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Single image deraining has become an important preprocessing task in the multimedia area, improving the performance of subsequent high-level computer vision tasks in rainy weather significantly. Previous efforts to restore rain-damaged images have mostly concentrated on feature extraction and contextual information mining. The fact that rain streaks and the background are frequently intermingled during the deraining process is ignored by the majority of these methods, which leads to redundant features and somewhat restricts the generalizability of deraining networks in real-world rainy situations. To address this issue, we present a novel multi-scale single image deraining network called Feature Decoupling and Reorganization Network (FDRNet). FDRNet introduces Dilated Pyramid Split Attention Module (DPSAM) to decouple input features and reorganize extracted features. Additionally, we propose a Dual Prior Fusion Module (DPFM) to extract and fuse prior information from images, which is demonstrated to support the preservation of structural information and the restoration of details. Extensive experiments on both synthetic and real-world datasets show that our proposed method achieves state-of-the-art results. [ABSTRACT FROM AUTHOR]

Low back pain is one of the most prevalent musculoskeletal ailments in the United States. Intraosseous radiofrequency ablation of the basivertebral nerve is an effective and durable therapy for low back pain and can be offered to patients who have chronic low back pain of greater than 6 months of duration, failure to respond to noninvasive therapies for 6 months, with either Modic Type I or Type II changes at L3–S1. This article reviews the anatomy and physiology, patient selection, technique, and evidence regarding basivertebral nerve ablation. [ABSTRACT FROM AUTHOR]

Chest wall pain affects many patients following chest surgery, fractures, or malignancies, and can be very difficult to manage with normal pharmacologic agents. Intercostal ablation provides one alternative treatment modality for patients suffering from intercostal pain. Intercostal cryoneurolysis involves using extreme cold to cause Wallerian degeneration of the targeted intercostal nerve. This article reviews the patient selection, technique, and complications in the utilization of intercostal neurolysis in the treatment of intractable chest pain. [ABSTRACT FROM AUTHOR]

This paper studies the fixed-time synchronization (FDTS) of complex-valued neural networks (CVNNs) based on quantized intermittent control (QIC) and applies it to image protection and 3D point cloud information protection. A new controller was designed which achieved FDTS of the CVNNs, with the estimation of the convergence time not dependent on the initial state. Our approach divides the neural network into two real-valued systems and then combines the framework of the Lyapunov method to give criteria for FDTS. Applying synchronization to image protection, the image will be encrypted with a drive system sequence and decrypted with a response system sequence. The quality of image encryption and decryption depends on the synchronization error. Meanwhile, the depth image of the object is encrypted and then the 3D point cloud is reconstructed based on the decrypted depth image. This means that the 3D point cloud information is protected. Finally, simulation examples verify the efficacy of the controller and the synchronization criterion, giving results for applications in image protection and 3D point cloud information protection. [ABSTRACT FROM AUTHOR]

This paper is dedicated to addressing the issue of the finite-time synchronization of complexed-valued neural networks with finite-time distributed delays. Some results are derived for finite-time synchronization of the drive-response system using the new Lyapunov–Krasovskii function and the analysis techniques. We then propose several numerical examples to determine the effectiveness of the results. [ABSTRACT FROM AUTHOR]

Feature extraction networks play a crucial role in classification algorithms. However, most convolutional neural networks use the form of residual block stacking to extract downstream features of images, and this simple form is not sufficient to obtain better classification performance. Therefore, this paper proposes a YOLOX detection framework based on an improved ConvNeXt which incorporates many advantages of Swin-Transformer with efficient classification performance. To address the problems of unstable IOU convergence and inaccurate regression coordinates of the algorithm, this paper adopts Manhattan distance as the new penalty term, and the new loss function combines the advantages of Euclidean distance and Manhattan distance, which has no gradient explosion in the early training period and can drop smoothly to a stable point in the late training period. The proposed algorithm is robust to negative effects such as dust, light, shadows, and occlusions, and is well-suited for masked-face detection in industrial and public scenarios. The proposed model is tested on the VOC dataset and the AIZOO open-source masked-face dataset, obtaining 5.58% AP improvement on the VOC dataset and reaching 96.665% AP on the masked-face dataset, which is better than other algorithms. • Designing a deep neural network to use for masked-face detection. • Anchor-free model is used to avoid time-consuming post-processing. • The improved ConvNeXt network improves classification performance. • Adopting Manhattan distance-based localization loss makes training stable. • The Mosaic data augmentation strategy alleviates the overfitting problem. [ABSTRACT FROM AUTHOR]

Background: Pseudomeningoceles most commonly occur due to prior trauma or surgery and are often located in the posterior paraspinous tissues. Here, we report a case of an intraosseous pseudomeningocele that mimicked an intra-osseous T2 hyperintense lesion in the L1 vertebral body.Case Description: A 64-year-old male presented with back, left lateral thigh and left knee pain lasting several months. He had no prior history of trauma or surgery. Radiographs of the lumbar spine showed mild levoscoliotic curvature of the lumbar spine, Baastrup's changes between the spinous processes, multilevel degenerative disc disease and facet arthropathy. Magnetic resonance imaging (MRI) of the lumbar spine performed without intravenous contrast showed severe spinal canal stenosis from L1-L2 to L3-L4 and moderate spinal canal stenosis at L4-L5. MRI also showed a 2.5-cm T2 hyperintense lesion involving the posterior aspect of the L1 vertebral body, with questionable contiguity with cerebrospinal fluid. Computed tomography (CT) myelogram was performed instead of biopsy. CT myelogram showed contiguity of the lesion with the intrathecal contrast and a rent in the posterior longitudinal ligament and anterior dura consistent with an intraosseous pseudomeningocele. The patient opted for non-operative management of the pseudomeningocele and his lumbar stenosis due to medical comorbidities.Conclusions: This case illustrates a rare case of an intra-osseous pseudomeningocele and highlights the importance of CT myelogram for diagnosis. [ABSTRACT FROM AUTHOR]

Spherical CdS nanoparticles with uniform diameter of 150 nm and good dispersity are prepared through the hydrothermal process with cadmium acetate and thiourea as precursors and cetyltrimethyl ammonium bromide as structure promoter. Shape and size of the CdS particles are strongly dependent on the stirring time in the pretreatment of the reactants before the hydrothermal process, and the growth mechanism is proposed. MoS 2 CdS composites are successfully synthesized by loading MoS 2 on the as-prepared CdS via the second hydrothermal process. The formation of MoS 2 on CdS is investigated through varying the reaction time in the second hydrothermal step. The MoS 2 CdS photocatalyst shows an optimal H 2 evolution rate of 5.24 mmol h −1 g −1 for water splitting under visible light in the presence of lactic acid as sacrificial agent. This study provides a simple way to prepare uniform CdS nanoparticles and CdS based visible-light-responded composite photocatalysts. [ABSTRACT FROM AUTHOR]

This paper investigates the stabilizing and synchronization problems of a memristor-based Chua chaotic system in a finite time. A lemma concerning the finite-time stability for an impulsive system is proposed by extending the finite-time stability theory. Then some finite-time stabilizing and synchronization criterion are presented which guarantee the finite-time stabilization and synchronization for the model considered. Finally, the efficiency of the control scheme is further demonstrated by the simulation examples. [ABSTRACT FROM AUTHOR]

ZnGa 2 O 4 nanoparticles are obtained by microwave-hydrothermal method through homogeneous coprecipitation reaction using urea as precipitant with surfactant assembly. Synthetic temperature, surfactant, and calcination temperature have the obvious effect on the formation and photocatalytic activity of ZnGa 2 O 4 . ZnGa 2 O 4 nanoparticles synthesized in the optimal conditions are highly dispersed and uniform with average diameter of 16.2 nm possessing a surface area of 70 m 2 g −1 . Under ultraviolet (UV) light illumination, the ZnGa 2 O 4 nanoparticles show an efficient photocatalytic activity in liquid phase degradation of organic dyes. The decomposition rates of methyl orange and methylene blue over the present ZnGa 2 O 4 nanoparticles are higher than those of commercial P25 (Degussa Co). [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a finite-time lag synchronization of coupled neural networks with time delay is investigated. By means of the Lyapunov stability theory, a feedback controller is designed for achieving lag synchronization between two delayed neural networks systems in finite time. Paper extends some basic results from the area of finite time to time-delay systems. Numerical simulations on coupled Lu neural systems illustrate the effectiveness of the results. [Copyright &y& Elsevier]

Many issues in science create individual and societal tensions with important implications outside the classroom. We describe one model that directly addresses such tensions by integrating science and religion in two parallel, integrated courses for science majors. Evaluation of the goals of the project—(1) providing students with strategies to identify and work through complex societal issues and their relation to science and (2) improving science knowledge and critical thinking skills—is presented. [ABSTRACT FROM AUTHOR]

This paper studies projective lag synchronization of coupled neural networks with time delay and parameter mismatch. An adaptive controller is designed to achieve weak projective lag synchronization of coupled neural networks. This method is employed to realize projective lag synchronization between coupled neural systems with an error level. Numerical simulation illustrates the effectiveness of the results. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the synchronization of two coupled identical chaotic systems with parameter mismatch via using periodically intermittent control. In general, parameter mismatches are considered to have a detrimental effect on the synchronization quality between coupled identical systems: in the case of small parameter mismatches the synchronization error does not decay to zero or even a nonzero mean. Larger values of parameter mismatches can even result in the loss of synchronization. via intermittent control with periodically intervals, we can obtain the weak synchronization. Some sufficient conditions for the stabilization and weak synchronization of a large class of coupled identical chaotic systems will be derived by using Lyapunov stability theory. The analytical results are confirmed by numerical simulations. [ABSTRACT FROM AUTHOR]

We have constructed a 27-kDa hTERT C-terminal polypeptide (hTERTC27) devoid of domains required for telomerase activity and demonstrated that it is capable of nuclear translocation/telomere-end targeting. Here we showed that expression of a low level of hTERTC27 renders hTERT positive HeLa cells sensitive to H2O2-induced oxidative stress and subsequent cell senescence. The senescence-associated gene, the cyclin/cdk inhibitor p21Waf1, was up-regulated. This occurs without changing the expression of endogenous hTERT, causing significant telomere shortening or inhibiting telomerase activity. Results from this study suggest for the first time that in addition to telomerase activity, the C-terminus of hTERT also plays a role in hTERT-mediated cellular resistance to oxidative stress. [Copyright &y& Elsevier]

Some qualitative analyses of bifurcations for an incommensurate fractional-order neural network with delays are considered. At first, we display an incommensurate five-neuron fractional-order bidirectional associative memory neural network (FOBAMNN) with four delays. Next, the existence and uniqueness of the solution are analyzed. Afterward, from the perspective of the two different cases of delays inducing bifurcations, some sufficient criteria of the stability and the occurrence of Hopf bifurcation are established. Some numerical simulations are designed to verify the feasibility and validity of the obtained theorems. In addition, the effects of the delays on the stability and bifurcation of the integer-order neural network and the fractional-order neural network are discussed and some meaningful results are presented in the end. • A type of incommensurate fractional-order neural network with multiple delays is developed. • The existence and uniqueness of the solution are analyzed. • The stability criterion and the onset of Hopf bifurcation are investigated. • Numerical simulations are presented to illustrate the derived key conclusions. [ABSTRACT FROM AUTHOR]

Purpose: To assess the safety, technical success, and clinical outcomes of percutaneous cryoablation (PCA) in patients with anterior renal tumors. Methods: A retrospective analysis of patients with anterior renal tumors, defined as tumors at or anterior to the level of the renal pelvis, treated with CT-guided PCA from 2008 to 2022. Summary statistics included demographics and baseline tumor attributes. Treatment and follow-up metrics included primary and secondary technical success, adverse events (AEs) according to the SIR classification, local recurrence, overall survival (OS), and cancer-specific survival (CSS)). 100 patients (60 males; mean age: 63, mean BMI: 33, mean Charlson comorbidity index:6) with 100 anterior renal tumors were included. Results: 78% of tumors were T1a and 22% T1b with mean maximal tumoral dimension of 29 mm (range: 6–62 mm) and mean distance to nearest critical structure 9 mm (range: 0–40 mm). Mean follow-up was 20.9 months (range: 3–103). 28% of PCAs required hydrodissection. Technical success was achieved in 92% of patients; with six remaining patients undergoing successful repeat PCA (secondary technical success: 98%). The remaining two patients without primary technical success were either surveilled or had a benign pathology on resulted concomitant biopsy. Four patients (4%) had major AEs (hemorrhage requiring prolonged admission, transfusion, or embolization (n = 3), perinephric abscess requiring drainage (n = 1)) and 27% had minor AEs. Eight patients (8%) had recurrence with a one-year OS of 94% and CSS of 100%. All recurrences underwent repeat ablation without additional recurrence and 3/8 (38%) were T1b and 5/8 (63%) were T1a tumors. Conclusion: PCA of anterior renal tumors can be performed safely with high rates of technical and oncologic success. [ABSTRACT FROM AUTHOR]

In this paper, a vector-borne disease model with two delays and reinfection is established and considered. First of all, the existence of the equilibrium of the system, under different cases of two delays, is discussed through analyzing the corresponding characteristic equation of the linear system. Some conditions that the system undergoes Hopf bifurcation at the endemic equilibrium are obtained. Furthermore, by employing the normal form method and the center manifold theorem for delay differential equations, some explicit formulas used to describe the properties of bifurcating periodic solutions are derived. Finally, the numerical examples and simulations are presented to verify our theoretical conclusions. Meanwhile, the influences of the degree of partial protection for recovered people acquired by a primary infection on the endemic equilibrium and the critical values of the two delays are analyzed. [ABSTRACT FROM AUTHOR]

Although ablations are performed with conscious sedation or general anesthesia, microwave ablations can be painful post procedure. Newer analgesic modalities, including regional blocks, have promoted the proliferation of less invasive anesthesia care for ablative procedures. This study evaluates whether bilateral paravertebral blocks reduce the need for additional analgesics in comparison to unilateral blocks in microwave ablations. In this retrospective study, individuals undergoing microwave ablation who underwent unilateral versus bilateral nerve blocks at a single institution from 2017 to 2019 were compared. Categorical variables were analyzed using Pearson's chi-squared tests. Comparisons of means were completed using multiple T-tests corrected using the Holm-Sidak method with α = 0.05. Regression modeling was used to identify factors related to increased MME (milligram morphine equivalent) usage and post-procedure admission rates. A total of 106 patients undergoing 112 liver MWA procedures were included in this analysis, with patients receiving either a bilateral or unilateral block. Pre-procedural characteristics demonstrated no significant differences in age or gender. Bilateral blocks were associated with decreased usage of gabapentin (14% vs. 0%, p = 0.01) and a lower rate of post-procedure admissions (OR 0.23, p = 0.003). Therefore, when using paravertebral blocks, bilateral blocks are superior to unilateral blocks, as demonstrated by decreased rates of hospital admission and reduced use of systemic neuropathic pain medication. Additionally, reducing post-procedural MME may reduce the rate of admission to the hospital. [ABSTRACT FROM AUTHOR]

• The compressive behaviour of GFRP-confined GRAC was investigated for the first time. • The effects of the GFRP confinement ratio, RA content and GRAC size were examined. • Compressive strength and ultimate strain models for GFRP-confined GRAC were proposed. • A unified stress–strain model was developed for GFRP-confined geopolymeric concrete with or without RA. Substituting geopolymeric recycled aggregate concrete (GRAC) for normal concrete (NC) to fill glass fibre-reinforced polymer (GFRP) tubes and produce green high-performance compression members is a promising construction technology. Although extensive research has been conducted on the performance of GFRP tubes filled with NC in the past decade, gaps in knowledge make it difficult to predict the mechanical behaviour of this new composite member. This paper presents an experimental and analytical study on the progressive failure of GFRP-confined GRAC under compressive loads. A comprehensive investigation was conducted on the effects of the confinement ratio, recycled aggregate (RA) content, and tube size on the compressive behaviour of GFRP-confined GRAC. The test results were compared with those from available studies on confined NC specimens with or without RA. This paper found that GFRP tube confinement had an advantage in alleviating the negative impact of RA on GRAC. The RA replacement ratio and cylindric dimension had no influence on the linear relationship between the confinement ratio and strength enhancement ratio. Predictive models considering the effect of RA content and GRAC size were proposed for the compressive strength and ultimate strain of GFRP-confined GRAC. Finally, a recalibrated stress–strain model was developed to describe the compressive behaviour of GFRP-confined geopolymeric concrete. [ABSTRACT FROM AUTHOR]

Although ablations are performed with conscious sedation or general anesthesia, microwave ablations can be painful post procedure. Newer analgesic modalities, including regional blocks, have promoted the proliferation of less invasive anesthesia care for ablative procedures. This study evaluates whether bilateral paravertebral blocks reduce the need for additional analgesics in comparison to unilateral blocks in microwave ablations. In this retrospective study, individuals undergoing microwave ablation who underwent unilateral versus bilateral nerve blocks at a single institution from 2017 to 2019 were compared. Categorical variables were analyzed using Pearson's chi-squared tests. Comparisons of means were completed using multiple T-tests corrected using the Holm-Sidak method with α = 0.05. Regression modeling was used to identify factors related to increased MME (milligram morphine equivalent) usage and post-procedure admission rates. A total of 106 patients undergoing 112 liver MWA procedures were included in this analysis, with patients receiving either a bilateral or unilateral block. Pre-procedural characteristics demonstrated no significant differences in age or gender. Bilateral blocks were associated with decreased usage of gabapentin (14% vs. 0%, p = 0.01) and a lower rate of post-procedure admissions (OR 0.23, p = 0.003). Therefore, when using paravertebral blocks, bilateral blocks are superior to unilateral blocks, as demonstrated by decreased rates of hospital admission and reduced use of systemic neuropathic pain medication. Additionally, reducing post-procedural MME may reduce the rate of admission to the hospital. [ABSTRACT FROM AUTHOR]

To access if the (MC)2 scoring system can identify patients at risk for major adverse events following percutaneous microwave ablation of renal tumors. Retrospective review of all adult patients who underwent percutaneous renal microwave ablation at two centers. Patient demographics, medical histories, laboratory work, technical details of the procedure, tumor characteristics, and clinical outcomes were collected. The (MC)2 score was calculated for each patient. Patients were assigned to low-risk (<5), moderate-risk (5–8) and high-risk (>8) groups. Adverse events were graded according to the criteria from the Society of Interventional Radiology guidelines. A total of 116 patients (mean age = 67.8 [95%CI 65.5–69.9], 66 men) were included. 10 (8.6%) and 22 (19.0%) experienced major or minor adverse events, respectively. The mean (MC)2 score for patients with major adverse events (4.6 [95%CI 3.3–5.8]) was not higher than those with either minor adverse events (4.1 [95%CI 3.4–4.8], p = 0.49) or no adverse events (3.7 [95%CI 3.4–4.1], p = 0.25). However, mean tumor size was greater in those with major adverse events (3.1 cm [95%CI 2.0–4.1]) than minor adverse events (2.0 cm [95%CI 1.8–2.3], p = 0.01). Patients with central tumors were also more likely to experience major adverse events compared to those without central tumors (p = 0.02). The area under the receiver operator curve to predict major adverse events was 0.61 (p = 0.15), indicating a poor ability of the (MC)2 score to predict major adverse events. The (MC)2 risk scoring system does not accurately identify patients at risk for major adverse events from percutaneous microwave ablation of renal tumors. The mean tumor size and central tumor location may serve as a better indicator for risk assessment of major adverse events. • (MC)2 score was not higher in patients with major adverse events, compared to minor or no events. • Tumor size was greater in patients with major adverse events than patients with minor adverse events. • Patients with central tumors were also more likely to experience major adverse events compared to those without central tumors. • (MC)2 score has poor ability to predict major adverse events. • Tumor size and tumor centrality may serve as better predictive factors of major adverse events. [ABSTRACT FROM AUTHOR]

Purpose: To compare outcomes in patients with T1b and T2a renal cell carcinoma (RCC) treated with percutaneous cryoablation (PCA) who underwent transarterial embolization (TAE) of the RCC prior to PCA (TAE + PCA) to patients who were treated with PCA alone. Methods: Retrospective review of all adult patients with T1b (4.1–7 cm) and T2a (7.1–10 cm) RCC treated with PCA from 2008 to 2021. Data collected included age, sex, tumor diameter, RENAL nephrometry score, technical success, adverse events (AEs), changes in serum creatinine, local control, and recurrence rates. A p value of 0.05 was considered the threshold for statistical significance. Results: 13 patients with 13 RCCs (mean age: 72.7 ± 10.4; 54% male) and 35 patients with 37 RCCs (mean age: 66.7 ± 10.6; 60% male) were included in the TAE + PCA and PCA groups, respectively. The TAE + PCA group had larger mean tumor diameter (5.7 ± 1.1 cm vs. 4.7 ± 0.6 cm; p < 0.0001) and higher mean RENAL nephrometry score (8.9 ± 1.1 vs. 7.8 ± 1.5; p = 0.02). There were no differences between the groups with respect to technical success of PCA (p = 0.46), local tumor control (p = 0.3), or mean number of procedures to achieve local tumor control (p = 0.85). Mean increase in serum creatinine was not significantly different between the two groups (p =.63). Major AEs were similar between the groups (p = 1); however, the TAE + PCA group had no major hemorrhagic AEs while the PCA alone group had three (8.3%). Conclusion: TAE + PCA in patients with T1b or T2 RCC is technically feasible without significant added detriment to renal function. This combined approach may help to reduce hemorrhagic AEs but larger patient cohorts are needed. [ABSTRACT FROM AUTHOR]

Antibiotic prophylaxis in interventional radiology (IR) is widely used; however, such practice is based on data from the surgical literature. Although published guidelines can help determine the need for prophylactic antibiotic use in the patient undergoing percutaneous procedures, local practice patterns often dictate when such medications are given. In this article, the current state of periprocedural antibiotic use in commonly performed IR procedures (i.e., tube and catheter placements) is presented. [ABSTRACT FROM AUTHOR]

Pointcloud is a collection of 3D object coordinate systems in 3D scene. Generally, point data in pointclouds represent the outer surface of an object. It is widely used in 3D reconstruction applications in various fields. When obtaining pointcloud data from RGB-D images, if part of the information in the RGB-D images is lost or damaged, the pointcloud data will be hollow or too sparse. Moreover, it is not conducive to the subsequent application of pointcloud data. Based on the boundary of the region to be repaired, we proposes to repair the damaged image and synthesize the complete pointcloud data after a series of preprocessing steps related to the image. Experiments show that the our method can effectively improve the restoration of the lost details of the pixel in the target area and that it will have the fuller pointcloud data after synthesizing the restored image. [ABSTRACT FROM AUTHOR]

Venous thromboembolism (VTE) in pediatric patients is an uncommon but serious diagnosis that has an array of therapeutic options and challenges. An assessment of the existing literature on management of pediatric patients with VTE was conducted. The interventions reviewed include anticoagulation, thrombolysis, thrombectomy, inferior vena cava (IVC) filters, and venous stenting. For each intervention, a discussion of mechanism of action, indications, contraindications, and potential complications was performed. While anticoagulants are considered the first-line pediatric VTE treatment, many drugs remain investigational in this patient population and treatment recommendations are extrapolated from adult practice. Thrombolysis may be indicated in cases of acute thrombosis requiring more rapid clot resolution but presents a greater bleeding risk than anticoagulation. Similarly, thrombectomy also provides rapid clot resolution and offers a larger therapeutic window and usage in more mature thrombi than thrombolysis. In select patient groups, IVC filters may be indicated in the prevention of PE but present with inherent thrombogenicity and risk of migration. The data regarding pediatric VTE treatment options, monitoring, and long term outcomes is limited compared to the adult population. The relatively few clinical trials including pediatric patients have a relatively small sample size and are heterogenous with regards to predisposing factors that further exacerbate generalizability. Additional research is needed to help construct and evaluate a robust treatment algorithm for pediatric patients with VTE. • Pediatric venothrombembolic disease is a challenging diagnosis for treatment given the paucity of literature and consensus. • Insertion of temporary inferior vena cava filters can mitigate risk of pulmonary thromboembolism but have challenges in pediatric patients given size. • Interventional techniques, ie thrombectomy and thrombolysis, to treat deep venous thrombosis in children is poorly described but has emerging potential. [ABSTRACT FROM AUTHOR]

In this paper, the generalized synchronization of nonlinear chaotic systems is investigated. Based upon reversibility of the Jacobian matrix and matrix theory, we carry out a series of elementary column transformations to Jacobian matrix. And then, according to Lyapunov function theory, sufficient conditions for generalized synchronization between drive system and response system with different dimensions are obtained. Numerical simulations are also given to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the mechanisms of small parametrical perturbations in controlling chaos in a class of non-autonomous piecewise smooth oscillators, which describe a large class of nonlinear dynamical systems in the real world. The analytical expressions of two homoclinic orbits of unperturbed piecewise smooth oscillators, which connect the same hyperbolic saddle point are solved analytically. Firstly, when there are no small parametrical perturbations, by using Melnikov׳s approach, it is rigorously proven that the homoclinic chaos in the Smale horseshoes sense exists when the system׳s parameters are selected above the threshold for chaos occurrence. Secondly, under the small parametrical perturbations, by using Melnikov׳s approach, a sufficient criterion is derived, serving as designing the parameters of the control signal, i.e., amplitude and phase position. In the process of computing Melnikov׳s functions, it is found that the expressions of Melnikov׳s functions could not be solved analytically because the homoclinic orbits are highly complicated. To this end, a numerical algorithm is proposed. Numerical simulations are presented to verify the theoretical results. The results of this paper can be used to explore the underlying chaotic behaviors of the inertial neural network model. [ABSTRACT FROM AUTHOR]

This paper considers the fixed-time synchronization (FIXTS) of neural networks (NNs) by using quantized intermittent control (QIC). Based on QIC, a fixed-time controller is designed to ensure that the NNs achieve synchronization in finite time. With this controller, the settling time can be estimated regardless of initial conditions. After ensuring that the system has stabilized through this strategy, it is suitable for image protection given the behavior of the system. Meanwhile, the encryption effect of the image depends on the encryption algorithm, and the quality of the decrypted image depends on the synchronization error of NNs. The numerical results show that the designed controller is effective and validate the practical application of FIXTS of NNs in image protection. [ABSTRACT FROM AUTHOR]

In this paper, an ideal current source forgetting memristor model is proposed. Based on the model, three kinds of synapses with long- and short-term memory are designed: the series forgetting memristor synapse, the forgetting memristor bridge synapse written independently and the forgetting memristor bridge synapse written in batches. Combined with the forgetting property, the long- and short-term weight of the forgetting synapse can be controlled by the long- and short-term resistance of memristors. Compared the three forgetting synapses, the series forgetting memristor synapse has the lowest requirement for memristors, the forgetting memristor bridge synapse written independently is the most flexible, and the forgetting memristor bridge synapse written in batches is the most convenient. Compared with traditional synapses, forgetting synapses with long- and short-term memory have multi-weight storage. When forgetting synapses are applied to associative memory, it can be found more patterns are stored in the neural network and different patterns are recalled at different time due to the forgetting effect. [ABSTRACT FROM AUTHOR]

This paper investigates the globally exponential stability of delayed switched systems via Razumikhin technique. According to mode-dependent dwell average time and multiple Lyapunov functions, new Razumikhin-type stability results are deduced. In contrast to the existing Rzumikhin-type results, the proposed ones are less conservative. In order to demonstrate the applicability, some stability and stabilization results for switched neural networks with time-varying delays are also derived. Several numerical examples are also employed to show the effectiveness and superiority of the obtained results. [ABSTRACT FROM AUTHOR]

This paper is concerned with the leader-following consensus problem for a class of nonlinear stochastic multiagent systems with immeasurable state variables. By virtual of the Lyapunov function method and the stochastic analysis techniques, the novel distributed protocols are established only with the output measurements such that the state variables of all followers ultimately track those of the leader. So as to reduce the frequencies of controller update and communication in the control process while preserving the desired tracking performance of each follower, the event-triggered as well as self-triggered mechanisms are concurrently considered in the output feedback control architecture. Simulation examples are presented to illustrate the effectiveness and validity of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper presents a microgrid system model considering three types of load and the user's satisfaction function. The objective function with mixed zero-one programming is used to maximize every user's profit and satisfaction in the way of the demand response management under real-time price. An energy function is used to transform the constrained problem into an unconstrained problem, and two neural networks are used to find the local optimal solutions of the objective function with different rates of convergence. A neurodynamic approach is used to combine the neural networks with the particle swarm optimization to find the global optimal solution of the objective function. The simulation results show that the combined approach is effective in solving the optimal problem. [ABSTRACT FROM AUTHOR]

This paper investigates a smoothing neural network (SNN) to solve a robust sparse signal reconstruction in compressed sensing (CS), where the objective function is nonsmooth l 1 -norm and the feasible set satisfies an inequality of l p -norm 2 ≥ p ≥ 1 which is used for measuring residual errors. With a smoothing approximate technique, the non-smooth and non-Lipschitz continuous issues of the l 1 -norm and the gradient of l p -norm can be solved efficiently. We propose a SNN which is modeled by a differential equation and give its circuit implementation. In this case, we prove the proposed SNN converges to the optimal of considered problem. Simulation results are discussed to demonstrate the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In many research literatures, the dynamical behaviour of cellular neural networks (CNNs) is simplified by using cloning template. However, the flaws of cloning template are obvious, because the correlation between weights of cells in CNNs is enhanced. In order to overcome the shortcomings of cloning template, value-varying templates can be used in CNNs. In this paper, associative memories based on CNNs with value-varying templates are investigated. A criterion about stability of CNNs is presented. Then, the problem about obtaining parameters of CNNs can be translated into a problem of solving linear equations for each cell. A design procedure of associative memories is given by our theories and methods. From the procedure, the parameters of CNNs can be obtained. Finally, three examples are used to demonstrate the effectiveness of our theories and methods. And the results show that success rate of associative memories is higher than previous methods. [ABSTRACT FROM AUTHOR]

This paper investigates the stability of impulsive neural networks with time delays. Based on a new tool called as uniformly exponentially convergent functions, an improved Razumikhin method leads to new, more permissive stability results. By comparison with the existing results, the rigorous restrictions on impulses, which are presented in the previous Razumikhin stability theorems, are removed. Moreover, the obtained results do not restrict that the time derivative of Lyapunov function is negative definite or positive definite under the Razumikhin condition. The effectiveness of the proposed results is demonstrated by three simple numerical examples. [ABSTRACT FROM AUTHOR]

Graphical abstract The high quality CsPbBr 3 -Cs 4 PbBr 6 perovskite composites solids were synthesized by a single atomic supersaturated recrystallization method. Abstract Here, we present a single atomic supersaturated recrystallization method to synthesize the green-emitting CsPbBr 3 -Cs 4 PbBr 6 perovskite composites in solid state with the highest PLQY of 40.8% in pure polar solvent. The component, morphology, and optical properties of the microcrystals can be tuned by varying growth time, the content of ammonium bromide, and bromine source. The developed method provides a new route to large-scale synthesize high quality perovskite composites emitters for light-emitting diodes. [ABSTRACT FROM AUTHOR]

This paper talks about the stability and synchronization problems of fractional-order quaternion-valued neural networks (FQVNNs) with linear threshold neurons. On account of the non-commutativity of quaternion multiplication resulting from Hamilton rules, the FQVNN models are separated into four real-valued neural network (RVNN) models. Consequently, the dynamic analysis of FQVNNs can be realized by investigating the real-valued ones. Based on the method of M -matrix, the existence and uniqueness of the equilibrium point of the FQVNNs are obtained without detailed proof. Afterwards, several sufficient criteria ensuring the global Mittag-Leffler stability for the unique equilibrium point of the FQVNNs are derived by applying the Lyapunov direct method, the theory of fractional differential equation, the theory of matrix eigenvalue, and some inequality techniques. In the meanwhile, global Mittag-Leffler synchronization for the drive–response models of the addressed FQVNNs are investigated explicitly. Finally, simulation examples are designed to verify the feasibility and availability of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a more general sparse signal recovery minimization model and a smoothing neural network optimal method for compress sensing problem, where the objective function is a L p − q minimization model which includes nonsmooth, nonconvex, and non-Lipschitz quasi-norm L p norms 1 ≥ p > 0 and nonsmooth L q norms 2 ≥ p > 1 , and its feasible set is a closed convex subset of R n . Firstly, under the restricted isometry property (RIP) condition, the uniqueness of solution for the minimization model with a given sparsity s is obtained through the theoretical analysis. With a mild condition, we get that the larger of the q , the more effective of the sparse recovery model under sensing matrix satisfies RIP conditions at fixed p . Secondly, using a smoothing approximate method, we propose the smoothing inertial projection neural network (SIPNN) algorithm for solving the proposed general model. Under certain conditions, the proposed algorithm can converge to a stationary point. Finally, convergence behavior and successful recover performance experiments and a comparison experiment confirm the effectiveness of the proposed SIPNN algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time synchronization of complex networks (CNs) with nonidentical nodes and stochastic noise perturbations. By designing new controllers, constructing Lyapunov functions and using the properties of Weiner process, different synchronization criteria are derived according to whether the node systems in the CNs or the goal system satisfies the corresponding conditions. Moreover, the role of the designed controllers is analyzed in great detail by constructing a suitable comparison system and a new method is presented to estimate the settling time by utilizing the comparison system. Results of this paper can be applied to both directed and undirected weighted networks. Numerical simulations are offered to verify the effectiveness of our new results. [ABSTRACT FROM AUTHOR]

This paper focuses on the hybrid effects of coupling, time-varying delay, intermittent controller on memristor-based neural networks. Firstly, we constructed an array of linearly coupled memristor-based neural networks with time-varying delay. Secondly, our sufficient conditions, ensuring the stability and synchronization, are dependent on coupling and intermittent control and show coupling and intermittent control on the stability and synchronization of memristor-based neural networks. Finally, numerical simulations were given to verify the theoretical results. [ABSTRACT FROM AUTHOR]

The urgent problem of impulsive moments which cannot be determined in advance brings new challenges beyond the conventional impulsive systems theory. In order to solve this problem, the novel concept of impulsive time window is proposed in this paper. And the stability problem of stochastic fuzzy uncertain delayed neural networks with impulsive time window is investigated. By combining the discretized Lyapunov function approach with mathematical induction method, several novel and easy-to-check sufficient conditions concerning the impulsive time window are derived to ensure that the model considered here is exponentially stable in mean square. Numerical simulations are presented to further demonstrate the effectiveness of the proposed stability criterion. [ABSTRACT FROM AUTHOR]

In this paper, a feedback neural network model is proposed for solving a class of convex quadratic bi-level programming problems based on the idea of successive approximation. Differing from existing neural network models, the proposed neural network has the least number of state variables and simple structure. Based on Lyapunov theories, we prove that the equilibrium point sequence of the feedback neural network can approximately converge to an optimal solution of the convex quadratic bi-level problem under certain conditions, and the corresponding sequence of the function value approximately converges to the optimal value of the convex quadratic bi-level problem. Simulation experiments on three numerical examples and a portfolio selection problem are provided to show the efficiency and performance of the proposed neural network approach. [ABSTRACT FROM AUTHOR]

[Display omitted] • Two-step microwave-assisted processes were used to prepare magnetic porous biochar. • The MPBC MW3 possessed high S BET of 2097.51 m2/g with superior adsorption performance. • The maximum uptake of Cr(VI) and TC by MPBC MW3 were 202.61 mg/g and 202.62 mg/g. • Chemical interactions (e.g. complexation and reduction) enhanced the Cr(VI) binding. • Pore filling, hydrogen bonding and π-π stacking interactions promoted the TC uptake. Magnetic porous water hyacinth-derived biochar (MPBC MW3) was synthesized via two-step Microwave (MW)-assisted processes. Characterization results not only testified high specific surface area (2097.50 m2/g) of the MPBC MW3 assisted by MW-assisted pyrolysis, but also revealed its favorable magnetism derived from MW-assisted hydrothermal process. The MPBC MW3 possessed pH-dependent monolayer adsorption capacities of 202.61 and 202.62 mg/g for Cr(VI) and TC with quick attainments of uptake equilibrium within 150 and 200 min. Moreover, the Cr(VI) and TC uptake were substantially steady under the interference from multifarious co-existing ions with slight decline after three adsorption–desorption cycles. Furthermore, the MPBC MW3 was demonstrated to achieve excellent Cr(VI) binding primarily through complexation, electrostatic interaction, reduction and ion exchange, while presenting outstanding TC removal via pore filling, π-π stacking, hydrogen bonding force, electrostatic interaction and complexation. All these findings suggested the MPBC MW3 synthesized by MW-assisted processes as an excellent adsorbent for purification of Cr(VI) and TC-contaminated water. [ABSTRACT FROM AUTHOR]

7,8-Dihydroxyflavone is a recently identified small molecular tropomyosin-receptor-kinase B (TrkB) agonist. Our preliminary structural−activity relationship (SAR) study showed that the 7,8-dihydroxy groups are essential for the agonistic effect. To improve the lead compound's agonistic activity, we have conducted an extensive SAR study and synthesized numerous derivatives. We have successfully identified 4′-dimethylamino-7,8-dihydroxyflavone that displays higher TrkB agonistic activity than that of the lead. This novel compound also exhibits a more robust and longer TrkB activation effect in animals. Consequently, this new compound reveals more potent antiapoptotic activity. Interestingly, chronic oral administration of 4′-dimethylamino-7,8-dihydroxyflavone and its lead strongly promotes neurogenesis in dentate gyrus and demonstrates marked antidepressant effects. Hence, our data support that the synthetic 4′-dimethylamino-7,8-dihydroxyflavone and its lead both are orally bioavailable TrkB agonists and possess potent antidepressant effects. [ABSTRACT FROM AUTHOR]

An abstract of the article "Adenoassociate Virus Mediated Long Term Expression of Human TERTC27 Polypeptide Inhibited Glioblastoma Carcinogenesis by Multiple Mechanisms," bySamuel S. Ng, Yi Gao, JunJian Huang, Cui-fen Huang, Hsiangfu Kung and Marie C. Lin is presented.