The process of information fusion needs to deal with a large number of uncertain information with multi-source, heterogeneity, inaccuracy, unreliability, and incompleteness. In practical engineering ...applications, Dempster–Shafer evidence theory is widely used in multi-source information fusion owing to its effectiveness in data fusion. Information sources have an important impact on multi-source information fusion in an environment with the characteristics of complex, unstable, uncertain, and incomplete. To address multi-source information fusion problem, this paper considers the situation of uncertain information modeling from the closed-world to the open-world assumption and studies the generation of basic probability assignment with incomplete information. A new method is proposed to generate the generalized basic probability assignment (GBPA) based on the triangular fuzzy number model under the open-world assumption. First, the maximum, minimum, and mean values for the triangular membership function of each attribute in classification problem can be obtained to construct a triangular fuzzy number representation model. Then, by calculating the length of the intersection points between the sample and the triangular fuzzy number model, a GBPA set with an assignment for the empty set can be determined. The proposed method can not only be used in different complex environments simply and flexibly, but also have less information loss in information processing. Finally, a series of comprehensive experiments basing on the UCI data sets is used to verify the rationality and superiority of the proposed method.
Poria cocos polysaccharide (PCP) is the major active ingredients of P. cocos and possesses various pharmacological effects, including anti-oxidative and anti-apoptosis effects and activity against ...cancer. This study investigated the immunomodulatory mechanism by which PCP acts on RAW 264.7 macrophages and LLC tumors in mice.
The concentrations of nitric oxide, and Th1, Th2, and Th17 cytokines were examined by Griess reaction and using a bead-based cytokine assessment kit. qRT-PCR and western blotting were used to investigate relevant signaling molecule expression.
Levels of nitric oxide, IL-2, IL-6, IL-17 A, TNF, and IFN-γ were increased by PCP while levels of IL-4 and IL-10 were unaffected. The addition of TAK-242 (TLR4 inhibitor) or assessment in C57BL/10ScNJ (TLR4-deficient) mice markedly reduced this effect. In C57BL/10 J (TLR4+/+wild-type) mice, the indices of organ immune activity were all elevated, and oral PCP delivery resulted in a significant reduction in tumor volume over a 25 day period. Relative to controls, TLR4, MyD88, TRAF-6, p-NF-κB and p-c-JUN expression significantly increased, while TRAM expression did not change. Nevertheless, there was no PCP-dependent activation of MyD88, TRAF-6, TRAM, p-NF-κB or p-c-JUN in TLR4-deficient mice.
These results support the concept that PCP may exhibit immunomodulatory activity through TLR4/TRAF6/NF-κB signaling both in vitro and in vivo.
With the success of immune checkpoint inhibitors (ICIs), significant progress has been made in the field of cancer immunotherapy. Despite the long-lasting outcomes in responders, the majority of ...patients with cancer still do not benefit from this revolutionary therapy. Increasing evidence suggests that one of the major barriers limiting the efficacy of immunotherapy seems to coalesce with the hypoxic tumor microenvironment (TME), which is an intrinsic property of all solid tumors. In addition to its impact on shaping tumor invasion and metastasis, the hypoxic TME plays an essential role in inducing immune suppression and resistance though fostering diverse changes in stromal cell biology. Therefore, targeting hypoxia may provide a means to enhance the efficacy of immunotherapy. In this review, the potential impact of hypoxia within the TME, in terms of key immune cell populations, and the contribution to immune suppression are discussed. In addition, we outline how hypoxia can be manipulated to tailor the immune response and provide a promising combinational therapeutic strategy to improve immunotherapy.
The cloud-top height (CTH) product derived from passive satellite instrument measurements is often used to make climate data records (CDR). CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder ...Satellite Observations) provides CTH parameters with high accuracy, but with limited temporal-spatial resolution. Recently, the Advanced Himawari Imager (AHI) onboard Japanese Himawari-8/-9, provides high temporal (every 10 min) and high spatial (2 km at nadir) resolution measurements with 16 spectral bands. This paper reports on a study to derive the CTH from combined AHI and CALIPSO using advanced machine learning (ML) algorithms with better accuracy than that from the traditional physical (TRA) algorithms. We find significant CTH improvements (1.54–2.72 km for mean absolute error, MAE) from four different machine learning algorithms (original MAE from TRA method is about 3.24 km based on CALIPSO data validation), particularly in high and optically thin clouds. In addition, we also develop a joint algorithm to combine optimal machine learning and traditional physical (TRA) algorithms of CTH to further reduce MAE to 1.53 km and enhance the layered accuracy (CTH < 18 km). While the ML-based algorithm improves CTH retrieval over the TRA algorithm, the lower or higher clouds still exhibit relatively large uncertainty. Combining both methods provides the better CTH than either alone. The combined approach could be used to process data from advanced geostationary imagers for climate and weather applications.
•A novel machine learning algorithm to retrieve cloud top height using Himawari-8•Significant improvements in cloud top height product from machine learning algorithm•A joint algorithm further reduces uncertainty in cloud top height.
We present a graph-theoretical approach to data clustering, which combines the creation of a graph from the data with Markov Stability, a multiscale community detection framework. We show how the ...multiscale capabilities of the method allow the estimation of the number of clusters, as well as alleviating the sensitivity to the parameters in graph construction. We use both synthetic and benchmark real datasets to compare and evaluate several graph construction methods and clustering algorithms, and show that multiscale graph-based clustering achieves improved performance compared to popular clustering methods without the need to set externally the number of clusters.
The reactivation of landslides has always been a prominent problem that has endangered town construction and people’s safety worldwide. At about 8 a.m. on July 12, 2018, on a mountain near the ...Bailong River in Nanyu Township, Zhouqu County, Gansu Province, China, a landslide collapse event occurred. About 10,000 m
3
of sloped material slid into the Bailong River, with the largest stone reaching 3 m
3
. As a result, a large number of houses were flooded. Highways and bridges were destroyed. Using field investigations, unmanned aerial vehicle (UAV) photography, InSAR traces, historical records, and multiple remote sensing images, we extracted the landslide’s geometry and geomorphic parameters to quantify the characteristics of the Jiangdingya landslide. Based on high-resolution topographic data collected before and after the landslide, the change in the geomorphological factors, geomorphologic stability, and detection of the precursory motion before the landslide failure were analyzed to fully investigate the temporal geomorphological changes. Synthesizing the above research, we discuss the causes of landslide reactivation. The Jiangdingya landslide is a typical ancient landslide formed by the coupling of internal and external dynamics. Rainfall, seismic fault zone activity, human activities, and river erosion were the main causes of this reactivation event.
•Subsidence caused by coal mining increases the likelihood of landslide occurrences.•Landslides occur in response to the spread of slow subsidence.•Subsidence curves can be adequately fitted with ...logistic regression.•The frequency ratio of landslides and fissures increases with subsidence.
Surface subsidence caused by underground coal mining affects the hillslope stability conditions. However, few studies have focused on the coupling relationship between slow surface subsidence and landslide occurrences. A detailed landslide and fissure inventory in a coal mining area in Shaanxi Province, China, was produced based on interpretation of multitemporal satellite images and unmanned aerial vehicle (UAV) surveys. We used the interferometric synthetic aperture radar (InSAR) technique and landslide and fissure spatiotemporal statistics to investigate the spreading process of the slow subsidence caused by underground mining and examined its impact on the occurrence of shallow landslides. The InSAR results indicate that the actual extent of the subsidence zone is larger than the range of underground mining, which formed a subsidence basin along the coal mining panels. The subsidence curves go through initial, accelerative, and slow subsidence stages and characterized by S-shaped, which can be adequately fitted with logistic regression. Moreover, subsidence does not cease after the end of coal exploitation. Logistic models predicted that the duration of residual subsidence reached about 2–3 years. Subsidence significantly increased the likelihood of landslide occurrences. The spatial pattern of landslides is associated with the actual coal mining. We also investigated the clustering phenomenon of landslides and fissures under the impacts of subsidence. The frequency ratio of landslides and fissures increased with the cumulative subsidence. Finally, we propose a schematic view for landslides caused by coal mining and precipitation. This study will be helpful for elucidating the spatial–temporal evolution of slow subsidence and its impact on loess landslides in coal mining area.
There is growing evidence that allergic rhinitis (AR) is associated with indoor environmental factors, but their role in childhood AR during early life remains unclear.
To investigate the association ...of preconceptional, prenatal, early postnatal, and current exposure to home environmental factors with childhood AR, and to further explore whether this association can be interacted by outdoor air pollution and temperature.
A retrospective cohort study of 8689 preschool children was conducted during 2019–2020 in Changsha, China. A standard questionnaire was used to collect data on each family’s health outcomes and home environments. We considered home environmental exposures during one year before conception, pregnancy, first year of life, and past year. Associations of indoor air pollution and allergens with AR were assessed by multiple logistic regression models.
Pre-birth exposure to indoor air pollution emitted by new furniture or redecoration and dampness related allergen derived from mold/damp stains and mold/damp clothes or bedding during 1 year before conception and pregnancy was significantly associated with increased AR, with adjusted ORs (95% CI) ranging from 1.35 (1.05–1.75) to 1.87 (1.55–2.27). Childhood AR was also significantly related with post-birth exposure to dampness related indoor allergen including mold/damp stains and mold/damp clothes or bedding in first year and past year and pollen allergen including total and nonflowing plants in past year, with a range of ORs (95% CI) from 1.20 (1.01–1.42) to 1.79 (1.42–2.27). We identified that pre-birth, particularly in utero exposure to both indoor air pollution from renovation and dampness related allergens, played a key role in AR development compared to post-birth exposures, and accumulative effect was observed with the highest risk of AR. High exposure to traffic-related air pollution (TRAP) including outdoor PM2.5, NO2, CO, and O3, as well as living near traffic road not only significantly increased adverse effect of home environmental factors but also decreased protective effect of household dogs on childhood AR. Early life exposure to low temperature in pregnancy and high temperature in first year significantly increased AR risk of home environmental exposure. Sensitivity analysis indicated that some sub-groups were more susceptible to AR risk of home environmental exposure.
Our study suggests that pre-birth exposure to home environmental factors played an important role in AR development and this effect can be interacted by TRAP and temperature, which supports a hypothesis of “(pre)fetal origin of childhood AR”.
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•Pre-birth home air pollution and allergen were related with allergic rhinitis (AR).•Post-birth home mold/dampness and plant allergens exposure increased AR risk.•Pre-birth is a critical window for AR risk of home environmental exposure.•Traffic-related air pollution increased AR risk of indoor environmental exposure.•Low and high temperature interacted with indoor environment on AR in early life.
To mitigate urban drainage network pressures and seek sustainable solutions, novel tools like graph theory are presently being studied. This paper presents a systematic literature review of ...graph-based approaches through an intensive content analysis based on 144 published papers. Comparisons are drawn between water distribution networks and urban drainage networks in terms of convergence and divergence, revealing more divergence in network topological characteristics but more convergence in functional features. The findings provide convincing evidence for applications in UDNs, despite limited numbers and depth. Subsequently, a comparison between graph-based and hydraulic-based approaches is shown, demonstrating distinct advantages of graph-based methods in cases with limited data and time constraints. Based on these findings, the paper suggests several potential directions, including the improvement of parameter calculation formulas, the definition of parameter mathematical ranges and the popularization of recommended values. Finally, the paper examines its own shortcomings.
Identification and monitoring of unstable slopes across wide regions using Synthetic Aperture Radar Interferometry (InSAR) can further help to prevent and mitigate geological hazards. However, the ...low spatial density of measurement points (MPs) extracted using the traditional time-series InSAR method in topographically complex mountains and vegetation-covered slopes makes the final result unreliable. In this study, a method of time-series InSAR analysis using single- and multi-look phases were adopted to solve this problem, which exploited single- and multi-look phases to increase the number of MPs in the natural environment. Archived ascending and descending Sentinel-1 datasets covering Zhouqu County were processed. The results revealed that nine landslides could be quickly identified from the average phase rate maps using the Stacking method. Then, the time-series InSAR analysis with single- and multi-look phases could be used to effectively monitor the deformation of these landslides and to quantitatively analyze the magnitude and dynamic evolution of the deformation in various parts of the landslides. The reliability of the InSAR results was further verified by field investigations and Unmanned Aerial Vehicle (UAV) surveys. In addition, the precursory movements and causative factors of the recent Yahuokou landslide were analyzed in detail, and the application of the time-series InSAR method in landslide investigations was discussed and summarized. Therefore, this study has practical significance for early warning of landslides and risk mitigation.
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