Memtransistor Devices Based on MoS 2 Multilayers with Volatile Switching due to Ag Cation Migration

In the recent years, the need for fast, robust, and scalable memory devices have spurred the exploration of advanced materials with unique electrical properties. Among these materials, 2D semiconductors are promising candidates as they combine atomically thin size, semiconductor behavior, and complementary metal-oxide-semiconductor compatibility. Here a three-terminal memtransistor device, based on multilayer MoS2 with ultrashort channel length, that combines the usual transistor behavior of 2D semiconductors with resistive switching memory operation is presented. The volatile switching behavior is explained by the Ag cation migration along the channel surface. An extensive physical and electrical characterization to investigate the fundamental properties of the device, is presented. Finally, a chain-type memory array architecture similar to a NAND flash structure consisting of memtransistors is demonstrated, where the individual memory devices can be selected for write and read, paving the way for high-density, 3D memories based on 2D semiconductors

Reservoir Computing with Charge-Trap Memory Based on a MoS2 Channel for Neuromorphic Engineering

Novel memory devices are essential for developing low power, fast, and accurate in-memory computing and neuromorphic engineering concepts that can compete with the conventional complementary metal-oxide-semiconductor (CMOS) digital processors. 2D semiconductors provide a novel platform for advanced semiconductors with atomic thickness, low-current operation, and capability of 3D integration. This work presents a charge-trap memory (CTM) device with a MoS2 channel where memory operation arises, thanks to electron trapping/detrapping at interface states. Transistor operation, memory characteristics, and synaptic potentiation/depression for neuromorphic applications are demonstrated. The CTM device shows outstanding linearity of the potentiation by applied drain pulses of equal amplitude. Finally, pattern recognition is demonstrated by reservoir computing where the input pattern is applied as a stimulation of the MoS2-based CTMs, while the output current after stimulation is processed by a feedforward readout network. The good accuracy, the low current operation, and the robustness to input random bit flip makes the CTM device a promising technology for future high-density neuromorphic computing concepts

Dietary supplements for the management of COVID-19 symptoms

SARS-CoV-2, the etiological agent of COVID-19, caused a pandemic in 2020, which is only recently slowing down. The symptoms of COVID-19 range from cough to fever and pneumonia and may persist beyond the active state of the infection, in a condition called post-COVID syndrome. The aim of this paper is to review the relationship between COVID-19 and nutrition and to discuss to most up-to-date dietary supplements proposed for COVID-19 treatment and prevention. Nutrition and nutritional dysregulations, such as obesity and malnutrition, are prominent risk factors for severe COVID-19. These factors exert anti-inflammatory and proinflammatory effects on the immune system, thus exacerbating or reducing the immunological response against the virus. As for the nutritional habits, the Western diet induces a chronic inflammatory state, whereas the Mediterranean diet exerts anti-inflammatory effects and has been proposed for ameliorating COVID-19 evolution and symptoms. Several vaccines have been researched and commercialized for COVID-19 prevention, whereas several drugs, although clinically tested, have not shown promising effects. To compensate for the lack of treatment, several supplements have been recommended for preventing or ameliorating COVID-19 symptoms. Thus, it is critical to review the dietary supplements proposed for COVID-19 treatment. Supplements containing α-cyclodextrin and hydroxytyrosol exhibited promising effects in several clinical trials and reduced the severity of the outcomes and the duration of the infection. Moreover, a supplement containing hydroxytyrosol, acetyl L-carnitine, and vitamins B, C, and D improved the symptoms of patients with post-COVID syndrome

Redox memristors with volatile threshold switching behavior for neuromorphic computing

The spiking neural network (SNN), closely inspired by the human brain, is one of the most powerful platforms to enable highly efficient, low cost, and robust neuromorphic computations in hardware using traditional or emerging electron devices within an integrated system. In the hardware implementation, the building of artificial spiking neurons is fundamental for constructing the whole system. However, with the slowing down of Moore’s Law, the traditional complementary metal-oxide-semiconductor (CMOS) technology is gradually fading and is unable to meet the growing needs of neuromorphic computing. Besides, the existing artificial neuron circuits are complex owing to the limited bio-plausibility of CMOS devices. Memristors with volatile threshold switching (TS) behaviors and rich dynamics are promising candidates to emulate the biological spiking neurons beyond the CMOS technology and build high-efficient neuromorphic systems. Herein, the state-of-the-art about the fundamental knowledge of SNNs is reviewed. Moreover, we review the implementation of TS memristor-based neurons and their systems, and point out the challenges that should be further considered from devices to circuits in the system demonstrations. We hope that this review could provide clues and be helpful for the future development of neuromorphic computing with memristors

Methodology for clinical research

A clinical research requires a systematic approach with diligent planning, execution and sampling in order to obtain reliable and validated results, as well as an understanding of each research methodology is essential for researchers. Indeed, selecting an inappropriate study type, an error that cannot be corrected after the beginning of a study, results in flawed methodology. The results of clinical research studies enhance the repertoire of knowledge regarding a disease pathogenicity, an existing or newly discovered medication, surgical or diagnostic procedure or medical device. Medical research can be divided into primary and secondary research, where primary research involves conducting studies and collecting raw data, which is then analysed and evaluated in secondary research. The successful deployment of clinical research methodology depends upon several factors. These include the type of study, the objectives, the population, study design, methodology/techniques and the sampling and statistical procedures used. Among the different types of clinical studies, we can recognize descriptive or analytical studies, which can be further categorized in observational and experimental. Finally, also pre-clinical studies are of outmost importance, representing the steppingstone of clinical trials. It is therefore important to understand the types of method for clinical research. Thus, this review focused on various aspects of the methodology and describes the crucial steps of the conceptual and executive stages

Ethical considerations regarding animal experimentation

Animal experimentation is widely used around the world for the identification of the root causes of various diseases in humans and animals and for exploring treatment options. Among the several animal species, rats, mice and purpose-bred birds comprise almost 90% of the animals that are used for research purpose. However, growing awareness of the sentience of animals and their experience of pain and suffering has led to strong opposition to animal research among many scientists and the general public. In addition, the usefulness of extrapolating animal data to humans has been questioned. This has led to Ethical Committees’ adoption of the ‘four Rs’ principles (Reduction, Refinement, Replacement and Responsibility) as a guide when making decisions regarding animal experimentation. Some of the essential considerations for humane animal experimentation are presented in this review along with the requirement for investigator training. Due to the ethical issues surrounding the use of animals in experimentation, their use is declining in those research areas where alternative in vitro or in silico methods are available. However, so far it has not been possible to dispense with experimental animals completely and further research is needed to provide a road map to robust alternatives before their use can be fully discontinued

Identifying Synergies and Barriers to the Adoption of Disruptive Technologies for Sustainable Societies - An Innovation Ecosystem Perspective

This paper contributes to the literature on the adoption of disruptive technologies for the transition to more sustainable societies by mapping businesses’ uptake in the Italian region of Piedmont from the perspective of innovation ecosystems. Despite their relevance for sustainability and competitiveness, evidence on the European Union indicates major weaknesses in the adoption of crucial disruptive technologies, recommending a stronger focus on the local and regional levels. This could be achieved via the perspective of innovation ecosystems so as to identify and strengthen industrial synergies in technology adoption, but current systematic research in this vein is limited by a lack of consistent and publically available data. Aiming to fill this gap, this study developed a highly scalable approach to map business actors and their uptake of emerging technologies. First, textual information on over 17,000 organizations operating in Piedmont was retrieved from the social network LinkedIn. Second, elementary text-mining techniques were used to verify their engagement with 5G Networks, Advanced Robotics, Artificial Intelligence, Autonomous Drive, Blockchain, and Drones. Third, uptakes within and across industries were statistically assessed. This identified 1273 businesses pertaining to 115 different sectors that already engaged with at least one of the above mentioned technological innovations, displayed some industrial synergies and complementarities, and confirmed key barriers to their uptake. Additional data would strengthen these results. Nonetheless, this study already provides preliminary evidence on technology adoption from the perspective of innovation ecosystems and a proof of concept for the use LinkedIn for ecosystem mapping

Trans-city data integration platforms: an explorative study on Smart Dublin and Torino City Lab

This paper contributes to the literature on living labs, innovation ecosystems, and the transformation to smart and sustainable cities by exploring the use of a trans-city data integration platform on the smart city programs Smart Dublin and Turin City Lab. Research on living labs and innovation ecosystems is growing and showing increasing interest in the urban scale and the development of smart cities. For the density and interconnectedness of actors and resources, smart cities are believed the perfect grounds for technological and social experimentation, and they may catalyze the transformation toward smart, sustainable, and inclusive societies. Crucially, this requires systematically collecting massive amounts of data from a multiplicity of local stakeholders. While research has often highlighted the opportunities and challenges related to this data collection at the city level, almost no study has yet investigated the potential of aggregating and integrating data from multiple cities via a common infrastructure. This explorative study aims at addressing this gap. Focusing on the smart city programs of Dublin and Turin, it fosters the conceptualization of trans-city data integration platforms and explores their applicability to two real-life smart city living labs. This was achieved by adopting the Quadruple Helix model of innovation, and then by qualitatively analyzing the two smart city programs and 53 subprojects. It was found that initiatives from Smart Dublin and the Torino City Lab display thematic overlaps and complementarities. Hence, this contributes to the existing literature by showing that a common infrastructure for data collection may be developed. Moreover, it informs policy makers and practitioners on the importance of collecting data that could be easily integrated also across geographies, so as to lead to major advantages of scale in the future

Laboratorio Venezia

Laboratorio Venezia è il primo quaderno dedicato ai lavori portati avanti nel Laboratorio di Analisi e rappresentazione del Corso di laurea in Urbanistica e Pianificazione del territorio dell’Università Iuav di Venezia, che ha come caso di studio la città di Venezia. La scelta è stata dettata da più motivi, da un lato la volontà di occuparci della città nella quale gli studenti trascorrono la maggior parte del loro tempo talvolta senza approfondirne la conoscenza, dall’altro la sfida da che la città lagunare pone per le sue peculiarità, il suo essere città globale inserita nei circuiti internazionali, la sua apparente immobilità in uno stato invece di fluttuante cambiamento