Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction

Multi-modal magnetic resonance imaging (MRI) plays a crucial role in comprehensive disease diagnosis in clinical medicine. However, acquiring certain modalities, such as T2-weighted images (T2WIs), is time-consuming and prone to be with motion artifacts. It negatively impacts subsequent multi-modal image analysis. To address this issue, we propose an end-to-end deep learning framework that utilizes T1-weighted images (T1WIs) as auxiliary modalities to expedite T2WIs' acquisitions. While image pre-processing is capable of mitigating misalignment, improper parameter selection leads to adverse pre-processing effects, requiring iterative experimentation and adjustment. To overcome this shortage, we employ Optimal Transport (OT) to synthesize T2WIs by aligning T1WIs and performing cross-modal synthesis, effectively mitigating spatial misalignment effects. Furthermore, we adopt an alternating iteration framework between the reconstruction task and the cross-modal synthesis task to optimize the final results. Then, we prove that the reconstructed T2WIs and the synthetic T2WIs become closer on the T2 image manifold with iterations increasing, and further illustrate that the improved reconstruction result enhances the synthesis process, whereas the enhanced synthesis result improves the reconstruction process. Finally, experimental results from FastMRI and internal datasets confirm the effectiveness of our method, demonstrating significant improvements in image reconstruction quality even at low sampling rates

Gut microbiota and risk of endocarditis: a bidirectional Mendelian randomization study

BackgroundThe associations between gut microbiota and cardiovascular disease have been reported in previous studies. However, the relationship between gut microbiota and endocarditis remains unclear.MethodsA bidirectional Mendelian randomization (MR) study was performed to detect the association between gut microbiota and endocarditis. Inverse variance weighted (IVW) method was considered the main result. Simultaneously, heterogeneity and pleiotropy tests were conducted.ResultsOur study suggests that family Victivallaceae (p = 0.020), genus Eubacterium fissicatena group (p = 0.047), genus Escherichia Shigella (p = 0.024), genus Peptococcus (p = 0.028) and genus Sellimonas (p = 0.005) play protective roles in endocarditis. Two microbial taxa, including genus Blautia (p = 0.006) and genus Ruminococcus2 (p = 0.024) increase the risk of endocarditis. At the same time, endocarditis has a negative effect on genus Eubacterium fissicatena group (p = 0.048). Besides, no heterogeneity or pleiotropy was found in this study.ConclusionOur study emphasized the certain role of specific gut microbiota in patients with endocarditis and clarified the negative effect of endocarditis on gut microbiota

Spatial-Temporal Evolution of Mining-Induced Rock Damage and Ground Control of Roadways

This open access book presents the Coal remains the primary energy source in China, with an estimated total coal reserve of 59 trillion tons at depths of less than 2000 meters. Among these, over 50% lie at depths exceeding 1000 meters, primarily distributed in central and eastern China. Deep coal mining has become the new norm for the coal industry’s development and resource exploitation. To ensure energy supply for the rapid economic development of central and eastern regions, mining coal resources from depths of over 1000 meters is inevitable. This endeavor holds significant strategic importance for safeguarding national energy security and supporting regional economic growth. However, mining-induced hazards, such as rock bursts, water inrushes, and roof collapses, continue to occur frequently in both local and state-owned coal mines. These incidents pose severe threats to the safety of coal production, tarnish the reputation of China's mining industry, and hinder its development. Therefore, advancing mining engineering—especially the theories of major accident prediction and control—is essential. A deeper understanding of the dynamic processes underlying mining-induced pressure and strata movement is necessary. Promoting safe and efficient coal mining through informed decision-making and management supported by scientific, quantitative methods is a critical and urgent task. Achieving informatization, intelligence, and visualization in mining operations will be key to fundamentally addressing the current safety challenges in China's mining industry. In recent years, the author and their team have conducted in-depth studies on models of dynamic disasters and surrounding rock control in deep mines, supported by projects under the National Basic Research Program (973 Program), the National Key R&D Program, as well as talent and general research funds and specialized consultancy projects from the Chinese Academy of Sciences. The main research focuses include constructing spatial structural models of overlying strata in mining areas, analyzing the spatiotemporal evolution of mining-induced stress, and developing proactive control technologies for dynamic disasters in mining areas. This book aims to provide foundational insights into the occurrence and control of major mining accidents. It proposes a decision-making framework for predicting and managing such disasters by controlling the movement of surrounding rock and stress conditions induced by mining. These efforts are expected to provide a reference for advancing research in related fields

Advanced Geological Prediction

Due to the particularity of the tunnel project, it is difficult to find out the exact geological conditions of the tunnel body during the survey stage. Once it encounters unfavorable geological bodies such as faults, fracture zones, and karst, it will bring great challenges to the construction and will easily cause major problems, economic losses, and casualties. Therefore, it is necessary to carry out geological forecast work in the tunnel construction process, which is of great significance for tunnel safety construction and avoiding major disaster accident losses. This lecture mainly introduces the commonly used methods of geological forecast in tunnel construction, the design principles, and contents of geological forecast and combines typical cases to show the implementation process of comprehensive geological forecast. Finally, the development direction of geological forecast theory, method, and technology is carried out. Prospects provide a useful reference for promoting the development of geological forecast of tunnels

3D Point Cloud Object Tracking Based on Multi-level Fusion of Transformer Features

During the 3D point cloud object tracking, some issues such as occlusion, sparsity, and random noise often arise. To address these challenges, this paper proposes a novel approach to 3D point cloud object tracking based on multi-level fusion of Transformer features. The method mainly consists of the point attention embedding module and the point attention enhancement module, which are used for feature extraction and feature matching processes, respectively. Firstly, by embedding two attention mechanisms into each other to form the point attention embedding module and fusing it with the relationship-aware sampling method proposed by PTTR (point relation transformer for tracking), the purpose of fully extracting features is achieved. Subsequently, the feature information is input into the point attention enhancement module, and through cross-attention, features from different levels are matched sequentially to achieve the goal of deep fusion of global and local features. Moreover, to obtain discriminative feature fusion maps, a residual network is employed to connect the fusion results from different layers. Finally, the feature fusion map is input into the target prediction module to achieve precise prediction of the final 3D target object. Experimental validation on KITTI, nuScenes, and Waymo datasets demonstrates the effectiveness of the proposed method. Excluding few-shot data, the proposed method achieves an average improvement of 1.4 percentage points in success and 1.4 percentage points in precision in terms of object tracking

Creep Effect and Prediction Method of Dynamic Disaster of Surrounding Rock

This open access book provides a comprehensive overview of the author’s in-depth insights into the theory, prediction methods, and developmental trends of creep instability and failure in coal-rock masses within mining stopes. The content primarily covers topics such as creep instability of coal-rock masses in stopes, creep instability of surrounding rock in roadways, large-scale roof creep instability, creep instability of overlying strata in goaf, rockburst, gas outburst, and principles and prediction of roof creep instability in fully mechanized mining faces. Additionally, it explores theoretical advancements in analyzing the energy principles of coal-rock masses and acoustic wave monitoring of coal-rock systems. This book serves as a valuable reference for professionals and researchers in mining engineering, mine construction, underground space engineering, and geotechnical engineering, as well as for faculty and students in related fields

Analysis of novel geometry-independent method for dialysis access pressure-flow monitoring

Abstract Background End-stage renal disease (ESRD) confers a large health-care burden for the United States, and the morbidity associated with vascular access failure has stimulated research into detection of vascular access stenosis and low flow prior to thrombosis. We present data investigating the possibility of using differential pressure (ΔP) monitoring to estimate access flow (Q) for dialysis access monitoring, with the goal of utilizing micro-electro-mechanical systems (MEMS) pressure sensors integrated within the shaft of dialysis needles. Methods A model of the arteriovenous graft fluid circuit was used to study the relationship between Q and the ΔP between two dialysis needles placed 2.5–20.0 cm apart. Tubing was varied to simulate grafts with inner diameters of 4.76–7.95 mm. Data were compared with values from two steady-flow models. These results, and those from computational fluid dynamics (CFD) modeling of ΔP as a function of needle position, were used to devise and test a method of estimating Q using ΔP and variable dialysis pump speeds (variable flow) that diminishes dependence on geometric factors and fluid characteristics. Results In the fluid circuit model, ΔP increased with increasing volume flow rate and with increasing needle-separation distance. A nonlinear model closely predicts this ΔP-Q relationship (R2 > 0.98) for all graft diameters and needle-separation distances tested. CFD modeling suggested turbulent needle effects are greatest within 1 cm of the needle tip. Utilizing linear, quadratic and combined variable flow algorithms, dialysis access flow was estimated using geometry-independent models and an experimental dialysis system with the pressure sensors separated from the dialysis needle tip by distances ranging from 1 to 5 cm. Real-time ΔP waveform data were also observed during the mock dialysis treatment, which may be useful in detecting low or reversed flow within the access. Conclusion With further experimentation and needle design, this geometry-independent approach may prove to be a useful access flow monitoring method.http://deepblue.lib.umich.edu/bitstream/2027.42/112774/1/12976_2008_Article_178.pd

Theory and application of mining mechanics and strata control

Studying the dynamic response of rock mass mining and strata control technology is of great significance for promoting safe and efficient coal production and ensuring stable energy supply. It is the theoretical basis for scientific mining of coal resources. Mine rock mass disasters (surrounding rock deformation, rock burst, etc.) occur frequently, and their formation-evolution-occurrence process is closely related to the evolution and distribution of mine-induced stress, strata movement, mine-induced disturbance and energy evolution. Based on the practical theory of ground pressure control, the progress and control criteria of strata control in the stope are presented. The mechanical models and design methods for quantitative analysis are established. Also, the targeted rock disaster control technology and the assorted equipment are innovatively developed. In the theory of mining mechanics and strata control, the strata control is divided into rock control in stope and surrounding rock control in roadway. The control or utilization of strata movement to change the conditions of disaster is proposed, and the criteria of “given deformation” and “limited deformation” are provided. The self-stabilization ability of surrounding rock can be changed by regulating the “3S” factors criteria (stress environment, structural properties, and support structure). With the goal of controlling rock mass disasters, the system of control and energy release with core of stress control in roadway surrounding rock is presented. The principle of rock mass disaster control considering stress and energy and the assessment criteria for weak surface (safety factor K and impact hazard factor U) are established. The ground pressure mechanical simulation test system in stope, the mining-induced stress test system, and the creep and dynamic disturbance impact loading test system are independently developed. The series equipment can realize the laboratory-scale reduction of the deformation-fracture-movement process of rock mass under the action of mine-induced stress, providing experimental equipment for studying the mechanical response of rock mass. Engineering case studies are conducted from four directions: rock control in the mining area, geological soft rock control, engineering soft rock roadway control, and rockburst control. The relevant research results are validated in engineering applications

A 91-Channel Hyperspectral LiDAR for Coal/Rock Classification

During the mining operation, it is a critical task in coal mines to significantly improve the safety by precision coal mining sorting and rock classification from different layers. It implies that a technique for rapidly and accurately classifying coal/rock in-site needs to be investigated and established, which is of significance for improving the coal mining efficiency and safety. In this letter, a 91-channel hyperspectral LiDAR (HSL) using an acousto-optic tunable filter (AOTF) as the spectroscopic device is designed, which operates based on the wide-spectrum emission laser source with a 5-nm spectral resolution to tackle this issue. The spectra of four-type coal/rock specimens collected by HSL are used to classify with three multi-label classifiers: naive Bayes (NB), logistic regression (LR), and support vector machine (SVM). Furthermore, we discuss and explore whether Gaussian fitting (GF) method and calibration with the reference whiteboard (RB) can enhance the classification accuracy. The experimental results show that the GF technique not only improves the accuracy of range measurement but also optimizes the classification performance using the spectra collected by the HSL. In addition, calibration with RB can improve classification accuracy as well. In addition, we also discuss methods to improve the calibration-free classification accuracy preliminarily.acceptedVersion© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works