LNG receiving terminal, as an important transfer station for China to receive imported LNG resources, still has problems such as high trial operation costs, large material consumption and long trial ...operation time. In response to this, technology improvement was implemented in the four processes of pipeline precooling, unloading pipeline filling, tank precooling and BOG system trial operation based on the trial operation of the LNG receiving terminal of PipeChina Shenzhen Natural Gas Co. Ltd., and the trial operation technology was applied practically. The results show that: pipeline precooling with liquid nitrogen could realize the precooling and filling of the unloading pipeline, the wharf circulation pipeline for cold insulation and the low-pressure LNG export pipeline at the same time, and the nitrogen can be recycled after precooling the unloading pipeline. Besides, the precooling of the next tank can be started while the first precooled tank is unloaded at a small flow. Thus, the two precooled tanks can
Depth estimation is a key problem in 3D computer vision and has a wide variety of applications. In this paper we explore whether deep learning network can predict depth map accurately by learning ...multi-scale spatio-temporal features from sequences and recasting the depth estimation from a regression task to an ordinal classification task. We design an encoder-decoder network with several multi-scale strategies to improve its performance and extract spatio-temporal features with ConvLSTM. The results of our experiments show that the proposed method has an improvement of almost 10% in error metrics and up to 2% in accuracy metrics. The results also tell us that extracting spatio-temporal features can dramatically improve the performance in depth estimation task. We consider to extend this work to a self-supervised manner to get rid of the dependence on large-scale labeled data.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
This study presents a detailed survey on recent development of logical networks and its applications, including the background of logical networks, the theory of a new matrix product called ...semi-tensor product (STP) of matrices, some fundamental works on logical networks, and some current research works. Particularly, some fundamental works on logical networks are presented for the past years, including controllability, stability and stabilisation, synchronisation, disturbance decoupling and so on. Due to the great potential of STP in dealing with logical networks, a surge of attraction from overseas is paid on the study of STP and its applications. Currently, some new research areas are widely studied including pinning control, function perturbations, system decomposition, trajectory control, output tracking issues, symbolic dynamics and so on. The main concern of this study is to present a comprehensive introduction to logical networks and some other applications under the framework of STP of matrices.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Abstract
Oncometabolites are pathognomonic hallmarks in human cancers, including glioma, leukemia, neuroendocrine tumors, and renal cancer. Oncometabolites are aberrantly accumulated from disrupted ...Krebs cycle and affect the catalytic activity of α-ketoglutarate–dependent dioxygenases. Oncometabolites indicate distinct cancer-related patterns ranging from oncogenesis and metabolism to therapeutic resistance. Here we discuss the current understanding of oncometabolites as well as the controversies and challenges associated with oncometabolite-driven cancers. New insights into the relationship between cancer and oncometabolites will elucidate novel therapeutic avenues for improved cancer treatment.
A major paradigm in cancer immunotherapy is the use of checkpoint inhibitors to break regulatory mechanisms that usually guard the host against autoimmune diseases. CTLA-4-targeting immunotherapy was ...the first example that helped establish this paradigm. However, the clinically tested anti-CTLA-4 antibodies exhibit suboptimal efficacy but high toxicity. Recent studies have demonstrated that immunotherapy-related adverse events (irAE) and the cancer immunotherapeutic effect (CITE) represent distinct and therapeutically separable activities of anti-CTLA-4 antibodies. The former is attributable to inactivation of the CTLA-4 checkpoint, while the latter is due to selective depletion of regulatory T cells (Treg) in a tumor microenvironment. Here we argue that for safer and more effective CTLA-4-targeting immune therapy, one should preserve rather than inhibit the CTLA-4 checkpoint while enhancing the efficacy and selectivity of Treg depletion in a tumor microenvironment.
Cancer therapeutic effect (CITE) of anti-CTLA-4 antibodies is due to selective depletion of tumor-infiltrating regulatory T cells (Treg).Immunotherapy-related adverse events (irAE) is attributable to CTLA-4 inactivation.pH-insensitive antibodies direct CTLA-4 to lysosomal degradation.pH-sensitive anti-CTLA-4 antibodies minimize irAE by preserving CTLA-4 recycling.Preserving CTLA-4 recycling enhances selective depletion of tumor-infiltrating Treg.Preserving the CTLA-4 checkpoint allows safer and more effective immunotherapy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Dense unconventional shale gas extraction activities have occurred in Appalachian Ohio since 2010 and they have caused various landcover changes and forest fragmentation issues. This research ...investigated the most recent boom of unconventional shale gas extraction activities and their impacts on the landcover changes and forest structural changes in the Muskingum River Watershed in Appalachian Ohio. Triple-temporal high-resolution natural-color aerial images from 2006 to 2017 and a group of ancillary geographic information system (GIS) data were first used to digitize the landcover changes due to the recent boom of these unconventional shale gas extraction activities. Geographic object-based image analysis (GEOBIA) was then employed to form forest patches as image objects and to accurately quantify the forest connectivity. Lastly, the initial and updated forest image objects were used to quantify the loss of core forest as the two-dimensional (2D) forest structural changes, and initial and updated canopy height models (CHMs) derived from airborne light detection and ranging (LiDAR) point clouds were used to quantify the loss of forest volume as three-dimensional (3D) forest structural changes. The results indicate a consistent format but uneven spatiotemporal development of these unconventional shale gas extraction activities. Dense unconventional shale gas extraction activities formed two apparent hotspots. Two-thirds of the well pad facilities and half of the pipeline right-of-way (ROW) corridors were constructed during the raising phase of the boom. At the end of the boom, significant forest fragmentation already occurred in both hotspots of these active unconventional shale gas extraction activities, and the areal loss of core forest reached up to 14.60% in the densest concentrated regions of these activities. These results call for attention to the ecological studies targeted on the forest fragmentation in the Muskingum River Watershed and the broader Appalachian Ohio regions.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Phenol‐based macrocyclic arenes have been widely used in supramolecular chemistry, significantly enriching the toolbox of the field. In contrast, naphthol‐based macrocyclic arenes are rather ...underdeveloped. Very recently, Gaeta and co‐workers successfully synthesized such macrocycles (referred to as prismnarenes) with good guest‐binding ability by reacting 2,6‐dimethoxynaphthalene with paraformaldehyde under optimized conditions. In view of the simple synthesis and good host–guest chemistry, we anticipate that this macrocycle will find similar success and wide applications as the phenol‐based macrocyclic arenes.
New macrocyclic arenes, so‐called prismnarenes, are readily synthesized from 2,6‐dimethoxynaphthalene and paraformaldehyde in the presence of templates. They adopt a prism‐like structure with an electron‐rich cavity and show excellent binding affinities towards organic cations. In view of the simple synthesis and good host–guest chemistry, they should find many uses in supramolecular chemistry.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
This paper introduces an innovative physics-informed deep learning framework for metamodeling of nonlinear structural systems with scarce data. The basic concept is to incorporate available, yet ...incomplete, physics knowledge (e.g., laws of physics, scientific principles) into deep long short-term memory (LSTM) networks, which constrains and boosts the learning within a feasible solution space. The physics constraints are embedded in the loss function to enforce the model training which can accurately capture latent system nonlinearity even with very limited available training datasets. Specifically for dynamic structures, physical laws of equation of motion, state dependency and hysteretic constitutive relationship are considered to construct the physics loss. In particular, two physics-informed multi-LSTM network architectures are proposed for structural metamodeling. The satisfactory performance of the proposed framework is successfully demonstrated through two illustrative examples (e.g., nonlinear structures subjected to ground motion excitation). It turns out that the embedded physics can alleviate overfitting issues, reduce the need of big training datasets, and improve the robustness of the trained model for more reliable prediction with extrapolation ability. As a result, the physics-informed deep learning paradigm outperforms classical non-physics-guided data-driven neural networks.
•Presented a novel physics-informed deep learning paradigm for metamodeling of nonlinear structures.•Incorporated physics knowledge into deep LSTM networks boosting the learning within a feasible solution space.•Developed two physics-informed multi-LSTM network architectures.•Demonstrated satisfactory performance of the proposed framework on two nonlinear systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Inhibition is the key factor of attentional control (AC). Basketball players are typically exposed to noise from the audience or opposing teams while competing. These distractions disrupt the ...attentional systems, ultimately compromise the athletes’ inhibition ability and directly affect their performance on the court. Hence, effective AC strategies are crucial. Two studies were demonstrated to investigate the effects of noise distractions on attentional control and the moderating effect of self-talk. In Study 1, 36 participants undertook the Stroop task, showing an increased error rate with noise distraction. Thirty-nine national second-level basketball players participated in Study 2, where they engaged in the Antisaccade task under both quiet and noise-distraction conditions, employing different self-talk strategies. Results showed that instructional self-talk reduced the antisaccade error rate in quiet conditions, while motivational self-talk increased the error rate under noise distractions. These findings suggests that noise distraction reduces AC. In competition scenarios, basketball players are required to appropriately implement self-talk strategies to improve AC and prevent potential counterproductive effects.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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