Sub-irrigation of Petunia: benefits in dry summers

With the increasing frequency and magnitude of warmer days during the summer in the UK, bedding plants which were a traditional part of the urban green landscape are perceived as unsustainable and water-demanding. During recent summers when bans on irrigation have been imposed, use and sales of bedding plants have dropped dramatically having a negative financial impact on the nursery industry. Retaining bedding species as a feature in public and even private spaces in future may be conditional on them being managed in a manner that minimises their water use. Using Petunia x hybrida ‘Hurrah White’ we aimed to discover which irrigation approach was the most efficient for maintaining plants’ ornamental quality (flower numbers, size and longevity), shoot and root growth under water deficit and periods of complete water withdrawal. Plants were grown from plugs for 51 days in wooden rhizotrons (0.35 m (h) x 0.1 m (w) x 0.065 m (d)); the rhizotrons’ front comprised clear Perspex which enabled us to monitor root growth closely. Irrigation treatments were: 1. watering with the amount which constitutes 50% of container capacity by conventional surface drip-irrigation (‘50% TOP’); 2. 50% as sub-irrigation at 10 cm depth (‘50% SUB’); 3. ‘split’ irrigation: 25% as surface drip- and 25% as sub-irrigation at 15 cm depth (‘25/25 SPLIT’); 4. 25% as conventional surface drip-irrigation (‘25% TOP’). Plants were irrigated daily at 18:00 apart from days 34-36 (inclusive) when water was withdrawn for all the treatments. Plants in ‘50% SUB’ had the most flowers and their size was comparable to that of ‘50% TOP’. Differences between treatments in other ‘quality’ parameters (height, shoot number) were biologically small. There was less root growth at deeper soil surface levels for ‘50% TOP’ which indicated that irrigation methods like ‘50% SUB’ and ‘25/25 SPLIT’ and stronger water deficits encouraged deeper root growth. It is suggested that sub-irrigation at 10 cm depth with water amounts of 50% container capacity would result in the most root growth with the maximum flowering for Petunia. Leaf stomatal conductance appeared to be most sensitive to the changes in substrate moisture content in the deepest part of the soil profile, where most roots were situated.

Separating skill from luck in REIT mutual funds

This study uses a bootstrap methodology to explicitly distinguish between skill and luck for 80 Real Estate Investment Trust Mutual Funds in the period January 1995 to May 2008. The methodology successfully captures non-normality in the idiosyncratic risk of the funds. Using unconditional, beta conditional and alpha-beta conditional estimation models, the results indicate that all but one fund demonstrates poor skill. Tests of robustness show that this finding is largely invariant to REIT market conditions and maturity.

Dynamic correlations across REIT sub-sectors

The issue of whether Real Estate Investment Trusts should pursue a focused or diversified investment strategy remains an ongoing debate within both the academic and industry communities. This paper considers the relationship between REITs focused on different property sectors in a GARCH-DCC framework. The daily conditional correlations reveal that since 1990 there has been a marked upward trend in the coefficients between US REIT sub-sectors. The findings imply that REITs are behaving in a far more homogeneous manner than in the past. Furthermore, the argument that REITs should be focused in order that investors can make the diversification decision is reduced.

Who benefits from reducing the cost of formality? Quantile regression discontinuity analysis

This paper studies the effects of increasing formality via tax reduction and simplification schemes on micro-firm performance. It uses the 1997 Brazilian SIMPLES program. We develop a simple theoretical model to show that SIMPLES has an impact only on a segment of the micro-firm population, for which the effect of formality on firm performance can be identified, and that can be analyzed along the single dimensional quantiles of the conditional firm revenues. To estimate the effect of formality, we use an econometric approach that compares eligible and non-eligible firms, born before and after SIMPLES in a local interval about the introduction of SIMPLES. We use an estimator that combines both quantile regression and the regression discontinuity identification strategy. The empirical results corroborate the positive effect of formality on microfirms' performance and produce a clear characterization of who benefits from these programs.

PDM 2006: Proceedings of the International Workshop on Data Mining

Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.