• European Marine Science
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Background: In 1999, the WHO estimated that one-third of the world's population had latent tuberculosis (LTBI) which was recently updated to one-fourth. However, this is still based on controversial assumptions in combination with tuberculin skin test (TST) surveys. Interferon-gamma release assays (IGRAs) with a higher specificity than TST have since been widely implemented, but never used to estimate the global LTBI prevalence. Methods: We conducted a systematic review and meta-analysis of LTBI estimates based on IGRA and TST results published between 2005 and 2018. Regional and global estimates of LTBI prevalence were calculated. Stratification was performed for low, intermediate and high TB incidence countries and a pooled estimate for each area was calculated using a random effects model. Findings: Among 3280 studies screened, we included 88 studies from 36 countries with 41 IGRA (n=67 167) and 67 TST estimates (n=284 644). The global prevalence of LTBI was 24.8% (95% CI: 19.7-30.0%) based on IGRA and 21.2% (95% CI: 17.9-24.4%) and 24.1% (95% CI: 19.7-29.9%) based on a 5 and 10 mm TST cut-offs, respectively. The prevalence estimates correlated significantly to WHO incidence rates. Interpretation: In the first study of the global prevalence of LTBI derived from both IGRA and TST, we found that one-fourth of the world's population is infected. This is of relevance as both tests, although imperfect, are used to identify individuals for preventive therapy. Enhanced efforts are needed to target the large pool of latently infected as they continuously constitutes a source of potential active TB. Funding Statement: This study was supported by NovoNordisk Foundation (NNF15OC0018034; CW), the Swedish Research Council (201602043; TS) and the Swedish Heart and Lung Foundation (20150236; TS). Declaration of Interests: The authors declare no competing interests.

This paper describes the utility of developing marine system models to aid the efficient and regulatory compliant development of offshore carbon storage, maximising containment assurance by well-planned monitoring strategies. Using examples from several model systems, we show that marine models allow us to characterize the chemical perturbations arising from hypothetical release scenarios whilst concurrently quantifying the natural variability of the system with respect to the same chemical signatures. Consequently models can identify a range of potential leakage anomaly detection criteria, identifying the most sensitive discriminators applicable to a given site or season. Further, using models as in-silico testbeds we can devise the most cost-efficient deployment of sensors to maximise detection of CO2 leakage. Modelling studies can also contribute to the required risk assessments, by quantifying potential impact from hypothetical release scenarios. Finally, given this demonstrable potential we discuss the challenges to ensuring model systems are available, fit for purpose and transferable to CCS operations across the globe.

Abstract Women are less likely to enroll in selective or scientific courses, applying for promotions and are particularly underrepresented in both middle and top positions in the STEM field. Quota are often advocated as an instrument to reduce this gender gap, but it remains unclear at what step of the career ladder they more effectively foster women's reaching the top. Many factors may affect quota's success or failure, such as how they would in turn affect teamwork and trust between members within organizations or coordination in applying for promotions. In this paper, by means of a laboratory experiment implementing a two-stage tournament, we evaluate the impact of three different interventions in affecting individual decision to climb the career ladder, abstracting away from other possible confounding factors. We find that, compared with no intervention, a gender quota introduced in the initial stage of competition was ineffective in encouraging women to compete for the top; quotas introduced in the final stage of competition or at both stages increased women's willingness to compete for the top, without distorting the performance of the winners.

Abstract We analyse models for panel data that arise in risk allocation problems, when a given set of sources are the cause of an aggregate risk value. We focus on the modelling and forecasting of proportional contributions to risk over time. Compositional data methods are proposed and the time-series regression is flexible to incorporate external information from other variables. We guarantee that projected proportional contributions add up to 100%, and we introduce a method to generate confidence regions with the same restriction. An illustration is provided for risk capital allocations.

Based on high-throughput density functional theory calculations, we investigated the effects of light interstitial H, B, C, and N atoms on the magnetic properties of cubic Heusler alloys, with the aim to design new rare-earth free permanent magnets. It is observed that the interstitial atoms induce significant tetragonal distortions, leading to 32 candidates with large ($>$ 0.4 MJ/m$^3$) uniaxial magneto-crystalline anisotropy energies (MAEs) and 10 cases with large in-plane MAEs. Detailed analysis following the the perturbation theory and chemical bonding reveals the strong MAE originates from the local crystalline distortions and thus the changes of the chemical bonding around the interstitials. This provides a valuable way to tailor the MAEs to obtain competitive permanent magnets, filling the gap between high performance Sm-Co/Nd-Fe-B and widely used ferrite/AlNiCo materials. 4 gigures

SummaryTrade restrictions for many endangered elasmobranch species exist to disincentivise their exploitation and curb their declines. However, the variety of products and the complexity of import/export routes make trade monitoring challenging. We investigate the use of a portable, universal, DNA-based tool which would greatly facilitatein-situmonitoring. We collected shark and ray samples across the Island of Java, Indonesia, and selected 28 species (including 22 CITES-listed species) commonly encountered in landing sites and export hubs to test a recently developed real-time PCR single-assay originally developed for screening bony fish. We employed a deep learning algorithm to recognize species based on DNA melt-curve signatures. By combining visual and machine learning assignment methods, we distinguished 25 out of 28 species, 20 of which were CITES-listed. With further refinement, this method can provide a practical tool for monitoring elasmobranch trade worldwide, without the need for a lab or the bespoke design of species-specific assays.HighlightsWe applied a portable, universal, closed-tube DNA barcoding approach originally developed for bony fishes to distinguish between shark and ray species traded in Indonesia.We built a deep machine learning model to automatically assign species from the qPCR fluorescence spectra produced by two barcodesThe model achieved 79.41% accuracy for classifying 28 elasmobranch species, despite the barcode regions being designed for teleost speciesThis tool can serve as a potent single-assayin-situdiagnostic tool to regulate trade operations and it will be significantly enhanced by further optimisation of the barcode regions to fit elasmobranch DNA sequence variation

Ghana Alternative Market was set up for SMEs and startups, who usually did not meet the requirements of the main stock exchange, to be listed and have access to equity financing. However, it has not been successful at getting SMEs listed, recording only 4 listings since its inception. This motivated the study to access factors that affect SMEs listing on the Ghana Alternative Market. Using a quantitative approach, we sampled 50 SMEs, 21 Brokers and 3 SMEs already listed on the GAX. We found that over half of the SMEs had some information about the GAX. However, their knowledge with regards to the benefits of listing on the GAX as well as what they require to list is very limited. Also, the findings revealed that SMEs had a difficulty accessing stock market operators as well as stock market information. LDMs showed commitment to the development of the GAX, however their efforts at getting SMEs on board has been passive. SMEs sampled also showed that they are willing to swap from alternative funding sources to the GAX when their concerns are addressed. They also stated that the relevant stakeholders should provide more information and education about the GAX in order to make it a viable option for them.