Controlled Synthesis of Titania using Water-soluble Titanium Complexes: A Review

The development of human society has led to the increase in energy and resources consumption as well as the arising problems of environmental damage and the toxicity to the human health. The development of novel synthesis method which tolerates utilization of toxic solvents and chemicals would fulfill the demand of the society for safer, softer, and environmental friendly technologies. For the past decades, a remarkable progress has been attained in the development of new water-soluble titanium complexes (WSTC) and their use for the synthesis of nanocrystalline titanium dioxide materials by aqueous solution-based approaches. The progress of synthesis of nanocrystalline titanium dioxide using such WSTCs is reviewed in this work. The key structural features responsible for the successfully controlled synthesis of TiO2 are discussed to provide guidelines for the morphology-controlled synthesis. Finally, this review ends with a summary and some perspectives on the challenges as well as new directions in this fascinating research

A comprehensive study in efficacy of Vietnamese herbal extracts on whiteleg shrimp (<em>Penaeus vannamei</em>) against <em>Vibrio parahaemolyticus</em> causing acute hepatopancreatic necrosis disease (AHPND)

Traditional Vietnamese herbal species were examined for their antimicrobial activity and disease resistance in whiteleg shrimp. In-vitro screening, the extracts of ten herbs were conducted to test the inhibition ability against Vibrio parahaemolyticus, causing acute hepatopancreatic necrosis disease. The results showed that five out of ten herbal species, including Pithecellobium dulce, Melaleuca leucadendron, Eucalyptus globulus, Mimosa pirga, and Hibiscus sabdariffa displayed potent antibacterial activity. Besides, three types of extracts of H. sabdariffa, E. globulus, and M. pirga were coated to the pellet feed at a concentration of 1%. After 30 days of feeding, the whiteleg shrimp (Penaeus vannamei) were challenged by V. parahaemolyticus through immersion. The growth performance (such as growth rate in length and weight, survival rate), hematological parameters of total hemocytes (THC), hyaline hemocytes (HC), and granulocytes (GC), and hepatopancreas recovery under the treatments with herbal extracts of the whiteleg shrimp were significantly enhanced as compared with the control (without herbal extract). The mortality and the bacterial density in the hepatopancreas of shrimp decreased. Specifically, the mortality of shrimp in the treatment supplemented with the methanol extract of H. sabdariffa was the lowest, followed by M. pirga and E. globulus. The experimental results also indicated that H. sabdariffa, E. globulus, and M. pirga could improve immune parameters and disease resistance; therefore, they should be employed in sustainable shrimp, practical farming

post hoc analysis of clarinet phase iii study to investigate the influence of diabetic status on progression free survival pfs of patients with neuroendocrine tumours nets treated with lanreotide lan or placebo pbo

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HierarchyNet : learning to summarize source code with heterogeneous representations

Code representation is important to machine learning models in the code-related applications. Existing code summarization approaches primarily leverage Abstract Syntax Trees (ASTs) and sequential information from source code to generate code summaries while often overlooking the critical consideration of the interplay of dependencies among code elements and code hierarchy. However, effective summarization necessitates a holistic analysis of code snippets from three distinct aspects: lexical, syntactic, and semantic information. In this paper, we propose a novel code summarization approach utilizing Heterogeneous Code Representations (HCRs) and our specially designed HierarchyNet. HCRs adeptly capture essential code features at lexical, syntactic, and semantic levels within a hierarchical structure. HierarchyNet processes each layer of the HCR separately, employing a Heterogeneous Graph Transformer, a Tree-based CNN, and a Transformer Encoder. In addition, HierarchyNet demonstrates superior performance compared to fine-tuned pre-trained models, including CodeT5, and CodeBERT, as well as large language models that employ zero/few-shot settings, such as CodeLlama, StarCoder, and CodeGen. Implementation details can be found at https://github.com/FSoft-AI4Code/HierarchyNet