Based on the dualistic model of passion, this study developed a joint moderated–mediating model to investigate the mechanism of dualistic passion on academic thriving. We surveyed 960 Chinese ...university students with a questionnaire. The results showed that harmonious and obsessive passion positively predicted academic thriving, with the effect of harmonious passion being stronger. Academic personal best goal mediated these relationships. Moreover, threat stress appraisal and academic workload jointly moderated the direct effects of harmonious passion on academic personal best goal and obsessive passion on academic personal best goal, and the first stage of the mediating effects of academic personal best goal between harmonious passion and academic thriving as well as obsessive passion and academic thriving. Specifically, for low–threat stress appraisal and academic workload, the direct effect of harmonious passion on academic personal best goal and the mediating effect of academic personal best goal were stronger. Meanwhile, for high–threat stress appraisal and academic workload, the same applied for obsessive passion. These findings provide important implications for educational practice by highlighting an underlying mechanism of how and when dualistic passion, particularly for obsessive passion, can initiate and maintain academic thriving.
Caly et al.1 reported that ivermectin inhibited severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) in vitro for up to 48 hours using ivermectin at 5 μM. The concentration resulting in 50% ...inhibition (IC50; 2 µM) was > 35× higher than the maximum plasma concentration (Cmax) after oral administration of the approved dose of ivermectin when given fasted. Simulations were conducted using an available population pharmacokinetic model to predict total (bound and unbound) and unbound plasma concentration‐time profiles after a single and repeat fasted administration of the approved dose of ivermectin (200 μg/kg), 60 mg, and 120 mg. Plasma total Cmax was determined and then multiplied by the lung:plasma ratio reported in cattle to predict the lung Cmax after administration of each single dose. Plasma ivermectin concentrations of total (bound and unbound) and unbound concentrations do not reach the IC50, even for a dose level 10× higher than the approved dose. Even with the high lung:plasma ratio, ivermectin is unlikely to reach the IC50 in the lungs after single oral administration of the approved dose (predicted lung: 0.0873 µM) or at doses 10× higher that the approved dose administered orally (predicted lung: 0.820 µM). In summary, the likelihood of a successful clinical trial using the approved dose of ivermectin is low. Combination therapy should be evaluated in vitro. Repurposing drugs for use in coronavirus disease 2019 (COVID‐19) treatment is an ideal strategy but is only feasible when product safety has been established and experiments of repurposed drugs are conducted at clinically relevant concentrations.
Using the method of meta-analysis to systematically evaluate the consistency of treatment schemes between Watson for Oncology (WFO) and Multidisciplinary Team (MDT), and to provide references for the ...practical application of artificial intelligence clinical decision-support system in cancer treatment. We systematically searched articles about the clinical applications of Watson for Oncology in the databases and conducted meta-analysis using RevMan 5.3 software. A total of 9 studies were identified, including 2463 patients. When the MDT is consistent with WFO at the 'Recommended' or the 'For consideration' level, the overall concordance rate is 81.52%. Among them, breast cancer was the highest and gastric cancer was the lowest. The concordance rate in stage I-III cancer is higher than that in stage IV, but the result of lung cancer is opposite (P < 0.05).Similar results were obtained when MDT was only consistent with WFO at the "recommended" level. Moreover, the consistency of estrogen and progesterone receptor negative breast cancer patients, colorectal cancer patients under 70 years old or ECOG 0, and small cell lung cancer patients is higher than that of estrogen and progesterone positive breast cancer patients, colorectal cancer patients over 70 years old or ECOG 1-2, and non-small cell lung cancer patients, with statistical significance (P < 0.05). Treatment recommendations made by WFO and MDT were highly concordant for cancer cases examined, but this system still needs further improvement. Owing to relatively small sample size of the included studies, more well-designed, and large sample size studies are still needed.
The Mesozoic Western Pacific subduction system significantly impacted the North China and South China blocks along the East Asian continental margin and influenced the tectonic, magmatic, ...metallogenic and geomorphic evolution of the region. However, the dynamics and impact on the zone along the East Asian ocean-continent connection zone remain debated. Here we provide a comprehensive synthesis of the state-of-the-art information from deformation analysis, magmatism, geochronology, tomography and other fields from this region. We evaluate first the pre-Yanshanian (pre-Jurassic) final assembly of blocks and the Late Triassic formation of the unified continental margin in East China. We then focus on the Jurassic and Cretaceous geological processes in the East Asian ocean-continent connection zone. The temporal and spatial evolution of structural propagation, sedimentary depocentre, age zonation and migration of magmatism, as well as the large-scale tectono-morphological inversion in the Earth surface system combined with deep processes, are probed. In the early Yanshannian Period (Early and Middle Jurassic, 200–160 Ma), the destruction of the North China Craton (NCC) was mainly affected by the westward early-stage layered rollback, and stepwise delamination and thinning of its continental lithosphere, resulting in the early Yanshanian westward migration of tectonism and magmatism. Coevally, the combined effect of the closure of the Mongal-Okhotsk Ocean to the north and the subduction of the Bangong-Co- Nujiang Ocean to the south imparted an overall compressional setting in the East Asian Ocean-Continent Connection Zone (EAOCCZ). The centres of asthenospheric upwelling and mantle extrusion at depth continued to migrate eastward, driving the eastward lithospheric thinning with periodic and alternating extension and compression. The South China Block experienced a westward flat subduction during the early Yanshanian Period, resulting in the westward propagation of deformation and magmatism, followed by late two-stage delamination to induce the eastward tectono-magmatism. The difference in tectono-magmatic styles between the North China and South China blocks is a result of the different mechanisms and syles of the deep delamination processes under the superconvergence regime of the East Asian and adjacent plates. Especially delamination under North China generated the northwestward layered and fractured subcontinental lithospheric mantle, whereas under the eastern South China Block, were the oceanic lithospheric mantle of the Paleo- Pacific Plate that underwent flat subduction, or continental garnet peridotite mantle. In the middle Yanshanian Period (Late Jurassic to early Early Cretaceous, 160–125 Ma), the EAOCCZ underwent escape tectonics to form some basins related to strike slip faulting. Generally the extensional basins in the tails of the triangular-shaped escape blocks are perpendicular to the extrusion direction. The transtensional or transpressional basins are controlled by the strike slip faults distributed on both sides of the triangular block, and the flexural basins occur in front. In the late Yanshanian Period (late Early Cretaceous-Late Cretaceous, 125–65 Ma), the Paleo-Pacific (Izanagi) Plate subducted NNW-ward beneath the Eurasian continent, and the subduction angles changed gradually following eastward mantle extrusion induced by the closure of the Okhotsk Ocean to the north and Bangong-Nujiang Ocean to the south, as well as the rollback and subduction retreat of the Paleo-Pacific Plate to the east. The EAOCCZ gradually experienced lithospheric collapse and the formation of metamorphic core complexes, as well as obvious landscape reversal. During 70–45 Ma, the Izanagi-Pacific Ridge subducted beneath the EAOCCZ to induce wide uplift resulting in the formation of the Cenozoic dextral transtension-related basins.
Learning Compact Binary Face Descriptor for Face Recognition Lu, Jiwen; Liong, Venice Erin; Zhou, Xiuzhuang ...
IEEE transactions on pattern analysis and machine intelligence,
2015-Oct.-1, 2015-Oct, 2015-10-1, 20151001, Letnik:
37, Številka:
10
Journal Article
Recenzirano
Binary feature descriptors such as local binary patterns (LBP) and its variations have been widely used in many face recognition systems due to their excellent robustness and strong discriminative ...power. However, most existing binary face descriptors are hand-crafted, which require strong prior knowledge to engineer them by hand. In this paper, we propose a compact binary face descriptor (CBFD) feature learning method for face representation and recognition. Given each face image, we first extract pixel difference vectors (PDVs) in local patches by computing the difference between each pixel and its neighboring pixels. Then, we learn a feature mapping to project these pixel difference vectors into low-dimensional binary vectors in an unsupervised manner, where 1) the variance of all binary codes in the training set is maximized, 2) the loss between the original real-valued codes and the learned binary codes is minimized, and 3) binary codes evenly distribute at each learned bin, so that the redundancy information in PDVs is removed and compact binary codes are obtained. Lastly, we cluster and pool these binary codes into a histogram feature as the final representation for each face image. Moreover, we propose a coupled CBFD (C-CBFD) method by reducing the modality gap of heterogeneous faces at the feature level to make our method applicable to heterogeneous face recognition. Extensive experimental results on five widely used face datasets show that our methods outperform state-of-the-art face descriptors.
Autophagy is a highly conserved process that degrades certain intracellular contents in both physiological and pathological conditions. Autophagy-related proteins (
) are key players in this pathway, ...among which
is indispensable in both canonical and non-canonical autophagy. Recent studies demonstrate that
modulates the immune system and crosstalks with apoptosis. However, our knowledge of the pathogenesis and regulatory mechanisms of autophagy in various immune related diseases is lacking. Thus, a deeper understanding of
's role in the autophagy mechanism may shed light on the link between autophagy and the immune response, and lead to the development of new therapies for autoimmune diseases and autoinflammatory diseases. In this focused review, we discuss the latest insights into the role of
in autoimmunity. Although these studies are at a relatively early stage,
may eventually come to be regarded as a "guardian of immune integrity." Notably, accumulating evidence indicates that other
genes may have similar functions.
In this paper, we propose a context-aware local binary feature learning (CA-LBFL) method for face recognition. Unlike existing learning-based local face descriptors such as discriminant face ...descriptor (DFD) and compact binary face descriptor (CBFD) which learn each feature code individually, our CA-LBFL exploits the contextual information of adjacent bits by constraining the number of shifts from different binary bits, so that more robust information can be exploited for face representation. Given a face image, we first extract pixel difference vectors (PDV) in local patches, and learn a discriminative mapping in an unsupervised manner to project each pixel difference vector into a context-aware binary vector. Then, we perform clustering on the learned binary codes to construct a codebook, and extract a histogram feature for each face image with the learned codebook as the final representation. In order to exploit local information from different scales, we propose a context-aware local binary multi-scale feature learning (CA-LBMFL) method to jointly learn multiple projection matrices for face representation. To make the proposed methods applicable for heterogeneous face recognition, we present a coupled CA-LBFL (C-CA-LBFL) method and a coupled CA-LBMFL (C-CA-LBMFL) method to reduce the modality gap of corresponding heterogeneous faces in the feature level, respectively. Extensive experimental results on four widely used face datasets clearly show that our methods outperform most state-of-the-art face descriptors.
In response to stimulation, B lymphocytes pursue a large number of distinct fates important for immune regulation. Whether each cell's fate is determined by external direction, internal stochastic ...processes, or directed asymmetric division is unknown. Measurement of times to isotype switch, to develop into a plasmablast, and to divide or to die for thousands of cells indicated that each fate is pursued autonomously and stochastically. As a consequence of competition between these processes, censorship of alternative outcomes predicts intricate correlations that are observed in the data. Stochastic competition can explain how the allocation of a proportion of B cells to each cell fate is achieved. The B cell may exemplify how other complex cell differentiation systems are controlled.
In this paper, we propose a simultaneous local binary feature learning and encoding (SLBFLE) approach for both homogeneous and heterogeneous face recognition. Unlike existing hand-crafted face ...descriptors such as local binary pattern (LBP) and Gabor features which usually require strong prior knowledge, our SLBFLE is an unsupervised feature learning approach which automatically learns face representation from raw pixels. Unlike existing binary face descriptors such as the LBP, discriminant face descriptor (DFD), and compact binary face descriptor (CBFD) which use a two-stage feature extraction procedure, our SLBFLE jointly learns binary codes and the codebook for local face patches so that discriminative information from raw pixels from face images of different identities can be obtained by using a one-stage feature learning and encoding procedure. Moreover, we propose a coupled simultaneous local binary feature learning and encoding (C-SLBFLE) method to make the proposed approach suitable for heterogenous face matching. Unlike most existing coupled feature learning methods which learn a pair of transformation matrices for each modality, we exploit both the common and specific information from heterogeneous face samples to characterize their underlying correlations. Experimental results on six widely used face datasets including the LFW, YouTube Face (YTF), FERET, PaSC, CASIA VIS-NIR 2.0, and Multi-PIE datasets are presented to demonstrate the effectiveness of the proposed methods.
The central dogma of the action of current anticancer drugs is that the drug tightly binds to its molecular target for inhibition. The reliance on tight ligand–receptor binding, however, is also the ...major root of drug resistance in cancer therapy. In this article, we highlight enzyme-instructed self-assembly (EISA)the integration of enzymatic transformation and molecular self-assemblyas a multistep process for the development of cancer therapy. Using apoptosis as an example, we illustrate that the combination of enzymatic transformation and self-assembly, in fact, is an inherent feature of apoptosis. After the introduction of EISA of small molecules in the context of supramolecular hydrogelation, we describe several key studies to underscore the promises of EISA for developing cancer therapy. Particularly, we will highlight that EISA allows one to develop approaches to target “undruggable” targets or “untargetable” features of cancer cells and provides the opportunity for simultaneously interacting with multiple targets. We envision that EISA, used separately or in combination with current anticancer therapeutics, will ultimately lead to a paradigm shift for developing anticancer medicine that inhibit multiple hallmark capabilities of cancer.
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