Mechanism and Application of Static Fracturing Technology on Deep Working Face

Static fracturing technology uses chemical expansion agents to fracture roofs. With the aim of fracturing corner roofs on deep working faces, in this study, the static fracturing technology was investigated through theoretical analysis, laboratory experiments, numerical calculations, and field practice. The theoretical analysis and experiments demonstrated that the swelling force increased with a decrease in the fracturing hole spacing, and the optimal water-cement ratio was 0.33. Twelve groups of FLAC3D models were designed using SPSSAU. The results revealed that the optimal fracturing effect was achieved when the hole diameter was 60 mm, hole spacing was 40 cm, and hole depth was 6 m. The fracturing effect of hard corner roofs was monitored by peering into the borehole and evaluating the support resistance. Thus, it can be concluded that within the fracturing range, internal fissures in the rock stratum are developed and linked to each other. The support pressure was the highest, 7 h after grouting, with a value of approximately 26.1 MPa, and then decreased gradually to 17.58 MPa, indicating that the static fracturing technology attained the expected results

Research on Reducing Mining-Induced Disasters by Filling in Steeply Inclined Thick Coal Seams

Surface filling during the mining of steeply inclined thick coal seams is an efficient method for restraining disasters caused by the cascading movement of overburden rocks. This study aims to control rock damage during the mining of thick coal seams steeply inclined at typically more than 45° in fully mechanized coal caving work surfaces with high section heights. Based on the green mining concept, we analyzed the movement of roof strata after filling using multiple methods, including field investigation, theoretical analysis, numerical calculation, and field monitoring. Results show that, in dynamic mine disasters caused mainly by complex coal conditions and strong disturbances in fully mechanized coal caving in large sections, the strength of the filling material is dependent on the features of the surrounding rock and burial depth. Also, the mining-induced peak stress shows a linear increase after filling, with the goafs in stress-free conditions, and failure zones occur in the roof and floor strata after mining. The stability of the rock pillars and overburden strata are better, and there are no large-scale tensile fissures in the ground surface. We adopted an intelligent underground radar detection technique that can reflect the rock-failure characteristics through the propagation characteristics of the electromagnetic spectrum. The detection results show that the coal goafs were filled properly as they were matched with the caving roof, which will collapse along with the release of the top coal, with the filling body able to move downward along with the discharge of top coal. The use of surface filling can restrain the dynamic disaster induced by a fully mechanized coal caving surface with a large section when mining steeply inclined thick coal seams, thereby ensuring safety and promoting the use of green mining practices

Developing a Gap-Filling Algorithm Using DNN for the Ts-VI Triangle Model to Obtain Temporally Continuous Daily Actual Evapotranspiration in an Arid Area of China

Temporally continuous daily actual evapotranspiration (ET) data play a critical role in water resource management in arid areas. As a typical remotely sensed land surface temperature (LST)-based ET model, the surface temperature-vegetation index (Ts-VI) triangle model provides direct monitoring of ET, but these estimates are temporally discontinuous due to cloud contamination. In this work, we present a gap-filling algorithm (TSVI_DNN) using a deep neural network (DNN) with the Ts-VI triangle model to obtain temporally continuous daily actual ET at regional scale. The TSVI_DNN model is evaluated against in situ measurements in an arid area of China during 2009–2011 and shows good agreement with eddy covariance (EC) observations. The temporal coverage was improved from 16.1% with the original Ts-VI tringle model to 67.1% with the TSVI_DNN model. The correlation coefficient (R), root mean square error (RMSE), bias, and mean absolute difference (MAD) are 0.9, 0.86 mm d−1, −0.16 mm d−1, and 0.65 mm d−1, respectively. When compared with the National Aeronautics and Space Administration (NASA) official MOD16 version 6 ET product, estimates of ET using TSVI_DNN are improved by approximately 49.2%. The method presented here can potentially contribute to enhanced water resource management in arid areas, especially under climate change

Short-Term Surveillance of Cytokines and C-Reactive Protein Cannot Predict Efficacy of Fecal Microbiota Transplantation for Ulcerative Colitis.

There were no reports on predicting long-term efficacy of fecal microbiota transplantation (FMT) for ulcerative colitis (UC). This study aimed to detect short-term changes of cytokines and C-reactive protein (CRP) in patients with UC undergoing FMT, and to evaluate the predictive value of CRP and cytokines for the long-term efficacy of FMT.Nineteen patients with moderate to severe UC (Mayo score ≥ 6) were treated with single fresh FMT through mid-gut. Serum samples were collected before and three days post-FMT. Clinical responses were evaluated by a minimum follow-up of three months. Patients with clinical improvement and remission at the assessment point of three-month were included as response group, while patients without clinical improvement or remission were included as non-response group. Serum concentrations of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-10, IL-11, IL-17A, IFN-γ, TNF, TNFR-1, TNFR-2, MCP-1, G-CSF, GM-CSF) and CRP were assayed to predict the clinical response of FMT.In total, 10.5% (2/19) of patients achieved clinical remission and 47.4% (9/19) achieved clinical improvement (Response group, including clinical remission and clinical improvement), 42.1% (8/19) failed to benefit from FMT (Non-response group). In both Response group and Non-response group, the level of CRP at three days after FMT didn't show significant decrease compared with that before FMT (p>0.05). However, in Response group, CRP level at three months after FMT decreased significantly than that before FMT (p0.05).Patients with moderate to severe UC presented a complex disorder of cytokines. However, the efficacy of FMT for UC might not be predicted by the short-term surveillance of cytokines and CRP

CD16 CAR-T cells enhance antitumor activity of CpG ODN-loaded nanoparticle-adjuvanted tumor antigen-derived vaccinevia ADCC approach

Abstract Background Combinatorial immunotherapy strategies for enhancing the responsiveness of immune system have shown great promise for cancer therapy. Engineered nanoformulation incorporated toll-like receptor (TLR) 9 agonist CpG ODN has shown more positive results in suppressing tumor growth and can significantly enhance other immunotherapy activity with combinatorial effects due to the innate and adaptive immunostimulatory effects of CpG. Results In the present work, protamine sulfate (PS) and carboxymethyl β-glucan (CMG) were used as nanomaterials to form nanoparticles through a self-assembly approach for CpG ODN encapsulation to generate CpG ODN-loaded nano-adjuvant (CNPs), which was subsequently mixed with the mixture of mouse melanoma-derived antigens of tumor cell lysates (TCL) and neoantigens to develop vaccine for anti-tumor immunotherapy. The obtained results showed that CNPs was able to effectively deliver CpG ODN into murine bone marrow-derived dendritic cells (DC) in vitro, and remarkably stimulate the maturation of DC cells with proinflammatory cytokine secretion. In addition, in vivo analysis showed that CNPs enhanced anti-tumor activity of PD1 antibody and CNPs-adjuvanted vaccine based on the mixture antigens of melanoma TCL and melanoma-specific neoantigen could not only induce anti-melanoma cellular immune responses, but also elicit melanoma specific humoral immune responses, which significantly inhibited xenograft tumor growth. Furthermore, CD16 CAR-T cells were generated by expressing CD16-CAR in CD3+CD8+ murine T cells. Conclusion Our results eventually showed that anti-melanoma antibodies induced by CNPs-adjuvanted TCL vaccines were able to collaborate with CD16-CAR-T cells to generate an enhanced targeted anti-tumor effects through ADCC (antibody dependent cell cytotoxicity) approach. CD16 CAR-T cells has thus a great potential to be an universal promising strategy targeting on solid tumor synergistic immunotherapy via co-operation with TCL-based vaccine

Concentrations of cytokines in UC and the healthy controls.

<p>Concentrations of cytokines in UC and the healthy controls.</p

Patients’ characteristics and clinical response.

<p>Patients’ characteristics and clinical response.</p