Network Formation Research Articles

Green innovation ecosystem evolution: Diffusion of positive green innovation game strategies on complex networks

The essence of the evolution of the green innovation ecosystem is the process by which the positive strategy of green innovation spreads in a complex network. In this study, the "Object-Technology-Environment-Management-Culture (OETMC)" structure paradigm of innovation ecosystems is presented, and a causal analysis framework of green innovation ecosystem evolution based on green innovation behavior strategy, supported by green innovation efficiency and focused on green innovation ecosystems is developed. Based on this framework, the structure of the green innovation ecosystem and the diffusion process of positive green innovation in the network are discussed. The results reveal the following. (1) The complexity of the green innovation ecological network has visibly improved, but numerous blank connections remain. These are the key constraints that hinder structural evolution. (2) The appearance of a large number of long-range connections weakens the constraint of geographical distance but also hinders edge nodes from joining the network. (3) The existence of preference attachment and power law distribution of the green innovation ecological network leads to the incomplete convergence of positive green innovation strategy at any initial strategy ratio. (4) Default cost and pollution tax rate ensure the enthusiasm of green innovation actors to seek innovation cooperation by increasing opportunity costs, thus accelerating the formation and reconstruction of the green innovation ecological network. These conclusions provide a decision-making reference for governments to encourage green innovation subjects to formulate targeted policies.

Privacy-Preserving and Diversity-Aware Trust-based Team Formation in Online Social Networks

As online social networks (OSNs) become more prevalent, a new paradigm for problem-solving through crowd-sourcing has emerged. By leveraging the OSN platforms, users can post a problem to be solved and then form a team to collaborate and solve the problem. A common concern in OSNs is how to form effective collaborative teams, as various tasks are completed through online collaborative networks. A team’s diversity in expertise has received high attention to producing high team performance in developing team formation (TF) algorithms. However, the effect of team diversity on performance under different types of tasks has not been extensively studied. Another important issue is how to balance the need to preserve individuals’ privacy with the need to maximize performance through active collaboration, as these two goals may conflict with each other. This research has not been actively studied in the literature. In this work, we develop a team formation (TF) algorithm in the context of OSNs that can maximize team performance and preserve team members’ privacy under different types of tasks. Our proposed PR iv A cy- D iversity- A ware T eam F ormation framework, called PRADA-TF , is based on trust relationships between users in OSNs where trust is measured based on a user’s expertise and privacy preference levels. The PRADA-TF algorithm considers the team members’ domain expertise, privacy preferences, and the team’s expertise diversity in the process of team formation. Our approach employs game-theoretic principles Mechanism Design to motivate self-interested individuals within a team formation context, positioning the mechanism designer as the pivotal team leader responsible for assembling the team. We use two real-world datasets (i.e., Netscience and IMDb) to generate different semi-synthetic datasets for constructing trust networks using a belief model (i.e., Subjective Logic) and identifying trustworthy users as candidate team members. We evaluate the effectiveness of our proposed PRADA-TF scheme in four variants against three baseline methods in the literature. Our analysis focuses on three performance metrics for studying OSNs: social welfare, privacy loss, and team diversity.

Visual Quantitation of Dopamine-Inspired Fluorescent Adhesion with Orthogonal Phenanthrenequinone Photochemistry.

Quantifying adhesion is crucial for understanding adhesion mechanisms and developing advanced dopamine-inspired materials and devices. However, achieving nondestructive and real-time quantitation of adhesion using optical spectra remains challenging. Here, we present a dopamine-inspired orthogonal phenanthrenequinone photochemistry strategy for the one-step adhesion and real-time visual quantitation of fluorescent spectra. This strategy utilizes phenanthrenequinone-mediated photochemistry to facilitate conjoined network formation in the adhesive through simultaneous photoclick cycloaddition and free-radical polymerization. The resulting hydrogel-like adhesive exhibits good mechanical performance, with a Young's modulus of 300 kPa, a toughness of 750 kJ m-3, and a fracture energy of 4500 J m-2. This adhesive, along with polycyclic aromatic phenanthrenequinones, shows strong adhesion (>100 kPa) and interfacial toughness thresholds (250 J m-2) on diverse surfaces─twice to triple as much as typical dopamine-contained adhesives. Importantly, such an adhesive demonstrates excellent fluorescent performance under UV irradiation, closely correlating with its adhesion strengths. Their fluorescence intensities remain constant after continuous stretching/releasing treatment and even in the dried state. Therefore, this dopamine-inspired orthogonal phenanthrenequinone photochemistry is readily available for real-time and nondestructive visual quantitation of adhesion performance under various conditions. Moreover, the adhesive precursor is chemically ultrastable for more than seven months and achieves adhesion on substrates within seconds upon blue light irradiation. As a proof-of-concept, we leverage the rapid and visual quantitation of adhesion and printability to create fluorescent patterns and structures, showcasing applications in information storage, adhesion prediction, and self-reporting properties. This general and straightforward strategy holds promise for rapidly preparing functional adhesive materials and designing high-performance wearable devices.

Enhanced DC Breakdown Strength of XLPE via Denser Cross-Linking Network Formation with Liquid Polybutadiene

Enhanced DC Breakdown Strength of XLPE via Denser Cross-Linking Network Formation with Liquid Polybutadiene

Elucidating the dynamics behavior of PFASs at the water and hydrophobic low-melting mixture solvents interphase

In this work, we studied the interphase dynamics of hydrophobic low-melting mixture solvents (LoMMSs) for the advanced remediation of per- and polyfluoroalkyl substances (PFASs) in wastewater systems by using classical molecular dynamics (MD) simulations. We showed the interaction between widely prevalent PFAS-specifically perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) and an innovative LoMMS composed of cineole (CIN) and linoleic acid (LNA) at equimolar ratios. Our investigations reveal that the interphase diffusion of PFASs through the LoMMS is a multi-stage process involving diffusion, interface sorption, and subsequent migration into the bulk aqueous phase. The simulations underscore a robust affinity between the PFASs molecules and the LoMMS, with the displacement of PFASs from the water interface marked by the formation of complex hydrogen-bonded networks. This intricate interplay results in a significant reorganization of water molecules, leading to potential clustering at the interface and compression of the fluid phase. These findings not only substantiate the efficacy of LoMMSs in PFASs extraction but also highlight the need to account for competitive interactions at the water interface, which could impede the absorption kinetics. By providing a detailed molecular-level narrative of the interphase capture phenomena, this study paves the way for designing efficient, low-toxicity LoMMS-based systems for the targeted removal of PFASs from contaminated water sources.

Membrane localization of actin filaments stabilizes giant unilamellar vesicles against external deforming forces

Actin organization is crucial for establishing cell polarity, which influences processes such as directed cell motility and division. Despite its critical role in living organisms, achieving similar polarity in synthetic cells remains challenging. In this study, we employ a bottom-up approach to investigate how molecular crowders facilitate the formation of cortex-like actin networks and how these networks localize and organize based on membrane shape. Using giant unilamellar vesicles (GUVs) as models for cell membranes, we show that actin filaments can arrange along the membrane to form cortex-like structures. Notably, this organization is achieved using only actin and crowders as a minimal set of components. We utilize surface micropatterning to examine actin filament organization in deformed GUVs adhered to various pattern shapes. Our findings indicate that at the periphery of spherical GUVs, actin bundles align along the membrane. However, in highly curved regions of adhered GUVs, actin bundles avoid crossing the highly curved edges perpendicular to the adhesion site and instead remain in the lower curved regions by aligning parallel to the micropatterned surface. Furthermore, the actin bundles increase the stiffness of the GUVs, effectively counteracting strong deformations when GUVs adhere to micropatterns. This finding is corroborated by real-time deformability cytometry on GUVs with synthetic actin cortices. By precisely manipulating the shape of GUVs, our study provides a minimal system to investigate the interplay between actin structures and the membrane. Our findings provide insights into the spatial organization of actin structures within crowded environments, specifically inside GUVs that resemble the size and shape of cells. This study advances our understanding of actin network organization and functionality within cell-sized compartments.

Optimizing the Microstructure and Properties of Fe–Ni–Cu–Mo–C Sintered Steel by TiB2

The Fe–Ni–Cu–Mo–C powder metallurgy sintered steels with TiB2 reinforced were prepared by the conventional powder metallurgy techniques. This study explored the influence of incremental TiB2 additions, ranging from 0.1 to 0.6 wt.%, on the microstructure and properties of these steels. The results reveal that the microstructures primarily consist of martensite, Ni-rich austenite, Cu-rich pearlite, TiB2, and Ti–O rich nanoparticles. The latter form via a reaction between TiB2 and free oxygen. Notably, both the density and impact strength of the steels showed enhancement with increasing TiB2 content. The optimal values, 7.25 g/cm3 for density and 17.23 J/cm2 for impact strength, were observed at a TiB2 concentration of 0.5%. The hardness and ultimate tensile strength also increased steadily, reaching maxima of 38.7 and 1083.7 MPa at 0.6% TiB2, respectively. However, excessive TiB2 led to the formation of a net-like B-containing eutectic network, adversely affecting the steel properties. Steels with 0.5% TiB2 exhibited excellent wear resistance. At 200 rpm, the dominant failure mode was abrasive wear, which shifted to adhesive wear with oxidation at 400 rpm, followed by abrasive wear.

Developmental dynamics of mitochondrial fission and fusion proteins in functionally divergent skeletal muscles of goat.

During skeletal muscle development, the intricate mitochondrial network formation relies on continuous fission and fusion. This process in larger mammals differs from rodents, the most used animal models. However, the expression pattern of proteins regulating mitochondrial dynamics in developing skeletal muscle remains unexplored in larger mammals. Therefore, we characterized the cellular expression and tissue-level distribution of these proteins during development taking goat as a model. We have performed histological and immunohistochemical analyses to study metabolic features in various muscles. Neonatal muscles display uniform distribution of mitochondrial activity. In contrast, adult muscles exhibit clear distinctions based on their function, whether dedicated for posture maintenance or facilitating locomotion. Mitochondrial fission proteins like DRP-1, MFF, and fusion proteins like MFN-1 and 2 are abundantly expressed in neonatal muscles. Fission proteins exhibit drastic downregulation with limited peripheral expression, whereas fusion proteins continue to express in a fiber-specific manner during adulthood. Locomotory muscles exhibit different fibers based on mitochondrial activity and peripheralization with high SDH activity. The proximity ligation assay between MFN1 and MFN2 demonstrates that their interaction is restricted to subsarcolemmal mitochondria in adult fibers while distributed evenly in neonatal fibers. These differences between postural and locomotory muscles suggest their physiological and metabolic properties are different.

THE SUCCESS OF ND-YAG LASER IN THE TREATMENT OF VENOUS MALFORMATIONS OF THE ORAL MUCOSA ABOUT TWO CASES

Venous malformations are the result of errors in endothelial cell morphogenesis, causing disorganized angiogenesis and intimal smooth muscle proliferation. (1) This results in the formation of dilated networks of venous lakes that are hemodynamically non-functional. (1,2) Depending on location, they may go unnoticed for years prior to presentation, and range from asymptomatic superficial varicosities to large deforming craniofacial lesions. The management of venous malformation will depend on the localization and expansion of the malformation, and there are multiple therapeutic approaches: sclerotherapy, surgery, and medical management. Lasers, another modality for treating VMs. we report two casesof success with the Nd Yag laser in the treatment ofsuperficialvenous malformations the oral mucosa.

BC-g-PAA: Characterization and Establishment of the IPN Hydrogel

A study on the manufacture of bacterial cellulose IPN hydrogel crosslinked poly acrylic acid using the MBA crosslinker. This study aims to characterize and observe the reaction to form bacterial cellulose-based hydrogel IPN. The BC-g-PAA was characterized by the degree of cross-linking, swelling ratio, and FTIR analysis. The results of this study found predictions of the reaction process for the formation of IPN Hydrogel in several process stages, namely 1) The polymerization process of bacterial cellulose chains that form cross-linked networks independently, 2) The process of cross-linking Acrylate monomers with MBA crosslinkers in three steps, i.e. initiation, propagation and termination, 3) Reaction process Formation of IPN network. The results of the characterization test for the degree of crosslinking were 54.55%; Swelling ratio of 1631.25%. FTIR analysis shows that there is a peak that identifies the occurrence of crosslinking

Physical Properties and Biochemical Composition of Extracellular Matrix-Derived Hydrogels Dictate Vascularization Potential in an Organ-Dependent Fashion.

The inherent extracellular matrix (ECM) originating from a specific tissue impacts the process of vascularization, specifically vascular network formation (VNF) orchestrated by endothelial cells (ECs). The specific contribution toward these processes of ECM from highly disparate organs such as the skin and lungs remains a relatively unexplored area. In this study, we compared VNF and ECM remodeling mediated by microvascular ECs within gel, lung, and combinations thereof (hybrid) ECM hydrogels. Irrespective of the EC source, the skin-derived ECM hydrogel exhibited a higher propensity to drive and support VNF compared to both lung and hybrid ECM hydrogels. There were distinct disparities in the physical properties of the three types of hydrogels, including viscoelastic properties and complex architectural configurations, including fiber diameter, pore area, and numbers among the fibers. The hybrid ECM hydrogel properties were unique and not the sum of the component ECM parts. Furthermore, cellular ECM remodeling responses varied with skin ECM hydrogels promoting matrix metalloproteinase 1 (MMP1) secretion, while hybrid ECM hydrogels exhibited increased MMP9, fibronectin, and collagen IV deposition. Principal component analysis (PCA) indicated that the influence of a gel's mechanical properties on VNF was stronger than the biochemical composition. These data indicate that the organ-specific properties of an ECM dictate its capacity to support VNF, while intriguingly showing that ECs respond to more than just the biochemical constituents of an ECM. The study suggests potential applications in regenerative medicine by strategically selecting ECM origin or combinations to manipulate vascularization, offering promising prospects for enhancing wound healing through pro-regenerative interventions.

Standardizing a method for functional assessment of neural networks in brain organoids

During the last decade brain organoids have emerged as an attractive model system, allowing stem cells to be differentiated into complex 3D models, recapitulating many aspects of human brain development. Whilst many studies have analysed anatomical and cytoarchitectural characteristics of organoids, their functional characterisation has been limited, and highly variable between studies. Standardised, consistent methods for recording functional activity are critical to providing a functional understanding of neuronal networks at the synaptic and network level that can yield useful information about functional network phenotypes in disease and healthy states. In this study we outline a detailed methodology for calcium imaging and Multi-Electrode Array (MEA) recordings in brain organoids. To illustrate the utility of these functional interrogation techniques in uncovering induced differences in neural network activity we applied various stimulating media protocols. We demonstrate overlapping information from the two modalities, with comparable numbers of active cells in the four treatment groups and an increase in synchronous behaviour in BrainPhys treated groups. Further development of analysis pipelines to reveal network level changes in brain organoids will enrich our understanding of network formation and perturbation in these structures, and aid in the future development of drugs that target neurological disorders at the network level.

Axion domain walls, small instantons, and non-invertible symmetry breaking

Non-invertible global symmetry often predicts degeneracy in axion potentials and carries important information about the global form of the gauge group. When these symmetries are spontaneously broken they can lead to the formation of stable axion domain wall networks which support topological degrees of freedom on their worldvolume. Such non-invertible symmetries can be broken by embedding into appropriate larger UV gauge groups where small instanton contributions lift the vacuum degeneracy, and provide a possible solution to the domain wall problem. We explain these ideas in simple illustrative examples and then apply them to the Standard Model, whose gauge algebra and matter content are consistent with several possible global structures. Each possible global structure leads to different selection rules on the axion couplings, and various UV completions of the Standard Model lead to more specific relations. As a proof of principle, we also present an example of a UV embedding of the Standard Model which can solve the axion domain wall problem. The formation and annihilation of the long-lived axion domain walls can lead to observables, such as gravitational wave signals. Observing such signals, in combination with the axion coupling measurements, can provide valuable insight into the global structure of the Standard Model, as well as its UV completion.

An Ultramicroporous Graphene-Based 3D Structure Derived from Cellulose-Based Biomass for High-Performance CO2 Capture.

The use of powered activated carbon is often limited by inconsistent particle sizes and porosities, leading to reduced adsorption efficiencies. In this study, we demonstrated a practical and environmentally friendly method for creating a 3D graphene nanostructure with highly uniform ultramicropores from wood-based biomass through a series of delignification, carbonization, and activation processes. In addition, we evaluated the capture characteristics of this structure for CO2, CH4, and N2 gases as well as its selectivity for binary-mixture gases. Based on textural and chemical analyses, the delignified monolith had a lamellar structure interconnected by cellulose-based fibers. Interestingly, applying the KOH vapor activation technique solely to the delignified samples led to the formation of a monolithic 3D network composed of interconnected graphene sheets with a high degree of crystallinity. Especially, the Act. 1000 sample exhibited a specific surface area of 1480 m2/g and a considerable pore volume of 0.581 cm3/g, featuring consistently uniform ultramicropores over 90% in the range of 3.5-11 Å. The monolithic graphene-based samples, predominantly composed of ultramicropores, demonstrated a notably heightened capture capacity of 6.934 mol/kg at 110 kPa for CO2, along with favorable selectivity within binary gas mixtures (CO2/N2, CO2/CH4, and CO2/CH4). Our findings suggest that this biomass-derived 3D structure has the potential to serve as a monolithic adsorbent in gas separation applications.

Circulating cluster miR-99b/let-7e/miR-125a expression associates with endothelial function, cytokine, and chemokine levels in myocardial infarction patients

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Spanish Ministry of Science and Innovation (ISCIII) co-financed by the European Regional Development Fund (ERDF), and by the Generalitat Valenciana Introduction During vascular remodelling following a myocardial infarction, miRNAs can modulate endothelial function in a post-transcriptional manner. Our study is focused on the cluster miR-99b/let-7e/miR-125a, examining its serum expression during the acute phase of a Non-ST-segment Elevation Myocardial Infarction (NSTEMI) and its expression one year later. Purpose All the miRNA miR-99b/let-7e/miR-125a cluster is hypothesized to impact endothelial function, specifically influencing cellular adhesion, proliferation, and vasculogenesis. Furthermore, it is hypothesized an association exists between the levels of miRNAs from this cluster during the acute phase of myocardial infarction and the serum levels of inflammatory cytokines and chemokines implicated in the pathology. Methods Serum RNA was extracted from control (n=41), acute NSTEMI phase (n=46), and one-year follow-up (n=24) patients. miRNA expression was quantified by qRT-PCR and miR-484 was used as endogenous control. Endothelial function was assessed by analyzing adhesion, proliferation, and vasculogenesis in human umbilical vein endothelial cells (HUVEC) and transfected with miRNA inhibitors and mimics. Serum levels of proinflammatory cytokines (IL-1β, IL-6, TNF-α, and VEGF-A), anti-inflammatory cytokines (IL-10 and IL-13), and chemokines (MCP-3, MDC, IL-8, and MIP-1α) were determined. Results The miRNA cluster components exhibited decreased expression during the acute phase of the infarction (p< 0.05) and returned to control levels after one year of follow-up. All the cluster components were high expressed in endothelial cells, and we determined the effect of these miRNAs or their inhibition on endothelial function. let-7e mimic increased (p< 0.05) cell adhesion, as well as the formation of tubular networks (p< 0.001). miR-125a inhibitor decreased cell proliferation (p< 0.05). Neither the mimic nor the inhibitor of miR-99b had effects on this endothelial function. let-7e exhibited a negative correlation with the proinflammatory cytokine TNF-α (r= -0.19, p= 0.0386) and a positive correlation with the levels of the anti-inflammatory cytokine IL-13 (r= 0.22, p= 0.0416). miR-99b showed a positive association with the chemokine MDC (r= 0.22, p= 0.0195), while the levels of miR-125a did not correlate with any of the analysed mediators. Conclusions miR-99b/let-7e/miR-125a cluster is implicated in NSTEMI and exhibits a consistent expression pattern in patients' serum, decreasing during the acute phase and returning to control levels one year after. Each of these miRNAs, especially let-7e and miR-125a, differentially affects cellular processes such as endothelial proliferation and angiogenesis. Additionally, let-7e and miR-99b miRNAs differentially impact the inflammation generated in NSTEMI. These results suggest the involvement of miRNAs from the same cluster in various processes that are coordinately activated in inflammatory situations, such as acute coronary syndrome.

Heat-induced lupin-whey protein emulsion-filled gels: Microstructural and rheological insights

This work investigates the rheological properties of lupin-whey emulsion-filled gels (EFGs) formed using a pilot scale plate heat exchanger. Samples were prepared with either lupin, whey, or a lupin-whey stabilized emulsion, mixed in a whey protein continuous phase. While whey protein in the continuous phase was mainly responsible for the formation of a primary gel network, differences were observed depending on the droplet-whey protein matrix interactions. Full or partial replacement of interfacial proteins with lupin proteins resulted in softer, more ductile gels. Amplitude sweeps showed that the structure was not only affected by the interactions between the droplets and the continuous network, but also by the droplet distribution within the matrix. This work demonstrates the importance of fine tuning the interactions and the distribution of oil droplets within the gel, as these properties will lead to structural heterogeneity at the micro-scale, causing profound differences in the rheological properties. Finally, continuous heating led to stiffer, more particulate gels compared to quiescent conditions, but similar mechanisms underpinned gel formation. Thus, it is demonstrated that the design of the interactions can be screened using an in situ rheometer, although the rheological properties are affected by the shear effect of the plate heat exchanger.

Mechanism and Model Analysis of Ultralow-Temperature Fluid Fracturing in Low-Permeability Reservoir: Insights from Liquid Nitrogen Fracturing

Ultralow-temperature fluids (such as liquid nitrogen, liquid CO2) are novel waterless fracturing technologies designed for dry, water-sensitive reservoirs. Due to their ultralow temperatures, high compression ratios, strong frost heaving forces, and low viscosities, they offer a solution for enhancing the fracturing and permeability of low-permeability reservoirs. In this study, we focus on the combined effects of high-pressure fluid rock breaking, low-temperature freeze-thaw fracturing, and liquid-gas phase transformation expansion on coal-rock in low-permeability reservoirs during liquid nitrogen fracturing (LNF). We systematically analyze the factors that limit the LNF effectiveness, and we discuss the pore fracture process induced by low-temperature fracturing in coal-rock and its impact on the permeability. Based on this analysis, we propose a model and flow for fracturing low-permeability reservoirs with low-temperature fluids. The analysis suggests that the Leidenfrost effect and phase change after ultralow-temperature fluids enter the coal support the theoretical feasibility of high-pressure fluid rock breaking. The thermal impact and temperature exchange rate between the fluid and coal determine the temperature difference gradient, which directly affects the mismatch deformation and fracture development scale of different coal-rock structures. The low-temperature phase change coupling fracturing of ultralow-temperature fluids is the key to the formation of reservoir fracture networks. The coal-rock components, natural fissures, temperature difference gradients, and number of cycles are the key factors in low-temperature fracturing. In contrast to those in conventional hydraulic fracturing, the propagation and interaction of fractures under low-temperature conditions involve multifield coupling and synergistic temperature, fluid flow, fracture development, and stress distribution processes. The key factors determining the feasibility of the large-scale application of ultralow-temperature fluid fracturing in the future are the reconstruction of fracture networks and the enhancement of the permeability response in low-permeability reservoirs. Based on these considerations, we propose a model and process for LNF in low-permeability reservoirs. The research findings presented herein provide theoretical insights and practical guidance for understanding waterless fracturing mechanisms in deep reservoirs.

Exploring Dynamic Changes in HIV-1 Molecular Transmission Networks and Key Influencing Factors: Cross-Sectional Study.

The HIV-1 molecular network is an innovative tool, using gene sequences to understand transmission attributes and complementing social and sexual network studies. While previous research focused on static network characteristics, recent studies' emphasis on dynamic features enhances our understanding of real-time changes, offering insights for targeted interventions and efficient allocation of public health resources. This study aims to identify the dynamic changes occurring in HIV-1 molecular transmission networks and analyze the primary influencing factors driving the dynamics of HIV-1 molecular networks. We analyzed and compared the dynamic changes in the molecular network over a specific time period between the baseline and observed end point. The primary factors influencing the dynamic changes in the HIV-1 molecular network were identified through univariate analysis and multivariate analysis. A total of 955 HIV-1 polymerase fragments were successfully amplified from 1013 specimens; CRF01_AE and CRF07_BC were the predominant subtypes, accounting for 40.8% (n=390) and 33.6% (n=321) of the specimens, respectively. Through the analysis and comparison of the basic and terminal molecular networks, it was discovered that 144 sequences constituted static molecular networks, and 487 sequences contributed to the formation of dynamic molecular networks. The findings of the multivariate analysis indicated that the factors occupation as a student, floating population, Han ethnicity, engagement in occasional or multiple sexual partnerships, participation in anal sex, and being single were independent risk factors for the dynamic changes observed in the HIV-1 molecular network, and the odds ratio (OR; 95% CIs) values were 2.63 (1.54-4.47), 1.83 (1.17-2.84), 2.91 (1.09-7.79), 1.75 (1.06-2.90), 4.12 (2.48-6.87), 5.58 (2.43-12.80), and 2.10 (1.25-3.54), respectively. Heterosexuality and homosexuality seem to exhibit protective effects when compared to bisexuality, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. Additionally, the National Eight-Item score and sex education experience were also identified as protective factors against dynamic changes in the HIV-1 molecular network, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. The HIV-1 molecular network analysis showed 144 sequences in static networks and 487 in dynamic networks. Multivariate analysis revealed that occupation as a student, floating population, Han ethnicity, and risky sexual behavior were independent risk factors for dynamic changes, while heterosexuality and homosexuality were protective compared to bisexuality. A higher National Eight-Item score and sex education experience were also protective factors. The identification of HIV dynamic molecular networks has provided valuable insights into the characteristics of individuals undergoing dynamic alterations. These findings contribute to a better understanding of HIV-1 transmission dynamics and could inform targeted prevention strategies.

Inclusion of gender and labour standards in preferential trade agreements: evidence from North American and Canada-Chile agreements

ABSTRACT This article analyses the causes of the incorporation of gender provisions into preferential trade agreements (PTAs), based an analysis of the reasons for the inclusion of both labour and gender provisions in the North American Free Trade Agreement (NAFTA) and the United States-Mexico-Canada Agreement (USMCA), and in the Canada-Chile Free Trade Agreement (CCFTA). Drawing upon feminist and constructivist analysis, it argues for the importance of ideational factors such as policy emulation, social learning, the formation of transnational advocacy networks (TANs), as well as the role of Global South actors. Gender provisions often contain neoliberal elements that promote female entrepreneurship rather than more transformational approaches. The comparison of the USMCA and the CCFTA shows that the inclusion of stronger gender provisions in labour chapters (as in the USMCA) may be a more effective way to promote the interests of vulnerable workers than the inclusion of a gender chapter.

Local number fluctuations in ordered and disordered phases of water across temperatures: Higher-order moments and degrees of tetrahedrality.

The isothermal compressibility (i.e., related to the asymptotic number variance) of equilibrium liquid water as a function of temperature is minimal under near-ambient conditions. This anomalous non-monotonic temperature dependence is due to a balance between thermal fluctuations and the formation of tetrahedral hydrogen-bond networks. Since tetrahedrality is a many-body property, it will also influence the higher-order moments of density fluctuations, including the skewness and kurtosis. To gain a more complete picture, we examine these higher-order moments that encapsulate many-body correlations using a recently developed, advanced platform for local density fluctuations. We study an extensive set of simulated phases of water across a range of temperatures (80-1600K) with various degrees of tetrahedrality, including ice phases, equilibrium liquid water, supercritical water, and disordered nonequilibrium quenches. We find clear signatures of tetrahedrality in the higher-order moments, including the skewness and excess kurtosis, which scale for all cases with the degree of tetrahedrality. More importantly, this scaling behavior leads to non-monotonic temperature dependencies in the higher-order moments for both equilibrium and non-equilibrium phases. Specifically, under near-ambient conditions, the higher-order moments vanish most rapidly for large length scales, and the distribution quickly converges to a Gaussian in our metric. However, under non-ambient conditions, higher-order moments vanish more slowly and hence become more relevant, especially for improving information-theoretic approximations of hydrophobic solubility. The temperature non-monotonicity that we observe in the full distribution across length scales could shed light on water's nested anomalies, i.e., reveal new links between structural, dynamic, and thermodynamic anomalies.