1,053 research outputs found
Mental Activity During Episodes of Sleepwalking, Night Terrors or Confusional Arousals: Differences Between Children and Adults
No full textAnna Castelnovo,1– 3 Giuseppe Loddo,4 Federica Provini,5,6 Silvia Miano,1 Mauro Manconi1,2,7 1Sleep Medicine Unit, Neurocenter of Southern Switzerland, Ospedale Civico, Lugano, Switzerland; 2Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland; 3University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; 4Department of Primary Care, Azienda USL di Bologna, Bologna, Italia; 5IRCSS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italia; 6Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italia; 7Department of Neurology, University Hospital, Inselspital, Bern, SwitzerlandCorrespondence: Anna Castelnovo Ospedale Civico Via Tesserete 46, Lugano, 6900, SwitzerlandEmail [email protected]/Background: Night terrors, sleepwalking and confusional arousals are behavioral manifestations of incomplete awakenings from sleep. According to international diagnostic criteria, these behaviors occur in the absence of any mental experience, or in the presence of very limited cognition or dream imagery (eg, a single visual scene). The aim of this study was to systematically and retrospectively investigate the mental content associated with sleep terrors and/or sleepwalking in both children and adults.Patients and Methods: Forty-five consecutive patients referred for a diagnosis of disorders of arousal (DOA) of all subtypes (sleepwalking/sleep terrors/confusional arousals) (25 adults: 30 ± 6 y, 15 females; 20 children: 10 ± 3 y, 6 females) underwent a detailed semi-structured interview about the mental content associated with their nocturnal episodes. The interview was comprehensive of specific questions about their subjective recall rate, several content details (characters, emotions, actions and setting/context), and hallucinatory or dissociative experiences during clinical episodes. Patients’ reports were classified for complexity (Orlinsky scale) and content (Hall and Van de Castle categories).Results: More than two-third of the children (n = 14) could not recall any mental activity associated with their episodes, whereas more than two-third (n = 16) of the adults recalled at least one mental experience. Half of the adult patients (n = 8) estimated that a specific mental content was subjectively present around 50% or more of the times. Seven adults and one child described clear and vivid hallucinatory experiences of “dreamed” objects or characters projected onto their real home environment, in the absence of any reality testing. Five adults and two children described one or more dissociative experiences. The content of the collected reports was dominated by dynamic actions acted out from a self-perspective, often with apprehension and in response to misfortune and danger, in a home-setting environment.Conclusion: These results suggest that current diagnostic criteria are tailored around the typical presentation of DOA in children, and do not always fit to adult patients with DOA. Furthermore, they support the concept that consciousness may reemerge in DOA patients during clinical episodes, in a peculiar dissociated, psychotic-like form.Keywords: somnambulism, confusional arousal, parasomnia, dream, consciousness, mental content, amnesi
A32 A33 A34 A. Bizzarri, P. Crupi, S. de Lorenzo, and M. Loddo Thermal effects on the time occurrence of earthquake failures: a deterministic approach.
No full textDeep learning based pipelines for Alzheimer's disease diagnosis: A comparative study and a novel deep-ensemble method
No full textBackground: Alzheimer's disease is a chronic neurodegenerative disease that destroys brain cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are not yet fully understood, and there is no curative treatment. However, neuroimaging tools currently offer help in clinical diagnosis, and, recently, deep learning methods have rapidly become a key methodology applied to these tools. The reason is that they require little or no image preprocessing and can automatically infer an optimal representation of the data from raw images without requiring prior feature selection, resulting in a more objective and less biased process. However, training a reliable model is challenging due to the significant differences in brain image types. Methods: We aim to contribute to the research and study of Alzheimer's disease through computer-aided diagnosis (CAD) by comparing different deep learning models. In this work, there are three main objectives: i) to present a fully automated deep-ensemble approach for dementia-level classification from brain images, ii) to compare different deep learning architectures to obtain the most suitable one for the task, and (iii) evaluate the robustness of the proposed strategy in a deep learning framework to detect Alzheimer's disease and recognise different levels of dementia. The proposed approach is specifically designed to be potential support for clinical care based on patients' brain images. Results: Our strategy was developed and tested on three MRI and one fMRI public datasets with heterogeneous characteristics. By performing a comprehensive analysis of binary classification (Alzheimer's disease status or not) and multiclass classification (recognising different levels of dementia), the proposed approach can exceed state of the art in both tasks, reaching an accuracy of 98.51% in the binary case, and 98.67% in the multiclass case averaged over the four different data sets. Conclusion: We strongly believe that integrating the proposed deep-ensemble approach will result in robust and reliable CAD systems, considering the numerous cross-dataset experiments performed. Being tested on MRIs and fMRIs, our strategy can be easily extended to other imaging techniques. In conclusion, we found that our deep-ensemble strategy could be efficiently applied for this task with a considerable potential benefit for patient management
A Combination of Visual and Temporal Trajectory Features for Cognitive Assessment in Smart Home
No full textThe rapid increase of the elderly population and new advances in pervasive computing technologies allow innovative tools and applications to support independent living for frail people and identify early symptoms of health problems, including neurodegenerative disorders. Among several studies reported in the literature, monitoring locomotion traces to detect symp-toms of cognitive impairment has gained increasing attention. Therefore, in this work, we propose a novel technique for the recognition of locomotion patterns related to cognitive decline based on sensor data acquired in smart homes. In particular, we introduce a vision-based method to graphically represent indoor trajectories with random rotation, using different handcrafted features designed for image analysis tasks and combined with features extracted directly from spatio-temporal sequences of movements. Experiments on a real-world dataset acquired in a smart-home test-bed show that the proposed approach achieves promising results.</p
Cryptocurrency scams: analysis and perspectives
No full textSince the inception of Bitcoin in 2009, the market of cryptocurrencies has grown beyond the initial expectations, as witnessed by the thousands of tokenised assets available on the market, whose daily trades amount to dozens of USD billions. The pseudonymity features of these cryptocurrencies have attracted the attention of cybercriminals, who exploit them to carry out potentially untraceable scams. The wide range of cryptocurrency-based scams observed over the last ten years has fostered the research on the analysis of their effects, and the development of techniques to counter them. However, doing research in this field requires addressing several challenges: for instance, although a few data sources about cryptocurrency scams are publicly available, they often contain incomplete or misclassified data. Further, there is no standard taxonomy of scams, which leads to ambiguous and incoherent interpretations of their nature. Indeed, the unavailability of reliable datasets makes it difficult to train effective automatic classifiers that can detect and analyse cryptocurrency scams. In this paper, we perform an extensive review of the scientific literature on cryptocurrency scams, which we systematise according to a novel taxonomy. By collecting and homogenising data from different public sources, we build a uniform dataset of thousands of cryptocurrency scams.We devise an automatic tool that recognises scams and classifies them according to our taxonomy.We assess the effectiveness of our tool through standard performance metrics.We also give an in-depth analysis of the classification results, offering several insights into threat types, from their features to their connection with other types. Finally, we provide a set of guidelines that policymakers could follow to improve user protection against cryptocurrency scams
A region proposal approach for cells detection and counting from microscopic blood images
No full textIn this paper, we propose a novel and efficient method for detecting and quantifying red cells from a microscopic blood image. The proposed system is based on a region proposal approach, namely the Edge Boxes, considered as the state-of-art region proposal method. Incorporating knowledge-based constraints into the detection process by Edge Boxes we can find cells proposals rapidly and efficiently. Experimental results on a well-known public dataset show both improved accuracy and increased over the state-of-art
New developments on front-end electronics for the CMS resistive plate chambers
No full textA novel version of the front-end electronics for the CMS resistive plate chambers is described. It is based on a new front-end ASIC, designed and manufactured in the 0.8 mu m BiCMOS technology by Austria Mikro Syteme. The main improvements with respect to the previous version (Loddo et al., Proceedings of the Fourth International Workshop on Resistive Plate Chambers and related Detectors, Napoli, 15-16 October 1997) concern the input impedance, the threshold uniformity and the timing performance. Simulation and test results will be shown, together with a brief description of the automatic test system for both front-end chip and board. (5 refs)
Architecture of a general purpose embedded Slow-Control Adapter ASIC for future high-energy physics experiments
No full textThis work is aimed at defining the architecture of a new digital ASIC, namely Slow-Control Adapter (SCA), which will be designed in a commercial 130-nm CMOS technology. This chip will be embedded within a high-speed data acquisition optical link (GBT) to control and monitor the front-end electronics in future high-energy physics experiments. The GBT link provides a transparent transport layer between the SCA and control electronics in the counting room. The proposed SCA supports a variety of common bus protocols to interface with end-user general-purpose electronics. Between the GBT and the SCA a standard 100 Mb/s IEEE-802.3 compatible protocol will be implemented. This standard protocol allows off-line tests of the prototypes using commercial components that support the same standard. The project is justified because embedded applications in modern large HEP experiments require particular care to assure the lowest possible power consumption, still offering the highest reliability demanded by very large particle detectors
Applicazione di un metodo di analisi geomorfometrica a supporto della cartografia pedologica in Sardegna
No full textThe Autonomous Region of Sardinia has recently funded the first batch of the " Land Unit and Soil Capability Map of Sardinia " at scale 1:50,000, as a support tool for spatial planning in coastal areas. The morphometric study carried out within the project starts from the need to develop thematic maps describing the physiographic units defined as areal homogeneity with type lithological and geomorphologic process . It is therefore proposed an approach based on geological mapping reclassified in terms of parent material and the elaboration of a DEM. This work is focused on the extraction of morphometric parameters from the DEM , and in particular on the classification of values of steepness integrated in an analysis model with the values of curvature. The product obtained is a classification of the territory in concave and convex shapes with positive and negative values and rising classes with different degrees of steepness .The first results for the two sample areas of Pula - Capoterra and Muravera - Quirra surface, net of flat areas affected by shell debris and Quaternary alluvial , has about 54,800 of which were made 836 observations , show how of parent material consisting metamorphites and plutonites of various types and from lave a composition intermediate - basic distribution of soil types is strongly influenced by the concavity and convexity of the forms .. The values of steepness do not seem to have an influence on the distribution of soil types . It is therefore considered that the methodological approach contributes significantly to the rock types considered , the realization of cards containing semi- detailed soil information and based on soil - landscape paradigm
Design and submission of rad-tolerant circuits for future front-end electronics at S-LHC
No full textThis work is aimed at defining the architecture of a new digital ASIC, namely Slow Control Architecture (SCA), which will be designed and fabricated in a commercial 130 nm CMOS technology. This chip will be embedded within a high-speed data acquisition optical link (GBT) to control and monitor the front-end electronics proposed for future high-energy physics experiments at the Super-Large Hadron Collider (SLHC), CERN, Geneva. The GBT link provides a transparent transport layer between the SCA and the control electronics in the counting room. It will be provided with rad-hard redundant logic for critical circuits. The project follows a set of designs that were recently developed via a 250 nm CMOS technology for LHC experiments. Since this 250 nm specific technology used to design ASICs for the LHC will no longer be available as it was in the past, requesting an update technology for future experiments must be satisfied in any case. A test chip that implements three different redundant methodologies against single event effects is also described
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