Energy Efficient Biomass Gassifier Stove for Domestic Purpose

Pakistan is facing issues with respect to sustainable energy and increasing of greenhouse gases, therefore, there is needed to take holistic approach to reduce energy crisis through the solution of renewable energy by natural resource management in the future. That is why this work has been carried out to develop and evaluate the performance of energy efficient biomass gasifier stove for domestic purposes as well as to compare its performance with improved cooking stove using locally available biomass fuels like wood chips. A biomass gasifier stove was developed and evaluated on wood chips fuel at National Agriculture Research Center (NARC), Islamabad. The design improvement of the stove focused on the following areas: provision of insulation around the chamber to reduce conduction heat loss across the walls of the chamber, incorporation of pot supporter as to minimize the smoke by direct contact to the fire and provision of sizable and adjustable air inlet to ensure the availability of sufficient air for the complete combustion of the fuel wood. The results obtained from this study showed that the gasifer wood stove has a maximum thermal efficiency of 30% as compared the thermal efficiency of improved stove of 18 %. Similarly, with a higher the useful heat energy output per kg of wood used was 1239.60 kJ/ kg than the useful heat energy output per kg of wood used by improved stove was 144.43 kJ/ kg. So, the performance of gasifier stove much better than improved stove. Keywords: Energy, Biomass, Gasifier Stove, Cooking Stove and Gasifer Wood Stov

Assessing the Impact of Builtup Areas on Development of Urban Heat Island in Lahore, Pakistan

The aim of present study is to evaluate and assess the impact of built-up areas on development of the urbanheat island (UHI).The study mainly focused on Lahore, which is one of the mega cities of Pakistan. In terms ofpopulation size, Lahore is the second largest city of Pakistan with 11.13 million inhabitants. The geospatial techniques(Remote Sensing and Geographical Information System) along with statistical applications were applied to find out theLand Cover Land Uses changes and consequent development of builtup areas over the period of 2000 and 2015. Tostudy the UHI, the meteorological data of each 30 minutes for 36 days starting from 30th June 2015 to 4th August 2015were collected through direct on site observation by using digital weather station. The results of UHI were crosschecked by obtaining land surface temperature by using thermal infrared (TIR) band 6 of the Landsat-7 TM. The resultsshow that the LCLU and built environment have direct impact on development of UHI. The areas where there wasmore vegetation cover had less temperature while in urban areas, the temperature was measured higher. Over the periodof 36 days, the average UHI remained 5.5°C and the highest intensity of UHI was observed as 8.3°C thus augmentedresearch rationale. The study suggests establishment of a thick network of automatic weather stations in Lahore togauge the urban heat island intensity and to plant indigenous trees on vacant swaths and develop urban forest tomitigate city’s rising temperature

Claudin-1 required for HCV virus entry has high potential for phosphorylation and O-glycosylation

HCV is a leading cause of hepatocellular carcinoma and cirrhosis all over the world. Claudins belong to family of tight junction's proteins that are responsible for establishing barriers for controlling the flow of molecules around cells. For therapeutic strategies, regulation of viral entry into the host cells holds a lot of promise. During HCV infection claudin-1 is highly expressed in liver and believed to be associated with HCV virus entry after HCV binding with or without co-receptor CD81. The claudin-1 assembly with tight junctions is regulated by post translational modifications. During claudins assembly and disassembly with tight junctions, phosphorylation is required at C-terminal tail. In cellular proteins, interplay between phosphorylation and O-β-GlcNAc modification is believed to be functional switch, but it is very difficult to monitor these functional and vibrant changes in vivo. Netphos 2.0 and Disphos 1.3 programs were used for potential phosphorylation; NetPhosK 1.0 and KinasePhos for kinase prediction; and YinOYang 1.2 and OGPET to predict possible O-glycosylation sites. We also identified Yin Yang sites that may have potential for O-β-GlcNAc and phosphorylation interplay at same Ser/Thr residues. We for the first time proposed that alternate phosphorylation and O-β-GlcNAc modification on Ser 192, Ser 205, Ser 206; and Thr 191 may provide an on/off switch to regulate assembly of claudin-1 at tight junctions. In addition these phosphorylation sites may be targeted by novel chemotherapeutic agents to prevent phosphorylation lead by HCV viral entry complex

Serine 204 phosphorylation and O-<it>β</it>-GlcNAC interplay of IGFBP-6 as therapeutic indicator to regulate IGF-II functions in viral mediated hepatocellular carcinoma

Abstract Hepatocellular carcinoma is mainly associated with viral hepatitis B and C. Activation of cell growth stimulator IGF-II gene is observed in tumor formation especially in viral associated hepatocellular carcinoma. Elevated IGF-II levels are indicator of increased risk for cholangiocellular and hepatocellular carcinomas through over saturation of IGF-II binding capacities with IGF receptors leading to cellular dedifferentiation. In HCV, core protein is believed to trans-activate host IGF-II receptor through PKC pathway and the inhibition of tumor cell growth can be achieved by blocking IGF-II pathway either at transcriptional level or increasing its binding with IGFBPs (Insulin like growth factor proteins) at C-terminal, so that it is not available in free form. IGFBP-6 is a specific inhibitor of IGF-II actions. Affinity of IGFBPs with IGFs is controlled by post-translational modifications. Phosphorylation of IGFBPs inhibits IGFs action on target cells while O-glycosylation prevents binding of IGFBP-6 to glycosaminoglycans and cell membranes and resulting in a 10-fold higher affinity for IGF-II. O-glycosylation and phosphorylation operate the functional expression of cellular proteins, this switching on and off the protein expression is difficult to monitor in vivo. By using neural network based prediction methods, we propose that alternate O-β-GlcNAc modification and phosphorylation on Ser 204 control the binding of IGFBP-6 with IGF-II. This information may be used for developing new therapies by regulating IGFBP-6 assembly with IGF-II to minimize the risk of viral associated hepatocellular carcinoma. We can conclude that during HCV/HBV infection, O-β-GlcNAc of IGFBP-6 at Ser 204 diminish their binding with IGF-II, increase IGF-II cellular expression and promote cancer progression which can lead to hepatocellular carcinoma. Furthermore, this site can be used for developing new therapies to control the IGF-II actions during viral infection to minimize the risk of hepatocellular carcinoma.</p

Serine 204 phosphorylation and O-β-GlcNAC interplay of IGFBP-6 as therapeutic indicator to regulate IGF-II functions in viral mediated hepatocellular carcinoma

Hepatocellular carcinoma is mainly associated with viral hepatitis B and C. Activation of cell growth stimulator IGF-II gene is observed in tumor formation especially in viral associated hepatocellular carcinoma. Elevated IGF-II levels are indicator of increased risk for cholangiocellular and hepatocellular carcinomas through over saturation of IGF-II binding capacities with IGF receptors leading to cellular dedifferentiation. In HCV, core protein is believed to trans-activate host IGF-II receptor through PKC pathway and the inhibition of tumor cell growth can be achieved by blocking IGF-II pathway either at transcriptional level or increasing its binding with IGFBPs (Insulin like growth factor proteins) at C-terminal, so that it is not available in free form. IGFBP-6 is a specific inhibitor of IGF-II actions. Affinity of IGFBPs with IGFs is controlled by post-translational modifications. Phosphorylation of IGFBPs inhibits IGFs action on target cells while O-glycosylation prevents binding of IGFBP-6 to glycosaminoglycans and cell membranes and resulting in a 10-fold higher affinity for IGF-II. O-glycosylation and phosphorylation operate the functional expression of cellular proteins, this switching on and off the protein expression is difficult to monitor in vivo. By using neural network based prediction methods, we propose that alternate O-β-GlcNAc modification and phosphorylation on Ser 204 control the binding of IGFBP-6 with IGF-II. This information may be used for developing new therapies by regulating IGFBP-6 assembly with IGF-II to minimize the risk of viral associated hepatocellular carcinoma. We can conclude that during HCV/HBV infection, O-β-GlcNAc of IGFBP-6 at Ser 204 diminish their binding with IGF-II, increase IGF-II cellular expression and promote cancer progression which can lead to hepatocellular carcinoma. Furthermore, this site can be used for developing new therapies to control the IGF-II actions during viral infection to minimize the risk of hepatocellular carcinoma

A Comparative Systematic Literature Review on Knee Bone Reports from MRI, X-Rays and CT Scans Using Deep Learning and Machine Learning Methodologies

The purpose of this research was to provide a &ldquo;systematic literature review&rdquo; of knee bone reports that are obtained by MRI, CT scans, and X-rays by using deep learning and machine learning techniques by comparing different approaches&mdash;to perform a comprehensive study on the deep learning and machine learning methodologies to diagnose knee bone diseases by detecting symptoms from X-ray, CT scan, and MRI images. This study will help those researchers who want to conduct research in the knee bone field. A comparative systematic literature review was conducted for the accomplishment of our work. A total of 32 papers were reviewed in this research. Six papers consist of X-rays of knee bone with deep learning methodologies, five papers cover the MRI of knee bone using deep learning approaches, and another five papers cover CT scans of knee bone with deep learning techniques. Another 16 papers cover the machine learning techniques for evaluating CT scans, X-rays, and MRIs of knee bone. This research compares the deep learning methodologies for CT scan, MRI, and X-ray reports on knee bone, comparing the accuracy of each technique, which can be used for future development. In the future, this research will be enhanced by comparing X-ray, CT-scan, and MRI reports of knee bone with information retrieval and big data techniques. The results show that deep learning techniques are best for X-ray, MRI, and CT scan images of the knee bone to diagnose diseases