Dense Network Research Articles

Social Network Density Mediates the Association Between Problematic Social Media Use and Depressive Symptoms

Previous studies have indicated that problematic social media use (PSMU) is positively related to depressive symptoms. However, the potential mechanisms underlying this relationship are not well understood. For example, prior research found that depressive symptoms are related to one’s social network structure, such as network size and density. Therefore, we examined whether one’s social network size and density mediate the relationship between PSMU and depressive symptoms. We conducted an in-person survey to collect measures of PSMU, social network size and density, and depressive symptoms. Our analysis showed that there was a positive relationship between PSMU and depressive symptoms, which was mediated by social network density but not size. Specifically, the greater one’s PSMU, the less dense their social network, and the greater their depressive symptoms. Our research suggests that PSMU may affect how individuals maintain their social connections with others, which may affect mental health. Implications were discussed.

Оценка развитости узлов и тесноты связи креативной сети в региональной локализации

The relevance of the study is due to the need to obtain comprehensive ideas about the specifics of regional localization of creative industries, the functioning of which is based on close connections between organizations that form a creative product and organizations that promote the distribution of a creative product. The article aims to assess the development of nodes and the connectivity density of a creative network within a regional localization context. The research methodology includes the use of statistical data processing methods, as well as comparative and correlation analysis. By examining the connectivity between nodes in the creative network of organizations operating in the performing arts sector and those in the field of artistic creation, the study concludes that the connections are predominantly strong. This is attributed to the high degree of regional localization among organizations producing and promoting creative products. These findings highlight the significant role of regional development tools in fostering this creative network, particularly through the implementation of organizational and financial support measures.

Formation of thermal-induced microgels from soy protein hydrolysates: Effects of selective proteolysis on glycinin/β-conglycinin

This study explored the impact of selective proteolysis on the formation of thermally induced soy protein microgels. Glycinin hydrolysate (GH) and β-conglycinin hydrolysate (CH) were obtained by subjecting soy protein isolate to selective proteolysis for different hydrolysis time (10–90 min), as confirmed by SDS-PAGE. In the early stages of hydrolysis, free sulfhydryl, surface hydrophobicity, storage modulus (G′) and loss modulus (G″) of GH and CH increased, which enhanced their gelling potential. However, as hydrolysis time increased, the gel properties of the hydrolysates progressively weakened. Structural characterization of microgels revealed that GH yielded microgels with smaller particle sizes and coarser and relatively dispersed granular structures, while CH resulted in microgels with lower potential values, smoother surfaces, and lumps resembling strand-like formations. Analysis of the structure and intermolecular force of microgels showed that the microgel formed by the GH gradually tended to be disordered, whereas the secondary structure of microgels formed by CH showed lower random coil content, resulting in a dense gel network aggregated through disulfide bonding, hydrophobic interactions and hydrogen bonding as demonstrated by frequency-dependent storage moduli measurements. Overall, this study presents a thorough characterization of microgels and shows that they can be tailored by selective proteolysis, which enables controlling the β-conglycinin/glycinin ratio of soy protein.

Development and characterization of tilapia skin collagen-inulin oleogel as the potential fat substitute in beef patty formulations

The effects of inulin addition, olive oil content, and ultrasonic treatment on the rheological, texture, and structural properties of collagen-based oleogels were investigated in this study. Furthermore, the fat substitution ability of the oleogel in low-fat beef patties was evaluated. Initially, a uniform and dense network cross-linked structure was found when the ratio of collagen to inulin complex was 1:5. The oleogel sample exhibited good stability and oil binding ability with an additional amount of 50 % olive oil. Ultrasonic treatment improved the stability of the oleogel structure in all samples. Additionally, the addition of inulin reduced cooking loss in beef patties. Beef patties prepared at a 50 % fat substitution level showed physical properties that were the least different from those of pure adipose tissue (control group), which could significantly reduce the content of saturated fatty acids and improve the storage stability of beef patties. This study provided guidance for the application of collagen-inulin oleogel in food processing.

Formation of Conjugated Polymer Monolayer Networks on Water Surface and Nonlinear Charge Transport

AbstractMaterial‐networked conduction paths provide nonlinear electronic properties, which are essential components of computing and physically mimic the brain. In this study, the formation of conjugated polymer monolayer networks and their nonlinear charge transport is demonstrated. Poly(3‐hexylthiophene) (P3HT) monolayer networks doped with 2,3,5,6‐tetrafluoro‐7,7,8,8‐tetracyanoquinodimethane (F4TCNQ) is fabricated using the co‐spread method with an amphiphilic liquid crystal molecule at the air–water interface. Atomic force microscopy and Ultraviolet–visible–near‐infrared absorption spectroscopy measurements reveal the network surface morphologies and doped electronic states. The correlation between the nonlinear electronic characteristics and network structures of the P3HT/F4TCNQ monolayer networks is further systematically investigated through current–voltage and voltage–time measurements for various doping levels, network densities, and numbers of transferred layers. The current–voltage characteristics of the P3HT/F4TCNQ monolayer network device with a simple two‐terminal structure exhibit nonlinear and ohmic conduction behavior, which depend strongly on the network density and geometric dimension (number of transferred layers). It is concluded that the nonlinear properties arise from the limited and unique network of 2D conduction passes. This study highlights the unique features of conducting polymer monolayer networks, paving the way for neuromorphic device applications including conjugated semiconducting polymer‐based material reservoirs with controllable nanostructures.

Mouse polyomavirus infection induces lamin reorganisation.

The nuclear lamina is a dense network of intermediate filaments beneath the inner nuclear membrane. Composed of A-type lamins (lamin A/C) and B-type lamins (lamins B1 and B2), the nuclear lamina provides a scaffold for the nuclear envelope and chromatin, thereby maintaining the structural integrity of the nucleus. A-type lamins are also found inside the nucleus where they interact with chromatin and participate in gene regulation. Viruses replicating in the cell nucleus have to overcome the nuclear envelope during the initial phase of infection and during the nuclear egress of viral progeny. Here, we focused on the role of lamins in the replication cycle of a dsDNA virus, mouse polyomavirus. We detected accumulation of the major capsid protein VP1 at the nuclear periphery, defects in nuclear lamina staining and different lamin A/C phosphorylation patterns in the late phase of mouse polyomavirus infection, but the nuclear envelope remained intact. An absence of lamin A/C did not affect the formation of replication complexes but did slow virus propagation. Based on our findings, we propose that the nuclear lamina is a scaffold for replication complex formation and that lamin A/C has a crucial role in the early phases of infection with mouse polyomavirus.

Neural network architecture of a mammalian brain

Connectomics research is making rapid advances, although models revealing general principles of connectional architecture are far from complete. Our analysis of 106 published connection reports indicates that the adult rat brain interregional connectome has about 76,940 of a possible 623,310 axonal connections between its 790 gray matter regions mapped in a reference atlas, equating to a network density of 12.3%. We examined the sexually dimorphic network using multiresolution consensus clustering that generated a nested hierarchy of interconnected modules/subsystems with three first-order modules and 157 terminal modules in females. Top-down hierarchy analysis suggests a mirror-image primary module pair in the central nervous system's rostral sector (forebrain-midbrain) associated with behavior control, and a single primary module in the intermediate sector (rhombicbrain) associated with behavior execution; the implications of these results are considered in relation to brain development and evolution. Bottom-up hierarchy analysis reveals known and unfamiliar modules suggesting strong experimentally testable hypotheses. Global network analyses indicate that all hubs are in the rostral module pair, a rich club extends through all three primary modules, and the network exhibits small-world attributes. Simulated lesions of all regions individually enabled ranking their impact on global network organization, and the visual path from the retina was used as a specific example, including the effects of cyclic connection weight changes from the endogenous circadian rhythm generator, suprachiasmatic nucleus. This study elucidates principles of interregional neuronal network architecture for a mammalian brain and suggests a strategy for modeling dynamic structural connectivity.

Transparent mechanism of salted egg (white) hierarchically and synergistically driven by NaCl, NaOH and thermal treatment: Based on empirical data and molecular simulation

Currently, it is a challenge that the yolk in salted preserved egg tends to preserved egg yolk due to extreme NaOH treatment. Therefore, NaCl, NaOH and thermal were successfully used to prepare a new translucent salted quail egg (T-SQE), which combined advantages of preserved egg white with transparent appearance and salted egg yolk with unique texture and odour. Moreover, transparency of opaque gel (Transmittance: 0.09 %) subjected to NaCl and thermal was demonstrated to be improved under the synergistic effect of NaOH (8.55 %) via empirical data and molecular simulation. The disordered and dense network in opaque T-SQE induced by NaCl and thermal tended to form an ordered, porous and transparent structure in presence of NaOH, with more immobilized water that was poorly bonded to protein, larger radius of gyration and lower hydrophobic interaction. This research provides new insight into understanding the influence of hierarchy and synergism on transparency of egg products.

Neural network reconstruction of the left atrium using sparse catheter paths.

Catheter-based radiofrequency ablation for pulmonary vein isolation has become the first line of treatment for atrial fibrillation in recent years. This requires a rather accurate map of the left atrial sub-endocardial surface including the ostia of the pulmonary veins, which requires dense sampling of the surface and currently takes more than 10min. The focus of this work is to provide left atrial visualization early in the procedure to ease procedure complexity and enable further workflows, such as using catheters that have difficulty sampling the surface. We propose a dense encoder-decoder network with a novel regularization term to reconstruct the shape of the left atrium from partial data which is derived from simple catheter maneuvers. To train the network, we acquire a large dataset of 3D atria shapes and generate corresponding catheter trajectories, from which traversed point clouds are obtained. Once trained, we show that the suggested network can sufficiently approximate the atrium shape based on a given trajectory. We compare several network solutions for the 3D atrium reconstruction. We demonstrate that the solution proposed produces realistic visualization using partial acquisition within a 3-min time interval using human clinical cases.

Context-Aware DGCN-Based Ship Formation Recognition in Remote Sensing Images

Ship detection and formation recognition in remote sensing have increasingly garnered attention. However, research remains challenging due to arbitrary orientation, dense arrangement, and the complex background of ships. To enhance the analysis of ship situations in channels, we model the ships as the key points and propose a context-aware DGCN-based ship formation recognition method. First, we develop a center point-based ship detection subnetwork, which employs depth-separable convolution to reduce parameter redundancy and combines coordinate attention with an oriented response network to generate direction-invariant feature maps. The center point of each ship is predicted by regression of the offset, target scale, and angle to realize the ship detection. Then, we adopt the spatial similarity of the ship center points to cluster the ship group, utilizing the Delaunay triangulation method to establish the topological graph structure of the ship group. Finally, we design a context-aware Dense Graph Convolutional Network (DGCN) with graph structure to achieve formation recognition. Experimental results on HRSD2016 and SGF datasets demonstrate that the proposed method can detect arbitrarily oriented ships and identify formations, attaining state-of-the-art performance.

Sustained-release effect of eggshell powder microcapsules on lavender essential oil

Eggshells are rich in Ca2+ and organic compounds, which can be taken as coupling agents for sustained-release materials. Essential oils are widely applied due to their excellent volatility, but poor sustained-release stability has limited their development. The study aimed to develop a novel eggshell powder (EP) sustained-release microcapsule, providing a new approach to protect the active ingredients of Lavender essential oil (LEO), and investigated the reasons for EP to regulate protein-polysaccharide microcapsule structure. Experimental results showed when the addition ratio of EP and Whey protein (WPI) was 1: 3, the dosage of LEO was 25%, the microcapsule displayed smooth and porous spherical structure. XRD and FT-IR indicated that a dense and orderly network structure was formed via the cross-linking reaction between eggshell powder and wall materials, which induced protein and polysaccharide to form special spherical hollow sustained-release shell structure through the calcium bridge (-COO-Ca-COO-), then achieved the sustained-release effect on LEO.

A Method by using predefined windows to improve the InSAR atmospheric correction model based on GNSS ZTD and its horizontal delay gradient

ABSTRACT Correcting the signal delay caused by electromagnetic waves passing through the atmosphere is crucial in InSAR. Atmospheric delays are significant enough to obscure the true deformation signal, making it difficult for InSAR to detect deformation signals at the millimetre scale. Therefore, it is imperative to mitigate atmospheric interference appropriately. To interpolate sparse GNSS networks and capture small-scale atmospheric delays, this study presents an enhanced method for constructing an atmospheric correction model based on GNSS Zenith Total Delay (ZTD) and its horizontal gradient, which is integrated within a predefined window. To validate the effectiveness of the improved model, we applied it to 27 InSAR short-time and short-spatial baseline unwrapped interferograms. These interferograms are composed of images observed by the Sentinel-1A satellite from January to December 2022 in Southern California. The corrective impact of the enhanced model is also compared against that of the initial inversion model and GACOS to confirm the viability of the approach. Results of the evaluation, considering root mean square error (RMSE), standard deviation (STD), and the correlation between phase and elevation, indicate that our enhanced method reduces correction errors by 35.10%, 20.05%, and 63.52%, respectively, compared to GACOS. Compared to the initial model, these reductions are 58.19%, 57.23%, and 4.34%, respectively. By integrating the outcomes from all three evaluation methods and analysing the corrected images, our enhanced model effectively resolves the inconsistency in correction effects resulting from the spatial variability of atmospheric delay. Moreover, incorporating the horizontal gradient in the inversion method has proven effective in capturing small-scale atmospheric delay signals. This highlights the feasibility and benefits of our enhanced model.

Nano-enhancing polymer as a fluid loss additive for ultra-high temperature cementing

The exploitation of ultra-deep oil and gas wells is accompanied by technical problems of ultra-high temperature, especially in the cementing process, which will directly deactivate many admixtures. By in-situ polymerization of the monomers and Nano-SiO2 to improve the temperature resistance, the resulting high temperature resistant composite polymer slurry system can show high efficiency in reducing fluid loss under the high temperature environment of 240℃. The synthesis of the high temperature resistant polymer was characterized by IR and 1H NMR, and its physicochemical properties were analyzed by DLS, GPC, TEM and Cryo-SEM. The synergistic mechanism of Nano-SiO2 on the high temperature resistance of the polymer was revealed by TGA. Using DLS, SEM and EDS, a series of cement slurry systems were used to analyze and compare the effect on fluid loss reduction of different adding methods of Nano-SiO2 in cement slurry at high temperature. The results showed that the grafted Nano-SiO2 polymer maintained effective adsorption capacity at high temperature without degradation, and its fluid loss reduction ability was significantly improved at high temperature. The high temperature resistant composite polymer is strongly adsorbed between cement particles to form a dense and robust spatial network structure. The CSH gel structure is optimized by the particle size gradation of the system, so as to obtain a dense cement cake, which is expected to be applied in high temperature cementing.

Myosin-I synergizes with Arp2/3 complex to enhance the pushing forces of branched actin networks.

Class I myosins (myosin-Is) colocalize with Arp2/3 complex-nucleated actin networks at sites of membrane protrusion and invagination, but the mechanisms by which myosin-I motor activity coordinates with branched actin assembly to generate force are unknown. We mimicked the interplay of these proteins using the "comet tail" bead motility assay, where branched actin networks are nucleated by the Arp2/3 complex on the surface of beads coated with myosin-I and nucleation-promoting factor. We observed that myosin-I increased bead movement efficiency by thinning actin networks without affecting growth rates. Myosin-I triggered symmetry breaking and comet tail formation in dense networks resistant to spontaneous fracturing. Even with arrested actin assembly, myosin-I alone could break the network. Computational modeling recapitulated these observations, suggesting myosin-I acts as a repulsive force shaping the network's architecture and boosting its force-generating capacity. We propose that myosin-I leverages its power stroke to amplify the forces generated by Arp2/3 complex-nucleated actin networks.

Connecting the dots: Network structures of internalizing and functional symptoms in a population-based cohort

ObjectiveComorbidities between internalizing disorders (IDs) and functional disorders (FDs) are well-documented, indicating shared pathways. However, their symptom-level relationships have been largely unexplored. This exploratory study employs a network approach to investigate symptoms of major depressive disorder (MDD), generalized anxiety disorder (GAD), myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), fibromyalgia (FM), and irritable bowel syndrome (IBS) to identify bridge symptoms explaining comorbidity between the two domains. MethodsWe used cross-sectional data on 72,919 adult subjects from the Lifelines Cohort Study, a Dutch general population sample. A total of 38 symptoms representing diagnostic criteria of IDs and FDs were assessed with validated questionnaires. Network models were estimated using eLasso, based on the Ising model, to identify bridge symptoms. The Network Comparison Test (NCT) was used to test whether there were differences in network structure and strength across sex and age. ResultsSymptoms were moderately connected, with a network density of 52.7%. ID and FD symptoms clustered in their respective domains, but were connected through the bridge symptoms, fatigue, difficulty concentrating, trouble sleeping, and unrefreshing sleep. Fatigue and difficulty concentrating had the most connections, associated with 86.6% and 78.9% of the other symptoms, respectively. NCTs indicated no differences in network connectivity between females versus males or younger versus older adults (>50 years). ConclusionsID and FD symptoms are moderately interconnected. Bridge symptoms displaying strong connections to multiple disorders may play a central role in the mechanisms underpinning the comorbidity between IDs and FDs.

Programmable soft DNA hydrogels stimulate cellular endocytic pathways and proliferation

Hydrogels are pivotal in tissue engineering, regenerative medicine, and drug delivery applications. Existing hydrogel platforms are not easily customizable and often lack precise programmability, making them less suited for 3D tissue culture and programming of cells. DNA molecules stand out among other promising biomaterials due to their unparalleled precision, programmability, and customization. In this study, we introduced a palette of novel cellular scaffolding platforms made of pure DNA-based hydrogel systems while improving the shortcomings of the existing platforms. We showed a quick and easy one step synthesis of DNA hydrogels using thermal annealing based on sequence specific hybridization strategy. We also demonstrated the formation of multi-armed branched supramolecular scaffolds with custom mechanical stiffness, porosity, and network density by increasing or decreasing the number of branching arms. These mechanically tuneable DNA hydrogels proved to be a suitable suitable platform for modulating the physiological processes of retinal pigment epithelial cells (RPE1). In-vitro studies showed dynamic changes at multiple levels, ranging from a change in morphology to protein expression patterns, enhanced membrane traffic, and proliferation. The soft DNA hydrogels explored here are mechanically compliant and pliable, thus excellently suited for applications in cellular programming and reprogramming. This research lays the groundwork for developing a DNA hydrogel system with a higher dynamic range of stiffness, which will open exciting avenues for tissue engineering and beyond.

Thermally Conductive Polydimethylsiloxane-Based Composite with a Three-Dimensional Vertically Aligned Thermal Network Incorporating Hexagonal Boron Nitride Nanosheets and Nanodiamonds.

Thermal interface materials play a pivotal role in efficiently transferring heat from heating devices to thermal management components, thereby reducing the risk of component degradation due to overheating. In this study, we propose a strategy for enhancing the out-of-plane thermal conductivity (TC) of composite materials by fabricating a three-dimensional (3D) thermal network within a polydimethylsiloxane (PDMS) matrix. Specifically, the composite material was designed to incorporate a dense thermal network comprising hexagonal boron nitride nanosheets (BNNSs) and nanodiamonds (NDs). The fabrication process commenced with the preparation of BNNSs through liquid-phase exfoliation, followed by the creation of a 3D BNNSs-NDs/polyimide aerogel thermal framework using a unidirectional solidification ice templating method and subsequent heat treatment. Vacuum impregnation and curing were then employed to finalize the production of the 3D BNNSs-NDs/PDMS composite material. Characterization analyses indicated that the addition of NDs filled the voids between BNNSs, leading to the densification of the thermal framework pore walls and the establishment of additional thermal pathways. Impressively, with concentrations of BNNSs and NDs of 17.99 and 7.71 wt %, respectively, the out-of-plane TC of the 3D BNNSs-NDs/PDMS composite material reached 1.623 W m-1 K-1, marking notable enhancements of 754.21% and 256.70% compared to those of pure PDMS and composites prepared via direct blending with randomly distributed BNNSs and NDs, respectively. Furthermore, the 3D BNNSs-NDs thermal framework improved the compressive strength and the dimensional stability of the composite material. Finite element simulations additionally confirmed the synergistic improvement of the TC achieved through the combination of BNNSs and NDs, demonstrating that the 3D BNNSs-NDs/PDMS composite material displayed superior heat conduction and a greater density of thermal pathways compared to those of its counterparts, including 3D BNNSs/PDMS and 3D NDs/PDMS composite materials. In summary, this work presents a strategy for enhancing the out-of-plane TC of polymer-based composite materials by incorporating vertically aligned thermal networks.

SRARDA: A lightweight adaptive residual dense attention generative adversarial network for image super-resolution

Image super-resolution (SR) is the task of inferring a high resolution (HR) image from one/multiple single low resolution (LR) input(s). Traditional networks are evaluated by pixel-level metrics such as Peak-Signal-to-Noise Ratio (PSNR) etc., which do not always align with human perception of image quality. They often produce excessively smooth images that lack high-frequency texture and appear unnatural. Therefore, in this paper, we propose a lightweight adaptive residual dense attention generative adversarial network (SRARDA) for image SR. Firstly, our generator adopts the residual in residual (RIR) structure but redesigns the basic module. By using dynamic residual connection (ARC) to dynamically adjust the importance of residual and main paths, we design a novel adaptive residual dense attention block (ARDAB) that enhances the feature extraction capability of the generator. In addition, we build a high-frequency filtering unit (HFU) to extract more high-frequency features from the LR space. Finally, to fully utilize the discriminator, we use WGAN to compute the difference between the HR image and the reconstructed image. Experiments demonstrate that SRARDA effectively addresses the issue of excessive smoothing in reconstructed images, while also enhancing visual quality.

Sodium alginate supramolecular nanofibers in synergy with surface crack engineering to prepare tough and highly sensitive hydrogels

Soft and wet hydrogels often struggle to achieve both toughness and high sensitivity simultaneously, limiting their usefulness in flexible devices. To tackle this challenge, we devised a strategy that combines supramolecular sodium alginate nanofibers, utilizing Zr4+ as physical crosslinkers, with surface crack engineering via the micro-phase separation of polyaniline, to create a physically and chemically dual crosslinked polyacrylamide (PAM)/sodium alginate (SA)/polyaniline (PANI) hydrogel with exceptional toughness and high sensitivity. Owing to the supramolecular sodium alginate nanofibers, the dual crosslinked hydrogel exhibited a tensile strength of 0.391 MPa, an elongation at break of 568.9 %, and a toughness of 1.020 MJ/m3. The in-situ polymerized polyaniline layer, confined within the dense network, introduced micro-cracks onto the hydrogel surface, resulting in a high gauge factor of 11.4 for the fabricated hydrogel. Furthermore, integrating this hydrogel into a triboelectric nanogenerator transformed it into self-powered sensors capable of detecting external forces and generating various signals without power supply. These findings suggest that the developed hydrogel held great potential in diverse fields, including human motion detection, human-machine interaction, and wearable electronic devices.

Natural Language Processing to assess structure and complexity of system requirements

AbstractThe development process of a system is shaped by numerous variables that influence its progress and outcome. As a result, complexity can increase throughout the development process, potentially leading to negative consequences, which makes the management of complexity critical. Most development processes begin with the definition of needs and requirements. In this paper, the authors present a novel approach that enables the automated extraction of structure from requirements specifications. The approach uses Natural Language Processing to elicit three structural layers from a set of requirements, which are subsequently analyzed using metrics to assess complexity. In a case study, the approach is demonstrated using a set of 79 requirements, within which 246 individual entities are identified. These entities and the requirements are structured and analyzed using network density and spectral entropy. The metrics allow for interpretation and insight generation, such as identifying an increase in the number of potentially problematic loops. The approach achieved a detection and structural accuracy of over 98% in the given case study and is planned to be expanded with future cases.