INDAGINI NON INVASIVE SU ALCUNE COLONNE DELLA VILLA ROMANA DEL CASALE, A PIAZZA ARMERINA

Alcune indagini non invasive sono state eseguite a supporto delle prove di verifica delle colonne prospicienti il Corridoio della Grande Caccia della Villa Romana del Casale, a Piazza Armerina. Scopo del progetto di indagine è la localizzazione di eventuali perni metallici e anomalie interne nelle dieci colonne che separano il Corridoio della Grande Caccia dal Peristilio e valutare il livello di portanza delle singole colonne. A tale scopo sono state eseguite indagini georadar e soniche. Le indagini georadar sono state effettuate utilizzando un apparecchiatura munita di antenna con frequenza centrale di 1000 MHz in modalità monostatica, per ogni colonna, sono stati acquisiti 4 profili verticali nel fusto, speculari a due a due, e due profili orizzontali: uno base del capitello e l’altro alla base del capitello. Operando con apparecchiatura sonica con sonde di 20 kHz, sono state effettuate circa un centinaio di acquisizione, allo scopo di ricostruire, per ciascuna colonna, un diagramma di distribuzione delle velocità sonica (Tomografia) e indagare sull’integrità del materiale costituente

A hybrid neuro--wavelet predictor for QoS control and stability

For distributed systems to properly react to peaks of requests, their adaptation activities would benefit from the estimation of the amount of requests. This paper proposes a solution to produce a short-term forecast based on data characterising user behaviour of online services. We use \emph{wavelet analysis}, providing compression and denoising on the observed time series of the amount of past user requests; and a \emph{recurrent neural network} trained with observed data and designed so as to provide well-timed estimations of future requests. The said ensemble has the ability to predict the amount of future user requests with a root mean squared error below 0.06\%. Thanks to prediction, advance resource provision can be performed for the duration of a request peak and for just the right amount of resources, hence avoiding over-provisioning and associated costs. Moreover, reliable provision lets users enjoy a level of availability of services unaffected by load variations

Automated diagnosis of encephalitis in pediatric patients using EEG rhythms and slow biphasic complexes

Slow biphasic complexes (SBC) have been identified in the EEG of patients suffering for inflammatory brain diseases. Their amplitude, location and frequency of appearance were found to correlate with the severity of encephalitis. Other characteristics of SBCs and of EEG traces of patients could reflect the grade of pathology. Here, EEG rhythms are investigated together with SBCs for a better characterization of encephalitis. EEGs have been acquired from pediatric patients: ten controls and ten encephalitic patients. They were split by neurologists into five classes of different severity of the pathology. The relative power of EEG rhythms was found to change significantly in EEGs labeled with different severity scores. Moreover, a significant variation was found in the last seconds before the appearance of an SBC. This information and quantitative indexes characterizing the SBCs were used to build a binary classification decision tree able to identify the classes of severity. True classification rate of the best model was 76.1% (73.5% with leave-one-out test). Moreover, the classification errors were among classes with similar severity scores (precision higher than 80% was achieved considering three instead of five classes). Our classification method may be a promising supporting tool for clinicians to diagnose, assess and make the follow-up of patients with encephalitis

The contribution of the supplementary motor area to explicit and implicit timing: A high-definition transcranial Random Noise Stimulation (HD-tRNS) study

It is becoming increasingly accepted that timing tasks, and underlying temporal processes, can be partitioned on the basis of whether they require an explicit or implicit temporal judgement. Most neuroimaging studies of timing associated explicit timing tasks with activation of the supplementary motor area (SMA). However, transcranial magnetic stimulation (TMS) studies perturbing SMA functioning across explicit timing tasks have generally reported null effects, thus failing to causally link SMA to explicit timing. The present study probed the involvement of SMA in both explicit and implicit timing tasks within a single experiment and using HighDefinition transcranial Random Noise Stimulation (HD-tRNS), a previously less used technique in studies of the SMA. Participants performed two tasks that comprised the same stimulus presentation but differed in the received task instructions, which might or might not require explicit temporal judgments. Results showed a significant HD-tRNS-induced shift of perceived durations (i.e., overestimation) in the explicit timing task, whereas there was no modulation of implicit timing by HD-tRNS. Overall, these results provide initial noninvasive brain stimulation evidence on the contribution of the SMA to explicit and implicit timing tasks

An entropy evaluation algorithm to improve transmission efficiency of compressed data in pervasive healthcare mobile sensor networks

Data transmission is the most critical operation for mobile sensors networks in term of energy waste. Particularly in pervasive healthcare sensors network it is paramount to preserve the quality of service also by means of energy saving policies. Communication and data transmission are among the most critical operation for such devises in term of energy waste. In this paper we present a novel approach to increase battery life-span by means of shorter transmission due to data compression. On the other hand, since this latter operation has a non-neglectable energy cost, we developed a compression efficiency estimator based on the evaluation of the absolute and relative entropy. Such algorithm provides us with a fast mean for the evaluation of data compressibility. Since mobile wireless sensor networks are prone to battery discharge-related problems, such an evaluation can be used to improve the electrical efficiency of data communication. In facts the developed technique, due to its independence from the string or file length, is extremely robust both for small and big data files, as well as to evaluate whether or not to compress data before transmission. Since the proposed solution provides a quantitative analysis of the source's entropy and the related statistics, it has been implemented as a preprocessing step before transmission. A dynamic threshold defines whether or not to invoke a compression subroutine. Such a subroutine should be expected to greatly reduce the transmission length. On the other hand a data compression algorithm should be used only when the energy gain of the reduced transmission time is presumably greater than the energy used to run the compression software. In this paper we developed an automatic evaluation system in order to optimize the data transmission in mobile sensor networks, by compressing data only when this action is presumed to be energetically efficient. We tested the proposed algorithm by using the Canterbury Corpus as well as standard pictorial data as benchmark test. The implemented system has been proven to be time-inexpensive with respect to a compression algorithm. Finally the computational complexity of the proposed approach is virtually neglectable with respect to the compression and transmission routines themselves

A Cascade Neural Network Architecture investigating Surface Plasmon Polaritons propagation for thin metals in OpenMP

Surface plasmon polaritons (SPPs) confined along metal-dielectric interface have attracted a relevant interest in the area of ultracompact photonic circuits, photovoltaic devices and other applications due to their strong field confinement and enhancement. This paper investigates a novel cascade neural network (NN) architecture to find the dependance of metal thickness on the SPP propagation. Additionally, a novel training procedure for the proposed cascade NN has been developed using an OpenMP-based framework, thus greatly reducing training time. The performed experiments confirm the effectiveness of the proposed NN architecture for the problem at hand

Digitization in the Market for Entrepreneurial Finance: Innovative Business Models and New Financing Channels

Digitization creates new financial channels that complement traditional intermediaries, but may raise concerns over fraud, cybersecurity, or bubbles. Artificial intelligence and machine learning change the way in which traditional investors work. This special issue focuses on economic, cultural, and regulatory determinants of fintech development, and on the new forms of information production and processing engendered by digital entrepreneurial finance. We provide a general overview of digitization in the market for entrepreneurial finance, illustrate how the different articles in the special issue contribute to advance our knowledge, and identify promising avenues for research

Low-protein diets in CKD: how can we achieve them? A narrative, pragmatic review

Low-protein diets (LPDs) have encountered various fortunes, and several questions remain open. No single study, including the famous Modification of Diet in Renal Disease, was conclusive and even if systematic reviews are in favour of protein restriction, at least in non-diabetic adults, implementation is lagging. LPDs are considered difficult, malnutrition is a threat and compliance is poor. LPDs have been reappraised in this era of reconsideration of dialysis indications and timing. The definition of a normal-adequate protein diet has shifted in the overall population from 1 to 1.2 to 0.8 g/kg/day. Vegan-vegetarian diets are increasingly widespread, thus setting the groundwork for easier integration of moderate protein restriction in Chronic Kidney Disease. There are four main moderately restricted LPDs (0.6 g/kg/day). Two of them require careful planning of quantity and quality of food: a â € traditionalâ €™ one, with mixed proteins that works on the quantity and quality of food and a vegan one, which integrates grains and legumes. Two further options may be seen as a way to simplify LPDs while being on the safe side for malnutrition: adding supplements of essential amino and keto acids (various doses) allows an easier shift from omnivorous to vegan diets, while protein-free food intake allows for an increase in calories. Very-low-protein diets (vLPDs: 0.3 g/kg/day) combine both approaches and usually require higher doses of supplements. Moderately restricted LPDs may be adapted to virtually any cuisine and should be tailored to the patients' preferences, while vLPDs usually require trained, compliant patients; a broader offer of diet options may lead to more widespread use of LPDs, without competition among the various schemas

Correlazioni tra le velocit\ue0 ultrasoniche e le caratteristiche petrografiche in ceramiche archeologiche: un primo approccio metodologico

L\u2019analisi delle velocit\ue0 degli ultrasuoni permette di investigare i caratteri tessiturali e strutturali e di individuare la presenza di eventuali difetti localizzati all\u2019interno del campione. La loro diffusione negli studi archeometrici \ue8 legata alla non distruttivit\ue0 e alla possibilit\ue0 di fornire risultati accurati in tempo reale. In questo lavoro sono state effettuate numerose analisi petrografiche in sezione sottile e misure di velocit\ue0 di propagazione degli ultrasuoni su reperti ceramici di interesse archeologico. In particolare sono stati selezionati ed analizzati ceramiche preistoriche ed anfore da trasporto del V-IV sec. a.C., caratterizzati da differente granulometria, composizione e struttura. Da questo primo approccio \ue8 stato possibile evidenziare che il parametro petrografico che influenza maggiormente la velocit\ue0 degli ultrasuoni \ue8 la forma e la disposizione spaziale dei pori, e la dimensione media degli inclusi, mentre correlazioni poco significative si ottengono prendendo in considerazione la percentuale e il tipo di inerte presente nell\u2019impasto ceramico