COVID-19 detection using ViT transformer-based approach from Computed Tomography Images

In here, we introduce a novel approach to enhance the accuracy and efficiency of COVID-19 diagnosis using CT images. Leveraging state-of-the-art Transformer models in computer vision, we employed the base ViT Transformer configured for 224x224-sized input images, modifying the output to suit the binary classification task. Notably, input images were resized from the standard CT scan size of 512x512 to match the model's expectations. Our method implements a systematic patient-level prediction strategy, classifying individual CT slices as COVID-19 or non-COVID. To determine the overall diagnosis for each patient, a majority voting approach as well as other thresholding approaches were employed. This method involves evaluating all CT slices for a given patient and assigning the patient the diagnosis that relates to the thresholding for the CT scan. This meticulous patient-level prediction process contributes to the robustness of our solution as it starts from 2D-slices to 3D-patient level. Throughout the evaluation process, our approach resulted in 0.7 macro F1 score on the COV19-CT -DB validation set. To ensure the reliability and effectiveness of our model, we rigorously validate it on the extensive COV-19 CT dataset, which is meticulously annotated for the task. This dataset, with its comprehensive annotations, reinforces the overall robustness of our solution

Italy (Chapter 10)

In 2014, more than 200,000 refugees and migrants fled for safety across the Mediterranean Sea. Crammed into overcrowded, unsafe boats, thousands drowned, prompting the Pope to warn that the sea was becoming a mass graveyard. The early months of 2015 saw no respite. In April alone more than 1,300 people drowned. This led to a large public outcry to increase rescue operations. Throughout this period, UNHCR and other humanitarian organisations, engaged in a series of largescale media advocacy exercises, aiming at convincing European countries to do more to help. It was crucial work, setting the tone for the dramatic rise in attention to the refugee crisis that followed in the second half of 2015. But the media was far from united in its response. While some outlets joined the call for more assistance, others were unsympathetic, arguing against increasing rescue operations. To learn why, UNHCR commissioned a report by the Cardiff School of Journalism to explore what was driving media coverage in five different European countries: Spain, Italy, Germany, the UK and Sweden. Researchers combed through thousands of articles written in 2014 and early 2015, revealing a number of important findings for future media advocacy campaigns. Most importantly, they found major differences between countries, in terms of the sources journalists used (domestic politicians, foreign politicians, citizens, or NGOs), the language they employed, the reasons they gave for the rise in refugee flows, and the solutions they suggested. Germany and Sweden, for example, overwhelmingly used the terms ‘refugee’ or ‘asylum seeker’, while Italy and the UK press preferred the word ‘migrant’. In Spain, the dominant term was ‘immigrant’. These terms had an important impact on the tenor of each country’s debate. Media also differed widely in terms of the predominant themes to their coverage. For instance, humanitarian themes were more common in Italian coverage than in British, German or Spanish press. Threat themes (such as to the welfare system, or cultural threats) were the most prevalent in Italy, Spain and Britain. Overall, the Swedish press was the most positive towards refugees and migrants, while coverage in the United Kingdom was the most negative, and the most polarised. Amongst those countries surveyed, Britain’s right-wing media was uniquely aggressively in its campaigns against refugees and migrants. This report provides important insights into each country’s press culture during a crucial period of agenda-setting for today’s refugee and migrant crisis. It also offers invaluable insights into historical trends. What emerges is a clear message that for media work on refugees, one size does not fit all. Effective media advocacy in different European nations requires targeted, tailored campaigns, which takes into account their unique cultures and political context

COVID-19 Detection Using Segmentation, Region Extraction and Classification Pipeline

Purpose: The main purpose in this study is to develop a pipeline for COVID-19 detection from a big and challenging database of Computed Tomography (CT) images. The proposed pipeline includes a segmentation part, a lung extraction part, and a classifier part. Methods: The methodologies tried in the segmentation part are traditional segmentation methods as well as UNet-based methods. In the classification part, a Convolutional Neural Network (CNN) was used to take the final diagnosis decisions. Results: In the segmentation part, the proposed segmentation methods show high dice scores on a publicly available dataset. In the classification part, the results were compared at slice-level and at patient-level as well. At slice-level, methods were compared and showed high validation accuracy indicating efficiency in predicting 2D slices. At patient level, the proposed methods were also compared in terms of validation accuracy and macro F1 score on the validation set. The dataset used for classification is COV-19CT Database. The method proposed here showed improvement from our precious results on the same dataset. Conclusion: The improved work in this paper has potential clinical usages for COVID-19 detection and diagnosis via CT images. The code is on github at https://github.com/IDU-CVLab/COV19D_3r

A Clinical Case of Successful Ballon Angioplasty in the Remote Period in a Middle-Aged Patient after Late Stent Restenosis

Scientific Supervisor: D. Y. Pavlova, Assistant professor; T. V. Zolotarova, Assistant Professor Head of the Department: M. S. Brynza, Candidate of Medicin

Newly proposed strategies to increase the energy efficiency of water systems

One of the main challenges in the water industry consists of the reduction of environmental impacts, as well as the containment of energy use. In this research work, new solutions to achieve a sustainable management of water networks have been developed and organized in three lines of research. The main line of research is based on the optimal location of hydraulic devices within a water distribution network in order to maximize the energy production and water savings, as well as to minimize the investment cost. Firstly, the installation of only Pumps As Turbines (PATs) has been analyzed within a literature synthetic network and a new Mixed Integer Non-Linear Programming (MINLP) model has been developed to perform the optimization. Such an optimization model has been defined by a thorough mathematical formulation in order to deal with the extremely hard technical and computational complexities affecting the optimization procedure. In this research, only deterministic solvers have been employed to search the optima, and a comparison of their performance has been also carried out. Most of the computations have been performed by a global optimization solver, which potentially finds the global optimum in both convex and non-convex problems, but is also used to find good quality local optima in very complex problems, where the achievement of the exact solution may require infinite computational time. Compared to other studies in literature on the same network, the proposed study accounts for crucial hydraulic aspects, such as the phenomenon of flow reversion during the day affecting the installation and the operation of the devices, as well as the need for installing machines generating a power above a minimum fixed value. A comparison with such previous literature works has been carried out in order to highlight the effectiveness of the newly proposed optimization procedure. Moreover, to develop a more realistic and comprehensive mathematical model, the simultaneous installation of PATs and Pressure Reducing Valves (PRVs) has been also modeled by the introduction of new variables and mathematical constraints. Indeed, in presence of large water savings but small energy recovery, a PRV might be a more viable solution than a PAT. Compared to other studies in literature optimizing the only location of PATs within the same synthetic network, the simultaneous installation of valves and turbines, as well as the formulation of new hydraulic constraints, has significantly increased the value of the optimization model. In addition, the optimization has been extended to a real water distribution network serving the Blackstairs region (IE), with the aim of testing the robustness of the model and of the optimization procedure in more complex and larger problems. Indeed, the computational complexity affecting the optimization procedure increases according to the size of the network and the mathematical formulation proposed for the synthetic network might be not suitable for such a more complex case study. Compared to the synthetic network where the pressure reduction up to defined minimum requirements has not compromised the hydraulic operation of the system, in the analyzed real water network the exploitation of the available excess pressure to save both water and energy raises the need for employing also pumping systems to supply the most remote nodes of the network. The installation of pumping systems within the network has been therefore included within the optimization procedure and the outcome has been a new model for a Global Optimization of Hydraulic Devices Location (GOHyDeL), suitable for any water distribution network. Such a new model has been the result of progressive findings and hard attempts to deal with the enormous complexities arising during the computation. In all the performed optimization, the maximized water and energy savings and the minimized installation costs have been assessed according to a cost model used by previous authors in literature, in order to make a more straightforward comparison with such literature works. However, more recent cost models available in literature have been also employed to achieve more reasonable and realistic values of the results. According to the comparison between results obtained by using different cost models, despite the employment of more recent models leading to significantly larger investment costs and, thus, smaller values of NPV, the solutions are quite similar in terms of location of installed devices, and the achieved savings are comparable as well. However, among all the devices, the PRVs have resulted to be more affected by the choice of the cost model, due to the strong dependency of the valve costs on the pipe diameter. On the whole, beyond the large feasibility of the model within the optimal location field, a remarkable value of the proposed research also results from the new formulation of mathematical constraints and variables, which requires less computational effort and could find application also in more general optimization problems. The second line of research defines and compares two alternative strategies to supply a real water distribution network. The first solution consists of an elevated reservoir, which is located upstream of a water distribution network and is supplied from the water source by a pumping system. In this scheme, the excess pressure is not dissipated by a traditional valve, but rather a pump as turbine is installed to contain the pressure, thus water leakage, and also recover energy. The second hydraulic scheme instead consists of a pump supplying the downstream network directly from the source. In this scheme there is not an excess pressure to convert in energy, since the elevated reservoir is bypassed and the flow is pumped to the network with lower head. Such new schemes represent two different strategies to increase the energy efficiency of a supply system, as alternatives to the use of elevated reservoir with dissipation of the excess pressure by means of pressure reducing valves. The two schemes have been properly designed in order to find the devices, in terms of diameter and rotational speed, minimizing the energy requirements, thus maximizing the energy efficiency of the whole system. Given the water network supplying a small village in Ballacolla area (IE), the direct supply of the network has resulted a more efficient strategy than the indirect supply scheme with energy recovery. Moreover, the two schemes have been compared by varying the operating conditions, thus considering different combinations of distance and elevation of the source from the water distribution network. The energy audit of the two schemes has been assessed by new energy efficiency indices and also by literature indices. The comparison has showed that the convenience of a scheme over the other significantly depends on the operating conditions. However, with equal values of pumping head in both the schemes, the indirect scheme with energy recovery is up to 5 % more convenient than the direct pumping scheme, which is instead more efficient if the pumping head could be reduced up to 6 %. In the third line of research a new strategy to save energy in the urban water management is presented. The proposed solution consists of a mixed PAT-pump turbocharger, that is a PAT-equipped turbopump exploiting an excess pressure within the fresh water network to produce energy, which is entirely used to carry a wastewater stream towards a treatment plant. In this system, the excess pressure is converted by the PAT in a mechanical torque, which in turn supplies the pump mounted on the same shaft. Such a plant arises whenever wastewater pumping station and excess pressure point could be co-located, thus in low ground areas where high clean-water pressures occur and sewage networks are equipped with pumping systems due to the need to treat the wastewater. In this application, the water distribution network serving Ballacolla area (IE) has been assumed as case study, since it is suitable for the installation of this kind of plant. A preliminary geometric selection of the devices has been performed by a new selection method based on the maximum daily averaged values of fresh and wastewater discharge. Then, the behavior of the plant has been simulated for several wastewater hydrographs by a new mathematical model. The benefits of the plants have been assessed and compared with a conventional wastewater pumping system working in ON/OFF mode. According to the comparison, the higher Net Present Value (NPV) of the MPP plant proves the advantage of this scheme over the conventional system, at least until the useful life of the plant is reached

Deep Learning Based Automated COVID-19 Classification from Computed Tomography Images

A method of a Convolutional Neural Networks (CNN) for image classification with image preprocessing and hyperparameters tuning was proposed. The method aims at increasing the predictive performance for COVID-19 diagnosis while more complex model architecture. Firstly, the CNN model includes four similar convolutional layers followed by a flattening and two dense layers. This work proposes a less complex solution based on simply classifying 2D-slices of Computed Tomography scans. Despite the simplicity in architecture, the proposed CNN model showed improved quantitative results exceeding state-of-the-art when predicting slice cases. The results were achieved on the annotated CT slices of the COV-19-CT-DB dataset. Secondly, the original dataset was processed via anatomy-relevant masking of slice, removing none-representative slices from the CT volume, and hyperparameters tuning. For slice processing, a fixed-sized rectangular area was used for cropping an anatomy-relevant region-of-interest in the images, and a threshold based on the number of white pixels in binarized slices was employed to remove none-representative slices from the 3D-CT scans. The CNN model with a learning rate schedule and an exponential decay and slice flipping techniques was deployed on the processed slices. The proposed method was used to make predictions on the 2D slices and for final diagnosis at patient level, majority voting was applied on the slices of each CT scan to take the diagnosis. The macro F1 score of the proposed method well-exceeded the baseline approach and other alternatives on the validation set as well as on a test partition of previously unseen images from COV-19CT-DB dataset

A bit more human?: trends in TV news coverage of BAME people during the pandemic

TV bulletins have reported on the extra dangers ethnic minority health workers have faced during the pandemic, but are less interested in how the hostile environment affects BAME and migrant workers. Analysis by Marina Morani and Lizzy Willmington (Cardiff University) also finds that BAME people are almost entirely absent from human interest stories

A Phenomenological Study on Teacher Perceptions of The Influence of Governance on Teacher Retention in Ugandan Private Primary Christian Schools

The purpose of this hermeneutic phenomenological study was to answer the following central research question, “what are teachers’ perceptions of the effects of governance on teacher retention in private primary Christian schools in Uganda?” The theoretical model that guided this study was an integrated model comprising distributed leadership and transformational leadership and its relationship to governance influences on teacher retention. The study utilized a hermeneutic phenomenological methodology for data analysis. The selected participants were comprised of 13 teachers from four approved Christian primary school sites located in the Wakiso district of Uganda. The primary data collection methods were individual questionnaires, in-depth individual interviews, and a focus group interview. Specific towards hermeneutic phenomenology, the collected information was coded for themes, and then those themes were interpreted to provide a detailed description of the teachers’ perceptions of governance and its influence on retention in primary Christian schools in Uganda. The researcher utilized NVivo 11 qualitative data analysis software to assist with thematic coding and organization. This research discovered evidence that private primary Christian schoolteachers in Uganda are passionate individuals who deeply care about their work quality and are greatly influenced by their governance use of transformational and distributed leadership methods. This influence extends to their retention desires

The 'hospectacle' of reporting from ICUs: what does the public want to see?

TV news bulletins have used footage from inside hospitals that are treating patients afflicted by coronavirus. Marina Morani, Maria Kyriakidou, Nikki Soo and Stephen Cushion (University of Cardiff) look at the ethical issues raised by these reports, and what the public thinks of them