The Relationship between Teachers’ Measures of Resilience and Self-efficacy with their Intent to Remain in the Teaching Profession.

The study examined MDCPS teachers’ measure of resiliency and self-efficacy and their intention to remain in the teaching profession. A survey was sent to 2,000 MDCPS teachers who work within schools located in the Central Region. The survey consisted of the Teachers’ Sense of Self-Efficacy Scale, the Teacher Resiliency Survey, and the Intent to Stay Scale. Demographics information, teaching assignment, preservice preparation program, and Title I school status questions were part of the survey to account for them as control variables. The survey concluded with questions regarding the COVID-19 pandemic. An ordinary least-squares regression analysis was used to predict the value of teachers’ intent to stay. The data on teacher resiliency were inconsistent when compared with the findings of the other data. Teacher-reported resiliency levels were extremely low when compared to the reported levels of self-efficacy and intent to stay. Four different regression models were run, two with the teacher resiliency variable and two without. The first regression model examined teachers’ intent to remain in the teaching profession with teacher resiliency as part of the variables. The results showed three variables with statistical significance: Teacher Self-Efficacy Scale (p=.004), teachers’ age (p=.020) and Title I school status (p= .045). The second model examined the relationship of teachers’ intent to remain in MDCPS with teacher resiliency as part of the variables. The results revealed two variables with statistical significance: Teacher Self-Efficacy Scale (p= .010) and teachers who work at K8 Centers (p=.007). The third regression model examined teachers’ intent to remain in the teaching profession without teacher resiliency as part of the variables. The results indicated three variables with statistical significance: Teacher Self-Efficacy Scale (p=.002), teachers’ age (p=.023) and working in a high school (p= .034). The fourth model examined the relationship of teachers’ intent to remain in MDCPS without teacher resiliency as part of the variables. The results revealed two variables with statistical significance: Teacher Self-Efficacy Scale (p= .008) and teachers who work at K8 Centers (p=.005)

SOCIAL WELFARE AND ENVIRONMENTAL DEGRADATION IN AGRICULTURE: THE CASE OF ECUADOR

A non-linear optimization model which maximizes total Ecuadorian social welfare, defined as the sum of consumers' and producers' surpluses for the four major crops (corn, bananas, rice and African palm) is developed to evaluate the tradeoff between welfare and environmental degradation in Ecuador. It was found that a total welfare loss of US$122 million (a 11 percent reduction - from US$ 1.112 billion to US$ 989.66 million) would be expected from a 30 percent reduction in the total pesticide load on the environment in the production of the four major crops. The distributional impacts of the welfare loss were found, however, to be significantly skewed toward the loss of consumers' surplus. Specifically, a 30 percent reduction of total pesticide load on the environment would result in a reduction of 3.86 percent of producers' total surplus while consumers would be expected to loose 19.46 percent of their total surplus.welfare tradeoff, environmental impacts, non-linear optimization, Environmental Economics and Policy,

POTENTIAL FARM-LEVEL IMPACTS OF PROPOSED FQPA IMPLEMENTATION: THE TENNESSEE CASE

This research estimates farm-level impacts of a potential ban on organophosphates and carbamates under the FQPA. Insecticide expenditure and first- and fifth-year yield impacts are estimated for five Tennessee representative farms. Results indicate that within five years, the ban could reduce net farm income on Tennessee farms by 16 to 46 percent.FQPA, organophosphates, carbamates, insecticides, farm-level analysis, Agricultural and Food Policy, Environmental Economics and Policy,

ESTIMATING PRICE VARIABILITY IN AGRICULTURE: IMPLICATIONS FOR DECISION MAKERS

Using a stochastic version of the POLYSYS modeling framework, an examination of projected variability in agricultural prices, supply, demand, stocks, and incomes is conducted for corn, wheat, soybeans, and cotton during the 1998-2006 period. Increased planting flexibility introduced in the 1996 farm bill results in projections of significantly higher planted acreage variability compared to recent historical levels. Variability of ending stocks and stock-to-use ratios is projected to be higher for corn and soybeans and lower for wheat and cotton compared to the 1986-96 period. Significantly higher variability is projected for corn prices, with wheat and soybean prices also being more variable. No significant change in cotton price variability is projected.POLYSYS model, Price variability, Stochastic simulation, Crop Production/Industries,

Polyhedral study of the 2-dominating set polytope of cycles and cactus graphs

Domination and its variations arise in many applications, in particular in those involving strategic placement of items at vertices of a network. For general graphs these problems are NP-hard, however, domination in graphs has been shown to be polynomially solvable in several graph classes. In this work we consider a generalization of this problem called k-domination in graphs.Sociedad Argentina de Informática e Investigación Operativ

Genotyping strategies for maximizing genomic information in evaluations of the Latxa dairy sheep breed

Genomic selection has been implemented over the years in several livestock species, due to the achievable higher genetic progress. The use of genomic information in evaluations provides better prediction accuracy than do pedigree-based evaluations, and the makeup of the genotyped population is a decisive point. The aim of this work is to compare the effect of different genotyping strategies (number and type of animals) on the prediction accuracy for dairy sheep Latxa breeds. A simulation study was designed based on the real data structure of each population, and the phenotypic and genotypic data obtained were used in genetic (BLUP) and genomic (single-step genomic BLUP) evaluations of different genotyping strategies. The genotyping of males was beneficial when they were genetically connected individuals and if they had daughters with phenotypic records. Genotyping females with their own lactation records increased prediction accuracy, and the connection level has less relevance. The differences in genotyping females were independent of their estimated breeding value. The combined genotyping of males and females provided intermediate accuracy results regardless of the female selection strategy. Therefore, assuming that genotyping rams is interesting, the incorporation of genotyped females would be beneficial and worthwhile. The benefits of genotyping individuals from various generations were highlighted, although it was also possible to gain prediction accuracy when historic individuals were not considered. Greater genotyped population sizes resulted in more accuracy, even if the increase seems to reach a plateau

Polyhedral study of the 2-dominating set polytope of cycles and cactus graphs

Domination and its variations arise in many applications, in particular in those involving strategic placement of items at vertices of a network. For general graphs these problems are NP-hard, however, domination in graphs has been shown to be polynomially solvable in several graph classes. In this work we consider a generalization of this problem called k-domination in graphs.Sociedad Argentina de Informática e Investigación Operativ

A Farm-Level Evaluation of Conditions Under Which Farmers Will Supply Biomass Feedstocks for Energy Production

This study evaluated the risk management potential of including biomass crops as a diversification strategy for a grain farm in northwest Tennessee. Results indicate that adding biomass crops to the farm enterprise mix could improve mean net revenues and reduced net revenue variability.Resource /Energy Economics and Policy,

Ensilaje de forraje de vegas naturales en Tierra del Fuego, Argentina

722-728Livestock activity in the Argentinian «Tierra del Fuego» island is based on highly variable natural grasslands (NG). The conservation of fodder, despite the unfavorable environment, is restricted to hay; conservation as silage could be constrained by fodder quality and low temperatures. The objective was to assess the quality of NG silages fermented under contrasting storing conditions. Typical meadow forage was ensiled in minisilos and stored under shelter (Shelter) or in the field (Field) in a complete block design with repeated measures in time (t). Forage was chopped and inoculated with lactic acid bacteria plus enzymes, and harvested with 420 g dry matter (DM) kg-1 fresh matter, 111 g crude protein kg-1 DM, 665 g ash-free neutral detergent fibre kg-1 DM, and 64 g water soluble carbohydrates kg-1 DM. Shelter minisilos had higher metabolizable energy concentration at 236 d (PTrat×t = 0.03; Shelter = 10.2 ; Field = 9.6 MJ kg-1 DM, P = 0.01), and lower DM losses (Shelter = -0.2; Campo = 22 percent, P = 0.02) and values of pH and N-NH3/total N (Field: 5.6 and 12 percent and Shelter: 4.4 and 6.8 percent, P = 0.01). Fermentation acids concentration was similar for both treatments with preponderance of lactic acid, but acetic acid concentration increased over time (Pt = 0.01). It was concluded that in «Tierra del Fuego», natural meadow forage quality is compatible with ensiling, but environmental conditions can limit the fermentation process. Additional key words: forage conservation, natural grasslands, Patagonia, silage