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Unmanned surface pursuit is a complex and challenging engineering problem, especially when conducted by multiple intelligent surface vehicles (ISVs). To enhance the pursuit performance and facilitate strategic interaction during the target pursuit, this paper proposes a novel game theory-based maneuver planning method for pursuit ISVs. Firstly, a specific two-player zero-sum pursuit–evasion game (ZSPEG)-based target-pursuit model is formed. To ensure the vehicles reach a quick consensus, a target-guided relay-pursuit mechanism and the corresponding pursuit payoffs are designed. Meanwhile, under the fictitious play framework, the behavioral pattern and the strategies of the target could be fictitiously learned. Furthermore, mixed-strategy Nash equilibrium (MNE) is employed to determine the motions for the vehicles, the value of which is the best response in the proposed ZSPEG model. Finally, simulations verify the effectiveness of the above methods in multi-ISV surface pursuit.

With the development of image processing technology and video analysis technology, forest fire monitoring technology based on video recognition is more and more important in the field of forest fire prevention and control. The objects currently applied to forest fire video image monitoring system monitoring are mainly flames and smoke. This paper proposes a forest fire risk monitoring and early warning algorithm, which integrates a deep learning model, infrared monitoring and early warning, and forest fire weather index. The algorithm first obtains the current visible image and infrared image of the same forest area, utilizing a smoke detection model based on deep learning to detect smoke in the visible image, and obtains the confidence level of the occurrence of fire in said visible image. Then, it determines whether the local temperature value of said infrared image exceeds a preset warning value, and obtains a judgment result based on the infrared image. It calculates again a current FWI based on environmental data, and determines a current fire danger level based on the current FWI. Finally, it determines whether or not to carry out a fire warning based on said fire danger level, said confidence level of the occurrence of fire in said visible image, and said judgment result based on the infrared image. The experimental results show that the accuracy of the algorithm in this paper reaches 94.12%, precision is 96.1%, recall is 93.67, and F1-score is 94.87. The algorithm in this paper can improve the accuracy of smoke identification at the early stage of forest fire danger occurrence, especially by excluding the interference caused by clouds, fog, dust, and so on, thus improving the fire danger warning accuracy.

Plasmonic photocatalytic nanocomposites of TiO2 and Au nanoparticles (NPs) have recently attracted the attention of researchers, who aim to improve the photocatalytic activity of potential TiO2 NPs. In this study, we report photocatalytic activity enhancement for a Au/TiO2 nanocomposite prepared by the plasma–liquid interaction method using an atmospheric microplasma apparatus. The enhanced photocatalytic activity of the prepared Au/TiO2 is demonstrated by the degradation of methylene blue (MB) in water under both ultraviolet (UV) and visible light irradiation. The prior treatment of TiO2 with microplasma in a NH3 and H2O2 solution is found to strongly improve the photocatalytic activity of both the treated TiO2 NPs, as well as the synthesized Au/TiO2 nanocomposite.

Current research on the photocatalytic activity of TiO2 mainly focuses on its nano- or micro-particle forms, which are difficult to recycle and apply in real engineering applications. This study aims to apply a small pilot of TiO2 in the ceramic form to remove carbamazepine (CBZ) from an aqueous solution under simulated sunlight. A high removal efficiency up to >99% was shown in a 5 mg L−1 CBZ solution after 6 h of irradiation with a total energy of 150.92 kJ. The kinetic degradation was not affected in an alkaline solution (at pH 7, pH 10, and pH 13) but was faster under acidic conditions (pH 2) in which CBZ existed in the protonated form. The presence of NO3− (10–50 mg L−1) slightly affected the photodegradation of CBZ while humic acid significantly reduced the photocatalytic activity. In addition, the presence of major ions in water also had a negative effect at concentrations between 10 and 50 mg L−1. The MS/MS was used to identify the transformation products of CBZ, and a possible degradation mechanism was proposed. The toxicity of CBZ and the by-products was primarily evaluated. The results showed that TiO2 ceramics show high reusability and stability with a photocatalytic performance of >95% and a mass loss of

Yeast Saccharomyces cerevisiae may be regarded as a cost-effective and environmentally friendly biosorbent for complex effluent treatment. The effect of pH, contact time, temperature, and silver concentration on metal removal from silver-containing synthetic effluents using Saccharomyces cerevisiae was examined. The biosorbent before and after biosorption process was analysed using Fourier-transform infrared spectroscopy, scanning electron microscopy, and neutron activation analysis. Maximum removal of silver ions, which constituted 94–99%, was attained at the pH 3.0, contact time 60 min, and temperature 20 °C. High removal of copper, zinc, and nickel ions (63–100%) was obtained at pH 3.0–6.0. The equilibrium results were described using Langmuir and Freundlich isotherm, while pseudo-first-order and pseudo-second-order models were applied to explain the kinetics of the biosorption. The Langmuir isotherm model and the pseudo-second-order model fitted better experimental data with maximum adsorption capacity in the range of 43.6–108 mg/g. The negative Gibbs energy values pointed at the feasibility and spontaneous character of the biosorption process. The possible mechanisms of metal ions removal were discussed. Saccharomyces cerevisiae have all necessary characteristics to be applied to the development of the technology of silver-containing effluents treatment.

5E-based science, technology, engineering, and mathematics (5E-STEM) education is known to be one of the most used pedagogical models in STEM-oriented science courses for middle school students. However, the 5E model lacks a clear explanation of how STEM subjects are strongly linked in each of its operational “E”. In this study, a novel approach was proposed with the use of the argumentation-supported 5E-STEM (A-5E-STEM) model in the science curriculum. The purpose of this study was to examine the differences in learning achievements, learning motivation, learning interest, and higher-order thinking skills of middle school students between teaching science using A-5E-STEM, 5E-STEM, and conventional didactic methods. A semi-experimental study with post-test only non-equivalent groups design was used. A “Separating Mixtures” unit in the 6th grade Natural Science curriculum was designed with A-5E-STEM and 5E-STEM model orientation. The participants were three 6th grade classes with a total of one hundred and twenty students at a public middle school in Hanoi City, Vietnam. The first experimental group was taught science using the A-5E-STEM model, the second experimental group was taught science using the 5E-STEM model, and a control group was taught the science unit with conventional didactic methods. A post-test was used to collect data on learning achievement, and questionnaires were used to collect data on learning motivation, interest, and higher-order thinking skills of middle school students in the science curriculum. The findings showed that the effect of teaching science using the A-5E-STEM model on learning achievement, motivation, interest, and higher-order thinking skills of middle school students was significantly superior to that of the 5E-STEM model and conventional didactic methods. Therefore, science teachers are expected to increase the use of the A-5E-STEM model in their related curriculum.

The paper considers the new effects of the nanoscale state of matter, which open up prospects for the development of electronic devices using new physical principles. The contacts of chemically homogeneous nanoparticles of yttrium-stabilized zirconium oxide (ZrO2—x mol% Y2O3, x = 0, 3, 4, 8; YSZ) with different sizes of 7.5 nm and 9 nm; 7.5 nm and 11 nm; and 7.5 nm and 14 nm, respectively, was studied on direct current using nanostructured objects in the form of compacts obtained by high-hydrostatic pressure (HP-compacts of 300MPa). A unique size effect of the nonlinear (rectifying-type contact) dependence of the electrical properties (in the region U < 2.5 V, I ≤ 2.7 mA) of the contact of different-sized YSZ nanoparticles of the same chemical composition is revealed, which indicates the possibility of creating semiconductor structures of a new type (homogeneous electronics). The electronic structure of the near-surface regions of nanoparticles of studied oxide materials and the possibility of obtaining specifically rectifying properties of the contacts were studied theoretically. Models of surface states of the Tamm-type are constructed considering the Coulomb long-range action. The discovered energy variance and its dependence on the curvature of the surface of nanoparticles made it possible to study the conditions for the formation of a contact potential difference in cases of nanoparticles of the same radius (synergistic effect), different radii (doped and undoped variants), as well as to discover the possibility of describing a group of powder particles within the Anderson model. The determined effect makes it possible to solve the problem of diffusion instability of semiconductor heterojunctions and opens up prospects for creating electronic devices with a fundamentally new level of properties for use in various fields of the economy and breakthrough critical technologies.

This article presents a review of many types of SERS sensors for food safety and environmental pollution monitoring based on detecting rhodamine. It introduces the basic concepts of substrates, enhancement factors, and mechanisms, devices’ sensors integrated with the microstructure. Here, we review the state-of-the-art research in the field of rhodamine monitoring and highlight the applications of SERS sensors. The trends in the development of substrates for different applications have been mentioned with the aim of providing an overview of the development of different SERS substrates. Thus, an efficient approach for rhodamine detection has a good perspective for application in environmental monitoring.

In our review, we have presented a summary of the research accomplishments of nanostructured multimetal-based electrocatalysts synthesized by modified polyol methods, especially the special case of Pt-based nanoparticles associated with increasing potential applications for batteries, capacitors, and fuel cells. To address the problems raised in serious environmental pollution, disease, health, and energy shortages, we discuss and present an improved polyol process used to synthesize nanoparticles from Pt metal to Pt-based bimetal, and Pt-based multimetal catalysts in the various forms of alloy and shell core nanostructures by practical experience, experimental skills, and the evidences from the designed polyol processes. In their prospects, there are the micro/nanostructured variants of hybrid Pt/nanomaterials, typically such as Pt/ABO3-type perovskite, Pt/AB2O4-type ferrite, Pt/CoFe2O4, Pt/oxide, or Pt/ceramic by modified polyol processes for the development of electrocatalysis and energy technology. In the future, we suggest that both the polyol and the sol-gel processes of diversity and originality, and with the use of various kinds of water, alcohols, polyols, other solvents, reducing agents, long-term capping and stabilizing agents, and structure- and property-controlling agents, are very effectively used in the controlled synthesis of micro/nanoparticles and micro/nanomaterials. It is understood that at the levels of controlling and modifying molecules, ions, atoms, and nano/microscales, the polyol or sol-gel processes, and their technologies are effectively combined in bottom-up and top-down approaches, as are the simplest synthetic methods of physics, chemistry, and biology from the most common aqueous solutions as well as possible experimental conditions.

Monofloral honey samples (Coffea robusta) from Vietnam were determined for their chemical compositions. This is the first report on the chemical composition and antioxidant activity of coffee honey from Vietnam. These samples were characterized by their high contents of total and reducing sugars, total phenolic contents, and total flavonoid contents. The contents of seven phenolic acids (PAs) were quantified by high performance liquid chromatography (HPLC) and analyzed with the assistance of principle component analysis (PCA) to differentiate the honey samples into groups. The hydroxymethylfurfural (HMF) (0.048–2.933 mg/kg) and free acid contents (20.326–31.163 meq/kg) of coffee honey were lower in Nepal, which reflected the freshness of the honey when conducting this survey. The coffee honey had total sugar and reducing sugar contents 831.711 g/kg and 697.903 g/kg, respectively. The high level of total phenolic (0.642 mg GAE/g) and flavonoid (0.0341 mg GE/g) contents of coffee honey contributed to their antioxidant activity of this honey sample. Among the coffee honey tested, the IC50 of DPPH radical-scavenging activities value was 1.134–17.031 mg/mL, while the IC50 of ABTS radical-scavenging activities value was 115.381–213.769 mg/mL. The phenolic acids composition analysis displayed that gallic acid appeared in high concentrations in all studied honey samples, ranging from 0.037–1.015 mg/kg, and ferulic acid content ranged from 0.193 to 0.276 mg/kg. The content of trigonelline and caffeine in coffee honey samples ranged from 0.314–2.399 mg/kg and 8.946–37.977 mg/kg. The data in this article highlight the relevance of coffee honey as a healthy substance.

We successfully prepared Au nanoparticles using the modified polyol methods and design of experiments. The desirable crystal structure and particle size of Au nanoparticles with various kinds of polyhedral and spherical shapes as well as various kinds of their morphologies or complete and rough spherical crystal surfaces were experimentally predicted in TEM and XRD measurements according to the theoretical calculation and data. The fine crystal formation of Au nanostructures by modified polyol methods with EG, PVP, and NaBH4 is of great importance to their practical applications. Our research shows that the critical nucleation, growth, and formation of sizes, shapes, and morphologies of Au nanoparticles were experimentally discussed in modified polyol methods and design of experiments. In this context, our particle size calculation can hold the greatest attraction for researchers in the field of nanoparticles.

As marine plastic pollution threatens the marine ecosystem seriously, the government needs to find an effective way to clean marine plastics. Due to the advantages of easy operation and high efficiency, autonomous underwater vehicles (AUVs) have been applied to clean marine plastics. As for the large-scale marine environment, the marine plastic cleaning task needs to be accomplished through the collaborative work of multiple AUVs. Assigning the cleaning task to each AUV reasonably and effectively has an essential impact on improving cleaning efficiency. The coordination of AUVs is subjected to harsh communication conditions. Therefore, to release the dependence on the underwater communications among AUVs, proposing a reliable multi-robot task allocation (MRTA) model is necessary. Inspired by the evolutionary game theory, this paper proposes a novel multi-robot task allocation (MRTA) model based on replicator dynamics for marine plastic cleaning. This novel model not only satisfies the minimization of the cost function, but also reaches a relatively stable state of the task allocation. A novel optimization algorithm, equilibrium optimizer (EO), is adopted as the optimizer. The simulation results validate the correctness of the results achieved by EO and the applicability of the proposed model. At last, several valuable conclusions are obtained from the simulations on the three different assumed AUVs.

Bioactive glasses 70SiO2–(30-x)CaO–xZnO (x = 1, 3, 5 mol.%) were prepared by the acid-free hydrothermal method in keeping with green chemical technology. The synthetic glasses were investigated by TG-DSC, BET, XRD, and SEM–EDX methods. All synthetic glasses present mesoporous structures consisting of aggregates of nanoparticles. The bioactivity of synthetic glasses was confirmed through the formation of the hydroxyapatite phase after an in vitro experiment in simulated body fluid (SBF) solution. The effect of Zn addition is shown through the decrease in the bioactivity of synthetic glasses. Additionally, the inductively coupled plasma optical emission spectrometry (ICP-OES) analysis indicates that the Zn ions were released from the glassy networks during in vitro experiments, and they act as Zn(OH)2 suspended precipitation to inhibit the apatite deposition. The in vitro experiment in cell culture matter was performed for SaOS2 and Eahy929 cells. The results confirm the biocompatibility of synthetic glasses and the role of Zn addition in the proliferation of living cells.

Nowadays, the payment scheme of European Day-Ahead Market is based on the market clearing price by running the Pan-European Hybrid Electricity Market Integration Algorithm. However, this conventional payment scheme is challenging because of the non-convexity and the short computation time requirement. Thus, the aim of this work is to propose a new clearing model in order to mitigate this challenge. The model is based on make-whole payment mechanism and it includes two major steps: (i) maximizing social welfare and (ii) achieving a Walrasian equilibrium by the “minimum-uplift approach”. The proposed model is validated and investigated by two case studies: one is an artificially created Day-Ahead Market session containing all type of bids encountered in Europe and containing a very large number of bids to stress the algorithm and the other is a reduced, but realistic, model of European market where real data from February to December of 2017 were considered. The tests show a consistent improvement of the numerical performances of the proposed model with respect to the conventional one while the economic performance is not altered, but is slightly improved. Moreover, because the tests are based on real data during a long period of time, the results show that proposed model is very promising for the real application.

In microgrids, distributed generators that cannot be dispatched, such as a photovoltaic system, need to control their output power at the maximum power point. The fluctuation of their output power should be minimized with the support of the maximum power point tracking algorithm under the variation of ambient conditions. In this paper, a new maximum power point tracking method based on the parameters of power deviation (ΔPPV), voltage difference (ΔVPV), and duty cycle change (ΔD) is proposed for photovoltaic systems. The presented algorithm achieves the following good results: (i) when the solar radiance is fixed, the output power is stable around the maximum power point; (ii) when the solar radiance is rapidly changing, the generated power is always in the vicinity of maximum power points; (iii) the effectiveness of energy conversion is comparable to that of intelligent algorithms. The proposed algorithm is presented and compared with traditional and intelligent maximum power point tracking algorithms on the simulation model by MATLAB/Simulink under different radiation scenarios to prove the effectiveness of the proposed method.

To enhance the effectiveness of TiO2 as a photocatalyst, it was believed that the drawbacks of the large bandgap and the rapid electron-hole recombination can be overcome by coupling TiO2 with plasmonic metal nanoparticles. The incorporation of the nanoparticles onto the TiO2 surface requires a suitable procedure to achieve the proper particle adhesion. In this work, we propose a simple, clean, and effective surface activation of TiO2 using plasma enhanced wet chemical surface treatment. Under only 5 min of plasma treatment in a 3% NH3/3% H2O2 solution, gold nanoparticles were found better adhered onto the TiO2 surface. Hence, the methylene blue degradation rate of the Au/TiO2 under sunlight treated was improved by a factor of 3.25 times in comparison to non-treated Au/TiO2 and by 13 times in comparison to the bare rutile TiO2.

The aim of this study was to clarify the relationship between dioxin concentrations in breast milk and the sister chromatid exchange (SCE) frequency in women from herbicide-sprayed and non sprayed areas. Blood samples were taken from 21 women with high TCDD (tetrachlorodibenzo-p-dioxin) levels from sprayed areas, 23 women with moderate TCDD levels from sprayed areas, and 19 women from non sprayed areas to determine their SCE frequency. The SCE frequencies for the high and moderate TCDD groups from the sprayed area and for the non sprayed area group were 2.40, 2.19, and 1.48 per cell, respectively. Multiple regression analysis showed that the standardized β values for 1,2,3,6,7,8-hexaCDD (β = 0.60), 1,2,3,4,6,7,8-heptaCDD (β = 0.64), and octaCDD (β = 0.65) were higher than those for TCDD (β = 0.34) and 1,2,3,7,8-pentaCDD (β = 0.42). The adjusted R2 value for polyCDDs (R2 = 0.38) was higher than that for polyCDD toxic equivalents (TEQ (toxic equivalents); R2 = 0.23). This study therefore shows that levels of hexa-, hepta-, and octaCDD, which were previously regarded as being less toxic than TCDD, are closely related to SCE frequency and that the level of dioxin (pg/g lipid) is potentially more useful as an indicator than TEQ value for explaining SCE frequency.