A modified lumped parameter model of distribution transformer winding

This work was supported by the National Key Research and Development Plan of China under Grant (2016YFB0900600XXX).The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction. A distributed parameters model can depict the winding characteristics accurately, but it requires complex calculations. Lumped parameter model requires less calculations, but its applicable frequency range is not wide. This paper studies the amplitude-frequency characteristics of the lightning wave, compares the transformer modelling methods and finally proposes a modified lumped parameter model, based on the above comparison. The proposed model minimizes the errors provoked by the lumped parameter approximation, and the hyperbolic functions of the distributed parameter model. By this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage response. The proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.publishersversionpublishe

NavCoT: Boosting LLM-Based Vision-and-Language Navigation via Learning Disentangled Reasoning

Vision-and-Language Navigation (VLN), as a crucial research problem of Embodied AI, requires an embodied agent to navigate through complex 3D environments following natural language instructions. Recent research has highlighted the promising capacity of large language models (LLMs) in VLN by improving navigational reasoning accuracy and interpretability. However, their predominant use in an offline manner usually suffers from substantial domain gap between the VLN task and the LLM training corpus. This paper introduces a novel strategy called Navigational Chain-of-Thought (NavCoT), where we fulfill parameter-efficient in-domain training to enable self-guided navigational decision, leading to a significant mitigation of the domain gap in a cost-effective manner. Specifically, at each timestep, the LLM is prompted to forecast the navigational chain-of-thought by: 1) acting as a world model to imagine the next observation according to the instruction, 2) selecting the candidate observation that best aligns with the imagination, and 3) determining the action based on the reasoning from the prior steps. Through constructing formalized labels for training, the LLM can learn to generate desired and reasonable chain-of-thought outputs for improving the action decision. Experimental results across various training settings and popular VLN benchmarks (e.g., Room-to-Room (R2R), Room-across-Room (RxR), Room-for-Room (R4R)) show the significant superiority of NavCoT over the direct action prediction variants. Through simple parameter-efficient finetuning, our NavCoT outperforms a recent GPT4-based approach with ~7% relative improvement on the R2R dataset. We believe that NavCoT will help unlock more task-adaptive and scalable LLM-based embodied agents, which are helpful for developing real-world robotics applications. Code is available at https://github.com/expectorlin/NavCoT

Fully 3D printed flexible, conformal and multi-directional tactile sensor with integrated biomimetic and auxetic structure

Tactile sensors play a crucial role in the development of biologically inspired robotic prostheses, particularly in providing tactile feedback. However, existing sensing technology still falls short in terms of sensitivity under high pressure and adaptability to uneven working surfaces. Furthermore, the fabrication of tactile sensors often requires complex and expensive manufacturing processes, limiting their widespread application. Here we develop a conformal tactile sensor with improved sensing performance fabricated using an in-house 3D printing system. Our sensor detects shear stimuli through the integration of an auxetic structure and interlocking features. The design enables an extended sensing range (from 0.1 to 0.26 MPa) and provides sensitivity in both normal and shear directions, with values of 0.63 KPa−1 and 0.92 N−1, respectively. Additionally, the sensor is capable of detecting temperature variations within the range of 40−90 °C. To showcase the feasibility of our approach, we have printed the tactile sensor directly onto the fingertip of an anthropomorphic robotic hand, the proximal femur head, and lumbar vertebra. The results demonstrate the potential for achieving sensorimotor control and temperature sensing in artificial upper limbs, and allowing the monitoring of bone-on-bone load

Tunable van Hove singularity without structural instability in Kagome metal CsTi3_3Bi5_5

In Kagome metal CsV$_3$Sb$_5$, multiple intertwined orders are accompanied by both electronic and structural instabilities. These exotic orders have attracted much recent attention, but their origins remain elusive. The newly discovered CsTi$_3$Bi$_5$ is a Ti-based Kagome metal to parallel CsV$_3$Sb$_5$. Here, we report angle-resolved photoemission experiments and first-principles calculations on pristine and Cs-doped CsTi$_3$Bi$_5$ samples. Our results reveal that the van Hove singularity (vHS) in CsTi$_3$Bi$_5$ can be tuned in a large energy range without structural instability, different from that in CsV$_3$Sb$_5$. As such, CsTi$_3$Bi$_5$ provides a complementary platform to disentangle and investigate the electronic instability with a tunable vHS in Kagome metals

Distinct Regulation of Host Responses by ERK and JNK MAP Kinases in Swine Macrophages Infected with Pandemic (H1N1) 2009 Influenza Virus

Swine influenza is an acute respiratory disease in pigs caused by swine influenza virus (SIV). Highly virulent SIV strains cause mortality of up to 10%. Importantly, pigs have long been considered “mixing vessels” that generate novel influenza viruses with pandemic potential, a constant threat to public health. Since its emergence in 2009 and subsequent pandemic spread, the pandemic (H1N1) 2009 (H1N1pdm) has been detected in pig farms, creating the risk of generating new reassortants and their possible infection of humans. Pathogenesis in SIV or H1N1pdm-infected pigs remains poorly characterized. Proinflammatory and antiviral cytokine responses are considered correlated with the intensity of clinical signs, and swine macrophages are found to be indispensible in effective clearance of SIV from pig lungs. In this study, we report a unique pattern of cytokine responses in swine macrophages infected with H1N1pdm. The roles of mitogen-activated protein (MAP) kinases in the regulation of the host responses were examined. We found that proinflammatory cytokines IL-6, IL-8, IL-10, and TNF-α were significantly induced and their induction was ERK1/2-dependent. IFN-β and IFN-inducible antiviral Mx and 2′5′-OAS were sharply induced, but the inductions were effectively abolished when ERK1/2 was inhibited. Induction of CCL5 (RANTES) was completely inhibited by inhibitors of ERK1/2 and JNK1/2, which appeared also to regulate FasL and TNF-α, critical for apoptosis in pig macrophages. We found that NFκB was activated in H1N1pdm-infected cells, but the activation was suppressed when ERK1/2 was inhibited, indicating there is cross-talk between MAP kinase and NFκB responses in pig macrophages. Our data suggest that MAP kinase may activate NFκB through the induction of RIG-1, which leads to the induction of IFN-β in swine macrophages. Understanding host responses and their underlying mechanisms may help identify venues for effective control of SIV and assist in prevention of future influenza pandemics

The complete mitochondrial genome of Neolissochilus benasi (Cypriniformes: Cyprinidae)

In this study, the complete mitochondrial genome of Neolissochilus benasi has been determined by polymerase chain reaction method for the first time. The overall base composition of N. benasi mitogenome is 31.8% for A, 27.4% for C, 15.9% for G and 25.0% for T. The percentage of G + C content is 41.3%. The mitogenome is a circular DNA molecule of 16 583 bp in length with a D-loop region and contains 22 transfer RNA (tRNA) genes, two ribosomal RNA (rRNA) genes and 13 protein-coding genes. The mitochondrial genome sequencing for N. benasi in this study provides important molecular data for further evolutionary analysis for Cyprinoidea

numericalinvestigationoflargebubbleentrapmentmechanismformicrondropletimpactondeeppool

Water droplet impacting into a deep liquid pool is one of the most well-known flow phenomena in fluid mechanics. As a ubiquitous natural aeration process, the coalescence of water droplets in lakes and ponds and the subsequent bubble entrapment are one of the most notable ways of gas-liquid exchange in nature, and it is of great significance for underwater sound transmission, aquatic ecosystems and chemical process. The shape of an oscillating droplet in impact under different surrounding medium and initial condition is a key factor for the subsequent cavity formation and bubble entrapment. In this study, the adaptive mesh refinement technique and volume of fluid (VOF) method are applied to the study of the water droplet impact phenomena. Five kinds of deformed micron water droplets with different aspect ratios and impact velocities of 4 m/s and 6 m/s are selected to investigate the influences of drop deformation and impact velocity on the bubble entrapment, capillary wave propagation, and vortex ring evolution. The results show that at low impact velocities (Fr = 75, We = 64.4, Re = 1160, V, = 4 m/s), the shape of water droplet does not cause the cavity formation and bubble entrapment to change significantly. However, under higher impact velocity (Fr = 112.5, We = 145, Re = 1740, V, = 6 m/s), deformed droplet with an aspect ratio of 1.33 coalesces with the pool, and large bubble entrainment occurs. The large bubble entrapment is affected mainly by the vortex ring generated under the free surface at the neck between the droplet and the pool. The vortex ring penetrates more deeply before it pulls the free surface to generate a rolling jet at the upper interface of the cavity. The rolling jets then contact the center of the cavity and collapse to entrain a large bubble. At the end of the bubble entrapment phenomenon, the cyclone inside the cavity pushes the sidewall of the cavity continuously, and effectively increases the lateral volume of the bubble, which plays a vital role in the bubble entrainment process. In the initial stage of the impact, the flatter the shape of the droplet, the greater the curvature of the jet generated on the neck between the droplet and the pool, the greater the strength of the vortex ring generated under the free surface. However, the vortex ring formed by the oblate-shaped water droplet is generated too close to the free surface, and the early free surface pulling reduces the strength of the vortex ring, thus the vorticity maximum value decays relatively fast