Fog computing (FC) has been presented as a modern distributed technology that will overcome the different issues that Cloud computing faces and provide many services. It brings computation and data storage closer to data resources such as sensors, cameras, and mobile devices. The fog computing paradigm is instrumental in scenarios where low latency, real-time processing, and high bandwidth are critical, such as in smart cities, industrial IoT, and autonomous vehicles. However, the distributed nature of fog computing introduces complexities in managing and predicting the execution time of tasks across heterogeneous devices with varying computational capabilities. Neural network models have demonstrated exceptional capability in prediction tasks because of their capacity to extract insightful patterns from data. Neural networks can capture non-linear interactions and provide precise predictions in various fields by using numerous layers of linked nodes. In addition, choosing the right inputs is essential to forecasting the correct value since neural network models rely on the data fed into the network to make predictions. The scheduler may choose the appropriate resource and schedule for practical resource usage and decreased make-span based on the expected value. In this paper, we suggest a model Neural Network model for fog computing task time execution prediction and an input assessment of the Interpretive Structural Modeling (ISM) technique. The proposed model showed a 23.9% reduction in MRE compared to other methods in the state-of-arts.

There are several factors that generate postharvest losses of Citrus sinensis, but none have been focused on the central jungle of the Junín region of Peru. The objective of this research was to evaluate postharvest losses of Citrus sinensis in the province of Satipo, Junín region of Peru, considering the stages of the production chain. The methodology was applied to descriptive and cross-sectional design. A sample of 10 orange trees, 3 transport intermediaries and 5 traders selected for compliance with minimum volume and quality requirements were used. The °Brix, pH and acidity characteristics of the fruit were determined. Subsequently, absolute and percentage losses were quantified through direct observation, surveys and interviews. The main postharvest losses of Citrus sinensis were 1.50% in harvesting and detaching, 1.75% in transport to the collection center, 2.23% in storage and transport by intermediaries, and 2.90% in storage and sale by retailers. The overall loss was 8.12% throughout the production chain and US$5.75 per MT of C. sinensis harvested. The main damages found were mechanical and biological, caused by poor harvesting and packaging techniques, precarious storage and careless transport of the merchandise.

Since 2019, major travel destinations worldwide have issued travel-related restrictions against COVID-19. There is much research on tourism, but few studies have been conducted to explain the relevance of revisiting intention from the perspective of the epidemic or the dramaturgical theory. The purpose of the research is to explore the impact of customer experience on revisit intention during the period of COVID-19 slowdown by using dramaturgical theory. This study used a survey methodology, and the questionnaire was distributed on an online questionnaire platform. The URL of the questionnaire was published on social media (such as Facebook and LINE) to collect data from 389 samples of people who have foreign travel experience. The data was analyzed by employing partial least square structural equation model (PLS-SEM) methodology with the help of the statistical software “SmartPLS”. The research findings are as follows: 1) setting, audience, and performance are the three important elements of dramaturgical theory that impact the experience quality; 2) customer experience of tourists has a significant impact on the experience quality; 3) experience quality has a significant positive impact on the experience value and relationship quality; 4) experience value and relationship quality are important predictors of revisit intention. This study provides academic implications regarding the use of dramaturgical theory in relation to customer experience and relationship constructs in the context of tourism. Furthermore, it also provides some practical implications to tourism practitioners and managers, which would assist tourism industries in developing successful marketing strategies for the possible recovery of COVID-19.

Potassium is an essential macronutrient for living creatures on earth and in plants, it plays a very significant role in determining the overall health of the plants. Although potassium is present in the soil, it is present in a form that is inaccessible to the plants, and hence synthetic harmful non-eco-friendly potassium fertilizers are used. To overcome this problem, the use of eco-friendly potassium-solubilizing bacteria comes into play. The goal of the present study was to assess the potassium-solubilizing bacteria that inhabit the farm rhizosphere, which demonstrate the presence of enzymes associated with plant growth promotion and antagonistic properties. A total of thirty-four isolates were isolated from the rhizosphere. All these isolates were subjected to a potassium solubilization test on Aleksandrov agar medium, out of which fourteen were found to possess potassium solubilizing ability. On the basis of the 16S rRNA gene sequencing, the most potential potassium-solubilizing bacterium was identified as Proteus mirabilis PSCR17. The plant growth promoting abilities and production of biocontrol enzymes of this isolate were evaluated, and the results indicated, in addition to potassium solubilization, the isolate was positive for indole acetic acid production, hydrogen cyanide production, amylase, catalase, cellulase, chitinase, and protease. The use of potassium fertilizers is harmful to the environment and ecosystem; hence, this study concludes that P. mirabilis PSCR17 can be used as a substitute for chemical potassium fertilizers to improve the growth and biocontrol traits of the plants in a sustainable manner after further research.

To achieve the Paris Agreement’s temperature goal, greenhouse gas emissions should be reduced as soon as, and by as much, as possible. By mid-century, CO₂ emissions would need to be cut to zero, and total greenhouse gases would need to be net zero just after mid-century. Achieving carbon neutrality is impossible without carbon dioxide removal from the atmosphere through afforestation/reforestation. It is necessary to ensure carbon storage for a period of 100 years or more. The study focuses on the theoretical feasibility of an integrated climate project involving carbon storage, emissions reduction and sequestration through the systemic implementation of plantation forestry of fast-growing eucalyptus species in Brazil, the production of long-life wood building materials and their deposition. The project defines two performance indicators: a) emission reduction units; and b) financial costs. We identified the baseline scenarios for each stage of the potential climate project and developed different trajectory options for the project scenario. Possible negative environmental and reputational effects as well as leakages outside of the project design were considered. Over 7 years of the plantation life cycle, the total CO₂ sequestration is expected to reach 403 tCO₂∙ha⁻¹. As a part of the project, we proposed to recycle or deposit for a long term the most part of the unused wood residues that account for 30% of total phytomass. The full project cycle can ensure that up to 95% of the carbon emissions from the grown wood will be sustainably avoided.

In light of the metaverse’s vast expansion, it’s a crucial intellectual platform that’s transforming the video game industry and spurring creative innovation and technological advancement. Considering the distinctive niche that Taiwan occupies within the realm of the video game industry, this study uses a total of 11 video game companies in Taiwan as samples. The study spans a period of 16 years, from 2007 to 2022, and utilizes the random effect regression model for analysis. The study results illustrate that intellectual capital efficiency exerts varying contributions to the creation of value across different corporate value indicators within the video game industry. Among the factors, HCE, SCE, and CEE demonstrate the highest explanatory power for ROE, reaching up to 82.23%. Following this, they account for 73.57% of the variance in market share, but only a meager 13.67% for Tobin’s Q. This study is the empirical evidence that different methods of measuring intellectual capital and various definitions of value creation in an industry may lead to divergent results and managerial implications in intellectual capital research. Hence, it is worthwhile for subsequent studies to continue clarifying and delving deeper into these aspects.