Several counterparts of Bayesian networks based on different paradigms have been proposed in evidence theory. Nevertheless, none of them is completely satisfactory. In this paper we will present a new one, based on a recently introduced concept of conditional independence. We define a conditioning rule for variables, and the relationship between conditional independence and irrelevance is studied with the aim of constructing a Bayesian-network-like model. Then, through a simple example, we will show a problem appearing in this model caused by the use of a conditioning rule. We will also show that this problem can be avoided if undirected or compositional models are used instead.
The relative proportions of free amino acids as well as the amino acid compositions of hydrolysed unprecipitated peptides and hydrolysed whole carcasses were quantified for two aphid species: the gall-dwelling social aphid Pemphigus spyrothecae and the pea aphid Acyrthosiphon pisum. The whole-tissue amino acid profiles of the two taxonomically distant species had a surprisingly high level of correspondence. In contrast, when comparing the A. pisum profiles obtained in the current study to those obtained in an earlier study, major differences were identified. It is concluded that there are good prospects for developing an artificial diet for P. spyrothecae. There may also exist considerable scope for tailoring the existing diets of A. pisum to suit specialised populations which develop poorly on the standard diet. The amino acid profile of P. spyrothecae is the first such profile that has been reported for a gall-forming aphid.
The prediction of traffic accident duration is great significant for rapid disposal of traffic accidents, especially for fast rescue of traffic accidents and re- moving traffic safety hazards. In this paper, two methods, which are based on artificial neural network (ANN) and support vector machine (SVM), are adopted for the accident duration prediction. The proposed method is demonstrated by a case study using data on approximately 235 accidents that occurred on freeways located between Dalian and Shenyang, from 2012 to 2014. The mean absolute error (MAE), the root mean square error (RMSE) and the mean absolute percentage error (MAPE) are used to evaluate the performances of the two measures. The conclusions are as follows: Both ANN and SVM models had the ability to predict traffic accident duration within acceptable limits. The ANN model gets a better result for long duration incident cases. The comprehensive performance of the SVM model is better than the ANN model for the traffic accident duration prediction.
We compare a recent selection theorem given by Chistyakov using the notion of modulus of variation, with a selection theorem of Schrader based on bounded oscillation and with a selection theorem of Di Piazza-Maniscalco based on bounded A , Λ-oscillation.
The aim of this study was to compare the isolation systems OptraDam® Plus and OptiDam™ with the conventional rubber dam in terms of objective and subjective parameters. The isolation systems were applied during the dental treatment of the patients. The time of preparation, placement, presence and removal were measured and the quality of isolation was evaluated. The median time of rubber dam placement was 76 s (Q1=62 s; Q3=111.25 s). The application time of OptraDam® Plus was significantly longer compared to the other systems (P ® plus. The results presented in this study could guide clinicians for choosing the most appropriate isolation system. and M. Kapitán, T. Suchánková Kleplová, J. Suchánek
Sampling of insect communities is very challenging and for reliable interpretation of results the effects of different sampling protocols and data processing on the results need to be fully understood. We compared three different commonly used methods for sampling forest beetles, freely hanging flight-intercept (window) traps (FWT), flight-intercept traps attached to trunks (TWT) and pitfall traps placed in the ground (PFT), in Scots pine dominated boreal forests in eastern Finland. Using altogether 960 traps, forming 576 sub-samples, at 24 study sites, 59760 beetles belonging to 814 species were collected over a period of a month. All of the material was identified to species, with the exception of a few species pairs, to obtain representative data for analyses. Four partly overlapping groups were used in the analyses: (1) all, (2) saproxylic, (3) rare and (4) red-listed species. In terms of the number of species collected TWTs were the most effective for all species groups and the rarer species the species group composed of (groups 1-2-3-4) the larger were the differences between the trap types. In particular, the TWTs caught most red-listed species. However, when sample sizes were standardized FWTs and TWTs caught similar number of species of all species groups. PFTs caught fewer species of all species groups, whether the sample sizes were standardized or not. In boreal forests they seem to be unsuitable for sampling saproxylic, rare and red-listed species. However, the PFTs clearly sampled different parts of species assemblages than the window traps and can be considered as a supplementary method. The abundance distribution of saproxylic species was truncated lognormal in TWT and pooled material, whereas unclassified material failed to reveal lognormal distribution in all the trap types and pooled material. The results show that even in boreal forests sample sizes of at least thousands, preferably tens of thousands of individuals, collected by a high number of traps are needed for community level studies. Relevant ecological classification of material is also very important for reliable comparisons. Differences in the performance of trap types should be considered when designing a study, and in particular when evaluating the results.