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Small farms are the mainstay of maize production in China. Its productivity is relatively low despite large farm inputs and the associated environmental footprints. Here, we studied public–private partnership (PPP) model for sustainable intensification of maize production to achieve co‐benefits of food security and environmental sustainability. The PPP model enabled the development of an effective partnership by bringing complementary skills, knowledge, proprietary products and technologies, and resources of public research community and private enterprises to create a new, operational maize farming system in China. We conducted on‐farm research with farmer participation in four major maize‐growing regions spanning temperate to sub‐tropical zones in China for 2 years. The PPP model achieved 78.7% of maize yield potential compared with 61.8% realized in smallholder farm (SHF) (11.0 Mg ha−1 vs. 8.6 Mg ha−1). Overall, environmental externalities of PPP were up to 32.7% lower than that of SHF, depending on the region studied. PPP significantly reduced reactive nitrogen losses by 31.3%–35.5% compared with SHF in both years. There was no significant difference between PPP and SHF for greenhouse gas emission in 2018, but it was significantly lower in PPP (19%) compared to SHF in 2019. Similarly, PPP significantly reduced soil acidification potential (by 10.1%–42.2%) and eutrophication of waterbodies (21.5%) in comparison to SHF. Overall, the net ecosystem economic budget increased 277 USD ha−1 with PPP. The PPP model provides new insights into improving food security and ecosystem and economic budget. As a logical progression to our research, future work should focus on (a) the reasons for the persistence of inter‐regional yield gap in PPP model and (b) to gain a better understanding of socioeconomic drivers critical for successful PPP in different maize‐growing regions.

Robotic vision servo technology has been developed to control a robotic arm to a specified position with the guidance of a vision sensor. However, for tasks that require high precision control, guidance by vision alone is not sufficient. We need to use compliance control method based on contact force information to accomplish fine-grained operations. In the paper, firstly, a geometric model-based joint angle selection criterion for force parameter identification is proposed, which can improve the stability and accuracy of force sensor parameter identification. Secondly, due to the unstable and too small values of the collected torque information, and in order to omit the tedious force analysis, as well as the costly trial-and-error process, we divide the shaft-hole assembly problem into two parts. One is to combine the point cloud normal vector estimation and posture transformation to achieve the control of the end point position of the axis body constant, while adjusting the posture of the shaft body by speed control; and the other is to use the force feedback damping control to complete the assembly tasks when the shaft body direction is consistent with the hole axis direction. After these two parts of operation, the decoupling of posture and position can be realized, shaft hole assembly at any posture of the workpiece (hole) can be completed. The effectiveness and feasibility of the algorithm is verified by conducting experiments on the UR5 robot.

Dimethyl phthalate (DMP), a phthalate ester (PAE), is a ubiquitous and organic pollutant. In this study, the toxicity of DMP to Escherichia coli K12 and its underlying mechanism were investigated. The results showed that DMP inhibited the growth of E. coli K12 and induced cell inactivation and/or death. DMP caused serious damage to the cell membrane of E. coli K12, and the damage increased with higher DMP concentrations. DMP exposure disrupted cell membranes, as evidenced by dose-dependent variations of cell structures, surface properties, and membrane compositions. Increases in the malondialdehyde (MDA) content indicated an increase in oxidative stress induced by DMP in E. coli K12. The activity of succinic dehydrogenase (SDH) was changed by DMP, which could affect energy metabolism in the membrane of E. coli K12. The expression levels of OmpA and OmpX were increased, and the expression levels of OmpF and OmpW were decreased, in E. coli K12 exposed to DMP. The toxicities of DMP to E. coli K12 could be ascribed to membrane disruption and oxidative stress-induced cell inactivation and/or death. The outcomes will shed new light on the assessment of the ecological effects of DMP.

Dimethyl phthalate (DMP) is a ubiquitous pollutant that is very harmful to organisms due to its mutagenicity, teratogenicity and carcinogenicity. Pseudomonas fluorescens (P. fluorescens) is one of the most important bacteria in the environment. In this study, the response of P. fluorescens to DMP was investigated. It was found that DMP greatly inhibited the growth and glucose utilization of P. fluorescens when the concentration of DMP was ranged from 20 to 40 mg/l. The surface hydrophobicity and membrane permeability of P. fluorescens were also increased by DMP. DMP could lead to the deformations of cell membrane and the mis-opening of membrane channels. RNA-Seq and RT-qPCR results showed that the expression of some genes in P. fluorescens were altered, including the genes involved in energy metabolism, ATP-binding cassette (ABC) transporting and two-component systems. Additionally, the productions of lactic acid and pyruvic acid were reduced and the activity of hexokinase was inhibited in P. fluorescens by DMP. Clearly, the results suggested that DMP contamination could alter the biological function of P. fluorescens in the environment.

Rice seedling blight, caused by Fusarium oxysporum, significantly affects global rice production levels. Fluoro-substituted benzothiadiazole derivatives (FBT) and chitosan oligosaccharide (COS) are elicitors that can enhance plant resistance to pathogen infection. However, there is a lack of information regarding FBT and COS used as elicitors in rice seedlings blight. Therefore, the aim of this study was to evaluate the effect of FBT and COS treatments on rice seedling blight and elucidate the molecular mechanisms of the two elicitors for inducing resistance using proteomic technique. Results indicated that FBT and COS significantly reduced the disease incidence and index, and relived the root growth inhibition caused by F. oxysporum (p < 0.05). Biochemical analyses demonstrated that these two elicitors effectively enhanced activities of defense enzymes. Moreover, the proteomic results of rice root tissues disclosed more differentially expressed proteins in diterpenoid biosynthesis pathway that were particularly stimulated by two elicitors compared to the other pathways studied, resulting in the accumulation of antimicrobial substance, momilactone. Findings of this study could provide sound theoretical basis for further applications of FBT and COS used as rice elicitors against seedling blight.

Rice seedling blight, caused by Fusarium oxysporum, significantly affects global rice production levels. Fluoro-substituted benzothiadiazole derivatives (FBT) and chitosan oligosaccharide (COS) are elicitors that can enhance plant resistance to pathogen infection. However, there is a lack of information regarding FBT and COS used as elicitors in rice seedlings blight. Therefore, the aim of this study was to evaluate the effect of FBT and COS treatments on rice seedling blight and elucidate the molecular mechanisms of the two elicitors for inducing resistance using proteomic technique. Results indicated that FBT and COS significantly reduced the disease incidence and index, and relived the root growth inhibition caused by F. oxysporum (p &lt, 0.05). Biochemical analyses demonstrated that these two elicitors effectively enhanced activities of defense enzymes. Moreover, the proteomic results of rice root tissues disclosed more differentially expressed proteins in diterpenoid biosynthesis pathway that were particularly stimulated by two elicitors compared to the other pathways studied, resulting in the accumulation of antimicrobial substance, momilactone. Findings of this study could provide sound theoretical basis for further applications of FBT and COS used as rice elicitors against seedling blight.

Accumulating clinical and experimental evidence has suggested that Helicobacter pylori (H. pylori) infection-associated gastric cancer (GC) is associated with high rates of mortality and serious health effects. The majority of patients succumb to H. pylori infection-associated GC due to metastasis. Mesenchymal stem cells (MSCs), which have multipotent differentiation potential, may be recruited into the tumor-associated stroma. MSCs are crucial components of the H. pylori infection-associated GC microenvironment, and may be critical for GC cell migration. In this study, an MSCs/H. pylori co-culture model was designed, and the effect of H. pylori-infected MSCs on the migration of GC cells was evaluated using a Transwell migration assay. H. pylori-infected MSC cytokine expression was evaluated using Luminex/ELISA. The expression of epithelial-mesenchymal transition (EMT) markers in the GC cells treated with supernatants from H. pylori-infected MSCs were detected by western blot analysis. The results demonstrated that the interaction between MSCs and H. pylori may induce GC cell migration, through secretion of a combination of cytokines that promote EMT in GC cells. The expression of phosphorylated forms of nuclear factor-κB (NF-κB) was observed to be increased in MSCs by H. pylori. Inhibition of NF-κB activation by pyrrolidine dithiocarbamate blocked the effects of H. pylori-infected MSCs on SGC-7901 human stomach adenocarcinoma cell migration. Overall, the results of the present study suggest that H. pylori-infected MSCs acquire a pro-inflammatory phenotype through secretion of a combination of multiple cytokines, a number of which are NF-κB-dependent. These cytokines enhance H. pylori infection-associated GC cell migration by promoting EMT in GC cells. The results of the present study provide novel evidence for the modulatory effect of MSCs in the tumor microenvironment and provide insight into the significance of stromal cell involvement in GC progression.

With the rapid development of social network analysis (SNA for short), people increasingly pay attention to segment micro-blog users in the SNAs. It's a new trend on classic marketing technique segmentation. In the case of micro-blog, it's useful to get a group of users with a common set of characters and learn what's on their mind. As is usually the case, the standard for measuring the category of the micro-blog users is multi-objective, i.e., the data is high dimensional. If you have a personal micro-blog account, it's easy enough to create the lists that might be most meaningful to you by using generic clustering algorithms. And if your business has Tens of millions of users, the near real-time requirement and the lack of efficient clustering algorithms to identify and distinguish them limits the power and scalability of this approach. To overcome these limitations, in this paper we introduce a novel distributed high dimensional data clustering algorithm based on Map-Reduce framework to distinguish the different communities from the entire social network, called CDGM-Clu. Extensive experiments on real and synthetic datasets show that the CDGM-Clu algorithm is significantly efficient and scalable, and useful for analyzing a large social network data.