Development of a Respirable Dust Mitigation System for a High Longwall Face at Sihe Colliery in China â a Case Study

Dust is a major hazard in underground coal mines that threatens the work health and safety of coal miners. The dust issue becomes increasingly significant with the development of highly mechanized coal mining. This issue is particularly serious at the high longwall faces of the Sihe colliery in China as the concentration of dust, in particular respirable dust, at these faces far exceeds the regulatory dust limits. Field testing and computational fluid dynamics (CFD) simulations were conducted to understand the sources of dust generation and its dynamic movement in the #5301 longwall face of high-cutting height at the colliery. The investigation results showed that shearer generated dust was minimal during the coal cutting operation; that face spalling and chock movement were the main dust generating sources, causing significant contamination to the walkway; and that the majority of dust particles from the face (regardless of source) eventually disperse into the main gate, where the dust concentration was greater than 500 mg/m3. These findings were used to develop an effective coal dust mitigation system involving the installation of dust scrubbers, curtains, and venture and crescent sprays. The results of CFD modeling indicate that the dust concentration could be significantly reduced by adopting the new dust mitigation system

Clinical value of TAT, PIC and t-PAIC as predictive markers for severe sepsis in pediatric patients

ObjectiveSepsis in pediatric patients can progress to severe sepsis, and identifying biomarkers of this progression may permit timely intervention to prevent it. This study aimed to investigate the ability of thrombin-antithrombin complex (TAT), α2-plasmininhibitor-plasmin complex (PIC) and tissue-type plasminogen activator-inhibitor complex (t-PAIC) to predict severe sepsis in pediatrics early.Methods148 eligible pediatric sepsis patients were enrolled in this study, and were then divided into those who progressed to severe sepsis (n = 50) or not (n = 98). Serum levels of TAT, PIC, and t-PAIC were analysed, and simplified pediatric critical illness score (PCIS) and DIC score were calculated on the day of pediatric sepsis diagnosis.ResultsCompared with sepsis patients, severe sepsis patients had higher levels of TAT, PIC and t-PAIC. Correlation analysis revealed that TAT, PIC and t-PAIC were significantly correlated with simplified PCIS and DIC score. ROC curve analysis suggested that TAT, PIC and t-PAIC could serve as biomarkers for predicting severe sepsis with the AUC up to 0.862, 0.759 and 0.851, respectively. Stratified analysis demonstrated that the patients with increased levels of TAT, PIC and t-PAIC had worse illness severity and clinical outcome. Univariate logistic regression analysis revealed that TAT, PIC and t-PAIC were all risk factors for severe sepsis, yet only TAT and t-PAIC were independent risk factors in multivariate model.ConclusionsTAT, PIC and t-PAIC could serve as biomarkers for predicting severe sepsis, and correlated with illness severity in pediatrics, what's more, serum levels of TAT and t-PAIC may be independent risk factors for pediatric severe sepsis

Development of a Respirable Dust Mitigation System for a High Longwall Face at Sihe Colliery in China – a Case Study

Dust is a major hazard in underground coal mines that threatens the work health and safety of coal miners. The dust issue becomes increasingly significant with the development of highly mechanized coal mining. This issue is particularly serious at the high longwall faces of the Sihe colliery in China as the concentration of dust, in particular respirable dust, at these faces far exceeds the regulatory dust limits. Field testing and computational fluid dynamics (CFD) simulations were conducted to understand the sources of dust generation and its dynamic movement in the #5301 longwall face of high-cutting height at the colliery. The investigation results showed that shearer generated dust was minimal during the coal cutting operation; that face spalling and chock movement were the main dust generating sources, causing significant contamination to the walkway; and that the majority of dust particles from the face (regardless of source) eventually disperse into the main gate, where the dust concentration was greater than 500 mg/m3. These findings were used to develop an effective coal dust mitigation system involving the installation of dust scrubbers, curtains, and venture and crescent sprays. The results of CFD modeling indicate that the dust concentration could be significantly reduced by adopting the new dust mitigation system

Study of slime water mixing process intensification using impingement flow regulation

slime water generally contains a large number of highly dispersed suspended particles, making solid-liquid separation difficult. Strengthening fluid mixing and particle collision by regulating turbulence is an effective way to achieve solid-liquid separation. Particle collision flocculation mostly occurs in turbulent environments where the motion of fine particles is strongly influenced by the turbulent minimum vortex scale. In this study, turbulent vortices are modulated by impinging flows to enhance the mixing of two different density suspensions and the collision of fine particles in the suspension. Two different solution models were used to simulate the mixing condition of the suspension and the distribution of the particles in the mixing drum in three dimensions. The water phase entering the mixing drum was considered as a continuous phase and the solid particles were considered as a continuous phase (suspension) or a secondary discrete phase (particles). The effects of different inlet fluid velocity ratios at different feed densities on the turbulent characteristic parameters and particle distribution in the mixing drum were analyzed. The results of the study show that the impact flow formed by the jets colliding vertically with each other can induce turbulent macro-vortices such as hairpin vortices, spanwise vortices and axial vortices. The velocity of particles moving in the turbulent macro-vortex is in the following order: Large particle size and density > Large particle size and small density > Small particle size and high density > Small particle size and density. The interaction between vortex and vortex and between vortex and the main fluid significantly increases the turbulent kinetic energy and decreases the vortex scale, resulting in a minimum scale vortex that is conducive to particle coalescence and collision; the minimum vortex scale generated in the flow field in the mixing drum is mainly smaller than the average minimum vortex scale. The minimum vortex scale tends to increase when the inlet flow rate and flow rate ratio increase from 1.258:1.87 to 1.882:1.258, independent of the inlet density. When the flow rate ratio is similar, the minimum vortex scale decreases only when the flow rate increases. An appropriate increase in the ratio of the upper and side feed flow rates helps fluid mixing and particle aggregation and collision, and the mixing density, apparent viscosity and particle coalescence are all optimal when the ratio of the upper and side feed flow rates is between 1.40 and 1.50. In addition, at the same flow rate ratio, the mixing uniformity and mixing strength are better than the case where the upper inlet feed density is greater than the side inlet feed density, which is more conducive to fluid mixing and particle collision. The study promotes slime water mixing and fine particle coalescence in mixing drums through the regulation of fluid hydraulic conditions, providing a new way of thinking about how to enhance the liquid-liquid mixing and solid-liquid separation process

Activation of BNIP3-mediated mitophagy protects against renal ischemia-reperfusion injury

Acute kidney injury (AKI) is a syndrome of abrupt loss of renal functions. The underlying pathological mechanisms of AKI remain largely unknown. BCL2-interacting protein 3 (BNIP3) has dual functions of regulating cell death and mitophagy, but its pathophysiological role in AKI remains unclear. Here, we demonstrated an increase of BNIP3 expression in cultured renal proximal tubular epithelial cells following oxygen-glucose deprivation-reperfusion (OGD-R) and in renal tubules after renal ischemia-reperfusion (IR)-induced injury in mice. Functionally, silencing Bnip3 by specific short hairpin RNAs in cultured renal tubular cells reduced OGD-R-induced mitophagy, and potentiated OGD-R-induced cell death. In vivo, Bnip3 knockout worsened renal IR injury, as manifested by more severe renal dysfunction and tissue injury. We further showed that Bnip3 knockout reduced mitophagy, which resulted in the accumulation of damaged mitochondria, increased production of reactive oxygen species, and enhanced cell death and inflammatory response in kidneys following renal IR. Taken together, these findings suggest that BNIP3-mediated mitophagy has a critical role in mitochondrial quality control and tubular cell survival during AKI

A lightweight Yunnan Xiaomila detection and pose estimation based on improved YOLOv8

IntroductionYunnan Xiaomila is a pepper variety whose flowers and fruits become mature at the same time and multiple times a year. The distinction between the fruits and the background is low and the background is complex. The targets are small and difficult to identify.MethodsThis paper aims at the problem of target detection of Yunnan Xiaomila under complex background environment, in order to reduce the impact caused by the small color gradient changes between xiaomila and background and the unclear feature information, an improved PAE-YOLO model is proposed, which combines the EMA attention mechanism and DCNv3 deformable convolution is integrated into the YOLOv8 model, which improves the model’s feature extraction capability and inference speed for Xiaomila in complex environments, and achieves a lightweight model. First, the EMA attention mechanism is combined with the C2f module in the YOLOv8 network. The C2f module can well extract local features from the input image, and the EMA attention mechanism can control the global relationship. The two complement each other, thereby enhancing the model’s expression ability; Meanwhile, in the backbone network and head network, the DCNv3 convolution module is introduced, which can adaptively adjust the sampling position according to the input feature map, contributing to stronger feature capture capabilities for targets of different scales and a lightweight network. It also uses a depth camera to estimate the posture of Xiaomila, while analyzing and optimizing different occlusion situations. The effectiveness of the proposed method was verified through ablation experiments, model comparison experiments and attitude estimation experiments.ResultsThe experimental results indicated that the model obtained an average mean accuracy (mAP) of 88.8%, which was 1.3% higher than that of the original model. Its F1 score reached 83.2, and the GFLOPs and model sizes were 7.6G and 5.7MB respectively. The F1 score ranked the best among several networks, with the model weight and gigabit floating-point operations per second (GFLOPs) being the smallest, which are 6.2% and 8.1% lower than the original model. The loss value was the lowest during training, and the convergence speed was the fastest. Meanwhile, the attitude estimation results of 102 targets showed that the orientation was correctly estimated exceed 85% of the cases, and the average error angle was 15.91°. In the occlusion condition, 86.3% of the attitude estimation error angles were less than 40°, and the average error angle was 23.19°.DiscussionThe results show that the improved detection model can accurately identify Xiaomila targets fruits, has higher model accuracy, less computational complexity, and can better estimate the target posture

Correlation between promoter methylation of p14ARF, TMS1/ASC, and DAPK, and p53 mutation with prognosis in cholangiocarcinoma

<p>Abstract</p> <p>Background</p> <p>To study the methylation status of genes that play a role in the p53-Bax mitochondrial apoptosis pathway and its clinical significance in cholangiocarcinoma.</p> <p>Patients and Methods</p> <p>Out of 36 cases cholangiocarcinoma patients from April 2000 to May 2005 were collected.Promoter hypermethylation of <it>DAPK</it>, <it>p14^ARF</it>, and <it>ASC </it>were detected by methylation-specific PCR on cholangiocarcinoma and normal adjacent tissues samples. Mutation of the p53 gene was examined by automated sequencing. Correlation between methylation of these genes and/or <it>p53 </it>mutation status with clinical characteristics of patients was investigated by statistical analysis.</p> <p>Results</p> <p>We found 66.7% of 36 cholangiocarcinoma patients had methylation of at least one of the tumor suppressor genes analyzed. <it>p53 </it>gene mutation was found in 22 of 36 patients (61.1%). Combined <it>p53 </it>mutation and <it>DAPK, p14^ARF, and/or ASC </it>methylation was detected in 14 cases (38.9%). There were statistically significant differences in the extent of pathologic biology, differentiation, and invasion between patients with combined <it>p53 </it>mutation and <it>DAPK, p14^ARF, and/or ASC </it>methylation compared to those without (P < 0.05). The survival rate of patients with combined <it>DAPK, p14^ARF, and ASC </it>methylation and <it>p53 </it>mutation was poorer than other patients (<it>P </it>< 0.05).</p> <p>Conclusion</p> <p>Our study indicates that methylation of <it>DAPK, p14^ARF, and ASC </it>in cholangiocarcinoma is a common event. Furthermore, <it>p53 </it>mutation combined with <it>DAPK, p14^ARF, and/or ASC </it>methylation correlates with malignancy and poor prognosis.</p

Detecting Structure of Complex Network by Quantum Bosonic Dynamics

We introduce a non-interacting boson model to investigate topological structure of complex networks in the present paper. By exactly solving this model, we show that it provides a powerful analytical tool in uncovering the important properties of real-world networks. We find that the ground state degeneracy of this model is equal to the number of connected components in the network and the square of coefficients in the expansion of ground state gives the averaged time for a random walker spending at each node in the infinite time limit. Furthermore, the first excited state appears always on its largest connected component. To show usefulness of this approach in practice, we carry on also numerical simulations on some concrete complex networks. Our results are completely consistent with the previous conclusions derived by graph theory methods.Comment: 4 pages, 3 figure