Determining the core radio luminosity function of radio AGNs via copula

The radio luminosity functions (RLFs) of active galactic nuclei (AGNs) are traditionally measured based on total emission, which doesn't reflect the current activity of the central black hole. The increasing interest in compact radio cores of AGNs requires determination of the RLF based on core emission (i.e., core RLF). In this work we have established a large sample (totaling 1207) of radio-loud AGNs, mainly consisting of radio galaxies (RGs) and steep-spectrum radio quasars (SSRQs). Based on the sample, we explore the relationship between core luminosity ($L_c$) and total luminosity ($L_t$) via a powerful statistical tool called "Copula". The conditional probability distribution $p(\log L_{c} \mid \log L_{t})$ is obtained. We derive the core RLF as a convolution of $p(\log L_{c} \mid \log L_{t})$ with the total RLF which was determined by previous work. We relate the separate RG and SSRQ core RLFs via a relativistic beaming model and find that SSRQs have an average Lorentz factor of $\gamma=9.84_{-2.50}^{+3.61}$, and that most are seen within $8^{\circ} \lesssim \theta \lesssim 45^{\circ}$ of the jet axis. Compared with the total RLF which is mainly contributed by extended emission, the core RLF shows a very weak luminosity-dependent evolution, with the number density peaking around $z\thicksim 0.8$ for all luminosities. Differences between core and total RLFs can be explained in a framework involving a combination of density and luminosity evolutions where the cores have significantly weaker luminosity evolution than the extended emission.Comment: Accepted for publication in the ApJ

Ghost field realizations of the spinor W2,sW_{2,s} strings based on the linear W(1,2,s) algebras

It has been shown that certain W algebras can be linearized by the inclusion of a spin-1 current. This Provides a way of obtaining new realizations of the W algebras. In this paper, we investigate the new ghost field realizations of the W(2,s)(s=3,4) algebras, making use of the fact that these two algebras can be linearized. We then construct the nilpotent BRST charges of the spinor non-critical W(2,s) strings with these new realizations.Comment: 10 pages, no figure

Peptide 17, an inhibitor of YAP/TEAD4 pathway, mitigates lung cancer malignancy

Purpose: To investigate whether and how peptide 17 affects lung cancer cells.Methods: Human lung carcinoma cells, LLC and PC-9, were employed to study the therapeutic effect of peptide 17 on lung cancer. After exogenous expression of peptide 17, a co-immunoprecipitation experiment was used to examine the inhibitory effect of peptide 17. CCK8 assay was employed to assess the lung cancer cells’ viability while clone formation assays were used to assess lung cancer cell proliferation. Colony number was also determined. The stimulatory effect of peptide 17 on lung cancer cell apoptosis was assessed by fluorescence-activated cell sorting (FACS).Results: Peptide 17 efficiently disrupted the interaction between YAP and TEAD4 (p < 0.001), and decreased the expression of CTGF and Cyr61. In addition, lung cancer cell viability and proliferation significantly decreased (p < 0.001) in a time- and concentration-dependent manner. On the other hand, the proportion of apoptotic cells was significantly elevated with rising concentration of peptide 17.Conclusion: Exogenous expression of peptide 17 activates Bcl2/Bax/caspase-9 signal and isresponsible for its inhibitory effects on lung cancer cells. Thus, peptide 17 is a promising target drug in lung cancer treatment.Keywords: Lung cancer, Yes-associate protein, Transcriptional enhancer activation domain 4 (TEAD4), Peptide 17, Apoptosi

Near-Infrared (NIR) Luminescent Homoleptic Lanthanide Salen Complexes Ln(4)(Salen)(4) (Ln = Nd, Yb Or Er)

The series of homoleptic tetranuclear [Ln(4)(L)(2)(HL)(2)(NO3)(2)(OH)(2)]center dot 2(NO3) (Ln = Nd, 1; Ln = Yb, 2; Ln = Er, 3; Ln = Gd, 4) have been self-assembled from the reaction of the Salen-type Schiff-base ligand H2L with Ln(NO3)(3)center dot 6H(2)O (Ln = Nd, Yb, Er or Gd), respectively (H2L: N, N'-bis(salicylidene) cyclohexane-1,2-diamine). The result of their photophysical properties shows that the strong and characteristic NIR luminescence for complexes 1 and 2 with emissive lifetimes in microsecond ranges are observed and the sensitization arises from the excited state (both (LC)-L-1 and (LC)-L-3) of the Salen-type Schiff-base ligand with the flexible linker.National Natural Science Foundation 21173165, 20871098Ministry of Education of China NCET-10-0936Higher Education of China 20116101110003State Key Laboratory of Structure Chemistry 20100014Education Committee Foundation of Shaanxi Province 11JK0588Hong Kong Research Grants Council, P. R. of China HKBU 202407, FRG/06-07/II-16)Hong Kong Research Grants Council, Robert A. Welch Foundation F-816Texas Higher Education Coordinating Board ARP 003658-0010-2006Petroleum Research Fund 47014-AC5Chemistr

Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems

As one of the central tasks in machine learning, regression finds lots of applications in different fields. An existing common practice for solving regression problems is the mean square error (MSE) minimization approach or its regularized variants which require prior knowledge about the models. Recently, Yi et al., proposed a mutual information based supervised learning framework where they introduced a label entropy regularization which does not require any prior knowledge. When applied to classification tasks and solved via a stochastic gradient descent (SGD) optimization algorithm, their approach achieved significant improvement over the commonly used cross entropy loss and its variants. However, they did not provide a theoretical convergence analysis of the SGD algorithm for the proposed formulation. Besides, applying the framework to regression tasks is nontrivial due to the potentially infinite support set of the label. In this paper, we investigate the regression under the mutual information based supervised learning framework. We first argue that the MSE minimization approach is equivalent to a conditional entropy learning problem, and then propose a mutual information learning formulation for solving regression problems by using a reparameterization technique. For the proposed formulation, we give the convergence analysis of the SGD algorithm for solving it in practice. Finally, we consider a multi-output regression data model where we derive the generalization performance lower bound in terms of the mutual information associated with the underlying data distribution. The result shows that the high dimensionality can be a bless instead of a curse, which is controlled by a threshold. We hope our work will serve as a good starting point for further research on the mutual information based regression.Comment: 28 pages, 2 figures, presubmitted to AISTATS2023 for reviewin

Evidence for lattice-polarization-enhanced field effects at the SrTiO₃-based heterointerface

Electrostatic gating provides a powerful approach to tune the conductivity of the two-dimensional electron liquid between two insulating oxides. For the LaAlO(3)/SrTiO(3) (LAO/STO) interface, such gating effect could be further enhanced by a strong lattice polarization of STO caused by simultaneous application of gate field and illumination light. Herein, by monitoring the discharging process upon removing the gate field, we give firm evidence for the occurrence of this lattice polarization at the amorphous-LaAlO(3)/SrTiO(3) interface. Moreover, we find that the lattice polarization is accompanied with a large expansion of the out-of-plane lattice of STO. Photo excitation affects the polarization process by accelerating the field-induced lattice expansion. The present work demonstrates the great potential of combined stimuli in exploring emergent phenomenon at complex oxide interfaces