Visual Opsin Diversity in Sharks and Rays

The diversity of color vision systems found in extant vertebrates suggests that different evolutionary selection pressures have driven specializations in photoreceptor complement and visual pigment spectral tuning appropriate for an animal's behavior, habitat, and life history. Aquatic vertebrates in particular show high variability in chromatic vision and have become important models for understanding the role of color vision in prey detection, predator avoidance, and social interactions. In this study, we examined the capacity for chromatic vision in elasmobranch fishes, a group that have received relatively little attention to date. We used microspectrophotometry to measure the spectral absorbance of the visual pigments in the outer segments of individual photoreceptors from several ray and shark species, and we sequenced the opsin mRNAs obtained from the retinas of the same species, as well as from additional elasmobranch species. We reveal the phylogenetically widespread occurrence of dichromatic color vision in rays based on two cone opsins, RH2 and LWS. We also confirm that all shark species studied to date appear to be cone monochromats but report that in different species the single cone opsin may be of either the LWS or the RH2 class. From this, we infer that cone monochromacy in sharks has evolved independently on multiple occasions. Together with earlier discoveries in secondarily aquatic marine mammals, this suggests that cone-based color vision may be of little use for large marine predators, such as sharks, pinnipeds, and cetaceans.This work was supported by the Australian Research Council (Grant Nos. DP0558681, CE0561903, DP110103294, and LP160100333), the State Government of Western Australia, and the Sea World Research and Rescue Foundatio

The influence of individual cognitive style on performance in management education

This paper reports the outcomes of an empirical study undertaken to explore the possibility that cognitive style may be an important factor influencing performance on certain types of task in management education. Four hundred and twelve final-year undergraduate degree students studying management and business administration were tested using the Allinson-Hayes Cognitive Style Index. Their cognitive styles were then compared with assessment grades achieved for academic modules, the task categories of which were deemed to be consonant with either the wholist/intuitive or the analytic style of working. Overall ability defined by final degree grades was also tested against individuals’ cognitive styles. As expected, students whose dominant cognitive styles were analytic attained higher grades for long term solitary tasks involving careful planning and analysis of information. However, contrary to expectations, performance on tasks believed to be more suited to the wholist/intuitive style was also higher for analytic individuals, as was overall ability defined by final degree grades. The results were discussed in terms of the nature of the tasks and the need for methods of performance assessment that are independent of an orientation bias. Without this, it is argued, employment selection criteria may favour the wrong type of candidate in some circumstances

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Machine learning and scoring functions (SFs) for molecular drug discovery: Prediction and characterisation of druggable drugs and targets

Predicting druggability and prioritising disease-modifying targets is critical in drug discovery. In this chapter, we describe the testing of a druggability rule based on 9 molecular parameters, which uses cutpoints for each molecular parameter and targets based on mixture clustering discriminant analysis. We demonstrate that principal component constructs and score functions of violations can be used to identify the hidden pattern of druggable molecules and disease targets. Random Forest and Artificial Neural Network rules to classify the high-score target from the low-score molecular violators, based both on molecular parameters and the principal component constructs, have confirmed the value of logD's inclusion in the scoring function. Our scoring functions of counts of violations and novel principal component analytic molecular and target-based constructs partitioned chemospace well, identifying both good and poor druggable molecules and targets. Viable molecules and targets were located in both the beyond Rule of 5 and expanded Rule of 5 regions. Random Forest and Artificial Neural Networks showed different variable importance profiles, with Artificial Neural Networks models performing better than Random Forests. The most important molecular descriptors that influence classification, by the Random Forest methods, were MW, NATOM, logD, and PSA. The optimal Artificial Neural Networks target models indicated that PSA and logD were more important than the traditional parameter MW. Overall, our score 4 partitions using logD were optimal at classification as shown in all Random Forests and Artificial Neural Networks analyses.I. L. Hudson, S. Y. Leemaqz and A. D. Abel

Preventive hoof trimming in dairy cattle: Determining current practices and identifying future research areas

Background: The extent to which preventive hoof trimming is implemented on Great Britain's (GB) dairy farms is unknown. The aims of this study were to determine common practices and capture producers’ input on key areas that require further research. Methods: An online survey was conducted over a 4-week period from March to April 2017. Results: A total of 338 valid survey responses were received. The majority of farmers undertook preventive hoof trimming (82.4%), and this was significantly positively associated with increased herd yield (p<0.001). Drying off was the most common time trimming was undertaken, with 72.2% of farmers who implemented preventive trimming doing so at this point in the management cycle. Of those undertaking preventive trimming, 46.4% solely used an external hoof trimmer, 31.7% solely used farm staff and the remainder (21.9%) used a combination of operators. Four over-arching themes were identified within the key research questions; when to trim, why we should trim, how to trim and who to trim. The most frequent questions related to optimal trimming timing, frequency and method. Conclusion: This study highlighted that preventive hoof trimming is a widespread practice on GB dairy farms, undertaken by both external hoof trimmers and farm staff. Despite this, farmers still want to know when they should undertake preventive hoof trimming and which technique they should use

Manipulation of colonic bacteria and volatile fatty acid production by dietary high amylose maize (amylomaize) starch granules

Aims : To study the effects of amylomaize starch and modified (carboxymethylated and acetylated) amylomaize starches on the composition of colonic bacteria and the production of volatile fatty acids, in mice. Methods and Results : Balb/c mice were fed with experimental diets containing various amount of amylomaize and modified amylomaize starches. Colonic bacterial populations and short-chain fatty acids were monitored. Results showed that the increases in indigenous bifidobacteria were detected in mice fed all starches tested; however, the highest numbers were observed in the group fed with 40% unmodified amylomaize starch. The starch type influenced the populations of indigenous Lactobacillus , Bacteroides and coliforms. High Lactobacillus numbers were achieved in the colon of mice fed with high concentration of amylomaize starch. Acetylated amylomaize starch significantly reduced the population of coliforms. In addition, orally dosed amylomaize utilizing bifidobacteria reached their highest levels when fed together with amylomaize or carboxymethylated amylomaize starch and in both cases butyrate levels were markedly increased. Conclusions: These results indicate that different amylomaize starches could generate desirable variation in gut microflora and that particular starches may be used to selectively modify gut function. Significance and Impact of Study: Amylomaize starch appeared to enhance the desirable composition of colonic bacteria in mice, and suggested it possessed the potential prebiotic properties.MTherefore, resistant starch and its chemical derivatives may exert beneficial impacts to the human colon

Adjustment to the Aggregate Association Index to Minimise the Impact of Large Samples

The past few decades have seen a great deal of attention given to the development of techniques to analysis the association between aggregated categorical data. One of the most recent additions to this analysis has been the development of the aggregate association index (AAI). One feature of the AAI is that its magnitude is affected by the sample size; as the sample size increases so too does the AAI, even when the marginal proportions remain unchanged. In this article, we propose adjustments to the AAI to overcome the effect of increasing sample size. The Adjusted AAI is shown to be more stable than the original AAI in response to any increase in the sample size. Fisher's criminal twin data (Fisher, J. R. Stat. Assoc. Ser. A 98, 39-82, 1935) is used to demonstrate the adjustments