The first ultra-high resolution Digital Terrain Model of the shallow-water sector around Lipari Island (Aeolian Islands, Italy)

Very high resolution bathymetric map obtained through multibeam echosounders data are crucial to generate accurate Digital Terrain Models from which the morphological setting of active volcanic areas can be analyzed in detail. Here we show and discuss the main results from the first multibeam bathymetric survey performed in shallow-waters around the island of Lipari, the largest and the most densely populated of the Aeolian Islands (southern Italy). Data have been collected in the depth range of 0.1-150 m and complete the already existent high-resolution multibeam bathymetry realized between 100 and 1300 m water depth. The new ultrahigh resolution bathymetric maps at 0.1-0.5 m provide new insights on the shallow seafloor of Lipari, allowing to detail a large spectrum of volcanic, erosive-depositional and anthropic features. Moreover, the presented data allow outlining the recent morphological evolution of the shallow coastal sector of this active volcanic island, indicating the presence of potential geo-hazard factors in shallow waters

A Heterosynaptic Learning Rule for Neural Networks

In this article we intoduce a novel stochastic Hebb-like learning rule for neural networks that is neurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the pre- and postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean learning time increases with the number of patterns to be learned polynomially, indicating efficient learning.Comment: 19 page

Multibeam bathymetry of Lipari island

Very high resolution bathymetric map obtained through multibeam echo-sounders data are crucial to generate accurate Digital Elevation Terrain Models from which the morphological setting of active volcanic areas can be analyzed in detail. Here we show and discuss the main results from the first multibeam bathymetric survey performed in shallow-waters around the Island of Lipari, the largest and the most densely populated of the Aeolian islands (Southern Italy). Data have been collected in the depth range of 0.1-150 m and complete the already existent high-resolution multibeam bathymetry realized between 100 and 1300 m water depth. The new ultra-high resolution bathymetric maps at 0.1-0.5 m provide new insights on the shallow seafloor of Lipari, allowing to detail a large spectrum of volcanic, erosive-depositional and anthropic features. Moreover, the presented data allow outlining the recent morphological evolution of the shallow coastal sector of this active volcanic island, indicating the presence of potential geo-hazard factors in shallow waters

ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application

This paper provides a description of ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model. This framework can be used to study the atmospheric boundary layer, surface layer, or the exchange of gases, moisture, heat, and momentum between the land surface and the lower atmosphere. The general aim of the framework is to allow the assimilation of various streams of observations (fluxes, mixing ratios at multiple heights, etc.) to estimate model parameters, thereby obtaining a physical model that is consistent with a diverse set of observations. The framework allows the retrieval of parameters in an objective manner and enables the estimation of information that is difficult to obtain directly by observations, for example, free tropospheric mixing ratios or stomatal conductances. Furthermore, it allows the estimation of possible biases in observations. Modelling the carbon cycle at the ecosystem level is one of the main intended fields of application. The physical model around which the framework is constructed is relatively simple yet contains the core physics to simulate the essentials of a well-mixed boundary layer and of the land–atmosphere exchange. The model includes an explicit description of the atmospheric surface layer, a region where scalars show relatively large gradients with height. An important challenge is the strong non-linearity of the model, which complicates the estimation of the best parameter values. The constructed adjoint of the tangent linear model can be used to mitigate this challenge. The adjoint allows for an analytical gradient of the objective cost function, which is used for minimisation of this function. An implemented Monte Carlo way of running ICLASS can further help to handle non-linearity and provides posterior statistics on the estimated parameters. The paper provides a technical description of the framework, includes a validation of the adjoint code, in addition to tests for the full inverse modelling framework, and a successful example application for a grassland in the Netherlands.</p

Failure to Respond after Reinstatement of Antidepressant Medication:A Systematic Review

BACKGROUND: Following remission of an anxiety disorder or a depressive disorder, antidepressants are frequently discontinued and in the case of symptom occurrence reinstated. Reinstatement of antidepressants seems less effective in some patients, but an overview is lacking. This systematic review aimed to provide insight into the magnitude and risk factors of response failure after reinstatement of antidepressants in patients with anxiety disorders, depressive disorders, obsessive-compulsive disorder (OCD), or posttraumatic stress disorder (PTSD). METHOD: PubMed, Embase, and trial registers were systematically searched for studies in which patients: (1) had an anxiety disorder, a depressive disorder, OCD, or PTSD and (2) experienced failure to respond after reinstatement of a previously effective antidepressant. RESULTS: Ten studies reported failure to respond following antidepressant reinstatement. The phenomenon was observed in 16.5% of patients with a depressive disorder, OCD, and social phobia and occurred in all common classes of antidepressants. The range of response failure was broad, varying between 3.8 and 42.9% across studies. No risk factors for failure to respond were investigated. The overall study quality was limited. CONCLUSION: Research investigating response failure is scarce and the study quality limited. Response failure occurred in a substantial minority of patients. Contributors to the relevance of this phenomenon are the prevalence of the investigated disorders, the number of patients being treated with antidepressants, and the occurrence of response failure for all common classes of antidepressants. This systematic review highlights the need for studies systematically investigating this phenomenon and associated risk factors

Sound localization with bilateral bone conduction devices

Purpose To investigate sound localization in patients bilaterally fitted with bone conduction devices (BCDs). Additionally, clinically applicable methods to improve localization accuracy were explored. Methods Fifteen adults with bilaterally fitted percutaneous BCDs were included. At baseline, sound localization, (un)aided pure-tone thresholds, device use, speech, spatial and qualities of hearing scale (SSQ) and York hearing-related quality of life (YHRQL) questionnaire were measured. Settings to optimize sound localizing were added to the BCDs. At 1 month, sound localization was assessed again and localization was practiced with a series of sounds with visual feedback. At 3 months, localization performance, device use and questionnaire scores were determined again. Results At baseline, one patient with congenital hearing loss demonstrated near excellent localization performance and four other patients (three with congenital hearing loss) localized sounds (quite) accurately. Seven patients with acquired hearing loss were able to lateralize sounds, i.e. identify whether sounds were coming from the left or right side, but could not localize sounds accurately. Three patients (one with congenital hearing loss) could not even lateralize sounds correctly. SSQ scores were significantly higher at 3 months. Localization performance, device use and YHRQL scores were not significantly different between visits. Conclusion In this study, the majority of experienced bilateral BCD users could lateralize sounds and one third was able to localize sounds (quite) accurately. The localization performance was robust and stable over time. Although SSQ scores were increased at the last visit, optimizing device settings and a short practice session did not improve sound localization