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The dysregulation of Angiotensin-converting enzyme 2 (ACE2) in central nervous system is believed associates with COVID-19 induced cognitive dysfunction. However, the detailed mechanism remains largely unknown. In this study, we performed a comprehensive system genetics analysis on hippocampal ACE2 based on BXD mice panel. Expression quantitative trait loci (eQTLs) mapping showed that Ace2 was strongly trans-regulated, and the elevation of Ace2 expression level was significantly correlated with impaired cognitive functions. Further Gene co-expression analysis showed that Ace2 may be correlated with the membrane proteins in Calcium signaling pathway. Further, qRT-PCR confirmed that SARS-CoV-2 spike S1 protein upregulated ACE2 expression together with eight membrane proteins in Calcium Signaling pathway. Moreover, such elevation can be attenuated by recombinant ACE2. Collectively, our findings revealed a potential mechanism of Ace2 in cognitive dysfunction, which could be beneficial for COVID-19-induced cognitive dysfunction prevention and potential treatment.
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Recently, N6-methyladenosine (m6A) has aroused widespread discussion in the scientific community as a mode of RNA modification. m6A comprises writers, erasers, and readers, which regulates RNA production, nuclear export, and translation and is very important for human health. A large number of studies have found that the regulation of m6A is closely related to the occurrence and invasion of tumors, while the homeostasis and function of the tumor microenvironment (TME) determine the occurrence and development of tumors to some extent. TME is composed of a variety of immune cells (T cells, B cells, etc.) and nonimmune cells (tumor-associated mesenchymal stem cells (TA-MSCs), cancer-associated fibroblasts (CAFs), etc.). Current studies suggest that m6A is involved in regulating the function of various cells in the TME, thereby affecting tumor progression. In this manuscript, we present the composition of m6A and TME, the relationship between m6A methylation and characteristic changes in TME, the role of m6A methylation in TME, and potential therapeutic strategies to provide new perspectives for better treatment of tumors in clinical work.
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Visual Simultaneous Localization and Mapping (V-SLAM) plays a crucial role in the development of intelligent robotics and autonomous navigation systems. However, it still faces significant challenges in handling highly dynamic environments. The prevalent method currently used for dynamic object recognition in the environment is deep learning. However, models such as Yolov5 and Mask R-CNN require significant computational resources, which limits their potential in real-time applications due to hardware and time constraints. To overcome this limitation, this paper proposes ADM-SLAM, a visual SLAM system designed for dynamic environments that builds upon the ORB-SLAM2. This system integrates efficient adaptive feature point homogenization extraction, lightweight deep learning semantic segmentation based on an improved DeepLabv3, and multi-view geometric segmentation. It optimizes keyframe extraction, segments potential dynamic objects using contextual information with the semantic segmentation network, and detects the motion states of dynamic objects using multi-view geometric methods, thereby eliminating dynamic interference points. The results indicate that ADM-SLAM outperforms ORB-SLAM2 in dynamic environments, especially in high-dynamic scenes, where it achieves up to a 97% reduction in Absolute Trajectory Error (ATE). In various highly dynamic test sequences, ADM-SLAM outperforms DS-SLAM and DynaSLAM in terms of real-time performance and accuracy, proving its excellent adaptability.
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Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information from diverse imagery conditions. However, even state-of-the-art methods may stumble in complex plantation patterns. Here, we propose a deep learning approach based on graphs to detect plantation lines in UAV-based RGB imagery, presenting a challenging scenario containing spaced plants. The first module of our method extracts a feature map throughout the backbone, which consists of the initial layers of the VGG16. This feature map is used as an input to the Knowledge Estimation Module (KEM), organized in three concatenated branches for detecting 1) the plant positions, 2) the plantation lines, and 3) the displacement vectors between the plants. A graph modeling is applied considering each plant position on the image as vertices, and edges are formed between two vertices (i.e. plants). Finally, the edge is classified as pertaining to a certain plantation line based on three probabilities (higher than 0.5): i) in visual features obtained from the backbone; ii) a chance that the edge pixels belong to a line, from the KEM step; and iii) an alignment of the displacement vectors with the edge, also from the KEM step. Experiments were conducted initially in corn plantations with different growth stages and patterns with aerial RGB imagery to present the advantages of adopting each module. We assessed the generalization capability in the other two cultures (orange and eucalyptus) datasets. The proposed method was compared against state-of-the-art deep learning methods and achieved superior performance with a significant margin considering all three datasets. This approach is useful in extracting lines with spaced plantation patterns and could be implemented in scenarios where plantation gaps occur, generating lines with few-to-no interruptions.
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The striatum plays a central role in directing many complex behaviors ranging from motor control to action choice and reward learning. In our study, we used 55 male CFW mice with rapid decay linkage disequilibrium to systematically mine the striatum-related behavioral functional genes by analyzing their striatal transcriptomes and 79 measured behavioral phenotypic data. By constructing a gene coexpression network, we clustered the genes into 13 modules, with most of them being positively correlated with motor traits. Based on functional annotations as well as Fisher's exact and hypergeometric distribution tests, brown and magenta modules were identified as core modules. They were significantly enriched for striatal-related functional genes. Subsequent Mendelian randomization analysis verified the causal relationship between the core modules and dyskinesia. Through the intramodular gene connectivity analysis, Adcy5 and Kcnma1 were identified as brown and magenta module hub genes, respectively. Knock outs of both Adcy5 and Kcnma1 lead to motor dysfunction in mice, and KCNMA1 acts as a risk gene for schizophrenia and smoking addiction in humans. We also evaluated the cellular composition of each module and identified oligodendrocytes in the striatum to have a positive role in motor regulation.
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Adenilil Ciclases , Corpo Estriado , Animais , Camundongos , Masculino , Corpo Estriado/metabolismo , Corpo Estriado/fisiologia , Adenilil Ciclases/genética , Comportamento Animal/fisiologia , Redes Reguladoras de Genes/genética , TranscriptomaRESUMO
BACKGROUND: There is growing evidence of a strong correlation between pain sensitivity and cognitive function under both physiological and pathological conditions. However, the detailed mechanisms remain largely unknown. In the current study, we sought to explore candidate genes and common molecular mechanisms underlying pain sensitivity and cognitive function with a transcriptome-wide association study using recombinant inbred mice from the BXD family. METHODS: The pain sensitivity determined by Hargreaves' paw withdrawal test and cognition-related phenotypes were systematically analyzed in 60 strains of BXD mice and correlated with hippocampus transcriptomes, followed by quantitative trait locus (QTL) mapping and systems genetics analysis. RESULTS: The pain sensitivity showed significant variability across the BXD strains and co-varies with cognitive traits. Pain sensitivity correlated hippocampual genes showed a significant involvement in cognition-related pathways, including glutamatergic synapse, and PI3K-Akt signaling pathway. Moreover, QTL mapping identified a genomic region on chromosome 4, potentially regulating the variation of pain sensitivity. Integrative analysis of expression QTL mapping, correlation analysis, and Bayesian network modeling identified Ring finger protein 20 (Rnf20) as the best candidate. Further pathway analysis indicated that Rnf20 may regulate the expression of pain sensitivity and cognitive function through the PI3K-Akt signaling pathway, particularly through interactions with genes Ppp2r2b, Ppp2r5c, Col9a3, Met, Rps6, Tnc, and Kras. CONCLUSIONS: Our study demonstrated that pain sensitivity is associated with genetic background and Rnf20-mediated PI3K-Akt signaling may involve in the regulation of pain sensitivity and cognitive functions.
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Fosfatidilinositol 3-Quinases , Proteínas Proto-Oncogênicas c-akt , Camundongos , Animais , Camundongos Endogâmicos C57BL , Teorema de Bayes , Limiar da Dor , CogniçãoRESUMO
We here describe the isolation of a novel exopolysaccharide from Acinetobacter rhizosphaerae, named ArEPS. The structure of ArEPS was characterized by analysis of the monosaccharide composition, molecular weight, infrared spectrum, methylation, and nuclear magnetic resonance spectrum. ArEPS was found to be an acidic heteropolysaccharide composed of glucose, galactose, galacturonic acid, glucuronic acid, mannose, and glucosamine; the molecular weight was 1533 kDa. Structural analysis showed that the main-chain structure of ArEPS predominantly comprised 1,3,6-ß-Glcp, 1,3,4-α-Galp, 1,2-ß-Glcp, 1,4-ß-GlcpA, 1,4-ß-GalpA, and the side-chain structure comprised 1,6-ß-Glcp, 1,3-ß-Galp, 1-α-Glcp, 1-ß-Galp, 1-α-Manp, 1,4,6-α-Glcp, 1,2,4-ß-Glcp, 1,2,3-ß-Glcp, and 1,3-ß-GlcpN. ArEPS significantly enhanced the tolerance of rice seedlings to salt stress. Specifically, plant height, fresh weight, chlorophyll content, and the K+/Na+ ratio increased by 51 %, 63 %, 29 %, and 162 %, respectively, and the malondialdehyde content was reduced by 45 % after treatment with 100 mg/kg ArEPS compared to treatment with 100 mM NaCl. Finally, based on the quadratic regression between fresh weight and ArEPS addition, the optimal ArEPS addition level was estimated to be 135.12 mg/kg. These results indicate the prospects of ArEPS application in agriculture.
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Acinetobacter , Oryza , Plântula , Plântula/química , Monossacarídeos/análise , Galactose/análise , Polissacarídeos/química , Peso MolecularRESUMO
BACKGROUND: Hepatocellular carcinoma (HCC) has very low overall survival. According to global cancer statistics, approximately 905677 new cases were reported in 2020, with at least 830180 of them being fatal. Cluster of differentiation 147 (CD147) is a novel, transmembrane glycoprotein that is expressed in a wide variety of tumor cells and plays an important role in various stages of tumor development. Based on the reports described previously, we theorize that CD147 may be used as a novel biological indicator to predict the prognosis of HCC. To study this possibility, expression profiles of CD147 and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed, and a hazard ratio (HR) was established. AIM: To explore the pattern of CD147 expression and its applicability in the prognosis of HCC. To establish HRs and probability points for predicting the prognosis of HCC by correlating CD147 expression with clinical characteristics. To determine if CD147 can be a reliable biomarker in HCC prognosis. METHODS: The CD147 expression profile in HCC and corresponding clinical data were obtained from TCGA database. The expression patterns of CD147 were then validated by analyzing data from the GEO database. In addition, CD147 immunohistochemistry in HCC was obtained from the Human Protein Atlas. CD147 expression patterns and clinical characteristics in the prognosis of HCC were analyzed by accessing the UALCAN web resource. Accuracy, sensitivity, and specificity of the CD147 expression profile in predictive prognosis were determined by the time-dependent receiver operating characteristic (ROC) curves. Kaplan-Meier curves were plotted to estimate the HR of survival in HCC. Univariate and multivariate Cox regression proportional hazards analyses of CD147 expression levels and clinical characteristics as prognostic factors of HCC were performed. Nomograms were used to establish probability points and predict prognosis. RESULTS: Data from TCGA and GEO databases revealed that CD147 was significantly overexpressed in HCC (P = 1.624 × 10-12 and P = 1.2 × 10-5, respectively). The expression of CD147 and prognosis of HCC were significantly correlated with the clinical characteristics of HCC as per the data from the UALCAN web resource (P < 0.05). Kaplan-Meier analysis of CD147 expression in HCC revealed that the high expression groups showed poor prognosis and an HR of survival > 1 [log-rank test, P = 0.000542, HR (in high expression group): 1.856, 95% confidence interval (CI): 1.308 to 2.636]. ROC curves were plotted to analyze the 1-year, 3-year, and 5-year survival rates. The area under the ROC curve values were 0.675 (95%CI: 0.611 to 0.740), 0.623 (95%CI: 0.555 to 0.692), and 0.664 (95%CI: 0.582 to 9.745), respectively. Univariate Cox analysis of CD147 expression and clinical characteristics of HCC and multivariate Cox analysis of CD147 patterns and pathological tumor-node-metastasis stage showed significant differences (univariate Cox, P = 0.00013, HR: 1.424, 95%CI: 1.884 to 1.707 and P = 0.00066, HR: 1.376, 95%CI: 1.145 to 1.654, respectively; multivariate Cox, P = 0.00578, HR: 1.507, 95%CI: 1.126 to 2.018 and P = 0.00336, HR: 1.443, 95%CI: 1.129 to 1.844, respectively). Nomograms were plotted to establish the probability points and predict prognosis. The total points ranged from 0 to 180, and the C-index value was 0.673 (95%CI: 0.600 to 1.000, P < 0.01). CONCLUSION: Overexpression of CD147 was correlated with poor prognosis in HCC. The CD147 expression profile combined with clinical characteristics can reliably predict the prognosis of HCC. CD147 can serve as a biomarker to predict the prognosis of HCC.
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Some weakly electric fish can use electric signals to interact and communicate with each other in dark and complex underwater environments where traditional underwater communication fails. In our previous work, we developed a bio-inspired electrocommunication system (BECS) that serves as an effective alternative to traditional methods in this challenging underwater scenario performing communication at a speed of approximately 1200 bps (bits per second) within approximately 3 m. In this study, a novel underwater wireless communication system (BECS-II) is proposed to upgrade the BECS with much better performance. We first propose theoretical and simulation models for electrocommunication, including the effects of the angular frequency and electrode impedance. A custom-made digital communication system is employed in BECS-II to improve the anti-interference ability and channel capacity of the BECS. In addition, a novel circuit optimization strategy was used to develop a customized circuit to enhance the transmitting and receiving capabilities of the BECS-II. Dual-frequency communication is proposed to meet the communication demands of different tasks by taking inspiration from the task allocation and evolution mechanisms of weakly electric fish. The experimental results showed that BECS-II outperformed BECS in high-frequency mode at both the communication speed (approximately 20 kbps) and distance (approximately 10 m), whereas in low-frequency mode, it extended the communication range by transmitting data up to a distance of approximately 20 m at a speed of approximately 200 bps. A substantial increase in the communication distance can expand the robot motion space in a group and improve group flexibility.
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Peixe Elétrico , Robótica , Animais , Comunicação , Simulação por Computador , Impedância ElétricaRESUMO
The locus at 17q12 erb-b2 receptor tyrosine kinase 2 (ERBB2) has been heavily amplificated and overexpressed in gastric cancer (GC), but it remains to be elucidated about the clinical significance of the co-amplification and co-overexpression of PGAP3 gene located around ERBB2 in GC. The profile of PGAP3 and ERBB2 in four GC cell lines and tissue microarrays containing 418 primary GC tissues was assessed to investigate the co-overexpression and clinical significance of the co-amplified genes, and to evaluate the impact of the co-amplified genes on the malignancy of GC. Co-amplification of PGAP3 and ERBB2 accompanied with co-overexpression was observed in a haploid chromosome 17 of NCI-N87 cells with double minutes (DMs). PGAP3 and ERBB2 were overexpressed and positively correlated in 418 GC patients. Co-overexpression of the PGAP3 and ERBB2 was correlated with T stage, TNM stage, tumour size, intestinal histological type and poor survival proportion in 141 GC patients. In vitro, knockdown of the endogenous PGAP3 or ERBB2 decreased cell proliferation and invasion, increased G1 phase accumulation and induced apoptosis in NCI-N87 cells. Furthermore, combined silencing of PGAP3 and ERBB2 showed an additive effect on resisting proliferation of NCI-N87 cells compared with targeting ERBB2 or PGAP3 alone. Taken together, the co-overexpression of PGAP3 and ERBB2 may be crucial due to its significant correlation with clinicopathological factors of GC. Haploid gain of PGAP3 co-amplified with ERBB2 is sufficient to facilitate the malignancy and progression of GC cells in a synergistic way.
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Receptor ErbB-2 , Neoplasias Gástricas , Humanos , Receptor ErbB-2/genética , Receptor ErbB-2/metabolismo , Neoplasias Gástricas/patologia , Linhagem Celular Tumoral , Proliferação de Células/genética , Hidrolases de Éster Carboxílico , Receptores de Superfície CelularRESUMO
The synthesis, structural characterization, exfoliation, and photophysical studies of two-dimensional (2-D) lanthanide phosphonates, named Ln(m-pbc); [Ln(m-Hpbc)(m-H2pbc)(H2O)] (Ln = Eu, Tb; m-pbc = 3-phosphonobenzoic acid) based on the phosphonocarboxylate ligand, are reported. These compounds are neutral polymeric 2D layered structures with pendent uncoordinated carboxylic groups between layers. The nanosheets were obtained by a top-down strategy involving sonication-assisted solution exfoliation and characterized by atomic force microscopy and transmission electron microscropy, showing lateral dimensions from nano- to micro-meter scales, and thicknesses down to several layers. The photoluminescence studies demonstrate that the m-pbc ligand acts as an efficient antenna toward Eu and Tb(III) ions. The emission intensities of dimetallic compounds are clearly enhanced after incorporation of Y(III) ions due to the dilution effect. Ln(m-pbc)s were then applied for labelling latent fingerprints. It is worth noting that the reaction between active carboxylic groups and fingerprint residues benefits the labelling, showing efficient imaging for fingerprints on all kinds of material surfaces.
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In this paper, we propose a hierarchical simulated annealing of erosion method (HSAE) to improve the computational efficiency of multiphase microstructure reconstruction, whose computational efficiency can be improved by an order of magnitude. Reconstruction of the two-dimensional (2D) and three-dimensional (3D) multiphase microstructures (pore, grain, and clay) based on simulated annealing (SA) and HSAE are performed. In the reconstruction of multiphase microstructure with HSAE and SA, three independent two-point correlation functions are chosen as the morphological information descriptors. The two-point cluster function which contains significant high-order statistical information is used to verify the reconstruction results. From the analysis of 2D reconstruction, it can find that the proposed HSAE technique not only improves the quality of reconstruction, but also improves the computational efficiency. The reconstructions of our proposed method are still imperfect. This is because the used two-point correlation functions contain insufficient information. For the 3D reconstruction, the two-point correlation functions of the 3D generation are in excellent agreement with those of the original 2D image, which illustrates that our proposed method is effective for the reconstruction of 3D microstructure. The comparison of the energy vs computational time between the SA and HSAE methods shows that our presented method is an order of magnitude faster than the SA method. That is because only some of the pixels in the overall hierarchy need to be considered for sampling.
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OBJECTIVE: This study aimed to detect the association between P-selectin autoantibody positive and response to steroid treatment in newly diagnosed immune thrombocytopenia (ITP) patients. METHODS: The data from 105 newly diagnosed adult ITP patients administered with first-line of steroid treatment from October 2016 to May 2021 were retrospectively analyzed. Treatment responses were evaluated within 3 months after the onset of treatment. RESULTS: Among the 105 patients, 80.00% (84/105) of patients presented with platelet glycoprotein-specific antibody positive; 44.76% (47/105) patients were anti-P-selectin positive, while 35.24% (37/105) were anti-P-selectin negative. No significant difference in overall response was observed between patients who were anti-P-selectin positive and those who were anti-P-selectin negative (74.47% vs. 89.19, χ2 = 2.910, p = 0.088). But patients who were anti-P-selectin negative had significantly higher complete response rate, compared to those who were anti-P-selectin positive (72.97% vs. 48.94%, χ2 = 4,965, p = 0.026). Logistic regression analysis revealed that anti-GP IIb/IIIa positive (OR = 3.114, p = 0.010, 95% CI: 1.313-7.388) and anti-P-selectin positive (OR = 0.309, p = 0.036, 95% CI: 0.127-0.753) were two factors that could affect patients' response. CONCLUSIONS: Our study found that ITP patients with anti-GP IIb/IIIa may have a higher response to steroid treatment, but anti-P-selectin-mediated-ITP might be less responsive to steroid treatment. In adults with ITP, the presence of anti-P-selectin autoantibodies is a predictive factor for poor response to steroid treatment.
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Púrpura Trombocitopênica Idiopática , Trombocitopenia , Adulto , Autoanticorpos , Plaquetas , Humanos , Glicoproteínas da Membrana de Plaquetas , Púrpura Trombocitopênica Idiopática/diagnóstico , Púrpura Trombocitopênica Idiopática/tratamento farmacológico , Estudos Retrospectivos , Esteroides/uso terapêutico , Trombocitopenia/diagnóstico , Trombocitopenia/tratamento farmacológicoRESUMO
BACKGROUND: Hypoxia-induced chemoresistance is recognized as a major obstacle to the successful treatment of gastric cancer (GC). Circular RNAs (circRNAs) have been proposed to implicate in resistance to chemotherapeutic drugs. However, whether circNRIP1 is involved in the development of hypoxia-induced 5-fluorouracil (5-FU) resistance remains largely unknown. METHODS: Gene expression was evaluated using quantitative real-time polymerase chain reaction and Western blot. The impact of circNRIP1 on hypoxia-induced resistance to 5-FU was investigated by determining glucose consumption, lactate production and glucose-6-phosphate (G6P) levels. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolim bromide assay was performed to assess cell survival. RESULTS: circNRIP1 was upregulated in GC cells. Hypoxia induced the upregulation of circNRIP1 and reduced the sensitivity of GC cells to 5-FU, as evidenced by the increase in multidrug resistance 1 gene, P-glycoprotein, hypoxia-inducible factor-1α (HIF-1α) and G6P levels, glucose consumption, lactate production, as well as cell survival. Silencing of circNRIP1 enhanced the sensitivity of GC cells to 5-FU under a hypoxic condition. microRNA (miR)-138-5p was confirmed as a downstream target gene of circNRIP1, and upregulation of miR-138-5p could reverse the effect of circNRIP1 on hypoxia-induced 5-FU resistance. Additionally, HIF-1α was a target gene of miR-138-5p. More significantly, the effect of circNRIP1 on hypoxia-induced 5-FU resistance was markedly blocked by 2-DG treatment. CONCLUSION: circNRIP1 functioned as a miR-138-5p sponge to enhance hypoxia-induced resistance to 5-FU through modulation of HIF-1α-dependent glycolysis, which provides a novel potential approach to overcome hypoxia-induced 5-FU resistance in GC.
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A powerful and efficient hybrid method combining the finite-element boundary-integral method with fast multipole method (FE-BI-FMM) is proposed in this paper to study the electromagnetic scattering characteristics from a coated object above a two-layered dielectric rough surface. The finite-element method (FEM) is applied to model the scattering from the coated object, and multiple interactions between the object and layered rough surface are handled by the FMM-enhanced boundary integral method (BIM). A hybrid solver is adopted to efficiently solve the FEM-BIM matrix equation. Several numerical results are presented, and the influence of several parameters of the composite model on the scattering characteristics is analyzed in detail. Both vertical and horizontal polarizations for the incident waves are considered.
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TOB1, a member of the BTG/TOB protein family, inhibits tumor cell proliferation. We previously observed down-regulation and phosphorylation of TOB1 in gastric cancer (GC). Here, we examined the subcellular distribution and clinical significance of TOB1 expression and phosphorylation in GC. Immunohistochemical analysis of 341 primary GC and corresponding normal gastric tissue samples demonstrated that nuclear TOB1 expression was lower in GC than normal tissue (80.4% vs. 92.4%), and decreased nuclear TOB1 expression correlated with high TNM stage. By contrast, phosphorylation of nuclear TOB1 was higher in GC than normal gastric tissue (66.0% vs. 36.4%), and was associated with poorly differentiated and high TNM stage tumors. Patients with intestinal type GC and increased nuclear TOB1 phosphorylation had poor overall survival. Multivariate survival analysis indicated the nuclear concentration of phosphorylated TOB1 was an independent prognostic factor for intestinal type GC. Overexpression of TOB1 containing mutations in its nuclear export signal inhibited GC cell proliferation, migration, and invasion compared to cells expressing TOB1 with the nuclear localization signal. Thus, decreased TOB1 expression and increased phosphorylation of nuclear TOB1 is associated with aggressive tumor behavior and poor prognosis in intestinal type GC. Additionally, TOB1 nuclear retention is critical for its anti-proliferative activity.
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The existing adaptive single-pixel imaging methods suffer from a waste of sampling resources. The sampling resources are not used adequately for superior localization of significant coefficients and reconstruction. In this paper, an adaptive single-pixel imaging method via the guided coefficients in the Haar wavelet tree is proposed. The goal is to achieve high quality imaging with less sampling resources. The guided coefficients are selected from the unsampled coefficients by a proposed same-scale prediction method based on the sampled coefficients. These guided coefficients are used to localize the significant coefficients with higher resolution belonging to the sampled coefficients and the significant coefficients belonging to the guided coefficients by a proposed guided prediction method. The significant guided coefficients are then used in the composite reconstruction method to reconstruct the image. Performance analysis shows that the proposed method reduces waste of the sampling resources and localizes more significant coefficients. Simulation results demonstrate that the proposed method improves the imaging quality in terms of peak signal-to-noise ratio up to 29.7 dB for the images containing regular and chaotic textures in the noise-free environment. The sampling rate for the same imaging quality can be reduced up to 56%. Under the noisy condition, the proposed method also achieves better imaging quality at a lower sampling rate.
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For lower sampling rate and better imaging quality, a compressive adaptive ghost imaging is proposed by adopting the sharing mechanism and fellow relationship in the wavelet tree. The sharing mechanisms, including intrascale and interscale sharing mechanisms, and fellow relationship are excavated from the wavelet tree and utilized for sampling. The shared coefficients, which are part of the approximation subband, are localized according to the parent coefficients and sampled based on the interscale sharing mechanism and fellow relationship. The sampling rate can be reduced owing to the fact that some shared coefficients can be calculated by adopting the parent coefficients and the sampled sum of shared coefficients. According to the shared coefficients and parent coefficients, the proposed method predicts the positions of significant coefficients and samples them based on the intrascale sharing mechanism. The ghost image, reconstructed by the significant coefficients and the coarse image at the given largest scale, achieves better quality because the significant coefficients contain more detailed information. The simulations demonstrate that the proposed method improves the imaging quality at the same sampling rate and also achieves a lower sampling rate for the same imaging quality for different types of target object images in noise-free and noisy environments.
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Three zinc(II) phosphonocarboxylates, [Zn3 (m-bpc)2 (OH)]â (CH3 )2 NH2 â H2 O (1), [Zn2 (m-bpc)(m-Hbpc)(4,4'-bpy)]â (CH3 )2 NH2 â H2 O (2) and [Zn3 (m-bpc)2 (4,4'-bpy)(CH3 )2 NH]â H2 O (3) (m-H3 bpc=3-phosphonobenzoic acid, 4,4'-bpy=4,4'-bipyridine), have been solvothermally synthesised to generate unique topologies, as characterised by single-crystal XRD. Compound 1 possesses a diamond topology, which has rarely been found among phosphonate-based metal-organic frameworks. Compound 2 shows a 2D layered structure with pendant m-Hbpc and 4, 4'-bpy ligands, in which the layers feature as a zeolite-like network. Compound 3 has a 3D sandwich pillared-layer framework with an interesting double-helix structure. Only 1 shows an adsorption capacity for CO2 of 28.5â cm3 g-1 at 273â K. Luminescence studies revealed that both 1 and 2 could be potential sensors to copper(II) ions.
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Single image superresolution (SR) aims to construct a high-resolution version from a single low-resolution (LR) image. The SR reconstruction is challenging because of the missing details in the given LR image. Thus, it is critical to explore and exploit effective prior knowledge for boosting the reconstruction performance. In this paper, we propose a novel SR method by exploiting both the directional group sparsity of the image gradients and the directional features in similarity weight estimation. The proposed SR approach is based on two observations: 1) most of the sharp edges are oriented in a limited number of directions and 2) an image pixel can be estimated by the weighted averaging of its neighbors. In consideration of these observations, we apply the curvelet transform to extract directional features which are then used for region selection and weight estimation. A combined total variation regularizer is presented which assumes that the gradients in natural images have a straightforward group sparsity structure. In addition, a directional nonlocal means regularization term takes pixel values and directional information into account to suppress unwanted artifacts. By assembling the designed regularization terms, we solve the SR problem of an energy function with minimal reconstruction error by applying a framework of templates for first-order conic solvers. The thorough quantitative and qualitative results in terms of peak signal-to-noise ratio, structural similarity, information fidelity criterion, and preference matrix demonstrate that the proposed approach achieves higher quality SR reconstruction than the state-of-the-art algorithms.