Artificial light spectra and plant growth : a thesis presented in partial fulfilment of the requirements for the degree of Master of Horticultural Science in Plant Science at Massey University

The growth, development and differentiation of plants growing in natural environments is determined by biotic, genetic and physical factors. Within each plant species the absolute limits of any growth response is established by inherent genetic information and the delineation of that response is, in turn, determined by the physiology of the plant. Among the most important physical factors in any natural environment are light quality, quantity and duration. Plant growth depends on a very narrow bandwidth of the electromagnetic spectrum which usually includes the near ultraviolet (down to 320 nm), the visible, and the near infra-red (up to 800 nm) regions. The radiation of this spectral range not only supplies the necessary energy for photosynthesis on which plant metabolism is based, but also by way of various photomorphogenetic processes, it controls, independently of photosynthesis, the way in which this captured energy is directed along the various metabolic pathways. Since for most processes other than photosynthesis, the amount of radiant energy initially absorbed is low, in relation to the response effect, these light reactions can be considered to belong to a group of photostimulus processes which are characterised by dose-effect relationships. These are exothermic in that they ultimately release, or direct an amount of stored energy, which may be very large as compared with the energy content of the radiation initially responsible for the stimulus (Wassink and Stolwijk, 1956)

Sleep and activity measurement in search and rescue aircraft crews using novel sensing technologies.

Helicopter search and rescue crews (SARC) remain on 24 hour alert. This requires the SARC to remain in a state of readiness and maximise sleep opportunities. When on duty, depending on their proximity to the SAR base, crew members may either sleep on-base or at home. These factors may lead to possible variations in the level of physical activity (PA), sleep duration (Sdur) and sleep efficiency (Sef). Purpose: To investigate the levels of PA, Sdur, and Sef of members of the SARC during a 24 hour on-call shift using several novel sensing technologies. Method: Ten members of the Dublin SARC (mean ± SD: age 40 ± 5 years; height 1.76 ± 0.06m; mass 89.2 ± 14 kg; 5 on-base, 5 off-base) were instrumented with 2 tri-axial accelerometers (XL) and a Sensewear armband (SW) with an internal accelerometer (SWXL). The XL were placed on the right ankle and right hip with the SW placed on the left triceps. Data was recorded for a 26 hour period during which the subjects kept a written record of their activity. Total estimated energy expenditure (tEEE), Seff and Sdur were calculated for each sensor during the 24 hour period. Sleep periods were verified for each subject using a written activity log. Results: Group: Based on the placement location of the sensors (ankle; waist; triceps) significant differences were observed for tEEE (1093.9kcal ± 329.8kcal; 502kcal ± 211.5 kcal; 2371.1kcal ± 838.2kcal , p<0.01). Sleep indices calculated from the SW were seen to be significantly different to the XL data, but not between the XL units themselves (triceps vs. ankle; waist): Sef (72.8% ± 18.5% vs. 96.3% ± 2.6%; 97.3% ± 1.9%, p<0.01) and Sdur ( 257.9mins ± 80.1mins vs. 371.3mins ± 49.0mins; 379.6mins ± 53.9mins, p<0.01). Home vs Base: Significant differences were seen for tEEE for the SW (1907.0kcal ± 397.3kcal vs. 2835.2kcal ± 940.4kcal, p<0.01) and SWXL (193.8kcal ± 63.2kcal vs. 893.2kcal ± 564.2kcal, p<0.01). Similarly a significant difference was observed for Seff (231.4mins ± 82.1mins; vs. 284.4mins ± 77mins, p<0.01) on the SW. Conclusion: The location of the sensor utilised to measure PA and sleep indices in SARC members appears to play a vital role in determining the accuracy of measurement. The SW recorded significant differences in PA levels and Sdur between SARC on-base and off-base. Further research is required to determine if this holds true for a larger sample size

Suffering in silence: children and unreported crime

This report presents the findings of a Scoping Inquiry into the hidden victimisation of children and young people, undertaken on behalf of the All Party Parliamentary Group (APPG) for Victims and Witnesses of Crime. The Inquiry was commissioned in response to findings from the most recent Crime Survey for England and Wales which indicates that less than one-fifth of children and young people who experience theft or violent crime report this to the police. The charity Victim Support, who provides the secretariat to the APPG, undertook research for the Inquiry in partnership with the University of Bedfordshire. Evidence was gathered in four ways: • a short review of existing literature; • an analysis of relevant data sources including the Crime Survey for England and Wales; • a rapid call for evidence from charities, service providers, statutory bodies and campaigners; and • three focus groups with children and young people

Assessment of Physical Activity in Search and Rescue Operations Using Accelerometer Based Technologies.

Helicopter search and rescue crews (SARC) operate on a 24 hour shift with crew members either sleeping on-base or at home depending on their proximity to the base. This may lead to possible variations in the level of physical activity (PA) that occurs between members of the crew. Aim: To investigate the levels of PA of members of the SARC during a 24 hour on-call shift using several novel sensing technologies. Method: Ten members of the Dublin SARC were instrumented with 2 tri-axial accelerometers (GT3X+), a Sensewear armband (SW) with an internal accelerometer (SWXL) and a Sensecam with an internal accelerometer. Data was recorded for a 26 hour period during which the subjects kept a written record of their activity. Sensors were kept on during all operations, the Sensecam was the only sensor removed while sleeping. Results: Within Group: Significant differences were observed for PA (p<0.01) due to the location of the sensors on the subject. Between Home and Base: Significant differences were seen for PA on the SW and SWXL (p<0.01). Conclusion: The location and type of sensor utilised in SARC operations appears to play a role in measurement of PA. The SW recorded significant differences in PA between SARC on-base and off-base, however the GT3X+ and SWXL were no different. Further research is required to align data from the Sensecam with the sensors used in this study to determine if it is possible to measure PA in this population with the Sensecam accelerometer data while also adding visual contextual data

A comparison of the aerobic energy demands of two commercially available cycle ergometers in trained cyclists

The purpose of this study was to compare the energy demands of two cycling ergometers, (Velotron Dynafit Pro and Monark 834E) commonly used in the physiological monitoring of elite athletes. Eight trained male cyclists with a minimum 2 years training and racing experience participated in the study. Each subject completed an exercise trial involving a maximal incremental test. Testing was performed in a random order on either the Velotron or Monark cycle ergometer at the same time of day with no more than 14 days between each testing session. Subjects were requested to maintain their normal training and nutritional practices during the course of the study but to refrain from any intensive training 48 hours prior to each testing session. During the incremental testing significant differences for power output (PO), heart rate (HR), and oxygen uptake (VO2) were found at both at fixed blood lactate (BL) reference points of; 2.5mmol l-1 (REF2.5mM) and at 4mmol.l-1 (REF4mM). Overall the Velotron appeared to provide a more specific measure of cycling performance with significantly lower energy demands at fixed submaximal exercise intensities being observed as well as a significantly greater peak power output and time to exhaustion being attained, which may reflect the specific cycling position adopted. Further research is required to compare the findings of this study with actual cycling performance