Insight into the improvement mechanism of gel properties of pea protein isolate based on the synergistic effect of cellulose nanocrystals and calcium ions

Here, the influence and potential mechanism by which cellulose nanocrystals (CNC) collaborated with Ca2+ enhancing the heat-induced gelation of pea protein isolate (PPI) were investigated. It was found that the combination of 0.45% CNC and 15 mM Ca2+ synergistically increased the gel strength (from 14.18 to 65.42 g) and viscoelasticity of PPI while decreased the water holding capacity. The improved particle size, turbidity, and thermostability as well as the reduced solubility, crystallinity, and gel porosity were observed in CNC/CaCl2 composite system. CNC fragments bind to specific amino acids in 11S legumin and 7S vicilin mainly through hydrogen bonding and van der Waals forces. Moreover, changes in the protein secondary structure and enhancement of the molecular interaction induced by CNC and Ca2+ could favor the robust gel network. The results will provide a new perspective on the functional regulation of pea protein and the creation of pea protein gel-based food.

Enhanced contact flexibility from nanoparticles in capillary suspensions

HYPOTHESIS

Sample-spanning particle networks are used to induce structure and a yield stress, necessary for 3D printing of porous ceramics and paints. In capillary suspensions, a small quantity of immiscible secondary fluid is incorporated into a suspension. By further adding nanoparticles with a range of hydrophobicities, the structure of the bridges and microparticle-microparticle contacts is expected to be modified, resulting in a tunable yield stress and shear moduli. Moreover, the compressibility of these samples, important in many processing and application steps, is expected to be sensitive to these changes.

EXPERIMENT

The nanoparticle hydrophobicity was altered and their position relative to the microparticles and the bridges was examined using confocal microscopy where the correlation between bridge size and network structure was observed. A step-wise uniaxial compression test on the confocal was conducted to monitor the microparticle movement and structural changes between capillary suspension networks with and without nanoparticles.

FINDINGS

Our observation suggests that nanoparticles induce the formation of thin liquid films on the surface of the microparticles, mitigating contact line pinning and promoting internal liquid exchange. Additionally, nanoparticles at microparticle contact regions further diminish Hertzian contact, enhancing the capacity for rearrangement. These effects enhance microparticle movement, narrowing the bridge size distribution.

Construction and evolutionary factors of spatial correlation network of China's provincial tourism resource conversion efficiency

Research objective

To explore the spatial correlation network characteristics and formation mechanisms of tourism resource conversion efficiency, and provide reference for the collaborative improvement of tourism resource conversion efficiency at the provincial level in China.

Research methods

Non parametric SBM efficiency measurement method and social network analysis method. Research hypothesis: The spatial network correlation characteristics of tourism resource conversion efficiency are obvious, and regional connections are close.

Research findings

(i) during the research period, the spatial connection strength of China's tourism resource conversion efficiency continued to increase and the spatial network structure of tourism resource conversion efficiency tended to become more complex and significantly more stable. (ii) A spatially linked network with a stable tourism resource conversion efficiency structure formed in China. The number of network relations and density of the network fluctuated and increased, while the network efficiency continued to decrease; however, a strong small-world nature was observed. (iii) The economic development level difference matrix, tourism industry agglomeration difference matrix, human capital difference matrix, and marketization degree difference matrix significantly and positively affected spatial association relationship establishment, while the provincial adjacency matrix significantly and negatively affected such relationships.

Helmet wearing detection algorithm based on improved YOLOv5

In industrial production, workers need to wear safety helmets at all times. However, due to different lighting, viewing angles, and the tendency of people to block each other, the precision of target detection is not high enough. Aiming at this problem, a real-time detection of helmets was achieved by improving the YOLOv5 algorithm. This algorithm introduces the lightweight network structure FasterNet, which uses partial convolution as the main operator to reduce the amount of calculations and parameters of the network; the boundary regression loss function Wise-IoU loss function with a dynamic focusing mechanism replaces the original loss function in YOLOv5; finally, the CBAM attention mechanism is introduced to obtain global context information and improve the detection ability of small targets. The experimental results show that the parameters of the improved YOLOv5 model are reduced by 12.68%, the computational amount is reduced by 10.8%, the mAP is increased from 88.3 to 92.3%, and the inference time is reduced by 81.5%, which is better than the performance of the original model and can detect helmet wearing effectively and in real time.

The dynamic risk spillover effects among carbon, renewable energy, and electricity markets based on the TVP-VAR-DY model

The linkages among carbon, renewable energy, and electricity markets are gradually strengthening. In order to prevent risk transmission among markets, this paper uses the TVP-VAR-DY (Time-Varying Parameter-Vector Auto Regression-Dynamic) model to analyze the dynamic risk spillover effects and network structure of risk transmission among carbon, renewable energy, and electricity markets. The empirical results show that there are significant asymmetric spillover effects among carbon, renewable energy, and electricity markets. The total spillover index shows that spillover effects among carbon, renewable energy, and electricity markets are time-varying, especially during unexpected events. Besides, the net spillover index indicates that the spillover effects are bidirectional, asymmetric, and time-varying. Finally, under the influence of unexpected events, the network structures of risk transmission among carbon, renewable energy, and electricity markets are heterogeneous. Compared to the Russia-Ukraine conflict, the COVID-19 pandemic has a more significant impact on these markets.

How Network Structure Shapes Languages: Disentangling the Factors Driving Variation in Communicative Agents

Languages show substantial variability between their speakers, but it is currently unclear how the structure of the communicative network contributes to the patterning of this variability. While previous studies have highlighted the role of network structure in language change, the specific aspects of network structure that shape language variability remain largely unknown. To address this gap, we developed a Bayesian agent-based model of language evolution, contrasting between two distinct scenarios: language change and language emergence. By isolating the relative effects of specific global network metrics across thousands of simulations, we show that global characteristics of network structure play a critical role in shaping interindividual variation in language, while intraindividual variation is relatively unaffected. We effectively challenge the long-held belief that size and density are the main network structural factors influencing language variation, and show that path length and clustering coefficient are the main factors driving interindividual variation. In particular, we show that variation is more likely to occur in populations where individuals are not well-connected to each other. Additionally, variation is more likely to emerge in populations that are structured in small communities. Our study provides potentially important insights into the theoretical mechanisms underlying language variation.

Network Polymer Properties Engineered Through Polymer Backbone Dispersity and Structure

Dispersity (Ð or Mw/Mn) is an important parameter in material design and as such can significantly impact the properties of polymers. Here, polymer networks with independent control over the molecular weight and dispersity of the linear chains that form the material are developed. Using a RAFT polymerization approach, a library of polymers with dispersity ranging from 1.2-1.9 for backbone chain-length (DP) 100, and 1.4-3.1 for backbone chain-length 200 were developed and transformed to networks through post-polymerization crosslinking to form disulfide linkers. The tensile, swelling, and adhesive properties were explored, finding that both at DP 100 and DP 200 the swelling ratio, tensile strength, and extensibility were superior at intermediate dispersity (1.3-1.5 for DP 100 and 1.6-2.1 for DP 200) compared to materials with either substantially higher or lower dispersity. Furthermore, adhesive properties for materials with chains of intermediate dispersity at DP 200 revealed enhanced performance compared to the very low or high dispersity chains.

Social network structure as a suicide prevention target

PURPOSE

The structure of relationships in a social network affects the suicide risk of the people embedded within it. Although current interventions often modify the social perceptions (e.g., perceived support and sense of belonging) for people at elevated risk, few seek to directly modify the structure of their surrounding social networks. We show social network structure is a worthwhile intervention target in its own right.

METHODS

A simple model illustrates the potential of interventions to modify social structure. The effect of these basic structural interventions on suicide risk is simulated and evaluated. Its results are briefly compared to emerging empirical findings for real network interventions.

RESULTS

Even an intentionally simplified intervention on social network structure (i.e., random addition of social connections) is likely to be both effective and safe. Specifically, this illustrative intervention had a high probability of reducing the overall suicide risk, without increasing the risk of those who were healthy at baseline. It also frequently resolved stable, high-risk clusters of people at elevated risk. These illustrative results are generally consistent with emerging evidence from real social network interventions for suicide.

CONCLUSION

Social network structure is a neglected, but valuable intervention target for suicide prevention.

Exotic and native plants play equally important roles in supporting and structuring plant-hummingbird networks within urban green spaces

Background

Urban gardens, despite their transformed nature, serve as invaluable microcosms for a quantitative examination of floral resource provision to urban pollinators, considering the plant's origin. Thus, knowledge has increased, emphasizing the importance of these green areas for hosting and conserving pollinator communities. However, there is a significant knowledge gap concerning the changing availability of these native and exotic floral resources over time and their impact on structuring interaction networks with specific pollinators.

Methods

Over a year-long period, monthly surveys were conducted to record both native and exotic plant species visited by hummingbirds in an urban garden at Tlaxcala, Mexico. Flower visits were recorded, and the total flowers on each plant visited were tallied. Additionally, all observed hummingbirds were recorded during the transect walks, regardless of plant visits, to determine hummingbird abundance. The interactions were summarized using matrices, and network descriptors like connectance, specializacion, nestedness, and modularity were computed. Plant and hummingbird species in the core and periphery of the network were also identified. Lastly, simulations were performed to assess the network's resilience to the extinction of highly connected native and exotic plant species, including those previously situated in the network's core.

Results

We recorded 4,674 interactions between 28 plant species, and eight hummingbird species. The majority of plants showed an ornithophilic syndrome, with 20 species considered exotic. Despite asynchronous flowering, there was overlap observed across different plant species throughout the year. Exotic plants like Jacaranda mimosifolia and Nicotiana glauca produced more flowers annually than native species. The abundance of hummingbirds varied throughout the study, with Saucerottia berillyna being the most abundant species. The plant-hummingbird network displayed high connectance, indicating generalization in their interaction. Significant nestedness was observed, mainly influenced by exotic plant species. The core of the network was enriched with exotic plants, while Basilinna leucotis and Cynanthus latirostris played central roles among hummingbirds. Network resilience to species extinction remained generally high.

Conclusions

Our findings provide valuable insights into the dynamics and structure of plant-hummingbird interactions in urban gardens, emphasizing the influence of exotic plant species and the network's resilience to perturbations. Understanding and managing the impact of exotic plants on such networks is crucial for the conservation and sustainable functioning of urban ecosystems.

Sex, health status and habitat alter the community composition and assembly processes of symbiotic bacteria in captive frogs

BACKGROUND

Frogs are critical economic animals essential to agricultural ecosystem equilibrium. However, Meningitis-like Infectious Disease (MID) often affects them in agricultural settings. While frog-associated microbiota contribute to elemental cycling and immunity, the effects of frog sex and health on gut bacteria remain understudied, and the relationship between frog habitat and soil microbes is unclear. We aimed to determine how frog sex, health status and habitat influence symbiotic bacteria and community assembly mechanism to provide guidance for sustainable frog farming and conservation.

RESULTS

We employed 16S rRNA sequencing to investigate gut microbiota differences in relation to frog sex and health status. We also compared symbiotic communities in frog-aggregation, native and soybean soil on the farm. Results showed that gut bacterial β-diversity and taxonomy were markedly influenced by frog sex and health. Healthy frogs had more robust gut bacterial metabolism than frogs infected with MID. Cooccurrence network analysis revealed that healthy female frogs had more complex microbial network structure than males; however, diseased males showed the greatest network complexity. The assembly mechanism of gut bacteria in male frogs was dominated by deterministic processes, whereas in female frogs it was dominated by stochastic processes. Among symbiotic bacteria in frog habitat soils, deterministic processes predominantly shaped the community assembly of soybean soil. In particular, soybean soil was enriched in pathogens and nitrogen functions, whereas frog-aggregation soil was markedly increased in sulphur respiration and hydrocarbon degradation.

CONCLUSION

Our study reveals that sex mainly alters the interaction network and assembly mechanism of frog intestinal bacteria; MID infection significantly inhibits the metabolic functions of intestinal bacteria. Furthermore, diverse frog habitat soils could shape more symbiotic bacteria to benefit frog farming. Our findings provide new horizons for symbiotic bacteria among frogs, which could contribute to sustainable agriculture and ecological balance.

In Search of Conceptual Clarity About the Structure of Psychopathic Traits in Children: A Network-Based Proposal

Psychopathic traits in childhood have been revealed as potential identifiers of risk, being predictive of later forms of behavioral maladjustment. Yet, it is still under debate how psychopathic traits in children should be best conceptualized and which are the core dimensions for construct definition and prediction. The present study aims to examine the structure of psychopathic traits in childhood, and its predictive value, by using a combination of traditional factor analysis and more recent network-based methods. Data on psychopathic traits, as measured by the Child Problematic Traits Inventory (CPTI), were collected in a large sample of children (n = 2454; 48.2% girls), aged 3 to 6 at the onset of the study (Mage = 4.26; SD = 0.91), who were followed-up one and two years later using parent- and teacher-reports. Results showed that psychopathic traits measured via CPTI are best conceptualized as five latent factors encompassing grandiosity, deceitfulness, callousness, impulsivity and need of stimulation, a result that converged across informants and time. Callousness and grandiosity emerged as central traits using network analysis of parent-reports, while deceitfulness was most central using teacher-reports. Finally, callousness, impulsivity and deceitfulness emerged as the best predictors of concurrent, prospective and stable conduct problems. These results provide a refined structure of psychopathic traits in children that better accounts for the core elements of the construct. Additional theoretical and practical implications will be discussed in terms of assessment, diagnostic classification and tailored prevention/intervention.

Technical and ethical considerations in telesurgery

Telesurgery, a cutting-edge field at the intersection of medicine and technology, holds immense promise for enhancing surgical capabilities, extending medical care, and improving patient outcomes. In this scenario, this article explores the landscape of technical and ethical considerations that highlight the advancement and adoption of telesurgery. Network considerations are crucial for ensuring seamless and low-latency communication between remote surgeons and robotic systems, while technical challenges encompass system reliability, latency reduction, and the integration of emerging technologies like artificial intelligence and 5G networks. Therefore, this article also explores the critical role of network infrastructure, highlighting the necessity for low-latency, high-bandwidth, secure and private connections to ensure patient safety and surgical precision. Moreover, ethical considerations in telesurgery include patient consent, data security, and the potential for remote surgical interventions to distance surgeons from their patients. Legal and regulatory frameworks require refinement to accommodate the unique aspects of telesurgery, including liability, licensure, and reimbursement. Our article presents a comprehensive analysis of the current state of telesurgery technology and its potential while critically examining the challenges that must be navigated for its widespread adoption.

Personal network dynamics across the life course: A relationship-related structural approach

Building on Georg Simmel's concept of "form", the article presents a relationship related structural concept of social relationships that specifically accounts for opportunities and constraints resulting from the fact that relationships are solidified patterns of interaction that, once established, can develop a power of their own (inertia, momentum) that cannot easily be influenced by the involved actors. In this "relationship-related structural approach", social relationships or "forms" can be understood as specific constellations of "basic structural properties", i.e. specifications of various aspects of quantity, of time, of space, of similarity, and including also a certain degree of freedom to enter or quit a relationship, knowledge about one another, and types and degree of institutionalization. The specification of these structural properties impacts the functional capacity of relationships, as well as the dynamics of both relationships and networks, especially the ways in which relationships are formed, maintained, or lost. Referring to various life course transitions from different phases of the life course, it is demonstrated how this approach helps to better understand the dynamics of social relationships and networks and the impact of life events on personal relationships across the life course. Finally, implications of this novel perspective for life course and network research are discussed.

Characteristics of insoluble soybean fiber (ISF) concentrated emulsions: Effects of pretreatment on ISF and freeze-thaw stability of emulsions

The properties of emulsions could be affected by the interactions between the components and network stabilization effect, which are commonly adjusted by changes in pH, ionic strength and temperature. In this work, insoluble soybean fiber (ISF) obtained via homogenization after alkaline treatment was pretreated firstly and then resultant emulsions were freeze-thawed. Heating pretreatment reduced droplet size, enhanced viscosity and viscoelasticity as well as subsequent stability of ISF concentrated emulsions, while both acidic pretreatment and salinized pretreatment decreased the viscosity and weakened the stability. Furthermore, ISF emulsions exhibited a good freeze-thaw performance which was further improved by secondary emulsification. Heating promoted the swelling of ISF and strengthened the gel-like structure of emulsions while salinization and acidization weakened the electrostatic interactions and caused the destabilization. These results indicated that pretreatment of ISF significantly influenced the concentrated emulsion properties, providing guidance for the fabrication of concentrated emulsions and related food with designed characteristics.

Recent developments in nanocellulose-based aerogels as air filters: A review

Today, one of the world's critical environmental issues is air pollution, which is the most important parameter threatening human health and the environment. Synthetic polymers are widely used in industrial air filter production; however, they are incompatible with the environment due to their secondary pollution. Using renewable materials to manufacture air filters is not only environmentally friendly but also essential. Recently, a new generation of biopolymers called cellulose nanofiber (CNF)-based hydrogels have been proposed, with three dimensional (3D) nanofiber networks and unique physical and mechanical properties. CNFs have become a hot research topic for application as air filter materials because they can compete with synthetic nanofibers due to their advantages, such as abundant, renewable, nontoxic, high specific surface area, high reactivity, flexibility, low cost, low density, and network structure formation. The main focus of the current review is the recent progress in the preparation and employment of nanocellulose materials, especially CNF-based hydrogels, to absorb PM and CO2. This study summarizes the preparation methods, modification strategies, fabrications, and further applications of CNF-based aerogels as air filters. Lastly, challenges in the fabrication of CNFs, and trends for future developments are presented.

Bayesian network model structure based on binary evolutionary algorithm

With the continuous development of new technologies, the scale of training data is also expanding. Machine learning algorithms are gradually beginning to be studied and applied in places where the scale of data is relatively large. Because the current structure of learning algorithms only focus on the identification of dependencies and ignores the direction of dependencies, it causes multiple labeled samples not to identify categories. Multiple labels need to be classified using techniques such as machine learning and then applied to solve the problem. In the environment of more training data, it is very meaningful to explore the structure extension to identify the dependencies between attributes and take into account the direction of dependencies. In this article, Bayesian network structure learning, analysis of the shortcomings of traditional algorithms, and binary evolutionary algorithm are applied to the randomized algorithm to generate the initial population. In the optimization process of the algorithm, it uses a Bayesian network to do a local search and uses a depth-first algorithm to break the loop. Finally, it finds a higher score for the network structure. In the simulation experiment, the classic data sets, ALARM and INSURANCE, are introduced to verify the effectiveness of the algorithm. Compared with NOTEARS and the Expectation-Maximization (EM) algorithm, the weight evaluation index of this article was 4.5% and 7.3% better than other schemes. The clustering effect was improved by 13.5% and 15.2%. The smallest error and the highest accuracy are also better than other schemes. The discussion of Bayesian reasoning in this article has very important theoretical and practical significance. This article further improves the Bayesian network structure and optimizes the performance of the classifier, which plays a very important role in promoting the expansion of the network structure and provides innovative thinking.

Network structure and stability of the river connectivity in a rapidly urbanizing region

River connectivity, which is key to the function of the river network, is deteriorating in highly urbanized areas. While previous studies have identified changes in the structure and connectivity of river networks, few studies have described the network structure of river connectivity and revealed the effects of urbanization on network structure. To this end, we detected the network structure and stability of river connectivity from a novel perspective of complex network theory. Taking the Taihu Plain as an example, we found that 1) the node degree of the river network was moderate (2.9), and the hub and connectivity were low (0.21 and 0.19, respectively). The hub and connectivity of the river network in the Yang-Cheng-Dian-Mao (YCDM) region were better than that in Wu-Cheng-Xi-Yu (WCXY) and Hang-Jia-Hu (HJH) regions. 2) The destruction of important nodes led to a dramatic decrease in the stability of river network connectivity. The river network structures on the Taihu Plain, HJH, WCXY, and YCDM were severely damaged when the removal rate of river network nodes exceeded 5 %, 7 %, 16 %, and 22 %, respectively. 3) The spatial response of the river network to urbanization was mainly negative, especially in highly urbanized regions. The effects of urbanization on network characteristics could be sorted as node degree (45 %), hub (21 %), and connectivity (18 %). Our results would provide theoretical support for the recognition, protection, and restoration of the river network in rapidly urbanizing regions.

Construction of catalyst layer network structure for proton exchange membrane fuel cell derived from polymeric dispersion

A rational design of the structure of catalyst layer (CL) is required for proton exchange membrane fuel cells to attain outstanding performance and excellent stability. It is crucial to have a profound comprehension of the correlations existing between the properties (catalyst ink), network structures of CL and proton exchange membrane fuel cells' performance for the rational design of the structure of CL. This study deeply investigates the effects of a series of alcohol solvents on the properties and network structure of CL. The results demonstrate that the CL aggregates in higher ε solution show smaller particle sizes, and the sulfonic acid groups (∼SO₃H) tend to extend more outward due to the strong dissociation. A more continuous and homogeneous ionomer distribution around Pt/C aggregates is observed in the CL, which improves the electrochemically active surface area (ECSA) and performance of the electrode. But, the electrode has a poor performance at high current density regions due to the mass transfer resistance. Based on this, a two-step solvent control strategy is proposed to maintain uniform ionomer and aggerates distribution and optimize the mass transfer for CL. The performance of the cell improves from 0.555 V to 0.615 V at 2000 mA·cm^-2.

Stability of Rosenzweig-MacArthur models with non-diffusive dispersal on non-regular networks

This paper examines the stability of the Rosenzweig-MacArthur model distributed to identical discrete habitat patches. Migration between patches is assumed to follow the non-diffusive rule that individuals have a fixed rate of leaving their local habitat patch and migrating to another. Under this non-diffusive migration rule, we found that population dispersal on a non-regular and connected habitat network can both stabilize and destabilize the Rosenzweig-MacArthur model. It is also shown that our non-diffusive migration rule apparently becomes diffusive if the habitat network is regular.

Influence and effect mechanism of disulfide bonds linkages between protein-coated lipid droplets and the protein matrix on the physicochemical properties, microstructure, and protein structure of ovalbumin emulsion gels

In this study, disulfide bonds between the interfacial protein film formed on the lipid particles and the protein in ovalbumin emulsion gels were blocked with 0, 1, 3, 5 and 10 mM of the N-ethylmaleimide (NEM) to explore the influence and effect mechanism of disulfide bonds between the interfacial proteins on the physicochemical properties, microstructure, and protein structure of sunflower oil-ovalbumin emulsion gels. Ovalbumin emulsion gels with NEM-treated ovalbumin emulsion (N-OE) had lower hardness, free sulfhydryl content, water holding capacity (WHC), and surface hydrophobicity, but higher spin-spin relaxation time (T₂) than ovalbumin emulsion gels with NEM-treated ovalbumin substrate solution (N-OSS). In addition, N-OE and N-OSS had lower hardness, free sulfhydryl content, WHC and surface hydrophobicity, as well as a more coarse and disordered microstructure than non-NEM treated ovalbumin emulsion gel (control group). The free sulfhydryl content, hardness, WHC, and surface hydrophobicity of the ovalbumin emulsion gels all decreased as the NEM concentration rose (p < 0.05), whereas the amide A band changed to higher wave numbers. These results collectively indicated that the reduction of disulfide between the interfacial layer and the proteins inhibited the hydrophobic effect, the formation of hydrogen bonds, and prevented the formation of larger aggregates. Thus the disulfide bonds between the interfacial proteins contribute to the hardness enhancement and water stabilization of the ovalbumin gel.

Sex differences in the interrelations between stress, craving and alcohol consumption across individuals and time during baclofen treatment for alcohol dependence

AIMS

Recent studies have suggested that females respond more favourably to baclofen treatment for alcohol use disorder. Females are generally more likely to drink to regulate stress reactivity and negative affect. This study thus aimed to evaluate the role of sex on the effect of baclofen on the relationship between daily alcohol consumption, stress and craving.

METHODS

A network analysis of fluctuations using vectorized autoregressive modelling was used to explore the relationship between daily surveys of alcohol consumption, stress and craving from daily diary data over 84 days from a randomised controlled trial of baclofen (30 mg or 75 mg per day) versus placebo in 104 participants with alcohol dependence (1, 2). Symptom interrelations across patients and across time were examined including temporal networks (time lagged), contemporaneous and between-subjects networks, and were examined for placebo and baclofen stratified by sex.

RESULTS

Overall, between persons, there was a significant relationship between stress and drinking in placebo treated individuals in females (r = -0.70, p < 0.001) but not males (r = 0.32, p = 0.054) that was not observed in baclofen treated individuals. No relationship was observed between stress and drinking in the baclofen group for either sex (p's < 0.45).

DISCUSSION

There appears to be some sex-specific differences whereby baclofen abolishes an overall association between stress and drinking in females, but this is not observed in males. Network analyses may assist in elucidating the mechanism of action of alcohol pharmacotherapies such as baclofen and understanding which symptoms and mechanisms are key for effective interventions.

Influential nodes identification in complex networks: a comprehensive literature review

Researchers have paid a lot of attention to complex networks in recent decades. Due to their rapid evolution, they turn into a major scientific and innovative field. Several studies on complex networks are carried out, and other subjects are evolving every day such as the challenge of detecting influential nodes. In this study, we provide a brief overview of complex networks, as well as several concepts key related to measurements, the structure of complex network and social influence, an important state of the art on complex networks including basic metrics on complex networks, the evolution of their topology over the years as well as the dynamic of networks. A detailed literature about influential finding approaches is also provided to indicate their strength and shortcomings. We aim that our contribution of literature can be an interesting base of information for beginners' scientists in this field. At the end of this paper, some conclusions are drawn and some future perspectives are mentioned to be studied as new directions in the future. More detailed references are provided to go further and deep in this area.

Comparing with oxygen, nitrate simplifies microbial community assembly and improves function as an electron acceptor in wastewater treatment

Biochemical oxidation and reduction are key processes in treating biological wastewater and they require the presence of electron acceptors. The functional impact of electron acceptors on microbiomes provides strategies for improving the treatment efficiency. This research focused on two of the most important electron acceptors, nitrate and oxygen. Molecule ecological network, null model, and functional prediction based on high-throughput sequencing were used to analyze the microbiomes features and assembly mechanism. The results revealed nitrate via the homogeneous selection (74.0%) decreased species diversity, while oxygen via the homogeneous selection (51.1%) and dispersal limitation (29.6%) increased the complexity of community structure. Microbes that were more strongly homogeneously selected for assembly included polyphosphate accumulating organisms (PAOs), such as Pseudomonas and variovorax in the nitrate impacted community; Pseudomonas, Candidatus_Accumulibacter, Thermomonas and Dechloromonas, in the oxygen impacted community. Nitrate simplified species interaction and increased the abundance of functional genes involving in tricarboxylic acid cycle (TCA cycle), electron transfer, nitrogen metabolism, and membrane transport. These findings contribute to our knowledge of assembly process and interactions among microorganisms and lay a theoretical basis for future microbial regulation strategies in wastewater treatment.

Food supply network disruption and mitigation: an integrated perspective of traceability technology and network structure

The 2019 coronavirus disease (COVID-19) epidemic has caused serious disruptions in food supply networks. Based on the case of the remerging epidemic in China, this paper aims to investigate food supply network disruption and its mitigation from technical and structural perspectives. To solve the optimal policy choice problem that how to improve mitigation capability of food supply networks by using traceability technology and adjusting network structure, the occurrence mechanism of food supply network disruptions is revealed through a case study of the remerging COVID-19 outbreak in Beijing's Xinfadi market. Five typical traceability solutions are proposed to mitigate network disruptions and their technical attributes are analyzed to establish disruption mitigation models. The structure of food supply networks is also controlled to mitigate disruptions. The structural attributes of three fundamental networks are extracted to adjust the network connections pattern in disruption mitigation models. Next, simulation experiments involving the disruption mitigation models are carried out to explore the independent and joint effects of traceability technology and network structure on mitigation capability. The findings suggest that accuracy makes a more positive effect on the mitigation capability of food supply networks than timeliness due to the various technical compositions behind them; the difference between these effects determines the choice decision of supply networks on traceability solution types. Likewise, betweenness centralization makes a positive effect but degree centralization makes a negative effect on mitigation capability because intermediary firms and focal firms in food supply networks have different behavior characteristics; these effects are both regulated by supply network types and exhibit different sensitivities. As for the joint effect of technical and structural attributes on mitigation capability, the joint effect of accuracy and betweenness centralization is bigger than the independent effects but smaller than their sum; the joint effect of timeliness and betweenness centralization depends on networks type; while the positive effect of accuracy or timeliness on mitigation capability is greater than the negative effect of degree centralization; theses joint effects are caused by the complicated interactive effects between technical composition and behaviors of intermediary firms or focal firms. These findings contribute to disruption management and decision-making theories and practices.

Structural changes in intercity mobility networks of China during the COVID-19 outbreak: A weighted stochastic block modeling analysis

This study focuses on a mesoscale perspective to examine the structural and spatial changes in the intercity mobility networks of China from three phases of before, during and after the Wuhan lockdown due to the outbreak of COVID-19. Taking advantages of mobility big data from Baidu Maps, we introduce the weighted stochastic block model (WSBM) to measure and compare mesoscale structures in the three mobility networks. The results reveal significant changes to volume and structure of the intercity mobility networks. Particularly, WSBM results show that the intercity network transformed from a typical core-periphery structure in the normal phase, to a hybrid and asymmetric structure with mixing core-peripheries and local communities in the lockdown phase, and to a multi-community structure with nested core-peripheries during the post-lockdown phase. These changes suggest that the outbreak of COVID-19 and the travel restrictions deconstructed the original hierarchy of the intercity mobility network in China, making the network more locally or regionally fragmented, even at the recovery stage. This study provides new empirical and methodological insights into understanding mobility network dynamics under the impact of COVID-19, helping assess the emergency-induced impact as well as the recovery process of the mobility network.

[Exploring and analyzing the improvement mechanism of U-Net and its application in medical image segmentation]

Remarkable results have been realized by the U-Net network in the task of medical image segmentation. In recent years, many scholars have been researching the network and expanding its structure, such as improvement of encoder and decoder and improvement of skip connection. Based on the optimization of U-Net structure and its medical image segmentation techniques, this paper elucidates in the following: First, the paper elaborates on the application of U-Net in the field of medical image segmentation; Then, the paper summarizes the seven improvement mechanism of U-Net: dense connection mechanism, residual connection mechanism, multi-scale mechanism, ensemble mechanism, dilated mechanism, attention mechanism, and transformer mechanism; Finally, the paper states the ideas and methods on the U-Net structure improvement in a bid to provide a reference for later researches, which plays a significant part in advancing U-Net.

The network structure of dysfunctional metacognition: Analysis of the MCQ-30

The Metacognitive Control System (MCS) model gives central importance to maladaptive metacognition in psychological vulnerability and disorder. The metacognitions questionnaire 30 (MCQ-30) is widely used to assess such metacognitions and to establish their effects. Previous studies consistently demonstrate that the MCQ-30 consists of five latent factors, with some factors showing wide-ranging positive associations with symptoms and some demonstrating more specific symptom links. Questions remain concerning relationships between MCQ-items (or domains) and the most central of these outside of the latent-factor model. In the present study we set out to explore the internal structure of the MCQ-30 using network analysis and estimated two graphical Gaussian models, one with items- and one with domains, in an unselected sample (N = 1080). The robustness and stability of the networks, as well as the node predictability were assessed. Among our observations was that the items of the MCQ-30 appeared to cluster in meaningful substructures, corresponding to metacognitive theory. Furthermore, "need for control" was the most centrally placed domain, suggesting it plays an important role in the network and that its activation has a strong influence on other nodes. The theoretical and clinical implications of the current findings are discussed in light of the metacognitive model of psychological disorder.

Egocentric network characteristics of people who inject drugs in the Chicago metro area and associations with hepatitis C virus and injection risk behavior

BACKGROUND

Hepatitis C (HCV) infection has been rising in the suburban and rural USA, mainly via injection-based transmission. Injection and sexual networks are recognized as an important element in fostering and preventing risky behavior; however, the role of social support networks has received somewhat less attention.

METHODS

Using baseline data from an ongoing longitudinal study, we examined the composition and structure of injection drug use (IDU), sex, and social support networks of young people who inject drugs (aged 18-30) and their injection network members. Lasso logistic regression was used to select a subset of network characteristics that were potentially important predictors of injection risk behaviors and HCV exposure.

RESULTS

Several measures of IDU, sexual, and support network structure and composition were found to be associated with HCV exposure, receptive syringe sharing (RSS), and ancillary equipment sharing. Gender and sexual relationships were important factors for all risk behaviors. Support network characteristics were also important, notably including a protective effect of majority Hispanic support networks for RSS and HCV exposure. Both IDU network residence heterogeneity and support network geography were associated with injection equipment sharing.

CONCLUSIONS

The associations of IDU and support network geography with equipment sharing highlight the need to extend harm reduction efforts beyond urban areas. Greater understanding of support network influences on risk behavior may provide important insights to strengthen the benefits of harm reduction. In considering the probability of HCV transmission, it is important to consider setting and network structures that promote propagation of risk.

Long-term dynamics of the network structures in seed dispersal associated with fluctuations in bird migration and fruit abundance patterns

In temperate zones, seed-dispersal networks by migratory birds are formed on long time scale. In mid-October from 2005 to 2016, to explore the dynamics of the network structures, we examined interannual variability of fruit abundance, bird migration, and seed-dispersal networks in central Japan. For 12 years, the fruit abundance exhibited a remarkable fluctuation across years, with the number of fruiting plants and matured fruits fluctuating repeatedly every other year, leading to the periodic fluctuations. The abundance of migratory birds was also fluctuated. According to the abundance of fruits and migratory birds, the 12 years was classified into three types: frugivores and fruits were abundant, frugivores were abundant but fruits were scarce, and frugivores were scarce. The seed-dispersal networks were investigated by collecting faeces and vomits of migrants. Of the 6652 samples collected from 15 bird species, 1671 (25.1%) included seeds from 60 plant species. Main dispersers were composed of Turdus pallidus, T. obscurus, and Zosterops japonicus. The network structures were almost nested for 12 years. Specifically, the nested structure was developed in years when fruit abundance was low. GLM analyses showed the abundance of migrants, particularly T. pallidus and T. obscurus, had strong positive effects on nested structure. It may be caused by the fact the two Turdus species were more frequently functioning as generalist dispersers when fruit abundance was lower. Our study suggested fruit abundance and foraging behaviour of frugivores determine the network structures of seed dispersal on long time scale.

A comprehensive assessment of fungi in urban sewer biofilms: Community structure, environmental factors, and symbiosis patterns

Sewers are important parts of wastewater treatment facilities and the fungal microbial communities therein make large contributions to the biotransformation of wastewater. Therefore, this experiment constructed an experimental sewer system and characterized the fungal microbial communities using ITS high-throughput sequencing technology in combination with network structure analysis and statistical correlation analysis methods. The results demonstrated that the overall diversity of the fungal communities gradually increased as growth phases progressed, but the dominant groups differed significantly among phases. In the early growth phase (RS1) the dominant genera were Apiotrichum and Inocybe, with abundances of 34% and 14%, respectively, while the middle and late growth phases (RS2 and RS3) were dominated by Candida, with a relative abundance of 47%-66%. CCA and correlation analysis showed that the fungal communities diversity from the artificial sewers had significant positive correlations with COD (r² = 0.44, p < 0.05) and NH₄⁺ (r² = 0.64, p < 0.05) and that environmental factors significantly influenced the abundances of Fusarium and Aspergillus. Network analysis revealed differences in the fungal groups representing key nodes during different periods. Candida, Trichosporon, Fusarium, and Aspergillus played important roles in the microbial ecosystem of the simulated sewer systems. This study provides data-supported insight into the bacterial-fungal interaction mechanisms and associated pollutant biodegradation technologies in sewers.

Dynamic changes in rhizosphere fungi in different developmental stages of wheat in a confined and isolated environment

As the core food crop of a bioregenerative life support system (BLSS), wheat is susceptible to pathogen infection due to the lack of effective microbial communities in the confined and isolated environment. Therefore, a thorough understanding of the dynamic changes in wheat rhizosphere fungi is of great significance for improving wheat production and ensuring the stability of the BLSS. In the current study, we collected samples of rhizosphere fungi in the four growth stages of wheat grown in the "Lunar Palace 365" experiment. We employed bioinformatics methods to analyze the samples' species composition characteristics, community network characteristics, and FUNGuild function analysis. We found that the species composition of rhizosphere fungi in the wheat at the tillering stage changed greatly in the closed and isolated environment, while the species composition in the seedling, flowering, and mature stage were relatively stable. The results of the FUNGuild function analysis showed that the functions of rhizosphere fungi changed during wheat development. The rhizosphere fungal community was centered on Ascomycota, Mortierellomycota, and Chytridiomycota, and the community showed the characteristics of a "small world" arrangement. The stage of wheat seedlings is characterized by a greater abundance, diversity, and complexity of the network of interactions in the rhizosphere mycorrhiza community, while the tillering stage exhibited a greater clustering coefficient. Based on the changes in species composition, guild function regulation, and community structure differences of the wheat rhizosphere fungi in the BLSS, our study identified the critical fungal species during wheat development, providing a reference for ensuring the health and yield of plants in the BLSS system. KEY POINTS: • The diversity, composition, FUNguild, and network structure of rhizosphere fungi were analyzed. • Ascomycota, Mortierellomycota, and Chytridiomycota were the center of the rhizosphere fungal community network. • The effects of different wheat developmental stages on the community composition, function, and network structure of rhizosphere fungi were examined.

The Role of Social Network Structure in the Emergence of Linguistic Structure

Social network structure has been argued to shape the structure of languages, as well as affect the spread of innovations and the formation of conventions in the community. Specifically, theoretical and computational models of language change predict that sparsely connected communities develop more systematic languages, while tightly knit communities can maintain high levels of linguistic complexity and variability. However, the role of social network structure in the cultural evolution of languages has never been tested experimentally. Here, we present results from a behavioral group communication study, in which we examined the formation of new languages created in the lab by micro-societies that varied in their network structure. We contrasted three types of social networks: fully connected, small-world, and scale-free. We examined the artificial languages created by these different networks with respect to their linguistic structure, communicative success, stability, and convergence. Results did not reveal any effect of network structure for any measure, with all languages becoming similarly more systematic, more accurate, more stable, and more shared over time. At the same time, small-world networks showed the greatest variation in their convergence, stabilization, and emerging structure patterns, indicating that network structure can influence the community's susceptibility to random linguistic changes (i.e., drift).

Association between social network structure and physical activity in middle-aged Korean adults

PURPOSE

Evidence suggests that physical activity participation is shaped through a myriad of structural aspects of social relationships. We examined the relationship between social network structure based on egocentric social network and physical activity.

METHODS

From 6799 middle-aged Korean adults, we assessed the social network density and proportion of closed triads, using the name generator module. Self-reported physical activity for functional and leisure purposes was calculated in metabolic equivalent of task (MET)-min/week. We employed sex-stratified, multivariable linear regression to assess the association between each network structure variable and total physical activity, adjusting for age, network size, socioeconomic status, and comorbidities. We also examined the association with moderate-to-vigorous physical activity (MVPA) and wrist-worn accelerometer assessed physical activity.

RESULTS

The network members of female participants were more likely to be of same sex and family member compared to those of males. There were no sex differences in average network size. Network density based on affiliation was sex-differentially associated with physical activity (male β -346.7, p 0.2221 and female β -528.6, p 0.0002). In parallel, the proportion of closed triads was negatively associated with physical activity only in females (male β -542.6, p 0.0551 and female β -641.51, p < 0.0001). However, network density and closed triads were insignificantly yet positively associated with MVPA in male (density β 229.7, p 0.3193 and closed triad β 109.21, p 0.6333). Network structure by contact frequency or emotional closeness and accelerometer-assessed physical activity showed inconsistent results.

CONCLUSION

Understanding the role of social network structures can help to achieve ideal physical activity level in the context of primary prevention of cardiometabolic disorders.

The structural equivalence of tourism cooperative network in the Belt and Road Initiative Area

This study constructed the international tourism cooperation network (ITCN) in the Belt and Road Initiative area and further analyzed the structural equivalence of the tourism cooperative network by block-modeling approach through Convergence of iterated Correlations CONCOR algorithm in UCINET 6 data set. The results displayed the layout of subgroups: The East Europe, North Asia-Pacific and South Asia were in core positions; Middle East, the Americas and Africa were at margins of the network. Besides, each inter-block relational pattern and the status of each block had been presented. The sociogram of inter-block density highlighted the importance of reciprocal ties. These ties were mainly constructed between core blocks, but seldom constructed between peripheral blocks. The degree of competition derived from structural equivalence can be balanced through the implementation of intra-block differential strategy and the design of inter-block relational patterns.

Community dynamics in rhizosphere microorganisms at different development stages of wheat growing in confined isolation environments

Wheat is the core food crop in bioregenerative life support systems (BLSSs). In confined isolation environments, wheat growth suffers from a lack of stable microbial communities and is susceptible to pathogenic infections due to the culture substrate's limitations. To overcome this limitation, the time series changes of wheat rhizosphere microorganisms in wheat production must be understood. In the present study, we examined the rhizosphere microbial samples from wheat at four different growth stages from plants collected from a BLSS plant cabin. We employed bioinformatics analysis strategies to analyze the characteristics of species composition, function prediction, and community network. The species composition of wheat rhizosphere microorganisms was relatively stable in the seedling, tillering, and flowering stages in confined isolation environments. However, we observed marked microbial changes at mature stages. The results of functional prediction analysis suggest that the rhizosphere microbial community function of "Energy metabolism" gradually decreased, and the function of "Transmembrane transport" gradually increased during wheat development. The construction of the rhizosphere microbial community is non-random, scale-free and has the characteristics of a small world. We found the tillering stage to be more complex than the other stages. Our study reveals the composition characteristics, functional changes, and community structure fluctuations of rhizosphere bacteria at different development stages of wheat in the isolated and controlled environment, providing a theoretical basis for the efficient production of BLSS plant systems. KEY POINTS: • We collected wheat rhizosphere microorganisms at different stages in a confined isolation environment. • The diversity, composition, function, and network structure of rhizosphere bacteria were analyzed. • The effect of different wheat stages on the composition, function, and network structure of rhizosphere microorganisms was speculated.

Network Structure of Callous-Unemotional Traits and Conduct Disorder Symptoms Among At-Risk Youth: Multi-Informant Reports and Gender Differences

Network analytic techniques examine how items used to measure underlying constructs are related to one another and identify core characteristics. While many studies have examined the covariance of callous-unemotional (CU) traits or features and conduct disorder (CD) symptoms, the inter-item relations of these constructs and the core characteristics of the CU construct are unclear. The present study aimed to examine the network connectivity of, and between, CU features and CD symptoms. We also examined both parent-reports and youth self-reports and gender differences. CU features and CD symptoms were rated by parents (n = 814; 74% mothers; age 23-73, M age = 43.86, SD = 8.13) and their child (n = 608; 57% female; age 7-19, M age = 13.98, SD = 2.36). Network plots depicted greater connectivity (i.e., density and weights) for CU features relative to CD symptoms across both informants. However, youth-reported CU features and CD symptoms were less densely connected than parent-reports. Items commonly comprising the callousness subscale were more central and linked the two constructs together, relative to uncaring items, across informant and gender. Gender related effects indicated lower centrality for male versus female youth, and this finding was particularly evident in youth-reports. Our findings highlight relations between CU features and CD symptoms, and point to the importance of callousness items in conceptualizations of CU features among high-risk youth from both the perspective of the parent and child. We also inform understanding of gender differences in CU features for which the literature is currently limited.

The impact of COVID-19 on industry-related characteristics and risk contagion

We use the cutting-edge causal forest algorithm to analyze the heterogeneous treatment effects of the COVID-19 outbreak on China's industry indexes. The variable importance index is used with the causal forest and complex network methods to analyze the characteristics of industrial relations and the types of industry risk contagion before and after the COVID-19 outbreak. The results show that the heterogeneity of industries was significantly weakened during the COVID-19 outbreak. In addition, the COVID-19 outbreak changed the original structure of the industry-related network, which shifted to a star network structure with leisure services at the core. It also changed the type of risk contagion between industries, from the original middleman risk type to the input risk type.

Identification of effective spreaders in contact networks using dynamical influence

Contact networks provide insights on disease spread due to the duration of close proximity interactions. For systems governed by consensus dynamics, network structure is key to optimising the spread of information. For disease spread over contact networks, the structure would be expected to be similarly influential. However, metrics that are essentially agnostic to the network's structure, such as weighted degree (strength) centrality and its variants, perform near-optimally in selecting effective spreaders. These degree-based metrics outperform eigenvector centrality, despite disease spread over a network being a random walk process. This paper improves eigenvector-based spreader selection by introducing the non-linear relationship between contact time and the probability of disease transmission into the assessment of network dynamics. This approximation of disease spread dynamics is achieved by altering the Laplacian matrix, which in turn highlights why nodes with a high degree are such influential disease spreaders. From this approach, a trichotomy emerges on the definition of an effective spreader where, for susceptible-infected simulations, eigenvector-based selections can either optimise the initial rate of infection, the average rate of infection, or produce the fastest time to full infection of the network. Simulated and real-world human contact networks are examined, with insights also drawn on the effective adaptation of ant colony contact networks to reduce pathogen spread and protect the queen ant.

Microporous polyimide VOC-rejective membrane for the separation of nitrogen/VOC mixture

The treatment of VOCs (volatile organic compounds) in waste streams is very important. Herein, we propose to use a network microporous polyimide (PI) membrane for the molecular sieving of nitrogen over VOC molecules to control their emission. 2,6,14-triaminotriptycene (Trip) was reacted with aromatic dianhydride monomers, such as 3,3',4,4'-benzophenone tetracarboxylic dianhydride (BTDA), to synthesize ultramicroporous polyimides, which readily form composite membranes via solution coating. The properties of the PIs were characterized by X-ray photoelectron spectroscopy (XPS), Brunner-Emmet-Teller (BET) analysis, etc., which validated the formation of a network structure and ultramicroporosity in these polyimides. Therefore, the outstanding separation performance for the separation of nitrogen over VOCs, such as cyclohexane, by molecular sieving was obtained by using these membranes; a rejection higher than 99 % was realized with a permeability of approximately 2000∼2600 Barrer under a temperature of 25 °C and feed concentration of 30,000 ± 2000 ppm. Finally, the stability of the Trip-BTDA-PI membrane over time was studied.

The evolution of a collaboration network and its impact on innovation performance under the background of government-funded support: an empirical study in the Chinese wind power sector

To accelerate the transformation and application of basic research results, the Chinese government has repeatedly mentioned in a government work report that it is necessary to support research and innovation collaborations between knowledge research institutions and enterprises. However, few studies have focused on the evolution of collaborations between these organizations and the impact of collaborations on innovation performance (IP) in the field of renewable energy under the background of government-funded support (GFS). Based on scientific publications, we construct a GFS collaboration network in the wind power field to investigate the evolution of network structure characteristics, attribute proximity variables, and applied research collaboration (ARC), and we study the impact of network evolution on the IP of actors. The results show that the focal actor of the collaboration network prefers to engage in ARC with partners who are familiar and have the same knowledge base in different provinces. This collaboration tendency will reduce geographical proximity and increase the direct ties, indirect ties, technological proximity, and ARC of the ego network. Among them, direct ties have an inverted U-shaped effect on IP, geographical proximity has a significantly negative impact on IP, and the remaining variables have positive impacts on IP. Taken together, when the direct ties is within a certain range, these collaboration tendencies in a GFS collaboration network positively affect the IP of research institutions and enterprises.

The network and dimensionality structure of affective psychoses: an exploratory graph analysis approach

BACKGROUND

The dimensional symptom structure of classes of affective psychoses, and more specifically the relationships between affective and mood symptoms, has been poorly researched. Here, we examined these questions from a network analysis perspective.

METHODS

Using Exploratory Graph Analysis (EGA) and network centrality parameters, we examined the dimensionality and network structure of 28 mood and psychotic symptoms in subjects diagnosed with schizoaffective disorder (n=124), psychotic bipolar disorder (n=345) or psychotic depression (n=245), such as in the global sample of affective psychoses.

RESULTS

EGA identified four dimensions in subjects with schizoaffective or bipolar disorders (depression, mania, positive and negative) and three dimensions in subjects with psychotic depression (depression, psychosis and activation). The item composition of dimensions and the most central symptoms varied substantially across diagnoses. The most central (i.e., interconnected) symptoms in schizoaffective disorder, psychotic bipolar disorder and psychotic depression were hallucinations, delusions and depressive mood, respectively. Classes of affective psychoses significantly differed in terms of network structure but not in network global strength.

LIMITATIONS

The cross-sectional nature of this study precludes conclusions about the causal dynamics between affective and psychotic symptoms.

CONCLUSION

EGA is a powerful tool for examining the dimensionality and network structure of symptoms in affective psychoses showing that both the interconnectivity pattern between affective and psychotic symptoms and the most central symptoms vary across classes of affective psychoses. The findings outline the value of specific diagnoses in explaining the relationships between mood and affective symptoms.

Transglutaminase-mediated crosslinking of Bambara groundnut protein hydrogels: Implications on rheological, textural and microstructural properties

Interest in plant protein-based hydrogels with desirable strength has been increasing in recent years. In this study, Bambara groundnut protein isolate (BPI) was crosslinked with transglutaminase (TGase) (0 - 25 U/g protein) during gelation and rheological, textural and microstructural properties of the resulting hydrogels were investigated. Treatment with TGase up to 15 U/g protein resulted in the formation of hydrogels with small pores and an organised homogeneous network. G' of TGase-treated BPI hydrogels was more than ten-fold higher than G" throughout the frequency range of 0-100 rad/s, suggesting dominance of the elastic like behaviour. BPI hydrogel with the highest G' (6967 Pa) and hardness (5.60 N) was formed at 15 U/g protein of TGase activity. The hydrogel had a high distribution β-sheets (53.52%) and α-helixes (26.17%) as compared to the β-turns and random coils. However, a further increase in TGase activity did not improve the hydrogel properties. Transglutaminase mediated crosslinking of BPI hydrogel was demonstrated by the reduction in amine and thiol groups and the formation of a new protein band (56 kDa) in crosslinked hydrogels. Overall, TGase promoted the formation of a strong gel with an organised network.

Plant Grafting Shapes Complexity and Co-occurrence of Rhizobacterial Assemblages

Grafting is a basic technique which is widely used to increase yield and enhance biotic and abiotic stress tolerance in plant production. The diversity and interactions of rhizobacterial assemblages shaped by grafting are important for the growth of their hosts but remain poorly understood. To test the hypothesis that plant grafting shapes complexity and co-occurrence of rhizobacterial assemblage, four types of plants, including ungrafted bottle gourd (B), ungrafted watermelon (W), grafted watermelon with bottle gourd rootstock (W/B), and grafted bottle gourd with watermelon rootstock (B/W), were cultivated in two soil types in a greenhouse, and the rhizosphere bacterial communities were analyzed by 16S rRNA gene high-throughput sequencing. Both the soil type and grafting significantly influenced the bacterial community composition. Grafting increased bacterial within-sample diversity in both soils. Core enriched operational taxonomic units (OTUs) in the W/B rhizosphere compared with the other three treatments (B, W, and B/W) were mainly affiliated with Alphaproteobacteria, Deltaproteobacteria, and Bacteroidetes, which are likely related to methanol oxidation, methylotrophy, fermentation, and ureolysis. Co-occurrence network analysis proved that grafting increased network complexity, including the number of nodes, edges, and modules. Moreover, grafting strengthened the structural robustness of the network in the rhizosphere, while ungrafted watermelon had the lowest network robustness. Homogeneous selection played a predominant role in bacterial community assembly, and the contribution of dispersal limitation was increased in grafted watermelon with bottle gourd rootstock. Grafting increased the diversity and transformed the network topology of the bacterial community, which indicated that grafting could improve species coexistence in the watermelon rhizosphere.

Datasets for the microstructure of nanoscale metal network structures and for its evolution during coarsening

The datasets in this work are files containing atom position coordinates of volume elements approximating nanoporous gold made by dealloying and annealing. The material is represented in an as-prepared state and in various stages of coarsening, as described in Phys. Rev. Mater, 3 (2019) 076001. Realistic initial structures of different solid fractions have been constructed by the leveled-wave algorithm, approximating mixtures at the end of early-stage spinodal decomposition. The microstructural evolution during coarsening by surface diffusion was approximated by on-lattice kinetic Monte-Carlo simulation. The data sets refer to solid fractions from 0.22 to 0.50, providing for different initial connectivity of the bicontinuous structures. Coarsening at two temperatures, 900 K and 1800 K, explores two different degrees of surface energy anisotropy - more faceted at 900 K and more rough at 1800 K. Each structure takes the form of a face-centred cubic lattice with approximately 32 million sites. A site can be occupied by either void or atom. 3D periodic boundary conditions are satisfied. Tables list each structure's properties, and specifically the specific surface area, two different measures for the ligament size, the net topological genus as well as the scaled genus. The atom coordinate files may serve as the basis for geometry analysis and for atomistic as well as finite element simulation studies of nanoporous as well as spinodally decomposed materials. The data sets are accessible via the TORE repository at http://hdl.handle.net/11420/3253.

Datasets for the microstructure of nanoscale metal network structures and for its evolution during coarsening

The datasets in this work are files containing atom position coordinates of volume elements approximating nanoporous gold made by dealloying and annealing. The material is represented in an as-prepared state and in various stages of coarsening, as described in Phys. Rev. Mater, 3 (2019) 076001. Realistic initial structures of different solid fractions have been constructed by the leveled-wave algorithm, approximating mixtures at the end of early-stage spinodal decomposition. The microstructural evolution during coarsening by surface diffusion was approximated by on-lattice kinetic Monte-Carlo simulation. The data sets refer to solid fractions from 0.22 to 0.50, providing for different initial connectivity of the bicontinuous structures. Coarsening at two temperatures, 900 K and 1800 K, explores two different degrees of surface energy anisotropy – more faceted at 900 K and more rough at 1800 K. Each structure takes the form of a face-centred cubic lattice with approximately 32 million sites. A site can be occupied by either void or atom. 3D periodic boundary conditions are satisfied. Tables list each structure's properties, and specifically the specific surface area, two different measures for the ligament size, the net topological genus as well as the scaled genus. The atom coordinate files may serve as the basis for geometry analysis and for atomistic as well as finite element simulation studies of nanoporous as well as spinodally decomposed materials. The data sets are accessible via the TORE repository at http://hdl.handle.net/11420/3253.

Influence of nanomaterial morphology of guar-gum fracturing fluid, physical and mechanical properties

Nanosilica, multiwalled carbon nanotubes and graphite powder have different effects on guar gum fracturing fluid because of the different morphologies of these nanomaterials. The results showed that the apparent viscosity, temperature tolerance, elastic modulus and tensile strength of nano-hybrid guar gum fracturing fluids were improved by nanomaterials compared to those properties of blank fracturing fluid (without nanomaterials). However, microscopic analysis by SEM and TEM revealed that different nanomaterials played different roles in the network structure of guar gum fracturing fluid. In terms of micro particle size, modified nano-SiO₂ (M-NS) played a nuclear point and skeleton role in the fracturing fluid and obviously enhanced the network structure. Hydroxylated multiwalled carbon nanotubes (MWNTs-OH) and guar gum macromolecular chains were intertwined. Graphene oxide (GO) intercalation entered the guar gum molecular chain and the interaction was relatively weak because of its sheet structure.

Evaluating the oil production and wastewater treatment efficiency by an extended two-stage network structure model with feedback variables

Oil is an indispensable and important energy source in modern society, and oil production plays a vital role in economic development. However, there is no denying that oil production has a very bad impact on the environment. To realize the sustainable development of oil production, the environmental problems caused by oil production need to be controlled and managed strictly. Aiming at the practical problems of insufficient recoverable reserves of high quality oil and aggravating environmental pollution, efficient oil production and wastewater treatment become more and more important. Therefore, the whole system is divided into two stages. The stage 1 is oil development, and the stage 2 is wastewater treatment. Considering that the model needs to solve the undesirable output, an extended two-stage Slacks-Based Measure (SBM) Data Envelopment Analysis (DEA) network structure model with a feedback variable is established. The efficiency value of each stage can be obtained, and the weakness of each stage can be identified, so that the efficiency value of the whole system is more accurate. And then thirteen oilfields are selected for the numerical analysis to verify the validity and accuracy of the proposed model, the results demonstrate that the overall system is efficient only if the two stages are efficient; the oil production has higher efficiencies than the oilfield wastewater treatment; There is a stronger relationship between the efficiency of oilfield wastewater treatment and the whole system. A comparison with a traditional model demonstrated that the proposed model has a more scientific, stable and practical evaluation methods.

Fabrication of a ferrocene-based monolithic column with a network structure and its application in separation of protein and small molecules

A novel ferrocene-based monolith with a network structure was fabricated via in situ free radical polymerization using vinyl ferrocene as the co-monomer within a stainless-steel column (50 × 4.6 mm i.d.) for the separation of proteins from complex bio-samples, taking merit of the specific absorption of ferrocene to protein, including human plasma, egg white, and standard proteins. The morphology and pore size distribution indicate that the optimized monolith has a relatively uniform structure with the network. The results showed that 26 fractions were separated from human plasma, and the column efficiency of the aromatic small molecule, naphthalene, was up to 30,560 plates m^-1. The homemade monolith showed excellent selectivity for intact proteins, mainly depending on the hydrophobic chromatography mechanism of ferrocene. In addition, the electrostatic interaction and hydrogen-bond interaction were the additional interactions in the chromatographic separation owing to the sandwich structure of ferrocene present in the monolithic column.

Phyllosphere epiphytic and endophytic fungal community and network structures differ in a tropical mangrove ecosystem

BACKGROUND

Revealing the relationship between plants and fungi is very important in understanding biodiversity maintenance, community stability, and ecosystem functioning. However, differences in the community and network structures of phyllosphere epiphytic and endophytic fungi are currently poorly documented. In this study, we examined epiphytic and endophytic fungal communities associated with the leaves of six mangrove species using Illumina MiSeq sequencing of internal transcribed spacer 2 (ITS2) sequences.

RESULTS

A total of 635 operational taxonomic units (OTUs) of endophytic and epiphytic fungi were obtained at a 97% sequence similarity level; they were dominated by Dothideomycetes and Tremellomycetes. Plant identity had a significant effect on the OTU richness of endophytic fungi, but not on epiphytic fungi. The community composition of epiphytic and endophytic fungi was significantly different, and plant identity had a greater effect on endophytic fungi than on epiphytic fungi. Network analysis showed that both epiphytic and endophytic network structures were characterized by significantly highly specialized and modular but lowly connected and anti-nested properties. Furthermore, the endophytic network had higher levels of specialization and modularity but lower connectance and stronger anti-nestedness than the epiphytic network.

CONCLUSIONS

This study reveals that the phyllosphere epiphytic and endophytic fungal communities differ, and plant identity has a greater effect on the endophytic fungi than on epiphytic fungi. These findings demonstrate the role of host plant identity in driving phyllosphere epiphytic and endophytic community structure.

Chronic Dysregulation of Cortical and Subcortical Metabolism After Experimental Traumatic Brain Injury

Traumatic brain injury (TBI) is a leading cause of death and long-term disability worldwide. Although chronic disability is common after TBI, effective treatments remain elusive and chronic TBI pathophysiology is not well understood. Early after TBI, brain metabolism is disrupted due to unregulated ion release, mitochondrial damage, and interruption of molecular trafficking. This metabolic disruption causes at least part of the TBI pathology. However, it is not clear how persistent or pervasive metabolic injury is at later stages of injury. Using untargeted 1H-NMR metabolomics, we examined ex vivo hippocampus, striatum, thalamus, frontal cortex, and brainstem tissue in a rat lateral fluid percussion model of chronic brain injury. We found altered tissue concentrations of metabolites in the hippocampus and thalamus consistent with dysregulation of energy metabolism and excitatory neurotransmission. Furthermore, differential correlation analysis provided additional evidence of metabolic dysregulation, most notably in brainstem and frontal cortex, suggesting that metabolic consequences of injury are persistent and widespread. Interestingly, the patterns of network changes were region-specific. The individual metabolic signatures after injury in different structures of the brain at rest may reflect different compensatory mechanisms engaged to meet variable metabolic demands across brain regions.