On the detection of dynamic responses in a drought-perturbed tropical rainforest in Borneo

The dynamics of aseasonal lowland dipterocarp forest in Borneo is influenced by perturbation from droughts. These events might be increasing in frequency and intensity in the future. This paper describes drought-affected dynamics between 1986 and 2001 in Sabah, Malaysia, and considers how it is possible, reliably and accurately, to measure both coarse- and fine-scale responses of the forest. Some fundamental concerns about methodology and data analysis emerge. In two plots forming 8 ha, mortality, recruitment, and stem growth rates of trees ≥10 cm gbh (girth at breast height) were measured in a ‘pre-drought’ period (1986–1996), and in a period (1996–2001) including the 1997–1998 ENSO-drought. For 2.56 ha of subplots, mortality and growth rates of small trees (10–<50 cm gbh) were found also for two sub-periods (1996–1999, 1999–2001). A total of c. 19 K trees were recorded. Mortality rate increased by 25% while both recruitment and relative growth rates increased by 12% for all trees at the coarse scale. For small trees, at the fine scale, mortality increased by 6% and 9% from pre-drought to drought and on to ‘post-drought’ sub-periods. Relative growth rates correspondingly decreased by 38% and increased by 98%. Tree size and topography interacted in a complex manner with between-plot differences. The forest appears to have been sustained by off-setting elevated tree mortality by highly resilient stem growth. This last is seen as the key integrating tree variable which links the external driver (drought causing water stress) and population dynamics recorded as mortality and recruitment. Suitably sound measurements of stem girth, leading to valid growth rates, are needed to understand and model tree dynamic responses to perturbations. The proportion of sound data, however, is in part determined by the drought itself.

Model-Centric, Context-Aware Software Adaptation

Software must be constantly adapted to changing requirements. The time scale, abstraction level and granularity of adaptations may vary from short-term, fine-grained adaptation to long-term, coarse-grained evolution. Fine-grained, dynamic and context-dependent adaptations can be particularly difficult to realize in long-lived, large-scale software systems. We argue that, in order to effectively and efficiently deploy such changes, adaptive applications must be built on an infrastructure that is not just model-driven, but is both model-centric and context-aware. Specifically, this means that high-level, causally-connected models of the application and the software infrastructure itself should be available at run-time, and that changes may need to be scoped to the run-time execution context. We first review the dimensions of software adaptation and evolution, and then we show how model-centric design can address the adaptation needs of a variety of applications that span these dimensions. We demonstrate through concrete examples how model-centric and context-aware designs work at the level of application interface, programming language and runtime. We then propose a research agenda for a model-centric development environment that supports dynamic software adaptation and evolution.

Augmenting Static Source Views in IDEs with Dynamic Metrics

Mainstream IDEs such as Eclipse support developers in managing software projects mainly by offering static views of the source code. Such a static perspective neglects any information about runtime behavior. However, object-oriented programs heavily rely on polymorphism and late-binding, which makes them difficult to understand just based on their static structure. Developers thus resort to debuggers or profilers to study the system's dynamics. However, the information provided by these tools is volatile and hence cannot be exploited to ease the navigation of the source space. In this paper we present an approach to augment the static source perspective with dynamic metrics such as precise runtime type information, or memory and object allocation statistics. Dynamic metrics can leverage the understanding for the behavior and structure of a system. We rely on dynamic data gathering based on aspects to analyze running Java systems. By solving concrete use cases we illustrate how dynamic metrics directly available in the IDE are useful. We also comprehensively report on the efficiency of our approach to gather dynamic metrics.

Tackling Software Navigation Issues of the Smalltalk IDE

The IDE used in most Smalltalk dialects such as Pharo, Squeak or Cincom Smalltalk did not evolve significantly over the last years, if not to say decades. For other languages, for instance Java, the available IDEs made tremendous progress as Eclipse or NetBeans illustrate. While the Smalltalk IDE served as an exemplar for many years, other IDEs caught up or even overtook the erstwhile leader in terms of feature-richness, usability, or code navigation facilities. In this paper we first analyze the difficulty of software navigation in the Smalltalk IDE and second illustrate with concrete examples the features we added to the Smalltalk IDE to fill the gap to modern IDEs and to provide novel, improved means to navigate source space. We show that thanks to the agility and dynamics of Smalltalk, we are able to extend and enhance with reasonable effort the Smalltalk IDE to better support software navigation, program comprehension, and software maintenance in general. One such support is the integration of dynamic information into the static source views we are familiar with. Other means include easing the access to static information (for instance by better arranging important packages) or helping developers re-locating artifacts of interest (for example with a categorization system such as smart groups).

Dynamic Optimization of SLA-Based Services Scaling Rules

Current advanced cloud infrastructure management solutions allow scheduling actions for dynamically changing the number of running virtual machines (VMs). This approach, however, does not guarantee that the scheduled number of VMs will properly handle the actual user generated workload, especially if the user utilization patterns will change. We propose using a dynamically generated scaling model for the VMs containing the services of the distributed applications, which is able to react to the variations in the number of application users. We answer the following question: How to dynamically decide how many services of each type are needed in order to handle a larger workload within the same time constraints? We describe a mechanism for dynamically composing the SLAs for controlling the scaling of distributed services by combining data analysis mechanisms with application benchmarking using multiple VM configurations. Based on processing of multiple application benchmarks generated data sets we discover a set of service monitoring metrics able to predict critical Service Level Agreement (SLA) parameters. By combining this set of predictor metrics with a heuristic for selecting the appropriate scaling-out paths for the services of distributed applications, we show how SLA scaling rules can be inferred and then used for controlling the runtime scale-in and scale-out of distributed services. We validate our architecture and models by performing scaling experiments with a distributed application representative for the enterprise class of information systems. We show how dynamically generated SLAs can be successfully used for controlling the management of distributed services scaling.

Knowledge Transfer Processes in the IS Offshore Outsourcing Transition: A Conceptual Model

Despite promising cost saving potential, many offshore software projects fail to realize the expected benefits. A frequent source of failure lies in the insufficient transfer of knowledge during the transition phase. Former literature has reported cases where some domains of knowledge were successfully transferred to vendor personnel whereas others were not. There is further evidence that the actual knowledge transfer processes often vary from case to case. This raises the question whether there is a systematic relationship between the chosen knowledge transfer process and know-ledge transfer success. This paper introduces a dynamic perspective that distinguishes different types of knowledge transfer processes explaining under which circumstances which type is deemed most appropriate to successfully transfer knowledge. Our paper draws on knowledge transfer literature, the Model of Work-Based Learning and theories from cognitive psychology to show how characteristics of know-ledge and the absorptive capacity of knowledge recipients fit particular knowledge transfer processes. The knowledge transfer processes are conceptualized as combinations of generic knowledge transfer activities. This results in six gestalts of know-ledge transfer processes, each representing a fit between the characteristics of the knowledge process and the characteristics of the knowledge to be transferred and the absorptive capacity of the knowledge recipient.

Complex visual hallucinations and attentional performance in eye disease and dementia: a test of the Perception and Attention Deficit model

OBJECTIVE This study aimed to test the prediction from the Perception and Attention Deficit model of complex visual hallucinations (CVH) that impairments in visual attention and perception are key risk factors for complex hallucinations in eye disease and dementia. METHODS Two studies ran concurrently to investigate the relationship between CVH and impairments in perception (picture naming using the Graded Naming Test) and attention (Stroop task plus a novel Imagery task). The studies were in two populations-older patients with dementia (n = 28) and older people with eye disease (n = 50) with a shared control group (n = 37). The same methodology was used in both studies, and the North East Visual Hallucinations Inventory was used to identify CVH. RESULTS A reliable relationship was found for older patients with dementia between impaired perceptual and attentional performance and CVH. A reliable relationship was not found in the population of people with eye disease. CONCLUSIONS The results add to previous research that object perception and attentional deficits are associated with CVH in dementia, but that risk factors for CVH in eye disease are inconsistent, suggesting that dynamic rather than static impairments in attentional processes may be key in this population.

ICOMF: Towards a Multi-cloud Ecosystem for Dynamic Resource Composition and Scaling

Modern cloud-based applications and infrastructures may include resources and services (components) from multiple cloud providers, are heterogeneous by nature and require adjustment, composition and integration. The specific application requirements can be met with difficulty by the current static predefined cloud integration architectures and models. In this paper, we propose the Intercloud Operations and Management Framework (ICOMF) as part of the more general Intercloud Architecture Framework (ICAF) that provides a basis for building and operating a dynamically manageable multi-provider cloud ecosystem. The proposed ICOMF enables dynamic resource composition and decomposition, with a main focus on translating business models and objectives to cloud services ensembles. Our model is user-centric and focuses on the specific application execution requirements, by leveraging incubating virtualization techniques. From a cloud provider perspective, the ecosystem provides more insight into how to best customize the offerings of virtualized resources.

Dynamic SLA management with forecasting using multi-objective optimization

Cost-efficient operation while satisfying performance and availability guarantees in Service Level Agreements (SLAs) is a challenge for Cloud Computing, as these are potentially conflicting objectives. We present a framework for SLA management based on multi-objective optimization. The framework features a forecasting model for determining the best virtual machine-to-host allocation given the need to minimize SLA violations, energy consumption and resource wasting. A comprehensive SLA management solution is proposed that uses event processing for monitoring and enables dynamic provisioning of virtual machines onto the physical infrastructure. We validated our implementation against serveral standard heuristics and were able to show that our approach is significantly better.

A Process Model of Complementarity and Substitution of Contractual and Relational Governance in IS Outsourcing

This paper develops a process model of how and why complementarity and substitution form over time between contractual and relational governance in the context of information systems outsourcing. Our analysis identifies four distinct process patterns that explain this formation as the outcome of interaction processes between key elements of both contractual and relational governance. These patterns unveil the dynamic nature of complementarity and substitution. In particular, we show that the relationship between contractual and relational governance oscillates between complementarity and substitution. Those oscillations are triggered mainly by three types of contextual events (goal fuzziness, goal conflict, and goal misalignment). Surprisingly, substitution of informal control did not occur as an immediate reaction to external events but emerged as a consequence of preceding complementarity. Thus, our study challenges the prevailing view of an either/or dichotomy of complementarity and substitution by showing that they are causally connected over time.

Precise Orbit Determination of Low Earth Satellites at AIUB using GPS and SLR data

An ever increasing number of low Earth orbiting (LEO) satellites is, or will be, equipped with retro-reflectors for Satellite Laser Ranging (SLR) and on-board receivers to collect observations from Global Navigation Satellite Systems (GNSS) such as the Global Positioning Sys- tem (GPS) and the Russian GLONASS and the European Galileo systems in the future. At the Astronomical Insti- tute of the University of Bern (AIUB) LEO precise or- bit determination (POD) using either GPS or SLR data is performed for a wide range of applications for satellites at different altitudes. For this purpose the classical numeri- cal integration techniques, as also used for dynamic orbit determination of satellites at high altitudes, are extended by pseudo-stochastic orbit modeling techniques to effi- ciently cope with potential force model deficiencies for satellites at low altitudes. Accuracies of better than 2 cm may be achieved by pseudo-stochastic orbit modeling for satellites at very low altitudes such as for the GPS-based POD of the Gravity field and steady-state Ocean Circula- tion Explorer (GOCE).

Statistical model-based segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs.

PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

A model-data comparison of Holocene timberline changes in the Swiss Alps reveals past and future drivers of mountain forest dynamics

Mountain vegetation is strongly affected by temperature and is expected to shift upwards with climate change. Dynamic vegetation models are often used to assess the impact of climate on vegetation and model output can be compared with paleobotanical data as a reality check. Recent paleoecological studies have revealed regional variation in the upward shift of timberlines in the Northern and Central European Alps in response to rapid warming at the Younger Dryas/Preboreal transition ca. 11700years ago, probably caused by a climatic gradient across the Alps. This contrasts with previous studies that successfully simulated the early Holocene afforestation in the (warmer) Central Alps with a chironomid-inferred temperature reconstruction from the (colder) Northern Alps. We use LandClim, a dynamic landscape vegetation model to simulate mountain forests under different temperature, soil and precipitation scenarios around Iffigsee (2065m a.s.l.) a lake in the Northwestern Swiss Alps, and compare the model output with the paleobotanical records. The model clearly overestimates the upward shift of timberline in a climate scenario that applies chironomid-inferred July-temperature anomalies to all months. However, forest establishment at 9800 cal. BP at Iffigsee is successfully simulated with lower moisture availability and monthly temperatures corrected for stronger seasonality during the early Holocene. The model-data comparison reveals a contraction in the realized niche of Abies alba due to the prominent role of anthropogenic disturbance after ca. 5000 cal. BP, which has important implications for species distribution models (SDMs) that rely on equilibrium with climate and niche stability. Under future climate projections, LandClim indicates a rapid upward shift of mountain vegetation belts by ca. 500m and treeline positions of ca. 2500m a.s.l. by the end of this century. Resulting biodiversity losses in the alpine vegetation belt might be mitigated with low-impact pastoralism to preserve species-rich alpine meadows.

Dynamic high-resolution computer simulation of electrophoretic enantiomer separations with neutral cyclodextrins as chiral selectors.

GENTRANS, a comprehensive one-dimensional dynamic simulator for electrophoretic separations and transport, was extended for handling electrokinetic chiral separations with a neutral ligand. The code can be employed to study the 1:1 interaction of monovalent weak and strong acids and bases with a single monovalent weak or strong acid or base additive, including a neutral cyclodextrin, under real experimental conditions. It is a tool to investigate the dynamics of chiral separations and to provide insight into the buffer systems used in chiral capillary zone electrophoresis (CZE) and chiral isotachophoresis. Analyte stacking across conductivity and buffer additive gradients, changes of additive concentration, buffer component concentration, pH, and conductivity across migrating sample zones and peaks, and the formation and migration of system peaks can thereby be investigated in a hitherto inaccessible way. For model systems with charged weak bases and neutral modified β-cyclodextrins at acidic pH, for which complexation constants, ionic mobilities, and mobilities of selector-analyte complexes have been determined by CZE, simulated and experimentally determined electropherograms and isotachopherograms are shown to be in good agreement. Simulation data reveal that CZE separations of cationic enantiomers performed in phosphate buffers at low pH occur behind a fast cationic migrating system peak that has a small impact on the buffer composition under which enantiomeric separation takes place.