Dual-Band Notch Filter Based on Twist Split Ring Resonators

A novel dual-band rectangular waveguide notch filter is experimentally investigated in this paper. Such filter is realized by integrating two pairs of split ring resonators (SRRs) printed on the two sides of a dielectric slab with twist angles and separated as a distance in the center of the rectangular waveguide. Due to the coupling effects between the twist SRRs and between the original SRRs and their mirror images generated by the metallic walls perpendicular to the E-field direction, it can flexibly contribute two disjunct resonance states and result in the dual-band notch properties. Furthermore, the two resonance frequencies can be controlled by changing the twist angles, resulting in the shifts of notch frequency bands

Original Article Fibrous hamartoma of infancy: a clinical pathological analysis of seventeen cases

Abstract: To discuss the clinical and pathological features, differential diagnosis and prognosis of fibrous hamartoma of infancy (FHI), seventeen FHI specimens were analyzed with H&E staining and strepavidin peroxidase (SP) immunohistochemistry to detect distinguishing tissue markers. The long-term outcomes of select cases were also obtained. Among the 17 patients (13 males, 4 females, average age 16 months), FHI manifested as a subcutaneous painless mass, primarily on the back of the neck, the upper arms and buttocks. One recurrence was noted among six follow-up cases. The tumors consisted of three main components: fibrous connective tissue; mature fat; and undifferentiated mesenchymal tissue. Immunohistochemistry revealed that fibrous connective tissue was positive for SMA and actin, mature fat tissue was positive for S-100 protein, and undifferentiated mesenchymal tissue was positive for CD34 and was partially positive for actin and SMA. The tumors were negative for desmin, NSE, bcl-2, β-catenin and Ki-67. In brief, FHI is a benign, fibroblastic/myofibroblastic proliferative lesion. Defined histologic features of FHI as presented here would distinguish FHI from similar invasive tumors including infant fibromatosis, calcifying aponeurotic fibroma, fibrous fatty tumor and embryonal rhabdomyosarcoma. Once clearly identified, FHI is curable with complete resection

Association between type 2 inflammatory diseases and neurodevelopmental disorders in low-birth-weight children and adolescents

BackgroundEvidence of the association of certain neurodevelopmental disorder with specific type 2 inflammatory (T2) disease has been found. However, the association of various neurodevelopmental disorders with T2 diseases as a whole remains unclear in low-birth-weight (LBW) infants.ObjectiveTo evaluate the association of type 2 inflammatory (T2) diseases with intellectual disability (ID), autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and learning disability (LD) in LBW children and adolescents.MethodsThe study sample was derived from 2005 to 2018 National Health Interview Survey sample child files. LBW children and adolescents aged 3–17 were included. History of T2 diseases (including asthma and atopic dermatitis) and four neurodevelopmental disorders were reported by adults in families. The relationship between T2 diseases and the risk of four neurodevelopmental disorders was investigated through multiple-weighted logistic regression. Age, sex, race/ethnicity, region, highest education in family and ratio of family income to the poverty threshold were adjusted as covariates for model estimation. Subgroup analyses were conducted by age stratification (3–11 and 12–17 years), sex (male and female), and race (white and non-white).Results11,260 LBW children aged 3–17 years [mean age (SE), 9.73 (0.05) years] were included, in which 3,191 children had T2 diseases. History of T2 diseases was associated with an increased risk of neurodevelopmental disorders, with an OR of 1.35 (95% CI, 0.99–1.84) for ID, 1.47 (95% CI, 1.05–2.05) for ASD, 1.81 (95% CI, 1.51–2.16) for ADHD, and 1.74 (95% CI, 1.49–2.04) for LD following the adjustment of all the covariates. The correlations between T2 disorders and each of the four neurodevelopmental disorders were significantly different by sex and race (all P for interaction < 0.001), and no differences were found in age stratification (all P for interaction > 0.05).ConclusionIn a nationally representative sample of children, we found a significant association of T2 diseases with ASD, ADHD, and LD, even after adjusting for demographic baseline. We also found that the association of T2 disease with neurodevelopmental disorders differed between sex and race. Further investigation is needed to evaluate causal relationships and elucidate their potential mechanisms

Suppression of Tumor Energy Supply by Liposomal Nanoparticle-Mediated Inhibition of Aerobic Glycolysis

Aerobic glycolysis enables cancer cells to rapidly take up nutrients (e.g., nucleotides, amino acids, and lipids) and incorporate them into the biomass needed to produce a new cell. In contrast to existing chemotherapy/radiotherapy strategies, inhibiting aerobic glycolysis to limit the adenosine 5′-triphosphate (ATP) yield is a highly efficient approach for suppressing tumor cell proliferation. However, most, if not all, current inhibitors of aerobic glycolysis cause significant adverse effects because of their nonspecific delivery and distribution to nondiseased organs, low bioavailability, and a narrow therapeutic window. New strategies to enhance the biosafety and efficacy of these inhibitors are needed for moving them into clinical applications. To address this need, we developed a liposomal nanocarrier functionalized with a well-validated tumor-targeting peptide to specifically deliver the aerobic glycolysis inhibitor 3-bromopyruvate (3-BP) into the tumor tissue. The nanoparticles effectively targeted tumors after systemic administration into tumor-bearing mice and suppressed tumor growth by locally releasing 3-BP to inhibit the ATP production of the tumor cells. No overt side effects were observed in the major organs. This report demonstrates the potential utility of the nanoparticle-enabled delivery of an aerobic glycolysis inhibitor as an anticancer therapeutic agent

Learning and Memory Alterations Are Associated with Hippocampal N-acetylaspartate in a Rat Model of Depression as Measured by 1H-MRS

It is generally accepted that cognitive processes, such as learning and memory, are affected in depression. The present study used a rat model of depression, chronic unpredictable mild stress (CUMS), to determine whether hippocampal volume and neurochemical changes were involved in learning and memory alterations. A further aim was to determine whether these effects could be ameliorated by escitalopram treatment, as assessed with the non-invasive techniques of structural magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS). Our results demonstrated that CUMS had a dramatic influence on spatial cognitive performance in the Morris water maze task, and CUMS reduced the concentration of neuronal marker N-acetylaspartate (NAA) in the hippocampus. These effects could be significantly reversed by repeated administration of escitalopram. However, neither chronic stress nor escitalopram treatment influenced hippocampal volume. Of note, the learning and memory alterations of the rats were associated with right hippocampal NAA concentration. Our results indicate that in depression, NAA may be a more sensitive measure of cognitive function than hippocampal volume

Planar Delaunay Mesh Smoothing Method Based on Angle and a Deep Q-Network

Mesh quality is critical to the accuracy and efficiency of finite element calculations, and mesh smoothing is an essential means of reducing the number of poor elements and improving mesh quality. The deep Q-network-based optimization algorithm for planar Delaunay mesh (unconstrained DQN) has attracted increasing attention due to its advantages in autonomous optimization. However, the unconstrained DQN model does not constrain the movement area of the central node during the training process, and element quality easily falls into a local optimum, resulting in a low generalization of the DQN model. In this paper, an updateable iterative inner polygon is proposed as a constraint to limit the central node’s movement and control the element’s angle. Next, the performance of different neural networks when training the same dataset is analyzed, and the appropriate neural network is selected. After that, the effectiveness and generalization of the method were analyzed. Finally, the results were compared with those obtained by existing methods. The results show that the proposed algorithm can improve the minimum angle of global elements and the shape of poor elements, and the trained DQN model has a high generalization

Tan-Sun Transformation-Based Phase-Locked Loop in Detection of the Grid Synchronous Signals under Distorted Grid Conditions

When three-phase voltages are polluted with unbalance, DC offsets, or higher harmonics, it is a challenge to quickly detect their parameters such as phases, frequency, and amplitudes. This paper proposes a phase-locked loop (PLL) for the three-phase non-ideal voltages based on the decoupling network composed of two submodules. One submodule is used to detect the parameters of the fundamental and direct-current voltages based on Tan-Sun transformation, and the other is used to detect the parameters of the higher-harmonic voltages based on Clarke transformation. By selecting the proper decoupling vector by mapping Hilbert space to Euclidean space, the decoupling control for each estimated parameter can be realized. The settling time of the control law can be set the same for each estimated parameter to further improve the response speed of the whole PLL system. The system order equals the number of the estimated parameters in each submodule except that a low-pass filter is required to estimate the average amplitude of the fundamental voltages, so the whole PLL structure is very simple. The simulation and experimental results are provided in the end to validate the effectiveness of the proposed PLL technique in terms of the steady and transient performance