Identification of Leaf Rust Virulence Pattern on Wheat Germplasm In Relation To Environmental Conditions in Faisalabad

One hundred and fifty varieties/lines were screened against wheat leaf rust. The natural environmental conditions of Ayub Agricultural Research Institute, Faisalabad were favorable for the development of leaf rust disease of wheat. Out of 150lines/cultivars which were screened against brown/leaf rust, 29 lines/cultivars were immune, the resistance was showed by 57 varieties and remaining all was susceptible. Values of area under disease progress curve (AUDPC) of all varieties were calculated. Also from the virulence and avirulence formula studied show that 57 varieties of leaf rust were avirulent and 49 varieties were virulent by leaf rust fungi, respectively. Environmental factors had great effect on the progress of leaf rusts diseases of wheat. Correlation between disease severity and environmental factors was also determined. Maximum varieties/lines showed comprehensible response to environmental factors. Four environmental factors (Temperature, Relative Humidity, Wind Speed and Rainfall) showed significant influence to disease severity. Five varieties/lines V-15, V-45, V-77, V-102, and V-118 showed considerable response to all environmental factors against brown rust. Utilization of this data for wheat improvement coupled with national varietal and gene deployment is discussed. The compiled field results exhibit that although the virulence frequency for some of the leaf rust resistance genes remained low, yet the presence of virulence against them is alarming under the circumstances when genetic base of resistance is stumpy in the presently cultivated varieties. On the basis of data these environmental factors were tested for correlation with leaf rust severities. It was concluded that screening and identifying the virulence pattern of leaf rust on wheat germplasm and utilizing these virulence genes on advanced lines may be helpful to produced for rust resistance in wheat to get maximum production. Keywords: Leafrust, Virulence Pattern, Resistance source, Epidemiology, Correlation

Knowledge Management approaches to model pathophysiological mechanisms and discover drug targets in Multiple Sclerosis

Multiple Sclerosis (MS) is one of the most prevalent neurodegenerative diseases for which a cure is not yet available. MS is a complex disease for numerous reasons; its etiology is unknown, the diagnosis is not exclusive, the disease course is unpredictable and therapeutic response varies from patient to patient. There are four established subtypes of MS, which are segregated based on different characteristics. Many environmental and genetic factors are considered to play a role in MS etiology, including viral infection, vitamin D deficiency, epigenetical changes and some genes. Despite the large body of diverse scientific knowledge, from laboratory findings to clinical trials, no integrated model which portrays the underlying mechanisms of the disease state of MS is available. Contemporary therapies only provide reduction in the severity of the disease, and there is an unmet need of efficient drugs. The present thesis provides a knowledge-based rationale to model MS disease mechanisms and identify potential drug candidates by using systems biology approaches. Systems biology is an emerging field which utilizes the computational methods to integrate datasets of various granularities and simulate the disease outcome. It provides a framework to model molecular dynamics with their precise interaction and contextual details. The proposed approaches were used to extract knowledge from literature by state of the art text mining technologies, integrate it with proprietary data using semantic platforms, and build different models (molecular interactions map, agent based models to simulate disease outcome, and MS disease progression model with respect to time). For better information representation, disease ontology was also developed and a methodology of automatic enrichment was derived. The models provide an insight into the disease, and several pathways were explored by combining the therapeutics and the disease-specific prescriptions. The approaches and models developed in this work resulted in the identification of novel drug candidates that are backed up by existing experimental and clinical knowledge

Identification of Yellow Rust Virulence Pattern on Wheat Germplasm in Relation to Environmental Conditions in Faisalabad

One hundred and fifty varieties/lines were screened against stripe. Most of the varieties/lines showed reaction to these diseases. For the development of stripe rust disease of wheat artificial and natural inoculums was relied upon for infection and the environmental conditions of Ayub Agricultural Research Institute, Faisalabad were favorable. Out of 150 lines/varieties which were screened against sixty four lines/varieties were immune, resistance shown by 42 lines/varieties and remaining all were susceptible against yellow rust. Area under disease progress curve (AUDPC) of all varieties was calculated. The virulence and avirulence formula studied showed that 42 varieties of yellow rust were avirulent and 29 varieties were virulent by yellow rust fungi. Environmental factors had great effect on the progress of stripe rust diseases of wheat. A positive linear relationship between temperature (maximum, minimum) and disease severity showed that maximum stripe rust develops was highly recognized to 28-32 °C maximum and 14-18 °C minimum temperatures. While, other environmental factors like relative humidity, rainfall and wind speed showed positive correlation. On the basis of data these environmental factors were tested for correlation with stripe rust severities. It was concluded that screening and identifying the virulence pattern of yellow rust on wheat germplasm and utilizing these virulence genes on advanced lines may be helpful to produced for rust resistance in wheat to get maximum production. Keywords: Yellow rust, Virulence Pattern, Resistance source, Epidemiology, Correlatio

Institutional Ownership and Discretionary Accruals: Empirical Evidences from Pakistani Listed Non-Financial Companies

Current study empirically investigates the impact of institutional ownership on discretionary accruals; we took a sample size of 68 listed non -financial companies from a population of 652 companies listed on Karachi Stock Exchange (KSE). This data was gathered for the period of 5 years, starting from 2006 up to 2010. Modified Jones Model was employed for this study to quantify discretionary accruals while institutional ownership measured by dividing number of shares kept by institutions from total number of shares outstanding. The fix effect model showed that the magnitude of discretionary accruals in Pakistani listed firms tends to significantly decrease for the firms where institutions hold a decent amount of share of that particular firm. Thus the findings of this study are in consensus with our hypothesis, which proposes that institutional ownership is quite an effective tool in aligning insider management and administration to take the right decision for value maximizing of the companies, and thus shareholders

Semi-Automated Approach to Map Clinical Concepts to SNOMED CT Terms by Using Terminology Server.

SNOMED CT has an enormous number of clinical concepts and mapping to SNOMED CT is considered as the foundation to achieve semantic interoperability in healthcare. Manual mapping is time-consuming and error-prone thus making this crucial step challenging. Terminology Servers provide an interface, which can be used to automate the process of retrieving data. Snowstorm is a terminology server developed by SNOMED International. In this work, the feasibility of using Snowstorm to automate the data retrieval and mapping has been discussed

Semi-Automated Approach to Retrieve SNOMED CT Hierarchy of Clinical Terms by Using Terminology Server.

SNOMED CT has an enormous number of clinical concepts and mapping to SNOMED CT is considered as the foundation to achieve semantic interoperability in healthcare. Manual mapping is time-consuming and error-prone thus making this crucial step challenging. In addition, hierarchy retrieval of clinical concepts increases the challenges for the user. Terminology Servers provide an interface, which can be used to automate the process of retrieving data. In this work, it is shown that Snowstorm can significantly improve the efficiency of retrieval process if used with semi-automated workflows

The Powers of the President against the Legislative Branch; According to the Constitution of Afghanistan

According to the Afghan Constitution, the President is the head of state and three branches, and also the head of the executive branch. The Constitution of Afghanistan in generally defines the powers of the President, one of which is the powers of the President against the legislative branch. Since these powers are not clearly defined in the constitution. Therefore, the constitution of Afghanistan needs a clear and light interpretation, which is a major problem in the Afghan constitution. The constitution also gives the president more powers than responsibilities, the main reason is that when the constitution was drafted; in addition to external interference, at the time the President of Afghanistan, Hamid Karzai, placed more powers in the constitution for his own benefit. So, it can be said the president had not exercised his powers against the legislative branch in accordance with the constitution

Digitized Engineering Notebook

Digitizing engineering notebooks, articles, assignments, multimedia things, event calendar and uploading downloading files from online web portal will certainly help engineering students in their studies. Here in this abstract we are proposing a system where students can share their notebooks on online web portal and others can read it and download it in a PDF format. This system will surly help and make updated all the students about college activities, studies and other activities. Proposed system will implement in Microsoft .Net Framework, C#.Net, ASP.Net and required an IIS web server to run it on live server. Developing this system require an IDE i.e. Visual Studio and backed database MS SQL to keep records of notebooks, data and assignments etc. There will be another super user which will manage student’s record and manage and restrict them to access the system. He can manage projects, assignments and assign to students

Engineering Social Learning Mechanisms for Multi-Agent Interaction

This thesis is strongly inspired by literature on animal social learning, applying it to multi-robot as well as human-robot interaction scenarios, Social learning, which can include complex or simple social mechanisms, allow us to understand cooperation and communication in animals, giving them better chances to survive for longer and thrive as a society. For this dissertation, to translate this understanding into socially rich behavior among multi-agent robots and Human-Robot Interaction, two experiments were conducted. The first experiment focused on how social learning might optimize cooperation among robots (in a robot 'society') for the problem of foraging. The task utilizes small and simple swarm robots to understand how such social mechanisms might play a role in establishing rules for emergent group behavior and how social rules might be engineered to gain useful effects in a group of robots. The study investigated exploratory behavior without interaction (asocial) and with interaction (social). The results from this exploratory study suggest that deterministic asocial exploration is best performed by a Spiral exploration mechanisms. However, these asocial exploration strategies are eclipsed by certain types of social reward sharing strategies as long as sharing occurs for at least half the lifetime of the robots. Sharing locations of reward caches for all time is of course the most optimal, but comes at the cost of communicating longer and hence using more energy both on the sender and receiver’s end. An analysis of a compromise strategy between completely asocial exploration and social reward location sharing is performed using strategies termed critical and conditional learning. It is found that the number of reward caches located through critical and conditional learning are intermediary to the two extremes, namely completely asocial and completely social foraging. The second experiment sought to understand if and how other types of social learning mechanisms such as observational conditioning can facilitate social information spread to human participants. The question of whether, and to what extent, a robot can influence a human's actions is asked through a study designed to understand if emotions displayed by a robot demonstrators can influence human observers. An immersive first-person gaming experience utilizing Unity was designed where a robot demonstrator reacted either positively or negatively to an external stimulus. Objective (position of player in-game) and subjective (Questionnaire) data collected on the human participants' reactions suggests that the virtual robot agent is successful in socially transmitting information. Through these studies, I seek to contribute to the understanding of the role simple social learning mechanisms can play in information transfer among human and robot agents, and to identify useful metrics for the detection of such social mechanisms