The Changing Role of Urdu News Media with Digital Communication in Pakistan

The growing use of digital media has influenced significantly the communication channels of society during recent years in the globe. The media and communication in Pakistan is transforming with information technology. The marvelous boost of digital media devices has changed the communication channels. With digital media revolution, the people in society who formerly had no chance to participate, now they have a great opportunity of to contribute. They can give feedback on news content, comment on stories and share information. If we talk about Urdu news in Pakistan, technology has not left it unchanged. The great revolution in technological field has modified the way public receives information on various aspects. This research work will boost our understanding of how effects of fast spreading technological means have affected traditional modes of Urdu news. During the past decades, western world has got a great benefit from immense development in information communication technology. Furthermore, developing world is widely seen accepting access to internet computer and mobile phone technology. Today's media organizations are extensively using various technological sources. This study also explore the phenomenon of adoption of information technology, role played by media in this digital age and to address the global audience and news collection, influence of internet and extent of freedom of expression to which it has impacted todays media in accessing and delivering information. Though traditional modes of information have got a great jolt by new digital platform and have brought great opportunities for information gathering ofUrdu news in Pakistan.</p

A STUDY ON INTERFERON APLHA RECEPTORS AND STAT1 AS THERAPY PREDICTORS IN HEPATITIS INFECTION

Introduction: Liver is a pivotal organ of the body and play very important role in the metabolism. If there is any problem in the liver then the herbs or different plants play an important role for the treatment of liver disorders. Objective of the study: The main objective of the study is to analyze the interferon aplha receptors and STAT1 as therapy predictors in hepatitis infection. Methodology of the study: This cross sectional study was conducted in hospital of Sialkot during September 2018 to January 2018. The purpose and benefits of the study were explained to each participant and informed written consent was obtained. By using non-probability convenience sampling, we enrolled treatment-naïve HCV mono-infected and HCV/HBV co-infected patients along with healthy controls. Out of the eligible patients, some were also positive with hepatitis B surface antigen (HbsAg) along with serum HBV-deoxyribonucleic acid (DNA) level. Results: The demographic values of patient group and control group shows a significant difference. The data suggest clearly that CD4 count decreases in abnormal liver function. There were non-significant relationship present in diseased group treated with different therapies like interferon and glutathione as as p<0.05. The level of micronutrients become decreases in diseased group. Of the eligible 171(88%) patients, 86(50.3%) were also positive with HbsAg. The final study sample had 191 subjects. Of them, there were 20(10.5%) in group-1a, 35(18.3%) in group-2a, 65(34%) in group-1b and 51(26.7%) in group-2b. Conclusion: It is concluded that hepatitis directly increase the liver enzymes even after receiving medication and other therapies. Expression rate of IFNAR-1 mRNA maybe useful index for predicting long-term efficacy of IFN therapy compared to STAT-1 and IFNAR-2. Replication of HBV-DNA is not the main factor leading to down-regulation of IFN-a receptors or STAT-1

Effect of Alpha-Type external input on annihilation of self-sustained activity in a two population neural field model

In the present work, we investigate the annihilation of persistent localized activity states (bumps) in a Wilson-Cowan type two-population neural field model in response to $\alpha$ -type spatio-temporal external input. These activity states serves as working memory in the prefrontal cortex. The impact of different parameters involved in the external input on annihilation of these persistent activity states is investigated in detail. The $\alpha$ -type temporal function in the external input is closer to natural phenomenon as observed in Roth et. al . ( Nature Neuroscience , vol. 19 (2016), 229–307). Two types of eraser mechanism are used in this work to annihilate the spatially symmetric solutions. Initially, if there is an activity in the network, inhibitory external input with no excitatory part and over excitation with no inhibition in the external input can kill the activity. Our results show that the annihilation of persistent activity states using $\alpha$ -type temporal function in the external input is more roubust and more efficient as compare to triangular one as used by Yousaf et al. ( Neural networks. , vol. 46 (2013), pp. 75–90). It is also found that the relative inhibition time constant plays a crucial role in annihilation of the activity. Runge-Kutta fourth order method has been employed for numerical simulations of this work.publishedVersio

Frequency of Hepatocellular Carcinoma in Patients Infected with Hepatitis C Virus visiting a Tertiary Care Hospital in Lahore for Computed Tomographic Evaluation

Background: Hepatitis C virus has been identified as one of the leading causes of chronic liver disease and its complications world-wide. Subsequent development of hepatocellular carcinoma in these patients is a major complication of this infection having serious implications on morbidity and mortality rates. The objective of this study was to find out the frequency of Hepatocellular carcinoma in patients suffering from Hepatitis C visiting Radiology department of a tertiary care hospital for multi-detector computed tomography evaluation.Methods: This cross-sectional analytical study was conducted at Shalamar Hospital Lahore. A total of 195 patients, suffering from Hepatitis C, visiting Shalamar Hospital, Lahore for evaluation by CT during 6 months study interval were included in this study. Abdominal CT was performed using Triphasic contrast enhancement protocol. All images were interpreted by a senior Radiologist. Frequency of Hepatocellular carcinoma was calculated. Statistical analysis was made using MEDCALC.Results: Out of 195, 63(32.3%) patients were seen to have hepatocellular carcinoma. This disease was more common in male, 45(34.6%) as compared to female patients 18 (27.7%). The presence of HCC showed statistically significant association with alcoholism, obesity, diabetes mellitus and cirrhosis.Conclusion: The study concluded that a substantial number of HCV positive patients develop HCC, which is more common in men as compared to women. The presence of HCC is strongly associated with alcoholism, obesity, diabetes mellitus and cirrhosis.Keywords: Hepatocellular carcinoma (HCC); Hepatitis C (HCV); Multi-detector Computed Tomography (MDCT)

Facial Expression Recognition of Instructor Using Deep Features and Extreme Learning Machine

Classroom communication involves teacher’s behavior and student’s responses. Extensive research has been done on the analysis of student’s facial expressions, but the impact of instructor’s facial expressions is yet an unexplored area of research. Facial expression recognition has the potential to predict the impact of teacher’s emotions in a classroom environment. Intelligent assessment of instructor behavior during lecture delivery not only might improve the learning environment but also could save time and resources utilized in manual assessment strategies. To address the issue of manual assessment, we propose an instructor’s facial expression recognition approach within a classroom using a feedforward learning model. First, the face is detected from the acquired lecture videos and key frames are selected, discarding all the redundant frames for effective high-level feature extraction. Then, deep features are extracted using multiple convolution neural networks along with parameter tuning which are then fed to a classifier. For fast learning and good generalization of the algorithm, a regularized extreme learning machine (RELM) classifier is employed which classifies five different expressions of the instructor within the classroom. Experiments are conducted on a newly created instructor’s facial expression dataset in classroom environments plus three benchmark facial datasets, i.e., Cohn–Kanade, the Japanese Female Facial Expression (JAFFE) dataset, and the Facial Expression Recognition 2013 (FER2013) dataset. Furthermore, the proposed method is compared with state-of-the-art techniques, traditional classifiers, and convolutional neural models. Experimentation results indicate significant performance gain on parameters such as accuracy, F1-score, and recall

Seasonal influence, heat unit accumulation and heat use efficiency in relation to maize grain yield in Pakistan

Variations in ambient temperature affect crop yield by modifying the duration of phenological phases and physiologicalprocesses. An experimental study was carried out at the Maize and Millets Research Institute (MMRI),Yusafwala, Sahiwal, Pakistan, to determine the seasonal effects of temperature on indigenous and exotic maize(Zea mays L.) hybrids based on morphological, phenological, physiological and grain quality traits in four differentgrowing seasons: kharif 2016 and 2017, and spring 2017 and 2018. Seven indigenous and three exotic hybridswere sown in a randomized complete block design with a split plot arrangement, in three replications. Significantdifferences between hybrids and growing seasons were found for grain yield, related traits and temperature indices(cumulative heat units, photothermal index and heat use efficiency). Correlation analysis disclosed a significantpositive relationship between grain yield and net photosynthetic rate (0.854, P≤0.01), number of grains per ear(0.624, P≤0.01) and heat use efficiency (0.980, P≤0.01) in spring seasons. During kharif, net photosynthetic rate(0.675, P≤0.01) and heat use efficiency (0.996, P≤0.01) contributed significantly to grain yield, whereas number ofgrains per ear (−0.146, not significant) had no significant impact on grain yield. Cumulative heat units and heat useefficiency resulted the temperature indices with the greatest influence on grain yield, and should be consideredduring the selection of parents to develop high-yielding, climate-smart maize hybrids. Indigenous maize hybridsshowed higher yields and were more heat tolerant than exotic hybrids, and the spring sowing season appearedto be the most suitable for the cultivation of maize crops

Dynamic Stability and Flight Control of Biomimetic Flapping-Wing Micro Air Vehicle

This paper proposes an approach to analyze the dynamic stability and develop trajectory-tracking controllers for flapping-wing micro air vehicle (FWMAV). A multibody dynamics simulation framework coupled with a modified quasi-steady aerodynamic model was implemented for stability analysis, which was appended with flight control block for accomplishing various flight objectives. A gradient-based trim search algorithm was employed to obtain the trim conditions by solving the fully coupled nonlinear equations of motion at various flight speeds. Eigenmode analysis showed instability that grew with the flight speed in longitudinal dynamics. Using the trim conditions, we linearized dynamic equations of FWMAV to obtain the optimal gain matrices for various flight speeds using the linear-quadratic regulator (LQR) technique. The gain matrices from each of the linearized equations were used for gain scheduling with respect to forward flight speed. The reference tracking augmented LQR control was implemented to achieve transition flight tracking that involves hovering, acceleration, and deceleration phases. The control parameters were updated once in a wingbeat cycle and were changed smoothly to avoid any discontinuities during simulations. Moreover, trajectories tracking control was achieved successfully using a dual loop control approach. Control simulations showed that the proposed controllers worked effectively for this fairly nonlinear multibody system

Fuzzy Graph Structures with Application

In this article, we introduce the notions of maximal products of fuzzy graph structures, regular fuzzy graph structures, and describe these notions with examples and properties. Further, we present the degree and total degree of a vertex in maximal product of fuzzy graph structures and explain some of their properties. Furthermore, we develop a flowchart to show general procedure of application of fuzzy graph structure, regarding identification of most controversial issues among countries

The Kingsguard OS-level mitigation against cache side-channel attacks using runtime detection

International audienceMost of the mitigation techniques against access-driven cache side-channel attacks (CSCAs) are not very effective. This is mainly because most mitigation techniques usually protect against any given specific vulnerability of the system and do not take a system-wide approach. Moreover, they either completely remove or greatly reduce the performance benefits. Therefore, to find a security vs performance trade-off, we argue in favor of need-based protection in this paper, which will allow the operating system to apply mitigation only after successful detection of CSCAs. Thus, detection can serve as a first line of defense against such attacks. In this work, we propose a novel OS-level runtime detection-based mitigation mechanism, called the Kingsguard, against CSCAs in general-purpose operating systems. The proposed mechanism enhances the security and privacy capabilities of Linux as a proof of concept, and it can be widely used in commodity systems without any hardware modifications. We provide experimental validation by mitigating three state-of-the-art CSCAs on two different cryptosystems running under Linux. We have also provided results by analyzing the effect of the combination of multiple attacks running concurrently under variable system noise. Our results show that the Kingsguard can detect and mitigate known CSCAs with an accuracy of more than 99% and 95%, respectively

Analysis of Trabecular Bone Mechanics Using Machine Learning

“Bone remodeling” is a dynamic process, and mutliphase analysis incorporated with the forecasting algorithm can help the biologists and orthopedics to interpret the laboratory generated results and to apply them in improving applications in the fields of “drug design, treatment, and therapy” of diseased bones. The metastasized bone microenvironment has always remained a challenging puzzle for the researchers. A multiphase computational model is interfaced with the artificial intelligence algorithm in a hybrid manner during this research. Trabecular surface remodeling is presented in this article, with the aid of video graphic footage, and the associated parametric thresholds are derived from artificial intelligence and clinical data