Cucumber (Cucumis sativus L.) is a tropical vegetable and a source of vitamins such as K, C, and B. It is commonly grown and sold for daily consumption, but picking the right fruit size is more profitable. Therefore, a method for estimating the fruit weight is highly recommended. This paper aimed to determine the dimensions of cucumber fruit based on its usual harvesting size and to establish a model to show the relationship between fruit weight, fruit length, and fruit diameter. Cucumber was planted in the experimental field belonging to the Faculty of Agricultural Biosystems Engineering, Royal University of Agriculture, Phnom Penh, Cambodia, from January to June 2022. In the study, 48 market-size fruits were randomly selected from the plots to measure their weight, length, and diameter. The result shows that fruit length and fruit diameter had a positive relationship (P < 0.001; R = 0.70). Fruit weight was 3.38 fruit length × fruit diameter (P <0.001; R = 0.95). Nevertheless, L/D ratio negatively affected fruit weight, when it exceeded 3:1. Fruit weight was greater than 100 g when fruit diameter was over 4 cm and fruit length was over 10 cm. Therefore, when picking cucumber fruits, one must consider fruit length and diameter to be profitable. Further studies will focus on measuring cucumber fruit already available on the market to understand more about actual consumer preferences.

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 order to strengthen the study of soil-landscape relationships in mountain areas, a digital soil mapping approach based on fuzzy set theory was applied. Initially, soil properties were estimated with the regression kriging (RK) method, combining soil data and auxiliary information derived from a digital elevation model (DEM) and satellite images. Subsequently, the grouping of soil properties in raster format was performed with the fuzzy c-means (FCM) algorithm, whose final product resulted in a fuzzy soil class variation model at a semi-detailed scale. The validation of the model showed an overall reliability of 88% and a Kappa index of 84%, which shows the usefulness of fuzzy clustering in the evaluation of soil-landscape relationships and in the correlation with soil taxonomic categories.

Based on the population change data of 2005–2009, 2010–2014, 2015–2019 and 2005–2019, the shrinking cities in Northeast China are determined to analyze their spatial distribution pattern. And the influencing factors and effects of shrinking cities in Northeast China are explored by using multiple linear regression method and random forest regression method. The results show that: 1) In space, the shrinking cities in Northeast China are mainly distributed in the “land edge” areas represented by Changbai Mountain, Sanjiang Plain, Xiaoxing’an Mountain and Daxing’an Mountain. In terms of time, the contraction center shows an obvious trend of moving northward, while the opposite expansion center shows a trend of moving southward, and the shrinking cities gather further; 2) in the study of influencing factors, the results of multiple linear regression and random forest regression show that socio-economic factors play a major role in the formation of shrinking cities; 3) the precision of random forest regression is higher than that of multiple linear regression. The results show that per capita GDP has the greatest impact on the contraction intensity, followed by the unemployment rate, science and education expenses and the average wage of on-the-job workers. Among the four influencing factors, only the unemployment rate promotes the contraction, and the other three influencing factors inhibit the formation of shrinking cities to various degrees.