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This study investigates the therapeutic potential of Indigo Naturalis (IN) in treating a Inflammatory Bowel Disease (IBD). The objective is to comprehensively examine the effects and pharmacological mechanisms of IN on IBD, assessing its potential as an novel treatment for IBD. Analysis of 11 selected papers is conducted to understand the effects of IN, focusing on compounds like indirubin, isatin, indigo, and tryptanthrin. This study evaluates their impact on Disease Activity Index (DAI) score, colon length, mucosal damage, and macrophage infiltration in Dextran Sulfate Sodium (DSS)-induced colitis mice. Additionally, It investigate into the anti-inflammatory mechanisms, including Aryl hydrocarbon Receptor (AhR) pathway activation, Nuclear Factor kappa B (NF-κB)/nod-like receptor family pyrin domain containing 3 (NLRP3)/Interleukin 1 beta (IL-1β) inhibition, and modulation of Toll-like receptor 4 (TLR4)/myeloid differentiation primary response 88 (MYD88)/NF-κB and Mitogen Activated Protein Kinase (MAPK) pathways. Immunomodulatory effects on T helper 17 (Th17)/regulatory T cell (Treg cell) balance and Glycogen synthase kinase-3 beta (GSK3-β) expression are also explored. Furthermore, the study addresses the role of IN in restoring intestinal microbiota diversity, reducing pathogenic bacteria, and increasing beneficial bacteria. The findings reveal that IN, particularly indirubin and indigo, demonstrates significant improvements in DAI score, colon length, mucosal damage, and macrophage infiltration in DSS-induced colitis mice. The anti-inflammatory effects are attributed to the activation of the AhR pathway, inhibition of inflammatory pathways, and modulation of immune responses. These results exhibit the potential of IN in IBD treatment. Notably, the restoration of intestinal microbiota diversity and balance further supports its efficacy. IN emerges as a promising and effective treatment for IBD, demonstrating anti-inflammatory effects and positive outcomes in preclinical studies. However, potential side effects necessitate further investigation for safe therapeutic development. The study underscores the need for future research to explore a broader range of active ingredients in IN to enhance therapeutic efficacy and safety.

Objectives: Gout is an inflammatory arthritis of the joints and soft tissues occurring due to deposition of monosodium urate (MSU) crystals, which are caused by persistent hyperuricemia. Soyeom pharmacopuncture is one treatment method that has been traditionally used for pain management in Oriental medicine. However, studies on its effect in reducing gout pain have been insufficient. Therefore, we selected Soyeom pharmacopuncture among natural products used in Korea as the new target of our study.Methods: The effects of Soyeom pharmacopuncture were examined in mouse models of acute gout induced by injection of MSU crystals into footpads. IL-1β, IL-6, and TNF-α production were examined by immunoblotting and enzyme-linked immunosorbent assay as hallmarks of NLRP3 inflammasome and cytokine activation.Results: Soyeom pharmacopuncture reduced foot edema in gout-induced mice, as well as IL-1β, nitrite, IL-6, and TNF-α production. Moreover, Soyeom pharmacopuncture also reduced MSU-induced gout inflammatory gene expressions, specifically those in the NF-kB pathway.Conclusion: Pharmacopuncture may serve as a new solution for other inflammatory diseases as well. Through active follow-up studies, we could thoroughly understand the clinical value of Soyeom pharmacopuncture.

Abstract Advanced high strength steel (AHSS) is a steel of multi-phase microstructure that is processed under several conditions to meet the current high-performance requirements from the industry. Deep neural network (DNN) has emerged as a promising tool in materials science for the task of estimating the phase volume fraction of these steels. Despite its advantages, one of its major drawbacks is its requirement of a sufficient amount of training data with correct labels to the network. This often comes as a challenge in many areas where obtaining data and labeling it is extremely labor-intensive. To overcome this challenge, an unsupervised way of learning DNN, which does not require any manual labeling, is proposed. Information maximizing generative adversarial network (InfoGAN) is used to learn the underlying probability distribution of each phase and generate realistic sample points with class labels. Then, the generated data is used for training an MLP classifier, which in turn predicts the labels for the original dataset. The result shows a mean relative error of 4.53% at most, while it can be as low as 0.73%, which implies the estimated phase fraction closely matches the true phase fraction. This presents the high feasibility of using the proposed methodology for fast and precise estimation of phase volume fraction in both industry and academia.

Abstract Background Paricalcitol is known to attenuate ischemic-reperfusion injury of various organs. However, it is not known whether paricalcitol prevents neuronal injury after global cerebral ischemia. The purpose of this study is to investigate the neuroprotective effect of paricalcitol in a rat model of transient global cerebral ischemia. Methods This is a prospective, randomized experimental study. Male Sprague-Dawley rats that survived 10 min of four-vessel occlusion were randomly assigned to two treatment groups: one group was treated with paricalcitol 1 μg/kg IP, and the other was given an equivalent volume of normal saline IP. Drugs were administered at 5 min, 1 day, 2 days, and 3 days after ischemia. Neurologic function was assessed at 2 h, 1 day, 2 days, 3 days, and 4 days after ischemia. We tested motor function 3 days after ischemia using the rotarod test. Also, we tested memory function 4 days after ischemia using the passive avoidance test. We assessed neuronal degeneration in the hippocampus of surviving rats 4 days after ischemia. Results Eight rats were allocated to each group. No significant differences were found between the groups in terms of survival rate, motor coordination, or memory function. The neurological function score 2-h post-ischemia was significantly higher in the paricalcitol group (p = 0.04). Neuronal degeneration was significantly less in the paricalcitol group compared with the control group (p = 0.01). Conclusions Paricalcitol significantly attenuated neuronal injury in the hippocampus. Although motor coordination, memory function, and survival rate were not significantly improved by paricalcitol treatment in this study, paricalcitol remains a potential neuroprotective drug after global cerebral ischemia.

Abstract Background Although spatial effects contribute to inequalities in health care service utilisation and other health outcomes in low and middle income countries, there have been no attempts to incorporate the impact of neighbourhood effects into equity analyses based on concentration indices. This study aimed to decompose and estimate the contribution of spatial effects on inequalities in uptake of HIV tests in Malawi. Methods We developed a new method of reflecting spatial effects within the concentration index using a spatial weight matrix. Spatial autocorrelation is presented using a spatial lag model. We use data from the Malawi Demographic Health Survey (n = 24,562) to illustrate the new methodology. Need variables such as ‘Any STI last 12 month’, ‘Genital sore/ulcer’, ‘Genital discharge’ and non need variables such as Education, Literacy, Wealth, Marriage, and education were used in the concentration index. Using our modified concentration index that incorporates spatial effects, we estimate inequalities in uptake of HIV testing amongst both women and men living in Malawi in 2015–2016, controlling for need and non-need variables. Results For women, inequalities due to need variables were estimated at − 0.001 and − 0.0009 (pro-poor) using the probit and new spatial probit estimators, respectively, whereas inequalities due to non-need variables were estimated at 0.01 and 0.0068 (pro-rich) using the probit and new spatial probit estimators. The results suggest that spatial effects increase estimated inequalities in HIV uptake amongst women. Horizontal inequity was almost identical (0.0103 vs 0.0102) after applying the spatial lag model. For men, inequalities due to need variables were estimated at − 0.0002 using both the probit and new spatial probit estimators; however, inequalities due to non-need variables were estimated at − 0.006 and − 0.0074 for the probit and new spatial probit models. Horizontal inequity was the same for both models (− 0.0057). Conclusion Our findings suggest that men from lower socioeconomic groups are more likely to receive an HIV test after adjustment for spatial effects. This study develops a novel methodological approach that incorporates estimation of spatial effects into a common approach to equity analysis. We find that a significant component of inequalities in HIV uptake in Malawi driven by non-need factors can be explained by spatial effects. When the spatial model was applied, the inequality due to non need in Lilongwe for men and horizontal inequity in Salima for women changed the sign. This approach can be used to explore inequalities in other contexts and settings to better understand the impact of spatial effects on health service use or other health outcomes, impacting on recommendations for service delivery.

Abstract Spatial weight matrices play a key role in econometrics to capture spatial effects. However, these constructs are prone to clustering and can be challenging to analyse in common statistical packages such as STATA. Multiple observations of survey participants in the same location (or cluster) have traditionally not been dealt with appropriately by statistical packages. It is common that participants are assigned Geographic Information System (GIS) data at a regional or district level rather than at a small area level. For example, the Demographic Health Survey (DHS) generates GIS data at a cluster level, such as a regional or district level, rather than providing coordinates for each participant. Moreover, current statistical packages are not suitable for estimating large matrices such as 20,000 × 20,000 (reflective of data within large health surveys) since the statistical package limits the N to a smaller number. In addition, in many cases, GIS information is offered at an aggregated level of geographical areas. To alleviate this problem, this paper proposes a bootstrap approach that generates an inverse distance spatial weight matrix for application in econometric analyses of health survey data. The new approach is illustrated using DHS data on uptake of HIV testing in low and middle income countries.

Although different regions of the brain are dedicated to specific functions, the intra- and inter-regional heterogeneity of astrocytes and microglia in these regions has not yet been fully understood. Recently, an advancement in various technologies, such as single-cell RNA sequencing, has allowed for the discovery of astrocytes and microglia with distinct molecular fingerprints and varying functions in the brain. In addition, the regional heterogeneity of astrocytes and microglia exhibits different functions in several situations, such as aging and neurodegenerative diseases. Therefore, investigating the region-specific astrocytes and microglia is important in understanding the overall function of the brain. In this review, we summarize up-to-date research on various intra- and inter-regional heterogeneities of astrocytes and microglia, and provide information on how they can be applied to aging and neurodegenerative diseases.

Protein aggregates of cofilin and actin have been found in neurons under oxygen–glucose deprivation. However, the regulatory mechanism behind the expression of Cfl1 during oxygen–glucose deprivation remains unclear. Here, we found that heterogeneous nuclear ribonucleoproteins (hnRNP) Q and hnRNP A1 regulate the translation of Cfl1 mRNA, and formation of cofilin–actin aggregates. The interaction between hnRNP A1 and Cfl1 mRNA was interrupted by hnRNP Q under normal conditions, while the changes in the expression and localization of hnRNP Q and hnRNP A1 increased such interaction, as did the translation of Cfl1 mRNA under oxygen–glucose deprived conditions. These findings reveal a new translational regulatory mechanism of Cfl1 mRNA in hippocampal neurons under oxygen–glucose deprivation.

Abstract Background Child maltreatment is a significant public health problem. Group Family Nurse Partnership (gFNP) is a new intervention for young, expectant mothers implemented successfully in pilot studies. This study was designed to determine the effectiveness and cost-effectiveness of gFNP in reducing risk factors for maltreatment with a potentially vulnerable population. Methods A multi-site, randomized controlled, parallel-arm trial and prospective economic evaluation was conducted, with allocation via remote randomization (minimization by site, maternal age group) to gFNP or usual care. Participants were expectant mothers aged below 20 years with at least one live birth, or aged 20–24 years with no live births and with low educational qualifications. Data from maternal interviews at baseline and when infants were 2, 6 and 12 months, and video-recording at 12 months, were collected by researchers blind to allocation. Cost information came from weekly logs completed by gFNP family nurses and other service delivery data reported by participants. Primary outcomes measured at 12 months were parenting attitudes (Adult-Adolescent Parenting Index, AAPI-2) and maternal sensitivity (CARE Index). The economic evaluation was conducted from a UK NHS and personal social services perspective with cost-effectiveness expressed in terms of incremental cost per quality-adjusted life year (QALY) gained. The main analyses were intention-to-treat with additional complier average causal effects (CACE) analyses. Results Between August 2013 and September 2014, 492 names of potential participants were received of whom 319 were eligible and 166 agreed to take part, 99 randomly assigned to receive gFNP and 67 to usual care. There were no between-arm differences in AAPI-2 total (7 · 5/10 in both, SE 0.1), difference adjusted for baseline, site and maternal age group 0 · 06 (95% CI − 0 · 15 to 0 · 28, p = 0 · 59) or CARE Index (intervention 4 · 0 (SE 0 · 3); control 4 · 7 (SE 0 · 4); difference adjusted for site and maternal age group − 0 · 68 (95% CI − 1 · 62 to 0 · 16, p = 0 · 25) scores. The probability that gFNP is cost-effective based on the QALY measure did not exceed 3%. Conclusions The trial did not support gFNP as a means of reducing the risk of child maltreatment in this population but slow recruitment adversely affected group size and consequently delivery of the intervention. Trial registration ISRCTN78814904 . Registered on 17 May 2013.

Semiconductors are promising for high performance spintronics but the low functioning temperature hampers their applications. Here the authors achieve a strong room temperature modulation of spin-dependent resistance in GaN nanowires, which marks an important step towards practical spintronic devices.

Background: Human immunodeficiency virus (HIV) is a significant contributor to Malawi's burden of disease. Despite a number of studies describing socio-economic differences in HIV prevalence, there is a paucity of evidence on socio-economic inequity in HIV testing in Malawi. Objective: To assess horizontal inequity (HI) in HIV testing in Malawi. Design: Data from the Demographic and Health Surveys (DHSs) 2004 and 2010 in Malawi are used for the analysis. The sample size for DHS 2004 was 14,571 (women =11,362 and men=3,209), and for DHS 2010 it was 29,830 (women=22,716 and men=7,114). The concentration index is used to quantify the amount of socio-economic-related inequality in HIV testing. The inequality is a primary method in this study. Corrected need, a further adjustment of the standard decomposition index, was calculated. Standard HI was compared with corrected need-adjusted inequity. Variables used to measure health need include symptoms of sexually transmitted infections. Non-need variables include wealth, education, literacy and marital status. Results: Between 2004 and 2010, the proportion of the population ever tested for HIV increased from 15 to 75% among women and from 16 to 54% among men. The need for HIV testing among men was concentrated among the relatively wealthy in 2004, but the need was more equitably distributed in 2010. Standard HI was 0.152 in 2004 and 0.008 in 2010 among women, and 0.186 in 2004 and 0.04 in 2010 among men. Rural–urban inequity also fell in this period, but HIV testing remained pro-rich among rural men (HI 0.041). The main social contributors to inequity in HIV testing were wealth in 2004 and education in 2010. Conclusions: Inequity in HIV testing in Malawi decreased between 2004 and 2010. This may be due to the increased support to HIV testing by global donors over this period.

Artificial intelligence has become the primary issue in the era of Industry 4.0, accelerating the realization of a self-driven smart factory. It is transforming various manufacturing sectors including the assembly line for a camera lens module. The recent development of bezel-less smartphones necessitates a large-scale production of the camera lens module. However, assembling the necessary parts of a module needs much room to be improved since the procedure followed by its inspection is costly and time-consuming. Consequently, the collection of labeled data is often limited. In this study, a reliable means to predict the state of an unseen camera lens module using simple semi-supervised regression is proposed. Here, an experimental study to investigate the effect of different numbers of training samples is demonstrated. The increased amount of data using simple pseudo-labeling means is shown to improve the general performance of deep neural network for the prediction of Modulation Transfer Function (MTF) by as much as 18%, 15% and 25% in terms of RMSE, MAE and R squared. The cross-validation technique is used to ensure a generalized predictive performance. Furthermore, binary classification is conducted based on a threshold value for MTF to finally demonstrate the better prediction outcome in a real-world scenario. As a result, the overall accuracy, recall, specificity and f1-score are increased by 11.3%, 9%, 1.6% and 7.6% showing that the classification of camera lens module has been improved through the suggested semi-supervised regression method.

Background: Young people (aged 16–24 years) with long-term health conditions tend to disengage from health services, resulting in poor health outcomes. They are prolific users of digital communications. Innovative UK NHS clinicians use digital communication with these young people. The NHS plans to use digital communication with patients more widely. Objectives: To explore how health-care engagement can be improved using digital clinical communication (DCC); understand effects, impacts, costs and necessary safeguards; and provide critical analysis of its use, monitoring and evaluation. Design: Observational mixed-methods case studies; systematic scoping literature reviews; assessment of patient-reported outcome measures (PROMs); public and patient involvement; and consensus development through focus groups. Setting: Twenty NHS specialist clinical teams from across England and Wales, providing care for 13 different long-term physical or mental health conditions. Participants: One hundred and sixty-five young people aged 16–24 years living with a long-term health condition; 13 parents; 173 clinical team members; and 16 information governance specialists. Interventions: Clinical teams and young people variously used mobile phone calls, text messages, e-mail and voice over internet protocol. Main outcome measures: Empirical work – thematic and ethical analysis of qualitative data; annual direct costs; did not attend, accident and emergency attendance and hospital admission rates plus clinic-specific clinical outcomes. Scoping reviews–patient, health professional and service delivery outcomes and technical problems. PROMs: scale validity, relevance and credibility. Data sources: Observation, interview, structured survey, routinely collected data, focus groups and peer-reviewed publications. Results: Digital communication enables access for young people to the right clinician when it makes a difference for managing their health condition. This is valued as additional to traditional clinic appointments. This access challenges the nature and boundaries of therapeutic relationships, but can improve them, increase patient empowerment and enhance activation. Risks include increased dependence on clinicians, inadvertent disclosure of confidential information and communication failures, but clinicians and young people mitigate these risks. Workload increases and the main cost is staff time. Clinical teams had not evaluated the impact of their intervention and analysis of routinely collected data did not identify any impact. There are no currently used generic outcome measures, but the Patient Activation Measure and the Physicians’ Humanistic Behaviours Questionnaire are promising. Scoping reviews suggest DCC is acceptable to young people, but with no clear evidence of benefit except for mental health. Limitations: Qualitative data were mostly from clinician enthusiasts. No interviews were achieved with young people who do not attend clinics. Clinicians struggled to estimate workload. Only eight full sets of routine data were available. Conclusions: Timely DCC is perceived as making a difference to health care and health outcomes for young people with long-term conditions, but this is not supported by evidence that measures health outcomes. Such communication is challenging and costly to provide, but valued by young people. Future work: Future development should distinguish digital communication replacing traditional clinic appointments and additional timely communication. Evaluation is needed that uses relevant generic outcomes. Study registration: Two of the reviews in this study are registered as PROSPERO CRD42016035467 and CRD42016038792. Funding: The National Institute for Health Research Health Services and Delivery Research programme.

Background: Effective programmes to help children manage their weight are required. ‘Families for Health’ focuses on a parenting approach, designed to help parents develop their parenting skills to support lifestyle change within the family. Families for Health version 1 showed sustained reductions in mean body mass index (BMI) z-score after 2 years in a pilot project. Objective: The aim was to evaluate its effectiveness and cost-effectiveness in a randomised controlled trial (RCT). Design: The trial was a multicentre, investigator-blind RCT, with a parallel economic and process evaluation, with follow-up at 3 and 12 months. Randomisation was by family unit, using a 1 : 1 allocation by telephone registration, stratified by three sites, with a target of 120 families. Setting: Three sites in the West Midlands, England, UK. Participants: Children aged 6–11 years who were overweight (≥ 91st centile BMI) or obese (≥ 98th centile BMI), and their parents/carers. Recruitment was via referral or self-referral. Interventions: Families for Health version 2 is a 10-week, family-based community programme with parallel groups for parents and children, addressing parenting, lifestyle, social and emotional development. Usual care was the treatment for childhood obesity provided within each locality. Main outcome measures: Joint primary outcome measures were change in children’s BMI z-score and incremental cost per quality-adjusted life-year (QALY) gained at 12 months’ follow-up (QALYs were calculated using the European Quality of Life-5 Dimensions Youth version). Secondary outcome measures included changes in children’s waist circumference, percentage body fat, physical activity, fruit/vegetable consumption and quality of life. Parents’ BMI and mental well-being, family eating/activity, parent–child relationships and parenting style were also assessed. The process evaluation documented recruitment, reach, dose delivered, dose received and fidelity, using mixed methods. Results: The study recruited 115 families (128 children; 63 boys and 65 girls), with 56 families randomised to the Families for Health arm and 59 to the ‘usual-care’ control arm. There was 80% retention of families at 3 months (Families for Health, 46 families; usual care, 46 families) and 72% retention at 12 months (Families for Health, 44 families; usual care, 39 families). The change in BMI z-score at 12 months was not significantly different in the Families for Health arm and the usual-care arm [0.114, 95% confidence interval (CI) –0.001 to 0.229; p = 0.053]. However, within-group analysis showed that the BMI z-score was significantly reduced in the usual-care arm (–0.118, 95% CI –0.203 to –0.034; p = 0.007), but not in the Families for Health arm (–0.005, 95% CI –0.085 to 0.078; p = 0.907). There was only one significant difference between groups for secondary outcomes. The economic evaluation, taking a NHS and Personal Social Services perspective, showed that mean costs 12 months post randomisation were significantly higher for Families for Health than for usual care (£998 vs. £548; p

This study analyzes valuable information (image feature information) from pixel-based images to systematize the form generation process utilizing this information. Information in architecture is mainly used as an analytical tool for functional design optimization. However, the Fourth Industrial Revolution and advances in information and communication technology have positioned information as a core value-creating tool. Consequently, there is a growing need to develop methodologies for effectively applying information to architectural design generation. This study combines digital technology with images, which directly influence architectural design, transforming them into numerical information. By systematizing the three-dimensional form generation process using low-level image feature information, it analyzes the relationship between the characteristics of valuable information and the generated forms. This approach helps identify the interrelationships between the characteristics of valuable information and the generated forms, the complementarity needed to mitigate the limitations of valuable information, and the potential for architectural applications of the three-dimensional form generation methodology utilizing image information. This approach reduces labor and enhances architectural aesthetics by instantly generating diverse early design alternatives. Such research can provide a more logical basis for avoiding intuitive judgments during the design decision-making process. It can also lay the groundwork for information-centric design systems in architecture.

Cancer stem-like cells (CSCs) have been suggested to be responsible for chemoresistance and tumor recurrence owing to their self-renewal capacity and differentiation potential. Although WEE1 is a strong candidate target for anticancer therapies, its role in ovarian CSCs is yet to be elucidated. Here, we show that WEE1 plays a key role in regulating CSC properties and tumor resistance to carboplatin via a microRNA-dependent mechanism. We found that WEE1 expression is upregulated in ovarian cancer spheroids because of the decreased expression of miR-424 and miR-503, which directly target WEE1. The overexpression of miR-424/503 suppressed CSC activity by inhibiting WEE1 expression, but this effect was reversed on the restoration of WEE1 expression. Furthermore, we demonstrated that NANOG modulates the miR-424/503-WEE1 axis that regulates the properties of CSCs. We also demonstrated the pharmacological restoration of the NANOG-miR-424/503-WEE1 axis and attenuation of ovarian CSC characteristics in response to atorvastatin treatment. Lastly, miR-424/503-mediated WEE1 inhibition re-sensitized chemoresistant ovarian cancer cells to carboplatin. Additionally, combined treatment with atorvastatin and carboplatin synergistically reduced tumor growth, chemoresistance, and peritoneal seeding in the intraperitoneal mouse models of ovarian cancer. We identified a novel NANOG-miR-424/503-WEE1 pathway for regulating ovarian CSCs, which has potential therapeutic utility in ovarian cancer treatment.

This paper presents a method used to identify partial discharge defects in cast-resin power transformers using a back-propagation algorithm. The Rogowski-type partial discharge (PD) sensor was designed with a planar and thin structure based on a printed circuit board to detect PD signals. PD electrode systems, such as metal protrusions, particle-on-insulators, delamination, and void defects, were fabricated to simulate the PD defects that occur in service. PD characteristics, such as rising time, falling time, pulse width, skewness, and kurtosis without phase-resolved partial discharge patterns, were extracted to intuitively analyze each PD pulse according to the type of PD defect. A backpropagation algorithm was designed to identify PD defects using a virtual instrument (VI) based on the LabVIEW program. The results show that the accuracy rate of back-propagation (BP) algorithm reaches over 92.75% in identifying four types of PD defects. [ABSTRACT FROM AUTHOR]

Gas-insulated switchgears (GISs) are important pieces of power equipment used to improve the reliability of power facilities. As the number of GISs increases, more insulation failures occur every year. The most common cause of insulation failure is particles and foreign bodies producing a partial discharge (PD), which causes deterioration of the insulation materials and results in insulation breakdown. However, it is not easy to detect them by conventional PD and ultra-high frequency (UHF) PD measurements because it is difficult to apply the conventional method to the GISs in service, and the UHF method is not always applicable to GISs. Therefore, an appropriate method to detect particles and foreign bodies in GISs is needed. In this study, experimental validation was performed to detect particles moving in GISs using the acoustic emission (AE) method. Acoustic wave signals were produced by the particles moving on the surface of a flat plate when applying voltage. An AE sensor with a frequency range of 50 to 400 kHz was used, and a decoupler and low-noise amplifier were designed to detect the acoustic wave signals with high sensitivity. Twelve types of particles were used, and one was selected to confirm the detectable minimum output voltage. In an actual factory test, the output voltage of the acoustic wave signals was analyzed while considering the applied voltage and signal attenuation. Consequently, it was confirmed that the AE measuring system proposed in this paper could detect particles moving inside GISs.

An arc fault is an electrical breakdown of the insulating medium in an electrical system. When arc faults occur, they cause electrical fires with local sparks and temperatures of over 5000 °C. A series arc is generated in series with a load due to an incomplete connection between cords or a loose connection between a cord and terminal. However, it is hard to detect series arc faults with arc protection devices because the fault current flowing by series arc in the circuit is not higher than the load current. Especially in Korea, preventing electrical fires by series arc is rarely applied because there is no national standard for arc fault circuit interrupters (AFCI) and arc fault detection devices (AFDD). Therefore, many studies for reliable arc detection and analysis are still necessary to prevent electrical fires. In this study, phase analyses of series arc signals for low-voltage electrical devices such as heaters, computers, refrigerators, and air conditioners were conducted. The arc generator was fabricated according to UL 6199 and an optimal filter was designed to detect series arc signals without any attenuation. The phase of detected series arc signals was analyzed according to load types and finally a new algorithm was proposed based on the result of phase-resolved series arc (PRSA) analysis to identify types of loads.

Metal oxide varistors (MOVs) are widely used to protect electrical and electronic devices that are very vulnerable to surges due to the low insulation level of the equipment. MOVs deteriorate gradually due to manufacturing defects, mechanical and thermal stress, or repeated protective operations against surges. These defects result in the thermal runaway of MOV and finally lead to the explosion and electric fire of electrical and electronic devices due to a short circuit and a line-to-ground fault. Therefore, the reliable assessment of the condition of MOV deterioration is required for electrical and electronic equipment. However, when most accelerated degradation tests for the MOV have been performed to date, an 8/20 μs standard surge current is applied under de-energized conditions, which is unlike the actual operating environment. In this study, a surge generator was designed to apply a surge current to MOVs to monitor their deterioration. Three different types of leakage currents were measured to analyze the change rates of their electrical characteristics of MOVs by comparing them with the reference voltage variation. Furthermore, the condition assessment of MOV deterioration under energized and de-energized conditions was investigated.