A novel spectral-efficient resource allocation approach for NOMA-based full-duplex systems

© 2019 IEEE. This paper investigates the coexistence of non- orthogonal multiple access (NOMA) and full-duplex (FD), where the NOMA successive interference cancellation technique is applied simultaneously to both uplink (UL) and downlink (DL) transmissions in the same time-frequency resource block. Specifically, we jointly optimize the user association (UA) and power control to maximize the overall sum rate, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize the UL users' decoding order and the DL users' clustering, which results in a mixed-integer non- convex problem. For solving this problem, we first relax the binary variables to be continuous, and then propose a low-complexity design based on the combination of the inner convex approximation framework and the penalty method. Numerical results show that the proposed algorithm significantly outperforms the conventional FD-based schemes, FD-NOMA and its half-duplex counterpart with random UA

Synthesis of biodegradable and antimicrobial nanocomposite film reinforced for coffee and agri-food product preservation.

The antimicrobial activity of silver nanoparticles is widely known. However, their application to biodegradable polymeric materials is still limited. In this work, we report a strategy involving the green synthesis of nanocomposite films based on a natural biodegradable matrix. Nanometer-sized silver nanoparticles (C-AgNPs) were synthesized with the aid of ultrasound waves between the silver nitrate solution and the nanocurcumin solution. The green synthesized C-AgNPs were found to have particle sizes in the range of 5–25 nm and demonstrated good antimicrobial activity against Clostridium perfringens, Staphylococcus aureus, Bacillus subtilis, Macrophoma theicola, and Aspergillus flavus. Owing to their physical–chemical and mechanical properties and the excellent antimicrobial activities, the obtained AgNPs were used together with chitosan, cassava starch, and poly(vinyl alcohol) (PVA) to make nanocomposite films, which are suitable for the packaging requirements of various key agricultural and food products such as coffee beans, bamboo straws, and fruits. The nanocomposite films lost up to 85% of their weight after being buried in the soil for 120 days. This indicates that the films made with natural biodegradable materials are environmentally friendly

Joint Power Control and User Association for NOMA-Based Full-Duplex Systems

© 1972-2012 IEEE. This paper investigates the coexistence of non-orthogonal multiple access (NOMA) and full-duplex (FD) to improve both spectral efficiency (SE) and user fairness. In such a scenario, NOMA based on the successive interference cancellation technique is simultaneously applied to both uplink (UL) and downlink (DL) transmissions in an FD system. We consider the problem of jointly optimizing user association (UA) and power control to maximize the overall SE, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize UL users' decoding order and DL users' clustering, which results in a mixed-integer non-convex problem. For practically appealing applications, we first relax the binary variables and then propose two low-complexity designs. In the first design, the continuous relaxation problem is solved using the inner convex approximation framework. Next, we additionally introduce the penalty method to further accelerate the performance of the former design. For a benchmark, we develop an optimal solution based on brute-force search (BFS) over all possible cases of UAs. It is demonstrated in numerical results that the proposed algorithms outperform the conventional FD-based schemes and its half-duplex counterpart, as well as yield data rates close to those obtained by BFS-based algorithm

Artificial intelligence-based solutions for coffee leaf disease classification

Coffee is one of the most widely consumed beverages and the quantity and quality of coffee beans depend significantly on the health and condition of coffee plants, particularly their leaves. The automation of coffee leaf disease classification using AI is an essential need, providing not only economic benefits but also contributing to environmental conservation and creating better conditions for sustainable coffee cultivation. Through the application of AI, early disease detection is facilitated, thereby reducing pest and disease control costs, minimizing crop losses, increasing coffee productivity and product quality, and promoting environmental preservation. Many studies have proposed AI algorithms for coffee disease classification. However, numerous algorithms employ classical algorithms, while some utilize deep learning, the current state-of-the-art in computer vision. The challenge lies in the fact that when using deep learning, a substantial amount of data is required for training. The design of deep learning architectures to enhance model accuracy while still working with a small training dataset remains an area of ongoing research. In this study, we propose deep learning-based method for coffee leaf disease classification. We propose the combination of different deep convolutional neural networks to further improve overall classification performance. Early and late fusion have been conducted to evaluate the effectiveness of the pre-trained model. Our experimental results demonstrate that the ensemble method outperforms single-model approaches, achieving high accuracy and precision in BRACOL coffee disease leaf

Environmentally Responsible Bioengineering for Spore Surface Expression of <em>Helicobacter pylori </em>Antigen

The development of genetic technologies and bioengineering are creating an increasing number of genetically engineered microorganisms with new traits for diverse industrial applications such as vaccines, drugs and pollutant degraders. However, the destiny of genetically engineered bacterial spores released into the environment as long-life organisms has remained a big environmental challenge. In this study, an environmentally responsible and sustainable gene technology solution based on the concept of thymine starvation is successfully applied for cloning and expression of a Helicobacter pylori antigen on Bacillus subtilis spore surface. As an example, a recombinant Bacillus subtilis strain A1.13 has been created from a gene fusion of the corresponding N-terminal fragment of spore coat protein CotB in B. subtilis and the entire urease subunit A (UreA) in H. pylori and the fusion showed a high stability of spore surface expression. The outcomes can open the door for developing highly safe spore vectored vaccines against this kind of pathogen and contributing to reduced potential risks of genetically engineered microorganisms released in the environment

Characteristics and mechanisms of cadmium adsorption onto biogenic aragonite shells-derived biosorbent: Batch and column studies

© 2018 Elsevier Ltd Calcium carbonate (CaCO3)-enriched biomaterial derived from freshwater mussel shells (FMS) was used as a non-porous biosorbent to explore the characteristics and mechanisms of cadmium adsorption in aqueous solution. The adsorption mechanism was proposed by comparing the FMS properties before and after adsorption alongside various adsorption studies. The FMS biosorbent was characterized using nitrogen adsorption/desorption isotherm, X-ray diffraction, scanning electron microscopy with energy dispersive spectroscopy, Fourier-transform infrared spectroscopy, and point of zero charge. The results of batch experiments indicated that FMS possessed an excellent affinity to Cd(II) ions within solutions pH higher than 4.0. An increase in ionic strength resulted in a significant decrease in the amount of Cd(II) adsorbed onto FMS. Kinetic study demonstrated that the adsorption process quickly reached equilibrium at approximately 60 min. The FMS biosorbent exhibited the Langmuir maximum adsorption capacity as follows: 18.2 mg/g at 10 °C Cd2+ > Cu2+ > Cr3+ > Zn2+. For column experiments, the highest Thomas adsorption capacity (7.86 mg/g) was achieved at a flow rate (9 mL/min), initial Cd(II) concentration (10 mg/L), and bed height (5 cm). The Cd(II) removal by FMS was regarded as non-activated chemisorption that occurred very rapidly (even at a low temperature) with a low magnitude of activation energy. Primary adsorption mechanism was surface precipitation. Cadmium precipitated in the primary (Cd,Ca)CO3 form with a calcite-type structure on the FMS surface. A crust of rhombohedral crystals on the substrate was observed by SEM. Freshwater mussel shells have the potential as a renewable adsorbent to remove cadmium from water

Digital and circular technologies for climate-smart and sustainable agriculture: The case of Vietnamese coffee

\ua9 Published under licence by IOP Publishing Ltd.This comprehensive article addresses the pressing challenges confronting the global agriculture, primarily driven by climate change and resource constraints. With a focus on promoting climate-smart and sustainable agricultural practices, the study explores the transformative potential of emerging technologies, e.g., the innovative use of digital technologies like Internet of Things, Artificial Intelligence, and Blockchain, showcasing real-world examples of their benefits, and circular technologies, e.g., waste-to-value practices. The challenges of population growth, climate change, environmental impact, and the plight of smallholder farmers are elucidated. Climate-Smart Agriculture initiatives supported by the World Bank Group demonstrate practical efforts in addressing these challenges, aligning with sustainable development goals. Here, we introduce an innovative and smart agriculture (INNSA) platform for the creation and operation of sustainable coffee value chain in Vietnam as a case of study. Thought-provoking questions for future research conclude the review, encouraging interdisciplinary collaboration. In summary, this article provides a compelling case for adopting sustainable agricultural practices through digital and circular technologies, offering a roadmap for global agriculture\u27s transformation and resilience in the face of climate change

Prophylactic immunization to <em>Helicobacter pylori</em> infection using spore vectored vaccines

BackgroundHelicobacter pylori infection remains a major public health threat leading to gastrointestinal illness and increased risk of gastric cancer. Mostly affecting populations in developing countries no vaccines are yet available and the disease is controlled by antimicrobials which, in turn, are driving the emergence of AMR.Materials and MethodsWe have engineered spores of Bacillus subtilis to display putative H. pylori protective antigens, urease subunit A (UreA) and subunit B (UreB) on the spore surface. Following oral dosing of mice with these spores, we evaluated immunity and colonization in animals challenged with H. pylori.ResultsOral immunization with spores expressing either UreA or UreB showed antigen-specific mucosal responses (fecal sIgA) including seroconversion and hyperimmunity. Following challenge, colonization by H. pylori was significantly reduced by up to 1-log.ConclusionsThis study demonstrates the utility of bacterial spores for mucosal vaccination to H. pylori infection. The heat stability and robustness of Bacillus spores coupled with their existing use as probiotics make them an attractive solution for either protection against H. pylori infection or potentially for therapy and control of active infection

Genomic and vaccine preclinical studies reveal a novel mouse-adapted Helicobacter pylori model for the hpEastAsia genotype in Southeast Asia

\ua9 2024 Crown Copyright.Introduction. Helicobacter pylori infection is a major global health concern, linked to the development of various gastrointestinal diseases, including gastric cancer. To study the pathogenesis of H. pylori and develop effective intervention strategies, appropriate animal pathogen models that closely mimic human infection are essential. Gap statement. This study focuses on the understudied hpEastAsia genotype in Southeast Asia, a region marked by a high H. pylori infection rate. No mouse-adapted model strains has been reported previously. Moreover, it recognizes the urgent requirement for vaccines in developing countries, where overuse of antimicrobials is fuelling the emergence of resistance. Aim. This study aims to establish a novel mouse-adapted H. pylori model specific to the hpEastAsia genotype prevalent in Southeast Asia, focusing on comparative genomic and histopathological analysis of pathogens coupled with vaccine preclinical studies. Methodology. We collected and sequenced the whole genome of clinical strains of H. pylori from infected patients in Vietnam and performed comparative genomic analyses of H. pylori strains in Southeast Asia. In parallel, we conducted preclinical studies to assess the pathogenicity of the mouse-adapted H. pylori strain and the protective effect of a new spore-vectored vaccine candidate on male Mlac:ICR mice and the host immune response in a female C57BL/6 mouse model. Results. Genome sequencing and comparison revealed unique and common genetic signatures, antimicrobial resistance genes and virulence factors in strains HP22 and HP34; and supported clarithromycin-resistant HP34 as a representation of the hpEastAsia genotype in Vietnam and Southeast Asia. HP34-infected mice exhibited gastric inflammation, epithelial erosion and dysplastic changes that closely resembled the pathology observed in human H. pylori infection. Furthermore, comprehensive immunological characterization demonstrated a robust host immune response, including both mucosal and systemic immune responses. Oral vaccination with candidate vaccine formulations elicited a significant reduction in bacterial colonization in the model. Conclusion. Our findings demonstrate the successful development of a novel mouse-adapted H. pylori model for the hpEastAsia genotype in Vietnam and Southeast Asia. Our research highlights the distinctive genotype and pathogenicity of clinical H. pylori strains in the region, laying the foundation for targeted interventions to address this global health burden

Design and fabrication of effective gradient temperature sensor array based on bilayer SnO2/Pt for gas classification

Classification of different gases is important, and it is possible to use different gas sensors for this purpose. Electronic noses, for example, combine separated gas sensors into an array for detecting different gases. However, the use of separated sensors in an array suffers from being bulky, high-energy consumption and complex fabrication processes. Generally, gas sensing properties, including gas selectivity, of semiconductor gas sensors are strongly dependent on their working temperature. It is therefore feasible to use a single device composed of identical sensors arranged in a temperature gradient for classification of multiple gases. Herein, we introduce a design for simple fabrication of gas sensor array based on bilayer Pt/SnO2 for real-time monitoring and classification of multiple gases. The study includes design simulation of the sensor array to find an effective gradient temperature, fabrication of the sensors and test of their performance. The array, composed of five sensors, was fabricated on a glass substrate without the need of backside etching to reduce heat loss. A SnO2 thin film sensitized with Pt on top deposited by sputtering was used as sensing material. The sensor array was tested against different gases including ethanol, methanol, isopropanol, acetone, ammonia, and hydrogen. Radar plots and principal component analysis were used to visualize the distinction of the tested gases and to enable effective classification