Symmetric Pattern Research Articles

Two-step Fourier single-pixel imaging for secure and efficient hidden information transmission

In the rapidly evolving field of optical information security, single-pixel imaging (SPI) has emerged as a promising technique for hidden information transmission. However, traditional SPI methods face significant challenges, including the need for excessive modulation patterns and the vulnerability of encrypted information during transmission. Furthermore, the field lacks efficient methods to reconstruct both plaintext and ciphertext images from the same set of single-pixel measurements. Here, we propose a novel and efficient encryption strategy for Fourier single-pixel imaging (FSPI) that addresses these critical challenges. Our approach integrates two key innovations: a two-step Fourier-total variation conjugate gradient descent (F-TVCGD) method and a dual-key decryption mechanism. The F-TVCGD method significantly reduces the number of modulation patterns required for image reconstruction, enhancing efficiency and minimizing data redundancy. Our dual-key mechanism enables the reconstruction of both plaintext and ciphertext images from a single set of single-pixel measurements using different decryption keys, significantly enhancing security without compromising efficiency. The incorporation of Fourier symmetric patterns improves the convergence robustness of the symmetric gradient descent (SGD) algorithm, leading to superior performance under challenging conditions such as sparse sampling and noise attacks. Numerical simulations and optical experiments validate our method's improvements in both accuracy and security compared to traditional approaches. Our findings demonstrate that the proposed F-TVCGD and SGD strategies effectively address the challenges of excessive modulation patterns and information vulnerability in FSPI.

Optimal Curve Fitting for Serial Chain in Six-Crease Origami Unit

Abstract Origami-inspired structures have been widely used in aerospace and robotics for three-dimensional (3D) symmetrical configurations using crease-symmetrical origami basic patterns. These patterns offer advantages in repeatable and systematic modeling and mass production. However, few studies have focused on 3D non-symmetrical structures using symmetrical origami basic patterns due to their structure complexity, limiting their application. Therefore, we aim to analyze the folding behavior in 3D non-symmetrical structures using a 6-crease symmetry origami base pattern. To achieve this goal, we first focus on behavior in a two-dimensional (2D) plane. This paper presents a scheme for the behavior of origami units with an optimal curve-fitting algorithm. The curve can be any 2D space curve. The fitting curve, constructed by numerical analysis and an optimal approaching scheme, can satisfy error requirements and retain foldable origami unit features. The paper verifies the feasibility of the curve-fitting scheme by presenting two curve examples, including a quadratic curve and a sin wave function. The results show that the fitting error is reduced by 99% when no boundary conditions are applied. This research provides valuable insights into understanding origami unit kinematic optimization through forward and inverse kinematics. It offers potential applications in the engineering design of foldable structures and precision origami-inspired mechanism, thereby opening avenues for further exploration of complex origami structures and their applications in emerging technologies.

Quantifying Drosophila melanogaster Eye Phenotypes: A Computational Approach Integrating ilastik and Flynotyper.

The Drosophila melanogaster compound eye is a well-structured and comprehensive array of around 800 ommatidia, exhibiting a symmetrical and hexagonal pattern. This regularity and ease of observation make the Drosophila eye system a powerful tool to model various human neurodegenerative diseases. However, ways of quantifying abnormal phenotypes, such as manual ranking of eye severity scores, have limitations, especially when ranking weak alterations in eye morphology. To overcome these limitations, computational approaches have been developed such as Flynotyper. The use of a ring light allows for better qualitative images accessing the intactness of individual ommatidia. However, these images cannot be analyzed by Flynotyper directly due to shadows on ommatidia introduced by the ring light. Here, we describe an unbiased way to quantify rough eye phenotypes observed in Drosophila disease models by combining two software, ilastik and Flynotyper. By preprocessing the images with ilastik, successful quantification of the rough eye phenotype can be achieved with Flynotyper.

Compact Substrate Integrated Waveguide Cubical Dielectric Resonator Antenna for fifth-generation applications

A comprehensive analysis of a wideband Cubical Dielectric Resonator Antenna is presented, specifically designed for 5G-NR wireless communication applications, focusing on the N257, and N258 frequency bands. This antenna exhibits symmetrical radiation patterns, a wider bandwidth, improved efficiency, and substantial gain characteristics. The design employs a low-loss substrate-integrated waveguide structure to enhance gain while reducing cross-polarization effects. This is accomplished through an innovative approach of establishing boundary conditions using copper wire stitching for vias, superseding the conventional soldering iron method, which guarantees minimal radiation leakage, compact dimensions, and reduced losses. The perforated dielectric resonator antenna possesses higher mode excitations, and implementing metallic strips on two resonator surfaces facilitates the simultaneous excitation of fundamental and higher-order modes, thereby yielding a broadband response. The overall dimensions of the antenna are 15.29 × 8.42 × 3.8 mm3(1.3×0.7×0.3)λ03, which facilitates a measured impedance bandwidth of 8.2 GHz, spanning from 24.4 to 32.6 GHz (28.7%), accompanied by a high gain of 8.1 dBi and efficiency levels reaching up to 94%. The prototype is constructed utilizing the standard printed circuit board technique, and simulation outcomes are derived using the High-Frequency Structure Simulator (HFSS).

Cascaded capsule twin attentional dilated convolutional network for malicious URL detection

Malware is one of the most popular cyber-attacks, and it is becoming more common on the network every day. In contrast to benign transmission, which typically exhibits symmetrical patterns, malware communication often shows asymmetrical behaviours, making detection a complex challenge. Fortunately, malware can be distinguished and identified for actual activities utilizing a variety of artificial intelligence methods. However, insufficient work has been allocated to the problem of handling high-dimensional and huge data. This paper proposes a novel deep learning-based approach to identify malicious Uniform Resource Locators (URLs) specifically designed to handle the challenges posed by large-scale and complex data. Initially, input data is sourced from a comprehensive Kaggle dataset, which includes diverse and large-scale URL samples. The URLs are then transformed into vector representations using a Vector Embedding Module, which employs a character-level word embedding technique to capture intricate patterns within the URLs. To further refine the data, the Chaotic Kookaburra Efficient-Bo Network (CKEBO-Net) is applied to extract the most significant features from these vectors, effectively reducing the dimensionality and computational burden. Subsequently, the Cascaded Capsule Twin Attentional Dilated Convolutional Network (C2TA_DiCN) model is introduced to classify and identify malicious URLs with high precision. This model leverages the unique strengths of capsule networks and attentional mechanisms, enhancing its capability to capture subtle dependencies within the data. Furthermore, the Lyrebird Meta-heuristic Optimization (LMO) algorithm is used to fine-tune the model parameters appropriately, ensuring that the training process is efficient and robust. The proposed approach is implemented using Python and rigorously evaluated on the Kaggle dataset. Simulation results demonstrate that the proposed method significantly outperforms existing models, achieving a malicious URL detection accuracy of 99.7%.

Torque-driven superhydrophobic cylinders swim in circles

A superhydrophobic cylinder is a circular cylinder with a boundary pattern of alternating shear-free menisci and solid portions. This article derives analytical solutions for the torque-driven Stokes flow around a superhydrophobic cylinder that is free to move, or ‘swim’, subject to the constraint that it is free of net force. The mathematical approach is a natural generalization of one used to solve for transverse shear flow over a superhydrophobic surface comprising a periodic array of no-shear slots (Crowdy 2011 Phys. Fluids 23 (doi: 10.1063/1.3605575 )). First, the torque-driven Stokes flow around a superhydrophobic cylinder with two unequal no-shear menisci and two equal solid portions is solved in detail. It is then shown how that analysis generalizes, in a natural way, to a cylinder with M no-shear menisci between M solid portions with full exposition given of the case of M = 3 equal solid portions. A further generalization to flow around a superhydrophobic cylinder with an N -fold rotationally symmetric patterning with M menisci in each 2 π / N sector is made. Torque-driven superhydrophobic cylinders with a no-shear pattern devoid of any rotational symmetry are shown to swim on circular trajectories with formulas for the radius and cylinder angular velocity on these trajectories derived here as functions of the no-shear pattern geometry. The M = 1 case of a ‘Janus’ superhydrophobic cylinder having one meniscus and one solid portion can be solved completely explicitly.

Radiation Pattern Analysis and Phase Shifter for Base Station Mobile Communication Circular Array Antenna at 900MHz Frequency by Using 4NEC2X Software

Background: This paper presents the utilization of phase shifters to manipulate and control the radiation patterns in Uniform Circular Array (UCA) antennas. UCAs, known for their 360-degree coverage and symmetrical radiation patterns, are enhanced by incorporating phase shifters, enabling dynamic beam steering and pattern shaping. Materials and Methods: A uniform circular antenna array operating at 900 GHz frequency has been intended for use in base stations using 4NEC2X simulation software. Results: A single-element dipole antenna having a 2.14 dBi gain is used as a base for constructing a uniform 0.5 λ spacing circular array. The number of elements gradually increased from 2 to 12, raising the gain to 12.3 dBi. HPBW decreased both in vertical and horizontal plans from 80o to 60o and 360o to 20o respectively this implies that the circular array antenna's directivity is enhanced. The eight-element array beam scanning was performed from 0o to 360o without any distortion in radiation pattern, gain, and directivity, contradictory with the linear array. Conclusions: The studied case and simulation output illustrate the impact of the element numbers and phase shifter configurations on properties of the radiation pattern of the uniform circular array can be obtained when increasing the number of elements, the gain increases too and scanning the main beam without any change and distortion

Graphene-Based Dual-Band Metasurface Absorber with High Frequency Ratio.

In this paper, we propose a novel dual-band metasurface absorber with a high frequency ratio based on graphene. By carefully designing a centrally symmetrical graphene pattern and positioning it on a glass medium, while utilizing ITO as a ground, the metasurface absorber achieves remarkable high frequency ratio microwave absorption. Specifically, this metasurface absorber exhibits two distinct resonance points at 3.7 GHz and 14 GHz, with an impressive frequency ratio over 3.5. It achieves over 90% absorption efficiency in the frequency ranges of 3.5-4.5 GHz and 13.5-14.5 GHz, highlighting its capability to effectively absorb microwaves across widely spaced frequency bands. Furthermore, the metasurface absorber demonstrates optical transparency and polarization insensitivity, adding to its versatility and potential applications. The measured results of the fabricated prototype validate its design and potential for practical use.

Walking on different inclines affects gait symmetry differently in the anterior-posterior and vertical directions: implication for future sensorimotor training

A symmetric gait pattern in humans reflects near-identical movement in bilateral limbs during walking. However, little is known about how gait symmetry changes on different inclines. This study aimed to address this knowledge gap using the central pattern generator and internal model hypotheses. Eighteen healthy young adults underwent five 2-minute walking trials (inclines of +15%, +8%, 0%, −8%, and −15%). Dependent variables included step time, step length, step width, maximum heel clearance, time to peaks of maximum heel clearance, their corresponding coefficients of variation (CV), and respective symmetry indices (SI). Significant differences were observed in SI of step length (p = .022), step length variability (p < .001), step width variability (p =.001), maximum heel clearance (p < .001), and maximum heel clearance variability (p = .049). Compared to level walking, walking at −8% and −15% inclines increased SI of step length (p = .011, p = .039 respectively) but decreased SI of maximum heel clearance (p = .025, p = .019 respectively). These observations suggested that incline walking affected gait symmetry differently, possibly due to varied internal models used in locomotion. Downhill walking improved vertical gait symmetry but reduced anterior-posterior symmetry compared to level walking. Downhill walking may be a preferable rehabilitation protocol for enhancing gait symmetry, as it activates internal model controls. Even slight downhill inclines could increase active control loading, beneficial for the elderly and those with impaired gait.

Fast and Efficient Drone Path Planning Using Riemannian Manifold in Indoor Environment

This paper introduces an innovative dual-path planning algorithm rooted in a topological three-dimensional Riemannian manifold (T3DRM) to optimize drone navigation in complex environments. It seamlessly integrates strategies for both discrete and continuous obstacles, employing spherical navigation for the former and hyperbolic paths for the latter. Serving as a transformative tool, the T3DRM facilitates efficient path planning by transitioning between discrete and continuous domains. In uncertain environments with unpredictable obstacle positions, our methodology categorizes these positions as discrete or continuous based on their distribution patterns. Discrete obstacles exhibit random distributions, while continuous obstacles display symmetrical patterns with continuity. Leveraging topological metrics, the T3DRM efficiently classifies these patterns for effective path planning. The findings of this research demonstrate the efficiency of path planning based on classified obstacle positions, enabling swift and efficient drone navigation. This research introduces a pioneering application of a T3DRM, accelerating drone navigation in uncertain environments through a dual approach that simultaneously transforms navigation in primal and dual domains. By enabling spherical and hyperbolic navigation concurrently, the T3DRM offers a comprehensive solution to discrete and continuous path planning challenges. The proposed approach can be used for various indoor applications, especially for warehouse management, surveillance and security, navigation in complex structures, indoor farming, site inspection, healthcare facilities, etc.

Ab initio calculations of anomalous seniority breaking in the πg9/2 shell for the N = 50 isotones

We performed ab initio valence-space in-medium similarity renormalization group (VS-IMSRG) calculations based on chiral two-nucleon and three-nucleon interactions to investigate the anomalous seniority breaking in the neutron number N=50 isotones: 92Mo, 94Ru, 96Pd, and 98Cd. Our calculations well reproduced the measured low-lying spectra and electromagnetic E2 transitions in these nuclei, supporting partial seniority conservation in the first πg9/2 shell. Recent experiments have revealed that, compared to the symmetric patterns predicted under the conserved seniority symmetry, the 41+→21+E2 transition strength in 94Ru is significantly enhanced and that in 96Pd is suppressed. In contrast, the 61+→41+ and 81+→61+ transitions exhibit the opposite trend. We found that this anomalous asymmetry is sensitive to subtle seniority breaking effects, providing a stringent test for state-of-the-art nucleon-nucleon interactions and nuclear models. We analyzed the anomalous asymmetry using VS-IMSRG calculations across various valence spaces. Our ab initio results suggest that core excitations of both proton and neutron across the Z=50 shell are ascribed to the observed anomalous seniority breaking in the N=50 isotones.

A Unified Hardware Design for Multiplication, Division, and Square Roots Using Binary Logarithms

Multiplication, division, and square root operations introduce significant challenges in digital signal processing (DSP) systems, traditionally requiring multiple operations that increase execution time and hardware complexity. This study presents a novel approach that leverages binary logarithms to perform these operations using only addition, subtraction, and shifts, enabling a unified hardware implementation—a marked departure from conventional methods that handle these operations separately. The proposed design, involving logarithm and antilogarithm calculations, exhibits an algebraically symmetrical pattern that further optimizes the processing flow. Additionally, this study introduces innovative log-domain correction terms specifically designed to minimize computation errors—a critical improvement over existing methods that often struggle with precision. Compared to standard hardware implementations, the proposed design significantly reduces hardware resource utilization and power consumption while maintaining high operational frequency.

Acoustic wave propagation in depth-evolving sound-speed field using the lattice Boltzmann method

This study investigates the propagation of sound waves within deep-sea low-sound-speed channels using the lattice Boltzmann method, with a key focus on the influence of depth-dependent sound speed on wave propagation. The depth-variable sound speed condition is realized through the incorporation of an external force proportional to the density gradient. After the model verification, investigations into the two-dimensional spreading of sound sources reveal that the depth-dependent sound speed curves the wave propagation. When source depths differing from the low-sound-speed channel, wave paths deviate due to contrasting speeds above and below. When the sound source is situated within the low-sound-speed channel, waves exhibit converging patterns. The simulations also detail the total reflection behavior of sound waves. When the incident angle falls exceeds the critical angle, the waves remain intact within the low-sound-speed channel, thereby enabling the preservation of high amplitude acoustic signals even at remote locations. The subsequent simulations of sound wave propagation around obstacles demonstrate that the low-sound-speed channel also exhibits better signal transmission capabilities in the presence of obstacles. In a uniform sound speed environment, acoustic wave propagation around a submarine exhibits a symmetric pattern. By contrast, under depth-evolving speed conditions, submarines operating at various depths manifest distinct propagation characteristics, such as asymmetric wave propagation during shallow diving, as well as wave attenuation or even silencing when cruising within low-sound-speed channels. These findings underscore the profound implications of depth-evolving sound speed on underwater acoustic signal detection and transmission.

The White Matter Fiber Tract Deforms Most in the Perpendicular Direction During In Vivo Volunteer Impacts.

White matter (WM) tract-related strains are increasingly used to quantify brain mechanical responses, but their dynamics in live human brains during invivo impact conditions remain largely unknown. Existing research primarily looked into the normal strain along the WM fiber tracts (i.e., tract-oriented normal strain), but it is rarely the case that the fiber tract only endures tract-oriented normal strain during impacts. In this study, we aim to extend the invivo measurement of WM fiber deformation by quantifying the normal strain perpendicular to the fiber tract (i.e., tract-perpendicular normal strain) and the shear strain along and perpendicular to the fiber tract (i.e., tract-oriented shear strain and tract-perpendicular shear strain, respectively). To achieve this, we combine the three-dimensional strain tensor from the tagged magnetic resonance imaging with the diffusion tensor imaging (DTI) from an open-access dataset, including 44 volunteer impacts under two head loading modes, i.e., neck rotations (N = 30) and neck extensions (N = 14). The strain tensor is rotated to the coordinate system with one axis aligned with DTI-revealed fiber orientation, and then four tract-related strain measures are calculated. The results show that tract-perpendicular normal strain peaks are the largest among the four strain types (p < 0.05, Friedman's test). The distribution of tract-related strains is affected by the head loading mode, of which laterally symmetric patterns with respect to the midsagittal plane are noted under neck extensions, but not under neck rotations. Our study presents a comprehensive invivo strain quantification toward a multifaceted understanding of WM dynamics. We find that the WM fiber tract deforms most in the perpendicular direction, illuminating new fundamentals of brain mechanics. The reported strain images can be used to evaluate the fidelity of computational head models, especially those intended to predict fiber deformation under noninjurious conditions.

The Impact of Population Shrinkage on Economic Resilience in Mountain Cities: A Case Study of Guizhou Province, China

With the recent changes in population structure and continuous urbanization, the degree of population shrinkage in mountain cities has increased, especially under the impact of the COVID-19 epidemic, and the economic development of such mountain cities has become a prominent issue. The epidemic has not only exposed the vulnerability of these cities to economic development but also aggravated the negative impact of population contraction, bringing about new challenges and pressures related to regional population development and economic resilience. This change has become an important topic in the study of mountain cities. Therefore, taking Guizhou Province as a case study, this work applies the population change rate, the entropy method, and a mediation effect model to study the spatiotemporal evolution of population shrinkage and economic resilience, and it explores how population shrinkage influences economic resilience. The results reveal the following: (1) Few counties experienced population shrinkage in Guizhou Province from 2013 to 2017, indicating a sporadic distribution pattern, whereas the degree of population shrinkage increased rapidly from 2018 to 2022, revealing an east–west symmetrical distribution pattern, with Guiyang city located on the central axis. (2) There are significant regional differences in the spatial distribution of the level of economic resilience between the two periods. Under the impact of COVID-19, from 2019 to 2022, although the overall level of economic resilience increased, the level of resilience in most counties tended to decrease. (3) Regarding the mediating effect, population shrinkage affected the level of economic resilience through general public budget expenditure, foreign trade investment, new urban employment, and GDP. The abovementioned findings are helpful for providing theoretical support and empirical guidance for the sustainable development of mountain cities in the face of population contraction, economic challenges, and promoting regional coordination.

Tailoring macrostructure and texture in bobbin-tool friction stir weld via manipulation of deformation behaviour of plasticised metal during welding enabled by modifying tool profile

Bobbin-tool friction stir welding is a variant of friction stir welding with high process flexibility that has garnered considerable attention from the community. The reliability of the weld is sensitive to the macrostructure and texture of the stir zone, which must be carefully tailored. The macrostructure of the stir zone is governed by the refill behaviour of the plasticised metal associated with the bobbin-tool; refill occurs preferentially near the upper and lower shoulders, creating a triangular gap at the mid-thickness level that is subsequently closed by the confluence of the layered refilling plasticised metal from the upper and lower levels. Volumetric defects easily develop in this triangular confluence region because the symmetrical confluence of the layered refilling metal has the inherent characteristic of limited intermixing. The visual appearance of the triangular region, featuring limited voiding, was improved by tapering the stirring probe. This modification reduced the volume of displaced metal, leaving a smaller gap to be refilled during welding. Concurrently, the symmetrical confluence pattern was altered to an asymmetrical pattern, which enhanced the intermixing of the layered refilling metal from the upper and lower levels and promoted gap closure. For defect-free welds, macroscopic deformation inhomogeneity under tensile loading was observed due to the presence of a strong basal texture in the stir zone. The texture was scattered by disrupting the regular shear deformation pattern in the stir zone, which was achieved by modifying the tool profile. The activation capability of both basal slip and extension twinning among various local regions across the stir zone was substantially reduced through texture tailoring, resulting in more homogeneous tensile deformation. Consequently, elongation was enhanced by 66 %. This study highlights an easy-to-perform and generic strategy that can improve the quality of bobbin-tool friction stir welds.

Effects of romosozumab combined with routine therapy on pain relief, disease progression and adverse reactions in patients with postmenopausal osteoporosis: a systematic review and meta-analysis.

Postmenopausal osteoporosis (PMOP) increases fracture risk in women. Though traditional treatments are slow to act, combining romosozumab with conventional therapy shows promise. Despite its growing use, studies on effectiveness are limited. This study aims to systematically evaluate the combined therapy's impact on pain relief, disease progression, and adverse reactions in PMOP patients. Databases including PubMed, EMBASE, ScienceDirect, and the Cochrane Library were searched from their inception to September 2023 to identify randomized controlled trials (RCTs) evaluating the role of romosozumab in PMOP. Random or fixed effect models were employed for statistical analysis. Two reviewers independently assessed the quality of the included studies and extracted the data. The meta-analysis was conducted using RevMan 5.4 software. Six RCTs with a total sample size of 17,985 cases were included. The incidence of vertebral fractures was compared and analyzed after 12 and 24 months of treatment. Romosozumab significantly reduced the incidence of vertebral fractures at 24 months (OR = 0.36; 95% CI: 0.35-0.52) but not at 12 months (OR = 0.39; 95% CI: 0.14-1.05). It was also associated with a decreased incidence of nonvertebral fractures (OR = 0.79; 95% CI: 0.66-0.94) and clinical fractures at 24 months (OR = 0.70; 95% CI: 0.59-0.82) compared to standard therapy. Romosozumab demonstrated a significant improvement in percentage change in bone mineral density (BMD) [mean difference (MD) = 10.38; 95% CI: 4.62-16.14] and in hip joint BMD (MD = 4.24; 95% CI: 2.92-5.56). There was no notable difference in adverse reactions compared to standard care (p > 0.05). Funnel plots displayed a predominantly symmetrical pattern, suggesting no evidence of publication bias in the selected literature. Combining romosozumab with conventional therapy effectively treats PMOP, significantly reducing vertebral, non-vertebral, and clinical fractures while increasing BMD in the hip, femoral neck, and lumbar spine. However, further high-quality studies are needed for validation.

Therapeutic Garden Design at Marzoeki Mahdi Hospital

Abstract Mental disorders is characterized by clinically significant disturbance in a person’s cognition, emotional regulation, or behavior. Dr. H. Marzoeki Mahdi Hospital (RSMM) is one of the mental hospitals that provides psychosocial rehabilitation services. Psychosocial rehabilitation consists of various activities to hone the patient’s ability so that they live independently. One of the activities is vocational and occupational therapy. The hospital garden is a necessity in the patient rehabilitation process so it needs to be designed to make it can be utilized optimally. The research objectives are to identify and analyze activities, user needs, potentials and constraints on the site; determine the design concept and create a therapeutic garden design for psychosocial rehabilitation at Marzoeki Mahdi Hospital. This research uses a descriptive method with stages such as preparation, research and analysis, concept and design. Data was collected through surveys, interviews, questionnaires and literature studies. The proposed design is a therapeutic garden to support psychosocial rehabilitation. The design concept applies one of patients rehabilitaion activities, namely socializing, which is depicted in a circular pattern and rehabilitation activities carried out repeatedly are depicted in a repetitive pattern. In addition, a symmetrical pattern is also applied which illustrates organized life and firmness. Based on this pattern, spaces are designed to support rehabilitation activities, namely the welcome area, active therapy area, passive therapy area and parking area.

Brain MRI findings in paediatric genetic disorders associated with white matter abnormalities.

To describe the specific brain magnetic resonance imaging (MRI) patterns of the paediatric genetic disorders associated with white matter abnormalities in Northern Finland. In this retrospective population-based longitudinal study, brain MRI scans accumulated from 1990 to 2019 at Oulu University Hospital, Finland, were assessed. Inclusion criteria were defined as leukodystrophies or genetic diseases with significant white matter abnormalities that did not meet the criteria for leukodystrophy, at least one brain MRI, and age under 18 years at diagnosis. A total of 83 patients (48 males, 35 females) were found with 52 different diseases. The median age at the time of the brain MRI was 22 months (interquartile range [IQR] = 46 months). In 72 (87%) of the children, brain MRIs revealed abnormal findings, including cerebral white matter abnormalities (n = 49, 59%), brainstem signal abnormalities (n = 28, 34%), thinning of the corpus callosum (n = 30, 36%), delayed myelination (n = 11, 13%), and permanent hypomyelination (n = 9, 11%). Symmetrical and bilateral white matter signal patterns of the brain MRI should raise suspicion of genetic disorders when the clinical symptoms are compatible. This study illustrates brain imaging patterns of childhood-onset genetic disorders in a population in Northern Finland and improves the diagnostic accuracy of rare genetic disorders.

A model reduction framework of flow maldistribution and mitigation strategy for parallel flow field based polymer exchange membrane fuel cell

Mitigating flow maldistribution plays a crucial role in next-generation industry-used parallel-based flow field design for polymer exchange membrane fuel cells (PEMFCs), especially for larger-size cells and higher current density. In this study, a model reduction framework is proposed to alleviate flow maldistribution among parallel gas flow channels and associated computational burden. The gas flow features and electrochemical kinetics of four mitigation strategies including expanded manifold, partially porous media, dot matrix, and partially narrow structures are investigated in detail. The results indicate that the fuel cell model and a fluid flow model without the reactions show similar maldistribution features among parallel channels. The observed flow maldistribution can be effectively reduced by mitigating designs. Expanding the manifold space significantly alleviates the vortex impeding the gas entry to individual channel inlet, and the inlet exhibits better flow uniformity and pressure drop in the direction perpendicular to the channel than in the parallel to. The fully-inserted and manifold-inserted porous media methods present symmetrical quadratic-shaped flow patterns among channels, while that of the partially-inserted porous media inside channels is unsymmetrical. Additionally, the concentration loss with a partially narrowed design decreases by 44.7%, 12.9%, and 24.2% compared with the expanded manifold, partial porous media, and dot matrix designs at 1.8 A cm−2 owing to better flow uniformity and mass transport. These model framework and mitigation strategies are valuable for designing future high-performance industrial PEMFCs.