7 research outputs found
A multi-prefecture study applying multivariate approaches for predicting and demystifying weather data variations affect COVID-19 spread
No full textSince the first cases were reported in Wuhan, China in December 2019, the massive SARS virus, known as COVID-19, is spreading at an alarming rate and is endangering the world. The whole world is now affected by this terrible epidemic including Pakistan. Because it provides a rich resource for studying the variants affecting the COVID-19 contagion, the spread of COVID-19 in Pakistan makes it necessary to assess the link between COVID-19 cases and weather parameters for management and policymakers. The proposed study uses a multivariate approach to demystify the impact of meteorological conditions on COVID-19 contagion, where in a case study, different regions of Pakistan are chosen. The multivariate techniques used in the proposed approach comprise linear multiple regression, linear stepwise regression, multiple adaptive regression splines, and loess regression. We also implement spline regression models for deeper analysis. A machine learning regressor was used to validate the results of the spline curve regression model. The performance of machine learning models and splines is measured using different performance metrics. Experiments show that weather parameters such as temperature and humidity are prominent features in predicting the spread of COVID-19. The spline curve results show that, except for Baluchistan, during the first wave, the temperature was positively correlated with daily confirmed cases, and during the second wave, the temperature was negatively correlated with daily confirmed cases in all other provinces. Another finding of the study is that when data from March 2020 to February 2021 were included, the humidity was inversely associated with mortality and confirmed cases in all provinces. Thus, increased humidity inhibits the spread of COVID-19 and reduces mortality
Soft Load Shedding Based Demand Control of Residential Consumers
No full textPower generation and consumption is an instantaneous process and maintaining the balance between demand and supply is crucial since the demand and supply mismatch leads to various risks like over-investment, over-generation, under-generation, and the collapse of the power system. Therefore, the reduction in demand and supply mismatch is critical to ensure the safety and reliability of power system operation and economics. A typical and common approach, called full load shedding (FLS), is practiced in cases where electric power demand exceeds the available generation. FLS operation alleviates the power demand by cutting down the load for an entire area or region, which results in several challenges and problems for the utilities and consumers. In this study, a demand-side management (DSM) technique, called Soft-load shedding (SLS), is proposed, which uses data analytics and software-based architecture, and utilizes the real-world time-series energy consumption data available at one-minute granularity for a diversified group of residential consumers. The procedure is based on pattern identification extracted from the dataset and allocates a certain quota of power to be distributed on selected consumers such that the excessive demand is reduced, thereby minimizing the demand and supply mismatch. The results show that the proposed strategy obtains a significant reduction in the demand and supply mismatch such that the mismatch remains in the range of 10–15%, especially during the period where demand exceeds generation, operating within the utility constraints, and under the available generation, to avoid power system failure without affecting any lifeline consumer, with a minimum impact on the consumer’s comfort
Phosphorus Fertilizer Response to Onion (Allium cepa L.) Yield in Punjab, Pakistan
No full textBackground: Onion (Allium cepa L.) is one of the most essential plants in food with high nutritional value. However, application of right dose of phosphorous (P) is one of the constraints to the profitable onion yields in soils deficient in P.Methods: A systematic study to confirm the best dose of P was conducted for six years in the P deficient soil in farmers’ fields. Based on the findings obtained from 2008-09 to 2010-11, the research was undertaken to determine the effect of different phosphorus levels on the yield of onion in the Randomized Complete Block Design (RCBD) with a total of 114 replicates in 2011-12 to 2012-13. Four treatments (160, 210, 260 and 310 kg P2O5 ha-1) were tested with N and K at 100 kg ha-1.Results: From the results of this investigation, the variance analysis showed the substantial P impact. The maximum marketable bulb yield (19.03 t ha-1) was obtained from the fertilizer combination NPK @ 100-310-100 kg ha-1 and was shown to be statistically higher than all other treatments.Conclusion: Nonetheless, the nutshell of the overall economic study is that poor farmers (Land holders >12 acres) may have options to select the NPK fertilizer combination @ 100:210:100 kg ha-1 and the average farmer may have options to select the NPK fertilizer combination @ 100:260:100 kg ha-1. But rich farmers (Land holders >25 acres) who can spend more money on fertilizers and are interested in the higher gross margin should follow the combination of NPK fertilizers @ 100:310:100 kg ha-1 to profitably increase their gross margin and maintain soil fertility for onion cultivation in Punjab, Pakistan. Keywords: Onion; NPK; Plant nutrition; Phosphorus; Pungency
Comparative Investigation of the Thermal Conductivity of Water-Based Nanofluids with and without the Combination of Alumina and Carbon Nanotubes
No full textIn the present study, the thermal conductivity of two distinct water-based nanofluids of single-walled CNTs and Al2O3, as well as their hybrid solution, was investigated experimentally. The Al2O3 and CNTs nanoparticle concentrations are taken to be 2%v/v, while the hybrid solution contained 2%v/v of both Al2O3 and CNTs nanoparticles. A PSS (Polly styrene sulphonic acid) solution was used as a surfactant to increase the suspension time of the nanoparticles to avoid sedimentation. The dispersion and breaking of the particles of CNT and Al2O3 into nano size were performed employing a probe sonicator and bath sonicator. Moreover, a hot plate magnetic stirrer was used to obtain a consistent liquid mixture. The experiments are performed on the Computer Controlled Thermal Conductivity of Liquid and Gases (TCLGC) unit available in the heat transfer lab at GIKI. The results concluded that the thermal conductivity of water-based single-walled CNT nanofluids was higher compared to Al2O3 and their hybrid solution. Therefore, Al2O3 and a hybrid solution are less desirable for thermal conduction compared to CNTs
Alleviation of Heat Stress in Tomato by Exogenous Application of Sulfur
No full textTemperature is a key factor influencing plant growth and productivity, however sudden increases in temperature can cause severe consequences in terms of crop performance. We evaluated the influence of elementary sulfur application on the physiology and growth of two tomato genotypes (“Ahmar” and “Roma”) grown in two growth chambers (at 25 and 45 °C). Plants were sprayed with 2, 4, 6, and 8 ppm sulfur 45 days after sowing (untreated plants were kept as control). Plants of the “Roma” cultivar receiving 6 ppm sulfur exhibited maximal shoot and root biomass values followed by those receiving 4 ppm under both temperature conditions. Maximal CO2 index, photosynthetic rate, transpiration rate, and greenness index values (188.1 µmol mol−1, 36.3 µmol CO2 m−2 s−1, 1.8 µmol H2O m−2 s−1, and 95 SPAD, respectively) were observed in plants of “Roma” cultivar grown at 25 °C, indicating positive influences of sulfur on tomato physiology. Similarly, sulfur maximized proline, nitrogen, phosphorus, and potassium contents in leaves of both genotypes at both temperatures. The differences between control and sulfur-treated plants grown under heat stress indicate a possible role of sulfur in mitigating heat stress. Overall, our results suggest that 6 ppm of sulfur is the best dose to alleviate tomato heat stress and enhance the morphological, physiological, and biochemical attributes of tomato plants
Uncovering the Cooling Potential by Water Circulation on the Hot Side of a Peltier Module
No full textThermolectric cooling offers several advantages over conventional refrigeration systems due to its light weight, environmental friendliness, silent operation, and no moving parts. In this work, a thermoelectric water cooling system is created in which water flowing at various flowrates removes heat produced on the hot side of the Peltier module. The cooling effect and coefficient of performance (COP) of the cooling system are experimentally determined at various flowrates of water on the hot side of the module. The cooling effect produced in water increases with the increase in flowrate. A similar trend is noticed for the COP of the system. The maximum cooling effect produced in water is 1363 W at 43 mL/s. The maximum COP of the system is 3.99
