Network Restoration Research Articles

Dacryodes edulis (G. Don) H.J. Lam modulates glucose metabolism, cholinergic activities and Nrf2 expression, while suppressing oxidative stress and dyslipidemia in diabetic rats

Ethnopharmacological relevanceDacryodes edulis L. is an evergreen tree indigenous to western and eastern Africa which is utilized for nutritional and medicinal purposes. Folklorically, different parts of the tree are used in treating and managing diabetes and its complications. AimsThe antidiabetic effect of the butanol fraction of D. edulis ethanol extract (BFDE) was studied in fructose-streptozotocin induced type 2 diabetic rats. MethodsThe ethanol extract was fractionated to yield the hexane, dichloromethane, ethyl acetate, butanol and aqueous fractions. The in vitro antidiabetic activities of the fractions were determined by their ability to inhibit α-glucosidase activity. BDFE was the most active and showed no cytotoxic effect while stimulating glucose uptake in 3T3-L1 adipocytes. Thus, selected for in vivo study. Diabetic rats were grouped into 4. The negative control group was administered water only, another group was treated with metformin (200 mg/kg bodyweight), while the other groups were administered BDFE at 150 and 300 mg/kg bodyweight respectively. Two other groups consisting of normal rats were given water and BFDE (300 mg/kg bodyweight) respectively, with the former serving as normal control. After 6 weeks of intervention, the rats were humanely sacrificed using appropriate anaesthesia. ResultsTreatment with the fraction significantly (p < 0.05) reduced the blood glucose level of the diabetic rats, with concomitant increase in serum insulin secretion. It also caused significant (p < 0.05) elevation of reduced glutathione level, superoxide dismutase, catalase, α-amylase, and ATPase activities, with concomitant depletion in myeloperoxidase activity, NO and MDA levels of the serum and pancreas. The pancreatic morphology and β-cell function were significantly improved in BFDE-treated rats, with restoration of the pancreatic capillary networks. Treatment with BFDE significantly (p < 0.05) inhibited the activities of glycogen phosphorylase, fructose 1,6 biphosphatase, glucose 6 phosphatase, and acetylcholinesterase, while suppressing the expression of Nrf2. HPLC analysis revealed the presence of gallic acid, vanillic acid, vanillin, and (−)-epicatechin in the fraction. ConclusionThese results portray the antidiabetic and antioxidative properties of BFDE, which may be a synergistic consequence of the identified phenolics.

A multi-objective evolutionary approach for planning and optimal condition restoration of secondary distribution networks

A secondary distribution network (SDN), corresponding to the final user low voltage distribution circuit, is continuously growing due to a persistent increase in load demand. Consequently, the performance of any optimized design will inevitably degrade over time. To avoid the associated repercussions such as faults, congestion, voltage drops, and other major quality issues, we are eventually prompted to redesign this part of the grid. To do so, we propose a Two-Stage Multi-Objective Evolutionary Approach (TS-MOEAP), which is able to find a new optimal network configuration, circumventing the associated quality issues. The proposed approach is oriented to improve the performance of SDNs by combining the concepts of network reconfiguration (NR) and optimal placement of distribution transformers (DTs). Due to the large and complex topology of SDNs, we deal with a hard combinatorial, non-convex, and nonlinear optimization problem. Consequently, to facilitate the resolution of the problem, the proposal is divided into two stages: (1) optimal placement and sizing of distribution transformers, as well as conductor sizing and branch routing, and (2) optimal network reconfiguration. For the first stage, an improved particle swarm optimization technique (IPSO) combined with a greedy algorithm is used, and for the second stage, an improved nondominated sorting genetic algorithm with a heuristic mutation operator (NSGA-HO) is implemented. The approach redesigns SDNs by minimizing total power loss and investment costs while satisfying quality issues and technical constraints. The proposed approach is validated by improving a real-life SDN with critical quality and technical issues. We also compare the results with respect to other state-of-the-art algorithms.

Decentralized Decision Making for the Restoration of Interdependent Networks

AbstractThis study introduces tractable algorithms to model the decentralized decision-making process for postdisaster restoration of interdependent networks. Restoration strategies are devised by ...

Restoration of auditory network after cochlear implant in prelingual deafness: a P300 study using LORETA.

SUMMARYThe concept of auditory restoration after cochlear implant (CI) in prelingual deafness is well described by a synaptic network model, whose development depends on sensory experience. The aim of this work was to study the associative networks activated by the CI in a population of prelingually deaf patients. In particular, the impact of age at time of first CI fitting and duration of CI use was evaluated. Twenty patients were tested and divided into three groups: early implanted and lengthy CI use (group A); late implanted and lengthy CI use (group B); late implanted and short CI use (group C). Each patient group was compared with a normal hearing age matched control group. All subjects underwent to auditory event-related potentials (ERPs) registration. ERP latencies and their cortical sources were investigated. Cortical source analysis was performed using LORETA (Low Resolution Electromagnetic Tomography) software. P300 latencies were significantly longer in patients than in controls. The amount of cortical activation was found to be significantly directly correlated with duration of implant use and significantly correlated inversely with age at implant. When comparing patients and controls, comparable cortical activation was only found in A patient group, and to a lesser extent in group B, while significantly lower activation was found in patient group C in the frontal and cingulate areas. CI adds a sensory modality in deafness patients, i.e. the auditory one. This involves areas implicated in sensory and cognitive functions, and needs some time to form. The duration of CI use is crucial: our results demonstrate the importance of long term use of the device in addition to an early time of implant.

Social vulnerability and equity perspectives on interdependent infrastructure network component importance

Critical infrastructure networks are often described as (i) interdependent in nature for operability, (ii) vulnerable against multiple natural or human-made hazards, and (iii) vital for providing the essential needs and ensuring the functionality of societies. Developing a plan for infrastructure network resilience is enabled by the identification of the most critical components that have the largest impact on the performance interdependent networks, as well as on society in terms of serving its needs. In this work, we propose a component importance measure that is driven by the social aspects of resilience, which quantifies the impact of equitable restoration activities on components of interdependent infrastructure networks. To integrate the social expectations from various perspectives in the restoration scheduling of interdependent infrastructure networks, we combine this component importance measure with multiple social vulnerability measures that define different socio-economic characteristics in a society. Finally, we implement a multi-criteria decision analysis technique to determine the final importance ranking of the components and illustrate our approach with two critical infrastructure networks in Shelby County, TN. To our knowledge, our proposed methodology is the first to incorporate both social equity and social vulnerability concepts with the component importance measures of critical interdependent infrastructure network restoration scheduling.

Mutational analysis of the Qi-site proton pathway in yeast cytochrome bc1 complex

The respiratory cytochrome bc1 complex functions as a protonmotive ubiquinol:cytochrome c oxidoreductase. Lysine 228 (K228) located within the quinol reduction (Qi) site of the bc1 complex, has been reported as a key residue for proton transfer during the redox chemistry cycle to substrate quinone at Qi. In yeast, while single mutations had no effect, the combination of K228L and F225L resulted in a severe respiratory growth defect and inhibition of O2 consumption in intact cells. The inhibition was overcome by uncoupling the mitochondrial membrane or by suppressor mutations in the region of K228L-F225L. We propose that the K228L mutation introduces energetic (and kinetic) barriers into normal electron- and proton transfer chemistry at Qi, which are relieved by dissipation of the opposing protonmotive force or through the restoration of favourable intraprotein proton transfer networks via suppressor mutation.

Defense Strategy for Resilient Shipboard Power Systems Considering Sequential Attacks

To increase the resilience of shipboard power systems, this paper presents an optimal defense strategy to protect critical lines against attacks. In the modeling, an attack is considered to destroy one critical bus, which may result in that all lines are connected to this bus will be out of service unless protection is enabled. Furthermore, after one true attack occurs, the network restoration is performed as soon as possible to pick up the critical loads and maintain system operation. To address the uncertain location of the attacks, a tri-level robust optimal defense strategy is set up to protect the critical lines under the worst attack. Moreover, a nested column-constraint generation method is employed to solve this model. A 60-bus shipboard power system is studied to demonstrate the effectiveness of the proposed model and the defense method.

Effective Energy Restoration of Wireless Sensor Networks by a Mobile Robot

As most existing sensors are powered by batteries, the coverage provided by a sensor network degrades over time and eventually disappears if energy is not restored. A popular approach to energy restoration is to use a robot acting as a mobile battery charger/changer. The robot decides where to move next according to a predefined on-line energy restoration strategy. The effectiveness of such a strategy depends on the number of nodes it is able to maintain operational at any given time, as well as on for how long a node whose battery is depleted remains non-operational. The ideal optimal on-line strategy (called OPTIMAL) occurs when the robot knows at any time the current status of all sensors, and it computes the best request to satisfy next, based on this information. Although optimal in terms of effectiveness, this centralized strategy would constantly require up-to-date global information; hence its high computational and communication costs make it not feasible. We consider a drastically different on-line strategy (called LIC), which is simple and fully decentralized, uses only local communication, requires no computations, and is highly scalable. In our strategy, the robot visits the sensors in a predefined circular order, moving in a clockwise direction and only when aware of a pending request. A sensor whose battery is about to become depleted originates a recharging request and waits for the robot; the request is forwarded according to the circular order in a counter-clockwise direction until it reaches either the robot or another sensor waiting for the robot. We show the perhaps unexpected result that, once the system becomes stable, in most networks the effectiveness of LIC is equivalent to that of OPTIMAL. In other words, in most cases, in spite of its simplicity and its extremely small (communication and computation) costs, the proposed decentralized strategy is as effective as the optimal centralized one. We augment our theoretical results with experimental analysis, confirming all the analytical results and showing among other things that the system stabilizes very quickly.

A Coordinated Optimal Feedback Control of Distributed Generators for Mitigation of Motor Starting Voltage Sags in Distribution Networks

This article proposes a coordinated optimal feedback control approach to mitigate the induction motor starting voltage sag and support the transient restoration in distribution networks. The proposed technique is expected to reduce the starting high current to maintain the network voltage using neighboring voltage supporting distributed generation. An optimal feedback-based coordinated controller (CC) has been designed to estimate the reactive power to be injected at different locations of the network based on the motor loads. The CC on top of the existing local controller (LC) uses motor voltage feedback signals, thereby adjusting the reactive power support based on the voltage sag. The proposed voltage sag mitigation strategy is tested in both 12.4 kV network and 123 bus larger distribution networks containing single and multiple motor and distributed generation units. From simulation results, it is revealed that the proposed coordinated optimal feedback control of VSDGs can provide a fast restoration of the motor starting transient voltage dip.

The Optimization Study about Fault Self-healing Restoration of Power Distribution Network Based on Multi-Agent Technology

The Optimization Study about Fault Self-healing Restoration of Power Distribution Network Based on Multi-Agent Technology

A maximal multiple coverage and network restoration problem for disaster recovery

The recovery of physically damaged infrastructure after disasters is critical to efficiently deliver disaster relief supplies and emergency services. The physical damage to road infrastructure from disasters can result in decreased road link capacities and an inability to meet the community’s emergency demand. This paper provides an infrastructure restoration plan for delivering critical services after disasters. We present a maximal multiple coverage and network recovery problem for the recovery and restoration of infrastructure systems after disasters. In the model, recovery crews make damaged arcs available by repairing components over a time horizon in a disrupted network. The model relocates emergency responders using the available arcs in the network to maximize multiple coverage of emergency service demand over the time horizon. We present two heuristics for the model. The first uses the Lagrangian and the linear programming relaxation solutions of the problem, and the second uses an integer rounding procedure applied to the linear programming relaxation solution. We test the model using a real-world example representing the road infrastructure and emergency services of the Bronx Borough in New York, NY during Hurricane Sandy. The results demonstrate that the integer rounding heuristic is effective in identifying near-optimal solutions. Our computational study suggests that our model can aid emergency managers in achieving their goals by scheduling effective restoration activities for real-time disaster recovery and long-term recovery planning.

Image restoration of finger-vein networks based on encoder-decoder model

Image restoration of finger-vein networks based on encoder-decoder model

Pollinator foraging flexibility mediates rapid plant-pollinator network restoration in semi-natural grasslands

We examined how plant-pollinator interactions were affected by time since habitat restoration and landscape connectivity by comparing plant-pollinator networks in restored, abandoned and continuously grazed semi-natural pastures in south-central Sweden. We measured richness of flowering plants and pollinators, and local plant-pollinator network characteristics including species composition as well as the number and identity of interactions, allowing a deeper understanding of species and interaction beta diversity. Pollinator richness and abundance were highest in restored grasslands. They successfully resembled continuously grazed grasslands. However, the turnover of interactions was extremely high among pasture categories (0.99) mainly due to high turnover of plant (0.74) and pollinator species (0.81). Among co-occurring plant and pollinator species, the turnover of interactions (0.66) was attributable mainly to differences in the number of links and to a lesser extent to species true rewiring (~0.17). Connectivity and time since restoration had no effect on the measured network properties. We show that plant-pollinator interactions can be rapidly restored even in relatively isolated grasslands. This is partly due to flexibility of most pollinators to establish interactions with the available flowering plants and relatively high species interaction rewiring, indicating that pollinators behavioural plasticity allow them to shift diets to adapt to new situations.

Biocompatibility and hemocompatibility of hydrothermally derived reduced graphene oxide using soluble starch as a reducing agent

Graphene-based nanomaterials (GBNs) have many applications as biomedical materials in tissue engineering and regenerative medicine. We report on the preparation of starch-(functionalized) reduced graphene oxide nanosheets (SRGO) using soluble starch as a reducing agent in a hydrothermal method, and their in vitro interactions with human skin fibroblasts and red blood cells (RBCs). Our results indicate that soluble SRGO nanosheets were prepared using graphene oxide (GO) as a raw material. SRGO-1 and -10, which were prepared using different concentrations of soluble starch after hydrothermal treatment, were characterized by ultraviolet-visible spectroscopy and showed a peak shift at 260 nm corresponding to the deoxygenation of GO and restoration of the conjugated aromatic structure. Dynamic light scattering and zeta potential measurements were used to determine Z-average sizes and surface charges of GO and SRGOs. X-ray diffractometry, attenuated total reflectance Fourier-transform infrared spectroscopy, and Raman spectroscopy revealed the progressive elimination of labile oxygen functional groups during hydrothermal treatment and restoration of the π-conjugated network. X-ray photoelectron spectroscopy showed de-oxidation of SRGOs, which had high carbon to oxygen ratios (C/O) as compared with GO. Interactions of SRGO-1 and -10 with skin fibroblasts showed excellent biocompatibility even at a concentration of 200 μg/ml with cell viabilities up to 88% and 90%, respectively, whereas notable cytotoxicity was observed for GO at 20 μg/ml. Similarly, SRGO-1 and -10 did not exhibit toxicity to RBCs compared to GO. Biofilm formation and metabolic activities of biofilm by the bacterium Staphylococcus aureus were also evaluated using a crystal violet and a tetrazolium reduction assay, respectively. The described hydrothermal method used to synthesize SRGO provides a cheap, facile, and environmentally friendly means of producing water-dispersible, biocompatible and hemocompatible reduced GOs for the fabrication of novel GBNs for various biomedical applications.

Power system restoration in distribution network using minimum spanning tree - Kruskal’s algorithm

&lt;span&gt;Events such as natural and manmade interference, line, transformer and feeder outages that occur in electric power distribution system negatively impact the continuity of power supply, thus affecting the power demand supply as well as customer’s satisfaction. In that cases, the restoration of power needs to be carried out immediately in order to guarantee the system’s reliability. The power flow path identification is considered as a difficult task especially in a huge system due to large number of switches. Kruskal’s algorithm is presented in this paper to find the minimum power flow path in a power distribution network. The comparison of performance between presented Kruskal’s algorithm and Binary Particle Swarm Optimization (BPSO) was made in solving a problem regarding network reconfiguration. The proposed load restoration approach is tested on IEEE 33-bus single feeder radial distribution system using MATLAB software. From the results, it is found that the presented Kruskal’s algorithm was able to search for the minimal power flow path that contribute to loss reduction for power restoration after the occurrence of fault.&lt;/span&gt;

Network Restoration in Wireless Sensor Networks for Next-Generation Applications

This paper investigates highly efficient network restoration models for wireless sensor networks (WSNs) to be deployed for next-generation (xG) applications. The developed network restoration models are designed with two main goals in mind. The first goal is to optimize network resource utilization, and the second is to protect the network against failures. In realizing the goal of optimizing resource usage, a peculiar feature of WSNs is exploited, namely, their ability to remain in active service even when one or more of their active elements (sensor nodes and/or connecting links) fail. To achieve the second goal of network protection, we leverage the advantage of p-cycle-based restoration solutions - the fact that they can provide ring-like recovery speeds with mesh-like capacity efficiencies - in developing optimal p-cycle restoration models that provide sufficient protection for the network against both link and node failures. In the restoration models developed, we employ a selection process that jointly considers the shortest lengths, best topologies, and capacity requirements of the available p-cycles in achieving new capacity-optimal p-cycle-based restoration solutions for the network. Comparative results obtained show that our developed selection-based capacity-efficient p-cycle restoration solutions for WSNs outperform other similar approaches for both network realization and protection, making them particularly ideal for xG applications.

Distributed Load Restoration in Unbalanced Active Distribution Systems

The resilience of modern power systems has been constantly threatened by various natural disasters and man-made attacks. Under those threats, fast and automatic restoration actions are critical for restoring impacted systems to normal operating conditions and preventing from additional disastrous consequences. Smart grid technologies, such as distributed energy resources (DERs) and microgrids, provide both opportunities and challenges for distribution system restoration. In this paper, distributed load restoration (DLR) in unbalanced active distribution networks is developed using the alternating direction method of multipliers (ADMMs) algorithm. The step-by-step restoration actions are provided to schedule the output of DERs and distribution system control devices, as well as the power consumption from transmission system restoration. The nonlinearities from three-phase unbalanced power flow and distribution components modeling are relaxed into a convex quadratic programming model. Then, the problem is decomposed into subproblems for each node by applying ADMM-DLR; and solves through each agent by exchanging limited information with neighboring nodes in an iterative procedure. The developed models and algorithms are validated and demonstrated through testing of the IEEE 13-node and 123-node test feeders. Simulation results demonstrate the effectiveness of restoring unbalanced distribution system with the hybrid bottom-up and top-down restoration strategies.

Coarse grained parallel quantum genetic algorithm for reconfiguration and service restoration of electric power networks

In this paper, a Coarse Grained Parallel Quantum Genetic Algorithm (CGPQGA) is proposed to solve the network reconfiguration and restoration problems in distribution networks with the objective of reducing network losses, balancing load and improving the quality of voltage in the system. Based on t he parallel evolutionary concept and the insights of quantum theory, a model of parallel quantum computation was simulated. In this frame, there are some demes (sub-populations) and some universes (groups of populations), which are structured in super star-shaped topologies. A new migration scheme based on penetration theory is developed to control both the migration rate and direction adaptively between demes and a coarse grained quantum crossover strategy is devised among universes. The proposed approach is tested on 33-bus distribution networks in two cases the first case without distributed generators and the second case with distributed generators, with the aim of minimizing the losses of reconfigured network, and minimize number of operated switches, deviation of bus voltages, and loading of transformer (power loss) where the choice of the switches to be opened is based on the calculation of voltages at the system buses, real and reactive power flow through lines, real power losses and voltage deviations, using distribution load flow (DLF) program. Simulation results prove the effectiveness of the proposed methodology in solving the current challenges in this phase.

Visualisation of impacts due to the proposed developmental projects in the ecologically fragile regions- Kodagu district, Karnataka

Assessing land use land cover changes in forested regions reflect the extent of anthropogenic pressure, ecosystem degradation and their impact on local wellbeing. The rapid expansion of linear developments such as roads, power lines will have an irreversible loss of habitat, as a result of forest fragmentation and consequent disruptions in the local ecological processes. The spatiotemporal land use analysis of Kodagu highlights the loss of forest cover due to an uncontrolled expansion of coffee plantations and other driving forces. The major cover of evergreen forest (40.47 to 27.14%) has lost due to interventions in terms of road, built-up areas and other changes. Around 66,892 ha of pristine forest cover was lost due to un-interrupted exploitation. Kushalnagara and Madikere taluks have lost the major chunk of forests due to construction (roads, homestays, villas, etc.) activities. Forest fragmentation analyses portray the status of forests in their condition across the temporal scale. The region had 32% of forest cover under interior or intact forests in 1973, whereas in 2018 it covers only 19% under various protected areas. Though Kodagu district is well connected with national and state high ways, the Government has now proposed to increase the road width of existing major highways (7) and a new railway line connecting Tellicherry and Mysore. The scenario based analysis has been done considering business as usual and with the expansion of linear alignments using Fuzzy-MCE-AHP-MCA. Forecasting future land use changes resulting from linear developments suggest the loss of core forest with the expansion of pre-existing roads. The loss of 8% forest cover with the expansion of linear alignments will have irreversible impacts on Kodagu landscape. The study reveals the causal factors for the disaster are the absence of prudent management of a landscape in the ecologically fragile region evident from the conversion of native forests to other land uses, disruption of stream network, construction of buildings along the water course disrupting the natural water flow, construction or expansion of existing roads, steep vertical cuts leading to structural instability, removal of native vegetation cover in highly undulating terrains with steep slopes leading to the weakening of terrain due to the lowered binding capability of soil, encroachment of local water bodies (such as ponds/tanks), etc. The study emphasizes the need for restoration of stream network, catchment treatment through planting of native species, arresting deforestation and restrictions of large-scale developmental projects with the detrimental land use changes. The outcome of the current research helps in evolving appropriate policies to review the proposed linear projects towards sustainable management of natural resources.

Automatic restoration of large-scale distribution networks with distributed generators, voltage control devices and heating loads

Energy supply interruption by permanent faults causes economic and social problems, dissatisfaction of customers and penalization to electrical power distribution companies. In the procedure to restore distribution networks, power interruption damages must be minimized by energizing the largest possible number of customer loads in the shortest time interval. The restoration problem of distribution networks can be mathematically formulated as a mixed integer nonlinear programming problem that is non-convex of type NP-complete. The existence of heating loads causes the cold load pickup condition in the distribution network that requires the step-by-step procedure increasing the complexity of the restoration problem. In this work, therefore, it is proposed a methodology to solve the restoration problem of large-scale distribution networks with heating loads where the mathematical model is subjected to intentional islanding of distributed generation and voltage control through optimized adjustments on capacitor banks and voltage regulators. The outcomes are achieved under a testing distribution system with 53 nodes and a real system with 7052 nodes.