The purpose of this work is to present the model of a Parabolic Trough Solar Collector (PTC) using the Finite Element Method to predict the thermal behavior of the working fluid along the collector receiver tube. The thermal efficiency is estimated based on the governing equations involved in the heat transfer processes. To validate the model results, a thermal simulation of the fluid was performed using Solidworks software. The maximum error obtained from the comparison of the modeling with the simulation was 7.6% at a flow rate of 1 L/min. According to the results obtained from the statistical errors, the method can effectively predict the fluid temperature at high flow rates. The developed model can be useful as a design tool, in the optimization of the time spent in the simulations generated by the software and in the minimization of the manufacturing costs related to Parabolic Trough Solar Collectors.

This study aimed to analyze government policies in education during the Covid-19 pandemic and how teachers exercised discretion in dealing with limitations in policy implementation. This research work used the desk review method to obtain data on government policies in the field of education during the Covid-19 pandemic. In addition, interviews were conducted to determine the discretion taken in implementing the learning-from-home policy. There were three learning models during the pandemic: face-to-face learning in turns (shifts), online learning, and home visits. Online learning policies did not work well at the pandemic’s beginning due to limited infrastructure and human resources. To overcome various limitations, the government provided internet quota assistance and curriculum adjustments and improved online learning infrastructure. The discretion taken by the teachers in implementing the learning-from-home policy was very dependent on the student’s condition and the availability of the internet network. The practical implication of this research is that street-level bureaucrats need to pay attention to discretionary standards when deciding to provide satisfaction to the people they serve.

Developing countries have witnessed a rise in infrastructure spending over the past decades; however, infrastructure spending in most developed countries, particularly the US, continues to decline. As a result, in 2021, the US Congress passed a Bipartisan Infrastructure Bill, which invests $1 trillion in the country’s infrastructure every year. Using the principal component analysis and VAR estimation, we analyzed the impact of infrastructure (transportation and water, railway networks, aviation, energy, and fixed telephone lines) on economic growth in the US. Our findings show that infrastructure spending positively and significantly impacted economic growth. Additionally, the impulse response analysis shows that shocks to infrastructure spending had positive and persistent effects on economic growth. Our results suggest that infrastructure investment spurs economic growth. Based on our findings, sustained public spending on transport and water, railway networks, aviation, energy, and fixed telephone lines infrastructure by the US government will positively impact economic growth in the country. The study also suggests that policies that promote infrastructure spending, such as the Bipartisan Infrastructure Law (Infrastructure Investment and Jobs Act) passed by the US Congress, should be enhanced to boost economic growth in the US. 

In this study, optical and microwave satellite observations are integrated to estimate soil moisture at the same spatial resolution as the optical sensors (5km here) and applied for drought analysis in the continental United States. A new refined model is proposed to include auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed soil moisture model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns. Currently, the USDM is providing a weekly map. Recently, “flash” drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively higher spatial resolution than those traditionally derived from passive microwave sensors, thus drought maps based on soil moisture anomalies can be obtained on daily basis and made the flash drought analysis and monitoring become possible.

Magnetic graphene oxide nanocomposites (M-GO) were successfully synthesized by partial reduction co-precipitation method and used for removal of Sr(II) and Cs(I) ions from aqueous solutions. The structures and properties of the M-GO was investigated by X-ray diffraction, Fourier transformed infrared spectroscopy, X-ray photoelectron spectroscopy, transmission electron microscopy, scanning electron microscopy, vibrating sample magnetometer (VSM) and N₂-BET measurements. It is found that M-GO has 2.103 mg/g and 142.070 mg/g adsorption capacities for Sr(II) and Cs(I) ions, respectively. The adsorption isotherm matches well with the Freundlich for Sr(II) and Dubinin–Radushkevich model for Cs(I) and kinetic analysis suggests that the adsorption process is pseudo-second-ordered.