Search Results (61)

Multi-branch towed array systems are an important component of subsea information collection, which is increasingly required for subsea pipeline laying and offshore platform construction as ocean energy is exploited. However, the complexity of underwater conditions poses challenges for marine towing systems when collecting information, including the possibility of towing cable collisions with protruding seabed or submerged organisms during towing system travel, or towing cable interactions during torsion. These collisions can affect and interfere with the collection of information by the towing system, and can cause damage to the towing system or even cause the towing cable to break. After the failure and detachment of the outboard guide cable of a multi-branch towing cable array, the formation of the towing system changes, and these changes are complex and related to the prevailing sea state. To study the important condition of the damaged towing system, this paper draws an analogy between the towing system and the trawl net, and speculates the formation change and mechanical response of the multi-branch towed array system after damage by combining the influencing factors of the deployment of the towing system. Full article

Submarine pipelines are highly susceptible to lateral buckling failure under service conditions of high temperature and pressure. While existing bearing capacity evaluation methods mainly focus on flat seabeds, research on the ultimate bearing capacity of pipelines buried in sloping seabeds is limited. This study applies the FELA method to analyze the ultimate bearing capacity of pipelines buried in inclined sandy seabeds under various loading directions. The results reveal that in sloping seabeds, the minimum ultimate bearing capacity (P_u,b) does not occur in the vertical direction, but rather deviates toward the outward normal direction of the seabed surface, moving toward the foot of the slope. The P_u,b is only 57% of the uplift bearing capacity in the extreme case. A predictive model was proposed to accurately determine the direction of P_u,b. The results also indicated that increasing the seabed slope angle leads to a significant reduction of bearing capacity, while increases in the internal friction angle of the seabed and the pipeline–soil interface friction angle enhance the bearing capacity. Moreover, the design code of DNV (2017) was identified as unsafe due to its omission of seabed inclination effects, and the P_u,b is only 75% of the best estimate of DNV (2017) in the extreme case. A reduction factor model was developed to mitigate this gap, offering a more reliable framework for evaluating the bearing capacity of pipelines. Full article

Diabetes mellitus often leads to peripheral neuropathy that compromises protective sensation in the feet and raises ulcer risk through mechanical overload. While prior research has introduced cellular-metamaterial-based shoe midsoles for dynamic plantar pressure redistribution, this study advances the field by delivering a complete, application-oriented workflow for physical prototyping and mechanical validation of such structures. Our pipeline integrates analytical synthesis of curved-beam unit cells, process calibration, and fabrication via thermoplastic polyurethane (TPU) fused-filament fabrication, producing customized, test-ready lattices suitable for future gait-simulation studies and in vivo assessment. Printed TPU tests showed a Young’s modulus of 44.5 MPa, ultimate tensile strength of 4.9 MPa, and strain at break ≈ 20% (Shore 84.5 A/37.2 D). The cellular unit’s compressive response was quantified by theoretical force-threshold estimates and controlled compression tests, enabling data-driven selection of unit cell geometry and arrangement for effective offloading. The response is rate-dependent: higher loading speed increases peak force and hysteresis, indicating that loading rate should be treated as a design parameter to tune dynamic behavior for the target application. Although the analytical model overestimates forces by roughly 50% on average relative to experiments, it accurately captures the influence of key geometric parameters on peak force. Accordingly, experimental data can identify cell strategic geometric parameters (i.e., Q), while the achievable maximum force can be predicted from the model by applying an appropriate correction factor. By connecting modeling, calibration, and experimental validation in one coherent path, the proposed workflow enables manufacturable lattices with controllable activation thresholds for plantar pressure redistribution and provides a practical bridge from concept to application. Full article

Spilled hydrocarbons released from oil pipeline accidents can result in long-term environmental contamination and significant damage to habitats. In this regard, evaluating actions in response to vulnerability scenarios is fundamental to emergency management and groundwater integrity. To this end, understanding the trajectories and their influence on the various parameters and characteristics of the contaminant’s fate through accurate numerical simulations can aid in developing a rapid remediation strategy. This paper develops a numerical model using the CactusHydro code, which is based on a high-resolution shock-capturing (HRSC) conservative method that accurately follows sharp discontinuities and temporal dynamics for a three-phase fluid flow. We analyze nine different emergency scenarios that represent the breaking of a diesel oil onshore pipeline in a porous medium. These scenarios encompass conditions such as dry season rupture, rainfall-induced saturation, and varying pipeline failure pressures. The influence of the spilled oil pressure and water saturation in the unsaturated zone is analyzed by following the saturation contour profiles of the three-phase fluid flow. We follow with the high-accuracy formation of shock fronts of the advective part of the migration. Additionally, the mass distribution of the expelled contaminant along the porous medium during the emergency is analyzed and quantified for the various scenarios. The results obtained indicate that the aquifer contamination strongly depends on the pressure outflow in the vertical flow. For a fixed pressure value, as water saturation increases, the mass of contaminant decreases, while the contamination speed increases, allowing the contaminant to reach extended areas. This study suggests that, even for LNAPLs, the distribution of leaked oil depends strongly on the spill pressure. If the pressure reaches 20 atm at the time of pipeline failure, then contamination may extend as deep as two meters below the water table. Additionally, different seasonal conditions can influence the spread of contaminants. This insight could directly inform guidelines and remediation measures for spill accidents. The CactusHydro code is a valuable tool for such applications. Full article

Packing food into lunch boxes requires the correct portion to be selected. Food items such as fried chicken, eggs, and sausages are straightforward to manipulate when packing. In contrast, deformable objects like spaghetti can give challenges to lunch box packing due to their fragility and tendency to break apart, and the fluctuating weight of noodles. Furthermore, achieving the correct amount is crucial for lunch box packing. This research focuses on self-learned grasping by a robotic arm to enable the ability to autonomously predict and grasp deformable objects, specifically spaghetti, to achieve the correct amount within specified ranges. We utilize deep reinforcement learning as the core learning. We developed a custom environment and policy network along a real-world scenario that was simplified as in a food factory, incorporating multi-sensors to observe the environment and pipeline to work with a real robotic arm. Through the study and experiments, our results show that the robot can grasp the spaghetti within the desired ranges, although occasional failures were caused by the nature of the deformable object. Addressing the problem under varying environmental conditions such as data augmentation can partially help model prediction. The study highlights the potential of combining deep learning with robotic manipulation for complex deformable object tasks, offering insight for applications in automated food handling and other industries. Full article

Mitochondria are critical for cellular energy, and while large deletions in their genome (mtDNA) are linked to primary mitochondrial diseases, their significance in cancer is less understood. Given cancer’s metabolic nature, investigating mtDNA deletions in tumors at various stages could provide insights into disease origins and treatment responses. In this study, we analyzed 148 bone marrow samples from 129 pediatric patients with B-cell (B-ALL) and T-cell (T-ALL) acute lymphoblastic leukemia at diagnosis, remission, and relapse using long-range PCR, next-generation sequencing, and the Splice-Break2 pipeline. Both T-ALL and B-ALL exhibited significantly more mtDNA deletions than did the controls, with T-ALL showing a ~100-fold increase and B-ALL a ~15-fold increase. The T-ALL samples also exhibited larger deletions (median size > 2000 bp) and greater heterogeneity, suggesting increased mitochondrial instability. Clustering analysis revealed distinct deletion profiles between ALL subtypes and across disease stages. Notably, large clonal deletions were detected in some B-ALL remission samples, including one affecting up to 88% of mtDNA molecules, which points toward treatment-driven selection or toxicity. A multivariate analysis confirmed that disease type, timepoint, and WHO subtype significantly influenced mtDNA deletion metrics, while age and gender did not. These findings suggest that mtDNA deletion profiling could serve as a biomarker for pediatric ALL and may indicate mitochondrial toxicity contributing to late effects in survivors. Full article

Water distribution is no arguably the most important factor in modern times, and water leak breaks are typically a consequence of failures in water distribution networks. But pipeline leakage breaks have become one of the most frequent consequences affecting the operation of water distribution networks (WDNs) and monitoring their health is often complicated. This paper proposes a leakage break diagnosis method based on an LSTM-FCN neural network model from high-frequency pressure data. Data preprocessing is used to avoid the influence of noise and information redundancy, and the LSTM module and the FCN module are used to extract and concatenate different leakage break features. The leakage break feature is sent to a dense classifier to obtain the predicted result. Two sample sets, steady state and water consumption, were obtained to verify the performance of the proposed leakage break diagnosis method. Three other models, LSTM, FCN, and ANN, were compared using the sample sets. The proposed LSTM-FCN model achieved an overall accuracy of 85% for leakage break detection, illustrating that the model could effectively learn the leakage break features in high-frequency time-series data and had a high accuracy for leakage break detection and leakage break degree prediction of new samples in WDNs. Meanwhile, the proposed method also had good adaptability to the variations in water consumption in actual WDNs. Full article

This study presents a systematic optimization of GTAW welding parameters to achieve a pipe-to-pipe butt weld with a root height consistently below 2 mm when joining stainless-steel 316L material, employing the Taguchi design of experiments. To the authors’ knowledge, no similar studies have been conducted to explore the optimization of welding parameters specifically aimed at minimizing weld root height under 2 mm in stainless-steel EO pipeline welding applications. This gap in the existing literature highlights the innovative aspect of the current study, which seeks to address these challenges and improve welding precision and joint reliability. Root height, also referred to as weld root reinforcement, is defined as the excess weld metal protruding beyond the inner surface root side of a butt-welded joint. The input parameters considered are the welding current, voltage, speed, and root gap configurations of 1, 1.5, and 2 mm. Welding was performed according to the Taguchi L-09 experimental design. Nine weld samples were evaluated using liquid penetrant testing to detect surface-breaking defects, such as porosity, laps, and cracks; X-ray radiography to identify internal defects; and profile radiography to assess erosion, corrosion, and root height. Among the nine welded plate samples, the optimal root height (less than 2 mm) was selected and further validated through the welding of a one-pipe sample. An additional macro examination was conducted to confirm the root height and assess the overall root weld integrity and quality. Full article

The energy dissipation of hydraulic structures is crucial to the overall safety and stability of hydraulic engineering projects. In order to isolate energy dissipators from hydraulic engineering projects and address the issues of vibration damage caused by the discharge structures, a new type of vertical jet energy dissipator was developed by placing crushing needles at the nozzle of the vertical jet pipeline. The crushing needles were mainly used to break the high-energy jet into several smaller jets. As the air is mixed with the water flow, the mechanical energy of the water flow is converted into internal energy and dissipated in the air. The structural parameters of the vertical jet energy dissipators include the size and number of crushing needles. In this paper, the first-order and second-order statistical characteristics and energy dissipation rate of vertical jet energy dissipators under different structural parameters are studied by means of numerical simulation and a physical model test. The results show that, within the scope of this study, the energy dissipation rate of a vertical jet increases with the increase in Reynolds number, the number of crushing needles, and the size of crushing needles; and the energy dissipation rate of the vertical jet increases by 1.04 to 4.89 times compared with that without crushing needles. Under the same Reynolds number, the height of the jet decreases with the increase in the number of crushing needles and the size of the crushing needles. With the vertical development of the flow, the vertical average velocity of the vertical jet energy dissipator is getting smaller and smaller. Adding crushing needles will hinder the upward diffusion of the jet, reduce the height of the jet, and accelerate the attenuation of the jet velocity. As a statistic result regarding the fluid stress, the Reynolds stress along the axis shows a slow upward trend at the potential core, soars at the shear layer, and finally decreases at the end of the jet. The flow has a higher convective transportation intensity in the lateral direction than in other directions. The addition of crushing needles can, to some extent, affect the fluid transport in that area, thereby altering the pressure in the region and dissipating the mechanical energy of the flow-induced vibrations when the jet impacts the crushing needles. The vertical jet-type energy dissipator proposed in this study addresses key engineering challenges, such as terrain constraints and the need for flexible design solutions. Its ability to efficiently dissipate energy while maintaining adaptability makes it a valuable tool for hydraulic engineers designing energy dissipation systems. The conclusions of this study provide a theoretical basis for the application of vertical jet energy dissipators. Full article

High-temperature pipelines, as core facilities in the fields of petrochemical and power, are constantly exposed to extreme working conditions ranging from 450 to 600 °C, facing risks of stress corrosion, creep damage, and other defects. Traditional shutdown inspections are time-consuming and costly. Meanwhile, existing electromagnetic acoustic transducers (EMATs) are restricted by their high-temperature tolerance (≤500 °C) and short-term stability (effective working duration < 5 min). This paper proposes a high-frequency circumferential guided wave (CLamb wave) EMAT based on a Halbach permanent magnet array. Through magnetic circuit optimization (Halbach array) and multi-layer insulation design, it enables continuous and stable detection on the surface of 600 °C pipelines for 10 min. The simulations revealed that the Halbach array increased the magnetic flux density by 1.4 times and the total displacement amplitude by 2 times at a magnet’s large lift-off (9 mm). The experimental results show that the internal temperature of the sensor remained stable below 167 °C at 600 °C. It was capable of detecting the smallest defect of a φ3 mm half-hole (depth half of the wall thickness), with a signal attenuation rate of only 0.32%/min. The signal amplitude of Q235 pipelines under high-temperature short-term detection (<5 min) was 1.5 times higher than that at room temperature. However, material degradation under high temperature led to insufficient long-term stability. This study breaks through the bottleneck of long-term detection of high-temperature EMATs, providing a new scheme for efficient online detection of high-temperature pipelines. Full article

Background: KMT2A rearrangements occur in ~10% of acute myeloid leukemia (AML) cases and are critical for classification, risk stratification, and use of targeted therapy. However, insertions involving the KMT2A gene can evade detection using chromosomal analysis and/or fluorescence in situ hybridization (FISH). Methods: We present a case of a 22-year-old woman with acute monoblastic leukemia harboring a cryptic KMT2A::AFDN fusion identified by RNA sequencing. Initial FISH showed a 3′ KMT2A deletion, while conventional karyotyping and the automated bioinformatic pipeline for optical genome mapping (OGM) did not identify the canonical translocation. Results: To resolve these discrepancies, metaphase KMT2A FISH (break-apart fusion probe) was performed to assess whether KMT2A was translocated to another chromosome. However, the results did not support this possibility. As the fusion signal remained on the normal chromosome 11, with the 5′ KMT2A signal localized to the derivative chromosome 11. A subsequent manual review of the OGM data revealed a cryptic ~300 kb insertion of AFDN into the 3′ region of KMT2A, reconciling the discrepancies between chromosomal analysis, FISH, and RNA fusion results. Conclusions: This case highlights the importance of integrating multiple testing modalities with expert review when there is a discrepancy. Our findings emphasize the need for a comprehensive approach to genomic assessment to enhance diagnostic accuracy and guide therapeutic decision-making. Full article

The operational condition of fire water supply aims to ensure the continuous and reliable supply of high-pressure water in emergency situations. Assuming a fire breaks out in a mountain village located far from the city center, due to the significantly higher flow rate and velocity of the water supply pipeline compared to normal operating conditions, any malfunction or shutdown of the pump caused by improper operation could result in catastrophic damage to the pipeline system. In response to the call for sustainable development, addressing this urgent academic challenge means finding a way to safely and economically maintain a continuous water supply to the target water demand point, even under extreme accident conditions. In this paper, drawing on engineering examples, we considered air tanks with varying process parameters installed at multiple locations within a water conveyance system to prevent water hammer and ensure water supply safety. To ensure that air tanks are of high quality and cost-effective after procurement and use, a multi-objective optimization design model comprising fitting, optimization, and evaluation plates was constructed, aimed at selecting certain process parameters. In the multi-objective optimization design model, Latin hypercube sampling improved by simulated annealing (LHS-SA), stepwise regression analysis (SRA), the Multi-Objective Whale Optimization Algorithm (MOWOA), and the Multi-Criteria Decision Analysis (MCDA) method with various weight biases are used to ensure the rationality of the optimization process. By comparing the optimization results obtained using these different MCDA methods, it is evident that the results output after AHP-EWM evaluation tend to be economic indicators, whereas the results output after FN-MABAC evaluation tend to be safety indicators. In addition, according to the sensitivity analysis of weight distribution, it can be inferred that the changes in maximum transient pressure head caused by water hammer have the most significant impact on final decision-making. Full article

Base-editing technologies, particularly cytosine base editors (CBEs), allow precise gene modification without introducing double-strand breaks; however, unintended RNA off-target effects remain a critical concern and are under studied. To address this gap, we developed the Pipeline for CRISPR-induced Transcriptome-wide Unintended RNA Editing (PiCTURE), a standardized computational pipeline for detecting and quantifying transcriptome-wide CBE-induced RNA off-target events. PiCTURE identifies both canonical ACW (W = A or T/U) motif-dependent and non-canonical RNA off-targets, revealing a broader WCW motif that underlies many unanticipated edits. Additionally, we developed two machine learning models based on the DNABERT-2 language model, termed STL and SNL, which outperformed motif-only approaches in terms of accuracy, precision, recall, and F1 score. To demonstrate the practical application of our predictive model for CBE-induced RNA off-target risk, we integrated PiCTURE outputs with the Predicting RNA Off-target compared with Tissue-specific Expression for Caring for Tissue and Organ (PROTECTiO) pipeline and estimated RNA off-target risk for each transcript showing tissue-specific expression. The analysis revealed differences among tissues: while the brain and ovaries exhibited relatively low off-target burden, the colon and lungs displayed relatively high risks. Our study provides a comprehensive framework for RNA off-target profiling, emphasizing the importance of advanced machine learning-based classifiers in CBE safety evaluations and offering valuable insights to inform the development of safer genome-editing therapies. Full article

Acid-fracturing technology has been applied to form pathways between deep oil/gas resources and oil production pipelines. The acid fracturing fluid is required to have special slow-release performance, with no acidity at low temperatures, while steadily generating acid at high temperatures underground. At present, commercial acid systems in oilfields present problems such as the uncontrollable release effect, high costs, and significant pollution. In this research, we designed an innovative chloroformate material and investigated the release of the acid at various temperatures. This new chloroformate material reacts slowly with water at room temperature, and can completely react with water to form hydrochloric acid at high temperatures, without residual organic chlorine and other harmful substances; thus, it is suitable for use as an acid agent in oilfields. To isolate the acid-release core material from the outer water phase, we encapsulated the former with various materials, such as cross-linked polyacrylate or polystyrene, to obtain microcapsules. By slowly breaking and degrading the shell layer at a high temperature, the goal of no acid being released at low temperatures with slow acid generation at a high temperature was achieved. The microcapsules were prepared using radical polymerization and the phase separation method. Furthermore, scanning electron microscopy, differential scanning calorimetry, chemical titration analysis, and other methods were used to characterize the structure and the sustained acid release of microcapsules. The results of thermogravimetry and other experiments showed that the prepared microcapsules successfully coated the chloroformate material. In contrast to the bare material, the slow-release performance of the microcapsules was significantly improved, and the continuous acid generating time was able to reach more than 10 h. Under optimum conditions, microcapsules with a uniform particle size with a sustained-release acid core were prepared, and the encapsulation efficiency reached up to 60%. Compared with traditional acid-release systems, the new system prepared in this study has better acid-release performance at high temperatures, while the product is both clean and convenient to use. Multiple important parameters, such as microcapsule particle size, can also be controlled by varying the experimental conditions to meet the needs of different oil/gas extraction environments. In summary, we prepared a promising new and efficient slow-release acid generation system, which has unique practical significance for optimizing current oilfield acid-fracturing technology. Full article

The degradation and failure of the urban water supply network may lead to serious safety hazards, including pipe breaks, water supply interruptions, water resource losses, and contaminant intrusions. The risk evaluation of water supply pipeline failure in a distribution network is a challenging task, because most of the available data cannot fully reflect pipeline failure events and many of the mechanisms still cannot be fully understood. Therefore, a predictive model is urgently needed to assess pipeline failure risk based on available data. In this paper, based on the traditional risk assessment theory, seven main factors affecting pipeline failure are selected and scored, and then a pipeline failure model is established by using the particle swarm optimization (PSO) neural network. The model uses the neural network training of historical data to evaluate the failure of the water supply pipeline, and the PSO is used to optimize the neural network to effectively improve the training time and accuracy. The model error and correlation coefficient are 0.003 and 0.987, respectively. The proposed model can be used as a powerful support tool to assist infrastructure managers and pipeline maintainers in their plans and decision-making. Full article