Network Structure Research Articles

Polarized social media networks: a novel approach to quantify the polarization level of individual users

ABSTRACT This paper presents a novel methodology to quantify users’ polarization within social media networks, focusing on network structure instead of content. We model polarized networks as directed graphs, collecting users’ follower/following connections data, and propose a simple algorithm to compute a Connectivity Score for each node in sub-graphs associated with identified contrary groups of the polarized network. Our method has several advantages: it relies solely on users’ follower/following connections data, which is objective, often public and easy to obtain. Also, this input data is usually memory-efficient, unlike the input data of content-based methods which may require a whole corpus. The algorithm's performance is assessed through application to Twitter's 116th Congressmembers network, comparing against a content analysis method: Sentiment score (using VADER), and two political behavior-based methods: Ideology score (based on co-sponsorship frequency) and Roll Call score (based on bill-voting similarity). The results demonstrate that: (1) users’ choice of connections on the social media can represent polarization behavior; (2) a meaningful correlation between Connectivity Scores and Ideology or Roll Call Scores shows that the political behavior of users is reflected in their social media connections; (3) Democrats’ Twitter following behavior and their bill-voting and bill co-sponsorship behavior (represented by Roll Call and Ideology) are all significantly more correlated than that of Republicans. We believe applying our algorithm in conjunction with other methods is a valuable contribution resulting in more comprehensive analysis of the social media polarization space.

Multimarket contact and price discrimination

Theoretical and empirical studies have demonstrated that multimarket contact facilitates tacit collusion and higher prices. In this study, we examine how multimarket contact influences firms' use of price discrimination. First, we demonstrate theoretically that additional coordination can lead firms to increase or reduce price discrimination, depending on underlying market factors. Next, we empirically investigate price differentials in the U.S. airline industry, employing a new instrumental variables approach to isolate the effects of multimarket contact. We find that multimarket contact results in larger differences in fare levels amongst consumers purchasing higher-priced tickets but smaller fare differences amongst those purchasing lower-priced tickets. Consistent with our theoretical model, multimarket contact more strongly influences fares on less concentrated routes. The findings emphasize the importance of accounting for cross-market or network structure as well as within-market structure when modeling market conduct and performance or when evaluating potential merger effects.

Get back: analysing the impact of the COVID-19 pandemic on the Lowlands festival

ABSTRACT This article investigates the impact of COVID-19 through a case study of Lowlands, a music festival in the Netherlands. Analysing how the Cultural and Creative Sector is affected by and recovering from the COVID-19 pandemic has received growing attention among academics. This article contributes to this body of research by analysing the structure and dynamics of the production network of Lowlands, combining elements of the Global Production Network approach and Grabher’s project-ecology framework. With this novel lens, we unravel the embeddedness of linkages between Lowlands’ management and its partners. We conclude by showing how these strong ties are simultaneously Lowlands’ strength and weakness, as recursive collaborations create an efficient production process but are also prone to fall away in crises like COVID-19, leaving the management without reliable alternatives. However, bonds of trust and friendship motivate and underpin mutual support, and therefore form a crucial key for its resilience.

A network analysis of catatonia symptoms across diagnoses

BackgroundCatatonia, as a transdiagnostic construct, manifests across various psychiatric and non-psychiatric conditions. Understanding how symptom variations impact the catatonia construct and differ across primary diagnoses (schizophrenia, bipolar disorder, unipolar depression, and neurological/metabolic/immunological condition) is essential to refine diagnostic and therapeutic approaches. This study aims to compare the symptom networks and centrality measures of these diagnoses. MethodsWe conducted a network analysis using Bush-Francis Catatonia Rating Scale (BFCRS) data from 118 patients, examining centrality measures and network comparisons across the four primary diagnostic groups. ResultsIn the general catatonia network, the three most central symptoms identified were Excitement (1.462), Perseveration (1.456), and Impulsivity (1.332). While the overall structure of the catatonia networks did not show significant differences between diagnoses in terms of symptom connections and centrality, variations in centrality measures were observed among the different networks. ConclusionsThe study reinforces the notion of catatonia as an independent syndrome relatively to psychiatric or non-psychiatric diagnoses. However, the variation in centrality of symptoms across different primary diagnoses provides critical insights that could aid clinicians in tailoring diagnostic and therapeutic strategies. Future research should further explore these relationships and develop more refined approaches to managing catatonia.

ODCS-YOLO detection algorithm for rail surface defects based on omni-dimensional dynamic convolution and context augmentation module

Abstract To solve the problems of easy miss and false detection on rail surface defects caused by small size, dense target, and high similarity between features and background, this paper proposed an improved detection algorithm in complex background. First, the conventional convolution of YOLOv5 backbone network is replaced with omni-dimensional dynamic convolution (ODConv), which improves the feature extraction capability of the network without increasing the computational cost; second, to improve the model's performance in detecting tiny objects, a two-layer context augmentation module(CAM) is introduced into the path aggregation network(PAN) structure; finally, the traditional non-maximum suppression(NMS) algorithm is replaced by the Soft-NMS algorithm in the network post-processing to reduce the false-alarm and miss-rate. The experimental results on the Railway Track Fault Detection public dataset show that the OD-YOLO (OD stands for ODConv) and C-PAN(CAM module is introduced into PAN) structures could achieve better performance in the same type of improved algorithms; compared with the baseline algorithm YOLOv5, the ODCS-YOLO (OD stands for ODConv, C stands for CAM, and S stands for Soft-NMS) algorithm improves the precision by 12.4%, the recall by 3.6%, the map50 by 8.6% and the GFLOPs is reduced by 0.6. Compared with seven classical object detection algorithms, the ODCS-YOLO algorithm achieves the highest detection accuracy, which makes it able to meet the real-time detection requirements of rail surface defects in real working conditions. The ODCS-YOLO model provides certain technical support for the defects detection and a new method for the detection of dense small objects.

Fabrication of ultra-precise flexible electrothermal film by direct-write printing porous graphene-Ag structure

In this study, graphene oxide (GO)‑silver nitrate (AgNO3) composite ink was prepared with stable printability, which could match the direct-write print technique for patterning GO-AgNO3 composite structure. Reduced graphene oxide (rGO)‑silver (Ag) porous structure could be obtained with a freeze-drying and gas phase reduction process. The rGO-Ag porous structure could reach a conductivity of 3.2 × 105 S/m through quantum penetration effect with the bridging action. Subsequently, polydimethylsiloxane (PDMS) encapsulated the rGO-Ag porous structure, and a special composite structure of PDMS/ rGO-Ag/PDMS films could be obtained by adjusting the wetting effect. PDMS provided a good tensile property and excellent bending resistance, and then a relative resistance changes within 5 % could be achieved after the number of 10,000 bending times. With the rGO-Ag porous structure compressed into a thinner film, an ultra-precise flexible electrothermal performance could be realized with the conductive network and flexible package structure. The surface temperature of fabricated composite film could reach 201.3 °C at the voltage of 7 V, within a heating time of 25 s, and maintaining the temperature for 1800 s. Meanwhile, the flexible electrothermal film could keep a stable temperature after 120 power on/power off cycles. Furthermore, the flexible electrothermal film also has a linear temperature control ability, which could carry out the linear temperature control with different temperature regions. At last, the ultra-precise flexible electrothermal film exhibits an excellent applying effect for the wrist hot compress, pipeline heating and window cleaning with uneven ice thickness. Therefore, the direct-write printed porous graphene-Ag structure presents a special property for fabricating ultra-precise flexible electrothermal film, which could provide a great research significance and application value in printing electronic structure and manufacturing electronic device.

Mechanism of Interconnected Pore Formation in High Internal Phase Emulsion-Templated Polymer.

High internal phase emulsion-templated polymer, named polyHIPE, has received widespread attention due to its great potential applications in many fields, such as separation, adsorption, heterogeneous catalysis, and sound absorption. The broad applicability is largely dependent on its adjustable opening structure. However, the question of why polyHIPE has an interconnected pore network structure is still to be discussed. Herein, different types (w/o, o/w, and o/o) of HIPEs are prepared and subsequently detected with laser scanning confocal microscopy (LSCM), and the polyHIPEs obtained by curing the HIPEs are characterized by SEM. The observations suggest that the interconnected pore formation is primarily due to the presence of the surfactant-rich phase in the film between the neighboring droplets in HIPE. The interconnected pores are generated by removal of the surfactant-rich domains in the postcuring procedure, and their sizes would be enlarged if the solubility of the surfactant in the continuous phase decreases in the curing stage.

Probing Viscoelastic Properties and Interfaces in High-Density Polyethylene Vitrimers at the Nanoscale Using Dynamic Mode Atomic Force Microscopy.

Vitrimers are a new class of heterogeneous polymers that combine the best features of thermosets with those of thermoplastics. The introduction of cross-links strongly changes the viscoelastic behavior of vitrimer materials. However, the characterization and understanding of the nanostructures and interfaces in vitrimers resulting from dynamic cross-linking formation remain a major challenge. Here, using dynamic modes of atomic force microscopy (AFM), namely intermodulation AFM (ImAFM) and AFM-based dynamic mechanical analysis (AFM-nDMA), local viscoelastic properties and interfaces at the nanoscale length of high-density polyethylene (HDPE) vitrimer materials are reported. ImAFM imaging in combination with the k-means clustering algorithm clearly reveals two distinct phases in the vitrimer system with highly different viscoelastic properties. AFM-nDMA further provides quantitative nanoviscoelastic properties at the nanoscale to confirm that there is a cross-linking-rich aggregation area forming a nanosize network structure in the cross-linking-poor matrix phase. The cross-linking-rich region shows a similar elastic modulus but much higher adhesion force measured by AFM compared to the cross-linking-poor HDPE matrix. Furthermore, the frequency influence on the local viscoelastic properties of HDPE vitrimer at the nanoscale was initially screened. The observed HDPE vitrimer nanostructures and viscoelastic properties at the nanoscale also provide explanations on the observed bulk HDPE vitrimer crystallinity decrease and dimensional stability increase compared to HDPE. Therefore, probing the viscoelastic properties and interfaces of HDPE vitrimer provides important insights into understanding of the correlations between the vitrimer nanostructure and the bulk mechanical and rheological behaviors.

Alpine meadow and alpine steppe plant-soil network in Qinghai-Tibet Plateau, China

Alpine meadow and alpine steppe are crucial ecosystem types in the Qinghai-Tibet Plateau. However, due to ecosystem fragility and human disturbance, the nutrient imbalance between plant and soil leads to grassland degradation. From a systematic perspective, there needs to be a comprehensive understanding of the plant and soil traits within these two ecosystem types. This study addressed this gap by constructing plant-soil trait networks for alpine meadow and alpine steppe, identifying bridge traits, and comparing the stability and distinctions of the two trait networks. The results demonstrated a significant difference in the distribution of network structure edge weights between the alpine meadow and steppe. In the network of alpine meadow, the soil organic carbon was responsible for linking plant and soil traits, exhibiting the highest impact. Conversely, the network of alpine steppe revealed an increasing negative correlation between plant and soil traits. The results of bridge traits agreed with the optimal distribution hypothesis. The bridge traits of the alpine meadow were aboveground traits (AGB or PlantC), while those of the alpine steppe were belowground traits (BGB and RootN). Based on our findings, different management measures could be taken. The alpine meadow could be primarily restored through natural processes, and climate warming would enhance its carbon sequestration capacity. The alpine steppe ecosystem exhibits low nitrogen availability, which could be augmented through fertilisation or the return of yak manure.

Nitrogen configuration modulation of porous graphitic carbon nanosheets for superior capacitive energy storage

Carbon nanosheets with layer-stacked porous structures and surface functionalized groups are beneficial for efficient ion storage in supercapacitor electrode materials, but achieving high cost-effectiveness and controllable surface groups remains a significant challenge. Herein, the biomass-derived chitosan and sodium alginate are selected as raw materials for self-assembly reaction with phytic acid as a cross-linking agent. The protonated chitosan and sodium alginate form a cross-linked network structure through hydrogen bonding and electrostatic adsorption, which is subsequently carbonized and activated to synthesize porous graphitic carbon nanosheets (PNPCN-X). PNPCN-X realizes an efficient distribution of porous and graphitic structures. It's noteworthy that phytic acid facilitates the fixation of N atoms, and various N configurations can be adjusted by altering the content of phytic acid. Optimized PNPCN-1.5 exhibits a high content of structurally stable pyridinic-N and graphitic-N configurations, which are confirmed to serve as active sites substantially augmenting the ion adsorption capacity through Density Functional Theory (DFT) calculations. Benefiting from its exceptional physicochemical properties, PNPCN-1.5 achieves 322 F g−1 as electrode materials in the three-electrode system, while the symmetrical supercapacitor assembled with EMIMBF4 electrolyte attains 56.29 W h kg−1. Furthermore, various kinetic analyses extensively elucidate its capacitance distribution characteristics and ion diffusion rates.

Au NPs modified Ni-B nanosheets/graphene oxide three-dimensional network as label-free electrochemical immunosensor for the detection of diethylstilbestrol

Three-dimensional (3D) network provide a promising platform for construction of high sensitive electrochemical immunosensor due to the benefits of high specific surface area and electron mobility. Herein, a sensitive label-free electrochemical immunosensor based on Au nanoparticles modified Ni-B nanosheets/graphene matrix was constructed to detect diethylstilbestrol (DES). The 3D network not only could increase the electron transport rate and surface area, but also could provide confinement area, which is conducive to increases the collision frequency with the active site. Moreover, Au NPs also have good biocompatibility, which is beneficial for ligating antibodies. Benefiting from the 3D network structure and Au collective effect, the electrochemical immunosensor possess sterling detection ability with wide linear response range (0.00038–150 ng/mL) and low detection limit (31.62 fg/mL). Moreover, the constructed immunosensor can also be extend to detect DES in Tap-water and river water. This work may provide a novel material model for the construction of high sensitive immunosensor.

ADP-Based Fault-Tolerant Control for Multiagent Systems With Semi-Markovian Jump Parameters.

This article analyzes and validates an approach of integration of adaptive dynamic programming (ADP) and adaptive fault-tolerant control (FTC) technique to address the consensus control problem for semi-Markovian jump multiagent systems having actuator bias faults. A semi-Markovian process, a more versatile stochastic process, is employed to characterize the parameter variations that arise from the intricacies of the environment. The reliance on accurate knowledge of system dynamics is overcome through the utilization of an actor-critic neural network structure within the ADP algorithm. A data-driven FTC scheme is introduced, which enables online adjustment and automatic compensation of actuator bias faults. It has been demonstrated that the signals generated by the controlled system exhibit uniform boundedness. Additionally, the followers' states can achieve and maintain consensus with that of the leader. Ultimately, the simulation results are given to demonstrate the efficacy of the designed theoretical findings.

Coaxial nanofibrous aerogel featuring porous network-structured channels for ovarian cancer treatment by sustained release of chitosan oligosaccharide

Ovarian cancer, the deadliest gynecological malignancy, primarily treated with chemotherapy. However, systemic chemotherapy often leads to severe toxic side effects and chemoresistance. Drug-loaded aerogels have emerged as a promising method for drug delivery, as they can improve drug solubility and bioavailability, control drug release, and reduce drug distribution in non-targeted tissues, thereby minimizing side effects. In this research, chitosan oligosaccharide (COS)-loaded nanofibers composite chitosan (CS) aerogels (COS-NFs/CS) with a porous network structure were created using nanofiber recombination and freeze-drying techniques. The core layer of the aerogel has a COS loading rate of 60 %, enabling the COS-NFs/CS aerogel to significantly inhibit the migration and proliferation of ovarian cancer cells (resulting in a decrease in the survival rate of ovarian cancer cells to 33.70 % after 48 h). The coaxial fiber's unique shell-core structure and the aerogel's porous network structure enable the COS-NFs/CS aerogels to release COS steadily and slowly over 30 days, effectively reducing the initial burst release of COS. Additionally, the COS-NFs/CS aerogels exhibit good biocompatibility, degradability (only retaining 18.52 % of their weight after 6 weeks of implantation), and promote angiogenesis, thus promoting wound healing post-oophorectomy. In conclusion, COS-NFs/CS aerogels show great potential for application in the treatment of ovarian cancer.

Bacterial networks and enzyme genes in bacterial floccules from hydrolysis and aeration reactors in a dairy wastewater treatment system.

The dairy industry generates substantial wastewater, which is commonly treated using integrated anaerobic hydrolysis and aerated biofilm reactors. However, the bacterial composition and functional differences within the generated floccules remain unclear. In this study, we employed 16S rRNA and metagenomic sequencing to compare bacterial communities and enzyme gene profiles between suspended floccules from the hydrolysis ponds and the aeration ponds. Results revealed that the bacterial phyla Firmicutes, Proteobacteria, and Bacteroidetes, dominated the wastewater treatment system and the relative abundance of these bacterial phyla varied in each pond. Additionally, the aeration ponds exhibited higher bacterial OTUs and enzyme gene abundance. Network analysis demonstrated a more complex bacterial network structure in the hydrolysis ponds compared to the aeration ponds. Furthermore, enzyme gene abundance revealed higher metabolic enzyme genes in the hydrolysis ponds, while signal transduction enzyme genes were more abundant in the aeration ponds. Notably, the top ten bacterial genera, primarily Hydromonas in the hydrolysis ponds and Ferruginibacter in the aeration ponds exhibited distinct contributions to signal transduction enzyme genes. Hydromonas dominated the metabolic enzyme genes in both ponds. These findings provide crucial insights for optimizing dairy wastewater treatment technologies.

Evolution and influential factors of inbound tourist flow network in China: a two-mode network perspective

ABSTRACT Different from existing studies focusing on tourist flow networks at the destination level, this study adopts a two-mode network analysis to identify the network structure, market groupings, and evolution of inbound tourist flows from 13 major origin countries to 31 destination provinces (municipalities, autonomous regions) in China. Furthermore, the quadratic assignment procedure (QAP) method is applied to analyse the influential factors of the formation of market groupings in the network. The results show that: (1) The connections within the destination-destination network and the origin-origin country network show a fluctuating increase trend. (2) Eastern provincial destinations occupy important positions in the network, and central and western destinations have played increasingly important roles in recent years. (3) Japan, South Korea, and the United States are the most important origin countries, and markets in Europe and Oceania have great potential. (4) Two market groupings led by Russia and Asian countries are relatively stable, while other origin countries have no specific regional preference. (5) Geographical distance exerts the most significant impact on the formation of market groupings, followed by tourism resources, economic development, and traffic accessibility.

MoSey1 regulates the unfolded protein response, appressorium development, and pathogenicity of Magnaporthe oryzae

Endoplasmic reticulum (ER) is an enclosed three-dimensional eukaryotic membrane network composed of flattened sacs. Fusion of homologous membranes to the ER membrane is essential for the maintenance of this network structure. In yeast, ER membrane fusion is mediated by Sey1p, whose paralogues function distinctly in different species. In this study, we investigated the biological functions of MoSEY1 in the devastating rice blast fungus Magnaporthe oryzae by functional genomic approach. Compared to wild type, deletion of MoSEY1 considerably decreased the growth and conidia production of M. oryzae. Additionally, the absence of MoSEY1 delayed appressorium formation and invasive hyphae growth. The appressorium function was also impaired in ΔMosey1 mutant. Subcellular localization analysis revealed that MoSey1 is localized at the ER. The ΔMosey1 mutant showed augmented sensitivity to ER stress. Additionally, we found that MoSey1 regulated the unfolded protein response, autophagy, and protein secretion in M. oryzae. In conclusion, our study unveiled the involvement of MoSey1 in the development, pathogenesis, and ER functions in M. oryzae.

Identification of the Core Characteristics of Vulnerable/Hypersensitive Narcissism and its Association with the Dark Triad in a Large International Sample: A Network Analysis Study.

The current paper aimed to investigate the network structure and centrality indexes of hypersensitive narcissism using the hypersensitive Narcissism Scale (HSN). Additionally, we aimed to explore its relationships with dark triad personality aspects. A globally diverse sample of "53,981" participants (47.9% non-United States responders) completed the HSN and Dark Triad Dirty Dozen scale (DTD). We estimated the network structure across genders to determine the core characteristics of hypersensitive narcissism. Additionally, bridge and central nodes (characteristics) were identified. All analyses were performed using R-Studio programming software. The network comparison test indicated significant differences in the network structures between males and females (Network-Invariance: 0.0489, P < 0.01; Global Strength Invariance: 0.101, P < 0.01). In the network of HSN for male participants, characteristics with the highest strength centrality were "Highly affected by criticism" (HSN.2, strength = 1.08) and "Self-absorbed in personal pursuits" (HSN.8, strength = 1.28). For female participants, "Self-absorbed in personal pursuits" (HSN.8, strength = 1.32) and "privately annoyed by others' needs" (HSN.10, strength = 1.21) were the highest central characteristics. The assessment of bridge strength indicated that nodes HSN.2 (Highly sensitive to criticism), scoring 0.42, and DTD.1 (Tendency to manipulate for gain, a component of Machiavellianism), scoring 0.428, showed the highest bridge strength values. The current study identified core characteristics of hypersensitive narcissism and its correlation with dark triad personality, revealing gender-specific patterns and bridging symptoms between the two constructs. These findings showed that focusing on these core characteristics may be advantageous in treating individuals exhibiting elevated levels of narcissism.

Identification of the Core Characteristics of Vulnerable/Hypersensitive Narcissism and its Association with the Dark Triad in a Large International Sample: A Network Analysis Study.

The current paper aimed to investigate the network structure and centrality indexes of hypersensitive narcissism using the hypersensitive Narcissism Scale (HSN). Additionally, we aimed to explore its relationships with dark triad personality aspects. A globally diverse sample of "53,981" participants (47.9% non-United States responders) completed the HSN and Dark Triad Dirty Dozen scale (DTD). We estimated the network structure across genders to determine the core characteristics of hypersensitive narcissism. Additionally, bridge and central nodes (characteristics) were identified. All analyses were performed using R-Studio programming software. The network comparison test indicated significant differences in the network structures between males and females (Network-Invariance: 0.0489, P < 0.01; Global Strength Invariance: 0.101, P < 0.01). In the network of HSN for male participants, characteristics with the highest strength centrality were "Highly affected by criticism" (HSN.2, strength = 1.08) and "Self-absorbed in personal pursuits" (HSN.8, strength = 1.28). For female participants, "Self-absorbed in personal pursuits" (HSN.8, strength = 1.32) and "privately annoyed by others' needs" (HSN.10, strength = 1.21) were the highest central characteristics. The assessment of bridge strength indicated that nodes HSN.2 (Highly sensitive to criticism), scoring 0.42, and DTD.1 (Tendency to manipulate for gain, a component of Machiavellianism), scoring 0.428, showed the highest bridge strength values. The current study identified core characteristics of hypersensitive narcissism and its correlation with dark triad personality, revealing gender-specific patterns and bridging symptoms between the two constructs. These findings showed that focusing on these core characteristics may be advantageous in treating individuals exhibiting elevated levels of narcissism.

Biodegradable Poly (L-Lactic acid) Fibrous Membrane with Ribbon-Structured Fibers and Ultrafine Nanofibers Enhances Air Filtration Performance.

Here, the poly (l-lactic acid) (PLLA) membrane with multi-structured networks (MSN) is successfully prepared by electrospinning technology for the first time. It is composed of micron-sized ribbon-structured fibers and ultrafine nanofibers with a diameter of tens of nanometers, and they are connected to form the new network structure. Thanks to the special fiber morphology and structure, the interception and electrostatic adsorption ability for against atmospheric particulate matter (PM) are significantly enhanced, and the resistance to airflow is reduced due to the "slip effect" caused by ultrafine nanofibers. The PLLA MSN membrane shows excellent filtration performance with ultra-high filtration efficiency (>99.9% for PM2.5 and >99.5% for PM0.3) and ultra-low pressure drop (≈20Pa). It has demonstrated filtration performance that even exceeds current non-biodegradable polymer materials, laying the foundation for future applications of biodegradable PLLA in the field of air filtration. In addition, this new structure also provides a new idea for optimizing the performance of other polymer materials.

The domino effect of teacher cognitive presence triggering events and resolution on student’s grit

The aim of this current study is to assess the essential role of teacher cognitive presence within the context of the community of inquiry framework in relation to enhancing students’ academic perseverance, more specifically this type of presence influences the most students’ academic perseverance. In order to test this hypothesis, an online questionnaire was created, including the community of inquiry scale and the grit scale. A total of 529 valid and consented answers were collected. We have further analyzed the structure of the variables network with network analysis and then we have employed several sequential mediation analyses testing the impact of cognitive presence triggering events and resolution on the relationship between all the other presences and students’ academic perseverance. A circular structure has emerged in network analysis and eight significant full complementary sequential mediation analysis. Results confirm the domino effect of teacher cognitive presence triggering events and resolution on student’s grit under the community of inquiry framework.