Study of intrinsic spin and orbital Hall effects in Pt based on a (6s, 6p, 5d) tight-binding model

We study the origin of the intrinsic spin Hall conductivity (SHC) and the d-orbital Hall conductivity (OHC) in Pt based on a multiorbital tight-binding model with spin-orbit interaction. We find that the SHC reaches 1000 \hbar/e\Omega cm when the resistivity \rho is smaller than ~10 \mu\Omega cm, whereas it decreases to 300 \hbar/e\Omega cm when \rho ~ 100 \mu\Omega cm. In addition, the OHC is still larger than the SHC. The origin of huge SHE and OHE in Pt is the large ``effective magnetic flux'' that is induced by the interorbital transition between d_{xy}- and d_{x2-y2}-orbitals with the aid of the strong spin-orbit interaction.Comment: 5 page

Synthesis and antiproliferative activities of quebecol and its analogs

Simple and efficient synthesis of quebecol and a number of its analogs was accomplished in five steps. The synthesized compounds were evaluated for antiproliferative activities against human cervix adenocarcinoma (HeLa), human ovarian carcinoma (SK-OV-3), human colon carcinoma (HT-29), and human breast adenocarcinoma (MCF-7) cancer cell lines. Among all the compounds, 7c, 7d, 7f, and 8f exhibited antiproliferative activities against four tested cell lines with inhibition over 80% at 75 μM after 72 h, whereas, compound 7b and 7g were more selective towards MCF-7 cell line. The IC50 values for compounds 7c, 7d, and 7f were 85.1 μM, 78.7 μM, and 80.6 μM against MCF-7 cell line, respectively, showing slightly higher antiproliferative activtiy than the synthesized and isolated quebecol with an IC50 value of 104.2 μM against MCF-7. [Refer to PDF for graphical abstract

Interpolating self-energy of the infinite-dimensional Hubbard model: Modifying the iterative perturbation theory

We develop an analytical expression for the self-energy of the infinite-dimensional Hubbard model that is correct in a number of different limits. The approach represents a generalization of the iterative perturbation theory to arbitrary fillings. In the weak-coupling regime perturbation theory to second order in the interaction U is recovered. The theory is exact in the atomic limit. The high-energy behavior of the self-energy up to order (1/E)**2 and thereby the first four moments of the spectral density are reproduced correctly. Referring to a standard strong-coupling moment method, we analyze the limit of strong U. Different modifications of the approach are discussed and tested by comparing with the results of an exact diagonalization study.Comment: LaTeX, 14 pages, 5 ps figures included, title changed, references updated, minor change

Optimization rules for SARS-CoV-2 M\u3csup\u3epro\u3c/sup\u3e antivirals: Ensemble docking and exploration of the coronavirus protease active site

© 2020 by the authors. Coronaviruses are viral infections that have a significant ability to impact human health. Coronaviruses have produced two pandemics and one epidemic in the last two decades. The current pandemic has created a worldwide catastrophe threatening the lives of over 15 million as of July 2020. Current research efforts have been focused on producing a vaccine or repurposing current drug compounds to develop a therapeutic. There is, however, a need to study the active site preferences of relevant targets, such as the SARS-CoV-2 main protease (SARS-CoV-2 Mpro), to determine ways to optimize these drug compounds. The ensemble docking and characterization work described in this article demonstrates the multifaceted features of the SARS-CoV-2 Mpro active site, molecular guidelines to improving binding affinity, and ultimately the optimization of drug candidates. A total of 220 compounds were docked into both the 5R7Z and 6LU7 SARS-CoV-2 Mpro crystal structures. Several key preferences for strong binding to the four subsites (S1, S1\u27, S2, and S4) were identified, such as accessing hydrogen binding hotspots, hydrophobic patches, and utilization of primarily aliphatic instead of aromatic substituents. After optimization efforts using the design guidelines developed from the molecular docking studies, the average docking score of the parent compounds was improved by 6.59 -log10(Kd) in binding affinity which represents an increase of greater than six orders of magnitude. Using the optimization guidelines, the SARS-CoV-2 Mpro inhibitor cinanserin was optimized resulting in an increase in binding affinity of 4.59 -log10(Kd) and increased protease inhibitor bioactivity. The results of molecular dynamic (MD) simulation of cinanserin-optimized compounds CM02, CM06, and CM07 revealed that CM02 and CM06 fit well into the active site of SARS-CoV-2 Mpro [Protein Data Bank (PDB) accession number 6LU7] and formed strong and stable interactions with the key residues, Ser-144, His-163, and Glu-166. The enhanced binding affinity produced demonstrates the utility of the design guidelines described. The work described herein will assist scientists in developing potent COVID-19 antivirals

The Hubbard model within the equations of motion approach

The Hubbard model has a special role in Condensed Matter Theory as it is considered as the simplest Hamiltonian model one can write in order to describe anomalous physical properties of some class of real materials. Unfortunately, this model is not exactly solved except for some limits and therefore one should resort to analytical methods, like the Equations of Motion Approach, or to numerical techniques in order to attain a description of its relevant features in the whole range of physical parameters (interaction, filling and temperature). In this manuscript, the Composite Operator Method, which exploits the above mentioned analytical technique, is presented and systematically applied in order to get information about the behavior of all relevant properties of the model (local, thermodynamic, single- and two- particle ones) in comparison with many other analytical techniques, the above cited known limits and numerical simulations. Within this approach, the Hubbard model is shown to be also capable to describe some anomalous behaviors of the cuprate superconductors.Comment: 232 pages, more than 300 figures, more than 500 reference

Interaction effects on common measures of sensitivity:Choice of measure, type I error, and power

Here we use simulation to assess previously unaddressed problems in the assessment of statistical interactions in detection and recognition tasks. The proportion of hits and false-alarms made by an observer on such tasks is affected by both their sensitivity and bias, and numerous measures have been developed to separate out these two factors. Each of these measures makes different assumptions regarding the underlying process and different predictions as to how false-alarm and hit rates should covary. Previous simulations have shown that choice of an inappropriate measure can lead to inflated type I error rates, or reduced power, for main effects, provided there are differences in response bias between the conditions being compared. Interaction effects pose a particular problem in this context. We show that spurious interaction effects in analysis of variance can be produced, or true interactions missed, even in the absence of variation in bias. Additional simulations show that variation in bias complicates patterns of type I error and power further. This under-appreciated fact has the potential to greatly distort the assessment of interactions in detection and recognition experiments. We discuss steps researchers can take to mitigate their chances of making an error

A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15-1.73 GHz

We conducted a search for narrowband radio signals over four observing sessions in 2020-2023 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions from a total of ~11,680 stars and planetary systems in the ~9 arcminute beam of the telescope. All detections were either automatically rejected or visually inspected and confirmed to be of anthropogenic nature. In this work, we also quantified the end-to-end efficiency of radio SETI pipelines with a signal injection and recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected signals over the usable frequency range of the receiver and 98.7% of the injections when regions of dense RFI are excluded. In another pipeline that uses incoherent sums of 51 consecutive spectra, the recovery rate is ~15 times smaller at ~6%. The pipeline efficiency affects calculations of transmitter prevalence and SETI search volume. Accordingly, we developed an improved Drake Figure of Merit and a formalism to place upper limits on transmitter prevalence that take the pipeline efficiency and transmitter duty cycle into account. Based on our observations, we can state at the 95% confidence level that fewer than 6.6% of stars within 100 pc host a transmitter that is detectable in our search (EIRP > 1e13 W). For stars within 20,000 ly, the fraction of stars with detectable transmitters (EIRP > 5e16 W) is at most 3e-4. Finally, we showed that the UCLA SETI pipeline natively detects the signals detected with AI techniques by Ma et al. (2023).Comment: 22 pages, 9 figures, submitted to AJ, revise