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Public Map Service Platforms (PMSPs) aggregate and disseminate the earth observation data. Leveraging spatiotemporal preference patterns derived from browsing targets within complex virtual trajectories on PMSPs aids in constructing user-profiles and comprehending their intentions. However, complex virtual trajectories, characterized by numerous trajectory points and overlapping pyramidal spatial structures, introduce inefficiencies and inaccuracies during browsing target extraction. To mitigate this, we propose an Optimized Spatial Structure Segmentation (OSSS) method that divides complex virtual trajectories into sub-trajectories with simplified spatial structures, enhancing the efficiency of browsing target extraction. Spatiotemporal reconstruction of these sub-trajectories establishes sequences of browsing targets, revealing patterns of interest transitions. Moreover, recognizing the spatial uncertainty inherent in complex virtual trajectories, which results in imprecise matching between browsing targets and spatial features, we introduce a spatial co-occurrence semantic modeling approach. This involves constructing a POI semantic space and introducing a semantic similarity matching method to reduce spatial uncertainty and refine the accuracy of mining spatiotemporal preference patterns. We evaluate these methods using real-world data from Tianditu. Results demonstrate that the OSSS improves extraction efficiency by 3.45 times and accuracy by 18.84%. Additionally, the semantic similarity approach combined with spatial co-occurrence effectively mitigates spatial uncertainty. This research contributes to advancing the intelligence of PMSPs.

An imbalance in urban development in China has become a contradiction. Points of Interest (POIs) serve as representations of the spatial distribution of urban functions. Analyzing POI spatial co-occurrence patterns can reveal the agglomeration patterns of urban functions across cities at different levels, providing insights into imbalances in urban development. Using POI data from 297 cities in China, the Word2vec model was employed to model the POI spatial co-occurrence patterns, allowing for the quantification of fine-granular urban functionality. Subsequently, the cities were clustered into five tiers representing different levels of development. An urban hierarchical disparity index and graph were introduced to examine variations in urban functions across different tiers. A significant correlation between POI spatial co-occurrence patterns and the GDP of cities at different levels was demonstrated. This study revealed a notable polarization trend characterized by the development of top-tier cities and lagging tail-end cities. Top-tier cities exhibit advantages in terms of their commercial environments, such as international banks, companies, and transportation facilities. Conversely, tail-end cities face deficiencies in urban infrastructure. It is crucial to coordinate resource allocation and establish sustainable development strategies that foster mutual support between the top-tier and tail-end cities.

Over the last decade, event prediction has drawn attention from both academic and industry communities, resulting in a substantial volume of scientific papers published in a wide range of journals by scholars from different countries and disciplines. However, thus far, a comprehensive and systematic survey of recent literature has been lacking to quantitatively capture the research progress as well as emerging trends in the event prediction field. Aiming at addressing this gap, we employed CiteSpace software to analyze and visualize data retrieved from the Web of Science (WoS) database, including authors, documents, research institutions, and keywords, based on which the author co-citation network, document co-citation network, collaborative institution network, and keyword co-occurrence network were constructed. Through analyzing the aforementioned networks, we identified areas of active research, influential literature, collaborations at the national level, interdisciplinary patterns, and emerging trends by identifying the central nodes and the nodes with strong citation bursts. It reveals that sensor data has been widely used for predicting weather events and meteorological events (e.g., monitoring sea surface temperature and weather sensor data for predicting El Nino). The real-time and multivariable monitoring features of sensor data enable it to be a reliable source for predicting multiple types of events. Our work offers not only a comprehensive survey of the existing studies but also insights into the development trends within the event prediction field. These findings will assist researchers in conducting further research in this area and draw a large readership among academia and industrial communities who are engaged in event prediction research.

The Rubinstein alternating-offers bargaining game is reconsidered, where players show fairness concerns and their fairness references are characterized by the Nash bargaining solution. The objective of this paper is to explore the impact of fairness concerns in the alternating-offer bargaining game. Alternating-offer bargaining with fairness concerns is developed. We construct a subgame perfect equilibrium and show its uniqueness. Then, it is shown that players’ payoffs in the subgame perfect equilibrium are positively related to their own fairness concern coefficient and bargaining power and negatively to the opponents’ fairness concern coefficient. Moreover, it is shown that the limited equilibrium partition depends on the ratio of discount rates of the two players when the time lapse between two offers goes to zero. Finally, the proposed model is applied to the bilateral monopoly market of professional basketball players, and some properties of equilibrium price are shown. Our result provides the implication that players should carefully weigh their own fairness concerns, bargaining power and fairness concerns of their opponents, and then make proposals, rather than simply follow the suggestion that the proposal at the current stage is higher than that at the past stages.

With the rapid development of nanozymes research, many carbon nanotubes (CNTs) and their derivatives have been reported as mimics of peroxidases. Despite this, their low peroxidase-like activity severely limited their ability to be applied. In this study, multi-walled CNTs were mixed with oxidizing agents to produce oxygenated carbon nanotubes (O-CNTs) that are rich in oxidizing functional groups. After the simple and green oxidation treatment, the CNTs' peroxidase-like activity was significantly improved. Intriguingly, the degree of oxidation affected the content of oxygen-containing functional groups, which gave O-CNTs different peroxidase-like functions. Since O-CNTs-7 (0.5 g CNTs treated with 3.5 g NaClO3) exhibited the best peroxidase-like activity, its steady-state dynamics and catalytic mechanism were analyzed. It is found that that hydroxyl radical may be the key oxygen active species in the reaction process. Furthermore, on the basis that ascorbic acid can inhibit the oxidation reaction of TMB, O-CNTs-7 was successfully applied to assay the total antioxidant capacity of fresh juice, beverages, and vitamin C tablets. It not only demonstrated how simple oxidation treatments can enhance the peroxidase-like activity of carbon-based nanozymes, but also demonstrated how these nanozymes can be applied to the design of biosensors with colorimetric analysis.

Objectives: Biofilms associated with implantable medical devices and wounds are clinically relevant, often requiring repeated use of antibiotics without success. A search for non-antibiotic antimicrobial and antibiofilm solutions is warranted, in line with antimicrobial stewardship. Our study aimed to evaluate the broad-spectrum antimicrobial efficacy of tetrasodium EDTA, ethanol and chlorhexidine hydrochloride (HCl) alone and in combination against clinically relevant planktonic and biofilm cells of bacterial and fungal pathogens. Methods: MICs and MBCs were determined for tetrasodium EDTA, ethanol and chlorhexidine HCl against planktonic cells of test pathogens. The MBEC Assay® biofilm inoculator device was used to evaluate the biofilm eradication ability of test antimicrobials alone and in combination against clinically relevant pathogens. The checkerboard microbroth dilution assay was performed to analyze the synergism between test antimicrobials. Results: Against planktonic cells, the combination of tetrasodium EDTA with ethanol or chlorhexidine HCl resulted in synergistic to indifferent activity, with no antagonism observed. Against mature biofilms, all combinations were synergistic. The MBEC of each test antimicrobial was decreased from 4- to -64-fold when used in combination as compared to when agents were used alone. We optimised the concentration of antimicrobials to achieve rapid eradication of pre-formed biofilms. A triple combination of 3% tetrasodium EDTA, 20% ethanol and 2.5 μg/mL chlorhexidine HCl completely eradicated 48-h-old biofilms of all test strains within 2 h. Conclusion: All three antimicrobial agents can be used together for prevention and treatment of biofilms and biofilm-related infections. The observed in vitro efficacy should be tested further through in vivo and clinical studies.

We study the propagation characteristics (spectral intensity and degree of coherence) of a new type of Lorentz non-uniformly correlated (LNUC) beam based on the extended Huygens–Fresnel principle and the spatial power spectrum of oceanic turbulence. The effects of the oceanic turbulence parameters and initial beam parameters on the evolution propagation characteristics of LNUC beams are studied in detail by numerical simulation. The results indicate that such beams exhibit self-focusing propagation features in both free space and oceanic turbulence. Decreasing the dissipation rate of kinetic energy per unit mass of fluid and the Kolmogorov inner scale, or increasing the relative strength of temperature to salinity undulations and the dissipation rate of mean-square temperature of the turbulent ocean tends to increase the negative effects on the beams. Furthermore, we propose a strategy of increasing the beam width and decreasing the coherence length, to reduce the negative effects of the turbulence.

This preclinical study in the gnotobiotic (Gn) pig model of human rotavirus (HRV) infection and disease evaluates the effect of probiotic Lactobacillus rhamnosus GG (LGG) as a mucosal adjuvant on the immunogenicity and cross-protective efficacy of the Lanzhou live oral trivalent (G2, G3, G4) vaccine (TLV, aka LLR3). Gn pigs were immunized with three doses of TLV with or without concurrent administration of nine doses of LGG around the time of the first dose of the TLV vaccination, and were challenged orally with the virulent heterotypic Wa G1P[8] HRV. Three doses of TLV were highly immunogenic and conferred partial protection against the heterotypic HRV infection. LGG significantly enhanced the intestinal and systemic immune responses and improved the effectiveness of protection against the heterotypic HRV challenge-induced diarrhea and virus shedding. In conclusion, we demonstrated the immune-stimulating effects of probiotic LGG as a vaccine adjuvant and generated detailed knowledge regarding the cross-reactive and type-specific antibody and effector B and T cell immune responses induced by the TLV. Due to the low cost, ease of distribution and administration, and favorable safety profiles, LGG as an adjuvant has the potential to play a critical role in improving rotavirus vaccine efficacy and making the vaccines more cost-effective.

ABSTRACT Central venous access devices (CVADs) are an essential component of modern health care. However, their prolonged use commonly results in microbial colonization, which carries the potential risk of hospital-acquired bloodstream infections. These infections complicate the treatment of already sick individuals and cost the existing health care systems around the world millions of dollars. The microbes that colonize CVADs typically form multicellular biofilms that are difficult to dislodge and are resistant to antimicrobial treatments. Clinicians are searching for better ways to extend the working life span of implanted CVADs, by preventing colonization and reducing the risk of bloodstream infections. In this study, we analyzed 210 bacterial and fungal isolates from colonized CVADs or human bloodstream infections from two hospitals geographically separated in the east and west of Canada and screened the isolates for biofilm formation in vitro. Twenty isolates, representing 12 common, biofilm-forming species, were exposed to 4% tetrasodium EDTA, an antimicrobial lock solution that was recently approved in Canada for use as a medical device. The EDTA solution was effective at eradicating surface-attached biofilms from each microbial species, indicating that it could likely be used to prevent biofilm growth within CVADs and to eliminate established biofilms. This new lock solution fits with antibiotic stewardship programs worldwide by sparing the use of important antibiotic agents, targeting prevention rather than the expensive treatment of hospital-acquired infections. IMPORTANCE The colonization of catheters by microorganisms often precludes their long-term use, which can be a problem for human patients that have few body sites available for new catheters. The colonizing organisms often form biofilms, and increasingly these organisms are resistant to multiple antibiotics, making them difficult to treat. In this article, we have taken microorganisms that are associated with biofilm formation in catheters from two Canadian hospitals and tested them with tetrasodium EDTA, a new antimicrobial catheter lock solution. Tetrasodium EDTA was effective at eliminating Gram-positive, Gram-negative, and fungal species and represents a promising alternative to antibiotic treatment with less chance of the organisms developing resistance. We expect that our results will be of interest to researchers and clinicians and will lead to improved patient care.

Vaccine development and pathogenesis studies for human enterovirus 71 are limited by a lack of suitable animal models. Here, we report the development of a novel neonatal gnotobiotic pig model using the non-pig-adapted neurovirulent human enterovirus 71 strain BJ110, which has a C4 genotype. Porcine small intestinal epithelial cells, peripheral blood mononuclear cells and neural cells were infected in vitro. Oral and combined oral–nasal infection of 5-day-old neonatal gnotobiotic pigs with 5×108 fluorescence forming units (FFU) resulted in shedding up to 18 days post-infection, with viral titers in rectal swab samples peaking at 2.22×108 viral RNA copies/mL. Viral capsid proteins were detected in enterocytes within the small intestines on post-infection days (PIDs) 7 and 14. Additionally, viral RNA was detected in intestinal and extra-intestinal tissues, including the central nervous system, the lung and cardiac muscle. The infected neonatal gnotobiotic pigs developed fever, forelimb weakness, rapid breathing and some hand, foot and mouth disease symptoms. Flow cytometry analysis revealed increased frequencies of both CD4+ and CD8+ IFN-γ-producing T cells in the brain and the blood on PID 14, but reduced frequencies were observed in the lung. Furthermore, high titers of serum virus-neutralizing antibodies were generated in both orally and combined oral–nasally infected pigs on PIDs 7, 14, 21 and 28. Together, these results demonstrate that neonatal gnotobiotic pigs represent a novel animal model for evaluating vaccines for human enterovirus 71 and for understanding the pathogenesis of this virus and the associated immune responses.

As essential equipment in rotating machinery, the fault diagnosis technology of rolling bearings has achieved great success. However, it still suffers from limitations in terms of generalization and noise resistance performance when operating under complex conditions. To accurately identify the fault types of rolling bearings under different loads and nosy environments, a novel intelligent fault diagnosis method is proposed. Firstly, the utilization of dilated convolution expands the network's receptive field, thereby effectively enhancing the scope of fault extraction. Then, by incorporating the Efficient Channel Attention (ECA) in different convolutional layers, the extracted features are adaptively recognized, highlighting important representation information and improving fault diagnosis performance. Finally, the proposed network is utilized for rolling bearing fault diagnosis under diverse operating and noise conditions, and its efficacy is evaluated on various datasets. The experimental results demonstrate that the proposed method exhibits good generalization performance and strong robustness, compared with other methods. [ABSTRACT FROM AUTHOR]