Exploring Social Issues in 'The Crybaby' Through Labovian Narrative Analysis Model

Narrative research is a framework of a qualitative research approach that involves the elicitation and analysis of stories to acquire a better knowledge of individuals, groups, and society. The content and structure of tales are used to develop and understand the information gathered through a narrative inquiry about persons and society. The purpose of this study was to conduct a qualitative investigation into Yudhi Herwibowo's short story "The Crybaby" to meet the study's objectives using the Labovian Narrative Analysis Model. The analysis of the lines taken from the text of the story demonstrates that society was callous and deaf to the cries of the orphans and that they were unable to provide a haven for them. When girls go to an orphanage, the grim picture of the orphanage reflects the savage and barbarous behavior of the workers who, instead of carrying out their responsibilities with integrity and caring for the helpless and the needy, treat them with an inhuman heart, tease them, molest them, and the girls are not safe there; they are rape who try their level best to leave that "Hell" even at the expense of their own lives. Keywords: The Crybaby, Qualitative Inquiry, Labovian Narrative Analysis Mode

Social Outcomes of Corporate Governance: Evidence from the Food Industry of Pakistan

Social and environmental problems are becoming strategic concerns for the managers in the current business scenario because it is challenging their sustainability. Here the need arises to respond to this changing phenomenon accordingly. In this regard social impact of corporate governance has not yet been explored where it can play a role of driver of excellence in terms of social performance and it is required to be studied. To check the existing situation, this study has been conducted where the social impact of corporate governance has been explored in the food Industry of Pakistan. Questionnaires have been filled from 176 managers working in six food producing firms listed in Pakistan Stock Exchange (PSX). Structural Equation Modeling based partial least square (PLS) has been used where Smart PLS has been used for model estimation. Results are supporting the stakeholder theory as Nestle Pakistan and Engro Foods are driving social excellence through corporate governance practices, where the corporations are showing strong positive relationships of corporate governance practices with stakeholders management, environmental integrity and protection, social cohesion and equity while insignificant relationship exists between strategic proactivity and corporate governance practices as people are resistant to change and innovation. The relationships can be explored in other industries like Oil and gas, Chemicals and Construction etc

Learning-Based Routing in Cognitive Networks

Intelligent Routing can influence the overall performance of a communication network’s throughput and efficiency. Routing strategies is required to adapt to changing network loads and different topologies. Learning from the network environment, in order to optimally adapt the network settings, is an essential requirement for providing efficient communication services in such environments. Cognitive networks are capable of learning and reasoning. They can energetically adapt to varying network conditions in order to optimize end-to-end performance and utilize network resources. In this paper we will focus machine learning in routing scheme that includes routing awareness, a routing reconfiguration

Reasons and Effects of Diversity of Education System in Pakistan at Elementary Level

Abstract Now a days Pakistan has several types of pedagogic systems. The origin of this matter can be pursued in copious factors; from foreign interferences to political flux. Education, which functions as the spinal cord for a nation’s survival, has underwent in Pakistan at the hands of political and socio-economic organizations. The fact that the multiple systems of education are sucking the blood out of this undeveloped nation is discouraging. It serves as a blow for the country to achieve collective objectives. Currently, this problem can be said to be stimulating other issues that are evolving in our society. This diversity is leading the nation into a nasty cycle of social discrepancy and political craving. However, today it has become essential to ensure uniformity in educational sector. The government needs to devise plans to deal with this state of educational emergency and take rational actions to reduce the invalid existing among these educational systems

Urinary Amylase as the First Line Diagnostic Tool for Acute Pancreatitis

Background: Diagnosis of acute pancreatitis is based on raised serum lipase and serum amylase in the blood. However, the levels of urinary amylase can be sought for being less invasive. The study aimed to find out the diagnostic accuracy of urinary amylase compared to serum amylase and serum lipase and their association with the degree of severity of acute pancreatitis. Methods: A randomized clinical control study was conducted on n=180 acute pancreatitis patients (18-50 year) in the Ziauddin and PNS Shifa Hospital, Karachi from September 2019- August 2020. Serum amylase, serum lipase and urinary amylase levels were checked at the time of admission followed by 24 hours and at discharge. ANOVA with post-hoc Tuckey’s test was used to determine the association of amylases with the severity of acute pancreatitis and p˂0.05 was considered as statistically significant. Results: The patients with acute pancreatitis had a mean age of 51.76 ±10.8. Urinary amylase had a strong significant association (p˂0.05) with acute pancreatitis compared to serum amylase and lipase (p=0.024). There was an insignificant association of urinary amylase with acute pancreatitis after 24 hours. Similarly, urinary amylase reported good diagnostic discrimination of acute pancreatitis as the accuracy index, the area under the ROC curve was one, showing higher sensitivity and specificity by covering the maximum population under the ROC curve. Conclusion: The significance of Urinary amylase (p˂0.05) was higher than serum amylase, serum lipase because of sensitivity and specificity for diagnosing acute pancreatitis representing a positive association with the degree of severity of the disease. Keywords: Acute Pancreatitis; Amylase; Lipase; Amylase

Overview of Liquid Crystal Research: Computational Advancements, Challenges, Future Prospects and Applications

Liquid crystal (LC) is a fascinating state of matter that combines order and mobility at multiple hierarchical levels, spanning from nanoscale to the macroscale, or from molecular to the macroscopic, and is composed of molecules and layers as thin as of a few nanometer in size. This unique combination allows such a system to adapt to a wide range of external stimuli, including temperature, magnetic field, electric field, mechanical stress, light, chemical reaction, and electrochemical response, by determining a new lowest energy configuration. Liquid crystalline nanostructures efficiently transmit and amplify information and attributes over macroscopic sizes due to their dynamic nature. The responsiveness and diversity of LCs provide enormous potential and challenges for fundamental scientific insights as well as opening the door to countless applied applications. Recent breakthroughs in nanotechnology have boosted the discipline, both in terms of theoretical simulations and the ability to fabricate nanoscale structures such as sub-wavelength gratings, nanoporous materials, and nanoparticles. Because LC materials are switchable, a new family of active plasmonic and nanophotonic devices is emerging, describing fascinating basic research processes as well as the creation of upgraded devices. This chapter discusses the fundamentals, computational advances, future prospects and challenges, as well as potential applications of LCs

EUGENOL AMELIORATES RHABDOMYOLYSIS-INDUCED ACUTE KIDNEY INJURY IN MICE

ABSTRACT   Background: Acute kidney injury (AKI) is a common and dangerous consequence of rhabdomyolysis which occurs in 50% of the cases with 5-10% mortality. In recent studies, eugenol has been reported as anti-fungal, antihyperglycemic, analgesic, anti-bacterial, anti-pyretic, anti-inflammatory and anti-oxidant agent. This study aimed to investigate the protective activity of eugenol on rhabdomyolysis-induced acute kidney injury (AKI) in mice.   Methods: Male, 24 BALB/c mice were divided into 4 groups (controls, AKI, eugenol and ascorbic acid as positive control). Controls and AKI were given normal saline, Eugenol (100 mg/kg bw) and ascorbic acid (200mg/kg) were given orally eugenol and ascorbic acid respectively for four days. After water deprivation for 24 hours, all animals, except controls, were injected with glycerol (50% - 10 ml/kg body weight intra-muscularly). After another 24 hours, blood samples were collected and kidneys were dissected out for biochemical investigations (serum urea and creatinine) and histopathological examination.    Results: Serum urea and creatinine levels compared to controls were significantly elevated in AKI group (p < 0.001) and significantly decreased, in eugenol and ascorbic acid groups (p < 0.001) compared to AKI group.  Histopathological examination revealed about 44% damage in the AKI group compared to the normal group (p < 0.001). Eugenol and ascorbic acid decreased the damage to 13% and 8% respectively compared to AKI group (p < 0.001). The tested compounds were found to reduce tubular cast formation. Conclusion: Eugenol has protective effects on rhabdomyolysis-induced AKI in mice. Further studies are required for evaluation of protective role of this compound in AKI

Microbiological Etiology of Chronic Cough Associated with Acute Exacerbation of Chronic Obstructive Pulmonary Disease (COPD): A Study from Karachi, Pakistan

Background: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) worsens the respiratory symptoms that are usually triggered by infection with bacteria or viruses or by environmental pollutants. Therefore, the aim of this study was to determine the bacterial etiology from sputum culture in patients suffering from acute exacerbation of COPD, admitted in hospital. Methods: The study was cross sectional observational, where sputum bacterial cultures were analyzed from the patients with Acute exacerbation COPD treated in the ICU of a tertiary care hospital for pulmonary disease from January 2019 to December 2019. Two sputum samples were collected from each patient for bacterial examination. The results of sputum bacterial culture findings were expressed as frequency and percentage by using SPSS. Results: In the present study, there were 1296 patients, both males 749 (57.8%) and females 547 (42.2%). The mean age of patients was 57.39±19.74years. 470 (36.3%) showed negative culture reports. 440 (34.0%) patients had Moraxella infection, which was most common organism in all patients, and 149 (11.5%) patients had Pseudomonas infection, 157(12.1%) patients had Yeast Albicans and in only 1 (0.1%) patient Enterobacter infection were found. Other pathogens in low frequency identified were Haemophilus parainfluenzae, Streptococcus pneumoniae, Escherichia coli and Haemophilus influenzae. It was observed that the frequency of infections was linked with increasing age. Conclusion: With increasing age, people are prone to acquire pulmonary infections specifically COPD. It is therefore very important to perform sputum culture to identify the causative agents and treat the patients with appropriate antibiotic to reduce the episodes of AECOPD. Keywords: Bacteria; Sputum Culture; COPD; Antibiotic; Cough

Microbial Fuel Cell Formulation from Nano-Composites

Petroleum and oil industry is a rich source of nonrenewable energy that ultimately results in threatening of ecosystem due to emission of greenhouse gases into the environment. In the current panorama of the energy demand, industries focus on alternate and renewable energy resources to meet energy gaps. Thus, an expedient fuel cell based on microbes can be valued as an economical and ecofriendly substitute of energy generator. These microbial fuel cells have commercialized platinum electrodes to generate cost-effective energy after oxidation of organic wastes catalyzed by biocatalyst. Nowadays, conventional carbon electrode as an anode is taking popularity in microbial fuel cell but displays poor performance. So, to improve the chemistry of electrodes, nano-composites fabricated from polar polymeric material as well as cost-effective oxides of metals are the raw material. In this chapter, green synthesis of nano-composites from conducting polymers and oxides of transition metals has been discussed. Anode modification by composite to treat wastewater as well as its role to generate electricity has been discussed briefly

Forecasting of Intellectual Capital by Measuring Innovation Using Adaptive Neuro-Fuzzy Inference System

Purpose – The aim of every organization is to achieve its set goals and objectives as well as secure competitive advantage over its competitors. However, these cannot be achieved or actualized if staff or workers act independently and do not share ideas. Today prominent businesses are becoming more aware that the knowledge of their employees is one of their primary assets. Sometimes organizational decisions cannot be effectively made with information alone; there is need for knowledge application. An effective Knowledge Management System can give a company the competitive edge it needs to be successful, and, for that reason, knowledge Management projects should be high priority. This means that for any organization to be competitive in today’s global world there is need for combination or pooling together of ideas by employees in order to achieve teamwork; this is in support of the saying that ‘two good heads are better than one’. Due to the advent of the knowledge-based economy and the developments in activity nature of the companies at international level, intellectual capital is taken to be one of the fundamental pillars of the companies for achieving efficiency. The aim of this study is to predict the amount and effectiveness of intellectual capital or intangible assets on the basis of innovation ability of the companies using an integrated artificial neural networks fuzzy logic analysis approach in order to cope with future challenges of strategic management. Design/methodology/approach – This paper suggests some guidelines for setting up the development of valuation approach based on application and adaption of selected financial and non-financial indicators by means of artificial neural networks and fuzzy logic. The artificial neural network model is highly accurate in predicting intellectual capital of the companies. This research paper presents the construction and design of Hybrid Application using Neural Network and Fuzzy Logic. This proposed system uses a simplified algorithmic design approach with wide range of input and output membership functions. In this research a hybrid Neuro-Fuzzy systems modelling methodology is developed and applied to an empirical data set in order to determine the hidden fuzzy if-then rules. Furthermore, the proposed methodology is a valuable tool for successful knowledge management. Findings – The findings show the opinion of that the complexity of development has been improved by expansion in the amount of knowledge available to organizations. Future research should contain of high degree of study to analytically examine the successful project knowledge management in different types of plans, companies and commences. Learning comes through creating and applying knowledge, whilst learning increases an individual's and organization's knowledge asset. Both learning and knowledge management feed off the same root: learning, improved capacity to perform work tasks, ability to make effective decisions, predict future parameters on the basis of some certain parameters and positively impact the world around us. Challenges – Identification and evaluation of the significant factors that create and determine enterprise value in industry is based on complex calculations involving many variables. Regardless of this reason, existing business valuation methods for such companies have to be improved with taking into account a numerous qualitative and even additional quantitative factors.Therefore, economic experts and scientists in the field of business valuation are confronted with new challenges in determination of appropriate approaches that should be able to eliminate the disadvantages of existing valuation methods. The environment in which businesses operate is ever changing. The market has become global and the technological advancement has changed the way business is done. The resulting impact of globalization is fierce competition that has altered the business landscape. Firms are increasingly employing various techniques in order to remain relevant and competitive. Since decision making is considered as the management main elements and sometimes equivalent to management itself, it is essential that researchers pay a specific attention to this field because if decisions are made in an optimized and effective form in an organization. This work is motivated by the need for a model that addresses the study of Knowledge in specific environments such as Business and Management, where several situations are very difficult to be analyze in conventional ways and therefore is insufficient in describing the complications of represent a realistic social phenomena and their social actors. Distributed Agency methodology will be used that requires the use of all available computational techniques and interdisciplinary theories as an approach to describe the interactions between agents in the development of social phenomena. Data Mining and Neuro-Fuzzy System are also used as part of the methodology to discover and assign rules on agents that represent real-world companies and employees. Practical implications – Today most organizations have discovered that advanced trainings can be considered as the key asset for modern organizations. This study presents a forecasting model that predicts intangible assets on the basis of innovation performance in organizational training using widely applied innovation criteria. The research focused on criteria, such as organization culture, ability to respond to organizational technology changes, relationship with other organizations in the training process and the use of high technology in education. The adaptive neuro-fuzzy inference systems (ANFIS) approach has been used to verify the proposed model. It is possible to predict innovation performance and it can also adjust allocated resources to organizational training system for its innovation objectives with this method. Originality/value – A great deal of work has been published over the past decade on the application of neural networks in diverse fields. This paper presents a model that measure and forecasts the intangible assets by the development of an Adaptive Neural Network with Fuzzy Inference system (ANFIS), using data that concern human capital, organizational support and innovativeness. The results indicate that fuzzy neural networks could be an efficient system that is easy to apply in order to accurately measure and forecast the intangible assets by measuring innovation capabilities of an organization or firm