Resummation of Boson-Jet Correlation at Hadron Colliders

We perform a precise calculation of the transverse momentum ($\vec{q}_T$) distribution of the boson+jet system in boson production events. The boson can be either a photon, $W$, $Z$ or Higgs boson with mass $m_V$, and $\vec{q}_T$ is the sum of the transverse momenta of the boson and the leading jet with magnitude $q_T=|\vec q_T|$. Using renormalization group techniques and soft-collinear effective theory, we resum logarithms $\log(Q/q_T)$ and $\log R$ at next-to-leading logarithmic accuracy including the non-global logarithms, where $Q$ and $R$ are respectively the hard scattering energy and the radius of the jet. Specifically, we investigate two scenarios of $p^J_T \lesssim m_V$ or $p^J_T \gtrsim m_V$ in $Z$+jet events, and we examine the $q_T$ distributions with different jet radii and study the effect of non-global logarithms. In the end we compare our theoretical calculations with Monte Carlo simulations and data from the LHC.Comment: 35 pages, 7 figure

Computation-Performance Optimization of Convolutional Neural Networks with Redundant Kernel Removal

Deep Convolutional Neural Networks (CNNs) are widely employed in modern computer vision algorithms, where the input image is convolved iteratively by many kernels to extract the knowledge behind it. However, with the depth of convolutional layers getting deeper and deeper in recent years, the enormous computational complexity makes it difficult to be deployed on embedded systems with limited hardware resources. In this paper, we propose two computation-performance optimization methods to reduce the redundant convolution kernels of a CNN with performance and architecture constraints, and apply it to a network for super resolution (SR). Using PSNR drop compared to the original network as the performance criterion, our method can get the optimal PSNR under a certain computation budget constraint. On the other hand, our method is also capable of minimizing the computation required under a given PSNR drop.Comment: This paper was accepted by 2018 The International Symposium on Circuits and Systems (ISCAS

Taiwanese Willingness to Communicate in English: Can Watching American Television Programs help?

This study explored the relationship between Taiwanese audiences\u27 use of American television programs and their willingness to communicate in English. Taiwanese participants filled out an online survey consisted of questions from uses and gratifications constructs and willingness to communicate constructs. In addition, different subtitle settings were also examined. Results indicated that participants with high integrative motivation consuming information from American television programs, in addition, the setting of subtitles were associated with perceived communication competence, integrative motivation, language anxiety and social interaction motivation

Purification and characterization of recombinant glucose dehydrogenase isolated from a hyperthermophilic Sulfolobus-like bacterium

This study aimed to clone and characterize a thermal resistant glucose dehydrogenase (GDH) and investigate its clinical potential. A Sulfolobus-like thermophilic microbe was first isolated from a hot spring in Taitung, Chihpen County, Taiwan. The gene encoding GDH was cloned from the bacterium and expressed in Escherichia coli. The molecular weight of the enzyme was found to be approximately 39,000 kDa. The enzyme is stable over pH 4.0 to 11.0 and has an optimum pH of 8.0. The thermostability range of the enzyme correlated well with that of the natural environment for Sulfolobus. The GDH showed high substrate specificity for glucose. GDH could be useful in biotechnological applications because of its higher thermostability and substrate specificity when compared with that of other glucose-degrading enzymes.Keywords: Glucose dehydrogenase, sequencing, glucose test strip, blood glucose meter, diabetes mellitu

Azimuthal angle for boson-jet production in the back-to-back limit

We show for the first time that the azimuthal angle between a vector boson and a jet, when using the Winner-Take-All recombination scheme, can be predicted at high precision in the back-to-back limit in the transverse plane. Specifically, we present a factorization theorem, and obtain numerical predictions at next-to-next-to-leading logarithmic (NNLL) accuracy. To allow for improved angular resolution, we provide results for track-based jet reconstruction, which only requires minimal changes in the calculation. We also find that linearly-polarized transverse momentum dependent (TMD) beam and jet functions enter at next-to-leading order (NLO) in the factorization theorem, originating from spin superpositions for one gluon, rather than the known case of spin correlations between gluons. We validate the switch from calorimetry to tracks using Pythia, and confirm the presence of linearly-polarized TMD functions using MCFM.Comment: 6 pages, 4 figure

5-ALA mediated photodynamic therapy induces autophagic cell death via AMP-activated protein kinase

Photodynamic therapy (PDT) has been developed as an anticancer treatment, which is based on the tumor-specific accumulation of a photosensitizer that induces cell death after irradiation of light with a specific wavelength. Depending on the subcellular localization of the photosensitizer, PDT could trigger various signal transduction cascades and induce cell death such as apoptosis, autophagy, and necrosis. In this study, we report that both AMP-activated protein kinase (AMPK) and mitogen-activated protein kinase (MAPK) signaling cascades are activated following 5-aminolevulinic acid (ALA)-mediated PDT in both PC12 and CL1-0 cells. Although the activities of caspase-9 and -3 are elevated, the caspase inhibitor zVAD-fmk did not protect cells against ALA-PDT-induced cell death. Instead, autophagic cell death was found in PC12 and CL1-0 cells treated with ALA-PDT. Most importantly, we report here for the first time that it is the activation of AMPK, but not MAPKs that plays a crucial role in mediating autophagic cell death induced by ALA-PDT. This novel observation indicates that the AMPK pathway play an important role in ALA-PDT-induced autophagy

Existence theorems for a crystal surface model involving the p-Laplace operator

The manufacturing of crystal films lies at the heart of modern nanotechnology. How to accurately predict the motion of a crystal surface is of fundamental importance. Many continuum models have been developed for this purpose, including a number of PDE models, which are often obtained as the continuum limit of a family of kinetic Monte Carlo models of crystal surface relaxation that includes both the solid-on-solid and discrete Gaussian models. In this paper we offer an analytical perspective into some of these models. To be specific, we study the existence of a weak solution to the boundary value problem for the equation - \Delta e^{-\mbox{div}\left(|\nabla u|^{p-2}\nabla u\right)}+au=f, where $p>1, a>0$ are given numbers and $f$ is a given function. This problem is derived from a crystal surface model proposed by J.L.~Marzuola and J.~Weare (2013 Physical Review, E 88, 032403). The mathematical challenge is due to the fact that the principal term in our equation is an exponential function of a p-Laplacian. Existence of a suitably-defined weak solution is established under the assumptions that $p\in(1,2], \ N\leq 4$, and $f\in W^{1,p}$. Our investigations reveal that the key to our existence assertion is how to control the set where -\mbox{div}\left(|\nabla u|^{p-2}\nabla u\right) is $\pm\infty$

NYCU-TWO at Memotion 3: Good Foundation, Good Teacher, then you have Good Meme Analysis

This paper presents a robust solution to the Memotion 3.0 Shared Task. The goal of this task is to classify the emotion and the corresponding intensity expressed by memes, which are usually in the form of images with short captions on social media. Understanding the multi-modal features of the given memes will be the key to solving the task. In this work, we use CLIP to extract aligned image-text features and propose a novel meme sentiment analysis framework, consisting of a Cooperative Teaching Model (CTM) for Task A and a Cascaded Emotion Classifier (CEC) for Tasks B&C. CTM is based on the idea of knowledge distillation, and can better predict the sentiment of a given meme in Task A; CEC can leverage the emotion intensity suggestion from the prediction of Task C to classify the emotion more precisely in Task B. Experiments show that we achieved the 2nd place ranking for both Task A and Task B and the 4th place ranking for Task C, with weighted F1-scores of 0.342, 0.784, and 0.535 respectively. The results show the robustness and effectiveness of our framework. Our code is released at github.Comment: De-Factify 2: Second Workshop on Multimodal Fact Checking and Hate Speech Detection, co-located with AAAI 202