Obstetric and perinatal outcomes of women with a history of recurrent pregnancy loss: a meta-analysis of cohort studies.

PURPOSE: To assess the risk of adverse obstetric and perinatal outcomes in subsequent pregnancies among women with a history of recurrent pregnancy loss (RPL). METHODS: Relevant studies were identified by searching the PubMed, Web of Science, and Embase databases. The pooled effect sizes were reported as odds ratios (OR) with their respective 95% confidence intervals (95% CI), and data analysis was performed using the random effects model. RESULTS: A total of 26 studies involving 4,730,728 women were included in this meta-analysis. The results reveal a significant increase in the prevalence of placenta accreta cases after RPL compared to women without RPL (pooled OR 4.04; 95% CI 1.16-14.15; 2 studies; I2 = 94%; P = 0.03). However, no elevated risk of aneuploidies (pooled OR 1.69, 95% CI 0.73-3.90; 5 studies; I2 = 48%; P = 0.22) or congenital anomalies (pooled OR 1.12, 95% CI 0.97-1.30; 7 studies; I2 = 13%; P = 0.12) in subsequent pregnancies of women with RPL was observed. Additionally, a moderate increase in the risk of various other obstetric and perinatal outcomes was found. The magnitude of the elevated risk of these adverse outcomes varied depending on the region. CONCLUSIONS: Women with a history of RPL exhibit a significantly elevated risk of placenta accreta in subsequent pregnancies, along with a moderate increase in the risk of various other adverse obstetric and perinatal outcomes. However, RPL does not signify an increased risk of aneuploidies or congenital anomalies in a consecutive pregnancy.

Cooperative defect engineering and ligand modification in UiO-66 to achieve high proton conductivity.

D-UiO-66-NIM with high proton conductivity has been synthesized through the dual strategy of defect engineering and ligand modification. Moreover, D-UiO-66-NIM exhibits good temperature cycling stability and durability in proton conductivity. This work has developed a new method to obtain efficient MOF-based proton conductors.

Effect of doping and defects on the electronic properties of MoS2/WSe2 bilayer heterostructure: a first-principles study.

This work studies the effect of Nb, Mo, Re dopant, and Se vacancy in WSe2 on the electronic and optical properties of the MoS2/WSe2 bilayer heterostructure based on first-principles calculations. Our research shows that the MoS2/WSe2 bilayer heterostructure exhibits a type-II band alignment with a valence band offset (VBO) of 1.07 eV and a conduction band offset (CBO) of 1.00 eV. It also shows that different dopants or defects can considerably modulate the energy band alignment and interlayer charge transfer of the heterostructure. Owing to the orbital hybridization of the dopant atoms with other atoms and the consequent enhancement of the coupling between the two structural layers, a transition of the band alignment from type-II to type-I is realized with the Re dopant. The effect of doping and defects on the electronic properties of heterojunctions contributes to applications in high-performance optoelectronic devices.

Mediating effect of adiponectin between free fatty acid and tumor necrosis factor-α in patients with diabetes.

BACKGROUND/OBJECTIVES: Increased free fatty acid (FFA) promotes adiponectin secretion in healthy subjects and induces inflammation in diabetes. Given the potential pro-inflammatory role of adiponectin in "adiponectin paradox", we performed this study in patients with type 2 diabetes mellitus (T2DM) to assess the association of FFA with adiponectin and to investigate whether adiponectin mediates FFA-related inflammation. METHODS: This cross-sectional study consisted of adult patients with T2DM. FFA, adiponectin, and tumor necrosis factor-α (TNF-α) were assayed from fasting venous blood after overnight fasting for at least 8 h. Multivariable linear regression analysis and restricted cubic splines (RCS) analysis were performed to identify the association between FFA and adiponectin. Mediation analysis was performed to determine the mediating effect of adiponectin on the association between FFA and TNF-α. RESULTS: This study included 495 participants, with 332 males (67.1%) and a mean age of 47.0 ± 11.2 years. FFA was positively associated with adiponectin (b = 0.126, 95%CI: 0.036-0.215, P = 0.006) and was the main contributor to the increase of adiponectin (standardized b = 0.141). The RCS analysis demonstrated that adiponectin increased with FFA when FFA was less than 0.7 mmol/L but did not further increase thereafter (Poverall < 0.001 and Pnon-linear < 0.001). In addition, adiponectin mediated the association between FFA and TNF-α. The mediating effect was 0.08 (95%CI: 0.03-0.13, P = 0.003) and the mediating effect percentage was 26.8% (95%CI: 4.5-49.2, P = 0.02). CONCLUSIONS: In patients with T2DM, FFA was positively associated with adiponectin when FFA was less than 0.7 mmol/L. Elevated adiponectin mediated FFA-related inflammation. This study may provide insights into the pro-inflammatory effect of adiponectin in T2DM.

Cerebrospinal fluid soluble growth stimulation expressed gene 2: A potential predictor of outcome for prognosis after aneurysmal subarachnoid hemorrhage.

Background: Serum concentration of soluble growth stimulation expressed gene 2 (sST2) appears to have prognostic value in patients with aneurysmal subarachnoid hemorrhage (aSAH) by now. This study aimed to investigate the relationship between cerebrospinal fluid (CSF) sST2 concentration and outcome in patients with aSAH. Methods: A total of 65 aSAH patients who met the inclusion criteria in the Neurosurgery Department of Jining No.1 People's Hospital from March 2021 to August 2022 were selected as the research objects. 35 patients with the third month Modified-Rankin-Scale (mRS) score of 0-2 were divided into good prognosis group, and 30 patients with the third month mRS score of 3-5 were divided into poor prognosis group. CSF was collected by lumbar puncture for the first 5 days after aneurysm surgery. CSF sST2 concentration was determined using an enzyme-linked immunosorbent assay. Results: In all patients, CSF sST2 concentrations initially increased, peaked on day 2, and then decreased. Compared with the good prognosis group, the sST2 concentration was significantly increased in the poor prognosis group at 1, 2, 3, 4 and 5 days after aSAH surgery. CSF sST2 concentration exhibited good diagnostic performance for predicting outcome (area under the receiver operating characteristic curve = 0.988). Additionally, CSF sST2 concentration has good performance for predicting cerebral edema, but only in the poor prognosis group (area under the curve = 0.93). Conclusions: Elevated CSF sST2 concentration is associated with poor outcome in aSAH patients. CSF sST2 may have a role as a predictive biomarker in these patients.

Bacterial transport mediated by micro-nanobubbles in porous media.

Determining the role of micro-nanobubbles (MNBs) in controlling the risk posed by pathogens to soil and groundwater during reclaimed water irrigation requires clarification of the mechanism of how MNBs block pathogenic bacteria. In this study, real-time bioluminescence imaging was used to investigate the effects of MNBs on the transport and spatiotemporal distribution of bioluminescent Escherichia coli 652T7 strain in porous media. The presence of MNBs significantly increased the retention of bacteria in the porous media, decreasing the maximum relative effluent concentration (C/C0) by 78 % from 0.97 (without MNBs) to 0.21 (with MNBs). The results suggested that MNBs provided additional sites at the air-water interface (AWI) for bacterial attachment and acted as physical obstacles to reduce bacterial passage. These effects varied with environmental conditions such as solution ionic strength and pore water velocity. The results indicated that MNBs enhanced electrostatic attachment of bacteria at the AWI and their mechanical straining in pores. This study suggests that adding MNBs in pathogen-containing water is an effective measure for increasing filtration efficiency and reducing the risk of pathogenic contamination during agricultural irrigation.

Design and evaluation of semicarbazide-embeddedd stationary phases for liquid chromatography.

Semicarbazide, as a derivative of urea, constitutes a great variety of functional molecules for different needs. Herein, novel stationary phases with an incorporated semicarbazide group were proposed. Using aliphatic (docosanoyl, C22) and aromatic (benzoyl, Bz) hydrazides, the semicarbazide-embedded ligands were synthesized before chemical modification of the silica gel, allowing for an accurate interpretation of the chromatographic properties of the corresponding packings. The new stationary phases were water-wettable, due to the presence of highly polar groups. In particular, Bz-semicarbazide (Bz-SCD) stationary phase was sufficiently hydrophilic to run in hydrophilic interaction (HILIC) mode, whilst the C22 (C22-SCD) equivalent, in spite of its reversed-phase nature, was markedly less hydrophobic than the referenced polar-embedded ones. The versatility of C22-SCD was demonstrated with a large selection of analytes, including geometric isomers and standard mixtures of polycyclic aromatic hydrocarbons, sulfonamides, sulfonylurea, substituted ureas, pyridines and carbamates, fat-soluble colorants, antifungal metabolites, angiotensin II receptor blockers and calcium channel blockers.

ResGEM: Multi-scale Graph Embedding Network for Residual Mesh Denoising.

Mesh denoising is a crucial technology that aims to recover a high-fidelity 3D mesh from a noise-corrupted one. Deep learning methods, particularly graph convolutional networks (GCNs) based mesh denoisers, have demonstrated their effectiveness in removing various complex real-world noises while preserving authentic geometry. However, it is still a quite challenging work to faithfully regress uncontaminated normals and vertices on meshes with irregular topology. In this paper, we propose a novel pipeline that incorporates two parallel normal-aware and vertex-aware branches to achieve a balance between smoothness and geometric details while maintaining the flexibility of surface topology. We introduce ResGEM, a new GCN, with multi-scale embedding modules and residual decoding structures to facilitate normal regression and vertex modification for mesh denoising. To effectively extract multi-scale surface features while avoiding the loss of topological information caused by graph pooling or coarsening operations, we encode the noisy normal and vertex graphs using four edge-conditioned embedding modules (EEMs) at different scales. This allows us to obtain favorable feature representations with multiple receptive field sizes. Formulating the denoising problem into a residual learning problem, the decoder incorporates residual blocks to accurately predict true normals and vertex offsets from the embedded feature space. Moreover, we propose novel regularization terms in the loss function that enhance the smoothing and generalization ability of our network by imposing constraints on normal consistency. Comprehensive experiments have been conducted to demonstrate the superiority of our method over the state-of-the-art on both synthetic and real-scanned datasets.

Self-Catalyzed Synthesis of Length-Controlled One-Dimensional Nickel Oxide@N-Doped Porous Carbon Nanostructures from Metal Ion Modified Nitrogen Heterocycles for Efficient Lithium Storage.

Transition metal oxides with the merits of high theoretical capacities, natural abundance, low cost, and environmental benignity have been regarded as a promising anodic material for lithium ion batteries (LIBs). However, the severe volume expansion upon cycling and poor conductivity limit their cycling stability and rate capability. To address this issue, NiO embedded and N-doped porous carbon nanorods (NiO@NCNR) and nanotubes (NiO@NCNT) are synthesized by the metal-catalyzed graphitization and nitridization of monocrystalline Ni(II)-triazole coordinated framework and Ni(II)/melamine mixture, respectively, and the following oxidation in air. When applied as an anodic material for LIBs, the NiO@NCNR and NiO@NCNT hybrids exhibit a decent capacity of 895/832 mA h g-1 at 100 mA g-1, high rate capability of 484/467 mA h g-1 at 5.0 A g-1, and good long-term cycling stability of 663/634 mA h g-1 at 600th cycle at 1 A g-1, which are much better than those of NiO@carbon black (CB) control sample (701, 214, and 223 mA h g-1). The remarkable electrochemical properties benefit from the advanced nanoarchitecture of NiO@NCNR and NiO@NCNT, which offers a length-controlled one-dimensional porous carbon nanoarchitecture for effective e-/Li+ transport, affords a flexible carbon skeleton for spatial confinement, and forms abundant nanocavities for stress buffering and structure reinforcement during discharge/charging processes. The rational structural design and synthesis may pave a way for exploring advanced metal oxide based anodic materials for next-generation LIBs.

FFCM-MRF: An accurate and generalizable cerebrovascular segmentation pipeline for humans and rhesus monkeys based on TOF-MRA.

PURPOSE: Cerebrovascular segmentation and quantification of vascular morphological features in humans and rhesus monkeys are essential for prevention, diagnosis, and treatment of brain diseases. However, current automated whole-brain vessel segmentation methods are often not generalizable to independent datasets, limiting their usefulness in real-world environments with their heterogeneity in participants, scanners, and species. MATERIALS AND METHODS: In this study, we proposed an automated, accurate and generalizable segmentation method for magnetic resonance angiography images called FFCM-MRF. This method integrated fast fuzzy c-means clustering and Markov random field optimization by vessel shape priors and spatial constraints. We used a total of 123 human and 44 macaque MRA images scanned at 1.5 T, 3 T, and 7 T MRI from 9 datasets to develop and validate the method. RESULTS: FFCM-MRF achieved average Dice similarity coefficients ranging from 69.16 % to 89.63 % across multiple independent datasets, with improvements ranging from 3.24 % to 7.3 % compared to state-of-the-art methods. Quantitative analysis showed that FFCM-MRF can accurately segment major arteries in the Circle of Willis at the base of the brain and small distal pial arteries while effectively reducing noise. Test-retest analysis showed that the model yielded high vascular volume and diameter reliability. CONCLUSIONS: Our results have demonstrated that FFCM-MRF is highly accurate and reliable and largely independent of variations in field strength, scanner platforms, acquisition parameters, and species. The macaque MRA data and user-friendly open-source toolbox are freely available at OpenNeuro and GitHub to facilitate studies of imaging biomarkers for cerebrovascular and neurodegenerative diseases.

A new synthesis strategy for nitrogen-doped carbon nanofibers with cobalt oxide nanoparticles as anodic electrode materials for lithium ion batteries.

Nitrogen-doped carbon nanoribbons and nanotubes decorated with Co3O4 nanoparticles were prepared by a metal-catalyzed graphitization-nitridization and oxidization process, using triazole and melamine as a solid nitrogen/carbon co-source, and assessed as anodes of lithium ion batteries (LIBs). These composite anodes display perfect electrochemical performance, indicating their potential for application in LIBs.

Decentralized Policy-Hidden Fine-Grained Redaction in Blockchain-Based IoT Systems.

Currently, decentralized redactable blockchains have been widely applied in IoT systems for secure and controllable data management. Unfortunately, existing works ignore policy privacy (i.e., the content of users' redaction policies), causing severe privacy leakage threats to users since users' policies usually contain large amounts of private information (e.g., health conditions and geographical locations) and limiting the applications in IoT systems. To bridge this research gap, we propose PFRB, a policy-hidden fine-grained redactable blockchain in decentralized blockchain-based IoT systems. PFRB follows the decentralized settings and fine-grained chameleon hash-based redaction in existing redactable blockchains. In addition, PFRB hides users' policies during policy matching such that apart from successful policy matching, users' policy contents cannot be inferred and valid redactions cannot be executed. Some main technical challenges include determining how to hide policy contents and support policy matching. Inspired by Newton's interpolation formula-based secret sharing, PFRB converts policy contents into polynomial parameters and utilizes multi-authority attribute-based encryption to further hide these parameters. Theoretical analysis proves the correctness and security against the chosen-plaintext attack. Extensive experiments on the FISCO blockchain platform and IoT devices show that PFRB achieves competitive efficiency over current redactable blockchains.

The Mediating Role of Emotion Management, Self-Efficacy and Emotional Intelligence in Clinical Nurses Related to Negative Psychology and Burnout.

Objective: To explore the influence of negative psychology and burnout in clinical nurses, and to analyse the mediating role between self-efficacy and emotional intelligence in emotion management. Methods: From January 2022 to December 2022, 12,704 clinical nurses from 32 general hospitals in Hunan Province were selected as research participants by convenience sampling. Negative psychology, emotion management, self-efficacy, emotional intelligence and burnout in clinical nurses were measured, and structural equation models were constructed to explore their impact on burnout in clinical nurses. Results: Clinical nurses' negative psychology had a positive effect on burnout (ß=0.60, 95% CI: 0.63-0.66), emotional intelligence (ß=-0.08, 95% CI: -0.10, -0.06) and the self-efficacy of emotion management (ß=-0.60, 95% CI: -0.05, -0.03) on burnout. Moreover, emotional intelligence and emotion management self-efficacy played a mediating role between negative psychology and burnout in nurses. Conclusion: Clinical nurses' negative psychology had a positive impact on burnout, and emotional intelligence and the self-efficacy of emotion management could alleviate the influence of negative psychology on burnout among nurses. Nurses' emotional intelligence and emotion management self-efficacy can be improved through practical training to help them cope with emotionally loaded situations and reduce stress responses.

Association between the SLC6A11 rs2304725 and GABRG2 rs211037 polymorphisms and drug-resistant epilepsy: a meta-analysis.

Background: Previous studies have shown that SLC6A11 and GABRG2 are linked to drug-resistant epilepsy (DRE), although there have been conflicting results in the literature. In this study, we systematically assessed the relationship between DRE and these two genes. Methods: We systematically searched the PubMed, Embase, Cochrane Library, Web of Science, Google Scholar, Wanfang Data, CNKI, and VIP databases. To clarify whether heterogeneity existed between studies, tools such as the Q-test and I 2 statistic were selected. According to study heterogeneity, we chose fixed- or random-effects models for analysis. We then used the chi-squared ratio to evaluate any bias of the experimental data. Results: In total, 11 trials and 3,813 patients were selected. To investigate the relationship with DRE, we performed model tests on the two genes separately. The results showed that SLC6A11 rs2304725 had no significant correlation with DRE risk in the allele, dominant, recessive, and additive models in a pooled population. However, for the over-dominant model, DRE was correlated with rs2304725 (OR = 1.08, 95% CI: 0.92-1.27, p = 0.33) in a pooled population. Similarly, rs211037 was weakly significantly correlated with DRE for the dominant, recessive, over-dominant, and additive models in a pooled population. The subgroup analysis results showed that rs211037 expressed a genetic risk of DRE in allele (OR = 1.01, 95% CI: 0.76-1.35, p = 0.94), dominant (OR = 1.08, 95% CI: 0.77-1.50, p = 0.65), and additive models (OR = 1.14, 95% CI: 0.62-2.09, p = 0.67) in an Asian population. Conclusion: In this meta-analysis, our results showed that SLC6A11 rs2304725 and GABRG2 rs211037 are not significantly correlated with DRE. However, in the over-dominant model, rs2304725 was significantly correlated with DRE. Likewise, rs211037 conveyed a genetic risk for DRE in an Asian population in the allele, dominant, and additive models.

Accurate Registration of Cross-Modality Geometry via Consistent Clustering.

The registration of unitary-modality geometric data has been successfully explored over past decades. However, existing approaches typically struggle to handle cross-modality data due to the intrinsic difference between different models. To address this problem, in this paper, we formulate the cross-modality registration problem as a consistent clustering process. First, we study the structure similarity between different modalities based on an adaptive fuzzy shape clustering, from which a coarse alignment is successfully operated. Then, we optimize the result using fuzzy clustering consistently, in which the source and target models are formulated as clustering memberships and centroids, respectively. This optimization casts new insight into point set registration, and substantially improves the robustness against outliers. Additionally, we investigate the effect of fuzzier in fuzzy clustering on the cross-modality registration problem, from which we theoretically prove that the classical Iterative Closest Point (ICP) algorithm is a special case of our newly defined objective function. Comprehensive experiments and analysis are conducted on both synthetic and real-world cross-modality datasets. Qualitative and quantitative results demonstrate that our method outperforms state-of-the-art approaches with higher accuracy and robustness. Our code is publicly available at https://github.com/zikai1/CrossModReg.

The interaction effect of transfusion history and previous stroke history on the risk of venous thromboembolism in stroke patients: a prospective cohort study.

BACKGROUND: Blood transfusion and previous stroke history are two independent risk factors of venous thromboembolism (VTE) in stroke patients. Whether the potential interaction of transfusion history and previous stroke history is associated with a greater risk of VTE remains unclear. This study aims to explore whether the combination of transfusion history and previous stroke history increases the risk of VTE among Chinese stroke patients. METHODS: A total of 1525 participants from the prospective Stroke Cohort of Henan Province were enrolled in our study. Multivariate logistic regression models were used to explore the associations among transfusion history, previous stroke history and VTE. The interaction was evaluated on both multiplicative and additive scales. The odds ratio (95% CI), relative excess risk of interaction (RERI), attributable proportion (AP), and synergy index (S) of interaction terms were used to examine multiplicative and additive interactions. Finally, we divided our population into two subgroups by National Institutes of Health Stroke Scale (NIHSS) score and re-evaluated the interaction effect in both scales. RESULTS: A total of 281 (18.4%) participants of 1525 complicated with VTE. Transfusion and previous stroke history were associated with an increased risk of VTE in our cohort. In the multiplicative scale, the combination of transfusion and previous stroke history was statistically significant on VTE in both unadjusted and adjusted models (P<0.05). For the additive scale, the RERI shrank to 7.016 (95% CI: 1.489 ~ 18.165), with the AP of 0.650 (95% CI: 0.204 ~ 0.797) and the S of 3.529 (95% CI: 1.415 ~ 8.579) after adjusting for covariates, indicating a supra-additive effect. In subgroups, the interaction effect between transfusion history and previous stroke history was pronouncedly associated with the increased risk of VTE in patients with NIHSS score > 5 points (P<0.05). CONCLUSIONS: Our results suggest that there may be a potential synergistic interaction between transfusion history and previous stroke history on the risk of VTE. Besides, the percentage of VTE incidence explained by interaction increased with the severity of stroke. Our findings will provide valuable evidence for thromboprophylaxis in Chinese stroke patients.

Mitochondrial genomic analyses provide new insights into the "missing" atp8 and adaptive evolution of Mytilidae.

BACKGROUND: Mytilidae, also known as marine mussels, are widely distributed in the oceans worldwide. Members of Mytilidae show a tremendous range of ecological adaptions, from the species distributed in freshwater to those that inhabit in deep-sea. Mitochondria play an important role in energy metabolism, which might contribute to the adaptation of Mytilidae to different environments. In addition, some bivalve species are thought to lack the mitochondrial protein-coding gene ATP synthase F0 subunit 8. Increasing studies indicated that the absence of atp8 may be caused by annotation difficulties for atp8 gene is characterized by highly divergent, variable length. RESULTS: In this study, the complete mitochondrial genomes of three marine mussels (Xenostrobus securis, Bathymodiolus puteoserpentis, Gigantidas vrijenhoeki) were newly assembled, with the lengths of 14,972 bp, 20,482, and 17,786 bp, respectively. We annotated atp8 in the sequences that we assembled and the sequences lacking atp8. The newly annotated atp8 sequences all have one predicted transmembrane domain, a similar hydropathy profile, as well as the C-terminal region with positively charged amino acids. Furthermore, we reconstructed the phylogenetic trees and performed positive selection analysis. The results showed that the deep-sea bathymodiolines experienced more relaxed evolutionary constraints. And signatures of positive selection were detected in nad4 of Limnoperna fortunei, which may contribute to the survival and/or thriving of this species in freshwater. CONCLUSIONS: Our analysis supported that atp8 may not be missing in the Mytilidae. And our results provided evidence that the mitochondrial genes may contribute to the adaptation of Mytilidae to different environments.

GraphReg: Dynamical Point Cloud Registration With Geometry-Aware Graph Signal Processing.

This study presents a high-accuracy, efficient, and physically induced method for 3D point cloud registration, which is the core of many important 3D vision problems. In contrast to existing physics-based methods that merely consider spatial point information and ignore surface geometry, we explore geometry aware rigid-body dynamics to regulate the particle (point) motion, which results in more precise and robust registration. Our proposed method consists of four major modules. First, we leverage the graph signal processing (GSP) framework to define a new signature, i.e., point response intensity for each point, by which we succeed in describing the local surface variation, resampling keypoints, and distinguishing different particles. Then, to address the shortcomings of current physics-based approaches that are sensitive to outliers, we accommodate the defined point response intensity to median absolute deviation (MAD) in robust statistics and adopt the X84 principle for adaptive outlier depression, ensuring a robust and stable registration. Subsequently, we propose a novel geometric invariant under rigid transformations to incorporate higher-order features of point clouds, which is further embedded for force modeling to guide the correspondence between pairwise scans credibly. Finally, we introduce an adaptive simulated annealing (ASA) method to search for the global optimum and substantially accelerate the registration process. We perform comprehensive experiments to evaluate the proposed method on various datasets captured from range scanners to LiDAR. Results demonstrate that our proposed method outperforms representative state-of-the-art approaches in terms of accuracy and is more suitable for registering large-scale point clouds. Furthermore, it is considerably faster and more robust than most competitors. Our implementation is publicly available at https://github.com/zikai1/GraphReg.

A Compact Four-Port MIMO Antenna for UWB Applications.

A compact four-port multiple-input multiple-output (MIMO) antenna for ultrawideband (UWB) applications is presented in this paper. The proposed antenna has four unit cell antennas. Each unit cell is placed orthogonal to its adjacent elements. The radiation element of each unit cell is composed of a cut semicircular patch and a stepped microstrip feed line. The whole ground on the back side consists of four parts of defective ground and their extended branches, which are connected through a "卍" structure. The main decoupling technology used in the MIMO antenna is polarization diversity. In addition, protruded ground and parasitic elements are added to achieve a higher isolation. This compact antenna has a small area of 45 mm × 45 mm and is printed on a single layer substrate (FR4) with an εr = 4.4 and a thickness of 1.6 mm. This antenna has an impedance bandwidth (S11 < −10 dB) of 3.1−13.1 GHz (123%) and an isolation of less than −17 dB. The envelope correction coefficient (ECC) is less than 0.02 and the average gain is 4 dBi. The ultrawide bandwidth and compact size of the proposed antenna make it a promising candidate for UWB applications.