Seasonal renewal time variability in the Curonian Lagoon caused by atmospheric and hydrographical forcing

The aim of this study was to investigate the variability of the water exchanges in the Curonian Lagoon based on the hydraulic regime and the atmospheric forcings. A finite element hydrodynamic model has been applied to the Curonian Lagoon to simulate the circulation patterns for 10 years. With the help of a transport–diffusion model, the salinity distribution and the renewal times of the Curonian Lagoon have been investigated when forced by river runoff, wind, and Baltic Sea level fluctuations. The hydrodynamic model has been validated using in situ salinity measurements. Model results show that the variability depends mainly on seasonal changes in hydrographic forcing and on the dominant wind regimes that prevail over the Curonian Lagoon. Exchanges between the southern and the northern part of the lagoon mostly depend on the wind forcing and are much less influenced by the river discharge. However, when looking at the water renewal time, the most important factor is the river discharge into the lagoon. Other physical forcings only marginally determine the renewal time, and not even ice cover is able to influence it. Even if ice cover strongly inhibits the exchanges between the southern and northern lagoon, it is basically not able to change the absolute value of the renewal times

ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants

A new model for transport and fate of chemicals in the aquatic environment is presented. The tool, named ChemicalDrift, is integrated into the open-source Lagrangian framework OpenDrift and is hereby presented for organic compounds. The supported chemical processes include the degradation, the volatilization, and the partitioning between the different phases that a target chemical can be associated with in the aquatic environment, e.g. dissolved, bound to suspended particles, or deposited to the seabed sediments. The dependencies of the chemical processes on changes in temperature, salinity, and particle concentration are formulated and implemented. The chemical-fate modelling is combined with wide support for hydrodynamics by the integration within the Lagrangian framework which provides e.g. advection by ocean currents, diffusion, wind-induced turbulent mixing, and Stokes drift generated by waves. A flexible interface compatible with a wide range of available metocean data is made accessible by the integration, making the tool easily adaptable to different spatio-temporal scales and fit for modelling of complex coastal regions. Further inherent capabilities of the Lagrangian approach include the seamless tracking and separation of multiple sources, e.g. pollutants emitted from ships or from rivers or water treatment plants. Specific interfaces to a dataset produced by a model of emissions from shipping and to an unstructured-grid oceanographic model of the Adriatic Sea are provided. The model includes a database of chemical parameters for a set of poly-aromatic hydrocarbons and a database of emission factors for different chemicals found in discharged waters from sulfur emission abatement systems in marine vessels. A post-processing tool for generating mean concentrations of a target chemical, over customizable spatio-temporal grids, is provided. Model development and simulation results demonstrating the functionalities of the model are presented, while tuning of parameters, validation, and reporting of numerical results are planned as future activities. The ChemicalDrift model flexibility, functionalities, and potential are demonstrated through a selection of examples, introducing the model as a freely available and open-source tool for chemical fate and transport that can be applied to assess the risks of contamination by organic pollutants in the aquatic environment

The effect of music-induced emotion on visual-spatial learning in people with Parkinson's disease: A pilot study

Introduction: Emotional states have been shown to influence cognitive processes including visual-spatial learning. Parkinson's Disease (PD), besides manifesting with the cardinal motor symptoms, presents cognitive and affective disturbances. Here we aimed at investigating whether manipulation of the emotional state by means of music was able to influence the performance of a visual-spatial learning task in a group of PD participants. Methods: Ten PD patients and 11 healthy elderly (ELD) were asked to perform a visual-spatial learning task while listening two musical pieces evoking a neutral emotion or fear. Targets were presented on a screen in a preset order over four blocks and subjects were asked to learn the sequence order by attending to the display. At the end of each block, participants were asked to verbally recall the sequence and a score was assigned (Verbal Score, VS). Results: Analysis of variance-type statistic test on the VS disclosed a significant effect of Music and sequence Blocks (p = 0.01 and p < 0.001, respectively) and a significant interaction between Group and sequence Blocks. Sequence learning occurred across the training period in both groups, but PD patients were slower than ELD and at the end of the training period learning performance was worse in PD with respect to ELD. In PD patients, like in ELD, fear-inducing music has a detrimental effect on visual-spatial learning performances, which are slower and decreased. Conclusion: These findings confirm an impairment in visual-spatial learning in PD and indicates that the emotional state influences this learning ability similarly to healthy controls

Trunk motion analysis: a systematic review from a clinical and methodological perspective

INTRODUCTION: This systematic literature review aims to check the current state of affairs of non-gait-related optoelectronic trunk movement analysis; results have been analyzed from a clinical and a methodological perspective. EVIDENCE ACQUISITION: Extensive research was performed on all papers published until December 31st, 2015, dealing with trunk movement analysis assessed by optoelectronic systems, excluding those related to gait. The research was performed on the 14th of January 2016 on three databases: Scopus, Science Direct and Pubmed. A reference search and expert consultation were also performed. EVIDENCE SYNTHESIS: Out of a total number of 8431 papers, 45 were deemed relevant: they included 1334 participants, 57.9% healthy, with age range 8-85. Few studies considered the whole trunk, and none focused on each vertebra independently: the trunk was almost always divided into three segments. Thirteen studies included 20 or more markers. Most of the papers focused mainly on the biomechanics of various movements; the lumbar area and low back pain were the most studied region and pathology respectively. CONCLUSIONS: This study has shown the relative scarcity of current literature focusing on trunk motion analysis. In clinical terms, results were sparse. The only quite well represented group of papers focused on the lumbar spine and pathologies, but the scarcity of individuals evaluated make the results questionable. The use of optoelectronic systems in the evaluation of spine movement is a growing research area. Nevertheless, no standard protocols have been developed so far. Future research is needed to define a precise protocol in terms of number and position of markers along the spine and movements and tasks to be evaluated

Web conversations about complementary and alternative medicines and cancer: Content and sentiment analysis

Background: The use of complementary and alternative medicine (CAM) among cancer patients is widespread and mostly self-administrated. Today, one of the most relevant topics is the nondisclosure of CAM use to doctors. This general lack of communication exposes patients to dangerous behaviors and to less reliable information channels, such as the Web. The Italian context scarcely differs from this trend. Today, we are able to mine and analyze systematically the unstructured information available in the Web, to get an insight of people's opinions, beliefs, and rumors concerning health topics. Objective: Our aim was to analyze Italian Web conversations about CAM, identifying the most relevant Web sources, therapies, and diseases and measure the related sentiment. Methods: Data have been collected using the Web Intelligence tool ifMONITOR. The workflow consisted of 6 phases: (1) eligibility criteria definition for the ifMONITOR search profile; (2) creation of a CAM terminology database; (3) generic Web search and automatic filtering, the results have been manually revised to refine the search profile, and stored in the ifMONITOR database; (4) automatic classification using the CAM database terms; (5) selection of the final sample and manual sentiment analysis using a 1-5 score range; (6) manual indexing of the Web sources and CAM therapies type retrieved. Descriptive univariate statistics were computed for each item: absolute frequency, percentage, central tendency (mean sentiment score [MSS]), and variability (standard variation Ò). Results: Overall, 212 Web sources, 423 Web documents, and 868 opinions have been retrieved. The overall sentiment measured tends to a good score (3.6 of 5). Quite a high polarization in the opinions of the conversation partaking emerged from standard variation analysis (δ≥1). In total, 126 of 212 (59.4%) Web sources retrieved were nonhealth-related. Facebook (89; 21%) and Yahoo Answers (41; 9.7%) were the most relevant. In total, 94 CAM therapies have been retrieved. Most belong to the "biologically based therapies or nutrition" category: 339 of 868 opinions (39.1%), showing an MSS of 3.9 (δ=0.83). Within nutrition, "diets" collected 154 opinions (18.4%) with an MSS of 3.8 (δ=0.87); "food as CAM" overall collected 112 opinions (12.8%) with a MSS of 4 (δ=0.68). Excluding diets and food, the most discussed CAM therapy is the controversial Italian "Di Bella multitherapy" with 102 opinions (11.8%) with an MSS of 3.4 (δ=1.21). Breast cancer was the most mentioned disease: 81 opinions of 868. Conclusions: Conversations about CAM and cancer are ubiquitous. There is a great concern about the biologically based therapies, perceived as harmless and useful, under-rating all risks related to dangerous interactions or malnutrition. Our results can be useful to doctors to be aware of the implications of these beliefs for the clinical practice. Web conversation exploitation could be a strategy to gain insights of people's perspective for other controversial topics

Is a wearable sensor-based characterisation of gait robust enough to overcome differences between measurement protocols? A multi-centric pragmatic study in patients with multiple sclerosis

Inertial measurement units (IMUs) allow accurate quantification of gait impairment of people with multiple sclerosis (pwMS). Nonetheless, it is not clear how IMU-based metrics might be influenced by pragmatic aspects associated with clinical translation of this approach, such as data collection settings and gait protocols. In this study, we hypothesised that these aspects do not significantly alter those characteristics of gait that are more related to quality and energetic efficiency and are quantifiable via acceleration related metrics, such as intensity, smoothness, stability, symmetry, and regularity. To test this hypothesis, we compared 33 IMU-based metrics extracted from data, retrospectively collected by two independent centres on two matched cohorts of pwMS. As a worst-case scenario, a walking test was performed in the two centres at a different speed along corridors of different lengths, using different IMU systems, which were also positioned differently. The results showed that the majority of the temporal metrics (9 out of 12) exhibited significant between-centre differences. Conversely, the between-centre differences in the gait quality metrics were small and comparable to those associated with a test-retest analysis under equivalent conditions. Therefore, the gait quality metrics are promising candidates for reliable multi-centric studies aiming at assessing rehabilitation interventions within a routine clinical context

A flexible <i>z</i>-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)

We propose a discrete multilayer shallow water model based on z-layers, which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a classical two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of surface layers with very small or negative thickness. With ad hoc treatment of advection terms at nonconformal edges that may appear owing to insertion/removal operations, mass conservation and the compatibility of the tracer equation with the continuity equation are preserved at a discrete level. This algorithm called z-surface-adaptive, can be reduced, as a particular case when all layers are moving, to the z-star coordinate. With idealized and realistic numerical experiments, we compare the z-surface-adaptive against z-star and we show that it can be used to simulate coastal flows effectively.</p

Modelling the Quality of Bathing Waters in the Adriatic Sea

The aim of this study is to develop a relocatable modelling system able to describe the microbial contamination that affects the quality of coastal bathing waters. Pollution events are mainly triggered by urban sewer outflows during massive rainy events, with relevant negative consequences on the marine environment and tourism and related activities of coastal towns. A finite element hydrodynamic model was applied to five study areas in the Adriatic Sea, which differ for urban, oceanographic and morphological conditions. With the help of transport-diffusion and microbial decay modules, the distribution of Escherichia coli was investigated during significant events. The numerical investigation was supported by detailed in situ observational datasets. The model results were evaluated against water level, sea temperature, salinity and E. coli concentrations acquired in situ, demonstrating the capacity of the modelling suite in simulating the circulation in the coastal areas of the Adriatic Sea, as well as several main transport and diffusion dynamics, such as riverine and polluted waters dispersion. Moreover, the results of the simulations were used to perform a comparative analysis among the different study sites, demonstrating that dilution and mixing, mostly induced by the tidal action, had a stronger effect on bacteria reduction with respect to microbial decay. Stratification and estuarine dynamics also play an important role in governing microbial concentration. The modelling suite can be used as a beach management tool for improving protection of public health, as required by the EU Bathing Water Directive

Actigraphic Sensors Describe Stroke Severity in the Acute Phase: Implementing Multi-Parametric Monitoring in Stroke Unit

Actigraphy is a tool used to describe limb motor activity. Some actigraphic parameters, namely Motor Activity (MA) and Asymmetry Index (AR), correlate with stroke severity. However, a long-lasting actigraphic monitoring was never performed previously. We hypothesized that MA and AR can describe different clinical conditions during the evolution of the acute phase of stroke. We conducted a multicenter study and enrolled 69 stroke patients. NIHSS was assessed every hour and upper limbs’ motor activity was continuously recorded. We calculated MA and AR in the first hour after admission, after a significant clinical change (NIHSS ± 4) or at discharge. In a control group of 17 subjects, we calculated MA and AR normative values. We defined the best model to predict clinical status with multiple linear regression and identified actigraphic cut-off values to discriminate minor from major stroke (NIHSS ≥ 5) and NIHSS 5–9 from NIHSS ≥ 10. The AR cut-off value to discriminate between minor and major stroke (namely NIHSS ≥ 5) is 27% (sensitivity = 83%, specificity = 76% (AUC 0.86 p < 0.001), PPV = 89%, NPV = 42%). However, the combination of AR and MA of the non-paretic arm is the best model to predict NIHSS score (R2: 0.482, F: 54.13), discriminating minor from major stroke (sensitivity = 89%, specificity = 82%, PPV = 92%, NPV = 75%). The AR cut-off value of 53% identifies very severe stroke patients (NIHSS ≥ 10) (sensitivity = 82%, specificity = 74% (AUC 0.86 p < 0.001), PPV = 73%, NPV = 82%). Actigraphic parameters can reliably describe the overall severity of stroke patients with motor symptoms, supporting the addition of a wearable actigraphic system to the multi-parametric monitoring in stroke units