Adventures and Misfortunes in Macondo: Rehabilitation of the Cienaga Grande

We describe trajectories of selected ecological indicators used as performance measures to evaluate the success of a mangrove rehabilitation project in the Ciénaga Grande de Santa Marta (CGSM) Delta-Lagoon complex, Colombia, as result of freshwater diversions initiated in 1995. There is a significant reduction in soil and water column salinity in all sampling stations following the hydraulic reconnection of the Clarín and Aguas Negras channels to the Magdalena River. Soil intersticial water salinity (depth: 0.5 m) (7 stations) and water column salinity (0.5 m) (10 stations) values declined significantly (soil <30 g kg-1; water <10 g kg-1) from 1994 to 2000. During 1994 soil interstitial water salinity ranged from 40 g kg-1 (Rinconada) to 100 g kg-1 (KM 13), while water column salinity fluctuated between 25-35 g kg-1 for most of the sampling stations. This salinity reduction increased mangrove forest regeneration promoting a net gain of 99 km2 from 1995 to 1999. The high precipitation recorded in 1995 and 1999 caused by El Niño-La Niña (ENSO), coinciding with the channels rehabilitation, influenced rapid mangrove regeneration. The lack of economic investment in the maintenance of the diversion structures from 2001 to 2004 caused a salinity increase affecting negatively already restored vegetation. A sustainable effort from the international community and the Colombian government is needed to maintain the strategic social and economic benefits reached until 2000 in the CGSM region.

Alligators and crocodiles as indicators for restoration of Everglades ecosystems

Alligators and crocodiles integrate biological impacts of hydrological operations, affecting them at all life stages through three key aspects of Everglades ecology: (1) food webs, (2) diversity and productivity, and (3) freshwater flow. Responses of crocodilians are directly related to suitability of environmental conditions and hydrologic change. Correlations between biological responses and environmental conditions contribute to an understanding of species’ status and trends over time. Positive or negative trends of crocodilian populations relative to hydrologic changes permit assessment of positive or negative trends in restoration. The crocodilian indicator uses monitoring parameters (performance measures) that have been shown to be both effective and efficient in tracking trends. The alligator component uses relative density (reported as an encounter rate), body condition, and occupancy rates of alligator holes; the crocodile component uses juvenile growth and hatchling survival. We hypothesize that these parameters are correlated with hydrologic conditions including depth, duration, timing, spatial extent and water quality. Salinity is a critical parameter in estuarine habitats. Assessments of parameters defined for crocodilian performance measures support these hypotheses. Alligators and crocodiles are the charismatic megafauna of the Everglades. They are both keystone and flagship species to which the public can relate. In addition, the parameters used to track trends are easy to understand. They provide answers to the following questions: How has the number of alligators or crocodiles changed? Are the animals fatter or thinner than they should be? Are the animals in the places (in terms of habitat and geography) where they should be? As surely as there is no other Everglades, no other single species defines the Everglades as does the American alligator. The Everglades is the only place in the world where both alligators and crocodiles exist. Crocodilians clearly respond to changes in hydrologic parameters of management interest. These relationships are easy to communicate and mean something to managers, decision makers, and the public. Having crocodilians on the list of system-wide, general indicators provides us with one of the most powerful tools we have to communicate progress of ecosystem restoration in Greater Everglades ecosystems to diverse audiences.

Roseate spoonbill reproduction as an indicator for restoration of the Everglades and the Everglades estuaries

Ecological monitoring is key to successful ecosystem restoration. Because all components within an ecosystem cannot be monitored, it is important to select indicators that are representative of the system, integrate system responses, clearly respond to system change, can be effectively and efficiently monitored, and are easily communicated. The roseate spoonbill is one ecological indicator species that meets these criteria within the Everglades ecosystem. Monitoring of roseate spoonbills in Florida Bay over the past 70 years has shown that aspects of this species’ reproduction respond to changes in hydrology and corresponding changes in prey abundance and availability. This indicator uses nesting location, nest numbers and nesting success in response to food abundance and availability. In turn, prey abundance is a function of hydrological conditions (especially water depth) and salinity. Metrics and targets for these performance measures were established based on previous findings. Values of each metric were translated into indices and identified as stoplight colors with green indicating that a given target has been met, yellow indicating that conditions are below the target, but within an acceptable range of it, and red indicating the measure is performing poorly in relation to the target.

Relationships Between Hydrology and Soils Describe Vegetation Patterns in Seasonally Flooded Tree Islands of the Southern Everglades, Florida

Tree island ecosystems are important and distinct features of Florida Everglades wetlands. We described the inter-relationships among abiotic factors describing seasonally flooded tree islands and characterized plant–soil relationships in tree islands occurring in a relatively unimpacted area of the Everglades. We used Principal Components Analysis (PCA) to reduce our multi-factor dataset, quantified forest structure and vegetation nutrient dynamics, and related these vegetation parameters to PCA summary variables using linear regression analyses. We found that, of the 21 abiotic parameters used to characterize the ecosystem structure of seasonally flooded tree islands, 13 parameters were significantly correlated with four principal components, and they described 78% of the variance among the study islands. Most variation was described by factors related to soil oxidation and hydrology, exemplifying the sensitivity of tree island structure to hydrologic conditions. PCA summary variables describing tree island structure were related to variability in Chrysobalanus icaco (L.) canopy cover, Ilex cassine (L.) and Salix caroliniana (Michx.) canopy cover, Myrica cerifera (L.) plot frequency, litter turnover, % phosphorus resorption of co-dominant species, and nitrogen nutrient-use efficiency. This study supported findings that vegetation characteristics can be sensitive indicators of variability in tree island ecosystem structure. This study produced valuable, information which was used to recommend ecological targets (i.e. restoration performance measures) for seasonally flooded tree islands in more impacted regions of the Everglades landscape.

Eastern oysters (Crassostrea virginica) as an indicator for restoration of Everglades Ecosystems

The Comprehensive Everglades Restoration Plan (CERP) attempts to restore hydrology in the Northern and Southern Estuaries of Florida. Reefs of the Eastern oyster Crassostrea virginica are a dominant feature of the estuaries along the Southwest Florida coast. Oysters are benthic, sessile, filter-feeding organisms that provide ecosystem services by filtering the water column and providing food, shelter and habitat for associated organisms. As such, the species is an excellent sentinel organism for examining the impacts of restoration on estuarine ecosystems. The implementation of CERP attempts to improve: the hydrology and spatial and structural characteristics of oyster reefs, the recruitment and survivorship of C. virginica, and the reef-associated communities of organisms. This project links biological responses and environmental conditions relative to hydrological changes as a means of assessing positive or negative trends in oyster responses and population trends. Using oyster responses, we have developed a communication tool (i.e., Stoplight Report Card) based on CERP performance measures that can distinguish between responses to restoration and natural patterns. The Stoplight Report Card system is a communication tool that uses Monitoring and Assessment Program (MAP) performance measures to grade an estuary's response to changes brought about by anthropogenic input or restoration activities. The Stoplight Report Card consists of both a suitability index score for each organism metric as well as a trend score (− decreasing trend, +/− no change in trend, and + increasing trend). Based on these two measures, a component score (e.g., living density) is calculated by averaging the suitability index score and the trend score. The final index score is obtained by taking the geometric score of each component, which is then translated into a stoplight color for success (green), caution (yellow), or failure (red). Based on the data available for oyster populations and the responses of oysters in the Caloosahatchee Estuary, the system is currently at stage “caution.” This communication tool instantly conveys the status of the indicator and the suitability, while trend curves provide information on progress towards reaching a target. Furthermore, the tool has the advantage of being able to be applied regionally, by species, and collectively, in concert with other species, system-wide.

Advanced methodologies in dynamic traffic assignment modeling of managed lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^

Fitting model-based psychometric functions to simultaneity and temporal-order judgment data: MATLAB and R routines

Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.

The Mathematics Anxiety of Bilingual Community College Students

Math anxiety levels and performance outcomes were compared for bilingual and monolingual community college Intermediate Algebra students attending a culturally diverse urban commuter college. Participants (N = 618, 250 men, 368 women; 361 monolingual, 257 bilingual) completed the Abbreviated Math Anxiety Scale (AMAS) and a demographics instrument. Bilingual and monolingual students reported comparable mean AMAS scores (20.6 and 20.7, respectively) and comparable proportions of math anxious individuals (50% and 48%, respectively). Factor analysis of AMAS scores, using principal component analysis by varimax rotation, yielded similar two-factor structures for both populations -- assessment and learning content -- accounting for 65.6% of the trace for bilingual AMAS scores. Statistically significant predictor variables for levels of math anxiety for the bilingual participants included (a) preparatory course enrollment (β = .236, p = .041) with those enrolled in prior preparatory courses scoring higher, (b) education major (β = .285, p = .018) with education majors scoring higher, and (c) business major (β = .252, p = .032) with business majors scoring higher. One statistically significant predictor variable emerged for monolingual students, gender (β = -.085, p = .001) with females ranking higher. Age, income, race, ethnicity, U.S. origin, science or health science majors did not emerge as statistically significant predictor variables for either group. Similarities between monolingual and bilingual participants included statistically significant negative linear correlations between AMAS scores and course grades for both bilingual (r = -.178, p = .017) and monolingual participants (r = -.203, p = .001). Differences included a statistically significant linear correlation between AMAS scores and final exam grades for monolingual participants only (r = -.253, p < .0009) despite no statistically significant difference in the strength the linear relationship of the AMAS scores and the final exam scores between groups, z = 1.35, p = .1756. The findings show that bilingual and monolingual students report math anxiety similarly and that math anxiety has similar associations with performance measures, despite differences between predictor variables. One of the first studies on the math anxiety of bilingual community college students, the results suggest recommendations for researchers and practitioners.

On Queueinginventory Models – product form solution; reservation, Cancellation and common life time

Queueing theory is the mathematical study of ‘queue’ or ‘waiting lines’ where an item from inventory is provided to the customer on completion of service. A typical queueing system consists of a queue and a server. Customers arrive in the system from outside and join the queue in a certain way. The server picks up customers and serves them according to certain service discipline. Customers leave the system immediately after their service is completed. For queueing systems, queue length, waiting time and busy period are of primary interest to applications. The theory permits the derivation and calculation of several performance measures including the average waiting time in the queue or the system, mean queue length, traffic intensity, the expected number waiting or receiving service, mean busy period, distribution of queue length, and the probability of encountering the system in certain states, such as empty, full, having an available server or having to wait a certain time to be served.

Effects of IFRS adoption on the financial statements of Nigerian listed entities: the case of oil and gas companies

On 28 July 2010, the Nigerian Federal Executive Council approved January 1, 2012 as the effective date for the convergence of Nigerian Statement of Accounting Standards (SAS) or Nigerian GAAP (NG-GAAP) with International Financial Reporting Standards (IFRS). By this pronouncement, all publicly listed companies and significant public interest entities in Nigeria were statutorily required to issue IFRS based financial statements for the year ended December, 2012. This study investigates the impact of the adoption of IFRS on the financial statements of Nigerian listed Oil and Gas entities using six years of data which covers three years before and three years after IFRS adoption in Nigeria and other African countries. First, the study evaluates the impact of IFRS adoption on the Exploration and Evaluation (E&E) expenditures of listed Oil and Gas companies. Second, it examines the impact of IFRS adoption on the provision for decommissioning of Oil and Gas installations and environmental rehabilitation expenditures. Third, the study analyses the impact of the adoption of IFRS on the average daily Crude Oil production cost per Barrel. Fourth, it examines the extent to which the adoption and implementation of IFRS affects the Key Performance Indicators (KPIs) of listed Oil and Gas companies. The study further explores the impact of IFRS adoption on the contractual relationships between Nigerian Government and Oil and Gas companies in terms of Joint Ventures (JVs) and Production Sharing Contracts (PSCs) as it relates to taxes, royalties, bonuses and Profit Oil Split. A Paired Samples t-test, Wilcoxon Signed Rank test and Gray’s (Gray, 1980) Index of Conservatism analyses were conducted simultaneously where the accounting numbers, financial ratios and industry specific performance measures of GAAP and IFRS were computed and analysed and the significance of the differences of the mean, median and Conservatism Index values were compared before and after IFRS adoption. Questionnaires were then administered to the key stakeholders in the adoption and implementation of IFRS and the responses collated and analysed. The results of the analyses reveal that most of the accounting numbers, financial ratios and industry specific performance measures examined changed significantly as a result of the transition from GAAP to IFRS. The E&E expenditures and the mean cost of Crude Oil production per barrel of Oil and Gas companies increased significantly. The GAAP values of inventories, GPM, ROA, Equity and TA were also significantly different from the IFRS values. However, the differences in the provision for decommissioning expenditures were not statistically significant. Gray’s (Gray, 1980) Conservatism Index shows that Oil and Gas companies were more conservative under GAAP when compared to the IFRS regime. The Questionnaire analyses reveal that IFRS based financial statements are of higher quality, easier to prepare and present to management and easier to compare among competitors across the Oil and Gas sector but slightly more difficult to audit compared to GAAP based financial statements. To my knowledge, this is the first empirical research to investigate the impact of IFRS adoption on the financial statements of listed Oil and Gas companies. The study will therefore make an enormous contribution to academic literature and body of knowledge and void the existing knowledge gap regarding the impact and implications of IFRS adoption on the financial statements of Oil and Gas companies.

Requirement Risk Level Forecast Using Bayesian Networks Classifiers

Requirement engineering is a key issue in the development of a software project. Like any other development activity it is not without risks. This work is about the empirical study of risks of requirements by applying machine learning techniques, specifically Bayesian networks classifiers. We have defined several models to predict the risk level for a given requirement using three dataset that collect metrics taken from the requirement specifications of different projects. The classification accuracy of the Bayesian models obtained is evaluated and compared using several classification performance measures. The results of the experiments show that the Bayesians networks allow obtaining valid predictors. Specifically, a tree augmented network structure shows a competitive experimental performance in all datasets. Besides, the relations established between the variables collected to determine the level of risk in a requirement, match with those set by requirement engineers. We show that Bayesian networks are valid tools for the automation of risks assessment in requirement engineering.

The dynamic decode-and-forward channel: SNR allocation.

In the half-duplex relay channel applying the decode-and-forward protocol the relay introduces energy over random time intervals into the channel as observed at the destination. Consequently, during simulation the average signal power seen at the destination becomes known at run-time only. Therefore, in order to obtain specific performance measures at the signal-to-noise ratio (SNR) of interest, strategies are required to adjust the noise variance during simulation run-time. It is necessary that these strategies result in the same performance as measured under real-world conditions. This paper introduces three noise power allocation strategies and demonstrates their applicability using numerical and simulation results.

Técnicas de manejo agropecuário sustentável

The competitiveness in the rural sector and the need to make viable and sustainable property, direct the farmer to seek new production strategies. In this sense, the book Techniques of sustainable agricultural management has as objective contributed information on concepts, management practices, technological innovations, which are applicable in the agricultural production. The same is composed of 13 chapters, topics covered in aquaculture production, management and dairy production, as general aspects of hematology fish; dynamics of decision-making and adaptive flow dairy production systems; importance of performance measures and body biometrics in small ruminants; milk production in beef cows; parasitism in beef cattle; performance of dairy cows in production; efficiency of cross beef cattle in finishing phase; development of Marchangus: five years; and, bovine growth efficiency. In vegetable production area are addressed matters relating on management and olive cultivation, species of great economic importance and diversification as alternative on the property; functional foods in fruit and vegetables; influence of environmental factors, harvesting and drying in the production and composition of essential oils of Mentha spp; and, implication of the contamination of corn grain by mycotoxins in livestock production. At the end of the book, the expectation of the authors is to have contributed with relevant themes of Brazilian agriculture, which could reflect positively on knowledge, values and quality of available material.

Annual Accountability Report

The South Carolina Office of Executive Policy and Programs submits an annual accountability report to the Governor and General Assembly that contains the agency's or department's mission, objectives to accomplish the mission, and performance measures that show the degree to which objectives are being met.

Annual accountability report, 1997-98

The South Carolina Office of Executive Policy and Programs submits an annual accountability report to the Governor and General Assembly that contains the agency's or department's mission, objectives to accomplish the mission, and performance measures that show the degree to which objectives are being met.