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1.  Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis 
Introduction:
Research and diagnosis in medicine and biology often require the assessment of a large amount of microscopy image data. Although on the one hand, digital pathology and new bioimaging technologies find their way into clinical practice and pharmaceutical research, some general methodological issues in automated image analysis are still open.
Methods:
In this study, we address the problem of fitting the parameters in a microscopy image segmentation pipeline. We propose to fit the parameters of the pipeline's modules with optimization algorithms, such as, genetic algorithms or coordinate descents, and show how visual exploration of the parameter space can help to identify sub-optimal parameter settings that need to be avoided.
Results:
This is of significant help in the design of our automatic parameter fitting framework, which enables us to tune the pipeline for large sets of micrographs.
Conclusion:
The underlying parameter spaces pose a challenge for manual as well as automated parameter optimization, as the parameter spaces can show several local performance maxima. Hence, optimization strategies that are not able to jump out of local performance maxima, like the hill climbing algorithm, often result in a local maximum.
doi:10.4103/2153-3539.109831
PMCID: PMC3678745  PMID: 23766941
Fluorescence; image processing; microscopy; parameter optimization; segmentation
2.  A bottom-up approach to estimating cost elements of REDD+ pilot projects in Tanzania 
Background
Several previous global REDD+ cost studies have been conducted, demonstrating that payments for maintaining forest carbon stocks have significant potential to be a cost-effective mechanism for climate change mitigation. These studies have mostly followed highly aggregated top-down approaches without estimating the full range of REDD+ costs elements, thus underestimating the actual costs of REDD+. Based on three REDD+ pilot projects in Tanzania, representing an area of 327,825 ha, this study explicitly adopts a bottom-up approach to data assessment. By estimating opportunity, implementation, transaction and institutional costs of REDD+ we develop a practical and replicable methodological framework to consistently assess REDD+ cost elements.
Results
Based on historical land use change patterns, current region-specific economic conditions and carbon stocks, project-specific opportunity costs ranged between US$ -7.8 and 28.8 tCOxxxx for deforestation and forest degradation drivers such as agriculture, fuel wood production, unsustainable timber extraction and pasture expansion. The mean opportunity costs for the three projects ranged between US$ 10.1 – 12.5 tCO2. Implementation costs comprised between 89% and 95% of total project costs (excluding opportunity costs) ranging between US$ 4.5 - 12.2 tCO2 for a period of 30 years. Transaction costs for measurement, reporting, verification (MRV), and other carbon market related compliance costs comprised a minor share, between US$ 0.21 - 1.46 tCO2. Similarly, the institutional costs comprised around 1% of total REDD+ costs in a range of US$ 0.06 – 0.11 tCO2.
Conclusions
The use of bottom-up approaches to estimate REDD+ economics by considering regional variations in economic conditions and carbon stocks has been shown to be an appropriate approach to provide policy and decision-makers robust economic information on REDD+. The assessment of opportunity costs is a crucial first step to provide information on the economic baseline situation of deforestation and forest degradation agents and on the economic incentives required to halt unsustainable land use. Since performance based REDD+ carbon payments decrease over time (as deforestation rates drop and for each saved ha of forest payments occur once), investments in REDD+ implementation have a crucial role in triggering sustainable land use systems by investing in the underlying assets and the generation of sustainable revenue streams to compensate for opportunity costs of land use change. With a potential increase in the land value due to effective REDD+ investments, expenditures in an enabling institutional environment for REDD+ policies are crucial to avoid higher deforestation pressure on natural forests.
doi:10.1186/1750-0680-7-9
PMCID: PMC3441278  PMID: 22877419
REDD+ economics; REDD+ cost elements; Opportunity costs; REDD+ implementation costs; Transaction costs; Institutional costs
3.  Quantitative multichannel NC-AFM data analysis of graphene growth on SiC(0001) 
Summary
Noncontact atomic force microscopy provides access to several complementary signals, such as topography, damping, and contact potential. The traditional presentation of such data sets in adjacent figures or in colour-coded pseudo-three-dimensional plots gives only a qualitative impression. We introduce two-dimensional histograms for the representation of multichannel NC-AFM data sets in a quantitative fashion. Presentation and analysis are exemplified for topography and contact-potential data for graphene grown epitaxially on 6H-SiC(0001), as recorded by Kelvin probe force microscopy in ultrahigh vacuum. Sample preparations by thermal decomposition in ultrahigh vacuum and in an argon atmosphere are compared and the respective growth mechanisms discussed.
doi:10.3762/bjnano.3.19
PMCID: PMC3304321  PMID: 22428109
FM-AFM; graphene; 6H-SiC(0001); KPFM; SPM
4.  Measurement of TLR-Induced Macrophage Spreading by Automated Image Analysis: Differential Role of Myd88 and MAPK in Early and Late Responses 
Sensing of infectious danger by toll-like receptors (TLRs) on macrophages causes not only a reprogramming of the transcriptome but also changes in the cytoskeleton important for cell spreading and motility. Since manual determination of cell contact areas from fluorescence micrographs is very time-consuming and prone to bias, we have developed and tested algorithms for automated measurement of macrophage spreading. The two-step method combines identification of cells by nuclear staining with DAPI and cell surface staining of the integrin CD11b. Automated image analysis correlated very well with manual annotation in resting macrophages and early after stimulation, whereas at later time points the automated cell segmentation algorithm and manual annotation showed slightly larger variation. The method was applied to investigate the impact of genetic or pharmacological inhibition of known TLR signaling components. Deficiency in the adapter protein Myd88 strongly reduced spreading activity at the late time points, but had no impact early after LPS-stimulation. A similar effect was observed upon pharmacological inhibition of MEK1, the kinase activating the mitogen-activated protein kinases (MAPK) ERK1/2, indicating that ERK1/2 mediates Myd88-dependent macrophages spreading. In contrast, macrophages lacking the MAPK p38 were impaired in the initial spreading response but responded normally 8–24 h after stimulation. The dichotomy of p38 and ERK1/2 MAPK effects on early and late macrophage spreading raises the question which of the respective substrate proteins mediate(s) cytoskeletal remodeling and spreading. The automated measurement of cell spreading described here increases the objectivity and greatly reduces the time required for such investigations and is therefore expected to facilitate larger throughput analysis of macrophage spreading, e.g., in siRNA knockdown screens.
doi:10.3389/fphys.2011.00071
PMCID: PMC3198511  PMID: 22028692
macrophage; spreading; TLR; image analysis

Results 1-4 (4)