Public Sector Innovation: Case Study of e-government Projects in Pakistan

This study analyses and examines in detail the impact of public sector innovation to improve public satisfaction level, it is about changing the traditional government into a more integrated and efficient one. Innovation is actually the engine of economic growth. Innovation in the public sector is an under-researched area. It deals with governance, political and human issues which are very difficult to solve. Since much of the topic and studies on innovation are focusing on the private sector, it is the aim of this study to analyse the process of innovation, mainly in Information and Communication Technology (ICT) in the public sector. This study will eventually be able to give e-government model/ guidelines that encapsulates the reality of innovation by the government. Innovation in government is not only about bringing a new breakthrough product to the people, but also to bring in changes to the culture in the organisation, the way a decision is made, and perhaps more importantly, how it can use technology to strengthen its role as the provider of social and economic welfare to the people. This study has also compared the findings of the e-government case study to the literature of innovation mainly in the area of process innovation. There is SWOT analysis with weight rating to judge the e-governance challenges, which Pakistan is facing as a developing nation. The study concludes that the public sector needs to overcome its traditional characteristics of poor agenda setting, unclear objectives, lack of transparency, and bureaucratic layers of decision-making processes. Keywords: Citizens, e-government Projects, ICT, Public Satisfaction, Public Sector Innovatio

Electrocardiogram as prognostic and diagnostic parameter in follow up of patients with heart failure

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Almost 25 years of chromatographic and spectroscopic analytical method development for petroleum hydrocarbons analysis in soil and sediment: State-of-the-art, progress and trends

This review provides a critical insight into the selection of chromatographic and spectroscopic techniques for semi-quantitative and quantitative detection of petroleum hydrocarbons in soil and sediment matrices. Advantages and limitations of both field screening and laboratory-based techniques are discussed and recent advances in chemometrics to extract maximum information from a sample by using the optimal pre-processing and data mining techniques are presented. An integrated analytical framework based on spectroscopic techniques integration and data fusion for the rapid measurement and detection of on-site petroleum hydrocarbons is proposed. Furthermore, factors influencing petroleum hydrocarbons analysis in contaminated samples are discussed and recommendations on how to reduce their influence provided

Rapid detection of alkanes and polycyclic aromatic hydrocarbons in oil-contaminated soil with visible near-infrared spectroscopy

Recent developments and applications of rapid measurement tools (RMTs) such as visible near‐infrared (vis–NIR) spectroscopy confirmed that these technologies can provide ‘fit for purpose’ and cost‐effective data for risk assessment and management of oil‐contaminated sites. Although vis–NIR spectroscopy has been used frequently to predict total petroleum hydrocarbons (TPHs), it has had limited use for polycyclic aromatic hydrocarbons (PAHs) and there has been none for alkanes. In the present study, the potential of vis–NIR spectroscopy (350–2500 nm) to measure PAHs and alkanes in 85 fresh (wet, unprocessed) oil‐contaminated soil samples collected from three sites in the Niger Delta, Nigeria, was evaluated. The vis–NIR signal and alkanes and PAHs measured in the laboratory by sequential ultrasonic solvent extraction followed by gas chromatography‐mass spectrometry (GC‐MS) were then used to develop calibration models using partial least squares regression (PLSR) and random forest (RF) modelling tools. Prior to model development, the pre‐processed spectra were divided into calibration (75%) and prediction (25%) sets. Results showed that the prediction performance of RF calibration models for both alkanes (a coefficient of determination (R2) of 0.58, a root mean square error of prediction (RMSEP) of 53.95 mg kg−1 and a residual prediction deviation (RPD) of 1.59) and PAHs (R2 = 0.71, RMSEP = 0.99 mg kg−1 and RPD = 1.99) outperformed PLSR (R2 = 0.36, RMSEP = 66.66 mg kg−1 and RPD = 1.29, and R2 = 0.56, RMSEP = 1.21 mg kg−1 and RPD = 1.55, respectively). The RF modelling approach accounted for nonlinearity of the soil spectral responses and therefore resulted in considerably greater prediction accuracy than the linear PLSR. Adoption of vis–NIR spectroscopy coupled with RF is recommended for rapid and cost‐effective assessment of PAHs and alkanes in contaminated soil

The relationship between serum osteopontin level and parameters of Chronic Kidney Disease – mineral bone disease in patients on regular hemodialysis

Background: Chronic Kidney Disease (CKD) is becoming a major health concern worldwide. For many patients, CKD is associated with substantial morbidity and mortality. Osteopontin (OPN) is an extracellular matrix protein first identified in bone tissue and has pleiotropic functions due to its common expression in the main organs and apparatuses. It is a phosphorylated glycophosphoprotein composed of 314 amino acids, involved in biomineralization and remodeling.Objective: This research aimed to assess the serum level of osteopontin in patients with end-stage renal disease (ESRD) on regular haemodialysis and to correlate osteopontin level in patients with ESRD on hemodialysis with other biomarkers CKD-MBD.Patients & Methods: This Study was conducted on 160 participants that were divided into two groups. Control group included 80 healthy subjects of both sexes, and patients group that included 80 ESRD patients on regular hemodialysis of both sexes. All studied groups were subjected to osteopontin level by enzyme-linked immunosorbent assay (ELISA).Results: Serum osteopontin levels were higher in ESRD patients on regular dialysis than in healthy individuals, where it might have a higher predictive value for CKD development. Also, they were positively correlated with serum phosphorus, serum alkaline phosphatase and serum parathyroid hormone, which are parameters of chronic kidney disease-mineral and bone disorder.Conclusion: Osteopontin may be considered an early marker of chronic kidney disease

Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy

The selection of calibration method is one of the main factors influencing measurement accuracy of soil properties estimation in visible and near infrared reflectance spectroscopy. In this study, the performance of three regression techniques, namely, partial least-squares regression (PLSR), support vector regression (SVR), and multivariate adaptive regression splines (MARS) were compared to identify the best method to assess organic matter (OM) and clay content in the salt-affected soils. One hundred and two soil samples collected from Northern Sinai, Egypt, were used as the data set for the calibration and validation procedures. The dry samples were scanned using a FieldSpec Pro FR Portable Spectroradiometer (Analytical Spectral Devices, ASD) with a measurement range of 350–2500 nm. The spectra were subjected to seven pre-processed techniques, e.g., Savitzky–Golay (SG) smoothing, first derivative with SG smoothing (FD-SG), second derivative with SG smoothing (SD-SG), continuum removed reflectance (CR), standard normal variate and detrending (SNV-DT), multiplicative scatter correction (MSC) and extended MSC. The results of cross-validation showed that in most cases MARS models performed better than PLSR and SVR models. The best predictions were obtained using MARS calibration methods with CR prep-processing, yielding R2, root mean squared error (RMSE), and ratio of performance to deviation (RPD) values of 0.85, 0.19%, and 2.63, respectively, for OM; and 0.90, 5.32%, and 3.15, respectively, for clay content

BETTERMENT OF DICLOFENAC-INDUCED NEPHROTOXICITY BY PENTOXIFYLLINE THROUGH MODULATION OF INFLAMMATORY BIOMARKERS

Objectives: Diclofenac-induced nephrotoxicity is caused by oxidative stress which leads to lipid peroxidation and formation of free radicals. Pentoxifylline can ameliorates renal tissue injury by its anti-inflammatory, antifibrotic, and antioxidant effects, so it mitigates the progression of renal diseases. Therefore, the aim of this study was to evaluate the nephroprotective effects of pentoxifylline on diclofenac-induced nephrotoxicity in rats. Methods: A total of 30 male Sprague-Dawley rats were allocated into three groups, Group 1 (n=10): Rats treated with distilled water 5 ml/kg plus normal saline 5 ml/kg for 12 days, Group 2 (n=10): Rats treated with distilled water 5 ml/kg plus diclofenac 15 mg/kg for 12 days, and Group 3 (n=10): Rats treated with pentoxifylline 100 mg/kg plus diclofenac 15 mg/kg for 12 days. Blood urea, creatinine, malondialdehyde (MDA), superoxide dismutase (SOD-1), glutathione reductase (GSH), neutrophil gelatinase associated lipocalin (NGAL), kidney injury molecules (KIM-1) vitronectin (VTN), integrin (ITG) , interleukin-18 (IL-18) and cystatin-C were used to measure the severity of nephrotoxicity. Results: Diclofenac-induced nephrotoxicity led to significant elevation in blood urea, serum creatinine, MDA, IL-18, KIM-1, NGAL, serum ITG, and VTN with decrease of SOD-1 and GSH sera levels p<0.05. Treatment with pentoxifylline showed no significant effect on all biomarker levels compared to diclofenac group except on serum level KIM-1 and serum VTN, p<0.05. Conclusion: Pentoxifylline produced significant nephroprotective effect on diclofenac-induced nephrotoxicity through modulation of inflammatory biomarkers

Comparative study of bioethanol production from sugarcane molasses by using Zymomonas mobilis and Saccharomyces cerevisiae

The study was designed to compare the bioethanol production from Zymomonas mobilis and Saccharomyces cerevisiae using molasses as production medium. The focus was on the retention time at lab scale. Bioethanol and petroleum blend can be used in existing gasoline engines. Present study showed a more cost-effective procedure for production of ethanol from sugar-cane molasses by using bacterial strain "Z. mobilis". Laboratory scale unit was designed to perform the experiments through batch fermentation and to determine the impact of leading parameters, including fermentation temperature, pH, sugar concentration, and nutrients. S. cerevisiae produced 8.3% (v/v) bioethanol provided sugar concentration 14 g /100 ml with the fermentation efficiency of 92.5%. On the contrary, Z.mobilis produced 9.3% (v/v) bioethanol by utilizing 16 g/100 ml sugar with the fermentation efficiency of 90.5%. Effect of nutrients on fermentation was determined using molasses as feedstock. Thin layer chromatography was also performed to assess the possible impurities in molasses as compared to the pure sugar. The pH and fermentation temperature was optimized for the enhanced yield of bioethanol.Key words: Bioethanol, molasses, fermentation, Zymomonas mobilis, Saccharomyces cerevisiae

Rapid prediction of total petroleum hydrocarbons concentration in contaminated soil using vis-NIR spectroscopy and regression techniques

Petroleum hydrocarbons contamination in soil is a worldwide significant environmental issue which has raised serious concerns for the environment and human health (Brevik and Burgess, 2013). Petroleum hydrocarbons encompass a mixture of short and long-chain hydrocarbon compounds. However the difference between the term petroleum hydrocarbons (PHC) as such and the term total petroleum hydrocarbons (TPH) should be noted. PHC typically refer to the hydrogen and carbon containing compounds that originate from crude oil, while TPH refer to the measurable amount of petroleum-based hydrocarbons in an environmental matrix and thus to the actual results obtained by sampling and chemical analysis (Coulon and Wu, 2017). TPH is thus a method-defined term. Among a range of techniques, gas chromatography is preferred for the measurement of hydrocarbon contamination in environmental samples, since it allows to detect a broad range of hydrocarbons and can provide both sensitivity and selectivity depending on the detector and hyphenated configuration used (Brassington et al., 2010; Drozdova et al., 2013). However, GC-based techniques can be time consuming and expensive and do not allowed rapid and broad scale analysis of petroleum contamination on-site (Okparanma and Mouazen, 2013; Okparanma et al., 2014)