Rapid high-resolution mid-IR imaging for molecular spectral histopathological diagnosis of oesophageal cancers

This thesis is written as part of Marie-Curie international training network called Mid-TECH. Mid-TECH is devoted to improve mid-infrared (MIR) technologies and consists of 15 PhD projects across European universities. This thesis aims to evaluate new technologies and concepts developed by the project partners for their applicability in a biomedical setting. The clinical problem to diagnose oesophageal cancers serves as an example case for this. The thesis consists of three projects all aimed to further the understanding of MIR hyperspectral imaging. The first project discussed in chapter 5 demonstrates the use of an new design of the United States Airforce resolution test chart. The new test chart is developed to evaluate spatial resolution of MIR hyperspectral imaging systems. The use of different materials is discussed and the new iteration of the thes chart is evaluated using a state of the art MIR imaging system. The second project discussed in chapter 6 evaluates the technical differences and their practical implications of discrete frequency MIR imaging systems compared to continuum source systems. A comparison of the two system types is drawn for imaging paraffin embedded sections of oesophageal tissue. Furthermore the effect of chemically removing the paraffin from the sample is compared to a mathematical correction algorithm. The system performance is compared based on their ability to differentiate healthy from cancerous tissue. The third project discussed in chapter 7 evaluates the potential of a new MIR detection scheme called upconversion in combination with a novel MIR laser source. It is a prove of concept study demonstrating that those two technologies can be deployed to do hyperspectral imaging in the MIR.European Commissio

UAVs for the Environmental Sciences

This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application

Supplementary report to the final report of the coral reef expert group: S6. Novel technologies in coral reef monitoring

[Extract] This report summarises a review of current technological advances applicable to coral reef monitoring, with a focus on the Great Barrier Reef Marine Park (the Marine Park). The potential of novel technologies to support coral reef monitoring within the Reef 2050 Integrated Monitoring and Reporting Program (RIMReP) framework was evaluated based on their performance, operational maturity and compatibility with traditional methods. Given the complexity of this evaluation, this exercise was systematically structured to address the capabilities of technologies in terms of spatial scales and ecological indicators, using a ranking system to classify expert recommendations.An accessible copy of this report is not yet available from this repository, please contact [email protected] for more information

Growing grass for a green biorefinery - an option for Ireland?

Growing grass for a green biorefinery – an option for Ireland? Mind the gap: deciphering the gap between good intentions and healthy eating behaviour Halting biodiversity loss by 2020 – implications for agriculture A milk processing sector model for Irelan

Impact of Geographical Information Systems on Geotechnical Engineering

Over the last four decades Geographical Information Systems (GIS) have emerged as the predominant medium for graphic representation of geospatial data, including geotechnical, geologic and hydrologic information routinely used by geotechnical and geoenvironmental engineers. GIS allow unlimited forms of spatial data to be co-mingled, weighted and sorted with any number of physical or environmental factors. These data can also be combined with weighted political and aesthetic values to create hybrid graphic products capable of swaying public perceptions and decision making. The downside of some GIS products is that their apparent efficacy and crispness can also be deceptive, if data of unparalleled reliability is absorbed in the mix. Disparities in data age and quality are common when compiling geotechnical and geoenvironmental data. Despite these inherent shortcomings, GIS will continue to grow and evolve as the principal technical communication medium over the foreseeable future and engineers will be forced to prepare their work products in GIS formats which can be widely disseminated through the world wide web. This paper presents the historical evolution of GIS technologies as it relates to the impact in geotechnical engineering, concluding with four case histories on the application of this emerging technology

Future ecosystem services of temperate grasslands: bridging scales towards high-resolution spatio-temporal monitoring

Temperate grasslands cover approximately 38% of the European agricultural area and provide various ecosystem services such as forage production, biodiversity conservation and carbon sequestration. These ecosystem services strongly depend on the biomass productivity, which with future global changes remains uncertain. Above all, an increasing atmospheric CO2 concentration ([CO2 ]) is assumed to enhance biomass productivity (called the CO2 fertilization effect; CFE) in particular under dry and hot conditions, while such probable future environmental conditions rather decrease the grassland productivity in general. However, recent doubts about the classic view on the CFE call for in-depth analysis of the interacting effects of the CFE and varying environmental conditions on grassland productivity, which is usually done by CO2 enrichment studies. Here, Free Air Carbon dioxide Enrichment (FACE) experiments have proven to be the most suitable approaches due to their minimal invasive character. Consequently, this study uses the worldwide longest operating FACE experiment on grassland, the Giessen FACE facility (GiFACE), to improve the assessment of the potential future of ecosystem services under global change. Initially, it was tested whether the CFE in the GiFACE grassland is reduced under more extreme average weather conditions and after single extreme climatic events. To cope with the real-world conditions, a specific approach, called moving subset analysis, was developed to enable the quantification of the CFE in dependence of average weather conditions under varying [CO2 ]s. Additionally, a time series analysis was developed to link single extreme climatic events (ECEs) with the strength of the CFE. It was found that the CFE was significant and strong under local average environmental conditions (defined by ±1 SD of long-term average conditions), but decreased under more extreme weather conditions. The strongest decrease in the CFE under ECEs was associated with intensive and long heat waves, and could be quantified to a large extent by calculating the Killing Degree Days (∼30% variance of the magnitude of the CFE). Since the CFE was found to be reduced under unfavourable environmental conditions, the potential of future grassland productivity was assessed in a further step. Therefore, potential future climate regimes and statistical models of biomass were created using the long-term experimental observations. Biomass was predicted using climate variable alterations within the potential climate regimes. The comparison of the potential regimes with the climate model projections for the years with a similar [CO2 ] compared to enriched [CO2 ]s revealed that biomass is likely to be reduced in the mid of 21st century despite the increase in [CO2 ], and thus that the CFE cannot compensate yield losses due to unfavourable environmental conditions. Short-term environmental changes such as ECEs were shown to affect the grassland productivity while their influence might be elusive to the traditional destructive sampling approaches at harvest dates. To overcome these sampling restrictions, in the final step of this study, the feasibility of the non-invasive hyperspectral monitoring of the GiFACE grassland on a high spatio-temporal resolution was investigated. Thus, methods were developed to work with hyperspectral data and the comprehensive statistical software CRAN R. The methods developed were used to derive transfer functions between hyperspectral measurements and various laboratory-derived grassland traits by applying machine learning approaches. Good to very good leave-one-out prediction results revealed that the most important ecosystem services can precisely be predicted by hyperspectral approaches. Hyperspectral predictions of the most important grassland traits during the vegetation period highlighted how remote sensing approaches can improve grassland management in future. Alarmingly, the reduced CFE and biomass productivity in grasslands under unfavourable future environmental conditions as detected in this thesis, suggest decreasing ecosystem services such as carbon sequestration and related climate mitigation function in future. This may – in a vicious circle – lead to a further aggravation of expected global changes and urgently calls for better mitigation and adaptation strategies. Measures necessary for this could be instructed and monitored by remote sensing methods, as was shown by the present thesis