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

Impact of water scarcity on food security at macro 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 regression 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 Macro level.The models has traced an adverse impact of water scarcity water scarcity on food security at macro levels. 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, Macro level

Impact of water scarcity on food security at meso 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). Simultaneous, structural and reduced form 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 Meso level. The models have traced an adverse impact of water scarcity water scarcity on food security at Meso levels. 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, Meso level, Simultaneous equations

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

Utilizing Big Data Analytics to Improve Education

Analytics can be defined as the process of determining, assessing, and interpreting meaning from volumes of data. It has been categorized in three different categories - descriptive, predictive and prescriptive. Predictive analysis can serve many segments of society as it can reveal hidden relationship which may not be apparent with descriptive modeling. Analytics advancement plays an important role in higher education planning. It answers several questions such as -which students will enroll in particular course, what courses are on trending or obsolete, what is the level of student satisfaction in the current education system, effectiveness of online study environment, how to design a better curriculum, likelihood of students transfer, drop out or failure to complete the course. Not only, data analytics helps in analyzing above points but also can be helpful in predictive modeling for faculty, administrative and students groups who are looking out for genuine results about the university rankings, based on which they make their decisions. Using the dataset “Academic Ranking of World Universities, 2003-2014”, we studied and analyzed to forecast how university’s management and faculty could adapt to changes to improve their education and thereby the ranking of their universities in the upcoming years. Microsoft SQL Server Data Mining Add-ins Excel 2008 was employed as a software mining tool for predicting the trending university ranking. This research paper concentrates upon predictive analysis of university ranking using forecasting based on data mining technique

Enzymatic saccharification and lactic acid production from banana pseudo-stem through optimized pretreatment at lowest catalyst concentration

This work estimates the potential of banana pseudo-stem with high cellulosic content 42.2- 63 %, for the production of fermentable sugars for lactic acid production through statistically optimized pretreatment method. To evaluate the catalyzed pretreatment efficiency of banana pseudo stem based on the enzymatic digestibility, Response Surface Methodology (RSM) was employed for the optimization of pretreatment temperature and time using lowest concentrations of H2SO4, NaOH, NaOH catalyzed Na2S and Na2SO3 that seemed to be significant variables with P<0.05. High F and R2 values and low p-value for hydrolysis yield indicated the model predictability. The optimized condition for NaOH was determined to be conc. 1 %, temperature 130 oC for 2.6 hr; Na2S; conc. 1 %, temperature 130 oC for 2.29 hr; Na2SO3; conc. 1 %, temperature 130 oC for 2.41 hr and H2SO4; conc. 1 %, temperature 129.45 oC for 2.18 hr, produced 84.91 %, 85.23 %, 81.2 % and 76.02 % hydrolysis yield, respectively. Sulphuric acid provided 33+1 gL-1 reducing sugars in pretreatment step along with 38+0.5 gL-1 during enzymatic hydrolysis. Separate hydrolysis and fermentation of resulting sugars showed that the conversion of glucans into lactic acid reached 92 % of the theoretical yield of glucose

Comparion of different POS tagging technique (N-Gram, HMM and Brill's tagger) for Bangla

Includes bibliographical references (page 6-7).There are different approaches to the problem of assigning each word of a text with a parts-of-speech tag, which is known as Part-Of-Speech (POS) tagging. In this paper we compare the performance of a few POS tagging techniques for Bangla language, e.g. statistical approach (n-gram, HMM) and transformation based approach (Brill’s tagger). A supervised POS tagging approach requires a large amount of annotated training corpus to tag properly. At this initial stage of POS-tagging for Bangla, we have very limited resource of annotated corpus. We tried to see which technique maximizes the performance with this limited resource. We also checked the performance for English and tried to conclude how these techniques might perform if we can manage a substantial amount of annotated corpus.Naushad UzZamanFahim Muhammad HasanMumit Kha

Optimization of dilute acid pretreatment of water hyacinth biomass for enzymatic hydrolysis and ethanol production

The present study was conducted for the optimization of pretreatment process that was used for enzymatic hydrolysis of lignocellulosic biomass (Water Hyacinth, WH), which is a renewable resource for the production of bioethanol with decentralized availability. Response surface methodology has been employed for the optimization of temperature (oC), time (hr)and different concentrations of maleic acid (MA), sulfuric acid (SA) and phosphoric acid (PA) that seemed to be significant variables with P < 0.05. High F and R2 values and low P-value for hydrolysis yield indicated the model predictability. The pretreated biomass producing 39.96 g/l, 39.86 g/l and 37.9 g/l of reducing sugars during enzymatic hydrolysis with yield 79.93, 78.71 and 75.9 % from PA, MA and SA treated respectively. The order of catalytic effectiveness for hydrolysis yield was found to be phosphoric acid > maleic acid > sulfuric acid. Mixture of sugars was obtained during dilute acid pretreatment with glucose being the most prominent sugar while pure glucose was obtained during enzymatic hydrolysis. The resulting sugars, obtained during enzymatic hydrolysis were finally fermented to ethanol, with yield 0.484 g/g of reducing sugars which is 95 % of theoretical yield (0.51 g/g glucose) by using commercial baker’s yeast (Sacchromyces cerveasiae)

Knowledge and attitudes about tetanus and rabies: a population-based survey from Karachi, Pakistan

OBJECTIVE: To evaluate public knowledge regarding predisposing factors, fatality and prevention of Tetanus and Rabies and attitudes toward vaccination and post-exposure prophylaxis. METHODS: A population-based, cross-sectional survey was conducted in all the 18 towns of Karachi, the largest metropolitan city of Pakistan, from December 2007 to January 2008. Men and women of more than 18 years of age were included in the study which used a self-reporting questionarre as its tool. RESULTS: There were 1201 people interviewed by the study. The majority of respondents had known or heard about Tetanus (n = 973; 81%) and rabies (n = 699; 58%). There were 29 (2.5%) reported dog bites on the subjects themselves and 218(18%) respondents reported dog bites among their family members during the preceeding one year. Only three (11%) of these dog bite victims received some kind of vaccine or post-exposure prophylaxis. The majority of the participants were not aware of the fatality of these diseases and the importance of vaccination and post-exposure prophylaxis. Of the total respondents, 563 (47%) reported an injury or wound during the preceeding one year. Of them, 426 (76%) received a Tetanus injection. Out of the total study population, 1019 (85%) respondents did not know that Tetanus could be a fatal disease, and 844 (70%) did not know that Tetanus could affect and kill newborns. Literate people and males were more likely to have adequate knowledge on multivariate analysis. CONCLUSION: Minor injuries and dog bites are a common occurrence in Karachi. Only a small proportion of these patients received post-exposure treatment. Most of the participants were not aware of the fatality of these diseases and the importance and affordability of vaccination in case of dog bites and minor trauma

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