Lensed: a code for the forward reconstruction of lenses and sources from strong lensing observations

Robust modelling of strong lensing systems is fundamental to exploit the information they contain about the distribution of matter in galaxies and clusters. In this work, we present Lensed, a new code which performs forward parametric modelling of strong lenses. Lensed takes advantage of a massively parallel ray-tracing kernel to perform the necessary calculations on a modern graphics processing unit (GPU). This makes the precise rendering of the background lensed sources much faster, and allows the simultaneous optimisation of tens of parameters for the selected model. With a single run, the code is able to obtain the full posterior probability distribution for the lens light, the mass distribution and the background source at the same time. Lensed is first tested on mock images which reproduce realistic space-based observations of lensing systems. In this way, we show that it is able to recover unbiased estimates of the lens parameters, even when the sources do not follow exactly the assumed model. Then, we apply it to a subsample of the SLACS lenses, in order to demonstrate its use on real data. The results generally agree with the literature, and highlight the flexibility and robustness of the algorithm.Comment: v2: major revision; accepted by MNRAS; lens reconstruction code available at http://glenco.github.io/lensed

Zooming into the Cosmic Horseshoe: new insights on the lens profile and the source shape

The gravitational lens SDSS J1148+1930, also known as the Cosmic Horseshoe, is one of the biggest and of the most detailed Einstein rings ever observed. We use the forward reconstruction method implemented in the lens fitting code Lensed to investigate with great detail the properties of the lens and of the background source. We model the lens with different mass distributions, focusing in particular on the determination of the slope of the dark matter component. The inherent degeneracy between the lens slope and the source size can be broken when we can isolate separate components of each lensed image, as in this case. For an elliptical power law model, $\kappa(r) \sim r^{-t}$, the results favour a flatter-than-isothermal slope with a maximum-likelihood value t = 0.08. Instead, when we consider the contribution of the baryonic matter separately, the maximum-likelihood value of the slope of the dark matter component is t = 0.31 or t = 0.44, depending on the assumed Initial Mass Function. We discuss the origin of this result by analysing in detail how the images and the sources change when the slope t changes. We also demonstrate that these slope values at the Einstein radius are not inconsistent with recent forecast from the theory of structure formation in the LambdaCDM model.Comment: 13 pages, 9 figures, accepted for publication in MNRA

Charged Black Hole Remnants at the LHC

We investigate possible signatures of long-lived (or stable) charged black holes at the Large Hadron Collider. In particular, we find that black hole remnants are characterised by quite low speed. Due to this fact, the charged remnants could, in some cases, be very clearly distinguished from the background events, exploiting dE/dX measurements. We also compare the estimate energy released by such remnants with that of typical Standard Model particles, using the Bethe-Bloch formula.Comment: 12 pages, 9 figures, minor changes to match the accepted version to appear in EPJ

A PCA-based automated finder for galaxy-scale strong lenses

We present an algorithm using Principal Component Analysis (PCA) to subtract galaxies from imaging data, and also two algorithms to find strong, galaxy-scale gravitational lenses in the resulting residual image. The combined method is optimized to find full or partial Einstein rings. Starting from a pre-selection of potential massive galaxies, we first perform a PCA to build a set of basis vectors. The galaxy images are reconstructed using the PCA basis and subtracted from the data. We then filter the residual image with two different methods. The first uses a curvelet (curved wavelets) filter of the residual images to enhance any curved/ring feature. The resulting image is transformed in polar coordinates, centered on the lens galaxy center. In these coordinates, a ring is turned into a line, allowing us to detect very faint rings by taking advantage of the integrated signal-to-noise in the ring (a line in polar coordinates). The second way of analysing the PCA-subtracted images identifies structures in the residual images and assesses whether they are lensed images according to their orientation, multiplicity and elongation. We apply the two methods to a sample of simulated Einstein rings, as they would be observed with the ESA Euclid satellite in the VIS band. The polar coordinates transform allows us to reach a completeness of 90% and a purity of 86%, as soon as the signal-to-noise integrated in the ring is higher than 30, and almost independent of the size of the Einstein ring. Finally, we show with real data that our PCA-based galaxy subtraction scheme performs better than traditional subtraction based on model fitting to the data. Our algorithm can be developed and improved further using machine learning and dictionary learning methods, which would extend the capabilities of the method to more complex and diverse galaxy shapes

Chrysotile detection in soils with proximal hyperspectral sensing and chemometrics

In this work the authors present an innovative methodology, based on proximal hyperspectral sensing and chemometric techniques, aimed at detecting asbestos containing soils. Short Wave InfraRed (SWIR) reflectance spectra of reference samples containing known chrysotile fractions were collected in laboratory. Since the identification of asbestos containing soils depends on the contaminant mass percentage (weight/weight), two supervised multivariate data projection methods were evaluated for asbestos concentration prediction. The first results are reported here, together with advantages and limits of the analytical methods. Orthogonal Partial Least Squares (PLS) regression showed the lowest error in prediction and the highest coefficient of determination in prediction. This technique would support screening activities frequently conducted during environmental assessment and remediation projects

Pulmonary tuberculosis followed by sarcoidosis in an HIV-infected patient: a case report and a simplified diagnostic flowchart for diagnosis and treatment of sarcoidosis

The diagnosis of sarcoidosis in a patient living with HIV infection is an uncommon event and a challenge for clinicians. Clinical manifestations are variable and fluctuating depending to adherence to ARV therapy and to the level of CD4 count. We analyze here one chronic case in which sarcoidosis appeared clinically two years after pulmonary tuberculosis. The course of the disease was influenced and prolonged by frequent interruptions of antiretroviral therapy. Moreover the diagnosis and the decision to treat have been delayed by the need of exclusion of other pathologies, principally tuberculosis reactivation/reinfection, other mycobacterial diseases, hematologic malignancies. We propose a simplified flowchart for diagnosis and follow up of sarcoidosis, which may also be applied to patients with HIV infection. Diagnosis of latent tuberculosis infection (LTBI) may be difficult in these patients, because the immunological paradox of sarcoidosis. For this reason, following exclusion of active tuberculosis, we advise to submit all sarcoidosis patients to IPT (isoniazid preventive therapy), when immunosuppressive therapy is started

Workers’ exposure assessment during the production of graphene nanoplatelets in r&d laboratory

Widespread production and use of engineered nanomaterials in industrial and research settings raise concerns about their health impact in the workplace. In the last years, graphene-based nanomaterials have gained particular interest in many application fields. Among them, graphene nanoplatelets (GNPs) showed superior electrical, optical and thermal properties, low-cost and availability. Few and conflicting results have been reported about toxicity and potential effects on workers’ health, during the production and handling of these nanostructures. Due to this lack of knowledge, systematic approaches are needed to assess risks and quantify workers’ exposure to GNPs. This work applies a multi-metric approach to assess workers’ exposure during the production of GNPs, based on the Organization for Economic Cooperation and Development (OECD) methodology by integrating real-time measurements and personal sampling. In particular, we analyzed the particle number concentration, the average diameter and the lung deposited surface area of airborne nanoparticles during the production process conducted by thermal exfoliation in two different ways, compared to the background. These results have been integrated by electron microscopic and spectroscopic analysis on the filters sampled by personal impactors. The study identifies the process phases potentially at risk for workers and reports quantitative information about the parameters that may influence the exposure in order to propose recommendations for a safer design of GNPs production process

Use of compositional analysis to distinguish farmed and wild gilthead seabream (Sparus aurata)

Recent food scares have emphasized the need for traceability in the food chain. This is particularly true in the fish sector, where a large difference in the final price between wild and farmed fish and even between farmed fish reared in different countries exists. So for these commercial and hygienic reasons it is very important to find useful tools for the characterization of quality of fish and for the differentiation of fish from different production methods and from different countries, in accordance with EC Regulation No. 2065/2001 and Italian Ministry of Agriculture Decree No. 27.03.02, that allow retail trade of fishery and aquaculture products only against the indication of the official commercial name, the method of production and the geographical origin of fish (Moretti et al., 2003)

Emergency laparotomy for misdiagnosed biliary cystadenoma originating from caudate lobe

BACKGROUND: Biliary cystadenoma is a rare benign neoplasm, which is often misdiagnosed for a hepatic abscess or a hydatid cyst that tends to recur and is at risk for progression to malignant neoplasm. CASE PRESENTATION: This case describes a 30-year-old woman admitted to our institution in an emergency setting. The patient was originally misdiagnosed as affected by a hepatic hydatid cyst at another hospital, and then emergently treated at our Institution for severe abdominal pain. Histologic evaluation of the cyst showed that it was a biliary cystadenoma and, therefore, the patient underwent a hepatic resection in order to completely remove the lesion. CONCLUSION: Complete excision of any suspicious hepatic cystic lesion remains the best method for diagnosis and treatment of cystadenoma. Incomplete excision of most biliary cystadenoma results in a higher rate of recurrence and the risk of malignant transformation. We report this case to elucidate the clinical presentation, preoperative evaluation, and surgical treatment of these rare lesions

SEAGLE--II: Constraints on feedback models in galaxy formation from massive early type strong lens galaxies

We use nine different galaxy formation scenarios in ten cosmological simulation boxes from the EAGLE suite of {\Lambda}CDM hydrodynamical simulations to assess the impact of feedback mechanisms in galaxy formation and compare these to observed strong gravitational lenses. To compare observations with simulations, we create strong lenses with $M_\star$ > $10^{11}$ $M_\odot$ with the appropriate resolution and noise level, and model them with an elliptical power-law mass model to constrain their total mass density slope. We also obtain the mass-size relation of the simulated lens-galaxy sample. We find significant variation in the total mass density slope at the Einstein radius and in the projected stellar mass-size relation, mainly due to different implementations of stellar and AGN feedback. We find that for lens selected galaxies, models with either too weak or too strong stellar and/or AGN feedback fail to explain the distribution of observed mass-density slopes, with the counter-intuitive trend that increasing the feedback steepens the mass density slope around the Einstein radius ($\approx$ 3-10 kpc). Models in which stellar feedback becomes inefficient at high gas densities, or weaker AGN feedback with a higher duty cycle, produce strong lenses with total mass density slopes close to isothermal (i.e. -d log({\rho})/d log(r) $\approx$ 2.0) and slope distributions statistically agreeing with observed strong lens galaxies in SLACS and BELLS. Agreement is only slightly worse with the more heterogeneous SL2S lens galaxy sample. Observations of strong-lens selected galaxies thus appear to favor models with relatively weak feedback in massive galaxies.Comment: re-submitted to MNRAS, bug fixed, conclusions unchanged, updated appendices and references, 23 pages, 10 Figures, 6 Table