Why high seed densities within buried mesh bags may overestimate depletion rates of soil seed banks

1. Estimates of seed bank depletion rates are essential for modelling and management of plant populations. The seed bag burial method is often used to measure seed mortality in the soil. However, the density of seeds within seed bags is higher than densities in natural seed banks, which may elevate levels of pathogens and influence seed mortality. The aim of this study was to quantify the effects of fungi and seed density within buried mesh bags on the mortality of seeds. Striga hermonthica was chosen as the study species because it has been widely studied but different methods for measuring seed mortality in the soil have yielded contradictory estimates. 2. Seed bags were buried in soil and exhumed at regular time intervals to monitor mortality of the seeds in three field experiments during two rainy seasons. The effect of fungal activity on seed mortality was evaluated in a fungi exclusion experiment. Differences in seed-to-seed interaction were obtained by using two and four densities within the seed bags in consecutive years. Densities were created by mixing 1000 seeds with 0, 10, 100 or 1000 g of coarse sand. 3. The mortality rate was significantly lower when fungi were excluded, indicating the possible role of pathogenic fungi. 4. Decreasing the density of seeds in bags significantly reduced seed mortality, most probably because of decreased seed-to-seed contamination by pathogenic fungi. 5. Synthesis and applications. Models of plant populations in general and annual weeds in particular often use values from the literature for seed bank depletion rates. These depletion rates have often been estimated by the seed bag burial method, yet seed density within seed bags may be unrealistically high. Consequently, estimates of seed mortality rates may be too high because of an overestimation of the effects of soil or seed-borne pathogens. Species that have been classified from such studies as having short-lived seed banks may need to be re-assessed using realistic densities either within seed bags or otherwise. Similarly, models of seed bank dynamics based on such overestimated depletion rates may lead to incorrect conclusions regarding the seed banks and, perhaps, the management of weeds and rare species.

Biomechanics of a branch-stem junction in softwood

Direct measurement of strain field in a mechanically loaded Norway spruce branch-stem junction was performed by means of electronic speckle pattern analysis. Results were compared with strain distribution in a polyester cast of identical shape as the branch-stem junction, and a simplified polyester model consisting of two half-cylinders. Compared to polyester models, the branch-stem junction was characterised by a very homogeneous distribution of strain, which can be interpreted as a homogeneous distribution of stress in terms of fraction of material strength. This optimised transfer of mechanical load from the branch to the stem is achieved by a combination of naturally optimised shape with, additionally, optimised mechanical wood properties in the junction area.

Attitudes of rural branch managers in Madhya Pradesh, India, toward their role as providers of financial services to the poor

Discussions on banking reforms to reduce financial exclusion have referred little to possible attitudinal constraints, on the part of staff at both branch and institutional levels, inhibiting the provision of financial services to the poor. The research project, funded by the ESCOR (now Social Science Research) Small Grants Committee, has focused on this aspect of financial exclusion. The research commenced in May 2001 and was completed in April 2002. Profiles of the rural bank branch managers, including personal background, professional background and workplace, are presented. Attitudes of managers toward aspects of their work environment and the rural poor are examined, using results from both quantitative and qualitative analysis. Finally, the emerging policy implications are discussed. These include bank reforms to address human resource management, the work environment, intermediate bank management and organization, and the client interface.

A new organization for a perceptron-based branch predictor and its FPGA implementation

An unaltered rearrangement of the original computation of a neural based predictor at the algorithmic level is introduced as a new organization. Its FPGA implementation generates circuits that are 1.7 faster than a direct implementation of the original algorithm. This faster clock rate allows to implement predictors with longer history lengths using the nearly the same hardware budget.

FPGA organization for the fast path-based neural branch predictor

This paper develops cycle-level FPGA circuits of an organization for a fast path-based neural branch predictor Our results suggest that practical sizes of prediction tables are limited to around 32 KB to 64 KB in current FPGA technology due mainly to FPGA area of logic resources to maintain the tables. However the predictor scales well in terms of prediction speed. Table sizes alone should not be used as the only metric for hardware budget when comparing neural-based predictor to predictors of totally different organizations. This paper also gives early evidence to shift the attention on to the recovery from mis-prediction latency rather than on prediction latency as the most critical factor impacting accuracy of predictions for this class of branch predictors.

A-optimality orthogonal forward regression algorithm using branch and bound

In this brief, we propose an orthogonal forward regression (OFR) algorithm based on the principles of the branch and bound (BB) and A-optimality experimental design. At each forward regression step, each candidate from a pool of candidate regressors, referred to as S, is evaluated in turn with three possible decisions: 1) one of these is selected and included into the model; 2) some of these remain in S for evaluation in the next forward regression step; and 3) the rest are permanently eliminated from S. Based on the BB principle in combination with an A-optimality composite cost function for model structure determination, a simple adaptive diagnostics test is proposed to determine the decision boundary between 2) and 3). As such the proposed algorithm can significantly reduce the computational cost in the A-optimality OFR algorithm. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm.