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Preventing high concentrations of fine particulate (PM2.5) to realize the goal of sustainable development is becoming a challenge for rapidly urbanized cities. Increasing vehicle ...emission due to inefficient urban form is thought to be the main cause of traffic congestion and increased PM2.5 concentrations. Previous efforts attributing PM2.5 concentrations to urban forms are yet to reach consistent conclusions on practical environmental protection strategies. In this study, we considered urban compositions and their spatial configuration to propose a new measurement—urban configuration—and document the effects of urban configuration on PM2.5 concentrations. Using 330 Chinese cities as our sample, we found that the areas of two types of urban facilities, namely, residence and industry, are positively related to PM2.5 concentrations, and the area of public service facilities is negatively related to PM2.5 concentrations. Regarding the spatial configuration of different urban compositions, we documented that residence–industry accessibility is a key factor of PM2.5 concentrations and plays a more important role than the residence–commerce accessibility. We also compared the influence of two accessibility indices (distance- and gravity-based accessibilities) and further found that the effect of reducing the residence–industry distance is more remarkable than the effect of increasing residential or industrial area on reducing PM2.5 concentrations. Our results indicate that the key to reaching sustainable urban expansion is to synchronize urban constructions with spatial configuration optimization. For Chinese cities, a 7.52% increase in residence area requires at least 1% decrease in the average residence–industry distance to eliminate the incremental effects of newly constructed residential region on PM2.5 concentrations. This study casts new light on the relationship between urban configuration and PM2.5 concentration and provides decision makers practical and realistic approaches in realizing sustainable development goals.
Horizontal axis wind turbine (HAWT) often works under yaw due to the stochastic variation of wind direction. Yaw also can be used as one of control methods for load reduction and wake redirection of ...HAWT. Thus, the aerodynamic performance under yaw is very important to the design of HAWT. For further insight into the highly unsteady characteristics aerodynamics of HAWT under yaw, this paper investigates the unsteady variations of the aerodynamic performance of a small wind turbine under static yawed and yawing process with sliding grid method, as well as the there-dimensional effect on the unsteady characteristics, using unsteady Reynolds-averaged Navier–Stokes (URANS) simulations. The simulation results are validated with experimental data and blade element momentum (BEM) results. The comparisons show that the CFD results have better agreement with the experimental data than both BEM results. The wind turbine power decreases according to a cosine law with the increase of yaw angle. The torque under yaw shows lower frequency fluctuations than the non-yawed condition due to velocity component of rotation and the influence of spinner. Dynamic yawing causes larger fluctuate than static yaw, and the reason is analyzed. The aerodynamic fluctuation becomes more prominent in the retreating side than that in the advancing side for dynamic yawing case. Variations of effective angle of attack and aerodynamic forces along the blade span are analyzed. The biggest loading position moves from middle span to outer span with the increase of yaw angle. Three-dimensional stall effect presents load fluctuations at the inner board of blade, and becomes stronger with the increase of yaw angle.
Several members of the FGF family have been identified as potential regulators of glucose homeostasis. We previously reported that a low threshold of FGF-induced FGF receptor 1c (FGFR1c) dimerization ...and activity is sufficient to evoke a glucose lowering activity. We therefore reasoned that ligand identity may not matter, and that besides paracrine FGF1 and endocrine FGF21, other cognate paracrine FGFs of FGFR1c might possess such activity. Indeed, via a side-by-side testing of multiple cognate FGFs of FGFR1c in diabetic mice we identified the paracrine FGF4 as a potent anti-hyperglycemic FGF. Importantly, we found that like FGF1, the paracrine FGF4 is also more efficacious than endocrine FGF21 in lowering blood glucose. We show that paracrine FGF4 and FGF1 exert their superior glycemic control by targeting skeletal muscle, which expresses copious FGFR1c but lacks β-klotho (KLB), an obligatory FGF21 co-receptor. Mechanistically, both FGF4 and FGF1 upregulate GLUT4 cell surface abundance in skeletal muscle in an AMPKα-dependent but insulin-independent manner. Chronic treatment with rFGF4 improves insulin resistance and suppresses adipose macrophage infiltration and inflammation. Notably, unlike FGF1 (a pan-FGFR ligand), FGF4, which has more restricted FGFR1c binding specificity, has no apparent effect on food intake. The potent anti-hyperglycemic and anti-inflammatory properties of FGF4 testify to its promising potential for use in the treatment of T2D and related metabolic disorders.
•A coupled model for predicting landslide-debris flow hazard chains was proposed.•The coupled model is capable of predicting the hazard chain by the hour.•The input of landslide area influences the ...prediction of debris flow.•The rainfall threshold curve supports landslide prediction in areas lacking data.
Landslides, debris flows, and other destructive natural hazards induced by heavy rainfall in mountainous regions are sometimes not independent but combined to form a disaster chain. Based on the integral link between the triggering of the landslide and the subsequent debris flow, we propose an approach that combines the Transient Rainfall Infiltration and Grid-Based Regional Slope Stability (TRIGRS) model and the Rapid Mass Movements Simulation (RAMMS) model to achieve hourly hazard prediction. The results indicate that the TRIGRS model performed well in predicting the spatial distribution of the shallow landslides, with a success rate of 81.86%. Thus, it is reasonable to use it as the initial input for debris flow simulations. The relationship between the landslide area and the accumulated rainfall obtained using the TRIGRS model is a power-law relationship, which provides a reference for regions that lack rainfall data to predict the material source of a debris flow. The coupled model was found to have a good accuracy of 76.77% in simulating the debris flow. This was close to the debris flow simulation based on the interpreted landslides, and it still produced reasonable results and a more practical value. Furthermore, the proposed coupled model can dynamically predict disasters by the hour based on actual rainfall events. Therefore, the results of this study help provide a more complete hazard prediction picture for rainfall-induced landslide-debris flow hazards in mountainous regions.
Iron is one of the important trace elements in life activities. Abnormal iron metabolism increases the incidence of many skeletal diseases, especially for osteoporosis. Iron metabolism plays a key ...role in the bone homeostasis. Disturbance of iron metabolism not only promotes osteoclast differentiation and apoptosis of osteoblasts but also inhibits proliferation and differentiation of osteoblasts, which eventually destroys the balance of bone remodeling. The strength and density of bone can be weakened by the disordered iron metabolism, which increases the incidence of osteoporosis. Clinically, compounds or drugs that regulate iron metabolism are used for the treatment of osteoporosis. The goal of this review summarizes the new progress on the effect of iron overload or deficiency on osteoporosis and the mechanism of disordered iron metabolism on osteoporosis. Explaining the relationship of iron metabolism with osteoporosis may provide ideas for clinical treatment and development of new drugs.
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.
Abstract
Polymer-supported nanozero-valent iron composites (D001-nZVI) were fabricated for the removal of lead ions from aqueous solutions by embedding nZVI into the porous polystyrene anion ...exchanger D001. Humic acid (HA) was selected as a model species because of its ubiquitous existence to gain insight into the influencing factors in the actual application process. The iron contents of the composites were approximately 11.2%, and the smallest ZVI particle size was ~ 5 nm. The experimental results showed that the effect of HA on the reduction of lead ions by D001-nZVI was a concentration-dependent process. At low HA concentrations, the surface-competitive adsorption of HA and Pb
2+
dominated; therefore, the removal efficiency of Pb
2+
by D001-nZVI decreased from 97.5 to 90.2% with an increasing HA concentration. When the HA concentration increased to 30 mg/L or more, the lead ions removal remained constant with the following possible cooperation mechanism: the competitive adsorption of HA and Pb
2+
on the nZVI surface and the well-dispersed particles were caused by electrostatic interactions between the HA coating and the nZVI surface. In addition, the adsorption complexation between HA and Pb
2+
also had a positive effect on the removal of Pb
2+
at higher concentrations of HA.
Although there was no significant heterogeneity in the meta-publication, sensitivity analyses revealed significant heterogeneity. Overall, the prevalence was higher in women (N = 6, R = 4.6%, 95% CI ...3.1%, 6.0%, and I2 = 99.8%) than in men (N = 6, R = 3.4%, 95% CI 2.0%, 4.7%, and I2 = 99.6the %); prevalence of type 2 diabetes (N = 9, R = 12.5%, 95% CI 7.7%, 17.3%, and I2 = 95.4%) was higher than type 1 diabetes (N = 7, R = 8.3%, 95% CI 6.4%, 10.2%, and I2 = 93.6%); the prevalence of DGP was slightly lower in DM patients aged over 60 years (N = 6, R = 5.5%, 95% CI 3.3%, 7.7%, and I2 = 99.9%) compared to patients under 60 years of age (N = 12, R = 15.8%, 95% CI 11 15.8%, 95% CI 11.4%, 20.2%, and I2 = 88.3%). In conclusion, our findings indicate that the combined estimated prevalence of gastroparesis in diabetic patients is 9.3%. However, the sensitivity of the results is high, the robustness is low, and there are significant bias factors. The subgroup analysis revealed that the prevalence of DM-DGP is associated with factors such as gender, diabetes staging, age, and study method.
Abstract
Continuous rigid-frame bridges are widely used, but the large deflection in the mid-span during operation has always been their disease. This problem is generally solved by setting the ...finished bridge pre-camber. There are many calculation methods for pre-camber, and the effects are different. In this paper, based on a large number of design parameters of continuous rigid-frame bridges obtained from the investigation, 18 finite element analysis models of different span combinations were established, and 30 sets of valid data were obtained under the action of multi-factor. The results show that the shrinkage and creep of concrete is the most important factor for the mid-span deflection of continuous rigid frame bridges, and the deflection amount has an obvious functional relationship with the span. The effect of prestress loss on mid-span deflection is second, and stiffness reduction has little effect on mid-span long-term deflection. In this paper, the least-squares method is used to perform polynomial fitting, and the fitting formula for the mid-span finished bridge pre-camber is finally obtained. The applicability of the calculation formula is proved by comparing it with the specification solution, the empirical solution, and the measured value.
Plant disease detection has an inestimable effect on plant cultivation. Accurate detection of plant disease can control the spread of disease early and prevent unnecessary loss. Strawberry ...verticillium wilt is a soil-borne, multi-symptomatic disease. To detect strawberry verticillium wilt accurately, we first propose a disease detection network based on Faster R-CNN and multi-task learning to detect strawberry verticillium wilt. Then, the strawberry verticillium wilt detection network (SVWDN), which uses attention mechanisms in the feature extraction of the disease detection network, is proposed. SVWDN detects verticillium wilt according to the symptoms of detected plant components (i.e.,young leaves and petioles). Compared with other existing methods for detecting disease from the whole plant appearance, the SVWDN automatically classifies the petioles and young leaves while determining whether the strawberry has verticillium wilt. To provide a dataset for evaluating and testing our method, we construct a large dataset that contains 3, 531 images with 4 categories (Healthy_leaf, Healthy_petiole, Verticillium_leaf and Verticillium_petiole). Each image also has a label to indicate whether the strawberry is suffering from verticillium wilt. With the proposed strawberry verticillium wilt detection network, we achieved a mAP of 77.54% on object detection of 4 categories and 99.95% accuracy for strawberry verticillium wilt detection.
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