers to the previous model syntax. The development of the syntax sequence is (1) an analysis of the curriculum and characteristics of students; (2) Product identification and analysis; (3) Make important questions about the product; (4) Question mapping; (5) analysis of equipment and materials needed for the product to be made; (6) create a business plan (7) product manufacturing process; (8) small-scale operations that include promotion and sales, (9). Summative evaluation; From the stages of the research carried out, the resulting Aiken's V value is 0.812 with a valid category, while the calculation of the Effectiveness value gets the results of 82.22 (effective) and Practicality of 89.33 (very practical). So it can be said that the production-based learning development model has validity, practicality and effectiveness values ​​that meet the requirements, so it is feasible to apply.