This paper examines the optimization of one of the most important metrological characteristics of dosimetric X-ray and gamma-ray installations – the geometric size of the uniform field of the gamma radiation field. The influence of the geometric shape of lead attenuators in verification installations on the size of the uniform region of the gamma radiation field is analyzed. It is shown that the use of classically shaped attenuators leads to a significant reduction in the width beam of uniform, which limits the number of simultaneously verified dosimetric instruments designed for measuring the air kerma rate. Experimental measurements of the air kerma rate were conducted using a setup with various attenuator combinations, and a comparison with published data was made. Based on the results, an optimized attenuator shape is proposed, ensuring both the required attenuation factor and maintaining the size of the uniform region of the gamma radiation field. A design implementation of optimized attenuators is presented, protected by a patent from the Eurasian Patent Office, confirming the novelty of the proposed technical solution.

Afrotropical inland waters remain poorly studied for rotifer diversity. Here, we provide new distribution data from Botswana and connect these local patterns to continental-scale biogeography using an Africa–Europe occurrence dataset. In Botswana, we analyzed rotifer species richness, functional traits, and environmental drivers using 37 samples from 15 water bodies spanning natural and anthropogenic habitats. We recorded 107 rotifer taxa: 92 identified to species or subspecies level and 14 to genus. Seventy taxa (~65%) are new records for Botswana, and one species, Donneria sudzukii, is reported for the first time in Africa. Physicochemical gradients explained community structure, with the first two constrained RDA axes accounting for 40.7% and 23.7% of variation. Axis 1 captured a mineralization gradient linked to total dissolved solids and temperature, whereas Axis 2 reflected oxygen concentration and pH. Traits tracked these gradients: warmer, more mineralized waters were associated with specific trophi types, compact body shapes, and intermediate body sizes, whereas less mineralized, better oxygenated sites were related to smaller taxa and alternative feeding morphologies. To place these trait–environment relationships in a broader geographic context, we then analyzed an Africa–Europe dataset (67,170 records) to quantify latitudinal patterns in thermal classes and morphological traits (geometric body shape and trophi type). Diversity showed clear latitudinal structuring: warm-water genera clustered at low latitudes, only Kellicottia and Didymodactylos had mean distributions above 50° N, and bdelloid families were associated with higher latitudes. Morphological traits also varied with latitude, with trilateral truncated pyramid body shapes and malleoramate trophi occurring closest to the equator. Overall, by combining new species-level data from Botswana with continent-scale occurrence patterns, we link local community assembly to macroecological structure in rotifer functional and biogeographical organization.

The exploitation of graphene's extraordinary properties depends on finding new ways to synthesize and process it without disrupting its fundamental structure.Here, we demonstrate the synthesis of highly processable and dispersible edge-functionalized graphene (EFG) directly from graphite by a combination of selective oxidation and physical exfoliation. Microscopy and spectral characterization reveals few-layer graphene nanoplatelets with defect-free basal planes and carboxylate and phenolic edge-functionalization.Its defect-free nature is reflected in its high conductivity (900Scm-1). The EFG has excellent dispersibility (100mgmL-1) in aqueous and organic solvents and forms asoft graphene doughthat can be molded to any geometric shape. The dried dough can readily reabsorb a wide variety of solvents indicative ofa highly porous and amphiphilic material.The unique properties of the graphene dough are demonstrated with the formation of a 3D-printed conductive scaffold, a printed circuit on paper, and the fabrication of a paramagnetic graphene dough. Significantly, free-standing and 3D-printed supercapacitors can be fabricated from ionic liquid-impregnateddough that gives an excellent gravimetric capacitance of210Fg-1and a high energy density of262.5WhKg-1.This high capacitance is synonymous with efficient pore utilisation during charge storage and supports the unique amphiphilic, nanoporous EFG structure.

Adverse bed-slope transitions can strongly reorganise open-channel turbulence, but their impact on anisotropy, intermittency, and nonlinear dynamics is not yet well quantified. This study experimentally investigates turbulence over an adverse sloping bed in an open channel, aiming to elucidate how bed-induced geometric transitions shape turbulence characteristics. High-frequency three-dimensional velocity measurements were acquired at multiple streamwise stations and depths, and analysed using Reynolds-stress anisotropy diagnostics, intermittency indicators based on quadrant joint-PDFs, velocity spectra, and chaos-information theoretic measures. The results show that turbulence anisotropy evolves gradually along the bed transition. The flow shifts from predominantly bi-directional states upstream toward more mixed states over the slope, followed by partial recovery downstream. Anisotropy is strongest near the bed, exhibits peaks just below mid-depth, and becomes more vertically self-similar with increasing current magnitude. Positionally, no anomalous tendency is observed under stronger currents. In contrast, intermittency remains strongly localised, with slope-transition stations acting as hotspots where joint-PDF contours broaden toward ejection-sweep dominance and spectra steepen. This is consistent with sporadic bursting and sharper departures from local trends, whereas non-transitional stations retain tighter contours and flatter spectra indicative of steadier coherence. Chaos and information analyses further indicate increasing trajectory divergence and reduced memory with height as slope-driven upwellings are present. Collectively, these observations suggest that anisotropy trends and intermittency hotspots can exhibit distinct spatial signatures. Therefore, anisotropy should be interpreted alongside intermittency and memory metrics for position-aware turbulence assessment over adverse slopes.

Tissue fluidity regulates many critical biological processes, including embryonic development, wound healing, and cancer metastasis. In confluent epithelia, where cell packing fraction is effectively fixed, the prevailing paradigm postulates that transitions between solid-like jammed and fluid-like unjammed states are governed by a geometric cell shape index determined by the balance of cortical tension and intercellular adhesion. Here, we challenge this geometric framework by reporting a mode of fluidization in epithelial monolayers that is entirely shape-independent. We observe that reducing cell-cell adhesion triggers a substantial increase in fluidity, yet this occurs without any corresponding change in cell shape, cell density, substrate traction, or junctional line tension. This decoupling of shape and fluidity reveals that current vertex models, which treat adhesion solely as a contribution to interfacial tension, are incomplete. To reconcile these findings, we extend the theoretical framework to account for the dual nature of adhesion -- its thermodynamic role in setting interfacial adhesion energy at the cell-cell junctions and its kinetic role in generating viscous drag as cells slide past their neighbors. This generalized model quantitatively captures the experimental data, demonstrating that the interplay between adhesive energetics and dissipative friction is essential for a complete understanding of epithelial fluidity.

Soil erosion, particularly ephemeral gully (EG) erosion, poses a significant threat to agricultural sustainability and ecosystem health. Despite their substantial impact on soil degradation, EGs have been relatively understudied, primarily due to their temporary nature and the limitations of existing measurement techniques. This study introduces an integrated approach for quantifying and analyzing EGs, addressing the critical need for accurate and scalable measurement methods. Our methodology combines three key components: (1) an updated portable field tool (Gulliometer), which improves upon existing designs to enhance data collection in diverse field conditions; (2) a standardized image acquisition protocol that ensures consistent, high-quality data capture; and (3) an image processing technique leveraging easy repetitive analysis of gully cross-sections. Laboratory validation using known geometric shapes demonstrated the high precision of our methodology, with error rates below 1%. Field applications in two distinct locations in Ontario, Canada, further confirmed the practicality and effectiveness of our approach under varied environmental conditions. This approach not only advances our understanding of ephemeral gully erosion but also aids in the development of effective soil conservation strategies and informed decision-making in land management.

Abstract This study introduces a geometric framework to explain how quantum particles, specifically protons, move through energy barriers in biological molecules like DNA. Rather than viewing this tunneling as a purely random event, we propose that it is governed by the structural complexity of the surrounding molecular environment. By treating the energy landscape as a geometric shape, we demonstrate that the environment acts as a regulator that either facilitates or hinders the movement of protons between genetic base pairs. We applied this model to compare the two primary building blocks of the DNA ladder: the Guanine-Cytosine (G-C) and Adenine-Thymine (A-T) pairs. Our findings reveal that the G-C pair possesses a structural configuration that makes proton movement significantly more likely compared to the A-T pair. This difference provides a clear physical explanation for why certain parts of our genetic code are more prone to spontaneous changes, or tautomeric shifts, which can lead to mutations. Furthermore, the research explores how the DNA molecule interacts with its surrounding cellular noise (e.g. water molecules and proteins). We find that the proton behaves in a hybrid manner (at times acting like a coherent wave that exists in multiple places at once), and at other times like a solid particle trapped by its environment. This dual behavior suggests that life operates at a delicate balance between quantum mechanical effects and classical stability.

The self-prioritization effect refers to the tendency for individuals to perceive self-related stimuli more accurately than other-related stimuli. We leveraged this phenomenon to investigate the mechanisms underlying empathy. According to the self-other merging hypothesis, empathy broadens self-representation to encompass others, predicting a reduced self-prioritization effect. In contrast, the self-other distinction hypothesis posits that empathy heightens the differentiation between self and other, predicting an increased self-prioritization effect. To test these competing hypotheses, we employed a perceptual task combined with electroencephalogram (EEG) recordings, and analyzed the data by using signal detection theory. Fifty-two participants aged 19 to 33years were randomly assigned to either a high-empathy or low-empathy group. Participants listened to an interview and were instructed to either empathize with or remain neutral toward the interviewee. Subsequently, they completed a shape-label matching task using geometrical shapes associated with the self, the interviewer, and the interviewee. The self-prioritization effect was measured by performance differences between self-related and other-related stimuli. Different performance indices provided support for each hypothesis. Specifically, the patterns observed in the sensitivity index (d') and the lateral positive component (LPC) of the event-related potential supported the self-other distinction hypothesis at the perceptual and attentional levels. In contrast, the patterns in the response bias index (c) and reaction time supported the self-other merging hypothesis at the response level. These findings suggest that empathy influences self-representation in distinct ways across different levels of processing.

Abstract This paper aims to study a self-supervised 3D clothing reconstruction method, which recovers the geometric shape and texture of human clothing from a single image. Compared with existing methods, we observe that three primary challenges remain: (1) 3D ground-truth meshes of clothing are usually inaccessible due to annotation difficulties and time costs; (2) Conventional template-based methods are limited in modeling non-rigid objects, e.g., handbags and dresses, which are common in fashion images; (3) The inherent ambiguity compromises the model training, such as the dilemma between a large shape with a remote camera or a small shape with a close camera. In an attempt to address the above limitations, we propose a causality-aware self-supervised learning method to adaptively reconstruct 3D non-rigid objects from 2D images without 3D annotations. In particular, to solve the inherent ambiguity among four implicit variables, i.e., camera position, shape, texture, and illumination, we introduce an explainable structural causal map (SCM) to build our model. The proposed model structure follows the spirit of the causal map, which explicitly considers the prior template in the camera estimation and shape prediction. During optimization, the causality intervention tool, i.e., two expectation-maximization loops, is deeply embedded in our algorithm to (1) disentangle four encoders and (2) facilitate the prior template. Extensive experiments on two 2D fashion benchmarks (ATR and Market-HQ) show that the proposed method could yield high-fidelity 3D reconstruction. Furthermore, we also verify the scalability of the proposed method on a fine-grained bird dataset, i.e., CUB.

Thermoforming is a widely used plastic packaging method due to its af-fordability, high protective performance, and ability to prevent mechanical damage to fruits during transportation. This study aimed to investigate the factors influencing the thermoforming packaging moulding process, evaluate the structural strength of thermoformed packaging, and assess the effective-ness of various shaped thermoformed containers in protecting pears. The prototype design was based on different geometric shapes and dimensions, divided into four relief geometries: cylindrical (M1), semi-circular (M2), geodesic dome (M3), square (M4), and commercial dome shapes. According to the mould thermoforming process, the mockups of each pattern were modelled using SolidWorks software and formed using a 3D printer. Polyvinyl chloride (PVC) plastic sheets were formed in a container mould with a ther-moformed machine under the same parameter conditions of time, tempera-ture, and pressure. The compression resistance of the thermoformed con-tainers was tested. According to these findings, the compression force was higher in inferior thermoformed containers than in superior thermoformed containers. This is due to the relief size, geometry, and dimensions of the thermoformed containers. Then, thermoformed containers were employed to perform the dart drop impact test, with the pears dropped from heights of 20, 40, and 60 cm. The thermoformed container sample with a square shape (M4) had the lowest proportion of bruises (8.33%) on fruit. For container sample M4, the bruised area (BA) was assessed at drop heights of 20, 40, and 60 cm at 97.12, 140.75, and 206.02 square millimeters, respectively. Based on this finding, the bruise volume increased as the impact height increased. Additionally, a drop test was performed at a height of 90 cm using a thermoformed container with pears in a double-wall corrugated board for the BC flute. A higher total area of bruises on pears without thermoformed containers was observed in the evaluation of bruised damage. Therefore, this study concludes that the shape, size, and relief position of thermoformed containers reduce the damage caused by the compression strength and drop-ping height during transportation.

Biological nanopores facilitate the continuous exchange of ions, molecules, and energy between living organisms and their environment. Scientists have used biological nanopores for sensing, such as gene sequencing and single‐molecule detection. However, biological nanopores are inherently fragile. Inspired by biological nanopores, scientists have developed solid‐state nanopores/nanochannels. These synthetic systems have stable physical properties, adjustable geometric shapes, and chemically modifiable surfaces. Metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) overcome the limitations of traditional solid‐state nanochannel surface functionalization through their designable framework structures. Here, we summarize the functionalization strategies and applications of MOFs and COFs on the inner wall and outer surface of solid‐state nanochannels. The functionalization can precisely regulate surface properties, chemical environment, and pore size, thereby achieving high sensitivity, selectivity, and specificity in solid‐state nanochannel sensing. Finally, the future development opportunities in this research field were discussed.

Dual-frequency ultrasonic holography by binary aperture plates.

Stability of the electric arc process during welding has been investigated in this study. A weld seam is produced in 2–4 seconds only, so the quality of connection directly depends on the stability of welding arc burning. The features of the electric arc process are determined by a combination of welding mode parameters: current, welding duration, lifting height, and preliminary rod departure. Establishing the mode parameters that enable stable arc burning is a complex practical task, solving which by the selection method does not warrant the optimal result. This paper reports results of investigating the welding of A500C reinforcing bars with a drawn arc in flux. The values of the coefficients of variation in the current and voltage, obtained by statistical processing of the welding arc oscillograms, were chosen as a criterion for quantitative assessment of the stability of the electric arc process. It was established that in the entire range of the studied modes , that is, the electric arc process is stable. The plots of variation coefficients depending on the welding current have extrema that correspond to the most stable welding mode. It is this feature of the variation coefficient function that makes it possible to determine the optimal value for the welding current. The influence of the welding mode parameters on the weld formation process was investigated. The resulting regression dependences enable predicting the volume of molten metal and, as a result, the geometric dimensions of the weld. Based on the study's results, an engineering methodology for searching for optimal welding mode parameters was devised. The welding mode parameters for reinforcing bars with a diameter of 16 mm were calculated. The established modes were tested when welding a batch of control samples in the amount of 10 pieces; the result is that the geometric dimensions and shape of the welds meet the requirements from DSTU B V.2.6-169:2011

It is generally acknowledged that computer-aided drafting (CAD) has rendered traditional construction and descriptive geometry methods obsolete. This two-part study experimented with SolidWorks in these two geometric areas by investigating assignments submitted by first-year engineering students at the Botswana International University of Science and Technology. The first part, conducted in 2017, used a simple geometric shape to train a cohort of 178 students on how SolidWorks could be used to mimic traditional construction geometry methods to model the shape. Participants were then assigned more complex geometries to apply appropriate SolidWorks methods to mimic the construction geometry methods of the assigned shapes. The students worked in groups of at least five members and completed the assignments in a three-hour lab session. The second part, conducted in 2024, addressed the visualization dilemma associated with the passive, teacher-centered methods used in demonstrating the descriptive geometry rabatment process. Another cohort of 557 students, working in groups of at least six members, developed SolidWorks models to demonstrate the process. This cohort was given over 12-hour lab sessions to complete the task. The results from the construction geometry experiments show that participants struggled to mimic traditional drawing techniques in SolidWorks, while the descriptive geometry cohort developed meaningful SolidWorks rabatment process models. These two CAD-based approaches are pedagogically important because, in the first part, traditional construction geometry was extended into platforms that support e-learning, while in the second part, a flipped learning approach to descriptive geometry was introduced.

As indoor robots are expected to operate in increasingly complex environments, the need for rich and scalable semantic representations has become critical. While semantic mapping is a standard tool, existing representations often fall at two extremes: dense voxel-based maps that are computationally expensive to query, or schematic graphs that lack geometric detail. This trade-off limits the scalability of semantic maps in real-world tasks. We propose an object-aware semantic mapping framework that models key static objects using probability density functions (PDFs). Objects like beds, fridges or desks are detected via 3D point cloud processing and encoded as 2D probabilistic occupancy distributions. This formulation provides a compact, robust representation that preserves semantic identity and geometric shape, while handling noise and partial views. The map is structured around rooms and their contents, enabling global relocalization and semantically informed path planning. Using Differential Evolution and Kullback-Leibler divergence, our method achieves robust relocalization without prior pose. Its object-centric, probabilistic nature also supports functional scene understanding for context-aware navigation. We validate our approach on a benchmark dataset and in a real apartment, showing improved performance over traditional methods in ambiguous or cluttered scenes, and demonstrating the advantages of a unified representation for multiple robotic behaviors.

ABSTRACT Herein, the photonic dispersion of metasurfaces is tailored via multiple Brillouin zone foldings (BZFs) to achieve robust ultrahigh‐ Q resonances and giant Goos‐Hänchen shifts (GHSs) with geometry‐free and angle‐insensitive properties. By introducing the geometric perturbation into the lattice, the guided resonances (GRs) lying below the radiative continuum are folded into the radiative continuum and evolve into BZF‐induced guided mode resonances (BZF‐GMRs) with ultrahigh Q factors. Remarkably, the Q factors of the BZF‐GMRs maintain ultrahigh across a wide momentum space and exhibit ultralow sensitivity to the geometric shape of the scatterers, inherited from the intrinsic infinitely high Q factors of the GRs. More importantly, it is discovered that the Q factor of the BZF‐GMR scales with the fourth power of the order of BZF. Leveraging these robust ultrahigh‐ Q BZF‐GMRs, we realize giant geometry‐free and angle‐insensitive GHSs (on the scale of 10 3 λ ). Full‐wave simulations are performed to demonstrate the enhancement of GHSs. This work not only reveals the relationship between BZF and GHS, but also offers a general route to achieving robust ultrahigh‐ Q resonances and giant GHSs.

Three-dimensional (3D) reconstruction using structured light is a fundamental technique for capturing the geometric shape of objects through the projection of fringe patterns. However, most of the existing structured light systems rely on a synchronization mechanism between the projector and camera components to image objects from a single viewpoint, limiting their capability to scale to full surface or format measurement. To this end, we propose to engineer a 3D imaging array system prototype by integrating multiple structured light units without imposing the synchronization requirement on them to provide a scalable and flexible solution for full surface 3D high-fidelity measurement. We demonstrate this approach with four asynchronous projector and camera units by analyzing and solving the fringe mixing imaging problem within each unit and between them. Specifically, we introduce a diffusion model-based generative learning framework, with a U-Net-like encoder-decoder architecture, for separating the fringe patterns from the mixed fringe observations within and across overlapping fields of view (FOVs) of adjacent units. Experimental results show that the proposed method is capable of generating high-quality fringe patterns under challenging mixing conditions and reconstructing object surfaces with remarkable geometric fidelity. It also generalizes well to complex object geometries, demonstrating strong potential for asynchronous, multi-view structured light 3D reconstruction.

Early childhood cognitive development requires engaging learning media. However, many PAUD classrooms still rely on monotonous activities that reduce children's motivation and limit cognitive progress. This study aimed to develop an Android-based interactive learning application to stimulate early childhood cognitive development, particularly in recognizing colors, geometric shapes, and sizes. The study used a research and development method based on the ADDIE model, which consists of analysis, design, development, implementation, and evaluation. The population comprised children at RA Al Ikhlas Birobuli. Participants for the classroom trial were selected through purposive sampling, focusing on children who took part in the learning activities during the implementation stage. Data were collected using observation sheets to measure learning engagement and cognitive performance, expert validation questionnaires to assess media and material feasibility, and cognitive tests in the form of a pretest and posttest to measure learning outcomes. Expert validation results indicated that the application was highly feasible, with a media feasibility score of 95% and a material feasibility score of 92%. Classroom implementation showed a significant improvement in children’s cognitive abilities, as indicated by higher posttest scores than pretest scores and a p-value of 0.000. The application includes interactive features such as visual animations, sound effects, game-based tasks, and a reward system, which increased engagement and motivation and supported constructivist principles that emphasize active and multisensory learning. In conclusion, the Android-based interactive application is effective, practical, and innovative for supporting early childhood cognitive development. It is recommended that PAUD teachers use this application as complementary learning media. Future studies should involve larger and more diverse samples and evaluate long-term learning retention and usability across different devices.

Wireless power transmission (WPT) is poised to revolutionize the future of wireless applications and sensing networks. High-gain antennas are essential for extending WPT coverage, but the unpredictable orientation of wireless devices remains a major challenge. To address this, this paper proposes a dielectric resonator antenna (DRA) with a new cone version (cupped-cone shape) to achieve high gain and a wideband circular polarization, ensuring consistent energy transfer regardless of device orientation. The proposed design enhances bandwidth by supporting multiple resonant modes. Combining two geometric shapes provides greater flexibility for fine-tuning and optimizing the DRA. The proposed DRA is excited using an innovative feeding mechanism with two elliptical slots and a modified microstrip feeding to produce wideband circular polarization, achieving large impedance and axial ratio bandwidths. The design is fabricated from polylactic acid using 3D printing technology, making it lightweight and cost-effective. Measurements show the antenna operates in the WPT band, covering the industrial, scientific, and medical (ISM) frequency of 5.8GHz with a 64% impedance bandwidth, 3-dB axial ratio bandwidth of approximately 31%, and a high gain of about 11.1 dBic by effectively utilizing a higher-order mode while maintaining the bandwidth.

This article provides a rigorous exploration of the transition from classical Cartesian coordinate systems to abstract geometric frameworks. It begins by establishing the “death of the fixed origin” arguing that modern analytical geometry is better understood through the lens of Commutative Algebra and Topology rather than simple numerical plotting. The text covers three major theoretical shifts: the development of Algebraic Varieties and Coordinate Rings, the introduction of Scheme Theory by Alexander Grothendieck, and the application of Sheaf Theory to maintain global consistency in complex manifolds. By synthesizing these high-level concepts, the article demonstrates how abstract geometry serves as the underlying language for both theoretical physics (specifically String Theory) and modern data science. As well as the article is designed for an advanced undergraduate or graduate-level audience. It successfully bridges the gap between pedagogical geometry and contemporary research. A particular strength of the piece is its treatment of Hilbert’s Nullstellensatz, which it uses to prove the fundamental link between algebraic ideals and geometric shapes. The inclusion of Differential Geometry and the Metric Tensor provides a holistic view, ensuring the reader understands both the algebraic and the continuous aspects of the field.