To a great extent, Pakistan and Turkey rely on imported fossil fuels to meet their energy demands. Pakistan is moving in the right direction, placing focus on renewable energy resources in its current infrastructure in order to address the energy shortage. Several projects (e.g., wind power and solar PV (photovoltaic) technologies) are operational or under development; they are intended to reduce energy challenges in Pakistan. The new government in Pakistan aims to increase the share of renewable energy in total power generation to 30% by 2030. On the other hand, Turkey surpasses Pakistan in renewable energy resources; for example, there are 186 operational wind energy power plants across the country. In addition, Turkey utilizes solar energy—mainly for residential usage. Turkey’s Vision 2023 energy agenda aims to supply 30% of their power demands from modern renewable energy resources. Turkey has implemented solar PV, solar buildings, wind power plants, geothermal energy resources, and biomass technology for heating, cooling and electricity generation. At present, Turkey’s supply to meet energy demands in the country is 56% fossil fuel energy resources and 44% renewable energy, including hydropower. Accessible details reveal that geothermal energy resources have been continuously neglected in Pakistan by the Ministry of Energy (power division); this is in contrast to the Turkish case, in which utilization of geothermal energy resources for heating and cooling purposes is efficient. With all the facts and figures under consideration, in this paper, comparative analyses are performed which reveal that the production of electricity from geothermal energy technologies is lower than the massive potential in both countries. Recommendations are made for important policies to promote renewable energy technologies, which could effectively support energy decentralization by providing electricity to rural areas and the national grid.

Globally, universities are evaluating and targeting to reduce their carbon emissions and operate on a sustainable basis. The overall aim of this study revolves in addressing the following three questions: (1) How to calculate carbon footprint, including indicators selection, criteria, and measurement, for higher education institutions? (2) How to evaluate impact and effectiveness of various mitigation strategies in context of a higher education institution? (3) What are the possible limitations of approach selected for carbon footprint calculation. This paper presents estimation of the carbon footprint of NED University using a carbon calculator along with the identification of sources with maximum contribution to its carbon footprint. The carbon footprint of the NED University main campus for 2017 was calculated to be approximately 21,500 metric tons of equivalent CO2 and carbon footprint per student was 1.79 metric tons of equivalent CO2. Scope 1 and Scope 2 emissions each contributed nearly 7% of the carbon footprint, while Scope 3 emissions accounted for 85.6% of the carbon footprint. Major interventions such as switching to renewables, usage of energy efficient appliances, electric vehicles, and massive tree plantation inside and outside the campus were identified as the most effective mitigation strategies.

The COVID-19 pandemic has significantly affected the psychological stability of general population of Pakistan. However, research on the severity of COVID-19 induced depression, anxiety, and stress (DAS) in Pakistan is scarce. This paper thereby investigates the severity of COVID-19 induced DAS based on demographic, socioeconomic, and personal feeling variables by modeling DAS. Snowball sampling strategy was adopted to conduct online survey from July 03, 2021 to July 09, 2021. Out of 2,442, 2,069 responses from Karachi were included. Descriptive and inferential statistics (binary and multinomial logistic regression analysis) were performed using SPSS V21 (IBM, 2013) to identify significant determinants and their association with DAS severity. The result of this study indicates 27.8, 21.7, and 18.3% respondents suffer from severe and extremely severe states of depression, anxiety, and stress, respectively. Binary logistic regression revealed that age is a significant determinant with odds of having 4.72 (95% CI = 1.86–11.97) and 5.86 (95% CI = 2.26–15.2) times greater depression, and stress for respondents aged 19–26 years. Moreover, gender-based difference is also observed with females 1.34 (95% CI = 1.08–1.68) and 1.75 (95% CI = 1.40–2.20) times more likely to exhibit anxiety and stress than males. Furthermore, marital status is a significant determinant of depression with odds of having depression is 0.67 (95% CI = 0.48–0.93) times greater for married population. Multinomial logistic regression revealed that those who believe COVID-19 pandemic has affected them mentally, fear new COVID-19 cases and deaths, depressed due to imposition of lockdown, believe they will not survive COVID-19 infection, and spend more time on social media gathering COVID-19 updates suffer from extremely severe state of depression (OR mental-effect-of-pandemic = 3.70, OR new-COVID-19-cases-and-deaths = 2.20, OR imposition-of-lockdown = 17.77, OR survival-probability = 8.17, OR time-on-social-media = 9.01), anxiety (OR mental-effect-of-pandemic = 4.78, OR new-COVID-19-cases-and-deaths = 3.52, OR imposition-of-lockdown = 5.06, OR survival-probability = 8.86, OR time-on-social-media = 5.12) and stress (OR mental-effect-of-pandemic = 6.07, OR imposition-of-lockdown = 11.38, OR survival-probability = 15.66, OR time-on-social-media = 4.39). Information regarding DAS severity will serve as a platform for research centers and psychological clinics, to work collectively and provide technology-based treatment to reduce the burden on the limited number of psychologist and psychotherapist.

The usage of BLDC motors in the low-power range is increasing rapidly in home appliances such as ceiling fans. This has necessitated the development of reliable, compact and efficient AC-DC power supplies for motor drive circuitry. This paper presents a power supply design consisting of an AC-DC isolated PFC Cuk converter with integrated magnetics that supplies a single-shunt voltage source inverter for the sensorless drive of the BLDC fan motor. The proposed power supply design is comprised of an integrated magnetics structure in which the two inductors and the transformer windings share the same core. The zero input and output ripple current conditions have been derived from the reluctance model of the magnetic assembly. Smooth operation of the motor by minimizing the motor torque ripples is evident from the results. The Cuk converter operates in continuous conduction mode (CCM), employing the current multiplier method. The CCM-based current multiplier control loop ensures a near-unity power factor as well as low total harmonic distortion in the supply current. The current loop also provides over-current protection, enhancing reliability of the system. Moreover, the speed of the BLDC motor is controlled by the field oriented control (FOC) algorithm, which enables direct operation with alternate energy sources such as batteries and solar photovoltaic panels. The performance of the proposed supply is validated: motor torque ripple is reduced to only 2.14% while maintaining 0.999 power factor and only 4.72% THD at full load. Failure modes analysis has also been performed through software simulations, using the PLECS simulation environment. Due to the reliable power supply design with low ripples, it is well suited for low-power BLDC motors in home appliances and small power tools, in addition to ceiling fans.

The effect of post-growth annealing treatment of zinc oxide (ZnO) nanorods on the electrical properties of their heterojunction diodes (HJDs) is investigated. ZnO nanorods are synthesized by the low-temperature aqueous solution growth technique and annealed at temperatures of 400 and 600°C. The as-grown and annealed nanorods are studied by scanning electron microscopy (SEM) and photoluminescence (PL) spectroscopy. Electrical characterization of the ZnO/Si heterojunction diode is done by current–voltage (I–V) and capacitance–voltage (C–V) measurements at room temperature. The barrier height (ϕ B), ideality factor (n), doping concentration and density of interface states (N SS) are extracted. All HJDs exhibited a nonlinear behavior with rectification factors of 23, 1,596 and 309 at ±5 V for the as-grown, 400 and 600°C-annealed nanorod HJDs, respectively. Barrier heights of 0.81 and 0.63 V are obtained for HJDs of 400 and 600°C-annealed nanorods, respectively. The energy distribution of the interface state density has been investigated and found to be in the range 0.70 × 1010 to 1.05 × 1012 eV/cm2 below the conduction band from E C = 0.03 to E C = 0.58 eV. The highest density of interface states is observed in HJDs of 600°C-annealed nanorods. Overall improved behavior is observed for the heterojunctions diodes of 400°C-annealed ZnO nanorods.

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