Probing Spin-Charge Relation by Magnetoconductance in One-Dimensional Polymer Nanofibers

Polymer nanofibers are one-dimensional organic hydrocarbon systems containing conducting polymers where the non-linear local excitations such as solitons, polarons and bipolarons formed by the electron-phonon interaction were predicted. Magnetoconductance (MC) can simultaneously probe both the spin and charge of these mobile species and identify the effects of electron-electron interactions on these nonlinear excitations. Here we report our observations of a qualitatively different MC in polyacetylene (PA) and in polyaniline (PANI) and polythiophene (PT) nanofibers. In PA the MC is essentially zero, but it is present in PANI and PT. The universal scaling behavior and the zero (finite) MC in PA (PANI and PT) nanofibers provide evidence of Coulomb interactions between spinless charged solitons (interacting polarons which carry both spin and charge)

A renormalizable SO(10) GUT scenario with spontaneous CP violation

We consider fermion masses and mixings in a renormalizable SUSY SO(10) GUT with Yukawa couplings of scalar fields in the representation 10 + 120 + 126 bar. We investigate a scenario defined by the following assumptions: i) A single large scale in the theory, the GUT scale. ii) Small neutrino masses generated by the type I seesaw mechanism with negligible type II contributions. iii) A suitable form of spontaneous CP breaking which induces hermitian mass matrices for all fermion mass terms of the Dirac type. Our assumptions define an 18-parameter scenario for the fermion mass matrices for 18 experimentally known observables. Performing a numerical analysis, we find excellent fits to all observables in the case of both the normal and inverted neutrino mass spectrum.Comment: 16 pages, two eps figure

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

An SO(10) Grand Unified Theory of Flavor

We present a supersymmetric SO(10) grand unified theory (GUT) of flavor based on an $S_4$ family symmetry. It makes use of our recent proposal to use SO(10) with type II seesaw mechanism for neutrino masses combined with a simple ansatz that the dominant Yukawa matrix (the {\bf 10}-Higgs coupling to matter) has rank one. In this paper, we show how the rank one model can arise within some plausible assumptions as an effective field theory from vectorlike {\bf 16} dimensional matter fields with masses above the GUT scale. In order to obtain the desired fermion flavor texture we use $S_4$ flavon multiplets which acquire vevs in the ground state of the theory. By supplementing the $S_4$ theory with an additional discrete symmetry, we find that the flavon vacuum field alignments take a discrete set of values provided some of the higher dimensional couplings are small. Choosing a particular set of these vacuum alignments appears to lead to an unified understanding of observed quark-lepton flavor: (i) the lepton mixing matrix that is dominantly tri-bi-maximal with small corrections related to quark mixings; (ii) quark lepton mass relations at GUT scale: $m_b\simeq m_{\tau}$ and $m_\mu\simeq 3 m_s$ and (iii) the solar to atmospheric neutrino mass ratio $m_\odot/m_{\rm atm}\simeq \theta_{\rm Cabibbo}$ in agreement with observations. The model predicts the neutrino mixing parameter, $U_{e3} \simeq \theta_{\rm Cabibbo}/(3\sqrt2) \sim 0.05$, which should be observable in planned long baseline experiments.Comment: Final version of the paper as it will appear in JHEP

Fluctuation-driven dynamics of the Internet topology

We study the dynamics of the Internet topology based on the empirical data on the level of the autonomous systems. It is found that the fluctuations occurring in the stochastic process of connecting and disconnecting edges are important features of the Internet dynamics. The network's overall growth can be described approximately by a single characteristic degree growth rate $g_{\rm eff} \approx 0.016$ and the fluctuation strength $\sigma_{\rm eff} \approx 0.14$, together with the vertex growth rate $\alpha \approx 0.029$. A stochastic model which incorporate these values and an adaptation rule newly introduced reproduces several features of the real Internet topology such as the correlations between the degrees of different vertices.Comment: Final version appeared in Phys. Rev. Let

Anti-fouling double-skinned forward osmosis membrane with zwitterionic brush for oily wastewater treatment

Despite its attractive features for energy saving separation, the performance of forward osmosis (FO) has been restricted by internal concentration polarization and fast fouling propensity that occur in the membrane sublayer. These problems have significantly affected the membrane performance when treating highly contaminated oily wastewater. In this study, a novel double-skinned FO membrane with excellent anti-fouling properties has been developed for emulsified oil-water treatment. The double-skinned FO membrane comprises a fully porous sublayer sandwiched between a highly dense polyamide (PA) layer for salt rejection and a fairly loose dense bottom zwitterionic layer for emulsified oil particle removal. The top dense PA layer was synthesized via interfacial polymerization meanwhile the bottom layer was made up of a zwitterionic polyelectrolyte brush-(poly(3-(N-2-methacryloxyethyl-N,N-dimethyl) ammonatopropanesultone), abbreviated as PMAPS layer. The resultant double-skinned membrane exhibited a high water flux of 13.7 ± 0.3 L/m2.h and reverse salt transport of 1.6 ± 0.2 g/m2.h under FO mode using 2 M NaCl as the draw solution and emulsified oily solution as the feed. The double-skinned membrane outperforms the single-skinned membrane with much lower fouling propensity for emulsified oil-water separation

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

Effects of Consecutive Versus Non-consecutive Days of Resistance Training on Strength, Body Composition, and Red Blood Cells

Health authorities worldwide recommend 2–3 days per week of resistance training (RT) performed ∼48–72 h apart. However, the influence of recovery period between RT sessions on muscle strength, body composition, and red blood cells (RBCs) are unclear.Aim: Examine the effects of three consecutive (C) or non-consecutive (NC) days of RT per week for 12 weeks on strength, body composition, and RBCs.Methods: Thirty young, healthy and recreationally active males were randomly assigned to 3 C (∼24 h between sessions) or NC (∼48–72 h between sessions) days of RT per week for 12 weeks. Both groups performed three sets of 10 repetitions at 10-repetition maximum (RM) of leg press, latissimus pulldown, leg curl, shoulder press, and leg extension for each session. Ten RM and body composition were assessed pre- and post-RT. RBC parameters were measured on the first session before RT, and 0 and 24 h post-3rd session in untrained (week 1) and trained (week 12) states.Results: No training × group interaction was found for all strength and body composition parameters (p = 0.075–0.974). Training increased strength for all exercises, bone mineral density, and total body mass via increased lean and bone mass (p < 0.001). There was no interaction (p = 0.076–0.994) and RT induced temporal changes in all RBC parameters (p < 0.001–0.003) except RBC corrected for plasma volume changes (time × training interaction; p = 0.001). Training increased hematocrit and lowered mean corpuscular hemoglobin and mean corpuscular hemoglobin concentration (p = 0.001–0.041) but did not alter uncorrected RBC, hemoglobin, mean corpuscular volume and RBC distribution width (p = 0.178–0.797).Conclusion: Both C and NC RT induced similar improvements in strength and body composition, and changes in RBC parameters