A Survey on Deep Multi-modal Learning for Body Language Recognition and Generation

Body language (BL) refers to the non-verbal communication expressed through physical movements, gestures, facial expressions, and postures. It is a form of communication that conveys information, emotions, attitudes, and intentions without the use of spoken or written words. It plays a crucial role in interpersonal interactions and can complement or even override verbal communication. Deep multi-modal learning techniques have shown promise in understanding and analyzing these diverse aspects of BL. The survey emphasizes their applications to BL generation and recognition. Several common BLs are considered i.e., Sign Language (SL), Cued Speech (CS), Co-speech (CoS), and Talking Head (TH), and we have conducted an analysis and established the connections among these four BL for the first time. Their generation and recognition often involve multi-modal approaches. Benchmark datasets for BL research are well collected and organized, along with the evaluation of SOTA methods on these datasets. The survey highlights challenges such as limited labeled data, multi-modal learning, and the need for domain adaptation to generalize models to unseen speakers or languages. Future research directions are presented, including exploring self-supervised learning techniques, integrating contextual information from other modalities, and exploiting large-scale pre-trained multi-modal models. In summary, this survey paper provides a comprehensive understanding of deep multi-modal learning for various BL generations and recognitions for the first time. By analyzing advancements, challenges, and future directions, it serves as a valuable resource for researchers and practitioners in advancing this field. n addition, we maintain a continuously updated paper list for deep multi-modal learning for BL recognition and generation: https://github.com/wentaoL86/awesome-body-language

Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications

Federated learning (FL) is a distributed deep learning method which enables multiple participants, such as mobile phones and IoT devices, to contribute a neural network model while their private training data remains in local devices. This distributed approach is promising in the edge computing system where have a large corpus of decentralized data and require high privacy. However, unlike the common training dataset, the data distribution of the edge computing system is imbalanced which will introduce biases in the model training and cause a decrease in accuracy of federated learning applications. In this paper, we demonstrate that the imbalanced distributed training data will cause accuracy degradation in FL. To counter this problem, we build a self-balancing federated learning framework call Astraea, which alleviates the imbalances by 1) Global data distribution based data augmentation, and 2) Mediator based multi-client rescheduling. The proposed framework relieves global imbalance by runtime data augmentation, and for averaging the local imbalance, it creates the mediator to reschedule the training of clients based on Kullback-Leibler divergence (KLD) of their data distribution. Compared with FedAvg, the state-of-the-art FL algorithm, Astraea shows +5.59% and +5.89% improvement of top-1 accuracy on the imbalanced EMNIST and imbalanced CINIC-10 datasets, respectively. Meanwhile, the communication traffic of Astraea can be 82% lower than that of FedAvg.Comment: Published as a conference paper at IEEE 37th International Conference on Computer Design (ICCD) 201

Livestock overgrazing disrupts the positive associations between soil biodiversity and nitrogen availability

8 páginas.- 4 figuras.- 1 tabla.- 64 referencias.- Additional supporting information may be found online in the Supporting Information sectionLivestock overgrazing influences both microbial communities and nutrient cycling in terrestrial ecosystems. However, the role of overgrazing in regulating the relationship between soil biodiversity and nitrogen availability remains largely unexplored.We performed long-term grazing exclusion experiments across eight sites along precipitation gradient covering three major types of grassland in northern China to compare the linkage between soil microbial diversity and N availability in overgrazed versus non-grazed conditions.We found a significantly positive association between fungal diversity and soil available N in non-grazed grasslands. However, the positive association was absent in overgrazed environments. Bacterial diversity is not related to soil available N in either non-grazed or overgrazed grasslands. Moreover, in bacterial community, we found a positive link between the relative abundance of Actinobacteria with soil available N in non-grazed, but not overgrazed, grasslands. Instead we found the links between relative abundance of Bacteroidetes and Acidobacteria with soil available N in overgrazed grasslands, but not non-grazed, grasslands.Synthesis. Our work provides evidence that the relationships between microbial diversity and ecosystem functions are context-dependent, and so microbial community diversity is likely not the major driver of soil N mineralization in overgrazed grasslands. Our study suggests that high intensity anthropogenic activities in grasslands restrains the capacity of diverse soil microbial communities to sustain ecosystem function, and more broadly the capacity of entire ecosystems to maintain important ecosystem processes such as plant production. Our study also indicates that the fundamental microbial communities associated with N availability change with differing land management strategies (e.g. livestock grazing).National Natural Science Foundation of China, Grant/Award Number: 31772652, U1603235, 31660679 and 31770500; National Key Research and Development Program of China, Grant/Award Number: 2016YFC0500602; Program for Introducing Talents to Universities, Grant/Award Number: B16011; Ministry of Education Innovation Team Development Plan, Grant/Award Number: 2013-373; Innovative Team of Grassland Resources from the Ministry of Education of China, Grant/Award Number: IRT_17R59; Horizon 2020 Framework Program, Grant/Award Number: H2020-MSCA-IF-2016Peer reviewe

A genome-wide association study identifies FSHR rs2300441 associated with follicle-stimulating hormone levels

Follicle-stimulating hormone (FSH) and luteinizing hormone (LH) play critical roles in female reproduction, while the underlying genetic basis is poorly understood. Genome-wide association studies (GWASs) of FSH and LH levels were conducted in 2590 Chinese females including 1882 polycystic ovary syndrome (PCOS) cases and 708 controls. GWAS for FSH level identified multiple variants at FSHR showing genome-wide significance with the top variant (rs2300441) located in the intron of FSHR. The A allele of rs2300441 led to a reduced level of FSH in the PCOS group (β = −.43, P = 6.70 × 10−14) as well as in the control group (β = −.35, P = 6.52 × 10−4). In the combined sample, this association was enhanced after adjusting for the PCOS status (before: β = −.38, P = 1.77 × 10−13; after: β = −.42, P = 3.33 × 10−16), suggesting the genetic effect is independent of the PCOS status. The rs2300441 explained sevenfold higher proportion of the FSH variance than the total variance explained by the two previously reported FSHR missense variants (rs2300441 R2 = 1.40% vs rs6166 R2 = 0.17%, rs6165 R2 = 0.03%). GWAS for LH did not identify any genome-wide significant associations. In conclusion, we identified genome-wide significant association between variants in FSHR and circulating FSH first, with the top associated variant rs2300441 might be a primary contributor at the population level

The importance of NOx control for peak ozone mitigation based on a sensitivity study using CMAQ‐HDDM‐3D model during a typical episode over the Yangtze River delta region, China.

In recent years, ground-level ozone (O3) has been one of the main pollutants hindering air quality compliance in China's large city-clusters including the Yangtze River Delta (YRD) region. In this work, we utilized the process analysis (PA) and the higher-order decoupled direct method (HDDM-3D) tools embedded in the Community Multiscale Air Quality model (CMAQ) to characterize O3 formation and sensitivities to precursors during a typical O3 pollution episode over the YRD region in July 2018. Results indicate that gas-phase chemistry contributed dominantly to the ground-level O3 although a significant proportion was chemically produced at the middle and upper boundary layer before reaching the surface via diffusion process. Further analysis of the chemical pathways of O3 and Ox formation provided deep insights into the sensitivities of O3 to its precursors that were consistent with the HDDM results. The first-order sensitivities of O3 to anthropogenic volatile organic compounds (AVOC) were mainly positive but small, and temporal variations were negligible compared with those to NOx. During the peak O3 time in the afternoon, the first- and second-order sensitivities of O3 to NOx were significantly positive and negative, respectively, suggesting a convex response of O3 to NOx over most areas including Shanghai, Hangzhou, Nanjing and Hefei. These findings further highlighted an accelerated decrease in ground-level O3 in the afternoon corresponding to continuous decrease of NOx emissions in the afternoon. Therefore, over the YRD region including its metropolises, NOx emission reductions will be more important in reducing the afternoon peak O3 concentration compared with the effect of VOC emission control alone

Effects of livestock overgrazing on the relationships between plant and microbial diversity across the temperate steppes in northern China

11 páginas.- 3 figuras.- 3 tablas.- 57 referencias.-Livestock overgrazing has led to worldwide grassland degradation, posing a significant threat to plant and soil microbial diversity. However, little is known about whether livestock overgrazing influences plant and soil microbial diversity linkages. We examined relationships between plant and soil microbial beta diversity in eight pairs of ungrazed and overgrazed sites across temperate steppes in northern China. Our results revealed a positive correlation between plant and microbial beta diversity across ungrazed grasslands, and overgrazing did not change this relationship. However, different mechanisms underlay the correlations between plant and microbial beta diversity in ungrazed and overgrazed grasslands. In ungrazed grasslands, plant and microbial diversity associations were maintained mainly due to their similar responses to the shared environmental factors. While in overgrazed grasslands, the maintenance of plant and microbial diversity associations was primarily due to their functional associations. Furthermore, the positive links between plant species and microbial taxa increased in overgrazed grasslands, indicating that more soil microbial taxa form close associations with plant species in overgrazed grasslands. Our work provides new insights regarding the mechanisms of plant and microbial communities that associate under different ecological contexts, ultimately suggesting that the functional associations of plant and microbial communities are tighter as grazing intensifies in grasslands.The work was made possible by the National Natural Science Founda-tion of China (No. 32271642, 32061143027). M.D-B. acknowledges support from the Spanish Ministry of Science and Innovation for the I+D+i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. M.D-B. is also supported by a project of the Fondo Europeo de Desarrollo Regional (FEDER) and the Consejería de Transformación Económica, Industria, Conocimiento y Universidades of the Junta de Andalucía (FEDER Andalucía 2014-2020 Objetivo temático“01 - Refuerzo de la investigación, el desarrollo tecnológico y la innovación”) associated with the research project P20_00879 (ANDABIOMA).Peer reviewe

Significant Impact of Reactive Chlorine on Complex Air Pollution Over the Yangtze River Delta Region, China

27 pags., 17 figs., 3 tabs.The chlorine radical (Cl) plays a crucial role in the formation of secondary air pollutants by determining the total atmospheric oxidative capacity (AOC). However, there are still large discrepancies among studies on chlorine chemistry, mainly due to uncertainties from three aspects: (a) Anthropogenic emissions of reactive chlorine species from disinfectant usage are typically overlooked. (b) The heterogeneous reaction uptake coefficients used in air quality models resulted in certain differences. (c) The co-effect of anthropogenic and natural emissions is rarely investigated. In this study, the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) modeling system (updated with 21 new reactions and a comprehensive emissions inventory) was used to simulate the combined impact of chlorine emissions on the air quality of a coastal city cluster in the Yangtze River Delta (YRD) region. The results indicate that the new emissions of reactive chlorine and the updated gas-phase and heterogeneous chlorine chemistry can significantly enhance the AOC by 21.3%, 8.7%, 43.3%, and 58.7% in spring, summer, autumn, and winter, respectively. This is more evident in inland areas with high Cl concentrations. Our updates to the chlorine chemistry also increases the monthly mean maximum daily 8-hr average (MDA 8) O3 mixing ratio by 4.1–7.0 ppbv in different seasons. Additionally, chlorine chemistry promotes the formation of fine particulate matter (PM2.5), with maximum monthly average enhancements of 4.7–13.3 μg/m3 in different seasons. This study underlines the significance of adding full chlorine emissions and updating chlorine chemistry in air quality models, and demonstrates that chlorine chemistry may significantly impact air quality over coastal regions.This research is supported by the National Natural Science Foundation of China under Grant 42075144. The CSIC team is supported by the European Research Council Executive Agency under the European Union's Horizon 2020 Research and Innovation Programme (Project ERC-2016- COG 726349 CLIMAHAL). The HKPolyU team is supported by the Hong Kong Research Grants Council (Project T24-504/17-N). This work is supported by Shanghai Technical Service Center of Science and Engineering Computing, Shanghai University.Peer reviewe

One-Pot Green Synthesis and Bioapplication ofl-Arginine-Capped Superparamagnetic Fe3O4 Nanoparticles

Water-solublel-arginine-capped Fe3O4 nanoparticles were synthesized using a one-pot and green method. Nontoxic, renewable and inexpensive reagents including FeCl3,l-arginine, glycerol and water were chosen as raw materials. Fe3O4 nanoparticles show different dispersive states in acidic and alkaline solutions for the two distinct forms of surface bindingl-arginine. Powder X-ray diffraction and X-ray photoelectron spectroscopy were used to identify the structure of Fe3O4 nanocrystals. The products behave like superparamagnetism at room temperature with saturation magnetization of 49.9 emu g−1 and negligible remanence or coercivity. In the presence of 1-ethyl-3-(dimethylaminopropyl) carbodiimide hydrochloride, the anti-chloramphenicol monoclonal antibodies were connected to thel-arginine-capped magnetite nanoparticles. The as-prepared conjugates could be used in immunomagnetic assay

MODERN NOMADISM ——A network of reciprocal moorings

The wave of modernization and the impact of globalization have gradually dissolved the traditional nomadic way of life[1]. However some people still choose to live a nomadic lifestyle for quality of life or economic reasons, but they are still under huge cultural and political pressure. According to the National Institutes of Health(NIH), there are 164 million migrant workers in the world, which can be thought of as modern day ”nomads”. This paper focuses on seasonally migrating Mexican farm workers without a permanent home, exploring how they can be provided with a “mooring system” and, through different forms of settlement patterns, form a network of sites that can better nourish a shared, intergrated economy with local communities. Nowadays, seasonal farm workers from Mexico who travel to California are relegated to the interstices of mainstream society and navigate marginal contexts. Geographically, many live in houses that require three families to squeeze together, even in their own truck. Socially, many interact with other marginal groups, such as immigrants from Mexico, and some indigenous Mexicans have a really tough life due to the language barriers. In addition to Poor working and living conditions, unequal systemic inputs, outputs and unhealthy cycles between migrant workers and local farms further exacerbate their division from the urban space. By diminishing their ability to support each other and the potential contribution they can make to the culture and functioning of the local community in California. To improve this situation above, this thesis suggests a different approach to nomadic “mooring” in their places of employment can better support the lives and economic needs of this population, and a closed loop economy system within this new model of “mooring” can be beneficial and essential to both the migrant “nomads” and their host communities. [1].Michaels, Eric. “The Last of the Nomads. the Last of the Ethnographies or ‘All Anthropologists Are Liars.’” Mankind, vol. 17, no. 1, 2009, pp. 34–46, https://doi.org/10.1111/j.1835-9310.1987.tb00740.x