RESUMEN

Smartphones, with embedded accelerometers, may be a viable method to monitor gait variability in the free-living environment. However, measurements estimated using smartphones must first be compared to known quantities to ensure validity. This study assessed the validity and reliability of smartphone-derived gait measures compared to a gold-standard footswitch system during overground walking. Seventeen adults completed three 8-minute overground walking trials during 3 separate visits. The stride time series was calculated as the time difference between consecutive right heel contact events within the footswitch and smartphone-accelerometry signals. Linear (average stride time, stride time standard deviation, and stride time coefficient of variation) and nonlinear (fractal scaling index, approximate entropy, and sample entropy) measures were calculated for each stride time series. Bland-Altman plots with 95% limits of agreement assessed agreement between systems. Intraclass correlation coefficients assessed reliability across visits. Bland-Altman plots revealed acceptable limits of agreement for all measures. Intraclass correlation coefficients revealed good-to-excellent reliability for both systems, except for fractal scaling index, which was moderate. The smartphone system is a valid method and performs similarly to gold-standard research equipment. These findings suggest the development and implementation of an inexpensive, easy-to-use, and ubiquitous telehealth instrument that may replace traditional laboratory equipment for use in the free-living environment.

RESUMEN

Thermal conduction for electronic devices has attracted extensive attention in light of the development of 5G communication. Thermally conductive materials with high thermal conductivity and extensive mechanical flexibility are extremely desirable in practical applications. However, the construction of efficient interconnected conductive pathways and continuous conductive networks is inadequate for either processing or actual usage in existing technologies. In this work, spherical copper nanoparticles (S-CuNPs) and urchin-inspired fractal-growth CuNPs (U-CuNPs), thermally conductive metal fillers induced by ionic liquids, were fabricated successfully through the electrochemical deposition method. Compared to S-CuNPs, the U-CuNPs shows larger specific surface contact area, thus making it easier to build a continuous conductive pathway network in the corresponding U-CuNPs/liquid silicone rubber (LSR) thermally conductive composites. The optimal loading of CuNP fillers was determined by evaluating the rheological performance of the prepolymer and the mechanical properties and thermal conductivity performances of the composites. When the filler loading is 150 phr, the U-CuNPs/LSR produces optimal mechanical properties (e.g., tensile strength and modulus), thermal conductivity (above 1000% improvement compared to pure LSR), and heating/cooling efficiency. The enhanced thermal conductivity of U-CuNPs/LSR was also confirmed through the finite element analysis (FEA) overall temperature distribution, indicating that U-CuNPs with larger specific surface contact areas exhibit more advantages in forming a continuous network in composites than S-CuNPs, making U-CuNPs/LSR a promising and competitive alternative to traditional flexible thermally interface materials.

Asunto(s)

RESUMEN

Subsurface substance migration in the fractured rock aquifer is mainly controlled by fractures, and immiscible fluid-fluid displacement in fractures is important to many geophysical processes and engineering activities. Using a fracture-visualization system, we present the qualitative and quantitative assessment of fracture geometry associated with fluid movement and distribution in the rough fracture. Based on fracture geometry and statistical analysis, we first conducted a quantitative study of fracture surface roughness and aperture distribution. Then, fractal dimensions of displacement front and residual oil distribution were determined by image processing procedures. Influenced by wettability and micro-scale roughness, at the end of the displacement, residual oil saturation of molded sample is lower (6.45%-25.74%), and displacement pattern is more uniform, indicating that displacement effect is better. Due to smaller differences in residual oil saturation (9.08%) under different injection directions, the impact of wettability on the displacement process is greater than that of anisotropic roughness. Additionally, the fractal dimension of the displacement front increased under low injection rates initially but decreased when the rate was increased later. Overall, visualized temporal monitoring of experimental images enabled us to provide a preliminary assessment of the impact of anisotropic roughness and the material constituting the fracture wall on invading fluid saturation and the fractal dimension of the displacement front under various injection rates.

Asunto(s)

RESUMEN

PURPOSE: Ultrasound imaging has emerged as a promising cost-effective and portable non-irradiant modality for the diagnosis and follow-up of diseases. Motion analysis can be performed by segmenting anatomical structures of interest before tracking them over time. However, doing so in a robust way is challenging as ultrasound images often display a low contrast and blurry boundaries. METHODS: In this paper, a robust descriptor inspired from the fractal dimension is presented to locally characterize the gray-level variations of an image. This descriptor is an adaptive grid pattern whose scale locally varies as the gray-level variations of the image. Robust features are then located based on the gray-level variations, which are more likely to be consistently tracked over time despite the presence of noise. RESULTS: The method was validated on three datasets: segmentation of the left ventricle on simulated echocardiography (Dice coefficient, DC), accuracy of diaphragm motion tracking for healthy subjects (mean sum of distances, MSD) and for a scoliosis patient (root mean square error, RMSE). Results show that the method segments the left ventricle accurately ( DC = 0.84 ) and robustly tracks the diaphragm motion for healthy subjects ( MSD = 1.10 mm) and for the scoliosis patient ( RMSE = 1.22 mm). CONCLUSIONS: This method has the potential to segment structures of interest according to their texture in an unsupervised fashion, as well as to help analyze the deformation of tissues. Possible applications are not limited to US image. The same principle could also be applied to other medical imaging modalities such as MRI or CT scans.

RESUMEN

Introduction: Electrical stimulation of the brain has shown promising prospects in treating various brain diseases. Although biphasic pulse stimulation remains the predominant clinical approach, there has been increasing interest in exploring alternative stimulation waveforms, such as sinusoidal stimulation, to improve the effectiveness of brain stimulation and to expand its application to a wider range of brain disorders. Despite this growing attention, the effects of sinusoidal stimulation on neurons, especially on their nonlinear firing characteristics, remains unclear. Methods: To address the question, 50 Hz sinusoidal stimulation was applied on Schaffer collaterals of the rat hippocampal CA1 region in vivo. Single unit activity of both pyramidal cells and interneurons in the downstream CA1 region was recorded and analyzed. Two fractal indexes, namely the Fano factor and Hurst exponent, were used to evaluate changes in the long-range correlations, a manifestation of nonlinear dynamics, in spike sequences of neuronal firing. Results: The results demonstrate that sinusoidal electrical stimulation increased the firing rates of both pyramidal cells and interneurons, as well as altered their firing to stimulation-related patterns. Importantly, the sinusoidal stimulation increased, rather than decreased the scaling exponents of both Fano factor and Hurst exponent, indicating an increase in the long-range correlations of both pyramidal cells and interneurons. Discussion: The results firstly reported that periodic sinusoidal stimulation without long-range correlations can increase the long-range correlations of neurons in the downstream post-synaptic area. These results provide new nonlinear mechanisms of brain sinusoidal stimulation and facilitate the development of new stimulation modes.

RESUMEN

ADHD is a prevalent childhood behavioral problem. Early ADHD identification is essential towards addressing the disorder and minimizing its negative impact on school, career, relationships, as well as general well-being. The present ADHD diagnosis relies primarily on an emotional assessment which can be readily influenced by clinical expertise and lacks a basis of objective markers. In this paper, an innovative IoT based ADHD detection is proposed using an EEG signal. To the input EEG signal, the min-max normalization technique is processed. Features are extracted as the subsequent step, where improved fuzzy feature, in which the entropy is estimated to increase the effectiveness of recognizing the vector along with, fractal dimension, wavelet transform and non-linear features are extracted. Also, proposes the new hybrid PUDMO algorithm to select the optimal features from the extracted feature set. Subsequently, the selected features are fed to the proposed hybrid detection system that including IDBN and LSTM classifier to detect whether it is ADHD or not. Further, the weights of both classifiers are tuned optimally as per the hybrid PUDMO algorithm to enhance the detection performance. The PUDMO achieved an accuracy of 0.9649 in the best statistical metric, compared to the SLO's 0.8266, SOA's 0.8201, SMA's 0.8060, BRO's 0.8563, DE's 0.8083, POA's 0.8537, and DMOA's 0.8647, respectively. Thus, the assessments and detection help the clinicians to take appropriate decision.

RESUMEN

Interparticle pore space and vugs are two different scales of pore space in vuggy porous media. Vuggy porous media widely exists in carbonate reservoirs, and the permeability of this porous media plays an important role in many engineering fields. It has been shown that the change of effective stress has important effects on the permeability of vuggy porous media. In this work, a fractal permeability model for vuggy porous media is developed based on the fractal theory and elastic mechanics. Besides, a Monte Carlo simulation is also implemented to obtain feasible values of permeability. The proposed model can predict the elastic deformation of the fractal vuggy porous media under loading stress, which plays a crucial role in the variations of permeability. The predicted permeability data based on the present fractal model are compared with experimental data, which verifies the validity of the present fractal permeability model for vuggy porous media. The parameter sensitivity analysis indicates that the permeability of stress-sensitivity vuggy porous media is related to the capillary fractal dimension, capillary fractal tortuosity dimension, Young's modulus, and Poisson's ratio.

RESUMEN

The aim of the present study is to investigate the complexity and stability of human ambulation and the implications on robotic prostheses control systems. Fourteen healthy individuals participate in two experiments, the first group run at three different speeds. The second group ascended and descended stairs of a five-level building block at a self-selected speed. All participants completed the experiment with seven inertial measurement units wrapped around the lower body segments and waist. The data were analyzed to determine the fractal dimension, spectral entropy, and the Lyapunov exponent (LyE). Two methods were used to calculate the long-term LyE, first LyE calculated using the full size of data sets. And the embedding dimensions were calculated using Average Mutual Information (AMI) and the False Nearest Neighbor (FNN) algorithm was used to find the time delay. Besides, a second approach was developed to find long-term LyE where the time delay was based on the average period of the gait cycle using adaptive event-based window. The average values of spectral entropy are 0.538 and 0.575 for stairs ambulation and running, respectively. The degree of uncertainty and complexity increases with the ambulation speed. The short term LyEs for tibia orientation have the minimum range of variation when it comes to stairs ascent and descent. Using two-way analysis of variance we demonstrated the effect of the ambulation speed and type of ambulation on spectral entropy. Moreover, it was shown that the fractal dimension only changed significantly with ambulation speed.

RESUMEN

The heightened prevalence of respiratory disorders, particularly exacerbated by a significant upswing in fatalities due to the novel coronavirus, underscores the critical need for early detection and timely intervention. This imperative is paramount, possessing the potential to profoundly impact and safeguard numerous lives. Medically, chest radiography stands out as an essential and economically viable medical imaging approach for diagnosing and assessing the severity of diverse Respiratory Disorders. However, their detection in Chest X-Rays is a cumbersome task even for well-trained radiologists owing to low contrast issues, overlapping of the tissue structures, subjective variability, and the presence of noise. To address these issues, a novel analytical model termed Exponential Pixelating Integral is introduced for the automatic detection of infections in Chest X-Rays in this work. Initially, the presented Exponential Pixelating Integral enhances the pixel intensities to overcome the low-contrast issues that are then polar-transformed followed by their representation using the locally invariant Mandelbrot and Julia fractal geometries for effective distinction of structural features. The collated features labeled Exponential Pixelating Integral with dually characterized fractal features are then classified by the non-parametric multivariate adaptive regression splines to establish an ensemble model between each pair of classes for effective diagnosis of diverse diseases. Rigorous analysis of the proposed classification framework on large medical benchmarked datasets showcases its superiority over its peers by registering a higher classification accuracy and F1 scores ranging from 98.46 to 99.45 % and 96.53-98.10 % respectively, making it a precise and interpretable automated system for diagnosing respiratory disorders.

RESUMEN

In this paper, we collected the individual tree point cloud data in the plots of Larix olgensis plantations with different thinning intensities in Mengjiagang Forest Farm, applied the fractal analysis theory to extract box dimensions (Db) on MATLAB platform, and characterized the structural complexity of L. olgensis. We assessed the effect of different thinning intensities and tree attributes on the structural complexity of L. olgensis. The results showed significant differences in L. olgensis Db between control (CK: 1.68±0.07), low and medium intensity thinning (T1, T2, T3: 1.74±0.07), and high intensity thinning (T4: 1.81±0.06), which indicated that the thinning intensity increased tree structural complexity. For trunk attribute, the diameter at breast height and tree height was significantly positively correlated with Db, while the height-to-diameter ratio was significantly negatively correlated with Db. For canopy attribute, crown volume, surface area, projected area, and crown diameter was significantly positively correlated with Db. Hegyi competition index was significantly negatively correlated with Db in the control and low-moderate-intensity thinning treatments, but not significantly correlated with Db in the high-intensity thinning treatment. It indicated that thinning influenced L. olgensis structural complexity, with trunk attribute and canopy attribute as the main drivers of L. olgensis structural complexity.

Asunto(s)

RESUMEN

The objective of this study is to investigate the dynamic mechanical properties of coal and rock under deep water conditions. The research employs an enhanced Split Hopkinson Pressure Bar (SHPB) testing system. Five sets of dynamic impact experiments were conducted on coal samples under varying loading conditions to analyse the changes in dynamic strength, energy dissipation, fractal dimension and other characteristics of coal samples under different water content states were analyzed. The experimental results demonstrate that: (1) Under specific strain rate conditions, the dynamic strength of saturated coal samples is lower than that of natural coal samples. As the strain rate gradually increases, the bonding force generated by free water and the Stefan effect jointly act, and the peak strength of saturated coal samples under high strain rate loading conditions is higher than that of natural coal samples. (2) Under certain strain rate conditions, the absorption energy of saturated coal samples is approximately 10% to30% lower than that of natural coal samples, and deformation hysteresis phenomenon occurs in natural coal samples, thereby improving the dynamic strength of natural coal samples relative to saturated coal samples; (3) The fractal dimension of saturated coal samples with a specific strain rate under three-dimensional dynamic static combination loading is higher than that of natural coal samples, and the percentage of small particle coal samples with debris is higher than that of natural coal samples; Finally, based on the HJC model, some coal samples were selected to simulate the coal rock failure characteristics during the triaxial loading process using ANSYS/LS-DYNA, and their stress-strain curves and failure morphology diagrams were obtained. The discrepancy between the numerical simulation and the experimental results was less than 10%, thereby further elucidating and corroborating the coal failure process and dynamic mechanical characteristics.

RESUMEN

To investigate the effects of high temperature and carbon fiber-bar reinforcement on the dynamic mechanical properties of concrete materials, a muffle furnace was used to treat two kinds of specimens, plain and carbon fiber-bar reinforced concrete, at high temperatures of 25, 200, 400 and 600 °C. Impact compression tests were carried out on two specimens after high-temperature exposure using a Hopkinson pressure bar (SHPB) test setup combined with a high-speed camera device to observe the crack extension process of the specimens. The effects of high temperature and carbon fiber-bar reinforcement on the peak stress, energy dissipation density, crack propagation and fractal dimension of the concrete were analyzed. The results showed that the corresponding peak strengths of the plain concrete specimens at 25, 200, 400, and 600 °C were 88.37, 93.21, 68.85, and 54.90 MPa, respectively, and the peak strengths after the high-temperature exposure first increased slightly and then decreased rapidly. The mean peak strengths corresponding to the carbon fiber-bar reinforced concrete specimens after high-temperature action at 25, 200, 400, and 600 °C are 1.13, 1.13, 1.21, and 1.19 times that of plain concrete, respectively, and the mean crushing energy consumption densities are 1.27, 1.31, 1.73, and 1.59 times that of plain concrete, respectively. The addition of carbon fiber-bar reinforcement significantly enhanced the impact resistance and energy dissipation of the concrete structure, and the higher the temperature was, the more significant the increase. An increase in temperature increases the number of crack extensions and width, and the high tensile strength of the carbon fiber-bar reinforcement and the synergistic effect with the concrete material reduce the degree of crack extension in the specimen. The fractal dimension of the concrete ranged from 1.92 to 2.68, that of the carbon fiber-bar reinforced concrete specimens ranged from 1.61 to 2.42, and the mean values of the corresponding fractal dimensions of the plain concrete specimens after high-temperature effects at 25, 200, 400, and 600 °C were 1.19, 1.21, 1.10, and 1.11 times those of the fiber-reinforced concrete specimens, respectively. The incorporation of carbon fiber-bar reinforcement reduces the degree of rupture and fragmentation of concrete under impact loading and improves the safety and stability of concrete structures.

RESUMEN

The pore structure of coal plays a key role in the effectiveness of gas extraction. Conventional hydraulic fracturing techniques have limited success in modifying the pore structure using clean fracturing fluid (CFF), and the stimulating effects of ultrasonic can enhance the effectiveness of CFF in modifying coal pore structures. To research the effects of ultrasonic stimulation on the pore structure of medium to high-rank coal when using CFF, this study employed mercury intrusion porosimetry (MIP) and low-temperature nitrogen adsorption (LT-N2A) methods to analyze the changes in pore structures after cooperative modification. The results indicate that the pore volume and surface area of medium to high rank coal exhibit an increase and followed by a decrease with increasing Ro,max values, while the average pore diameter and permeability demonstrate a decrease and followed by an increase with Ro,max. Although there are some variations in the results of MIP and LT-N2A analysis for different pore size ranges, the overall findings suggest that ultrasonic stimulation in conjunction with CFF effectively alters the coal pore structure. The most significant improvement was observed in coking coal, where pore volume increased by 22%, pore area decreased by 11% and tortuosity decreased by 47%. The improvement of lean coal is the smallest, the pore volume increases by about 7%, and the surface area decreases by about 14%. It is found that the modification of coal pore volume is mainly concentrated in transition pores and macropores. These research outcomes provide valuable insights into the application of ultrasonic technology in coalbed gas extraction.

RESUMEN

Reservoir nearshore areas are influenced by both terrestrial and aquatic ecosystems, making them sensitive regions to water quality changes. The analysis of basin landscape hydrological features provides limited insight into the spatial heterogeneity of eutrophication in these areas. The complex characteristics of shoreline morphology and their impact on eutrophication are often overlooked. To comprehensively analyze the complex relationships between shoreline morphology and landscape hydrological features, with eutrophication, this study uses Danjiangkou Reservoir as a case study. Utilizing Landsat 8 OLI remote sensing data from 2013 to 2022, combined with a semi-analytical approach, the spatial distribution of the Trophic State Index (TSI) during flood discharge periods (FDPs) and water storage periods (WSPs) was obtained. Using Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP), explained the relationships between landscape composition, landscape configuration, hydrological topography, shoreline morphology, and TSI, identified key factors at different spatial scales and validated their reliability. The results showed that: (1) There is significant spatial heterogeneity in the TSI distribution of Danjiangkou Reservoir. The eutrophication levels are significant in the shoreline and bay areas, with a tendency to extend inward only during the WSPs. (2) The importance of landscape composition, landscape configuration, hydrological topography, and shoreline morphology to TSI variations during the FDPs are 25.12 %, 29.6 %, 23.09 %, and 22.19 % respectively. Besides shoreline distance, the Landscape Shape Index (LSI) and Hypsometric Integral (HI) are the two most significant environmental variables overall during the FDPs. Forest and grassland areas become the most influential factors during the WSPs. The influence of landscape patterns and hydrological topography on TSI varies at different spatial scales. At the 200 m riparian buffer zone, the increase in cropland and impervious areas significantly elevates eutrophication levels. (3) Morphology complexity, shows a noticeable threshold effect on TSI, with complex shoreline morphology increasing the risk of eutrophication.

RESUMEN

With regard to deep mining in metal mines, an investigation into the failure mode of deep fractured rock masses and their corresponding acoustic emission signal characteristics is conducted via uniaxial compression tests. Subsequently, a fractal damage renormalization group mechanical model is developed to explain the behavior of those fractured rock masses. Employing the bonded block model (BBM) numerical simulation method, fracture process in synthetic rock samples is analyzed, thereby validating the efficacy of the mechanical model. The numerical simulations highlight the critical role of fractures expansion in underlying the deterioration of rock mass strength. As the peak load decreases, the fracture fractal dimension increases, leading to a significant 14.2% reduction in compressive strength accompanied by an approximate 8.7% rise in average fracture fractal dimension. A comparative analysis of tetrahedral and voronoi block synthetic rock samples reveals the tetrahedral block samples exhibit a superior ability to depict the fracture behavior of fractured rock masses. Specifically, they offer a more accurate simulation of acoustic emission characteristics and failure modes. Furthermore, variations in the fracture fractal dimension with respect to the hole defect's position are observed, with the maximum value occurring along the vertical axis of the hole defect. This observation underscores the potential utility of visually monitoring deep rock fracture dynamics as an effective mean for quantitatively evaluating fracture damage and strength degradation in deep rock formations.

RESUMEN

The main cause of acute coronary syndrome (ACS) is plaque rupture and thrombus formation. However, it has not been fairly successful to identify vulnerable plaque to rupture using conventional parameters of intravascular imaging modalities. Fractal analysis is one of the mathematical models to examine geometrical features of picture image using a specific parameter called as fractal dimension (FD) which suggests geometric complexity of the image. This study examined FD of the optical coherence tomography (OCT)-derived images of the culprit plaque in patients with ACS vs stable angina pectoris (SAP) to evaluate the feasibility of FD for identifying vulnerable coronary plaques prone to provoke ACS distinguished from stable plaques only provoking SAP. We examined 65 cases (34 ACS patients, 31 SAP patients) in which the culprit lesion was imaged by OCT before percutaneous coronary intervention in patients with ACS and SAP. The culprit plaque lesion in the ACS group had a significantly larger mean lipid arc (203.8 ± 39.4° vs 152.3 ± 34.5°, p < 0.001) and a larger lipid plaque length (12.6 ± 5.1 mm vs 7.7 ± 2.7 mm, p < 0.001) and a thinner fibrous cap thickness (75.3 ± 22.3 µm vs 134.8 ± 53.2 µm, p < 0.001) than those in the SAP group. The prevalence of OCT-derived macrophage infiltration (Mph) in the entire culprit coronary vessel as well as that of the OCT-derived thin-cap fibroatheroma (TCFA) at the culprit lesion were significantly greater in the ACS group than those in the SAP group, respectively (Mph: 61.8% vs 35.5%, p = 0.048; TCFA: 44.1% vs 6.4%, p < 0.001). The FD of culprit plaque in the ACS group was significantly greater than in the SAP group (2.401 ± 0.073 vs 2.341 ± 0.051, p < 0.001). In multivariate regression analysis, the presence of Mph was a significant determinant of FD (regression coefficient estimate 0.049, CI 0.018-0.079, p = 0.002). The FD of OCT-derived image of culprit coronary plaque in the ACS group was significantly greater than that in the SAP group, indicating that the culprit plaque in ACS were structurally more complex. Therefore, fractal analysis of coronary OCT images might be clinically useful for identifying coronary plaques prone to provoke ACS.

RESUMEN

Our article explores a variety of modern research techniques employed in neuroanatomy and neurophysiology. We highlight the use of computer technologies, image analysis methods, and innovative approaches that expand our understanding of anatomical structures. The techniques we discuss include fractal analysis, the Pickworth method, scanning microscopy, and advanced computer image processing systems. Fractal analysis, in particular, offers a unique perspective on brain structures and functions and is a key tool in neuroanatomical research. We also focus on its application in neuroanatomical studies, particularly in cases of Alzheimer's disease and epilepsy. These modern research methods not only enhance our knowledge but also have significant clinical potential. Their use in diagnosing neurological diseases like Alzheimer's and epilepsy promises faster and more accurate diagnoses. We emphasize the combination of multiple methods for improved quality of anatomical structure imaging.

RESUMEN

Although ischemia increases the abundance of plasminogen activator inhibitor-1 (PAI-1), its source and role in the ischemic brain remain unclear. We detected PAI-1-immunoreactive cells with morphological features of reactive astrocytes in the peri-ischemic cortex of mice after an experimentally-induced ischemic lesion, and of a chimpanzee that suffered a naturally-occurring stroke. We found that although the abundance of PAI-1 increases 24 hours after the onset of the ischemic injury in a non-reperfusion murine model of ischemic stroke, at that time-point there is no difference in astrocytic reactivity and the volume of the ischemic lesion between wild-type (Wt) animals and in mice either genetically deficient (PAI-1-/-) or overexpressing PAI-1 (PAI-1Tg). In contrast, 72 hours later astrocytic reactivity and the volume of the ischemic lesion were decreased in PAI-1-/- mice and increased in PAI-1Tg animals. Our immunoblottings and fractal analysis studies show that the abundance of astrocytic PAI-1 rises during the recovery phase from a hypoxic injury, which in turn increases the abundance of glial fibrillary acidic protein (GFAP) and triggers morphological features of reactive astrocytes. These studies indicate that cerebral ischemia-induced release of astrocytic PAI-1 triggers astrocytic reactivity associated with enlargement of the necrotic core.

RESUMEN

Fractal assembly technology enables scalable construction of organic crystal patterns for emerging nanoelectronics and optoelectronics. Here, a polymer-templating assembly strategy is presented for centimeter-scale patterned growth of fractal organic crystals (FOCs). These structures are formed by drop-coating perylene solution directly onto a gelatin-modified surface, resulting in the formation of crisscross fractal patterns. By adjusting the tilt angle of the template, the morphology of FOCs can be effectively controlled, with the diameter distribution of each level branch ranging from hundreds to ten micrometers. The planar FOC device exhibits flexible photoreception and photosynaptic capabilities, with a high specific detectivity of 1.35 × 109 Jones and paired-pulse facilitation (PPF) index of 104%, withstanding a 0.5 cm bending radius during bending test. These findings present a reliable route for large-scale assembly of flexible organic crystalline materials toward neuromorphic electronics.

RESUMEN

Purpose: To reveal the causality between retinal vascular density (VD), fractal dimension (FD), and brain cortex structure using Mendelian randomization (MR). Design: Cross-sectional study. Participants: Genome-wide association studies of VD and FD involving 54 813 participants from the United Kingdom Biobank were used. The brain cortical features, including the cortical thickness (TH) and surface area (SA), were extracted from 51 665 patients across 60 cohorts. Surface area and TH were measured globally and in 34 functional regions using magnetic resonance imaging. Methods: Bidirectional univariable MR (UVMR) was used to detect the causality between FD, VD, and brain cortex structure. Multivariable MR (MVMR) was used to adjust for confounding factors, including body mass index and blood pressure. Main Outcome Measures: The global and regional measurements of brain cortical SA and TH. Results: At the global level, higher VD is related to decreased TH (ß = -0.0140 mm, 95% confidence interval: -0.0269 mm to -0.0011 mm, P = 0.0339). At the functional level, retinal FD is related to the TH of banks of the superior temporal sulcus and transverse temporal region without global weighted, as well as the SA of the posterior cingulate after adjustment. Vascular density is correlated with the SA of subregions of the frontal lobe and temporal lobe, in addition to the TH of the inferior temporal, entorhinal, and pars opercularis regions in both UVMR and MVMR. Bidirectional MR studies showed a causation between the SA of the parahippocampal and cauda middle frontal gyrus and retinal VD. No pleiotropy was detected. Conclusions: Fractal dimension and VD causally influence the cortical structure and vice versa, indicating that the retinal microvasculature may serve as a biomarker for cortex structural changes. Our study provides insights into utilizing noninvasive fundus images to predict cortical structural deteriorations and neuropsychiatric disorders. Financial Disclosures: The author(s) have no proprietary or commercial interest in any materials discussed in this article.