Improving comfort levels in a traditional high altitude Nepali house

Humla Province is a remote mountainous region of northwest Nepal. The climate is harsh and the local people are extremely poor. Most people endure a subsistence culture, living in traditional housing. Energy for cooking and heating comes from fuelwood, supplies of which are diminishing. In order to improve the indoor environment and reduce fuelwood use, smokeless stoves are being introduced to replace the open fire in Humli homes. There is some concern, however, that comfort levels may not be as acceptable with these stoves. The aim of this research was therefore to investigate ways in which the comfort levels in traditional Humli housing might be improved using simple and low cost strategies. Temperature data was recorded in four rooms of a traditional Humli home over a 12-day period and used with fuelwood data to validate a TRNSYS simulation model of the house. This model was then used to evaluate the impact on comfort levels in the house of various energy conservation strategies using PMV and PPD indicators. As a single strategy, it was found that reducing infiltration of outside air was likely to be more effective than increasing the insulation level in the ceilings. The most successful strategy, however, was the creation of sunspaces at the entrances to the living rooms. This strategy increased average internal temperatures by 1.7 and 2.3 °C. In combination with increased insulation levels, the sunspaces reduced comfort dissatisfaction levels by over 50%.

A high altitude observation of the beautiful firetail Stagonopleura bella from East Gippsland, Victoria

There has been little research on the ecological requirements of the Beautiful Firetail Stagonopleura bella, and its habitat preferences are poorly understood. On mainland Australia, the Beautiful Firetail is generally considered to be a bird of coastal regions and the lowlands. This note reports an observation of Beautiful Firetails on the Great Dividing Range at a height of more than 1100 metres above sea level from an atypical habitat for mainland Australia. It appears that the observation may be the highest altitude at which this species has been recorded on the mainland.

Thermal evaluation of a greenhouse in a remote high altitude area of Nepal

Remote communities in the high altitude areas of Nepal suffer both chronic and acute malnutrition. This is due to a shortage of arable land and a harsh climate. For seven months of the year, the harvesting of fresh vegetables is almost impossible. Greenhouse technology, if appropriate for the location and its community, can extend the growing season considerably. Experience in the Ladakh region of India indicates that year-round cropping is possible in greenhouses in cold mountainous areas. A simple 50-m2 greenhouse has been constructed in Simikot, the main town of Humla, northwest Nepal. This paper describes the evaluation of the thermal performance of that greenhouse. Both measurement and simulation were used in the evaluation. Measurements during the winter of 2006-7 indicate that the existing design is capable of producing adequate growing conditions for some vegetable crops, but that improvements are required if crops like tomatoes are to be grown successfully. Options to improve the thermal performance of the greenhouse have been investigated by simulation. Improvements to the building envelope such as wall insulation, double-glazing and using a thermal screen were simulated with a validated TRNSYS model. The impact of the addition of nighttime heat from internal passive solar water collectors was also predicted. The simulations indicate that the passive solar water collectors would raise the average greenhouse air temperature by 2.5°C and the overnight air temperature would increase by 4.0°C. When used in combination, overnight temperatures are predicted to by almost 7°C higher.

Migrating swans profit from favourable changes in wind conditions at low altitude

Because energy reserves limit flight range, wind assistance may be of crucial importance for migratory birds. We tracked eight Bewick's swans Cygnus columbianus bewickii, using 95-g satellite transmitters with altimeters and activity sensors, during their spring migration from Denmark to northern Russia in 1996. During the 82 occasions where a swan's location was recorded in flight, average flight altitude was 165 m a.s.1. with a maximum of 759 m a.s.1., despite winds often being more favourable at higher altitudes. We also counted Bewick's swans departing from the Gulf of Finland and subsequently passing an observatory in the next major stop-over area 800 km further north in the White Sea, northern Russia, during the springs of 1994, 1995 and 1996. A comparison of these counts with wind data provided evidence for Bewick's swans using favourable changes in wind conditions to embark on migration. Changes in the numbers of birds arriving in the White Sea correlated best with favourable changes in winds in the Gulf of Finland 1 day earlier. Again, migratory volume showed a correlation with winds at low altitudes only, despite wind conditions for the swans being more favourable at high altitudes. We conclude that the relatively large Bewick's swan tends to gear its migration to wind conditions at low altitude only. We argue that Bewick's swans do not climb to high altitudes because of mechanical and physiological limitations with respect to the generation of power for flight and to avoid rapid dehydration.

Flight altitude of trans-Sahara migrants in autumn: a comparison of radar observations with predictions from meteorological conditions and water and energy balance models

Radar observations on the altitude of bird migration and altitudinal profiles of meteorological conditions over the Sahara desert are presented for the autumn migratory period. Migratory birds fly at an average altitude of 1016 m (a.s.l.) during the day and 571 m during the night. Weather data served to calculate flight range using two models: an energy model (EM) and an energy-and-water model (EWM). The EM assumes that fuel supply limits flight range whereas the EWM assumes that both fuel and water may limit flight range. Flight ranges estimated with the EM were generally longer than those with the EWM. This indicates that trans-Sahara migrants might have more problems balancing their water than their energy budget. However, if we assume fuel stores to consist of 70% instead of 100% fat (the remainder consisting of 9% protein and 21% water), predicted flight ranges of the EM and EWM largely overlap. Increased oxygen extraction, reduced flight costs, reduced exhaled air temperature, reduced cutaneous water loss and increased tolerance to water loss are potential physiological adaptations that would improve the water budget in migrants. Both the EM and EWM predict optimal flight altitudes in agreement with radar observations in autumn. Optimal flight altitudes are differently predicted by the EM and EWM for nocturnal spring migration. During spring, the EWM predicts moderately higher and the EM substantially higher flight altitudes than during autumn. EWM predictions are therefore in better agreement with radar observations on flight altitude of migrants over the Negev desert in spring than EM predictions.

Increased hypoxic dose after training at low altitude with 9h per night at 3000m normobaric hypoxia

This study examined effects of low altitude training and a live-high: train-low protocol (combining both natural and simulated modalities) on haemoglobin mass (Hbmass), maximum oxygen consumption (VO2max), time to exhaustion, and submaximal exercise measures. Eighteen elite-level race-walkers were assigned to one of two experimental groups; lowHH (low Hypobaric Hypoxia: continuous exposure to 1380 m for 21 consecutive days; n = 10) or a combined low altitude training and nightly Normobaric Hypoxia (lowHH+NHnight: living and training at 1380 m, plus 9 h.night-1 at a simulated altitude of 3000 m using hypoxic tents; n = 8). A control group (CON; n = 10) lived and trained at 600 m. Measurement of Hbmass, time to exhaustion and VO2max was performed before and after the training intervention. Paired samples t-tests were used to assess absolute and percentage change pre and post-test differences within groups, and differences between groups were assessed using a one-way ANOVA with least significant difference post-hoc testing. Statistical significance was tested at p < 0.05. There was a 3.7% increase in Hbmass in lowHH+NHnight compared with CON (p = 0.02). In comparison to baseline, Hbmass increased by 1.2% (±1.4%) in the lowHH group, 2.6% (±1.8%) in lowHH+NHnight, and there was a decrease of 0.9% (±4.9%) in CON. VO2max increased by ~4% within both experimental conditions but was not significantly greater than the 1% increase in CON. There was a ~9% difference in pre and post-intervention values in time to exhaustion after lowHH+NH-night (p = 0.03) and a ~8% pre to post-intervention difference (p = 0.006) after lowHH only. We recommend low altitude (1380 m) combined with sleeping in altitude tents (3000 m) as one effective alternative to traditional altitude training methods, which can improve Hbmass.

Spatial model for predicting the presence of cinnamon fungus (Phytophthora cinnamomi) in sclerophyll vegetation communities in south-eastern Australia

The pathogen Phytophthora cinnamomi causes extensive 'dieback' of Australian native vegetation. This study investigated the distribution of infection in an area of significant sclerophyll vegetation in Australia. It aimed to determine the relationship of infection to site variables and to develop a predictive model of infection. Site variables recorded at 50 study sites included aspect, slope, altitude, proximity to road and road characteristics, soil profile characteristics and vegetation attributes. Soil and plant tissues were assayed for the presence of the pathogen. A geographical information systyem (GIS) was employed to provide accurate estimations of spatial variables and develop a predictive model for the distribution of P. cinnamomi. The pathogen was isolated from 76% of the study sites. Of the 17 site variables initially investigated during the study a logistic regression model identified only two, elevation and sun-index, as significant in determining the probability of infection. The presence of P. cinnamomi infection was negatively associated with elevation and positively associated with sun-index. The model predicted that up to 74% of the study area (11 875 ha) had a high probability of being affected by P. cinnamomi. However, the present areas of infection were small, providing an opportunity for management to minimize spread into highly susceptible uninvaded areas.

Robust extended Kalman filter based technique for location management in PCS networks

Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using Robust Extended Kalman Filter as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.

Spatial prediction of rufous bristlebird habitat in a coastal heathland: a GIS-based approach

1. To develop a conservation management plan for a species, knowledge of its distribution and spatial arrangement of preferred habitat is essential. This is a difficult task, especially when the species of concern is in low   abundance. In south-western Victoria, Australia, populations of the rare rufous bristlebird Dasyornis broadbenti are threatened by fragmentation of suitable habitat. In order to improve the conservation status of this species, critical habitat requirements must be identified and a system of corridors must be established to link known populations. A predictive spatial model of rufous bristlebird habitat was developed in order to identify critical areas requiring preservation, such as corridors for dispersal.
2. Habitat models generated using generalized linear modelling techniques can assist in delineating the specific habitat requirements of a species. Coupled with geographic information system (GIS) technology, these models can be extrapolated to produce maps displaying the spatial configuration of suitable habitat.
3. Models were generated using logistic regression, with bristlebird presence or absence as the dependent variable and landscape variables, extracted from both GIS data layers and multispectral digital imagery, as the predictors. A multimodel inference approach based on Akaike’s information criterion was used and the resulting model was applied in a GIS to extrapolate predicted likelihood of occurrence across the entire area of concern. The predictive performance of the selected model was evaluated using the receiver operating characteristic (ROC) technique. A hierarchical partitioning protocol was used to identify the predictor variables most likely to influence variation in the dependent variable. Probability of species presence was used as an index of habitat suitability.
4. Negative associations between rufous bristlebird presence and  increasing elevation, 'distance to cree', 'distance to coast' and sun index were evident, suggesting a preference for areas relatively low in altitude, in close proximity to the coastal fringe and drainage lines, and receiving less direct sunlight. A positive association with increasing habitat complexity also suggested that this species prefers areas containing high vertical density of vegetation.
5. The predictive performance of the selected model was shown to be high (area under the curve 0·97), indicating a good fit of the model to the data. Hierarchical partitioning analysis showed that all the variables considered had significant  independent contributions towards explaining the variation in the dependent variable. The proportion of the total study area that was predicted as suitable habitat for the rufous bristlebird (using probability of occurrence at a ≥0·5 level ) was 16%.
6. Synthesis and applications. The spatial model clearly delineated areas predicted as highly suitable rufous bristlebird habitat, with evidence of potential corridors linking coastal and inland populations via gullies. Conservation of this species will depend on management actions that protect the critical habitats identified in the model. A multi-scale  approach to the modelling process is recommended whereby a spatially explicit model is first generated using landscape variables extracted from a GIS, and a second model at site level is developed using fine-scale habitat variables measured on the ground. Where there are constraints on the time and cost involved in measuring finer scale variables, the first step alone can be used for conservation planning.

Landscape characteristics associated with species richness and occurrence of small native mammals inhabiting a coastal heathland: a spatial modelling approach

In the coastal region of south-western Victoria, Australia, populations of native small mammal species are restricted to patches of suitable habitat in a highly fragmented landscape. The size and spatial arrangement of these patches is likely to influence both the occupancy and richness of species at a location. Geographic Information System (GIS)-based habitat models of the species richness of native small mammals, and individual species  occurrences, were developed to produce maps displaying the spatial  configuration of suitable habitat. Models were generated using either generalised linear Poisson regression (for species richness) or logistic regression (for species occurrences) with species richness or  presence/absence as the dependent variable and landscape variables, extracted from both GIS data layers and multi-spectral digital imagery, as the predictor variables. A multi-model inference approach based on the Akaike Information Criterion was used and the resulting model was applied in a GIS framework to extrapolate predicted richness/likelihood of occurrence across the entire area of the study. A negative association between species  richness and elevation, habitat complexity and sun index indicated that richness within the study area decreases with increasing altitude, vertical vegetation structure and exposure to solar radiation. Landform  characteristics were important (to varying degrees) in determining habitat occupancy for all of the species examined, while the influence of habitat complexity was important for only one of the species. Performance of all but one of the models generated using presence/absence data was high, as indicated by the area under the curve of a receiver-operating characteristic plot. The effective conservation of the small mammal species in the area of concern is likely to depend on management actions that promote the protection of the critical habitats identified in the models.

Mobility modelling and trajectory prediction for cellular networks with mobile base stations

This paper provides mobility estimation and prediction for a variant of GSM network which resembles an adhoc wireless mobile network where base stations and users are both mobile. We propose using Robust Extended Kalman Filter (REKF)as a location heading altitude estimator of mobile user for next node (mobile-base station)in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm can successfully track the mobile users with less system complexity as it requires either one or two closest mobile-basestation measurements. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.

Robust extended kalman filter applied to location tracking and trajectory prediction for PCS networks

Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using robust extended Kalman filter (REKF) as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model and more effective in comparison with the standard Kalman filter.

Location based power control for mobile devices in a cellular network

This paper provides location estimation based power control strategy for cellular radio systems via a location based interference management scheme. Our approach considers the carrier-to-interference as dependent on the transmitter and receiver separation distance and therefore an accurate estimation of the precise locations can provide the power critical mobile user to control the transition power accordingly. In this fully
distributed algorithms, we propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user’s closest mobile base station from the user’s location, heading and altitude. Our analysis demonstrates that this algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations and hence enable the user to transmit at the rate that is sufficient for the interference management. Our power control
algorithms based on this estimation converges to the desired power trajectory. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation.