Monitoring the ecological environment of open-pit coalfields in cold zone of Northeast China using Landsat time series images of 2000-2015

Procjena pogoršanja ekološkog okruženja i vegetacije rudnika u Kini zbog prekomjernog vađenja ugljena važna je zbog osjetljivog ekološkog okruženja i niske temperature u hladnim i sušnim područjima. U ovom se istraživanju kao primjeri uzimaju rudnici Haizhou, Gulianhe i Huolinhe s otvorenim jamskim oknom te se predlaže metoda za procjenu njihovog ekološkog okruženja primjenom Landsat vremenske serije slika na temelju varijacija Normalized Difference Vegetation Index-a (NDVI) rudnika s otvorenim jamskim oknom u hladnim i sušnim područjima. Prosječna NDVI vrijednost rudarskog područja izračunavala se svakog mjeseca primjenom podataka Landsat serije slika od 2000 do 2015. Područje nalazišta ugljena pod vegetacijom određeno je u skladu s graničnim vrijednostima NDVI pa su tako izrađeni grafikoni godišnjeg maksimalnog NDVI i područja pod vegetacijom. Prilagodili smo liniju trenda varijacije maksimalne vrijednosti NDVI i područja pod vegetacijom kako bi se smanjio učinak meteoroloških čimbenika na NDVI vrijednosti. Rezultati pokazuju da se poslije zatvaranja jame i čišćenja područja odlaganja, naglo, tijekom zadnjeg desetljeća, povećao NDVI rudnika s otvorenim jamskim otvorom i područja pod vegetacijom, a ekološko okruženje tih rudnika se očito poboljšalo. Rudarske aktivnosti su dovele do naglog opadanja godišnjeg maksimalnog NDVI i područja pod vegetacijom s trajno smrznutim slojem tla, a ekološko okruženje rudnika se nastavlja pogoršavati. Premda četverogodišnji prosječni NDVI ostaje nepromijenjen u dijelovima nalazišta ugljena koji se eksploatiraju, a nemaju trajno smrznuti sloj tla, područje ugljenokopa pod vegetacijom se linearno smanjuje, ukazujući na činjenicu da se ekološko okruženje ugljenokopa pogoršava. Sa stajališta zaštite ekološkog okruženja, rezultati ovog istraživanja čine osnovu za donošenje odluke o otvaranju velikih rudnika s otvorenim jamskim oknom u hladnim i sušnim područjima.Evaluating the deterioration of ecological environment and vegetation of coalfields caused by China’s large-scale coal mining activities is important because of the fragile ecological environment and low temperature in cold and arid areas. This study takes the open coal pits of Haizhou, Gulianhe, and Huolinhe as examples and proposes a method for evaluating their ecological environment using Landsat time series images based on the Normalized Difference Vegetation Index (NDVI) variations of open-pit coalfields in cold and arid zones. The average NDVI value of the mining area each month was calculated using Landsat image data from 2000 to 2015. The vegetation cover area in the coalfields was extracted according to the NDVI threshold, and the scatter plots of the annual maximum NDVI and vegetation cover area were drawn. We fitted the variation trend line of maximum NDVI value and vegetation cover area to reduce the effect of meteorological factors on NDVI values. Results show that after the closure of open pit and reclamation of dump area, the NDVI of open-pit coalfields and vegetation cover area have been increasing rapidly over the last decade, and the ecological environment of these coalfields has obviously improved. The coal mining activities have led to the rapid decline of annual maximum NDVI and vegetation cover area of the coalfields in permafrost zones, and the ecological environment of coalfields continues to deteriorate. Although the quarterly average NDVI remains unchanged in non-permafrost mining coalfields under coal exploitation, the vegetation cover area in the coalfields decreases linearly, indicating that the ecological environment of the coalfields tends to deteriorate. From an ecological environment protection perspective, the results of this study provide a basis for decision making in constructing large-scale open pits in cold and arid zones

Role of ε-Poly-lysine in mixed surimi gel: concentration, underlying mechanism, and application

The effects of different concentrations of ε-Poly-lysine (ε-PL: 0.005%, 0.01%, 0.02%, 0.04%, and 0.06%) on the marine fish-egg white protein compound gels, treated with 0.4% TGase induced cross-linking were systematically investigated under low salt and phosphorus-free conditions (0.5% NaCl). The results showed the combination of ε-PL and TGase had a synergistic effect on improving sectional gel properties of composite surimi samples. Wherein the rheological, LF-NMR, and SEM results confirmed that the addition of ε-PL based on 0.4% TGase significantly improved the gel strength (to the highest value: 781.63 g·cm), apparent viscosity, and G 'value of the composite surimi sample, as well as reduced the internal water fluidity of surimi, accompanied by the emergence of a more dense and uniform gel network structure. Notably, ε-PL treatment significantly inhibited fat oxidation in the compound surimi gel and the degree of inhibition was proportional to its addition (decreased from 2.03 to 1.67 mg·kg−1). However, the addition of a small amount (0.005%) or an excessive amount (0.06%) of ε-PL on the gel properties of composite surimi samples witnessed the negative effects of the changes in the internal water distribution state and the cooking loss. To sum up, moderate ε-PL (0.04%) treatment combined with TGase induction can maximize the performance of mixed surimi gel and inhibit fat oxidation. The research results supply a diverse perspective and theoretical basis for the development of 'low salt and no phosphorus' surimi product ingredients

Associations between computed tomography markers of cerebral small vessel disease and hemorrhagic transformation after intravenous thrombolysis in acute ischemic stroke patients

BackgroundHemorrhagic transformation (HT) is common among acute ischemic stroke patients after treatment with intravenous thrombolysis (IVT). We analyzed potential relationships between markers of cerebral small vessel disease (CSVD) and HT in patients after IVT.MethodsThis study retrospectively analyzed computed tomography (CT) data for acute ischemic stroke patients before and after treatment with recombinant tissue plasminogen activator at a large Chinese hospital between July 2014 and June 2021. Total CSVD score were summed by individual CSVD markers including leukoaraiosis, brain atrophy and lacune. Binary regression analysis was used to explore whether CSVD markers were related to HT as the primary outcome or to symptomatic intracranial hemorrhage (sICH) as a secondary outcome.ResultsA total of 397 AIS patients treated with IVT were screened for inclusion in this study. Patients with missing laboratory data (n = 37) and patients treated with endovascular therapy (n = 42) were excluded. Of the 318 patients included, 54 (17.0%) developed HT within 24–36 h of IVT, and 14 (4.3%) developed sICH. HT risk was independently associated with severe brain atrophy (OR 3.14, 95%CI 1.43–6.92, P = 0.004) and severe leukoaraiosis (OR 2.41, 95%CI 1.05–5.50, P = 0.036), but not to severe lacune level (OR 0.58, 95%CI 0.23–1.45, P = 0.250). Patients with a total CSVD burden ≥1 were at higher risk of HT (OR 2.87, 95%CI 1.38–5.94, P = 0.005). However, occurrence of sICH was not predicted by CSVD markers or total CSVD burden.ConclusionIn patients with acute ischemic stroke, severe leukoaraiosis, brain atrophy and total CSVD burden may be risk factors for HT after IVT. These findings may help improve efforts to mitigate or even prevent HT in vulnerable patients

High Altitude test of RPCs for the ARGO-YBJ experiment

A 50 m**2 RPC carpet was operated at the YangBaJing Cosmic Ray Laboratory (Tibet) located 4300 m a.s.l. The performance of RPCs in detecting Extensive Air Showers was studied. Efficiency and time resolution measurements at the pressure and temperature conditions typical of high mountain laboratories, are reported.Comment: 16 pages, 10 figures, submitted to Nucl. Instr. Met

An evaluation method of pig cleaning capacity based on contact friction characteristics

Based on the three-dimensional finite element numerical simulation, an evaluation method of pig cleaning capacity was innovatively proposed from the perspective of the contact friction characteristics of the sealing component. Three-dimensional finite element models were established for two kinds of typical pigs running in horizontal straight pipeline with ANSYS, and the accuracy of the models was verified by field tests. Further, the cleaning capacity of the two kinds of pigs under different friction conditions were compared respectively through analysis on the calculation results. The research results show that the contact friction coefficient can affect the sealing tightness, tangent scraping force and effective cleaning area of running pigs. The scraping force increases with the increasing of friction coefficient while the sealing tightness and the contact area decrease. If the material and interference of the sealing components are identical under the same friction condition, the sealing tightness and the scraping force of the straight plate pig are superior to those of cup pig. However, the effective cleaning area of the cup pig is larger than that of the straight plate pig with same running distance. Appropriate pig should be selected according to the type of impurity in the pipeline to be cleaned, so that the cleaning capacity and efficiency can be improved effectively

Research on the Method of Urban Jobs-Housing Space Recognition Combining Trajectory and POI Data

With the gradual emergence of the separation and dislocation of urban jobs-housing space, rational planning of urban jobs-housing space has become the core issue of national land-spatial planning. To study the existing relationship between workspaces and living spaces, a new method to identify jobs-housing space is proposed, which not only considers the static spatial distribution of urban public facilities but also identifies the jobs-housing space by analyzing the real mobility characteristics of people from a humanistic perspective. This method provides a new framework for the identification of urban jobs-housing space by integrating point-of-interest (POI) and trajectory data. The method involves three steps: Firstly, based on the trajectory data, we analyze the characteristics of the dynamic flow of passengers in the grid and construct the living factors and working factors to identify the distribution of jobs-housing space. Secondly, we reclassify the POIs to calculate the category ratios of different types of POIs in the grid to identify the jobs-housing space. Finally, an OR operation is performed on the results obtained by the two methods to obtain the final recognition result. We selected Haikou City as the experimental area to verify the method proposed in this paper. The experimental results show that the recognition accuracy of the travel flow model is 72.43%, the POI quantitative recognition method’s accuracy is 74.94%, and the accuracy of the method proposed in this paper is 85.90%, which is significantly higher than the accuracy of the previous two methods. Therefore, the method proposed here can serve as a reference for subsequent research on urban jobs-housing space

Quantitative Evaluation of Grassland SOS Estimation Accuracy Based on Different MODIS-Landsat Spatio-Temporal Fusion Datasets

Estimating the Start of Growing Season (SOS) of grassland on the global scale is an important scientific issue since it can reflect the response of the terrestrial ecosystem to environmental changes and determine the start time of grazing. However, most remote sensing data has coarse- temporal and spatial resolution, resulting in low accuracy of SOS retrieval based on remote sensing methods. In recent years, much research has focused on multi-source data fusion technology to improve the spatio-temporal resolution of remote sensing information, and to provide a feasible path for high-accuracy remote sensing inversion of SOS. Nevertheless, there is still a lack of quantitative evaluation for the accuracy of these data fusion methods in SOS estimation. Therefore, in this study, the SOS estimation accuracy is quantitatively evaluated based on the spatio-temporal fusion daily datasets through the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and other models in Xilinhot City, Inner Mongolia, China. The results show that: (1) the accuracy of SOS estimation based on spatio-temporal fusion daily datasets has been slightly improved, the average Root Mean Square Error (RMSE) of SOS based on 8d composite datasets is 11.1d, and the best is 9.7d (fstarfm8); (2) the estimation accuracy based on 8d composite datasets (RMSE¯ = 11.1d) is better than daily fusion datasets (RMSE¯ = 18.2d); (3) the lack of the Landsat data during the SOS would decrease the quality of the fusion datasets, which ultimately reduces the accuracy of the SOS estimation. The RMSE¯ of SOS based on all three models increases by 11.1d, and the STARFM is least affected, just increases 2.7d. The results highlight the potential of the spatio-temporal data fusion method in high-accuracy grassland SOS estimation. It also shows that the dataset fused by the STARFM algorithm and composed for 8 days is better for SOS estimation