The main pathogen that deteriorates the quality of rose flowers during the postharvest stage belongs to the fungal genus Botrytis. The chemical products used to control the disease caused by this pathogen have been losing effectiveness due to the appearance of resistance. The present study describes the in vitro and in vivo fungicidal activity of Pelargonium graveolens essential oil and its chemical composition. The essential oil was obtained by hydrodistillation, and the in vitro fungicidal activity was determined by agar diffusion assays, showing 100% of fungal growth inhibition at 250 ppm. In vivo assays were performed on Rosa grandiflora flowers treated with 250 ppm of P. graveolens essential oil, using distillate water as a positive control and the commercial fungicide carbendazim as a negative one. No significant differences were obtained between the treatment with the essential oil and the treatment with the commercial fungicide. The chemical profile of the essential oil was determined by GC-MS. The main compounds detected were geraniol (24.89%), citronellol (19.50%), linalool (10.92%) and γ-eudesmol (8.93%). These results encourage the possible use of P. graveolens essential oil for the control of B. cinerea in rose flowers.

This study was conducted to determine crop water stress index (CWSI) values and irrigation timing in the case of Derinkuyu dry bean ( Phaseolus vulgaris L.). In 2017, dry beans were grown as the main crop according to the field design consisting of plots divided into randomised blocks. Irrigation treatment comprised full irrigation (I100) and irrigation issues with three different levels of water stress (I66, I33, I0). This study applied 602 mm of water under the I100 irrigation. The yield of Derinkuyu dry beans was equal to 3576.6 kg∙ha ^–1 in I100 irrigation. The lower limit (LL) value, which is not necessary for the determination of CWSI, was obtained as the canopy–air temperature difference ( Tc – Ta) versus the air vapour pressure deficit ( VPD). The upper limit (UL) value, at which the dry beans were wholly exposed to water stress, was obtained at a constant temperature. The threshold CWSI value at which the grain yield of dry beans started to decrease was determined as 0.33 from the measurements made with an infrared thermometer before irrigation in I66 irrigation treatment. As a result, it can be suggested that irrigation should be applied when the CWSI value is 0.33 in dry beans. Furthermore, the correlation analysis revealed a negative correlation between grain yield and crop water stress index and a positive correlation between yield and chlorophyll content. According to variance analysis, significant relationships were found between the analysed parameters at p ≤ 0.01 and p ≤ 0.05.

Mobile Ad hoc Network (MANET) is a type of Ad hoc network. General properties of MANET open the network to various security threats. Network layer-based Active attacks are widespread and destructive. Available security solutions contain complex calculations. Therefore, the objective of this research is to propose a lightweight security mechanism to enhance the security of data communications between source and destination nodes in a MANET from network layer-based active attack. Blackhole is used as a network layer-based Active attack. The network performance is evaluated using Packet Delivery Ratio (PDR), Average End-to-End Delay (AEED), Throughput, and Simulation Processing Time at Intermediate Nodes (SPTIN). The controller network was used to compare the performance of each network. During the experiment due to the impact of the blackhole attack, compared to the controller network, the PDR was found to be 0.28%, AEED was infinity and Throughput was 0.33%. The performance of the proposed security mechanism was compared with that of the controller network, and the values of PDR, AEED, Throughput, and SPTIN were found to be 98.0825%, 100.9346%, 99.9988%, and 96.5660%, respectively. The data packet delivery ratio was 100.00% compared to that of the controller network. The network that was affected by a blackhole attack showed a higher amount of ADDR than the controller network and the lowest amount of PDR. The network that was affected by the blackhole showed underperformance compared to the controller network. The proposed security mechanism performs well in PDR, AEED, and Throughput compared to the controller network. The AEED and SPTIN values prove that the proposed solution is free from complex calculations. The scope of the solution can be expanded into a lightweight Intruder Detection System to handle different types of security attacks in MANETs.

The high-temperature deformation process and dynamic recrystallization (DRX) process of 21-4N were investigated under the conditions of the deformation temperature range of 1273~1453K, the strain rate range of 0.01~10s–1 and the deformation degree of 60% (the total deformation is 0.916) by using Gleeble-1500D thermal simulated test machine. The curves of stress-strain (σ – ε) were obtained, and the curves of work hardening rate (θ) and strain (ε) were obtained by taking derivative of σ – ε. The DRX critical strains under different conditions were determined by the curves of work hardening rate (θ – ε), and the DRX critical strain model was established. The peak strains of 21-4N were obtained by the curves of σ – ε, the relationship between peak stress (σp) and critical strain (εc) was determined, and the peak strain model was established. The DRX volume fraction models of 21-4N were established by using Avrami equation. The DRX grain size of 21-4N was calculated by Image Pro Plus 6.0, and its DRX grain size models were established.

The study sought to use computer techniques to detect selected psychological traits based on the nature of the writing and to evaluate the effectiveness of the resulting software. Digital image processing and deep neural networks were used. The work is complex and multidimensional in nature, and the authors wanted to demonstrate the feasibility of such a topic using image processing techniques and neural networks and machine learning. The main studies that allowed the attribution of psychological traits were based on two models known from the literature, KAMR and DA. The evaluation algorithms that were implemented allowed the evaluation of the subjects and the assignment of psychological traits to them. The DA model turned out to be more effective than the KAMR model.