Robust T2 control chart using median-based estimators

One of the most widely used multivariate control charts is the Hotelling T². In order to construct a Hotelling T² control chart, the mean vector (μ) and the variance–covariance matrix (Σ) must be first estimated. The classical estimators of μ and Σ are usually used to design Hotelling T² control chart. The classical estimators are sensitive to the presence of outliers. One way to deal with outliers is to use robust estimators. In this study, a robust T² control chart is proposed. The mean vector is obtained from the sample median. The median absolute deviation and the comedian are used as the estimates of the elements of the variance–covariance matrix. The proposed robust estimators of the mean vector and the variance–covariance matrix are compared with the sample mean vector and the sample variance–covariance matrix, and the M estimator of these parameters, through efficiency and robustness measures. The performances of the proposed robust T² control chart and the classical and the M estimators are also compared by means of average run length. Simulation results reveal that the proposed robust T² control chart has much better performance than the traditional Hotelling T² and similar performance to the M estimator in detecting shifts in process mean vector. Use of other robust estimators to estimate the process parameters is an area for further research.     

Exergoeconomic and thermodynamic analyses of an externally fired combined cycle with hydrogen production and injection to the combustion chamber

A hydrogen production unit is successfully integrated with an externally fired combined cycle using biomass fuel. The hydrogen produced in an electrolyzer can be used for other purposes, but when there is temporarily no market for it is injected into the combustion chamber of an externally fired combined cycle. Injecting hydrogen into the combustion chamber was found to reduce fuel consumption by almost 27%. Moreover, hydrogen injection decreased the energy efficiency and exergy efficiency by 45%, and decreased both the exergy loss and exergy destruction rates. Meanwhile, CO₂ emissions decreased by 32%. However, there are some disadvantages to hydrogen injection, especially from the viewpoint of exergoeconomics. The total unit product cost for the externally fired combined cycle with hydrogen injection is almost 27% more than the unit without hydrogen injection, although the exergy loss and destruction costs decreased with hydrogen injection. The value of the relative cost difference with hydrogen injection rises by 40%. Also the exergoeconomic assessment demonstrates that the cost of components (purchase and maintenance) are higher than cost of components' exergy destruction for both cycles, i.e., with and without hydrogen injection. As the compressor pressure ratio increases, optimal points are identified for biomass flow rate, energy and exergy efficiencies, exergy destruction and loss rates, exergy destruction and loss exergy cost rates, total unit product cost and relative cost difference.     

Courtyard design impact on indoor thermal comfort and utility costs for residential households: Comparative analysis and deep-learning predictive model

A courtyard is an architectural design element which is often known as microclimate modifiers and is responsible to increase the indoor occupant comfort in traditional architecture. The aim of this study is to conduct a parametric evaluation of courtyard design variants in a residential building of different climates with a focus on indoor thermal comfort and utility costs. A brute-force approach is applied to generate a wide range of design alternatives and the simulation workflow is conducted by Grasshopper together with the environmental plugins Ladybug and Honeybee. The main study objective is the evaluation of the occupant thermal comfort in an air-conditioned residential building, energy load, and cost analysis, derived from different design variables including courtyard geometry, window-to-wall ratio, envelope materials, heating, and cooling set-point dead-bands, and building geographical location. Furthermore, a Deep Learning model is developed using the inputs and outputs of the simulation and analysis to transform the outcomes into the algorithmic and tangible environment feasible for predictive applications. The results suggest that regarding the thermal loads, costs, and indoor thermal comfort index (PMV), there are high correlations between the outdoor weather variation and dead-band ranges, while in extreme climates such as Singapore, courtyard spaces might not be efficient enough as expected. Finally, the highly accurate deep learning model is also developed, delivering superior predictive capabilities for the thermal comfort and utility costs of the courtyard designs.     

Effect of alumina content and heat treatment on microstructure and upconversion emission of Er3+ions in oxyfluoride glass-ceramics

The effect of alumina content and heat treatment temperature and time, on microstructure and Er3+ (0.5 mol.%) emission of oxy-fluoride glass-ceramics were investigated in this research. Two values of 1.8 (SA1.8Er0.5) and 2.18 (SA2.18Er0.5) were selected in this re-search for SiO2/Al2O3 ratio. According to DTA results, precursor glasses were heat treated at 630, 660 and 690 °C for 4 h and some glasses were also heat treated at 630 °C for 48 and 72 h. The results indicated that alumina content had significant effect on phase separation and vis-cosity of the glasses. Therefore the size, size distribution, and volume concentration of nano CaF2 crystals which precipitated during the heat treatment depended on alumina content of the glass. Due to the much smaller size of the precipitated CaF2 crystals in the glasses of low alumina content, these samples maintained excellent transparency and had narrower crystal size distribution than the high alumina glasses. The crystal size was increased markedly with the temperature increasing from 630 to 690 °C. On the other hand a slight increase was observed in the crystal size by raising the heat treatment time in both glasses. Results indicated that in low alumina content glass (SA2.18Er0.5) the size of CaF2 nanocrystals was controlled in one order of magnitude. The increase of heat treatment time and temperature led to the incorporation of Er3+ ions into CaF2 crystalline phase, increasing significantly the upconversion intensity. After heat treatment at 690 ℃ for 4 h, atomic force microscope (AFM) re-vealed the development of small crystals with an average size of 80 and 30 nm in SA1.8Er0.5 and SA2.18Er0.5 samples, respectively.     

Reducing Irrigation Deficiencies Based Optimizing Model for Multi-Reservoir Systems Utilizing Spider Monkey Algorithm

Continuous droughts and water scarcity have led to the need for optimal exploitation of dams’ reservoirs. Thus, the new meta-heuristic algorithm, spider monkey, is suggested for complex modeling of the multi-reservoir system in Iran with the aim of decreasing irrigation deficiencies. Golestan and Voshmgir dams’ operations are optimized with the spider monkey algorithm. The algorithm based on the exchange of information between local and global leaders with the other monkeys which improves the convergence speed. Average deficiencies for Golestan dam is computed as 2.1 and 1.9 MCM by spider monkey algorithm while it is respectively computed as 6.7, 16.4, 11.1, 4.1, 14.6, 19 MCM by particle swarm algorithm, harmony search algorithm, imperialist competitive algorithm, water cycle algorithm, genetic algorithm, and standards operation policy method. Also, the computation time of the spider monkey algorithm is 50 and 47 s for the Golestan and Voshmgir dams while the genetic algorithm optimizes the problem in 172.6 s and 112 s and the particle swarm algorithm needs 117.4 s and 100 s for the Golestan and Voshmgir, respectively. Also, root means square error (RMSE) and mean absolute error between demand and released water for the spider monkey algorithm have the least values among the applied evolutionary algorithms. Thus, the spider monkey algorithm is suggested as an appropriate method for optimizing the operation policy for the dam and reservoir systems.     

Synthesis of Modified RGD-Based Peptides and Their in vitro Activity

Arg-Gly-Asp (RGD) peptides represent the most outstanding recognition motif involved in cell adhesion that binds to the α_vβ₃ integrin, which has been targeted for cancer therapy. Various RGD-containing peptides and peptidomimetics have been designed and synthesized to selectively inhibit this integrin. In this study, the synthesis of RGD-based peptides through the incorporation of the short bioactive peptide Phe-Ala-Lys-Leu-Phe (FAKLF) at the C and N termini of RGD has been achieved by using a solid-phase peptide synthesis approach. The peptides were purified by means of preparative RP-HPLC and their structures were confirmed through HRMS (ESI). The MTT assay revealed that the RGD and FAKLF peptides inhibited the proliferation of human umbilical vein endothelial cells (HUVECs) in a dose-dependent manner, with IC₅₀ values of 3000 and 500 ng mL⁻¹, respectively. Interestingly, a drastic improvement was observed in the antiproliferative activity of the combined structures of the FAKLFRGD and RGDFAKLF peptides, leading to IC₅₀ values of 200 and 136.7 ng mL⁻¹, respectively. Meanwhile, based on apoptosis results, the potential of peptides to induce apoptosis, in accordance with their antiproliferative activity, indicated that the RGD and FAKLF peptides, and the peptides synthesized based on their combinations induced cell apoptosis in a dose-dependent manner followed by inhibition of the proliferation of endothelial cells. Moreover, the incorporation of d -leucine increased the induction of apoptosis by these peptides.