Challenged Index: Why Newsweek's List of America's 100 Best High Schools Doesn't Make the Grade

Some schools on Newsweek's list of America's Top 100 high schools have large achievement gaps, grossly shortchange disadvantaged groups, and have a substantial number of drop-outs

A Sum Greater Than the Parts: What States Can Teach Each Other About Charter Schooling

States with a significant charter sector know firsthand that the success or failure of a charter school is not a matter of chance, but subject to variances in state laws and a state's educational, political, and regulatory climate. In this report, Sara Mead and Andrew J. Rotherham draw on the experiences of 12 states, proposing those lessons that are necessary for charter school quality and growth

Tariff Rate Quotas and New Zealand’s Meat and Dairy Trade

The tariff rate quota (TRQ) system was formalised in the Uruguay Round with the aim of maintaining and improving market access for agricultural products. Under this system, a lower tariff rate is applied to imports up to the quota limit, with a higher (and often prohibitive) tariff rate levied on products imported beyond this quota. However, the success of the TRQ system has been limited, with dairy and meat products in particular still facing relatively high barriers to international trade. In this paper, we examine the impact of the TRQ system on New Zealand’s meat and dairy trade. We draw together theoretical and empirical insights and present preliminary findings arising from interviews with key stakeholders. In particular, we examine whether the TRQ system has achieved its objectives from the perspective of the dairy and meat sectors in New Zealand and we analyse problems that appear to exist with the system. We also examine implications of reform of the TRQ system, including lower in- and over-quota rates, increased quota limits and more transparent and efficient administration methods.Agribusiness, Agricultural and Food Policy, Crop Production/Industries, Environmental Economics and Policy, Farm Management, International Relations/Trade, Land Economics/Use, Livestock Production/Industries,

Herbicide mixtures at high doses slow the evolution of resistance in experimentally evolving populations of Chlamydomonas reinhardtii

The widespread evolution of resistance to herbicides is a pressing issue in global agriculture. Evolutionary principles and practices are key to the management of this threat to global food security. The application of mixtures of herbicides has been advocated as an anti-resistance strategy, without substantial empirical support for its validation. We evolved experimentally populations of the unicellular green chlorophyte, Chlamydomonas reinhardtii, to minimum inhibitory concentrations (MICs) of single-herbicide modes of action and to pair-wise and three-way mixtures between different herbicides at various total combined doses. Herbicide mixtures were most effective when each component was applied at or close to its MIC. When doses were high, increasing the number of mixture components was also effective in reducing the evolution of resistance. Employing mixtures at low combined doses did not retard resistance evolution, even accelerating the evolution of resistance to some components. At low doses, increasing the number of herbicides in the mixture tended to select for more generalist resistance (cross-resistance). Our results reinforce findings from the antibiotic resistance literature and confirm that herbicide mixtures can be very effective for resistance management, but that mixtures should only be employed where the economic and environmental context permits the applications of high combined doses

Statistical modelling of transcript profiles of differentially regulated genes

Background: The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA) and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results: Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Splitline" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t) = A + (B + Ct)Rt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data allowed 11% of the Escherichia coli features to be fitted by an exponential function, and 25% of the Rattus norvegicus features could be described by the critical exponential model, all with statistical significance of p < 0.05. Conclusion: The statistical non-linear regression approaches presented in this study provide detailed biologically oriented descriptions of individual gene expression profiles, using biologically variable data to generate a set of defining parameters. These approaches have application to the modelling and greater interpretation of profiles obtained across a wide range of platforms, such as microarrays. Through careful choice of appropriate model forms, such statistical regression approaches allow an improved comparison of gene expression profiles, and may provide an approach for the greater understanding of common regulatory mechanisms between genes

The effect of within-crop habitat manipulations on the conservation biological control of aphids in field-grown lettuce

Within-crop habitat manipulations have the potential to increase the biological control of pests in horticultural field crops. Wildflower strips have been shown to increase the abundance of natural enemies, but there is little evidence to date of an impact on pest populations. The aim of this study was to determine whether withincrop wildflower strips can increase the natural regulation of pests in horticultural field crops. Aphid numbers in plots of lettuce grown adjacent to wildflower strips were compared with those in plots grown in the absence of wildflowers. The presence of wildflower strips led to a decrease in aphid numbers on adjacent lettuce plants during June and July, but had less impact in August and September. The decrease in aphid numbers was greatest close to the wildflower strips and, the decrease in aphid numbers declined with increasing distance from the wildflower strips, with little effect at a distance of ten metres. The main natural enemies found in the crop were those that dispersed aerially, which is consistent with data from previous studies on cereal crops. Analysis and interpretation of natural enemy numbers was difficult due to low recovery of natural enemies, and the numbers appeared to follow changes in aphid abundance rather than being directly linked to the presence of wildflower strips. Cutting the wildflower strips, to remove floral resources, had no impact on the reduction in aphid numbers achieved during June and July, but decreased the effect of the wildflower strips during August and September. The results suggest that wildflower strips can lead to increased natural regulation of pest aphids in outdoor lettuce crops, but more research is required to determine how this is mediated by natural enemies and how the impact of wildflower strips on natural pest regulation changes during the growing season

Performance of carrot and onion seed primed with beneficial microorganisms in glasshouse and field trials

Beneficial microorganisms (Clonostachys rosea IK726, Pseudomonas chlororaphis MA342, Pseudomonas fluorescens CHA0, Trichoderma harzianum T22 and Trichoderma viride S17a) were successfully applied to carrot and onion seed during a commercial drum priming process. Applied microorganisms were recovered above the target of at least 1 × 105 cfu g−1 seed following subsequent application of pesticides to the seed according to standard commercial practices of film-coating carrot and pelletting onion seed. Two glasshouse experiments consistently showed that priming improved emergence of carrot seed and that C. rosea IK726 further improved emergence time. Priming improved emergence of onion seed in one glasshouse experiment, but had an unexpected negative effect on emergence in the second experiment, possibly due to the proliferation of an unidentified indigenous microorganism during priming, becoming deleterious in high numbers. In this experiment, the application of beneficial microorganisms during priming negated this effect and significantly improved emergence. For each crop, a series of field trials was also carried out over three years, at two different sites each year. Although some positive effects of different seed treatments were seen on emergence or yield in individual field trials, no consistent effects were found for primed or microorganism-treated seed across all sites and years. However, a combined analysis of data for all years and sites indicated that pesticide application did consistently improve emergence and yield for both carrot and onion. This is the first comprehensive study assessing glasshouse and field performance of carrot and onion seed primed with beneficial microorganisms during a commercial process of drum priming in the UK

Activation workers’ perceptions of their long-term unemployed clients’ attitudes towards employment

The Work Programme’s use of severe social security benefit sanctions reflects British coalition ministers’ belief that many people on out-of-work benefits do not want a job. While a substantial empirical literature has repeatedly demonstrated that in fact unemployed benefit claimants possess the same work values as the employed and that the vast majority want paid work, it has ignored some conservative authors’ pleas to consider the views and experiences of people who work with the unemployed. Forty employees of agencies contracted to help unemployed people into employment were interviewed in summer 2011. Respondents had spent an estimated combined total of 147,000 hours in the presence of people who have claimed Jobseeker’s Allowance (JSA) for over six months. Most said that between a quarter and half of their present clients did not want employment. This finding does not contradict existing research, given that most JSA claimants re-enter employment within six months. However, all forty agreed that many others remained unemployed because they were choosy in the jobs they were willing to undertake, and,most strikingly, respondents overwhelmingly endorsed the view that a ‘dependency culture’ exists in households and neighbourhoods that have experienced joblessness for several generations

A sensitivity analysis of the prediction of the nitrogen fertilizer requirement of cauliflower crops using the HRI WELL_N computer model

HRI WELL_N is an easy to use computer model, which has been used by farmers and growers since 1994 to predict crop nitrogen (N) requirements for a wide range of agricultural and horticultural crops. A sensitivity analysis was carried out to investigate the model predictions of the N fertilizer requirement of cauliflower crops, and, at that rate, the yield achieved, yield response to the fertilizer applied, N uptake, NO3-N leaching below 30 and 90 cm and mineral N at harvest. The sensitivity to four input factors – soil mineral N before planting, mineralization rate of soil organic matter, expected yield and duration of growth – was assessed. Values of these were chosen to cover ranges between 40% and 160% of values typical for field crops of cauliflowers grown in East Anglia. The assessments were made for three soils – sand, sandy loam and silt – and three rainfall scenarios – an average year and years with 144% or 56% of average rainfall during the growing season. The sensitivity of each output variable to each of the input factors (and interactions between them) was assessed using a unique ‘sequential' analysis of variance approach developed as part of this research project. The most significant factors affecting N fertilizer requirement across all soil types/rainfall amounts were soil mineral N before planting and expected yield. N requirement increased with increasing yield expectation, and decreased with increasing amounts of soil mineral N before planting. The responses to soil mineral N were much greater when higher yields were expected. Retention of N in the rooting zone was predicted to be poor on light soils in the wettest conditions suggesting that to maximize N use, plants needed to grow rapidly and have reasonable yield potential. Assessment of the potential impacts of errors in the values of the input factors indicated that poor estimation of, in particular, yield expectation and soil mineral N before planting could lead to either yield loss or an increased level of potentially leachable soil mineral N at harvest. The research demonstrates the benefits of using computer simulation models to quantify the main factors for which information is needed in order to provide robust N fertilizer recommendations

Temperature, light and nitrate sensing coordinate Arabidopsis seed dormancy cycling resulting in winter and summer annual phenotypes

Seeds use environmental cues to sense the seasons and their surroundings to initiate the plants life cycle. Dormancy cycling underlying this process is extensively described, but the molecular mechanism is largely unknown. To address this we selected a range of representative genes from published array experiments in the laboratory and investigated their expression patterns in seeds of Arabidopsis ecotypes, having contrasting life cycles, over an annual dormancy cycle in the field. We show how mechanisms identified in the laboratory are coordinated in response to the soil environment to determine dormancy cycles that result in winter and summer annual phenotypes. Our results are consistent with a seed specific response to seasonal temperature patterns (temporal sensing) involving the gene DELAY OF GERMINATION1 (DOG1) that indicates the correct season; and concurrent temporally driven co-opted mechanisms that sense spatial signals i.e. nitrate via CBL-INTERACTING PROTEIN KINASE 23 (CIPK23) phosphorylation of the NITRATE TRANSPORTER 1 (NRT1.1) and light via PHYTOCHROME A (PHYA). In both ecotypes studied, when all three genes have low expression there is enhanced GIBBERELLIN 3 BETA-HYDROXYLASE 1 (GA3ox1) expression, exhumed seeds have the potential to germinate in the laboratory, and the initiation of seedling emergence occurs following soil disturbance (exposure to light) in the field. Unlike DOG1, expression of MOTHER of FLOWERING TIME (MFT) has an opposite thermal response in seeds of the two ecotypes indicating a role in determining their different dormancy cycling phenotypes