Holographic Mutual Information of Two Disjoint Spheres

We study quantum corrections to holographic mutual information for two disjoint spheres at a large separation by using the operator product expansion of the twist field. In the large separation limit, the holographic mutual information is vanishing at the semiclassical order, but receive quantum corrections from the fluctuations. We show that the leading contributions from the quantum fluctuations take universal forms as suggested from the boundary CFT. We find the universal behavior for the scalar, the vector, the tensor and the fermionic fields by treating these fields as free fields propagating in the fixed background and by using the 1/n prescription. In particular, for the fields with gauge symmetries, including the massless vector boson and massless graviton, we find that the gauge parts in the propagators play indispensable role in reading the leading order corrections to the bulk mutual information.Comment: 37 pages, 1 figure; significant revisions, corrected the discussions on the computations of the mutual information in CFT, conclusions unchange

A γ\gamma-ray Quasi-Periodic modulation in the Blazar PKS 0301−-243?

We report a nominally high-confidence $\gamma$-ray quasi-periodic modulation in the blazar PKS 0301$-$243. For this target, we analyze its \emph{Fermi}-LAT Pass 8 data covering from 2008 August to 2017 May. Two techniques, i.e., the maximum likelihood optimization and the exposure-weighted aperture photometry, are used to build the $\gamma$-ray light curves. Then both the Lomb-Scargle Periodogram and the Weighted Wavelet Z-transform are applied to the light curves to search for period signals. A quasi-periodicity with a period of $2.1\pm0.3$ yr appears at the significance level of $\sim5\sigma$, although it should be noted that this putative quasi-period variability is seen in a data set barely four times longer. We speculate that this $\gamma$-ray quasi-periodic modulation might be evidence of a binary supermassive black hole.Comment: 9 pages, 8 figures; Accepted for publication in Ap

Adaptive Sparse Pairwise Loss for Object Re-Identification

Object re-identification (ReID) aims to find instances with the same identity as the given probe from a large gallery. Pairwise losses play an important role in training a strong ReID network. Existing pairwise losses densely exploit each instance as an anchor and sample its triplets in a mini-batch. This dense sampling mechanism inevitably introduces positive pairs that share few visual similarities, which can be harmful to the training. To address this problem, we propose a novel loss paradigm termed Sparse Pairwise (SP) loss that only leverages few appropriate pairs for each class in a mini-batch, and empirically demonstrate that it is sufficient for the ReID tasks. Based on the proposed loss framework, we propose an adaptive positive mining strategy that can dynamically adapt to diverse intra-class variations. Extensive experiments show that SP loss and its adaptive variant AdaSP loss outperform other pairwise losses, and achieve state-of-the-art performance across several ReID benchmarks. Code is available at https://github.com/Astaxanthin/AdaSP.Comment: Accepted by CVPR 202

Metali u medu iz provincije Henan, Kina: sustavna analiza metodom ICP-AES

In this study, the method for determining ten elements (including K, Na, Ca, Mg, Fe, Mn, Cu, Zn, Pb, and Cd) was designed. With this method, we evaluated 15 honey samples, including three kinds of honey collected from 11 different geographic sites in Henan province of China, with inductively coupled plasma atomic emission spectrometry (ICP-AES). The obtained detecting data were analysed with principal component analysis, correlation analysis, and cluster analysis techniques. The results showed that the recovery is in the range of 93.0−107.0 %, and the relative standard deviations (RSDs) were all below 5.89 %, which indicates that the current analytical method is dependable for the detection of metallic elements in honey. This work is licensed under a Creative Commons Attribution 4.0 International License.U ovom istraživanju osmišljena je metoda određivanja deset elemenata (K, Na, Ca, Mg, Fe, Mn, Cu, Zn, Pb i Cd). Tom metodom evaluirano je 15 uzoraka meda, uključujući tri vrste meda prikupljenih s 11 lokaliteta u provinciji Henan, Kina, atomskom emisijskom spektrometrijom s induktivno spregnutom plazmom (ICP-AES). Dobiveni podatci proučeni su analizom glavnih komponenti, korelacijskom analizom i tehnikama klasterskih analiza. Rezultati su pokazali da se oporaba kreće u rasponu od 93,0 do 107,0 %, a relativne standardne devijacije (RSD) bile su ispod 5,89 %, što ukazuje da je trenutačna analitička metoda pouzdana za otkrivanje metala u medu. Ovo djelo je dano na korištenje pod licencom Creative Commons Imenovanje 4.0 međunarodna

A selected pre-amplification strategy for genetic analysis using limited DNA targets

Background: Limited DNA resources or limited DNA targets in predominant backgrounds for genetic tests can lead to misdiagnosis. We developed a strategy to selectively increase the amount of minor targets through a specific pre-amplification procedure. Methods: We used the model of circulating cell free (ccf) male fetal DNA as a minor target in the predominant maternal plasma DNA to evaluate the strategy. The sex determining region (SRY) locus on the Y chromosome was used to identify ccf fetal DNA, and the human glyceraldehydes-3-phosphate dehydrogenase (GAPDH) gene was used to identify ccf total DNA in maternal plasma. We selectively pre-amplified the minor target SRY locus using the Expand Long Template PCR system and assessed the efficiency of the pre-amplification by real-time PCR, for both SRY and GAPDH, to compare the quantities of pre-amplified fetal DNA with those of maternal total DNA without pre-amplification. Results: The selected pre-amplification increased the amount of ccf fetal DNA dramatically (Wilcoxon test: p=0.000, the fold change=11,596). After selected pre-amplification, a proportion of 2.19% of the ccf fetal minor part in the predominant maternal component was changed up to 25,334%. The increased amounts of ccf fetal DNA found with the pre-amplification are not correlated to the amounts found without the procedure (r=−0.017, p=0.949). Conclusions: This strategy may be useful in genetic analysis with limited DNA resources and limited DNA targets in predominant background molecules. However, this approach is not suitable for quantitative assessments, due to the fact that quantitative imbalanced amplification was observed as a result of the pre-amplification procedure. Clin Chem Lab Med 2009;47:288-9

Inductive Meta-path Learning for Schema-complex Heterogeneous Information Networks

Heterogeneous Information Networks (HINs) are information networks with multiple types of nodes and edges. The concept of meta-path, i.e., a sequence of entity types and relation types connecting two entities, is proposed to provide the meta-level explainable semantics for various HIN tasks. Traditionally, meta-paths are primarily used for schema-simple HINs, e.g., bibliographic networks with only a few entity types, where meta-paths are often enumerated with domain knowledge. However, the adoption of meta-paths for schema-complex HINs, such as knowledge bases (KBs) with hundreds of entity and relation types, has been limited due to the computational complexity associated with meta-path enumeration. Additionally, effectively assessing meta-paths requires enumerating relevant path instances, which adds further complexity to the meta-path learning process. To address these challenges, we propose SchemaWalk, an inductive meta-path learning framework for schema-complex HINs. We represent meta-paths with schema-level representations to support the learning of the scores of meta-paths for varying relations, mitigating the need of exhaustive path instance enumeration for each relation. Further, we design a reinforcement-learning based path-finding agent, which directly navigates the network schema (i.e., schema graph) to learn policies for establishing meta-paths with high coverage and confidence for multiple relations. Extensive experiments on real data sets demonstrate the effectiveness of our proposed paradigm