Orange (Belgium)

Counterfactuals are central in causal human reasoning and the scientific discovery process. The uplift, also called conditional average treatment effect, measures the causal effect of some action, or treatment, on the outcome of an individual. This paper discusses how it is possible to derive bounds on the probability of counterfactual statements based on uplift terms. First, we derive some original bounds on the probability of counterfactuals and we show that tightness of such bounds depends on the information of the feature set on the uplift term. Then, we propose a point estimator based on the assumption of conditional independence between the counterfactual outcomes. The quality of the bounds and the point estimators are assessed on synthetic data and a large real-world customer data set provided by a telecom company, showing significant improvement over the state of the art.

ObjectiveTo compare the processes and outcomes of care in patients who had a stroke treated in urban versus rural hospitals in Australia.DesignObservational study using data from a multicentre national registry.SettingData from 50 acute care hospitals in Australia (25 urban, 25 rural) which participated in the Australian Stroke Clinical Registry during the period 2010–2015.ParticipantsPatients were divided into two groups (urban, rural) according to the Australian Standard Geographical Classification Remoteness Area classification. Data pertaining to 28 115 patients who had a stroke were analysed, of whom 8159 (29%) were admitted to hospitals located within rural areas.Primary and secondary outcome measuresRegional differences in processes of care (admission to a stroke unit, thrombolysis for ischaemic stroke, discharge on antihypertensive medication and provision of a care plan), and survival analyses up to 180 days and health-related quality of life at 90–180 days.ResultsCompared with those admitted to urban hospitals, patients in rural hospitals less often received thrombolysis (urban 12.7% vs rural 7.5%, p<0.001) or received treatment in stroke units (urban 82.2% vs rural 76.5%, p<0.001), and fewer were discharged with a care plan (urban 61.3% vs rural 44.7%, p<0.001). No significant differences were found in terms of survival or overall self-reported quality of life.ConclusionsRural access to recommended components of acute stroke care was comparatively poorer; however, this did not appear to impact health outcomes at approximately 6 months.

This chapter contains background information on the concepts that form the basis for the research. The author provides an overview of the integration of security activities in traditional procedural approaches and discusses the potential differences in agile, iterative, contexts. Concepts such as “continuous integration,” “continuous deployment,” and “shift left” are introduced. The challenges and opportunities to achieve security assurance in DevOps environments are discussed, and the objective of the research project is presented.

Customer churn is a major concern for large companies (notably telcos), even in a big data world. Customer retention campaigns are routinely used to prevent churn, but targeting the right customers on the basis of their historical profile is a difficult task. Companies usually have recourse to two data-driven approaches: churn prediction and uplift modeling. In churn prediction, customers are selected on the basis of their propensity to churn in a near future. In uplift modeling, only customers reacting positively to the campaign are considered. Though uplift is better suited to maximize the efficiency of the retention campaign because of its causal aspect, it suffers from several estimation issues. To improve the uplift accuracy, this paper proposes to leverage historical data about the reachability of customers during a campaign. We suggest several strategies to incorporate reach information in uplift models, and we show that most of them outperform the classical churn and uplift models. This is a promising perspective for churn prevention in the telecommunication sector, where uplift modeling has failed so far to provide a significant advantage over non-causal approaches.

Resection of a pelvic tumor is challenging because of its complex three-dimensional (3D) anatomy and deep-seated location with nearby vital structures. The resection is technically demanding if a custom implant is used for reconstruction of the bone defect as the surgeon needs to ensure the resection margin is sufficiently wide and the orientation of intended resection planes must match that of the custom implant. We describe a novel workflow of performing a partial acetabular resection in a patient with pelvic chondrosarcoma and reconstruction with a custom pelvic implant in a one-step operation. A multi-planar bone resection was virtually planned. A computer-aided design implant that both matched the bone defect and biomechanically evaluated was prefabricated with 3D printing technology. The 3D-printed patient-specific instruments (PSIs) were used to reproduce the same planned resection. The histology of the tumor specimen showed a clear resection margin. The errors of the achieved resection and implant position were deviating (1–4 mm) from the planned. The patient could walk unaided with a good hip function. No tumor recurrence and implant loosening were noted at 11 months after surgery. The use of this novel CT-based method for surgical planning, the engineering software for implant design and validation, together with 3D printing technology for implant and PSI fabrication makes it possible to generate a personalized, biomechanically evaluated implant for accurate reconstruction after a pelvic tumor resection in a one-step operation. Further study in a larger population is needed to assess the clinical efficacy of the workflow in complex bone tumor surgery.

This document introduces the main MVNO solutions. It attempts to identify what are the strategic elements in the network architecture. The general trend is most probably an evolution towards an MVNO owning the whole core network architecture and buying access service to an MNO. A cost oriented pricing mode for these access services should be put in place, more systematically driven by regulation agencies promoting competition for mobile data services via the MVNO operating mode. A simple global economic model is proposed for MVNO and MNO. It explains why the activity of mobile network operator is limited to a small number of players and how an MVNO mode makes possible extending the viability of the mobile operator business to other actors.

To estimate the exposure around a base station, the frequency-selective electromagnetic field measurement with a spectrum analyzer and antenna is the most appropriate method. In this paper, a theoretical model for the wideband code division multiaccess signal, which is measured by a spectrum analyzer, is extended to the measurement of the signal used in the universal mobile telecommunications system (UMTS), where the transmitted signal is subject to power control. The developed model is successfully validated by measurements. It is shown that the presence of power control has important implications on the achievable accuracy of the measurements. Based on the developed model, the optimal settings of the spectrum analyzer are proposed for the exposure assessment around UMTS base stations.