The loss and recovery potential of net ecosystem productivity in mining areas: A global assessment based on data for 2000–2020

Climate change control requires more land to increase ecosystem carbon sequestration. With the high-intensity development of mineral resources in past decades, massive mining areas have been generated worldwide. However, few studies have evaluated the carbon sequestration of these mining areas. In this study, we analyzed the net ecosystem productivity (NEP) changes and calculated the NEP losses in global terrestrial mining areas. We adopted the random forest model to evaluate the NEP recovery potential and its driving factors. The key findings are that (1) the NEP of global mining areas exhibited a relatively obvious decreasing trend from 2000 to 2020, with an overall reduction of 29.1% and a maximum decline of 35.7%. By 2020, the NEP loss in mining areas was 11.9 g C m−2 year−1, and the total loss reached 576.9 Gg C year−1. (2) Global mining areas demonstrate significant NEP recovery potential, with an average of 12.0 g C m−2 year−1. Notably, Oceania and South America have significantly higher recovery potentials, with average mine site NEP recovery potentials of 15.9 g C m−2 year−1 and 16.1 g C m−2 year−1. In contrast, European mines have considerably lower recovery potentials of less than 10 g C m−2 year−1. In Asia, North America and Africa, the NEP recovery potential varies widely from mine to mine, but generally meets the global average. (3) The annual precipitation, population density, organic soil carbon, and average slope are important drivers of NEP recovery in mining areas and exhibit positive correlations with the NEP recovery potential. In contrast, mine area and minimum temperature exhibit a negative correlation. The dependency curves of the three drivers, standardized precipitation evapotranspiration index, average elevation, and annual maximum temperature, are U-shaped, indicating that the recovery potential was poorer in the tropical and frigid zones with less precipitation. The results of this study provide a scientific basis for ecological restoration and sustainable development of mining areas worldwide

Helper T Cell (CD4(+)) Targeted Tacrolimus Delivery Mediates Precise Suppression of Allogeneic Humoral Immunity

Antibody-mediated rejection (ABMR) is a major cause of dysfunction and loss of transplanted kidney. The current treatments for ABMR involve nonspecific inhibition and clearance of T/B cells or plasma cells. However, the prognosis of patients following current treatment is poor. T follicular helper cells (Tfh) play an important role in allograft-specific antibodies secreting plasma cell (PC) development. Tfh cells are therefore considered to be important therapeutic targets for the treatment of antibody hypersecretion disorders, such as transplant rejection and autoimmune diseases. Tacrolimus (Tac), the primary immunosuppressant, prevents rejection by reducing T cell activation. However, its administration should be closely monitored to avoid serious side effects. In this study, we investigated whether Tac delivery to helper T (CD4(+)) cells using functionalized mesoporous nanoparticles can block Tfh cell differentiation after alloantigen exposure. Results showed that Tac delivery ameliorated humoral rejection injury in rodent kidney graft by suppressing Tfh cell development, PC, and donor-specific antibody (DSA) generation without causing severe side effects compared with delivery through the drug administration pathway. This study provides a promising therapeutic strategy for preventing humoral rejection in solid organ transplantation. The specific and controllable drug delivery avoids multiple disorder risks and side effects observed in currently used clinical approaches

Transient flow analysis in a Roots blower: Experimental and numerical investigations

It is widely acknowledged that rotary positive displacement machines exhibit highly unsteady flow fields that affect their performance. The presence of the operational clearances impacts this unsteady flow field and further affects the performance. However, the exact nature of these unsteady flow mechanisms remains largely unknown that necessitates both detailed experimental investigations and computational modelling. Thus, the present study employs both optical visualization and unsteady Reynolds-Averaged Navier Stokes (URANS) computational modelling methods while focussing on investigating the transient flow field inside a Roots blower, a general type of the rotary positive displacement machine. Straight lobes in a Roots blower provide convenient optical access to experimentally analyse internal flow and compare it with the predictions obtained by standard computational models. In the first part of this paper, this study covers the low-speed experimental investigations using i) High-Speed Camera (HC), ii) the continuous High-Speed Particle Image Velocimetry (CPIV) and, iii) the instantaneous PIV (IPIV) obtained with a double pulse laser and a double shutter camera. Relative merits from these techniques are discussed with respect to the Roots blower unsteady flow mechanisms. In addition, computational analyses are performed using a combination of in-house and commercial modelling methods and the results are compared against the experiments. The results confirm the existence of highly three-dimensional and unsteady flow field where certain distinct flow mechanisms originating from the operational clearances impact the performance of the Roots blower. The study also highlights challenges of the experimental and computational methods used for evaluation of positive displacement machines that impact the accuracy of results

Elevated Serum IL-21 Levels Are Associated With Stable Immune Status in Kidney Transplant Recipients and a Mouse Model of Kidney Transplantation

Allograft rejection after renal transplantation remains a challenge to overcome. Interleukin (IL)-21, a cytokine with pleiotropic effects, maintains immune homeostasis post-transplantation. Here, we report higher levels of IL-21 in kidney transplant recipients with non-rejection (NR) than in recipients with T cell-mediated rejection (TCMR, P \u3c 0.001) and antibody-mediated rejection (ABMR, P = 0.005). We observed a negative correlation between IL-21 and creatinine (Cr) levels (P = 0.016). The receiving operating characteristic (ROC) curve showed a promising diagnostic value of IL-21 to identify acute rejection with an area under the curve (AUC) of 0.822 (P \u3c 0.001). In contrast, exogenous administration of IL-21 accelerated acute rejection in a comparative translational kidney transplant (KT) mouse model. Reduced IL-21 levels in the peripheral blood were observed in KT mice after IL-21 injection. Further analysis revealed that increased IL-21 levels in the spleen induced proliferation of CD4+ T cells and CD19+ B cells after IL-21 treatment. Our findings suggest a critical function of IL-21 in kidney transplantation and the potential involvement of the IL-21/IL-21R pathway in acute rejection management

Facile pyrolysis approach of folic acid-derived high graphite N-doped porous carbon materials for the oxygen reduction reaction

One-step pyrolysis process to design hierarchical micro/mesoporous m-NC materials with high graphite N dopant as excellent ORR electrocatalytic.</p

SnS2@C Hollow Nanospheres with Robust Structural Stability as High-Performance Anodes for Sodium Ion Batteries

Abstract Constructing unique and highly stable structures with plenty of electroactive sites in sodium storage materials is a key factor for achieving improved electrochemical properties through favorable sodium ion diffusion kinetics. An SnS2@carbon hollow nanospheres (SnS2@C) has been designed and fabricated via a facile solvothermal route, followed by an annealing treatment. The SnS2@C hybrid possesses an ideal hollow structure, rich active sites, a large electrode/electrolyte interface, a shortened ion transport pathway, and, importantly, a buffer space for volume change, generated from the repeated insertion/extraction of sodium ions. These merits lead to the significant reinforcement of structural integrity during electrochemical reactions and the improvement in sodium storage properties, with a high specific reversible capacity of 626.8 mAh g−1 after 200 cycles at a current density of 0.2 A g−1 and superior high-rate performance (304.4 mAh g−1 at 5 A g−1)

Driver Fatigue Detection Using Improved Deep Learning and Personalized Framework

In transportation, drivers’ state directly affects traffic safety. Therefore, an accurate driver’s fatigue detection is crucial for ensuring driving safety. Real-time and accurate technology is needed for driver fatigue detection. To address this problem, this article proposes a fatigue detection method based on an improved deep learning and personalized framework. First, clustering is applied to face size, and cluster numbers are used to determine the number of detection layers. Then, the size of anchor boxes is set according to the face size. In the proposed framework, the number of convolutional networks is set according to the principle that the receptive field should match the face size in the predicted feature map. Finally, a variety of fatigue features are learned by minimizing the loss function. In addition, a personalized face fatigue detection method is put forward for building a fatigue detection framework to judge the driver’s fatigue status more reasonably. The experimental results show that the proposed method based on an improved clustering method and local receptive field can improve the detection speed of driver’s fatigue while maintaining high detection accuracy. The proposed method can reach 125 fps by using GPU GeForce GTX TITAN, which satisfies the real-time requirement. In addition, the personalized framework can achieve high detection accuracy while keeping acceptable speed. The proposed model can accurately and timely detect driver fatigue, which can help to avoid accidents. </jats:p