{"id":31632,"date":"2022-01-10T22:29:05","date_gmt":"2022-01-10T14:29:05","guid":{"rendered":"https:\/\/swarma.org\/?p=31632"},"modified":"2022-01-10T22:29:05","modified_gmt":"2022-01-10T14:29:05","slug":"pnas%e9%80%9f%e9%80%92%ef%bc%9a%e7%bb%93%e5%90%88%e7%be%a4%e4%bd%93%e6%99%ba%e6%85%a7%e4%b8%8e%e6%9c%ba%e5%99%a8%e6%99%ba%e8%83%bd%ef%bc%8c%e8%be%a8%e5%88%ab%e8%99%9a%e5%81%87%e8%a7%86%e9%a2%91","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=31632","title":{"rendered":"PNAS\u901f\u9012\uff1a\u7ed3\u5408\u7fa4\u4f53\u667a\u6167\u4e0e\u673a\u5668\u667a\u80fd\uff0c\u8fa8\u522b\u865a\u5047\u89c6\u9891"},"content":{"rendered":"
\n
\n
\n
\n
\n

<\/p>\n<\/section>\n

\n
\n
\n
\n
\n
\n

<\/section>\n<\/section>\n
\n
\n

\u6458\u8981<\/strong><\/p>\n<\/section>\n<\/section>\n

\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
\n
\n
\n
<\/strong>\u673a\u5668\u80fd\u591f\u751f\u6210\u865a\u5047\u89c6\u9891\uff0c\u8fd9\u63d0\u51fa\u4e86\u4e00\u4e2a\u91cd\u8981\u7684\u793e\u4f1a\u95ee\u9898\uff1a\u6211\u4eec\u5982\u4f55\u77e5\u9053\u6211\u4eec\u89c2\u770b\u7684\u89c6\u9891\u662f\u771f\u662f\u5047\uff1f\u5728\u4e24\u4e2a\u670915016\u540d\u53c2\u4e0e\u8005\u7684\u5728\u7ebf\u7814\u7a76\u4e2d\uff0c\u6211\u4eec\u5c55\u793a\u4e86\u771f\u5b9e\u89c6\u9891\u548c\u865a\u5047\u89c6\u9891\uff0c\u5e76\u8981\u6c42\u53c2\u4e0e\u8005\u8fa8\u522b\u89c6\u9891\u7684\u771f\u5047\u3002\u6211\u4eec\u6bd4\u8f83\u4e86\u6b63\u5e38\u4eba\u7c7b\u89c2\u5bdf\u8005\u548c\u5148\u8fdb\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u6a21\u578b\u7684\u8868\u73b0\uff0c\u53d1\u73b0\u5b83\u4eec\u8fa8\u522b\u7684\u51c6\u786e\u6027\u76f8\u4f3c\uff0c\u4f46\u6240\u72af\u7684\u9519\u8bef\u7c7b\u578b\u4e0d\u540c\u3002\u603b\u7684\u6765\u8bf4\uff0c\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\u6a21\u578b\u8f85\u52a9\u4e0b\u7684\u4eba\u7c7b\u89c2\u5bdf\u8005\u6bd4\u4e24\u8005\u5355\u72ec\u8fa8\u522b\u7684\u8868\u73b0\u90fd\u66f4\u597d\uff0c\u4f46\u662f\u6a21\u578b\u7684\u9519\u8bef\u9884\u6d4b\u5e38\u5e38\u4f1a\u964d\u4f4e\u4eba\u7c7b\u89c2\u5bdf\u8005\u7684\u8868\u73b0\u3002\u4e3a\u4e86\u63a2\u8ba8\u4eba\u7c7b\u548c\u673a\u5668\u68c0\u6d4b\u865a\u5047\u89c6\u9891\u7684\u76f8\u5bf9\u4f18\u52bf\u548c\u52a3\u52bf\uff0c\u6211\u4eec\u8003\u5bdf\u4e86\u4eba\u7c7b\u548c\u673a\u5668\u5728\u89c6\u9891\u7279\u5f81\u4e0a\u7684\u8868\u73b0\uff0c\u5e76\u8bc4\u4f30\u4e86\u968f\u673a\u5e72\u9884\u5bf9\u8fa8\u522b\u865a\u5047\u89c6\u9891\u7684\u5f71\u54cd\u3002\u6211\u4eec\u53d1\u73b0\u5e72\u6270\u9762\u90e8\u89c6\u89c9\u5904\u7406\u7684\u64cd\u4f5c\u4f1a\u964d\u4f4e\u4eba\u7c7b\u89c2\u5bdf\u8005\u7684\u8868\u73b0\uff0c\u800c\u5bf9\u6a21\u578b\u5f71\u54cd\u4e0d\u5927\uff0c\u8fd9\u8868\u660e\u4eba\u7c7b\u5bf9\u9762\u90e8\u7279\u5f81\u7684\u8ba4\u77e5\u80fd\u529b\u5728\u8fa8\u522b\u865a\u5047\u89c6\u9891\u4e2d\u8d77\u5230\u4e86\u91cd\u8981\u4f5c\u7528\u3002<\/strong><\/span><\/strong><\/section>\n

<\/span><\/strong><\/section>\n
The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model\u2019s prediction are more accurate than either alone, but inaccurate model predictions often decrease participants\u2019 accuracy. To probe the relative strengths and weaknesses of humans and machines as detectors of deepfakes, we examine human and machine performance across video-level features, and we evaluate the impact of preregistered randomized interventions on deepfake detection. We find that manipulations designed to disrupt visual processing of faces hinder human participants\u2019 performance while mostly not affecting the model\u2019s performance, suggesting a role for specialized cognitive capacities in explaining human deepfake detection performance.<\/span><\/strong><\/section>\n
<\/span><\/section>\n

<\/section>\n

\u7814\u7a76\u9886\u57df\uff1a<\/strong><\/strong><\/span><\/strong><\/span><\/strong><\/span><\/strong>\u4eba\u5de5\u667a\u80fd\uff0c\u7fa4\u4f53\u667a\u6167\uff0c\u4eba\u673a\u534f\u4f5c<\/strong><\/strong><\/span><\/strong><\/span><\/strong><\/span><\/strong><\/span><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

\n
\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n
\n
<\/strong><\/section>\n<\/section>\n
\n

\u90ed\u745e\u4e1c <\/span>| \u4f5c\u8005<\/strong><\/span><\/strong><\/p>\n

\u5f20\u6fb3<\/span> | \u5ba1\u6821<\/strong><\/span><\/strong><\/span><\/p>\n

\u9093\u4e00\u96ea<\/span> | \u7f16\u8f91<\/strong><\/span><\/p>\n<\/section>\n


<\/section>\n


<\/p>\n

<\/p>\n

\n
\n
\n

\u8bba\u6587\u9898\u76ee\uff1a<\/span><\/p>\n

Deepfake detection by human crowds, machines, and machine-informed crowds<\/span><\/p>\n

\u8bba\u6587\u5730\u5740\uff1a<\/span><\/p>\n

https:\/\/www.pnas.org\/content\/119\/1\/e2110013119<\/span><\/p>\n<\/section>\n<\/section>\n<\/blockquote>\n


<\/p>\n


<\/section>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

1. \u6570\u636e\u4e16\u754c\u771f\u5047\u96be\u8fa8<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u773c\u89c1\u672a\u5fc5\u4e3a\u5b9e\uff0c\u82f1\u5267\u300a\u771f\u76f8\u6355\u6349\u300b\u4e2d\u76d1\u63a7\u5f71\u50cf\u5c31\u88ab\u6076\u610f\u4fee\u6539\u3002\u5728\u865a\u6784\u7684\u5f71\u89c6\u4e16\u754c\u4e4b\u5916\uff0c\u4e5f\u5b58\u5728\u5982 Deepfake \u7b49\u80fd\u591f\u751f\u6210\u865a\u5047\u89c6\u9891\u548c\u56fe\u7247\u7684\u6280\u672f\u3002\u4e3a\u4e86\u63a2\u8ba8\u5982\u4f55\u66f4\u597d\u7684\u5e94\u5bf9\u865a\u5047\u89c6\u9891\u5e26\u6765\u7684\u95ee\u9898\u30022019-2020\u5e74\u95f4\uff0c\u4e9a\u9a6c\u900a\u3001\u8138\u4e66\u548c\u8c37\u6b4c\u5171\u540c\u60ac\u8d4f\u767e\u4e07\u7f8e\u91d1\uff0c\u5728\u673a\u5668\u5b66\u4e60\u5e73\u53f0Kaggle\u4e0a\u5bfb\u6c42\u80fd\u591f\u7cbe\u51c6\u8fa8\u522b\u865a\u5047\u89c6\u9891\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u3002\u53c2\u8d5b\u7b97\u6cd5\u7684\u5e73\u5747\u51c6\u786e\u7387\u7ea6\u4e3a 65%\uff0c\u5176\u4e2d\u6700\u4f73\u7b97\u6cd5\u7684\u51c6\u786e\u7387\u4e5f\u672a\u8d85\u8fc780%\u3002<\/span><\/p>\n


<\/p>\n

\u5b9e\u9645\u4e0a\uff0cDeepfake\u7684\u6362\u8138\u89c6\u9891\u5728\u80cc\u666f\u548c\u5149\u7167\u7b49\u7ec6\u8282\u4e0a\uff0c\u96be\u514d\u4f1a\u548c\u771f\u5b9e\u89c6\u9891\u6709\u6240\u4e0d\u540c\u3002\u7136\u800c\u4e00\u822c\u8ba4\u4e3a\u6b63\u5e38\u4eba\u5e76\u4e0d\u64c5\u957f\u6355\u6349\u8fd9\u4e9b\u7ec6\u5fae\u7684\u5dee\u5f02\uff0c\u56e0\u6b64\u673a\u5668\u5b66\u4e60\u6a21\u578b\u6210\u4e3a\u5e94\u5bf9\u6b64\u7c7b\u95ee\u9898\u7684\u5e38\u89c1\u65b9\u6cd5\u3002\u4f46\u662f\u4eba\u7c7b\u4e5f\u6709\u6a21\u578b\u6240\u4e0d\u5177\u5907\u7684\u4f18\u52bf\uff0c\u6bd4\u5982\u5bf9\u9762\u90e8\u91cd\u8981\u7279\u5f81\u5341\u5206\u654f\u611f\u3002\u90a3\u4e48\u673a\u5668\u5b66\u4e60\u6a21\u578b\u548c\u4eba\u5230\u5e95\u5b70\u5f3a\u5b70\u5f31\u5462\uff1f\u5982\u4f55\u80fd\u5c06\u8fa8\u522b\u7684\u51c6\u786e\u5ea6\u6700\u5927\u5316\uff1f<\/span><\/p>\n


<\/p>\n


<\/p>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

2. \u4eba\u673a\u5927\u6218\uff0c\u5b70\u5f3a\u5b70\u5f31\uff1f<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

PNAS\u6700\u8fd1\u53d1\u8868\u7684\u4e00\u9879\u7814\u7a76\u89e3\u7b54\u4e86\u4e0a\u8ff0\u95ee\u9898\u3002\u5728\u4e24\u4e2a\u6709\u5927\u91cf\u53c2\u4e0e\u8005\u7684\u5728\u7ebf\u5b9e\u9a8c\u4e2d\uff0c\u7814\u7a76\u4eba\u5458\u5411\u88ab\u8bd5\u5c55\u793a\u4e86\u771f\u5b9e\u89c6\u9891\u548c\u865a\u5047\u89c6\u9891\uff0c\u5e76\u8981\u6c42\u4ed6\u4eec\u8fa8\u522b\u89c6\u9891\u7684\u771f\u5047\u3002\u7b2c\u4e00\u4e2a\u5b9e\u9a8c\u5171\u6709882\u4eba\u53c2\u4e0e\uff0c\u88ab\u8bd5\u81f3\u5c11\u8fa8\u522b\u4e86 10 \u7ec4\u89c6\u9891\u7247\u6bb5\u3002\u7ed3\u679c\u8868\u660e\uff0c82% \u7684\u88ab\u8bd5\u51c6\u786e\u5ea6\u9ad8\u4e8e\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u5e73\u5747\u503c\u3002\u5728\u7528\u4e8e\u5b9e\u9a8c\u7684\u5171 56 \u7ec4\u89c6\u9891\u4e2d\uff0c28\u7ec4\u88ab\u8d85\u8fc783%\u7684\u88ab\u8bd5\u6210\u529f\u8fa8\u522b\uff0c16\u7ec4\u88ab65%-82%\u7684\u88ab\u8bd5\u6210\u529f\u8fa8\u522b\uff0c9\u7ec4\u88ab50%-65%\u7684\u88ab\u8bd5\u6210\u529f\u8fa8\u522b\uff0c\u4ec5\u67093\u7ec4\u89c6\u9891\uff0c\u88ab\u8bd5\u6210\u529f\u8fa8\u522b\u7684\u6bd4\u4f8b\u5c0f\u4e8e50%\u3002<\/span><\/p>\n


<\/p>\n

\u7b2c\u4e8c\u9879\u5b9e\u9a8c\u4e2d\u5171\u6709 9492 \u4eba\u53c2\u4e0e\uff0c\u4ed6\u4eec\u9700\u8981\u5bf9\u6240\u7ed9\u89c6\u9891\u7684\u771f\u5b9e\u7a0b\u5ea6\u6253\u5206\uff0c\u603b\u8ba1\u6253\u52067.4\u4e07\u4f59\u6b21\u3002\u7ed3\u679c\u8868\u660e\uff0c\u4eba\u7c7b\u88ab\u8bd5\u7684\u8868\u73b0<\/span>\uff08\u84dd\u8272\u548c\u9ec4\u8272\uff09<\/span>\u5747\u7565\u4f4e\u4e8e\u673a\u5668\u5b66\u4e60\u6a21\u578b\uff0c\u5176\u4e2d\u4ec5\u6709 13%-37% \u88ab\u8bd5\u7684\u8868\u73b0\u4f18\u4e8e\u6a21\u578b\u3002\u7136\u800c\uff0c\u5c06\u4f17\u4eba\u7ed9\u51fa\u7684\u771f\u5b9e\u7a0b\u5ea6\u6253\u5206\u5e73\u5747\u540e\uff0c\u5176\u65b9\u5dee\u53d8\u5c0f\uff0c\u4e14\u51c6\u786e\u5ea6\u8fbe\u5230\u751a\u81f3\u8d85\u8fc7\u4e86\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002\u8fd9\u8bf4\u660e\u53ef\u901a\u8fc7\u7fa4\u4f53\u667a\u6167\uff0c\u5224\u522b\u89c6\u9891\u771f\u5047\u3002<\/span><\/p>\n


<\/p>\n

       <\/span>        <\/span><\/p>\n

<\/span><\/p>\n

\u56fe1. \u4eba\u7c7b\u53c2\u4e0e\u8005\u5728\u4e24\u79cd\u5b9e\u9a8c\u4e2d\u8868\u73b0\u7684\u5c0f\u63d0\u7434\u56fe\uff0c\u5b9e\u9a8c\u4e8c\u4e2d\u7684R\u4ee3\u8868\u62db\u52df\u7684\u53c2\u4e0e\u8005\uff0c\u4ed6\u4eec\u5fc5\u9700\u6bcf\u4eba\u5b8c\u621020\u6b21\u5b9e\u9a8c\uff0c\u51719492\u4eba\uff0cNR\u4ee3\u8868\u7f51\u7edc\u53c2\u4e0e\u8005\uff0c\u53ef\u4ee5\u5b8c\u6210\u4efb\u610f\u6b21\u5b9e\u9a8c\uff0c\u5171\u8ba167647\u4eba\u3002<\/span><\/section>\n


<\/p>\n

\u8be5\u7814\u7a76\u8fd8\u6d4b\u8bd5\u4e86\u4eba\u673a\u534f\u4f5c\u8fa8\u522b\u865a\u5047\u89c6\u9891\u7684\u51c6\u786e\u5ea6\u3002\u88ab\u8bd5\u53ef\u5728\u505a\u51fa\u5224\u65ad\u540e\u770b\u5230\u6a21\u578b\u505a\u51fa\u7684\u5224\u65ad\uff0c\u5e76\u636e\u6b64\u51b3\u5b9a\u662f\u5426\u6539\u4e3b\u610f\u3002\u7ed3\u679c\u8868\u660e\uff0c\u4eba\u673a\u534f\u4f5c\u540e\uff0c\u88ab\u8bd5\u8fa8\u522b\u7684\u51c6\u786e\u7387\u4ece66%\u63d0\u9ad8\u5230\u4e8673%\u3002\u4ece\u56fe2\u5c55\u793a\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b<\/span>\uff08\u7ea2\u7ebf\uff09<\/span>\u3001\u7fa4\u4f53\u667a\u6167<\/span>\uff08\u84dd\u7ebf\uff09<\/span>\u548c\u4eba\u673a\u534f\u4f5c<\/span>\uff08\u7eff\u7ebf\uff09<\/span>\u8fa8\u522b\u865a\u5047\u89c6\u9891\u51c6\u786e\u5ea6\u7684ROC\u66f2\u7ebf\u4e2d\uff0c\u80fd\u591f\u770b\u51fa\u4eba\u673a\u534f\u4f5c\u80fd\u591f\u6700\u597d\u5730\u8fa8\u522b\u865a\u5047\u89c6\u9891\u3002<\/span><\/p>\n

       <\/span>        <\/span><\/p>\n

<\/span><\/p>\n

\u56fe2.\u4e0d\u540c\u65b9\u6cd5\u8fa8\u522b\u865a\u5047\u89c6\u9891\u51c6\u786e\u5ea6\u7684ROC\u66f2\u7ebf<\/span><\/p>\n


<\/p>\n

\u4eba\u673a\u534f\u4f5c\u65f6\uff0c\u82e5\u673a\u5668\u7684\u9884\u6d4b\u662f\u6b63\u786e\u7684\uff0c\u5219\u88ab\u8bd5\u51c6\u786e\u5ea6\u63d0\u5347\u6700\u660e\u663e\uff0c\u800c\u82e5\u673a\u5668\u7684\u9884\u6d4b\u4e0d\u51c6\u786e\u6216\u8005\u4e0d\u786e\u5b9a\u65f6\uff0c\u88ab\u8bd5\u51c6\u786e\u5ea6\u53cd\u800c\u964d\u4f4e\uff0c\u5982\u56fe3\u6240\u793a\u3002<\/span><\/p>\n

       <\/span>        <\/span><\/p>\n

<\/span><\/section>\n
\u56fe3.\u673a\u5668\u9884\u6d4b\u6b63\u786e\u3001\u9519\u8bef\u6216\u4e0d\u786e\u5b9a\u65f6\uff0c\u88ab\u8bd5\u6539\u53d8\u51b3\u5b9a\u540e\u8fa8\u522b\u51c6\u786e\u5ea6\u6539\u53d8\uff08\u6a2a\u8f74\uff09\u7684\u6982\u7387\u5bc6\u5ea6\u3002<\/span><\/section>\n


<\/p>\n

\u9762\u5bf9\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7ed9\u51fa\u7684\u9519\u5224\uff0c\u4eba\u4eec\u5f80\u5f80\u4f1a\u53d7\u5176\u5f71\u54cd\u3002\u5bf9\u6b64\uff0c\u4e00\u4e2a\u9884\u671f\u66f4\u6709\u6548\u7684\u4eba\u673a\u534f\u4f5c\u65b9\u6848\u662f\u6253\u7834\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u9ed1\u7bb1\uff0c\u8ba9\u6a21\u578b\u5728\u7ed9\u51fa\u7ed3\u679c\u4e4b\u5916\uff0c\u6307\u660e\u505a\u51fa\u5224\u65ad\u6240\u4f9d\u8d56\u7684\u7279\u5f81\u3002<\/span><\/p>\n


<\/p>\n


<\/p>\n

\n
\n
\n
\n
\n

<\/section>\n

<\/section>\n
\n
<\/svg><\/section>\n<\/section>\n<\/section>\n
\n

3. \u4eba\u673a\u534f\u4f5c\uff0c\u5404\u53d6\u6240\u957f<\/strong><\/strong><\/p>\n<\/section>\n

\n

<\/section>\n

<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


<\/p>\n

\u89c6\u9891\u662f\u5f02\u6784\u7684\u3001\u9ad8\u7ef4\u7684\u5a92\u4f53\uff0c\u4eba\u7c7b\u5728\u67d0\u4e9b\u573a\u666f\u4e0b\u5fc5\u7136\u6bd4\u673a\u5668\u8868\u73b0\u66f4\u597d\u3002\u4f8b\u5982\u5728\u8fa8\u522b\u653f\u6cbb\u4eba\u7269\u7684\u89c6\u9891\u65f6\uff0c\u4eba\u7c7b\u5177\u5907\u80cc\u666f\u77e5\u8bc6\uff0c\u81ea\u7136\u80fd\u8fbe\u5230\u66f4\u9ad8\u7684\u51c6\u786e\u5ea6\u3002\u800c\u5f53\u89c6\u9891\u4e2d\u51fa\u73b0\u4e24\u4eba\u800c\u4e0d\u662f\u4e00\u4eba\u65f6\uff0c\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u8868\u73b0\u4e5f\u4e0d\u5982\u4eba\u7c7b\u3002\u4f46\u5728\u53e6\u4e00\u4e9b\u573a\u666f\u4e0b\uff0c\u6bd4\u5982\u89c6\u9891\u4e0d\u591f\u6e05\u6670\u6216\u80cc\u666f\u8f83\u6697\u65f6\uff0c\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u8fa8\u522b\u5219\u66f4\u51c6\u786e\u3002\u6b64\u5916\uff0c\u4eba\u7c7b\u88ab\u8bd5\u5728\u8fa8\u522b\u6d89\u53ca\u5230\u6124\u6012\u60c5\u7eea\u65f6\u7684\u865a\u5047\u89c6\u9891\u65f6\uff0c\u51c6\u786e\u5ea6\u4e5f\u4f1a\u964d\u4f4e\u3002<\/span><\/p>\n


<\/p>\n

\u5c3d\u7ba1\u8be5\u7814\u7a76\u7684\u5b9e\u9a8c\u73af\u5883\u53ca\u865a\u5047\u4fe1\u606f\u7684\u6bd4\u4f8b\u4e0e\u771f\u5b9e\u5a92\u4f53\u73af\u5883\u6709\u6240\u4e0d\u540c\uff0c\u4f46\u5176\u521d\u6b65\u7ed3\u8bba\u4ecd\u5177\u6709\u6307\u5bfc\u610f\u4e49\u3002\u672a\u6765\u8fa8\u522b\u6570\u636e\u4e16\u754c\u4e2d\u865a\u5047\u4fe1\u606f\u7684\u7814\u7a76\uff0c\u9700\u8981\u8003\u8651\u5982\u4f55\u7ed3\u5408\u4eba\u7c7b\u7684\u7fa4\u4f53\u667a\u6167\u4ee5\u53ca\u673a\u5668\u7684\u667a\u80fd\uff0c\u5404\u53d6\u5176\u6240\u957f\u3002<\/span><\/p>\n


<\/p>\n


<\/span><\/p>\n

\n
\n
\n
\n

\u590d\u6742\u79d1\u5b66\u6700\u65b0\u8bba\u6587<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

\n


<\/p>\n<\/section>\n

\u96c6\u667a\u6591\u56fe\u9876\u520a\u8bba\u6587\u901f\u9012\u680f\u76ee\u4e0a\u7ebf\u4ee5\u6765\uff0c\u6301\u7eed\u6536\u5f55\u6765\u81eaNature\u3001Science<\/span>\u7b49\u9876\u520a\u7684\u6700\u65b0\u8bba\u6587\uff0c\u8ffd\u8e2a\u590d\u6742\u7cfb\u7edf\u3001\u7f51\u7edc\u79d1\u5b66\u3001\u8ba1\u7b97\u793e\u4f1a\u79d1\u5b66\u7b49\u9886\u57df\u7684\u524d\u6cbf\u8fdb\u5c55\u3002\u73b0\u5728\u6b63\u5f0f\u63a8\u51fa\u8ba2\u9605\u529f\u80fd\uff0c\u6bcf\u5468\u901a\u8fc7\u5fae\u4fe1\u670d\u52a1\u53f7\u300c\u96c6\u667a\u6591\u56fe\u300d\u63a8\u9001\u8bba\u6587\u4fe1\u606f\u3002\u626b\u63cf\u4e0b\u65b9\u4e8c\u7ef4\u7801\u5373\u53ef\u4e00\u952e\u8ba2\u9605\uff1a<\/span>
<\/p>\n

<\/p>\n

\n


<\/p>\n<\/section>\n


<\/p>\n

\n

\u63a8\u8350\u9605\u8bfb<\/span><\/strong><\/strong><\/p>\n