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

Excitonic Effects in Quantum Wires

We review the effects of Coulomb correlation on the linear and non-linear optical properties of semiconductor quantum wires, with emphasis on recent results for the bound excitonic states. Our theoretical approach is based on generalized semiconductor Bloch equations, and allows full three-dimensional multisubband description of electron-hole correlation for arbitrary confinement profiles. In particular, we consider V- and T-shaped structures for which significant experimental advances were obtained recently. Above band gap, a very general result obtained by this approach is that electron-hole Coulomb correlation removes the inverse-square-root single-particle singularity in the optical spectra at band edge, in agreement with previous reports from purely one-dimensional models. Strong correlation effects on transitions in the continuum are found to persist also at high densities of photoexcited carriers. Below bandgap, we find that the same potential- (Coulomb) to kinetic-energy ratio holds for quite different wire cross sections and compositions. As a consequence, we identify a shape- and barrier-independent parameter that governs a universal scaling law for exciton binding energy with size. Previous indications that the shape of the wire cross-section may have important effects on exciton binding are discussed in the light of the present results.Comment: Proc. OECS-5 Conference, G\"ottingen, 1997 (To appear in Phys. Stat. Sol. (b)

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

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

What drives the active involvement in business angel groups? The role of angels' decision-making style, investment-specific human capital and motivations

This paper sheds light over the operations and internal structure of business angel groups (BAGs), a leading actor inside the informal venture capital industry, due to its capability to build cognitive resources and shared competencies that are eventually provided to funded ventures alongside equity capital. We develop a framework based on the role of business angels' decision-making style, human capital and motivation as major determinants of their active involvement in the many different activities performed by angel groups, either investment related activities or group management activities. Our empirical analysis relies on a novel survey-based dataset containing qualitative and quantitative information provided by the members of two large and rather homogeneous business angel groups located in France and in Italy. Results show that business angels with a control-oriented decision-making style tend to be more actively involved in key angel group activities. Human capital built through investment experience, retirement status, as well as initial motivation to join an angel group are also significant drivers of angel involvement in several key BAG activities

A lightweight prototype of a magnetometric system for unmanned aerial vehicles

Detection of the Earth’s magnetic field anomalies is the basis of many types of studies in the field of earth sciences and archaeology. These surveys require different ways to carry out the measures but they have in common that they can be very tiring or expensive. There are now several lightweight commercially available magnetic sensors that allow light-UAVs to be equipped to perform airborne measurements for a wide range of scenarios. In this work, the realization and functioning of an airborne magnetometer prototype were presented and discussed. Tests and measures for the validation of the experimental setup for some applications were reported. The flight sessions, appropriately programmed for different types of measurements, made it possible to evaluate the performance of this detection methodology, highlighting the advantages and drawbacks or limitations and future developments. From the results obtained it was possible to verify that the measurement system is capable of carrying out local and potentially archaeological magnetometric measurements with the necessary precautions

GADA titer-related risk for organ-specific autoimmunity in LADA subjects subdivided according to gender (NIRAD study 6).

CONTEXT: Latent autoimmune diabetes in adults (LADA) includes a heterogeneous population wherein, based on glutamic acid decarboxylase antibody (GADA) titer, different subgroups of subjects can be identified. OBJECTIVE: The aim of the present study was to evaluate GADA titer-related risk for β-cell and other organ-specific autoimmunity in LADA subjects. METHODS: Adult-onset autoimmune diabetes subjects (n=236) and type 2 diabetes (T2DM) subjects (n=450) were characterized for protein tyrosine phosphatase (IA-2IC and IA-2(256-760)), zinc transporter 8 (ZnT8), thyroid peroxidase, (TPO), steroid 21-hydroxylase (21-OH), tissue transglutaminase (tTG), and antiparietal cell (APC) antibodies. RESULTS: High GADA titer compared to low GADA titer showed a significantly higher prevalence of IA-2IC, IA-2(256-760), ZnT8, TPO, and APC antibodies (P≤0.04 for all comparison). 21-OH antibodies were detected in 3.4% of high GADA titer. A significant decreasing trend was observed from high GADA to low GADA and to T2DM subjects for IA-2(256-760), ZnT8, TPO, tTG, and APC antibodies (P for trend≤0.001). TPO was the only antibody showing a different prevalence between gender; low GADA titer and T2DM female patients had a higher frequency of TPO antibody compared to males (P=0.0004 and P=0.0006, respectively), where the presence of high GADA titer conferred an odds ratio of 8.6 for TPO compared to low GADA titer. After subdividing high and low GADA titer subjects according to the number of antibodies, we observed that 73.3% of high GADA titer subjects were positive for at least one or more antibodies, compared to 38.3% of low GADA titer (P<0.0001). CONCLUSIONS: In LADA subjects, high GADA titer was associated with a profile of more severe autoimmunity and, in male gender, specifically predisposed to thyroid autoimmunity. A regular screening for other antibodies is recommended in LADA patients according to GADA titer and gender

Effects of carboxy-terminal modifications of proteinase 3 (PR3) on the recognition by PR3-ANCA

Effects of carboxy-terminal modifications of proteinase 3 (PR3) on the recognition by PR3-ANCA.BackgroundAutoantibodies directed against neutrophil proteinase 3 (PR3-ANCA) from patients with Wegener's granulomatosis and microscopic polyangiitis recognize conformational epitopes of PR3. During maturation of neutrophils, PR3 undergoes amino-terminal and carboxy-terminal processing. In contrast to amino-terminal processing, the effects of carboxy-terminal processing on recognition of PR3 by PR3-ANCA remain unknown. Carboxy-terminally modified or tagged recombinant PR3 (rPR3) molecules may be useful for the refinement of diagnostic assays and for the study of biological processes.MethodsThis study was designed to determine whether 293 cells can be used to express specifically designed carboxy-terminal variants of rPR3, and to evaluate the effects of different carboxy-terminal modifications on the recognition by PR3-ANCA in the capture ELISA.ResultsThe rPR3-variants secreted into the media supernatants of transfected 293 cells escaped proteolytic processing. Furthermore, in contrast to the effects of amino-terminal pro-peptide deletion on PR3-ANCA binding, carboxy-terminal modifications (deletion and additions) did not significantly affect recognition by PR3-ANCA.ConclusionsThis expression system is ideally suited for the expression of custom-designed carboxy-terminal rPR3 variants, and major conformational effects of carboxy-terminal modifications seem unlikely

Geophysical Constraints to Reconstructing the Geometry of a Shallow Groundwater Body in Caronia (Sicily)

The characterization of a groundwater body involves the construction of a conceptual model that constitutes the base knowledge for monitoring programs, hydrogeological risk assessment, and correct management of water resources. In particular, a detailed geological and geophysical approach was applied to define the alluvial Caronia Groundwater Body (CGWB) and to reconstruct a hydrogeological flow model. The analysis of the CGWB, located in north-eastern Sicily, was initially approached through a reanalysis of previous stratigraphic (boreholes) and geophysical (vertical electrical soundings and seismic refraction profiles) data, subsequently integrated by new seismic acquisitions, such as Multichannel Analysis of Surface Waves (MASW) and horizontal-to-vertical seismic ratio (HVSR). The analysis and reinterpretation of geoelectrical data allowed the construction of a preliminary 3D resistivity model. This initial modeling was subsequently integrated by a geophysical data campaign in order to define the depth of the bottom of the shallow CGWB and the thickness of alluvial deposits. Finally, a preliminary mathematical model flow was generated in order to reconstruct the dynamics of underground water. The results show that integration of multidisciplinary data represent an indispensable tool for the characterization of complex physical systems