A study protocol : using demand-side financing to meet the birth spacing needs of the underserved in Punjab Province in Pakistan

Background: High fertility rates, unwanted pregnancies, low modern contraceptive prevalence and a huge unmet need for contraception adversely affect women's health in Pakistan and this problem is compounded by limited access to reliable information and quality services regarding birth spacing especially in rural and underserved areas. This paper presents a study protocol that describes an evaluation of a demand-side financing (DSF) voucher approach which aims to increase the uptake of modern contraception among women of the lowest two wealth quintiles in Punjab Province, Pakistan. Methods/Design: This study will use quasi-experimental design with control arm and be implemented in: six government clinics from the Population Welfare Department; 24 social franchise facilities branded as `Suraj' (Sun), led by Marie Stopes Society (a local non-governmental organization); and 12 private sector clinics in Chakwal, Mianwali and Bhakkar districts. The study respondents will be interviewed at baseline and endline subject to voluntary acceptance and medical eligibility. In addition, health service data will record each client visit during the study period. Discussion: The study will examine the impact of vouchers in terms of increasing the uptake of modern contraception by engaging private and public sector service providers (mid-level and medical doctors). If found effective, this approach can be a viable solution to satisfying the current demand and meeting the unmet need for contraception, particularly among the poorest socio-economic group

Detection of immunoglobulins and complement components in formalin fixed and paraffin embedded renal biopsy material by immunoflourescence technique

Background: The technique of direct immunoflourescence (IF) is essential in the accurate diagnosis of renal glomerular diseases. The optimal results are obtained when the procedure is done on fresh frozen tissue (IF-F). However, techniques are available for IF study on formalin fixed and paraffin embedded (FFPE) renal biopsy specimens with variable reported success rates. Objectives: We evaluated three such techniques on FFPE tissue and compared the results with those obtained by IF-F from the same patients. Materials and Methods: Heat treatment with Tris buffer and citrate buffer, and pronase treatment of the FFPE material was carried out. Direct IF was done for renal panel immunoglobulins and complement components on all biopsies and the results were compared with the historical IF-F study. Results: When compared to the IF-F, the immunoflourescence staining on the paraffin sections was less sensitive and less intense in all immune complex-mediated renal diseases, but the diagnostic findings were detected in majority of the cases. Conclusions: In conclusion, it is possible to establish the diagnosis in most cases of immune complex-mediated glomerular diseases with IF on paraffin embedded tissue specimens

A novel hybrid technique using fuzzy logic, neural networks and genetic algorithm for intrusion detection system

As the number of people who use the internet continues to rapidly increase, security has become an increasingly important concern in the online world. Many researchers in the past have developed detection systems to identify and detect intruders using data mining. These systems can be found in use today. However, the existing methods had the disadvantages in terms of detection accuracy and time overhead. To enhance the IDS detection accuracy and reduces the required time a novel intrusion detection system is proposed that will ensure the safety of data communication by locating any unauthorized users and efficiently identifying any unwanted visitors to wireless networks. In this paper, a hybrid algorithm is proposed for the removal of uncertainty and the prediction of outcomes. Fuzzy logic is utilized in the process of removing uncertainty, whereas neural networks are utilized for the purpose of prediction. The Genetic Algorithm is utilized in order to effect improvements in the accuracy of prediction results. Experiments have been carried out in order to evaluate the proposed intrusion detection system, which has an overall detection accuracy of 99.12 %. The proposed model's performance has been put to evaluation utilizing tenfold cross-validation, which has been completed