Influence of benzothiophene acceptor moieties on the non-linear optical properties of pyreno-based chromophores: first-principles DFT framework.

Herein, a series of heterocyclic organic compounds (PYFD1-PYFD7) are designed with different acceptor moieties at the terminal position of a reference compound (PYFR) for nonlinear optical (NLO) active materials. The optoelectronic characteristics of the designed chromophores were investigated using density functional theory (DFT) calculations with the M06/6-311G(d,p) functional. Frontier molecular orbital (FMO) analysis revealed a significant decrease in the energy of the band gaps (2.340-2.602 eV) for the derivatives as compared to the PYFR reference compound (3.12 eV). An efficient transfer of charge from the highest occupied molecular orbital (HOMO) to the lowest unoccupied molecular orbital (LUMO) was seen, which was further corroborated by the density of states (DOS) and transition density matrix (TDM) heat maps. The results of the global reactivity parameters (GRPs) indicated that all derivatives exhibited greater softness (σ = 0.384-0.427 eV) and lower hardness (η = 0.394-1.302 eV) as compared to PYFR, indicating a higher level of polarizability in the derivatives. Moreover, all of the derivatives showed significant findings in terms of nonlinear optical (NLO) results as compared to the reference chromophore. PYFD2 showed the most effective NLO response (α = 1.861 × 10-22 and ßtot = 2.376 × 10-28 esu), including a lowered band gap of 2.340 eV, the maximum softness value of 0.4273 eV, and the lowest hardness value of 1.170 eV as compared to other chromophores. The incorporation of different acceptors and thiophene as a π-spacer in this structural alteration significantly contributed to achieving remarkable NLO responses. Therefore, our findings may motivate experimentalists to synthesize these designed NLO active materials for the current advanced technological applications.

IoT and Ensemble Long-Short-Term-Memory-Based Evapotranspiration Forecasting for Riyadh.

Evapotranspiration (ET) is the fundamental component of efficient water resource management. Accurate forecasting of ET is essential for efficient water utilization in agriculture. ET forecasting is a complex process due to the requirements of large meteorological variables. The recommended approach is based on the Internet of Things (IoT) and an ensemble-learning-based approach for meteorological data collection and ET forecasting with limited meteorological conditions. IoT is part of the recommended approach to collect real-time data on meteorological variables. The daily maximum temperature (T), mean humidity (Hm), and maximum wind speed (Ws) are used to forecast evapotranspiration (ET). Long short-term memory (LSTM) and ensemble LSTM with bagged and boosted approaches are implemented and evaluated for their accuracy in forecasting ET values using meteorological data from 2001 to 2023. The results demonstrate that the bagged LSTM approach accurately forecasts ET with limited meteorological conditions in Riyadh, Saudi Arabia, with the coefficient of determination (R2) of 0.94 compared to the boosted LSTM and off-the-shelf LSTM with R2 of 0.91 and 0.77, respectively. The bagged LSTM model is also more efficient with small values of root mean squared error (RMSE) and mean squared error (MSE) of 0.42 and 0.53 compared to the boosted LSTM and off-the-shelf LSTM models.

Nutritional status, antioxidant activity and total phenolic content of different fruits and vegetables' peels.

The present study assessed nutritional status, antioxidant activity, and total phenolic content in fruits, i.e., mango (Mangifera indica), apple (Malus domestica), and vegetable, i.e., bottle gourd (Lagenaria siceraria), and ridge gourd (Luffa acutangula) peels. The antioxidant activity and total phenolic content (TPC) were evaluated by using methanol extracts along with 2, 2-diphenyl-1-picrylhydrazyl (DPPH), Folin-Ciocalteu (FC) assay, respectively having Butylated hydroxytoluene (BHT) and Gallic acid (GA) as standard. The TPC and antioxidant activity in the peels ranged from 20 mg GAE/g to 525 mg GAE/g and 15.02% to 75.95%, respectively, which revealed that investigated fruit and vegetable peels are rich source of phytochemical constituents. Bottle gourd peels exhibited the highest value of DPPH compared to the rest of the peels included in the study. Likewise, mango peels had the highest TPC as compared to the rest of the fruit peels. This research showed that the utilization of agricultural wastes should be promoted at commercial level to achieve the nutritional benefit at zero cost and minimize the generation of biological waste.