A Generalized Convolution with a Weight Function for the Fourier Cosine and Sine Transforms

A generalized convolution with a weight function for the Fourier cosine and sine transforms is introduced. Its properties and applications to solving a system of integral equations are considered

Isolation and production of polyhydroxybutyrate (PHB) from Bacillus pumilus NMG5 strain for bioplastic production and treatment of wastewater from paper factories

Polyhydroxybutyrate (PHB) has the potential to replace traditional plastics and limit environmental pollution caused by plastic waste. This study combined wastewater treatment with PHB production to reduce costs. Bacteria capable of synthesizing PHB were isolated from paper mill wastewater and identified using Matrix Assisted Laser Desorption/Ionization–Time of Flight (MALDI-TOF) mass spectrometry and 16S rRNA gene analysis. Bacillus pumilus NMG5 strain was found to have a good yield in modified Nutrient Broth culture, reaching 42.28% of dry biomass. The PHB product was analyzed using FTIR spectroscopy and 1H NMR spectroscopy. The bacterial strain was also tested for its ability to treat paper mill wastewater, and it showed impressive results in terms of biochemical oxygen demand (COD), total nitrogen, and total phosphorus, with efficiencies of 95.93%, 79.36%, and 83.55%, respectively. The study found that wastewater treatment combined with PHB production was a promising solution to reduce costs and limit environmental pollution. The bacterial strain B. pumilus NMG5 had a high yield of PHB, and the PHB product was of high quality, as confirmed by FTIR and 1H NMR spectroscopy. Furthermore, the bacterial strain showed impressive results in treating paper mill wastewater with high COD, total nitrogen, and total phosphorus efficiencies. These results suggest that this harmless bacterium could be used in paper mill wastewater treatment systems to produce PHB, providing a sustainable and environmentally friendly solution

Few-Shot Object Detection via Synthetic Features with Optimal Transport

Few-shot object detection aims to simultaneously localize and classify the objects in an image with limited training samples. However, most existing few-shot object detection methods focus on extracting the features of a few samples of novel classes that lack diversity. Hence, they may not be sufficient to capture the data distribution. To address that limitation, in this paper, we propose a novel approach in which we train a generator to generate synthetic data for novel classes. Still, directly training a generator on the novel class is not effective due to the lack of novel data. To overcome that issue, we leverage the large-scale dataset of base classes. Our overarching goal is to train a generator that captures the data variations of the base dataset. We then transform the captured variations into novel classes by generating synthetic data with the trained generator. To encourage the generator to capture data variations on base classes, we propose to train the generator with an optimal transport loss that minimizes the optimal transport distance between the distributions of real and synthetic data. Extensive experiments on two benchmark datasets demonstrate that the proposed method outperforms the state of the art. Source code will be available

PRELIMINARY STUDY OF THE ANTIOXIDANT PROPERTIES OF OPHIOCORDYCEPS SOBOLIFERA

The aim of study was to determine preliminary phytochemical analysis and the antioxidant potential of Ophiocordyceps sobolifera. The antioxidant activity of Ophiocordyceps sobolifera was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and total antioxidant activity methods. Phytochemical analyses revealed the presence of steroids, triterpenoids, alkaloids, phenolics, flavoinods, protein, carbohydarte and saponins. The antioxidant activity of the ethanol extracts and water extracts showed high antioxidant activity with the lowest half maximal inhibitory concentration (IC50) values to 0.70 from 0.95mg/mL, realtively. Total antioxidant capacity of the O. sobolifera showed contained from 5.52 ± 0.14 to 12,71 ± 0.23 mg GA/g or from 3.55 ± 0.15 to 7.87 ± .05 μmol AS/g. These data suggest that O. sobolifera is a natural source of antioxidants

The influence of brand equity on consumer responses toward Cho Gao dragon fruits brand

This thesis study wants to implement a model test for better understandings of brand equity and consumer responses toward Cho Gao Dragon Fruit brand. With the rapid growth of agriculture, including domestic consumption and export of the dragon fruits, it is crucial to differentiate the Cho Gao Dragon Fruits to other competitors in both domestic and foreign markets. Using Structural equation modeling (SEM) to analyze the data of 274 questionnaires to investigate the effects of brand equity and its dimensions on consumer responses. The results show that brand equity dimensions such as brand awareness, brand association, perceived quality are interrelated and those dimensions have a direct and significant effect on brand equity, except brand awareness. The results support the assumption that brand equity has a positive relationship with consumer responses. The findings shed light on the current issues of the market for dragon fruits, which enables us to provide some suggestions for the Government to facilitate farmers and traders in building brand names, marketers for doing marketing activities, and students to know about brand equity of agricultural product such as dragon fruits

A Comparative Study of Optical Bistability in Three-Level EIT Configurations

We present a comparative study of optical bistability (OB) in three-level atomic configurations, including $\Lambda$-, cascade-, and V- types under the conditions of electromagnetically induced transparency (EIT). In the steady regime, the input-output intensity relations for the OB in each configuration have been derived in analytical form. The model allows one to construct a clear picture on how the threshold intensity, and other characteristics of the OB are continuously modified with respects to controllable parameters of the laser fields, cooperation parameter, and other physical parameters of atomic system. The results showed that the threshold intensity of OB in $\Lambda$-type system is much less than the other ones and the threshold intensity of OB in V-type system is the largest one. The analytical result is convenient to choose excitation configuration for experimental observations and related applications in photonic devices

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part I: Fundamentals and Enabling Technologies

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce the chances of catching the virus and spreading it across the community. This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In this Part I, we provide a comprehensive background of social distancing including basic concepts, measurements, models, and propose various practical social distancing scenarios. We then discuss enabling wireless technologies which are especially effect- in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. The companion paper Part II surveys other emerging and related technologies, such as machine learning, computer vision, thermal, ultrasound, etc., and discusses open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice

A Comprehensive Survey of Enabling and Emerging Technologies for Social Distancing—Part II: Emerging Technologies and Open Issues

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, and even enforce social distancing practice. In Part I, an extensive background of social distancing is provided, and enabling wireless technologies are thoroughly surveyed. In this Part II, emerging technologies such as machine learning, computer vision, thermal, ultrasound, etc., are introduced. These technologies open many new solutions and directions to deal with problems in social distancing, e.g., symptom prediction, detection and monitoring quarantined people, and contact tracing. Finally, we discuss open issues and challenges (e.g., privacy-preserving, scheduling, and incentive mechanisms) in implementing social distancing in practice. As an example, instead of reacting with ad-hoc responses to COVID-19-like pandemics in the future, smart infrastructures (e.g., next-generation wireless systems like 6G, smart home/building, smart city, intelligent transportation systems) should incorporate a pandemic mode in their standard architectures/designs