The Impacts of Collective Action in Common-Pool Resources ——Evidence From the Field of Grassland Use

The deterioration of common-pool resources is a serious issue faced by over the world now. How to manage public resources sustainably is extremely urgent. Collective action plays an important role in the sustainable management of common-pool resources. It creates a common goal that makes resource users not only concern their individual interests, but also the collective interests, in order to avoid the common-pool resource dilemma. The extent of collective interests that resource users concern affects their decisions in collective action, which further impacts the sustainable use of common-pool resources. We use a grazing experiment to observe and measure collective action. Combining the experimental data with the data in the real world, we find that resource users with more collective interests in collective action have higher grassland quality and less grazing livestock. Moreover, we use principal components analysis measuring collective action indicators to verify the robustness of these findings. A mechanism analysis is conducted to explain why collective action has positive effects on grassland restoration. Heterogeneity analysis examines the different impacts of collective actions with various natural endowments and individual characteristics. This study proves that collective action has positive impacts on the sustainable management of common-pool resources, which provides an empirical evidence on sustainable use of public natural resources through community-based natural resource management

Electrospun polyvinyl alcohol/carbon dioxide modified polyethyleneimine composite nanofiber scaffolds

A novel biocompatible polyvinyl alcohol/carbon dioxide modified polyethyleneimine (PVA/PEI-CO2) composite nanofiber was fabricated by a green and facile protocol, which reduces the cytotoxicity of PEI through the surface modification of the PEI with CO2. The 13C NMR spectrum, elemental analysis, and TGA show that CO2 has been incorporated in the PEI surface resulting in a relatively stable structure. The resulting PVA/PEI-CO2 composite nanofibers have been characterized by attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), contact angle, and scanning electron microscopy (SEM). The results show that the average diameters of the nanofibers range from 265 ± 53 nm to 423 ± 80 nm. The cytotoxicity of PVA/PEI-CO2 composite nanofibers was assessed by cytotoxicity evaluation using the growth and cell proliferation of normal mice Schwann cells. SEM and the MTT assay demonstrated the promotion of cell growth and proliferation on the PVA/PEI-CO2 composite scaffold. It suggests that PEI-CO2 can have tremendous potential applications in biological material research

Strong Consistency of MLE in Nonlinear Mixed-effects Models with Large Cluster Size

The search for conditions for the consistency of maximum likelihood estimators in nonlinear mixed effects models is difficult due to the fact that, in general, the likelihood can only be expressed as an integral over the random effects. For repeated measurements or clustered data, we focus on asymptotic theory for the maximum likelihood estimator for the case where the cluster sizes go to infinity, which is a minimum assumption required to validate most of the available methods of inference in nonlinear mixed-effects models. In particular, we establish sufficient conditions for the (strong) consistency of the maximum likelihood estimator of the fixed effects. Our results extend the results of Jennrich (1969) and Wu (1981) for nonlinear fixed-effects models to nonlinear mixed-effects models

Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening

Under the flourishing development in performance, current image-text retrieval methods suffer from $N$-related time complexity, which hinders their application in practice. Targeting at efficiency improvement, this paper presents a simple and effective keyword-guided pre-screening framework for the image-text retrieval. Specifically, we convert the image and text data into the keywords and perform the keyword matching across modalities to exclude a large number of irrelevant gallery samples prior to the retrieval network. For the keyword prediction, we transfer it into a multi-label classification problem and propose a multi-task learning scheme by appending the multi-label classifiers to the image-text retrieval network to achieve a lightweight and high-performance keyword prediction. For the keyword matching, we introduce the inverted index in the search engine and create a win-win situation on both time and space complexities for the pre-screening. Extensive experiments on two widely-used datasets, i.e., Flickr30K and MS-COCO, verify the effectiveness of the proposed framework. The proposed framework equipped with only two embedding layers achieves $O(1)$ querying time complexity, while improving the retrieval efficiency and keeping its performance, when applied prior to the common image-text retrieval methods. Our code will be released.Comment: 11 pages, 7 figures, 6 table

The numerical simulation on the regularity of dust dispersion in whole-rock mechanized excavation face with different air-draft amount

AbstractAn experimental investigation was carried out on coal dust-inertant mixture explosions. Tests of explosion severity and flammability limit were conducted by using the Siwek 20 L vessel and influences of ignition energy, coal dust calorific value, coal dust concentration and inertant composition were taken into account. The increase of inerting results with ignition energy is followed by an approximate stabilization when ignition energy exceeds 5kJ. The ignition energy region of 5-10kJ is appropriate for inerting testing, whereas ignitors with energy lower than 5kJ produce unrealistic inerting results. The inerting effectiveness of inertant increases with the reduction of coal dust calorific value. Coal dust concentrations near the stoichiometric concentration require the greatest amount of inertant to suppress explosions. As the coal dust concentration increases beyond the stoichiometric, the amount of inertant requirement is reduced. Due to the efficient decomposition and particular flame extinguishing mechanism, monoammonium phosphate represents more excellent inerting effectiveness than calcium carbonate

A High-Performance Liquid Chromatography:Chemiluminescence Method for Potential Determination of Vardenafil in Dietary Supplement

A flow method of high-performance liquid chromatography (HPLC) seperation and chemiluminescence (CL) detection for sensitive vardenafil analysis in dietary supplements was developed. The vardenafil separation was achieved on a C18 column at 30°C using ethanol-H3PO4 and ethylenediaminetetraacetic acid disodium salt (Na2EDTA) aqueous solution (25 : 75, v/v%) as mobile phase. The followed continuous CL detection was conducted based on the strong CL enhancement by the presence of vardenafil to luminol-K3Fe(CN)6 reaction in alkaline medium. At the flow rate of 0.8 mL/min, the vardenafil retention time (tR) was 6.4 min. Factors that affected the HPLC resolution and CL detection were studied and optimized. The calibration curve obtained for vardenafil standard was linear in concentration range of 8.0 × 10−7 ~ 1.0 × 10−4 mol/L. The relative standard deviations (RSD) of intraday and interday precision were less than 3.5%. The proposed method was applied to the vardenafil determination in oral liquid, wine, and capsule samples