We present a comparison between the performance of a selection of source finders (SFs) using a new software tool called Hydra. The companion paper, Paper I, introduced the Hydra tool and demonstrated its performance using simulated data. Here we apply Hydra to assess the performance of different source finders by analysing real observational data taken from the Evolutionary Map of the Universe (EMU) Pilot Survey. EMU is a wide-field radio continuum survey whose primary goal is to make a deep ($20\mu$Jy/beam RMS noise), intermediate angular resolution ($15^{\prime\prime}$), 1 GHz survey of the entire sky south of $+30^{\circ}$ declination, and expecting to detect and catalogue up to 40 million sources. With the main EMU survey it is highly desirable to understand the performance of radio image SF software and to identify an approach that optimises source detection capabilities. Hydra has been developed to refine this process, as well as to deliver a range of metrics and source finding data products from multiple SFs. We present the performance of the five SFs tested here in terms of their completeness and reliability statistics, their flux density and source size measurements, and an exploration of case studies to highlight finder-specific limitations.

The latest generation of radio surveys are now producing sky survey images containing many millions of radio sources. In this context it is highly desirable to understand the performance of radio image source finder (SF) software and to identify an approach that optimises source detection capabilities. We have created Hydra to be an extensible multi-SF and cataloguing tool that can be used to compare and evaluate different SFs. Hydra, which currently includes the SFs Aegean, Caesar, ProFound, PyBDSF, and Selavy, provides for the addition of new SFs through containerisation and configuration files. The SF input RMS noise and island parameters are optimised to a 90% ‘percentage real detections’ threshold (calculated from the difference between detections in the real and inverted images), to enable comparison between SFs. Hydra provides completeness and reliability diagnostics through observed-deep ($\mathcal{D}$) and generated-shallow ($\mathcal{S}$) images, as well as other statistics. In addition, it has a visual inspection tool for comparing residual images through various selection filters, such as S/N bins in completeness or reliability. The tool allows the user to easily compare and evaluate different SFs in order to choose their desired SF, or a combination thereof. This paper is part one of a two part series. In this paper we introduce the Hydra software suite and validate its $\mathcal{D/S}$ metrics using simulated data. The companion paper demonstrates the utility of Hydra by comparing the performance of SFs using both simulated and real images.

Microscopic examination of blood smears remains the gold standard for laboratory inspection and diagnosis of malaria. Smear inspection is, however, time-consuming and dependent on trained microscopists with results varying in accuracy. We sought to develop an automated image analysis method to improve accuracy and standardization of smear inspection that retains capacity for expert confirmation and image archiving. Here, we present a machine learning method that achieves red blood cell (RBC) detection, differentiation between infected/uninfected cells, and parasite life stage categorization from unprocessed, heterogeneous smear images. Based on a pretrained Faster Region-Based Convolutional Neural Networks (R-CNN) model for RBC detection, our model performs accurately, with an average precision of 0.99 at an intersection-over-union threshold of 0.5. Application of a residual neural network-50 model to infected cells also performs accurately, with an area under the receiver operating characteristic curve of 0.98. Finally, combining our method with a regression model successfully recapitulates intraerythrocytic developmental cycle with accurate lifecycle stage categorization. Combined with a mobile-friendly web-based interface, called PlasmoCount, our method permits rapid navigation through and review of results for quality assurance. By standardizing assessment of Giemsa smears, our method markedly improves inspection reproducibility and presents a realistic route to both routine lab and future field-based automated malaria diagnosis.

The objective was to compare the performance of the updated Charlson comorbidity index (uCCI) and classical CCI (cCCI) in predicting 30-day mortality in patients with Staphylococcus aureus bacteraemia (SAB). All cases of SAB in patients aged ⩾14 years identified at the Microbiology Unit were included prospectively and followed. Comorbidity was evaluated using the cCCI and uCCI. Relevant variables associated with SAB-related mortality, along with cCCI or uCCI scores, were entered into multivariate logistic regression models. Global model fit, model calibration and predictive validity of each model were evaluated and compared. In total, 257 episodes of SAB in 239 patients were included (mean age 74 years; 65% were male). The mean cCCI and uCCI scores were 3.6 (standard deviation, 2.4) and 2.9 (2.3), respectively; 161 (63%) cases had cCCI score ⩾3 and 89 (35%) cases had uCCI score ⩾4. Sixty-five (25%) patients died within 30 days. The cCCI score was not related to mortality in any model, but uCCI score ⩾4 was an independent factor of 30-day mortality (odds ratio, 1.98; 95% confidence interval, 1.05–3.74). The uCCI is a more up-to-date, refined and parsimonious prognostic mortality score than the cCCI; it may thus serve better than the latter in the identification of patients with SAB with worse prognoses.

An obesity paradox has been proposed in many conditions including HIV. Studies conducted to investigate obesity and its effect on HIV disease progression have been inconclusive and are lacking for African settings. This study investigated the relationship between overweight/obesity (BMI≥25 kg/m2) and HIV disease progression in HIV+ asymptomatic adults not on antiretroviral treatment (ART) in Botswana over 18 months. A cohort study in asymptomatic, ART-naïve, HIV+ adults included 217 participants, 139 with BMI of 18·0–24·9 kg/m2 and seventy-eight participants with BMI≥25 kg/m2. The primary outcome was time to event (≥25 % decrease in cluster of differentiation 4 (CD4) cell count) during 18 months of follow-up; secondary outcomes were time to event of CD4 cell count<250 cells/µl and AIDS-defining conditions. Proportional survival hazard models were used to compare hazard ratios (HR) on time to events of HIV disease progression over 18 months. Higher baseline BMI was associated with significantly lower risk of an AIDS-defining condition during the follow-up (HR 0·218; 95 % CI 0·068, 0·701; P=0·011). Higher fat mass at baseline was also significantly associated with decreased risk of AIDS-defining conditions during the follow-up (HR 0·855; 95 % CI 0·741, 0·987; P=0·033) and the combined outcome of having CD4 cell count≤250/µl and AIDS-defining conditions, whichever occurred earlier (HR 0·918; 95 % CI 0·847, 0·994; P=0·036). All models were adjusted for covariates. Higher BMI and fat mass among the HIV-infected, ART-naïve participants were associated with slower disease progression. Mechanistic research is needed to evaluate the association between BMI, fat mass and HIV disease progression.

From the photoinduced transport of energy that accompanies photosynthesis to the transcontinental transmission of optical data that enable the Internet, our world relies and thrives on optical signals. To highlight the importance of optics to society, the United Nations designated 2015 as “The International Year of Light and Light-based Technologies.” Although conventional optical technologies are limited by diffraction, plasmons—collective oscillations of free electrons in a conductor—allow optical signals to be tailored with nanoscale precision. Following decades of fundamental research, several plasmonic technologies have now emerged on the market, and numerous industrial breakthroughs are imminent. This article highlights recent industrially relevant advances in plasmonics, including plasmonic materials and devices for energy; for medical sensing, imaging, and therapeutics; and for information technology. Some of the most exciting industrial applications include solar-driven water purifiers, cell phone Raman spectrometers, high-density holographic displays, photothermal cancer therapeutics, and nanophotonic integrated circuits. We describe the fundamental scientific concepts behind these and related technologies, as well as the successes and challenges associated with technology transfer.

We have obtained long slit spectra of 3C 67 and 3C 277.1 with the HST/STIS spectrograph. We present our preliminary results on the diagnostic emission line ratios along the radio source axes in 3C 67 and 3C 277.1.

We have obtained HST/STIS long slit spectroscopy of the aligned emission line nebulae in three compact steep spectrum (CSS) radio sources — 3C 67, 3C 277.1, and 3C 303.1. We find systematic offsets (˜300–500 kms) of the emission line velocities on one or both sides of the radio sources. We also see evidence for broad lines (FWHM ˜500 kms) and complex emission line profiles. In 3C 303.1 the data are consistent with multiple components and possibly split lines. The amplitude of the velocity variations is not so large as to exclude gravitationally-induced motions. However, the complex kinematics, the lack of a signature of Keplerian rotation, and the association of the velocity variations with the radio lobes are consistent with the observed ˜300–500 kms velocities being driven by the expansion of the radio source. Acceleration of the clouds by the bow shock is plausible given the estimated densities in the clouds and the velocities observed in the much smaller compact symmetric objects and with expansion velocities estimated from spectral ageing. This conclusion is unchanged if we consider the scenario in which the cloud acceleration is dominated by the post bow shock flow.

Sets of microsatellites extracted from both a genomic library (gSSRs) and from expressed sequence tag sequence (eSSRs), and single nucleotide polymorphisms (SNPs) were applied to assess the levels of genetic diversity in a sample of 70 barley accessions, originating from 28 countries in Asia, Africa, the Middle East and Europe. The eSSR assays detected a mean of 9.5 alleles per locus, and the gSSRs only 5.7 alleles per locus, but the polymorphism information content values for the two assay types were indistinguishable. Strong and statistically significant correlations were observed between the eSSR and gSSR (r = 0.86, P < 0.05), the eSSR and SNP (r = 0.74, P < 0.05) and the gSSR and SNP genotypes (r = 0.67, P < 0.05). Accessions originating from the Middle East and Asia had the highest levels of genetic diversity. Pairwise genetic similarity ranged from 0.16 to 0.87 (mean 0.43), indicating that the sample was genetically diverse. When clustered on the basis of genotype, Asian and African accessions tended to be grouped together, but those originating from the Middle East were not concentrated in any particular cluster.

Drought is one of the major factors limiting crop production worldwide. Dry areas are a much less homogeneous population of target environments than areas with high and reliable rainfall. In this paper we argue that a decentralized participatory plant breeding programme can address the complexity of dry areas, characterized by high and repeatable genotype × locations and genotype × years within locations interactions, more efficiently and effectively than a centralized non-participatory plant breeding programme. This is because varieties can be tailored not only to the multitude of target environments typical of dry areas, but also to diverse clients needs. In addition, varieties can be delivered in a shorter time and with a higher probability of adoption. Decentralized participatory plant breeding also has beneficial effects on biodiversity because selection is for specific adaptation rather than for broad spatial adaptation. The paper gives examples of methodological aspects including the modes of farmer selection, the precision of the trials, the efficiency of selection, the response to selection, the role of the type of germplasm and the role of molecular breeding in a participatory breeding programme. The paper gives the example of drought-resistant barley lines identified through extensive field testing and selection in a decentralized participatory breeding programme, and concludes that this type of plant breeding may be better targeted, more relevant and more appropriate for poor farmers in marginal areas.

The RAPD–PCR technique was used to study genetic variation within and among geographical populations of the Hessian fly, Mayetiola destructor (Say), from Morocco and Syria, associated with the fly’s ability to overcome resistance in three wheat cultivars containing H5, H13 and H22 resistance genes. Variation was detected both for the level of susceptibility of the cultivars and RAPD profiles of M. destructor populations. By the use of RAPD–PCR, high genetic variability was detected among individuals and populations of M. destructorwithin and between areas separated geographically. The DNA fingerprints of populations of M. destructor were area-specific with Nei’s measures of genetic distance ranging from 0.156 (between Abda and Beni Mellal, Morocco) to 1.977 (between Marchouch, Morocco and Lattakia, Syria). Cluster analysis of the genetic distances among the populations, identified the Syrian population as an outlier. A highly significant correlation (r = 0.81) observed between the genetic and geographic distances among the populations, provided genetic support for dispersal of the fly from its presumed origin in West Asia to Morocco.