Large Field Research Articles

Acknowledging Montessori Education — a Research Perspective of Montessori's Legacy for the Future

On 6 May 2022, 70 years after Maria Montessori’s death, Stockholm University and the Department of Education and Didactics organized an international Montessori symposium. The idea was to present a breadth of research on Maria Montessori. The symposium dealt with Maria Montessori in the interwar period, an analysis of the history of ideas. Another presentation suggested possible research models to study this large field. The symposium also presented interpretations of Montessori’s writings that point her out as a visionary and pioneer in education for a sustainable world. An additional research area addressed was the potential of neuroscience to examine the effects of teaching theory and learning in Montessori education. Finally, this report describes a study on whether Montessori-inspired education compared to traditional education stands up in areas of socio-economic disadvantage.

Utilizing an aspheric lens and compound ellipsoidal cavity for a laser uniform illumination system

To achieve uniform laser illumination of an active imaging system with a small aperture diameter and large field angle, we have developed what we believe to be a novel structure for achieving uniform beam shaping that integrates a laser source, an aspheric lens, and a composite ellipsoidal cavity to enable active laser illumination. Through an aspheric lens, the fundamental mode Gaussian beam is transformed into double Gaussian and flat-top radiation at the target plane. The double Gaussian radiation is further reflected by a complex ellipsoidal cavity, where it is evenly distributed into equal radiation flux. This flux combines with the flat-top radiation, resulting in a uniform distribution at the target plane. The parameters of the complex ellipsoidal cavity are determined using an equalization algorithm. After combining the transmission for flat-top shaping by the aspheric lens and secondary reflection shaping by the composite ellipsoidal cavity, we achieved an aperture measuring 29.7 mm with an aperture angle of 84.0°, at a distance of 2 m from the target plane, with a diameter of 3.6 m, resulting in uniformity reaching 92.7%. RMS and MT/R determine the effectiveness of the compound ellipsoidal cavity design, depending on the maximum reflection angle and transmission angle. MT/R is inversely proportional to the maximum reflection angle, while RMS is directly proportional to the transmission angle. By setting the maximum reflection angle to 32.0° and the transmission angle to 8.0°, we were able to achieve a minimum root-mean-square focusing radius of 108.6 µm along with a minimum effective MT/R ratio of 1.07. The overlap degree between transmission and reflection directly impacts the target plane’s uniformity, adjusted through a defined adjustment factor. Optimizing this factor to 0.9 maximizes the uniformity of the target plane.

Nighttime large-field video image change detection based on adaptive superpixel reconstruction and multi-scale singular value decomposition fusion

With the development of technology and the needs of social governance, surveillance equipment has been widely used. It is very mature to detect the change of surveillance video images in conventional scenes through video image change detection algorithms. However, in the large field of view environment at night, there are complex random noise and low signal-to-noise ratio in surveillance video images, which makes it difficult for people to find small moving targets. To this end, we propose a new method for nighttime large-field surveillance video image change detection based on adaptive superpixel reconstruction and multi-scale singular value decomposition fusion. The proposed method consists of two parts. On the one hand, an adaptive superpixel reconstruction method is used to reconstruct the two denoised difference images by selecting different segmentation parameters, and the edge information of the two reconstructed difference images is significantly enhanced. On the other hand, a multi-scale singular value decomposition fusion method is used to fuse the two difference images. The multi-scale singular value decomposition fusion obtains a robust difference image by selecting fusion rules at different scales and using the complementary information of different difference images, and the Fuzzy c-means (FCM) clustering algorithm is used to obtain the final changed image. Experimental results on a self-built nighttime large-field video image dataset with two resolutions show that the proposed method is superior to other algorithms in terms of detection accuracy and robustness.

Thickness and Structure of Permafrost in Oil and Gas Fields of the Yamal Peninsula: Evidence from Shallow Transient Electromagnetic (sTEM) Survey

The Yamal-Nenets Autonomous District, especially the Yamal Peninsula located in the permafrost zone, stores Russia’s largest oil and gas resources. However, development in the area is challenging because of its harsh climate and engineering–geological features. Drilling in oil and gas fields in permafrost faces problems that are fraught with serious accident risks: soil heaving leading to the collapse of wellheads and hole walls, deformation and breakage of casing strings, gas seeps or explosive emissions, etc. In this respect, knowledge of the permafrost’s structure is indispensable to ensure safe geological exploration and petroleum production in high-latitude regions. The extent and structure of permafrost in West Siberia, especially in its northern part (Yamal and Gydan Peninsulas), remain poorly studied. More insights into the permafrost’s structure have been obtained by a precise sTEM survey in the northern Yamal Peninsula. The sTEM soundings were performed in a large oil and gas field where permafrost is subject to natural and anthropogenic impacts, and its degradation, with freezing–thawing fluctuations and frost deformation, poses risks to exploration and development operations, as well as to production infrastructure. The results show that permafrost in the western part of the Yamal geocryological province is continuous laterally but encloses subriver and sublake unfrozen zones (taliks) and lenses of saline liquid material (cryopegs). The total thickness of perennially frozen rocks is 200 m. The rocks below 200 m have negative temperatures but are free from pore ice. Conductive features (<10 Ohm﮲m) traceable to the permafrost base may represent faults that act as pathways for water and gas fluids and, thus, can cause a geohazard in the oil and gas fields (explosion of frost mounds, gas blow during shallow drilling, etc.).

Plant diversity drives positive microbial associations in the rhizosphere enhancing carbon use efficiency in agricultural soils

Expanding and intensifying agriculture has led to a loss of soil carbon. As agroecosystems cover over 40% of Earth’s land surface, they must be part of the solution put in action to mitigate climate change. Development of efficient management practices to maximize soil carbon retention is currently limited, in part, by a poor understanding of how plants, which input carbon to soil, and microbes, which determine its fate there, interact. Here we implement a diversity gradient by intercropping undersown species with barley in a large field trial, ranging from one to eight undersown species. We find that increasing plant diversity strengthens positive associations within the rhizosphere soil microbial community in relation to negative associations. These associations, in turn, enhance community carbon use efficiency. Jointly, our results highlight how increasing plant diversity in agriculture can be used as a management strategy to enhance carbon retention potential in agricultural soils.

Dynamic geometric phase holography based on in-plane switching liquid crystal

ABSTRACT Liquid crystal geometric phase modulation technology is expected to achieve thin, small and achromatic spatial light modulation, which in turn has the potential to achieve holographic displays with large field angles and high clarity. This article presents a continuous dynamic geometric phase liquid crystal spatial light modulation method based on in-plane switching (IPS) mode. The relationship between geometric phase modulation and driving voltage is calibrated by using interferometry. Two hundred fifty-six phase orders within the phase modulation range of 0~π/2 is achieved. Subsequently, a phase hologram with a modulation range of 0~π/2 was designed by combining the GS (Gerchberg-Saxton) algorithm and single Fourier transform, demonstrating the holographic display capability. This article provides a low-cost approach for dynamic geometric phase holographic display.

Prediction of human initial operation situation in confined space with a multi-task deep neural network

Most large manufacturing fields still rely on manual operations, requiring operators to enter the Confined Space (CS) to conduct assembly and maintenance tasks. The ergonomics analysis combined with the Digital Human Model (DHM) can provide valuable suggestions and guidance for product structure design and process planning. Due to the particularity of CS, the current algorithms applied to DHM operation planning are not suitable for CS operations. To address this challenge, we introduce a novel approach to predict the initial operation situation in CS. The Restriction State Expression Model for Bi-Directional Confined Space (RSEMfBDCS) is introduced to quantify the restricted degree, and a novel multi-task deep neural network, as the Human Operation Situation Prediction Network in CS (HOSPNiCS) is developed to predict the initial operation situation in CS, which includes operation reachability, the initial OPI, and the initial OPII of the operators. Training and Verifying by the data collected from the real operation cases, HOSPNiCS distinguishes whether the manual operation is reachable with an average accuracy of 0.996, and the average accuracy for initial OPI prediction can reach 0.957. For initial OPII prediction, HOSPNiCS has an average distance error of 0.036 m and an average angle error of 0.395°. Based on the proposed approach, the engineering designers can swiftly ascertain operation reachability and get the initial OPI and OPII of DHM with the help of the prediction results. In light of this, the human operation simulation would be more practical for future human factor analysis.

Nonlinear Electrophoresis of Microparticles in Shear Thinning Fluids.

The nonlinear electric field dependence of particle electrophoresis has been demonstrated to occur in Newtonian fluids for highly charged particles under large electric fields. It has also been predicted to arise from the rheological effects of non-Newtonian fluids even at small electric fields. We present in this work an experimental verification of nonlinear electrophoresis in shear thinning xanthan gum solutions through a straight rectangular microchannel. The addition of polymer into a Newtonian buffer solution is found to change the electric field dependence from linear to superlinear for electroosmotic, electrokinetic, and electrophoretic velocities. The nonlinear index of each of these electrokinetic phenomena increases with the increasing polymer or buffer concentration, among which electrophoresis exhibits the strongest nonlinearity. Both these observed trends are captured by a dimensionless electrokinetic shear thinning number that depends on the power-law index of fluid viscosity and the Debye length.

Custom microfluidic chip design enables cost-effective three-dimensional spatiotemporal transcriptomics with a wide field of view.

Spatial transcriptomic techniques offer unprecedented insights into the molecular organization of complex tissues. However, integrating cost-effectiveness, high throughput, a wide field of view and compatibility with three-dimensional (3D) volumes has been challenging. Here we introduce microfluidics-assisted grid chips for spatial transcriptome sequencing (MAGIC-seq), a new method that combines carbodiimide chemistry, spatial combinatorial indexing and innovative microfluidics design. This technique allows sensitive and reproducible profiling of diverse tissue types, achieving an eightfold increase in throughput, minimal cost and reduced batch effects. MAGIC-seq breaks conventional microfluidics limits by enhancing barcoding efficiency and enables analysis of whole postnatal mouse sections, providing comprehensive cellular structure elucidation at near single-cell resolution, uncovering transcriptional variations and dynamic trajectories of mouse organogenesis. Our 3D transcriptomic atlas of the developing mouse brain, consisting of 93 sections, reveals the molecular and cellular landscape, serving as a valuable resource for neuroscience and developmental biology. Overall, MAGIC-seq is a high-throughput, cost-effective, large field of view and versatile method for spatial transcriptomic studies.

Fourier ptychographic microscopy with multi-height illumination based on energy threshold pre-search

Fourier ptychographic microscopy (FPM) technology combines the concepts of synthetic aperture imaging, ptychography, and phase retrieval to address the contradiction between the large field of view and high resolution in traditional microscopy and can achieve high-resolution amplitude and phase images with a large field of view. However, for most samples, the primary information is concentrated in the low-frequency region, and traditional single-height FPM may suffer from insufficient sampling, leading to low reconstruction accuracy. In addition, the reconstruction process typically requires a large number of low-resolution images, which also significantly reduces the reconstruction efficiency. To overcome these issues, this paper proposes a form of FPM with multi-height illumination based on an energy threshold pre-search. This method simply involves moving the LED array to three planes for multi-height sample illumination on the traditional FPM hardware, thus improving the sampling conditions and enhancing the reconstruction accuracy. The low-resolution images acquired in this way are then screened using an energy threshold method to select images with higher energy, and a phase retrieval method is employed to reconstruct high-resolution complex amplitude images. The results of simulations and experiments demonstrate that compared to traditional methods, our approach not only improves the reconstruction accuracy but also reduces the number of low-resolution images by at least approximately 60%, thereby significantly enhancing the reconstruction efficiency.

Choice Overload in Crowded Primary Elections

The number of candidates running in U.S. primary elections is increasing. Contested primary elections force voters to decide between candidates that share party labels and are ideologically similar. Similar to contexts of non-partisan elections, an increase in the number of candidates should exacerbate the cognitive demand of voting in primary elections. We expect large candidate fields in primaries make voters (1) spend less time looking at each candidate profile, (2) more likely to abstain, (3) more likely to vote based on ballot position, and (4) more likely to feel overwhelmed with the decision. All four of these expectations were preregistered. We test the effect of large candidate fields on voter behavior using a survey experiment ( n = 2000) fielded by YouGov. We find large candidate fields cause respondents to spend less time looking at candidate profiles, to select candidates in the first half of the ballot, and to feel overwhelmed by the decision-making process. In contrast to our expectations, we find large candidate fields make respondents less likely to abstain.

Target localization and defect detection of distribution insulators based on ECA‐SqueezeNet and CVAE‐GAN

AbstractInsulators, as typical equipment for distribution networks, provide good electrical insulation between live conductors and earth. Timely and accurate detection is essential for insulator detection issues. However, as the complexity of neural networks increases, the detection efficiency is often lower. Therefore, this paper proposes a fast insulator positioning and defect detection method. Firstly, for insulator target localization, the SqueezeNet network is improved using ECA attention mechanism. In addition, to address the issue of low defect detection accuracy, a joint algorithm has been proposed. The integration of convolutional variational autoencoder (CVAE) and generative adversarial network (GAN) solve their own shortcomings due to different image focus angles. The target localization accuracy reaches 94.30%, and the defect detection accuracy reaches 89.60%. It solves the problems of difficulty in locating small targets in a large field of view and inaccurate detection due to a small number of abnormal samples. This method has been tried and tested in practical distribution network systems.

Criticality of the O(N) universality via global solutions to nonperturbative fixed-point equations

Fixed-point equations in the functional renormalization group approach are integrated from large to vanishing field, where an asymptotic potential in the limit of large field is implemented as initial conditions. This approach allows us to obtain a global fixed-point potential with high numerical accuracy, that incorporates the correct asymptotic behavior in the limit of large field. Our calculated global potential is in good agreement with the Taylor expansion in the region of small field, and it also coincides with the Laurent expansion in the regime of large field. Laurent expansion of the potential in the limit of large field for general case, that the spatial dimension d is a continuous variable in the range 2≤d≤4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2\\le d \\le 4$$\\end{document}, is obtained. Eigenfunctions and eigenvalues of perturbations near the Wilson–Fisher fixed point are computed with the method of eigenperturbations. Critical exponents for different values of d and N of the O(N) universality class are calculated.

A flexible high-precision photoacoustic retinal prosthesis.

Retinal degenerative diseases of photoreceptors are a leading cause of blindness with no effective treatment. Retinal prostheses seek to restore sight by stimulating remaining retinal cells. We here present a photoacoustic retinal stimulation technology. We designed a polydimethylsiloxane and carbon-based flexible film that converts near-infrared laser pulses into a localized acoustic field, aiming at high-precision acoustic activation of mechanosensitive retinal cells. This photoacoustic stimulation of wild-type and degenerated ex vivo retinae resulted in robust and localized retinal ganglion cell activation with sub-100-µm resolution in both wild-type and degenerated ex vivo retinae. Our millimeter-size photoacoustic film generated neural activation in vivo along the visual pathway to the superior colliculus, as measured by functional ultrasound imaging when the film was implanted in the rat subretinal space and stimulated by pulsed laser. Biosafety of the film was indicated by absence of short-term adverse effect under optical coherence tomography retinal imaging, while local thermal increase was measured below 1 °C. These findings demonstrate the potential of our photoacoustic stimulation for visual restoration in blind patients with a high spatial precision and a large field of view.

Spatial memory obviates following behaviour in an information centre of wild fruit bats.

According to the information centre hypothesis (ICH), colonial species use social information in roosts to locate ephemeral resources. Validating the ICH necessitates showing that uninformed individuals follow informed ones to the new resource. However, following behaviour may not be essential when individuals have a good memory of the resources' locations. For instance, Egyptian fruit bats forage on spatially predictable trees, but some bear fruit at unpredictable times. These circumstances suggest an alternative ICH pathway in which bats learn when fruits emerge from social cues in the roost but then use spatial memory to locate them without following conspecifics. Here, using an unique field manipulation and high-frequency tracking data, we test for this alternative pathway: we introduced bats smeared with the fruit odour of the unpredictably fruiting Ficus sycomorus trees to the roost, when they bore no fruits, and then tracked the movement of conspecifics exposed to the manipulated social cue. As predicted, bats visited the F. sycomorus trees with significantly higher probabilities than during routine foraging trips (of >200 bats). Our results show how the integration of spatial memory and social cues leads to efficient resource tracking and highlight the value of using large movement datasets and field experiments in behavioural ecology. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Thin layer axion dynamo

We study interacting classical magnetic and pseudoscalar fields in frames of the axion electrodynamics. A large scale pseudoscalar field can be the coherent superposition of axions or axion like particles. We consider the evolution of these fields inside a spherical clump. Decomposing the magnetic field into the poloidal and toroidal components, we take into account their symmetry properties. Within a spherical clump, we use a thin layer approximation in the induction and Klein–Gordon equations, where the dependence of the fields on the latitude is accounted for. Then, we derive the dynamo equations in the low mode approximation. The nonlinear evolution equations for the harmonics of the magnetic and pseudoscalar fields are solved numerically. As an application, we consider a dense axion star embedded in solar plasma. The behavior of the harmonics and their typical oscillations frequencies are obtained. We suggest that such small size axionic objects, containing oscillating magnetic fields, can cause electromagnetic flashes, recently observed in the solar corona, contributing to the corona heating.

An effective imaging based diagnosis of Solar Photovoltaic System and performance parameters for smart solar power grid

Another of the most attractive power generation sources for residential, corporate, and commercial operations is energy production. Due to this compelling qualities, photovoltaic systems (PV) electricity production have increasingly attracted the attention of researchers and professionals. Nonetheless, the greatest obstacle in generating energy from the sun is the predictable discontinuous output power from photovoltaic (PV) systems, which is largely caused by climate. The power differential of a photovoltaic panels may considerably reduce the financial profit of large scale solar fields. For everyday proper management of electricity supply production, distribution, and storing as well as for judgement on the electricity market, results were consistent prediction of the electricity output of solar PV systems is essential. The 5 subjects mentioned in this article are: The varied faults which might occur in PV panels; internet Photovoltaic panels monitoring; Use of machine learning approaches in Photovoltaic module damage detection; Advantages of fault diagnosis in PV panels and the various motion sensors used for this purpose are discussed. Recommendation for future possible research paths are given in view of the evaluated research.

Automated analysis framework of strain partitioning and deformation mechanisms via multimodal fusion and computer vision

Simultaneously investigating strain partitioning and the underlying deformation mechanisms for both the grain interior and the grain boundary (GB) is essential for understanding the complex plastic deformation of hexagonal close-packed metals. To this end, an automated analysis framework based on high-resolution digital image correlation (HRDIC) and electron backscatter diffraction (EBSD) data fusion and computer vision, integrating nanoscale resolution and a large field of view, is proposed. This framework consists of: (1) HRDIC-EBSD data fusion; (2) Segmenting the strain field into individual grains each with a core and a mantle; (3) Data clustering of the Matrix and slip bands (SBs) for each grain; (4) Full slip system (SS) identification and SS assignment to the SBs. The capabilities of this framework were demonstrated on Mg-10Y during compression. The strain field data, which was segmented into different clusters, including grain mantle, grain core, Matrix, and SBs, was analyzed statistically and quantitatively. The pixel-based slip activity, which considers the SB morphology, was obtained from a statistical perspective. Inter-granular accommodating mechanisms, including GB strain, slip transfer, and GB sliding, were quantitatively analyzed. Overall, this analysis framework, which can be applied to other materials, can automatically and statistically evaluate both nanoscale strain fields and underlying intra- and inter-granular deformation mechanisms grain-by-grain. This work provides valuable experimental insights into plastic deformation and accommodation mechanisms for polycrystals.

Large power dynamic range microwave electric field sensing in a vapor cell

Large power dynamic range microwave electric field sensing in a vapor cell

Tunable electronic and optical properties of a Type-ⅡViolet Phosphorus/MoS2 heterojunction: First-principles calculation

Photodetectors based on heterostructures have garnered significant research interest due to their superior self-powering and responsiveness capabilities. In this work, the optoelectronic properties of a violet phosphorus (VP/MoS2)/MoS2 heterojunction are investigated through first-principles calculations. The results reveal that the VP/MoS2 heterojunction possesses an indirect bandgap and a type-II band alignment. The interface potential drop (Ep) of the VP/MoS2 heterojunction is 5.45 eV by studying the interfacial interaction, suggesting the formation of a large in-built electric field and an excellent self-powering capability. The absorption coefficient of VP/MoS2 heterojunction are significantly higher in the UV and visible regions. Under biaxial strain, the VP/MoS2 heterostructure can undergo transformations from a semiconductor to a metal, from an indirect to a direct bandgap, and from a type-II to a type-I energy band structure. Moreover, the light trapping ability in the near-infrared region is significantly enhanced. These findings underscore the broader potential application of VP/MoS2 heterostructures in high-performance optoelectronic devices.