Purpose
The purpose of this paper is to propose a stochastic optimisation model for integrating service and maintenance policies in order to solve the queuing problem and the cost of maintenance ...activities for public transport services, with a particular focus on urban ropeway system.
Design/methodology/approach
The authors adopt the following approaches: a discrete-event model that uses a set of interrelated queues for the formulation of the service problem using a cost-based expression; and a maintenance model consisting of preventive and corrective maintenance actions, which considers two different maintenance policies (periodic block-type and age-based).
Findings
The work shows that neither periodic block-type maintenance nor an age-based maintenance is necessarily the best maintenance strategy over a long system lifecycle; the optimal strategy must consider both policies.
Practical implications
The maintenance policies are then evaluated for their impact on the service and operation of the transport system. The authors conclude by applying the proposed optimisation model using an example concerning ropeway systems.
Originality/value
This is the first study to simultaneously consider maintenance policy and operational policy in an urban aerial ropeway system, taking up the problem of queuing with particular attention to the unique requirements public transport services.
Sleep-wake disturbances are extremely common after a traumatic brain injury (TBI). The most common disturbances are insomnia (difficulties falling or staying asleep), increased sleep need, and ...excessive daytime sleepiness that can be due to the TBI or other sleep disorders associated with TBI, such as sleep-related breathing disorder or post-traumatic hypersomnia. Sleep-wake disturbances can have a major effect on functional outcomes and on the recovery process after TBI. These negative effects can exacerbate other common sequelae of TBI—such as fatigue, pain, cognitive impairments, and psychological disorders (eg, depression and anxiety). Sleep-wake disturbances associated with TBI warrant treatment. Although evidence specific to patients with TBI is still scarce, cognitive-behavioural therapy and medication could prove helpful to alleviate sleep-wake disturbances in patients with a TBI.
•This is the first review determining psychological morbidities amidst COVID-19 pandemic.•Almost half of the general public had a significant mental health impact.•Poor sleep quality was the ...commonest problem followed by stress, psychological distress.•The burden was highest among the COVID-19 patients followed by healthcare workers.
This review was done to synthesize the existing evidence on the prevalence of various psychological morbidities among general public, healthcare workers and COVID-19 patients amidst this pandemic situation. Systematic searches were conducted in various databases and search engines such as Medline, Chinese national knowledge infrastructure, Cochrane library, ScienceDirect, and Google Scholar from inception until 22 April 2020. Newcastle Ottawa scale was used to assess the quality of included studies. We carried out a meta-analysis with random-effects model and reported pooled prevalence with 95% confidence intervals (CIs).A total of 50 studies were included in the review. Only seven studies (14%) had low risk of bias. Pooled prevalence rate of psychological morbidities includes poor sleep quality (40%), stress (34%), psychological distress (34%), insomnia (30%), post-traumatic stress symptoms (27%), anxiety (26%), depression (26%). Pooled prevalence rate of psychological morbidities with respect to impact of event due to COVID-19 pandemic was 44% (95%CI-42% to 47%). The burden of these psychological morbidities was highest among the COVID-19 patients followed by healthcare workers and general population.
•Develop innovative machine-learning techniques for railway predictive maintenance.•Address big data challenges coming from large and complex multi-detector network.•Develop human-interpretable rules ...to facilitate railway operations.•Develop innovative prediction of alarms related to catastrophic component failure in advance.
Rail network velocity is defined as system-wide average speed of line-haul movement between terminals. To accommodate increased service demand and load on rail networks, increase in network velocity, without compromising safety, is required. Among many determinants of overall network velocity, a key driver is service interruption, including lowered operating speed due to track/train condition and delays caused by derailments. Railroads have put significant infrastructure and inspection programs in place to avoid service interruptions. One of the key measures is an extensive network of wayside mechanical condition detectors (temperature, strain, vision, infrared, weight, impact, etc.) that monitor the rolling-stock as it passes by. The detectors are designed to alert for conditions that either violate regulations set by governmental rail safety agencies or deteriorating rolling-stock conditions as determined by the railroad.
Using huge volumes of historical detector data, in combination with failure data, maintenance action data, inspection schedule data, train type data and weather data, we are exploring several analytical approaches including, correlation analysis, causal analysis, time series analysis and machine learning techniques to automatically learn rules and build failure prediction models. These models will be applied against both historical and real-time data to predict conditions leading to failure in the future, thus avoiding service interruptions and increasing network velocity. Additionally, the analytics and models can also be used for detecting root cause of several failure modes and wear rate of components, which, while do not directly address network velocity, can be proactively used by maintenance organizations to optimize trade-offs related to maintenance schedule, costs and shop capacity. As part of our effort, we explore several avenues to machine learning techniques including distributed learning and hierarchical analytical approaches.
Minichromosome maintenance proteins (MCMs) are DNA-dependent ATPases that bind to replication origins and license them to support a single round of DNA replication. A large excess of MCM2-7 assembles ...on chromatin in G1 phase as pre-replication complexes (pre-RCs), of which only a fraction become the productive CDC45-MCM-GINS (CMG) helicases that are required for genome duplication
. It remains unclear why cells generate this surplus of MCMs, how they manage to sustain it across multiple generations, and why even a mild reduction in the MCM pool compromises the integrity of replicating genomes
. Here we show that, for daughter cells to sustain error-free DNA replication, their mother cells build up a nuclear pool of MCMs both by recycling chromatin-bound (parental) MCMs and by synthesizing new (nascent) MCMs. Although all MCMs can form pre-RCs, it is the parental pool that is inherently stable and preferentially matures into CMGs. By contrast, nascent MCM3-7 (but not MCM2) undergo rapid proteolysis in the cytoplasm, and their stabilization and nuclear translocation require interaction with minichromosome-maintenance complex-binding protein (MCMBP), a distant MCM paralogue
. By chaperoning nascent MCMs, MCMBP safeguards replicating genomes by increasing chromatin coverage with pre-RCs that do not participate on replication origins but adjust the pace of replisome movement to minimize errors during DNA replication. Consequently, although the paucity of pre-RCs in MCMBP-deficient cells does not alter DNA synthesis overall, it increases the speed and asymmetry of individual replisomes, which leads to DNA damage. The surplus of MCMs therefore increases the robustness of genome duplication by restraining the speed at which eukaryotic cells replicate their DNA. Alterations in physiological fork speed might thus explain why even a minor reduction in MCM levels destabilizes the genome and predisposes to increased incidence of tumour formation.
Gas-insulated substation (GIS) equipment served in the traction power-supply system (TPSS) of the high-speed railway (HSR) suffers from extremely severe traction load conditions during its lifetime. ...In this paper, three major issues related to the actual field maintenance operations of GIS equipment in TPSS are addressed: 1) s-dependent degradation and shock process; 2) both spatial and temporal failure thresholds of shocks; and 3) incomplete maintenance (i.e., nonignorable maintenance time). To model the deterioration and failure process of GIS equipment, the hard failure model and the soft failure model are proposed. The characteristic function is utilized to bridge the s-dependent degradation and shock process in the soft failure model, while the extreme shock model (with spatial threshold) and δ-shock model (with temporal threshold) are introduced in the hard failure model. Furthermore, the index of availability, which combines both reliability and maintainability, is derived under the incomplete maintenance consideration. Based on the balance of availability and maintenance cost, the maintenance strategy with periodic inspections for GIS equipment in the long-run time span is developed. Optimizations of three decision parameters (i.e., inspection period, extreme shock threshold, and δ-shock threshold) are implemented to achieve the best performance (with high availability and low maintenance cost) of the maintenance strategy.
While there has been considerable work over the years on the basic deterministic economic production quantity (EPQ) and its derivative models, there have been few extensions of these models that ...recognize the potential effects of machine degradation. As maintenance activities can keep machines in good operation, it should be integrated into EPQ models to meet real situations. Due to machine degradation, this paper integrates predictive maintenance into EPQ model in which autoregressive integrated moving average model is adopted to predict system’s healthy indicator. Moreover, two kinds of system out-of-control states are considered in this proposed EPQ model: in State I, the system produces non-conforming items; and in State II, the system fails. Aiming at minimizing the expected average total cost and optimizing the EPQ, suitable maintenance intervals and frequency are determined prior to any predicted failure. Finally, a case study is presented and the computational results are discussed to show the efficiency of this integrated EPQ model.
To prospectively assess sleep reactivity as a diathesis of insomnia, and to delineate the interaction between this diathesis and naturalistic stress in the development of insomnia among normal ...sleepers.
Longitudinal.
Community-based.
2,316 adults from the Evolution of Pathways to Insomnia Cohort (EPIC) with no history of insomnia or depression (46.8 ± 13.2 y; 60% female).
None.
Participants reported the number of stressful events they encountered at baseline (Time 1), as well as the level of cognitive intrusion they experienced in response to each stressor. Stressful events (OR = 1.13; P < 0.01) and stress-induced cognitive intrusion (OR = 1.61; P < 0.01) were significant predictors of risk for insomnia one year hence (Time 2). Intrusion mediated the effects of stressful events on risk for insomnia (P < 0.05). Trait sleep reactivity significantly increased risk for insomnia (OR = 1.78; P < 0.01). Further, sleep reactivity moderated the effects of stress-induced intrusion (P < 0.05), such that the risk for insomnia as a function of intrusion was significantly higher in individuals with high sleep reactivity. Trait sleep reactivity also constituted a significant risk for depression (OR = 1.67; P < 0.01) two years later (Time 3). Insomnia at Time 2 significantly mediated this effect (P < 0.05).
This study suggests that premorbid sleep reactivity is a significant risk factor for incident insomnia, and that it triggers insomnia by exacerbating the effects of stress-induced intrusion. Sleep reactivity is also a precipitant of depression, as mediated by insomnia. These findings support the stress-diathesis model of insomnia, while highlighting sleep reactivity as an important diathesis.
Drake CL, Pillai V, Roth T. Stress and sleep reactivity: a prospective investigation of the stress-diathesis model of insomnia.
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