Co-induced nano-structures on Si(111) surface

The interaction of cobalt atoms with silicon (111) surface has been investigated by means of scanning tunneling microscopy (STM) and low-energy electron diffraction (LEED). Besides the Co silicide islands, we have successfully distinguished two inequivalent Co-induced $\sqrt{13}\times\sqrt{13}$ reconstructions on Si (111) surface. Our high-resolution STM images provide some structural properties of the two different $\sqrt{13}\times\sqrt{13}$ derived phases. Both of the two phases seem to form islands with single domain. The new findings will help us to understand the early stage of Co silicide formations.Comment: 4pages 4figure

Radiant energy absorption studies for laser propulsion

A study of the energy absorption mechanisms and fluid dynamic considerations for efficient conversion of high power laser radiation into a high velocity flow is presented. The objectives of the study are: (1) to determine the most effective absorption mechanisms for converting laser radiation into translational energy, and (2) to examine the requirements for transfer of the absorbed energy into a steady flow which is stable to disturbances in the absorption zone. A review of inverse Bremsstrahlung, molecular and particulate absorption mechanisms is considered and the steady flow and stability considerations for conversion of the laser power to a high velocity flow in a nozzle configuration is calculated. A quasi-one-dimensional flow through a nozzle was formulated under the assumptions of perfect gas

Scoping review and bibliometric analysis of Big Data applications for Medication adherence: An explorative methodological study to enhance consistency in literature

Background: Medication adherence has been studied in different settings, with different approaches, and applying different methodologies. Nevertheless, our knowledge and efficacy are quite limited in terms of measuring and evaluating all the variables and components that affect the management of medication adherence regimes as a complex phenomenon. The study aim is mapping the state-of-the-art of medication adherence measurement and assessment methods applied in chronic conditions. Specifically, we are interested in what methods and assessment procedures are currently used to tackle medication adherence. We explore whether Big Data techniques are adopted to improve decision-making procedures regarding patients' adherence, and the possible role of digital technologies in supporting interventions for improving patient adherence and avoiding waste or harm. Methods: A scoping literature review and bibliometric analysis were used. Arksey and O'Malley's framework was adopted to scope the review process, and a bibliometric analysis was applied to observe the evolution of the scientific literature and identify specific characteristics of the related knowledge domain. Results: A total of 533 articles were retrieved from the Scopus academic database and selected for the bibliometric analysis. Sixty-one studies were identified and included in the final analysis. The Morisky medication adherence scale (36%) was the most frequently adopted baseline measurement tool, and cardiovascular/hypertension disease, the most investigated illness (38%). Heterogeneous findings emerged from the types of study design and the statistical methodologies used to assess and compare the results. Conclusions: Our findings reveal a lack of Big Data applications currently deployed to address or measure medication adherence in chronic conditions. Our study proposes a general framework to select the methods, measurements and the corpus of variables in which the treatment regime can be analyzed

Unraveling the Effect of Carbon Nanotube Oxidation on Solid-State Decomposition of Ammonia Borane/Carbon Nanotube Composites

Among the routes to perform hydrogen release from ammonia in solid state, the nanoconfinement into a carbonaceous matrix or the use of carbon-supported catalysts for the thermal degradation of ammonia borane (AB) is the most interesting one. Oxidized carbon nanotubes (CNTs) represent a suitable choice for preparing AB mixtures or for anchoring catalysts for dehydrogenation. Nevertheless, literature lacks detailed study about the influence of CNT oxidation degree on the AB degradation/hydrogen release. In this study, we first described in a comprehensive way that the thermal degradation of AB mixed with CNTs by varying the CNT oxidation degree enlightens the degradative routes mainly active in each case. Using highly oxidized CNTs, we observed a decrement of activation energy of the degradative process up to around 53% and the activation/suppression of different pathways based on the amount of oxygen functionalities present in the mixtures. Furthermore, the presence of oxidized CNTs modulated the solid-state reactivity of AB reducing the release of nitrogen/boron species together with hydrogen. These findings lead the way for the design of new hydrogen storage materials

Laser-heated rocket studies

CW laser heated rocket propulsion was investigated in both the flowing core and stationary core configurations. The laser radiation considered was 10.6 micrometers, and the working gas was unseeded hydrogen. The areas investigated included initiation of a hydrogen plasma capable of absorbing laser radiation, the radiation emission properties of hot, ionized hydrogen, the flow of hot hydrogen while absorbing and radiating, the heat losses from the gas and the rocket performance. The stationary core configuration was investigated qualitatively and semi-quantitatively. It was found that the flowing core rockets can have specific impulses between 1,500 and 3,300 sec. They are small devices, whose heating zone is only a millimeter to a few centimeters long, and millimeters to centimeters in radius, for laser power levels varying from 10 to 5,000 kW, and pressure levels of 3 to 10 atm. Heat protection of the walls is a vital necessity, though the fraction of laser power lost to the walls can be as low as 10% for larger powers, making the rockets thermally efficient

Learning to See through a Few Pixels: Multi Streams Network for Extreme Low-Resolution Action Recognition

Human action recognition is one of the most pressing questions in societal emergencies of any kind. Technology is helping to solve such problems at the cost of stealing human privacy. Several approaches have considered the relevance of privacy in the pervasive process of observing people. New algorithms have been proposed to deal with low-resolution images hiding people identity. However, many of these methods do not consider that social security asks for real-time solutions: active cameras require flexible distributed systems in sensible areas as airports, hospitals, stations, squares and roads. To conjugate both human privacy and real-time supervision, we propose a novel deep architecture, the Multi Streams Network. This model works in real-time and performs action recognition on extremely low-resolution videos, exploiting three sources of information: RGB images, optical flow and slack mask data. Experiments on two datasets show that our architecture improves the recognition accuracy compared to the two-streams approach and ensure real-time execution on Edge TPU (Tensor Processing Unit)

Social participation of families with children with autism spectrum disorder in a science museum

This article describes a qualitative research study undertaken as a collaboration between museum and occupational therapy (OT) researchers to better understand museum experiences for families with a child or children impacted by autism spectrum disorder (ASD). Inclusion for visitors with ASD is an issue that museums are increasingly considering, and the social dimension of inclusion can be particularly relevant for this audience. The construct of social participation, used in OT, provides a promising avenue for museum professionals to think about inclusion. Social participation situates social and community experiences within the context of peoples’ diverse motivations and the strategies they use to navigate environments. This study took these multiple factors into account when observing families’ museum visits—including analysis of their motivations for visiting, environmental features that influenced their visit, family strategies used before and during the visit, and the families’ definitions of a successful visit. Learning more about these factors that are associated with social participation can inform future efforts to improve museum inclusion for families with children with ASD

Topic modeling and user network analysis on twitter during world lupus awareness day

Twitter is increasingly used by individuals and organizations to broadcast their feelings and practices, providing access to samples of spontaneously expressed opinions on all sorts of themes. Social media offers an additional source of data to unlock information supporting new insights disclosures, particularly for public health purposes. Systemic lupus erythematosus (SLE) is a complex, systemic autoimmune disease that remains a major challenge in therapeutic diagnostic and treatment management. When supporting patients with such a complex disease, sharing information through social media can play an important role in creating better healthcare services. This study explores the nature of topics posted by users and organizations on Twitter during world Lupus day to extract latent topics that occur in tweet texts and to identify what information is most commonly discussed among users. We identified online influencers and opinion leaders who discussed different topics. During this analysis, we found two different types of influencers that employed different narratives about the communities they belong to. Therefore, this study identifies hidden information for healthcare decision-makers and provides a detailed model of the implications for healthcare organizations to detect, understand, and define hidden content behind large collections of text

Ultrasensitive Piezoresistive and Piezocapacitive Cellulose-Based Ionic Hydrogels for Wearable Multifunctional Sensing

Tactile sensors, namely, flexible devices that sense physical stimuli, have received much attention in the last few decades due to their applicability in a wide range of fields like the world of wearables, soft robotics, prosthetics, and e-skin. Nevertheless, achieving a trade-off among stretchability, good sensitivity, easy manufacturability, and multisensing ability is still a challenge. Herein, an extremely flexible strain sensor composed of a cellulose-based hydrogel is presented. A natural biocompatible carboxymethylcellulose (CMC) hydrogel endowed with ionic conductivity by sodium chloride (NaCl) was used as the sensitive part. Both the sensible layer and electrodes were investigated with an innovative approach for wearable sensor applications based on electrochemical impedance spectroscopy to find the best device configuration. The sensor, exploitable both as a piezoresistor and as a piezocapacitor, presents high sensitivity to external stimuli, together with an extreme stretchability of up to 600%, showing the best strain and temperature sensitivity among the ionic conductive hydrogel-based devices presented in the literature. The very high strain sensitivity enables the hydrogel to be implemented in wearable strain sensors to monitor different human motions and physiological signals, representing a valid solution for the realization of transparent, easily manufacturable, and low-environmental-impact devices

Ultrasensitive Piezoresistive and Piezocapacitive Cellulose-Based Ionic Hydrogels for Wearable Multifunctional Sensing

Tactile sensors, namely, flexible devices that sense physical stimuli, have received much attention in the last few decades due to their applicability in a wide range of fields like the world of wearables, soft robotics, prosthetics, and e-skin. Nevertheless, achieving a trade-off among stretchability, good sensitivity, easy manufacturability, and multisensing ability is still a challenge. Herein, an extremely flexible strain sensor composed of a cellulose-based hydrogel is presented. A natural biocompatible carboxymethylcellulose (CMC) hydrogel endowed with ionic conductivity by sodium chloride (NaCl) was used as the sensitive part. Both the sensible layer and electrodes were investigated with an innovative approach for wearable sensor applications based on electrochemical impedance spectroscopy to find the best device configuration. The sensor, exploitable both as a piezoresistor and as a piezocapacitor, presents high sensitivity to external stimuli, together with an extreme stretchability of up to 600%, showing the best strain and temperature sensitivity among the ionic conductive hydrogel-based devices presented in the literature. The very high strain sensitivity enables the hydrogel to be implemented in wearable strain sensors to monitor different human motions and physiological signals, representing a valid solution for the realization of transparent, easily manufacturable, and low-environmental-impact devices