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Climate change has been drastically affecting cotton not only in Pakistan but also all over the world. Normally cotton is known as heat tolerant when compared with other crops, but if the high temperature occurs during flowering period the yield decreases significantly. Marker assisted gene pyramiding provides a sustainable solution to improve heat tolerance. A total of seven genotypes were developed by a series of crossing seven tolerant genotypes over the period of three years. Tolerant genotypes were selected by screening for important transcription factors (GHSP26, HSP3, HSFA2, DREB1A, HSP101, DREB2A, GhNAC2, HSPCB, GhWRKY41, TPS, GbMYB5, ANNAT8, GhMPK17, GhMKK1, GhMKK3, GhMPK2, HSC70, APX1 and GhPP2A1). The seven genotypes were evaluated under normal and heat stress in a multi-year trial. The traits related to heat tolerance, such as cell membrane stability, relative water content, excised leaf water loss, plant height, number of nodes, internodal length, number of buds, number of bolls and leaf area was observed under normal and heat stress conditions. The developed genotypes showed improvement in cell membrane stability and relative water content under heat stress. The genotypes [(VH-305×MNH-886)×MNH-1035)×NIAB-78)], [(MNH-1035×MNH-886)×MNH-886)×SM-431] and [(MNH-1035×MNH-886)×MNH-886)×SS-32] depicted heat tolerance and could be used as heat tolerant material for variety development in breeding programs. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) performance depends on the accuracy of the system model. Moreover, the optimization algorithm of MPC requires numerous online computations. These inherent limitations of MPC hinder its application in power electronics systems. This paper proposes a two-part solution for these challenges for a three-phase inverter with an output LC filter. The first part of the control scheme is a linear and modified model-free approach based on the auto-regressive structure (ARX) with exogenous input. The second part is the computationally efficient optimization algorithm based on the active set method to solve the optimization problem of the MFPC. The objective of the control scheme is to regulate the output voltages of the inverter in the presence of constraints. The constraints are the maximum admissible filter current and optimal duty cycle to avoid any damage to the system. To validate the performance of the proposed control scheme, simulations and hardware-in-loop (HIL) real-time investigations have been performed, comparing the results of the proposed approach with the model-based predictive control. The results showcase the computational efficiency and effectiveness of the MFPC approach, demonstrating its potential for overcoming the limitations of traditional MPC in power electronics systems. [ABSTRACT FROM AUTHOR]

Sustainable urban water management is essential to handle water scarcity, leakage, and inefficient distribution. This paper covers water management in urban areas, including an introduction, an overview of water management practices, the characteristics and functioning of water distribution systems, monitoring and control systems for efficient distribution, smart systems for optimization, strategies for water conservation and waste management, per capita water demand analysis, and desalination plant overviews. The article proposes a blockchain-based water management architecture with IoT sensors for accurate reporting. The framework uses blockchain technology to authenticate and share real-time data between sensors and the water distribution dashboard. It also has a modular API for water leakage detection and flow control to decrease water waste and enhance distribution. The suggested approach might enhance water management; however, its execution is complex. Maintaining the framework's efficacy is advised. The research provides insights into water management and proposes a technology solution employing blockchain and IoT sensors for trustworthy data reporting and effective water distribution to promote sustainable urban water management. [ABSTRACT FROM AUTHOR]