HOSPICIJ-POTREBA HUMANOG DRUŠTVA

Hrvatsko zakonodavstvo i regulativa palijativne skrbi imaju postavljene neke smjernice za razvoj u Republici Hrvatskoj. Međutim, da uhvatimo korak s razvijenim zemljama treba puno toga pravno i organizacijski urediti. Imamo znanje, imamo volju , imamo svijest nesebičnog djelovanja, ali nemamo financijske mogućnosti u ovom trenutku.O palijativnoj skrbi svaki pojedinac počinje razmišljati tek onda kada mu se razboli član njegove obitelji. Da smo u stanju podići ovu djelatnost u prioritete, našla bi se i sredstva za nju. Da bismo mogli iskoristiti znanje koje imamo treba odmah djelovati. To neće biti jednostavan proces, no u svijetu postoji puno modela i primjera, pa bi se uz iskustvo drugih, naš stručni kadar, te djelovanje na fleksibilnost hrvatske birokracije, okolnosti mogle promijeniti u pozitivnom smislu. Ne zbog nas, ali možda i za nas

Towards the development of a more accurate monitoring procedure for invertebrate populations, in the presence of an unknown spatial pattern of population distribution in the field

Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid

A Novel Approach to Evaluation of Pest Insect Abundance in the Presence of Noise

Evaluation of pest abundance is an important task of integrated pest management. It has recently been shown that evaluation of pest population size from discrete sampling data can be done by using the ideas of numerical integration. Numerical integration of the pest population density function is a computational technique that readily gives us an estimate of the pest population size, where the accuracy of the estimate depends on the number of traps installed in the agricultural field to collect the data. However, in a standard mathematical problem of numerical integration, it is assumed that the data are precise, so that the random error is zero when the data are collected. This assumption does not hold in ecological applications. An inherent random error is often present in field measurements, and therefore it may strongly affect the accuracy of evaluation. In our paper, we offer a novel approach to evaluate the pest insect population size under the assumption that the data about the pest population include a random error. The evaluation is not based on statistical methods but is done using a spatially discrete method of numerical integration where the data obtained by trapping as in pest insect monitoring are converted to values of the population density. It will be discussed in the paper how the accuracy of evaluation differs from the case where the same evaluation method is employed to handle precise data. We also consider how the accuracy of the pest insect abundance evaluation can be affected by noise when the data available from trapping are sparse. In particular, we show that, contrary to intuitive expectations, noise does not have any considerable impact on the accuracy of evaluation when the number of traps is small as is conventional in ecological applications