No description available.

No description available.

No description available.

No description available.

No description available.

The ecological success of social insects is frequently ascribed to improvements in task performance due to division of labour amongst workers. While much research has focused on improvements associated with lifetime task specialization, members of colonies can specialize on a given task over shorter time periods. Eusocial bees in particular must collect pollen and nectar rewards to survive, but most workers appear to mix collection of both rewards over their lifetimes. We asked whether bumblebees specialize over timescales shorter than their lifetime. We also explored factors that govern such patterns, and asked whether reward specialists made more foraging bouts than generalists. In particular, we described antennal morphology and size of all foragers in a single colony and related these factors to each forager's complete foraging history, obtained using radio frequency identification (RFID). Only a small proportion of foragers were lifetime specialists; nevertheless, >50% of foragers specialized daily on a given reward. Contrary to expectations, daily and lifetime reward specialists were not better foragers (being neither larger nor making more bouts); larger bees with more antennal olfactory sensilla made more bouts, but were not more specialized. We discuss causes and functions of short and long-term patterns of specialization for bumblebee colonies.

Computer algorithms are routinely used to aid in the identification of biological patterns not easily detected with standard statistics. Currently, observed changes in normal patterns of feeding behavior (FB) are used to identify morbid feedlot cattle. The objective of this study was to use pattern classification techniques to develop algorithms capable of identifying morbid (M) cattle earlier than traditional pen checking methods. In two separate studies, individual feeding behaviour was obtained from 384 feedlot steers (228 ± 22.7 kg, initial BW) in a 226 d trial (model dataset), and 384 feedlot heifers (322 ± 34.7 kg, initial BW) in a 142 d trial (naive dataset). Data was collected using an automated feed bunk monitoring system. FB variables calculated included feeding duration, inter-meal interval (min., max., avg., SD and total; min/d) and feeding frequency (visits/d). Animal health records including the number of times treated, d in the hospital and d on feed were also collected. Ninety-three and 53 morbid (M) animals were identified in each trial respectively, and were categorized into low, moderate and high groups, based on severity of sickness. FB data for 68 cattle from the model dataset (45 classified as Moderate and 25 classified as High) was analyzed to develop an algorithm which would aid in identifying morbid FB. This algorithm was later tested on 18 M animals (12 classified as Moderate and 6 as High) in the naive dataset. The pattern recognition procedure involved reducing data dimensionality via Principal Component Analysis, followed by K-means clustering and finally the development of a binary string to aid in the classification of M feeding behaviour. The developed procedure resulted in an overall classification accuracy of 84 % (82.5 and 85 % accuracy for H and M, respectively) for the model dataset, and 75 % overall (100 and 50 % accuracy for H and M, respectively) for the naive dataset. The model predicted morbidity on average 3.3 and 1.2 d earlier than pen checkers could for each trial respectively. The application of pattern recognition algorithms to FB shows value as a method of identifying morbid cattle in advance of overt physical signs of morbidity.

Computer algorithms are routinely used to aid in the identification of biological patterns not easily detected with standard statistics. Currently, observed changes in normal patterns of feeding behavior (FB) are used to identify morbid feedlot cattle. The objective of this study was to use pattern classification techniques to develop algorithms capable of identifying morbid (M) cattle earlier than traditional pen checking methods. In two separate studies, individual feeding behaviour was obtained from 384 feedlot steers (228 ± 22.7 kg, initial BW) in a 226 d trial (model dataset), and 384 feedlot heifers (322 ± 34.7 kg, initial BW) in a 142 d trial (naive dataset). Data was collected using an automated feed bunk monitoring system. FB variables calculated included feeding duration, inter-meal interval (min., max., avg., SD and total; min/d) and feeding frequency (visits/d). Animal health records including the number of times treated, d in the hospital and d on feed were also collected. Ninety-three and 53 morbid (M) animals were identified in each trial respectively, and were categorized into low, moderate and high groups, based on severity of sickness. FB data for 68 cattle from the model dataset (45 classified as Moderate and 25 classified as High) was analyzed to develop an algorithm which would aid in identifying morbid FB. This algorithm was later tested on 18 M animals (12 classified as Moderate and 6 as High) in the naive dataset. The pattern recognition procedure involved reducing data dimensionality via Principal Component Analysis, followed by K-means clustering and finally the development of a binary string to aid in the classification of M feeding behaviour. The developed procedure resulted in an overall classification accuracy of 84 % (82.5 and 85 % accuracy for H and M, respectively) for the model dataset, and 75 % overall (100 and 50 % accuracy for H and M, respectively) for the naive dataset. The model predicted morbidity on average 3.3 and 1.2 d earlier than pen checkers could for each trial respectively. The application of pattern recognition algorithms to FB shows value as a method of identifying morbid cattle in advance of overt physical signs of morbidity.

The aim of this study was to explore how caregivers caring for severely demented patients experience ethical conflict situations. Feeding patients in a late state of dementia was chosen as focus. Special attention was paid to analyses of the caregivers' experiences with regard to their feelings, use of force, interpretations of the patients' behaviour and their ethical reasoning. The study was carried out in five separate parts, presented as five papers. A phenomenological - hermeneutic approach was consistent. Personal interviews, a projective defence mechanism test, the Meta Contrast Technique and an analysis of patient/caregiver behaviour as shown in video taped feeding sessions were the methods used. Study participants were forty-one caregivers in psychogeriatric care, registered nurses, licensed practical nurses and nurses' assistants. The result indicated that, when facing ethical decisions the caregivers were caught in a double bind conflict due to the contradicting ethical demands "Keep the patient alive!" and "Don't cause the patient suffering!". The difficulty to interpret what the patients experienced and the impossibility to know for sure what actions would be right or wrong were sources of anxiety. They defined force feeding individually, yet a pattern was found. Some caregivers defined force feeding according to the amount of persuasiveness or violence they had to perform. Some regarded force feeding from a patient wish perspective. A majority combined the two dimensions. The caregivers' ethical reasoning showed that their decision making was to be regarded as a process grounded on ethical rules. Interdependence in the relation caregiver/patient made them develop their reasoning in a direction of existential reasoning. / <p>S. 1-38: sammanfattning, s. 39-113: 5 uppsatser</p> / digitalisering@umu

Genetic variation between individuals is of great importance for the development of breeding programmes, to select for animals with the most favourable traits. Many production companies routinely measure the feed intake of their animals, in order to calculate efficiency traits such as feed conversion ratio. The development of electronic feeders which automatically record individual intake on a visit-by-visit basis now allows the short-term feeding behaviour of animals to be monitored and analysed as another source of variation between individuals. Due to differences in the resolutions of these feeders as a measurement tool, a standard unit of feeding event needs to be estimated to allow for comparisons between studies. Different models for estimation of the defining value of a meal, the meal criterion, have been used, with the most recent incorporating the change in satiety with time since last feeding as part of the model. In this study I developed a new methodology, based on these models, for use when a within meal population of intervals cannot be easily modelled. I then used this model for application to data from four lines of broiler chickens to estimate meal criteria and compare feeding behaviour within and between the lines. Significant differences were found between fast and slow growing birds, with the faster growing birds having fewer but larger meals than the slower growing birds. However, the lines showed similar structure and bouting of their feeding behaviour, indicating that the fundamental controls of feeding behaviour, such as hunger and satiety, in these lines had been unaltered despite intensive selection for growth. The models were also applied across poultry species, kept in different experimental conditions. A similar structure to the feeding behaviour was found across all these species, with all showing clear separation of feeding events into bouts. In order to estimate the potential use of these behavioural observations in a breeding programme, the heritabilities and genetic correlations with existing performance traits were calculated for the four broiler lines. Heritabilities of all feeding behaviour traits were found to be moderate to high, and very similar across the lines. Correlations with performance traits, however, were low, meaning that there were no clear links of the traits with the current production goals investigated. This indicates that past selection for production has had limited impact on feeding behaviour and also that potential selection for feeding behaviour will have little effect on production gains. To identify the areas of the genome controlling feeding behaviour, traits were associated with a SNP panel. Many regions were found to have highly significant association with feeding behaviour traits, with the most highly correlated traits showing associations with the same regions, suggesting pleiotropic effects of genes in these regions. Future work in this area should include identification of individual genes controlling feeding behaviour to allow prediction of the effects of selection for favourable feeding behaviour on other traits, and comparison of the genotypes of different lines of broilers, to further understand the control of feeding behaviour.