Castel de Bonayre: riscontri archeologici e problemi topografici a Cagliari in età catalano-aragonese

Nella prima metà del XIV secolo i Catalano-Aragonesi conquistarono Castel di Cagliari e si aprirono un varco verso l’occupazione dell’intera isola di Sardegna. Nello svolgersi di tali cruciali eventi si inserisce il destino di Castel di Bonaria, che nacque come accampamento militare di Alfonso il Magnanimo, crebbe tanto da diventare la prima capitale del Regnum Sardiniae et Corsicae e rapidamente declinò fino a sparire del tutto nel corso di circa un decennio. Se della sua vita giuridica abbiamo ampia testimonianza documentaria, al contrario i dati archeologici e le notizie topografiche risultano molto scarsi e consentono di delinearne solo vaga­mente i confini e gli elementi caratteristici.  During the first half of the XIV Century the Catalan-Aragoneses conquered Castel di Cagliari and started the conquest of the entire island of Sardinia. In these crucial events it appears the destiny of Castel di Bonaria, born as military encampment of Alfonso the Magnanimous, and growned up so much to become the first capital of the Regnum Sardiniae et Corsicae and quickly declined, till to disappear completely in approximately a decade. If of its legal life we have many documentary testimoniances, on the contrary, the archaeological data and the topographical news are too insufficient and concur to only vaguely delineate its borders and its characteristic elements. 

Recognition of elementary arm movements using orientation of a tri-axial accelerometer located near the wrist

In this paper we present a method for recognising three fundamental movements of the human arm (reach and retrieve, lift cup to mouth, rotation of the arm) by determining the orientation of a tri-axial accelerometer located near the wrist. Our objective is to detect the occurrence of such movements performed with the impaired arm of a stroke patient during normal daily activities as a means to assess their rehabilitation. The method relies on accurately mapping transitions of predefined, standard orientations of the accelerometer to corresponding elementary arm movements. To evaluate the technique, kinematic data was collected from four healthy subjects and four stroke patients as they performed a number of activities involved in a representative activity of daily living, 'making-a-cup-of-tea'. Our experimental results show that the proposed method can independently recognise all three of the elementary upper limb movements investigated with accuracies in the range 91–99% for healthy subjects and 70–85% for stroke patients

Danon disease in a Sardinian family: different aspects of the same mutation-a case report

Background Danon disease (DD) is a rare X-linked disorder due to mutations in the lysosome-associated membrane protein 2 gene. It is characterized by a clinical triad of hypertrophic cardiomyopathy, skeletal myopathy, and a variable degree of intellectual disability. Case summary In this case series, we describe a mother and her son affected by DD, highlighting consistent clinical severity despite the expected variability related to gender. The mother (Case 1) presented isolated cardiac involvement, with an arrhythmogenic phenotype that evolved into severe heart failure requiring heart transplantation (HT). Danon disease was diagnosed 1 year after this event. Her son (Case 2) showed an earlier age onset of symptoms with complete atrioventricular block and fast progression of cardiac disease. Diagnosis was established 2 years after clinical presentation. He is currently listed for HT. Discussion In both of our patients, diagnostic delay was extremely long and could have been avoided by emphasizing the relevant clinical red flags. Patients affected by DD may present clinical heterogeneity in terms of natural history, age of onset, and cardiac and extracardiac involvement, even in the same family. Early diagnosis that phenotypic sex differences may impact is a crucial factor in managing patients with DD. Considering the rapid progression of cardiac disease and the poor prognosis, early diagnosis is important and close surveillance should be mandatory during follow-up

Recent Advances in the Processing and Rendering Algorithms for Computer-Generated Holography

Digital holography represents a novel media which promises to revolutionize the way the users interacts with content. This paper presents an in-depth review of the state-of-the-art algorithms for advanced processing and rendering of computer-generated holography. Open-access holographic data are selected and characterized as references for the experimental analysis. The design of a tool for digital hologram rendering and quality evaluation is presented and implemented as an open-source reference software, with the aim to encourage the approach to the holography research area, and simplify the rendering and quality evaluation tasks. Exploration studies focused on the reproducibility of the results are reported, showing a practical application of the proposed architecture for standardization activities. A final discussion on the results obtained is reported, also highlighting the future developments of the reconstruction software that is made publicly available with this work

A 14-3-3γ dimer-based scaffold bridges CtBP1-S/BARS to PI(4)KIIIβ to regulate post-Golgi carrier formation

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An Integrated Approach for the Monitoring of Brain and Autonomic Response of Children with Autism Spectrum Disorders during Treatment by Wearable Technologies

Autism Spectrum Disorders (ASD) are associated with physiological abnormalities, which are likely to contribute to the core symptoms of the condition. Wearable technologies can provide data in a semi-naturalistic setting, overcoming the limitations given by the constrained situations in which physiological signals are usually acquired. In this study an integrated system based on wearable technologies for the acquisition and analysis of neurophysiological and autonomic parameters during treatment is proposed and an application on five children with ASD is presented. Signals were acquired during a therapeutic session based on an imitation protocol in ASD children. Data were analyzed with the aim of extracting quantitative EEG (QEEG) features from EEG signals as well as heart rate and heart rate variability (HRV) from ECG. The system allowed evidencing changes in neurophysiological and autonomic response from the state of disengagement to the state of engagement of the children, evidencing a cognitive involvement in the children in the tasks proposed. The high grade of acceptability of the monitoring platform is promising for further development and implementation of the tool. In particular if the results of this feasibility study would be confirmed in a larger sample of subjects, the system proposed could be adopted in more naturalistic paradigms that allow real world stimuli to be incorporated into EEG/psychophysiological studies for the monitoring of the effect of the treatment and for the implementation of more individualized therapeutic programs

Person-centric decision support systems and ontologies: advanced architectures for the next generation of clinical applications

Today the importance of knowledge for medicine as a task requiring computer support in clinical and applied research receives a great emphasis. As pointed out by several researchers, although there is the need of a personalized treatment, nowadays there is a little knowledge about how to identify the most suitable treatment or integration of treatment for each specific patient. There is a need to bring the assessment and the therapy out of the clinical environment and develop a patient-centric home-based intervention solution requiring a minimal human involvement and therefore extremely cost effective. The strict focus on the medical setting has now broadened across the healthcare spectrum, and instead of artificial intelligence systems, it is typical to describe them as Clinical Decision Support Systems (CDSS). Pattern classification, expert and artificial intelligence systems, better described as knowledge-based CDSS, are today found an effective application and represent in perspective a real technological breakthrough. A CDSS consists of the objective and quantitative assessment of clinical data; the decision support for treatment planning through pattern classification algorithms; and the provision of warnings and motivating feedback to improve compliance and long-term outcome. Developments in computational techniques including clinical decision support systems, information processing, wireless communication and data mining hold new premises in personal health systems. Pervasive healthcare architectures are today found an effective application and represent in perspective a real technological breakthrough promoting a paradigm shift from diagnosis and treatment of patients based on symptoms to diagnosis and treatment based on risk assessment. Such architectures must be able to collect and manage a large quantity of data supporting the physicians in their decision process through a continuous pervasive remote monitoring model aimed to enhance the understanding of the dynamic disease state and personal risk. The medical knowledge is frequently updated and re-evaluated comprising new risk factors identification, new drugs and diagnostic tests, new evidences from clinical studies. The challenge faced today is to incorporate the most recent and evidence-based knowledge into personal health systems and to transform collected information into valuable knowledge and intelligence to support decision making. Several expert systems tailored to specific diseases are nowadays available in clinical research, often covering the topics addressed by European priorities. Technology can play a key role to gain the continuity of care and a person-centric model, focusing on a knowledge-based approach integrating past and current data of each patient together with statistical evidences. In currently applied care practices, the emergence of clinical symptoms allows a disease to be discovered. Only then, a diagnosis is obtained and a treatment is provided. Currently, different healthcare practice models are used. In some models, the Hospital is the core of the care and any level of technology available at the patient site may help in providing information useful for both monitoring, early diagnosis and preventive treatments. In other models dedicated call centres or point of care act as an intermediary between hospital/heath care professional and patients. Many of the solutions available today on the market follow the above-mentioned model and call centre services or point of care are used by the patients just as a complement to the hospital-centred healthcare services. In a more advanced concept focused on the empowerment, the ownership of the care service is fully taken by the individual. This model is suitable for any of the stages of an individual’s care cycle, providing prevention, early diagnosis services and personalized chronic disease management. Under this model, the technological innovations can help each persons to self-engage and manage his/her own health status, minimizing any interaction with other health care actors. Solutions fully led by the patients are the overwhelming majority of those developed by research efforts covering chronic disease management, lifestyle management and independent living. Even if, in the clinical practice this model has not been yet implemented, it can be considered as a target to be reached achieving at the same time the empowerment of the users and the reduction of workload and costs, preserving the quality and safety of care. However, this model often fails to give the expected results and research is under development. This happens for a series of concomitant causes, ranging from legal and societal obstacles, to the issues to be tackled before these wearable devices are ready for general use, up to the inappropriate use of the decision support system, as well as to win the scepticism of many healthcare professionals. Wearable devices need to be non-intrusive, easy to use, comfortable to wear, efficient in power consumption, privacy compliant, with very low failure rates and high accuracy in triggering alarms, especially if used for diagnostic purposes. The decision support system must infuse clinical knowledge into methodology and technology, thus enhancing the reliability of high-level processing systems customized to his/her personal needs represents the next critical step. The currently used approaches are only based on values of health-related parameters, often monitored instantaneously during a check-up. Moreover, the correlation across physiological, psycho-emotional, environmental and behavioural parameters are poorly explored, because the diagnosis of a disease largely depends on the experience of the individual doctors