Assessing multi-hazard susceptibility to cryospheric hazards:Lesson learnt from an Alaskan example

Classifying a given landscape on the basis of its susceptibility to surface processes is a standard procedure in low to mid-latitudes. Conversely, these procedures have hardly been explored in periglacial regions. However, global warming is radically changing this situation and will change it even more in the future. For this reason, understanding the spatial and temporal dynamics of geomorphological processes in peri-arctic environments can be crucial to make informed decisions in such unstable environments and shed light on what changes may follow at lower latitudes. For this reason, here we explored the use of data-driven models capable of recognizing locations prone to develop retrogressive thaw slumps (RTSs) and/or active layer detachments (ALDs). These are cryospheric hazards induced by permafrost degradation, and their development can negatively affect human settlements or infrastructure, change the sediment budget and release greenhouse gases. Specifically, we test a binomial Generalized Additive Modeling structure to estimate the probability of RST and ALD occurrences in the North sector of the Alaskan territory. The results we obtain show that our binary classifiers can accurately recognize locations prone to RTS and ALD, in a number of goodness-of-fit (AUCRTS = 0.83; AUCALD = 0.86), random cross-validation (mean AUCRTS = 0.82; mean AUCALD = 0.86), and spatial cross-validation (mean AUCRTS = 0.74; mean AUCALD = 0.80) routines. Overall, our analytical protocol has been implemented to build an open-source tool scripted in Python where all the operational steps are automatized for anyone to replicate the same experiment. Our protocol allows one to access cloud-stored information, pre-process it, and download it locally to be integrated for spatial predictive purposes

Charlson comorbidity index, neutrophil-to-lymphocyte ratio and undertreatment with renin-angiotensin-aldosterone system inhibitors predict in-hospital mortality of hospitalized COVID-19 patients during the omicron dominant period

Purpose: To investigate the clinical predictors of in-hospital mortality in hospitalized patients with Coronavirus disease 2019 (COVID-19) infection during the Omicron period. Methods: All consecutive hospitalized laboratory‐confirmed COVID-19 patients between January and May 2022 were retrospectively analyzed. All patients underwent accurate physical, laboratory, radiographic and echocardiographic examination. Primary endpoint was in-hospital mortality. Results: 74 consecutive COVID-19 patients (80.0 ± 12.6 yrs, 45.9% males) were included. Patients who died during hospitalization (27%) and those who were discharged alive (73%) were separately analyzed. Compared to patients discharged alive, those who died were significantly older, with higher comorbidity burden and greater prevalence of laboratory, radiographic and echographic signs of pulmonary and systemic congestion. Charlson comorbidity index (CCI) (OR 1.76, 95%CI 1.07-2.92), neutrophil-to-lymphocyte ratio (NLR) (OR 1.24, 95%CI 1.10-1.39) and absence of angiotensin-converting enzyme inhibitors (ACEI)/angiotensin II receptor blockers (ARBs) therapy (OR 0.01, 95%CI 0.00-0.22) independently predicted the primary endpoint. CCI ≥7 and NLR ≥9 were the best cut-off values for predicting mortality. The mortality risk for patients with CCI ≥7, NLR ≥9 and not in ACEI/ARBs therapy was high (86%); for patients with CCI <7, NLR ≥9, with (16.6%) or without (25%) ACEI/ARBs therapy was intermediate; for patients with CCI <7, NLR <9 and in ACEI/ARBs therapy was of 0%. Conclusions: High comorbidity burden, high levels of NLR and the undertreatment with ACEI/ARBs were the main prognostic indicators of in-hospital mortality. The risk stratification of COVID-19 patients at hospital admission would help the clinicians to take care of the high-risk patients and reduce the mortality

Retrogressive thaw slump susceptibility in the northern hemisphere permafrost region

Mean annual temperatures in the Arctic and subarctic have increased in recent decades, increasing the number of permafrost hazards. Retrogressive thaw slumps (RTSs), triggered by the thawing of ground ice in permafrost soil, have become more common in the Arctic. Many studies report an increase in RTS activity on a local or regional scale. In this study, the primary goals are to: (i) examine the spatial patterns of the RTS occurrences across the circumpolar permafrost region, (ii) assess the environmental factors associated with their occurrence and (iii) create the first susceptibility map for RTS occurrence across the Northern Hemisphere. Based on our results, we predicted high RTS susceptibility in the continuous permafrost regions above the 60th latitude, especially in northern Alaska, north-western Canada, the Yamal Peninsula, eastern Russia and the Qinghai-Tibetan Plateau. The model indicated that air temperature and soil properties are the most critical environmental factors for the occurrence of RTSs on a circumpolar scale. Especially, the climatic conditions of thaw season were highlighted. This study provided new insights into the circumpolar susceptibility of ice-rich permafrost soils to rapid permafrost-related hazards like RTSs and the associated impacts on landscape evolution, infrastructure, hydrology and carbon fluxes that contribute to global warming.</p

Offline and online LSTM networks for respiratory motion prediction in MR-guided radiotherapy

Objective. Gated beam delivery is the current clinical practice for respiratory motion compensation in MR-guided radiotherapy, and further research is ongoing to implement tracking. To manage intra-fractional motion using multileaf collimator tracking the total system latency needs to be accounted for in real-time. In this study, long short-term memory (LSTM) networks were optimized for the prediction of superior–inferior tumor centroid positions extracted from clinically acquired 2D cine MRIs. Approach. We used 88 patients treated at the University Hospital of the LMU Munich for training and validation (70 patients, 13.1 h), and for testing (18 patients, 3.0 h). Three patients treated at Fondazione Policlinico Universitario Agostino Gemelli were used as a second testing set (1.5 h). The performance of the LSTMs in terms of root mean square error (RMSE) was compared to baseline linear regression (LR) models for forecasted time spans of 250 ms, 500 ms and 750 ms. Both the LSTM and the LR were trained with offline (offline LSTM and offline LR) and online schemes (offline+online LSTM and online LR), the latter to allow for continuous adaptation to recent respiratory patterns. Main results. We found the offline+online LSTM to perform best for all investigated forecasts. Specifically, when predicting 500 ms ahead it achieved a mean RMSE of 1.20 mm and 1.00 mm, while the best performing LR model achieved a mean RMSE of 1.42 mm and 1.22 mm for the LMU and Gemelli testing set, respectively. Significance. This indicates that LSTM networks have potential as respiratory motion predictors and that continuous online re-optimization can enhance their performance

INFN What Next: Ultra-relativistic Heavy-Ion Collisions

This document was prepared by the community that is active in Italy, within INFN (Istituto Nazionale di Fisica Nucleare), in the field of ultra-relativistic heavy-ion collisions. The experimental study of the phase diagram of strongly-interacting matter and of the Quark-Gluon Plasma (QGP) deconfined state will proceed, in the next 10-15 years, along two directions: the high-energy regime at RHIC and at the LHC, and the low-energy regime at FAIR, NICA, SPS and RHIC. The Italian community is strongly involved in the present and future programme of the ALICE experiment, the upgrade of which will open, in the 2020s, a new phase of high-precision characterisation of the QGP properties at the LHC. As a complement of this main activity, there is a growing interest in a possible future experiment at the SPS, which would target the search for the onset of deconfinement using dimuon measurements. On a longer timescale, the community looks with interest at the ongoing studies and discussions on a possible fixed-target programme using the LHC ion beams and on the Future Circular Collider.Comment: 99 pages, 56 figure

Thermophysical and Electrochemical Properties of Ethereal Functionalised Cyclic Alkylammonium-based Ionic Liquids as Potential Electrolytes for Electrochemical Applications

International audienceA series of hydrophobic room temperature ionic liquids (ILs) based on ethereal functionalised pyrrolidinium, piperidinium and azepanium cations bearing the bis[(trifluoromethyl)sulfonyl]imide, [TFSI]−, anion were synthesized and characterized. Their physicochemical properties such as density, viscosity and electrolytic conductivity, and thermal properties including phase transition behaviour and decomposition temperature have been measured. All of the ILs showed low melting point, low viscosity and good conductivity and the latter properties have been discussed in terms of the IL fragility, an important electrolyte feature of the transport properties of glass‐forming ILs. Furthermore, the studied [TFSI]−‐based ILs generally exhibit good electrochemical stabilities and, by coupling electrochemical experiments and DFT calculations, the effect of ether functionalisation at the IL cation on the electrochemical stability of the IL is discussed. Preliminary investigations into the Li‐redox chemistry at a Cu working electrode are also reported as a function of ether‐functionality within the pyrrolidinium‐based IL family. Overall, the results show that these ionic liquids are suitable for electrochemical devices such as battery systems, fuel cells or supercapacitors

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p &lt; 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Sicurezza 4P. Lo studio alla base del software XLAW per prevedere e prevenire i crimini

Innovazione è la chiave che apre le porte del futuro. Sicurezza 4P ha fatto tesoro degli insegnamenti di chi là fuori, in tutti i settori, è riuscito a offrire qualcosa che prima non c’era e ora c’è. Si spiega l’iter tortuoso che ha portato alla scoperta di un algoritmo mica da ridere. Si parla della prevenzione dei crimini predatori urbani, e lo si fa con un tono e un metodo diverso rispetto al semplice manuale. Tanti esempi fanno da sfondo a uno stile che rompe un po’ con la tradizione manualistica per andare ad accogliere un linguaggio semplice, tipico da racconto, accessibile anche e soprattutto a chi sente un impellente bisogno di sentirsi protetto. Tra Riserve di Caccia, numeri e tentativi, l’autore ci guida in un mondo che ai più può risultare sconosciuto, ma che in fin dei conti altro non è che il luogo dove trascorriamo una grossa fetta della giornata, del week end, della vita. Se essere innovativi e originali è un concetto applicabile a tutto, lo è a prescindere quando si parla del tema della sicurezza. Sicurezza 4P è lo studio alla base di uno strumento nuovo e utile nelle mani delle forze dell’ordine: il software XLAW per prevedere e prevenire i crimini

Multi-hazard susceptibility mapping of cryospheric hazards in a high-Arctic environment: Svalbard Archipelago

The Svalbard Archipelago represents the northernmost place on Earth where cryospheric hazards, such as thaw slumps (TSs) and thermo-erosion gullies (TEGs) could take place and rapidly develop under the influence of climatic variations. Svalbard permafrost is specifically sensitive to rapidly occurring warming, and therefore, a deeper understanding of TSs and TEGs is necessary to understand and foresee the dynamics behind local cryospheric hazards' occurrences and their global implications. We present the latest update of two polygonal inventories where the extent of TSs and TEGs is recorded across Nordenskiöld Land (Svalbard Archipelago), over a surface of approximately 4000 km2. This area was chosen because it represents the most concentrated ice-free area of the Svalbard Archipelago and, at the same time, where most of the current human settlements are concentrated. The inventories were created through the visual interpretation of high-resolution aerial photographs as part of our ongoing effort toward creating a pan-Arctic repository of TSs and TEGs. Overall, we mapped 562 TSs and 908 TEGs, from which we separately generated two susceptibility maps using a generalised additive model (GAM) approach, under the assumption that TSs and TEGs manifest across Nordenskiöld Land, according to a Bernoulli probability distribution. Once the modelling results were validated, the two susceptibility patterns were combined into the first multi-hazard cryospheric susceptibility map of the area. The two inventories are available at https://doi.org/10.1594/PANGAEA.945348 (Nicu et al., 2022a) and https://doi.org/10.1594/PANGAEA.945395 (Nicu et al., 2022b)

Spatial modeling of cryospheric hazards: predicting retrogressive thaw slumps in Alaska

Classifying a given landscape on the basis of its susceptibility to surface processes is a standard procedure in low to mid latitudes. Conversely, these procedures have hardly been explored in peri-glacial regions, mostly because of the limited presence of human settlements and thus of the need for risk assessment. However, global warming is radically changing this situation and will change it even more in the years to come. For this reason, understanding the spatial and spatio-temporal dynamics of gemorphological processes in peri-arctic environments can be crucial to make informed decision in such unstable environments but also to shed light on what changes may follow at lower latitudes. For this reason, here we explored the use of artificially intelligent models capable of recognizing locations prone to develop retrogressive thaw slumps (RTS). These are cryospheric hazards induced by permafrost degradation and their development can negatively affect human settlements or infrastructure, change the sediment budget dynamics and release greenhouse gases. Specifically, we test a binomial Generalized Additive Modeling structure to estimate probability of RTS occurrences/development in the North sector of the Alaskan territory. The results we obtain show that our binary classifier is able to accurately recognize locations prone to RTS, in a number of goodness-of-fit and cross-validation routines. Overall, our analytical protocol has been implemented with the idea in mind of building an open source tool scripted in Python