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Demand response (DR) is the change in electric consumption by prompting consumers to change their normal consumption patterns in response to financial incentives. In various forms of DR, the contract-based DR is a framework to achieve a certain reduction by the contract with individual participants for their reduction. However, in practice, it is inevitable to encounter a default, implying that some of the participants fail contracted reduction owing to an unexpected event. This study develops a method to detect defaulting participants in contract-based DR. The method iterates two steps: estimating the most suspicious participant and inspecting its smart meter. By utilizing block-sparse structures in the detection problem, it can exactly determine the defaulting participants with a small number of inspections. The performance is evaluated by simulation, which indicates that our method has much higher performance than the conventional method in the sense that the number of inspections approximately 96.8% fewer than that of the conventional one.

BackgroundStroke stands as a prominent cause of mortality and disability worldwide, posing a major public health concern. Recent years have witnessed rapid advancements in artificial intelligence (AI). Studies have explored the utilization of AI in imaging analysis, assistive rehabilitation, treatment, clinical decision-making, and outcome and risk prediction concerning stroke. However, there is still a lack of systematic bibliometric analysis to discern the current research status, hotspots, and possible future development trends of AI applications in stroke.MethodsThe publications on the application of AI in stroke were retrieved from the Web of Science Core Collection, spanning 2004–2024. Only articles or reviews published in English were included in this study. Subsequently, a manual screening process was employed to eliminate literature not pertinent to the topic. Visualization diagrams for comprehensive and in-depth analysis of the included literature were generated using CiteSpace, VOSviewer, and Charticulator.ResultsThis bibliometric analysis included a total of 2,447 papers, and the annual publication volume shows a notable upward trajectory. The most prolific authors, countries, and institutions are Dukelow, Sean P., China, and the University of Calgary, respectively, making significant contributions to the advancement of this field. Notably, stable collaborative networks among authors and institutions have formed. Through clustering and citation burst analysis of keywords and references, the current research hotspots have been identified, including machine learning, deep learning, and AI applications in stroke rehabilitation and imaging for early diagnosis. Moreover, emerging research trends focus on machine learning as well as stroke outcomes and risk prediction.ConclusionThis study provides a comprehensive and in-depth analysis of the literature regarding AI in stroke, facilitating a rapid comprehension of the development status, cooperative networks, and research priorities within the field. Furthermore, our analysis may provide a certain reference and guidance for future research endeavors.

BackgroundVascular cognitive impairment (VCI) manifests in memory impairment, mental slowness, executive dysfunction, behavioral changes, and visuospatial abnormalities, significantly compromising the quality of daily life for patients and causing inconvenience to caregivers. Neuroimaging serves as a crucial approach to evaluating the extent, location, and type of vascular lesions in patients suspected of VCI. Nevertheless, there is still a lack of comprehensive bibliometric analysis to discern the research status and emerging trends concerning VCI neuroimaging.ObjectiveThis study endeavors to explore the collaboration relationships of authors, countries, and institutions, as well as the research hotspots and frontiers of VCI neuroimaging by conducting a bibliometric analysis.MethodsWe performed a comprehensive retrieval within the Core Collection of Web of Science, spanning from 2000 to 2023. After screening the included literature, CiteSpace and VOSviewer were utilized for a visualized analysis aimed at identifying the most prolific author, institution, and journal, as well as extracting valuable information from the analysis of references.ResultsA total of 1,024 publications were included in this study, comprising 919 articles and 105 reviews. Through the analysis of keywords and references, the research hotspots involve the relationship between neuroimaging of cerebral small vessel disease (CSVD) and VCI, the diagnosis of VCI, and neuroimaging methods pertinent to VCI. Moreover, potential future research directions encompass CSVD, functional and structural connectivity, neuroimaging biomarkers, and lacunar stroke.ConclusionThe research in VCI neuroimaging is constantly developing, and we hope to provide insights and references for future studies by delving into the research hotspots and frontiers within this field.

IntroductionPost-stroke dysphagia (PSD) is associated with various complications that increase morbidity and mortality rates. Acupuncture has been used extensively in China to treat these complications; however, its therapeutic efficacy remains uncertain. We therefore aimed to study the clinical effects of acupuncture on PSD.MethodsPatients (n = 101) were randomly divided into acupuncture (n = 50) and rehabilitation training control (n = 51) groups based on the treatment used. Both groups were treated once daily, 6 days a week, for a total of 4 weeks. Pulse oxygen saturation (SpO2) and standardized swallowing assessment (SSA) were performed before the intervention, 2 weeks into treatment, after the intervention (4 weeks post-intervention), and at a 6-month follow-up (28 weeks). The levels of hemoglobin (Hb) and albumin (ALB), and 5-hydroxytryptamine (5-HT) and dopamine (DA) were measured before the intervention, 2 weeks into treatment, and after the intervention (4 weeks), as nutrition and swallowing function indices, respectively.ResultsFollowing the intervention, significant differences were observed between the acupuncture and control groups. The acupuncture group exhibited considerably superior enhancements in SpO2 and SSA scores at 4 weeks (p 0.005).ConclusionAcupuncture treatment can improve the swallowing function and nutritional status of patients with PSD, and increase the levels of 5-HT and DA. These findings strongly support the efficacy of acupuncture as a therapeutic intervention in patients with PSD.Clinicaltrial registration: identifier, ChiCTR2100052201. (https://www.chictr.org.cn/).

BackgroundFunctional near infrared spectroscopy (fNIRS) has developed rapidly in recent years, and there are more and more studies on fNIRS. At present, there is no bibliometric analysis of the top 100 most cited articles on fNIRS research.ObjectiveTo identify the top 100 most cited articles on fNIRS and analyze those most fundamental and popular articles through bibliometric research methods.MethodsThe literature on fNIRS of web of science from 1990 to 2023 was searched and the top 100 most cited articles were identified by citations. Use the bibliometrix package in R studio and VOSviewer for data analysis and plotting to obtain the output characteristics and citation status of these 100 most cited articles, and analyze research trends in this field through keywords.ResultsA total of 9,424 articles were retrieved from web of science since 1990. The average citation number of the 100 articles was 457.4 (range from 260 to 1,366). Neuroimage published the most articles (n = 31). Villringer, A. from Leipzig University had the largest number of top 100 papers. Harvard University (n = 22) conducted most cited articles. The United States, Germany, Japan, and the United Kingdom had most cited articles, respectively. The most common keywords were near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fMRI, spectroscopy. The fund sources mostly came from National Institutes of Health Unitd States (NIH) and United States Department of Health Human Services (n = 28).ConclusionNeuroimage was the most popular journal. The top countries, institutions, and authors were the United States, Harvard University, and Villringer, A., respectively. Researchers and institutions from North America and Europe contributed the most. Near-infrared spectroscopy, activation, cerebral-blood-flow, brain, newborn-infants, oxygenation, cortex, fmri, spectroscopy, stimulation, blood-flow, light-propagation, infants, tissue comprise the future research directions and potential topic hotspots for fNIRS.

PurposeThis bibliometric study explores cerebral palsy (CP) research from 2003 to 2022 to reveal the topic hotspots and collaborations.MethodsWe retrieved studies on CP from the Web of Science Core Collection from 2003 to 2022 and then used CiteSpace and Bibliometrix to perform a bibliometric analysis and attain knowledge mapping, including publication outputs, funding, journals, authors, institutions, countries/territories, keywords, collaborative relationships, and topic hotspots.ResultsIn total, 8,223 articles were published from 2003 to 2022. During this period, the number of publications increased continuously. Developmental Medicine and Child Neurology was the most productive and frequently co-cited journal. Boyd was the most productive and influential author, with 143 publications and 4,011 citations. The United States and Vrije Universiteit Amsterdam were the most productive countries and institutions, respectively. Researchers and institutions from the USA, Australia, and Canada constituted the core research forces, with extensive collaborations worldwide. The most common keywords were gait (553), rehabilitation (440), spasticity (325), botulinum toxin (174), therapy (148), upper extremity (141), quality of life (140), disability (115), pain (98), electromyography (97), kinematics (90), balance (88), participation (85), and walking (79).ConclusionThis study provides a systematic and comprehensive analysis of the CP-related literature. It reveals that Developmental Medicine and Child Neurology is the most active journal in this field. The USA, Vrije Universiteit Amsterdam, and Boyd are the top countries, institutions, and authors, respectively. Emerging treatment methods, complication management, and functional recovery comprise the future research directions and potential topic hotspots for CP.

Abstract This paper presents an innovative health-risk assessment methodology for the preventive protection of metal cultural relics in museums, which is based on the improved rank correlation analysis and AHP fuzzy synthetic evaluation (Relics—AHP—FSE). The approach combines the established ABC method for analyzing the pertinent environmental risk level. In this study, metal cultural relics are introduced as the research subjects. Based on the current scientific knowledge and requirements reported in international norms, a three-level index framework for assessing the health-risk is established in a hierarchical manner, and the quantitative indicators with typical correlations are proposed. The Relics—AHP—FSE approach is applied to the results of the 2022 temporary exhibition “Zhaizi China: Henan Xia, Shang and Zhou Dynasties civilization exhibition” of Shanghai Museum (China), a renowned institution boasting a significant collection of invaluable relics. In addition, the study accomplishes a scientific and practical health-risk assessment of relics. By utilizing online monitoring data and employing the expert judgment method, this study presents a comprehensive method for assessing the health-risk of metal cultural relics efficiently and conveniently. This cultural heritage protection method is specifically for safeguarding cultural relics exhibited in museums, developed in close collaboration with conservation scientists.

Abstract Background Neurogenic detrusor overactivity (NDO) is a serious and common complication after spinal cord injury, affecting patients’ quality of life seriously. Therefore, we developed this research protocol to evaluate the efficacy of repetitive functional magnetic stimulation (rFMS) in the sacral nerve in patients with neurogenic detrusor overactivity (NDO) after suprasacral spinal cord injury (SCI) and provide more options for rFMS in treating NDO after suprasacral SCI. Methods This study is a single-center, randomized, parallel-group clinical trial. We will recruit the patients with NDO after suprasacral SCI in the Rehabilitation Department of the Affiliated Hospital of Southwest Medical University from September 2022 to August 2023. They will be assigned to the rFMS group and the sham stimulation group randomly. The sample size is 66, with 33 patients in each group. The rFMS group will receive real rFMS treatment of the sacral nerve (100% stimulation intensity, 5 Hz, 20 min each time, five times a week), and the sham group will receive sham stimulation. Both groups will receive similar treatment strategies, including medication, standard urine management, acupuncture treatment, and health education. The bladder compliance (bladder capacity/detrusor pressure) and pudendal nerve electromyography will be evaluated at baseline, 8th week of treatment. The residual volume of the bladder and bladder diary will be recorded once a week during 8 weeks of treatments. SCI-QOL and NBSS will be evaluated at baseline, the 4th and 8th week of treatment. In addition, the above assessments will be followed up at 8 weeks after the end of treatment. Discussion It is expected that the bladder function, symptoms, and quality of life might be significantly improved after rFMS of the sacral nerve. Trial registration The China Clinical Trials Registry has approved this study, registration number: ChiCTR2100045148. Registered on April 7, 2021.

BackgroundDysphagia represents one of the common complications following a stroke, and post-stroke dysphagia (PSD) can lead to aspiration, pneumonia, and malnutrition, thus prolonging hospital stay, escalating medical expenditures, and imposing a substantial economic strain on both patients and society. The utilization of bibliometric analysis offers a quantitative approach for investigating the existing literature and recognizes the current status of the research. However, bibliometric analysis on the subject of PSD remains absent. Consequently, we carried out this study to provide researchers with insights, facilitating their further exploration of PSD.MethodsConducting a bibliometric analysis of articles pertaining to PSD retrieved over the past two decades enables us to acquire the research hotspots and trends in this area. The publications concerning PSD were searched from the Core Collection of Web of Science, spanning the period ranging from 2003 to 2023. Articles or reviews published in English were included in this study. Subsequently, we employed CiteSpace and VOSviewer software to visualize the retrieved articles, thereby identifying the cooperative relationships of authors, institutions, and countries, as well as relevant information about journals and references.ResultsThis study comprised 866 papers in total, and the number of articles published each year shows an overall growth trend. As for the analysis of the authors, Dziewas R. was the most prolific author with 21 articles. The most frequently published institutions, countries, and journals were the University of Manchester, China, and Dysphagia, with 28, 254, and 75 publications, respectively. And the co-cited authors and journals with the highest counts were Martino R and Stroke. According to the analysis of keywords and references, dysphagia screening and assessment, prevention of pneumonia, rehabilitation approaches, and nutritional management of PSD are considered research hotpots. Additionally, future research may focus on the topics of systematic review and meta-analysis, noninvasive brain stimulation, and lesion location.ConclusionThrough the bibliometrics analysis of PSD, we can capture the research hotspots and frontiers of PSD, thereby providing inspiration and reference for subsequent studies in this field.

In a network system, there inevitably be a few connection failures at nodes, such as delay. Once a failure occurs, the network administrator must detect failure sources as soon as possible to maintain communication over the network. Group testing is a method for detecting failure nodes in networks using a small number of measurements, provided that the measurement matrix is constructed appropriately. A promising method for constructing measurement matrices is given by the binary correlation matrices. This study analyzes the performance limitation of group testing based on the binary correlation measurement matrix. We derive the upper and lower bounds of the minimum number of measurements needed for network detection. Moreover, we propose a sufficient condition of network topology, under which the failure vertices in the network can be detected with optimal performance, and we also provide a detection scheme with guaranteed exactness for the network. Numerical example indicates that for the network that satisfies the proposed sufficient condition, the administrator can exactly detect the failure vertices with optimal performance by using our proposed detection scheme.

Histone post-translational modifications (HPTMs) are essential epigenetic mechanisms that affect chromatin-associated nuclear processes without altering the DNA sequence. With the application of mass spectrometry-based proteomics, novel histone lysine acylation, such as propionylation, butyrylation, crotonylation, malonylation, succinylation, glutarylation, and lactoylation have been successively discovered. The emerging diversity of the lysine acylation landscape prompted us to investigate the function and mechanism of these novel HPTMs in health and disease. Recently, it has been reported that β-hydroxybutyrate (BHB), the main component of the ketone body, has various protective roles beyond alternative fuel provision during starvation. Histone lysine β-hydroxybutyrylation (Kbhb) is a novel HPTMs identified by mass spectrometry, which regulates gene transcription in response to carbohydrate restriction or elevated BHB levels in vivo and vitro. Recent studies have shown that histone Kbhb is strongly associated with the pathogenesis of metabolic cardiovascular diseases, kidney diseases, tumors, neuropsychiatric disorders, and metabolic diseases suggesting it has different functions from histone acetylation and methylation. This review focuses on the writers, erasers, sites, and underlying functions of histone Kbhb, providing a glimpse into their complex regulation mechanism.

Sensing the cloud movement information has always been a difficult problem in photovoltaic (PV) prediction. The information used by current PV prediction methods makes it challenging to accurately perceive cloud movements. The obstruction of the sun by clouds will lead to a significant decrease in actual PV power generation. The PV prediction network model cannot respond in time, resulting in a significant decrease in prediction accuracy. In order to overcome this problem, this paper develops a visual transformer model for PV prediction, in which the target PV sensor information and the surrounding PV sensor auxiliary information are used as input data. By using the auxiliary information of the surrounding PV sensors and the spatial location information, our model can sense the movement of the cloud in advance. The experimental results confirm the effectiveness and superiority of our model.

Delirium is a cognitive disorder with complex etiology, which brings a great burden to social health care. Articles with high citation frequency can provide important information about the current research situation in a certain field. Web of Science was used to search the 100 most-cited articles and we extracted key information, such as the authors, countries/regions, institutions, journals, and study types of these articles. CiteSpace was used to visually analyze the keywords. Our bibliometric analysis shows that the attention in this field continues to rise. Authors from the United States published the most articles and Inouye SK is the most influential author in the field. The journals that published these articles have high impact factors. Cohort studies are the main cited articles in this field, and there are a large number of systematic reviews or meta-analyses of cohort studies. Risk factors for delirium, psychometric evaluation, hospital care, and various clinical study design are still the focus of research. In short, we summarized the 100 most-cited articles in the field of delirium to identify the current status and global trends. These results enable researchers to understand the quality and trend of research in the field of delirium and make better use of the classical literature.

The future power grid will have more distributed energy sources, and the widespread access of distributed energy sources has the potential to improve the energy efficiency, resilience, and sustainability of the system. However, distributed energy, mainly wind power generation and photovoltaic power generation, has the characteristics of intermittency and strong randomness, which will bring challenges to the safe operation of the power grid. Accurate prediction of solar power generation with high spatial and temporal resolution is very important for the normal operation of the power grid. In order to improve the accuracy of distributed photovoltaic power generation prediction, this paper proposes a new distributed photovoltaic power generation prediction model: ROLL-GNN, which is defined as a prediction model based on rolling prediction of the graph neural network. The ROLL-GNN uses the perspective of graph signal processing to model distributed generation production timeseries data as signals on graphs. In the model, the similarity of data is used to capture their spatio-temporal dependencies to achieve improved prediction accuracy.

Introduction Neuropathic pain is one of the common complications of spinal cord injuries (SCI), which will slow down the recovery process and result in lower quality of life. Previous studies have shown that repeated transcranial magnetic stimulation (rTMS) of the motor cortex (M1) can reduce the average pain and the most severe pain of neuropathic pain after SCI. The dorsolateral prefrontal cortex (DLPFC) area is a common target of rTMS. Recently, a few studies found that rTMS of DLPFC may relieve the neuropathic pain of SCI. Compared with the M1 area, the efficacy of rTMS treatment in the DLPFC area in improving neuropathic pain and pain-related symptoms in patients with SCI is still unclear. Therefore, our study aims to evaluate the non-inferiority of rTMS in the DLPFC vs M1 in patients with neuropathic pain after SCI, in order to provide more options for rTMS in treating neuropathic pain after SCI.Methods and analysis We will recruit 50 subjects with neuropathic pain after SCI. They will be randomly assigned to the DLPFC- rTMS and M1-rTMS groups and be treated with rTMS for 4 weeks. Except for the different stimulation sites, the rTMS treatment programmes of the two groups are the same: 10 Hz, 1250 pulses, 115% intensity threshold, once a day, five times a week for 4 weeks. VAS, simplified McGill Pain Questionnaire, Spinal Cord Injury Pain Date Set, Pittsburgh Sleep Quality Index and Hamilton Anxiety Scale will be evaluated at baseline, second week of treatment, fourth week of treatment and 4 weeks after the end of treatment. And VAS change will be calculated.Ethics and dissemination The Ethics Committee of the Affiliated Hospital of Southwest Medical University has approved this trial, which is numbered KY2020041. Written informed consent will be provided to all participants after verification of the eligibility criteria. The results of the study will be published in peer-reviewed publications.Trial registration number ChiCTR2000032362.

The penetration of multi-carrier energy systems in distribution system gains more and more concerns. In this paper, a bi-level transactive energy trading framework is proposed to improve the energy scheduling and operation efficiency for multi-carrier energy systems which are modeled as energy hubs (EHs). In the upper level, each EH in the distribution system not only makes energy scheduling decisions considering supplies and demands of local energy, but also trades energy with each other to further maximize their social welfare. The associated trading payment among EHs is made in a fair manner by applying Nash bargaining theory. We solve the bargaining problem by decomposing it into two subproblems: operation cost minimization problem and payment bargaining problem. Then, based on the trading decision, the nodal equivalent loads of EHs are sent to the distribution system operator (DSO) without publishing trading details. By applying the second-order cone programming (SOCP), DSO reconfigures the network to reduce the transmission loss of the system in the lower level. The network reconfiguration and the trading behavior of EHs interact and iterate until the convergence. Numerical studies on modified IEEE 33-bus distribution system demonstrate the effectiveness of the proposed framework.

Although many countries prefer deregulated power markets as a means of containing power costs, a monopoly may still exist. In this study, an agent-based bidding simulation framework is proposed to detect whether there will be a monopoly in the power market. A security-constrained unit commitment (SCUC) is conducted to clear the power market. Using the characteristics that the agent can fully explore in a certain environment and the Q-learning algorithm, each power producer in the power market is modeled as an agent, and the agent selects a quotation strategy that can improve profits based on historical bidding information. The numerical results show that in a power market with monopoly potential among the power producers, the profits of the power producers will not converge, and the locational marginal price will eventually become unacceptable. Whereas, in a power market without monopoly potential, power producers will maintain competition and the market remains active and healthy.

Objective:To explore the diagnostic value of Fuld Object Memory Evaluation (FOME) on dementia after stroke.Methods:A total of 100 patients with vascular dementia (the case group) were tested by the FOME and Mini-Mental State Examination (MMSE) with 100 healthy subjects who did physical examination in the same period of our hospital (the control group). The FOME involved direction recognition, object naming, visual naming, first, second, and last recall and the final memory. The MMSE tested the orientation, immediate recall, calculating ability and attention, delayed recall, naming, retelling orally, language comprehension, reading comprehension, language expression and visuospatial ability. The comparison was done on the results of the tests and the background conditions, such as gender, age, education and residence; and it was also analysed by ROC curve with the diagnostic value of the FOME on vascular dementia, calculating the diagnostic sensitivity, specificity and Jordon index, and comparing with the results of MMSE.Results:There was no statistical significance between the two groups (P> 0.05) in aspects of gender, age, educational level and residence; while the differences between test results of the two groups were statistically significant (t=14.707 and t=13.486, P< 0.001), and the scores of the case group were lower than those of the control group. As the ROC curve shown, the optimal cutoff value of MMSE was 27, that of the FOME was 14, the sensitivity of MMSE was 63.98%, the specificity of MMSE was 94.17%, and those of the FOME were 63.45%and 95.48%, respectively.Conclusion:The FOME can be equivalent to the MMSE in the diagnosis of dementia after stroke; with advantages in no considering education background and age, which can be expected to have a wider clinical application.

Abstract Background Lower limb strengthening, especially the quadriceps training, is of much necessity for patients with knee osteoarthritis (KOA). Previous studies suggest that strengthening of the hip muscles, especially the hip abductor, can potentially relieve the KOA-associated symptoms. Nevertheless, the effects of quadriceps combined with hip abductor strengthening remain unclear. Therefore, the current randomized controlled trial is designed aiming to observe whether quadriceps in combination with hip abductor strengthening can better improve the function and reduce pain in KOA patients than quadriceps training alone. Methods A total of 80 subjects with symptomatic KOA will be recruited from the communities and hospital outpatient, and will be randomly assigned to the experiment group (Quadriceps-plus-hip-abductor-strengthening) or the control group (Quadriceps-strengthening). Specifically, participants in the experiment group will complete 4 exercises to train the quadriceps and hip abductor twice a day for 6 weeks at home, while those in the control group will only perform 2 exercises to strengthen the quadriceps. Besides, all patients will also receive usual care management, including health education and physical agent therapy when necessary. Knee pain will be measured using the Visual Analogue Scale (VAS) at baseline, in every week during the course of treatment, as well as 8 and 12 weeks after randomization. Furthermore, knee function will be measured using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scale, and the quality of life will be measured using the MOS Item Short-form Health Survey (SF-36). In this study, several simple tests will be applied to assess the objective function. All the assessments except for VAS will be carried out at baseline, and in the 6th, 8th and 12th weeks respectively. Discussion Our findings will provide more evidence for the effects of hip abductor strengthening on relieving pain and improving function in KOA patients. Hip abductor strengthening can be added into the muscle training program for KOA patients as a supplementary content if it is proved to be effective. Trial registration The current study has been registered with the Chinese Clinical Trials Registry (the registration number is ChiCTR-IOC-15007590, 3rd December, 2015).

In recent years, P2P lending industry in China has appeared a lot of escape events in the process of its rapid development.Bases on deep analysis of the related concepts for P2P lending and big data, combining innovatively the risk pre-warning of platform with big data, an effective risk pre-warning model of P2P lending platform was constructed according to the collection of huge amounts of data, big data technology including Spark distributed computation and machine learning.Based on the establishment of multi-dimensional risk assessment, the model can be achieved on real-time, accurate, comprehensive monitoring for the risk of P2P lending, thus effectively reducing the frequency of financial fraud, escape malicious event, so as to the majority of investors’ money to maintain security and social stability.

To study the corrosion degradation of cable wires in a bridge’s life, this research work created an accelerated corrosion test device, which sought to identify an optimal constant strain level. An accelerated corrosion test was carried out and the corroded specimens were scanned using super depth 3D microscopy technology. Mass loss and minimum cross-sectional diameter was measured to understand the degradation characteristics of cable wires at variable strains and corrosion time. The variation of elastic modulus, yield load, and ultimate load of corroded wires, subjected to a tensile test, were analyzed. The experimental results illustrate that the average mass loss ratio of the corroded cable wires increases nonlinearly as corrosion time increases. The higher the stress level, the more serious the corrosion level. The minimum cross-sectional diameter has good correlation with corrosion time and stress level. The elastic modulus of wires does not change significantly with the increase of corrosion time. Yield load and ultimate load decreases with the increase of strain level, and the rates of decline under different strains are nonlinear.

Corrosion cracking of reinforced concrete caused by chloride salt is one of the main determinants of structure durability. Monitoring the entire process of concrete corrosion cracking is critical for assessing the remaining life of the structure and determining if maintenance is needed. Fiber Bragg Grating (FBG) sensing technology is extensively developed in photoelectric monitoring technology and has been used on many projects. FBG can detect the quasi-distribution of strain and temperature under corrosive environments, and thus it is suitable for monitoring reinforced concrete cracking. According to the mechanical principle that corrosion expansion is responsible for the reinforced concrete cracking, a package design of reinforced concrete cracking sensors based on FBG was proposed and investigated in this study. The corresponding relationship between the grating wavelength and strain was calibrated by an equal strength beam test. The effectiveness of the proposed method was verified by an electrically accelerated corrosion experiment. The fiber grating sensing technology was able to track the corrosion expansion and corrosion cracking in real time and provided data to inform decision-making for the maintenance and management of the engineering structure.