Portugueses Gaúchos: socio-political transnationalism, integration and identities in the River Plate Region

Através da análise de entrevistas com emigrantes portugueses e os seus descendentes na região platina, o artigo explora as relações entre integração e participação em associações de emigrantes, e como elas se inter-relacionam com a identidade colectiva na sociedade de recepção. Examinamos o papel das associações de emigrantes na construção e reforço dos símbolos, referências e identidades nacionais, e como simultaneamente facilitam a integração. Sugerimos que a activação de identidades do país de origem não tem efeitos etnicizantes; pelo contrário, funciona como recurso efectivo da integração, promovendo as redes sociais abertas

Do fado ao tango: a emigração portuguesa para a Região Platina

É conhecida a importância da emigração espanhola e italiana na constituição das sociedades nacionais do cone sul da América Latina; muito menos se sabe sobre a emigração portuguesa, especialmente nos países de fala hispânica. Este artigo explora as dinâmicas migratórias e as características dos imigrantes portugueses na região do Rio da Prata, área que abarca a República Oriental do Uruguai, as províncias do litoral argentino e os estados do Sul do Brasil. Após uma introdução em que se descreve a singularidade histórica e geográfica da região, apresenta-se uma análise sucinta dos processos migratórios que a foram povoando entre meados do século XIX e o final do século XX. Identificam-se políticas migratórias na origem e no destino e periodizam-se os fluxos migratórios provenientes de Portugal. Em seguida, apresentam-se alguns elementos de caracterização dos vários núcleos de imigrantes portugueses e luso-descendentes, bem como as respectivas dinâmicas associativas. O artigo conclui com uma série de reflexões comparativas

Motion Planning of an Innovative Serial Robot for Energy Consumption Reduction with "On Fly" Pieces Grasping

The following study deals with the on-line motion planning of an innovative SCARA like robot with unlimited joint rotations. The application field is the robotic interception of moving objects randomly distributed on a conveyor and detected by a vision system. A motion planning algorithm was developed in order to achieve a satisfactory cycle time and energy consumption. The algorithm is based on the evaluation of the inertial actions arisen in the robot structure during the pick and place motions and it aims to keep constant the rotation velocity of the first joint during the motion, the grasping and the discarding phases. Since the algorithm must be applied run time and the number of the reachable pieces can be high, a particular care was dedicated to the computational burden reduction. Subsequently to an analytic study of the kinematical constraints and the criteria definition for the choice of which piece to grasp, a devoted simulation software was developed. The software allows the control and the evaluation of the effects of all the main parameters on the system behavior and a comparison of the cycle time and the energy consumption between the proposed algorithm and a standard point-to-point motion strategy

Quantification of the immune content in neuroblastoma: Deep learning and topological data analysis in digital pathology

We introduce here a novel machine learning (ML) framework to address the issue of the quantitative assessment of the immune content in neuroblastoma (NB) specimens. First, the EUNet, a U-Net with an EfficientNet encoder, is trained to detect lymphocytes on tissue digital slides stained with the CD3 T-cell marker. The training set consists of 3782 images extracted from an original collection of 54 whole slide images (WSIs), manually annotated for a total of 73,751 lymphocytes. Resampling strategies, data augmentation, and transfer learning approaches are adopted to warrant reproducibility and to reduce the risk of overfitting and selection bias. Topological data analysis (TDA) is then used to define activation maps from different layers of the neural network at different stages of the training process, described by persistence diagrams (PD) and Betti curves. TDA is further integrated with the uniform manifold approximation and projection (UMAP) dimensionality reduction and the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm for clustering, by the deep features, the relevant subgroups and structures, across different levels of the neural network. Finally, the recent TwoNN approach is leveraged to study the variation of the intrinsic dimensionality of the U-Net model. As the main task, the proposed pipeline is employed to evaluate the density of lymphocytes over the whole tissue area of the WSIs. The model achieves good results with mean absolute error 3.1 on test set, showing significant agreement between densities estimated by our EUNet model and by trained pathologists, thus indicating the potentialities of a promising new strategy in the quantification of the immune content in NB specimens. Moreover, the UMAP algorithm unveiled interesting patterns compatible with pathological characteristics, also highlighting novel insights into the dynamics of the intrinsic dataset dimensionality at different stages of the training process. All the experiments were run on the Microsoft Azure cloud platform

Species distribution modeling of a new invasive mosquito: a Bayesian approach

Aedes koreicus is a highly invasive mosquito, recognised as zoonotic vector of infectious diseases. Native to East-Asia, it has recently become established in Europe. Only limited data is currently available on its ecology. Using data from LExEM, a project that aims to study Ae. koreicus, we created a presence/absence dataset of Ae. koreicus in Northeast Italy. We enriched this dataset with remotely sensed predictors (MODIS LST and NDWI), land use and topographic information to create a Bayesian SDM. Bayesian data analysis is particularly useful when distribution data of a species is sparse, as is often the case with new invasive species. It allows the inclusion of prior knowledge about the species, and thus provides more robust coefficient estimates. We used both mildly and strongly informed priors derived from the scientific literature. Data acquisition regarding the ecology of invasive species and the modelling of their potential distribution are critical in supporting public health policy. Indeed, the spread of new invasive mosquitoes is of increasing concern due to the risk of outbreaks of exotic vector-borne diseases that they can trigge

An integrated pest control strategy against the Asian tiger mosquito in northern Italy: a case study

BACKGROUND In Europe, Aedes albopictus is an invasive mosquito species known to be a major nuisance as well as a vector of a range of arboviruses. A number of studies have indicated that community participation programmes are an effective pest control tool to reduce mosquito populations. However, few studies have evaluated the effectiveness of a community-based approach in Europe. In this study, we examined two Ae. albopictus control strategies that implemented a community-based approach in northern Italy: one was a partial intervention that included a public education campaign and the larviciding of public spaces, and the other was a full intervention that additionally included a door-to-door campaign. This latter consisted of going door to door actively to educate residents about control measures and deliver larvicide tablets for treating catch basins at home. A site where no intervention measures were carried out was used as a control. RESULTS In the site where a full intervention was carried out, Ae. albopictus egg density was 1.6 times less than at the site that received partial intervention, and 1.9 times less than at the non-intervention site. No significant reduction in egg density was achieved in the partial intervention site. CONCLUSIONS In our study, Ae. albopictus populations were most effectively reduced by larviciding both public and private catch basins. Door-to-door education was effective in convincing residents to apply control measures on their property; however, this method was labour intensive and costly. It may be possible to reduce personnel costs by involving volunteers or using a ‘hot spot’ approac

Laboratory colonization and biological data of Aedes koreicus

Aedes koreicus (Hulecoeteomyia koreica)*, an invasive mosquito species in Europe, occurs in Belgium and in Italy since 2008 and 2011, respectively. While Aedes koreicus is established in a limited area in Belgium, it is currently spreading in the northern Italy. However, the biology and the ecology of this species remain poorly known and yet, further investigations are warranted to assess its invasion capacity in Europe. Moreover, competition with other container breeding mosquitoes, as Aedes albopictus (Stegomyia albopicta)*, has to be tested. Therefore, a laboratory colony of Aedes koreicus has been established with the aim to assess the effect of different biotic and abiotic parameters, such as temperature, diet, larval density and/or presence of a competitive species, on the development of this species under laboratory conditions. At the beginning, we faced several issues to obtain a viable colony such as the absence of free mating and the dessication of eggs. Here, we described the protocol and the different approaches used to improve its rearing including induced copulation technique. Preliminary experiments showed that the developmental time (from first instar larva to adult) of Aedes koreicus females (15.0 ± 0.14 days) was longer than Aedes albopictus females (12.8 ± 0.18 days) at 23 ± 1°C with a 16L:8D photoperiod. For Aedes koreicus, comparison between a rich diet and a poor diet showed that a rich diet decreased the developmental time (15 ± 0.14 vs. 18 ± 0.22 days) and increased the wing length of the females (4.32 ± 0.012 vs. 3.64 ± 0.018 mm). Now, experiments are ongoing to better understanding the biology of Aedes koreicus and to evaluate its competition with Aedes albopictus. *newly named are in parenthesi

An integrated control program against Aedes albopictus in Northern Italy: a case study

Aedes albopictus is a major biting nuisance and a competent vector for many arboviruses. During the last decades, it has colonized almost all the Italian territory. Integrated mosquito management of Ae. albopictus is particularly difficult because many breeding sites are present in private areas. Therefore, public education campaign has become a basic tool to involve homeowners in mosquito control, and door-to-door active education has been recently carried out with success in Spain, the United-States and Thailand. The present study, conducted in the municipality of San Michele all’Adige (Trento) in 2015, aimed to assess a community-based integrated mosquito control strategy including a public education campaign (public meetings and distribution of flyers), larvicide treatments of public catch basins, and door-to-door visits consisting in homeowners’ education, garden inspection and/or delivery of larvicide tabs. All these control measures were implemented in one site (full intervention site), while only public education and public larvicide treatments were implemented in a second site (partial intervention site). A third site was used as control (no intervention site). Biweekly egg counts from 95 ovitraps were modelled by a zero-inflated negative binomial mixed model to evaluate the efficacy of the type of intervention against mosquito abundance. In the full intervention site, 181/297 houses have been visited in June and in September, and 2210 larvicide tabs have been delivered. The total number of private catch basins with mosquito larvae decreased three times between June and September, showing a correct use of larvicide tabs by homeowners. The average egg density in the full intervention site was 2.2 lower as compared to the no intervention site, whereas the average egg densities in the partial and the no intervention sites were similar. Our results confirm that only an integrated mosquito control strategy targeting both public and private areas can be effective against Ae. albopictus

Integrating deep and radiomics features in cancer bioimaging

Almost every clinical specialty will use artificial intelligence in the future. The first area of practical impact is expected to be the rapid and accurate interpretation of image streams such as radiology scans, histo-pathology slides, ophthalmic imaging, and any other bioimaging diagnostic systems, enriched by clinical phenotypes used as outcome labels or additional descriptors. In this study, we introduce a machine learning framework for automatic image interpretation that combines the current pattern recognition approach (“radiomics”) with Deep Learning (DL). As a first application in cancer bioimaging, we apply the framework for prognosis of locoregional recurrence in head and neck squamous cell carcinoma (N=298)from Computed Tomography (CT)and Positron Emission Tomography (PET)imaging. The DL architecture is composed of two parallel cascades of Convolutional Neural Network (CNN)layers merging in a softmax classification layer. The network is first pretrained on head and neck tumor stage diagnosis, then fine-tuned on the prognostic task by internal transfer learning. In parallel, radiomics features (e.g., shape of the tumor mass, texture and pixels intensity statistics)are derived by predefined feature extractors on the CT/PET pairs. We compare and mix deep learning and radiomics features into a unifying classification pipeline (RADLER), where model selection and evaluation are based on a data analysis plan developed in the MAQC initiative for reproducible biomarkers. On the multimodal CT/PET cancer dataset, the mixed deep learning/radiomics approach is more accurate than using only one feature type, or image mode. Further, RADLER significantly improves over published results on the same data