Optimality Analysis and Block Sparse Algorithm for Complex Compressed Sensing

Recently, many new challenges in Compressed Sensing (CS), such as block sparsity, arose. In this paper, we present a new algorithm for solving CS with block sparse constraints (BSC) in complex fields. Firstly, based on block sparsity characteristics, we propose a new model to deal with CS with BSC and analyze the properties of the functions involved in this model. We then present a new $\tau$-stationary point and analyze corresponding first-order sufficient and necessary conditions. That ensures we to further develop a block Newton hard-thresholding pursuit (BNHTP) algorithm for efficiently solving CS with BSC. Finally, preliminary numerical experiments demonstrate that the BNHTP algorithm has superior performance in terms of recovery accuracy and calculation time when compared with the classical AMP algorithm.Comment: arXiv admin note: text overlap with arXiv:0906.3173 by other author

Using General Anesthesia plus Muscle Relaxant in a Patient with Spinal Muscular Atrophy Type IV: A Case Report

Spinal muscular atrophy (SMA) is a rare genetic disease characterized by degeneration of spinal cord motor neurons, which results in hypotonia and muscle weakness. Patients with type IV SMA often have onset of weakness from adulthood. Anesthetic management is often difficult in these patients as a result of muscle weakness and hypersensitivity to neuromuscular blocking agents as shown by (Lunn and Wang; 2008, Simic; 2008, and Cifuentes-Diaz et al.; 2002). Herein we report a case of anesthetic management of a patient with SMA type IV for mammectomy and review some other cases of SMA patients receiving different kinds of anesthesia

MSECNet: Accurate and Robust Normal Estimation for 3D Point Clouds by Multi-Scale Edge Conditioning

Estimating surface normals from 3D point clouds is critical for various applications, including surface reconstruction and rendering. While existing methods for normal estimation perform well in regions where normals change slowly, they tend to fail where normals vary rapidly. To address this issue, we propose a novel approach called MSECNet, which improves estimation in normal varying regions by treating normal variation modeling as an edge detection problem. MSECNet consists of a backbone network and a multi-scale edge conditioning (MSEC) stream. The MSEC stream achieves robust edge detection through multi-scale feature fusion and adaptive edge detection. The detected edges are then combined with the output of the backbone network using the edge conditioning module to produce edge-aware representations. Extensive experiments show that MSECNet outperforms existing methods on both synthetic (PCPNet) and real-world (SceneNN) datasets while running significantly faster. We also conduct various analyses to investigate the contribution of each component in the MSEC stream. Finally, we demonstrate the effectiveness of our approach in surface reconstruction.Comment: Accepted for ACM MM 202

Poly[(μ 6-benzene-1,2,4,5-tetra­carboxyl­ato)bis­(1,10-phenanthroline-κ 2 N,N′)dimanganese(II)]

The title polymeric compound, [Mn2(C10H2O8)(C12H8N2)2]n, was obtained by the reaction of manganese(II) chloride tetra­hydrate with benzene-1,2,4,5-tetra­carboxylic acid (H4bta) in aqueous solution. Each Mn2+ ion is coordinated in a distorted octa­hedral geometry by two N atoms from one 1,10-phenanthroline ligand and four O atoms [Mn—O = 2.116 (2)–2.237 (2) Å] from three bta4− ligands, which also act as bridging groups between the Mn2+ ions

Intranasal Immunization with Chitosan/pCAGGS-flaA Nanoparticles Inhibits Campylobacter jejuni in a White Leghorn Model

Campylobacter jejuni is the most common zoonotic bacterium associated with human diarrhea, and chickens are considered to be one of the most important sources for human infection, with no effective prophylactic treatment available. We describe here a prophylactic strategy using chitosan-DNA intranasal immunization to induce specific immune responses. The chitosan used for intranasal administration is a natural mucus absorption enhancer, which results in transgenic DNA expression in chicken nasopharynx. Chickens immunized with chitosan-DNA nanoparticles, which carried a gene for the major structural protein FlaA, produced significantly increased levels of serum anti-Campylobacter jejuni IgG and intestinal mucosal antibody (IgA), compared to those treated with chitosan-DNA (pCAGGS). Chitosan-pCAGGS-flaA intranasal immunization induced reductions of bacterial expellation by 2-3 log10 and 2 log10 in large intestine and cecum of chickens, respectively, when administered with the isolated C. jejuni strain. This study demonstrated that intranasal delivery of chitosan-DNA vaccine successfully induced effective immune response and might be a promising vaccine candidate against C. jejuni infection

Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud Segmentation

3D point clouds can flexibly represent continuous surfaces and can be used for various applications; however, the lack of structural information makes point cloud recognition challenging. Recent edge-aware methods mainly use edge information as an extra feature that describes local structures to facilitate learning. Although these methods show that incorporating edges into the network design is beneficial, they generally lack interpretability, making users wonder how exactly edges help. To shed light on this issue, in this study, we propose the Diffusion Unit (DU) that handles edges in an interpretable manner while providing decent improvement. Our method is interpretable in three ways. First, we theoretically show that DU learns to perform task-beneficial edge enhancement and suppression. Second, we experimentally observe and verify the edge enhancement and suppression behavior. Third, we empirically demonstrate that this behavior contributes to performance improvement. Extensive experiments performed on challenging benchmarks verify the superiority of DU in terms of both interpretability and performance gain. Specifically, our method achieves state-of-the-art performance in object part segmentation using ShapeNet part and scene segmentation using S3DIS. Our source code will be released at https://github.com/martianxiu/DiffusionUnit

Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game

In this study, we explore the robustness of cooperative multi-agent reinforcement learning (c-MARL) against Byzantine failures, where any agent can enact arbitrary, worst-case actions due to malfunction or adversarial attack. To address the uncertainty that any agent can be adversarial, we propose a Bayesian Adversarial Robust Dec-POMDP (BARDec-POMDP) framework, which views Byzantine adversaries as nature-dictated types, represented by a separate transition. This allows agents to learn policies grounded on their posterior beliefs about the type of other agents, fostering collaboration with identified allies and minimizing vulnerability to adversarial manipulation. We define the optimal solution to the BARDec-POMDP as an ex post robust Bayesian Markov perfect equilibrium, which we proof to exist and weakly dominates the equilibrium of previous robust MARL approaches. To realize this equilibrium, we put forward a two-timescale actor-critic algorithm with almost sure convergence under specific conditions. Experimentation on matrix games, level-based foraging and StarCraft II indicate that, even under worst-case perturbations, our method successfully acquires intricate micromanagement skills and adaptively aligns with allies, demonstrating resilience against non-oblivious adversaries, random allies, observation-based attacks, and transfer-based attacks

2,2′-(p-Phenyl­ene)bis­(4,5-dihydro-1H-imidazol-3-ium) bis­(3-nitro­benzoate)

In the title compound, C12H16N4 +·2C7H4NO4 −, the complete 2,2′-(p-phenyl­ene)bis­(4,5-dihydro-1H-imidazol-3-ium) (bib) dication is generated by crystallographic inversion symmetry. The bib cations reside on crystallographic inversion centers, which coincide with the centroids of the respective benzene rings. In the cation, the imidazole ring adopts an envelop conformation with the flap atom displaced by 0.082 (3) Å from the plane through the other ring atoms. In the crystal, the cations and anions are linked through inter­molecular N—H⋯O hydrogen bonds, forming chains running along the a axis. C—H⋯O inter­actions also occur. Weak π–π contacts between the imidazole rings of bib and between the benzene rings of NB [centroid–centroid distances = 3.501 (1) and 3.281 (2) Å, respectively] may further stabilize the structure

The therapeutic evaluation and mechanism on treating bronchial hyper-responsiveness cough by ziyinqingre prescription

Objective: Discussing the effects of Ziyinqingre prescription on the level of airway resistance (Rrs), airway response threshold (Dmin), airway conductance (sGrs) and the level of inflammatory cytokines interleukin-4 (IL-4) and interferon-γ (IFN-γ) of the bronchial hyper-responsiveness (BHR) cough patients.Method: 84 subjects diagnosed as BHR were randomly divided into 42 Chinese Traditional medicine group and 42 control group. The Chinese Traditional Medicine group received Ziyinqingre prescription twice a day and the control group received 10mg Montelukast Sodium tablets once a day for two weeks. Observe the clinical symptoms improvement and the changes of the level of the Rrs, Dmin, sGrs and IL-4, IFN-γ.Results: After receiving the medicine, the symptoms of the Chinese medicine group were obviously alleviated, the outcome was more satisfied than that of the control group. Compared with the control group, the level of Dmin increased and sGrs level decreased more obviously (P<0.05); the level of IL-4 decreased and IFN-γlevel increased more obviously in the Chinese medicine group (P<0.05).Conclusion: Ziyinqingre prescription can not only improve BHR patients’ symptoms, but reduce the level of bronchial responsiveness, which proved a better curative effect of Chinese medicine. The mechanism is probably due to relieving the airway inflammation by keeping the balance between Th1 and Th2 cells.Keywords: Ziyinqingre prescription; cough; bronchial hyper-responsiveness; therapeutic mechanis

catena-Poly[[aqua­(dipyrido[3,2-a:2′,3′-c]phenazine-κ2 N 4,N 5)zinc(II)]-μ-pyrazine-2,3-dicarboxyl­ato-κ3 N 1,O 2:O 3]

In the title compound, [Zn(C6H2N2O4)(C18H10N4)(H2O)]n or [Zn(PZDC)(DPPZ)(H2O)]n (where DPPZ is dipyrido[3,2-a:2′,3′-c]phenazine and H2PZDC is pyrazine-2,3-dicarboxylic acid), the Zn atom is six-coordinated in a slightly distorted octa­hedral coordination geometry by three N atoms from one DPPZ ligand and one PZDC2− dianion, three O atoms from two different PZDC2− ligands and one water mol­ecule. Each PZDC2− dianion serves as a spacer, connecting adjacent metal atoms into a polymeric chain structure parallel to the b axis. The chain motif is consolidated into a three-dimensional supra­molecular network by O—H⋯O and O—H⋯N hydrogen bonds and π–π aromatic stacking inter­actions involving adjacent DPPZ ligands and PZDC2− dianions with centroid–centroid separations of 3.522 (6) and 3.732 (8) Å, respectively