Abstract
The fibre optic current sensor demonstrated here uses the intrinsic temperature and wavelength dependence of the Verdet constant of a terbium gallium garnet (TGG) magneto-optic material and the two micro-optic linear polarizers attached, to simultaneously extract the values of temperature and the optical Faraday rotation (induced by the presence of the magnetic field due an electric current on a conductor) without any extra optical component attached to the optical sensor head. The simultaneous measurement is achieved by illuminating the sensor head with a broadband optical source and by careful signal processing of the originated channelled-spectrum, compensate the sensor's temperature dependence.

Abstract
Reducing the costs associated with health care services is on the agenda, if possible, improving their quality. The Lean management approach has proven to provide good results in creating value and reducing waste. This paper is based on an exploratory case study in the logistic operations of a Northern Portuguese hospital, focusing on the delivery plans of products needed between the central warehouse and the internal medicine ward. Using PDCA improvement cycles and other lean tools, this study analyzed the actual delivery system, identified inefficiencies, and proposed and evaluated some solutions. The aim was to address different types of waste, such as the time the ward head nurse spent to launch orders and perform the reception/arrangement of the products or the excess of products leaving the central warehouse. Although a daily delivery with a fixed stock level seems to be a good delivery system for a large group of products, the recorded or possible failures have led us to devise an optimization model to improve the deliveries. The preliminary results suggest that a weekly plan with a daily delivery of products (to be repeated every week) is even more optimal, not only because it relieves the head nurse of logistical tasks but also because it takes into account the units of products per package. Although this model can be generalized to other nursing wards, some limitations are addressed, namely its non (daily) standardization, leading to some complexity in its handling by the logistic central warehouse operators.

Abstract
In this work, we targeted the search engine of a sports-related website that presented an opportunity for search result quality improvement. We reframed the engine as a Federated Search instance, where each collection represented a searchable entity type within the system, using Apache Solr for querying each resource and a Python Flask server to merge results. We extend previous work on individual search term weighing, making use of past search terms as a relevance indicator for user selected documents. To incorporate term weights we define four strategies combining two binary variables: integration with default relevance (linear scaling or linear combination) and search term frequency (raw value or log-smoothed). To evaluate our solution, we extracted two query sets from search logs: one with frequently submitted queries, and another with ambiguous result access patterns. We used click-through information as a relevance proxy and tried to mitigate its limitations by evaluating under distinct IR metrics, including MRR, MAP and NDCG. Moreover, we also measured Spearman rank correlation coefficients to test similarities between produced rankings and reference orderings according to user access patterns. Results show consistency across all metrics in both sets. Previous search terms were key to obtaining a higher effectiveness, with runs that used pure search term frequency performing best. Compared to the baseline, our best strategies were able to maintain quality on frequent queries and improve retrieval effectiveness on ambiguous queries, with up to six percentage points better performance on most metrics.

Abstract
Modelling of material appearance from reflectance measurements has become increasingly prevalent due to the development of novel methodologies in Computer Graphics. In the last few years, some advances have been made in measuring the light-material interactions, by employing goniometers/reflectometers under specific laboratory's constraints. A wide range of applications benefit from data-driven appearance modelling techniques and material databases to create photorealistic scenarios and physically based simulations. However, important limitations arise from the current material scanning process, mostly related to the high diversity of existing materials in the real-world, the tedious process for material scanning and the spectral characterisation behaviour. Consequently, new approaches are required both for the automatic material acquisition process and for the generation of measured material databases. In this study, a novel approach for material appearance acquisition using hyperspectral data is proposed. A dense 3D point cloud filled with spectral data was generated from the images obtained by an unmanned aerial vehicle (UAV) equipped with an RGB camera and a hyperspectral sensor. The observed hyperspectral signatures were used to recognise natural and artificial materials in the 3D point cloud according to spectral similarity. Then, a parametrisation of Bidirectional Reflectance Distribution Function (BRDF) was carried out by sampling the BRDF space for each material. Consequently, each material is characterised by multiple samples with different incoming and outgoing angles. Finally, an analysis of BRDF sample completeness is performed considering four sunlight positions and 16x16 resolution for each material. The results demonstrated the capability of the used technology and the effectiveness of our method to be used in applications such as spectral rendering and real-word material acquisition and classification. (C) 2021 The Authors. Published by Elsevier Ltd.

Abstract
We introduce an evolutionary dynamical model for corruption in a democratic state describing the interactions between citizens, government and officials, where the voting power of the citizens is the main mechanism to control corruption. Three main scenarios for the evolution of corruption emerge depending on the efficiency of the institutions and the social, political, and economic characteristics of the State. Efficient institutions can create a corruption intolerant self-reinforcing mechanism. The lack of political choices, weaknesses of institutions and vote buying can create a self-reinforcing mechanism of corruption. The ambition of the rulers can induce high levels of corruption that can be fought by the voting power of the citizens creating corruption cycles.

Abstract