The strategic impact of airline group diversification: the cases of Emirates and Lufthansa

The airline industry is a diverse sector, requiring the support of a varied range of ancillary businesses such as maintenance, catering and travel agencies to carry out its activities. Many of these supporting businesses demonstrate the potential to drive wider profit margins despite generating lower revenues than the airlines themselves, making them attractive investment opportunities in a sector prone to volatile and often lacklustre trading. This study investigates two of the largest diversified airline groups, Germany's Lufthansa Group and Dubai's Emirates Group, each adopting a distinct approach towards diversification that may serve as a model for airline groups worldwide. The areas investigated were Cargo, Maintenance, Catering and Travel Services. The research found that whilst diversification may not always present the most attractive option financially, strategic factors can often outweigh such concerns. Business units studied were found to have variable prospects; particularly in the case of Catering, a sector on the rise – versus in-house Maintenance, which for airlines, is likely to see decline. The pursuit of third party revenue streams to offset weak internal trading and growth in competencies were found to be the key drivers of success. Interplay between segments was also apparent, showing that a well-organised diversification strategy can achieve robust cross-functional benefits and deliver significant value to the parent organisation

Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry

Being dynamic in time and space, seasonal snow represents a difficult target for ongoing in situ measurement and characterisation. Improved understanding and modelling of the seasonal snowpack requires mapping snow depth at fine spatial resolution. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial variability of snow depth is evaluated within an alpine catchment of the Pisa Range, New Zealand. Digital surface models (DSMs) at 0.15&thinsp;m spatial resolution in autumn (snow-free reference) winter (2 August 2016) and spring (10 September 2016) allowed mapping of snow depth via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by the propagation of check point residuals from the aero-triangulation of constituent DSMs and via comparison of snow-free regions of the spring and autumn DSMs. The accuracy of RPAS-derived snow depth was validated with in situ snow probe measurements. Results for snow-free areas between DSMs acquired in autumn and spring demonstrate repeatability yet also reveal that elevation errors follow a distribution that substantially departs from a normal distribution, symptomatic of the influence of DSM co-registration and terrain characteristics on vertical uncertainty. Error propagation saw snow depth mapped with an accuracy of ±0.08&thinsp;m (90&thinsp;% c.l.). This is lower than the characterization of uncertainties on snow-free areas (±0.14&thinsp;m). Comparisons between RPAS and in situ snow depth measurements confirm this level of performance of RPAS photogrammetry while also highlighting the influence of vegetation on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine-scale spatial variability. Despite limitations accompanying RPAS photogrammetry, which are relevant to similar applications of surface and volume change analysis, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological catchment ( ∼ 0.4&thinsp;km2) at very high resolution. Resolving snowpack features associated with redistribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data will enhance understanding of physical processes controlling spatial distributions of seasonal snow and their relative importance on varying spatial and temporal scales.</p

Curative pelvic exenteration for recurrent cervical carcinoma in the era of concurrent chemotherapy and radiation therapy. A systematic review

International audienceOBJECTIVE: Pelvic exenteration requires complete resection of the tumor with negative margins to be considered a curative surgery. The purpose of this review is to assess the optimal preoperative evaluation and surgical approach in patients with recurrent cervical cancer to increase the chances of achieving a curative surgery with decreased morbidity and mortality in the era of concurrent chemoradiotherapy. METHODS: Review of English publications pertaining to cervical cancer within the last 25 years were included using PubMed and Cochrane Library searches. RESULTS: Modern imaging (MRI and PET-CT) does not accurately identify local extension of microscopic disease and is inadequate for preoperative planning of extent of resection. Today, only half of pelvic exenteration procedures obtain uninvolved surgical margins. CONCLUSION: Clear margins are required for curative pelvic exenterations, but are poorly predictable by pre-operative assessment. More extensive surgery, i.e. the infra-elevator exenteration with vulvectomy, is a logical surgical choice to increase the rate of clear margins and to improve patient survival following surgery for recurrent cervical carcinoma

The functional response of a generalist predator

Peer reviewedPublisher PD

New European Union fisheries regulations could benefit conservation of marine animals

Peer Reviewe