Trajectory Envelope of a Subsea Shuttle Tanker Hovering in Stochastic Ocean Current - Model Development and Tuning

A subsea shuttle tanker (SST) concept for liquid carbon dioxide transportation was recently proposed to support studies evaluating the ultra-efficient underwater cargo submarine concept. One important topic is the position keeping ability of SST during the offloading process. In this process, the SST hovers above the well and connects with the wellhead using a flowline. This process takes around 4 h. Ocean currents can cause tremendous drag forces on the subsea shuttle tanker during this period. The flow velocities over hydroplanes are low throughout this process, and the generated lift forces are generally insufficient to maintain the SST’s depth. The ballast tanks cannot provide such fast actuation to cope with the fluctuation of the current. It is envisioned that tunnel thrusters that can provide higher frequency actuation are required. This paper develops a maneuvering model and designs a linear quadratic regulator that facilitates the SST station-keeping problem in stochastic current. As case studies, the SST footprints at 0.5 m/s, 1.0 m/s, and 1.5 m/s mean current speeds are presented. Numerical results show that the designed hovering control system can ensure the SST’s stationary during offloading. The required thrust from thrusters and the propeller are presented. The presented model can serve as a basis for obtaining a more efficient design of the SST and provide recommendations for the SST operation.acceptedVersio

Change Diffusion: Change Detection Map Generation Based on Difference-Feature Guided DDPM

Deep learning (DL) approaches based on CNN-purely or Transformer networks have demonstrated promising results in bitemporal change detection (CD). However, their performance is limited by insufficient contextual information aggregation, as they struggle to fully capture the implicit contextual dependency relationships among feature maps at different levels. Additionally, researchers have utilized pre-trained denoising diffusion probabilistic models (DDPMs) for training lightweight CD classifiers. Nevertheless, training a DDPM to generate intricately detailed, multi-channel remote sensing images requires months of training time and a substantial volume of unlabeled remote sensing datasets, making it significantly more complex than generating a single-channel change map. To overcome these challenges, we propose a novel end-to-end DDPM-based model architecture called change-aware diffusion model (CADM), which can be trained using a limited annotated dataset quickly. Furthermore, we introduce dynamic difference conditional encoding to enhance step-wise regional attention in DDPM for bitemporal images in CD datasets. This method establishes state-adaptive conditions for each sampling step, emphasizing two main innovative points of our model: 1) its end-to-end nature and 2) difference conditional encoding. We evaluate CADM on four remote sensing CD tasks with different ground scenarios, including CDD, WHU, Levier, and GVLM. Experimental results demonstrate that CADM significantly outperforms state-of-the-art methods, indicating the generalization and effectiveness of the proposed model

Systems mapping of HIV-1 infection

<p>Abstract</p> <p>Mathematical models of viral dynamics <it>in vivo</it> provide incredible insights into the mechanisms for the nonlinear interaction between virus and host cell populations, the dynamics of viral drug resistance, and the way to eliminate virus infection from individual patients by drug treatment. The integration of these mathematical models with high-throughput genetic and genomic data within a statistical framework will raise a hope for effective treatment of infections with HIV virus through developing potent antiviral drugs based on individual patients’ genetic makeup. In this opinion article, we will show a conceptual model for mapping and dictating a comprehensive picture of genetic control mechanisms for viral dynamics through incorporating a group of differential equations that quantify the emergent properties of a system.</p

Intensive blood pressure control after endovascular thrombectomy for acute ischaemic stroke (ENCHANTED2/MT): a multicentre, open-label, blinded-endpoint, randomised controlled trial

Background: The optimum systolic blood pressure after endovascular thrombectomy for acute ischaemic stroke is uncertain. We aimed to compare the safety and efficacy of blood pressure lowering treatment according to more intensive versus less intensive treatment targets in patients with elevated blood pressure after reperfusion with endovascular treatment. Methods: We conducted an open-label, blinded-endpoint, randomised controlled trial at 44 tertiary-level hospitals in China. Eligible patients (aged ≥18 years) had persistently elevated systolic blood pressure (≥140 mm Hg for >10 min) following successful reperfusion with endovascular thrombectomy for acute ischaemic stroke from any intracranial large-vessel occlusion. Patients were randomly assigned (1:1, by a central, web-based program with a minimisation algorithm) to more intensive treatment (systolic blood pressure target <120 mm Hg) or less intensive treatment (target 140–180 mm Hg) to be achieved within 1 h and sustained for 72 h. The primary efficacy outcome was functional recovery, assessed according to the distribution in scores on the modified Rankin scale (range 0 [no symptoms] to 6 [death]) at 90 days. Analyses were done according to the modified intention-to-treat principle. Efficacy analyses were performed with proportional odds logistic regression with adjustment for treatment allocation as a fixed effect, site as a random effect, and baseline prognostic factors, and included all randomly assigned patients who provided consent and had available data for the primary outcome. The safety analysis included all randomly assigned patients. The treatment effects were expressed as odds ratios (ORs). This trial is registered at ClinicalTrials.gov, NCT04140110, and the Chinese Clinical Trial Registry, 1900027785; recruitment has stopped at all participating centres. Findings: Between July 20, 2020, and March 7, 2022, 821 patients were randomly assigned. The trial was stopped after review of the outcome data on June 22, 2022, due to persistent efficacy and safety concerns. 407 participants were assigned to the more intensive treatment group and 409 to the less intensive treatment group, of whom 404 patients in the more intensive treatment group and 406 patients in the less intensive treatment group had primary outcome data available. The likelihood of poor functional outcome was greater in the more intensive treatment group than the less intensive treatment group (common OR 1·37 [95% CI 1·07–1·76]). Compared with the less intensive treatment group, the more intensive treatment group had more early neurological deterioration (common OR 1·53 [95% 1·18–1·97]) and major disability at 90 days (OR 2·07 [95% CI 1·47–2·93]) but there were no significant differences in symptomatic intracerebral haemorrhage. There were no significant differences in serious adverse events or mortality between groups. Interpretation: Intensive control of systolic blood pressure to lower than 120 mm Hg should be avoided to prevent compromising the functional recovery of patients who have received endovascular thrombectomy for acute ischaemic stroke due to intracranial large-vessel occlusion. Funding: The Shanghai Hospital Development Center; National Health and Medical Research Council of Australia; Medical Research Futures Fund of Australia; China Stroke Prevention; Shanghai Changhai Hospital, Science and Technology Commission of Shanghai Municipality; Takeda China; Hasten Biopharmaceutic; Genesis Medtech; Penumbra