Università degli studi di Cassino e del Lazio Meridionale

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.

As the standardization of 5G solidifies, researchers are speculating what 6G will be. The integration of sensing functionality is emerging as a key feature of the 6G Radio Access Network (RAN), allowing for the exploitation of dense cell infrastructures to construct a perceptive network. In this IEEE Journal on Selected Areas in Communications (JSAC) Special Issue overview, we provide a comprehensive review on the background, range of key applications and state-of-the-art approaches of Integrated Sensing and Communications (ISAC). We commence by discussing the interplay between sensing and communications (S&C) from a historical point of view, and then consider the multiple facets of ISAC and the resulting performance gains. By introducing both ongoing and potential use cases, we shed light on the industrial progress and standardization activities related to ISAC. We analyze a number of performance tradeoffs between S&C, spanning from information theoretical limits to physical layer performance tradeoffs, and the cross-layer design tradeoffs. Next, we discuss the signal processing aspects of ISAC, namely ISAC waveform design and receive signal processing. As a step further, we provide our vision on the deeper integration between S&C within the framework of perceptive networks, where the two functionalities are expected to mutually assist each other, i.e., via communication-assisted sensing and sensing-assisted communications. Finally, we identify the potential integration of ISAC with other emerging communication technologies, and their positive impacts on the future of wireless networks.

What is a reconfigurable intelligent surface? What is a smart radio\nenvironment? What is a metasurface? How do metasurfaces work and how to model\nthem? How to reconcile the mathematical theories of communication and\nelectromagnetism? What are the most suitable uses and applications of\nreconfigurable intelligent surfaces in wireless networks? What are the most\npromising smart radio environments for wireless applications? What is the\ncurrent state of research? What are the most important and challenging research\nissues to tackle?\n These are a few of the many questions that we investigate in this short opus,\nwhich has the threefold objective of introducing the emerging research field of\nsmart radio environments empowered by reconfigurable intelligent surfaces,\nputting forth the need of reconciling and reuniting C. E. Shannon's\nmathematical theory of communication with G. Green's and J. C. Maxwell's\nmathematical theories of electromagnetism, and reporting pragmatic guidelines\nand recipes for employing appropriate physics-based models of metasurfaces in\nwireless communications.\n

During the rapid rise in COVID-19 illnesses and deaths globally, and notwithstanding recommended precautions, questions are voiced about routes of transmission for this pandemic disease. Inhaling small airborne droplets is probable as a third route of infection, in addition to more widely recognized transmission via larger respiratory droplets and direct contact with infected people or contaminated surfaces. While uncertainties remain regarding the relative contributions of the different transmission pathways, we argue that existing evidence is sufficiently strong to warrant engineering controls targeting airborne transmission as part of an overall strategy to limit infection risk indoors. Appropriate building engineering controls include sufficient and effective ventilation, possibly enhanced by particle filtration and air disinfection, avoiding air recirculation and avoiding overcrowding. Often, such measures can be easily implemented and without much cost, but if only they are recognised as significant in contributing to infection control goals. We believe that the use of engineering controls in public buildings, including hospitals, shops, offices, schools, kindergartens, libraries, restaurants, cruise ships, elevators, conference rooms or public transport, in parallel with effective application of other controls (including isolation and quarantine, social distancing and hand hygiene), would be an additional important measure globally to reduce the likelihood of transmission and thereby protect healthcare workers, patients and the general public.

We present the first results of the Fermilab National Accelerator Laboratory (FNAL) Muon g -2 Experiment for the positive muon magnetic anomaly a g -2=2. The anomaly is determined from the precision measurements of two angular frequencies. Intensity variation of high-energy positrons from muon decays directly encodes the difference frequency a between the spin-precession and cyclotron frequencies for polarized muons in a magnetic storage ring. The storage ring magnetic field is measured using nuclear magnetic resonance probes calibrated in terms of the equivalent proton spin precession frequency 0

Purpose – The purpose of this paper is to identify and describe the most prominent research areas connected with “Big Data” and propose a thorough definition of the term. Design/methodology/approach – The authors have analysed a conspicuous corpus of industry and academia articles linked with Big Data to find commonalities among the topics they treated. The authors have also compiled a survey of existing definitions with a view of generating a more solid one that encompasses most of the work happening in the field. Findings – The main themes of Big Data are: information, technology, methods and impact. The authors propose a new definition for the term that reads as follows: “Big Data is the Information asset characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value.” Practical implications – The formal definition that is proposed can enable a more coherent development of the concept of Big Data, as it solely relies on the essential strands of current state-of-the-art and is coherent with the most popular definitions currently used. Originality/value – This is among the first structured attempts of building a convincing definition of Big Data. It also contains an original exploration of the topic in connection with library management.

Airborne transmission is a pathway of contagion that is still not sufficiently investigated despite the evidence in the scientific literature of the role it can play in the context of an epidemic. While the medical research area dedicates efforts to find cures and remedies to counteract the effects of a virus, the engineering area is involved in providing risk assessments in indoor environments by simulating the airborne transmission of the virus during an epidemic. To this end, virus air emission data are needed. Unfortunately, this information is usually available only after the outbreak, based on specific reverse engineering cases. In this work, a novel approach to estimate the viral load emitted by a contagious subject on the basis of the viral load in the mouth, the type of respiratory activity (e.g. breathing, speaking, whispering), respiratory physiological parameters (e.g. inhalation rate), and activity level (e.g. resting, standing, light exercise) is proposed. The results showed that high quanta emission rates (>100 quanta h−1) can be reached by an asymptomatic infectious SARS-CoV-2 subject performing vocalization during light activities (i.e. walking slowly) whereas a symptomatic SARS-CoV-2 subject in resting conditions mostly has a low quanta emission rate (<1 quantum h−1). The findings in terms of quanta emission rates were then adopted in infection risk models to demonstrate its application by evaluating the number of people infected by an asymptomatic SARS-CoV-2 subject in Italian indoor microenvironments before and after the introduction of virus containment measures. The results obtained from the simulations clearly highlight that a key role is played by proper ventilation in containment of the virus in indoor environments.

MicroRNAs are short regulatory RNAs that negatively modulate protein expression at a post-transcriptional level and are deeply involved in the pathogenesis of several types of cancers. Here we show that miR-221 and miR-222, encoded in tandem on chromosome X, are overexpressed in the PC3 cellular model of aggressive prostate carcinoma, as compared with LNCaP and 22Rv1 cell line models of slowly growing carcinomas. In all cell lines tested, we show an inverse relationship between the expression of miR-221 and miR-222 and the cell cycle inhibitor p27(Kip1). We recognize two target sites for the microRNAs in the 3' untranslated region of p27 mRNA, and we show that miR-221/222 ectopic overexpression directly results in p27 down-regulation in LNCaP cells. In those cells, we demonstrate that the ectopic overexpression of miR-221/222 strongly affects their growth potential by inducing a G(1) to S shift in the cell cycle and is sufficient to induce a powerful enhancement of their colony-forming potential in soft agar. Consistently, miR-221 and miR-222 knock-down through antisense LNA oligonucleotides increases p27(Kip1) in PC3 cells and strongly reduces their clonogenicity in vitro. Our results suggest that miR-221/222 can be regarded as a new family of oncogenes, directly targeting the tumor suppressor p27(Kip1), and that their overexpression might be one of the factors contributing to the oncogenesis and progression of prostate carcinoma through p27(Kip1) down-regulation.

During the 2020 COVID-19 pandemic, an outbreak occurred following attendance of a symptomatic index case at a weekly rehearsal on 10 March of the Skagit Valley Chorale (SVC). After that rehearsal, 53 members of the SVC among 61 in attendance were confirmed or strongly suspected to have contracted COVID-19 and two died. Transmission by the aerosol route is likely; it appears unlikely that either fomite or ballistic droplet transmission could explain a substantial fraction of the cases. It is vital to identify features of cases such as this to better understand the factors that promote superspreading events. Based on a conditional assumption that transmission during this outbreak was dominated by inhalation of respiratory aerosol generated by one index case, we use the available evidence to infer the emission rate of aerosol infectious quanta. We explore how the risk of infection would vary with several influential factors: ventilation rate, duration of event, and deposition onto surfaces. The results indicate a best-estimate emission rate of 970 ± 390 quanta/h. Infection risk would be reduced by a factor of two by increasing the aerosol loss rate to 5 h−1 and shortening the event duration from 2.5 to 1 h.

After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.

Adaptation and innovation are extremely important to the manufacturing industry. This development should lead to sustainable manufacturing using new technologies. To promote sustainability, smart production requires global perspectives of smart production application technology. In this regard, thanks to intensive research efforts in the field of artificial intelligence (AI), a number of AI-based techniques, such as machine learning, have already been established in the industry to achieve sustainable manufacturing. Thus, the aim of the present research was to analyze, systematically, the scientific literature relating to the application of artificial intelligence and machine learning (ML) in industry. In fact, with the introduction of the Industry 4.0, artificial intelligence and machine learning are considered the driving force of smart factory revolution. The purpose of this review was to classify the literature, including publication year, authors, scientific sector, country, institution, and keywords. The analysis was done using the Web of Science and SCOPUS database. Furthermore, UCINET and NVivo 12 software were used to complete them. A literature review on ML and AI empirical studies published in the last century was carried out to highlight the evolution of the topic before and after Industry 4.0 introduction, from 1999 to now. Eighty-two articles were reviewed and classified. A first interesting result is the greater number of works published by the USA and the increasing interest after the birth of Industry 4.0.

The recent Covid-19 pandemic has had significant psychological and social effects on the population. Research has highlighted the impact on psychological well-being of the most exposed groups, including children, college students, and health workers, who are more likely to develop post-traumatic stress disorder, anxiety, depression, and other symptoms of distress. The social distance and the security measures have affected the relationship among people and their perception of empathy toward others. From this perspective, telepsychology and technological devices assume important roles to decrease the negative effects of the pandemic. These tools present benefits that could improve psychological treatment of patients online, such as the possibility to meet from home or from the workplace, saving money and time and maintaining the relationship between therapists and patients. The aim of this paper is to show empirical data from recent studies on the effect of the pandemic and reflect on possible interventions based on technological tools.

Magnetite nanoparticles (Fe₃O₄) represent the most promising materials in medical applications. To favor high-drug or enzyme loading on the nanoparticles, they are incorporated into mesoporous materials to form a hybrid support with the consequent reduction of magnetization saturation. The direct synthesis of mesoporous structures appears to be of interest. To this end, magnetite nanoparticles have been synthesized using a one pot co-precipitation reaction at room temperature in the presence of different bases, such as NaOH, KOH or (C₂H₅)₄NOH. Magnetite shows characteristics of superparamagnetism at room temperature and a saturation magnetization (Ms) value depending on both the crystal size and the degree of agglomeration of individual nanoparticles. Such agglomeration appears to be responsible for the formation of mesoporous structures, which are affected by the pH, the nature of alkali, the slow or fast addition of alkaline solution and the drying modality of synthesized powders.

Alzheimer's disease and related dementias (ADRDs) are a global crisis facing the aging population and society as a whole. With the numbers of people with ADRDs predicted to rise dramatically across the world, the scientific community can no longer neglect the need for research focusing on ADRDs among underrepresented ethnoracial diverse groups. The Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART; alz.org/ISTAART) comprises a number of professional interest areas (PIAs), each focusing on a major scientific area associated with ADRDs. We leverage the expertise of the existing international cadre of ISTAART scientists and experts to synthesize a cross-PIA white paper that provides both a concise "state-of-the-science" report of ethnoracial factors across PIA foci and updated recommendations to address immediate needs to advance ADRD science across ethnoracial populations.

Although Big Data is a trending buzzword in both academia and the industry, its meaning is still shrouded by much conceptual vagueness. The term is used to describe a wide range of concepts: from the technological ability to store, aggregate, and process data, to the cultural shift that is pervasively invading business and society, both drowning in information overload. The lack of a formal definition has led research to evolve into multiple and inconsistent paths. Furthermore, the existing ambiguity among researchers and practitioners undermines an efficient development of the subject. In this paper we have reviewed the existing literature on Big Data and analyzed its previous definitions in order to pursue two results: first, to provide a summary of the key research areas related to the phenomenon, identifying emerging trends and suggesting opportunities for future development; second, to provide a consensual definition for Big Data, by synthesizing common themes of existing works and patterns in previous definitions.

Recently, the so-called cell-free (CF) massive MIMO architecture has been introduced, wherein a very large number of distributed access points simultaneously and jointly serve a much smaller number of mobile stations. This letter introduces a user-centric (UC) virtual cell approach to CF massive MIMO, wherein each user is served only by a limited number of access points. The UC approach requires less backhaul overhead than the CF approach, and outperforms the latter in terms of achievable rate-per-user for the vast majority of the users in the network.

A dorsal frontoparietal network, including regions in intraparietal sulcus (IPS) and frontal eye field (FEF), has been hypothesized to control the allocation of spatial attention to environmental stimuli. One putative mechanism of control is the desynchronization of electroencephalography (EEG) alpha rhythms (approximately 8-12 Hz) in visual cortex in anticipation of a visual target. We show that brief interference by repetitive transcranial magnetic stimulation (rTMS) with preparatory activity in right IPS or right FEF while subjects attend to a spatial location impairs identification of target visual stimuli approximately 2 s later. This behavioral effect is associated with the disruption of anticipatory (prestimulus) alpha desynchronization and its spatially selective topography in parieto-occipital cortex. Finally, the disruption of anticipatory alpha rhythms in occipital cortex after right IPS- or right FEF-rTMS correlates with deficits of visual identification. These results support the causal role of the dorsal frontoparietal network in the control of visuospatial attention, and suggest that this is partly exerted through the synchronization of occipital visual neurons.

The CRESST experiment is a direct dark matter search which aims to measure interactions of potential dark matter particles in an Earth-bound detector. With the current stage, CRESST-III, we focus on a low energy threshold for increased sensitivity towards light dark matter particles. In this paper we describe the analysis of one detector operated in the first run of CRESST-III (05/2016--02/2018) achieving a nuclear recoil threshold of 30.1 eV. This result was obtained with a 23.6 g ${\mathrm{CaWO}}_{4}$ crystal operated as a cryogenic scintillating calorimeter in the CRESST setup at the Laboratori Nazionali del Gran Sasso (LNGS). Both the primary phonon (heat) signal and the simultaneously emitted scintillation light, which is absorbed in a separate silicon-on-sapphire light absorber, are measured with highly sensitive transition edge sensors operated at $\ensuremath{\sim}15\text{ }\text{ }\mathrm{mK}$. The unique combination of these sensors with the light element oxygen present in our target yields sensitivity to dark matter particle masses as low as $160\text{ }\text{ }\mathrm{MeV}/{\mathrm{c}}^{2}$.

Fifth-generation (5G) cellular communications promise to deliver the gigabit experience to mobile users, with a capacity increase of up to three orders of magnitude with respect to current long-term evolution (LTE) systems. There is widespread agreement that such an ambitious goal will be realized through a combination of innovative techniques involving different network layers. At the physical layer, the orthogonal frequency division multiplexing (OFDM) modulation format, along with its multiple-access strategy orthogonal frequency division multiple access (OFDMA), is not taken for granted, and several alternatives promising larger values of spectral efficiency are being considered. This article provides a review of some modulation formats suited for 5G, enriched by a comparative analysis of their performance in a cellular environment, and by a discussion on their interactions with specific 5G ingredients. The interaction with a massive multiple-input, multiple-output (MIMO) system is also discussed by employing real channel measurements.

Despite the relevance of corruption in project selection, planning and delivery, the project management literature pays little attention to this crucial phenomenon. This paper sets the background to foster the discussion concerning how to select, plan and deliver infrastructure in corrupt project contexts. It presents the different types of corruptions and the characteristics of projects that are more likely to suffer from it. Corruption is particularly relevant for large and uncommon projects where the public sector acts as client/owner or even as the main contractor. Megaprojects are “large unique projects” where public actors play a key role and are very likely to be affected by corruption. Corruption worsens both cost and time performance, and the benefits delivered. This paper leverages the institutional theory to introduce the concept of “corrupt project context” and, using the case study of the Italian high-speed railways, shows the impact of a corrupt context on megaprojects.