The Iceland Greenland Seas Project

A coordinated atmosphere-ocean research project, centered on a rare wintertime field campaign to the Iceland and Greenland Seas, seeks to determine the location and causes of dense water formation by cold-air outbreaks. The Iceland Greenland Seas Project (IGP) is a coordinated atmosphere-ocean research program investigating climate processes in the source region of the densest waters of the Atlantic Meridional Overturning Circulation. During February and March 2018, a field campaign was executed over the Iceland and southern Greenland Seas that utilized a range of observing platforms to investigate critical processes in the region – including a research vessel, a research aircraft, moorings, sea gliders, floats and a meteorological buoy. A remarkable feature of the field campaign was the highly-coordinated deployment of the observing platforms, whereby the research vessel and aircraft tracks were planned in concert to allow simultaneous sampling of the atmosphere, the ocean and their interactions. This joint planning was supported by tailor-made convection-permitting weather forecasts and novel diagnostics from an ensemble prediction system. The scientific aims of the IGP are to characterize the atmospheric forcing and the ocean response of coupled processes; in particular, cold-air outbreaks in the vicinity of the marginal-ice zone and their triggering of oceanic heat loss, and the role of freshwater in the generation of dense water masses. The campaign observed the lifecycle of a long-lasting cold-air outbreak over the Iceland Sea and the development of a cold-air outbreak over the Greenland Sea. Repeated profiling revealed the immediate impact on the ocean, while a comprehensive hydrographic survey provided a rare picture of these subpolar seas in winter. A joint atmosphere-ocean approach is also being used in the analysis phase, with coupled observational analysis and coordinated numerical modelling activities underway

Tenure security and household investment decisions for urban sanitation: The case of Dakar, Senegal

This article was published in the journal, Habitat International [© Elsevier Ltd.] and the definitive version is available at: http://dx.doi.org/10.1016/j.habitatint.2013.02.004This paper explores the relevance of householders' security of tenure to their willingness to pay the capital and operational costs for sanitation in low-income urban areas. When the sanitation norm is self-managed on-site systems, as is the case in many low-income areas of towns and cities, household investment decisions in sanitation are inherently linked to tenure security. Based on evidence gathered in Dakar, Senegal, it is de facto rather than de jure tenure rights that provide sufficient security for household investment in sanitation. We make a critical distinction between willingness to invest and willingness to pay for the capital investment costs and on-going operational servicing costs of sanitation. Whilst tenants and those with lower tenure security do not invest in capital infrastructure, they are willing to pay for the operational aspects of sanitation services. Current formal policy settings and strategies for urban sanitation tend not to cater for this group; this is a fundamental oversight as these constitute significant and growing segments of the population. Land tenure and sanitation issues need to be considered in an integrated way and the capital and operational costs need to be disaggregated in planning to respond more effectively to the spending decisions of the urban poor

Assessment of suitable hospital location using GIS and machine learning

Choosing the suitable site for a new hospital is a difficult aspect of decision-making for the decision-makers. Large data availability with challenging features and the proliferation of different methodologies have made it extremely difficult to select the best models that perform for a particular site selection problem. This research provided a comprehensive study for hospital site suitability and introduced machine learning models. The experiment was conducted in two study areas which are Gaza Strip, Palestine and Melaka, Malaysia. First, the conditioning factors were optimized and ranked to identify and select the most correlated factors to predict the suitability of a hospital site by applying the correlation feature selection (CFS) algorithm and the greedy-stepwise search method. Second, to assess the hospital site suitability, three machine learning (ML) models, namely, support vector machine (SVM), multilayer perceptron (MLP) and linear regression (LR) were introduced to predict the suitability of the hospital site. In addition, two multi-criteria decision-making models (MCDM), namely, analytical hierarchy process (AHP) and fuzzy overlay were used to compare the models and verify the results. The ML models Performance were verified using the receiver operating characteristics (ROC) curves and cross-validation with other evaluation metrics; correlation coefficient, root mean square error (RMSE), mean absolute error (MAE), relative absolute error (RAE), as well as root relative squared error (RRSE). The comparison of the model shows that in Melaka and Gaza Strip, MLP (AUC: 92.20%, 84.90%) and AHP (AUC: 91.40% and 83.20%) are more reliable and acceptable for hospital suitability mapping in both locations with consistent and realistic results. The high-level performance and accuracy of the model outcomes supported the conclusion that the proposed methodology in this research can successfully produce a site suitability map for locating new hospitals. Third, an insight into the machine learning models utilized and how their predicted weights affect hospital site suitability mapping was provided. A clear dissimilarity between the ML and MCDM models in terms of the predicted weights characteristics of the conditioning factors in both study areas are discovered. The study has revealed that some conditioning factors are more significant than others because of inherent traits associated with the spatial characteristics of each case study that results in the differences in the weights. Fourth, five location-allocation models were implemented based on the calculus of coverage, mainly implemented in the search for poor coverage to propose new hospital sites in both study areas. In this research, site suitability from one study area to another was verified using all the implemented methods. Thus, the proposed approaches would be effectively and easily replicated in other regions. Moreover, the results of the proposed approaches provided detailed information that would be useful to decision makers to locate the hospital for effective health delivery planning and implementation

L'afflusso di novellame alla foce del fiume Magra (La Spezia): risultati del primo anno di indagini

Pubblicazione in Atti dei Seminari delle Unita' Operative responsabili dei Progetti di Ricerca promossi nell'ambito dello schema preliminare di piano per la Pesca e l'Acquacoltura - Istituto di Zoologia dell'Università di Parm

Evolution of Denmark Strait overflow cyclones and their relationship to overflow surges

Mesoscale features present at the Denmark Strait sill regularly enhance the volume transport of the Denmark Strait overflow (DSO). They are important for the Atlantic Meridional Overturning Circulation and ultimately, for the global climate system. Using a realistic numerical model, we find new evidence of the causal relationship between overflow surges (i.e., mesoscale features associated with high‐transport events) and DSO cyclones observed downstream. Most of the cyclones form at the Denmark Strait sill during overflow surges and, because of potential vorticity conservation and stretching of the water column, grow as they move equatorward. A fraction of the cyclones form downstream of the sill, when anticyclonic vortices formed during high‐transport events start collapsing. Regardless of their formation mechanism, DSO cyclones weaken starting roughly 150 km downstream of the sill, and potential vorticity is only materially conserved during the growth phase

The attitude and knowledge of pediatricians and family physicians toward COVID-19 vaccination in children: A cross-sectional study

COVID-19 vaccines to children are expected to reduce the transmission of the disease to high-risk groups and achieve herd immunity in younger populations. A positive attitude toward COVID-19 vaccination in children among healthcare workers (HCWs) is predicted to reduce parents’ hesitancy to vaccinate their children. This study aimed to assess the knowledge and attitude of pediatricians and family physicians toward COVID-19 vaccination in children. A total of 112 pediatricians and 96 family physicians (specialists and residents) were interviewed to assess the level of knowledge, attitude, and perceived safety of COVID-19 vaccines for children. Physicians willing to receive regular COVID-19 vaccination (analogous to the influenza vaccine) had significantly higher knowledge and attitude scores (P 67%). Around 71% of physicians believed COVID-19 vaccines for children do not cause or worsen any health condition. Educational and training programs that increase the knowledge of physicians about COVID-19 vaccines and their safety in children are recommended to inform a more positive attitude