Recurrence in a patient with a 10-year history of sinonasal mucosal melanoma manifesting as facial swelling

Sinonasal mucosal melanoma is a rare tumor that develops slowly and may manifest with non specific signs and symptoms, causing significant delay in diagnosis. Local recurrence is common and usually occurs within the first two years after the initial treatment. Prognosis of recurrent lesions is poor and 5-year survival ranges between 10-47%. We report the clinical, radiographic, histopathological and immunohistochemical findings of a recurrent sinonasal mucosal melanoma which was diagnosed 10 years after the initial treatment, in a patient who presented with unilateral facial swelling and one-sided difficulty in breathing of two years duration. We discuss the causes of late diagnosis and review the negative predictive factors for recurrence and survival. As early diagnosis is of paramount importance for prognosis, we emphasize the signs and symptoms of patients with a history of sinonasal mucosal melanoma which should raise the suspicion for recurrence, in spite of a long time interval since diagnosis

Application of nano-hydroxyapatite/chitosan scaffolds on rat calvarial critical-sized defects : a pilot study

The purpose of this pilot study was to evaluate for the first time the effect of 75/25 w/w nano-Hydroxyapatite/Chitosan (nHAp/CS) scaffolds on Guided Bone Regeneration (GBR) in rat calvarial critical-sized defects (CSDs). Six adult Sprague Dawley rats, 3 males and 3 females, were used. Two CSDs, full thickness and 5mm in diameter, were trephined in both sides of the parietal bone. The right CSD was filled with nHAp/CS scaffold, while the left CSD remained empty, as the control group. The wound was sutured in layers. Rats were euthanized with diethyl ether inhalation at 2, 4 and 8 weeks after surgical procedure. Histological and histomorphometric analysis was performed within distinct regions of interest (ROI): the lateral area inward of the middle sagittal seam; the lateral area outward of the middle sagittal seam and the central area. The mean surface of newly formed bone (in ?m2) in the lateral area inward of the middle sagittal seam of all rats was significantly higher (P=0.039) in the experimental group (91733.00±38855.60) than the control group (46762.17±25507.97). The NOex-c, defined as total number of osteocytes (OST) in newly formed bone surface in experimental group [experimental OST] minus the total number of osteocytes in newly formed bone surface in control group [control OST], was significantly greater (P=0.029) at 4th week post-surgery. Within the experimental group, a statistically significant increase (P=0.042) in the surface of newly formed bone was noticed in rats euthanized in 4th week compared with rats euthanized in 2nd week after surgery in the lateral area inward of the middle sagittal seam. The results of this study suggest that 75/25 w/w nHAp/CS scaffolds should be considered as a suitable biomaterial for GBR

Investigation and determination of the geothermal parameters of the ground in Cyprus for the exploitation of geothermal energy and the impact of the results in the design of the geothermal systems

The Energy Service of the Ministry of Commerce, Industry and Tourism has the overall responsibility for Energy matters in Cyprus and specifically for preparing and implementing programmes for energy conservation, the promotion of renewable energy sources (RES) and the development of technologies for the utilization of RES. The Government of Cyprus being aware of the benefits of geothermal energy and in order to increase the share of energy from renewable sources consumed in heating and cooling in 2020, promotes the geothermal energy systems through a Scheme that provides financial incentives for the utilization of RES for heating and cooling. However, the lack of valid data for the ground thermal properties in Cyprus was one of the main obstacles for the design of efficient geothermal systems, the implementation of the Schemes in the field of geothermal energy and the calculation of the share of energy from renewable sources for heating and cooling according to the methodology defined by the E.U in the directive 2009/28/EC. In an effort to identify suitable energy efficient systems for heating and cooling of buildings and the correct calculations of their contribution to the national targets, the Energy Service participated in a project founded by the Research Promotion Foundation of Cyprus to investigate and determine the geothermal parameters of the ground of Cyprus at six representative sites in Cyprus, for use in the design of ground heat exchanger applications and ground thermal storage. The paper presents the importance of the Isothermal map that helps consultants to design efficiently geothermal energy systems, calculate effectively heat losses of buildings to the ground and design the thermal energy storage equipment. The importance’s of the results are analyzed by national authorities’ experts’ point of view for evaluating geothermal applications bridging in this way the gap between technical output and commercial reality

A MSFD complementary approach for the assessment of pressures, knowledge and data gaps in Southern European Seas : the PERSEUS experience

PERSEUS project aims to identify the most relevant pressures exerted on the ecosystems of the Southern European Seas (SES), highlighting knowledge and data gaps that endanger the achievement of SES Good Environmental Status (GES) as mandated by the Marine Strategy Framework Directive (MSFD). A complementary approach has been adopted, by a meta-analysis of existing literature on pressure/impact/knowledge gaps summarized in tables related to the MSFD descriptors, discriminating open waters from coastal areas. A comparative assessment of the Initial Assessments (IAs) for five SES countries has been also independently performed. The comparison between meta-analysis results and IAs shows similarities for coastal areas only. Major knowledge gaps have been detected for the biodiversity, marine food web, marine litter and underwater noise descriptors. The meta-analysis also allowed the identification of additional research themes targeting research topics that are requested to the achievement of GES. 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license.peer-reviewe

Artificial Intelligence Techniques for Modern Energy Applications

Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and nowadays are very popular. They are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems and once trained can perform prediction and generalization at very high speed. AI-based systems are being developed and deployed worldwide in a wide variety of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. This chapter presents a review of the main AI techniques such as expert systems, artificial neural networks, genetic algorithms, fuzzy logic and hybrid systems, which combine two or more techniques. It also outlines some applications in the energy sector

That’s all I know: Inferring the status of extremely data-limited stocks

There is a growing number of methods to assess data-limited stocks. However, most of these methods require at least some basic data, such as commercial catches and life history information. Meanwhile, there are many commercial stocks with an even higher level of data limitation, for which the inference of stock status and the formulation of advice remain challenging. Here, we present a stepwise approach to achieve the best possible understanding of extremely data-limited stocks and facilitate their management. As a case study we use a stock of the shrimp Plesionika edwardsii (Decapoda, Pandalidae) from the eastern Mediterranean Sea, where the only available data was a sub optimal sample of length frequencies coming from a small-scale trap fishery. We use a suite of different methods to explore and process the data, estimate the growth parameters, estimate the natural and fishing mortalities, and approximate the reference points, in order to provide a preliminary evaluation of stock status. We implement multiple methods for each step of this process, highlighting the strong and weak points of each one of them. Our approach illustrates the better insights that can be gained by applying ensembles of models, rather than a single ‘best’ model when working with limited data of poor quality. The stepwise approach we propose here is transferable to other extremely data-limited stocks to elucidate their status and inform their management.JRC.D.2-Water and Marine Resource

Uncertainty in Marine Species Distribution Modelling: Trying to Locate Invasion Hotspots for <i>Pterois miles</i> in the Eastern Mediterranean Sea

Biological invasions are considered among the largest threats to native biodiversity. The Mediterranean Sea, connecting the Indo-Pacific and Atlantic oceans, is characterized as a global marine invasion hotspot, due to a multitude of human pathways and vectors such as shipping, aquaculture, tourism, and the opening of the Suez Canal, which have led to the introduction of nearly 700 alien species into the Mediterranean Sea. Among the species introduced, the lionfish Pterois miles could be considered the fastest spreading invasive fish species of the last decade (2012–2022) and has been recorded in all countries of the eastern Mediterranean Sea, reaching as far north as Croatia. Here, we present a Bayesian additive regression tree modelling framework for an updated species distribution modelling invasion map under current and future climate conditions. All climate uncertainty sources have been used, as these are available from the Bio-Oracle, the unique marine predictors database. Important outputs of the current approach are the model’s inadequacy to accurately predict the most recent expansion of species in the Adriatic Sea, and the uncertainty estimation, that are high in areas with confirmed occurrence of individuals, in simulations that can help the decision makers and policy officers understand model limitations and take more informed actions

Uncertainty in Marine Species Distribution Modelling: Trying to Locate Invasion Hotspots for Pterois miles in the Eastern Mediterranean Sea

Biological invasions are considered among the largest threats to native biodiversity. The Mediterranean Sea, connecting the Indo-Pacific and Atlantic oceans, is characterized as a global marine invasion hotspot, due to a multitude of human pathways and vectors such as shipping, aquaculture, tourism, and the opening of the Suez Canal, which have led to the introduction of nearly 700 alien species into the Mediterranean Sea. Among the species introduced, the lionfish Pterois miles could be considered the fastest spreading invasive fish species of the last decade (2012&ndash;2022) and has been recorded in all countries of the eastern Mediterranean Sea, reaching as far north as Croatia. Here, we present a Bayesian additive regression tree modelling framework for an updated species distribution modelling invasion map under current and future climate conditions. All climate uncertainty sources have been used, as these are available from the Bio-Oracle, the unique marine predictors database. Important outputs of the current approach are the model&rsquo;s inadequacy to accurately predict the most recent expansion of species in the Adriatic Sea, and the uncertainty estimation, that are high in areas with confirmed occurrence of individuals, in simulations that can help the decision makers and policy officers understand model limitations and take more informed actions