Cutting the Error by Half: Investigation of Very Deep CNN and Advanced Training Strategies for Document Image Classification

We present an exhaustive investigation of recent Deep Learning architectures, algorithms, and strategies for the task of document image classification to finally reduce the error by more than half. Existing approaches, such as the DeepDocClassifier, apply standard Convolutional Network architectures with transfer learning from the object recognition domain. The contribution of the paper is threefold: First, it investigates recently introduced very deep neural network architectures (GoogLeNet, VGG, ResNet) using transfer learning (from real images). Second, it proposes transfer learning from a huge set of document images, i.e. 400,000 documents. Third, it analyzes the impact of the amount of training data (document images) and other parameters to the classification abilities. We use two datasets, the Tobacco-3482 and the large-scale RVL-CDIP dataset. We achieve an accuracy of 91.13% for the Tobacco-3482 dataset while earlier approaches reach only 77.6%. Thus, a relative error reduction of more than 60% is achieved. For the large dataset RVL-CDIP, an accuracy of 90.97% is achieved, corresponding to a relative error reduction of 11.5%

The Role of FDI on Stock Market Development: The Case of Pakistan

The purpose of this study is to empirically analyze the role of foreign direct investment in developing host country’s stock markets and to examine whether they are related or not. The key interest turns around the admiring role of FDI in Stock market development of Pakistan. Our work also aims to investigate the effect of foreign direct investment along with domestic savings, exchange rate and inflation in developing Pakistan stock markets in a rapidly changing political environment. This study applies Ordinary Least Square (OLS) method of regression by using annual time series data for the period 1988-2009 in case of Pakistan to estimate empirical relationships among variables. The results disclose a positive impact of foreign direct investment along with other explanatory variables in developing Stock markets of Pakistan. The study findings can be used to help government policy makers to encourage FDI and take various steps to provide incentives and save foreign investors interest in a volatile political environment that prevailing in the country. Adequate facility of infrastructure can enhance FDI. The volatility of exchange rate and inflation rate should also be minimized through monitory policy while domestic savings must also be encouraged in the country through appropriate and encouraging saving policies. Our effort exclusively study development of Stock markets in Pakistan with special reference to foreign direct investment and other variables. Our study depicts a closer relationship between FDI and Stock Market Development

Poverty and Social Impact Analysis of Workers Welfare Fund

This study conducts the poverty and social impact analysis of the workers welfare fund (WWF) program across Pakistan. It finds that colossal documentation, delayed free disbursement, and distance of school from home are the main hurdles in the way of education. New housing schemes are moving at a slower pace with compromised quality, and repair work is not being done on a regular basis. Sanitation and sewerage issues in labour colonies are creating health and environmental hazard. Discrimination in health care facilities and rent-seeking is very obvious. There is a detailed process review of WWF that borrows advice from such programs in other parts of the world. It is important to note that after the 18th constitutional amendment, labour market reforms are now responsibilities of provincial governments. However we explain that such a transition is painstakingly slow. Keywords: Education, Conditional cash transfers, Gender balanc

Circulating microRNAs in oncogenic viral infections: potential diagnostic biomarkers

Cancer is a leading cause of high death rate worldwide. One strategy to control the disease is the early diagnosis by novel biomarkers that express during early stage of the disease. The recent diagnostic strategies in cancer don’t have enough specificity to promote the detection of cancer at its beginning. Many biomarkers like protein biomarkers and metabolites are being used for diagnosis of various cancer types but miRNAs are excellent among them, because they have distinctive biochemical characteristics. Moreover, to raise the precision and capability of miRNA to diagnose cancer, the analyzing of both miRNAs and as well as selective mRNA will help in creating a more complete categorizer. Virus constitutes the cause of 20% of entire human cancer cases and both RNA and DNA viruses are linked with tumors in both animal and man. Even though many viruses can cause different tumors in animals, only some of them are linked with human cancers and are presently regarded as oncogenic viruses. These viruses include Human Papillomavirus (HPV), Hepatitis B (HBV) and Hepatitis C Virus (HCV), Epstein Barr Virus (EBV), Human Herpes Virus 8 (HHV8), Human T cell Leukemia Virus (HTLV) and Merkel Cell Polyomavirus (MCPyV). Expression data of miRNA in several cancers reveal that miRNA profile is different in cancer cells as compared to normal cells. So, miRNA could be useful biomarker for the detection of cancer. The present study strengthens a foundation and gives a logic to investigate the ability of miRNAs as circulating biomarkers in various cancers

Progranulin in frontotemporal lobar degeneration and neuroinflammation

Progranulin (PGRN) is a pleiotropic protein that has gained the attention of the neuroscience community with recent discoveries of mutations in the gene for PGRN that cause frontotemporal lobar degeneration (FTLD). Pathogenic mutations in PGRN result in null alleles, and the disease is likely the result of haploinsufficiency. Little is known about the normal function of PGRN in the central nervous system apart from a role in brain development. It is expressed by microglia and neurons. In the periphery, PGRN is involved in wound repair and inflammation. High PGRN expression has been associated with more aggressive growth of various tumors. The properties of full length PGRN are distinct from those of proteolytically derived peptides, referred to as granulins (GRNs). While PGRN has trophic properties, GRNs are more akin to inflammatory mediators such as cytokines. Loss of the neurotrophic properties of PGRN may play a role in selective neuronal degeneration in FTLD, but neuroinflammation may also be important. Gene expression studies suggest that PGRN is up-regulated in a variety of neuroinflammatory conditions, and increased PGRN expression by microglia may play a pivotal role in the response to brain injury, neuroinflammation and neurodegeneration

Evaluation of Antibiotic Resistance and Virulence Genes among Clinical Isolates of Pseudomonas aeruginosa from Cancer Patients

Objectives: The objectives of this study were to evaluate P. Aeruginosa isolates from cancer patients for the phenotypic pattern of antibiotic resistance and to detect the gene responsible for virulence as well as antibiotic resistance. Methods: A total of 227 P. aeruginosa isolates were studied and 11 antibiotics were applied for susceptibility testing. PCR detection of the genes BIC, TEM, IMP, SPM, AIM, KPC, NDM, GIM, VIM, OXA, toxA and oprI was done. Finally, the carbapenem resistant isolates were tested for phenotypic identification of carbapenemase enzyme by Modified Hodge test. Results: The results showed that the isolates were resistant to imipenem (95%), cefipime (93%), meropenem (90%), polymixin B (71%), gentamicin (65%), ciprofloxacin (48%), ceftazidime (40%), levofloxacin (39%), amikacin (32%), tobramycin (28%) and tazobactum (24%). The PCR detection of the carbapenem resistant genes showed 51% isolates were positive for IMP, GIM and VIM, 38% for AIM and SPM, 30% for BIC, 20% for TEM and NDM, 17% for KPC and 15% for OXA. However, toxA and oprI genes were not detected. 154 carbapenem resistant isolates were found positive phenotypically for carbapenemase enzyme identification by Modified Hodge test. Conclusion: The co-existence of multiple drug-resistant bodies and virulent genes has important implications for the treatment of patients. This study provides information about treating drug-resistant P. Aeruginosa and the relationship of virulent genes with phenotypic resistance patterns