A World of Difference: Divergent Word Interpretations among People

Divergent word usages reflect differences among people. In this paper, we present a novel angle for studying word usage divergence -- word interpretations. We propose an approach that quantifies semantic differences in interpretations among different groups of people. The effectiveness of our approach is validated by quantitative evaluations. Experiment results indicate that divergences in word interpretations exist. We further apply the approach to two well studied types of differences between people -- gender and region. The detected words with divergent interpretations reveal the unique features of specific groups of people. For gender, we discover that certain different interests, social attitudes, and characters between males and females are reflected in their divergent interpretations of many words. For region, we find that specific interpretations of certain words reveal the geographical and cultural features of different regions.Comment: 4 pages, 1 figure, published at ICWSM'1

Direct Observation of the Magnetic Anisotropy of an Fe (II) Spin Crossover Molecular Thin Film

Spin crossover molecules are a promising candidate for molecular spintronics that aim for ultrafast and low-power devices for data storage and magnetic and information sensing. The rapid spin state transition is best controlled by non-thermal methods including magnetic field. Unfortunately, the magnetic field normally required to switch the spin state is normally high (~30 T), which calls for better understanding of the fundamental mechanism. In this work, we provide clear evidence of magnetic anisotropy in the local orbital moment of a molecular thin film based on spin crossover complex [Fe(H2B(pz)2)2(bipy)] (pz = pyrazol−1−yl, bipy = 2,2’−bipyridine). Field dependent X-ray magnetic circular dichroism measurements indicate that the magnetic easy axis for the orbital moment is along the surface normal direction. Along with the presence of a critical field, our observation points to the existence of an anisotropic energy barrier in the high-spin state. The estimated nonzero coupling constant of ~2.47 ´ 10-5 eV molecule-1 indicates that the observed magnetocrystalline anisotropy is mostly due to spin-orbit coupling. The spin- and orbital-component anisotropies are determined to be 30.9 and 5.04 meV molecule-1, respectively. Furthermore, the estimated g factor in the range of 2.2-2.45 is consistent with the expected values. This work has paved the way for an understanding of the spin-switching mechanism in the presence of magnetic perturbations

TikTalk: A Video-Based Dialogue Dataset for Multi-Modal Chitchat in Real World

To facilitate the research on intelligent and human-like chatbots with multi-modal context, we introduce a new video-based multi-modal dialogue dataset, called TikTalk. We collect 38K videos from a popular video-sharing platform, along with 367K conversations posted by users beneath them. Users engage in spontaneous conversations based on their multi-modal experiences from watching videos, which helps recreate real-world chitchat context. Compared to previous multi-modal dialogue datasets, the richer context types in TikTalk lead to more diverse conversations, but also increase the difficulty in capturing human interests from intricate multi-modal information to generate personalized responses. Moreover, external knowledge is more frequently evoked in our dataset. These facts reveal new challenges for multi-modal dialogue models. We quantitatively demonstrate the characteristics of TikTalk, propose a video-based multi-modal chitchat task, and evaluate several dialogue baselines. Experimental results indicate that the models incorporating large language models (LLM) can generate more diverse responses, while the model utilizing knowledge graphs to introduce external knowledge performs the best overall. Furthermore, no existing model can solve all the above challenges well. There is still a large room for future improvements, even for LLM with visual extensions. Our dataset is available at \url{https://ruc-aimind.github.io/projects/TikTalk/}.Comment: Accepted to ACM Multimedia 202

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production

A Compatible Control Algorithm for Greenhouse Environment Control Based on MOCC Strategy

Conventional methods used for solving greenhouse environment multi-objective conflict control problems lay excessive emphasis on control performance and have inadequate consideration for both energy consumption and special requirements for plant growth. The resulting solution will cause higher energy cost. However, during the long period of work and practice, we find that it may be more reasonable to adopt interval or region control objectives instead of point control objectives. In this paper, we propose a modified compatible control algorithm, and employ Multi-Objective Compatible Control (MOCC) strategy and an extant greenhouse model to achieve greenhouse climate control based on feedback control architecture. A series of simulation experiments through various comparative studies are presented to validate the feasibility of the proposed algorithm. The results are encouraging and suggest the energy-saving application to real-world engineering problems in greenhouse production. It may be valuable and helpful to formulate environmental control strategies, and to achieve high control precision and low energy cost for real-world engineering application in greenhouse production. Moreover, the proposed approach has also potential to be useful for other practical control optimization problems with the features like the greenhouse environment control system

5-Fluorouracil targets thymidylate synthase in the selective suppression of TH17 cell differentiation

While it is well established that treatment of cancer patients with 5-Fluorouracil (5-FU) can result in immune suppression, the exact function of 5-FU in the modulation of immune cells has not been fully established. We found that low dose 5-FU selectively suppresses TH17 and TH1 cell differentiation without apparent effect on Treg, TH2, and significantly suppresses thymidylate synthase (TS) expression in TH17 and TH1 cells but has a lesser effect in tumor cells and macrophages. Interestingly, the basal expression of TS varies significantly between T helper phenotypes and knockdown of TS significantly impairs TH17 and TH1 cell differentiation without affecting the differentiation of either Treg or TH2 cells. Finally, low dose 5-FU is effective in ameliorating colitis development by suppressing TH17 and TH1 cell development in a T cell transfer colitis model. Taken together, the results highlight the importance of the anti-inflammatory functions of low dose 5-FU by selectively suppressing TH17 and TH1 immune responses