Why Teach? Exploring the Motivations and Expectations of First-year, Alternatively Certified Agriscience Teachers

School-Based agricultural education increasingly depends upon alternatively certified (AC) teachers to teach agriculture across the United States. Understanding why these individuals become teachers is an important step to better recruit and retain educators who do not complete traditional preparation programs. The purpose of our study was to explore the backgrounds, motivations, and expectations of AC agriscience teachers joining the profession. Our study was guided by the social cognitive career theory and utilized a qualitative phenomenological approach. We interviewed seven AC agriscience teachers in Florida during their first-year teaching to explore their journey into teaching agricultural education. Six major themes were found, including background and interest in agriculture, positive teaching self-efficacy expectations, positive teaching outcome expectations, right location and right time, exciting but challenging, and more than expected. We recommend providing support programs tailored for AC agriscience teachers that are guided by the similar backgrounds, motivations, and expectations of AC teachers

Effect of Tuned Parameters on a LSA MCQ Answering Model

This paper presents the current state of a work in progress, whose objective is to better understand the effects of factors that significantly influence the performance of Latent Semantic Analysis (LSA). A difficult task, which consists in answering (French) biology Multiple Choice Questions, is used to test the semantic properties of the truncated singular space and to study the relative influence of main parameters. A dedicated software has been designed to fine tune the LSA semantic space for the Multiple Choice Questions task. With optimal parameters, the performances of our simple model are quite surprisingly equal or superior to those of 7th and 8th grades students. This indicates that semantic spaces were quite good despite their low dimensions and the small sizes of training data sets. Besides, we present an original entropy global weighting of answers' terms of each question of the Multiple Choice Questions which was necessary to achieve the model's success.Comment: 9 page

Non Destructive Evaluation of Containment Walls in Nuclear Power Plants

Two functions are regularly tested on the containment walls in order to anticipate a possible accident. The first is mechanical to resist at a possible internal over-pressure and the second is to prevent leakage. The reference accident LLOCA (Large Loss of Coolant Accident) is the rupture of a pipe in the primary circuit of a nuclear plant. In this case, the pressure and temperature can reach 5 bar and 180°C in 20 seconds. The national project ‘Non-destructive testing of the containment structures of nuclear plants’ aims at studying the non-destructive techniques capable to evaluate the concrete properties and its damaging or progression of cracks. This 4-year-project is segmented into two parts. The first consists in developing and selecting the most relevant NDEs (Non Destructive Evaluations) in the laboratory to reach these goals. These evaluations are developed in conditions representing the real conditions of the stresses generated during ten-yearly visits of the plants or those related to an accident. The second part consists in applying the selected techniques to two containment structures under pressure. The first (technique) is proposed by the ONERA (National Office for Aerospace Studies and Research of France) and the second is a mock-up of a containment wall on a 1/3 scale made by EDF (Electricity of France) within the VeRCoRs program. Communication bears on the part of the project that concerns the damaging and cracking follow-up. The tests are done in bending on 3 or 4 points in order to study the cracks’ generation, their propagation, as well as their opening and closing. The mostly ultrasonic techniques developed concern linear or non-linear acoustic: acoustic emission [1], LOCADIFF (Locating with diffuse ultrasound) [2], energy diffusion, surface waves velocity and attenuation, DAET (Dynamic Acousto-Elasticity Testing) [3]. The data contribute to providing the mapping of the parameters searched for, either in volume, in surface or globally. Image correlation is an important additional asset to validate the coherence of the data. The spatial normalization of the data allows proposing algorithms on the combination of the experimental data. The tests results are presented and they show the capacity and the limits of the evaluation of the volume, surface or global data. A data fusion procedure is associated with these results

Challenging the other: exploring the role of opponent gender in digital game competition for female players

The present study investigated the effect of opponent gender on the game experience of female players. Concretely, it looked into skill perception and player emotions of women in same-gender and cross-gender game competition. We set up a 2 (male vs. female opponent) x 2 (low vs. high competitive women) x 2 (lost vs. won game) experimental design in which women were instructed to play against a proclaimed male and female competitor. Unknowingly, participants played against an AI, however, which was configured to produce a winning and a losing condition for each opponent by manipulating difficulty. Results indicated that opponent gender only had an effect on perceived stress, which was higher with male opponents. Moreover, players evaluated their own gaming skills as lower when they thought they were playing against men and the skills of presumed male opponents as higher. Importantly our results also showed that the above described pattern for self-perceived skills and perceived opponent skills was modulated by trait competitiveness with a larger effect size for low competitive women. Overall, this study illustrates that gender dynamics affect the play experience of women in cross-gender gaming competition. Implications and suggestions for future research are discussed

Microbial activity monitoring by the Integrated Arctic Earth Observing System (MamSIOS)

Microorganisms, though already integral elements, are likely to play an increasingly important role in the Earth’s climate system (Falkowski et al., 2008) and are known to affect polar biogeochemical cycles (Larose et al., 2013a). In particular, they play important roles in the generation and decomposition of climate active gases. However, current climate models do not take into account the response of microbial activity and their influence in biochemical cycles (Incorporating microbial processes into climate models, ASM report). To improve the predictive ability of climate models, it is important to understand the mechanisms by which microorganisms regulate terrestrial greenhouse gas flux and to determine whether changes in microbial processes will lead to net positive or negative feedbacks on greenhouse gas emissions (Singh et al., 2010). This contribution has been particularly overlooked for the polar regions (Figure 1), where the environment has traditionally been considered too harsh for significant microbial activity to occur. It has long been considered that any life, if present at all, was either dormant or functioning sub-optimally, as living organisms have to be well adapted or highly resistant to extreme cold and desiccation, low nutrient availability and seasonally variable UV radiation levels in order to survive (Harding et al., 2011; Cameron et al., 2012; Goordial et al., 2013; Larose et al., 2013a). However, it is now clear that microbial presence is ubiquitous across the polar regions, and recent research into the polar aerobiome points toward a potentially dynamic polar microbial community and with it, the possibility of significant microbial activity within the snowpack (Redeker et al., 2017), even in the most remote locations (Pearce et al., 2009). Research into the aerobiome has also demonstrated that microorganisms in aerial fallout may remain both viable and active (Sattler et al., 2001; Harding et al., 2011). Furthermore, the presence of microbes in remote, low nutrient, low water, very cold environments such as polar glacial surfaces is now well established for a number of key sites (Hodson et al., 2008; Larose et al., 2010)

Bacterial diversity in snow on North Pole ice floes

The microbial abundance and diversity in snow on ice floes at three sites near the North Pole was assessed using quantitative PCR and 454 pyrosequencing. Abundance of 16S rRNA genes in the samples ranged between 43 and 248 gene copies per millilitre of melted snow. A total of 291,331 sequences were obtained through 454 pyrosequencing of 16S rRNA genes, resulting in 984 OTUs at 97 % identity. Two sites were dominated by Cyanobacteria (72 and 61 %, respectively), including chloroplasts. The third site differed by consisting of 95 % Proteobacteria. Principal component analysis showed that the three sites clustered together when compared to the underlying environments of sea ice and ocean water. The Shannon indices ranged from 2.226 to 3.758, and the Chao1 indices showed species richness between 293 and 353 for the three samples. The relatively low abundances and diversity found in the samples indicate a lower rate of microbial input to this snow habitat compared to snow in the proximity of terrestrial and anthropogenic sources of microorganisms. The differences in species composition and diversity between the sites show that apparently similar snow habitats contain a large variation in biodiversity, although the differences were smaller than the differences to the underlying environment. The results support the idea that a globally distributed community exists in snow and that the global snow community can in part be attributed to microbial input from the atmosphere. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00792-014-0660-y) contains supplementary material, which is available to authorized users

Signature of a Pre-Human Population Decline in the Critically Endangered Reunion Island Endemic Forest Bird Coracina newtoni

The exceptional biodiversity of Reunion Island is threatened by anthropogenic landscape changes that took place during the 350 years of human colonization. During this period the human population size increased dramatically from 250 to 800,000. The arrival of humans together with the development of agriculture, invasive species such as rats and cats, and deforestation has lead to the extinction of more than half of the original vertebrate species of the island. For the remaining species, significant work is being carried out to identify threats and conservation status, but little genetic work has been carried on some of the most endangered species. In the last decade theoretical studies have shown the ability of neutral genetic markers to infer the demographic history of endangered species and identify and date past population size changes (expansions or bottlenecks). In this study we provide the first genetic data on the critically endangered species the Reunion cuckoo-shrike Coracina newtoni. The Reunion cuckoo-shrike is a rare endemic forest bird surviving in a restricted 12-km2 area of forested uplands and mountains. The total known population consists of less than one hundred individuals out of which 45 were genotyped using seventeen polymorphic microsatellite loci. We found a limited level of genetic variability and weak population structure, probably due to the limited geographic distribution. Using Bayesian methods, we identified a strong decline in population size during the Holocene, most likely caused by an ancient climatic or volcanic event around 5000 years ago. This result was surprising as it appeared in apparent contradiction with the accepted theory of recent population collapse due to deforestation and predator introduction. These results suggest that new methods allowing for more complex demographic models are necessary to reconstruct the demographic history of populations