Neurological disorders like stroke are one of the main causes of motor dysfunction and gait function disabilities in humans. These disorders impact the mobility of patients often leading to weakened and impaired ankle joints which further compromise their balance and walking abilities. Over the span of the last twenty years, there has been a rising interest in designing, developing, and using rehabilitative robots for patients suffering from various ankle joint disabilities. These robotic devices are developed by employing diverse mechanical designs, materials, and control strategies. The aim of this study is to provide a detailed overview of the recent developments in mechanical design, actuation, and control strategies of ankle rehabilitation robots. Experimental evaluation of the discussed ankle robots has also been carried out discussing their results and limitations. This article concludes by highlighting future challenges and opportunities for the advancement of ankle rehabilitation robots, stressing the need for robust and effective devices to better serve patients.

This research uses EBSD data of two thermo-mechanically processed medium carbon (C45EC) steel samples to simulate micromechanical deformation and damage behavior. Two samples with 83% and 97% spheroidization degrees are subjected to virtual monotonic quasi-static tensile loading. The ferrite phase is assigned already reported elastic and plastic parameters, while the cementite particles are assigned elastic properties. A phenomenological constitutive material model with critical plastic strain-based ductile damage criterion is implemented in the DAMASK framework for the ferrite matrix. At the global level, the calibrated material model response matches well with experimental results, with up to ~97% accuracy. The simulation results provide essential insight into damage initiation and propagation based on the stress and strain localization due to cementite particle size, distribution, and ferrite grain orientations. In general, it is observed that the ferrite–cementite interface is prone to damage initiation at earlier stages triggered by the cementite particle clustering. Furthermore, it is observed that the crystallographic orientation strongly affects the stress and stress localization and consequently nucleating initial damage.

Competition between concentrated solar power and solar photovoltaic has been the subject of frequent debate in recent years based on their cost of fabrication, efficiency, storage, levelized cost of energy, reliability, and complexity of respective technologies. Taking Pakistan as a testbed, a study was conducted to determine which technology is economical in a particular location and climate. The study assesses the meteorological, orographic, and spatial factors that impact the performance and cost of both renewable energy systems. A SWOT analysis, followed by technoeconomic analyses, was conducted to determine suitable sites for setting up solar power plants in Pakistan. A detailed assessment of siting factors for solar power plants was conducted to shortlist the most suitable sites. Based on the results, economic analysis was performed to install 100 MW photovoltaic and parabolic trough power plants at selected locations. The levelized cost of energy for the 100 MW parabolic trough is 10.8 cents/kWh and 12 cents/kWh in best-case scenarios, i.e., for locations of Toba and Quetta, respectively, whereas the LCOEs of 100 MW photovoltaic systems stand comparatively low at 7.36 cents/kWh, 7.21 cents/kWh, 7.01 cents/kWh, 6.82 cents/kWh, 6.02 cents/kWh, and 5.95 cents/kWh in Multan, Bahawalpur, Rahim Yar Khan, Hyderabad, Quetta, and Toba, respectively. The results favor choosing solar PV plants over solar CSP plants in terms of finances in the selected regions. The findings will assist financiers and policymakers in creating better policies in terms of long-term goals.

Pakistan is among the countries that have already crossed the water scarcity line, and the situation is worsened due to the recent pandemic. This is because the major budget of the country is shifted to primary healthcare activities from other development projects that included water treatment and transportation infrastructure. Consequently, water-borne diseases have increased drastically in the past few months. Therefore, there is a dire need to address this issue on a priority basis to ameliorate the worsening situation. One possible solution is to shift the focus/load from mega-projects that require a plethora of resources, money, and time to small domestic-scale systems for water treatment. For this purpose, domestic-scale solar stills are designed, fabricated, and tested in one of the harshest climatic condition areas of Pakistan, Rahim Yar Khan. A comprehensive overview of the regional climatology, including wind speed, solar potential, and ambient temperature is presented for the whole year. The analysis shows that the proposed system can adequately resolve the drinking water problems of deprived areas of Pakistan. The average water productivity of 1.5 L/d/m² is achieved with a total investment of PKR 3000 (<$20). This real site testing data will serve as a guideline for similar system design in other arid areas globally.

Functional metal parts with complicated geometry and internal features for the aerospace and automotive industries can be created using the laser powder bed fusion additive manufacturing (AM) technique. However, the lack of uniform quality of the produced parts in terms of strength limits its enormous potential for general adoption in industries. Most of the defects in selective laser melting (SLM) parts are associated with a nonuniform melt pool size. The melt pool area may fluctuate in spite of constant SLM processing parameters, like laser power, laser speed, hatching distance, and layer thickness. This is due to heat accumulation in the current track from previously scanned tracks in the current layer. The feedback control strategy is a promising tool for maintaining the melt pool dimensions. In this study, a dynamic model of the melt pool cross-sectional area is considered. The model is based on the energy balance of lumped melt pool parameters. Energy coming from previously scanned tracks is considered a source of disturbance for the current melt pool cross-section area in the control algorithm. To track the reference melt pool area and manage the disturbances and uncertainties, a linear active disturbance rejection control (LADRC) strategy is considered. The LADRC control technique is more successful in terms of rapid reference tracking and disturbance rejection when compared to the conventional PID controller. The simulation study shows that an LADRC control strategy presents a 65% faster time response than the PID, a 97% reduction in the steady state error, and a 98% reduction in overshoot. The integral time absolute error (ITAE) performance index shows 95% improvement for reference tracking of the melt pool area in SLM. In terms of reference tracking and robustness, LADRC outperforms the PID controller and ensures that the melt pool size remains constant.

The emergence of surgical robots has revolutionized complex operations, improving precision, lowering operating risks, and shortening recovery periods. Given the merits, an eight degrees of freedom (DOF) hybrid surgical robot (HSR) has been proposed, which leverages the benefits of both serial and parallel manipulators. However, its performance is hindered by the constrained range of motion of its parallel platform. To address the issue, this research presents a systematic approach for designing and optimizing the proposed HSR. The first step is the design of the HSR, followed by a multi-stage design analysis of its parallel platform, concentrating on kinematic, geometrical, and singularity analysis. Higher values of the condition number indicate singular configurations in the platform’s workspace, highlighting the need for an optimized design. For optimization of the platform, performance parameters like global condition number (GCN), actuator forces, and stiffness are identified. Initially, the design is optimized by targeting GCN only through a genetic algorithm (GA). This approach compromised the other parameters and raised the need for simultaneous optimization employing a non-dominated sorting genetic algorithm (NSGA II). It offered a better trade-off between performance parameters. To further assess the working of the optimized parallel platform, workspace analysis and motion planning of a predefined trajectory have been performed.