‘猴灾’背后保护工作人员、农民与猴的互动：以广西一保 护区为例

Human-wildlife conflict has become a global challenge. Crop damage by wildlife can cause significant economic loss and primates such as monkeys can cause particular problem to farmers. The monkey problem has already become intense in communi-ties near white-headed langur national nature reserve of Guangxi, China, and involve not only farmers and monkeys, but also conservation staffs as they are regarded as the guards of monkeys. An understanding of the relationship among farmers, monkeys and conservation staffs is important to approach the monkey problem. I use in-terpretive multi-actors approach, which closely links to actor network theory, to in-vestigate local perceptions and understandings towards crop damage by monkeys, interactions between monkeys, farmers and conservation staffs, as well as how farmer-monkey relations evolve. My findings have described farmers’ rich under-standings towards the extent of crop damage and crop foraging behaviour of monkeys. Mutual and interactive processes take place between farmers and monkeys, while farmers and conservation staffs interact concerning legitimizing compensation. My thesis further discusses factors that farmers’ perceptions, the mutual learning and ad-justment in farmer-monkey relations, and how their relations are influenced by conservation and other social change. Lastly, I discuss how the monkey problem has transfigured into a conservation problem, when ‘unprotected pest’ turns into ‘pro-tected pest’. These findings and analysis help us to better understand human perception in human-wildlife conflict scenario, farmer-monkey relations and the relation-ship between local community and protected areas. Moreover, it is a try to use actor network theory in studying human-animal interactions.人兽冲突已经成为全球性的挑战。野生动物取食农作物能造成严重的经济损失，而诸如猕猴等灵长类所造成的农作物损害被称为“猴灾”。在广西崇左白头叶猴国家级保护区周边，由猕猴造成的猴灾已经非常严重。这不仅牵涉到农民和猕猴，也事关保护区工作人员，因为他们被视为猕猴的守护者。了解农民，猕猴和保护工作人员之间的关系对妥善处理猴灾十分重要。本篇论文中，我使用深受行动者网络理论影响的多行动者方法，来深入了解当地人对猕猴取食农作物的感知和认识，农民、猕猴、保护工作人员之间的互动，以及农民与猕猴关系的演变过程。我的研究描述了农民对农作物受损类型和程度以及对猕猴取食农作物行为的了解，同时将猕猴拟人化的现象。我同时深入描述了农民与猕猴的双向互动过程。农民和猕猴从经验中熟悉对方活动的时间空间特征，以及农作物和环境，将其运用在农民的防控和猕猴的取食措施中。我也描述了保护工作人员与农民互动的各个方面，如保护者社区宣教，农民汇报索取赔偿，农民暗害猕猴的传闻，二者间将赔偿正当化和不正当化的言论，以及有关猕猴来历的‘谣言’。接着我讨论了如何解读农民对猴灾的感知，农民与猕猴相互学习和调整适应的过程，保护政策、城乡迁移、耕作方式改变对农民与猕猴关系的影响，以及猕猴的保护等级如何让猴灾成为一个保护问题。这些发现和讨论能帮助我们更好地理解人兽冲突背景下人的感知，农民与猕猴的关系，以及保护区与社区的关系。同时，它也是将行动者网络理论运用到人与动物的互动中的一次尝试

Look, Listen and Learn - A Multimodal LSTM for Speaker Identification

Speaker identification refers to the task of localizing the face of a person who has the same identity as the ongoing voice in a video. This task not only requires collective perception over both visual and auditory signals, the robustness to handle severe quality degradations and unconstrained content variations are also indispensable. In this paper, we describe a novel multimodal Long Short-Term Memory (LSTM) architecture which seamlessly unifies both visual and auditory modalities from the beginning of each sequence input. The key idea is to extend the conventional LSTM by not only sharing weights across time steps, but also sharing weights across modalities. We show that modeling the temporal dependency across face and voice can significantly improve the robustness to content quality degradations and variations. We also found that our multimodal LSTM is robustness to distractors, namely the non-speaking identities. We applied our multimodal LSTM to The Big Bang Theory dataset and showed that our system outperforms the state-of-the-art systems in speaker identification with lower false alarm rate and higher recognition accuracy.Comment: The 30th AAAI Conference on Artificial Intelligence (AAAI-16

The Assembly of Black Hole Mass and Luminosity Functions of High-redshift Quasars via Multiple Accretion Episodes

The early evolution of the quasar luminosity function (QLF) and black hole mass function (BHMF) encodes key information on the physics determining the radiative and accretion processes of supermassive black holes (BHs) in high-$z$ quasars. Although the QLF shape has been constrained by recent observations, it remains challenging to develop a theoretical model that explains its redshift evolution associated with BH growth self-consistently. In this study, based on a semi-analytical model for the BH formation and growth, we construct the QLF and BHMF of the early BH population that experiences multiple accretion bursts, in each of which a constant Eddington ratio is assigned following a Schechter distribution function. Our best-fit model to reproduce the observed QLF and BHMF at $z\simeq 6$ suggests that several episodes of moderate super-Eddington accretion occur and each of them lasts for $\tau \simeq 20-30$ Myr. The average duty cycle in super-Eddington phases is $\simeq 15\%$ for massive BHs that reach $\gtrsim 10^8~M_\odot$ by $z\simeq 6$, which is nearly twice that of the entire population. We also find that the observed Eddington-ratio distribution function is skewed to a log-normal shape owing to detection limits of quasar surveys. The predicted redshift evolution of the QLF and BHMF suggests a rapid decay of their number and mass density in a cosmic volume toward $z\gtrsim 6$. These results will be unveiled by future deep and wide surveys with the James Webb Space Telescope, Roman Space Telescope, and Euclid.Comment: 25 pages, 11 figures; accepted by Ap

Exploring Privacy-traces of Users from Online Community: A Case Study of Diabetes Topic Discussions

Online health communities (OHCs) have already become essential medium for people to obtain medical knowledge, share experiences and emotions. OHC users are able to post user-generated content (UGC) to interact with each other. However, the large amount of UGC may lead to personal information even privacy disclosed online. Although such disclosure may help users to trade some social support, which is the basis of sustaining a successful OHC, the users should be aware of the risks of leaving such traces online. This study selects a popular online Q & A community “Zhihu” in China as the research target. By collecting all questions and corresponding answers from 4 diabetes sub-communities, we would like to identify online privacy-traces of users from UGC. According to the theory of Communication Privacy Management, we build an explanatory model to understand user behaviors of concealing or revealing private information from the aspects of user characteristics, peer attention, and social support effects

Forsythiaside A inhibits hydrogen peroxide-induced inflammation, oxidative stress, and apoptosis of cardiomyocytes

Purpose: To investigate the effect of forsythiaside A on heart failure.Methods: An in vitro cell model of myocardial injury was established by incubating H9c2 primary cardiomyocytes with hydrogen peroxide (H2O2). Apoptosis was measured by flow cytometry. Expression of inflammatory factors, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), was determined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and enzymelinkedimmunosorbent assay (ELISA). Oxidative stress was evaluated by measuring malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) levels by ELISA.Results: Incubation with H2O2 increased H9c2 cell apoptosis (p < 0.001). Treatment with forsythiaside A reduced Bax expression and enhanced Bcl-2 expression which suppressed apoptosis of H2O2- induced H9c2 cells. Forsythiaside A also attenuated the H2O2-induced increase in TNF-α and IL-6expressions in H9c2 cells (p < 0.001). The H2O2-induced increase in MDA and decrease in SOD and GSH-Px in H9c2 cells were reversed by treatment with forsythiaside A. IκBα protein expression was downregulated, whereas p65 phosphorylation (p-p65), p-IκBα, nuclear factor erythropoietin-2-related factor 2 (Nrf2), and heme oxygenase 1 (HO-1) were upregulated in H2O2-induced H9c2 cells. Forsythiaside A increased IκBα, Nrf2, and HO-1 expression and decreased p-p65 and p-IκBα expression in H2O2-induced H9c2 cells.Conclusion: Forsythiaside A exerts anti-inflammatory, anti-oxidant, and anti-apoptotic effects against H2O2-induced H9c2 cells through inactivation of NF-κB pathway and activation of Nrf2/HO-1 pathway. These results support the potential clinical application of forsythiaside A for the treatment of heart failure

Accurate Single Stage Detector Using Recurrent Rolling Convolution

Most of the recent successful methods in accurate object detection and localization used some variants of R-CNN style two stage Convolutional Neural Networks (CNN) where plausible regions were proposed in the first stage then followed by a second stage for decision refinement. Despite the simplicity of training and the efficiency in deployment, the single stage detection methods have not been as competitive when evaluated in benchmarks consider mAP for high IoU thresholds. In this paper, we proposed a novel single stage end-to-end trainable object detection network to overcome this limitation. We achieved this by introducing Recurrent Rolling Convolution (RRC) architecture over multi-scale feature maps to construct object classifiers and bounding box regressors which are "deep in context". We evaluated our method in the challenging KITTI dataset which measures methods under IoU threshold of 0.7. We showed that with RRC, a single reduced VGG-16 based model already significantly outperformed all the previously published results. At the time this paper was written our models ranked the first in KITTI car detection (the hard level), the first in cyclist detection and the second in pedestrian detection. These results were not reached by the previous single stage methods. The code is publicly available.Comment: CVPR 201