In the last ten years, pedagogy has been evolving rapidly in terms of teaching approaches. This study is an attempt to analyze the recently developed novel pedagogy models. STEM integration and classroom engagement are primary approaches in pedagogy in recent times. The article aims to provide educators with some analytical tools to complement the modernization of STEM pedagogy. Integration flow and skill-set balancing, along with matrix analysis, are projected to be efficient solutions for evolved pedagogy. A novel PESTLE model is framed for tackling the changes in pedagogies during pandemics and emergencies. Inquiry-based learning can foster and accelerate the cause of integrating subjects in STEM pedagogy. In addition, the article discusses the post-pandemic scenario of pedagogy in the education system as a whole.

This article aims to present some opportunities for improved solar energy utilization by raising the share of renewables in energy generation in the Visegrád Countries (Poland, Czech Republic, Slovakia, and Hungary). The analysis is based on the status of the renewable energy targets in the member countries and their future possibilities. This paper derives input through a thorough investigation of independent data, government policies, European Commission reports, and other data available online with free access. The analysis is processed by focusing on Hungary, as a country with various possible facets of solar energy demand and supply in the region. The assessment methodology is in the context of a geographical map, technical regression analysis, temperature distribution profiles, and the relative trends of solar potential in Hungary. The country currently has ten solar power plants with more than 10 MWp, and five remarkable plants under 10 MWp capacity spread over Hungary. The analysis on geographical aspects clubbed with technical and solar affecting parameters was carried out to harvest the sustainable potential of solar energy in the region. This study attempts to establish a relationship between the current and future prospects of solar energy in Hungary as a nation, and as part of the Visegrád countries, based on assessment for a sustainable future.

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Solar drying has emerged as a potential drying solution for agricultural products in many developing nations. The drying behavior of the product to be dried depends on many parameters of the dryer. A box-type natural convective solar dryer was developed to analyze the drying performance of Wood chips. Experiments revealed promising drying results with drying efficiency. The design of the dryer could further be enhanced by hybridization with an external heat source.

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The future of conventional fuels has limited sustainability and creates disquietude because of the ubiquitous energy crisis worldwide. The judicious use of biomass or wood-based fuels is inevitable. The quality of wood fuels depends on the moisture content, and subsequently, solar drying solutions can play a vital role in adequately storing and controlling moisture in the fuels. In the present study, a novel forced convection cabinet-type solar dryer was developed and investigated for its thermal performance. An artificial neural network (ANN model) was created to predict the final moisture content of the drying system. The drying behavior of three distinct wood fuels, i.e., woodchips, sawdust, and pellets, was kept under observation to plot the drying curve based on their calculated moisture ratio. The dryer reached a maximum temperature of 60 °C while maintaining a temperature gradient of 10–20 °C. The maximum thermal energy and exergy efficiency was recorded as 55% and 51.1%, respectively. The ANN-optimized model was found suitable with reasonable values of coefficient of correlation (R) for the model.

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