*2.4. Sample Collection and Processing*

*Plasma.* Peripheral blood was collected into 4 mL K3-EDTA vacutainer tubes, which were kept on ice at all times. Samples were centrifuged at 4 °C to pellet cells and the plasma was collected and kept on ice for extraction of ascorbate. Plasma samples were treated with an equal volume of ice-cold 0.54 M perchloric acid containing the metal chelator DTPA (100 μmol/L) to precipitate protein [21]. The de-proteinated supernatants were stored at −80 °C until HPLC analysis.

*Urine.* Urine was collected into pre-weighed 50 mL sample containers and an aliquot was removed for urinary creatinine determinations. Urine samples were treated with an equal volume of ice-cold 0.54 M perchloric acid containing the metal chelator DTPA (100 μmol/L) to precipitate protein [21]. The de-proteinated supernatants were stored at −80 °C until HPLC analysis.


4.1.1. Neural Networks

Moayedi et al. [126] synthesized a new EHO-MLP ensemble with a multi-layer perceptron (MLP) neural network to predict cooling load. The results revealed that EHO-MLP performed efficiently for adjusting biases of the MLP and the neural weights. It also outperformed the ACO [55] and EHO [105] optimization algorithms both in training and testing accuracies. Meanwhile, EHO-MLP took less time than ACO [55] and EHO [105] with regard to the time-effectiveness of the models.

Kowsalya et al. [127] used EHO to optimize neural network weights. The performance of the proposed method was evaluated on evaluation metrics. It was concluded that the proposed method provided better accuracy than existing classifiers.

Sahlol et al. [128] applied EHO to neural networks to classify each cell for the acute lymphoblastic leukemia problem. In the proposed method, the weights and biases of the network were updated by the EHO algorithm. The research results showed that EHO outperformed other classification methods.

#### 4.1.2. Underwater Sensor Networks

Kaur et al. [129] used EHO to solve underwater sensor networks optimization tasks. The research outcomes indicated that the proposed approach showed better performance than other strategies for most parameters.

#### 4.1.3. Unmanned Aerial Vehicle Path Planning

Alihodzic et al. [130] considered an approximation algorithm, adjusted EHO (AEHO), to solve the unmanned aerial vehicle (UAV) path planning problem. AEHO was used for adjusting the UAV path planning problem and it was compared with other state-of-the-art algorithms. The simulation experiments showed that AEHO obtained a safe flight path and was an excellent choice for the UAV path planning problem.


Characterisation of Endo-Polygalacturonases Activities of Rice (*Oryza sativa*) Fungal Pathogens in Nigeria, West Africa

*Adekunle Odunayo Adejuwon, Marina Donova, Victoria Anatolyivna Tsygankova and Olubunmi Obayemi*


**4. Conclusions**

The current study investigates the effect of alloy temper conditions on the behavior upon friction stir deposition. The deposited AMPs were characterized in terms of macro and microstructural features as well as the hardness distribution. Based on the obtained results, the following conclusions can be outlined:

**Author Contributions:** Conceptualization, M.M.Z.A., E.E. and M.M.E.-S.S.; methodology, M.M.Z.A., E.E., and M.M.E.-S.S.; software, M.M.E.-S.S. and M.I.A.H.; validation, B.A. and K.T.; formal analysis, M.M.E.-S.S. and M.M.Z.A.; investigation, M.M.E.-S.S. and M.M.Z.A.; resources, B.A. and K.T.; data curation, M.M.E.-S.S.; writing—original draft preparation, E.E. and M.M.E.-S.S.; writing—review and editing, M.M.E.-S.S. and M.M.Z.A.; visualization, M.I.A.H.; supervision, M.M.Z.A. and M.M.E.-S.S.; project administration, M.M.Z.A. and M.M.E.-S.S.; funding acquisition, B.A. and K.T. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the extremely large size.

**Conflicts of Interest:** The authors declare no conflict of interest.