Khalifa University

About: Khalifa University is a education organization based out in Abu Dhabi, United Arab Emirates. It is known for research contribution in the topics: Computer science & Adsorption. The organization has 3752 authors who have published 10909 publications receiving 141629 citations.

Antibacterial Activity of Ti3C2Tx MXene

Abstract: MXenes are a family of atomically thin, two-dimensional (2D) transition metal carbides and carbonitrides with many attractive properties. Two-dimensional Ti3C2Tx (MXene) has been recently explored for applications in water desalination/purification membranes. A major success indicator for any water treatment membrane is the resistance to biofouling. To validate this and to understand better the health and environmental impacts of the new 2D carbides, we investigated the antibacterial properties of single- and few-layer Ti3C2Tx MXene flakes in colloidal solution. The antibacterial properties of Ti3C2Tx were tested against Escherichia coli (E. coli) and Bacillus subtilis (B. subtilis) by using bacterial growth curves based on optical densities (OD) and colonies growth on agar nutritive plates. Ti3C2Tx shows a higher antibacterial efficiency toward both Gram-negative E. coli and Gram-positive B. subtilis compared with graphene oxide (GO), which has been widely reported as an antibacterial agent. Concentratio...

Superconducting qubit–oscillator circuit beyond the ultrastrong-coupling regime

Abstract: A circuit that pairs a flux qubit with an LC oscillator via Josephson junctions pushes the coupling between light to matter to uncharted territory, with the potential for new applications in quantum technologies. The interaction between an atom and the electromagnetic field inside a cavity1,2,3,4,5,6 has played a crucial role in developing our understanding of light–matter interaction, and is central to various quantum technologies, including lasers and many quantum computing architectures. Superconducting qubits7,8 have allowed the realization of strong9,10 and ultrastrong11,12,13 coupling between artificial atoms and cavities. If the coupling strength g becomes as large as the atomic and cavity frequencies (Δ and ωo, respectively), the energy eigenstates including the ground state are predicted to be highly entangled14. There has been an ongoing debate15,16,17 over whether it is fundamentally possible to realize this regime in realistic physical systems. By inductively coupling a flux qubit and an LC oscillator via Josephson junctions, we have realized circuits with g/ωo ranging from 0.72 to 1.34 and g/Δ ≫ 1. Using spectroscopy measurements, we have observed unconventional transition spectra that are characteristic of this new regime. Our results provide a basis for ground-state-based entangled pair generation and open a new direction of research on strongly correlated light–matter states in circuit quantum electrodynamics.

The iCub humanoid robot: an open platform for research in embodied cognition

Abstract: We report about the iCub, a humanoid robot for research in embodied cognition. At 104 cm tall, the iCub has the size of a three and half year old child. It will be able to crawl on all fours and sit up to manipulate objects. Its hands have been designed to support sophisticate manipulation skills. The iCub is distributed as Open Source following the GPL/FDL licenses. The entire design is available for download from the project homepage and repository (http://www.robotcub.org). In the following, we will concentrate on the description of the hardware and software systems. The scientific objectives of the project and its philosophical underpinning are described extensively elsewhere [1].

Blockchain for AI: Review and Open Research Challenges

Abstract: Recently, artificial intelligence (AI) and blockchain have become two of the most trending and disruptive technologies. Blockchain technology has the ability to automate payment in cryptocurrency and to provide access to a shared ledger of data, transactions, and logs in a decentralized, secure, and trusted manner. Also with smart contracts, blockchain has the ability to govern interactions among participants with no intermediary or a trusted third party. AI, on the other hand, offers intelligence and decision-making capabilities for machines similar to humans. In this paper, we present a detailed survey on blockchain applications for AI. We review the literature, tabulate, and summarize the emerging blockchain applications, platforms, and protocols specifically targeting AI area. We also identify and discuss open research challenges of utilizing blockchain technologies for AI.

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study.

Abstract: Background: The recent coronavirus disease (COVID-19) pandemic is taking a toll on the world’s health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and health care organizations assess the needs of their stakeholders and address them appropriately. Objective: This study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic. Methods: Leveraging a set of tools (Twitter’s search application programming interface (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined search terms (“corona,” “2019-nCov,” and “COVID-19”), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic. Results: Out of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss), while the lowest was 3.94 (travel bans and warnings). Conclusions: Public health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.