Controlling the polarisation correlation of photon pairs from a charge-tuneable quantum dot

Correlation between the rectilinear polarisations of the photons emitted from the biexciton decay in a single quantum dot is investigated in a device which allows the charge-state of the dot to be controlled. Optimising emission from the neutral exciton states maximises the operating efficiency of the biexciton decay. This is important for single dot applications such as a triggered source of entangled photons. As the bias on the device is reduced correlation between the two photons is found to fall dramatically as emission from the negatively charged exciton becomes significant. Lifetime measurements demonstrate that electronic spin-scattering is the likely cause.Comment: 3 figure

Incubation experiments using nitrogen isotope discrimination to estimate ammonia emission from amended sheep manure treatments.

Two 10-day in vitro experiments were conducted to investigate the relationship between nitrogen (N) isotope discrimination (δ15N) and ammonia (NH3) emissions from sheep manure. In Exp. 1, three different manure mixtures were set up: control (C); C mixed with lignite (C+L); and grape marc (GM), with 5, 4 and 5 replications, respectively. For C, urine and faeces were collected from sheep fed a diet of 550 g lucerne hay/kg, 400 g barley grain/kg and 50 g faba bean/kg; for C+L, urine and faeces were collected from sheep fed the C diet and 100 g ground lignite added to each incubation system at the start of the experiment; for GM, urine and faeces were collected from sheep fed a diet consisting of C diet with 200 g/kg of the diet replaced with GM. In Exp. 2, three different urine-faeces mixtures were set up: 2U:1F, 1.4U:1F, and 1U:1F with urine to faeces ratios of 2:1, 1.4:1, and 1:1, respectively, each with 5 replications. Lignite in C+L led to significantly lower cumulative manure-N loss by 81% and 68% in comparison with C and GM groups, respectively (P = 0.001). Cumulative emitted manure NH3-N was lower in C+L than C and GM groups by 35% and 36%, respectively (P = 0.020). Emitted manure NH3-N was higher in 2U:1F compared to 1.4U:1F and 1U:1F by 18% and 26%, respectively (P &lt; 0.001). This confirms the relationship between manure δ15N and cumulative NH3-N loss reported by earlier studies, which may be useful for estimating NH3 losses.</p

Direct and generative retrieval of autobiographical memories: The roles of visual imagery and executive processes.

Two experiments used a dual task methodology to investigate the role of visual imagery and executive resources in the retrieval of specific autobiographical memories. In Experiment 1, dynamic visual noise led to a reduction in the number of specific memories retrieved in response to both high and low imageability cues, but did not affect retrieval times. In Experiment 2, irrelevant pictures reduced the number of specific memories but only in response to low imageability cues. Irrelevant pictures also increased response times to both high and low imageability cues. The findings are in line with previous work suggesting that disrupting executive resources may impair generative, but not direct, retrieval of autobiographical memories. In contrast, visual distractor tasks appear to impair access to specific autobiographical memories via both the direct and generative retrieval routes, thereby highlighting the potential role of visual imagery in both pathways

新規なバイオ燃料電池材料システムの開発 : プロジェクト名：人工細胞新規マイクロ・リアクタ・システムの開発

指導教員；山口, 猛

Process Monitoring Using Optical Ultrasonic Wave Detection

Certain microstructural features of materials, such as grain size in metals, porosity in ceramics, and structural phase compositions, are important for determining mechanical properties. Many of these microstructural features have been characterized by ultrasonic wave propagation measurements, such as wave velocity and attenuation. Real-time monitoring of ultrasonic wave propagation during the processing stage would be valuable for following the evolution of these features. This paper describes the application of laser ultrasonic techniques to the monitoring of ceramic sintering. Prior to this work, ultrasonic wave measurements of the sintering of ceramics have been made only through direct contact with the material with a buffer rod [1,2]. Recently, several advances have been made using lasers for both generation and detection of ultrasonic waves in a totally noncontacting manner for material microstructure evaluation [3–5]. Application of laser ultrasonic techniques now opens the possibility for real-time monitoring of materials in very hostile environments as are encountered during processing [6]

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