Making Robotic Dogs Detect Objects That Real Dogs Recognize Naturally: A Pilot Study

The recent advancements in artificial intelligence (AI) and deep learning have enabled smart products, such as smart toys and robotic dogs, to interact with humans more intelligently and express emotions. As a result, such products become intensively sensorized and integrate multi-modal interaction techniques to detect and infer emotions from spoken utterances, motions, pointing gestures and observed objects, and to plan their actions. However, even for the predictive purposes, a practical challenge for these smart products is that deep learning algorithms typically require high computing power, especially when applying a multimodal method. Moreover, the memory needs for deep learning models usually surpass the limit of many low-end mobile computing devices as their complexities boost up. In this study, we explore the application of lightweight deep neural networks, SqueezeDet model and Single Shot Multi-Box Detector (SSD) model with MobileNet as the backbone, to detect canine beloved objects. These lightweight models are expected to be integrated into a multi-modal emotional support robotics system designed for a smart robot dog. We also introduce our future research works in this direction

Protective Effect of Tartaty Buckwheat Extract Fermented with Pleurotus eryngii on Alcoholic Liver and Stomach Injury in Mice

Objective: To investigate the antioxidant activity of fermented tartaty buckwheat extract of Pleurotus eryngii in vitro as well as its protective effect on alcohol-induced liver and gastric mucosa injury in vivo. Methods: The study involved determining the contents of functional components in fermented tartary buckwheat extract and observing its antioxidant capacity. Mice models of chronic alcoholic liver and gastric mucosa injury were established using Lieber-DeCarli liquid feed. The protective effects of fermented tartary buckwheat extract at low and high doses (1.5 g/kg B.W., 3.0 g/kg B.W.) were investigated for both liver and gastric mucosa injury. Results: The extract of fermented buckwheat with Pleurotus eryngii contained more antioxidant components, the contents of polyphenols, flavonoids and triterpenes were 11.40±0.32 mgGAE/g DW, 17.19±0.30 mg RE/g DW and 7.59±0.24 mg/g, respectively. The contents of rutin and quercetin were as follows: 13.55±0.05 and 0.665±0.01 mg/g. The iron reducing antioxidant capacity and DPPH and ABTS+ free radical scavenging efficiency of Tartary buckwheat extract were 16.66±0.65, 33.49±1.26 and 15.68±1.17 μmol Trolox/g DW, respectively. Compared with the model group, both high-dose and low-dose groups significantly reduced malondialdehyde (P<0.05), aspartate aminotransferase (P<0.01), alanine aminotransferase (P<0.01), lactate dehydrogenase (P<0.05), and interleukin-1β (P<0.05) levels and significantly increased levels of superoxide dismutase (P<0.01) and glutathione peroxidase (P<0.01), downregulated protein expression levels of reactive oxygen species (P<0.01), rat sarcoma (P<0.01), rapidly accelerated fibrosarcoma (P<0.01), extracellular signal-regulated kinases (P<0.05), and mitogen activated protein kinase kinase (P<0.05). Conclusion: Fermented tartaty buckwheat extract of Pleurotus eryngii has good antioxidant activity, and has obvious protective effect on chronic alcoholic liver and gastric mucosa injury in mice

Optimal Rain Gauge Network Design Aided by Multi-Source Satellite Precipitation Observation

Optimized rain gauge networks minimize their input and maintenance costs. Satellite precipitation observations are particularly susceptible to the effects of terrain elevation, vegetation, and other topographical factors, resulting in large deviations between satellite and ground-based precipitation data. Satellite precipitation observations are more inaccurate where the deviations change more drastically, indicating that rain gauge stations should be utilized at these locations. This study utilized satellite precipitation observation data to facilitate rain gauge network optimization. The deviations between ground-based precipitation data and three types of satellite precipitation observation data were used for entropy estimation. The rain gauge network in the Oujiang River Basin of China was optimally designed according to the principle of maximum joint entropy. Two optimization schemes of culling and supplementing 40 existing sites and 35 virtual sites were explored. First, the optimization and ranking of the rain gauge station network showed good stability and consistency. In addition, the joint entropy of deviation was larger than that of ground-based precipitation data alone, leading to a higher degree of discrimination between rain gauge stations and enabling the use of deviation data instead of ground-based precipitation data to assist network optimization, with more reasonable and interpretable results

Gefitinib metabolism-related lncRNAs for the prediction of prognosis, tumor microenvironment and drug sensitivity in lung adenocarcinoma

Abstract The complete compound of gefitinib is effective in the treatment of lung adenocarcinoma. However, the effect on lung adenocarcinoma (LUAD) during its catabolism has not yet been elucidated. We carried out this study to examine the predictive value of gefitinib metabolism-related long noncoding RNAs (GMLncs) in LUAD patients. To filter GMLncs and create a prognostic model, we employed Pearson correlation, Lasso, univariate Cox, and multivariate Cox analysis. We combined risk scores and clinical features to create nomograms for better application in clinical settings. According to the constructed prognostic model, we performed GO/KEGG and GSEA enrichment analysis, tumor immune microenvironment analysis, immune evasion and immunotherapy analysis, somatic cell mutation analysis, drug sensitivity analysis, IMvigor210 immunotherapy validation, stem cell index analysis and real-time quantitative PCR (RT-qPCR) analysis. We built a predictive model with 9 GMLncs, which showed good predictive performance in validation and training sets. The calibration curve demonstrated excellent agreement between the expected and observed survival rates, for which the predictive performance was better than that of the nomogram without a risk score. The metabolism of gefitinib is related to the cytochrome P450 pathway and lipid metabolism pathway, and may be one of the causes of gefitinib resistance, according to analyses from the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Immunological evasion and immunotherapy analysis revealed that the likelihood of immune evasion increased with risk score. Tumor microenvironment analysis found most immune cells at higher concentrations in the low-risk group. Drug sensitivity analysis found 23 sensitive drugs. Twenty-one of these drugs exhibited heightened sensitivity in the high-risk group. RT-qPCR analysis validated the characteristics of 9 GMlncs. The predictive model and nomogram that we constructed have good application value in evaluating the prognosis of patients and guiding clinical treatment

Predictive value of peripheral blood leukocytes-based methylation of Long non-coding RNA MALAT1 and H19 in the chemotherapy effect and prognosis of gastric cancer

Background: The predictive value of the methylation of Long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and H19 promoters in peripheral blood leukocytes as a non-invasive biomarker for the chemotherapy effect and prognosis gastric cancer (GC) is unclear. Methods: The DNA methylation of H19 and MALAT1 between chemotherapy-sensitive and non-sensitive groups and between groups with better and worse survival of GC was compared using regression analyses. Several predictive nomograms were constructed. The genetic alteration of MALAT1 and H19 and the association between gene expression and immune status in GC were also investigated using bioinformatics analysis. Results: Higher genetic methylations in peripheral blood were noticed in GC groups with poorer survival. The constructed nomograms presented strong predictive values for the chemotherapy effect and 3-year survival of disease-free survival, progression-free survival, and overall survival, with the area under the curve as 0.838, 0.838, 0.912, and 0.925, respectively. Significant correlations between MALAT1 or H19 expression and marker genes of immune checkpoints and immune pathways were noticed. The high infiltration of macrophages in H19-high and low infiltration of CD8+ T cells in MALAT1-high groups were associated with worse survival of GC. Conclusions: MALAT1 and H19 have the potential to predict the chemotherapy response and clinical outcomes of GC

Comparison of Soluble Dietary Fibers Extracted from Ten Traditional Legumes: Physicochemical Properties and Biological Functions

Soluble dietary fibers (SDFs) exist as the major bioactive components in legumes, which exhibit various biological functions. To improve the potential applications of legume SDFs as healthy value-added products in the functional food industry, the physicochemical properties and biological functions of SDFs from ten selected traditional legumes, including mung bean, adzuki bean, red bean, red sword bean, black bean, red kidney bean, speckled kidney bean, common bean, white hyacinth bean, and pea, were studied and compared. Results showed that the physicochemical properties of SDFs varied in different species of legumes. All legume SDFs almost consisted of complex polysaccharides, which were rich in pectic-polysaccharides, e.g., homogalacturonan (HG) and rhamnogalacturonan I (RG I) domains. In addition, hemicelluloses, such as arabinoxylan, xyloglucan, and galactomannan, existed in almost all legume SDFs, and a large number of galactomannans existed in SDFs from black beans. Furthermore, all legume SDFs exhibited potential antioxidant, antiglycation, immunostimulatory, and prebiotic effects, and their biological functions differed relative to their chemical structures. The findings can help reveal the physicochemical and biological properties of different legume SDFs, which can also provide some insights into the further development of legume SDFs as functional food ingredients

More effective strategies are required to strengthen public awareness of COVID-19: evidence from Google Trends

Background: The outbreak of coronavirus disease 2019 (COVID-19) has posed stress on the health and well-being of both Chinese people and the public worldwide. Global public interest in this new issue largely reflects people's attention to COVID-19 and their willingness to take precautionary actions. This study aimed to examine global public awareness of COVID-19 using Google Trends. Methods: Using Google Trends, we retrieved public query data for terms of "2019-nCoV + SARS-CoV-2 + novel coronavirus + new coronavirus + COVID-19 + Corona Virus Disease 2019" between the 31st December 2019 and the 24th February 2020 in six major English-speaking countries, including the USA, the UK, Canada, Ireland, Australia, and New Zealand. Dynamic series analysis demonstrates the overall change trend of relative search volume (RSV) for the topic on COVID-19. We compared the top-ranking related queries and sub-regions distribution of RSV about COVID-19 across different countries. The correlation between daily search volumes on the topic related to COVID-19 and the daily number of people infected with SARS-CoV-2 was analyzed. Results: The overall search trend of RSV regarding COVID-19 increased during the early period of observing time and reached the first apex on 31st January 2020. A shorter response time and a longer duration of public attention to COVID-19 was observed in public from the USA, the UK, Australia, and Canada, than that in Ireland and New Zealand. A slightly positive correlation between daily RSV about COVID-19 and the daily number of confirmed cases was observed (P

Preparation and Characterization of Highly Ordered Mercapto-Modified Bridged Silsesquioxane for Removing Ammonia-Nitrogen from Water

In acidic conditions, mesoporous molecular sieves SBA-15 and SBA-15-SH were synthesized. Structural characterization was carried out by powder X-ray diffraction (XRD), Fourier Transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), 13C CP MAS-NMR, 29Si CP MAS-NMR and nitrogen adsorption&ndash;desorption (BET). The results showed that in SBA-15-SH, the direct synthesis method made the absorption peak intensity weaker than that of SBA-15, while the post-grafted peak intensity did not change. Their spectra were different due to the C-H stretching bands of Si-O-Si and propyl groups. But their structure was still evenly distributed and was still hexangular mesoporous structure. Their pore size increased, and the H-SBA-15-SH had larger pore size. The adsorption of ammonia-nitrogen by molecular sieve was affected by the relative pressure and the concentration of ammonia-nitrogen, in which the adsorption capacity of G-SBA-15-SH was the largest and the adsorption capacity of SBA-15 was the smallest