Miracle-dz/UniFAR-FTUs huggingface dataset:
Fundamental Study Theory of genetic algorithms

(i) We investigate spectral andgeometric properties of the mutation-crossover operator in a genetic algorithm with general-size alphabet. By computing spectral estimates, we show how the crossover operator enhances the averaging procedure of the mutation operator in the random generator phase of the genetic algorithm. By mapping our model to the multi-set model often investigatedin the literature, we compute correspond ing spectral estimates for mutation-crossover in the multi-set model. (ii) Various types of unscaledor scaled5tness selection mechanisms are consid eredsuch as proportional 5tness selection, rank selection, andtournament 5tness selection. We allow 5tness selection mechanisms where the 5tness of an individual or creature depends upon the population it resides in. We investigate contracting properties of these 5tness selection mechanisms and combine them with the crossover operator to obtain a model for genetic drift. This has applications to the study of genetic algorithms with zero or extremely low mutation rate. (iii) We discuss a variety of convergent simulated-annealing-type algorithms with mutationcrossover as generator matrix. (iv) The theory includes proof of strong ergodicity for various types of scaled genetic algorithms using common 5tness selection methods. If the mutation rate converges to a positive value, andthe other operators of the genetic algorithm converge, then the limit probability d istribution over populations is fully positive at uniform populations whose members have not necessarily optimal 5tness. (v) In what follows, suppose the mutation rate converges to zero su6ciently slow to assure weak ergodicity of the inhomogeneous Markov chain describing the genetic algorithm, unbounded power-law scaling for the 5tness selection is used , mutation andcrossover commute, andthe 5tness function is injective which is a minor restriction in regardto function optimization. (va) If a certain integrable convergence condition is satis5ed such that the selection pressure increases fast, then there is essentially no other restriction on the crossover operation, andthe algorithm asymptotically behaves as the following take-the-best search algorithm: (1) mutate
Some features of the general Fermat point

Given a triangle with vertices P 1, P 2, P 3 its Fermat point is defined as that point F which minimises the sum P 1 F + P 2 F + P 3 F. It is known that if each of the angles P 1, P 2, P 3 is less than 120°, then F will be the point inside the triangle at which each pair of P 1, P 2, P 3 subtend an angle of 120°, while if any of the angles at P 1, P 2, P 3 exceed 120° then F will coincide with that vertex – see Figure (1).
Upvote or Downvote ABA for Autism? Content and Support in Reddit Posts

Abstract Reddit discourse surrounding treatments for autistic individuals is easily accessible. Multiple Reddit threads discuss Applied Behavior Analysis (ABA) as one option. Such content impacts decision-making despite the absence of gatekeeping mechanisms to identify misinformation. Using a cross-sectional design, this study explores perceptions of ABA-based interventions shared on Reddit by exploring posts’ content, stance and evidence used to support claims. Posts examined generally lacked support of scientific evidence. Additionally, perspectives on ABA were influenced by personal experiences with the intervention. This data provides insight to support healthcare professionals and families engaged in shared decision-making regarding intervention choices.
Autophagic degradation of LOX-1 is involved in the maintenance of vascular integrity injured by oxLDL and protected by Berberine

Damage to vascular endothelial cells (VECs) and vascular smooth muscle cells (VSMCs) caused by oxidized low-density lipoprotein (oxLDL) contributes to cardiovascular and cerebrovascular diseases. Protection effects of Berberine (BBR) on the cardiovascular system have been reported, however, the molecular mechanism of vascular protection is still unclear. In this study, we established two hyperlipidemia models in zebrafish and VEC-VSMC co-culture using high-cholesterol food (HCF) and oxLDL, respectively. We demonstrated that HCF doubled total cholesterol and total glyceride levels, and BBR decreased these indices in a concentration-dependent manner. Lipid staining and hematoxylin-eosin staining revealed that BBR inhibited oxLDL-induced VSMC bulge-like proliferation and migration toward VECs and prevented the HCF-induced trunk vascular obstruction in zebrafish. Immunoblot analysis, cell immunofluorescence, co-immunoprecipitation assays, and transmission electron microscopy showed that oxLDL/HCF increased lectin-like oxLDL receptor-1 (LOX-1) expression at least 5-fold and significantly inhibited autophagolysosome formation in the blood vessel cells and in zebrafish. These observations were associated with endothelial-to-mesenchymal transition (EMT) in VECs and triggered VE-cadherin ectopic expression in VSMCs, and they were responsible for aberrant VSMC migration and vascular occlusion. However, BBR, by promoting autolysosome formation and degradation of LOX-1, reversed the above events and maintained intracellular homeostasis of vessel cells and vascular integrity. In conclusion, regulation of autophagy may be an effective approach to treating oxLDL-induced cardiovascular diseases by reducing LOX-1 protein level. BBR can protect blood vessels by adjusting the oxLDL-LOX-1-EMT-autophagy axis. This study is a step toward the development of new applications of BBR.
Seed Priming with Single-Walled Carbon Nanotubes Grafted with Pluronic P85 Preserves the Functional and Structural Characteristics of Pea Plants

The engineering of carbon nanotubes in the last decades resulted in a variety of applications in electronics, electrochemistry, and biomedicine. A number of reports also evidenced their valuable application in agriculture as plant growth regulators and nanocarriers. In this work, we explored the effect of seed priming with single-walled carbon nanotubes grafted with Pluronic P85 polymer (denoted P85-SWCNT) on Pisum sativum (var. RAN-1) seed germination, early stages of plant development, leaf anatomy, and photosynthetic efficiency. We evaluated the observed effects in relation to hydro- (control) and P85-primed seeds. Our data clearly revealed that seed priming with P85-SWCNT is safe for the plant since it does not impair the seed germination, plant development, leaf anatomy, biomass, and photosynthetic activity, and even increases the amount of photochemically active photosystem II centers in a concentration-dependent manner. Only 300 mg/L concentration exerts an adverse effect on those parameters. The P85 polymer, however, was found to exhibit a number of negative effects on plant growth (i.e., root length, leaf anatomy, biomass accumulation and photoprotection capability), most probably related to the unfavorable interaction of P85 unimers with plant membranes. Our findings substantiate the future exploration and exploitation of P85-SWCNT as nanocarriers of specific substances promoting not only plant growth at optimal conditions but also better plant performance under a variety of environmental stresses.
Disorder origin of Raman scattering in perovskite single crystals

The anharmonic lattice dynamics of oxide and halide perovskites play a crucial role in their mechanical and optical properties. Raman spectroscopy is one of the key methods used to study these structural dynamics. However, despite decades of research, existing interpretations cannot explain the temperature dependence of the observed Raman spectra. We demonstrate the non-monotonic evolution with temperature of the scattering intensity and present a model for 2nd-order Raman scattering that accounts for this unique trend. By invoking a low-frequency anharmonic feature, we are able to reproduce the Raman spectral line-shapes and integrated intensity temperature dependence. Numerical simulations support our interpretation of this low-frequency mode as a transition between two minima of a double-well potential surface. The model can be applied to other dynamically disordered crystal phases, providing a better understanding of the structural dynamics, leading to favorable electronic, optical, and mechanical properties in functional materials.
Application of BPSO algorithm in model-based fault diagnosis of distribution network

A scheme of model-based fault diagnosis is proposed for distribution network,which obtains the minimal conflict sets according to the difference between the simulative data of distribution network principle model and the actual observed data,applies the discrete BPSO(Binary Particle Swarm Optimization)algorithm to reason out the possible fault elements and fault forms,and adopts the Bayesian method to finally determine the diagnosis conclusion with the highest probability. Practical modelling,programming and experiment verify its reliability and effectiveness. Simulative results show that,compared with HS-Tree algorithm,Boolean Algebra algorithm and genetic algorithm,the discrete binary particle swarm optimization algorithm has higher search efficiency,saving 1 / 3～1 / 2 of search time and avoiding memory overflow.
An adaptive simultaneous iteration reconstruction technique for three-dimensional ionospheric tomography

The three-dimensional reconstruction of a tilt series for ionospheric tomography is commonly carried out using one of iterative algorithms such as the simultaneous iteration reconstruction technique(SIRT). This reconstruction algorithm cannot do the high computation efficiency and reconstruction accuracy is low.Here,we develop an adaptive simultaneous iteration reconstruction technique for ionospheric tomography,which is based on an adaptive adjustment method for the relaxation factor and weighted parameter by the reconstruction results of the previous iterative ionospheric electron density.Using a combination of simulation and real datasets for the experiment and comparing with ionosonde observations,it is shown that this new algorithm ASIRT has a better reconstruction quality than the SIRT.Moreover,it is able to accelerate the reconstruction speed.
Fast Detection of Heavy Metal Content in Fritillaria thunbergii by Laser-Induced Breakdown Spectroscopy with PSO-BP and SSA-BP Analysis

Fast detection of heavy metals is important to ensure the quality and safety of herbal medicines. In this study, laser-induced breakdown spectroscopy (LIBS) was applied to detect the heavy metal content (Cd, Cu, and Pb) in Fritillaria thunbergii. Quantitative prediction models were established using a back-propagation neural network (BPNN) optimized using the particle swarm optimization (PSO) algorithm and sparrow search algorithm (SSA), called PSO-BP and SSA-BP, respectively. The results revealed that the BPNN models optimized by PSO and SSA had better accuracy than the BPNN model without optimization. The performance evaluation metrics of the PSO-BP and SSA-BP models were similar. However, the SSA-BP model had two advantages: it was faster and had higher prediction accuracy at low concentrations. For the three heavy metals Cd, Cu and Pb, the prediction correlation coefficient (Rp2) values for the SSA-BP model were 0.972, 0.991 and 0.956; the prediction root mean square error (RMSEP) values were 5.553, 7.810 and 12.906 mg/kg; and the prediction relative percent deviation (RPD) values were 6.04, 10.34 and 4.94, respectively. Therefore, LIBS could be considered a constructive tool for the quantification of Cd, Cu and Pb contents in Fritillaria thunbergii.
Dense Multi-planar Scene Reconstruction from Sparse Point Cloud

There are multi-planar scenes everywhere in our daily life. However, given its lack and self-repeat of the texture, there would be problems of over scarcity and holes on the reconstructed point cloud by the method of multiview reconstruction. Further, there would be vacillation over the reconstructed facades using the method of fitting the reconstructed point cloud with miniature facets. To address these problems, we propose a method of piecewise reconstruction of each plane from the sparse point cloud. The proposed method first improves the J-linkage algorithm,with the stratified sampling instead of the random sampling. We then fit the point cloud with planes using the improved J-linkage algorithm, to obtain the multi-planar model of the scene. Finally, we extract and reconstruct the planar regions with the multi-planar model as well as an unsupervised segmentation algorithm. Besides, the non-planar areas are reconstructed by using the clustering views for multi-view stereo/patch-based multi-view stereo(CMVS/PMVS) algorithm.Experimental results of the multi-planar model demonstrate that the improved J-linkage algorithm can enhance the accuracy of the multi-planar model. Also, the experimental results of 3D reconstruction show that our method not only can effectively overcome holes and jaggies problems, but also can model the complete planar regions.
Gamma-Maxwell distribution

ABSTRACT A new two-parameter distribution, the gamma-Maxwell distribution, isproposed and studied. We generate the new distribution using the gamma-G generator of distributions. The proposal distribution can be seen as an extension of the Maxwell distribution with more flexibility in terms of the distribution asymmetry and kurtosis. We study some probability properties, discuss maximum-likelihood estimation and present a real data application indicating that the new distribution can improve the ordinary Maxwell distribution in fitting real data.
Applications of EOF Analysis to the Spatial Estimation of Circulation Features in the Ocean Sampled by High-Resolution CTD Soundings

Abstract The application of empirical orthogonal function analysis to the estimation of geostrophic circulation features in the ocean is studied with particular reference to spatial series of near-synoptic profiles of CTD data retrieved during intensive surveys of the Alboran Sea (western Mediterranean) and the Bransfield Strait (Antarctica). In both regions, horizontal interpolation of principal components of the observed specific volume profiles provides an efficient method of generating a fully three-dimensional representation of the dynamic height field and geostrophic flow structure, which retains the full resolution of the input profile data. Principal components of profiles sampled by “shallow” soundings are estimated using a simple least squares regression method, leading to a more accurate estimate of dynamic height than one based on profile substitution. Spatial correlation and cross-validation analysis yield consistent results in identifying those vertical modes that account for most of the res.
Demodex Blepharitis: A Survey-Based Approach to Investigate Knowledge, Attitudes, and Practices Among Optometrists in India

Purpose To investigate the knowledge, attitudes, and practice towards Demodex blepharitis among optometrists in India. Methods The study was conducted in the form of an online survey using Research Electronic Data Capture (REDCap). The survey link was distributed via direct e-mail and social media platforms, and it was comprised of 20 questions divided into two sections. The first section focused on the practitioners’ demographics and their views on the general health of the eyelid. The second section of the survey was specific and aimed at obtaining information on identifying and treating Demodex blepharitis, and was only completed by those respondents who looked for Demodex mites. Results The survey was completed by 174 optometrists. The prevalence of blepharitis in the general population was judged by the respondents to be 40%, whereas the prevalence of Demodex mites was estimated to be 29%. Interestingly, the prevalence of Demodex mites in people with blepharitis was estimated to be 30%. This estimated prevalence was substantially lower than that reported in the literature on the subject. 66% of participants believed Demodex mites to be a significant cause of ocular discomfort, whereas only 30% of participants would intervene to diagnose and manage Demodex blepharitis in their patients. Optometrists differed in their preferred method of diagnosis and management of Demodex infestation in eyelids. Conclusion The result of this survey suggests that Demodex blepharitis is a highly under-diagnosed condition in India, with nearly 30% of surveyed optometrists managing this condition. The study also observed a lack of awareness and consensus among surveyed optometrists with regards to diagnosis and appropriate treatment methods to control Demodex infestation in eyelids.
Feasibility studies of micro wind turbines installed on electric vehicles as range extenders using real-time analytical simulation with multi driving cycles scenarios

The proposed work aims to generate electricity by utilising the air flowing around the vehicle through the micro wind turbines (MWTs). In this case, the electricity produced can be used to charge up the battery or power up additional vehicle accessories, which increases the efficiency or/and range of the vehicle. Three driving cycles have been conducted to examine the model’s performance in moderate, highly dynamic and highway driving scenarios. The analytical works resulted in an 8.38%, 4.6% and 1.01% efficiency increase for the case of the Highway driving cycle (FTP), the new European driving cycle (NEDC) and the standardisation random test aggressive driving cycle (RTS), respectively when adding the micro wind turbines model. In terms of range analysis, 16, 11 and 2 km of the range were added to the full battery charge range of the vehicle when the vehicle was simulated for the case FTP, NEDC and RTS driving cycles scenarios, respectively. The results conclude that the value of micro wind turbines is shimming with highway driving scenarios where the effect of regenerative braking is absent and the drag force acting on the vehicle is at its highest rate.
Optimization Applying Response Surface Methodology in the Co-treatment of Urban and Acid Wastewater from the Quiulacocha Lagoon, Pasco (Peru)

The co-treatment of acidic water (AW) and urban wastewater (UWW) is a technique that allows mitigating the negative impact of AW on natural aquatic environments, which represents one of the major environmental problems globally. The aim of this research was to determine the optimal conditions through the response surface methodology (RSM) with a central composite design (CCD) for the co-treatment of AW from the Quiulacocha lagoon in Pasco and UWW from a municipality in Lima, Peru, having as factors the molar ratio of total iron (FeT) and total phosphorus (PT), time (min) and stirring speed (rpm). Data processing was performed using the Design-Expert 11 software, and analysis of variance (ANOVA) with a confidence interval of 95% (α = 0.05) was used. The statistical models obtained showed high determination coefficients (R²), higher than 92% for pH, conductivity and FeT removal. While the removal of COD, PT and obtained a value of R²>0.80, as well as evidenced compliance with the level of significance P value > 0.05. The optimal conditions determined by the statistical model were given at a FeT /PT molar ratio (33:1), a stirring time of 5 min and a speed of 255 rpm. In these conditions, the COD was reduced by 71.78%, FeT by 99.48%, and PT by 84.29% with a residual concentration of 1.3 mg/L; the pH obtained a value of 5.7 and the turbidity 56 NTU. Better efficiency of the co-treatment for the reduction of pollutants in the AW of the Quiulacocha lagoon is evidenced, applying an experimental design to optimize the operating conditions, taking into account that the molar ratio is a significant factor and that optimizing it would allow the co-treatment to be replicated. Co-treatment is a sustainable and promising alternative for the treatment of AW and UWW, since it does not require the use of chemical agents to treat water. However, post-treatments would still be required to comply with certain regulations or to reuse the treated water on a larger scale.
CONSENSUS CONDITIONS OF MULTI-AGENT SYSTEMS WITH UNBALANCED TOPOLOGY AND STOCHASTIC DISTURBANCES

Consensus conditions of multi-agent systems with general directed communication topology and Guassian communication noises are investigated.Here the topology includes not only the balanced graphes but also unbalanced graphes,and the latter is the main concern of this paper.By using the results of Markov chains,a communication class of network nodes is given.By considering the influence of the noises,the consensus conditions are provided:(1) for the case where the information received by some agents in the communication class corrupted by noises,a sufficient and necessary condition of mean square consensus is given.It is shown that this condition can also ensure almost sure consensus. (2) For the case where no information received by the agents in the communication class is corrupted,but the information received by some agents outside of the communication class is corrupted,a sufficient condition of mean square consensus is obtained,which is shown to be necessary in some sense. (3) For the case without noise,a sufficient and necessary condition of consensus is presented.
Adaptive control of nonlinear system by using neural networks

For a class of nonlinear affine unknown system, its states are assumed not all observable. First, the state equations and output equations are obtained by dynamic recurrent neural networks, repectively. By using Lyapunov theory, it is proved that the identification error ∈L\-∞; Second, The controller is designed by state feedback to make the output of system tracks the reference. It is proved that track error is appoximated to zero. At last, a simulation demonstrates the validity of this method.
Sharp image interpolation by mapping level curves

In this paper we describe a novel approach to image interpolation while preserving sharp edge information. Many interpolation methods already have been proposed in the literature, but suffer from one or more artifacts such as aliasing, blurring, ringing etc. Non-linear methods or edge-directed methods result in sharp interpolated images but often look segmented or have great visual degradation in fine structured textures. We concentrate in this paper on tackling blurred edges by mapping the image's level curves. Image's level curves or isophotes are spatial curves with a constant intensity level. The mapping of these intensity levels can be seen as a local contrast enhancement problem, therefore we can rely on some contrast enhancement techniques. A great advantage of this approach is that the shape of the level curves (and of the objects) are preserved and no explicit edge detection is needed here. Additional constraints in function of the image interpolation are defined in this flexible framework. Different strategies of extending greyscale interpolation to colour images are also discussed in this paper. The results show a large improvement in visual quality: the edges are sharper and ringing effects are removed.