A Review on Autism Spectrum Disorder Screening by Artificial Intelligence Methods.

PURPOSE: With the increasing prevalence of autism spectrum disorders (ASD), the importance of early screening and diagnosis has been subject to considerable discussion. Given the subtle differences between ASD children and typically developing children during the early stages of development, it is imperative to investigate the utilization of automatic recognition methods powered by artificial intelligence. We aim to summarize the research work on this topic and sort out the markers that can be used for identification. METHODS: We searched the papers published in the Web of Science, PubMed, Scopus, Medline, SpringerLink, Wiley Online Library, and EBSCO databases from 1st January 2013 to 13th November 2023, and 43 articles were included. RESULTS: These articles mainly divided recognition markers into five categories: gaze behaviors, facial expressions, motor movements, voice features, and task performance. Based on the above markers, the accuracy of artificial intelligence screening ranged from 62.13 to 100%, the sensitivity ranged from 69.67 to 100%, the specificity ranged from 54 to 100%. CONCLUSION: Therefore, artificial intelligence recognition holds promise as a tool for identifying children with ASD. However, it still needs to continually enhance the screening model and improve accuracy through multimodal screening, thereby facilitating timely intervention and treatment.

Time difference detection based on sliding window all-phase FFT and Kalman filtering for precise flow measurement.

Coriolis mass flowmeter (CMF) measures the mass flow rate by detecting the time difference, typically using frequency domain methods. However, the spectrum leakage is the primary challenge. To address this issue, a new time difference detection method is proposed utilizing sliding window and all-phase fast Fourier transform. The computational complexity is reduced considering the changes in signal frequency. To further improve the stability and response speed of the measured value, a Kalman filtering algorithm based on variance detection is also proposed for post-processing. A transmitter system is developed to validate the proposed methods. The results demonstrate that, for single phase fluids, the accuracy is better than 0.5‰ and the repeatability is better than 0.2‰, thereby offering an improvement in the accuracy of CMF and supporting for industrial applications.

Uncovering potential distinctive acoustic features of healing music.

Background: Music therapy is a promising complementary intervention for addressing various mental health conditions. Despite evidence of the beneficial effects of music, the acoustic features that make music effective in therapeutic contexts remain elusive. Aims: This study aimed to identify and validate distinctive acoustic features of healing music. Methods: We constructed a healing music dataset (HMD) based on nominations from related professionals and extracted 370 acoustic features. Healing-distinctive acoustic features were identified as those that were (1) independent from genre within the HMD, (2) significantly different from music pieces in a classical music dataset (CMD) and (3) similar to pieces in a five-element music dataset (FEMD). We validated the identified features by comparing jazz pieces in the HMD with a jazz music dataset (JMD). We also examined the emotional properties of the features in a Chinese affective music system (CAMS). Results: The HMD comprised 165 pieces. Among all the acoustic features, 74.59% shared commonalities across genres, and 26.22% significantly differed between the HMD classical pieces and the CMD. The equivalence test showed that the HMD and FEMD did not differ significantly in 9.46% of the features. The potential healing-distinctive acoustic features were identified as the standard deviation of the roughness, mean and period entropy of the third coefficient of the mel-frequency cepstral coefficients. In a three-dimensional space defined by these features, HMD's jazz pieces could be distinguished from those of the JMD. These three features could significantly predict both subjective valence and arousal ratings in the CAMS. Conclusions: The distinctive acoustic features of healing music that have been identified and validated in this study have implications for the development of artificial intelligence models for identifying therapeutic music, particularly in contexts where access to professional expertise may be limited. This study contributes to the growing body of research exploring the potential of digital technologies for healthcare interventions.

Asymmetric pre-growing season warming may jeopardize seed reproduction of the sand-stabilizing shrub Caragana microphylla.

Our current understanding of the processes and mechanisms by which seasonal asymmetric warming affects seed reproduction in semiarid regions, which are essential in preserving the stability of both vegetation ecosystem structure and function, remains poorly understood. Here, we conducted a field warming experiment, including pre-growing season warming (W1), in-growing season warming (W2), and combined pre- and in-growing season warming (W3) treatments, to investigate the seed reproductive strategy of Caragana microphylla, an important sand-stabilizing shrub, from the perspective of reproductive phenology, reproductive effort, and reproductive success. Results show that the warming treatments advanced the initial stages of reproductive phenology, prolonged its duration, and decreased its synchrony (magnitude = W3 > W2 > W1). Additionally, flowering phenology was more sensitive to warming than podding phenology. The W1 treatment inclined seed reproduction towards the conservative strategy with low reproductive effort and success. The W3 treatment tended to increase seed reproductive effort and success. While the W2 treatment did not affect reproductive success, it did increase reproductive effort. Changes in reproductive phenology explained 20 % of the variation in reproductive effort and 38 % of the variation in reproductive success. However, these changes also directly hindered reproductive success (direct effect = -0.57) while indirectly promoting reproductive success (indirect effect = 0.27) by increasing reproductive efforts. Our results reveal that the seasonal asymmetry of warming altered the seed reproduction strategy of sand-stabilizing shrubs, with warmer winters and springs before the growing season decreasing seed fecundity.

Institutional Trust as a Protective Factor during the COVID-19 Pandemic in China.

Previous research has demonstrated that institutional trust protects subjective well-being during pandemics. However, the potential mediation mechanisms underlying this linkage remain unclear. This study constructs a mediating model to investigate the effect of institutional trust on subjective well-being and the mediating roles of belief in a just world and fear of COVID-19 in the Chinese context. To this end, we survey a sample of 881 participants. The results show that institutional trust, belief in a just world, fear of COVID-19, and subjective well-being (i.e., life satisfaction, positive affect, and negative affect) are significantly interrelated. The results also indicate a significant impact of institutional trust on life satisfaction, positive affect, and negative affect. Belief in a just world and fear of COVID-19, independently and in sequence, mediate the relationship between institutional trust and subjective well-being.