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The aim of this study was to the evaluate volumetric and linear adaptation of an indirect adhesive restoration, comparing a novel chairside 3D printer to conventional milling techniques. An intact upper premolar was selected, prepared for an overlay restoration, and replicated. A standardized overlay restoration was designed with CAD software (Cerec inLab CAD SW 4.5.2, Dentsply Sirona, Charlotte, NC, USA), maintaining equal morphology for each sample. Restorations were produced with three CAM processes: chairside 3D printer (D-FAB, DWS, Thiene, Italy), chairside milling unit (Cerec MCXL, Dentsply Sirona, Charlotte, NC, USA), and an industrial milling machine serving as control (Micro 5x, Aman Girrbach, Mäder, Austria). Once cemented, specimens were scanned using micro-computed tomography to assess volumetric, internal, and external adaptation. Data were statistically analyzed with ANOVA and post hoc Bonferroni tests. CAM technique significantly affected volumetric adaptation (p < 0.001), with the chairside 3D printer performing the best and chairside milling unit the worst. Concerning internal adaptation, the chairside milling unit performed significantly worse than the other groups (p < 0.001). No significant differences were reported for external adaptation (p > 0.05). In conclusion, CAM technique influenced volumetric and internal adaptation, with the 3D printer showing optimal volumetric adaptation and chairside milling poor internal adaptation.

Driven by technological advances in various fields (AI, 5G, VR, IoT, etc.) together with the emergence of digital twins technologies (HDT, HAL, BIM, etc.), the Metaverse has attracted growing attention from scientific and industrial communities. This interest is due to its potential impact on people lives in different sectors such as education or medicine. Specific solutions can also increase inclusiveness of people with disabilities that are an impediment to a fulfilled life. However, security and privacy concerns remain the main obstacles to its development. Particularly, the data involved in the Metaverse can be comprehensive with enough granularity to build a highly detailed digital copy of the real world, including a Human Digital Twin of a person. Existing security countermeasures are largely ineffective and lack adaptability to the specific needs of Metaverse applications. Furthermore, the virtual worlds in a large-scale Metaverse can be highly varied in terms of hardware implementation, communication interfaces, and software, which poses huge interoperability difficulties. This paper aims to analyse the risks and opportunities associated with adopting digital replicas of humans (HDTs) within the Metaverse and the challenges related to managing digital identities in this context. By examining the current technological landscape, we identify several open technological challenges that currently limit the adoption of HDTs and the Metaverse. Additionally, this paper explores a range of promising technologies and methodologies to assess their suitability within the Metaverse context. Finally, two example scenarios are presented in the Medical and Education fields.

Smart cities and 6G are technological areas that have the potential to transform the way we live and work in the years to come. Until this transformation comes into place, there is the need, underlined by research and market studies, for a critical reassessment of the entire wireless communication sector for smart cities, which should include the IoT infrastructure, economic factors that could improve their adoption rate, and strategies that enable smart city operations. Therefore, from a technical point of view, a series of stringent issues, such as interoperability, data privacy, security, the digital divide, and implementation issues have to be addressed. Notably, to concentrate the scrutiny on smart cities and the forthcoming influence of 6G, the groundwork laid by the current 5G, with its multifaceted role and inherent limitations within the domain of smart cities, is embraced as a foundational standpoint. This examination culminates in a panoramic exposition, extending beyond the mere delineation of the 6G standard toward the unveiling of the extensive gamut of potential applications that this emergent standard promises to introduce to the smart cities arena. This paper provides an update on the SC ecosystem around the novel paradigm of 6G, aggregating a series of enabling technologies accompanied by the descriptions of their roles and specific employment schemes.

Hemoproteins include several heme-binding proteins with distinct structure and function. The presence of the heme group confers specific reactivity and spectroscopic properties to hemoproteins. In this review, we provide an overview of five families of hemoproteins in terms of dynamics and reactivity. First, we describe how ligands modulate cooperativity and reactivity in globins, such as myoglobin and hemoglobin. Second, we move on to another family of hemoproteins devoted to electron transport, such as cytochromes. Later, we consider heme-based reactivity in hemopexin, the main heme-scavenging protein. Then, we focus on heme–albumin, a chronosteric hemoprotein with peculiar spectroscopic and enzymatic properties. Eventually, we analyze the reactivity and dynamics of the most recently discovered family of hemoproteins, i.e., nitrobindins.

Femtosecond coherent Raman techniques have significant diagnostic value for the sensitive and non-intrusive measurement of temperature, pressure, and composition of gas mixtures. Due to the low density of samples, however, such measurements make use of high-energy amplified laser sources, with unwieldy and costly experimental setups. In this paper, we demonstrate an experimental setup equipped with a low-energy and low-average-power femtosecond oscillator allowing measurement of the pure-rotational spectrum of nitrogen down to atmospheric pressure using impulsive stimulated Raman scattering. Using a simplified model to analyze the experimental data we were able to derive the gas temperature with reasonable accuracy.

Nanostructured titania is one of the most commonly encountered constituents of nanotechnology devices for use in energy-related applications, due to its intrinsic functional properties as a semiconductor and to other favorable characteristics such as ease of production, low toxicity and chemical stability, among others. Notwithstanding this diffusion, the quest for improved understanding of the physical and chemical mechanisms governing the material properties and thus its performance in devices is still active, as testified by the large number of dedicated papers that continue to be published. In this framework, we consider and analyze here the effects of the material morphology and structure in determining the energy transport phenomena as cross-cutting properties in some of the most important nanophase titania applications in the energy field, namely photovoltaic conversion, hydrogen generation by photoelectrochemical water splitting and thermal management by nanofluids. For these applications, charge transport, light transport (or propagation) and thermal transport are limiting factors for the attainable performances, whose dependence on the material structural properties is reviewed here on its own. This work aims to fill the gap existing among the many studies dealing with the separate applications in the hope of stimulating novel cross-fertilization approaches in this research field.

Activated hard carbons, obtained from the pyrolysis of various waste biomasses, were prepared and characterized for use as the active material for the fabrication of battery electrodes. The preparation consisted of a pyrolysis process, followed by an activation with KOH and a further high-temperature thermal process. TG and DTA were used to discriminate the steps of the activation process, while SEM, XRD, and Raman characterization were employed to evaluate the effects of activation. The activated carbons were tested as electrodes in lithium-sulfur and lithium-ion batteries. The carbonaceous materials coming from cherry stones and walnut shells have proved to be particularly suitable as electrode components. When used as anodes in lithium-ion batteries, both carbons exhibited a high first cycle discharge capacity, which was not restored during the next charge. After the first two cycles, in which there was a marked loss of capacity, both electrodes showed good reversibility. When used as cathodes in lithium-sulfur batteries, both carbons exhibited good catalytic activity against the redox reaction involving sulfur species with good cycle stability and satisfactory Coulombic efficiency.

The sudden outbreak and worldwide spread of the SARS-CoV-2 pandemic pushed the scientific community to find fast solutions to cope with the health emergency. COVID-19 complexity, in terms of clinical outcomes, severity, and response to therapy suggested the use of multifactorial strategies, characteristic of the network medicine, to approach the study of the pathobiology. Proteomics and interactomics especially allow to generate datasets that, reduced and represented in the forms of networks, can be analyzed with the tools of systems biology to unveil specific pathways central to virus–human host interaction. Moreover, artificial intelligence tools can be implemented for the identification of druggable targets and drug repurposing. In this review article, we provide an overview of the results obtained so far, from a systems biology perspective, in the understanding of COVID-19 pathobiology and virus–host interactions, and in the development of disease classifiers and tools for drug repurposing.

Craniofacial abnormalities are a common group of congenital developmental disorders that can require intensive oral surgery as part of their treatment. Neural crest cells (NCCs) contribute to the facial structures; however, they are extremely sensitive to high levels of oxidative stress, which result in craniofacial abnormalities under perturbed developmental environments. The oxidative stress-inducing compound auranofin (AFN) disrupts craniofacial development in wildtype zebrafish embryos. Here, we tested whether the antioxidant Riboceine (RBC) rescues craniofacial defects arising from exposure to AFN. RBC rescued AFN-induced cellular apoptosis and distinct defects of the cranial cartilage in zebrafish larvae. Zebrafish embryos exposed to AFN have higher expression of antioxidant genes gstp1 and prxd1, with RBC treatment partially rescuing these gene expression profiles. Our data suggest that antioxidants may have utility in preventing defects in the craniofacial cartilage owing to environmental or genetic risk, perhaps by enhancing cell survival.

Impulsive stimulated Raman scattering (ISRS) is a nonlinear pump–probe spectroscopy technique particularly suitable to study vibrational intermolecular and intramolecular modes in complex systems. For the latter, recent studies of ISRS microscopy with low-energy laser sources have attracted attention for investigation of photosensitive or biological samples. Following this stream of interest, in this paper, we report an investigation on the relationship between femtosecond ISRS data and pump–probe Z-scan measurements, showing that the latter technique is capable of capturing the Kerr nonlinearities induced by the molecular vibrational modes. To this aim, firstly, spectrally filtered and Raman-induced Kerr ISRS signals were simultaneously acquired to determine the sample nonlinear response and to establish the reference data for the Z-scan analysis. Then, by adopting a suitable experimental arrangement to avoid thermo-optical effects, we were able to unambiguously observe the Raman-induced effects in Z-scan measurements, thus obtaining a consistent picture between ISRS and Z-scan for the first time, to the best of our knowledge. Practical applications of the proposed method include calibrated measurements of the contribution of the internal (Raman) and external molecular modes to the nonlinear refractive index.

This study addresses the relationship between material morphology (size, growth parameters and interfaces) and optical emissions in ZnO through an experimental approach, including the effect of different material dimensions from bulk to nano-size, and different excitations, from optical sources to ionizing radiation. Silica supported ZnO nanoparticles and ligand capped ZnO nanoparticles are synthesized through a sol–gel process and hot injection method, respectively. Their optical properties are investigated by radioluminescence, steady-state and time-resolved photoluminescence, and compared to those of commercial micrometric powders and of a bulk single crystal. The Gaussian spectral reconstruction of all emission spectra highlights the occurrence of the same emission bands for all samples, comprising one ultraviolet excitonic peak and four visible defect-related components, whose relative intensities and time dynamics vary with the material parameters and the measurement conditions. The results demonstrate that a wide range of color outputs can be obtained by tuning synthesis conditions and size of pure ZnO nanoparticles, with favorable consequences for the engineering of optical devices based on this material.

This paper deals with inverse problems related to degenerate fractional integro-differential equations in Banach spaces. We study existence, uniqueness and regularity of solutions to the problem, claiming to extend well known studies for the case of non-fractional equations. Our method is based on transforming the inverse problem to a direct problem and identifying the conditions under which this direct problem has a unique solution. The conditions under which the unique strict solution can be compared with the case of a mild solution, obtained in previous studies under quite restrictive requirements, are on the underlying functions. Applications from partial differential equations are given to illustrate our abstract results.

The nonlinear dynamical behaviour of a network that is submitted to disturbances is the starting point of this work, where we consider a low voltage line (the network) with nonlinear varistor filters responding, dynamically, to those disturbances. Network models consider static measurements, and here we develop an iterative model to deal with dynamical measurements. We begin with the one-dimensional communication line model using reflected and incident signals, which are dependent on the node parameters, proceeding a time-step computation. Each node is a space representation that consolidates parameters for a specific vertex and its edges. Nonlinear functions are applied within the node and will contribute to the general process running on the structure. The idea of a structure and its related processes leads to a new concept of sustainability and system robustness. This concludes the work, along with several experimental and simulation results, with direct advantages to electromagnetic interference control and mitigation.

The aim of the study was to test the validity of the Malocclusion Impact Questionnaire (MIQ) in a NZ sample and to evaluate possible cross-cultural differences in MIQ data between a NZ and a UK sample. A cross-sectional, non-random sample of young people, aged 10–16 years, attending their first appointment at the orthodontic clinic of New Zealand’s National Centre for Dentistry were asked to complete a questionnaire. This consisted of the 17 item MIQ, the short form CPQ11-14-ISF16 and two global questions. Some basic demographic and clinical data were collected. Sixty-six participants completed the questionnaire; however, the data for 2 were excluded due to the number of incomplete responses. MIQ was found to have excellent internal consistency (Cronbach’s alpha 0.924), good construct validity (Spearman’s rho, 0.661 global Q1 ‘Overall, how much do your teeth bother you?’; 0.583 global Q2 ‘Overall, how much do your teeth affect your life?’). MIQ also demonstrated good criterion validity with CPQ11-14-ISF16 (Pearson rho, 0.625). The Rasch analysis confirmed that the questionnaire performed similarly and there was no differential item functioning between the two populations. The main differences between the samples were that the young people in NZ were less concerned about their malocclusion and reported lower item-impact scores compared with the young people in the UK.

Precise measurements of the energy spectra and of the composition of cosmic rays in the PeV region could improve our knowledge regarding their origin, acceleration mechanism, propagation, and composition. At the present time, spectral measurements in this region are mainly derived from data collected by ground-based detectors, because of the very low particle rates at these energies. Unfortunately, these results are affected by the high uncertainties typical of indirect measurements, which depend on the complicated modeling of the interaction of the primary particle with the atmosphere. A space experiment dedicated to measurements in this energy region has to achieve a balance between the requirements of lightness and compactness, with that of a large acceptance to cope with the low particle rates. CaloCube is a four-year-old R&D project, approved and financed by the Istituto Nazionale di Fisica Nucleare (INFN) in 2014, aiming to optimize the design of a space-borne calorimeter. The large acceptance needed is obtained by maximizing the number of entrance windows, while thanks to its homogeneity and high segmentation this new detector achieves an excellent energy resolution and an enhanced separation power between hadrons and electrons. In order to optimize detector performances with respect to the total mass of the apparatus, comparative studies on different scintillating materials, different sizes of crystals, and different spacings among them have been performed making use of MonteCarlo simulations. In parallel to simulations studies, several prototypes instrumented with CsI(Tl) (Caesium Iodide, Tallium doped) cubic crystals have been constructed and tested with particle beams. Moreover, the last development of CaloCube, the Tracker-In-Calorimeter (TIC) project, financed by the INFN in 2018, is focused on the feasibility of including several silicon layers at different depths in the calorimeter in order to reconstruct the particle direction. In fact, an important requirement for γ -ray astronomy is to have a good angular resolution in order to allow precise identification of astrophysical sources in space. In respect to the traditional approach of using a tracker with passive material in front of the calorimeter, the TIC solution can save a significant amount of mass budget in a space satellite experiment, which can then be exploited to improve the acceptance and the resolution of the calorimeter. In this paper, the status of the project and perspectives for future developments are presented.

The topic of nearly zero-energy buildings (n-ZEB), introduced by the Directive 2010/31/EU will direct the building market toward ever greater energy efficiency of new buildings. In some contexts, however, the building market for high-efficiency buildings has evolved, in recent years, on the basis of national and regional laws that have contributed to the acceleration of the process. This paper analyses the case study of the Lombardy Region (Italy), which transposed and assimilated the Directive 91/2002 (Energy Performance Building Directive), as of 2006, with regional legislation for energy efficiency of buildings. Within a few years the market for high energy-performance of buildings in the Lombardy Region had grown substantially: to date nearly 7500 energy performance certificates for buildings of Class A and Class A+ have been issued. The paper therefore analyses a success story in what is a field of great current interest, namely n-ZEB buildings. In the first part of the work, the evolution in terms of energy efficiency of the housing market in the Lombardy Region has been analyzed, with particular reference to the high energy-performance of buildings. The second part focuses on a sample of 20 n-ZEB buildings in order to highlight the design choices applied to them.

In the last few years, one of the main characteristics of the current technological development is the constantly increasing need for data exchange among various types of devices, both mobile and fixed. Within this context, the direct communications between devices has the potential to create new, location-based peer-to-peer applications and services, as well as to help offload traffic from the congested traditional cellular networks. The main hurdles for this kind of Device to Device (D2D) communications are throughput, spectral efficiency, latency and fairness. Most of these hurdles can be overcome by the use of the new Social IoT (SIoT) paradigm, of things and people involved together in the network, guided autonomously by social relationships following the rules set by their owners. This paper aims to investigate the state of the art of socially-driven D2D communications. Upon an initial analysis, we perform an in-deep literature investigation of the main directions in which social ties can improve D2D communication, draw conclusions and identify the research topics left open.

The main argument of this work is that innovation flourishes and emerges in a creative environment where the actors interact freely, to the extent that this environment is a complex adaptive system. Public or institutional policies, trying to induce innovation, must be careful to not stifle or interrupt the emergence of novelties in the path from creation and conception to market involvement. Our proposed model argues that innovation emerges wherever evolution, learning, mutation, and competition between individuals and firms are permitted, without restrictions or pre-defined paths to the market. We describe two cases of innovation by way of example: the first case shows how several—and sometimes anonymous—elements interact and compete in a typical environment of innovation, while the second case shows how continuous policies to foment innovation may create results to the contrary. In addition, we show technology clusters as cases where the emergence of innovation can be fostered by policies that observe the complex adaptive system characteristics.

The intensive rice cultivation area in northwestern Italy hosts the largest surface of rice paddies in Europe, and it is valued as a substantial habitat for aquatic biodiversity, with the paddies acting as a surrogate for the lost natural wetlands. The extent of submerged paddies strictly depends on crop management practices: in this framework, the recent diffusion of rice seeding in dry conditions has led to a reduction of flooded surfaces during spring and could have contributed to the observed decline of the populations of some waterbird species that exploit rice fields as foraging habitat. In order to test the existence and magnitude of a decreasing trend in the extent of submerged rice paddies during the rice-sowing period, MODIS remotely-sensed data were used to estimate the extent of the average flooded surface and the proportion of flooded rice fields in the years 2000–2016 during the nesting period of waterbirds. A general reduction of flooded rice fields during the rice-sowing season was observed, averaging − 0.86 ± 0.20 % per year (p-value < 0.01). Overall, the loss in submerged surface area during the sowing season reached 44 % of the original extent in 2016, with a peak of 78 % in the sub-districts to the east of the Ticino River. Results highlight the usefulness of remote sensing data and techniques to map and monitor water dynamics within rice cropping systems. These techniques could be of key importance to analyze the effects at the regional scale of the recent increase of dry-seeded rice cultivations on watershed recharge and water runoff and to interpret the decline of breeding waterbirds via a loss of foraging habitat.

The extension of the fractional order derivative to the distributed order fractional derivative (DOFD) is somewhat simple from a formal point of view, but it does not yet have a simple, obvious analytic form that allows its fast numerical calculation, which is necessary when solving differential equations with DOFD. In this paper, we supply a simple analytic kernel for the Caputo DOFD and the Caputo-Fabrizio DOFD, which may be used for numerical calculation in cases where the weight function is unity. This, in turn, could potentially allow faster solution of differential equations containing DOFD. Utilizing an analytical formulation of simple physical systems with phenomenological equations that include a DOFD, we show the relevant differences between the Caputo DOFD and the Caputo-Fabrizio DOFD. Finally, we propose a model based on DOFD for modeling composed materials that comprise different constituents, and show its compatibility with thermodynamics.