Determinants of Urban Poverty: The Case of Medium Sized City in Pakistan

Urban poverty, which is distinct from rural poverty due to demographic, economic and political aspects remain hitherto unexplored, at the city level in Pakistan. We have examined the determinants of urban poverty in Sargodha, a medium-size city of Pakistan. The analysis is based on the survey of 330 households. Results suggest that employment in public sector, investment in human capital and access to public amenities reduce poverty while employment in informal sector, greater household size and female dominated households increase poverty. We recommend greater investment in human capital and public amenities as a strategy for poverty alleviation.Urban Poverty, Pakistan

Determinants of Urban Poverty : The Case of Medium Sized City in Pakistan

Urban poverty, which is distinct from rural poverty due to demographic, economic and political aspects remain hitherto unexplored, at the city level in Pakistan. We have examined the determinants of urban poverty in Sargodha, a medium-size city of Pakistan. The analysis is based on the survey of 330 households. Results suggest that employment in public sector, investment in human capital and access to public amenities reduce poverty while employment in informal sector, greater household size and female dominated households increase poverty. We recommend greater investment in human capital and public amenities as a strategy for poverty alleviation.Urban Poverty, Pakistan

Stack-run adaptive wavelet image compression

We report on the development of an adaptive wavelet image coder based on stack-run representation of the quantized coefficients. The coder works by selecting an optimal wavelet packet basis for the given image and encoding the quantization indices for significant coefficients and zero runs between coefficients using a 4-ary arithmetic coder. Due to the fact that our coder exploits the redundancies present within individual subbands, its addressing complexity is much lower than that of the wavelet zerotree coding algorithms. Experimental results show coding gains of up to 1:4dB over the benchmark wavelet coding algorithm

The impact of human capital on urban poverty: The case of Sargodha city

The positive relationship between human capital and income/wages has been supported by empirical research. Millennium Development Goals (MDGs) and the Poverty Reduction Strategy Paper (PRSP) enormously emphasize on human capital for curbing poverty. The economic development in East Asian countries is also linked with investment in education for the development of human capital. This study is designed to investigate the relationship of different levels of education and experience upon urban poverty at medium sized city in Pakistan such as Sargodha. A survey-based analysis was carried out on a sample of 330 households. Poverty status of the individual is defined by using adjusted official poverty line. Results show that education and experience is negatively related with the poverty status of individuals and this fact sustains even in separate gender estimates as well. This implies education of poor is necessary in breaking the vicious circle of poverty. Combined effort by public, private, community participation and NGO’s with special focus on elementary (Primary and middle) education is suggested for reducing poverty by increasing the productivity of the poor through education.Human Capital, Urban Poverty, Sargodha, Pakistan

Determinants of Urban Poverty: The Case of Medium Sized City in Pakistan

The process of urbanisation has dual impact on the development process of an economy. Initially, it encourages the workers to switch from low productive sector i.e. agriculture to high productive sectors like services and manufacturing [Becker, et al. (1994)]. Subsequently, it generates formidable problems for residents by depriving them of access to essential basic needs [Egziabher (2000)]. It is also observed that the poor try to urbanise faster as compared to the whole population [Ravallion (2007)] and this urbanisation process leads toward the emergence of urban poverty. Urban poverty is distinct from the rural poverty with respect to its incidence, economic, demographic and political aspects. The urban poverty can be controlled by developing the clear understanding of its nature, magnitude and intensit

THERAPEUTIC DRUG TRIAL IN ALBINO MICE AGAINST TRYPANOSOMIASIS

This study was conducted to determine the trypanocidal efficacy of Antrycide, Fatrybanil and Trypamedium in albino mice experimentally infected sub-cutaneously with Trypanosoma evansi. For this purpose, 25 albino mice were randomly divided into five equal groups i.e. A, B, C, D and E. Groups A, B and C were infected and then treated with Antrycide, Fatrybanil and Trypamedium, respectively. Group D was kept as infected and group E non-infected control. On the basis of blood smear examination, the efficacy of Antrycide and Fatrybanil was found 100% when used in single dose as compared to Trypamedium which was 100% effective with second dose

Lumbar Spine Aneurysmal Bone Cyst

An Aneurysmal Bone Cyst (ABC) is a benign, locally aggressive, vascular, and expansile bony tumor of idiopathic etiology containing multiple thin-walled blood-filled channels, mostly diagnosed in pediatric and adolescent age groups. These lesions can cause local pain, pathological fractures, spinal deformity, and neurological deficits. The treatment of choice for ABC is highly debatable according to the literature. The treatment choices are simple curettage and grafting, complete surgical resection with or without prior selective arterial embolization, radiotherapy, or a combination of these procedures according to the case. Each modality is having different outcomes, technical requirements, and complications. We are reporting a case of Aneurysmal Bone Cyst of the lumbar spine in a young patient treated by surgery

Risk factors for mortality of patients with ceftriaxone resistant E. coli bacteremia receiving carbapenem versus beta lactam/beta lactamase inhibitor therapy

Objective: Extended spectrum β-lactamases (ESBL) producing Enterobacteriaceae predominantly E. coli and K. pneumoniae bacteremia have limited treatment options and high mortality. The objective was to determine the risk factors for in-hospital mortality particularly treatment with carbapenem versus beta lactam/beta lactamase combination (BL/BLI) in patients with ceftriaxone resistant E. coli bacteremia. A retrospective cohort study was conducted at the Aga Khan University, Karachi, Pakistan. Adult patients with sepsis and monomicrobial ceftriaxone resistant E. coli bacteremia were enrolled. Factors associated with mortality in patients were determined using logistic regression analysis. Results: Mortality rate was 37% in those empirically treated with carbapenem compared to 20% treated with BL/BLI combination therapy (p-value: 0.012) and was 21% in those treated with a carbapenem compared to 13% in patients definitively treated with BL/BLI combination therapy (p-value: 0.152). In multivariable logistic regression analysis, only Pitt bacteremia score of ≥ four was significantly associated with mortality (OR: 7.7 CI 2.6-22.8) while a urinary source of bacteremia was protective (OR: 0.26 CI 0.11-0.58). In-hospital mortality in patients with Ceftriaxone resistant E. coli bacteremia did not differ in patients treated with either a carbapenem or BL/BLI combination. However, Pitt bacteremia score of ≥ 4 was strongly associated with mortality

Context-aware convolutional neural network for grading of colorectal cancer histology images

Digital histology images are amenable to the application of convolutional neural networks (CNNs) for analysis due to the sheer size of pixel data present in them. CNNs are generally used for representation learning from small image patches (e.g. 224 × 224) extracted from digital histology images due to computational and memory constraints. However, this approach does not incorporate high-resolution contextual information in histology images. We propose a novel way to incorporate a larger context by a context-aware neural network based on images with a dimension of 1792 × 1792 pixels. The proposed framework first encodes the local representation of a histology image into high dimensional features then aggregates the features by considering their spatial organization to make a final prediction. We evaluated the proposed method on two colorectal cancer datasets for the task of cancer grading. Our method outperformed the traditional patch-based approaches, problem-specific methods, and existing context-based methods. We also presented a comprehensive analysis of different variants of the proposed method