Numerical Analysis and Strength Evaluation of an Exposed River Crossing Pipeline with Casing Under Flood Load

Pipelines in service always experience complicated loadings induced by operational and environmental conditions. Flood is one of the common natural hazard threats for buried steel pipelines. One exposed river crossing X70 gas pipeline induced by flood erosion was used as a prototype for this study. A mechanical model was established considering the field loading conditions. Morison equations were adopted to calculate distributional hydrodynamic loads on spanning pipe caused by flood flow. Nonlinear soil constraint on pipe was considered using discrete nonlinear soil springs. An explicit solution of bending stiffness for pipe segment with casing was derived and applied to the numerical model. The von Mises yield criterion was used as failure criteria of the X70 pipe. Stress behavior of the pipe were analyzed by a rigorous finite element model established by the general-purpose Finite-Element package ABAQUS, with 3D pipe elements and pipe-soil interaction elements simulating pipe and soil constraints on pipe, respectively. Results show that, the pipe is safe at present, as the maximum von Mises stress in pipe with the field parameters is 185.57 MPa. The critical flow velocity of the pipe is 5.8 m/s with the present spanning length. The critical spanning length of the pipe is 467 m with the present flow velocity. The failure pipe sections locate at the connection point of the bare pipe and the pipe with casing or the supporting point of the bare pipe on riverbed

TRANSOM: An Efficient Fault-Tolerant System for Training LLMs

Large language models (LLMs) with hundreds of billions or trillions of parameters, represented by chatGPT, have achieved profound impact on various fields. However, training LLMs with super-large-scale parameters requires large high-performance GPU clusters and long training periods lasting for months. Due to the inevitable hardware and software failures in large-scale clusters, maintaining uninterrupted and long-duration training is extremely challenging. As a result, A substantial amount of training time is devoted to task checkpoint saving and loading, task rescheduling and restart, and task manual anomaly checks, which greatly harms the overall training efficiency. To address these issues, we propose TRANSOM, a novel fault-tolerant LLM training system. In this work, we design three key subsystems: the training pipeline automatic fault tolerance and recovery mechanism named Transom Operator and Launcher (TOL), the training task multi-dimensional metric automatic anomaly detection system named Transom Eagle Eye (TEE), and the training checkpoint asynchronous access automatic fault tolerance and recovery technology named Transom Checkpoint Engine (TCE). Here, TOL manages the lifecycle of training tasks, while TEE is responsible for task monitoring and anomaly reporting. TEE detects training anomalies and reports them to TOL, who automatically enters the fault tolerance strategy to eliminate abnormal nodes and restart the training task. And the asynchronous checkpoint saving and loading functionality provided by TCE greatly shorten the fault tolerance overhead. The experimental results indicate that TRANSOM significantly enhances the efficiency of large-scale LLM training on clusters. Specifically, the pre-training time for GPT3-175B has been reduced by 28%, while checkpoint saving and loading performance have improved by a factor of 20.Comment: 14 pages, 9 figure

Iron chelation effect of curcumin and baicalein on aplastic anemia mouse model with iron overload

Objective(s): The current work aimed to assess whether curcumin and baicalein can chelate iron in aplastic anemia (AA) complicated with iron overload, exploring the potential mechanisms.Materials and Methods: A mouse model of AA with iron overload complication was firstly established. Low and high-dose curcumin or baicalein treatment groups were set up, as well as the deferoxamine positive control, normal and model groups (n=8). Hemogram and bone marrow mononuclear cell detection were performed, and TUNEL and immunohistochemical staining were used to evaluate hematopoiesis and apoptosis in the marrow. ELISA, Western blot, and qRT-PCR were employed to assess serum iron (SI), serum ferritin (SF), bone morphogenetic protein 6 (BMP-6), SMAD family member4 (SMAD4) and transferrin receptor 2 (TfR2) amounts. Results: Both curcumin and baicalein improved white blood cell (increase of 0.28-0.64×109/l in high-dose groups) and hemoglobin (increase of around 10 g/l) amounts significantly, which may related to decreased apoptosis (nearly 30%-50% of that in the model group) in the bone marrow, while their effects on platelet recovery were limited and inferior to that of deferoxamine (DFO). Both test compounds up-regulated hepcidin and its regulators (BMP-6, SMAD, and TfR2) at the protein and mRNA levels; high dosage treatment may be beneficial, being better than DFO administration in lessening iron deposition in the bone marrow.Conclusion: Curcumin and baicalein protect hematopoiesis from immune and iron overload-induced apoptosis, exerting iron chelation effects in vivo

A Discontinuous RNA Platform Mediates RNA Virus Replication: Building an Integrated Model for RNA–based Regulation of Viral Processes

Plus-strand RNA viruses contain RNA elements within their genomes that mediate a variety of fundamental viral processes. The traditional view of these elements is that of local RNA structures. This perspective, however, is changing due to increasing discoveries of functional viral RNA elements that are formed by long-range RNA–RNA interactions, often spanning thousands of nucleotides. The plus-strand RNA genomes of tombusviruses exemplify this concept by possessing different long-range RNA–RNA interactions that regulate both viral translation and transcription. Here we report that a third fundamental tombusvirus process, viral genome replication, requires a long-range RNA–based interaction spanning ∼3000 nts. In vivo and in vitro analyses suggest that the discontinuous RNA platform formed by the interaction facilitates efficient assembly of the viral RNA replicase. This finding has allowed us to build an integrated model for the role of global RNA structure in regulating the reproduction of a eukaryotic RNA virus, and the insights gained have extended our understanding of the multifunctional nature of viral RNA genomes

Multifaceted Regulation of Translational Readthrough by RNA Replication Elements in a Tombusvirus

Translational readthrough of stop codons by ribosomes is a recoding event used by a variety of viruses, including plus-strand RNA tombusviruses. Translation of the viral RNA-dependent RNA polymerase (RdRp) in tombusviruses is mediated using this strategy and we have investigated this process using a variety of in vitro and in vivo approaches. Our results indicate that readthrough generating the RdRp requires a novel long-range RNA-RNA interaction, spanning a distance of ∼3.5 kb, which occurs between a large RNA stem-loop located 3'-proximal to the stop codon and an RNA replication structure termed RIV at the 3'-end of the viral genome. Interestingly, this long-distance RNA-RNA interaction is modulated by mutually-exclusive RNA structures in RIV that represent a type of RNA switch. Moreover, a different long-range RNA-RNA interaction that was previously shown to be necessary for viral RNA replicase assembly was also required for efficient readthrough production of the RdRp. Accordingly, multiple replication-associated RNA elements are involved in modulating the readthrough event in tombusviruses and we propose an integrated mechanistic model to describe how this regulatory network could be advantageous by (i) providing a quality control system for culling truncated viral genomes at an early stage in the replication process, (ii) mediating cis-preferential replication of viral genomes, and (iii) coordinating translational readthrough of the RdRp with viral genome replication. Based on comparative sequence analysis and experimental data, basic elements of this regulatory model extend to other members of Tombusviridae, as well as to viruses outside of this family

Simulating long-term carbon nitrogen and phosphorus biogeochemical cycling in agricultural environments

Understanding how agricultural practices alter biogeochemical cycles is vital for maintaining land productivity, food security, and other ecosystem services such as carbon sequestration. However, these are complex, highly coupled long-term processes that are difficult to observe or explore through empirical science alone. Models are required that capture the main anthropogenic disturbances, whilst operating across regions and long timescales, simulating both natural and agricultural environments, and shifts among these. Many biogeochemical models neglect agriculture or interactions between carbon and nutrient cycles, which is surprising given the scale of intervention in nitrogen and phosphorus cycles introduced by agriculture. This gap is addressed here, using a plant-soil model that simulates integrated soil carbon, nitrogen and phosphorus (CNP) cycling across natural, semi-natural and agricultural environments. The model is rigorously tested both spatially and temporally using data from long-term agricultural experiments across temperate environments. The model proved capable of reproducing the magnitude of and trends in soil nutrient stocks, and yield responses to nutrient addition. The model has potential to simulate anthropogenic effects on biogeochemical cycles across northern Europe, for long timescales (centuries) without site-specific calibration, using easily accessible input data. The results demonstrate that weatherable P from parent material has a considerable effect on modern pools of soil C and N, despite significant perturbation of nutrient cycling from agricultural practices, highlighting the need to integrate both geological and agricultural processes to understand effects of land-use change on food security, C storage and nutrient sustainability. The results suggest that an important process or source of P is currently missing in our understanding of agricultural biogeochemical cycles. The model could not explain how yields were sustained in plots with low P fertiliser addition. We suggest that plant access to organic P is a key uncertainty warranting further research, particularly given sustainability concerns surrounding rock sources of P fertiliser

Economic Structure and Intensity Influence Air Pollution Model

AbstractThis study analyzes the impact of economic structure and intensity on the level of air pollution. This is done by the estimation of Structural Equation Model with two latent variables describing the economic structure and the intensity of economic activity, which influence air pollution. It is further assumed that there are causal link with these two factors, one of them is influenced by international trade intensity, per capita income and the level of trade liberalization, the other is influenced by urban percentage and industry. The estimation results suggest that the impact of economic growth on air pollution intensity varies in the structure and the intensity of economic activity. The estimation results show that the structure effect which is 0.85 is higher than intensity which is 0.05 on the level of air pollution. Model with the better fit to the data, indices of goodness-offit are relatively satisfaction and meet the requirements. This results show that for many developing countries, urbanization and industrialization change economic structure-as a consequence-to increase air pollution