Maintenance Activities Research Articles

Enhanced measurement and optimization of railway profile parameters for large tamping machine operations

Abstract In the realm of modern railway maintenance, the employment of large tamping machine for the enhancement of track geometry and elasticity, and the minimization of disturbance to the roadbed, has become a key operational approach. However, factors such as repeated load applications, changes in topography and geology, and ongoing maintenance activities have been known to cause significant deviations of the actual track location from its original design. These deviations present challenges, such as increased construction difficulty and workload, during tamping operations predicated on the original design. Moreover, methods based on manual intervention have rendered large machine maintenance operations inefficient. In this paper, an optimisation method for railway profile parameters suitable for large tamping machine operations is proposed. The method integrates the total least squares method and the direct search method, enabling the accurate fitting of slope segments preceding and following the slope change points and the alignment of circular curve segments to determine the optimal curve radius. Consequently, optimised profile parameters for the continuous track section are obtained. Focusing on the Beijing–Guangzhou line, the operational efficacy of the proposed optimisation method is compared with that of the artificial slope method. The results showed that the proposed optimisation method is not only more accurate and efficient but also adheres to the principle of ‘prefer lifting rather than descending’ of the railways. The method further provides a theoretical basis and practical guidance for the optimisation of railway profile, underscoring the potential for improved maintenance efficiency and enhanced safety in train operations.

Imperfect maintenance modelling and estimation for interval-censored data

The paper proposes a new maintenance model for a repairable system. The system is inspected at deterministic times. If a failure occurs between two successive inspections, a minimal repair is performed. At inspection times, two types of maintenance actions can be performed. The first originality of the paper is to consider that the choice between these two types of maintenance depends on the fact that there has been a failure or not since the previous inspection. If no failure has occurred since the last inspection, the maintenance, simply denoted PM, corresponds to a basic preventive maintenance action, whose effect is planned by the initial maintenance plan. If at least one failure has occurred since the last inspection, the maintenance, denoted PCM, includes both the preventive action planned by the initial maintenance plan, and a specific corrective action which aims to fix the defects that have happened since the last inspection. Both types of maintenances are assumed to be imperfect, of the ARA (Arithmetic Reduction of Age) type, with different parameters. Moreover, the paper derives several statistical inference methods for this model. The usual case of complete data is first considered. The second originality of the paper is to analyse interval-censored data in this imperfect maintenance framework. This situation holds when failure times are not observed, and the only information is the fact that failures have occurred or not between two inspections. The quality of the proposed methods is assessed on simulated data. Finally, a real dataset from a gas transmission system operator is provided and analysed with the proposed approach.

Modulation of brain energy metabolism in hepatic encephalopathy: impact of glucose metabolic dysfunction.

Cerebral function is linked to a high level of metabolic activity and relies on glucose as its primary energy source. Glucose aids in the maintenance of physiological brain activities; as a result, a disruption in metabolism has a significant impact on brain function, launching a chain of events that leads to neuronal death. This metabolic insufficiency has been observed in a variety of brain diseases and neuroexcitotoxicity disorders, including hepatic encephalopathy. It is a significant neurological complication that develops in people with liver disease, ranging from asymptomatic abnormalities to coma. Hyperammonemia is the main neurotoxic villain in the development of hepatic encephalopathy and induces a wide range of complications in the brain. The neurotoxic effects of ammonia on brain function are thought to be mediated by impaired glucose metabolism. Accordingly, in this review, we provide an understanding of deranged brain energy metabolism, emphasizing the role of glucose metabolic dysfunction in the pathogenesis of hepatic encephalopathy. We also highlighted the differential metabolic profiles of brain cells and the status of metabolic cooperation between them. The major metabolic pathways that have been explored are glycolysis, glycogen metabolism, lactate metabolism, the pentose phosphate pathway, and the Krebs cycle. Furthermore, the lack of efficacy in current hepatic encephalopathy treatment methods highlights the need to investigate potential therapeutic targets for hepatic encephalopathy, with regulating deficient bioenergetics being a viable alternative in this case. This review also demonstrates the importance of the development of glucose metabolism-focused disease diagnostics and treatments, which are now being pursued for many ailments.

A Data-Driven Modeling Framework for Lithium Metal Battery Health Estimation

The Achilles' heel of LMB, despite its high theoretical energy density, has been its limited lifespan and variability in aging trajectories due to coupling of multiple failure mechanisms. Effective health estimation could enable timely maintenance actions before failure and a rapid LMB development iteration. Data-driven methods capture a wide spectrum of failure mechanisms and incorporates aging behavior variability. Recent work around data-driven LMB health estimation rely on empirical correlations observed specific to the datasets [1][2], and lack adaptability for a wide variety of experimental conditions and cell behaviors, especially those with a flat discharge capacity retention followed by abrupt decline.In this work, we cycled 36 LMB cells across various temperatures and charge/discharge rates. The examined cells exhibit significant cell-to-cell variabilities even under identical experimental conditions, and consistent abrupt capacity fade behaviors. We extracted an extensive inventory of non-invasive features based on cycle-to-cycle variation of LMB external voltage-current measurements throughout aging, and managed to accurately track LMB capacity fade with quantified confidence intervals using these features combined with machine learning tools. The identified features provide not only reliable and robust LMB health monitoring performance, but also starting points for further first-principal modeling and experimental investigation to demystify LMB aging mechanisms. The abundance of discovered features, along with an automatic and time-efficient correlation mining pipeline, enables the generalizability of our proposed framework toward a wide variety of LMB cells.

Integrated design and maintenance strategies for wind turbine gearboxes

PurposeThe purpose of this paper is to optimize the maintenance strategies for wind turbine (WT) gearboxes to minimize costs associated with PM actions, cooling, production loss and gearbox replacement. Two approaches, periodic imperfect maintenance and a novel design incorporating alternating gearboxes are compared to identify the most cost-effective solution.Design/methodology/approachThis study employs mathematical modeling to analyze the design, operation and maintenance of WT gearboxes. Two maintenance strategies are investigated, involving periodic imperfect maintenance actions and the incorporation of two similar gearboxes operating alternately. The models determine optimal preventive maintenance (PM) and switching periods to minimize total expected costs over the operating time span.FindingsThe research findings reveal, for the considered case of a moroccan wind farm, that the use of two similar gearboxes operating alternately is more cost-effective than relying on a single gearbox. The mathematical models developed enable the determination and comparison of optimal strategies for various WT gearbox scenarios and associated maintenance costs.Research limitations/implicationsLimitations may arise from simplifications in the mathematical models and assumptions about degradation, temperature monitoring and maintenance effectiveness. Future research could refine the models and incorporate additional factors for a more comprehensive analysis.Practical implicationsPractically, the study provides insights into optimizing WT gearbox maintenance strategies, considering the trade-offs between PM actions, cooling, production loss and gearbox replacement costs. The findings can inform decisions on maintenance planning and design modifications to enhance cost efficiency.Social implicationsWhile the primary focus is on cost optimization, the study indirectly contributes to the broader societal goal of sustainable energy production. Efficient maintenance strategies for WTs help ensure reliable and cost-effective renewable energy, potentially benefiting communities relying on wind power.Originality/valueThis paper introduces two distinct strategies for WT gearbox maintenance, extending beyond traditional periodic maintenance. The incorporation of alternating gearboxes presents a novel design approach. The developed mathematical models offer a valuable tool for determining and comparing optimal strategies tailored to specific WT scenarios and associated maintenance costs.

Research on the plastic radius of pile penetration in CPT clayey seabed

Offshore jackups are frequently employed for well workover or maintenance operations, necessitating repeated usage at the same location. Precisely defining the radius of the soil's plastic zone during pile penetration offers a theoretical foundation for establishing the minimum pile spacing required for subsequent well workover or maintenance activities. This study examines the radius of the plastic zone in the seabed of silty soil in the offshore region of the Yellow River Delta and the bearing capacity at various pile diameters following pile penetration, utilizing the Cone Penetration Test (CPT). The specific conclusions are as follows: (1) The disturbance radius of pile penetration into seabed silty soil ranges from approximately 2D to 3D; (2) Utilizing the pile bearing capacity calculation method proposed by Eslami and Fellenius, it is determined that the bearing capacity at a distance of 2.66D from the pile core is equivalent to the initial penetration bearing capacity; (3) According to the Mohr-Coulomb yield criterion theory, the plastic radius of pile penetration in seabed silty soil is calculated to be between 2.4D and 3.2D; (4) The disturbance radius derived from fitting the optimal bearing capacity curve aligns with the minimum pile spacing calculated according to the Mohr-Coulomb yield criterion theory, thereby confirming that the CPT test can accurately estimate the plastic radius of pile penetration.

Assessment of Maintenance Activities and Strategies for Tractor and Operator Care in Gurage Zone, Wolkite Town, Ethiopia

Data was collected from 53 tractor operators and stakeholders from the Wolkite. Many types of tractors were used and the common brands were Sonalika, Indo-farm, John Deer, Massey, Fergusson, and New Holland. Of these tractors, about 30.18%, 20.75%, and 18.86% were used for plowing, harrowing, transporting, threshing, planting, and spraying activities by Sonalika, Indo-farm, and John deer respectively. Regarding training to operate the machine, about 71.69% replied yes and about 28.31% replied don't have the training to maintain the machine, but they develop their skills through different experiences. But for their maintenance activities, they replied as 22.64% for daily, 92.45% for weekly, and 100% for monthly. In the case of checking the fluid level of the tractors about 9.43% within 3 hours, 20.75% within 6 hours, and 84.9% within 10 hours with oil level, about 3.77% within 3 hours, 11.32% within 6 hours and 98.11 within 10 hours for checking the water level and lastly about 15.09% within 3 hours, 71.69% within 6 hours and 94.33% within 10 hours to check the level of fuels. Moreover the washing of the tractors after the operation was 1.88% washed their tractors after operation; about 5.66% didn't wash their tractors, and about 92.46 washed without schedule. For lubricating different rotating parts of the tractors, about 56% of the respondents lubricate their tractor parts and about 92.45% of the respondents clean the battery cables and terminals frequently. About 3.77% and 16.98% use shelter for their tractors and record-keeping experience during their work.

The pontine Kölliker-Fuse nucleus is important for reduced post-inspiratory airflow elicited by stimulation of the ventral respiratory parafacial region.

Considering that the retrotrapezoid nucleus/respiratory parafacial region (RTN/pFRG) would be an important center in the central nervous system involved in the maintenance and modulation of respiratory activity, we hypothesized that neurons in this nucleus would also be involved in the postinspiratory phase of the respiratory cycle through a connection with the pontine Kölliker-Fuse (KF) region. Here we performed pharmacogenetic manipulation (AAV-hM3D(Gq)-mCherry or AAV-hM4D(Gi)-mCherry) in VGlut2-cre, Ai6 conscious mice to evaluate breathing parameters through whole body plethysmography under baseline conditions (normoxia: FiO2 = 0.21) or under hypercapnia or hypoxia challenges (FiCO2 = 0.07 or FiO2 = 0.08). Under normoxia, selective stimulation of RTN/pFRG resulted in a smaller increase in VE (1,272 ± 102.5, vs. RTN/pFRG stimulation: 1,878 ± 122.1 ml/kg/min), due to a smaller increase in VT (5.4 ± 0.35, vs. RTN/pFRG stimulation: 7.77 ± 0.21 ml/kg) without changing fR in a condition of KF inhibition. However, inhibition of the VGlut2 neurons in the KF did affect the TE1 produced by selective activation of RTN/pFRG (119.9 ± 2.53, vs. RTN/pFRG stimulation: 104 ± 2.46 ms). Both the hypercapnia and hypoxia ventilatory response were reduced after inhibition of VGlut2-expressing KF neurons. Therefore, consistent with anatomical projections RTN/pFRG neurons regulate lung ventilation by controlling all aspects of breathing, i.e breathing frequency, inspiration, postinspiration and active expiration. All the modulation seems to be dependent on the integrity of the glutamatergic neurons in the KF region.

Assessment of UHF Frequency Range for Failure Classification in Power Transformers.

Ultrahigh-frequency (UHF) sensing is one of the most promising techniques for assessing the quality of power transformer insulation systems due to its capability to identify failures like partial discharges (PDs) by detecting the emitted UHF signals. However, there are still uncertainties regarding the frequency range that should be evaluated in measurements. For example, most publications have stated that UHF emissions range up to 3 GHz. However, a Cigré brochure revealed that the optimal spectrum is between 100 MHz and 1 GHz, and more recently, a study indicated that the optimal frequency range is between 400 MHz and 900 MHz. Since different faults require different maintenance actions, both science and industry have been developing systems that allow for failure-type identification. Hence, it is important to note that bandwidth reduction may impair classification systems, especially those that are frequency-based. This article combines three operational conditions of a power transformer (healthy state, electric arc failure, and partial discharges on bushing) with three different self-organized maps to carry out failure classification: the chromatic technique (CT), principal component analysis (PCA), and the shape analysis clustering technique (SACT). For each case, the frequency content of UHF signals was selected at three frequency bands: the full spectrum, Cigré brochure range, and between 400 MHz and 900 MHz. Therefore, the contributions of this work are to assess how spectrum band limitation may alter failure classification and to evaluate the effectiveness of signal processing methodologies based on the frequency content of UHF signals. Additionally, an advantage of this work is that it does not rely on training as is the case for some machine learning-based methods. The results indicate that the reduced frequency range was not a limiting factor for classifying the state of the operation condition of the power transformer. Therefore, there is the possibility of using lower frequency ranges, such as from 400 MHz to 900 MHz, contributing to the development of less costly data acquisition systems. Additionally, PCA was found to be the most promising technique despite the reduction in frequency band information.

Segmenting hydrogen‐induced cracking defects in steel through scanning acoustic microscopy and deep neural networks

AbstractHydrogen‐induced cracking (HIC) presents a significant concern in industries, such as oil and gas, petrochemicals, and aerospace, where high‐strength steel is prevalently used. This phenomenon compromises the structural integrity of steel pipelines and equipment. Accurate detection and monitoring of HIC are crucial for the safety and reliability of these assets. While traditional defect detection methods are usually costly and easily affected by human physiological state, deep learning approaches offer both time and financial benefits along with high accuracy. This study focuses on employing deep learning to segment HIC in steel, utilizing the robust and state‐of‐the‐art YOLOv8‐seg architecture for defect identification and segmentation. The process involves acquiring two‐dimensional B‐scan images through a scanning acoustic microscopy (SAM) system, followed by employing the YOLOv8‐seg architecture to address the segmentation task within these images. The experimental results demonstrate the effectiveness of the YOLOv8‐seg model, achieving a mean average precision (mAP) score greater than ˜0.95. Notably, this research pioneers the development of a framework for reconstructing HIC within steel based on B‐scan image segmentation results, offering researchers and professionals a comprehensive understanding of internal defects in steel blocks. This work underscores the potential of YOLOv8‐seg architecture for accurate detection and segmentation of HIC in steel, providing a valuable tool for inspection and maintenance activities.

Physical activity maintenance in colorectal cancer survivors after an exercise intervention applying behaviour change techniques: a systematic review and meta-analysis.

The purpose of this systematic review and meta-analysis is to determine the long-term effect of combined physical activity (PA) and behaviour change techniques (BCT) interventions in PA maintenance of colorectal cancer survivors (CRCS) and identify the most frequent BCT implemented in them. PRISMA recommendations were followed. Databases were searched for randomized controlled trials up to October 2023. Studies in which CRCS completed a PA intervention based on any Theoretical Model of Behaviour Change (TMBC) and a subsequent follow-up period were included. Between-group differences at baseline and after follow-up were pooled for meta-analysis. BCT codification was performed using the BCT taxonomy v1. Methodological quality and evidence certainty were also assessed. Five studies involving 906 CRCS met the inclusion criteria. PA interventions applying BCT showed a significant change with a small positive effect (pooled SMD = 0.22 (0.09, 0.35)) on the PA after a follow-up period between 3 and 12months. Twenty-two different BCTs were identified (mean 17.2, range 15-19) of which 12 were common across all interventions. PA and BCT interventions have been found to be effective in improving the long-term maintenance of PA in CRCS. Further studies with higher methodological quality are needed to confirm these findings. Aerobic exercise, pedometers, PA diaries and educational materials seem to be important aspects to achieve sustainable adherence to an active lifestyle over time. Supervision, access to fitness areas and applying some BCT appear to be differentiating features to obtain more successful PA maintenance.

The impact of the COVID-19 pandemic on the psychosomatic status of emeritus professors: The importance of active lifestyles

AbstractPurposeThe COVID-19 pandemic has had an enormous negative impact on the psychosomatic status of the general population, and especially of more vulnerable populations, such as older people. The present study aimed to assess changes in psychosomatic status before and after the COVID-19 pandemic among emeritus professors over 70 years of age.Materials/MethodsA total of 56 emeritus professors aged 77.4 ± 6.1 (74.1% male) participated in the study. The study was conducted between September 2022 and January 2023, after approximately two and a half years of the COVID-19 pandemic. Sociodemographic characteristics, including socioeconomic status, were assessed in the questionnaire, along with active involvement in academic life and healthcare/sports. Physical and mental fatigue were assessed using a self-report questionnaire, and the impact of fatigue on physical and cognitive function was measured using the Fatigue Impact Scale. Participants evaluated their physical/mental fatigue and physical/cognitive function before and after the COVID-19 pandemic.ResultsAmong the participating emeritus professors, 15% reported higher levels of physical fatigue (Z = −1.992, P = 0.046, r = 0.28) and mental fatigue (Z = −2.154, P = 0.031, r = 0.31) following the COVID-19 pandemic. A significant difference was found in physical function assessed before and after the COVID-19 pandemic, t(51) = −2.986, P = 0.004, g = 0.22, while cognitive function showed a non-significant difference, t(51) = −1.265, P = 0.212, g = 0.12. After the COVID-19 pandemic, 26.9% of participants reported reduced physical function and 19.2% showed reduced cognitive function. Infection with the COVID-19 virus resulted in increased mental fatigue and reduced cognitive function among the participating emeritus professors.ConclusionThe COVID-19 pandemic (and the introduction of restrictions on social activities) had a substantial and similar impact on the psychosomatic status of emeritus professors at both medical and sports universities. Furthermore, the reduction in physical and mental/cognitive function was exacerbated in those who were infected by SARS-CoV-2. Importantly, however, the overall impact of the COVID-19 pandemic was smaller in the population of emeritus professors than in the general elderly population. This may be due to the better maintenance of physical and mental activity in the former population, thus emphasising the importance of remaining physically and mentally active in old age, especially in the context of critical life events.

An environmentally-friendly optimization framework for road pricing and pavement management under public-private-partnership

Vehicular emissions and the unsustainable development of transportation systems have received increasing attention in recent years. On one hand, transportation emissions increase as car ownership increases. On the other hand, construction of the new transportation infrastructure and maintenance of the existing transportation facilities are needed as travel demand increases. Thus there is a growing market for Public-Private Partnership (PPP), which aims to overcome existing deficiencies of traditional approaches while stimulating the sustainable development of transportation systems. This paper proposes an environmentally-friendly multi-objective optimization framework to derive dynamic toll pricing strategies and pavement maintenance and rehabilitation (M&R) activities for road networks containing PPP projects. A case study of a road network containing toll and toll-free highways in Florida, United States is used to verify the performance of the proposed approach. The results show that the public and private sectors could coordinate their actions to guarantee profits for the private sector while alleviating negative externalities for society.

Bevacizumab Erlotinib Switch Maintenance in Chemo-Responsive Advanced Gallbladder and Cholangiocarcinoma (BEER BTC): A Multicenter, Open-Label, Randomized, Phase II Trial.

Patients with chemotherapy-responsive advanced biliary tract cancers (BTCs) are usually observed after 6 months of gemcitabine-based therapy. There is limited prospective evidence for maintenance strategies after chemotherapy. This investigator-initiated, open-label, randomized, integrated phase II-III study enrolled adult patients with advanced BTC from two cancer centers in India. Patients with histologically confirmed advanced biliary tract adenocarcinoma who had at least disease stabilization after 6 months of gemcitabine-based chemotherapy were randomly assigned (1:1) to either active surveillance or switch maintenance, which was a combination of bevacizumab 5 mg/kg intravenous once every 21 days plus erlotinib 100 mg once daily. Both arms were continued until disease progression, unacceptable toxicity, or patient decision to withdraw. The primary end point of the phase II component of the trial was investigator-evaluated progression-free survival. This trial is registered with Clinical Trials Registry of India (CTRI/2019/05/019323I). From May 2021 to November 2022, 98 patients were randomly assigned to active surveillance (n = 49) or bevacizumab-erlotinib (n = 49). A majority of patients had gallbladder cancer (80%). The median follow-up was 13.4 months. The median progression-free survival was 3.1 months (95% CI, 2.47 to 3.64) in the active surveillance group versus 5.3 months (95% CI, 3.53 to 7.04) in the bevacizumab-erlotinib group (hazard ratio, 0.51 [95% CI, 0.33 to 0·74]; P = .0013). The most common grade 3 class-specific adverse events associated with bevacizumab-erlotinib were acneiform rash 1 (2%) and oral stomatitis 1 (2%) with erlotinib and bleeding 1 (2%) with bevacizumab. The combination of bevacizumab and erlotinib as switch maintenance improves progression-free survival with an acceptable safety profile compared with active surveillance in patients with advanced BTCs in this phase II study. The trial moves on to the phase III component to evaluate improvement in overall survival.

The Application of Infrared Thermography for Enhancing Maintenance in Public University

A university’s main function is to produce quality graduates, and in doing so, university buildings do play significant roles and are vital assets and resources. Hence, to prolong a university building lifecycle to ensure all university activities to continue performing at an optimum level, building maintenance management is central. Eventhough previous studies have been conducted in this area, university buildings maintenance is still viewed as insignificant. The research about utilization of infrared thermography in term of maintenance in public universities is still lacking. The objective of this research was to provide recommendations for areas within the public universities that can benefit from the application of infrared thermography to enhance maintenance. The research method used in this research was a qualitative method. Three public universities that were established for more than 50 years were chosen as case studies. The data was collected through narrative review and then analyzed. The findings highlighted the benefits of implementing infrared thermography in older building maintenance within public universities, particularly in improving energy efficiency and identifying hidden issues such as moisture intrusion and structural defects. The study emphasized the importance of timely maintenance actions based on infrared thermography assessments to reduce energy consumption and apply predictive maintenance strategies. By conducting in-depth analyses at three established public universities in Malaysia, the researchers demonstrate the effectiveness of infrared thermography in enhancing maintenance practices and prolonging the lifecycle of university buildings.

Studi Eksplorasi Sistem Drainase Fasilitas Sisi Udara di Bandar Udara: A Systematic Review

The Airside is a vital area related to aircraft movement. A drainage system needs to be implemented at each airport to support airside safety. This research aims to find out the drainage system at several airports. The exploration study of the drainage system on the air side uses a qualitative method based on a systematic literature review by comparing studies obtained through Google Scholar in the 2015-2024 period. Then, the author analyzes the issues raised using GAP analysis techniques. The sample airports are Juwata Tarakan Airport, Rahadi Oesman Ketapang Airport, Sultan Muhammad Salahuddin Bima Airport, Kualanamu Deli Serdang Airport, and Husein Sastranegara Bandung Airport. This study found that several factors, including structural damage, inefficiency of channel dimensions, instability of retaining walls, lack of rain catchment areas, and accumulated sedimentation, cause the overflow of water that arises when rain occurs. Therefore, it can be concluded that the airport needs to evaluate the effectiveness of channel dimensions using hydrological and hydraulic analysis methods. In addition to evaluation, the drainage system needs to be maintained, which refers to KP 94 of 2015 and KP 326 of 2019. Drainage maintenance activities can be carried out by cleaning sedimentation, vines, grass, and sediment in the channel to save operational costs and increase the channel's life. In addition, overflows on the air side can be minimized, and the safety of flight operations can be guaranteed.

Eight-year follow-up of patient-reported outcomes in patients with breast cancer participating in exercise studies during chemotherapy.

Numerous randomized controlled trials (RCTs) have shown beneficial exercise effects on fatigue, anxiety and depression and health-related quality of life (HRQoL) in breast cancer (BC) patients during and shortly after treatment. Here, we investigated the long-term effects of exercise during chemotherapy for BC on these outcomes. We invited participants of two highly comparable RCTs that investigated the effects of exercise (EX) (versus usual care (UC)) during chemotherapy in patients with non-metastatic BC (N = 357) to participate in an 8-year follow-up. In both trials, fatigue, anxiety and depression and HRQoL were assessed using the same questionnaires, at multiple timepoints. Linear mixed-effect models were used to compare study arms over time. In total, 156 participants (EX = 82; UC = 74) completed the follow-up questionnaires. EX reported comparable general (between-group difference 0.73, 95% confidence interval (- 0.35; 1.80), ES = 0.18) and physical fatigue (0.55 (- 0.55; 1.65), ES = 0.13), small but statistically significantly higher levels of anxiety (1.24 (0.47 to 2.00), ES = 0.39) and depression (1.10 (0.34; 1.85), ES = 0.38), significantly lower global HRQoL (- 5.99 (- 10.65; - 1.32), ES = 0.34) and comparable summary HRQoL (- 1.90 (- 4.70; 0.89), ES = 0.16) compared to UC. No long-term beneficial effects of exercise during chemotherapy on BC patients' fatigue, anxiety, depression or HRQoL were observed. The less favourable outcomes for mood and HRQoL that were observed 8years after participation in an exercise intervention may be explained by selective loss-to-follow-up. The results highlight the need to incorporate strategies that promote physical activity maintenance after participation in an exercise programme to also counteract long-term detrimental side effects of cancer treatment.

Implementing Component Degradations into a Modelica Model of an iPWR System to Develop Health Monitoring Techniques

The economic operation of small modular reactors will partly rely on managing and reducing inspection and maintenance activities while supporting new operational paradigms like load-following. Turbine control valves throttle the steam from the steam generator into the steam turbine while maintaining the pressure within the steam generator at a constant set point. Degradation of these components could impact the ability to manage electrical power production. Utilizing the Idaho National Laboratory Hybrid repository and the Oak Ridge National Laboratory TRANSFORM library developed for multiphysics simulations in Dymola/Modelica, an integral pressurized water reactor system was modeled based on the available specifications of the NuScale power module. The effects of various component degradation modes have been implemented into the model in order to simulate faulted plant data during both steady-state and load-following operations. The fault modes resemble different physical fault modes that may occur at an operating nuclear power plant; a leaking turbine control valve and a valve actuator failure due to loss of hydraulic pressure have been implemented. A neural network autoencoder is employed in conjunction with statistical analysis, namely, simple signal thresholding (SST) or sequential probability ratio testing (SPRT), to identify the presence of a fault. Fuzzy logic is additionally employed in a novel and promising manner to classify the state of the system based on the cumulative sum of the neural network residuals. SST and SPRT are both successfully validated using healthy data and proved capable of identifying both fault types; fuzzy logic identified the false positives and classified the faulted data correctly.

Environmental impacts from traffic on highway construction work zones: Framework and simulations

Emissions from internal combustion engine vehicles on highways are the major contributors to global warming in the United States. Transportation sector pavement-related emissions come from gasolines and diesel use in vehicles from pavement-vehicle interaction, which is affected by pavement conditions, and by the trucking of new pavement materials and demolition. The objective of this study was to develop a framework for determining the fuel use resulting in environmental impacts caused by construction work zones (CWZs) on a range of vehicles and to produce initial calculations of these impacts by modeling traffic closure conditions for highway maintenance and rehabilitation activities. The study included two common highway categories—freeways/multi-lane highways and two-lane highways. The framework was demonstrated using three CWZ operations under different traffic congestion levels. In the simulation results for a freeway with a CWZ and heavy congestion, fuel consumption increased by 85% and the carbon-dioxide equivalent emissions increased by 86%. Changing CWZ traffic congestion from heavy (average speed 5 mph) to medium (average speed 25 mph for a freeway section) reduced fuel consumption by 40% on a freeway. This study also included use of a pilot car in a CWZ on a two-lane road typical of lower traffic volume state highways and county roads to compare with the drive cycles in MOVES used for the scenarios. The pilot-car operation scenario results indicate that a one-lane closure with pilot-car operation on a two-lane road might consume 13% excess fuel because of idling time and the slow movement of vehicles following the pilot car.

Evaluating the Impact of Maintenance Actions on Diverse Users in Shared Automobile, Bicycle, and Pedestrian Facilities

Evaluating the Impact of Maintenance Actions on Diverse Users in Shared Automobile, Bicycle, and Pedestrian Facilities