The purpose of Vehicular Ad Hoc Network (VANET) is to provide users with better information services through effective communication. For this purpose, IEEE 802.11p proposes a protocol standard based on enhanced distributed channel access (EDCA) contention. In this standard, the backoff algorithm randomly adopts a lower bound of the contention window (CW) that is always fixed at zero. The problem that arises is that in severe network congestion, the backoff process will choose a smaller value to start backoff, thereby increasing conflicts and congestion. The objective of this paper is to solve this unbalanced backoff interval problem in saturation vehicles and this paper proposes a method that is a deep neural network Q-learning-based channel access algorithm (DQL-CSCA), which adjusts backoff with a deep neural network Q-learning algorithm according to vehicle density. Network simulation is conducted using NS3, the proposed algorithm is compared with the CSCA algorithm. The find is that DQL-CSCA can better reduce EDCA collisions.

Horticulture is a widespread activity in family farming in the Transamazonian region—Pará, with emphasis on production aimed at the family’s own consumption. The lettuce cultivar Vanda (Lactuca sativa L.) represents a significant part of this production, which prioritizes the use of internal labor. The main objective of this work was to evaluate the development of lettuce CV Vanda grown in beds using organic compost and chemical fertilization (NPK). The criteria considered to evaluate this performance were: Root system development, plant height and total fresh mass production. The best averages in relation to root development occurred in the plots cultivated with organic compost in the proportion of 5 kg/m², due to its characteristics as a fertilizer and soil conditioner. The cultivation with the use of NPK provided the best averages in relation to the production of total fresh mass and plant height, results that were mainly attributed to the extra supply of nitrogen in the covering fertilization, which consisted in the addition of 10 g urea per square meter via soil. Statistical analysis showed no statistically significant difference regarding plant height for both treatments. And in relation to root development, the difference was statistically significant.

In this study, the effect of porogenic solvents on pore size distribution of the polycaprolactone (PCL) thin films was investigated. Five thin PCL films were prepared using the solvent-casting method. Chloroform, Methylene Chloride (MC) and three different compositions of MC/ Dimethylformamide (DMF) (80/20, 50/50 and 20/80) were used as solvents. Scanning Electron Microscopy (SEM) investigations were employed to study morphology and consequently the pore size distribution of the prepared films. The PCL films made by chloroform and MC as a solvent were completely non-porous. Whereas the other films (made by a combination of MC and DMF) showed both uni-modal and bi-modal pore size distributions.

Energy systems face serious difficulties due to economic policy uncertainty, which affects consumption trends and makes the shift to sustainability more difficult. While adjusting for economic growth and carbon emissions, this study examines the dynamic relationship between economic policy uncertainty and energy consumption (including renewable and nonrenewable) in China from 1985Q1 to 2023Q4. The research reveals the frequency-specific and time-varying relationships between these variables by employing sophisticated techniques such as Wavelet Cross-Quantile Correlation (WCQC) and Partial WCQC (PWCQC). Economic policy uncertainty and energy consumption do not significantly correlate in the short term; however, over the long term, economic policy uncertainty positively correlates with renewable energy consumption at medium-to-upper quantiles, indicating that it may play a role in encouraging investments in sustainable energy. On the other hand, EPU has a negative correlation with nonrenewable energy usage at lower quantiles, indicating a slow move away from fossil fuels. These results are confirmed by robustness testing with Spearman-based WCQC techniques. The study ends with policy recommendations to maximize economic policy uncertainty’s long-term impacts on renewable energy, reduce dependency on fossil fuels, and attain environmental and energy sustainability in China.