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This study aims to investigate the feasibility of proposed microgrid (MG) that comprises photovoltaic, wind turbines, battery energy storage and diesel generator to supply a residential building in Grindelwald which is chosen as the test location.

Three operational configurations were used to run the proposed MG. In the first configuration, the electric energy can be vended and procured utterly between the main-grid and MG. In the second configuration, the energy trade was performed within 15 kWh as the maximum allowable limit of energy to purchase and sell. In the third configuration, the system performance in the stand-alone operation mode was investigated. A whale optimization technique is used to determine the optimal size of MG in all proposed configurations. The cost of energy (COE) and other measures are used to evaluate the system performance.

The obtained results revealed that the first configuration is the most beneficial with COE of 0.253$/KWh and reliable 100%. Furthermore, the whale optimization algorithm is sufficiently feasible as compared to other techniques to apply in the applications of MG.

The value of the proposed research is to investigate to what extend the integration between MG and main-grid is beneficial economically and technically. As opposed to previous research studies that have focused predominantly only on the optimal size of MG.

Three-way decision (3WD) and probabilistic rough sets (PRSs) are theoretical tools capable of simulating humans' multi-level and multi-perspective thinking modes in the field of decision-making. They are proposed to assist decision-makers in better managing incomplete or imprecise information under conditions of uncertainty or fuzziness. However, it is easy to cause decision losses and the personal thresholds of decision-makers cannot be taken into account. To solve this problem, this paper combines picture fuzzy (PF) multi-granularity (MG) with 3WD and establishes the notion of PF MG 3WD.

An effective incomplete model based on PF MG 3WD is designed in this paper. First, the form of PF MG incomplete information systems (IISs) is established to reasonably record the uncertain information. On this basis, the PF conditional probability is established by using PF similarity relations, and the concept of adjustable PF MG PRSs is proposed by using the PF conditional probability to fuse data. Then, a comprehensive PF multi-attribute group decision-making (MAGDM) scheme is formed by the adjustable PF MG PRSs and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Finally, an actual breast cancer data set is used to reveal the validity of the constructed method.

The experimental results confirm the effectiveness of PF MG 3WD in predicting breast cancer. Compared with existing models, PF MG 3WD has better robustness and generalization performance. This is mainly due to the incomplete PF MG 3WD proposed in this paper, which effectively reduces the influence of unreasonable outliers and threshold settings.

The model employs the VIKOR method for optimal granularity selections, which takes into account both group utility maximization and individual regret minimization, while incorporating decision-makers' subjective preferences as well. This ensures that the experiment maintains higher exclusion stability and reliability, enhancing the robustness of the decision results.

The purpose of this paper is to study the effects of voltage on microstructure and properties of micro-arc oxidation (MAO) ceramic coatings formed on AZ31B magnesium alloy under the constant current–constant voltage operation mode.

The wear and corrosion resistance of MAO coating on AZ31B magnesium alloy was studied by MAO in silicate electrolyte under constant current and constant voltage.

When the voltage is 360 V, the wear and corrosion resistance of AZ31B magnesium alloy is the best.

The wear and corrosion resistance of MAO coating on AZ31B magnesium alloy was studied by friction wear and electrochemical workstation.

The purpose of this study was to the low-temperature synthesis of cobalt-containing diopside pigments based on granulated blast furnace slag and to study the characteristics of the mineral formation processes, changes in the structure and colour indices.

Synthesis of cobalt-containing diopside pigments based was carried out by the directional formation of the mineralogical composition with the introduction of part of the components using granulated blast-furnace slag.

It has been established that the formation of the diopside phase in pigments containing blast-furnace slag as the main component proceeds at low temperatures (1,100°C–1,150 °C). The colour of diopside pigments is formed because of the isomorphic substitution of Si4+ ions for Al3+ ions and Mg2+ ions for Co2+ ions. It is expedient to add CoO in an amount of 0.9 mol (18 Wt.%) into the composition of diopside pigments based on blast-furnace slag to obtain defect-free violet glazes.

The developed diopside pigments enable obtaining of high-quality violet glazes for ceramics. The application of the obtained results can significantly reduce the consumption of traditional raw materials in the composition of silicate ceramic pigments, as well as reduce their firing temperature.

Calcium, magnesium and silicon oxides are the main components of blast-furnace slag. In addition, granulated blast furnace slag is mainly represented by the glassy phase, which determines its high activity during the firing process. These factors are prerequisites for using the blast-furnace slag as a valuable substitute for chemically pure or natural raw materials in silicate pigments and reducing their firing temperature.

The purpose of this paper was to prepare a ternary hierarchical rough particle to accelerate the anti-corrosive design for coastal concrete infrastructures.

A kind of micro-nano hydrophobic ternary microparticles was fabricated from SiO₂/halloysite nanotubes (HNTs) and recycled concrete powders (RCPs), which was then mixed with sodium silicate and silane to form an inorganic slurry. The slurry was further sprayed on the concrete surface to construct a superhydrophobic coating (SHC). Transmission electron microscopy and energy-dispersive X-ray spectroscopy mappings demonstrate that the nano-sized SiO₂ has been grafted on the sub-micron HNTs and then further adhered to the surface of micro-sized RCP, forming a kind of superhydrophobic particles (SiO₂/HNTs@RCP) featured of abundant micro-nano hierarchical structures.

The SHC surface presents excellent superhydrophobicity with the water contact angle >156°. Electrochemical tests indicate that the corrosion rate of mild steel rebar in coated concrete reduces three-order magnitudes relative to the uncoated one in 3.5% NaCl solution. Water uptake and chloride ion (Cl^-) diffusion tests show that the SHC exhibits high H₂O and Cl^- ions barrier properties thanks to the pore-sealing and water-repellence properties of SiO₂/HNTs@RCP particles. Furthermore, the SHC possesses considerable mechanical durability and outstanding self-cleaning ability.

SHC inhibits water uptake, Cl^- diffusion and rebar corrosion of concrete, which will promote the sustainable application of concrete waste in anti-corrosive concrete projects.

A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing process is always accompanied by order splitting and merging; besides, in each stage of the process, there are always multiple machine groups that have different production capabilities and capacities. This paper studies a multi-agent based scheduling architecture for the radio frequency identification (RFID)-enabled semiconductor back-end shopfloor, which integrates not only manufacturing resources but also human factors.

The architecture includes a task management (TM) agent, a staff instruction (SI) agent, a task scheduling (TS) agent, an information management center (IMC), machine group (MG) agent and a production monitoring (PM) agent. Then, based on the architecture, the authors developed a scheduling method consisting of capability & capacity planning and machine configuration modules in the TS agent.

The authors used greedy policy to assign each order to the appropriate machine groups based on the real-time utilization ration of each MG in the capability & capacity (C&C) planning module, and used a partial swarm optimization (PSO) algorithm to schedule each splitting job to the identified machine based on the C&C planning results. At last, we conducted a case study to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

This paper proposes a multi-agent based real-time scheduling framework for semiconductor back-end industry. A C&C planning and a machine configuration algorithm are developed, respectively. The paper provides a feasible solution for semiconductor back-end manufacturing process to realize real-time scheduling.

This paper aims to achieve phosphating via optimal features of Mg metal as a suitable base coating, which is considered for other properties such as barrier properties against the passage of several factors.

In this research, in the phosphate bath, immersion time, temperature and the content of sodium nitrite as an accelerator were changed.

As a result, increasing the immersion time of AZ31 Mg alloy samples in the phosphating bath as well as increasing the ratio of sodium dodecyl sulfate (SDS) concentration to sodium nitrite concentration in the phosphating bath formulation increase the mass of phosphating formed per unit area of the Mg alloy. The results of the scanning electron microscope test showed phosphating is not completely formed in short immersion times, which is a thin and uneven layer.

Mg and its alloys are sensitive to galvanic corrosion, which would lead to generating several holes in the metal. As such, it causes a decrease in mechanical stability as well as an unfavorable appearance.

Mg is used in several industries such as automobile and computer parts, mobile phones, astronaut compounds, sports goods and home appliances.

Nevertheless, Mg has high chemical reactivity, so an oxide-hydroxide layer is formed on its surface, which has a harmful effect on the adhesion and uniformity of the coating applied on Mg.

By increasing the ratio of SDS concentration to sodium nitrite concentration in the phosphating bath, the corrosion resistance of the phosphating increases.

To improve the corrosion resistance of magnesium alloys, the construction of protective coatings is necessary to extend the service life of Mg-based materials.

SiO₂ nanoparticles modified by dodecyltrimethoxysilane (DTMS) were added to the PP and a superhydrophobic Mg(OH)₂/PP-60mSiO₂ composite coating was fabricated on the surface of AZ31 magnesium alloy via the hydrothermal method and subsequently the immersion treatment.

Hydrophilic SiO₂ nanoparticles become hydrophobic after modified by DTMS, showing a higher dispersibility in xylene. By incorporating modified SiO₂ nanoparticles into the composite PP coating, the hydrophobicity of the layer was enhanced, resulting in a contact angle of 166.3° and a sliding angle of 3.4°. It also improved the water repellency and durability of the coating. Furthermore, the intermediate layer of Mg(OH)₂ significantly strengthened the bond between the PP layer and the substrate. The Mg(OH)₂/PP-60mSiO₂ composite coating significantly enhances the corrosion resistance of the magnesium alloy by effectively blocking the infiltration of the corrosion anions during corrosion. The corrosion current density of the Mg(OH)₂/PP-60mSiO₂ composite coating is approximately 8.23 × 10^–9 A·cm^-2, which can achieve a magnitude three times lower than its substrate, making it a promising surface modification for the Mg alloy.

The composite coating effectively and durably enhances the corrosion resistance of magnesium alloys.

This paper aims to assess the impact of digital financial innovation on financial system development in Common Market for eastern and Southern Africa (COMESA). This paper evaluates the dynamic relationship between digital financial innovation measures and financial system development using time series data from COMESA countries for the period 1997–2019.

A dynamic autoregressive distributed lag model (ARDL) was adopted and the mean group (MG), pooled mean group (PMG) and dynamic fixed effect (DFE) of the model were estimated to evaluate the short- and long-run impact. In addition, the dynamic generalized method of moments (DGMM) was adopted for a robustness check. The Hausman test results show PMG to be the most consistent and efficient estimator, while the coefficient of lagged dependent variable of different GMM is less than the fixed effect coefficient, and, as such, suggests system GMM is the most suitable estimator. Data for the study were sourced from World Bank Development Indicator (WDI, 2020), World Governance Indicator (WGI, 2020) and World Bank Global Financial Development Database (GFD, 2020).

The result shows that digital financial innovation significantly impacts financial system development in the long run. As such, the evidence revealed that automated teller machines (ATMs), point of sale (POS), mobile payments (MP) and mobile banking are significant and contribute positively to financial system development in the long run, while mobile money (MM) and Internet banking (INB) are insignificant but exhibit positive and inverse relationship with financial development respectively. Further investigation revealed that institutional quality and a stable macroeconomic environment including their interactive term are significantly imperative in predicting financial system development in the COMESA region.

Researchers recommend a cohesive and conscious policy that would checkmate the divergence in the short run and suggest a common regional innovative financial strategy that could be pursued to incentivize technology transfer needed to promote financial system development in the long run. More so, plausible product and process innovations may be adapted to complement innovative institutions in the different components of the COMESA financial system.

Digital financial innovation services if well managed increase the inherent benefits in financial system development.

To the best of the authors’ knowledge, this paper presents new background information on digital financial innovation that may stimulate the development of the financial system, particularly in the COMESA region. It also exposes the relevance of digital financial innovation, institutional quality and stable macroeconomic environment as well as their interactive effect on COMESA financial system development.

This study aims to examine the effect of traditional fermentation on gari’s total heavy metal and mineral nutrient content.

This study used a quantitative approach, descriptive-analytical design to baseline the risk of heavy metals and experimental design to assess the effect of traditional fermentation. Data were analyzed using descriptives, univariate and multivariate analysis.

Although gari is rich in mineral nutrients (total calcium 3.9 ± 0.1 g/kg, copper 5.5 ± 0.02 mg/kg, iron 97.1 ± 5.8 mg/kg, potassium 9.1 ± 0.29 g/kg and zinc 3.4 ± 0.11 mg/kg), the significant levels of heavy metals (total arsenic 1.2 ± 0.01, cadmium 2.5 ± 0.04, lead 1.7 ± 0.01, mercury 2.8 ± 0.01 and tin 1.7 ± 0.02 mg/kg) present are a cause for concern. The results further suggested that traditional fermentation has reductive effects on some heavy metals and stabilizing or concentrating effects on mineral nutrients.

This paper provides evidence that traditional fermentation may have exploitable differential effects on heavy metal contaminants and mineral nutrients that should be further explored.

Thise study reports fermentation implications for mitigating food with high heavy metal contaminants with minimal nutrient loss.

This study fulfills an identified need to optimize traditional fermentation to ensure food safety and nutrient security.