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This paper studies the common variational inclusion problem in real Hilbert spaces. To solve this problem, we propose a new accelerated approach with two initial parameter steps and establish a strong convergence theorem. Our scheme combines the viscosity approximation method with Tseng's forward backward-forward splitting method and uses self-adaptive step sizes. We simultaneously compute the inertial extrapolation and viscosity approximation at the first step of each iteration. We show that the iterative method converges strongly under conventional and appropriate assumptions. We also study some applications to the common minimum point problems, split feasibility problems, and to the least absolute selection and shrinkage operators (LASSO). Finally, we present two numerical results in Hilbert space and an application to the LASSO problem in order to illustrate the convergence analysis of the considered methods as well as compare our results to the related ones introduced by Cholamjiak et al. (J. Sci. Comput., 88(85), 2021) and Gibali and Thong (Calcolo, 55(49), 2018). [ABSTRACT FROM AUTHOR]

Computer vision has found many applications in automatic wildlife data analytics and biodiversity monitoring. Automating tasks like animal recognition or animal detection usually require machine learning models (e.g., deep neural networks) trained on annotated datasets. However, image datasets built for general purposes fail to capture realistic conditions of ecological studies, and existing datasets collected with camera-traps mainly focus on medium to large-sized animals. There is a lack of annotated small-sized animal datasets in the field. Small-sized animals (e.g., small mammals, frogs, lizards, arthropods) play an important role in ecosystems but are difficult to capture on camera-traps. They also present additional challenges: small animals can be more difficult to identify and blend more easily with their surroundings. To fill this gap, we introduce in this paper a new dataset dedicated to ecological studies of small-sized animals, and provide benchmark results of computer vision-based wildlife monitoring. The novelty of our work lies on SAWIT (small-sized animal wild image dataset), the first real-world dataset of small-sized animals, collected from camera traps and in realistic conditions. Our dataset consists of 34,434 images and is annotated by experts in the field with object-level annotations (bounding boxes) providing 34,820 annotated animals for seven animal categories. The dataset encompasses a wide range of challenging scenarios, such as occlusions, blurriness, and instances where animals blend into the dense vegetation. Based on the dataset, we benchmark two prevailing object detection algorithms: Faster RCNN and YOLO, and their variants. Experimental results show that all the variants of YOLO (version 5) perform similarly, ranging from 59.3% to 62.6% for the overall mean Average Precision (mAP) across all the animal categories. Faster RCNN with ResNet50 and HRNet backbone achieve 61.7% mAP and 58.5% mAP respectively. Through experiments, we indicate challenges and suggest research directions for computer vision-based wildlife monitoring. We provide both the dataset and the animal detection code at https://github.com/dtnguyen0304/sawit. [ABSTRACT FROM AUTHOR]

Carbon sources are considered as critical input for the health and immunity of aquatic animals. The present study investigated the impact of different carbon sources on water quality parameters, carbon to nitrogen (C/N) ratio and microbial community in sediments, and health responses of marron (Cherax cainii) under laboratory conditions. Following one week of acclimation, 120 marron were randomly assigned to 12 experimental tanks. There were four treatments including one untreated control and three groups with carbon addition to maintain a C/N ratio of 12 maintained in culture water. Carbon supplementation groups included corn flour (CBC12), molasses (MBC12) and wheat flour (WBC12). At the end of the 60-day trial, MBC12 resulted in the highest sediment C/N ratio, followed by CBC12. Weight gain and specific growth rate were higher in MBC12, compared to control. The protease activity in marron hepatopancreas, total haemocyte count and lysozyme activity in haemolymph were highest in MBC12. Analysis of 16S rRNA sequence data of tank sediments revealed increased bacterial alpha diversity in MBC12 and WBC12. Proteobacteria was the most abundant phylum in MBC12 (88.6%), followed by control (82.4%) and CBC12 (72.8%). Sphingobium and Novosphingobium were the most abundant genera in control and MBC12 groups, respectively. Higher Aeromonas abundance in CBC12 and Flavobacterium in WBC12 were observed. Overall results indicated that MBC12 led to improved water quality, retaining high C/N ratio and enriched the bacterial populations in sediments resulting in improved growth and immune performance of marron. [ABSTRACT FROM AUTHOR]

This paper studies the multiple-sets split feasibility problem in Hilbert spaces. To solve this problem, we propose a new algorithm and establish a strong convergence theorem for it. Our scheme combines the hybrid projection method with the proximal point algorithm. We show that the iterative method converges strongly under weaker assumptions than the ones used recently by Yao et al. (Optimization 69(2):269–281, 2020). We also study an application to the split feasibility problem and give a strong convergence result to the minimum-norm solution to the problem. Thereafter, some numerical examples are conducted in order to illustrate the convergence analysis of the considered methods as well as compare our results to the related ones introduced by Buong (Numer Algorithms 76:783–798, 2017) and Yao et al. (2020). We end this paper by considering an application of our method to a class of optimal control problems and compare our result with the one introduced by Anh et al. (Acta Math Vietnam 42:413–429, 2017). [ABSTRACT FROM AUTHOR]

Green knowledge sharing and behaviors are vital for organizations to implement green supply chain management and promote green entrepreneurship. These solutions support firms to understand market and customer needs through which they are able to carry out the practices which strengthen their sustainability. By realizing the significance, the research develops a model which integrates the concept of green supply chain management, green entrepreneurship, and sustainable development goals. The framework also builds to evaluate the moderating role of green knowledge sharing and employee green behavior. Proposed hypotheses are tested in the sample Vietnamese textile managers, and PLS-SEM methodology was employed to evaluate the model reliability, validity, and association among constructs. Generated results reveal the positive impact of green supply chain and green entrepreneurship on sustainable environment, and results also reveal that green knowledge sharing and employee green behavior both have the potential of being a moderator which enhances the relationship among outlined constructs. The revelation provides important insights for organizations to look into these parameters in order to achieve sustainability in a longer run. [ABSTRACT FROM AUTHOR]

This document is a retraction note for an article titled "Moderating role of green knowledge sharing and employee green behavior among the relationship of green supply chain management, green entrepreneurship, and sustainable development goal: evidence from Vietnam textile sector." The article has been retracted by the publisher due to concerns about the peer review process, references, and citation behavior. The authors of the article have not responded to correspondence regarding the retraction. Springer Nature, the publisher, remains neutral in regards to jurisdictional claims and institutional affiliations. [Extracted from the article]

Feeding freshwater crayfish species with different diets not only affects the water quality but also induces the abundance of various microbial communities in their digestive tracts. In this context, very limited research has been undertaken to understand the impacts of various protein incorporated aqua-diets on the characteristics of water and its microbial communities. In this study, we have critically analysed the water quality parameters including pH, dissolved oxygen, nitrate, nitrite, ammonia and phosphorus, as well as bacterial communities under marron (Cherax cainii) aquaculture, fed fishmeal (FM) and poultry by-product meal (PBM)-based diets for 60 days. The results unveiled that over the time, feeding has significant impacts on organic waste accumulation, especially ammonia, nitrate, nitrite and phosphate, while no effects were observed on pH and dissolved oxygen. Analysis of 16S rRNA sequence data of water sample indicated significant (P < 0.05) shift of microbial abundance in post-fed FM and PBM water with the evidence of microbial transmission from the gut of marron. Post-fed marron resulted in a significant correlation of Hafnia, Enterobacter, Candidatus Bacilloplasma and Aquitella with the quality and microbial population of water. The results of this study generated valuable knowledge database of microbes-water relationship for better health management practices and production of marron aquaculture fed with FM and PBM diets in under restricted feeding regime with the feeding ratios provided. [ABSTRACT FROM AUTHOR]

PM0.1 has been believed to have adverse short- and long-term effects on human health. However, the information of PM0.1 that is needed to fully evaluate its influence on human health and environment is still scarce in many developing countries. This is a comprehensive study on the levels, chemical compositions, and source apportionment of PM0.1 conducted in Hanoi, Vietnam. Twenty-four-hour samples of PM0.1 were collected during the dry season (November to December 2015) at a mixed site to get the information on mass concentrations and chemical compositions. Multiple linear regression analysis was utilized to investigate the simultaneous influence of meteorological factors on fluctuations in the daily levels of PM0.1. Multiple linear regression models could explain about 50% of the variations of PM0.1 concentrations, in which wind speed is the most important variable. The average concentrations of organic carbon (OC), elemental carbon (EC), water-soluble ions (Ca2+, K+, Mg2+, Na+, NH4+, Cl−, NO3−, SO42−, C2O42−), and elements (Be, Al, V, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Sb, Ba, Tl, Pb, Na, Fe, Mg, K, and Ca) were 2.77 ± 0.90 μg m−3, 0.63 ± 0.28 μg m−3, 0.88 ± 0.39 μg m−3, and 0.05 ± 0.02 μg m−3, accounting for 51.23 ± 9.32%, 11.22 ± 2.10%, 16.28 ± 2.67%, and 1.11 ± 0.94%, respectively. A positive matrix factorization model revealed the contributions of five major sources to the PM0.1 mass including traffic (gasoline and diesel emissions, 46.28%), secondary emissions (31.18%), resident/commerce (12.23%), industry (6.05%), and road/construction (2.92%). [ABSTRACT FROM AUTHOR]

A comprehensive emission inventory (EI) was conducted in Ho Chi Minh City (HCMC), the largest city of Vietnam rapid urbanization rate. In 2017, HCMC had 8.6 million inhabitants with a total of nine millions of private vehicles, 19 manufacturing and industrial zones, 30 industrial clusters, and numerous other factories and enterprises. All those sources could contribute to the high levels of emissions which caused the potentially negative impact on human health and environment. The aims of this study were (i) application bottom-up and top-down approaches to conduct a complete air emission inventory, (ii) development of spatial distribution of air emission, and (iii) estimation of emission forecast for HCMC by 2025 and 2030. A combination of bottom-up and top-down approaches was employed to conduct air pollution EI, in which EMISENS model was utilized to generate the EI for road traffic sources. The results showed that the motorcycles were the main reasons of emission in HCMC, contributing 90% of CO, 68% of non-methane volatile organic compounds (NMVOC), 63% of CH4, 41% of SO2, 29% of NOx, and 18% of patriculate matter (PM2.5). The emission forecasts for HCMC by 2025 and 2030 also were calculated based on the data of strategies and plans for socioeconomic development of HCMC. The results showed that the emissions of pollutants will increase around 30 to 50% by the year 2025 and from 40 to 65% by the year 2030. If the local government does not have any plan for the reduction of emissions (scenario of socioeconomic development as usual), the emissions will increase significantly. [ABSTRACT FROM AUTHOR]

Concentrations of PCDD/Fs, dioxin-like PCBs (dl-PCBs), PeCB and HCB were determined in flue gas, fly ash and bottom ash samples collected from brick production, steel production, and zinc production plants, an industrial waste incinerator and a medical waste incinerator in northern Vietnam to understand the contamination levels, accumulation patterns and extent of emission. Total TEQs concentrations of PCDD/Fs and dl-PCBs in flue gas and ash samples from these industrial plants ranged from 0.304 to 50.55 pg/Nm3 and 1.43 to 440 pg/g, respectively. PeCB and HCB residues in flue gas samples ranged from 0.839 to 46.59 ng/Nm3 and 1.16 to 60.5 ng/Nm3, respectively. The emission factors of 4.8-740 ngTEQs/tonne for PCDD/Fs and dl-PCBs, 67.12-240.7 µg/ton for PeCB and 11.64-889.3 µg/ton for HCB were obtained in flue gas samples. This is among the first reports on the emission factor of PCDD/Fs, dl-PCBs, PeCB, HCB in brick production, zinc production and waste incineration in Vietnam. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present a new iteration method based on the hybrid method in mathematical programming, extragradient method, and Mann's method for finding a common element of the solution set of equilibrium problems, the solution set of variational inequality problems for a monotone, Lipschitz continuous mapping and the set of fixed points for a nonexpansive semigroup in Hilbert spaces. We obtain a strong convergence theorem for the sequences generated by this process. The results in this paper generalize and extend some well-known strong convergence theorems in the literature. [ABSTRACT FROM AUTHOR]