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达标排污不等于免责！福建适用《生态环境法典》首案宣判_我的网站

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Brain-reading AI model reveals how different brain regions are linked to cognitive functions. Photo: Courtesy of Lu Han
Chinese scientists have developed a “brain-reading” AI model that could help predict the risk of depression among adolescents up to four years in advance by analyzing how humans respond to facial expressions, a technology expected to inspire future development of embodied intelligent humanoids capable of perceiving human emotion and thoughts through nuanced facial cues. 
WHO data show that around 332 million people worldwide have depression, about one-third of whom have treatment-resistant forms of the condition. In China, an estimated 95 million people suffer from depression, National Business Daily reported, citing statistics from the China Mental Health Survey. 
Using data from a population-based longitudinal adolescent cohort recruited across several European countries, the research team led by Lu Han, assistant professor at the School of Artificial Intelligence, Shenzhen University, has built an AI model that predicted which 19-year-olds were more likely to develop depression at the age of 23. The predictions were backed up by an independent clinical cohort of individuals with depression. The team’s paper was published in the journal Science Advances this month.
According to Lu, the study used brain scans taken at age 19 to predict depression-related symptoms at age 23. The study focuses on adolescence because the transition from adolescence to early adulthood is a key developmental period when depressive symptoms can increase rapidly. The earlier risks are identified, the greater the opportunity for prevention, Lu told the Global Times on Monday, adding that the findings need to be further validated in middle-aged and older adults and across different ethnic groups in future research. 
In this study, the researchers analyzed data from adolescents in the IMAGEN, a population-based longitudinal cohort recruited across several European countries. At age 19, participants underwent an fMRI emotional-face task, and their emotional symptoms were assessed using standardized questionnaires. Genetic data obtained from blood samples were also analyzed, and participants were followed up at age 23. The researchers examined whether neural representations of angry faces at age 19 were associated with emotional symptoms and could predict elevated emotional symptoms four years later.
According to Lu, people without depression can more easily distinguish emotional changes based on others’ facial expressions and respond accordingly – for example, responding with friendliness to a smiling expression. But people with depression cannot do this, and are more likely to assume people are angry with them. 
A brain-aligned deep-learning model developed by Lu’s team suggested that those participants whose brains were less able to distinguish between different facial emotions and tended to perceive others as angry were more likely to develop symptoms of depression and anxiety in adulthood. 
The hypothesis that adolescents at risk of depression may respond differently to other people’s facial expressions than those without such risk based on the negative information processing bias long observed in depression research: people at risk of depression are more likely to notice, interpret, or remember negative social information, Lu said. 
The researchers focused on angry facial expressions because they signal social threat and rejection, which are closely linked to interpersonal difficulties and negativity bias associated with depression. They hope to further understand how this bias develops within the visual system. 
Building on this, they created a deep learning model, which mimics how the brain processes visual information, to predict how the brain encodes abstract emotional concepts such as anger.
They found that 19-year-olds whose response to facial expressions was skewed in favour of negative emotions or memories were the most likely to develop some form of depression.
Based on these findings, Lu’s team then developed a marker that can identify possible warning signs. 
According to Lu, the study found that the computational biomarker was linked to the depression-related variant rs11123030 and polygenic risk for depression, suggesting that genetic susceptibility may affect emotional perception. It also provided predictive information beyond family stress and socioeconomic factors, complementing rather than replacing environmental risk factors. Therefore, depression is neither purely genetic nor purely psychological, but a complex mental disorder arising from the interplay of genetic susceptibility, brain development, emotional and cognitive processes, and life experiences. 
According to Lu, the study is also expected to advance AI by aligning deep neural networks with human brain activity and using parameter perturbations to probe neural mechanisms, allowing models to both predict and explain how biases may arise. 
The findings suggest that future affective computing and embodied AI should go beyond simply labeling facial expressions, incorporating visual details while preventing prior assumptions from overriding real-time sensory input, Lu said, adding that the findings could provide valuable insights for developing more interpretable robotic perception systems that more closely emulate the way humans process emotions.
。    AI摘要      福建上杭法院审结全省首例适用《生态环境法典》案件，认定两家混凝土企业粉尘致果园受损，虽排放达标仍须承担无过错侵权责任，判令连带赔偿果农28.5万元。         福建日报·新福建客户端8月17日讯（福建日报记者 苏依婕 通讯员 温东英）8月17日，龙岩市上杭县人民法院对一起环境污染责任纠纷案作出一审判决，依法认定当地两家混凝土企业持续排放水泥粉尘的行为与周边柚子果园受损存在直接因果关系，判令两家企业连带承担相应生态侵权赔偿责任。这是自8月15日《中华人民共和国生态环境法典》正式施行以来，福建省首例适用该法典审结的案件。    “水泥灰飘进果园，侵蚀果树、腐蚀土壤，大片果树慢慢枯死，几年心血全白费了。”说起自己的遭遇，果农老邱满是无奈。

B | 2011年，老邱在上杭县稔田镇楼岗村下斜角租下30亩地，种植红心柚，后来又引进泰国青柚，靠着这片果园维持全家生计。    2023年，甲、乙两家混凝土企业落地本村，甲公司在距离果园仅50米处建起水泥搅拌生产线，之后两家合伙运营，对外以乙公司名义生产。自2023年5月投产以来，该公司生产线的水泥粉尘持续飘入柚子果园，污染日趋严重。同年11月，不少柚子树开始枯萎死亡，老邱随即找企业协商赔偿，双方由此产生矛盾。

C |     2024年4月，经稔田镇人民调解委员会调解，乙公司一次性向老邱赔付此前粉尘污染造成的果园损失3.8万元。同年5月，企业加装治污设备，但前期堆积的粉尘叠加日常扬尘，持续腐蚀土壤、损伤果树，果园受损情况并未好转。

D | 两家企业认为，后期果树衰败是农户疏于管理导致，不愿再承担额外赔偿。协商无果后，老邱以自家农场名义向法院提起环境污染侵权诉讼。    粉尘致害、农作物减产、土壤污染……由于这起案件涉及诸多专业难题，承办法官张兴发多次往返果园、厂区实地走访，委托第三方机构鉴定污染因果与财产损失。

E | 鉴定机构出具了因果关系认定，评估机构则根据原地修复、异地重建果园等不同的修复方案给出三档损失认定。

F |     为破解专业认定难题，法院还引入了“生态技术调查官”，邀请农林专家一同现场勘验、取样研判。“叶片上白色结块检测就是水泥粉尘。果园无遮挡区域的果树烂枯、有竹林遮挡的长势完好，粉尘污染和果树受损的因果关系很明确，且与鉴定机构出具的污染因果关系认定可以相互印证。”生态技术调查官、农林专家刘德春解释道，泰国青柚根系娇气，粉尘长期改变土质，果树受损后无法复原，确实造成果农的损失。综合考量果树实际受损程度和果园经营现状，原地修复和异地重建果园不具有经济性和可行性，刘德春建议参照当地征地时对果树的补偿标准来计算损失较为公允。    审理过程中，企业方认为生产线已通过环评验收、排放检测达标，无需对果园后续损失承担责任。    “即使环评达标、主观无过错，也不能成为免责的理由。”承办法官张兴发当庭释明，依据《生态环境法典》，环境侵权适用无过错责任原则和举证责任倒置。

G | 企业排污造成他人损害，不管有没有主观过错，都要承担责任；企业要想免责，需拿出证据，证明损害与自身排污行为不存在因果关系，或者存在法律规定的免责、减责情形。    本案中，两家混凝土企业始终未能拿出有效证据，证明果树大面积受损与厂区扬尘无因果关系。综合全案证据、鉴定评估结论与技术调查官意见，法院最终认定，两家企业共同排污是果园受损的直接原因，判令双方连带赔偿果农经济损失28.5万元，执行时扣除此前已赔付的3.8万元。

H |     “产业发展必须守住生态保护和群众财产权益两条底线。

I | ”省法院生态环境审判庭副庭长袁春怡表示，本案是福建省首例适用《生态环境法典》审结的案件，清晰地传递出法律划定的行为边界，污染者不能以“已经尽到注意义务”或“技术达标”为由免责，强化对受害者权益的保护，彰显生态环境法典以人为本的生态法治底色。无过错责任的刚性约束，也将促使企业将环境风险评估前置，优化生产工艺，从源头减少损害发生。

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