Positive regional species-people correlations: A sampling artefact or a key issue for sustainable development?

Many studies are documenting positive large-scale species– people correlations (Luck, 2007; Schuldt & Assmann, 2010). The issue is scale dependent: the local association of species richness and people is in many cases a negative one (Pautasso, 2007; Pecher et al., 2010). This biogeographical pattern is thus important for conservation. If species-rich regions are also densely populated, preserving biodiversity becomes more difficult, ceteris paribus, than if species-rich regions were sparsely populated. At the same time, positive, regional species–people correlations are an opportunity for the biodiversity education of the majority of the human population and underline the importance of conservation in human-modified landscapes (e.g. Sheil & Meijaard, 2010; Ward, 2010).

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin.

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.

A Framework of Issues in Large Process Modelling Projects

As process management projects have increased in size due to globalised and company-wide initiatives, a corresponding growth in the size of process modeling projects can be observed. Despite advances in languages, tools and methodologies, several aspects of these projects have been largely ignored by the academic community. This paper makes a first contribution to a potential research agenda in this field by defining the characteristics of large-scale process modeling projects and proposing a framework of related issues. These issues are derived from a semi -structured interview and six focus groups conducted in Australia, Germany and the USA with enterprise and modeling software vendors and customers. The focus groups confirm the existence of unresolved problems in business process modeling projects. The outcomes provide a research agenda which directs researchers into further studies in global process management, process model decomposition and the overall governance of process modeling projects. It is expected that this research agenda will provide guidance to researchers and practitioners by focusing on areas of high theoretical and practical relevance.

Concurrent multi-scale modeling of civil infrastructures for analyses on structural deterioration—Part I : Modeling methodology and strategy

This paper aims to develop the methodology and strategy for concurrent finite element modeling of civil infrastructures at the different scale levels for the purposes of analyses of structural deteriorating. The modeling strategy and method were investigated to develop the concurrent multi-scale model of structural behavior (CMSM-of-SB) in which the global structural behavior and nonlinear damage features of local details in a large complicated structure could be concurrently analyzed in order to meet the needs of structural-state evaluation as well as structural deteriorating. In the proposed method, the “large-scale” modeling is adopted for the global structure with linear responses between stress and strain and the “small-scale” modeling is available for nonlinear damage analyses of the local welded details. A longitudinal truss in steel bridge decks was selected as a case to study how a CMSM-of-SB was developed. The reduced-scale specimen of the longitudinal truss was studied in the laboratory to measure its dynamic and static behavior in global truss and local welded details, while the multi-scale models using constraint equations and substructuring were developed for numerical simulation. The comparison of dynamic and static response between the calculated results by different models indicated that the proposed multi-scale model was found to be the most efficient and accurate. The verification of the model with results from the tested truss under the specific loading showed that, responses at the material scale in the vicinity of local details as well as structural global behaviors could be obtained and fit well with the measured results. The proposed concurrent multi-scale modeling strategy and implementation procedures were applied to Runyang cable-stayed bridge (RYCB) and the CMSM-of-SB of the bridge deck system was accordingly constructed as a practical application.

Towards improvement of autonomous glider navigation accuracy through the use of regional ocean models

Autonomous underwater gliders are robust and widely-used ocean sampling platforms that are characterized by their endurance, and are one of the best approaches to gather subsurface data at the appropriate spatial resolution to advance our knowledge of the ocean environment. Gliders generally do not employ sophisticated sensors for underwater localization, but instead dead-reckon between set waypoints. Thus, these vehicles are subject to large positional errors between prescribed and actual surfacing locations. Here, we investigate the implementation of a large-scale, regional ocean model into the trajectory design for autonomous gliders to improve their navigational accuracy. We compute the dead-reckoning error for our Slocum gliders, and compare this to the average positional error recorded from multiple deployments conducted over the past year. We then compare trajectory plans computed on-board the vehicle during recent deployments to our prediction-based trajectory plans for 140 surfacing occurrences.

Autonomous underwater vehicle trajectory design coupled with predictive ocean models : a case study

Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

Large-Eddy Simulation of physiological pulsatile non-newtonian flow in a channel with double constriction

Physiological pulsatile flow in a 3D model of arterial double stenosis, using the modified Power-law blood viscosity model, is investigated by applying Large Eddy Simulation (LES) technique. The computational domain has been chosen is a simple channel with biological type stenoses. The physiological pulsation is generated at the inlet of the model using the first four harmonics of the Fourier series of the physiological pressure pulse. In LES, a top-hat spatial grid-filter is applied to the Navier-Stokes equations of motion to separate the large scale flows from the subgrid scale (SGS). The large scale flows are then resolved fully while the unresolved SGS motions are modelled using the localized dynamic model. The flow Reynolds numbers which are typical of those found in human large artery are chosen in the present work. Transitions to turbulent of the pulsatile non-Newtonian along with Newtonian flow in the post stenosis are examined through the mean velocity, wall shear stress, mean streamlines as well as turbulent kinetic energy and explained physically along with the relevant medical concerns.

Evaluating automatic road detection across a large aerial imagery collection

The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we present a public database and evaluation protocol for the evaluation of road extraction algorithms, and propose an improved automatic seed finding technique to initialise road extraction, based on a combination of geometric and colour features.

Optimisation of Banana streak virus (BSV) diagnostic assays

Bananas are one of the world�fs most important crops, serving as a staple food and an important source of income for millions of people in the subtropics. Pests and diseases are a major constraint to banana production. To prevent the spread of pests and disease, farmers are encouraged to use disease�] and insect�]free planting material obtained by micropropagation. This option, however, does not always exclude viruses and concern remains on the quality of planting material. Therefore, there is a demand for effective and reliable virus indexing procedures for tissue culture (TC) material. Reliable diagnostic tests are currently available for all of the economically important viruses of bananas with the exception of Banana streak viruses (BSV, Caulimoviridae, Badnavirus). Development of a reliable diagnostic test for BSV is complicated by the significant serological and genetic variation reported for BSV isolates, and the presence of endogenous BSV (eBSV). Current PCR�] and serological�]based diagnostic methods for BSV may not detect all species of BSV, and PCR�]based methods may give false positives because of the presence of eBSV. Rolling circle amplification (RCA) has been reported as a technique to detect BSV which can also discriminate between episomal and endogenous BSV sequences. However, the method is too expensive for large scale screening of samples in developing countries, and little information is available regarding its sensitivity. Therefore the development of reliable PCR�]based assays is still considered the most appropriate option for large scale screening of banana plants for BSV. This MSc project aimed to refine and optimise the protocols for BSV detection, with a particular focus on developing reliable PCR�]based diagnostics Initially, the appropriateness and reliability of PCR and RCA as diagnostic tests for BSV detection were assessed by testing 45 field samples of banana collected from nine districts in the Eastern region of Uganda in February 2010. This research was also aimed at investigating the diversity of BSV in eastern Uganda, identifying the BSV species present and characterising any new BSV species. Out of the 45 samples tested, 38 and 40 samples were considered positive by PCR and RCA, respectively. Six different species of BSV, namely Banana streak IM virus (BSIMV), Banana streak MY virus (BSMYV), Banana streak OL virus (BSOLV), Banana streak UA virus (BSUAV), Banana streak UL virus (BSULV), Banana streak UM virus (BSUMV), were detected by PCR and confirmed by RCA and sequencing. No new species were detected, but this was the first report of BSMYV in Uganda. Although RCA was demonstrated to be suitable for broad�]range detection of BSV, it proved time�]consuming and laborious for identification in field samples. Due to the disadvantages associated with RCA, attempts were made to develop a reliable PCR�]based assay for the specific detection of episomal BSOLV, Banana streak GF virus (BSGFV), BSMYV and BSIMV. For BSOLV and BSGFV, the integrated sequences exist in rearranged, repeated and partially inverted portions at their site of integration. Therefore, for these two viruses, primers sets were designed by mapping previously published sequences of their endogenous counterparts onto published sequences of the episomal genomes. For BSOLV, two primer sets were designed while, for BSGFV, a single primer set was designed. The episomalspecificity of these primer sets was assessed by testing 106 plant samples collected during surveys in Kenya and Uganda, and 33 leaf samples from a wide range of banana cultivars maintained in TC at the Maroochy Research Station of the Department of Employment, Economic Development and Innovation (DEEDI), Queensland. All of these samples had previously been tested for episomal BSV by RCA and for both BSOLV and BSGFV by PCR using published primer sets. The outcome from these analyses was that the newly designed primer sets for BSOLV and BSGFV were able to distinguish between episomal BSV and eBSV in most cultivars with some B�]genome component. In some samples, however, amplification was observed using the putative episomal�]specific primer sets where episomal BSV was not identified using RCA. This may reflect a difference in the sensitivity of PCR compared to RCA, or possibly the presence of an eBSV sequence of different conformation. Since the sequences of the respective eBSV for BSMYV and BSIMV in the M. balbisiana genome are not available, a series of random primer combinations were tested in an attempt to find potential episomal�]specific primer sets for BSMYV and BSIMV. Of an initial 20 primer combinations screened for BSMYV detection on a small number of control samples, 11 primers sets appeared to be episomal�]specific. However, subsequent testing of two of these primer combinations on a larger number of control samples resulted in some inconsistent results which will require further investigation. Testing of the 25 primer combinations for episomal�]specific detection of BSIMV on a number of control samples showed that none were able to discriminate between episomal and endogenous BSIMV. The final component of this research project was the development of an infectious clone of a BSV endemic in Australia, namely BSMYV. This was considered important to enable the generation of large amounts of diseased plant material needed for further research. A terminally redundant fragment (.1.3 �~ BSMYV genome) was cloned and transformed into Agrobacterium tumefaciens strain AGL1, and used to inoculate 12 healthy banana plants of the cultivars Cavendish (Williams) by three different methods. At 12 weeks post�]inoculation, (i) four of the five banana plants inoculated by corm injection showed characteristic BSV symptoms while the remaining plant was wilting/dying, (ii) three of the five banana plants inoculated by needle�]pricking of the stem showed BSV symptoms, one plant was symptomless while the remaining had died and (iii) both banana plants inoculated by leaf infiltration were symptomless. When banana leaf samples were tested for BSMYV by PCR and RCA, BSMYV was confirmed in all banana plants showing symptoms including those were wilting and/or dying. The results from this research have provided several avenues for further research. By completely sequencing all variants of eBSOLV and eBSGFV and fully sequencing the eBSIMV and eBSMYV regions, episomal BSV�]specific primer sets for all eBSVs could potentially be designed that could avoid all integrants of that particular BSV species. Furthermore, the development of an infectious BSV clone will enable large numbers of BSVinfected plants to be generated for the further testing of the sensitivity of RCA compared to other more established assays such as PCR. The development of infectious clones also opens the possibility for virus induced gene silencing studies in banana.

Escalation of conflict in large private family businesses

This study investigates escalation of intra-familial conflicts in family top management teams. Using a Critical Incident Technique approach, this study uses interviews to collect data from 23 family and non-family individuals and groups within six large-scale privately-held family businesses in Indonesia. The study develops a theoretical model to explain why family business conflicts escalate and become destructive. An inductive content analysis found that the use of a dominating strategy by both parties in dealing with conflict, the expression of negative emotions, and the involvement of non-family employees are more likely to cause escalation. This study contributes to the theory of family business conflict to help family business more satisfying and productive.

Cross-layer design and optimization for wireless networked control systems

Wireless networked control systems (WNCSs) have been widely used in the areas of manufacturing and industrial processing over the last few years. They provide real-time control with a unique characteristic: periodic traffic. These systems have a time-critical requirement. Due to current wireless mechanisms, the WNCS performance suffers from long time-varying delays, packet dropout, and inefficient channel utilization. Current wirelessly networked applications like WNCSs are designed upon the layered architecture basis. The features of this layered architecture constrain the performance of these demanding applications. Numerous efforts have attempted to use cross-layer design (CLD) approaches to improve the performance of various networked applications. However, the existing research rarely considers large-scale networks and congestion network conditions in WNCSs. In addition, there is a lack of discussions on how to apply CLD approaches in WNCSs. This thesis proposes a cross-layer design methodology to address the issues of periodic traffic timeliness, as well as to promote the efficiency of channel utilization in WNCSs. The design of the proposed CLD is highlighted by the measurement of the underlying network condition, the classification of the network state, and the adjustment of sampling period between sensors and controllers. This period adjustment is able to maintain the minimally allowable sampling period, and also maximize the control performance. Extensive simulations are conducted using the network simulator NS-2 to evaluate the performance of the proposed CLD. The comparative studies involve two aspects of communications, with and without using the proposed CLD, respectively. The results show that the proposed CLD is capable of fulfilling the timeliness requirement under congested network conditions, and is also able to improve the channel utilization efficiency and the proportion of effective data in WNCSs.

Robots for environmental monitoring : significant advancements and applications

Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.

Construct design for efficient, effective and high-throughput gene silencing in plants

Post-transcriptional silencing of plant genes using anti-sense or co-suppression constructs usually results in only a modest proportion of silenced individuals. Recent work has demonstrated the potential for constructs encoding self-complementary 'hairpin' RNA (hpRNA) to efficiently silence genes. In this study we examine design rules for efficient gene silencing, in terms of both the proportion of independent transgenic plants showing silencing, and the degree of silencing. Using hpRNA constructs containing sense/anti-sense arms ranging from 98 to 853 nt gave efficient silencing in a wide range of plant species, and inclusion of an intron in these constructs had a consistently enhancing effect. Intron-containing constructs (ihpRNA) generally gave 90-100% of independent transgenic plants showing silencing. The degree of silencing with these constructs was much greater than that obtained using either co-suppression or anti-sense constructs. We have made a generic vector, pHANNIBAL, that allows a simple, single PCR product from a gene of interest to be easily converted into a highly effective ihpRNA silencing construct. We have also created a high-throughput vector, pHELLSGATE, that should facilitate the cloning of gene libraries or large numbers of defined genes, such as those in EST collections, using an in vitro recombinase system. This system may facilitate the large-scale determination and discovery of plant gene functions in the same way as RNAi is being used to examine gene function in Caenorhabditis elegans.

A discussion of “Estimating the historical and future probabilities of large terrorist events'' by Aaron Clauset and Ryan Woodard

The terrorist attacks in the United States on September 11, 2001 appeared to be a harbinger of increased terrorism and violence in the 21st century, bringing terrorism and political violence to the forefront of public discussion. Questions about these events abound, and “Estimating the Historical and Future Probabilities of Large Scale Terrorist Event” [Clauset and Woodard (2013)] asks specifically, “how rare are large scale terrorist events?” and, in general, encourages discussion on the role of quantitative methods in terrorism research and policy and decision-making. Answering the primary question raises two challenges. The first is identify- ing terrorist events. The second is finding a simple yet robust model for rare events that has good explanatory and predictive capabilities. The challenges of identifying terrorist events is acknowledged and addressed by reviewing and using data from two well-known and reputable sources: the Memorial Institute for the Prevention of Terrorism-RAND database (MIPT-RAND) [Memorial Institute for the Prevention of Terrorism] and the Global Terror- ism Database (GTD) [National Consortium for the Study of Terrorism and Responses to Terrorism (START) (2012), LaFree and Dugan (2007)]. Clauset and Woodard (2013) provide a detailed discussion of the limitations of the data and the models used, in the context of the larger issues surrounding terrorism and policy.