Inhibition of the NLRP3 inflammasome attenuates spiral ganglion neuron degeneration in aminoglycoside-induced hearing loss

Aminoglycosides are a widely used class of antibacterials renowned for their effectiveness and broad antimicrobial spectrum.However,their use leads to irreversible hearing damage by causing apoptosis of hair cells as their direct target.In addition,the hearing damage caused by aminoglycosides involves damage of spiral ganglion neurons upon exposure.To investigate the mechanisms underlying spiral ganglion neuron degeneration induced by aminoglycosides,we used a C57BL/6J mouse model treated with kanamycin.We found that the mice exhibited auditory deficits following the acute loss of outer hair cells.Spiral ganglion neurons displayed hallmarks of pyroptosis and exhibited progressive degeneration over time.Transcriptomic profiling of these neurons showed significant upregulation of genes associated with inflammation and immune response,particularly those related to the NLRP3 inflammasome.Activation of the canonical pyroptotic pathway in spiral ganglion neurons was observed,accompanied by infiltration of macrophages and the release of proinflammatory cytokines.Pharmacological intervention targeting NLRP3 using Mcc950 and genetic intervention using NLRP3 knockout ameliorated spiral ganglion neuron degeneration in the injury model.These findings suggest that NLRP3 inflammasome-mediated pyroptosis plays a role in aminoglycoside-induced spiral ganglion neuron degeneration.Inhibition of this pathway may offer a potential therapeutic strategy for treating sensorineural hearing loss by reducing spiral ganglion neuron degeneration.

Adaptive multicascade attribute reduction based on quantum-inspired mixed co-evolution

Due to the fact that conventional heuristic attribute reduction algorithms are poor in running efficiency and difficult in accomplishing the co-evolutionary reduction mechanism in the decision table, an adaptive multicascade attribute reduction algorithm based on quantum-inspired mixed co-evolution is proposed. First, a novel and efficient self- adaptive quantum rotation angle strategy is designed to direct the participating populations to mutual adaptive evolution and to accelerate convergence speed. Then, a multicascade model of cooperative and competitive mixed co-evolution is adopted to decompose the evolutionary attribute species into subpopulations according to their historical performance records, which can increase the diversity of subpopulations and select some elitist individuals so as to strengthen the sharing ability of their searching experience. So the global optimization reduction set can be obtained quickly. The experimental results show that, compared with the existing algorithms, the proposed algorithm can achieve a higher performance for attribute reduction, and it can be considered as a more competitive heuristic algorithm on the efficiency and accuracy of minimum attribute reduction.

Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

A design problem with deficient information is generally described as wicked or ill-defined.The information insufficiency leaves designers with loose settings,free environments,and a lack of strict boundaries,which provides them with more opportunities to facilitate innovation.Therefore,to capture the opportunity behind the uncertainty of a design problem,this study models an innovative design as a composite solving process,where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems,knowledge,and solutions.Additionally,a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem,solution,and knowledge spaces,to provide designers with a distinct design strategy and method for innovative design.The three spaces interact and co-evolve through iterative mappings,including problem structuring,knowledge expansion,and solution generation.The mappings carry the information processing and decision-making activities of the design,and create the path to satisfying solutions.Finally,a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

Cooperative co-evolution based distributed path planning of multiple mobile robots

This paper proposes novel multiple-mobile-robot collision avoidance path planning based on cooperative co-evolution,which can be executed fully distributed and in parallel. A real valued co-evolutionary algorithm is developed to coordinate the movement of multiple robots in 2D world, avoiding C-space or grid net searching. The collision avoidance is achieved by cooperatively co-evolving segments of paths and the time interval to pass them. Methods for constraint handling, which are developed for evolutionary algorithm, make the path planning easier. The effectiveness of the algorithm is demonstrated on a number of 2Dpath planning problems.

Harmony search algorithm with differential evolution based control parameter co-evolution and its application in chemical process dynamic optimization

A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.

Pathogenetic Consequences of Cytomegalovirus-Host Co-evolution

Co-evolution has been shown to result in an adaptive reciprocal modification in the respective behaviors of interacting populations over time. In the case of host-parasite co-evolution,the adaptive behavior is most evident from the reciprocal change in fitness of host and parasite-manifested in terms of pathogen survival versus host resistance. Cytomegaloviruses and their hosts represent a pairing of populations that has co-evolved over hundreds of years. This review explores the pathogenetic consequences emerging from the behavioral changes caused by co-evolutionary forces on the virus and its host.

Adaptive co-evolution of strategies and network leading to optimal cooperation level in spatial prisoner's dilemma game

We study evolutionary prisoner＇s dilemma game on adaptive networks where a population of players co-evolves with their interaction networks. During the co-evolution process, interacted players with opposite strategies either rewire the link between them with probability p or update their strategies with probability 1 - p depending on their payoffs. Numerical simulation shows that the final network is either split into some disconnected communities whose players share the same strategy within each community or forms a single connected network in which all nodes are in the same strategy. Interestingly, the density of cooperators in the final state can be maximised in an intermediate range of p via the competition between time scale of the network dynamics and that of the node dynamics. Finally, the mean-field analysis helps to understand the results of numerical simulation. Our results may provide some insight into understanding the emergence of cooperation in the real situation where the individuals＇ behaviour and their relationship adaptively co-evolve.

A cooperative Co-evolutional immune algorithm

A co-evolutional immune algorithm for the optimization of a function with real parameters is de-scribed.It uses a cooperative co-evolution of two populations,one is a population of antibodies and theother is a population of successful mutation vectors.These two population evolve together to improve thediversity of the antibodies.The algorithm described is then tested on a suite of optimization problems.The results show that on most of test functions,this algorithm can converge to the global optimum atquicker rate in a given range,the performance of optimization is improved effetely.

Adaptive Co-evolution Model for Multi-agent System

It is important to harmonize effectively the behaviors of the agents in the multi-agent system (MAS) to complete the solution process. The co-evolution computing techniques, inspired by natural selection and genetics, are usually used to solve these problems. Based on learning and evolution mechanisms of the biological systems, an adaptive co-evolution model was proposed in this paper. Inner-population, inter-population, and community learning operators were presented. The adaptive co-evolution algorithm (ACEA) was designed in detail. Some simulation experiments were done to evaluate the performance of the ACEA. The results show that the ACEA is more effective and feasible than the genetic algorithm to solve the optimization problems.

A Co-Evolution Model for Dynamic Social Network and Behavior

Individual behaviors, such as drinking, smoking, screen time, and physical activity, can be strongly influenced by the behavior of friends. At the same time, the choice of friends can be influenced by shared behavioral preferences. The actor-based stochastic models (ABSM) are developed to study the interdependence of social networks and behavior. These methods are efficient and useful for analysis of discrete behaviors, such as drinking and smoking;however, since the behavior evolution function is in an exponential format, the ABSM can generate inconsistent and unrealistic results when the behavior variable is continuous or has a large range, such as hours of television watched or body mass index. To more realistically model continuous behavior variables, we propose a co-evolution process based on a linear model which is consistent over time and has an intuitive interpretation. In the simulation study, we applied the expectation maximization (EM) and Markov chain Monte Carlo (MCMC) algorithms to find the maximum likelihood estimate (MLE) of parameter values. Additionally, we show that our assumptions are reasonable using data from the National Longitudinal Study of Adolescent Health (Add Health).

Hybrid Support Vector Regression with Parallel Co-Evolution Algorithm Based on GA and PSO for Forecasting Monthly Rainfall

Accurate and timely monthly rainfall forecasting is a major challenge for the scientific community in hydrological research such as river management project and design of flood warning systems. Support Vector Regression (SVR) is a very useful precipitation prediction model. In this paper, a novel parallel co-evolution algorithm is presented to determine the appropriate parameters of the SVR in rainfall prediction based on parallel co-evolution by hybrid Genetic Algorithm and Particle Swarm Optimization algorithm, namely SVRGAPSO, for monthly rainfall prediction. The framework of the parallel co-evolutionary algorithm is to iterate two GA and PSO populations simultaneously, which is a mechanism for information exchange between GA and PSO populations to overcome premature local optimum. Our methodology adopts a hybrid PSO and GA for the optimal parameters of SVR by parallel co-evolving. The proposed technique is applied over rainfall forecasting to test its generalization capability as well as to make comparative evaluations with the several competing techniques, such as the other alternative methods, namely SVRPSO (SVR with PSO), SVRGA (SVR with GA), and SVR model. The empirical results indicate that the SVRGAPSO results have a superior generalization capability with the lowest prediction error values in rainfall forecasting. The SVRGAPSO can significantly improve the rainfall forecasting accuracy. Therefore, the SVRGAPSO model is a promising alternative for rainfall forecasting.

Co-evolution of nuclear rings,bars and the central intensity ratio of their host galaxies

Using a sample of 13 early-type spiral galaxies hosting nuclear rings,we report remarkable correlations between the properties of the nuclear rings and the central intensity ratio(CIR) of their host galaxies.The CIR,a function of intensity of light within the central 1.5 and 3 arcsec region,is found to be a vital parameter in galaxy evolution,as it shares strong correlations with many structural and dynamical properties of early-type galaxies,including mass of the central supermassive black hole(SMBH).We use archival HST images for aperture photometry at the centre of the galaxy image to compute the CIR.We observe that the relative sizes of nuclear rings and ring cluster surface densities strongly correlate with the CIR.These correlations suggest reduced star formation in the centres of galaxies hosting small and dense nuclear rings.This scenario appears to be a consequence of strong bars as advocated by the significant connection observed between the CIR and bar strengths.In addition,we observe that the CIR is closely related with the integrated properties of the stellar population in the nuclear rings,associating the rings hosting older and less massive star clusters with low values of CIR.Thus,the CIR can serve as a crucial parameter in unfolding the coupled evolution of bars and rings as it is intimately connected with both their properties.

Performance analysis of single-focus phase singularity based on elliptical reflective annulus quadrangle-element coded spiral zone plates

Optical vortices generated by the conventional vortex lens are usually disturbed by the undesired higher-order foci,which may lead to additional artifacts and thus degrade the contrast sensitivity. In this work, we propose an efficient methodology to combine the merit of elliptical reflective zone plates(ERZPs) and the advantage of spiral zone plates(SZPs) in establishing a specific single optical element, termed elliptical reflective annulus quadrangle-element coded spiral zone plates(ERAQSZPs) to generate single-focus phase singularity. Differing from the abrupt reflectance of the ERZPs, a series of randomly distributed nanometer apertures are adopted to realize the sinusoidal reflectance. Typically, according to our physical design, the ERAQSZPs are fabricated on a bulk substrate;therefore, the new idea can significantly reduce the difficulty in the fabrication process. Based on the Kirchhoff diffraction theory and convolution theorem, the focusing performance of ERAQSZPs is calculated. The results reveal that apart from the capability of generating optical vortices,ERAQSZPs can also integrate the function of focusing, energy selection, higher-order foci elimination, as well as high spectral resolution together. In addition, the focusing properties can be further improved by appropriately adjusting the parameters, such as zone number and the size of the consisted primitives. These findings are expected to direct a new direction toward improving the performance of optical capture, x-ray fluorescence spectra, and forbidden transition.

Transportation and sealing pattern of the temporary plugging ball at the spiral perforation in the horizontal well section

Multistage fracturing of horizontal wells is a critical technology for unconventional oil and gas reservoir stimulation. Ball-throwing temporary plugging fracturing is a new method for realizing uniform fracturing along horizontal wells and plays an important role in increasing oil and gas production. However,the transportation and sealing law of temporary plugging balls(TPBs) in the perforation section of horizontal wells is still unclear. Using COMSOL computational fluid dynamics and a particle tracking module, we simulate the transportation process of TPBs in a horizontal wellbore and analyse the effects of the ball density, ball diameter, ball number, fracturing fluid injection rate, and viscosity on the plugging efficiency of TPB transportation. This study reveals that when the density of TPBs is close to that of the fracturing fluid and a moderate diameter of the TPB is used, the plugging efficiency can be substantially enhanced. The plugging efficiency is greater when the TPB number is close to twice the number of perforations and is lower when the number of TPBs is three times the number of perforations.Adjusting the fracturing fluid injection rate from low to high can control the position of the TPBs,improving plugging efficiency. As the viscosity of the fracturing fluid increases, the plugging efficiency of the perforations decreases near the borehole heel and increases near the borehole toe. In contrast, the plugging efficiency of the central perforation is almost unaffected by the fracturing fluid viscosity. This study can serve as a valuable reference for establishing the parameters for temporary plugging and fracturing.

Terahertz quasi-perfect vortex beam with integer-order and fractional-order generated by spiral spherical harmonic axicon

We propose a new method to generate terahertz perfect vortex beam with integer-order and fractional-order. A new optical diffractive element composed of the phase combination of a spherical harmonic axicon and a spiral phase plate is designed and called spiral spherical harmonic axicon. A terahertz Gaussian beam passes through the spiral spherical harmonic axicon to generate a terahertz vortex beam. When only the topological charge number carried by spiral spherical harmonic axicon increases, the ring radius of terahertz vortex beam increases slightly, so the beam is shaped into a terahertz quasi-perfect vortex beam. Importantly, the terahertz quasi-perfect vortex beam can carry not only integer-order topological charge number but also fractional-order topological charge number. This is the first time that vortex beam and quasi-perfect vortex beam with fractional-order have been successfully realized in terahertz domain and experiment.

Motorized spiral enteroscopy:A cautious step forward in technological innovation

With the continuous advancement in medical technology,endoscopy has gained significant attention as a crucial diagnostic tool.The introduction of motorized spiral enteroscopy(MSE)represents a significant advancement in the diagnosis and treatment of small bowel diseases.While there are safety concerns and a high reliance on the operator’s skills,MSE should not be disregarded entirely.Instead,it should be considered as a supplementary endoscopic technique,particularly in situations where conventional endoscopy proves ineffective.Through continuous research and technical optimization,MSE has the potential to become an im-portant addition to the endoscopy toolbox in the future.We call on colleagues in the industry to work together to promote the improvement of MSE technology through continuous research and practice,with the aim to bring out its unique value in endoscopy while ensuring patient safety.

Device-assisted enteroscopy: Are we ready to dismiss the spiral?

Motorized spiral enteroscopy(MSE)is the latest advance in device-assisted enteroscopy.Adverse events related to MSE were discussed in a recent large systematic review and meta-analysis and were directly compared with those of balloon enteroscopy in a case-matched study and a randomized controlled trial.Following the real-life application of MSE,an unexpected safety issue emerged regarding esophageal injury and the technique has been withdrawn from the global market,despite encouraging results in terms of diagnostic and therapeutic yield.We conducted an Italian multicenter real-life prospective study,which was prematurely terminated after the withdrawal of MSE from the market.The primary goals were the evaluation of MSE performance(both diagnostic and therapeutic)and its safety in routine endoscopic practice,particularly in the early phase of introduction in the endoscopic unit.A subanalysis,which involved patients who underwent MSE after unsuccessful balloon enteroscopy,demonstrated,for the first time,the promising performance of MSE as a rescue procedure.Given its remarkable performance in clinical practice and its potential role as a backup technique following a previously failed enteroscopy,it may be more appropriate to refine and enhance MSE in the future rather than completely abandoning it.

Study on the Relationship between Structural Aspects and Aerodynamic Characteristics of Archimedes Spiral Wind Turbines

A combined experimental and numerical research study is conducted to investigate the complex relationship between the structure and the aerodynamic performances of an Archimedes spiral wind turbine(ASWT).Two ASWTs are considered,a prototypical version and an improved version.It is shown that the latter achieves the best aerodynamic performance when the spread angles at the three sets of blades areα_(1)=30°,α_(2)=55°,α3=60°,respectively and the blade thickness is 4 mm.For a velocity V=10 m/s,a tip speed ratio(TSR)=1.58 and 2,the maximum CP values are 0.223 and 0.263 for the prototypical ASWT and improved ASWT,respectively,and the maximum C_(P) enhancement is 17.93%.For V=10 m/s and TSR=2,the CP values of the prototypical ASWT and improved ASWT are 0.225 and 0.263,respectively,with an aerodynamic performance enhancement of 16.88%.Through mutual verification of the test outcomes and numerical results,it is concluded that the proposed approach can effectively lead to aerodynamic performance improvement.

Fusion of Spiral Convolution-LSTM for Intrusion Detection Modeling

Aiming at the problems of low accuracy and slow convergence speed of current intrusion detection models,SpiralConvolution is combined with Long Short-Term Memory Network to construct a new intrusion detection model.The dataset is first preprocessed using solo thermal encoding and normalization functions.Then the spiral convolution-Long Short-Term Memory Network model is constructed,which consists of spiral convolution,a two-layer long short-term memory network,and a classifier.It is shown through experiments that the model is characterized by high accuracy,small model computation,and fast convergence speed relative to previous deep learning models.The model uses a new neural network to achieve fast and accurate network traffic intrusion detection.The model in this paper achieves 0.9706 and 0.8432 accuracy rates on the NSL-KDD dataset and the UNSWNB-15 dataset under five classifications and ten classes,respectively.

Effectiveness of magnetic resonance imaging and spiral computed tomography in the staging and treatment prognosis of colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a prevalent cancer type in clinical settings;its early signs can be difficult to detect,which often results in late-stage diagnoses in many patients.The early detection and diagnosis of CRC are crucial for improving treatment success and patient survival rates.Recently,imaging techniques have been hypothesized to be essential in managing CRC,with magnetic resonance imaging(MRI)and spiral computed tomography(SCT)playing a significant role in enhancing diagnostic and treatment approaches.AIM To explore the effectiveness of MRI and SCT in the preoperative staging of CRC and the prognosis of laparoscopic treatment.METHODS Ninety-five individuals admitted to Zhongshan Hospital Xiamen University underwent MRI and SCT and were diagnosed with CRC.The precision of MRI and SCT for the presurgical classification of CRC was assessed,and pathological staging was used as a reference.Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of blood volume,blood flow,time to peak,permeability surface,blood reflux constant,volume transfer constant,and extracellular extravascular space volume fraction on the prognosis of patients with CRC.RESULTS Pathological biopsies confirmed the following CRC stages:23,23,32,and 17 at T1,T2,T3,and T4,respectively.There were 39 cases at the N0 stage,22 at N1,34 at N2,44 at M0 stage,and 51 at M1.Using pathological findings as the benchmark,the combined use of MRI and SCT for preoperative TNM staging in patients with CRC demonstrated superior sensitivity,specificity,and accuracy compared with either modality alone,with a statistically significant difference in accuracy(P<0.05).Receiver operating characteristic curve analysis revealed the predictive values for laparoscopic treatment prognosis,as indicated by the areas under the curve for blood volume,blood flow,time to peak,and permeability surface,blood reflux constant,volume transfer constant,and extracellular extravascular space volume fraction were 0.750,0.683,0.772,0.761,0.709,0.719,and 0.910,respectively.The corresponding sensitivity and specificity values were also obtained(P<0.05).CONCLUSION MRI with SCT is effective in the clinical diagnosis of patients with CRC and is worthy of clinical promotion.