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The Jinchuan Nickel Mine is the largest large-scale copper–nickel sulfide deposit in China and the third largest in the world. Due to the deep burial of the ore body, high geostress, and broken ore rock, the downward layered cementing and filling mining method with high cost and low production capacity is adopted. The Jinchuan Nickel Mine uses bar milling sand as the filling aggregate and cement as the cementing material and adopts pipeline autoclave conveying filling mining technology with a high cement-to-sand ratio and high concentration of filling slurry, which results in the high cost of filling mining and poor mining economic benefits. In order to reduce the cost of filling mining, the Jinchuan Nickel Mine has carried out a series of research on low-cost filling mining technology by utilizing solid waste, such as using metallurgical slag instead of cement to develop low-cost filling cementitious material, using waste rock and bar mill sand as the mixed aggregate, using waste rock and tailing sand as the mixed aggregate, mixing fly ash with the mixed aggregate, and mixing copper processing tailing with the mixed aggregate. The strength of the 3d, 7d, and 28d cemented filling body of waste rock and bar mill sand reached 1.5 MPa, 2.6 MPa, and 4.8 MPa, respectively; the strength of the 3d, 7d, and 28d cemented filling body of waste rock tailings reached 4.7 MPa, 6.1 MPa, and 9.0 MPa, respectively; the strength of the 3d, 7d, and 28d cemented filling body of mixed fly ash reached 2.0 MPa, 2.0 MPa, 6.1 MPa, and 9.0 MPa, respectively; the strength of 3d, 7d, and 28d doped fly ash cemented filling body reached 2.0 MPa, 2.7 MPa, and 5.9 MPa, respectively; the strength of the 3d, 7d, and 28d doped copper-selecting tailings cemented filling body reached 1.55 MPa, 3.11 MPa, and 5.10 MPa respectively; and the strength of 3d early-strength type green filling cementitious material increased to 1.73 MPa. The application of cemented filling with solid waste resources in the Jinchuan Nickel Mine has been successful and popularized and applied in the Longshou Mine and the second mine area. Early-strength green filling cementitious materials and mixed aggregate paste filling technology are the research and development direction for utilization in Jinchuan Nickel Mine filling and mining.

In the context of global climate warming, climate change is subtly reshaping the patterns of wildfires. Therefore, it is particularly urgent to conduct in-depth research on climate change, wildfires, and their management strategies. This study relies on detailed fire point data from 2001 to 2020, skillfully incorporating a spatial autocorrelation analysis to uncover the mysteries of spatial heterogeneity, while comprehensively considering the influences of multiple factors such as climate, terrain, vegetation, and socioeconomic conditions. To simulate fire conditions under future climates, we adopted the BCC-CSM2-MR climate model, presetting temperature and precipitation data for two scenarios: a sustainable low-development path and a high-conventional-development path. The core findings of the study include the following: (i) In terms of spatial heterogeneity exploration, global autocorrelation analysis reveals a striking pattern: within the southern forest region, 63 cities exhibiting a low–low correlation are tightly clustered in provinces such as Hubei, Anhui, and Zhejiang, while 48 cities with a high–high correlation are primarily distributed in Guangxi and Guangdong. Local autocorrelation analysis further refines this observation, indicating that 24 high–high correlated cities are highly concentrated in specific areas, 14 low–low correlated cities are located in Hainan, and there are only 3 sparsely distributed cities with a low–high correlation. (ii) During the model construction and validation process, this study innovatively adopted the LR-RF-SVM ensemble model, which demonstrated exceptional performance indicators: an accuracy of 91.97%, an AUC value of 97.09%, an F1 score of 92.13%, a precision of 90.75%, and a recall rate of 93.55%. These figures, significantly outperforming those of the single models SVM and RF, strongly validate the superiority of the ensemble learning approach. (iii) Regarding predictions under future climate scenarios, the research findings indicate that, compared to the current fire situation in southern forest areas, the spatial distribution of wildfires will exhibit a noticeable expansion trend. High-risk regions will not only encompass multiple cities in Hunan, Hubei, southern Anhui, all of Jiangxi, and Zhejiang but will also extend northward into southern forest areas that were previously considered low-risk, suggesting a gradual northward spread of fire risk. Notably, despite the relatively lower fire risk in some areas of Fujian Province under the SS585 scenario, overall, the probability of wildfires occurring in 2090 is slightly higher than that in 2030, further highlighting the persistent intensification of forest fire risk due to climate change. [ABSTRACT FROM AUTHOR]

Forest fires are a major natural calamity that inflict substantial harm on forest resources and the socio-economic landscape. The eastern region of China is particularly susceptible to frequent forest fires, characterized by high population density and vibrant economic activities. Precise forecasting in this area is essential for devising effective prevention strategies. This research utilizes a blend of kernel density analysis, autocorrelation analysis, and the standard deviation ellipse method, augmented by geographic information systems (GISs) and deep-learning techniques, to develop an accurate prediction system for forest-fire occurrences. The deep-learning model incorporates data on meteorological conditions, topography, vegetation, infrastructure, and socio-cultural factors to produce monthly forecasts and assessments. This approach enables the identification of spatial patterns and temporal trends in fire occurrences, enhancing both the precision and breadth of the predictions. The results show that global and local autocorrelation analyses reveal high-incidence areas mainly concentrated in Guangdong, Fujian, and Zhejiang provinces, with cities like Jiangmen exhibiting distinct concentration characteristics and a varied spatial distribution of fire occurrences. Kernel density analysis further pinpoints high-density fire zones primarily in Meizhou, Qingyuan, and Jiangmen in Guangdong Province, and Dongfang City in Hainan Province. Standard deviation ellipse and centroid shift analysis indicate a significant northward shift in the fire-occurrence centroid over the past 20 years, with an expanding spatial distribution range, decreasing flattening, and relatively stable fire-occurrence direction. The model performs effectively on the validation set, achieving an accuracy of 80.6%, an F1 score of 81.6%, and an AUC of 88.2%, demonstrating its practical applicability. Moreover, monthly fire zoning analysis reveals that high-incidence areas in spring and winter are mainly concentrated in Guangdong, Fujian, Zhejiang, and Hainan, while autumn shows widespread medium-incidence areas, and summer presents lower fire occurrences in most regions. These findings illustrate the influence of seasonal climate variations on fire occurrences and highlight the necessity for enhanced fire monitoring and prevention measures tailored to different seasons. [ABSTRACT FROM AUTHOR]

Incorporating nano-dispersions into thermoelectric (TE) materials is an effective approach to enhance the TE properties. Herein, the TE performance of Cu2Se thin film is significantly enhanced by incorporating highly dispersed SnSe nano-inclusions. The high power factor (PF, ∼11.0 μW cm−1 K−2, 310 K) at near room temperature is achieved mainly due to the enhanced energy filtering effect that originated from the potential barrier difference. The total thermal conductivity is decreased owing to the simultaneously reduced electrical conductivity and enhanced phonon scattering. As a result, a high zT value (∼0.59 at 375 K) is achieved, which is about 12 times of pristine Cu2Se film. Remarkably, the calculated average zT values of Cu2Se/SnSe films from 310 to 375 K greatly exceed those of the pristine Cu2Se film, as well as the most state-of-the-art studies. High room-temperature PF and average zT value are crucial for expanding the practical application of Cu2Se at near room temperature. This work provides a feasible strategy to optimize the zT values of some other TE films by introducing nano-dispersions. [ABSTRACT FROM AUTHOR]

Contemporary research on terrestrial carbon exchange processes is paramount for a nuanced comprehension of global and local climatic fluctuations and their interaction with anthropogenic activities. This study delves into the spatiotemporal dynamics of vegetation carbon exchanges within the Three Northern Protection Forest Project Area, leveraging two decades of MODIS NPP data and an innovative NEP estimation model. Our analysis highlights a generally increasing trend in Net Ecosystem Productivity (NEP) from 2000 to 2020, with significant growth in approximately 32.97% of the study area and slight increases in 24.18%. Notably, lower NEP values were found in desert and arid zones, whereas higher values were observed in more vegetated regions like Ningxia, Hebei, Inner Mongolia, and the northeast. The study also assesses the impact of climate variables and land-use changes on NEP, identifying both negative and positive correlations in specific regions. Despite the overall positive trend towards ecological restoration and enhancement, significant uncertainties remain, emphasizing the urgent need for further research to support ecosystem resilience and sustainable management practices. [ABSTRACT FROM AUTHOR]

Objective: to observe the effect differences and safety between acupuncture and sham acupuncture for female depression on the basis of conventional western medicine therapy., Methods: Forty-two patients with depression who met the criteria were randomly assigned into an observation group and a control group, 21 patients in each group. The basic treatment in the two groups was fluoxetine. The patients in the observation group were treated with acupuncture at Zhongwan (CV 12), Xiawan (CV 10), Qihai (CV 6), Guanyuan (CV 4) and bilateral Shangqu (KI 17). Sham acupuncture was used at the above points in the control group. The treatment was given once a day on the first 3 days and once every 3 days after that, totally for 8 weeks. The scores of self-rating depression scale (SDS) and Montgomery Asberg depression rating scale (MADRS) were compared before and after 4-week and 8-week treatment in the two groups. The effects and adverse reactions were evaluated., Results: After 4-week and 8-week treatment, the SDS and MADRS scores were significantly lower than those before treatment in the two groups (all P <0.05), and the scores in the observation group were lower than those in the control group (both P <0.05). The improvements of SDS and MADRS scores in the observation group before and after treatment were better than those in the control group (both P <0.05). The total effective rates of SDS, MADRS scores were 85.7% (18/21), 90.5% (19/21) in the observation group, which were better than 38.1% (8/21), 57.1% (12/21) in the control group (both P <0.05). The adverse reactions in the observation group were significantly lower than those in the control group ( P <0.05)., Conclusion: Acupuncture combined with fluoxetine are effective and safe for female depression.