Hexa-aryl/alkylsubstituted Cyclopropanes

A series of penta-aryl/alkyl-1-(toluene-4-sulfonyl)-4,5-dihydro-1H-pyrazole 5a-c was synthesized by addition of methyllithium or phenylllithium followed by trapping the nitrogen anion intermediate with tosyl-fluoride to cyclic azines 2a,b. Addition of methyllithium or phenyllithium to 5a-c generated a series of hexa-aryl/alkylsubstituted-4,5-dihydro-3H-pyrazoles 6a-c. Neat thermolysis of hexa-aryl/alkylsubstituted-4,5-dihydro-3H-pyrazoles 6a-c at 200◦C produced hexa-aryl/alkylsubstituted cyclopropanes 7a-c in high yield

COVALENT CONJUGATION OF ANTIBODY AND GOLD NANOPARTICLE FOR DEVELOPMENT OF LATERAL FLOW IMMUNOASSAY TEST STRIP

Nanotechnology is one of the fastest growing technologies in this era. Gold nanoparticle (AuNP) based immunoassays have been performed on the basis of antigen-antibody interaction using AuNP antibody conjugates. Lateral flow immunoassays(LFA) which are also based on AuNP antibody conjugates are useful innovation in nanotechnology and widely applied in medicine and research fields. However, there are some limitations of the present LFA kits such as sensitivity and stability. In the study, we showed the result of covalent conjugation of anti-rotavirus antibody and AuNP for generating a lateral flow immunoassay strip to detect rotavirus in fecal samples. The suitable conditions for coating polyethylene glycol (PEG) on the surface of AuNP were 10.0 mM PEG for 3 hours at room temperature (25 oC). Optimized conditions for covalent conjugation of antibody and AuNP were pH 4.0, 0.1 mg antibody/conjugate, 0.01 mM reactant EDC/NHS [1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride/(N-hydroxy sulfosuccinimide]. The coupling reaction was carried out at room temperature for 90 min. The conjugate pad, antibody immobilized nitrocellulose membrane strip were created with investigated conditions for generating an LFA test strip. The limit of detection of LFA test strip was determined by 1.6 × 105 virus particles/ml, three times lower than that of Rotaclone kit (UK). The generated strip could be used to detect rotavirus in fecal sample of patient.

Applications of 2,3-Diketoesters in Organic Synthesis and Stereoselective Transformations

Dimethyldioxyrane oxidation of δ-hydroxy-α-diazo-β-ketoesters that are prepared by zinc triflate catalyzed Mukaiyama-aldol condensation of methyl diazoacetoacetates with aldehydes, occurred in quantitative yield to form dihydrofuranols that undergo acid catalyzed dehydration under mild conditions to generate 3-methoxyfuran-2-carboxylates in good yield. Oxidation of ζ-keto-α-diazo-β-ketoesters that are formed by zinc triflate catalyzed Mukaiyama-Michael condensation of methyl diazoacetoacetate enones procduced their 2,3,7-diketoester derivative in quantitative yield. The intramolecular acid catalyzed aldol cyclization of 2,3,7-triketoesters provides highly functionalized cyclopentanones with good diastereoselectivity in high overall yields via kinetically controlled and stereodivergent catalytic processes. Lewis acid catalysis gives high selectivity for the 1,3-anti tetrasubstituted cyclopentanones, whereas Brønsted acid catalysis produces the corresponding 1,3-syn diastereomer. The first enantioselective transformation of 2,3-diketoesters was demonstrated in carbonyl-ene reactions catalyzed by [Cu((S,S)-tert-Bu-box)](SbF6)2 generating chiral α-functionalized-α-hydroxy-β-ketoesters in up to 94% yield and 97% ee. The suggested mode of activation is bi-dentate coordination between copper and the oxygen atoms of the two keto-carbonyl groups. The 2,3-diketoesters are conveniently accessed from the corresponding α-diazo-β-ketoester, and catalyst loading as low as 1.0 mol % is achieved

Unsupervised Detection of Anomalous Sound for Machine Condition Monitoring using Fully Connected U-Net

Anomaly detection in the sound from machines is an important task in machine monitoring. An autoencoder architecture based on the reconstruction error using a log-Mel spectrogram feature is a conventional approach for this domain. However, because of the non-stationary nature of some sounds from the target machine, such a conventional approach does not perform well in those circumstances. In this paper, we propose a novel approach regarding the choice of used features and a new auto-encoder architecture. We created the Mixed Feature, which is a mixture of different sound representations, and a new deep learning method called Fully-Connected U-Net, a form of autoencoder architecture. With experiments on the same dataset as the baseline system, using the same architecture for all types of machines, the experimental results showed that our methods outperformed the baseline system in terms of the AUC and pAUC evaluation metrics. The optimized model achieved 83.38% AUC and 64.51% pAUC on average overall machine types on the developed dataset and outperformed the published baseline by 13.43% AUC and 8.13% pAUC

Natural frequencies and critical loads of functionally graded single span beams resting on winkler’s elastic foundation

Natural frequencies and critical loads of functionally graded single span beams resting on Winkler’s elastic foundation with general boundary conditions are presented in this paper. The analytical model of the beam is described by using the first order shear deformation theory, however, the transverse shear stress is derived from expression of the normal stress and equilibrium equation and thus, its shear correction factor is then obtained analytically. The effective material properties of the beam are assumed to follow simple power law form. The governing equation of motion of the beam is derived based on Lagrange’s equations with specific boundary conditions satisfied with the Lagrange’s multipliers. Comparisons between the results of present study with available results in the literature show a good agreement. In addition, parametric analysis is carried out, including material distribution, boundary conditions and axial load as well as foundation factor and slenderness ratio

Organisational Baseline Study: Overview report for Tra Hat CSV, Vietnam (VN03)

This report covers the Organisational Baseline Study (OBS) for the CCAFS Climate-Smart Village Tra Hat in the South Viet Nam. During October 2014 interviews were conducted with local stakeholders at ten organisations who are working or collaborating with farmers and/or the community in Vinh Loi district, Bac Lieu province. The Tra Hat CSV is located near the coastal area, at tail end of a primary canal of Quan Lo Phung Hiep system (QLPH), the Mekong Delta of Vietnam, it usually causes lack of fresh water in from QLPH in dry season. There are two distinct dry season (December to April) and rainy season (May to November) which typhoon happens seldom in rainy season. Protected by dyke and sluice system of QLPH in Bac Lieu province, Tra Hat has not been affected by saline intrusion for last 15 years. The main farming systems in the village comprise two or three rice crops per year, small livestock as pig, chicken and ducks. Besides, mixed fruit garden and cash crop are often blended in residential area. Ground water and water in ponds is popular in household to provide domestic water, raising fish or garden irrigation and livestock, especially in dry season. The objectives of the OBS study are to: Provide indicators to monitor changes in behaviours and practices of locally relevant organisations that have climate change related activities in Bac Lieu over time Understand the provision of information/services at the local level that informs farmers’ decision making about their livelihood strategies in response to climate change This OBS report also supplements to the quantitative Household Baseline Survey (HBS) and the qualitative Village Baseline Studies (VBS) in Tra Hat CSV and surrounding villages

A Novel Explainable Artificial Intelligence Model in Image Classification problem

In recent years, artificial intelligence is increasingly being applied widely in many different fields and has a profound and direct impact on human life. Following this is the need to understand the principles of the model making predictions. Since most of the current high-precision models are black boxes, neither the AI scientist nor the end-user deeply understands what's going on inside these models. Therefore, many algorithms are studied for the purpose of explaining AI models, especially those in the problem of image classification in the field of computer vision such as LIME, CAM, GradCAM. However, these algorithms still have limitations such as LIME's long execution time and CAM's confusing interpretation of concreteness and clarity. Therefore, in this paper, we propose a new method called Segmentation - Class Activation Mapping (SeCAM) that combines the advantages of these algorithms above, while at the same time overcoming their disadvantages. We tested this algorithm with various models, including ResNet50, Inception-v3, VGG16 from ImageNet Large Scale Visual Recognition Challenge (ILSVRC) data set. Outstanding results when the algorithm has met all the requirements for a specific explanation in a remarkably concise time.Comment: Published in the Proceedings of FAIC 202

Sound-Dr: Reliable Sound Dataset and Baseline Artificial Intelligence System for Respiratory Illnesses

As the burden of respiratory diseases continues to fall on society worldwide, this paper proposes a high-quality and reliable dataset of human sounds for studying respiratory illnesses, including pneumonia and COVID-19. It consists of coughing, mouth breathing, and nose breathing sounds together with metadata on related clinical characteristics. We also develop a proof-of-concept system for establishing baselines and benchmarking against multiple datasets, such as Coswara and COUGHVID. Our comprehensive experiments show that the Sound-Dr dataset has richer features, better performance, and is more robust to dataset shifts in various machine learning tasks. It is promising for a wide range of real-time applications on mobile devices. The proposed dataset and system will serve as practical tools to support healthcare professionals in diagnosing respiratory disorders. The dataset and code are publicly available here: https://github.com/ReML-AI/Sound-Dr/.Comment: 9 pages, PHMAP2023, PH

EXTRACTION AND PROPERTY STUDIES OF COENZYME Q10 FROM RECOMBINANT AGROBACTERIUM TUMEFACIENS

In this report, some results of extraction and characterization of CoQ10 from recombinant A. tumefaciens are presented. Four different cell breaking methods (sonication, acidic treatment, ethanol treatment, and enzymatic lysis) in combination with the extracting steps were carried out to extract CoQ10 and the results showed that ethanol treatment was the most efficient method. Appropriate conditions for CoQ10 extraction were 25 oC, 24 hours incubation and ethanol solvent/biomass ratio of 10:1 (ml/g). Characterization of extracted CoQ10 showed that CoQ10 was sensitive to light, but stable in the temperature ranges of 4 – 60 oC and the pH range of 6.0 – 9.0. Obtained results in present study should be applied in the large scale for CoQ10 extraction, providing the CoQ10 product for testing production of functional foods

Willingness to adopt improved shrimp aquaculture practices in Vietnam

The shrimp industry plays a leading role in aquaculture development in Vietnam. Currently, the government is running a credit subsidy program to support farmers investing in improved production methods. This paper aimed to investigate white-legged shrimp farmers’ willingness to invest in improved production methods and to examine whether the current government policy for the sector is in line with farmers’ preferences using a discrete choice experiment. The results show that farmers do not care about the environmental impacts but emphasize increased yields and more successful crops as the main drivers of their willingness to invest. There is a mismatch between the current subsidized interest rate and farmers’ required interest rate. These findings suggest that to promote better investment in improved production methods, the government should focus on the regulatory framework, monitoring and control of environmental impacts, and reevaluate the size of the credit subsidy.acceptedVersio