Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognizing the topological charge of orbital angular momentum beams under atmospheric turbulence by linear photodiode array detectors with convolutional neural networks

We propose a new scheme for recognizing the topological charge (TC) of orbital angular momentum (OAM) beams using convolutional neural networks (CNN) based on the focusing of cylindrical lenses and the detection of linear photodiode arrays (PDAs). Simulations and experiments are conducted. For the superimposed OAM sets with different TC values and different TC intervals, the effects of atmospheric turbulence disturbances on recognition accuracy are explored separately, where the turbulence disturbances to the superimposed OAM beams are measured by the coherence length r0. The simulation results show that the recognition accuracy decreases as the turbulence disturbances increase. With 16-unit PDAs, the TC of the superimposed OAM set l∈{±1, ±2, ±3, ±4} can be recognized with 100% accuracy under weak (the coherence length r0 =16.16 cm ) and intermediate (the coherence length r0 =10.66 cm ) turbulence disturbances, and above 90% accuracy under a strong (the coherence length 0 r = 4.06 cm ) turbulence disturbance. In the experiment under weak (the coherence length r0 =13.01 cm) and intermediate (the coherence length r0 = 8.59 cm) laboratory-simulated turbulence disturbances, with 16-unit PDAs, the recognition accuracy reaches 100% and 99.65%, respectively. The experimental results verify the results of the simulation.
Chiral particles in a circularly polarised light field: new effects and applications

Cross sections of scattering, absorption, and light pressure for a chiral spherical particle in a circularly polarised light field are studied for different values of the radius, dielectric constant, permeability, and parameter of the chiral particle. The conditions are found under which the cross sections of absorption and light pressure differ significantly when nanoparticles are exposed to light with different polarisations, which can be used to improve synthesis of chiral nanoparticles of complex structure.
Optimal growth and transition to turbulence in channel flow with spanwise magnetic field

Instability and transition to turbulence in a magnetohydrodynamic channel flow are studied numerically for the case of a uniform magnetic field imposed along the spanwise direction. Optimal perturbations and their maximum amplifications over finite time intervals are computed in the framework of the linear problem using an iterative scheme based on direct and adjoint governing equations. It is shown that, at sufficiently strong magnetic field, the maximum amplification is no longer provided by classical streamwise rolls, but rather by rolls oriented at an oblique angle to the basic flow direction. The angle grows with the Hartmann number Ha and reaches the limit corresponding to purely spanwise rolls at Ha between 50 and 100 depending on the Reynolds number. Direct numerical simulations are applied to investigate the transition to turbulence at a single subcritical Reynolds number Re = 5000 and various Hartmann numbers. The transition is caused by the transient growth and subsequent breakdown of optimal perturbations, which take the form of one or two symmetric optimal modes (streamwise, oblique or spanwise modes depending on Ha) with low-amplitude three-dimensional noise added at the moment of strongest energy amplification. A sufficiently strong magnetic field (Ha larger than approximately 30) is found to completely suppress the instability. At smaller Hartmann numbers, the transition is observed but it is modified in comparison with the pure hydrodynamic case.
Aircraft Icing Caused by Large Supercooled Droplets

Abstract The characteristic of aircraft icing environments containing large supercooled droplets are described. Substantial loss in rate of climb capability can result from less than 10 minutes duration in conditions where fewer than 0.1–1 cm−3 of droplets 30–400 μm in diameter are present. These conditions are found to have a greater effect than those where the liquid water was confined to smaller (generally less than about 30 μm diameter) droplets. Measurements from research aircraft flying in regions containing these large droplets, located in the Sierra Nevada in California, near Amarillo, Texas, and in northern Arizona are presented. Temperatures ranged from −5.5° to −9.4°C in 13 regions. The sizes of the droplets responsible for performance loss varied with each encounter but ranged from tens to hundreds of micrometers, and these were accompanied by few to no ice crystals. Two case studies are examined in further detail, including the weather conditions present at the time of the encounters. The met.
An Exact Test for Additivity in Two-Way Tables under Biadditive Modelling

Interaction in a two-way classification table with one observation per cell has to be modeled in order to avoid a saturated model. Different models for the interaction term have been proposed, and multiplicative models are the most common. In these multiplicative (bilinear or biadditive) models, the interaction term is written as a product of two terms or as a sum of such products (see Denis and Gower, 1994). In particular, the main effects appear as parameters in the interaction term. At the same time, a graphical tool called biplot has been used to diagnose models for the interaction. In this article, we propose a polynomial description of the interaction terms, when the biplot suggests that nonlinear functions of the main effects are a better description of the interaction. Our modelling permits to introduce an exact test for the presence of the interaction. We illustrate our method on data sets and simulated data, and these suggest that our test is more powerful than Mandel's (1961) test.
Wall Shear Stress and Reynolds Stresses in a Low-Reynolds-Number Turbulent Square-Duct Flow.

Turbulence measurements have been performed by using an LDV in a fully developed squareduct flow at low Reynolds number Re〓7000. A local wall shear stress, turbulence intensities and Reynolds shear stresses, -(u'v')^^^ and -(u'w')^^^, are presented to discuss the consistency of recently reported low-Reynolds-number DNS data(Gavrilakis 1992;Huser and Biringen 1993)with the experimental results. In contrast to high-Reynolds-number cases, the spanwise (z-directional)profile of a wall shear stress has two peaks in 0lz/Hl0.5, one of which is located at a wall bisector z/H=0.5 and another of which is around z/H=0.1, and the maximum appears at the wall bisector. Such low-Reynolds-number behaviour has also been observed for the wall stress in the DNS. However, some of turbulence statistics, in particular turbulence intensities, reported by the DNS study are found to be inconsistent with those of the present experiment. This could suggest the possibility that DNS fails in predicting proper statistics if the axial extent of a computational domain is not taken to be long enough to capture a large-scale structure in the axial direction.
The Improvement of Probability Judgements

SUMMARY A subject S assesses the probability for an event A as q. In this paper, it is shown how the assessment can be improved. Improvement requires two functions fi(q) (i = 0, 1); the probability for q when A is true (i = 1) and when A is false (i = 0). It is shown that data on S's probability assessments can be used to update these functions. Specific, normal forms for them are examined. The connection with calibration is explored. 1. THE TRANSFORMATION OF PROBABILITY JUDGEMENTS CONSIDER a subject, S, who has provided his personal probability for an event A. In this paper we address the problem of whether his probability assessment can be improved, not by providing information additional to that which S already has, or even by S remembering something he had temporarily forgotten, a process Brown and Lindley (1980) have termed "digging in S's psychological field"; but by a better understanding of the assessment mechanism. It is shown that improvement is possible and the method of making it is described. Let the event A under consideration initially have probability y. Because Bayes' theorem in log-odds form is linear, it is convenient to suppose S's statement of probability assessment is that the log-odds for A is q. Our question is: can we transform q to a new value, q* say, which, in some sense, is a better assessment of the log-odds? Two examples may be illuminating. Example 1 S is given an almanac question, with two possible answers, say an upper and a lower one. Data set (a) below provides an example. Before seeing the question he is told that one, and only one, of the answers is correct and that they are equally likely to be correct. On seeing the question he is asked for the probability that the upper answert is correct. Here y =-. The
Cervical Transformation Zone Segmentation and Classification based on Improved Inception-ResNet-V2 Using Colposcopy Images

The second most frequent malignancy in women worldwide is cervical cancer. In the transformation(transitional) zone, which is a region of the cervix, columnar cells are continuously converting into squamous cells. The most typical location on the cervix for the development of aberrant cells is the transformation zone, a region of transforming cells. This article suggests a 2-phase method that includes segmenting and classifying the transformation zone to identify the type of cervical cancer. In the initial stage, the transformation zone is segmented from the colposcopy images. The segmented images are then subjected to the augmentation process and identified with the improved inception-resnet-v2. Here, multi-scale feature fusion framework that utilizes 3 × 3 convolution kernels from Reduction-A and Reduction-B of inception-resnet-v2 is introduced. The feature extracted from Reduction-A and Reduction -B is concatenated and fed to SVM for classification. This way, the model combines the benefits of residual networks and Inception convolution, increasing network width and resolving the deep network’s training issue. The network can extract several scales of contextual information due to the multi-scale feature fusion, which increases accuracy. The experimental results reveal 81.24% accuracy, 81.24% sensitivity, 90.62% specificity, 87.52% precision, 9.38% FPR, and 81.68% F1 score, 75.27% MCC, and 57.79% Kappa coefficient.
A developmental study of random generation in children

2Random generation is a complex task, and is affected by several aspects ofresponse configuration. For example, among adult subjects, the number of responsealternatives affects response sequences; a larger set size leads to response alternativesbeing sampled with uneven probabilities. This effect has been attributed to therequirement to maintain an internal representation of all response choicessimultaneously, based on the finding that the visual provision of response alternativesremoves the set size effect in random number generation (Towse, 1998). It is ofinterest, then, to establish whether children are also affected by changes in the numberof response alternatives.
NDT for evaluation of volumetric water content in wood structures

– The condition of the wood structure and its components should be carefully recorded before considering any action. The diagnosis of wood structures in heritage should precede any intervention. Is important to know preliminarily the construction and structural system, the decay condition and the causes. Furthermore, damage or structural failure should be considered. The diagnosis must be based principally on measurements of physical parameters using non-destructive testing (NDT), and if necessary on laboratory testing. Water is one of the principal causes of wood decay. In this study Ground-penetrating radar (GPR) and time domain reflectometry (TDR) was used to estimate the dielectric permittivity and successively the volumetric water content of several types of wood. An empirical relationship was found between the dielectric constant and volumetric water content. Results were applied to a case study: the Cathedral of Foggia.
Investigating spatial macroscopic metastability of perovskite solar cells with voltage dependent photoluminescence imaging

Metastability is a characteristic feature of perovskite solar cell (PSC) devices that affects power rating measurements and general electrical behaviour. In this work the metastability of different types of PSC devices is investigated through current–voltage (I–V) testing and voltage dependent photoluminescence (PL-V) imaging. We show that advanced I–V parameter acquisition methods need to be applied for accurate PSC performance evaluation, and that misleading results can be obtained when using simple fast I–V curves, which can lead to incorrect estimation of cell efficiency. The method, as applied in this work, can also distinguish between metastability and degradation, which is a crucial step towards reporting stabilised efficiencies of PSC devices. PL-V is then used to investigate temporal and spatial PL response at different voltage steps. In addition to the impact on current response, metastability effects are clearly observed in the spatial PL response of different types of PSCs. The results imply that a high density of local defects and non-uniformities leads to increased lateral metastability visible in PL-V measurements, which is directly linked to electrical metastability. This work indicates that existing quantitative PL imaging methods and point-based PL measurements of PSC devices may need to be revisited, as assumptions such as the absence of lateral currents or uniform voltage bias across a cell area may not be valid.
Investigation of light propagation methods used to calculate wave-optical PSF

In this study, we investigated the suitability of various light propagation methods and their usefulness in terms of calculating the wave-optical point spread function (PSF) of an optical imaging system. To analyze an aberration in an optical imaging system in order to obtain its PSF, light propagation methods are widely used to obtain the light intensity distribution on the observation plane. Both the Fresnel-Kirchhoff and Rayleigh-Sommerfeld diffraction formulae are commonly used in light propagation simulations. Recently, there have been many reports concerning light propagation methods in the field of digital holography. These methods are based on the Rayleigh-Sommerfeld diffraction formula and use discrete Fourier transformation. These methods are referred to as the angular spectrum and Fresnel diffraction methods. In this study, these propagation methods are evaluated in terms of the degree of accuracy offered and their associated calculation costs. In order to demonstrate and investigate the features of these propagation methods, we employed a Tessar lens system, which is composed of four lenses. The wavefront aberration of the lens system is obtained by a ray tracing simulation and is used to generate the generalized pupil function. Next, the Rayleigh- Sommerfeld diffraction formula and the light propagation method based on this formula are used to calculate the waveoptical PSF using the pupil function. We applied these simulation methods to various recently proposed propagation methods and discussed the suitability of the various light propagation methods under consideration for calculating the wave-optical PSF.
Estradiol Detection for Aquaculture Exploiting Plasmonic Spoon-Shaped Biosensors

In this work, a surface plasmon resonance (SPR) biosensor based on a spoon-shaped waveguide combined with an estrogen receptor (ERα) was developed and characterized for the detection and the quantification of estradiol in real water samples. The fabrication process for realizing the SPR platform required a single step consisting of metal deposition on the surface of a polystyrene spoon-shaped waveguide featuring a built-in measuring cell. The biosensor was achieved by functionalizing the bowl sensitive surface with a specific estrogen receptor (ERα) that was able to bind the estradiol. In a first phase, the biosensor tests were performed in a phosphate buffer solution obtaining a limit of detection (LOD) equal to 0.1 pM. Then, in order to evaluate the biosensor’s response in different real matrices related to aquaculture, its performances were examined in seawater and freshwater. The experimental results support the possibility of using the ERα-based biosensor for the screening of estradiol in both matrices.
The Status and Challenges of Image Data Augmentation Algorithms

Image data-augmentation algorithms effectively trump the problem of insufficient training samples for deep learning in some application fields, and it is typically for scholars to choose some of them for various computer vision tasks. But as the algorithms develop rapidly, the early proposed classification that the data-augmentation algorithms are sorted into classical ways and generating methods is no more suitable, because such classification misses some other meaningful strategies. Besides, it is frustrating for someone to decide which is the exact method to undertake, though there are too many optional algorithms to choose. Towards the goal of making some suggestions, the paper categorizes image data-augmentation algorithms into three kinds from the perspective of algorithm strategy, and they are matrix transformation algorithm, feature expansion algorithm and model generation based on neural network algorithm. The paper analyzes the typical algorithm principle, performance, application scenarios, research status and future challenges, and forecasts the development trend of data augmentation algorithms. The paper can provide academic reference for data augmentation algorithm in the fields of medicine and military.
A Hierarchical Accident Recognition Method for Highway Traffic Systems

With the rapid development of highway traffic systems, the accident rate of highway remains high. Once an accident occurs, it will cause serious casualties. In this paper, we proposed a highway accident identification method for real-time accident detection through high-speed monitoring. The proposed method focuses on high detecting speed and high recall for car accident. The designed system consists of four parts: first, yolov3 is used to detect the car. Second, identified car frames are put the identified car frame into the Mosse Tracker for tracking. Third, speed and future center point are estimated according to its size and pixel movement. If the speed exceeds a certain threshold or the future center points among other trackers are too close, the object frame will be put into a trained SVM model. Finally, the flow vector estimation calculation will be used to determine whether there is an accident. The system has fast detection speed, high recall and strong real-time performance. Through this system, we can send warning information to upstream car drivers and traffic management personnel to improve the efficiency of accident handling and reduce the rate of highway traffic accidents and casualties.
Modeling and High-performance Trajectory Optimization of the Industrial Robot

Rapidity, accuracy and energy cost are the key performance indexes for of the work of industrial robot. In this paper, the shortest time and the minimum energy consumption are taken as the goal for the comprehensive optimization. The control vector parameterization method is used to reasonably refine the time grid of the optimization problem. Then, an efficient control strategy for non-uniform adaptive mesh refinement is proposed. According to different changing trends, time nodes are merged or inserted into the time grid. While reducing the number of discrete grids, it also ensures the accuracy of the solution. Taking the Manutec R3 industrial robot as the object, the trajectory optimization simulation calculation is carried out. According to the verification of the simulation computing, the proposed method can significantly improve the time grid refinement. Compared with the traditional CVP method, not only the calculation time is shortened, but also more accurate results can be obtained.
Structure formation in non-local bouncing models

In this study, we investigate the growth of structures within the Deser-Woodard nonlocal theory and extend it to various bouncing cosmology scenarios. Our findings show that the observable structure growth rate, fσ 8, in a vacuum-dominated universe is finite within the redshift range of 0 < z < 2, contrary to previous literature. Although fσ 8 exhibits no divergences, we observe a slight difference between the evolution of the ΛCDM and the non-local DW II models. Regarding structure formation in bouncing cosmologies, we evaluate the evolution of fσ 8 near the bouncing point. Among the different bouncing cases we explore, the oscillatory bounce and pre-inflationary asymmetrical bounce demonstrate a physical profile where the growth rate begins as a small perturbation in the early epoch and increases with inflation, which can be regarded as the seeds of large-scale structures. These findings are significant because they shed light on the growth of seed fluctuations into cosmic structures resulting from non-local effects.
Long-term duration of protection of ancestral-strain monovalent vaccines and effectiveness of the bivalent BA.1 boosters against COVID-19 hospitalisation during a period of BA.5, BQ.1, CH.1.1. and XBB.1.5 circulation in England

Abstract Background Bivalent BA.1 booster vaccines were offered to adults aged 50 years and older and clinically vulnerable individuals as part of the autumn COVID-19 booster vaccination programme 2022 in England. Methods A test-negative case-control study was used to estimate the duration of protection of the monovalent vaccines against hospitalisation as compared to those unvaccinated. In addition, the incremental VE of the bivalent BA.1 booster vaccines was estimated relative to those with waned immunity where the last dose was at least 6 months prior amongst those aged 50 years and older. Findings The protection conferred by the monovalent vaccines was well maintained long-term: absolute VE against hospitalisation amongst those aged 65 years and older who had received at least 3 doses plateaued from 6 months after the last dose at around 50%. Incremental VE (in addition to the protection from earlier vaccines) of the bivalent BA.1 boosters against hospitalisation peaked at 53.0% (95% C.I.; 47.9-57.5%) (equivalent to an absolute VE of approximately 75%) before waning to around 35.9% (95% C.I.; 31.4-40.1%) after 10 or more weeks. Interpretation This study provides evidence of the long-term duration of protection of the monovalent vaccines, suggesting individuals at lower risk of severe disease who did not receive a booster in autumn 2022 may not require regular re-vaccination. Furthermore, this study finds good evidence that the bivalent BA.1 booster vaccines are highly effective against hospitalisation amongst those aged 50 years and older with the sub-lineages of Omicron present in the autumn/winter of 2022 in England. Funding None.
Hierarchical Linear Model of Monthly Rainfall with Regional and Seasonal Interaction Effects

According to the hierarchical characteristics of monthly rainfall in different regions, the paper takes the geographical factors and seasonal factors into the hierarchical linear model as the level effect. Through clustering methods we select two more representative regional meteorological data. We establish three-layer model by transforming the interactive structure date into nested structure data. According the model theory we perform the corresponding model calculations, optimization and analysis, accordingly to interpret the level effects, and residual test. The results show that most of the difference in Monthly Rainfall was respectively explained by Variables (Meteorological factors, seasonal effects, geographic effects) in different levels.