Managing technology risk in R&D project planning: Optimal timing and parallelization of R&D activities.

An inherent characteristic of R&D projects is technological uncertainty, which may result in project failure, and time and resources spent without any tangible return. In pharmaceutical projects, for instance, stringent scientific procedures have to be followed to ensure patient safety and drug efficacy in pre-clinical and clinical tests before a medicine can be approved for production. A project consists of several stages, and may have to be terminated in any of these stages, with typically a low likelihood of success. In project planning and scheduling, this technological uncertainty has typically been ignored, and project plans are developed only for scenarios in which the project succeeds. In this paper, we examine how to schedule projects in order to maximize their expected net present value, when the project activities have a probability of failure, and where an activity's failure leads to overall project termination. We formulate the problem, show that it is NP-hard and develop a branchand- bound algorithm that allows to obtain optimal solutions. We also present polynomial-time algorithms for special cases, and present a number of managerial insights for R&D project and planning, including the advantages and disadvantages of parallelization of R&D activities in different settings.Applications; Branch-and-bound; Computational complexity; Exact algorithms programming; Integer; Pharmaceutical; Project management; Project scheduling; R&D projects analysis of algorithms; Risk industries;

Observing and tracking bandlimited graph processes from sampled measurements

A critical challenge in graph signal processing is the sampling of bandlimited graph signals; signals that are sparse in a well-defined graph Fourier domain. Current works focused on sampling time-invariant graph signals and ignored their temporal evolution. However, time can bring new insights on sampling since sensor, biological, and financial network signals are correlated in both domains. Hence, in this work, we develop a sampling theory for time varying graph signals, named graph processes, to observe and track a process described by a linear state-space model. We provide a mathematical analysis to highlight the role of the graph, process bandwidth, and sample locations. We also propose sampling strategies that exploit the coupling between the topology and the corresponding process. Numerical experiments corroborate our theory and show the proposed methods trade well the number of samples with accuracy

Genetic structure of captive and free-ranging okapi (Okapia johnstoni) with implications for management

Breeding programs for endangered species increasingly use molecular genetics to inform their management strategies. Molecular approaches can be useful for investigating relatedness, resolving pedigree uncertainties, and for estimating genetic diversity in captive and wild populations. Genetic data can also be used to evaluate the representation of wild population genomes within captive population gene-pools. Maintaining a captive population that is genetically representative of its wild counterpart offers a means of conserving the original evolutionary potential of a species. Okapi, an even-toed ungulate, endemic to the Democratic Republic of Congo, have recently been reclassified as Endangered by the IUCN. We carried out a genetic assessment of the ex-situ okapi (Okapia johnstoni) population, alongside an investigation into the genetic structure of wild populations across their geographic range. We found that while levels of nuclear (12 microsatellite loci) genetic variation in the wild, founder and captive okapi populations were similar, mitochondrial (833 bp of Cyt b, CR, tRNA-Thr and tRNA-Pro) variation within captive okapi was considerably reduced compared to the wild, with 16 % lower haplotype diversity. Further, both nuclear and mitochondrial alleles present in captivity provided only partial representation of those present in the wild. Thirty mitochondrial haplotypes found in the wild were not found in captivity, and two haplotypes found in captivity were not found in the wild, and the patterns of genetic variation at microsatellite loci in our captive samples were considerably different to those of the wild samples. Our study highlights the importance of genetic characterisation of captive populations, even for well-managed ex-situ breeding programs with detailed studbooks. We recommend that the captive US population should be further genetically characterised to guide management of translocations between European and US captive population

Fuzzy support vector machines for pattern classification

In response to the Ebola virus disease (EVD) outbreak in West Africa, the World Health Organization has advised all nations to prepare for the detection, investigation and management of confirmed and suspected EVD cases in order to prevent further spread through international travel. To gain insights into the state of preparedness of European hospitals, an electronic survey was circulated in August–September 2014 to 984 medical professionals representing 736 hospitals in 40 countries. The survey addressed the willingness and capacity to admit patients with suspected EVD as well as specific preparedness activities in response to the current Ebola crisis. Evaluable responses were received from representatives of 254 (32%) hospitals in 38 countries, mostly tertiary care centres, of which 46% indicated that they would admit patients with suspected EVD. Patient transfer agreements were in place for the majority of hospitals that would not admit patients. Compared with non-admitting hospitals, admitting hospitals were more frequently engaged in various preparedness activities and more often contained basic infrastructural characteristics such as admission rooms and laboratories considered important for infection control, but some gaps and concerns were also identified. The results of this survey help to provide direction towards further preparedness activities and prioritisation thereof

Compressive 3D ultrasound imaging using a single sensor

Three-dimensional ultrasound is a powerful imaging technique, but it requires thousands of sensors and complex hardware. Very recently, the discovery of compressive sensing has shown that the signal structure can be exploited to reduce the burden posed by traditional sensing requirements. In this spirit, we have designed a simple ultrasound imaging device that can perform three-dimensional imaging using just a single ultrasound sensor. Our device makes a compressed measurement of the spatial ultrasound field using a plastic aperture mask placed in front of the ultrasound sensor. The aperture mask ensures that every pixel in the image is uniquely identifiable in the compressed measurement. We demonstrate that this device can successfully image two structured objects placed in water. The need for just one sensor instead of thousands paves the way for cheaper, faster, simpler, and smaller sensing devices and possible new clinical applications