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Accurate regulation of the liquid level in a quadruple tank system (QTS) is not easy and imposes higher requirements on control strategies, so the design of controllers in these systems is challenging due to the difficulty of dynamic analysis of its nonlinear characteristics and parametric uncertainties. To overcome these problems in liquid level regulation and increase the robustness to the pump coefficients, this article proposes and investigates the use of an optimal hybrid fractional-order type-2 fuzzy-PID (OH-FO-T2F-PID) regulator using a combination of two bio-inspired evolutionary optimizers, namely augmented grey wolf optimizer and cuckoo search optimizer, which gives rise to the new hybrid A-GWOCS algorithm. This control mechanism was chosen to facilitate the convergence of the water liquids in the two tanks as quickly as possible to the corresponding required values. In addition, a collaborative optimization technique with several objectives is used to adjust the regulator parameters. The capability and efficiency of the suggested regulator is first investigated through computer simulation results and then confirmed by real-time control experimental results on the QTS based on dSPACE 1104 computation engine. The findings showed that the suggested OH-FO-T2F-PID regulator significantly outperformed both the optimized ADRC and the OH-FO-T1F-PID regulators. Specifically, it reduced the rising time by 17.02% and 95.21%, respectively, and the settling time by 25.13% and 74.28%. Additionally, the designed OH-FO-T2F-PID regulator successfully eliminated the steady-state error and overshoot, enabling precise regulation of the QTS, and maintenance the liquid level at the desired set point under a wide range of working situations. The robustness of the recommended regulator is also studied by considering - 50% disturbance in the QTS parameters, and the findings showed that the OH-FO-T2F-PID regulator is less susceptible to variations in parameters., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Monitoring of water quality is one of the world's main intentions for countries. Classification techniques based on support vector machines (SVMs) and artificial neural network (ANN) has been widely used in several applications of water research. Water quality assessment with high accuracy and efficiency with innovational approaches permitted us to acquire additional knowledge and information to obtain an intelligent monitoring system. In this paper, we present the use of principal component analysis (PCA) combined with SVM and ANN with decision templates combination data fusion method. PCA was used for features selection from original database. The multi-layer perceptron network (MLP) and the one-against-all strategy for SVM method have been widely used. Decision templates are applied to increase the accuracy of the water quality classification. The specific classification approach was employed to assess the water quality of the Tilesdit dam in Algeria as a study area, defined with a dataset of eight physicochemical parameters collected in the period 2009-2018, such as temperature, pH, electrical conductivity, and turbidity. The selection of the excellent parameters of the used models can be improving the performance of classification process. In order to assess their results, an experiment step using collected dataset corresponding to the accuracy and running time of training and test phases, and robustness to noise, is carried out. Various scenarios are examined in comparative study to obtain the most results of decision step with and without feature selection of the input data. From the results, we found that the integration of SVM and ANN with PCA yields accuracy up than 98%. The combination by decision templates of two classifiers SVM and ANN with PCA yields an accuracy of 99.24% using k-fold cross-validation. The combination data fusion enhanced expressively the results of the proposed monitoring framework that had proven a considerable ability in surface water quality assessment., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Four Turkish provenances and five Lebanese provenances of Cedrus libani A. Rich. and one Cypriot provenance of C. brevifolia Henry were compared during the third year of growth in a controlled-climate greenhouse after exposure to a well-watered or moderate-drought treatment. Effects of treatment on CO(2) assimilation (A), stomatal conductance (g(s)), (13)C isotope composition (delta(13)C), growth and biomass were assessed. Hydraulic conductivity and shoot vulnerability to cavitation were measured in well-watered plants only. The Lebanese provenances of C. libani had the highest growth rates, but were the most sensitive to drought. The Turkish provenances of C. libani showed moderate growth rates and moderate drought sensitivity. Cedrus brevifolia had the lowest growth rate and was least sensitive to drought. For each provenance, mean biomass values were positively correlated with delta(13)C and intrinsic water-use efficiency (A/g(s)), and negatively correlated with g(s). Drought reduced growth and favored carbon storage in roots, increasing the ratio of root biomass to aboveground biomass. The drought treatment increased delta(13)C and A/g(s). Specific hydraulic conductivity (K(s)) was similar for the provenance groups, whereas leaf-specific conductivity (K(l)) was lower in the Lebanese provenances than in the other provenances. Within each provenance group, provenances with the highest K(l) were most susceptible to xylem cavitation, but were also the most productive. Growth and drought adaptation were linked with precipitation in each provenance's native range.

We studied hydraulic traits of young plants of the Mediterranean cedar species Cedrus atlantica (Endl.) G. Manetti ex Carrière (Luberon, France), C. brevifolia (Hook. f.) Henry (Cyprus), C. libani A. Rich (Hadeth El Jebbe, Lebanon) and C. libani (Armut Alani, Turkey). With an optimum water supply, no major differences were observed among species or provenances in either stem hydraulic conductivity (Ks) or leaf specific conductivity (Kl) measured on the main shoot. A moderate soil drought applied for 10 weeks induced marked acclimation through a reduction in Ks, particularly in the Lebanese provenance of C. libani, and a decrease in tracheid lumen size in all species. Cedrus atlantica, which had the smallest tracheids, was the species most vulnerable to embolism: a 50% loss in hydraulic conductivity (PsiPLC50) occurred at a water potential of -4.4 MPa in the well-watered treatment, and at -6.0 MPa in the moderate drought treatment. In the other species, PsiPLC50 was unaffected by moderate soil drought, and only declined sharply at water potentials between -6.4 and -7.5 MPa in both irrigation treatments. During severe drought, Ks of twigs and stomatal conductance (g(s)) were measured simultaneously as leaf water potential declined. For all species, lower vulnerability to embolism based on loss of Ks was recorded on current-year twigs. The threshold for stomatal closure (10% of maximum g(s)) was reached at a predawn water potential (Psi(pd)) of -2.5 MPa in C. atlantica (Luberon) and at -3.1 MPa in C. libani (Lebanon), whereas the other provenance and species had intermediate Psi(pd) values. Cedrus brevifolia, with a Psi(pd) (-3.0 MPa) close to that of C. libani (Lebanon), had the highest stomatal conductance of the study species. The importance of a margin of safety between water potential causing stomatal closure and that causing xylem embolism induction is discussed.

Changes in photosystem II (PSII) thermotolerance during drought and recovery were studied under controlled conditions in three Mediterranean cedar species (Cedrus brevifolia Henry, C. libani Loudon and C. atlantica Manetti). The temperature at which the quantum yield of PSII photochemistry was reduced by 15% of its value at 25 degrees C was 3 to 4 degrees C higher in drought-treated plants than in well-watered plants. The drought-induced increase in PSII thermotolerance was already evident 8 days after water had been withheld from the seedlings, when net CO(2) assimilation was still at 80% of its initial value, and was visible for up to 12 days after re-watering. When seedlings of the three species were exposed to temperatures above 45 degrees C for 5 h, both maximal quantum yield of PSII photochemistry and net CO(2) assimilation rate were significantly reduced in unconditioned seedlings, whereas drought-preconditioned seedlings were almost unaffected by the heat treatment. Drought-preconditioned seedlings still exhibited a higher tolerance to heat stress than unconditioned seedlings 60 days after re-watering, although the transient, drought-induced osmotic adjustment had fully disappeared. Among species, C. atlantica was the most heat sensitive, whereas the heat treatment had no significant effect on the parameters measured in C. brevifolia.