Effect of phosphate fertilizer-coated Dicarboxylic Acid Polymer on rice yield and components under greenhouse conditions

A significant amount of phosphorus (P) becomes fixed by aluminium (Al) and iron (Fe) in acidic soils, leading to decreased efficiency in P utilization and subsequently lowering crop yield. Enhanced P fertilization offers a potential solution, as the dicarboxylic acid polymer (DCAP) coating on P fertilizer promotes increased plant productivity and more effective P utilization. The improvement achieved through enhanced P fertilization can contribute to higher rice yields in acidic soils, accompanied by an increase in P solubility. The study aimed to determine the impact of DCAP-mixed phosphate fertilizer on P uptake by plants, absorption efficiency, and rice yield. The results demonstrated a significant increase in available P (about 3.5 mg P/kg) when DCAP was used in a greenhouse setting, resulting in elevated yields and total P absorption (ranging from 0.03 to 0.05 grams/pot). However, the addition of 60 kg of phosphate mixed with DCAP has not yet demonstrated a significant increase in available phosphorus in the soil compared to adding just 60 kg of phosphate. The application of phosphate at a dose of 30 kg of P2O5 mixed with DCAP for growth and phosphorus absorption yield results equivalent to using 60 kg of P2O5 without DCAP. Furthermore, the use of DCAP in conjuction with 50% P fertilizer increased P availability by the same amount as that achieved with 100% P fertilizer. Consequently, DCAP reduced chemical P fertilizer in the soil by approximately 50%. However, it is essential to evaluate the effectiveness of mixed phosphate fertilizer (DCAP) under field conditions before recommending its widespread use

Gap functions and error bounds for variational-hemivariational inequalities

In this paper we investigate the gap functions and regularized gap functions for a class of variational–hemivariational inequalities of elliptic type. First, based on regularized gap functions introduced by Yamashita and Fukushima, we establish some regularized gap functions for the variational–hemivariational inequalities. Then, the global error bounds for such inequalities in terms of regularized gap functions are derived by using the properties of the Clarke generalized gradient. Finally, an application to a stationary nonsmooth semipermeability problem is given to illustrate our main results

ĐỀ XUẤT ĐIỀU CHỈNH CẤU TRÚC DỮ LIỆU CỦA CƠ SỞ DỮ LIỆU TÀI NGUYÊN, MÔI TRƯỜNG BIỂN VÀ HẢI ĐẢO QUỐC GIA

Recognising the limitations encountered during the operation of the national database of resources, environment of seas and islands, the article proposed to adjust the data structure of this database aiming at easily updating, managing and distributing the existing data as well as new data, improving the quality and reliability of the data but not disturbing the status quo. This adjustment has not only been established in accordance with other maritime countries and international institutions of marine data, but also taken into account the characteristics of the data and the current management model of Vietnam. This proposal aimed at completing national database of resources, environment of seas and islands, making it more dynamic, easily updated and manageable with important, diversified and abundant data sources, in natural resources, marine and island environment of Vietnam, being worthy of a national database. The proposal is the result of the Cooperation Protocol with the United States “Researches on building database, standards, and documentation in the sea of Vietnam” of Vietnam Ocean Data and Information Center (VODIC).Nhìn nhận những hạn chế đang gặp phải trong quá trình vận hành khai thác cơ sở dữ liệu tài nguyên, môi trường biển và hải đảo quốc gia, bài viết đề xuất điều chỉnh cấu trúc dữ liệu cho cơ sở dữ liệu này với mục tiêu dễ dàng cập nhật, quản lý và phân phối các dữ liệu đã có và nhiều dữ liệu mới, nâng cao chất lượng, độ tin cậy của số liệu nhưng không làm xáo trộn hiện trạng. Điều chỉnh này cũng phù hợp với cách làm hiện tại của nhiều quốc gia biển và các tổ chức dữ liệu biển quốc tế, và có tính đến sự đặc thù về dữ liệu và mô hình quản lý hiện tại của Việt Nam. Đề xuất này nhằm hoàn thiện cơ sở dữ liệu tài nguyên, môi trường biển và hải đảo quốc gia có tính năng động hơn, dễ dàng cập nhật quản lý được nhiều nguồn số liệu quan trọng, đa dạng và phong phú về tài nguyên, môi trường biển và hải đảo Việt Nam, xứng tầm của một cơ sở dữ liệu quốc gia. Đề xuất là kết quả nghiên cứu của nhiệm vụ hợp tác theo nghị định thư với Hoa Kỳ, “Nghiên cứu xây dựng cơ sở dữ liệu, chuẩn dữ liệu và tài liệu các vùng biển Việt Nam” của Trung tâm Thông tin, dữ liệu biển và hải đảo

On Throughput for UAV Relay Assisted for Use in Disaster Communications

In this paper, the system performance of an energy harvesting (EH) unmanned aerial vehicle (UAV) system for use in disasters was investigated. The communication protocol was divided into two phases. In the first phase, a UAV relay (UR) harvested energy from a power beacon (PB). In the second phase, a base station (BS) transmitted the signal to the UR using non-orthogonal multiple access (NOMA); then, the UR used its harvested energy from the first phase to transfer the signal to two sensor clusters, i.e., low-priority and high-priority clusters, via the decode-and-forward (DF) technique. A closed-form expression for the throughput of the cluster heads of these clusters was derived to analyze the system performance. Monte Carlo simulations were employed to verify our approach

G-CAME: Gaussian-Class Activation Mapping Explainer for Object Detectors

Nowadays, deep neural networks for object detection in images are very prevalent. However, due to the complexity of these networks, users find it hard to understand why these objects are detected by models. We proposed Gaussian Class Activation Mapping Explainer (G-CAME), which generates a saliency map as the explanation for object detection models. G-CAME can be considered a CAM-based method that uses the activation maps of selected layers combined with the Gaussian kernel to highlight the important regions in the image for the predicted box. Compared with other Region-based methods, G-CAME can transcend time constraints as it takes a very short time to explain an object. We also evaluated our method qualitatively and quantitatively with YOLOX on the MS-COCO 2017 dataset and guided to apply G-CAME into the two-stage Faster-RCNN model.Comment: 10 figure

Secondary Network Throughput Optimization of NOMA Cognitive Radio Networks Under Power and Secure Constraints

Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance

Secondary Network Throughput Optimization of NOMA Cognitive Radio Networks Under Power and Secure Constraints

Recently, the combination of cognitive radio networks with the nonorthogonal multiple access (NOMA) approach has emerged as a viable option for not only improving spectrum usage but also supporting large numbers of wireless communication connections. However, cognitive NOMA networks are unstable and vulnerable because multiple devices operate on the same frequency band. To overcome this drawback, many techniques have been proposed, such as optimal power allocation and interference cancellation. In this paper, we consider an approach by which the secondary transmitter (STx) is able to find the best licensed channel to send its confidential message to the secondary receivers (SRxs) by using the NOMA technique. To combat eavesdroppers and achieve reasonable performance, a power allocation policy that satisfies both the outage probability (OP) constraint of primary users and the security constraint of secondary users is optimized. The closed-form formulas for the OP at the primary base station and the leakage probability for the eavesdropper are obtained with imperfect channel state information. Furthermore, the throughput of the secondary network is analyzed to evaluate the system performance. Based on that, two algorithms (i.e., the continuous genetic algorithm (CGA) for CR NOMA (CGA-CRN) and particle swarm optimization (PSO) for CR NOMA (PSO-CRN)), are applied to optimize the throughput of the secondary network. These optimization algorithms guarantee not only the performance of the primary users but also the security constraints of the secondary users. Finally, simulations are presented to validate our research results and provide insights into how various factors affect system performance

SYNTHESIS OF STARCH MODIFIED MONTMORILLONITE AS AN EFFECTIVE ADSORBENT FOR Pb (II) REMOVAL FROM WATER

The adsorbent is prepared by the montmorillonite co-modification with starch for the removal of Pb (II) ions from aqueous solution. The Fourier-transformed infrared (FTIR), X-ray diffraction (XRD) spectroscopies were used to determine the structure and characteristics of the adsorbent. The main factors affecting the removal of Pb (II) ions were investigated, including the effect of pH, contact time, adsorbent dosage and the initial concentration of Pb (II). Batch process can be used for adsorption and equilibrium studies. The experimental data were fitted using Freundlich and Langmuir adsorption models. The Langmuir isotherm best fitted the experimental data with R2 0.99 and maximum Pb (II) adsorption capacity of 21.5 mg/g indicated monolayer adsorption. Kinetic studies using pseudo-first-order and pseudo-second-order rate models showed that the process complied well with the pseudo second-order rate model

Throughput Optimization for NOMA Energy Harvesting Cognitive Radio with Multi-UAV-Assisted Relaying under Security Constraints

This paper investigates the throughput of a non-orthogonal multiple access (NOMA)-based cognitive radio (CR) system with multiple unmanned aerial vehicle (UAV)-assisted relays under system performance and security constraints. We propose a communication protocol that includes an energy harvesting (EH) phase and multiple communication phases. In the EH phase, the multiple UAV relays (URs) harvest energy from a power beacon. In the first communication phase, a secondary transmitter (ST) uses the collected energy to send confidential signals to the first UR using NOMA. Simultaneously, a ground base station communicates with a primary receiver (PR) under interference from the ST. In the subsequent communication phases, the next URs apply the decode-and-forward technique to transmit the signals. In the last communication phase, the Internet of Things destinations (IDs) receive their signals in the presence of an eavesdropper (EAV). Accordingly, the outage probability of the primary network, the throughput of the secondary network, and the leakage probability at the EAV are analyzed. On this basis, we propose a hybrid search method combining particle swarm optimization (PSO) and continuous genetic algorithm (CGA) to optimize the UR configurations and the NOMA power allocation to maximize the throughput of the secondary network under performance and security constraints

Current medical product development for diagnosis, surgical planning and treatment in the areas of Neurosurgery, Orthopeadic and Dental-Cranio-Maxillofacial surgery in Vietnam

With the population of 86 million and good GDP growth in recent decades, the medical market in Vietnam is growing fast. However, most of the medical technology products are imported, and the number of locally manufactured ones is limited and they do not have the high competition capability in term of quality, quantity and types. In this paper, the current product development in Vietnam for diagnosis, surgical planning and treatment in the areas of Rehabilitation, Neurosurgery, Orthopeadic and Dental-Cranio-Maxillofacial surgery is presented. A roadmap for medical technology development in Vietnam is propose