Commodity Agreements and the New International Economic Order

[No abstract

How Have Changes in OSD-Level Oversight of Major Defense Acquisition Programs Influenced Cost Growth?

Naval Postgraduate School Acquisition Research Progra

Mutation of Arabidopsis SPLICEOSOMAL TIMEKEEPER LOCUS1 Causes Circadian Clock Defects

The circadian clock plays a crucial role in coordinating plant metabolic and physiological functions with predictable environmental variables, such as dusk and dawn, while also modulating responses to biotic and abiotic challenges. Much of the initial characterization of the circadian system has focused on transcriptional initiation, but it is now apparent that considerable regulation is exerted after this key regulatory step. Transcript processing, protein stability, and cofactor availability have all been reported to influence circadian rhythms in a variety of species. We used a genetic screen to identify a mutation within a putative RNA binding protein (SPLICEOSOMAL TIMEKEEPER LOCUS1 [STIPL1]) that induces a long circadian period phenotype under constant conditions. STIPL1 is a homolog of the spliceosomal proteins TFP11 (Homo sapiens) and Ntr1p (Saccharomyces cerevisiae) involved in spliceosome disassembly. Analysis of general and alternative splicing using a high-resolution RT-PCR system revealed that mutation of this protein causes less efficient splicing of most but not all of the introns analyzed. In particular, the altered accumulation of circadian-associated transcripts may contribute to the observed mutant phenotype. Interestingly, mutation of a close homolog of STIPL1, STIP-LIKE2, does not cause a circadian phenotype, which suggests divergence in function between these family members. Our work highlights the importance of posttranscriptional control within the clock mechanism. © 2012 American Society of Plant Biologists. All rights reserved

Commodity Agreements and the New International Economic Order

[No abstract

Adoption of precision livestock farming technologies has the potential to mitigate greenhouse gas emissions from beef production

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometer based sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kgCO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3  months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems

Adoption of precision livestock farming technologies has the potential to mitigate greenhouse gas emissions from beef production

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometer based sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kgCO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3  months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems

The impacts of precision livestock farming tools on the greenhouse gas emissions of an average Scottish dairy farm

Precision livestock farming (PLF) tools are increasingly used in daily herd management to improve health, welfare, and overall production. While not intended to reduce greenhouse gas (GHG) emissions on farm, PLF tools can do so indirectly by improving overall efficiency, thereby reducing the emissions per unit of product. This work modelled the potential effects of commercially available PLF tools on whole enterprise and product emissions of two average Scottish dairy farm systems (an 8,000  L and 10,000  L herd) using the Agrecalc carbon foot printing tool. Scenarios modelled included an improvement infertility and an improvement in fertility and yield from the introduction of an accelerometer-based sensor, and an improvement in health from introduction of an accelerometer-based sensor, with and without the use of management interventions. Use of a sensor intended to improve fertility had the large streduction in total emissions (kg CO2e) of −1.42% for a 10,000  L farm, with management changes applied. The largest reduction in emissions from milk production (kg CO2e) of −2.31% was observed via fertility technology application in an 8,000  L farm, without management changes. The largest reduction in kg CO2e per kg fat and protein corrected milk of −6.72% was observed from an improvement in fertility and yield in a 10,000  L herd, with management changes. This study has highlighted the realistic opportunities available to dairy farmers in low and high input dairy systems to reduce their emissions through adoption of animal mounted PLF technologies

Measuring Metacognition in Cancer: Validation of the Metacognitions Questionnaire 30 (MCQ-30)

Objective The Metacognitions Questionnaire 30 assesses metacognitive beliefs and processes which are central to the metacognitive model of emotional disorder. As recent studies have begun to explore the utility of this model for understanding emotional distress after cancer diagnosis, it is important also to assess the validity of the Metacognitions Questionnaire 30 for use in cancer populations. Methods 229 patients with primary breast or prostate cancer completed the Metacognitions Questionnaire 30 and the Hospital Anxiety and Depression Scale pre-treatment and again 12 months later. The structure and validity of the Metacognitions Questionnaire 30 were assessed using factor analyses and structural equation modelling. Results Confirmatory and exploratory factor analyses provided evidence supporting the validity of the previously published 5-factor structure of the Metacognitions Questionnaire 30. Specifically, both pre-treatment and 12 months later, this solution provided the best fit to the data and all items loaded on their expected factors. Structural equation modelling indicated that two dimensions of metacognition (positive and negative beliefs about worry) were significantly associated with anxiety and depression as predicted, providing further evidence of validity. Conclusions These findings provide initial evidence that the Metacognitions Questionnaire 30 is a valid measure for use in cancer populations

An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas

Current satellite remote sensing methods struggle to detect and map forest degradation, which is a critical issue as it is likely a major and growing source of carbon emissions and biodiveristy loss. TanDEM-X InSAR phase height (hϕ) is a promising variable for measuring forest disturbances, as it is closely related to the mean canopy height, and thus should decrease if canopy trees are removed. However, previous research has focused on relatively flat terrains, despite the fact that much of the world’s remaining tropical forests are found in hilly areas, and this inevitably introduces artifacts in sideways imaging systems. In this paper, we find a relationship between hϕ and aboveground biomass change in four selectively logged plots in a hilly region of central Gabon. We show that minimising multilooking prior to the calculation of hϕ strengthens this relationship, and that degradation estimates across steep slopes in the surrounding region are improved by selecting data from the most appropriate pass directions on a pixel-by-pixel basis. This shows that TanDEM-X InSAR can measure the magnitude of degradation, and that topographic effects can be mitigated if data from multiple SAR viewing geometries are available

Furthering alternative cultures of valuation in higher education research

The value of higher education is often implicit or assumed in educational research. The underlying and antecedent premises that shape and influence debates about value remain unchallenged which perpetuates the dominant, but limiting, terms of the debate and fosters reductionism. I proceed on the premise that analyses of value are not self–supporting or self-referential but are embedded within prevailing cultures of valuation. I contend that challenging, and providing alternatives to, dominant narratives of higher education requires an appreciation of those cultures. I therefore highlight some of the existing cultures of valuation and their influence. I then propose Sayer’s concept of lay normativity as a culture of valuation and discuss how it translates into the practices of research into higher education, specifically the practice of analysis. I animate the discussion by detecting the presence of lay normativity in the evaluative space of the capability approach