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This research aimed to develop an optimal expert system by adopting a simplified approach. The methodology integrates an expert judgment approach, limitation inference, and establishing a threshold value. Expert judgment is pivotal in assigning a percentage weight to each rule, facilitating a nuanced evaluation of diagnostic criteria to augment the system's precision. Moreover, incorporating limitation inference strategically constrains the number of user inquiries, streamlining the diagnostic process and enhancing overall efficiency. Additionally, the imposition of a threshold value ensures a more precise early diagnosis by delineating specific criteria for condition identification. This comprehensive approach underscores the paramount importance of user experience and aims to alleviate the burden on individuals seeking a diagnosis. Ultimately, the anticipated outcome of this study is the development of an expert system poised to deliver early diagnoses with heightened efficiency and accuracy. By integrating expert judgment, limitation inference, and threshold values, this research embodies a refined and user-centric paradigm for eye disease diagnosis, promising significant advancements in global eye health. [ABSTRACT FROM AUTHOR]

Based on wind profile radar data, this paper aims at different typhoon processes landed and affected Fujian from 2011 to 2019, according to the nature of typhoon rainstorm, it can be classified into outer precipitation before typhoon landed, main body precipitation and precipitation at the rear of typhoon, the change of the characteristic quantities in approaching time of the occurrence of short-term heavy rainfall was analyzed, and the typhoon case in 2020 was back calculated. The results show that, the characteristics of low-level jet streams (maximum wind speed at low altitude, minimum height of jet streams, and low-level jet stream index), as well as the magnitude of vertical wind shear below 700 hPa, have important indicative significance for the occurrence of short-term heavy rainfall. (1) More than 80 % of short-term heavy rainfall occurred 3 h before the low-level jet stream already existed. The maximum wind speed below 2 km was basically close to a normal distribution, and the occurrence of heavy precipitation showed a bimodal pattern. The percentage of wind speed between 8 and 32 m/s was the highest, exceeding 85 %. The wind direction of the strong wind is mainly NE, SE, and SW. Classification analysis showed that the distribution characteristics of wind speed of the main precipitation were the same as before, but the wind direction SE was higher than NE. The wind speed of pre-landfall precipitation was basically skewed, and the occurrence time of heavy precipitation followed a normal distribution. The percentage of wind speed between 16 and 32 m/s was the highest, and the wind direction was the same as before classification. The maximum wind speed of precipitation in the rear was basically bimodal distribution, with a relatively even distribution, and the wind direction was mainly SE and SW. (2) In the 3 h before the occurrence of short-term heavy precipitation, there was an increase in the maximum wind speed value, a decrease in the minimum extension height, and an increase in the low-level jet stream index I. As short-term heavy rainfall approached, the intensity of the low-level jet stream remained high and its proportion increased. The minimum achievable extension height gradually decreased and remained stable at a low value. In the first 2 h of heavy rainfall, the wind speed reached its maximum, the extension height was the lowest, and the lowlevel jet stream index I was the highest. Classifying and discussing it, the precipitation in the rear was different, and the lowest height decreased to the lowest at the time of occurrence, at which point the I value reached its maximum. The characteristics of the other two categories were the same as before the classification. (3) The vertical wind shear from the ground to different isobaric surfaces gradually decreased with the increase of height. With the approach of short-term heavy rainfall, the vertical wind shear of each layer basically decreased gradually, after the beginning of heavy rainfall, which decreased to the minimum. The characteristics of main body precipitation were the same as before the classification. Pre-landfall precipitation, in addition to the gradual decrease of vertical wind shear from the ground to 925 hPa, both 850 hPa and 700 hPa increased first and then decreased, vertical wind shear decreased to the minimum after the beginning of heavy rainfall. Precipitation at rear of typhoon, vertical wind shear from ground to 700 hPa increased compared with that before the occurrence of heavy rainfall, while wind shear from ground to 925 hPa and 850 hPa showed the characteristics of decreasing when heavy rainfall occurred. (4)The median values of various physical quantities before the occurrence of typhoon short-term heavy rainfall were selected as the thresholds of short-term heavy rainfall will occur. The intensity of LLJ is about 21 m/s, the lowest height is about 0.65 km, the LLJ index I is about 36 x 10-3s-1. Vertical wind shear from the ground to 925 hPa, 850 hPa and 700 hPa are respectively about 15.9 x 10-3s-1, 11.2 x 10-3s-1 and 5.1 x 10-3s-1. [ABSTRACT FROM AUTHOR]

This paper deals with an impulsive degenerate logistic model, where pulses are introduced for modeling interventions or disturbances, and the degenerate logistic term may describe refugees or protections zones for a species. First, the principal eigenvalue depending on impulse rate, which is regarded as a threshold value, is introduced and characterized. Second, the asymptotic behavior of the population is fully investigated and sufficient conditions for the species to be extinct, persist, or grow unlimitedly are given. Our results extend those of the well-understood logistic and Malthusian models. Finally, numerical simulations emphasize our theoretical results, highlighting that a medium impulse rate is more favorable for species to persist, a small rate results in extinction, and a large rate leads the species to unlimited growth. [ABSTRACT FROM AUTHOR]

Abstract Purpose To investigate the value and age- and gender-specific threshold values of bone mineral density (BMD) by quantitative computed tomography (QCT) for the prediction of spontaneous thoracolumbar vertebral fractures and thoracolumbar junction fractures accompanying distant vertebral fractures. Methods Among the 556 patients included, 68 patients had thoracolumbar vertebral fractures (12 patients with distant vertebral fractures, 56 patients without distant vertebral fractures) and 488 patients had no vertebral fractures. All patients were grouped by gender and age. According to the principle of Youden index, the threshold values were calculated from receiver operating characteristic (ROC) curves. Results The threshold values for predicting thoracolumbar vertebral fractures were 89.8 mg/cm3 for all subjects, 90.1 mg/cm3 for men, and 88.6 mg/cm3 for women. The threshold values for men aged

Purpose: To investigate the value and age- and gender-specific threshold values of bone mineral density (BMD) by quantitative computed tomography (QCT) for the prediction of spontaneous thoracolumbar vertebral fractures and thoracolumbar junction fractures accompanying distant vertebral fractures. Methods: Among the 556 patients included, 68 patients had thoracolumbar vertebral fractures (12 patients with distant vertebral fractures, 56 patients without distant vertebral fractures) and 488 patients had no vertebral fractures. All patients were grouped by gender and age. According to the principle of Youden index, the threshold values were calculated from receiver operating characteristic (ROC) curves. Results: The threshold values for predicting thoracolumbar vertebral fractures were 89.8 mg/cm3 for all subjects, 90.1 mg/cm3 for men, and 88.6 mg/cm3 for women. The threshold values for men aged < 60 years old and ≥ 60 years old were 117.4 mg/cm3 and 87.5 mg/cm3, respectively. The threshold values for women aged < 60 years old and ≥ 60 years old were 88.6 and 68.4 mg/cm3, respectively. The threshold value for predicting spontaneous thoracolumbar junction fractures with distant vertebral fractures was 62.7 mg/cm3. Conclusions: QCT provides a good ability to predict age- and gender-specific spontaneous thoracolumbar vertebral fractures, and to further predict spontaneous thoracolumbar junction fractures with distant vertebral fractures. [ABSTRACT FROM AUTHOR]

At present, the tobacco baking process in China mainly relies on manual monitoring, which has problems of subjectivity, fuzziness and high cost. Research on using machine vision methods to monitor and judge real-time changes in tobacco quality during the baking process is gradually increasing. Real time monitoring needs to be based on efficient and accurate segmentation of roasted tobacco leaf images, so the research on segmentation of roasted tobacco leaf images has become particularly important. A segmentation method for roasted tobacco leaf images based on K-means clustering algorithm was proposed. Firstly, the image was read and RGB was converted to the CYMK color space. Then, the grayscale image of the K-channel in the CYMK color space was extracted. We clustered the single channel image again, determined the image segmentation threshold based on the cluster center, and finally used image processing methods to segment the image. We compared three clustering methods of K-means, fuzzy C-means clustering (FCM) and Gaussian mixture clustering (GMM). The results showed that the pixel accuracy of the K-means algorithm was 97. 8%, the intersection to union ratio was 96. 43%, and the Dice coefficient was 98. 2%, all of which were better than the other two methods. The K-means algorithm could better extract the contour of tobacco leaves, remove redundant information and make the segmentation results clearer. [ABSTRACT FROM AUTHOR]

In this article, we develop a Hepatitis B virus model with six compartments affected by environmental fluctuations since the Hepatitis B virus produces serious liver infections in the human body, putting many people at high risk. The existence of a global positive solution is shown to prove the positivity of solutions. We demonstrate that the system experiences the extinction property for a specific parametric restriction. Besides that, we obtain the stochastic stability region for the proposed model through the stationary distribution. To determine the appearance and disappearance of infection in the population, we find and analyze the reproduction ratio R0S$$ {R}_0&#x0005E;S $$. In addition, we have verified the condition of the reproduction ratio through the graphical simulations. [ABSTRACT FROM AUTHOR]

One of the most serious diseases affecting dairy cattle, causing significant losses both in breeding and economy, is mastitis, an inflammation of the mammary gland. Due to the economic importance of this issue, many research teams are striving to develop an easy-to-apply and, most importantly, effective method to prevent mastitis. The use of traditional methods for mastitis detecting and treating, as well as improvement in hygienic conditions, have not yielded the expected results in combating this disease combating. Currently, the main task is to find the tools that would allow for the rapid detection of mastitis and the improvement of udder health in cows while maintaining high milk production, which is essential for the profitability of dairy cattle farming. Accurate and rapid diagnostic tools, with the simultaneous capability of identifying pathogens, may help to reduce losses. Sufficient sensitivity and specificity for tests are required to minimize the number of false-positive and false-negative cases. Efforts are also being made to determine the optimal threshold value for detecting the disease at its earliest possible stage. The estimation of somatic cell count (SCC) as a phenotypic indicator of mastitis is widely used. A more precise parameter for accurately describing udder health is the differential somatic cell count (DSCC). The well-known California Mastitis Test (CMT) is an inexpensive, easy, and rapid method for mastitis detection useful on farms. The latest diagnostic methods for mastitis utilize tests based on the activity of N-acetyl-β-d-glucosaminidase (NAGase) or lactate dehydrogenase (LDH) as well as the determination of acute phase proteins (APPs) in blood serum and milk (such as haptoglobin, serum amyloid A, fibrinogen, and ceruloplasmin). Research also focuses on the genomic improvement of mastitis resistance in successive generations, and for this purpose, many quantitative trait loci (QTLs) and single nucleotide polymorphisms (SNPs) have been identified. In recent years, immunotherapy has become an increasingly common area of research, including vaccinations, T/B cell immunotherapy, RNA immunotherapy, epigenetic immunotherapy, stem cell therapy, and native secretory factors. An important aspect of the control of mastitis is the implementation of strategies that focus primarily on preventing the disease through appropriate breeding and farm management practices. In the forthcoming years, a significant challenge will be the development of universal diagnostic and therapeutic strategies that can be effectively implemented as alternatives to antibiotic therapy. Future research should prioritize the advancement of preventive and therapeutic techniques, such as immunotherapies, bacteriocins, herbal therapy, and nanoparticle technology. [ABSTRACT FROM AUTHOR]

The dielectric constant and the dispersion relation of the Ordinary mode (O-mode) instability has been discussed by using the Vlasov kinetic model in the presence of the Heaviside distribution function. The Heaviside distribution includes relativistic effects for both the parallel and perpendicular streaming. It is noted that the relativistic effects play a destabilizing role for the O-mode at higher magnetic field in comparison to the non-relativistic case. The growth rate of O-mode instability is calculated analytically for different values of parallel and perpendicular streaming. It is shown that the parallel streaming destabilizes the O-mode where as the perpendicular streaming provides a stabilizing effect. The results of the non-relativistic O-mode instability have been retrieved under limiting case. [ABSTRACT FROM AUTHOR]

The accurate analysis of human dynamic behavior is very important for overcoming the limitations of movement diversity and behavioral adaptability. In this paper, a wearable device-based human dynamic behavior recognition method is proposed. The method collects acceleration and angular velocity data through a six-axis sensor to identify information containing specific behavior characteristics in a time series. A human movement data acquisition platform, the DMP attitude solution algorithm, and the threshold algorithm are used for processing. In this experiment, ten volunteers wore wearable sensors on their bilateral forearms, upper arms, thighs, calves, and waist, and movement data for standing, walking, and jumping were collected in school corridors and laboratory environments to verify the effectiveness of this wearable human movement recognition method. The results show that the recognition accuracy for standing, walking, and jumping reaches 98.33%, 96.67%, and 94.60%, respectively, and the average recognition rate is 96.53%. Compared with similar methods, this method not only improves the recognition accuracy but also simplifies the recognition algorithm and effectively saves computing resources. This research is expected to provide a new perspective for the recognition of human dynamic behavior and promote the wider application of wearable technology in the field of daily living assistance and health management. [ABSTRACT FROM AUTHOR]

Glacial lake outburst floods (GLOF) hazards in alpine areas are increasing. The effects of climate change on GLOF hazards are unclear. This study examined 37 glacial lakes and climate data from 15 meteorological stations and explored the correlation between climate variations at different temporal scales. The results indicate that 19 GLOFs hazards occurred in El Niño (warm) years, 8 GLOFs hazards occurred in La Niña (cold) years, 3 GLOFs hazards occurred in cold/warm or warm/cold transition years, and 7 GLOFs hazards occurred in normal years. The higher the fluctuations, the higher the probability of GLOF hazards. Climatic conditions can be divided into three categories: extreme temperature and precipitation, as represented by the Guangxie Co GLOF; extreme precipitation, as represented by the Poge Co GLOF; and extreme temperature, as represented by the Tsho Ga GLOF. [ABSTRACT FROM AUTHOR]

The groundwater table depth, which is typically shallow in coastal areas, is one of the decisive conditions impacting soil salinization. The influence mechanism of shaollow groundwater table depth change on the evolution of saline-alkali land is still unclear. In this study, Huanghua City, a coastal city of the Bohai Sea in China, was selected as the research area, and four wells with groundwater table depths ranging from shallow to deep were studied. The groundwater table depth was divided into three levels based on the average groundwater table depth over 30 years, namely shallow, medium, and deep. We analyzed the influence of changes in groundwater table depth in each well on the evolution of saline-alkali land within a radius of 2 km. The results showed that changes in groundwater table depth did not cause conversion between saline-alkali land grades in shallow areas, whereas, in medium-depth areas, changes in groundwater table depth caused conversion among saline-alkali land grades. In deep areas, changes in groundwater table depth did not affect the conversion of moderate/heavy saline-alkali land to non-mild saline-alkali land. The lower limit and upper limit of the groundwater table depth response threshold of saline-alkali land were found to be 1.35 and 3.58 m, respectively, in this coastal area. When the groundwater table depth of saline-alkali land remains lower than 1.35 m for a long period, it will become heavily salinized, one appropriate treatment measure in this instance is to plant saline-alkali tolerant plants beacause improving saline-alkali land by reducing the groundwater table depth is a challenge. When the groundwater table depth of saline-alkali land remains greater than 3.58 m for a long period, changes in groundwater table depth will not influence the gradual reduction of salinization, the saline-alkali land should be properly irrigated and drained to avoid secondary salinization caused by the groundwater level rising to the upper limit of the response threshold. When the water depth in saline-alkali land remains between 1.35 and 3.58 m for a long time, the degree of salinization will change with the change in water depth, the underground water depth can be reduced under a subsurface drainage system in order to treat the saline-alkali land. The research results can provide a scientific basis for improvement of saline-alkali land. [ABSTRACT FROM AUTHOR]

Background: It is mandatory to label food products with the 14 main allergens in the EU. Reasonable allergen labeling requires knowledge of population‐based thresholds derived from food challenges. The aim of this study was to evaluate the threshold‐distribution in clinically verified food allergic patients for allergens mandatory for labeling. Methods: All positive open oral food challenges and double‐blind placebo‐controlled food challenges (DBPCFC) performed at the Allergy Center, Odense University Hospital, Denmark (2000–2022) were included. For each included challenge, the cumulative threshold (LOAEL) was obtained and NOAEL estimated. Data were modelled as an interval censored log‐normal distribution. Results: Overall, 38 of all 2612 challenges (1.5%) in 1229 patients (717 male, 986 children) reacted to <5 mg protein. The majority of the most sensitive patients reacted with a Sampson severity score of 2–3. Using interval censored log‐normal models only five groups (hens´ egg, fish, peanut, milk, tree‐nuts) elicited reactions after ingestion of 0.5 mg protein and in low frequencies of the population. Hen's egg was the most potent allergen, with reactivity to <0.5 mg protein in 0.24% [0.13–0.44%] of egg allergic patients while the estimated fraction of allergic patients reacting to a eliciting dose on 0.5 mg protein for most other allergens were below 0.04%. Conclusion: Our data demonstrates that the majority of food allergic patients as expected tolerating traces of allergenic foods without developing severe allergic symptoms and signs. Hen's egg appears to be the food most likely to elicit reactions in the most sensitive individuals at very low doses. [ABSTRACT FROM AUTHOR]

Determining background aerosol optical depth threshold value (BAOD) is critical to aerosol type identification and air pollution control. This study presents a statistical method to select the best BAOD threshold value using the VIIRS DB AOD products at 1 × 1 degree resolution from 2012 to 2019 as a major testbed. A series of multiple lognormal distributions with 1 to 5 peaks are firstly applied to fit the AOD histogram at each grid point, and the distribution with the highest correlation coefficient (R) gives preliminary estimations of BAOD, which is defined as either the intersection point of the first two normal distribution curves when having multiple peaks, or the midpoint between the peak AOD and the first AOD with non-zero probability when the mono peak is the best fit. Then, the lowest 1st to 100th percentile AOD distributions are compared with the preliminary BAOD distribution on a global scale. The final BAOD is obtained from the best cutoff percentile AOD distributions with the lowest bias compared with preliminary BAOD. Results show that the lowest 30th percentile AOD is the best estimation of BAOD for different AOD datasets and different seasons. Analysis of aerosol chemical information from MERRA-2 further supports this selection. Based on the BAOD, we updated the VIIRS aerosol type classification scheme, and the results show that the updated scheme is able to achieve reliable detection of aerosol type change in low aerosol loading conditions. [ABSTRACT FROM AUTHOR]

Background: Food allergy is common in childhood with some children having a low threshold and being difficult to protect from accidental ingestion of the offending food. Therapies for this potentially life‐threatening condition are highly needed. The aim of this study was to evaluate the efficacy of Omalizumab in food‐allergic children. Methods: This is a single‐center, double‐blind, placebo‐controlled study. Food allergic children with a cumulative threshold ≤443 mg food protein at DBPCFC were randomized to Omalizumab (asthma dose) or placebo (3:1). After 3 months, a second DBPCFC was performed (steps 3, 10, 30, 100, 300, 1000, and 3000 mg food protein), followed by a separate open challenge up to 10,000 and 30,000 mg food protein if negative. Responders were defined as ≥2‐step increases in threshold. Non‐responders received high‐dose Omalizumab. A third DBPCFC was performed after 6 months. Skin testing, blood samples, and the severity of atopic co‐morbidity were registered during the study and 3 months after treatment. Results: In total, 20 children were evaluated at 3 months (14 Omalizumab, 6 placebo). All treated with Omalizumab increased their threshold at least two steps and with a significant difference between the Omalizumab and the placebo group (p =.003), although the intended number of included children was not reached. The threshold before Omalizumab treatment was 13–443 mg food protein while the threshold after 3 months of treatment increased up to 44,000 mg (1143–44,000). In the placebo group, two children improved threshold during the study. Conclusion: An increase in the threshold level during Omalizumab treatment significantly improve patient safety and protected all children against small amount of allergen. [ABSTRACT FROM AUTHOR]

Solar radio bursts are intense radio radiation sources that occur during the energy-release process and represent a hot topic in solar-physics and space-weather research. In this paper, we present a multimode prediction model for daily solar radio bursts. The model uses deep learning and machine learning to obtain data information from different dimensions and to establish the relationship between the characteristics of the solar active region on the solar surface and solar radio bursts. For this model, we use data from the Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) total solar magnetic map, the Royal Observatory of Belgium World Data Centre in Brussels, and NOAA sunspot parameters (including number, area, and type of sunspots) as inputs. The output results are then compared with the list of solar radio bursts recorded by the Radio Solar Telescope Network (RSTN) to determine whether solar radio bursts are present and to determine the key parameters for determining radio bursts. Based on 5449 days of observational data, we find that the prediction accuracy of the model is 0.898 ± 0.011, and that the number of sunspots is a key parameter in determining the occurrence of solar radio bursts. Specifically, when the number of sunspots is greater than 15, the probability of occurrence of solar radio bursts is greater than 90%. We have identified the key parameters and thresholds for determining solar radio bursts and highlighted the key parameters for space-weather prediction. In addition, the prediction model can also be used for predicting in other fields. [ABSTRACT FROM AUTHOR]

Providing adequate green cover in the form of trees, parks and gardens is a nature-based solution which every city must adopt to address the urbanization and its impacts, as it helps to reduce the temperature, maintain the ecology and biodiversity, provide recreational facilities for the city inhabitants and many more. Accurate mapping and monitoring of Urban Green Spaces (UGS) through satellite images is essential to check whether a city has adequate green cover or not. Studies on UGS have mostly used Landsat and Sentinel-2A satellite images for extracting the green covered areas in cities. Though it is advantageous to use these freely available images, however the accuracy of extraction is a major concern as the images are of >10m spatial resolution. Distinguishing the various green cover types, such as trees, shrubs, cropland, etc. is not an easy task in low and medium resolution satellite images. To overcome these drawbacks, one has to use high (1-10m) and very-high resolution (<1m) images for extracting the UGS accurately, however, purchasing such 'cm' resolution satellite images is a costly affair. In order to balance between the cost and resolution, the best and viable option is to use the Google earth (GE) imagery and the same was attempted in the present study by proposing a simple threshold-based approach to extract the UGS and its types from GE imagery. To illustrate the proposed method, 15 sites from the city of Vellore, India were taken and the latest cloud free GE imagery was then downloaded, projected and carefully checked for its range of pixel values in different types of UGS classes. The threshold values of each UGS type were then used to reclassify the original GE image and finally the accuracy assessment was performed on the reclassified UGS map. The results were promising as the overall accuracy (OA) was > 90% at 12 sites and only 3 out of 15 sites exhibits OA in the range of 75-86%. In order to assess the performance of the proposed approach at other locations, 5 cities across the globe [2 from India (Bangalore and Hyderabad) and 3 from abroad (Barcelona, Kuala Lumpur, New York)] were taken and the results revealed that the proposed method performs well in extracting the UGS and its types as the OA was found to be above 90% at all the 5 cities. The proposed approach can be used by civic authorities not only to check whether the city has adequate green cover or not but also can monitor whether UGS has increased or decreased over the years using the historical GE images. [ABSTRACT FROM AUTHOR]

Background: Magnesium (Mg) is an essential element and participates in many metabolic pathways. Many studies have found a certain negative correlation between magnesium and blood glucose parameters, but the dose–response relationship between them is still a relatively narrow research field. We aim to explore the dose–response relationship between plasma and dietary Mg and type 2 diabetes (T2DM) among childbearing women in a nationally representative sample. And we will also initially explore the threshold of dietary and plasma magnesium in the prevention of T2DM and their consistency. Methods: A total of 2912 18–44 year-old childbearing women were recruited from the China Adult Chronic Disease and Nutrition Surveillance (2015). Multivariate logistic regression was used to explore the dose–response relationship between plasma and dietary Mg and glucose parameters. The threshold effect between Mg and T2DM was explored by a restricted cubic spline regression. Results: It was found that when plasma Mg was increased by 0.041 mmol/L, the risk of T2DM, impaired fasting glucose (IFG), and HbA1c-hyperglycemia was reduced by 18%, 19%, and 18%, respectively. The possible threshold value for plasma Mg to prevent the risk of T2DM was 0.87 mmol/L. Through the quality control of the sample dietary survey data, 2469 cases were finally included for dietary analysis. And the possible threshold value for dietary Mg to prevent the risk of T2DM was 408 mg/d. Taking the recommended dietary Mg intake of 330 mg/d as the reference group, when the Mg intake reached 408 mg/d, the risk of T2DM was significantly reduced. And the average plasma Mg level of the people whose dietary intake reached 408 mg/d was 0.87 mmol/L. Conclusions: These results indicate that dietary Mg and plasma Mg have good consistency on the threshold effect of glucose parameters in women of childbearing age. [ABSTRACT FROM AUTHOR]

With the widespread application of the modular multilevel converter (MMC) in the fields of electronic and electrical engineering, the open-circuit failure problem of the power devices in submodules (SMs) has become the main factor restricting its stable operation. Therefore, power device open-circuit fault diagnosis is widely studied as the main means to ensure the ongoing and stable operation of MMCs. The existing fault diagnosis approaches on the basis of voltage of capacitor change are only applicable to fault diagnosis under active power conditions. However, in reactive power scenarios, MMC systems have very important applications, such as power grid steady-state reactive power regulation and transient reactive power support. Therefore, an effective fault diagnosis method based on the capacitance voltage change rate is put forward for the diagnosis of faults under reactive conditions. This method differentiates the capacitor voltage and compares it with the threshold to diagnose faults under reactive power operation. The proposed method is simulated using PSCAD simulation software. Simulation results verify the practicability of the presented approach. [ABSTRACT FROM AUTHOR]

Abstract The Trust-Aware Aggregation Authentication Protocol for SIoT Networks is a security process intended for SIoT platforms. It concentrates on ensuring the reliability of communication and data aggregation between interrelated IoT devices. This protocol deploys authentication systems for verifying the identities of devices and integrates trust-aware mechanisms to estimate the trustworthiness of data exchanged from the social environment of SIoT. By establishing a trustworthy and secure communication structure, this protocol improves the entire integrity and security of SIoT networks, addressing potential vulnerabilities connected with social communications between IoT devices. Therefore, this study develops an enhanced Trust Management using Locally Weighted Salp Swarm Algorithm with Deep learning (ETM-LWSSADL) technique for SIoT Networks. The ETM-LWSSADL technique computes direct and indirect trust values and is assessed depending upon different weighing factors for maximizing the application performance and creating a secure data transmission process. During authentication process, when the SIoT device with total trust value (TTV)is not greater than the threshold value (THV) or authentication token is invalid, the gateways then disregard the node. Besides, bidirectional gated recurrent unit (BiGRU) model is applied to generate a THV on collected traffic data. Moreover, the ETM-LWSSADL technique exploits the LWSSA technique for optimum hyper parameter selection of the BiGRU algorithm. To highlight the enhanced performance of the ETM-LWSSADL methodology, an extensive range of simulations can be involved.

The potential of using organisms as bioindicators of marine litter has been an area of general interest in multiple scientific and monitoring programs across the globe. Procellariiformes seabirds are particularly vulnerable to plastic contamination, which makes them a research focus group. This study investigated plastic ingestion in deceased fledglings and adults Cory’s shearwaters (Calonectris borealis) collected over eight years (2015 to 2022) at two Atlantic archipelagos: the Azores and the Canaries. Necropsies were carried out in a total of 1,238 individuals showing a high prevalence of plastic ingestion (90%), with approximately 80% of items recovered from the gizzard. Fledglings carried greater plastic loads compared to adults, yet plastic morphologies were similar between both age classes. The temporal analyses conducted with generalised additive mixed-effect models revealed a distinct temporal trend in plastic numbers, but not in terms of plastic mass. In addition, the spatial analyses showed that Cory’s shearwaters from the Canary Islands ingest a higher quantity of plastic and a greater proportion of threadlike items than the Azorean birds. These results suggest higher contamination at the NW Africa foraging grounds next to the Canaries and highlight fisheries as a potential source of marine litter in that region. On the other hand, the information gathered from the Azorean birds suggests they would be able to monitor changes in the composition of the plastic items floating in the North Atlantic Subtropical Gyre. Overall, our outcomes support the use of Cory’s shearwater fledglings that are victims of light pollution as a key bioindicator of plastic contamination in the North Atlantic. For its policy application, the presented threshold value in combination with the assessment method will enable effective tracking of floating plastic litter in the framework of the MSFD and OSPAR.

Given constrained healthcare budgets and many competing demands, public health decision-making requires comparing the expected cost and health outcomes of alternative strategies and associated adoption and financing actions. Opportunity cost (comparing outcomes from the best alternative use of budgets or actions in decision making) and more recently net benefit criteria (relative valuing of effects at a threshold value less costs) have been key concepts and metrics applied toward making such decisions. In an ideal world, opportunity cost and net benefit criteria should be mutually supportive and consistent. However, that requires a threshold value to align net benefit with opportunity cost assessment. This perspective piece shows that using the health shadow price as the ICER threshold aligns net benefit and opportunity cost criteria for joint adoption and financing actions that arise when reimbursing any new strategy or technology under a constrained budget. For an investment strategy with ICER at the health shadow price Bc = 1/(1/n + 1/d-1/m), net benefit of reimbursing (adopting and financing) that strategy given an incremental cost-effectiveness ration (ICER) of actual displacement, d, in financing, is shown to be equivalent to that of the best alternative actions, the most cost-effective expansion of existing programs (ICER = n) funded by the contraction of the least cost-effective programs (ICER = m). Net benefit is correspondingly positive or negative if it is below or above this threshold. Implications are discussed for creating pathways to optimal public health decision-making with appropriate incentives for efficient displacement as well as for adoption actions and related research.

An image processing-based Firebug Swarm Optimization (FSO) algorithm is developed in this article to detect maximum power point tracking (MPPT) under shadowing conditions on PV arrays. After capturing an image and applying image processing techniques, the proposed method can detect the shading portion of photovoltaic array (PV). The image processing results can then be used to modify the current rating in power equations. The Firebug swarm optimization (FSO) algorithm is metaheuristic algorithm that identifies and controls switching configurations under partial shading patterns by detecting the maximum global peak point (GPP) of output power generated by multiple configurations. This research is proposed with an image processing edge detection algorithm called the Otsu-Canny algorithm for detecting the partial shade on PV array. The FSO algorithm is used to rearrange the shaded photovoltaic array to significantly reduce the power and efficiency losses. MATLAB simulations were carried out using a 280 W PV panel to verify the efficiency of the proposed FSO MPPT technique with an image processing-based algorithm. The proposed FSO MPPT scheme's performance is compared to current cutting-edge MPPT methods. Under partial shading conditions, the proposed algorithm successfully detected the maximum peak point of a photovoltaic array, increasing power output and efficiency. [ABSTRACT FROM AUTHOR]

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The study explores the functionality and performance of Air Circuit Breaker (ACB) as a protective mechanism employing air arc extinguishing medium. ACBs find utility in both low and medium voltage panels, utilizing atmospheric pressure air to extinguish arcs generated during switching events or disturbances. This research undertakes a comprehensive analysis of ACB components, wiring configurations, and the calibration of threshold values, including the electric tripping unit system. Employing a methodology involving observation, interviews, and literature review, the study determines critical parameters such as the incoming current value (2000 A), Ir (0.4), Lsd (2), and Tr (0.5). The established threshold limit for ACB activation is set at 800 A, with the Lsd/current reaching 1,600 A upon ACB activation, triggering automatic tripping if the current surpasses 1,600 A. The study also identifies the activation time (0.5 seconds) for ACB tripping upon receiving currents exceeding 1,600 A. Analysis reveals pre-alarm deactivation at 85% current level, while activation occurs at 90%, indicating impending electrical tripping. For instance, Ir of 800 A signifies overload threshold, leading to automatic ACB deactivation and circuit shutdown upon current surpassing 800 A. Similarly, exceeding the short circuit threshold of 1,600 A triggers automatic ACB activation, ensuring circuit safety. This research sheds light on critical aspects of ACB functionality and performance, offering insights into its efficient operation and protective capabilities in electrical systems. [ABSTRACT FROM AUTHOR]

Full waveform inversion (FWI) is a nonlinear data fitting process that can derive high-resolution model parameters through iteration. In this process, step length is related to inversion accuracy and computational efficiency. It can be calculated efficiently with the inexact line search method, which does not require a misfit function to achieve the exact minimum. This method is aimed toward obtaining the appropriate descent using evaluation conditions and initial step length. Moreover, it does not depend on the form of the misfit function. In the inexact line search method, the evaluation condition and initial step length are obviously important factors. In this work, the classical Armijo, Wolfe, and Goldstein evaluation conditions in solving optimization problems in mathematics are studied and compared in detail. Numerical examples from the synthetic data of the overthrust model show that the convergence characteristics of Armijo and Goldstein are similar and that the computational efficiency is high and conducive to seismic FWI. In addition, the adaptive Barzilai-Borwein (ABB) method is adopted in FWI. The ABB method maximizes the changes in model parameters and gradients to adaptively calculate the initial step length. The threshold value of the ABB method for the initial step length estimation is also studied to explore a suitable threshold value that can ensure that large and small step lengths are frequently adopted in FWI. Numerical examples from the synthetic data of the overthrust model demonstrate the validity of the ABB method. Moreover, the inversion is superior when the threshold value is less than 0.5. [ABSTRACT FROM AUTHOR]

Ecotourism is a form of tourism involving responsible travel to natural areas, conserving the environment, and improving the well-being of the local people. Its purpose may be to educate the traveler, to provide funds for ecological censervation, to directly benifit the economic development, and political empowerment of local communities. Ecotourism has come up as an important conservation strategy in the tropical areas where diversity of species and habitats are threatened because of the traditional forms of development. This study deals with a non-linear mathematical model with a novel idea for sustainable development of biomass with ecotourism which is imperative in the present scenario. Stability and bifurcation analysis of the model is done and it is observed from our study that the system predicts unstability and exhibits bifurcation if ecotourism goes beyond a threshold value.

The accurate analysis of human dynamic behavior is very important for overcoming the limitations of movement diversity and behavioral adaptability. In this paper, a wearable device-based human dynamic behavior recognition method is proposed. The method collects acceleration and angular velocity data through a six-axis sensor to identify information containing specific behavior characteristics in a time series. A human movement data acquisition platform, the DMP attitude solution algorithm, and the threshold algorithm are used for processing. In this experiment, ten volunteers wore wearable sensors on their bilateral forearms, upper arms, thighs, calves, and waist, and movement data for standing, walking, and jumping were collected in school corridors and laboratory environments to verify the effectiveness of this wearable human movement recognition method. The results show that the recognition accuracy for standing, walking, and jumping reaches 98.33%, 96.67%, and 94.60%, respectively, and the average recognition rate is 96.53%. Compared with similar methods, this method not only improves the recognition accuracy but also simplifies the recognition algorithm and effectively saves computing resources. This research is expected to provide a new perspective for the recognition of human dynamic behavior and promote the wider application of wearable technology in the field of daily living assistance and health management.

Accurate ecological water regulation to achieve the optimal coupling between ecological water supply and vegetation water demand is the key challenge for ecological conservation in arid regions. Previous studies have mainly focused on the relationship between vegetation and specific water supply methods in arid regions. However, there has been limited attention to the maximum thresholds of Enhanced Vegetation Index (EVI) and area for vegetation protection and restoration under limited water conditions.Therefore, this study targets the mainstream of the Tarim River and conducts a systematic analysis of the maximum thresholds of EVI and area for vegetation protection and restoration under water constraints. Firstly, vegetation change patterns were discriminated using logistic and Gaussian functions. The results indicated that with enhanced watershed water resources management, both vegetation EVI and Evapotranspiration (ET) showed an increasing trend, which was projected to continue in the future. Based on the discrimination of vegetation change patterns, this study innovatively defined regions with linear, logarithmic, logical, and Gaussian patterns as area expansion zones requiring priority in ensuring ecological water supply, and regions with exponential patterns as quality improvement zones for improving vegetation restoration quality.By extracting vegetation EVI and ET indicators and constructing copula function in the two zones, the joint distribution function revealed that under water constraints, the range of natural vegetation expansion area-EVI threshold in the Tarim River was 17959.02 (EVI: 0.137) ∼ 18279.75 (EVI: 0.137) km2. The maximum threshold of vegetation EVI in the quality improvement zone was 0.223. Under current conditions, the average vegetation EVI in the area expansion zone was 0.137 (stable level), indicating a threshold for natural vegetation restoration of 0.137. During normal water years, besides increasing vegetation EVI to the threshold of natural vegetation restoration, the area could still expand by 665.06 ∼ 985.79 km2, corresponding to a vegetation area threshold of 17959.02 ∼ 18279.75 km2. In wet water years, the natural vegetation area could expand by 5172.53 ∼ 5493.26 km2, with a vegetation area threshold of 22466.49 ∼ 22787.22 km2.

To improve the effect of foreign language teaching in colleges and universities with high efficiency, this paper constructs a BP neural network optimized by multi-data chain by integrating multi-data chain and BP neural network, which effectively solves the shortcomings of BP neural network that is easy to fall into the local optimum. It optimizes the initial value and the threshold value of this neural network. On this basis, the multi-data chain optimized neural network is used to analyze the existing data related to English teaching in colleges and universities, to present the proportion of factors affecting foreign language teaching in colleges and universities in the form of data, and to summarize the reasons for acting the teaching effect and the problems existing in the current foreign language teaching classroom. Teachers and students make positive improvements to foreign language classroom teaching based on the data presented by the neural network to improve the effect of foreign language teaching in colleges and universities. Combined with the BP neural network optimized with multiple data chains, this paper conducted an experimental analysis of students’ concentration, satisfaction with the classroom, and performance. As can be seen from the results of data calculation, after the factors affecting the teaching effect were summarized and corrected, the concentration level of the two students in the experiment was significantly improved, and both remained above 50%. In addition, there was a massive difference in the grades of the same group of students before and after the improvement. The average grade of the control group was 76.47 and the middle grade of the experimental group was 87.6.

Increasing salinization of groundwater used for irrigation is a current and growing problem for vegetable production in greenhouses in the Mediterranean Basin. Vegetable growers in this system require clear information of crop response to salinity, particularly of threshold values. For sweet pepper in Mediterranean greenhouses, this work (i) evaluated the effect of increasing salinity on various parameters of crop yield, fruit quality and plant water relations, and (ii) determined threshold and slope values for the Maas and Hoffman (M&H) model. Sweet pepper was grown with nutrient solutions (ns) with electrical conductivities (EC) of 2.5 (T1), 3.5 (T2), 4.5 (T3), 5.5 (T4), 6.5 (T5) and 7.5 (T6) dS m−1. There were substantial and statistically significant reductions in total and marketable yield, dry matter production (DMP) and average fruit weight, with increasing salinity. In treatment T4 (ns of 5.5 dS m−1), the respective reductions for these parameters, compared to T1 (ns of 2.5 dS m−1), were 37%, 37%, 47%, 52% and 30%. Applying the M&H model, soil solution EC threshold (ECsst) values for total and marketable yield were 4.8 and 5.0 dS m−1. The respective slope values were − 8.0 and − 12.0%/dS m−1. The more rapid decline in marketable yield was influenced by a large increase in the incidence of blossom end rot (BER) with increasing salinity. In treatment T1, 25% of discarded fruit had BER which increased to 70% in T6. Average fruit size was affected by salinity, but fruit number was not. Most fruit quality parameters were unaffected by increasing salinity. However, fruits were more red and more yellow. Leaf water potential (ΨW), leaf osmotic potential (ΨO), stomatal conductance (gS) and leaf turgor potential (ΨP) followed the Maas and Hoffman model, with ΨW, ΨO and gS declining and ΨP increasing after the EC threshold value. The ECsst value for ΨW was 5.0 dS m−1, and for ΨO, gS and ΨP was 5.6–5.8 dS m−1. Considering all data, an ECsst value of 5.0 dS m−1 is suggested for sweet pepper grown in Mediterranean greenhouses.

Background: Endometrial proliferative lesions (EPL) usually refer to endometrial hyperplasia (EH) and endometrial cancer (EC). Among patients with premenopausal EPL who wish to preserve their fertility, only those with EH and early-stage EC have the possibility to undergo fertility preservation therapy. However, there is currently a lack of specific and reliable screening criteria and models for identifying these patients. Methods: This study utilized a retrospective diagnostic study design. The training set included medical record information that met the criteria between August 2017 and October 2022, while the validation set consisted of medical record information that met the criteria from November 2022 to May 2023. The endometrial pathological test served as the gold standard. The serum anti-Mullerian hormone (AMH) level before endometrial sampling and a regression model were employed to predict EPL. Results: The study included a total of 1209 patients with PCOS (1119 in the control group and 90 in the endometrial proliferative lesion group) and 5366 women without PCOS (5249 in the control group and 117 in the proliferative lesion group). In the case of PCOS patients aged 20–39 years, the most effective screening threshold for AMH was found to be a serum AMH level of ≤5.39 ng/mL. The model used for this group was logit(p) = −2.562 − 0.430 × AMH + 0.127 × BMI + 1.512 × hypertension + 0.956 × diabetes −1.145 × regular menstruation. On the other hand, for non-PCOS women aged 20–39 years, the optimal screening threshold for AMH was determined to be a serum AMH value of ≤2.18 ng/mL. The model used for this group was logit(p) = −3.778 − 0.823 × AMH + 0.176 × BMI + 2.660 × diabetes −1.527 × regular menstruation −1.117 × dysmenorrhea. It is important to note that all of these findings have successfully passed internal verification. Conclusion: For PCOS and non-PCOS women aged 20–39 years, the serum AMH test and related multiple regression models were obtained for the warning of EPL. [ABSTRACT FROM AUTHOR]

DEMATEL technique is a graphical representation method to deal with complex systems. The final analyzed cause and effect categorization would be fundamentally dependent on the threshold value setting. This research is intended to present some mathematical models for calculating the threshold value in the DEMATEL method. The min(max) operator has been intentionally used for considering three equations to identify the threshold value. Additionally, the proposed mathematical equations are gradually developed to gain more useful data to yield a threshold value as well. Particularly, the expert's initial scoring for building the primary matrix would also be applied in one equation. Results show eliciting an expert's opinions regarding the value of a threshold value determination leads to setting relatively high thresholds. But, there would be an equation which takes advantage of more data derived from the total influence matrix T. Moreover, a span of different threshold values is gained by making use of the Hamacher t-conorms operator which especially would cause better complexity management of the final total matrix T based on expert's opinions. As a contribution to this research, threshold value determination is developed mathematically by making use of the direct data gained by the total matrix T. Besides combining data derived from total matrix T, the initial influence direct matrix given by experts, a simpler aggregating procedure and no need for statistical information compared to special Lenth's method hints at this research's novelty as well. [ABSTRACT FROM AUTHOR]

The establishment of the reference ambient background concentrations (ABCs) and quality reference values (QRVs) for trace metal (TM) concentrations in soils are required for the environmental assessment and any implementation of a protective action. This information is lacking for soils of the eastern Mitidja plain, which is an important agricultural production area in Algeria. Data for the aqua regia extractable Cd, Cr, Cu, Fe, Ni, Pb and Zn concentrations from 180 composite topsoil samples taken across the Mitidja plain in a stratified random pattern were statistically analysed. Descriptive statistical methods and linear regression equations were applied to determine the upper limit of the ABCs for the TMs. After removal of outliers, the derived QRVs were: Cd 0.24, Cr 62.1, Cu 99.3, Fe 45 590, Ni 47.7, Pb 33 and Zn 115 mg/kg. Iron is a macro element in the soils, but is included as its concentration can be used to normalise the concentrations of the other elements. The derived QRVs are similar or less than those reported for other regions of the world, apart from Cu, where a wide range (36 to 206 mg/kg) is reported. These reference values can be used to identify areas that may require follow-up surveys or to identify priority sites for decision making.

Time series analysis is a method of key importance for systems of various hierarchies' economic security studies. This article's main goal is to develop an economic security rapid indicators system, introducing threshold values and utilizing indices with a one-month sampling period, and its approbation during Russia's economic security operational monitoring. In order to develop such a system, the authors accumulated economic security world experience including reliability, visibility and tree structure principles. The authors' monitoring system includes four spheres: real economy, social, monetary and foreign economic, each of which contains three indicators. In order to organize economic security monitoring, it is proposed to use the index method, which converts indicators into a dimensionless form with integral values in subsequent calculations. Based on integral indices values, the economic security generalized index is synthesized, which can be used to analyze a system's development trends. We present economic security normalized indicators and integral indices dynamics for the years 2020–2022, which show two crises dynamics. The first is due the COVID-19 pandemic, while the second is associated with economic sanctions against Russia, implemented in 2022. The proposed economic security operational monitoring indicators system can be used effectively in the government's practical tasks in order to ensure the required level of economic security. This is especially true for rapid diagnosis of crisis phenomena in countries and individual regions. [ABSTRACT FROM AUTHOR]

Copyright of Lubrication Engineering (0254-0150) is the property of Editorial Office of LUBRICATION ENGINEERING and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Proton nuclear magnetic resonance (NMR) is widely applied to characterize the microscopic properties of hydrogen‐containing porous media. The transverse relaxation time cutoff (T2c) value is the crucial parameter for the quantitative analysis of NMR data. Currently, there is no universal method for the determination of the T2c in clayey soils. This study aimed to develop a laboratory method for determining the T2c of remoulded loess by the freezing point of loosely bound water. Malan loess, a kind of typical clayey silt, was used as test material. Based on the soil freezing characteristic, NMR measurements were performed on remoulded loess with different macro‐parameter controls during the cooling process to obtain the T2 spectrum at each target temperature. By analysing the variation of unfrozen water content with temperature reduction, the freezing point of loosely bound water and the T2c value within the freezing‐point range was determined. The freezing point of loosely bound water in remoulded loess is about −3 to −5°C and that of firmly bound water is less than −5°C. Accordingly, the T2c value of remoulded loess is determined to be 1.5–1.8 ms. The assessment of heating and cooling process and different methods for determining the T2c shows that the laboratory method by the freezing point is effective and reliable, and the T2c determined by statistical methods is worthy of further study and improvement. The saturated permeability of remoulded loess is evaluated according to the determined T2c, and two NMR‐based permeability equations can well reflect pore water distribution in remoulded loess, but to a certain extent, both equations ignore soil microstructure, pore connectivity and chemical effects of pore solution. The laboratory method by the freezing point and the determined T2c value of remoulded loess fill the gap of NMR measurement in loess analysis and are of great significance for low‐plastic clays and clay types. [ABSTRACT FROM AUTHOR]