Effect of dietary restriction and subsequent re-alimentation on the transcriptional profile of bovine ruminal epithelium

peer-reviewedCompensatory growth (CG) is utilised worldwide in beef production systems as a management approach to reduce feed costs. However the underlying biology regulating the expression of CG remains to be fully elucidated. The objective of this study was to examine the effect of dietary restriction and subsequent re-alimentation induced CG on the global gene expression profile of ruminal epithelial papillae. Holstein Friesian bulls (n = 60) were assigned to one of two groups: restricted feed allowance (RES; n = 30) for 125 days (Period 1) followed by ad libitum access to feed for 55 days (Period 2) or (ii) ad libitum access to feed throughout (ADLIB; n = 30). At the end of each period, 15 animals from each treatment were slaughtered and rumen papillae harvested. mRNA was isolated from all papillae samples collected. cDNA libraries were then prepared and sequenced. Resultant reads were subsequently analysed bioinformatically and differentially expressed genes (DEGs) are defined as having a Benjamini-Hochberg P value of <0.05. During re-alimentation in Period 2, RES animals displayed CG, growing at 1.8 times the rate of their ADLIB contemporary animals in Period 2 (P < 0.001). At the end of Period 1, 64 DEGs were identified between RES and ADLIB, with only one DEG identified at the end of Period 2. When analysed within RES treatment (RES, Period 2 v Period 1), 411 DEGs were evident. Genes identified as differentially expressed in response to both dietary restriction and subsequent CG included those involved in processes such as cellular interactions and transport, protein folding and gene expression, as well as immune response. This study provides an insight into the molecular mechanisms underlying the expression of CG in rumen papillae of cattle; however the results suggest that the role of the ruminal epithelium in supporting overall animal CG may have declined by day 55 of re-alimentation.SMW received financial assistance from Science Foundation Ireland (SFI) contract no 09/ RFP/GEN2447

Estimating bus passenger waiting times from incomplete bus arrivals data

This paper considers the problem of estimating bus passenger waiting times at bus stops using incomplete bus arrivals data. This is of importance to bus operators and regulators as passenger waiting time is a key performance measure. Average waiting times are usually estimated from bus headways, that is, time gaps between buses. It is both time-consuming and expensive to measure bus arrival times manually so methods using automatic vehicle location systems are attractive; however, these systems do not usually provide 100% data coverage and missing data are problematical. The paper contributes to the general theory of estimating headway variance using incomplete data. Various methods for replacing missing buses or discarding spurious bus headways are compared and tested on different data sets.<br/

Quantifying the environmental benefits of collection/delivery points

Using a node-based routing and scheduling package, this paper estimates the environmental impacts of using a local railway station as a collection/delivery point (CDP) for small parcel transactions. This delivery option was compared with a typical existing situation where some customers who suffer a failed home delivery attempt decide to travel to the carrier's depot to collect their goods. The modelled results suggested that, at a 20 per cent take-up level, the CDP method would reduce the carbon monoxide emissions associated with the deliveries by around 20 per cent and other emissions (nitrogen oxide, particulate matter, carbon dioxide and hydrocarbons) by between 13 per cent and 15 per cent, with higher savings at higher take-up levels. The customer mileage attributable to the collection was modelled to reduce by up to 33 per cent. Modest travel savings were also found for the carrie

Regularity diagnosis by Automatic Vehicle Location raw data

Bus regularity is a crucial factor for high frequency public transport systems, because it represents a relevant measure of quality of service for both users and transit agencies. Low regularities for users are associated with bunching phenomena or large gaps between buses, which result in low attractiveness of the service for transit agencies. Therefore, evaluating the regularity is extremely desirable, but may also be a complex task in medium-size cities due to the huge amount of data which must be collected and processed effectively. Automatic Vehicle Location (AVL) technologies, which are particularly used by transit agencies in Western Europe, can address the data collection problem, but they involve several challenges such as correcting anomalies in collected raw data and processing information efficiently. In this paper, we propose a method to automatically handle AVL raw data for measuring the Level of Service (LoS) of bus regularity at each bus stop and time interval of any high frequency route. The results are represented by easy-to-read control dashboards and graphs.We discuss the experimentation of this method in a real case study to provide insights into the detailed characterization of bus regularity. The method is applied to data obtained from the transport agency CTM in Cagliari (Italy), whose vehicles are all equipped with AVL technologies