This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition. Specifically, we formulate the objective function into the ...group-wise least square loss regularized by low rank and sparsity with respect to two latent variables, model parameters and grouping information, for joint optimization. To handle this non-convex optimization, we decompose it into two sub-tasks, multi-task learning and task relatedness discovery. First, we convert this non-convex objective function into the convex formulation by fixing the latent grouping information. This new objective function focuses on multitask learning by strengthening the shared-action relationship and action-specific feature learning. Second, we leverage the learned model parameters for the task relatedness measure and clustering. In this way, HC-MTL can attain both optimal action models and group discovery by alternating iteratively. The proposed method is validated on three kinds of challenging datasets, including six realistic action datasets (Hollywood2, YouTube, UCF Sports, UCF50, HMDB51 & UCF101), two constrained datasets (KTH & TJU), and two multi-view datasets (MV-TJU & IXMAS). The extensive experimental results show that: 1) HC-MTL can produce competing performances to the state of the arts for action recognition and grouping; 2) HC-MTL can overcome the difficulty in heuristic action grouping simply based on human knowledge; 3) HC-MTL can avoid the possible inconsistency between the subjective action grouping depending on human knowledge and objective action grouping based on the feature subspace distributions of multiple actions. Comparison with the popular clustered multi-task learning further reveals that the discovered latent relatedness by HC-MTL aids inducing the group-wise multi-task learning and boosts the performance. To the best of our knowledge, ours is the first work that breaks the assumption that all actions are either independent for individual learning or correlated for joint modeling and proposes HC-MTL for automated, joint action grouping and modeling.
Studies on the association between adiponectin and leptin and anxiety and depression among postmenopausal women are limited. Therefore, the present study specifically evaluates the mutual ...relationships between adiponectin and leptin and anxiety and depression in postmenopausal women.
In this cross-sectional study, a total of 190 women aged 40-65 years were enrolled. Depression symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D), and anxiety symptoms were evaluated using the Hamilton Anxiety Rating Scale (HAM-A). Fasting specimens were collected to measure sex hormone, glucose, insulin, and adipokine levels. Multiple linear regression analysis was performed to evaluate the associations between depression and anxiety and adipocyte-derived hormones.
The study was performed in a hospital medical center.
Among 190 enrolled postmenopausal women, Spearman's rank correlation analysis revealed significant correlations between CES-D and HAM-A (r = 0.715, P < 0.0001), between CES-D and adiponectin (p = 0.009) and leptin (p = 0.015), and between HAM-A and adiponectin (p = 0.01) and leptin (p = 0.001). The subjects with CES-D ≥ 16 and with HAM-A ≥ 18 had higher adiponectin levels than those with CES-D < 16 and HAM-A < 18, respectively. After adjusting for age, body mass index, exercise, alanine amino transferase and parameters of lipid profiles, Log adiponectin levels were found to be significantly associated with both CES-D and HAM-A, and Log leptin levels were only significantly associated with HAM-A.
The data show that adiponectin and leptin levels are significantly associated with depression and anxiety symptoms. These results suggest that higher adiponectin and lower leptin levels may serve as potential markers related to anxiety and mood in postmenopausal women. More future research that is designed to deal with the important confounders (e.g., population heterogeneity) is needed to investigate comprehensively on these associations.
Lifting heptagon symbols to functions Dixon, Lance J.; Liu, Yu-Ting
The journal of high energy physics,
10/2020, Letnik:
2020, Številka:
10
Journal Article
Recenzirano
Odprti dostop
A
bstract
Seven-point amplitudes in planar
N
= 4 super-Yang-Mills theory have previously been constructed through four loops using the Steinmann cluster bootstrap, but only at the level of the ...symbol. We promote these symbols to actual functions, by specifying their first derivatives and boundary conditions on a particular two-dimensional surface. To do this, we impose branch-cut conditions and construct the entire heptagon function space through weight six. We plot the amplitudes on a few lines in the bulk Euclidean region, and explore the properties of the heptagon function space under the coaction associated with multiple polylogarithms.
Fast and efficient cleanup of crude oil spills is still a global challenge because most of the crude oils are highly viscous and lowly fluid. Herein, a kind of polydimethylsiloxane‐decorated wood ...carbon sponges (PDMS@WCS) with desirable compressibility and hydrophobicity for the fast adsorption and enhanced recovery of crude oil via the promotion of Joule‐heating and photothermal effect is reported. Moreover, the PDMS@WCS can be compressed and released at a constant strain of 50% for over times without structural damage due to the protection of PDMS coating. Thus, the adsorbed crude oil can be facilely excluded from PDMS@WCS under external pressure to show enhanced recovery.
Compressible and hydrophobic wood carbon sponges are elegantly fabricated from natural balsa woods and applied for the rapid recovery of high viscosity crude oil via the promotion of Joule‐heating and photothermal effect. Moreover, they possess a vertical porous structure inherited from natural wood that can greatly reduce the transport path of crude oil and increase the oil adsorption rate.
A
bstract
I present a conjecture that all two-loop MHV amplitudes in planar
N
= 4 super-Yang-Mills theory possess an antipodal symmetry when evaluated on parity-even kinematics. The symmetry acts as ...a change of basis on the symbol letters, followed by the antipode operation associated with the Hopf algebra structure of multiple polylogarithms. At the symbol level, I provide the symmetry map explicitly for amplitudes with up to eight external particles, and also provide evidence at all multiplicities. Intriguingly, the map acts as an isomorphism on the normal fans of the Newton polytopes of the symbol letters. The conjectured symmetry is one of the rare known cases where the antipode map shows up in physically important examples.
The current strategies for nanoelectrode functionalization usually involve sophisticated modification procedures, uncontrollable and unstable modifier assembly, as well as a limited variety of ...modifiers. To address this issue, we propose a versatile strategy for large‐scale synthesis of biomimetic molecular catalysts (BMCs) modified nanowires (NWs) to construct functionalized electrochemical nanosensors. This design protocol employs an easy, controllable and stable assembly of diverse BMCs‐poly(3,4‐ethylenedioxythiophene) (PEDOT) composites on conductive NWs. The intrinsic catalytic activity of BMCs combined with outstanding electron transfer ability of conductive polymer enables the nanosensors to sensitively and selectively detect various biomolecules. Further application of sulfonated cobalt phthalocyanine functionalized nanosensors achieves real‐time electrochemical monitoring of intracellular glutathione levels and its redox homeostasis in single living cells for the first time.
Versatile and large‐scale synthesis of biomimetic molecular catalyst modified nanowires provides an innovative perspective for simple and stable construction of functionalized electrochemical nanosensors. Such nanosensors enable the sensitive and selective detection of diverse biomolecules, and for the first time achieve real‐time electrochemical monitoring of intracellular glutathione levels and its redox homeostasis in single living cells.
Lung cancer is one of the greatest threats to human health, and is initially detected and attacked by the immune system through tumor‐reactive T cells. The aim of this study was to determine the ...basic characteristics and clinical significance of the peripheral blood T‐cell receptor (TCR) repertoire in patients with advanced lung cancer. To comprehensively profile the TCR repertoire, high‐throughput sequencing was used to identify hypervariable rearrangements of complementarity determining region 3 (CDR3) of the TCR β chain in peripheral blood samples from 64 advanced lung cancer patients and 31 healthy controls. We found that the TCR repertoire differed substantially between lung cancer patients and healthy controls in terms of CDR3 clonotype, diversity, V/J segment usage, and sequence. Specifically, baseline diversity correlated with several clinical characteristics, and high diversity reflected a better immune status. Dynamic detection of the TCR repertoire during anticancer treatment was useful for prognosis. Both increased diversity and high overlap rate between the pre‐ and post‐treatment TCR repertoires indicated clinical benefit. Combination of the diversity and overlap rate was used to categorize patients into immune improved or immune worsened groups and demonstrated enhanced prognostic significance. In conclusion, TCR repertoire analysis served as a useful indicator of disease development and prognosis in advanced lung cancer and may be utilized to direct future immunotherapy.
What's new?
T cells are essential players in the anti‐cancer immune response. Characterization of the T‐cell receptor (TCR) repertoire is a promising method for assessing tumor activity, directing therapy, and predicting prognosis; however, the importance of the TCR repertoire in lung cancer is unclear. This sequencing analysis found that the peripheral blood TCR repertoire of patients with advanced lung cancer was significantly different from that of healthy individuals. The peripheral blood TCR repertoire correlated with several clinical characteristics and patient immune status. Dynamic TCR repertoire analysis served as a useful indicator of disease development and may be utilized to direct future immunotherapy.
A strategy for one‐pot and large‐scale synthesis of functionalized core–shell nanowires (NWs) to high‐efficiently construct single nanowire electrodes is proposed. Based on the polymerization ...reaction between 3,4‐ethylenedioxythiophene (EDOT) and noble metal cations, manifold noble metal nanoparticles‐polyEDOT (PEDOT) nanocomposites can be uniformly modified on the surface of any nonconductive NWs. This provides a facile and versatile approach to produce massive number of core–shell NWs with excellent conductivity, adjustable size, and well‐designed properties. Nanoelectrodes manufactured with such core–shell NWs exhibit excellent electrochemical performance and mechanical stability as well as favorable antifouling properties, which are demonstrated by in situ intracellular monitoring of biological molecules (nitric oxide) and unraveling its relevant unclear signaling pathway inside single living cells.
Versatile one‐pot synthesis of functionalized core–shell nanowires breaks through the limitation of nanoelectrode materials to facilely construct high‐performance single nanowire electrodes. Concurrently with excellent electrochemical, mechanical, and antifouling properties, the nanowire electrodes show great superiority in real‐time monitoring of biological molecules and unraveling the relevant signaling pathway inside single living cells.
Multi-view matching is an important but a challenging task in view-based 3D model retrieval. To address this challenge, we propose an original multi-modal clique graph (MCG) matching method in this ...paper. We systematically present a method for MCG generation that is composed of cliques, which consist of neighbor nodes in multi-modal feature space and hyper-edges that link pairwise cliques. Moreover, we propose an image set-based clique/edgewise similarity measure to address the issue of the set-to-set distance measure, which is the core problem in MCG matching. The proposed MCG provides the following benefits: 1) preserves the local and global attributes of a graph with the designed structure; 2) eliminates redundant and noisy information by strengthening inliers while suppressing outliers; and 3) avoids the difficulty of defining high-order attributes and solving hyper-graph matching. We validate the MCG-based 3D model retrieval using three popular single-modal data sets and one novel multi-modal data set. Extensive experiments show the superiority of the proposed method through comparisons. Moreover, we contribute a novel real-world 3D object data set, the multi-view RGB-D object data set. To the best of our knowledge, it is the largest real-world 3D object data set containing multi-modal and multi-view information.
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