Using gait videos to automatically assess anxiety.

Background: In recent years, the number of people with anxiety disorders has increased worldwide. Methods for identifying anxiety through objective clues are not yet mature, and the reliability and validity of existing modeling methods have not been tested. The objective of this paper is to propose an automatic anxiety assessment model with good reliability and validity. Methods: This study collected 2D gait videos and Generalized Anxiety Disorder (GAD-7) scale data from 150 participants. We extracted static and dynamic time-domain features and frequency-domain features from the gait videos and used various machine learning approaches to build anxiety assessment models. We evaluated the reliability and validity of the models by comparing the influence of factors such as the frequency-domain feature construction method, training data size, time-frequency features, gender, and odd and even frame data on the model. Results: The results show that the number of wavelet decomposition layers has a significant impact on the frequency-domain feature modeling, while the size of the gait training data has little impact on the modeling effect. In this study, the time-frequency features contributed to the modeling, with the dynamic features contributing more than the static features. Our model predicts anxiety significantly better in women than in men (r Male = 0.666, r Female = 0.763, p < 0.001). The best correlation coefficient between the model prediction scores and scale scores for all participants is 0.725 (p < 0.001). The correlation coefficient between the model prediction scores for odd and even frame data is 0.801~0.883 (p < 0.001). Conclusion: This study shows that anxiety assessment based on 2D gait video modeling is reliable and effective. Moreover, we provide a basis for the development of a real-time, convenient and non-invasive automatic anxiety assessment method.

Multi-Access Edge Computing (MEC) Based on MIMO: A Survey.

With the rapid development of wireless communication technology and the emergence of intelligent applications, higher requirements have been put forward for data communication and computing capacity. Multi-access edge computing (MEC) can handle highly demanding applications by users by sinking the services and computing capabilities of the cloud to the edge of the cell. Meanwhile, the multiple input multiple output (MIMO) technology based on large-scale antenna arrays can achieve an order-of-magnitude improvement in system capacity. The introduction of MIMO into MEC takes full advantage of the energy and spectral efficiency of MIMO technology, providing a new computing paradigm for time-sensitive applications. In parallel, it can accommodate more users and cope with the inevitable trend of continuous data traffic explosion. In this paper, the state-of-the-art research status in this field is investigated, summarized and analyzed. Specifically, we first summarize a multi-base station cooperative mMIMO-MEC model that can easily be expanded to adapt to different MIMO-MEC application scenarios. Subsequently, we comprehensively analyze the current works, compare them to each other and summarize them, mainly from four aspects: research scenarios, application scenarios, evaluation indicators and research issues, and research algorithms. Finally, some open research challenges are identified and discussed, and these indicate the direction for future research on MIMO-MEC.

Dynamic transcriptome analysis of Maiwa yak corpus luteum during the estrous cycle.

Maiwa yak is a special breed of animal living on the Qinghai-Tibet Plateau, which has great economic value, but its fertility rate is low. The corpus luteum (CL) is a temporary tissue that plays a crucial role in maintaining the physiological cycle. However, little is known about the transcriptome profile in Maiwa yak CL. In the present study, the transcriptome of Maiwa yak CL at early (EYCL), middle (MYCL) and late-stages (LYCL) was studied employing high-throughput sequencing. A total of 25,922 transcripts were identified, including 22,277 known as well as 3,645 novel ones. Furthermore, 690 and 212 differentially expressed (DE) mRNAs were detected in the EYCL vs. MYCL and MYCL vs. LYCL groups, respectively. KEGG pathway enrichment analysis of DEGs illustrated that the most enriched pathway was PI3K-Akt pathway. Furthermore, twenty-six DEGs were totally found to be associated with different biological processes of CL development. One of these genes, PGRMC1, displayed a dynamical expression trend during the lifespan of yak CL. The knockdown of PGRMC1 in luteinized yak granulosa cells resulted in defective steroidogenesis. In conclusion, this study analyzed the transcriptome profiles in yak CL of different stages, and provided a novel database for analyzing the gene network in yak CL.HIGHLIGHTSThe manuscript analyzed the transcriptome profiles in yak CL during the estrous cycle.Twenty-six DEGs were found to be associated with the development or function of CL.One of the DEGs, PGRMC1, was found to be responsible for steroidogenesis in luteinized yak granulosa cells.

Sirtuin 7 is essential for the survival and synthesis of oestrogen in yak (Bos grunniens) cumulus granulosa cells.

Cumulus granulosa cells (CGCs) are a type of important ovarian somatic cells that carries out various functions related to oogenesis, follicular development and embryogenesis. The study on the development and function of CGCs facilitates the understanding of reproductive regulation in female animals. Sirtuin 7 (SIRT7) is a member of the sirtuin family of NAD+-dependent deacetylases mediating numerous biological processes. In this study, we detected the localization of SIRT7 in yak ovaries as well as explored the function of SIRT7 in yak CGCs. The results revealed that the SIRT7 protein was mainly localized in the cytoplasm of oocytes, granulosa cells and theca cells. The knockdown of SIRT7 in yak CGCs repressed cell proliferation and impacted the expressions of several apoptosis-related genes. Furthermore, oestrogen synthesis was also inhibited in SIRT7-deficient yak CGCs. The expressions of several sterogenesis-related genes decreased significantly following SIRT7 knockdown. In addition, the lack of SIRT7 in yak CGCs resulted in decreased levels of the TGFB/SMAD family members TGFB1, TGFBR1 SMAD2 and SMAD3. Moreover, the activation of the TGFB/SMAD pathway by adding TGFB/SMAD pathway activator SRI-011381 partially rescued the level of oestrogen secreted by SIRT7-deficient yak CGCs, as well as the expressions of steroidogenesis-related genes NR5A1 and CYP19A1. This research is the first to focus on the role of SIRT7 in yak ovary, and the outcomes offer new insights into the mechanism governing yak reproduction.

Ge nanowires on top of a Ge substrate for applications in anodes of Li and Na ion batteries: a first-principles study.

In this study, density functional theory (DFT) was used to research the adsorption and diffusion features of Li and Na on Ge nanowires on top of a Ge substrate. The adsorption energies at different positions are 0.71-1.28 eV for Na and -2.96--2.13 eV for Li. The adsorption energies can be further reduced by surface modification with one or two P atoms. In particular, the sidewall of the Ge nanowire modified by two P atoms is most favorable to adsorb Li/Na. In addition, we used the nudged elastic band (NEB) method to study the diffusion pathways of Li/Na on the sidewall of Ge NW and the Ge substrate and computed their energy barriers. When Li or Na diffuses across the Ge NW, the energy barrier is 0.65 or 0.79 eV, indicating that the Ge NW can be applied to anodes in lithium and sodium ion batteries. Finally, the insertion of more lithium and sodium atoms into the Ge NW would cause volume expansion and the average length of Ge-Ge bonds to increase. This work will contribute to studying the adsorption and diffusion of Li and Na on nanowires with a substrate and the volume expansion caused by the insertion of Li/Na into the nanowires. Additionally, it provides guidance for designing Ge anodes for sodium ion batteries.

The surface passivation of Ge(100) and Ge(111) anodes in Ge-air batteries with different doping types and concentrations.

The surface passivation of Ge(100) and Ge(111) anodes in Ge-air batteries with different doping types and concentrations is analyzed by density function theory (DFT) calculations. Compared with Ge(111) anodes, the surface passivation is restrained on Ge(100) anodes as they have larger binding energies with GeO2 layers. Meanwhile, doping would hinder the formation of a GeO2 layer on Ge anodes, especially for p-type doping, like B. The dissimilarities of the electrostatic potential differences and projected local density of states between the p-type Ge(100)/GeO2 and Ge(111)/GeO2 also reveal the origins of their distinct performances in Ge-air batteries. Furthermore, the I-V curves show that the Ge(100)/GeO2/Ge(100) device has a higher current than the Ge(111)/GeO2/Ge(111) device. This work would help to fundamentally comprehend the different electrochemical properties of Ge-air batteries with different orientations and doping and provide guidelines for the design of Ge anodes in Ge-air batteries.