Volume 3

Abstract:

HCV is a life-threatening disease that causes several liver disorders such as liver fibrosis, cirrhosis, and hepatocellular carcinoma (HCC)-second leading type of cancer. Although directing acting antivirals (DAAs) are showing some promising results, despite the liver complications caused by HCV are likely to persist in near future. HCV induced HCC is a slowly progressing multiple step process. This carcinogenesis is acquired over the years via production of a cirrhotic tissue microenvironment. Some cellular proteins and eukaryotic translation initiators were seen to increase translation of HCV polyprotein precursor and hence intracellular replication of viral gene. Which in turn upsets the regulation of several cytokines leading to cytokine storm in the liver and peripheral blood mononuclear cells (PBMCs). This plays a role in liver disease progression, thus signifying role of PBMCs in HCC induction over time.

Abstract:

Mushroom is a delicious and delicatessen food all over the world. As they have no skin, moisture is required to produce the fruit or sporophore of mushrooms. For this reason, mushrooms need an environment (humidity 80% to 90% and temperature 14˚C to 18˚C) that has high humidity to avoid water loss. For this, farmers have to spend much time in the cultivation room to maintain a proper environment. This paper introduces the Internet of Things (IoT) based automatic environment controller. This controller can monitor the ideal environment of the cultivation room ubiquitously. The proposed system can monitor and control the humidity and temperature of the mushroom cultivation room and presents the data on the cloud server every thirty seconds in the form of tables and graphs. A cost-effective solution is provided using the less-costly and low-power consumes hardware to design the controller. The system is evaluated and experimental results show that it can be efficiently used as an environment controller.

Abstract:

Nanocomposite has found application in the modern field of technology based on its specific properties. A nanocomposite of alumina and zirconia (Al2O3-ZrO2) was synthesized using a simple Sol-Gel technique and sintered at different temperatures from 500 ºC to 1100 C with an interval of 200 ºC. A thin film was deposited on a 1 mm thick aluminum sheet. The structural simulation of the deposited thin film was analyzed using ANSYS. Particle size and phase are verified by XRD. DSC-TGA (SDT) analysis was used to determine the 1100 ºC of Al2O3/ZrO2 nanocomposite for thin film by dipping method. SEM Material morphology of the synthesized material performed by the SEM method in particle size 90-100nm.

Abstract:

The problem of climate change is worldwide and causing diverse effects on all aspects of life. Altering rain patterns could cause floods in certain areas and droughts in the other causing a direct threat to our food security. This study was conducted to analyze different indicators of climate change in three cities of Punjab Province of Pakistan (Lahore, Faisalabad and Multan). Secondary data was collected from Pakistan Meteorological Department. Study parameters were minimum temperature, maximum temperature, annual rainfall and diurnal temperature rainfall. Results showed that minimum temperature anomaly decreased during most of the years from 1977 to 1998. 10-years moving average of minimum temperature anomaly remained negative till early 21^st century for Lahore, Faisalabad and Multan. Afterwards, 10-years moving average of minimum temperature anomaly increased gradually and became positive. Maximum DTR was 1.75, 2.0 and 1.50 for Lahore, Faisalabad and Multan, respectively. A great variation in annual rainfall has been observed from 1977 to 2016. 10-years moving average of annual rainfall anomaly remained positive in most of the years. A great variation in maximum temperature anomaly was observed during the entire study period for all districts. Considering the climatic variations in the study area, there is need to analyze vulnerability of Punjab Province of Pakistan.

Abstract:

This paper presents the importance of Artificial intelligence (AI) in the computing education, which has become an important and powerful aspect of human lives. It is still a field in its beginnings, but as time progresses, we will observe how AI evolves and explores its untapped potential. The rapid development regarding scrutiny of learning outcomes for higher education, establishment and implementation of international standards shows the need of the technology. Many higher education institutes of the world are adopting information and communication technology (ICT) to enhance the Course Learning Outcomes (CLO) of the students based on the revised Bloom Taxonomy that assists the institutions to analyze the outcomes of students in planning the course and techniques to improve and enhance the performance of students. This research paper analysis the importance of blooms in integration of computing technologies and smart learning environment and provides the encouraging results when analyzed by using supervised machine learning methods during the COVID-19 pandemic situation. In this research, we have designed an ICT based framework to achieve the learning outcomes of the students in computing subjects. It is worth mentioning that the proposed educational model reports the promising results of a bout of 83% accuracy. The accuracy of the model is also verified from self-assessment reports of the students.

Abstract:

An effective and sustainable solar energy generating system is needed given the current global energy problem. The need to use solar energy properly is necessary because it is one of the most readily available sources of energy. The conversion of solar energy to electric energy uses silicon solar panels, which have an efficiency of between 15% and 20%. The solar cell efficiency is nevertheless decreased by the dust that wind and storms bring. In this study, a sensor-based system is used to monitor the dust buildup on the solar panel and to remove the dust by washing and moistening the panel’s surface. The output conversion efficiency and sensor data are taken into consideration by a fuzzy logic system, which forecasts when the solar panel will need to be cleaned.