Dynamic Maintenance Research Articles

Minimum Strongly Connected Subgraph Collection in Dynamic Graphs

Real-world directed graphs are dynamically changing, and it is important to identify and maintain the strong connectivity information between nodes, which is useful in numerous applications. Given an input graph G , we study a new problem, minimum strongly connected subgraph collection (MSCSC), which asks for a complete collection of subgraphs, each of which contains a maximal set of nodes that are strongly connected to each other via minimum number of edges in G. MSCSC is NP-hard, and its computation and maintenance are challenging, especially on large-scale dynamic graphs. Thus, we resort to approximate MSCSC with theoretical guarantees. We develop a series of approximate MSCSC methods for both static and dynamic graphs. Specifically, we first develop a static MSCSC method MSC that only needs one scan of the graph G , runs in linear time w.r.t. , the number of edges, and provides rigorous approximation guarantees. Then, based on MSC, we leverage a reduced directed acyclic graph of G to design incremental MSCSC method MSC i with two variants to handle edge insertions efficiently. We further develop MSC d that updates MSCSC under edge deletions by efficiently scanning only locally affected subgraphs. Moreover, to demonstrate the high utility, we conduct two use case studies to apply our MSCSC methods to boost the efficiency of dynamic strongly connected component (SCC) maintenance and dynamic SCC-based reachability index maintenance. Extensive experiments on 8 large graphs, including 3 billion-edge graphs, validate the superior efficiency of our methods.

Technique for intraoperative monitoring of corticospinal tract integrity using an electrode with a dynamic balloon

Aim. To present a technique for continuous monitoring of corticospinal tract integrity using an electrode with a dynamic balloon, examine the advantages and disadvantages of the selected and alternative monitoring techniques.Materials and methods. At the 1st stage, an electrode combined with a dynamic balloon was prepared. At the 2nd stage, continuous monitoring of the corticospinal tract using direct stimulation of the cortex using ballon grid during the main stage of cerebral surgery was performed. At the 3rd stage, interpretation of the obtained neurophysiological responses was performed.Results. The presented technique of continuous monitoring of the integrity of the corticospinal tract through direct cortical stimulation using the developed device prevents false response decreases which significantly helps with the interpretation of the obtained results and increases information value of the technique. The described technique is based on the presented clinical observations of intracerebral tumor resection, as well as microsurgical aneurysm clipping using the technique. During surgery, no false decrease of the neurophysiological signal amplitude was observed due to dynamic ballon inflation and maintenance of close contact between the electrode and the surface of the brain. A surgery performed using this technique allowed to achieve a favorable neurological outcome in a patient in the postoperative period.Conclusion. The presented device allows to perform continuous neuromonitoring using direct cortical electrostimulation with a strip electrode at any level of brain retraction. The technique decreases the risk of primary and secondary injury of the corticospinal and corticobulbar tracts which increases safety of neurosurgical intervention and decreases risks of neurological complications.

A NEW SOLUTION FOR MAINTENANCE SCHEDULING OF DISTRIBUTED GENERATIONS BASED ON MONTE-CARLO SIMULATION AND GAME THEORY

This paper presents a new solution for maintenance scheduling of Distributed Generation (DG) in deregulated power markets by applying an independent market for DG maintenance scheduling based on game theory. Maintenance scheduling is one of the important issues in restructured power electricity markets, because each distribution generation company desires to maximize its own payoffs and independent system operator (ISO) has its own reliability concerns that mostly, these two points of view are against with each other. The paper presents a dynamic Distribution Resources Maintenance Market (DRMM) based on dynamic game theory for resolving maintenance scheduling problem of distributed generation resources in deregulated environment. In this market, distribution generation companies are set their strategies to participate in DRMM by considering load, primary resources and seasonal forced outage rate uncertainties and behaviour of other DG companies that participate in market. On the other hand, ISO manages the maintenance market based on reliability and offering incentives /penalties for DG companies. This paper studied the ISO acts by using Monte-Carlo simulation for reliability indices assessment relying on load and resources uncertainties and interactions between DG companies. Numerical results are determined by using an applicable case study for testing accuracy and applicability of the new proposed solution.

Hematopoietic stem cell quiescence and DNA replication dynamics maintained by the resilient β-catenin/Hoxa9/Prmt1 axis

AbstractMaintenance of quiescence and DNA replication dynamics are 2 paradoxical requirements for the distinct states of dormant and active hematopoietic stem cells (HSCs), which are required to preserve the stem cell reservoir and replenish the blood cell system in response to hematopoietic stress, respectively. Here, we show that key self-renewal factors, β-catenin or Hoxa9, largely dispensable for HSC integrity, in fact, have dual functions in maintaining quiescence and enabling efficient DNA replication fork dynamics to preserve the functionality of hematopoietic stem and progenitor cells (HSPCs). Although β-catenin or Hoxa9 single knockout (KO) exhibited mostly normal hematopoiesis, their coinactivation led to severe hematopoietic defects stemmed from aberrant cell cycle, DNA replication, and damage in HSPCs. Mechanistically, β-catenin and Hoxa9 function in a compensatory manner to sustain key transcriptional programs that converge on the pivotal downstream target and epigenetic modifying enzyme, Prmt1, which protects the quiescent state and ensures an adequate supply of DNA replication and repair factors to maintain robust replication fork dynamics. Inactivation of Prmt1 phenocopied both cellular and molecular phenotypes of β-catenin/Hoxa9 combined KO, which at the same time could also be partially rescued by Prmt1 expression. The discovery of the highly resilient β-catenin/Hoxa9/Prmt1 axis in protecting both quiescence and DNA replication dynamics essential for HSCs at different key states provides not only novel mechanistic insights into their intricate regulation but also a potential tractable target for therapeutic intervention.

The mitogenomic landscape of Banisteriopsis caapi (Malpighiaceae), the sacred liana used for ayahuasca preparation.

The sacred ayahuasca brew, utilized by indigenous communities in the Amazon and syncretic religious groups in Brazil, primarily consists of a decoction of two plants: (i) the Amazonian liana known as Mariri or Jagube (Banisteriopsis caapi), and (ii) the shrub referred as Chacrona or Rainha (Psychotria viridis). While Chacrona leaves are rich in N,N-Dimethyltryptamine (DMT), a potent psychedelic, the macerated vine of Mariri provides beta-carboline alkaloids acting as monoamine oxidase inhibitors, preventing DMT's degradation. This study sequenced, assembled, and analyzed the complete genome of B. caapi's mitochondrion, yielding a circular structure spanning 503,502 bp. Although the mtDNA encompasses most plant mitochondrial genes, it lacks some ribosomal genes, presents some atypical genes, and contains plastid pseudogenes, suggesting gene transfer between organelles. The presence of a 7-Kb repetitive segment containing copies of the rrnL and trnfM genes suggests mitogenome isomerization, supporting the hypothesis of dynamic mitogenome maintenance in plants. Phylogenetics and phylogenomics across 24 Malpighiales confirms the sample's placement in the "Tucunacá" ethnovariety, aligning with morphological identification. This study spearheads efforts to decode the genome of this esteemed Malpighiaceae.

Dynamic establishment and maintenance of the human intestinal B cell population and repertoire following transplantation in a pediatric-dominated cohort.

It is unknown how intestinal B cell populations and B cell receptor (BCR) repertoires are established and maintained over time in humans. Following intestinal transplantation (ITx), surveillance ileal mucosal biopsies provide a unique opportunity to map the dynamic establishment of recipient gut lymphocyte populations in immunosuppressed conditions. Using polychromatic flow cytometry that includes HLA allele group-specific antibodies distinguishing donor from recipient cells along with high throughput BCR sequencing, we tracked the establishment of recipient B cell populations and BCR repertoire in the allograft mucosa of ITx recipients. We confirm the early presence of naïve donor B cells in the circulation (donor age range: 1-14 years, median: 3 years) and, for the first time, document the establishment of recipient B cell populations, including B resident memory cells, in the intestinal allograft mucosa (recipient age range at the time of transplant: 1-44 years, median: 3 years). Recipient B cell repopulation of the allograft was most rapid in infant (<1 year old)-derived allografts and, unlike T cell repopulation, did not correlate with rejection rates. While recipient memory B cell populations were increased in graft mucosa compared to circulation, naïve recipient B cells remained detectable in the graft mucosa for years. Comparisons of peripheral and intra-mucosal B cell repertoires in the absence of rejection (recipient age range at the time of transplant: 1-9 years, median: 2 years) revealed increased BCR mutation rates and clonal expansion in graft mucosa compared to circulating B cells, but these parameters did not increase markedly after the first year post-transplant. Furthermore, clonal mixing between the allograft mucosa and the circulation was significantly greater in ITx recipients, even years after transplantation, than in deceased adult donors. In available pan-scope biopsies from pediatric recipients, we observed higher percentages of naïve recipient B cells in colon allograft compared to small bowel allograft and increased BCR overlap between native colon vs colon allograft compared to that between native colon vs ileum allograft in most cases, suggesting differential clonal distribution in large intestine vs small intestine. Collectively, our data demonstrate intestinal mucosal B cell repertoire establishment from a circulating pool, a process that continues for years without evidence of stabilization of the mucosal B cell repertoire in pediatric ITx patients.

Dynamic Grouping in Maintenance Planning and Optimization: an Industrial Application

In this paper, we present a grouping maintenance approach that allows efficiently considering economic dependence between components and also the impact of dynamic context such as changes in the degradation process, limited number of maintenance teams, occurrence of maintenance opportunities, etc. A real industrial case study is used to investigate the applicability and the robustness of the dynamic grouping maintenance approach in the maintenance optimization framework.

Dynamic Condition-Based Maintenance for Lifetime Delayed Degradation Process With Heterogeneity

Dynamic Condition-Based Maintenance for Lifetime Delayed Degradation Process With Heterogeneity

Research on Operation and Maintenance Strategy of New Energy Photovoltaic Power Generation System Considering Extreme Weather Conditions

Abstract This paper employs the gray correlation analysis method to compute the correlation between irradiance, ambient temperature, wind speed, and photovoltaic power generation efficiency. This method relies on screened data for data normalization, and after processing, it determines the degree of similarity between the factors. We propose a dynamic combined maintenance strategy for PV power generation systems that considers reliability, overhaul resources, and overhaul time constraints. We propose a two-layer optimization strategy based on extreme weather factors and failure-related characteristics, and we use empirical analysis to investigate the maintenance strategy’s effectiveness. The analysis reveals a positive correlation between irradiance and PV power generation efficiency, with a multiplicative increase in the range of 1-3. In the correlation analysis of ambient temperature and wind speed variables, the power generation curve is not consistent with its trend, which is related to the influence of extreme temperature and extreme wind speed, and the meteorological factors affecting the PV power generation efficiency change at different moments of the day, where the correlation coefficient at 6:45 is 0.912. When the failure correlation strength increases to a value of 0.1, the number of repairs rises to 8. When the weather accessibility ratio is 0.2, the reduction in system availability is up to 62%. The two-layer optimization strategy, which considers extreme weather factors and failure-related characteristics, is both economical and universal.

Bridge BIM Dynamic Temperature Sensing Identification and Operation and Maintenance Technology

With the high-quality development of transportation in China, highway bridges, as the core part of transportation infrastructure, have received widespread attention for their safety and operation management. Especially in the field of super large bridges, due to their importance in transportation and enormous social benefits, safety and operation management are particularly crucial. This research focused on the operation and maintenance management of super large bridges, especially how to improve the efficiency and effectiveness of bridge operation and maintenance management through BIM (Building Information Modeling) technology. This technology deepened the understanding of bridge structure and performance by establishing a detailed BIM model. By standardizing model data and establishing coding systems, data interoperability and management efficiency were improved, providing decision support for the daily management and maintenance of bridges. According to experimental data, it can be concluded that the accuracy of basic information judgment, temperature and humidity accuracy, bridge status judgment accuracy, and operation and maintenance information accuracy of BIM dynamic temperature recognition and maintenance technology for bridges were among four sets of data. The accuracy rates of all four data items were between 91.20% and 94.27%, indicating a high accuracy rate. The comprehensive application of these technologies aims to improve the operation and maintenance management level of super large bridges, ensure their long-term stability and safety, and contribute to the sustainable development of transportation systems.

A novel refined maintenance strategy for full life cycle of high‐speed automatic train protection system

AbstractAutomatic train protection (ATP) system is essential for ensuring the safe operation of high‐speed trains. However, the existing extensive and fixed maintenance mode of the ATP system results in a waste of resources. To achieve a state of operation and maintenance that ensures both protection capability and economic efficiency, a lean method in a dynamic maintenance mode for the full life cycle of the ATP system is proposed. Firstly, reliability tests are carried out based on historical failure data. The parameter values of the possible life distribution are estimated by maximum likelihood method, and the optimal life distribution of different devices is obtained through the Kolmogorov–Smirnov hypothesis test. Secondly, a dynamic failure rate function is introduced to describe the impact of maintenance on device performance. A refined maintenance model is then established within the life cycle, and the dynamically changing preventive maintenance intervals and frequencies are obtained using a genetic algorithm. Finally, to mitigate the impact of the intermittent operation of ATP system on maintenance, the multidimensional relationships among the maintenance strategy, service time and operation mileage are revealed. The effectiveness of the proposed method is verified through an example test on a type of driver machine interface device.

Dynamic joint sensor selection and maintenance optimization in partially observable deteriorating systems

We consider a degrading system with costly but silent failures. The system can be partially observed using a set of heterogeneous noisy sensors at a given cost, where each sensor noise level is a function of the system state. The goal is to devise a dynamic joint sensor selection and maintenance optimization model to minimize the total expected discounted cost of the system. We develop an infinite-horizon discrete-time partially observable Markov decision process model to dynamically prescribe the sensor subsets for system monitoring and the timing of maintenance activities. We perform numerical experiments for a system with up to ten sensors and compare the proposed optimal policy with four heuristic policies. We observe that the proposed approach consistently outperforms all heuristic policies considered. Through a comprehensive analysis of numerical experiments, our study shows the efficacy of the proposed model’s optimal policy in strategically selecting sensors to achieve precise system state estimation while managing costs. Through these experiments, we find that it is optimal to use lower-cost, higher-variance sensors and often fuse them for more accurate estimations. However, the choice depends on the system state and sensor quality distribution. Importantly, our model excels in determining the best action by considering these factors, underscoring its practical applicability.

Alveolar epithelial progenitor cells require Nkx2-1 to maintain progenitor-specific epigenomic state during lung homeostasis and regeneration

Lung epithelial regeneration after acute injury requires coordination cellular coordination to pattern the morphologically complex alveolar gas exchange surface. During adult lung regeneration, Wnt-responsive alveolar epithelial progenitor (AEP) cells, a subset of alveolar type 2 (AT2) cells, proliferate and transition to alveolar type 1 (AT1) cells. Here, we report a refined primary murine alveolar organoid, which recapitulates critical aspects of in vivo regeneration. Paired scRNAseq and scATACseq followed by transcriptional regulatory network (TRN) analysis identified two AT1 transition states driven by distinct regulatory networks controlled in part by differential activity of Nkx2-1. Genetic ablation of Nkx2-1 in AEP-derived organoids was sufficient to cause transition to a proliferative stressed Krt8+ state, and AEP-specific deletion of Nkx2-1 in adult mice led to rapid loss of progenitor state and uncontrolled growth of Krt8+ cells. Together, these data implicate dynamic epigenetic maintenance via Nkx2-1 as central to the control of facultative progenitor activity in AEPs.

Protein O-GlcNAcylation: The sweet hub in liver metabolic flexibility from a (patho)physiological perspective.

O-GlcNAcylation is a dynamic, reversible and atypical O-glycosylation that regulates various cellular physiological processes via conformation, stabilisation, localisation, chaperone interaction or activity of target proteins. The O-GlcNAcylation cycle is precisely controlled by collaboration between O-GlcNAc transferase and O-GlcNAcase. Uridine-diphosphate-N-acetylglucosamine, the sole donor of O-GlcNAcylation produced by the hexosamine biosynthesis pathway, is controlled by the input of glucose, glutamine, acetyl coenzyme A and uridine triphosphate, making it a sensor of the fluctuation of molecules, making O-GlcNAcylation a pivotal nutrient sensor for the metabolism of carbohydrates, amino acids, lipids and nucleotides. O-GlcNAcylation, particularly prevalent in liver, is the core hub for controlling systemic glucose homeostasis due to its nutritional sensitivity and precise spatiotemporal regulation of insulin signal transduction. The pathology of various liver diseases has highlighted hepatic metabolic disorder and dysfunction, and abnormal O-GlcNAcylation also plays a specific pathological role in these processes. Therefore, this review describes the unique features of O-GlcNAcylation and its dynamic homeostasis maintenance. Additionally, it explains the underlying nutritional sensitivity of O-GlcNAcylation and discusses its mechanism of spatiotemporal modulation of insulin signal transduction and liver metabolic homeostasis during the fasting and feeding cycle. This review emphasises the pathophysiological implications of O-GlcNAcylation in nonalcoholic fatty liver disease, nonalcoholic steatohepatitis and hepatic fibrosis, and focuses on the adverse effects of hyper O-GlcNAcylation on liver cancer progression and metabolic reprogramming.

Lateral olfactory tract usher substance (LOTUS), an endogenous Nogo receptor antagonist, ameliorates disease progression in amyotrophic lateral sclerosis model mice

Nogo–Nogo receptor 1 (NgR1) signaling is significantly implicated in neurodegeneration in amyotrophic lateral sclerosis (ALS). We previously showed that lateral olfactory tract usher substance (LOTUS) is an endogenous antagonist of NgR1 that prevents all myelin-associated inhibitors (MAIs), including Nogo, from binding to NgR1. Here we investigated the role of LOTUS in ALS pathogenesis by analyzing G93A-mutated human superoxide dismutase 1 (SOD1) transgenic (Tg) mice, as an ALS model, as well as newly generated LOTUS-overexpressing SOD1 Tg mice. We examined expression profiles of LOTUS and MAIs and compared motor functions and survival periods in these mice. We also investigated motor neuron survival, glial proliferation in the lumbar spinal cord, and neuromuscular junction (NMJ) morphology. We analyzed downstream molecules of NgR1 signaling such as ROCK2, LIMK1, cofilin, and ataxin-2, and also neurotrophins. In addition, we investigated LOTUS protein levels in the ventral horn of ALS patients. We found significantly decreased LOTUS expression in both SOD1 Tg mice and ALS patients. LOTUS overexpression in SOD1 Tg mice increased lifespan and improved motor function, in association with prevention of motor neuron loss, reduced gliosis, increased NMJ innervation, maintenance of cofilin phosphorylation dynamics, decreased levels of ataxin-2, and increased levels of brain-derived neurotrophic factor (BDNF). Reduced LOTUS expression may enhance neurodegeneration in SOD1 Tg mice and ALS patients by activating NgR1 signaling, and in this study LOTUS overexpression significantly ameliorated ALS pathogenesis. LOTUS might serve as a promising therapeutic target for ALS.

Dynamic fleet maintenance management model applied to rolling stock

Dynamic fleet maintenance management model applied to rolling stock

Distributed or centralized? Long-term dynamic allocation and maintenance planning of modular equipment to produce multi-product natural gas based on life cycle thinking

With the increasing complexity of the natural gas trading market, enhancing the flexibility of multi-product natural gas production has practical significance for improving the whole life cycle benefits of gas fields. At present, the collaborative relationship between multi-product process optimization and modular equipment has not been studied enough; there is still a lack of integrated model coupling process optimization, modular equipment design, and scheduling optimization. Therefore, this paper utilizes the convenient scheduling technique across multiple blocks and establishes a distributed multi-product natural gas processing model based on life cycle thinking, facilitating the enduring, dynamic configuration and upkeep administration of modular equipment. The established optimization model is formulated to maximize the net present value of profits, allowing for the selection of optimal production strategy for various natural gas products, such as LNG (Liquefied Natural Gas), CNG (Compressed Natural Gas), NG (Natural Gas), mainly including volume distribution, capacity of gas, and installation, utilization, inter-block scheduling, and recovery of modular equipment, etc. Modular equipment within multiple blocks can be dynamically adjusted based on the production status of the gas field and the market demand for multi-product natural gas. By researching actual production cases, the effectiveness and reliability of this approach have been verified. The results indicate that the net present value of the equipment cost is 89 % of the traditional equipment, which significantly improves production system flexibility and economic benefits of the gas field. This study proposes new operational and management ideas for future distributed multi-product production models in gas fields by considering the efficiency of natural gas resource development and utilization, as well as the risk resistance of the multi-product natural gas industry chain.

Blockchain-based digital twin data provenance for predictive asset management in building facilities

Purpose The purpose of this study is to focus on structured data provision and asset information model maintenance and develop a data provenance model on a blockchain-based digital twin smart and sustainable built environment (DT) for predictive asset management (PAM) in building facilities.Design/methodology/approach Qualitative research data were collected through a comprehensive scoping review of secondary sources. Additionally, primary data were gathered through interviews with industry specialists. The analysis of the data served as the basis for developing blockchain-based DT data provenance models and scenarios. A case study involving a conference room in an office building in Stockholm was conducted to assess the proposed data provenance model. The implementation utilized the Remix Ethereum platform and Sepolia testnet.Findings Based on the analysis of results, a data provenance model on blockchain-based DT which ensures the reliability and trustworthiness of data used in PAM processes was developed. This was achieved by providing a transparent and immutable record of data origin, ownership and lineage.Practical implications The proposed model enables decentralized applications (DApps) to publish real-time data obtained from dynamic operations and maintenance processes, enhancing the reliability and effectiveness of data for PAM.Originality/value The research presents a data provenance model on a blockchain-based DT, specifically tailored to PAM in building facilities. The proposed model enhances decision-making processes related to PAM by ensuring data reliability and trustworthiness and providing valuable insights for specialists and stakeholders interested in the application of blockchain technology in asset management and data provenance.

Remaining useful life prediction of equipment considering dynamic thresholds under the influence of maintenance

A novel approach for predicting remaining useful life (RUL) is proposed for situations where maintenance threshold and failure threshold exhibit dynamic behavior due to uncertainties in degradation and the influence of detection strategies during maintenance processes. The approach introduces maintenance threshold error to establish a multi-stage maintenance-impact degradation model with dynamic maintenance threshold based on the Wiener process. This model considers the impact of maintenance on degradation rate, amount, and path. Moreover, by using the first hitting time (FHT) and introducing failure threshold error to reflect the dynamic behavior of the failure threshold, the formula for predicting equipment RUL is derived. The model parameters are estimated using both the maximum likelihood estimation (MLE) approach and Bayesian formula. The proposed approach was validated with simulation data and gyroscope degradation data, and the results demonstrate its ability to effectively enhance the precision of equipment RUL prediction.

Salinity-gradient solar pond: History and progress review

A salinity gradient solar pond (SGSP) is a large and deep artificial basin of layered brine, which collects and stores-simultaneously-solar energy for use in various applications. Experimental and theoretical studies have been launched to understand the thermal behavior of SGSPs, under different operating conditions. This article then traces the history of SGSPs, from their natural discovery to their current artificial applications and the progress of studies and research, according to their chronological sequence, in terms of determining their physical and dynamic aspects, their operation, management and maintenance. It has extensively covered the theoretical and experimental studies, as well as the direct and laboratory applications of this technology, especially the most famous and influential in this field, classified according to the aspect covered by the study, with a comparison between the different results obtained. In addition, it highlighted the latest methods to improve the performance of an SGSP and facilitate its operation, such as the use of a magnetic field and the adoption of remote data acquisition, in the aim of expanding research and enhancing the benefit of this technology.