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Transverse vibration of drillpipe in coring drilling is undesirable. Here, the influence of the core on drillpipe vibration is considered for the first time. Attention is focused on the vibrations of the coring drillpipe as these vibrations lead to contact and collision between drillpipe and core. A reduced-order model of drill string motion is established considering fluid load and core constraints. This model considers fluid action as distributed load and drillpipe as beam structure. The constraint of the core on lateral vibration of the drillpipe is simplified as a nonlinear force. The method of multiple scales is used to analyze the disturbance of the drillpipe’s primary resonance and harmonic resonance, and the influence law of different parameters on the drillpipe resonance is obtained. The results show that damping inhibits resonance vibration, and external excitation determines the resonance type. The existence of the core will aggravate the resonance vibration of the drillpipe. The analysis results are helpful in understanding the resonance of the drillpipe in coring drilling. Some measures to suppress resonance are given in this paper. This study can provide guidance for further research on drillpipe resonance in core drilling.

The borehole hydraulic mining method has unique advantages for underground oil shale exploitation. Breaking rock with a high-pressure water jet is a crucial step to ensure the smooth implementation of borehole hydraulic mining in oil shale. The hydraulic performance of the nozzle determines the efficiency and quality of high-pressure water jet technology. To obtain a superior hydraulic performance nozzle, based on the bionic non-smooth theory, a circular groove was selected as the bionic unit to design a bionic straight cone nozzle. The structural parameters of the circular groove include the groove depth, width, and slot pitch. The optimization objective was to minimize the pressure drop, where the fluid has the least resistance. A genetic algorithm was used to optimize the structural parameters of the circular grooves in the inlet and outlet sections of the bionic straight cone nozzle. The optimal structural parameters of the nozzle were as follows: the inlet diameter was 15 mm, the inlet length was 20 mm, the outlet diameter was 4 mm, the length-to-diameter ratio was 3, and the contraction angle was 30°. In addition, in the inlet section, the groove width, slot pitch, and groove depth were 3.9 mm, 5.2 mm, and 5.5 mm, respectively, and the number of circular grooves was 2. Moreover, in the outlet section, the groove width, slot pitch, and groove depth were 2.25 mm, 3 mm, and 5.5 mm, respectively, and the number of circular grooves was 2. The CFD numerical simulation results showed that under the same numerical simulation conditions, compared with the conventional straight cone nozzle, the bionic straight cone nozzle velocity increase rate could reach 13.45%. The research results can provide scientific and valuable references for borehole hydraulic mining of high-pressure water jets in oil shale drilling.

Traditional coiled tubing radial drilling with the same diameter cannot support deep and ultra-deep wells for high-pressure hydraulic jet drilling due to small diameter and sizeable hydraulic loss over long distances. The novel downhole movable pipe radial hydraulic drilling technique extracts a small diameter high-pressure injection pipe from the (tubing pipe) oil pipe and then drills it horizontally into the formation to form a radial hole. Dynamic sealing is the core of this technology, which achieves high-pressure fluid sealing while ensuring the injection pipe smoothly slides out of the oil pipe. A sealing tool is designed between the tubing and the injection pipe to prevent the leakage of high-pressure fluid. In this paper, the finite element model of the sealing tool was established, and the deformation and stress of the sealing tool under different interference and fluid pressure were simulated and analyzed. The relationship between stress distribution and contact pressure under the corresponding conditions was obtained. The results show that the von Mises stress increases significantly with the increase in fluid pressure under certain interference conditions. When the fluid pressure was 35 MPa, 52 MPa, and 70 MPa, the maximum von Mises stress was 29.65 MPa, 30.87 MPa, and 32.47 MPa, respectively, within a reasonable range. The stress peak area changes simultaneously, indicating that the possible damage location changes with the fluid pressure change. The maximum contact pressure between the sealing ring and the smooth rod increases with interference and fluid pressure, which always meets the sealing conditions. A laboratory test bench was built to test the high-pressure sealing performance of the sealing tool. Combined with the simulation data and test results, the downhole continuous rod dynamic sealing tool was modified to provide theoretical guidance for practical application.

Neuromorphic computing, a promising solution to the von Neumann bottleneck, is paving the way for the development of next‐generation computing and sensing systems. Axon‐multisynapse systems enable the execution of sophisticated tasks, making them not only desirable but essential for future applications in this field. Anisotropic materials, which have different properties in different directions, are being used to create artificial synapses that can mimic the functions of biological axon‐multisynapse systems. However, the restricted variety and unadjustable conductive ratio limit their applications. Here, it is shown that anisotropic artificial synapses can be achieved on isotropic materials with externally localized doping via electron beam irradiation (EBI) and purposefully induced trap sites. By employing the synapses along different directions, artificial neural networks (ANNs) are constructed to accomplish variable neuromorphic tasks with optimized performance. The localized doping method expands the axon‐multisynapse device family, illustrating that this approach has tremendous potentials in next‐generation computing and sensing systems. Neuromorphic computing provides a promising solution to the von Neumann bottleneck, paving the way for next‐generation computing systems. This study demonstrates an approach to realize anisotropic artificial synapses on isotropic materials via localized electron beam irradiation. Axon‐multisynapse systems are constructed to enhance the performance of artificial neural networks (ANNs). This method exhibits significant potentials for advanced computing and sensing system.

Significance With a combination of HPLC and carbon fiber electrodes, we demonstrate that grafted neural stem cells directly release dopamine in the damaged striatum in vivo and partially rescue a Parkinson’s disease (PD) model. ( i ) Primitive neural stem cell–dopamine-like neuron (pNSC–DAn) retained tyrosine hydroxylase expression and reduced the PD-like asymmetric rotation; ( ii ) depolarization-evoked dopamine release and reuptake were significantly rescued in striatum in vitro (brain slices) and in vivo, as determined jointly by microdialysis-based HPLC and electrochemical micro-carbon fiber electrodes; and ( iii ) the rescued dopamine was released directly from the grafted pNSC–DAn (not from the injured original cells). Thus, pNSC–DAn grafts release and reuptake dopamine in the striatum in vivo and alleviate PD symptoms in rats, providing proof-of-concept for human clinical translation. Embryonic stem cell-based therapies exhibit great potential for the treatment of Parkinson’s disease (PD) because they can significantly rescue PD-like behaviors. However, whether the transplanted cells themselves release dopamine in vivo remains elusive. We and others have recently induced human embryonic stem cells into primitive neural stem cells (pNSCs) that are self-renewable for massive/transplantable production and can efficiently differentiate into dopamine-like neurons (pNSC–DAn) in culture. Here, we showed that after the striatal transplantation of pNSC–DAn, ( i ) pNSC–DAn retained tyrosine hydroxylase expression and reduced PD-like asymmetric rotation; ( ii ) depolarization-evoked dopamine release and reuptake were significantly rescued in the striatum both in vitro (brain slices) and in vivo, as determined jointly by microdialysis-based HPLC and electrochemical carbon fiber electrodes; and ( iii ) the rescued dopamine was released directly from the grafted pNSC–DAn (and not from injured original cells). Thus, pNSC–DAn grafts release and reuptake dopamine in the striatum in vivo and alleviate PD symptoms in rats, providing proof-of-concept for human clinical translation.

Neuromorphic computing, a promising solution to the von Neumann bottleneck, is paving the way for the development of next‐generation computing and sensing systems. Axon‐multisynapse systems enable the execution of sophisticated tasks, making them not only desirable but essential for future applications in this field. Anisotropic materials, which have different properties in different directions, are being used to create artificial synapses that can mimic the functions of biological axon‐multisynapse systems. However, the restricted variety and unadjustable conductive ratio limit their applications. Here, it is shown that anisotropic artificial synapses can be achieved on isotropic materials with externally localized doping via electron beam irradiation (EBI) and purposefully induced trap sites. By employing the synapses along different directions, artificial neural networks (ANNs) are constructed to accomplish variable neuromorphic tasks with optimized performance. The localized doping method expands the axon‐multisynapse device family, illustrating that this approach has tremendous potentials in next‐generation computing and sensing systems.

Recently, many versatile Multi-modal Large Language Models (MLLMs) have emerged continuously. However, their capacity to query information depicted in visual charts and engage in reasoning based on the queried contents remains under-explored. In this paper, to comprehensively and rigorously benchmark the ability of the off-the-shelf MLLMs in the chart domain, we construct ChartX, a multi-modal evaluation set covering 18 chart types, 7 chart tasks, 22 disciplinary topics, and high-quality chart data. Besides, we develop ChartVLM to offer a new perspective on handling multi-modal tasks that strongly depend on interpretable patterns, such as reasoning tasks in the field of charts or geometric images. We evaluate the chart-related ability of mainstream MLLMs and our ChartVLM on the proposed ChartX evaluation set. Extensive experiments demonstrate that ChartVLM surpasses both versatile and chart-related large models, achieving results comparable to GPT-4V. We believe that our study can pave the way for further exploration in creating a more comprehensive chart evaluation set and developing more interpretable multi-modal models. Both ChartX and ChartVLM are available at: https://github.com/UniModal4Reasoning/ChartVLM