Impact of water scarcity on food security at micro level in Pakistan

Pakistan is confronting the problem of water scarcity which is rendering an adverse impact on food security. The study examines the impact of water scarcity on food security in an era of climate change. It further focuses on projecting the future trends of water and food stock. The research effort probes the links among water scarcity, climate change, food security, water security, food inflation, poverty and management of water resources. Data on food security was collected from the FSA (Food Security analysis) of the Sustainable development Policy institute (SDPI) and Food insecurity and Vulnerability Information mapping system (FIVIMS). Logistic equations have been employed to catch the effect of water scarcity on three components of food security separately. In fact, the present study develops a series of models that captures the impact of water scarcity on the components of food security at Micro level. The models have traced an adverse impact of water scarcity water scarcity on food security at Micro level. The findings so obtained may help in proposing the policy guidelines for overcoming water scarcity and handling with food insecurity caused by water scarcity and other factors.Water scarcity, Water supply, Water Demand, Food security, Micro level, Logistic regression

Behavior and Strength of RC Spandrel Members Under Unsymmetrical Bending and Torsion Including CFRP Retrofitting

This dissertation presents the outcome of an experimental and theoretical investigation of the behavior and strength of reinforced concrete spandrel members both with and without carbon fiber reinforced polymer (CFRP) retrofitting. Both isolated spandrel members with L-shaped cross section as well as those integrated with reinforced concrete slabs are studied. A series of isolated spandrel members were tested under separate and combined actions of unsymmetrical bending and torsion. Six of these specimens were retrofitted externally with high-strength CFRP strips. Materially nonlinear analysis procedures are also formulated and programmed for the spandrel members with and without CFRP retrofitting. Furthermore, ultimate bending-torsion interaction expressions for the spandrel members are developed including the influence of CFRP retrofitting. Tests are also conducted on three slab-beam systems up to their load-carrying capacities. Theoretically predicted behavior and strength of the spandrel members and slab-beam systems are found to be in good agreement with those based on the laboratory tests. The study shows that CFRP retrofitting results in a significant to a dramatic increase in the bending strength of L-shaped spandrel members. The use of CFRP retrofitting is also shown to increase the torsional strength of such members by up to fifty percent

Natural and engineered resistance to wheat streak mosaic virus (Tritimovirus: Potyviridae)

Wheat streak mosaic virus (WSMV) is a new virus of wheat crop in Australia. Discovered in the Australian Capital Territory (ACT) in 2003, the virus has put Australian commercial bread wheat at a risk of major losses. Although, the virus is naturally transmitted by Wheat curl mites (WCM), some of the Australian farming community expressed concerns that grazing of early sown, dual-purpose wheat for winter forage may have a role in the spread of WSMV. We probed this issue in a series of experiments with housed sheep grazing on WSMV infected wheat plants. However, we find no evidence for the suggestion that grazing sheep spread the WSMV between plants in a grazed wheat crop as a consequence of the grazing process itself. We tested for natural resistance against WSMV in diverse germplasm including three different known resistance sources in cultivated wheat. Previously reported resistances were effective against the Australian isolate of WSMV. Some accessions of these resistances were ineffective at higher temperatures (all Wsm1 and most Wsm2 accessions); some were reported to have linked negative agronomic traits (most accessions of Wsm1). Two exceptions were c2652 and Wsm2 accession CA745 which were very effective at controlled higher temperatures (28{u00B0}C), in the glasshouse, and also protected plants from symptoms and yield loss following WSMV mechanical inoculation in the field, making these two sources particularly useful in the relatively warm Australian agro-climate. New molecular markers were developed for the various derivatives of Wsm1 resistance that should help speed up the breeding of resistance into wheat cultivars. These Wsm1 markers are now being used by CSIRO for breeding Wsm1-resistance into elite wheat cultivars. Furthermore, we developed and tested two independent transgenic strategies based on intron-hairpin RNA (ihpRNAi) and artificial microRNAs (amiRNA). Both strategies were effective in conferring immunity in transgenic wheat to mechanically inoculated WSMV. We classified this resistance as immunity by four criteria: no disease symptoms were produced; Enzyme linked immunosorbent assay (ELISA) readings were as in un-inoculated plants; viral sequences could not be detected by RT-PCR from leaf extracts; and leaf extracts failed to give infections in susceptible plants when used in test-inoculation experiments. We developed ihpRNA or RNAi based immune transgenic wheat by designing an RNAi construct to target the Nuclear inclusion protein 'a' (NIa) gene of WSMV. The Northern and Southern blot hybridization analysis indicated the ihpRNA transgene integrated into the wheat genome and was processed into typical 21-24 nucleotide long siRNAs and correlated with immunity in transgenic plants. In order to achieve amiRNA immunity, we designed five artificial microRNAs (amiRNA) against different portions of the WSMV genome, utilising published miRNA sequence and folding rules; these amiRNAs were incorporated into five duplex arms of the polycistronic rice primary microRNA (pri-miR395) and transformed into wheat. Southern blot hybridisation showed that the transgene was stably integrated into the wheat genome and processed into small RNAs, both correlating with transgenic resistance against WSMV. As a consequence of the work described in this thesis, the wheat industry in Australia and abroad has both conventional and transgenic options for the control of this serious viral pathogen

Testing the law of one price in gram, mash and masoor markets of Pakistan

This study examines the market integration of three pulses explicitly known as gram, masoor and mash in Pakistan. The study develops a critical estimation of market integration in pulses market of Pakistan. Market integration provides valuable information about the dynamics of market adjustment and has implications for a sustainable agriculture development. The government intervention might be justified by market integration as this phenomenon raises a question whether there are present market imperfections. This study used the monthly wholesale price (Rs. /40kg) data from January 1991 to September 2010 of gram, mash and masoor in logarithmic form and empirically estimated the degree of integration in the markets of the three pulses. The study is employing an econometric technique of co-integration analysis. Co-integration results show that all gram, masoor and mash markets are highly co-integrated in the long run. The high degree of market integration observed in this case is consistent with the view that Pakistan’s pulses markets are quite competitive and provide little justification for extensive and costly government intervention designed to improve competitiveness to enhance market efficiency

Predicting Educational Relevance For an Efficient Classification of Talent

This research work utilizes machine learning approach to build a predictive model for the prediction of the students and the job seekers’ to quantify their fitness's for the courses and jobs they plan to pursue, respectively. Some of the existing research utilizes GPA for academic prediction and use personality prediction and computing in social domains for various industrial goals. On the other hand, this research work advances the state of the art to correlate and blend the personality features with the academic attributes to identify and classify the relevant talent of the individuals for the academic and real world success with improved predictive modeling. This work incorporates three algorithms to quantify a talent in the relevance, and then predict good fit students and good fit candidates, based on supervised learning, stochastic probability distribution and classification rules, etc. This work opens many opportunities for future research towards Genomics data mining to mine individuals for various areas

We Are What We Generate - Understanding Ourselves Through Our Data

AbstractWe have tendency to exhibit ourselves through the data we share about ourselves including, liking, friendship, follows, disliking, pictures, audio, videos, causes, blogs and sites. Such data about us have already been used by big data companies to create customized ads and marketing tactics. However, while such data being in unstructured and noisy format, utilization and research is at its early stages. In this paper, we elaborate on the idea of understanding individuals through lens of data they produce in context of our main research work for Predicting Educational Relevance For an Efficient Classification of Talent (PERFECT) algorithm engine. We illustrate some of research problems in relevance of such data and identify research problem as ground for this paper. We present sub set of our framework including algorithm and math constructs, for the problem we identify. We conclude that such analytics and cognitive research can help to improve education, healthcare, Job economy, crime control, etc. Thus we coin the phrase “we are what we generate”, with our work in this paper. We suggest future work and opportunities in relevant directions