Complete trails of co-authorship network evolution

The rise and fall of a research field is the cumulative outcome of its intrinsic scientific value and social coordination among scientists. The structure of the social component is quantifiable by the social network of researchers linked via co-authorship relations, which can be tracked through digital records. Here, we use such co-authorship data in theoretical physics and study their complete evolutionary trail since inception, with a particular emphasis on the early transient stages. We find that the co-authorship networks evolve through three common major processes in time: the nucleation of small isolated components, the formation of a tree-like giant component through cluster aggregation, and the entanglement of the network by large-scale loops. The giant component is constantly changing yet robust upon link degradations, forming the network's dynamic core. The observed patterns are successfully reproducible through a new network model

Dialogue based interfaces for universal access.

Conversation provides an excellent means of communication for almost all people. Consequently, a conversational interface is an excellent mechanism for allowing people to interact with systems. Conversational systems are an active research area, but a wide range of systems can be developed with current technology. More sophisticated interfaces can take considerable effort, but simple interfaces can be developed quite rapidly. This paper gives an introduction to the current state of the art of conversational systems and interfaces. It describes a methodology for developing conversational interfaces and gives an example of an interface for a state benefits web site. The paper discusses how this interface could improve access for a wide range of people, and how further development of this interface would allow a larger range of people to use the system and give them more functionality

A Framework to Determine Prominent Research Topics and Experts from Google Scholar

In today’s digital era, most scholarly publications are made available online. These include the data of a university’s research publications which can be reached through Google Scholar. Determining the prominent research areas of a university and finding its experts is the motivation of this study. Although many people may be aware of the published articles of certain university researchers, however there are little or no information on the main research areas of the university where the researchers belong to. Thus, this study will investigate how the prominent research areas can be determined by implementing Refined Text Clustering (RTC) technique for clustering scholarly data based on the titles of publications. Then, an expert search approach can be used to determine the key players who are the experts in each research cluster. The Expert Finding System (EFS) is proposed by applying statistical analysis based on the total of number researcher’s publications and their number of citations

Pair production of charged Higgs bosons in the Left-Right Twin Higgs model at the ILC and LHC

Left-Right twin Higgs(LRTH) model predicts the existence of a pair of charged Higgs $\phi^{\pm}$. In this paper, we study the production of the charged Higgs bosons pair $\phi^{\pm}$ via the process $e^{+}e^{-}\to \phi^{+}\phi^{-}$ at the International Linear Collider(ILC). The numerical results show that the production rates are at the level of several tens fb, this process can produce the adequate distinct multi-jet final states and the SM background can be efficiently reduced. We also discuss the charged Higgs boson pair production via the process $q\bar{q}\to \phi^{+}\phi^{-}$ at the $CERN$ Large Hadron Collider(LHC) and estimate there production rates. We find that, as long as the charged Higgs bosons are not too heavy, they can be abundantly produced at the LHC. The possible signatures of these new particles might be detected at the ILC and LHC experiments.Comment: 15 pages, 5 figures, discussion extended, reference added, typos fixed, revised version to be published in Eur.Phys.J.

TeV-scale seesaw from a multi-Higgs model

We suggest new simple model of generating tiny neutrino masses through a TeV-scale seesaw mechanism without requiring tiny Yukawa couplings. This model is a simple extension of the standard model by introducing extra one Higgs singlet, and one Higgs doublet with a tiny vacuum expectation value. Experimental constraints, electroweak precision data and no large flavor changing neutral currents, are satisfied since the extra doublet only has a Yukawa interaction with lepton doublets and right-handed neutrinos, and their masses are heavy of order a TeV-scale. Since active light neutrinos are Majorana particles, this model predicts a neutrinoless double beta decay.Comment: 21 pages, 8 figure

Break up of heavy fermions at an antiferromagnetic instability

We present results of high-resolution, low-temperature measurements of the Hall coefficient, thermopower, and specific heat on stoichiometric YbRh2Si2. They support earlier conclusions of an electronic (Kondo-breakdown) quantum critical point concurring with a field induced antiferromagnetic one. We also discuss the detachment of the two instabilities under chemical pressure. Volume compression/expansion (via substituting Rh by Co/Ir) results in a stabilization/weakening of magnetic order. Moderate Ir substitution leads to a non-Fermi-liquid phase, in which the magnetic moments are neither ordered nor screened by the Kondo effect. The so-derived zero-temperature global phase diagram promises future studies to explore the nature of the Kondo breakdown quantum critical point without any interfering magnetism.Comment: minor changes, accepted for publication in JPS

Self-similar disk packings as model spatial scale-free networks

The network of contacts in space-filling disk packings, such as the Apollonian packing, are examined. These networks provide an interesting example of spatial scale-free networks, where the topology reflects the broad distribution of disk areas. A wide variety of topological and spatial properties of these systems are characterized. Their potential as models for networks of connected minima on energy landscapes is discussed.Comment: 13 pages, 12 figures; some bugs fixed and further discussion of higher-dimensional packing

Modeling the influence of attitudes, trust, and beliefs on endoscopists’ acceptance of artificial intelligence applications in medical practice

IntroductionThe potential for deployment of Artificial Intelligence (AI) technologies in various fields of medicine is vast, yet acceptance of AI amongst clinicians has been patchy. This research therefore examines the role of antecedents, namely trust, attitude, and beliefs in driving AI acceptance in clinical practice.MethodsWe utilized online surveys to gather data from clinicians in the field of gastroenterology.ResultsA total of 164 participants responded to the survey. Participants had a mean age of 44.49 (SD = 9.65). Most participants were male (n = 116, 70.30%) and specialized in gastroenterology (n = 153, 92.73%). Based on the results collected, we proposed and tested a model of AI acceptance in medical practice. Our findings showed that while the proposed drivers had a positive impact on AI tools’ acceptance, not all effects were direct. Trust and belief were found to fully mediate the effects of attitude on AI acceptance by clinicians.DiscussionThe role of trust and beliefs as primary mediators of the acceptance of AI in medical practice suggest that these should be areas of focus in AI education, engagement and training. This has implications for how AI systems can gain greater clinician acceptance to engender greater trust and adoption amongst public health systems and professional networks which in turn would impact how populations interface with AI. Implications for policy and practice, as well as future research in this nascent field, are discussed