Hand and Arm Gesture-based Human-Robot Interaction: A Review

The study of Human-Robot Interaction (HRI) aims to create close and friendly communication between humans and robots. In the human-center HRI, an essential aspect of implementing a successful and effective HRI is building a natural and intuitive interaction, including verbal and nonverbal. As a prevalent nonverbally communication approach, hand and arm gesture communication happen ubiquitously in our daily life. A considerable amount of work on gesture-based HRI is scattered in various research domains. However, a systematic understanding of the works on gesture-based HRI is still lacking. This paper intends to provide a comprehensive review of gesture-based HRI and focus on the advanced finding in this area. Following the stimulus-organism-response framework, this review consists of: (i) Generation of human gesture(stimulus). (ii) Robot recognition of human gesture(organism). (iii) Robot reaction to human gesture(response). Besides, this review summarizes the research status of each element in the framework and analyze the advantages and disadvantages of related works. Toward the last part, this paper discusses the current research challenges on gesture-based HRI and provides possible future directions.Comment: 10 pages, 1 figure

Vanillin Alleviates High Fat Diet-Induced Obesity and Improves the Gut Microbiota Composition

Vanillin, a simple phenolic compound, exists marginally in some plants and can be produced by microbes. This study uses high-fat-diet (HFD) induced obese mice to study the effect of vanillin on obesity and obtain positive results. First, both body and adipose tissue weight are reduced. Second, the blood properties signaling certain disorders such as ALT, LDH, glucose, cholesterol, LDL-C, TG and HDL-C are ameliorated and both insulin sensitivity, and glucose tolerance are improved. Third, vanillin reduced elevated levels of inflammatory factors including LPS, IL-6, and TNF-α in plasma and liver tissue resulting from obesity. Finally, the production of short chain fatty acids (SCFAs) is enhanced. Additionally, study results demonstrate that vanillin significantly alleviates obesity-related gut microbiota (GM) disorders including the decrease of alpha- and beta-diversity. Furthermore, vanillin reduces the abundance of Firmicutes phylum, increases the richness of Bacteroidetes and Verrucomicrobiota phyla, and inhibits the expansion of the lipopolysaccharide (LPS)-producing bacteria Bilophila genus and the H2S-producing bacteria Desulfovibrio genus

Group Equivariant BEV for 3D Object Detection

Recently, 3D object detection has attracted significant attention and achieved continuous improvement in real road scenarios. The environmental information is collected from a single sensor or multi-sensor fusion to detect interested objects. However, most of the current 3D object detection approaches focus on developing advanced network architectures to improve the detection precision of the object rather than considering the dynamic driving scenes, where data collected from sensors equipped in the vehicle contain various perturbation features. As a result, existing work cannot still tackle the perturbation issue. In order to solve this problem, we propose a group equivariant bird's eye view network (GeqBevNet) based on the group equivariant theory, which introduces the concept of group equivariant into the BEV fusion object detection network. The group equivariant network is embedded into the fused BEV feature map to facilitate the BEV-level rotational equivariant feature extraction, thus leading to lower average orientation error. In order to demonstrate the effectiveness of the GeqBevNet, the network is verified on the nuScenes validation dataset in which mAOE can be decreased to 0.325. Experimental results demonstrate that GeqBevNet can extract more rotational equivariant features in the 3D object detection of the actual road scene and improve the performance of object orientation prediction.Comment: 8 pages,3 figures,accepted by International Joint Conference on Neural Networks (IJCNN)202

Attention-based BILSTM for the degradation trend prediction of lithium battery

There is an irreversibility in the decline of Li-ion batteries, and the performance of individual cells in the battery pack will gradually decline as the number of times the on-board Li-ion battery is charged and discharged increases This situation can significantly affect the daily use of electric vehicles, for example by shortening the driving range, and in addition, the deterioration of the battery performance increases the probability of electric vehicle breakdowns. Very little work has been done on the prediction of lithium battery performance degradation in long-mileage states, accurate prediction of future battery performance degradation can significantly reduce the probability of EV failure, making battery performance prediction very important. In this paper, we propose a BILSTM network based on an attention mechanism and utilize grey relation analysis and empirical modal decomposition in the input link of the network to address the shortcomings exposed by deep learning in the work on temporal prediction. The adopted approach can effectively address the impact of data noise and redundant features on the prediction work that occurs in deep learning. According to the experimental results, the prediction performance of the model proposed in this paper is found to be higher than other networks in both types of data set

Role of IgA in the early-life establishment of the gut microbiota and immunity: Implications for constructing a healthy start

Colonization and maturation of the gut microbiota (GM) during early life is a landmark event that fundamentally influences the (early) immunity and later-life health of various mammals. This is a delicate, systematic process that is biologically actively regulated by infants and their mothers, where (secretory) IgA, an important regulator of microbes found in breast milk and generated actively by infants, may play a key role. By binding to microbes, IgA can inhibit or enhance their colonization, influence their gene expression, and regulate immune responses. IgA dysfunction during early life is associated with disrupted GM maturation and various microbe-related diseases, such as necrotizing enterocolitis and diarrhea, which can also have a lasting effect on GM and host health. This review discusses the process of early GM maturation and its interaction with immunity and the role of IgA (focusing on milk secretory IgA) in regulating this process. The possible application of this knowledge in promoting normal GM maturation processes and immune education has also been highlighted

The effect of Codonopis bulleynana Forest ex Diels on chronically constipated mice

To verify the laxative effect of Codonopsis bulleyana and its effect on intestinal microbiota, a long-term constipation model was established using 3.0 mg/kg loperamide hydrochloride, after which, the long-term constipation model was administered by 0.2 g/ml high-dose Codonopsis bulleyana water extract. The therapeutic effects were observed by measuring defecation amount and feces moisture content. The composition of intestinal microbiota was detected and analyzed using16S rDNA sequencing technology. The results showed that Codonopsis bulleyana water extract can increase stool quantity and promote intestinal tract movement in constipated mice. Obvious changes were shown in intestinal microbiota of chronically constipated mice treated with Codonopsis bulleyana water extract as the proportion of beneficial bacteria increased in the model treated by Codonopsis bulleyana. Codonopsis bulleyana water extract alleviates constipation symptoms caused by loperamide hydrochloride and improves the intestinal microbiota in constipated mice. Keyword: Codonopsis bulleyana, Long-term constipation, 16S rDNA, Intestinal microbiot

Multi-omics analyses reveal that the gut microbiome and its metabolites promote milk fat synthesis in Zhongdian yak cows

Background Yak cows produce higher quality milk with higher concentrations of milk fat than dairy cows. Recently, studies have found the yak milk yield and milk fat percentage have decreased significantly over the past decade, highlighting the urgency for yak milk improvement. Therefore, we aimed to analyze how the gut microbiome impacts milk fat synthesis in Zhongdian yak cows. Methods We collected milk samples from Zhongdian yak cows and analyzed the milk fat percentage, selecting five Zhongdian yak cows with a very high milk fat percentage (>7%, 8.70 ± 1.89%, H group) and five Zhongdian yak cows with a very low milk fat percentage (<5%, 4.12 ± 0.43%, L group), and then obtained gut samples of these ten Zhongdian yak cows through rectal palpation. Gut metagenomics, metabolomics, and conjoint metagenomics and metabolomics analyses were performed on these samples, identifying taxonomic changes, functional changes, and changes in gut microbes-metabolite interactions within the milk fat synthesis-associated Zhongdian yak cows gut microbiome, to identify potential regulatory mechanisms of milk fat at the gut microbiome level in Zhongdian yak cows. Results The metagenomics analysis revealed Firmicutes and Proteobacteria were significantly more abundant in the gut of the high-milk fat Zhongdian yak cows. These bacteria are involved in the biosynthesis of unsaturated fatty acids and amino acids, leading to greater efficiency in converting energy to milk fat. The metabolomics analysis showed that the elevated gut metabolites in high milk fat percentage Zhongdian yak cows were mainly enriched in lipid and amino acid metabolism. Using a combined metagenomic and metabolomics analysis, positive correlations between Firmicutes (Desulfocucumis, Anaerotignum, Dolosiccus) and myristic acid, and Proteobacteria (Catenovulum, Comamonas, Rubrivivax, Marivita, Succinimouas) and choline were found in the gut of Zhongdian yak cows. These interactions may be the main contributors to methanogen inhibition, producing less methane leading to higher-efficient milk fat production. Conclusions A study of the gut microbe, gut metabolites, and milk fat percentage of Zhongdian yak cows revealed that the variations in milk fat percentage between yak cows may be caused by the gut microbes and their metabolites, especially Firmicutes-myristic acid and Proteobacteria-choline interactions, which are important to milk fat synthesis. Our study provides new insights into the functional roles of the gut microbiome in producing small molecule metabolites and contributing to milk performance traits in yak cows

Cyanidin-3-O-glucoside Regulates the Expression of Ucp1 in Brown Adipose Tissue by Activating Prdm16 Gene

(1) Background: Brown adipose tissue (BAT) burns energy to produce heat. Cyanidin-3-O-glucoside (C3G) can then enhance the thermogenic ability of BAT in vivo. However, the mechanism by which C3G regulates Ucp1 protein expression remains unclear. (2) Methods: In this study, C3H10T12 brown adipose cells and db/db mice and mice with high-fat, high-fructose, diet-induced obesity were used as the model to explore the effect of C3G on the expression of the Ucp1 gene. Furthermore, the 293T cell line was used for an in vitro cell transgene, a double luciferase reporting system, and yeast single hybridization to explore the mechanism of C3G in regulating Ucp1 protein. (3) Results: we identified that, under the influence of C3G, Prdm16 directly binds to the &minus;500 to &minus;150 bp promoter region of Ucp1 to activate its transcription and, thus, facilitate BAT programming. (4) Conclusions: This study clarified the mechanism by which C3G regulates the expression of the Ucp1 gene of brown fat to a certain extent