Critical Links Research Articles

Resilience analysis of highway network under rainfall using a data-driven percolation theory-based method

This paper proposes a data-driven approach using percolation theory to analyze the resilience of highway networks under rainfall conditions. The proposed approach's main contribution is integrating real-world traffic data with percolation theory to evaluate the impact of rainfall on traffic flow and identify the critical links of highway networks. The resilience indicators, accounting for network topology and functionality, were formulated. To calculate these indicators under various rainfall intensities, the traffic flow fundamental diagrams were established using empirical rainfall and traffic data, and a probabilistic rainfall simulation model was developed. A case study of the East Midlands, UK highway network under a heavy rainfall event on September 27, 2019, validated the approach's feasibility. Furthermore, control experiments showed that the critical links identified by the proposed method enhance highway network resilience more effectively than traditional methods, thus validated the novelty of our approach.

Monitoring using artificial intelligence reveals critical links between housing conditions and respiratory health in pigs

Respiratory disease is the most significant issue in the pig industry and leads to high mortality and reduced growth rates. Housing conditions are crucial for maintaining the health and welfare of animals to optimize growth rates. This study aimed to evaluate the respiratory health status of pigs raised in different housing conditions using artificial intelligence (AI) technology and to determine the relationships between respiratory health and environmental factors. Eighty growing pigs (Largewhite × Landrace) × Duroc) were randomly distributed into two housing conditions: the control group, which had normal housing conditions, and the treatment group, which had poor housing conditions. A two-sample t test was performed to compare the groups, and a cross-correlation analysis was conducted to determine associations between respiratory health and days of exposure to environmental factors. The results show significant (p < 0.001) lower incidence of respiratory health status along with a significant (p < 0.001) greater frequency of coughing in pigs raised under poor housing conditions. Respiratory health is negatively associated with high exposure to temperature, relative humidity, and CO2 at lags 0 (R = -0.873, -0.887, and -0.869, respectively), -1 (R = -0.708, -0.742, and -0.705, respectively), and -2 (R = -0.545, -0.590, and -0.599, respectively). Furthermore, respiratory health was negatively associated with high exposure to NH3 (R = -0.420) at lag 0. In conclusion, AI technology is an effective tool for monitoring respiratory health. However, further evaluation and calibration of the alarm system threshold are recommended. These findings suggest that maintaining proper control of environmental factors can help prevent respiratory diseases in pigs.

Enabling efficient routing for traffic engineering in SDN with Deep Reinforcement Learning

Traffic Engineering (TE) is applied to optimize network transmission efficiency by managing the routing of complicated traffic. Emerging Deep Reinforcement Learning (DRL) and Software-Defined Networking (SDN) provide flexible ability for traffic management and congestion control. However, existing methods either cannot reroute the network-wide traffic in an accurate way or encounter too much calculation latency due to the inference of mathematical optimization techniques. In this paper, we propose a flexible and link-reconfigurable TE solution called EfficientTE that effectively adjusts the traffic routing based on real-time traffic demands. By analyzing the characteristics of network topology and traffic, EfficientTE selects a few links that are critical for congestion in the network. Then, we propose the idea of virtual capacity that helps the DRL algorithm adjust to different link bandwidths. Based on the traffic demand and topology information collected by the SDN controller, the DRL algorithm is used to dynamically adjust the virtual capacity of the critical links to reshape the network. To ensure network performance with low disturbance, we selectively reroute the Top-K critical flows using the weighted K-shortest path algorithm, while forwarding the major flows with default rerouting. Experiments show that EfficientTE optimizes maximum link utilization and outperforms existing TE solutions by improving the load-balancing performance ratio by at least 6.13%, 18.78%, 16.20%, and 22.81% respectively in four network topologies.

Identification of Critical Links Based on Electrical Betweenness and Neighborhood Similarity in Cyber-Physical Power Systems.

Identifying critical links is of great importance for ensuring the safety of the cyber-physical power system. Traditional electrical betweenness only considers power flow distribution on the link itself, while ignoring the local influence of neighborhood links and the coupled reaction of information flow on energy flow. An identification method based on electrical betweenness centrality and neighborhood similarity is proposed to consider the internal power flow dynamic influence existing in multi-neighborhood nodes and the topological structure interdependence between power nodes and communication nodes. Firstly, for the power network, the electrical topological overlap is proposed to quantify the vulnerability of the links. This approach comprehensively considers the local contribution of neighborhood nodes, power transmission characteristics, generator capacity, and load. Secondly, in communication networks, effective distance closeness centrality is defined to evaluate the importance of communication links, simultaneously taking into account factors such as the information equipment function and spatial relationships. Next, under the influence of coupled factors, a comprehensive model is constructed based on the dependency relationships between information flow and energy flow to more accurately assess the critical links in the power network. Finally, the simulation results show the effectiveness of the proposed method under dynamic and static attacks.

The Involvement of Cysteine-X-Cysteine Motif Chemokine Receptors in Skin Homeostasis and the Pathogenesis of Allergic Contact Dermatitis and Psoriasis.

Members of the C-X-C motif chemokine receptor (CXCR) superfamily play central roles in initiating the innate immune response in mammalian cells by orchestrating selective cell migration and immune cell activation. With its multilayered structure, the skin, which is the largest organ in the body, performs a crucial defense function, protecting the human body from harmful environmental threats and pathogens. CXCRs contribute to primary immunological defense; these receptors are differentially expressed by different types of skin cells and act as key players in initiating downstream innate immune responses. While the initiation of inflammatory responses by CXCRs is essential for pathogen elimination and tissue healing, overactivation of these receptors can enhance T-cell-mediated autoimmune responses, resulting in excessive inflammation and the development of several skin disorders, including psoriasis, atopic dermatitis, allergic contact dermatitis, vitiligo, autoimmune diseases, and skin cancers. In summary, CXCRs serve as critical links that connect innate immunity and adaptive immunity. In this article, we present the current knowledge about the functions of CXCRs in the homeostasis function of the skin and their contributions to the pathogenesis of allergic contact dermatitis and psoriasis. Furthermore, we will examine the research progress and efficacy of therapeutic approaches that target CXCRs.

The importance of the gut microbiome and its signals for a healthy nervous system and the multifaceted mechanisms of neuropsychiatric disorders.

Increasing evidence links the gut microbiome and the nervous system in health and disease. This narrative review discusses current views on the interaction between the gut microbiota, the intestinal epithelium, and the brain, and provides an overview of the communication routes and signals of the bidirectional interactions between gut microbiota and the brain, including circulatory, immunological, neuroanatomical, and neuroendocrine pathways. Similarities and differences in healthy gut microbiota in humans and mice exist that are relevant for the translational gap between non-human model systems and patients. There is an increasing spectrum of metabolites and neurotransmitters that are released and/or modulated by the gut microbiota in both homeostatic and pathological conditions. Dysbiotic disruptions occur as consequences of critical illnesses such as cancer, cardiovascular and chronic kidney disease but also neurological, mental, and pain disorders, as well as ischemic and traumatic brain injury. Changes in the gut microbiota (dysbiosis) and a concomitant imbalance in the release of mediators may be cause or consequence of diseases of the central nervous system and are increasingly emerging as critical links to the disruption of healthy physiological function, alterations in nutrition intake, exposure to hypoxic conditions and others, observed in brain disorders. Despite the generally accepted importance of the gut microbiome, the bidirectional communication routes between brain and gut are not fully understood. Elucidating these routes and signaling pathways in more detail offers novel mechanistic insight into the pathophysiology and multifaceted aspects of brain disorders.

GhCNGC13 and 32 Act as Critical Links between Growth and Immunity in Cotton.

Cyclic nucleotide-gated ion channels (CNGCs) remain poorly studied in crop plants, most of which are polyploid. In allotetraploid Upland cotton (Gossypium hirsutum), silencing GhCNGC13 and 32 impaired plant growth and shoot apical meristem (SAM) development, while triggering plant autoimmunity. Both growth hormones (indole-3-acetic acid and gibberellin) and stress hormones (abscisic acid, salicylic acid, and jasmonate) increased, while leaf photosynthesis decreased. The silenced plants exhibited an enhanced resistance to Botrytis cinerea; however, Verticillium wilt resistance was weakened, which was associated with LIPOXYGENASE2 (LOX2) downregulation. Transcriptomic analysis of silenced plants revealed 4835 differentially expressed genes (DEGs) with functional enrichment in immunity and photosynthesis. These DEGs included a set of transcription factors with significant over-representation in the HSF, NAC, and WRKY families. Moreover, numerous members of the GhCNGC family were identified among the DEGs, which may indicate a coordinated action. Collectively, our results suggested that GhCNGC13 and 32 functionally link to photosynthesis, plant growth, and plant immunity. We proposed that GhCNGC13 and 32 play a critical role in the "growth-defense tradeoff" widely observed in crops.

Puckered and JNK signaling in pioneer neurons coordinates the motor activity of the Drosophila embryo

Central nervous system organogenesis is a complex process that obeys precise architectural rules. The impact that nervous system architecture may have on its functionality remains, however, relatively unexplored. To clarify this problem, we analyze the development of the Drosophila embryonic Ventral Nerve Cord (VNC). VNC morphogenesis requires the tight control of Jun kinase (JNK) signaling in a subset of pioneer neurons, exerted in part via a negative feedback loop mediated by the dual specificity phosphatase Puckered. Here we show that the JNK pathway autonomously regulates neuronal electrophysiological properties without affecting synaptic vesicle transport. Manipulating JNK signaling activity in pioneer neurons during early embryogenesis directly influences their function as organizers of VNC architecture and, moreover, uncovers a role in the coordination of the embryonic motor circuitry that is required for hatching. Together, our data reveal critical links, mediated by the control of the JNK signaling cascade by Puckered, between the structural organization of the VNC and its functional optimization.

Comparison of topological functionality-based resilience metrics using link criticality

Resilient road networks ensure that transportation systems can withstand and return to normal performance fast after disruptions. Ensuring a better network structure for the system promises better resilience, irrespective of demand variations. Comparison between the ability of different topological functionality-based metrics in literature to measure resilience is an unexplored area. This study will bridge the gap by evaluating four such metrics. The distinguishing feature of the study is that link criticality approach and traffic functionality measures are used for comparing the metrics. The links are removed according to the order of their criticality ranking, and network performance is measured using Global Importance Index. The advantages of the proposed methodology are twofold. First, the position of critical links provides insight into the network characteristics measured by the metric. Second, the usage of traffic functionality-based performance measure for comparison ensures that the metric captures traffic perspective also. The position of critical links obtained using the four metrics for the networks considered in the study provides interesting observations about the network property that influences them. Also, the networks degrade the maximum when links are removed according to number of independent paths ranking when the network is not already majorly disrupted. Hence, it is more effective at measuring resilience in such networks. For networks that are already disrupted, removing links based on Global efficiency affected the network more.

The Heat and Carbon Characteristics of Modeled Mesoscale Eddies in the South–East Atlantic Ocean

AbstractMesoscale eddies provide critical links between the atmosphere and the ocean interior modulating the exchanges of key climatic tracers across the air‐sea and mixed‐layer interface. Mesoscale eddies, widespread in the Southern Ocean, are unresolved by Earth System Models; to what extent they modify contemporary and future heat and CO2 uptake remains unknown. The missing contribution of mesoscale eddies and their effects on properties and fluxes of heat and CO2 are investigated in the South‐East Atlantic using a mesoscale resolving (1/12°) physical biogeochemical model. Unsupervised Self‐Organizing Maps are used to separate anticyclonic and cyclonic eddies into distinct sub‐categories based on spatial characteristics in relative vorticity. Thermal drivers dominated over non‐thermal on partial pressure of ocean CO2 (pCO2sw) leading to a weaker CO2 sink in anticyclonic eddies and a stronger CO2 sink in cyclonic eddies relative to the climatological mean. Magnitudes and depth extents of tracer anomalies scale with eddy size but are also dependent on background tracer gradients. Resolving only the largest (>50 km radii) eddies leads to underestimations in total magnitude of heat storage by 52% and 77%, and underestimations of 61% and 77% in dissolved inorganic carbon (CT) storage for anticyclonic and cyclonic eddies respectively. The inclusion of smaller eddy features (<50 km) also offsets the asymmetry in heat and CT storage between anticyclonic and cyclonic eddies. Resolving eddies explicitly or improvements in existing parameterizations that fail to sufficiently include eddy effects are crucial to improving estimates of heat and CO2.

Range-constrained traffic assignment for electric vehicles under heterogeneous range anxiety

This paper studied the range-constrained traffic assignment problem (RTAP), where heterogeneous range anxiety is considered among the driving population by electric vehicles (EVs). In order not to get stranded en-route, each EV driver is assumed to have his/her own driving range limit for being able to complete the trip. As a result, two types of multi-class RTAP can be defined through discrete or continuous distributed range anxiety. Given path-based side constraint structures, we proposed two variational inequality (VI) formulations for modeling discrete and continuous RTAPs, where the former is finite-dimensional according to a discrete number of user classes and the latter is infinite-dimensional accounting for an infinite number of user classes. We reformulate the continuous RTAP into finite-dimensional by merging adjacent EV drivers into one group. A unified path-based solution framework is developed to solve the two RTAPs, built upon the gradient projection algorithm. We design column generation and dropping schemes to adaptively maintain compact path sets and an inner equilibration strategy to accelerate convergence. Finally, a small network is used to examine the correctness and effectiveness of proposed models, and a large Winnipeg network is adopted to evaluate the impacts of stochastic driving range on network flows and computation costs. Numerical results provide compelling evidence of the outstanding superiority of the proposed algorithm, and show that EV drivers with heightened sensitivity towards range anxiety may contribute to the emergence of critical links experiencing severe congestion.

Comparing Macroscale and Microscale Walkability Indicators to Establish Pick-Up/Drop-Off Locations for a Microtransit Service in a Suburban Area

Microtransit is a shared mobility service that operates between fixed-route transit and ride-hailing. It operates with a fleet of vans or minibuses within a service zone that is usually located in a rural or suburban car-oriented area with a transport demand that is temporally and spatially dispersed. Microtransit often expects customers to walk a short distance to pick-up/drop-off (PUDO) locations. The PUDO points need to be quickly, easily, and safely reachable by pedestrians. Thus, PUDO locations must be chosen after analyzing the walkability of the suburban area served by microtransit. This paper presents a comparison of macroscale and microscale indicators to assess the walkability of suburban neighborhoods where microtransit has to be introduced. We chose three suburban neighborhoods (Partanna Mondello, Tommaso Natale, and Mondello) in Palermo, Italy, as a study area, aiming to identify the best places to locate PUDO stops for a microtransit service. A GIS database has been built associating each link with a series of qualitative and quantitative attributes. Finally, we developed a walkability index that indicates the attractiveness of specific locations in terms of intermodal walkability. We also identified the critical pedestrian links that need actions to improve their walkability.

Hydrogen energy development in China: Potential assessment and policy implications

Hydrogen is a promising alternative energy source for sustainable development worldwide. Despite being the world's largest hydrogen producer, China's hydrogen energy development is uneven across regions and sectors. The lack of a comprehensive and systematic analysis makes it difficult for policymakers to identify critical areas and links for targeted action. This study aims to establish a comprehensive multi-indicator framework based on a supply-demand-policy model to rank the city's hydrogen development potential. Findings are as follows. First, demand, supply, and policy environment shape the hydrogen market. Second, the development potential of hydrogen varies considerably across regions, and regional development is dependent largely on leading cities. Third, four hydrogen development patterns have been identified: advantage-demonstration, policy-guided, market-driven, and potential-enhancing. This research provides theoretical support and practical guidance for building a hydrogen-based society and may also be applied to similar energy sources.

Harnessing sulfate-reducing bacteria with plants growing to revitalize metal-tainted coal mine soils in Midwest China: metal sequestration performance, ecological networking interaction, and functional enzymatic prediction.

Heavy metal contamination from coal mining calls for advanced bioremediation, i.e., using sulfate-reducing bacteria (SRB) technology. Yet, the interaction of SRB with native soil microbiota during metal sequestration, especially in the presence of plants, remains ambiguous. In this study, we assessed the metal sequestration capabilities, ecological network interactions, and enzymatic functions in soils treated with a predominant SRB consortium, mainly Desulfovibrio (14 OTUs, 42.15%) and Desulfobulbus (7 OTUs, 42.27%), alongside Acacia dealbata (AD) and Pisum sativum (PS) plants. The SRB consortium notably enhanced the immobilization of metals such as Zn, Cu, As, and Pb in soil, with the conversion of metals to residual forms rising from 23.47 to 75.98%. Plant inclusion introduced variability, potentially due to changes in root exudates under metal stress. While AD flourished, PS demonstrated significant enhancement in conjunction with SRB, despite initial challenges. Comprehensive microbial analyses revealed the pivotal role of SRB in influencing microbial networking, underpinning critical ecological links. This interplay between plants and SRB not only enhanced microbial diversity but also enriched soil nutrients. Further, enzymatic assessments, highlighting enzymes like NADH:ubiquinone reductase and non-specific serine/threonine protein kinase, reinforced contribution of SRB to energy metabolism and environmental resilience of the entire soil microbial community. Overall, this research underscores the potential of SRB-driven bioremediation in revitalizing soils affected by coal mining.

Identification of Critical Links in Urban Road Network Based on GIS

A GIS-based method is proposed to identify critical links in urban road networks. This study utilizes a geographic information system (GIS) to evaluate the distribution of road infrastructure, road density, and network accessibility at the micro, meso, and macro levels. At the micro level, GIS is used to assess the distribution of public facilities along the roads. At the meso level, a city’s road density distribution is evaluated. At the macro level, a spatial barrier model and a transportation network model are constructed to assess the network accessibility. An inverse distance weighting method is employed to interpolate the accessibility. Furthermore, a network topology is established, and the entropy method is utilized to evaluate the sections comprehensively. The sections are ranked based on the evaluation results to identify the critical links in the urban road network. The road-network data and points of interest (POI) data from the Anning District in Lanzhou are selected for a case study, and the results indicate that the top five critical links have scores of 0.641, 0.571, 0.570, 0.519, and 0.508, respectively. Considering the three indicators enhances the accuracy of critical section identification, demonstrating the effectiveness of the proposed method. Visualizing each indicator using GIS 10.7 provides a new approach to identifying critical links in urban road networks and offers essential theoretical support for urban planning.

Assessing transportation network redundancy by integrating route diversity and spare capacity

In this paper, we develop a new transportation network redundancy measure by integrating the route diversity and spare capacity dimensions, which have been demonstrated as two complementary dimensions of redundancy and assessed separately in the literature. Instead of modelling redundancy as two separate measures with significantly different units and scales, an integrative measure is beneficial for comprehensive comparison and selection of redundancy enhancement schemes. Specifically, we represent the transportation network by adding a virtual link directly connecting each origin-destination (O-D) pair. The virtual link choice probability is affected by both the route diversity of the O-D pair and the spare capacity of these routes, which is used in the proposed measure. Numerical examples in the realistic Winnipeg network are conducted. The effectiveness of the proposed measure is further verified by applying it to identify the critical links in the Shanghai Expressway Network, where a severe traffic accident happened in 2016.

Poverty, policies, and politics: a rights-based approach to food insecurity in Africa

Food and nutrition insecurity remain serious African concerns, reflecting government failure to meet global and regional human rights obligations to assure food availability, accessibility, utilisation, stability, sustainability, and agency. According to recent data, more than one-third of people facing severe food insecurity around the world live in Africa. The numbers may continue to rise in the absence of deliberate and human rightscentred solutions. The second biennial review report of the African Union on the Malabo Declaration on Accelerated Agricultural Growth and Transformation for Shared Prosperity and Improved Livelihoods conceded that the continent is not on track to meet the targets set out in the Declaration to end food insecurity and improve nutrition. This article investigates and advocates for a human rights-based approach to food andnutrition security. It highlights the critical links between the six main elements of food security, namely, availability, access, utilisation, stability, agency, and sustainability, and the normative obligations of states on the right to food and its interdependence with other fundamental human rights. It critically analyses the available legal frameworks on addressing foodinsecurity and its challenges, and proposes a human rights-based approach.

The usage of probiotic microorganisms in production technology of European grayling fish stock

European grayling is a perspective object of a recreational fishing. In addition, the presence of this species in sufficient quantities in rivers has a positive influence on the formation of the recreational attractiveness of mountain regions, where tourism is one of the main sources of local communities existence. However, grayling stocks in the watercourses of Ukraine are significantly depleted nowadays, and populations are in a condition of lack, what has led to the inclusion of this species into the Red Book of Ukraine. Working out of biotechnologies of artificial reproduction of rare fish species in aquaculture conditions for the further reintroduction of the resulting offspring into natural water bodies takes an important place in the system of environmental protection measures to preserve biodiversity. After all, the reintroduction into nature of artificially obtained fish fry is one of the effective ways to restore the optimal number and structure of rare fish species natural populations, and this, in turn, will allow in the future to restore the limited exploitation of the stock of these fish species. One of the critical artificial fish reproduction technology links is the transfer of larvae to external nutrition. Namely on this stage the highest mortality rates are observed. The usage of live feeds as a starter fodder can significantly improve the situation. Forage organisms, in addition to having high nutritional value, can serve as delivering tools of various targeted products, including probiotics, to a fish larvae organism. The assessment of the usage of probiotic strain Lactobacillus casei IMV B-7280 feasibility is carried, and also the possibility of usage the culture Daphnia magna Straus, 1820 grown in the presence of trehalose lipids, within the technology of early feeding of the European grayling Thymallus thymallus (Linnaeus, 1758). It was shown that the larvae of the European grayling, which received investigated probiotic microorganisms strain, had 15% bigger weight on the final stages of feeding than the larvae of the control group. Introduction to the diet of grown-up grayling larvae of the culture Daphnia magna, previously received of common cultivation with microalgae Desmodesmus armatus (Chodat) E.H.Hegewald 2000 with addition of trehalose lipids, contributed to the reduction of larval mortality and the acceleration of their growth rate. Further improvement of proposed approaches of growing grayling fish planting material can be extrapolated to other fish species and in the future may be applicable in the process of growing rare fish species in conditions of farm aquaculture fish farms, what will allow them to be involved into environmental protection activities by placing appropriate orders. This, in its turn, will contribute to the stable development of communities in rural areas.

The Impact of Climate‐Driven Lake Level Changes on Mantle Melting in Continental Rifts

AbstractClimate cycles fundamentally control surface processes that affect the distribution of water and sediment, and their associated loads, across the Earth's surface. Here, we use a geodynamic model to examine how water loading can affect mantle melt generation in continental rift settings covered by deep lakes. Our modeling results suggest that lake level fluctuations can modulate the timing and rate of mantle melting. A rapid lake level drop of 800 m has the potential to increase mantle melt volumes by enhancing mantle upwelling beneath the rift, whereas a lake level rise can lead to a reduction of mantle melting. The volume of melt produced driven by lake level fluctuations is also dependent on crustal rheology, extension rate, mantle potential temperature, and lithosphere thickness. Our study identifies the importance of water loading for controlling rift processes, while also demonstrating critical links between changing climate, rift evolution and mantle melting.

Active pantograph in high-speed railway: Review, challenges, and applications

The pantograph–catenary system (PCS) vibration causes the pantograph–catenary contact force (PCCF) to fluctuate, deteriorating current collection quality and damaging the electrical equipment. The active pantograph is one of the most promising methods for suppressing PCS coupling vibration and improving the current collection quality of high-speed trains. This paper first summarizes the research progress of five critical links in the active pantograph, including PCS modeling, control algorithm, hardware support, and HIL test verification. Then, the impact of the PCS model on numerical simulation accuracy and calculation time, the pros and cons of different control algorithms, and the execution mechanism selection are discussed. Finally, the active pantograph’s future development trend and research direction are prospected, such as model optimization, algorithm design, and signal correction. The analysis results show that establishing the PCS model should consider the representation of system dynamics and calculation efficiency. Control targets need to reflect the current collection quality comprehensively, and the measurement system needs to minimize the effect of locomotive disturbances on the observation results. The actuator structure needs to execute the control commands efficiently and quickly without affecting the operation of the raising mechanism. These factors, together with the real-time control algorithm, determine the practical effectiveness of the active pantograph.