Search

Introduction: Patients presenting with head and neck squamous cell carcinoma of unknown primary (HNSCCUP) remain challenging clinical scenarios as large variation exists in practices used to locate the primary. Objective: The objective of this systematic review is to review of the literature and offer recommendations for oropharyngeal biopsies in HNSCCUP. Method: Pubmed, Medline and Embase were searched to identify studies from inception to October 2021. The Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) guidelines were followed. Results: A total of 483 articles were included and screened, 41 studies met the inclusion criteria, including over 3400 patients from the original articles (122 of these patients were reported on in two sequential articles by a single author – table 1) and 4 large metaanalyses including 1852 patients. The primary site identification rate following random biopsies or deep tissue biopsies is less than 5% in most studies. The mean detection rate following ipsilateral tonsillectomy is 34%; two pooled analyses indicate that the mean detection rate following tongue base mucosectomy is 64%, with this figure rising when the tonsils are negative. Conclusions: High level evidence is lacking, with heterogeneity in the reported studies. Published meta‐analyses are based on retrospective data. There is little evidence supporting the practice of random/non‐directed oropharyngeal biopsies. Available evidence supports palatine tonsillectomy and tongue base mucosectomy compared to deep tissue biopsies. [ABSTRACT FROM AUTHOR]

Various models have been proposed to estimate the TBM penetration rate. Generally, the input parameters of these models can be divided into two categories: Machine parameters and geological engineering parameters. The engineering geological parameters will significantly influence the penetration rate if the machine operational parameters are kept within a reasonable near-optimal range. However, while some performance prediction models can be used for many common project settings, they have lower accuracy in certain applications. This study compared the observed penetration rate of a hard rock TBM with those predicted by MCSM, Norwegian University of Science and Technology (NTNU), Farrokh–Rostami, and Ramezanzadeh’s models in the Kerman water tunnel (KWT). Next, joint survey data are collected from the different zones of the KWT. For this purpose, a 3D discrete fracture network (DFN) model code was generated in Mathematica© version 13. The joint data’s orientation, persistence, and spacing were used to develop a 3D-DFN model for estimating the blockiness rate (BR) index. The BR index is the actual joint intensity in 2D (P21) and 3D (P32). In this study, the BR index is the newest rock mass parameter introduced and used to predict the penetration rate of TBM. This index can serve as a rock mass parameter that provides excellent and realistic results for predicting penetration rate (PR). The corresponding determination coefficient values of the PR with P32 and P21 are R2 = 0.96 and R2 = 0.98, respectively, and with CIA and UCS, are R2 = 0.42 and R2 = 0.49, respectively. Furthermore, using the DFN model showed its potential to be an accurate and reliable method for the overall estimation of the in-situ rock mass fragmentation, which highly controls the penetration rate of TBM. Research Highlights: The penetration rate of a hard rock TBM was compared with the NTNU, MCSM, Farrokh-Rostami, and Ramezanzadeh predictive models in the Kerman water tunnel (KWT). A 3D-Discrete fracture network (DFN) model code was generated. Four different zones of KWT were studied to discriminate rock mass parameters or intact rock parameters that affect the penetration rate of TBM. The BR index is the newest rock mass parameter that has been introduced and used to predict the penetration rate of TBM. The Blockiness Rate (BR) index as rock mass parameters has verified that it highly influences the penetration rate of TBM. [ABSTRACT FROM AUTHOR]

In order to study the rock-breaking process of a 17-inch disc-type cutterhead in a full-face tunnel boring machine (TBM), we utilized the discrete element method software EDEM to analyze the in-fluence of relevant parameters (cutter spacing, penetration depth, installation radius, phase difference) on rock-breaking loads and efficiency. Firstly, validate the rationality of the discrete element model for the disc cutter rock-breaking process. Subsequently, establish a simulation of sequential rock-breaking with multiple rotating disc cutters and analyze the load characteristics as well as specific energy consumption. Simulation results indicate that within certain parameter ranges, an increase in cutter penetration depth leads to an increase in average load force, while an increase in cutter spacing and installation radius initially results in an increase in average load force followed by a decrease. An increase in phase difference results in an initial decrease in average load force followed by an increase. Based on orthogonal tests, a combination of rock-breaking parameters with values of 100 mm for cutter spacing, 8 mm for penetration depth, 650 mm for installation radius, and 45° for phase difference was found to yield lower specific energy consumption. This method can provide reference for cutter arrangement and cutterhead performance prediction. [ABSTRACT FROM AUTHOR]

Two series of experiments were carried out to examine pressurised bentonite slurry infiltration into saturated sand columns. Three types of sand were examined, and water–bentonite and water–bentonite–sand slurries were used in series 1 and 2, respectively. Series 1 investigated the effect of sand particle size and series 2 examined the effect of the fine-sand particle content in the slurry. Scanning electron microscopy (SEM) imaging was used to observe the morphological features of the dry slurry-infiltrated sand samples. A solution for the infiltration distance during mud spurt for water–bentonite–sand slurry infiltration was verified using the data from series 2. The infiltration test results showed that the hydraulic conductivity of the slurry-infiltrated coarse sand for slurry in series 2 was lower than that in series 1. Visual observations and the SEM images showed that sand particles were bound to a bentonite film, indicating that, during infiltration, the channels for fluid flow among the sand particles are blocked by the bentonite particles adhered to the sand particles. The solution for the infiltration distance during mud spurt for water–bentonite–sand slurry infiltration showed good agreement with the experimental results. [ABSTRACT FROM AUTHOR]

This paper introduces a test system for microwave-assisted dual-mode mechanical cutting of hard rock under true triaxial compression. The test system was developed by Northeastern University, China, to simulate the cutting and breaking of hard rock by a tunnel boring machine (TBM). The test system is mainly composed of a dual-mode mechanical cutting subsystem, a true triaxial loading subsystem and a high-power microwave presplitting subsystem. The system performs dual-mode cutting under true triaxial stress, applies a single sensor to monitor the three-dimensional force of the cutter head, and integrates the reduction in the vibration and resistance to torsion during the cutting process. Mechanical cutting tests of basalt under different amounts of microwave irradiation and true triaxial stress conditions were conducted in Chifeng, Inner Mongolia, China. The results showed that microwave radiation presplitting effectively improved the efficiency of mechanical rock breaking. However, after 180 s of microwave irradiation, true triaxial high stress inhibited the mechanical breaking of basalt in terms of the overall excavation depth. During the tests, each system performed stably. The test results verified the reliability of the test system. Highlights: A true triaxial stress microwave-assisted mechanical dual-mode cutting test system is independently developed. The proposed system simulates rock breaking by a microwave-assisted roadheader under different ground stress conditions. The cutting test system innovates in three main facets: it carries out a dual-mode cutting test system in rock breaking; it realizes a unified monitoring output of a single sensor for the three-dimensional force; and it integrates the seismic resistance and torsion resistance to create a smooth system body. As the cutting test is conducted, the effective influence range of microwave radiation on rock is verified, and the degree of influence of true triaxial high stress on microwave-assisted mechanical cutting is revealed, providing guidance for deep microwave-assisted rock breaking of roadheaders. The necessity and feasibility of the system development is thus verified. [ABSTRACT FROM AUTHOR]

Tunnel boring machines (TBMs) are used to excavate tunnels in a manner where the rock is constantly penetrated with rotating cutter heads. Fine particles of the rock minerals are thereby generated. Workers on and in the vicinity of the TBM are exposed to particulate matter (PM) consisting of bedrock minerals including α-quartz. Exposure to respirable α-quartz remains a concern because of the respiratory diseases associated with this exposure. The particle size distribution of PM and α-quartz is of special importance because of its influence on adverse health effects, monitoring and control strategies as well as accurate quantification of α-quartz concentrations. The major aim of our study was therefore to investigate the particle size distribution of airborne PM and α-quartz generated during tunnel excavation using TBMs in an area dominated by gneiss, a metamorphic type of rock. Sioutas cascade impactors were used to collect personal samples on 3 separate days. The impactor fractionates the dust in 5 size fractions, from 10 µm down to below 0.25 µm. The filters were weighted, and the α-quartz concentrations were quantified using X-ray diffraction (XRD) analysis and the NIOSH 7500 method on the 5 size fractions. Other minerals were determined using Rietveld refinement XRD analysis. The size and elemental composition of individual particles were investigated by scanning electron microscopy. The majority of PM mass was collected on the first 3 stages (aerodynamic diameter = 10 to 0.5 µm) of the Sioutas cascade impactor. No observable differences were found for the size distribution of the collected PM and α-quartz for the 3 sampling days nor the various work tasks. However, the α-quartz proportion varied for the 3 sampling days demonstrating a dependence on geology. The collected α-quartz consisted of more particles with sizes below 1 µm than the calibration material, which most likely affected the accuracy of the measured respirable α-quartz concentrations. This potential systematic error is important to keep in mind when analyzing α-quartz from occupational samples. Knowledge of the particle size distribution is also important for control measures, which should target particle sizes that efficiently capture the respirable α-quartz concentration. [ABSTRACT FROM AUTHOR]

Hard rock tunnel boring machines (TBMs) are increasingly widely used in tunnel construction today; however, TBMs are deeply buried underground and have a low perception of the underground surrounding rock conditions and excavation parameters. In order to ensure the safety of TBM digging, this paper describes the research carried out relating to the accurate prediction of TBM digging parameters and the precise prediction of tunnel surrounding rock grades. Based on the on-site excavation parameters and geological data of a certain water diversion project in Xinjiang, the thrust, torque, rotational speed, net excavation speed, construction speed, and excavation specific energy of the stable section of TBM excavation are selected as the input parameters for the model. A convolutional neural network optimized–long short-term time series prediction model (CNN-LSTM model) is established to predict the excavation parameters under various levels of surrounding rock conditions. The research results indicate that the CNN-LSTM model has a high prediction accuracy, with most data having a relative prediction error rate (Er) within 10%, root mean square error (RMSE) within 5%, mean absolute percentage error (MAPE) within 10%, and goodness of fit (R2) above 0.9. The model can assist in parameter setting, engineering planning and disposal of high-risk holes in the TBM digging process, and improve the safety level of TBM digging. [ABSTRACT FROM AUTHOR]

Mud caking on shield cutterhead is a critical issue for tunnel safety, and temperature and duration are factors that can affect the characteristics of mud cake. Therefore, the aim of this study is to explore the characteristics of different temperatures and action times on the adhesion and hardness of red-bed geological mud cake. A self-designed experimental apparatus was used to simulate the adhesion of mud cake on the cutterhead. The adhesion and hardness of the mud cake were analyzed through mud cake shedding tests and hardness tests. In addition, water film theory is used to analyze the adhesion mechanism of the mud cake. The results indicate that temperature and duration are key factors affecting mud cake shedding. Within the range of 25~150 °C, mud cake shedding efficiency is positively correlated with temperature and duration. However, temperatures above 150 °C promote the sintering of the mud cake, reducing its shedding efficiency. The hardness of the mud cake increases with temperatures above 150 °C, where the mud cake hardens and sinters, increasing the difficulty of shield tunneling. The water content of mud cake is influenced by temperature and time, affecting the amount of mud cake shedding. As the water content increases, the shedding initially decreases and then increases, reaching its minimum at about 30%, where the adhesion is strongest. By controlling the temperature and time, the water content can be optimized, improving the handling of mud cake. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The construction of tunnels in conditions of dense urban development affects buildings, structures, and engineering communications located at the surface. In this work, through dispersion analysis, factors influencing the settlement of the earth's surface and buildings during tunneling were selected. Subsequently, a model based on statistically significant parameters that can predict deformations at the pre-design stage was created. This research was conducted using data from geotechnical monitoring obtained during the construction of underground structures, with information about the technological parameters of shield tunneling in the construction of the single-track lines of the Moscow Metro using TBM with face-support pressure and engineering–geological conditions. In the obtained model, there is a clear dependency between the additional displacement of the monitoring object located above the projected tunnel and the average face-support pressure causing the mentioned deformations. The response is also affected by the soil deformation model at the tunnel face, the depth of the tunnel, and the soil excavation for the installation of one ring. [ABSTRACT FROM AUTHOR]

Water content is an important factor affecting the rock-breaking efficiency of tunnel boring machine (TBM) disc cutters. However, limited efforts have been made to study the fracturing mechanism of sandstone excavation by TBM disc cutters under varying water content conditions. To investigate the breakage behavior of water-soaked sandstone by TBM disc cutters, five sets of penetration tests on sandstone specimens with different water content levels were performed. The tests were conducted using a modified RYL-600 computer-controlled rock shear rheometer. An acoustic emission (AE) monitoring system was utilized throughout the entire process to track the AE activity of the specimens. The force–depth curves of the penetration process at various water content levels were investigated. The effects of water content on AE characteristics, rock fracture properties, and specific energy were analyzed. The results indicate that AE activity can be divided into three stages: quiet period, slow rise period, and active period. With increasing water content, peak penetration force, consumed energy, and specific energy decrease gradually, while chip volume increases. Water promotes mutual penetration of surface and internal cracks of the specimen, resulting in the formation of larger chip volumes. These findings provide theoretical guidance for designing and improving TBM cutter head parameters in water-rich soft rock formations. [ABSTRACT FROM AUTHOR]

This paper presents the outcomes of a sequence of three-dimensional numerical simulation models conducted in linear cutting mode, employing the LS-DYNA software. The primary objective was to scrutinize the side force values exerted on the gauge cutters. To accomplish this, an assortment of simulation models was meticulously constructed and executed, employing the Lagrange and SPG computational algorithms, along with the JHC and RHT constitutive material models. By comparing the outcomes of these models with the linear cutting experiments documented in the literature, specifically concerning the Colorado red Granite, it was determined that the SPG computational algorithm and the RHT constitutive material model proved to be the most suitable for simulating rock-cutting scenarios. Building upon the chosen computational algorithm and constitutive material model, a series of numerical models was then crafted to simulate the penetration of gauge cutters in both longitudinal and transverse orientations relative to their tips. Subsequently, the applied side forces were extracted, and a statistical model was developed to accurately predict the side forces experienced by the gauge cutters, yielding a coefficient of determination of 93%. [ABSTRACT FROM AUTHOR]

Research on automation and intelligent operation of tunnel boring machine (TBM) is receiving more and more attention, benefiting from the increasing construction data. However, most studies on TBM operations optimization were trained by the labels of human drivers’ decisions, which were subjective and stochastic. As a result, the control parameters suggested by these models could hardly surpass the performance of a human driver, even the possibility of subjective incorrect decisions. Considering that the geomechanical feedback to TBM under drivers’ actions is objective, in this paper, a transformer-based model called the geological response for tunnel boring machine (GRTBM), is proposed to learn the relationship between operation-adjust and TBM monitoring changes. Additionally, with the model-based offline reinforcement learning, this paper provided a novel approach to optimizing the TBM excavation operations. The decision processes, recorded in the Yin-song TBM project for a waterway tunnel in Jilin Province of China, were used for the validation of the model. By adopting an implicit perception of geological conditions in the GRTBM model, the suggested method achieved the desired state within a single action, greatly outperformed the practical adjustments where 500 s were taken, revealing the fact that the proposed model has the potential to surpass the capability of human beings.

Tunnelling with a Tunnel Boring Machine (TBM) offers several advantages over conventional tunnelling methods when covering long distances, particularly regarding time, safety, and environmental impact. Prior to starting a TBM project, performance analysis is a crucial stage necessary to inform the initial investment decision and project cost estimation. However, this analysis requires extensive fieldwork and laboratory studies. The Advance Rate (AR), calculated from the Utilization Factor (U) – the ratio of excavation time to total project time – is a widely accepted measure of TBM performance. Total project time encompasses various parameters, including boring time, cutter inspection and replacement times, and constant factors like re-gripping, service, and maintenance times. In this study, we employed analytical methods, statistical analysis, and genetic programming approaches to evaluate the AR and thus enhance TBM performance analysis. Gamma tests were conducted to identify interrelated parameters in TBM operations. The results from these tests showed that the Applied Force per Cutter (FN) and penetration values (together forming the Field Penetration Index or FPI) are useful in estimating cutter consumption. While FN can be determined through laboratory tests, its field determination is challenging. We have developed several charts and a function derived from genetic programming to estimate the AR of a TBM. The study demonstrated that this function, formulated using genetic programming, possesses strong predictive capability and can significantly improve TBM performance analysis. [ABSTRACT FROM AUTHOR]

The generation of CO2 is an important element in assessing the environmental impact generated in a tunnel construction project, making this knowledge very useful for evaluating different alternatives. In this study, an analysis of the carbon footprint has been carried out, including the main elements during the construction phase of a tunnel employing a tunnel boring machine (TBM). The research proposes several options for an easy and quick calculation of CO2 generation in a design phase. Its determination can be crucial for decision-making before and during the execution of any tunnel in the near future. The estimation models have been validated based on real case studies, defining the carbon footprint of each construction element. The proposed procedure can apply to any tunnel. However, it should be noted that it is an approximate analysis, and the limitations described in each section should be considered. The main CO2 generator found in the construction process is the lining element; the percentage varies between 50% in tunnels with smaller diameters (4–5 m) and 75% for tunnels with larger diameters (9–10 m), followed by the auxiliary elements, 16%, and the operation of the tunnel boring machine itself, 11.2%, while the other parts remain in a range between 1.3 and 5.7%. This knowledge makes it possible to define the aspects on which efforts should be focussed to reduce the carbon footprint of the tunnel construction process. [ABSTRACT FROM AUTHOR]

Accurate evaluation of cutter life at different cutter positions on the cutter head is helpful to determine the time of cutter change and reduce the time of cutter wear measurement, which is of great significance to improve the tunneling efficiency of tunnel boring machine (TBM) projects. Unfortunately, there is no unified cutter life evaluation index now. The field data of cutter wear are collected from a section of a long TBM tunneling water conveyance tunnel in China. Two kinds of cutter life evaluation indexes (based on the radial wear extent of cutter rings and replacement number of cutter rings) are selected and the variation rule between these two kinds of indexes with cutter installation radius is statistically analyzed. The results show that the regression relationships between the two kinds of cutter life evaluation indexes and installation radius mainly present linear functions and quadratic functions. Those regression relationships are affected by factors such as wear type, installation angle, cutter spacing, influence width, and allowable limit wear extent of cutter rings. Considering the calculation accuracy of the evaluation index, the actual working conditions of the disc cutter, and ignoring the influence of tunnel diameter, it is recommended to preferentially choose the radial wear extent of cutter rings per unit rolling distance as the evaluation index of cutter life. The research results can provide a reference for the selection of cutter life evaluation index, prediction of disc cutter life at different cutter positions, and establishment of cutter life prediction mode. [ABSTRACT FROM AUTHOR]

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The complex red-bed geology is primarily composed of iron-rich sedimentary rock layers with clay minerals as a major component. The soil water content exceeds 30%, and its high viscosity and water content lead to the easy formation of mud cake on the cutterhead, endangering the safety and progress of construction, which poses a significant challenge for tunnel boring machines (TBMs). The use of dispersants to eliminate mud cake is a common method in engineering projects. This paper presents an improved disintegration experiment instrument to study the disintegration characteristics of mud cake from the red-bed geology under different dispersant solutions, proposing a dispersant formulation suitable for the red-bed geology of the Haizhu Bay Tunnel project. The results indicate that mud cake samples exhibit a moderate disintegration effect in pure water. Furthermore, it has been observed that the disintegration effect decreases as the thickness of mud cake increases. Sodium silicate solution was not suitable for treating the red-bed geological mud cake, while sodium hexametaphosphate and oxalic acid solutions had a good promoting effect on the disintegration of red-bed geological mud cake. However, there was a threshold for the dispersant concentration; exceeding this threshold actually worsened the disintegration effect. Ultimately, the engineering application of a 10% oxalic acid solution, which proved effective in disintegrating the mud cake, significantly enhanced the excavation efficiency in the Haizhu Bay Tunnel project. [ABSTRACT FROM AUTHOR]

The advance rate (AR) of tunnel boring machines (TBMs) plays a pivotal role in evaluating their efficiency in tunnel engineering projects. This study focuses on the development of precise prediction models for TBM performance employing advanced algorithms, including gene expression programming, time series analysis, multivariate regression, artificial neural networks, particle aggregation algorithms, genetic algorithms, adaptive neural fuzzy inference systems, and support vector machines. The AR, serving as a performance metric, becomes the specific target for prediction models. A test database comprising 3597 datasets was curated from a tunneling project at the Sar Pol Zahab, Bazi Daraz water transfer tunnel. Utilizing 21 parameters as input variables, intelligent AR models were formulated based on comprehensive training and testing patterns, incorporating geological features and the key machine parameters influencing AR. Quantitative evaluation of the models involved statistical indicators such as root mean square error (RMSE), coefficient of determination (R2), and variance calculation. Comparative analysis based on RMSE, MAE, MAPE, VAF, and R2 superior gene expression function models showed that the gene expression algorithm with 1.41, 0.66, 6.33, 98.88, and 0.95 ahead of the nose is better than other approaches. These results underscore the efficacy of the gene expression programming-based model, suggesting its potential to yield a novel functional equation for accurate TBM performance prediction. [ABSTRACT FROM AUTHOR]

Tunnel boring machine (TBM) reducers are important components of TBM's cutter-head drive system. In order to reveal the dynamic characteristics of the two-stage planetary gear transmission system of the TBM reducer, the influence factors such as tooth surface friction, the time-varying meshing stiffness, the backlash and meshing error of the two-stage planetary gear transmission system of the TBM reducer are considered. The torsional dynamics model of the two-stage planetary gear transmission system of the TBM reducer is established by the lumped parameter method, and its dynamic characteristics are solved and analyzed. The inherent characteristic analysis results show three vibration modes of the planetary gear train: rigid body vibration mode, torsional vibration mode and the planetary gear vibration mode; the vibration displacement of each gear and the dynamic meshing force between the gear pairs are obtained from the dynamic response analysis. The result lays the foundation for the dynamic optimization design of planetary gear trains.

Abstract The vibration of tunnel boring machine (TBM) is very difficult to monitor on sites, and related research on prediction methods is rare. Based on the field tunnelling test of a TBM in the Xinjiang Ehe project, the vibration information of the main beam of the TBM under different surrounding rock conditions is collected. The relationships among the tunnelling parameters, surrounding rock parameters and vibration parameters were studied. The results show that the penetration, cutter head speed, torque and thrust are important parameters affecting TBM vibration. In addition, the field penetration index and cutter head driving power index are significantly related to the root mean square of acceleration. Based on this, a multiple regression prediction model of TBM vibration is established. The model was verified and analysed via field projects, and the relative prediction error was less than 12%. This method can be used to predict the vibration of a TBM in real time through characteristic parameters without the use of a traditional monitoring system. This approach is highly important for determining the status of TBM equipment in real time.

This community service aims to enhance knowledge and expertise in organizational management and children's play module preparation for the Forum Taman Baca Masyarakat (FTBM) in Jepara Regency. The service used the Participatory Action Research (PAR) method, with the participants being representatives of TBM managers who are members of FTBM. A questionnaire was used as the instrument for evaluating the activity, and the results of which were analyzed descriptively. The service results indicate a significant increase in workshop participants' understanding. A total of 9 participants (30%) who were initially in the low understanding category succeeded in increasing to the high category, including 18 participants (60%). The workshop activity on preparing children's play modules also made a positive contribution to the participants, particularly in terms of module preparation. There was a significant increase in understanding, where 10 participants (33.33%) who were initially in the low understanding category succeeded in increasing to the high category, involving 20 participants (66.67%). This activity was successful in achieving positive results and supporting the development of participants’ skills and understanding of organizational management and module preparation.

During the construction of tunnels using tunnel-boring machines (TBMs), the wear of disc cutters is an unavoidable process. The timely replacement of worn disc cutters can have a positive effect on construction time and therefore on costs. The wear of disc cutters can be assessed using various measurement methods. The aim of this article is to show different methods of measuring and evaluating the wear of disc cutters and to present their main advantages and disadvantages. In this study, four different wear-measuring methods were used and applied to a worn double disc cutter: a macroscopic visual inspection, profile measurement with a caliper, weighing, and close-range photogrammetry. The results of the measurements showed that the worn disc cutter was subject to normal abrasive wear, with local steel chipping occurring. Based on the close-range photogrammetry measurements, a profile of the worn disc cutter was also created and compared with the original profile. It was found that the best results for the wear assessment of a disc cutter can be achieved by using several measurement methods simultaneously. The integration of different measurement and evaluation methods is therefore recommended for a comprehensive understanding of disc cutter wear. [ABSTRACT FROM AUTHOR]

In order to solve the problem of the poor adaptability of the TBM digging process to changes in geological conditions, a new TBM digging model is proposed. An ensemble learning prediction model based on XGBoost, combined with Optuna for hyperparameter optimization, enables the real-time identification of surrounding rock grades. Firstly, an original dataset was established based on the TBM tunneling parameters under different surrounding rock grades based on the KS tunnel. Subsequently, the RF–RFECV was employed for feature selection and six features were selected as the optimal feature subset according to the importance measure of random forest features and used to construct the XGBoost identification model. Furthermore, the Optuna framework was utilized to optimize the hyperparameters of XGBoost and validated by applying the established TBM dataset of the KS Tunnel. In order to verify the applicability and efficiency of the proposed model in surrounding rock grade identification, the prediction results of five commonly used machine learning models, Optuna–XGBoost, Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Decision Tree (DT), XGBoost, and PSO–XGBoost, were compared and analyzed. The main conclusions are as follows: the feature selection method based on RF–RFECV improved the accuracy by 8.26%. Among the optimal feature subset, T was the most essential feature for the model's input, while PR was the least important. The Optuna–XGBoost model proposed in this paper had higher accuracy (0.9833), precision (0.9803), recall (0.9813), and F1 score (0.9807) than other models and could be used as an effective means for the lithological identification of surrounding rock grade. [ABSTRACT FROM AUTHOR]

Introduction: Tubercular meningitis (TBM) is a serious public health problem in developing countries as it leads to significant mortality and residual neurological sequelae. The estimated mortality due to TBM in India is 1.5 per 100,000 population. In resource-limited settings, only the Ziehl-Neelsen (ZN) stain, which has very little sensitivity, is available. The World Health Organization recommended the Loop Mediated Isothermal Amplification (TB LAMP) assay for pulmonary tuberculosis only. We evaluated this test for tubercular meningitis as well. Methodology: In a cross-sectional study of 2-year duration, we have taken 239 cerebrospinal fluid samples from suspected cases of tubercular meningitis patients. ZN staining along with Mycobacteria Growth Indicator Tube (MGIT) TB culture, Xpert MTB/RIF Ultra assay, and commercial TB LAMP assay were performed for each sample. Results: Out of 239 samples, 40 samples (16.73%) were found TB LAMP assay positive, 48 samples (20.08%) were found Xpert ultra-assay positive, 12 samples (5.02%) were MGIT TB culture positive and acid-fast bacillus smear positive in ten samples (4.18 %). Out of 12 MGITpositive samples, all samples (100%) were TB LAMP and Xpert ultra positive and one sample (8.33%) was ZN smear positive. In 199 negative samples from the TB LAMP assay, eight samples were positive by Xpert, none by MGIT TB culture and AFB smear. Sensitivity and specificity were found as 100% and 87.66%, respectively, for the TB LAMP assay. Conclusion: TB LAMP assay is a rapid, cost-effective, sensitive, and specific test for tubercular meningitis infection in resource-limited settings. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The vibration of tunnel boring machine (TBM) is very difficult to monitor on sites, and related research on prediction methods is rare. Based on the field tunnelling test of a TBM in the Xinjiang Ehe project, the vibration information of the main beam of the TBM under different surrounding rock conditions is collected. The relationships among the tunnelling parameters, surrounding rock parameters and vibration parameters were studied. The results show that the penetration, cutter head speed, torque and thrust are important parameters affecting TBM vibration. In addition, the field penetration index and cutter head driving power index are significantly related to the root mean square of acceleration. Based on this, a multiple regression prediction model of TBM vibration is established. The model was verified and analysed via field projects, and the relative prediction error was less than 12%. This method can be used to predict the vibration of a TBM in real time through characteristic parameters without the use of a traditional monitoring system. This approach is highly important for determining the status of TBM equipment in real time. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

At present, the splicing of steel arches for open-type TBM suffers from the problems of labor-intensive, time-consuming, low efficiency and greater potencial risk to workers. Rock-fall and collapse caused by untimely support is still one of the main construction accidents. In this paper, a novel steel arch splicing manipulator is developed for unmanned and automated steel arch splicing, and a backstepping method based cascade control strategy is proposed to improve the trajectory tracking control performance. Firstly, the inner-loop controller is designed to compensate the flow coupling between each joint-driven hydraulic cylinder based on dynamic analysis and feedback linearization. Secondly, the adaptive robust controller is adopted for outer-loop controller design to deal with parametric uncertainties and external disturbances. Finally, the system stability is proved by Lyapunov function, then comparative experiments are conducted to verify the effectiveness and superiority of the proposed control scheme. It can be concluded that the proposed controller has a better trajectory tracking control performance, while the control input is much smoother than that of traditional PID controller. [ABSTRACT FROM AUTHOR]

In order to determine the safety status and key influencing factors of TBM tunnel construction, combined with the characteristics of TBM tunnel construction, the safety risk evaluation index system of TBM tunnel construction was built and the combination weighting method based on two-tuple linguistic was proposed. The fuzzy normal distribution under the condition of multi-level intersection was introduced as the membership function distribution of fuzzy evaluation grade and the comprehensive evaluation model of safety risk of TBM tunnel construction was built. It conducted analysis by taking the Western Water Diversion Route of Anyang City in the South-to-North Water Diversion Project as an example. The results show that the construction safety risk level is in the middle risk level, and the safety accident risk is a lower risk; technical risk, equipment risk, management risk and natural risk are medium risks; geological risk is a higher risk and should be emphasized for control. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)