Is it worth changing pattern recognition methods for structural health monitoring?

The key element of this work is to demonstrate alternative strategies for using pattern recognition algorithms whilst investigating structural health monitoring. This paper looks to determine if it makes any difference in choosing from a range of established classification techniques: from decision trees and support vector machines, to Gaussian processes. Classification algorithms are tested on adjustable synthetic data to establish performance metrics, then all techniques are applied to real SHM data. To aid the selection of training data, an informative chain of artificial intelligence tools is used to explore an active learning interaction between meaningful clusters of data

Direct monitoring of photon induced isomerization, dissociation and electron detachment of the green fluorescent protein chromophore anion

We present the first experimental demonstration of Z↔E photoisomerization the GFP chromophore anion, HBDI−, in the gas phase. In the single photon absorption regime, the photoisomerization action spectra show two maxima at 480 nm and 455 nm. In the multiphoton absorption regime, photodissociation and photodetachment channels modify the appearance of the photoisomerization band. This work provides a new approach to characterize photoisomerization pathways in biomolecular ions

Importance of Baseline Specification in Evaluating Conservation Interventions and Achieving No Net Loss of Biodiversity

There is an urgent need to improve the evaluation of conservation interventions. This requires specifying an objective and a frame of reference from which to measure performance. Reference frames can be baselines (i.e., known biodiversity at a fixed point in history) or counterfactuals (i.e., a scenario that would have occurred without the intervention). Biodiversity offsets are interventions with the objective of no net loss of biodiversity (NNL). We used biodiversity offsets to analyze the effects of the choice of reference frame on whether interventions met stated objectives. We developed 2 models to investigate the implications of setting different frames of reference in regions subject to various biodiversity trends and anthropogenic impacts. First, a general analytic model evaluated offsets against a range of baseline and counterfactual specifications. Second, a simulation model then replicated these results with a complex real world case study: native grassland offsets in Melbourne, Australia. Both models showed that achieving NNL depended upon the interaction between reference frame and background biodiversity trends. With a baseline, offsets were less likely to achieve NNL where biodiversity was decreasing than where biodiversity was stable or increasing. With a no‐development counterfactual, however, NNL was achievable only where biodiversity was declining. Otherwise, preventing development was better for biodiversity. Uncertainty about compliance was a stronger determinant of success than uncertainty in underlying biodiversity trends. When only development and offset locations were considered, offsets sometimes resulted in NNL, but not across an entire region. Choice of reference frame determined feasibility and effort required to attain objectives when designing and evaluating biodiversity offset schemes. We argue the choice is thus of fundamental importance for conservation policy. Our results shed light on situations in which biodiversity offsets may be an inappropriate policy instrumen

Choosing prevention or cure when mitigating biodiversity loss: trade-offs under ‘no net loss’ policies

1. Biodiversity cannot always be conserved. Economic development activities can result in biodiversity losses, but also increase human wellbeing, so trade-offs must sometimes be made between conservation and development. An alternative strategy to avoidance of impacts through the strict protection of biodiversity (‘prevention’) is to permit certain biodiversity losses and fully compensate for them through offsets elsewhere (‘cure’). 2. Here, we build a stochastic simulation model to explore trade-offs between biodiversity loss prevention and cure, in the context of development under ‘no net loss’ (NNL) biodiversity policies. Our model implements a Management Strategy Evaluation framework, monitoring outcomes using four different performance metrics: total biodiversity, net biodiversity, total economic activity, and development activity. 3. We find that a "cure" strategy can potentially perform just as well as a prevention strategy in terms of biodiversity objectives, whilst outperforming the latter from an economic perspective. However, this does not undermine the need for a mitigation hierarchy, and the best-performing strategy depends strongly upon both the degree of compliance with the NNL policy and upon underlying ecological parameters. 4. Perhaps counterintuitively, when evaluated as advised by the technical literature (i.e. against an appropriate counterfactual scenario), we find that net biodiversity outcomes are highest when natural ecosystem recovery rates are slow (so long as development rates are also slow). 5. Finally, using the illustrative example of US wetlands, we suggest that real-world NNL policies could already be driving landscape-scale avoidance of development impacts under a "prevention" approach. 6. Policy implications. No net loss (NNL) biodiversity policy is currently being developed or implemented by over 100 countries worldwide and incorporated into environmental safeguards by multinational lenders. The socio-ecological model presented here can be used to advise decision makers about the best structure for nascent NNL policy on the basis of region-specific ecosystem recovery rates, development activity, legal compliance and monitoring uncertainty. Further, the model presents a means for estimating the degree to which biodiversity impacts are avoided by developers under NNL – an important monitoring consideration given that ensuring high levels of avoidance is crucial to robust NNL policy, but which has to date evaded assessment through purely empirical means

No net loss for people and biodiversity

Governments, businesses, and lenders worldwide are adopting an objective of no net loss (NNL) of biodiversity that is often partly achieved through biodiversity offsetting within a hierarchy of mitigation actions. Offsets aim to balance residual losses of biodiversity caused by development in one location with commensurate gains at another. Although ecological challenges to achieve NNL are debated, the associated gains and losses for local stakeholders have received less attention. International best practice calls for offsets to make people no worse off than before implementation of the project, but there is a lack of clarity concerning how to achieve this with regard to people's use and nonuse values for biodiversity, especially given the inevitable trade‐offs when compensating biodiversity losses with gains elsewhere. This is particularly challenging for countries where poor people depend on natural resources. Badly planned offsets can exacerbate poverty, and development and offset impacts can vary across spatial‐temporal scales and by location, gender, and livelihood. We conceptualize the no‐worse‐off principle in the context of NNL of biodiversity, by exploring for whom and how the principle can be achieved. Changes in the spatial and temporal distribution of biodiversity‐related social impacts of a development and its associated offset can lead to social inequity and negatively impact people's well‐being. The level of aggregation (regional, village, interest group, household, and individual) at which these social impacts are measured and balanced can again exacerbate inequity in a system. We propose that a determination that people are no worse off, and preferably better off, after a development and biodiversity offset project than they were before the project should be based on the perceptions of project‐affected people (assessed at an appropriate level of aggregation); that their well‐being associated with biodiversity losses and gains should be at least as good as it was before the project; and that this level of well‐being should be maintained throughout the project life cycle. Employing this principle could help ensure people are no worse off as a result of interventions to achieve biodiversity NNL

A sampling-based approach for information-theoretic inspection management

A partially supervised approach to Structural Health Monitoring is proposed, to manage the cost associated with expert inspections and maximize the value of monitoring regimes. Unlike conventional data-driven procedures, the monitoring classifier is learnt online while making predictions—negating the requirement for complete data before a system is in operation (which are rarely available). Most critically, periodic inspections are replaced (or enhanced) by an automatic inspection regime, which only queries measurements that appear informative to the evolving model of the damage-sensitive features. The result is a partially supervised Dirichlet process clustering that manages expert inspections online given incremental data. The method is verified on a simulated example and demonstrated on in situ bridge monitoring data

Foundations of population-based SHM, Part I : homogeneous populations and forms

In Structural Health Monitoring (SHM), measured data that correspond to an extensive set of operational and damage conditions (for a given structure) are rarely available. One potential solution considers that information might be transferred, in some sense, between similar systems. A population-based approach to SHM looks to both model and transfer this missing information, by considering data collected from groups of similar structures. Specifically, in this work, a framework is proposed to model a population of nominally-identical systems, such that (complete) datasets are only available from a subset of members. The SHM strategy defines a general model, referred to as the population form, which is used to monitor a homogeneous group of systems. First, the framework is demonstrated through applications to a simulated population, with one experimental (test-rig) member; the form is then adapted and applied to signals recorded from an operational wind farm

Probabilistic inference for structural health monitoring: new modes of learning from data

In data-driven structural health monitoring (SHM), the signals recorded from systems in operation can be noisy and incomplete. Data corresponding to each of the operational, environmental, and damage states are rarely available a priori; furthermore, labeling to describe the measurements is often unavailable. In consequence, the algorithms used to implement SHM should be robust and adaptive while accommodating for missing information in the training data—such that new information can be included if it becomes available. By reviewing novel techniques for statistical learning (introduced in previous work), it is argued that probabilistic algorithms offer a natural solution to the modeling of SHM data in practice. In three case-studies, probabilistic methods are adapted for applications to SHM signals, including semisupervised learning, active learning, and multitask learning

Biodiversity means business: Reframing global biodiversity goals for the private sector

The Convention on Biological Diversity strategic goals direct the conservation and sustainable use of biodiversity from global to local scales. Yet business’ role in meeting the strategic goals and being accountable for their impacts and dependencies on biodiversity are still not fully and coherently outlined. We demonstrate how business actions can contribute to the strategic goals using 10 publicly available case studies, covering businesses of various sizes, from multiple sectors, operating in different contexts. The case studies show some businesses already contribute to meeting biodiversity goals, often without realizing. We consider the drivers of business engagement with biodiversity; problems in interpreting the scale of impacts through corporate reporting; the implications for changing the way businesses engage with biodiversity goals; and how businesses could contribute more under the post‐2020 framework for biodiversity. We call for increased business accountability for nature and that all in conservation—policymakers, practitioners, researchers, communities—do more to connect businesses with the strategic goals. Clearer business roles and responsibilities within international targets form a critical step toward the fundamental systems‐level change required to reverse biodiversity loss

A hepatitis C virus DNA vaccine encoding a secreted, oligomerized form of envelope proteins is highly immunogenic and elicits neutralizing antibodies in vaccinated mice

Hepatitis C virus (HCV) persistently infects approximately 71 million people globally. To prevent infection a vaccine which elicits neutralizing antibodies against the virus envelope proteins (E1/E2) which are required for entry into host cells is desirable. DNA vaccines are cost-effective to manufacture globally and despite recent landmark studies highlighting the therapeutic efficacy of DNA vaccines in humans against cervical cancer, DNA vaccines encoding E1/E2 developed thus far are poorly immunogenic. We now report a novel and highly immunogenic DNA vaccination strategy that incorporates secreted E1 and E2 (sE1 and sE2) into oligomers by fusion with the oligomerization domain of the C4b-binding protein, IMX313P. The FDA approved plasmid, pVax, was used to encode sE1, sE2, or sE1E2 with or without IMX313P, and intradermal prime-boost vaccination studies in BALB/c mice showed that vaccines encoding IMX313P were the most effective in eliciting humoral and cell-mediated immunity against the envelope proteins. Further boosting with recombinant E1E2 proteins but not DNA nor virus-like particles (VLPs) expressing E1E2 increased the immunogenicity of the DNA prime-boost regimen. Nevertheless, the antibodies generated by the homologous DNA prime-boost vaccinations more effectively inhibited the binding of VLPs to target cells and neutralized transduction with HCV pseudoparticles (HCVpp) derived from different genotypes including genotypes 1, 2, 3, 4, 5, and 6. This report provides the first evidence that IMX313P can be used as an adjuvant for E1/E2-based DNA vaccines and represents a translatable approach for the development of a HCV DNA vaccine.Makutiro Ghislain Masavuli, Danushka K. Wijesundara, Alexander Underwood, Dale Christiansen, Linda Earnest-Silveira, Rowena Bull, Joseph Torresi, Eric J. Gowans and Branka Grubor-Bau