Toxicity of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in the developing male Wistar(Han) rat I: no decrease in epididymal sperm count after a single acute dose

It has been reported that fetal exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) causes defects in the male reproductive system of the rat. We set out to replicate and extend these effects using a robust experimental design. Groups of 75 (control vehicle) or 55 (50, 200 or 1000 ng of TCDD kg-1 bodyweight) female Wistar(Han) rats were exposed to TCDD on Gestational Day (GD) 15, then allowed to litter. The high dose group dams showed no sustained weight loss compared to control, but four animals had total litter loss. Pups in the high dose group showed reduced body weight up till day 21, and pups in the medium dose group showed reduced body weight in the first week post partum. Balano-preputial separation (BPS) was significantly delayed in the high dose group male offspring. There were no significant effects of treatment when the offspring were subjected to a functional observational battery, or mated with females to assess reproductive capability. 25 males per group were killed on post natal day (PND) 70, and ~60 animals per group (~30 for the high dose group) on PND120 to assess seminology and other endpoints. At PND120, the two highest dose groups showed a statistically significant elevation of sperm counts, compared to control; however, this effect was small (~30%), within the normal range of sperm counts for this strain of rat, was not reflected in testicular spermatid counts nor PND70 data, and is therefore postulated to have no biological significance. Although there was an increase in the proportion of abnormal sperm at PND70, seminology parameters were otherwise unremarkable. Testis weights in the high dose group were slightly decreased at PND 70 and 120, and at PND120, brain weights were decreased in the high dose group, liver to body weight ratios were increased for all three dose groups, with an increase in inflammatory cell foci in the epididymis in the high dose group. These data show that TCDD is a potent developmental toxin after exposure of the developing fetus, but that acute developmental exposure to TCDD on GD15 caused no decrease in sperm counts.

A Decomposition, Construction and Post-Processing Approach for Nurse Rostering

This paper presents our work on decomposing a specific nurse rostering problem by cyclically assigning blocks of shifts, which are designed considering both hard and soft constraints, to groups of nurses. The rest of the shifts are then assigned to the nurses to construct a schedule based on the one cyclically generated by blocks. The schedules obtained by decomposition and construction can be further improved by a variable neighborhood search. Significant results are obtained and compared with a genetic algorithm and a variable neighborhood search approach on a problem that was presented to us by our collaborator, ORTEC bv, The Netherlands. We believe that the approach has the potential to be further extended to solve a wider range of nurse rostering problems.

An Indirect Genetic Algorithm for Set Covering Problems

This paper presents a new type of genetic algorithm for the set covering problem. It differs from previous evolutionary approaches first because it is an indirect algorithm, i.e. the actual solutions are found by an external decoder function. The genetic algorithm itself provides this decoder with permutations of the solution variables and other parameters. Second, it will be shown that results can be further improved by adding another indirect optimisation layer. The decoder will not directly seek out low cost solutions but instead aims for good exploitable solutions. These are then post optimised by another hill-climbing algorithm. Although seemingly more complicated, we will show that this three-stage approach has advantages in terms of solution quality, speed and adaptability to new types of problems over more direct approaches. Extensive computational results are presented and compared to the latest evolutionary and other heuristic approaches to the same data instances.

'An Indirect Genetic Algorithm for Set Covering Problems'

This paper presents a new type of genetic algorithm for the set covering problem. It differs from previous evolutionary approaches first because it is an indirect algorithm, i.e. the actual solutions are found by an external decoder function. The genetic algorithm itself provides this decoder with permutations of the solution variables and other parameters. Second, it will be shown that results can be further improved by adding another indirect optimisation layer. The decoder will not directly seek out low cost solutions but instead aims for good exploitable solutions. These are then post optimised by another hill-climbing algorithm. Although seemingly more complicated, we will show that this three-stage approach has advantages in terms of solution quality, speed and adaptability to new types of problems over more direct approaches. Extensive computational results are presented and compared to the latest evolutionary and other heuristic approaches to the same data instances.