Multilayer Plasmonic Nanostructures for Improved Sensing Activities Using a FEM and Neurocomputing-Based Approach

In order to obtain optimized elementary devices (photovoltaic modules, power transistors for energy efficiency, high-efficiency sensors) it is necessary to increase the energy conversion efficiency of these devices. A very effective approach to achieving this goal is to increase the absorption of incident radiation. A promising strategy to increase this absorption is to use very thin regions of active material and trap photons near these surfaces. The most effective and cost-effective method of achieving such optical entrapment is the Raman scattering from excited nanoparticles at the plasmonic resonance. The field of plasmonics is the study of the exploitation of appropriate layers of metal nanoparticles to increase the intensity of radiation in the semiconductor by means of near-field effects produced by nanoparticles. In this paper, we focus on the use of metal nanoparticles as plasmonic nanosensors with extremely high sensitivity, even reaching single-molecule detection. The study conducted in this paper was used to optimize the performance of a prototype of a plasmonic photovoltaic cell made at the Institute for Microelectronics and Microsystems IMM of Catania, Italy. This prototype was based on a multilayer structure composed of the following layers: glass, AZO, metal and dielectric. In order to obtain good results, it is necessary to use geometries that orthogonalize the absorption of light, allowing better transport of the photocarriers—and therefore greater efficiency—or the use of less pure materials. For this reason, this study is focused on optimizing the geometries of these multilayer plasmonic structures. More specifically, in this paper, by means of a neurocomputing procedure and an electromagnetic fields analysis performed by the finite elements method (FEM), we established the relationship between the thicknesses of Aluminum-doped Zinc oxide (AZO), metal, dielectric and their main properties, characterizing the plasmonic propagation phenomena as the optimal wavelengths values at the main interfaces AZO/METAL and METAL/DIELECTRIC

Frequency of left ventricular hypertrophy in non-valvular atrial fibrillation

Left ventricular hypertrophy (LVH) is significantly related to adverse clinical outcomes in patients at high risk of cardiovascular events. In patients with atrial fibrillation (AF), data on LVH, that is, prevalence and determinants, are inconsistent mainly because of different definitions and heterogeneity of study populations. We determined echocardiographic-based LVH prevalence and clinical factors independently associated with its development in a prospective cohort of patients with non-valvular (NV) AF. From the "Atrial Fibrillation Registry for Ankle-brachial Index Prevalence Assessment: Collaborative Italian Study" (ARAPACIS) population, 1,184 patients with NVAF (mean age 72 \ub1 11 years; 56% men) with complete data to define LVH were selected. ARAPACIS is a multicenter, observational, prospective, longitudinal on-going study designed to estimate prevalence of peripheral artery disease in patients with NVAF. We found a high prevalence of LVH (52%) in patients with NVAF. Compared to those without LVH, patients with AF with LVH were older and had a higher prevalence of hypertension, diabetes, and previous myocardial infarction (MI). A higher prevalence of ankle-brachial index 640.90 was seen in patients with LVH (22 vs 17%, p = 0.0392). Patients with LVH were at significantly higher thromboembolic risk, with CHA2DS2-VASc 652 seen in 93% of LVH and in 73% of patients without LVH (p <0.05). Women with LVH had a higher prevalence of concentric hypertrophy than men (46% vs 29%, p = 0.0003). Logistic regression analysis demonstrated that female gender (odds ratio [OR] 2.80, p <0.0001), age (OR 1.03 per year, p <0.001), hypertension (OR 2.30, p <0.001), diabetes (OR 1.62, p = 0.004), and previous MI (OR 1.96, p = 0.001) were independently associated with LVH. In conclusion, patients with NVAF have a high prevalence of LVH, which is related to female gender, older age, hypertension, and previous MI. These patients are at high thromboembolic risk and deserve a holistic approach to cardiovascular prevention

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Creep assessment in hyperelastic material by 3D neural network reconstructor using bulge testing

In this paper is presented a new methodology based on Neural Network which, making use of the Bulge Testing able to reconstruct the three-dimensional dome of the bulge test and also to obtain the membrane stress and strain fields of the material under investigation

A cloud-based flexible solution for psychometric tests validation, administration and evaluation

Psychological tests generally provide an evaluation scale to evaluate whether or not the subject manifests some traits. Such kind of tests are generally used for attitude evaluation, personal selection, educational and rehabilitation purposes, as well as for the diagnosis of cognitive disorders. The use of test and other questions-based diagnostic tools, represents one of the main and principal actions in order to start a clinical and therapeutic path, as well as for the evaluation and assessment of the possible educational and rehabilitation effort. Unfortunately such tests are generally the result of a long and difficult process of validation for their standardization, simplification and reorganizations driven by operations performed by means of complex statistical methods. In the work presented on this paper we developed a unified cloud-based resource for the management and execution of all the task related to psychometric testing, from the creation of a test, to its validation and use. The solution has been designed to grant maximum flexibility allocating resources on a cloud service. Such resources can be used as a remote support for the psychologists designing and administering the test, as well as computing platform to unburden the single terminals of the heavy computations required during the standardization procedure. Moreover, by means of the distributed database, our solution is also able to support the simplification and reorganization process, as well as to serve as online platform for the administration and consequent scoring of the finalized and standardized test

A spiking neural network-based model for anaerobic digestion process

There are many conversion technologies for the transformation of biomass into usable energy forms. Among these technologies, anaerobic digestion is one of the most attractive. In many papers appeared in the literature it has been demonstrated that the application of efficient mathematical models is an essential requirement to improve digester’s performance. In this paper a spiking neural network-based model for anaerobic digestion process is proposed. This model performs a long-term prediction of the concentration of the biogas (CH4 and CO2) at the 100th day of the process, by analysing the concentration evolution of 6 measurable marker-molecules (MMM) namely CH4, CH4S, CO2, H2, H2S and NH3 during the first 10 days of the process. For the validation of the model, a small domestic digester was realized. The tests carried out show an excellent agreement between the predicted values and those obtained with the digeste

A Multithread Nested Neural Network Architecture to Model Surface Plasmon Polaritons Propagation

Surface Plasmon Polaritons are collective oscillations of electrons occurring at the interface between a metal and a dielectric. The propagation phenomena in plasmonic nanostructures is not fully understood and the interdependence between propagation and metal thickness requires further investigation. We propose an ad-hoc neural network topology assisting the study of the said propagation when several parameters, such as wavelengths, propagation length and metal thickness are considered. This approach is novel and can be considered a first attempt at fully automating such a numerical computation. For the proposed neural network topology, an advanced training procedure has been devised in order to shun the possibility of accumulating errors. The provided results can be useful, e.g., to improve the efficiency of photocells, for photon harvesting, and for improving the accuracy of models for solid state devices

A new design methodology for window‐based FIR filters

Abstract This letter describes a novel window‐based approach to FIR filter design. The window is constructed on the use of equispaced Gaussian basis functions. Unlike other known window‐based methods that do not allow for a satisfactory degree of control over band edges, the proposed method affords very good solution for controlling critical frequencies. In addition, the proposed window method is easier to implement than Kaiser's and affords a better passband flatness than any known design approach. It also yields stopband attenuations and control of critical frequencies which turn out to be very close to those obtainable with Parks–McClellan's method. So the proposed GBR window approach appears to be a significant step forward