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Prion Protein Genotypes in Pakistani Goats
Babar, M.E.,Nawaz, M.,Nasim, A.,Abdullah, M.,Imran, M.,Jabeen, R.,Chatha, S.A.,Haq, A.U.,Nawaz, A.,Mustafa, H.,Nadeem, A. Asian Australasian Association of Animal Productio 2008 Animal Bioscience Vol.21 No.7
The PCR-amplified prion protein (PrP) gene was sequenced to determine the frequency of scrapie-associated as well as novel PrP genotypes in 72 healthy goats representing five breeds. A total of six genotypes were detected, resulting from the three reported 143 (H/R), 154 (R/H) and 240 (S/P) and the two novel 39 (S/R) and 185 (I/F) amino acid polymorphisms. Of the four silent mutations 42 (a$\rightarrow$g), 138 (c$\rightarrow$t), 231 (c$\rightarrow$a) and 237 (g$\rightarrow$c) detected in this study, 237 (g$\rightarrow$c) is novel. A genotype (SIP/RFP) harboring three amino acid polymorphisms 39 (S/R), 185 (I/F) and 240 (S/P) was found in few goats. Although both scrapie-associated genotypes with 143 (H/R) and 154 (R/H) polymorphisms and others with 39 (S/R), 185 (I/F) and 240 (S/P) polymorphisms were present in the studied Pakistani goats, their frequency was lower than that of the wild-type genotype SHRIS/SHRIS (34.7%). These results emphasize the need for further sequencing of the PrP gene in a large number of goats representing the five studied breeds, so that overall PrP variability can be assessed in these breeds in research addressing future concerns about scrapie.
SILAR deposited iron phosphate as a bifunctional electrocatalyst for efficient water splitting
Babar, P.T.,Lokhande, A.C.,Shim, H.J.,Gang, M.G.,Pawar, B.S.,Pawar, S.M.,Kim, Jin Hyeok Elsevier 2019 JOURNAL OF COLLOID AND INTERFACE SCIENCE - Vol.534 No.-
<P><B>Abstract</B></P> <P>The development of efficient and earth-abundant electrocatalysts for overall water splitting is important but still challenging. Herein, iron phosphate (FeP<I>i</I>) electrode is synthesized using a successive ionic layer deposition and reaction (SILAR) method on a nickel foam substrate at room temperature and is used as a bifunctional electrocatalyst for water splitting. The prepared FeP<I>i</I> electrodes show excellent electrocatalytic activity and stability for the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). The FeP<I>i</I> electrode exhibits low overpotential of 230 mV and 157 mV towards the OER and HER, respectively, with superior long-term stability. As a result, an electrolyzer that exploits FeP<I>i</I> as both the anode and the cathode is constructed, which requires a cell potential of 1.67 V to deliver a 10 mA cm<SUP>−2</SUP> current density in 1 M KOH solution. The exceptional features of the catalyst lie in its structure and active metal sites, increasing surface area, accelerated electron transport and promoted reaction kinetics. This study may provide a facile and scalable approach to design a high-efficiency, earth-abundant electrocatalyst for water splitting.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
P.T. Babar,A.C. Lokhande,조은애,B.S. Pawar,M.G. Gang,S.M. Pawar,J.H. Kim 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.70 No.-
Porous iron–nickel hydroxyphosphate and iron–cobalt hydroxyphosphate electrodes are prepared byone-step electrodeposition method. The as-prepared iron–nickel hydroxyphosphate and iron–cobalthydroxyphosphate electrodes show excellent performance for water splitting with high catalytic activitytowards the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), with a loweroverpotential of 220 and 235 mV for the OER and 145 and 160 mV for the HER, respectively. Moreover,two-electrode electrolyzer using iron-nickel hydroxyphosphate as both the anode and cathode requires acell voltage of 1.65 V while iron–cobalt hydroxyphosphate requires cell voltage of 1.67 V to gain currentdensity of 10 mA cm 2.
Smart Cities’ Automatic Image-Based Waste Segregation through an Intelligent Agent Using CNN
Joan Conag Vargas,Sheikh Babar Hameed,Taliah Tajammal,Gulzar Ahmad,Rahat H. Bokhari 한국차세대컴퓨팅학회 2022 한국차세대컴퓨팅학회 학술대회 Vol.2022 No.10
Rapidly growing innovative technologies enabled human beings to enjoy smart city services despite the development of such cities are still facing several challenges needed to be addressed. The waste management in smart cities particularly its segregation by smart methods is one of the primary concerns as the amount of waste generated every day by citizens is increasing. A comprehensive intelligent waste management system is direly needed to address the situation. This article aims to segregate recyclable and non-recyclable types of garbage collected from smart cities using the Intelligent Agent proposed and developed so far. The expected smart solution should provide the best level of accuracy at the lowest possible cost. Our study proposed a model to differentiate and segregate waste into recyclable and organic objects based on Intelligent Agent developed using a Convolutional Neural Network (CNN). The model proposed comprises of Intelligent Agent developed and the existing CNN model which is commonly used for transfer learning. The classification accuracy achieved is up to 93.27% which is better than the already published results of different models discussed in the recent past research studies. Furthermore, how can recyclable and organic waste be utilized in the future is part of our ongoing study. The findings may be of interest to practitioners and the researchers’ community working in the relevant field.