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Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with a strong genetic liability. Despite extensive studies, however, the underlying pathogenic mechanism still remains elusive. In the present study, we identified a homozygous mutation in the intron 1 of Wnt1 via large-scale screening of ASD risk/causative genes and verified that this mutation created a new splicing donor site in the intron1, and consequently, a loss of WNT1 expression. Interestingly, humanized rat models harboring this mutation exhibited robust ASD-like behaviors including impaired ultrasonic vocalization (USV), decreased social interactions, and restricted and repetitive behaviors. Moreover, in the substantia nigra compacta (SNpc) and the ventral tegmental area (VTA) of mutant rats, dopaminergic (DAergic) neurons were dramatically lost, together with a comparable decrease in striatal DAergic fibers. Furthermore, using single-cell RNA sequencing, we demonstrated that the decreased DAergic neurons in these midbrain areas might attribute to a shift of the boundary of the local pool of progenitor cells from the hypothalamic floor plate to the midbrain floor plate during the early embryonic stage. Moreover, treatments of mutant rats with levodopa could attenuate the impaired USV and social interactions almost completely, but not the restricted and repetitive behaviors. Our results for the first time documented that the developmental loss of DAergic neurons in the midbrain underlies the pathogenesis of ASD, and that the abnormal progenitor cell patterning is a cellular underpinning for this developmental DAergic neuronal loss. Importantly, the effective dopamine therapy suggests a translational significance in the treatment of ASD.

structural diagram ,loss function of the neural network and the time correlation coefficient function

Traffic surveillance cameras are located in urban traffic network system in abundance. These videos are mainly used for public safety and traffic accident monitoring. With the increase in urban traffic congestion, the road section queue detection technology becomes the insistent demands for urban traffic management. Considering the characteristics of the surveillance cameras in city intersection area, the paper used maximum similarity matching standard method which is based on the fixed background area window to correct the deviation between the lane region in real-time image collection and the lane region in setting, then adopted the AOI region partition method for mapping the distance in video image to the actual distance, at the same time, based on the road section multi-lane queuing model analyzed the features of queuing lane. The veins' differences between having vehicle lane and empty lane are obvious, therefore the paper selected the vein unit to express traffic vein image. Simple vein unit reflected the difference on gray level in neighborhood, and effectively reflected the veins' differences between having vehicle lane and empty lane. After removing the noise, the empty lane region at the end of queue could be detected, and the real-time length of the road section vehicle queue can also be calculated. The validity of the algorithm is validated by checking the actual intersection video images and actual queue length data.

Previous methods of optimization are designed for determinate quantum, which can hardly used in optimizing the parameters in traffic state detection algorithm, since traffic state is a fuzzy variable based on the sense, and it is different to determine a benchmark for optimization. This paper puts forward a driver-based evaluation approach which can solve the vague problem in determination of traffic state. Based on the evaluation, an optimization model is presented, and the time window and three common thresholds (speed, occupation, and volume) are analyzed in a detailed example. We argue that this optimization approach can be used not only on the traffic state detection model, but also on the vague quantum algorithm in other fields.

Data from 24 craniofacial dimensions were compiled for samples representing all the human populations of the world. These were converted into C scores and used to construct Euclidean Distance dendrograms. The populations of the world are best depicted as 8 major regional clusters representing: Africa, Amerind, Asia-Mainland, Australo-Melanesia, Eskimo-Siberia, Europe, India, and Jomon-Pacific. The mainland Asian cluster divided into northern and southern components. The Neolithic in both areas is less clearly associated with the northern or southern components and may represent the form of their undifferentiated precursors. This needs to be tested by the addition of further specimens and an adequate sample from South China. Mongols are peripheral members of the Asia-Mainland cluster and should not be thought of as typifying the region as a whole. The use of the term "Mongoloid" is inappropriate in both theory and practice.