Strong gravitational lensing in a squashed Kaluza-Klein black hole spacetime

We investigate the strong gravitational lensing in a Kaluza-Klein black hole with squashed horizons. We find the size of the extra dimension imprints in the radius of the photon sphere, the deflection angle, the angular position and magnification of the relativistic images. Supposing that the gravitational field of the supermassive central object of the Galaxy can be described by this metric, we estimated the numerical values of the coefficients and observables for gravitational lensing in the strong field limit.Comment: 13pages, 5 figures, Final version appeared in PR

Retraction and Generalized Extension of Computing with Words

Fuzzy automata, whose input alphabet is a set of numbers or symbols, are a formal model of computing with values. Motivated by Zadeh's paradigm of computing with words rather than numbers, Ying proposed a kind of fuzzy automata, whose input alphabet consists of all fuzzy subsets of a set of symbols, as a formal model of computing with all words. In this paper, we introduce a somewhat general formal model of computing with (some special) words. The new features of the model are that the input alphabet only comprises some (not necessarily all) fuzzy subsets of a set of symbols and the fuzzy transition function can be specified arbitrarily. By employing the methodology of fuzzy control, we establish a retraction principle from computing with words to computing with values for handling crisp inputs and a generalized extension principle from computing with words to computing with all words for handling fuzzy inputs. These principles show that computing with values and computing with all words can be respectively implemented by computing with words. Some algebraic properties of retractions and generalized extensions are addressed as well.Comment: 13 double column pages; 3 figures; to be published in the IEEE Transactions on Fuzzy System

Lightweight Image Inpainting by Stripe Window Transformer with Joint Attention to CNN

Image inpainting is an important task in computer vision. As admirable methods are presented, the inpainted image is getting closer to reality. However, the result is still not good enough in the reconstructed texture and structure based on human vision. Although recent advances in computer hardware have enabled the development of larger and more complex models, there is still a need for lightweight models that can be used by individuals and small-sized institutions. Therefore, we propose a lightweight model that combines a specialized transformer with a traditional convolutional neural network (CNN). Furthermore, we have noticed most researchers only consider three primary colors (RGB) in inpainted images, but we think this is not enough. So we propose a new loss function to intensify color details. Extensive experiments on commonly seen datasets (Places2 and CelebA) validate the efficacy of our proposed model compared with other state-of-the-art methods. Index Terms: HSV color space, image inpainting, joint attention, stripe window, transformerComment: 6 pages and 5 images, contributions to MLSP 202

Structural study in Highly Compressed BiFeO3 Epitaxial Thin Films on YAlO3

We report a study on the thermodynamic stability and structure analysis of the epitaxial BiFeO3 (BFO) thin films grown on YAlO3 (YAO) substrate. First we observe a phase transition of MC-MA-T occurs in thin sample (<60 nm) with an utter tetragonal-like phase (denoted as MII here) with a large c/a ratio (~1.23). Specifically, MII phase transition process refers to the structural evolution from a monoclinic MC structure at room temperature to a monoclinic MA at higher temperature (150oC) and eventually to a presence of nearly tetragonal structure above 275oC. This phase transition is further confirmed by the piezoforce microscopy measurement, which shows the rotation of polarization axis during the phase transition. A systematic study on structural evolution with thickness to elucidate the impact of strain state is performed. We note that the YAO substrate can serve as a felicitous base for growing T-like BFO because this phase stably exists in very thick film. Thick BFO films grown on YAO substrate exhibit a typical "morphotropic-phase-boundary"-like feature with coexisting multiple phases (MII, MI, and R) and a periodic stripe-like topography. A discrepancy of arrayed stripe morphology in different direction on YAO substrate due to the anisotropic strain suggests a possibility to tune the MPB-like region. Our study provides more insights to understand the strain mediated phase co-existence in multiferroic BFO system.Comment: 18 pages, 6 figures, submitted to Journal of Applied Physic

Exploring Business Intelligent Indexes of a Korean Style Theme Restaurant Taiwan

Recently, the major development of food & beverage management information system had changed from the point-of-sale (POS) system for stand-alone restaurant to the combination of headquarter control mechanism and E-commerce operation strategy (also called chain-integration applications). Development of enterprise business intelligence (BI) becomes one of the strategic solutions as facing the complex competition business environment. The goal of this paper is to explore the business intelligent indexes of a Korean style theme restaurant in Taiwan and verify some of these indexes by analyze the business data of this restaurant. Four research methods will be used in this paper including literature analysis, site observation, case interview and business data analysis. This paper proposed 18 operation KPIs which are sorted out with Balanced Scorecard (BSC) concept for the target restaurant. The constraint business financial data at two months of this restaurant were used to verify the effectiveness of proposed KPIs. Results of this paper showed that the expected operation KPIs are effective and concentrate much more in the financial and customer dimensions

Mutations in the PKM2 exon-10 region are associated with reduced allostery and increased nuclear translocation.

PKM2 is a key metabolic enzyme central to glucose metabolism and energy expenditure. Multiple stimuli regulate PKM2's activity through allosteric modulation and post-translational modifications. Furthermore, PKM2 can partner with KDM8, an oncogenic demethylase and enter the nucleus to serve as a HIF1α co-activator. Yet, the mechanistic basis of the exon-10 region in allosteric regulation and nuclear translocation remains unclear. Here, we determined the crystal structures and kinetic coupling constants of exon-10 tumor-related mutants (H391Y and R399E), showing altered structural plasticity and reduced allostery. Immunoprecipitation analysis revealed increased interaction with KDM8 for H391Y, R399E, and G415R. We also found a higher degree of HIF1α-mediated transactivation activity, particularly in the presence of KDM8. Furthermore, overexpression of PKM2 mutants significantly elevated cell growth and migration. Together, PKM2 exon-10 mutations lead to structure-allostery alterations and increased nuclear functions mediated by KDM8 in breast cancer cells. Targeting the PKM2-KDM8 complex may provide a potential therapeutic intervention

Defect-engineered graphene for bulk supercapacitors with high energy and power densities

The development of high-energy and high-power density supercapacitors (SCs) is critical for enabling next-generation energy storage applications. Nanocarbons are excellent SC electrode materials due to their economic viability, high-surface area, and high stability. Although nanocarbons have high theoretical surface area and hence high double layer capacitance, the net amount of energy stored in nanocarbon-SCs is much below theoretical limits due to two inherent bottlenecks: i) their low quantum capacitance and ii) limited ion-accessible surface area. Here, we demonstrate that defects in graphene could be effectively used to mitigate these bottlenecks by drastically increasing the quantum capacitance and opening new channels to facilitate ion diffusion in otherwise closed interlayer spaces. Our results support the emergence of a new energy paradigm in SCs with 250% enhancement in double layer capacitance beyond the theoretical limit. Furthermore, we demonstrate prototype defect engineered bulk SC devices with energy densities 500% higher than state-of-the-art commercial SCs without compromising the power density.Comment: 15 pages, 5 figures, and 8 supplemental figure

DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling

Pre-trained models like BERT (Devlin et al., 2018) have dominated NLP / IR applications such as single sentence classification, text pair classification, and question answering. However, deploying these models in real systems is highly non-trivial due to their exorbitant computational costs. A common remedy to this is knowledge distillation (Hinton et al., 2015), leading to faster inference. However -- as we show here -- existing works are not optimized for dealing with pairs (or tuples) of texts. Consequently, they are either not scalable or demonstrate subpar performance. In this work, we propose DiPair -- a novel framework for distilling fast and accurate models on text pair tasks. Coupled with an end-to-end training strategy, DiPair is both highly scalable and offers improved quality-speed tradeoffs. Empirical studies conducted on both academic and real-world e-commerce benchmarks demonstrate the efficacy of the proposed approach with speedups of over 350x and minimal quality drop relative to the cross-attention teacher BERT model.Comment: 13 pages. Accepted to Findings of EMNLP 202