Role Performance of the Frontline Extension Agents in the Integrated Agricultural Extension Strategy of Sri Lanka

A novel extension strategy is in existence in Sri Lanka since 1994 integrating the extension efforts of Departments of Agriculture (DOA), Export Agriculture (DEA), Animal Production and Health (AP&H) and the Coconut Cultivation Board (CCB). Team efforts by theses agencies from national to grass root level, is a prominent feature of the Integrated Extension Strategy (IAES). Field Extension Teams (FET) were established for geographically demarcated areas (Govi Kendraya) consisting of frontline extension agents from four implementing agencies to service the farmer. The major objective of this study was thus to explore the predicting factors that influenced the role performance of these extension agents. Extension Agents from 4 of 15 districts, where lAES was active were selected randomly for the study. Two self-administered questionnaires, one to be completed by extension agents and the other by immediate supervisory officers appraising their performance formed the main source of data collection. The sample contained 275 extension agents of a total of 1364 and 201 questionnaires were collected for data analyses. The main statistical procedures employed were Exploratory Data Analysis, ANOVA, Pearson Product Correlation and Step-wise Multiple Regression. Analyses revealed that the age and experience of the respondents, of whom two thirds were males, were 43 and 17 years respectively. The extension agents had negative attitudes towards IAES. Although the quality of work was good the quantity of work performed by them was poor. They showed higher levels of motivation, role clarity and commitment and conversely low role ambiguity and role overload. Of the variables tested, some variables namely: attitudes towards GET members, role overload, valacy, participation, technical supervision and also quality, quantity and overall performances showed significant differences among the extension agents of the participating agencies in the IAES. Many variables namely: attitudes towards IAES, Guide and Extension Team (GET), motivation, valency, role commitment, role ambiguity, group cohesion, group interaction, followership, participation, technical supervision and administrative supervision showed significant relationships with the dependent variable role performance but the magnitudes of relationships shown by all variables were small. Attitudes towards GET, Role commitment, motivation, participation and technical supervision were the principal variables that could predict and explain the role performance of the extension agents. Nevertheless; attitudes towards IAES, valency, followership, group cohesiveness and administrative supervision were the other variables which could explain and predict role performance as second category predictors from the step-wise regression analyses. A distinct feature of these findings was that all the above variables collectively could predict and explain slightly over one-third of the variance in role performance. This indicated the substantial presence of various other facilitating and inhibiting factors out side the control of role incumbents

Modulation Of Water-Exchange Rates Of Lanthanide(iii)-Containing Complexes Using Polyethylene Glycol

MODULATION OF WATER-EXCHANGE RATES OF LANTHANIDE(III)-CONTAINING COMPLEXES USING POLYETHYLENE GLYCOL by BUDDHIMA N. SIRIWARDENA-MAHANAMA May 2014 Advisor: Dr. Matthew J. Allen Major: Chemistry Degree: Doctor of Philosophy A modular system of lanthanide(III)-containing polyethylene glycol (PEG) conjugates was synthesized and characterized to investigate the influence of length and density of PEG on water-exchange rates of lanthanide(III)-containing complexes. The water-exchange rates of lanthanide(III)-containing complexes contribute to the efficiency of these complexes as T1-shortening and paramagnetic chemical exchange saturation transfer (PARACEST) contrast agents for magnetic resonance imaging (MRI). Because the mechanism of these two MRI methods is vastly different, there is a need to tune the water-exchange rates of lanthanide(III)-containing complexes over a broad range: towards fast rates (108 s-1) for T1-shortening agents and slow rates (103 s-1) for PARACEST agents. As a result, extensive research efforts have contributed to tuning water-exchange rates of both types of contrast agents using coordination-chemistry-based strategies. These studies reveal that small modifications in the structure of lanthanide(III)-containing complexes lead to considerable changes in water-exchange rates. This thesis tests the hypothesis that hydrophilic PEG alters the accessibility of bulk water and the extent of hydrogen bonding between lanthanide(III)-coordinated and bulk water. To test this hypothesis, a PEG-based lanthanide(III)-containing model system was designed and synthesized to investigate the influence of length and density of PEG on the water-exchange rates of lanthanide(III)-containing complexes. Properties of the new complexes that are relevant to MRI, including water-exchange rates, were determined using relaxometric and spectroscopic techniques. The modular lanthanide(III)-containing system designed to investigate the influence of length of PEG demonstrated that PEG is able to tune water-exchange rates of lanthanide(III)-containing polyaminopolycarboxylate-type complexes toward slower rates. The ability of PEG to tune water-exchange rates toward slower rates as a function of the length of PEG is likely due to the variation in extent of hydrogen bonding between coordinated and bulk water. These findings provide insight into the influence of length and density of PEG on water-exchange rate and contrast agent efficiency and are expected to be useful in the design of contrast agents with optimum water-exchange rates

Multi-User Eye-Tracking

The human gaze characteristics provide informative cues on human behavior during various activities. Using traditional eye trackers, assessing gaze characteristics in the wild requires a dedicated device per participant and therefore is not feasible for large-scale experiments. In this study, we propose a commodity hardware-based multi-user eye-tracking system. We leverage the recent advancements in Deep Neural Networks and large-scale datasets for implementing our system. Our preliminary studies provide promising results for multi-user eye-tracking on commodity hardware, providing a cost-effective solution for large-scale studies

X-DisETrac: Distributed Eye-Tracking with Extended Realities

Humans use heterogeneous collaboration mediums such as in-person, online, and extended realities for day-to-day activities. Identifying patterns in viewpoints and pupillary responses (a.k.a eye-tracking data) provide informative cues on individual and collective behavior during collaborative tasks. Despite the increasing ubiquity of these different mediums, the aggregation and analysis of eye-tracking data in heterogeneous collaborative environments remain unexplored. Our study proposes X-DisETrac: Extended Distributed Eye Tracking, a versatile framework for eye tracking in heterogeneous environments. Our approach tackles the complexity by establishing a platform-agnostic communication protocol encompassing three data streams to simplify data aggregation and analytics. Our study establishes seminal work in multi-user eye-tracking in heterogeneous environments.https://digitalcommons.odu.edu/gradposters2023_sciences/1010/thumbnail.jp

AGCM Biases in Evaporation Regime: Impacts on Soil Moisture Memory and Land-Atmosphere Feedback

Because precipitation and net radiation in an atmospheric general circulation model (AGCM) are typically biased relative to observations, the simulated evaporative regime of a region may be biased, with consequent negative effects on the AGCM s ability to translate an initialized soil moisture anomaly into an improved seasonal prediction. These potential problems are investigated through extensive offline analyses with the Mosaic land surface model (LSM). We first forced the LSM globally with a 15-year observations-based dataset. We then repeated the simulation after imposing a representative set of GCM climate biases onto the forcings - the observational forcings were scaled so that their mean seasonal cycles matched those simulated by the NSIPP-1 (NASA Global Modeling and Assimilation Office) AGCM over the same period-The AGCM s climate biases do indeed lead to significant biases in evaporative regime in certain regions, with the expected impacts on soil moisture memory timescales. Furthermore, the offline simulations suggest that the biased forcing in the AGCM should contribute to overestimated feedback in certain parts of North America - parts already identified in previous studies as having excessive feedback. The present study thus supports the notion that the reduction of climate biases in the AGCM will lead to more appropriate translations of soil moisture initialization into seasonal prediction skill

Contribution of Soil Moisture Information to Streamflow Prediction in the Snowmelt Season: A Continental-Scale Analysis

In areas dominated by winter snowcover, the prediction of streamflow during the snowmelt season may benefit from three pieces of information: (i) the accurate prediction of weather variability (precipitation, etc.) leading up to and during the snowmelt season, (ii) estimates of the amount of snow present during the winter season, and (iii) estimates of the amount of soil moisture underlying the snowpack during the winter season. The importance of accurate meteorological predictions and wintertime snow estimates is obvious. The contribution of soil moisture to streamflow prediction is more subtle yet potentially very important. If the soil is dry below the snowpack, a significant fraction of the snowmelt may be lost to streamflow and potential reservoir storage, since it may infiltrate the soil instead for later evaporation. Such evaporative losses are presumably smaller if the soil below the snowpack is wet. In this paper, we use a state-of-the-art land surface model to quantify the contribution of wintertime snow and soil moisture information -- both together and separately -- to skill in forecasting springtime streamflow. We find that soil moisture information indeed contributes significantly to streamflow prediction skill

Land-Focused Changes in the Updated GEOS FP System (Version 5.25)

Many of the changes imposed in the January 2020 upgrade from Version 5.22 to 5.25 of the Goddard Earth Observing System (GEOS) Forward Processing (FP) analysis system were designed to increase the realism of simulated land variables. The changes, which consist of both land model parameter updates and improvements to the physical treatments employed for various land processes, have generally positive or neutral impacts on the character of the FP product, as documented here