Band-wise Hyperspectral Image Pansharpening using CNN Model Propagation

Hyperspectral pansharpening is receiving a growing interest since the last few years as testified by a large number of research papers and challenges. It consists in a pixel-level fusion between a lower-resolution hyperspectral datacube and a higher-resolution single-band image, the panchromatic image, with the goal of providing a hyperspectral datacube at panchromatic resolution. Thanks to their powerful representational capabilities, deep learning models have succeeded to provide unprecedented results on many general purpose image processing tasks. However, when moving to domain specific problems, as in this case, the advantages with respect to traditional model-based approaches are much lesser clear-cut due to several contextual reasons. Scarcity of training data, lack of ground-truth, data shape variability, are some such factors that limit the generalization capacity of the state-of-the-art deep learning networks for hyperspectral pansharpening. To cope with these limitations, in this work we propose a new deep learning method which inherits a simple single-band unsupervised pansharpening model nested in a sequential band-wise adaptive scheme, where each band is pansharpened refining the model tuned on the preceding one. By doing so, a simple model is propagated along the wavelength dimension, adaptively and flexibly, with no need to have a fixed number of spectral bands, and, with no need to dispose of large, expensive and labeled training datasets. The proposed method achieves very good results on our datasets, outperforming both traditional and deep learning reference methods. The implementation of the proposed method can be found on https://github.com/giu-guarino/R-PN

Neostigmine-Induced Reversal of Faecal Impaction and Severe Constipation in a Young Patient with Systemic Sclerosis

No abstract availabl

Beware the wrong way! A report on gastrografin inhalation

An 83-year-old man was admitted to the Emergency Department of St. Anna University Hospital, Cona, Italy, after he had inhaled diatrizoate (gastrografin), a well-known hyperosmolar contrast agent, during an X-ray of the upper gastrointestinal tract. The family physician recommended the patient to take the test in order to demonstrate a possible hiatal hernia. While swallowing gastrografin he had an esophageal spasm (detected at fluoroscopy), which led to the inhalation of the contrast agent. After the episode, he was completely asymptomatic, eupnoeic, and with a good peripheral oxygen saturation. The physical examination was unremarkable. A chest X-ray of the lungs showed accumulation of the contrast agent in the distal bronchial tree (arrows in Figure 1A and B), with the right part being more involved because of the straight orientation of the right bronchus

Smart Society and Artificial Intelligence: Big Data Scheduling and the Global Standard Method Applied to Smart Maintenance

Abstract The implementation of artificial intelligence (AI) in a smart society, in which the analysis of human habits is mandatory, requires automated data scheduling and analysis using smart applications, a smart infrastructure, smart systems, and a smart network. In this context, which is characterized by a large gap between training and operative processes, a dedicated method is required to manage and extract the massive amount of data and the related information mining. The method presented in this work aims to reduce this gap with near-zero-failure advanced diagnostics (AD) for smart management, which is exploitable in any context of Society 5.0, thus reducing the risk factors at all management levels and ensuring quality and sustainability. We have also developed innovative applications for a human-centered management system to support scheduling in the maintenance of operative processes, for reducing training costs, for improving production yield, and for creating a human–machine cyberspace for smart infrastructure design. The results obtained in 12 international companies demonstrate a possible global standardization of operative processes, leading to the design of a near-zero-failure intelligent system that is able to learn and upgrade itself. Our new method provides guidance for selecting the new generation of intelligent manufacturing and smart systems in order to optimize human–machine interactions, with the related smart maintenance and education

Scaling Expected Force: Efficient Identification of Key Nodes in Network-based Epidemic Models

Centrality measures are fundamental tools of network analysis as they highlight the key actors within the network. This study focuses on a newly proposed centrality measure, Expected Force (EF), and its use in identifying spreaders in network-based epidemic models. We found that EF effectively predicts the spreading power of nodes and identifies key nodes and immunization targets. However, its high computational cost presents a challenge for its use in large networks. To overcome this limitation, we propose two parallel scalable algorithms for computing EF scores: the first algorithm is based on the original formulation, while the second one focuses on a cluster-centric approach to improve efficiency and scalability. Our implementations significantly reduce computation time, allowing for the detection of key nodes at large scales. Performance analysis on synthetic and real-world networks demonstrates that the GPU implementation of our algorithm can efficiently scale to networks with up to 44 million edges by exploiting modern parallel architectures, achieving speed-ups of up to 300x, and 50x on average, compared to the simple parallel solution

Comparison between Capillary and Serum Lactate Levels in Predicting Short-Term Mortality of Septic Patients at the Emergency Department

Sepsis is a time-dependent and life-threating condition related to macro- and micro-circulatory impairment leading to anaerobic metabolism and lactate increase. We assessed the prognostic accuracy of capillary lactates (CLs) vs. serum ones (SLs) on 48-h and 7-day mortality in patients with suspected sepsis. This observational, prospective, single-centre study was conducted between October 2021 and May 2022. Inclusion criteria were: (i) suspect of infection; (ii) qSOFA ≥ 2; (iii) age ≥ 18 years; (iv) signed informed consent. CLs were assessed with LactateProTM2®. 203 patients were included: 19 (9.3%) died within 48 h from admission to the Emergency Department, while 28 (13.8%) within 7 days. Patients deceased within 48 h (vs. survived) had higher CLs (19.3 vs. 5 mmol/L, p < 0.001) and SLs (6.5 vs. 1.1 mmol/L, p = 0.001). The best CLs predictive cut-off for 48-h mortality was 16.8 mmol/L (72.22% sensitivity, 94.02% specificity). Patients within 7 days had higher CLs (11.5 vs. 5 mmol/L, p = 0.020) than SLs (2.75 vs. 1.1 mmol/L, p < 0.001). The multivariate analysis confirmed CLs and SLs as independent predictors of 48-h and 7-day mortality. CLs can be a reliable tool for their inexpensiveness, rapidity and reliability in identifying septic patients at high risk of short-term mortality

Evaluation of Anti-SARS-CoV-2 IgA Response in Tears of Vaccinated COVID-19 Subjects

Secretory IgA (sIgA), which may play an important role in the early defense against SARS-CoV-2 infection, were detected in the eye of COVID-19 patients. However, an evaluation of the sIgA response in the tears of vaccinated or non-vaccinated COVID-19 subjects is still lacking. Aimed at characterizing sIgA mucosal immunity in the eye, this study analyzed tear samples from 77 COVID-19 patients, including 63 vaccinated and 14 non-vaccinated subjects. The groups showed similar epidemiological features, but as expected, differences were observed in the percentage of asymptomatic/pauci-symptomatic subjects in the vaccinated vs. non-vaccinated cohort (46% and 29% of the total, respectively). Consistent with this, ocular sIgA values, evaluated by a specific quantitative ELISA assay, were remarkably different in vaccinated vs. non-vaccinated group for both frequency (69.8% vs. 57.1%, respectively) and titer (1372.3 U/mL vs. 143.7 U/mL, respectively; p = 0.01), which was significantly differently elevated depending on the type of administered vaccine. The data show for the first time significant differences of available vaccines to elicit sIgA response in the eye and suggest that quantitative tear-based sIgA tests may potentially serve as a rapid and easily accessible biomarker for the assessment of the development of a protective mucosal immunity toward SARS-CoV-2

Presepsin levels and COVID-19 severity: a systematic review and meta-analysis

Plasmatic presepsin (PSP) is a novel biomarker reported to be useful for sepsis diagnosis and prognosis. During the pandemic, only few studies highlighted a possible correlation between PSP and COVID-19 severity, but results remain inconsistent. The present study aims to establish the correlation between PSP and COVID-19 severity. English-language papers assessing a correlation between COVID-19 and PSP from MEDLINE, PubMed, Google Scholar, Cochrane Library, MeSH, LitCovid NLM, EMBASE, CINAHL Plus and the World Health Organization (WHO) website, published from January 2020 were considered with no publication date limitations. Two independent reviewers performed data abstraction and quality assessment, and one reviewer resolved inconsistencies. The protocol was registered on PROSPERO (CRD42022325971).Fifteen articles met our eligibility criteria. The aggregate study population included 1373 COVID-19 patients who had undergone a PSP assessment. The random-effect meta-analysis was performed in 7 out of 15 selected studies, considering only those reporting the mean PSP levels in low- and high-severity cases (n = 707).The results showed that the pooled mean difference of PSP levels between high- and low-severity COVID-19 patients was 441.70 pg/ml (95%CI: 150.40-732.99 pg/ml).Our data show that presepsin is a promising biomarker that can express COVID-19 severity

Cardiac tamponade as a late complication of a minor trauma due to syncope: A case report and literature review

Haemopericardium with cardiac tamponade following minor blunt trauma is a rare, life-threatening condition. The diagnosis of cardiac tamponade as well as therapeutic management may be delayed, since the link between trauma and illness is often overlooked. We report the case of an old woman who developed a relatively delayed cardiac tamponade due to an otherwise minor blunt chest trauma following syncope

A case of hemorrhagic shock due to massive upper gastrointestinal bleeding: from the differential diagnosis to the correct management

Upper Gastro-Intestinal Bleeding (UGIB) spans from minor bleeding to life-threatening events. Identification of early signs of shock, proper management of hemodynamically unstable patients, and correct risk stratification are essential for an appropriate diagnostic workup and therapy. This case reports a young man admitted to the emergency department with haematemesis. His medical history was unremarkable, without any risk factors for gastrointestinal bleeding. A few hours after admission, further episodes of haematemesis occurred, and the patient's condition rapidly deteriorated to irreversible shock. A contrast-enhanced computed tomography (CECT) revealed morphological features of chronic liver disease and oesophagal varices. The patient underwent upper gastrointestinal endoscopy, confirming oesophagal varices with massive bleeding. Although promptly applied, endoscopic hemostasis was ineffective, and the patient died twenty-four hours after admission. Based on this case, we reviewed the diagnostic and therapeutic approaches for patients with massive UGIB and provided a practical approach to this life-threatening emergency