Wearable Bioimpedance-Based Deep Learning Techniques for Live Fish Health Assessment under Waterless and Low-Temperature Conditions.

(1) Background: At present, physiological stress detection technology is a critical means for precisely evaluating the comprehensive health status of live fish. However, the commonly used biochemical tests are invasive and time-consuming and cannot simultaneously monitor and dynamically evaluate multiple stress levels in fish and accurately classify their health levels. The purpose of this study is to deploy wearable bioelectrical impedance analysis (WBIA) sensors on fish skin to construct a deep learning-based stress dynamic evaluation model for precisely estimating their accurate health status. (2) Methods: The correlation of fish (turbot) muscle nutrients and their stress indicators are calculated using grey relation analysis (GRA) for allocating the weight of the stress factors. Next, WBIA features are sieved using the maximum information coefficient (MIC) in stress trend evaluation modeling, which is closely related to the key stress factors. Afterward, a convolutional neural network (CNN) is utilized to obtain the features of the WBIA signals. Then, the long short-term memory (LSTM) method learns the stress trends with residual rectification using bidirectional gated recurrent units (BiGRUs). Furthermore, the Z-shaped fuzzy function can accurately classify the fish health status by the total evaluated stress values. (3) Results: The proposed CNN-LSTM-BiGRU-based stress evaluation model shows superior accuracy compared to the other machine learning models (CNN-LSTM, CNN-GRU, LSTM, GRU, SVR, and BP) based on the MAPE, MAE, and RMSE. Moreover, the fish health classification under waterless and low-temperature conditions is thoroughly verified. High accuracy is proven by the classification validation criterion (accuracy, F1 score, precision, and recall). (4) Conclusions: the proposed health evaluation technology can precisely monitor and track the health status of live fish and provides an effective technical reference for the field of live fish vital sign detection.

Stress Evaluation of Mouse Husbandry Environments for Improving Laboratory Animal Welfare.

Animal welfare is recognized as essential for the coexistence of humans and animals. Considering the increased demand and interest in animal welfare, many methods for improving animal welfare are being devised, but which method reduces animal stress has not been scientifically verified. Therefore, reducing animal stress by providing a proper breeding environment and environmental enrichment can be the basis for animal study. In this study, stress levels were assessed based on the mouse-breeding environment. We considered that the higher the body weight and the lower the corticosterone concentration, the lower the stress. According to the results, animals in the individual ventilation cages were determined to have lower serum cortisol concentrations, while the body weight of the animals was increased when in individual ventilation cages compared with individual isolated cages and when providing environmental enrichment compared with group breeding or not providing environmental enrichment. The results provide appropriate guidelines for improving laboratory animal welfare.

All-in-one calcium nanoflowers for dual outputs biosensor: A simultaneous strategy for depression drug evaluation and non-invasive stress assessment.

Although enzyme-based signal amplification has been well developed for biosensors, their application in low-abundance biomarker under complicated conditions detection remains challenge. Cortisol is a steroid hormone and a quantitative evaluation of cortisol can objectively assess stress and depression. However, various factors can induce slight cortisol changes in body fluids, and this in turn sets a strict requirement for bedside testing of cortisol for evaluation of stress. Herein, all-in-one calcium nanoflowers (CaHPO4-AM-HRP-SA NFs) integrated with horseradish peroxidase (HRP), α-amylase (α-AM), and streptavidin (SA) have been synthesized to develop a simple but powerful biosensor for cortisol detection. High specific surface area and allosteric modulator provided by the hybrid nanoflowers as inherent advantages significantly boosted the catalytical ability and stability compared with the free enzymes. CaHPO4-AM-HRP-SA NFs also endowed the sensor with two output signals of one sample, leading the as-prepared sensor to realize self-calibration detection. Aside from using a traditional microplate reader to measure the signal, it could also be read out by a handheld blood glucose meter and a mobile phone. The sensor exhibited attractive simplicity and sensitivity with a low LOD of 98.5 pg mL-1. It accomplished the sensitive evaluation of cortisol in rat serum and assessed the antidepressant effects of different medications. The non-invasive and reliable cortisol detection is also achieved in human urine and saliva samples. Overall, we have demonstrated that the sensor can be deployed as a promising platform to evaluate drug efficiency and monitor stress in a simple and non-invasive manner.

Stress Evaluation of Welded Joints with Metal Magnetic Memory Testing Based on Tension-Compression Fatigue Test.

Metal magnetic memory testing (MMMT) is an effective nondestructive technique for fatigue damage monitoring of weldments because of its capacity for stress evaluation. An experimental investigation of the effect of the applied fatigue stress on MMMT signals, including the tangential component Bx and the normal component Bz, during tension-compression fatigue tests in welded joints was carried out systematically. The Bx and Bz signals at different fatigue cycles and fatigue stresses were collected and analyzed, and the results showed that there was a peak of Bx and abnormal peaks of Bz that existed at the welded joint before loading. After loading, the peak of Bx and the abnormal peaks of Bz reversed, and the Bx signals moved upward and the Bz signals rotated anticlockwise dramatically in the first few fatigue cycles. After the fatigue cycle number was larger than 1000, Bx and Bz were stable, with very little fluctuation. In addition, the characteristics of Bx signals, the mean value, and the peak value of the average of Bx had an extremely significant linear relationship with the applied fatigue stress during the stable stage of the fatigue test, which indicates that MMMT is a feasible method for fatigue stress evaluation and even residual fatigue life estimation for weldments in service.

Photoelastic Stress Field Recovery Using Deep Convolutional Neural Network.

Recent work has shown that deep convolutional neural network is capable of solving inverse problems in computational imaging, and recovering the stress field of the loaded object from the photoelastic fringe pattern can also be regarded as an inverse problem solving process. However, the formation of the fringe pattern is affected by the geometry of the specimen and experimental configuration. When the loaded object produces complex fringe distribution, the traditional stress analysis methods still face difficulty in unwrapping. In this study, a deep convolutional neural network based on the encoder-decoder structure is proposed, which can accurately decode stress distribution information from complex photoelastic fringe images generated under different experimental configurations. The proposed method is validated on a synthetic dataset, and the quality of stress distribution images generated by the network model is evaluated using mean squared error (MSE), structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and other evaluation indexes. The results show that the proposed stress recovery network can achieve an average performance of more than 0.99 on the SSIM.

Magnetic Barkhausen Noise Transient Analysis for Microstructure Evolution Characterization with Tensile Stress in Elastic and Plastic Status.

Stress affects the microstructure of the material to influence the durability and service life of the components. However, the previous work of stress measurement lacks quantification of the different variations in time and spatial features of micromagnetic properties affected by stress in elastic and plastic ranges, as well as the evolution of microstructure. In this paper, microstructure evolution under stress in elastic and plastic ranges is evaluated by magnetic Barkhausen noise (MBN) transient analysis. Based on a J-A model, the duration and the intensity are the eigenvalues for MBN transient analysis to quantify transient size and number of Barkhausen events under stress. With the observation of domain wall (DW) distribution and microstructure, the correlation between material microstructure and MBN transient eigenvalues is investigated to verify the ability of material status evaluation on the microscopic scale of the method. The results show that the duration and the intensity have different change trends in elastic and plastic ranges. The eigenvalue fusion of the duration and intensity distinguishes the change in microstructure under the stress in elastic and plastic deformation. The appearance of grain boundary (GB) migration and dislocation under the stress in the plastic range makes the duration and the intensity higher on the GB than those inside the grain. Besides, the reproducibility of the proposed method is investigated by evaluating microstructure evolution for silicon steel sheet and Q235 steel sheet. The proposed method investigates the correlation between the microstructure and transient micromagnetic properties, which has the potential for stress evaluation in elastic and plastic ranges for industrial materials.

Development of Social Support Model to Reduce Menopause Women’s Anxiety / Desarrollo del modelo de apoyo social para reducir la ansiedad de la menopausia femenina

Background: Menopause is a natural phase of a woman's life when menstrual periods stop permanently and cause psychological symptoms such as anxiety. anxiety can be reduced when women get social support. Objective: The purpose of this study is to develop a social support model to reduce anxiety in menopausal women. Method: This study applied explanatory research design with a Cross-sectional approach. The study population was selected 197 menopausal women who were in 11 clusters in Diwek - Jombang Regency. The participants were selected using Cluster Random sampling. The data analyzed by using the Partial Least Square test. The inclusion criteria of this research are 1) Women Menopause Age 45-55 years old experiencing anxiety, 2) Registered in couples of childbearing age records 2017 of Diwek District Health Center, while the exclusion criteria of this research are 1) Menopausal women single/ virgin, 2) Using tranquilizers, 3) Using hormone replacement therapy (TSH). Results: The results showed that (1) individual factors significantly influenced the evaluation of stress (path coefficient of -0.056, t = 3.74); (2) social networking significantly influences stress evaluation (path coefficient -0.147, t = 2.13); (3) social support significantly influences stress evaluation (path coefficient -0.117, t = 2.02); (4) social support significantly influences anxiety (path coefficient -0.326, t = 5.25); and (5) stress evaluation significantly influences anxiety (path coefficient 0.196, t = 9.07). Conclusion: The development of social support models to reduce postmenopausal anxiety has a significant direct effect. The development of the model consists of stress assessment consisting of experience, trust, coping resources, informative support and award support. The development of social support is highly recommended to reduce anxiety among menopausal women by promoting stress evaluation and social support from close relationships.(AU)

Antecedentes: la menopausia es una fase natural de la vida de una mujer en la que los períodos menstruales se detienen de forma permanente y provocan síntomas psicológicos como la ansiedad. la ansiedad se puede reducir cuando las mujeres obtienen apoyo social. Objetivo: El propósito de este estudio es desarrollar un modelo de apoyo social para reducir la ansiedad en mujeres menopáusicas. Método: Este estudio aplicó un diseño de investigación explicativa con un enfoque transversal. La población del estudio fue seleccionada 197 mujeres menopáusicas que estaban en 11 grupos en Diwek - Jombang Regency. Los participantes fueron seleccionados mediante muestreo aleatorio por conglomerados. Los datos analizados mediante la prueba de mínimos cuadrados parciales. Los criterios de inclusión de esta investigación son 1) Mujeres con menopausia de 45 a 55 años que experimentan ansiedad, 2) Registradas en parejas en edad fértil en 2017 del Diwek District Health Center, mientras que los criterios de exclusión de esta investigación son 1) Mujeres menopáusicas solteras / virgen, 2) Usar tranquilizantes, 3) Usar terapia de reemplazo hormonal (TSH). Resultados: Los resultados mostraron que (1) los factores individuales influyeron significativamente en la evaluación del estrés (coeficiente de trayectoria de -0,056, t = 3,74); (2) las redes sociales influyen significativamente en la evaluación del estrés (coeficiente de trayectoria -0,147, t = 2,13); (3) el apoyo social influye significativamente en la evaluación del estrés (coeficiente de trayectoria -0,117, t = 2,02); (4) el apoyo social influye significativamente en la ansiedad (coeficiente de trayectoria -0,326, t = 5,25); y (5) la evaluación del estrés influye significativamente en la ansiedad (coeficiente de trayectoria 0,196, t = 9,07). Conclusión: El desarrollo de modelos de apoyo social para reducir la ansiedad posmenopáusica tiene un efecto directo significativo...(AU)

Salt and Drought Stress Responses in Cultivated Beets (Beta vulgaris L.) and Wild Beet (Beta maritima L.).

Cultivated beets, including leaf beets, garden beets, fodder beets, and sugar beets, which belong to the species Beta vulgaris L., are economically important edible crops that have been originated from a halophytic wild ancestor, Beta maritima L. (sea beet or wild beet). Salt and drought are major abiotic stresses, which limit crop growth and production and have been most studied in beets compared to other environmental stresses. Characteristically, beets are salt- and drought-tolerant crops; however, prolonged and persistent exposure to salt and drought stress results in a significant drop in beet productivity and yield. Hence, to harness the best benefits of beet cultivation, knowledge of stress-coping strategies, and stress-tolerant beet varieties, are prerequisites. In the current review, we have summarized morpho-physiological, biochemical, and molecular responses of sugar beet, fodder beet, red beet, chard (B. vulgaris L.), and their ancestor, wild beet (B. maritima L.) under salt and drought stresses. We have also described the beet genes and noncoding RNAs previously reported for their roles in salt and drought response/tolerance. The plant biologists and breeders can potentiate the utilization of these resources as prospective targets for developing crops with abiotic stress tolerance.

Time-Response-Histogram-Based Feature of Magnetic Barkhausen Noise for Material Characterization Considering Influences of Grain and Grain Boundary under In Situ Tensile Test.

Stress is the crucial factor of ferromagnetic material failure origin. However, the nondestructive test methods to analyze the ferromagnetic material properties' inhomogeneity on the microscopic scale with stress have not been obtained so far. In this study, magnetic Barkhausen noise (MBN) signals on different silicon steel sheet locations under in situ tensile tests were detected by a high-spatial-resolution magnetic probe. The domain-wall (DW) motion, grain, and grain boundary were detected using a magneto-optical Kerr (MOKE) image. The time characteristic of DW motion and MBN signals on different locations was varied during elastic deformation. Therefore, a time-response histogram is proposed in this work to show different DW motions inside the grain and around the grain boundary under low tensile stress. In order to separate the variation of magnetic properties affected by the grain and grain boundary under low tensile stress corresponding to MBN excitation, time-division was carried out to extract the root-mean-square (RMS), mean, and peak in the optimized time interval. The time-response histogram of MBN evaluated the silicon steel sheet's inhomogeneous material properties, and provided a theoretical and experimental reference for ferromagnetic material properties under stress.

Effectiveness of a Voice-Based Mental Health Evaluation System for Mobile Devices: Prospective Study.

BACKGROUND: We developed a system for monitoring mental health using voice data from daily phone calls, termed Mind Monitoring System (MIMOSYS), by implementing a method for estimating mental health status from voice data. OBJECTIVE: The objective of this study was to evaluate the potential of this system for detecting depressive states and monitoring stress-induced mental changes. METHODS: We opened our system to the public in the form of a prospective study in which data were collected over 2 years from a large, unspecified sample of users. We used these data to analyze the relationships between the rate of continued use, the men-to-women ratio, and existing psychological tests for this system over the study duration. Moreover, we analyzed changes in mental data over time under stress from particular life events. RESULTS: The system had a high rate of continued use. Voice indicators showed that women have more depressive tendencies than men, matching the rate of depression in Japan. The system's voice indicators and the scores on classical psychological tests were correlated. We confirmed deteriorating mental health for users in areas affected by major earthquakes in Japan around the time of the earthquakes. CONCLUSIONS: The results suggest that although this system is insufficient for detecting depression, it may be effective for monitoring changes in mental health due to stress. The greatest feature of our system is mental health monitoring, which is most effectively accomplished by performing long-term time-series analysis of the acquired data considering the user's life events. Such a system can improve the implementation of patient interventions by evaluating objective data along with life events.

Water Extract of Cryphaea heteromalla (Hedw.) D. Mohr Bryophyte as a Natural Powerful Source of Biologically Active Compounds.

Bryophytes comprise of the mosses, liverworts, and hornworts. Cryphaea heteromalla, (Hedw.) D. Mohr, is a non-vascular lower plant belonging to mosses group. To the date, the most chemically characterized species belong to the liverworts, while only 3.2% and 8.8% of the species belonging to the mosses and hornworts, respectively, have been investigated. In this work, we present Folin-Ciocalteu and oxygen radical absorbance capacity (ORAC) data related to crude extracts of C. heteromalla obtained by three different extraction solvents: pure water (WT), methanol:water (80:20 v/v) (MET), and ethanol:water (80:20 v/v) (ETH). The water extract proved to be the best solvent showing the highest content of biophenols and the highest ORAC value. The C. heteromalla-WT extract was investigated by HPLC-TOF/MS (High Performance Liquid Chromatography-Time of Flight/Mass Spectrometry) allowing for the detection of 14 compounds, five of which were phenolic compounds, derivatives of benzoic, caffeic, and coumaric acids. Moreover, the C. heteromalla WT extract showed a protective effect against reactive oxygen species (ROS) generation induced by tert-butyl hydroperoxide (TBH) on the murine NIH-3T3 fibroblast cell line.

Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection.

Body acceleration due to heartbeat-induced reaction forces can be measured as mobile phone accelerometer (m-ACC) signals. Our aim was to test the feasibility of using m-ACC to detect changes induced by stress by ultra-short heart rate variability (USV) indices (standard deviation of normal-to-normal interval-SDNN and root mean square of successive differences-RMSSD). Sixteen healthy volunteers were recruited; m-ACC was recorded while in supine position, during spontaneous breathing at rest conditions (REST) and during one minute of mental stress (MS) induced by arithmetic serial subtraction task, simultaneous with conventional electrocardiogram (ECG). Beat occurrences were extracted from both ECG and m-ACC and used to compute USV indices using 60, 30 and 10s durations, both for REST and MS. A feasibility of 93.8% in the beat-to-beat m-ACC heart rate series extraction was reached. In both ECG and m-ACC series, compared to REST, in MS the mean beat duration was reduced by 15% and RMSSD decreased by 38%. These results show that short term recordings (up to 10 s) of cardiac activity using smartphone's accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus.

Use of Time-Dependent Multispectral Representation of Magnetic Barkhausen Noise Signals for the Needs of Non-Destructive Evaluation of Steel Materials.

Due to the existing relationship between microstructural properties and magnetic ones of the ferromagnetic materials, the application potential of the magnetic Barkhausen noise (BN) method to non-destructive testing is constantly growing. However, the stochastic nature of the Barkhausen effect requires the use of advanced signal processing methods. Recently, the need to apply time-frequency (TF) transformations to the processing of BN signals arose. However, various TF methods have been used in the majority of cases for qualitative signal conditioning and no extensive analysis of TF-based information has been conducted so far. Therefore, in this paper, the wide analysis of BN TF representation was carried out. Considering the properties of TF transformations, the Short-Time Fourier Transform (STFT) was used. A procedure for definition of the envelopes of the TF characteristic was proposed. To verify the quality of extracted features, an analysis was performed on the basis of BN signals acquired during stress loading experiments of steel elements. First, the preliminary experiments were processed for various parameters of the measuring system and calculation procedures. The feature extraction procedure was performed for different modes of TF representations. Finally, the distributions of TF features over the loading stages are presented and their information content was validated using commonly used features derived from time T and frequency F domains.

Stress reactivity and emotion in premenstrual syndrome.

BACKGROUND: Hormone level fluctuation across the menstrual cycle causes women to experience negative emotions and also affects their mood regulation and stress sensitivity. However, the stress reactivity and emotional variations in women with premenstrual syndrome (PMS), who are especially sensitive to the variations in hormone cycles, have not been explained. METHODS: The present study used an electroencephalogram (EEG) stress evaluation test, a physiology stress evaluation test, and the positive affect and negative affect scale (PANAS) to evaluate the stress reactivity pattern and emotional state of women with PMS. RESULTS: The results showed that women with PMS had higher negative affect and lower positive affect compared with controls. Moreover, under stressful conditions, the women with PMS had a higher alpha activity and a lower respiration rate than the controls. The differences in stress reactivity and emotional states between women with PMS and controls were based on a covariant analysis with menstrual cycle (luteal and follicular phases) as the covariate. CONCLUSION: The results demonstrated that, compared with controls, women suffering from PMS have a continuous abnormality in emotional state and stress reactivity, which was independent of the menstrual cycle.

Stress Distribution Profile Imaging With Spectral Fabry-Perot Interferometry in Thin Layer Substrates for Surface Micromachining.

We have used spectral two-layer interferometry (STLI) imaging for estimation of the stress distribution profiles (SDPs) in thin film substrates, enabling fast and reliable all-optical methodology for the evaluation of pre-stress topography profiles in silicon wafers deposited with thin films. Specifically, in polycrystalline silicon (PS) and silicon nitride (SN) thin films, we demonstrate a nondestructive, systematic, and robust capability for consistent stress distribution profile (SDP) evaluation relying on STLI. In particular, for PS and SN devices, the SDP estimation is consistent and is compared with complementary characterization of the films.

A Steel Wire Stress Measuring Sensor Based on the Static Magnetization by Permanent Magnets.

A new stress measuring sensor is proposed to evaluate the axial stress in steel wires. Without using excitation and induction coils, the sensor mainly consists of a static magnetization unit made of permanent magnets and a magnetic field measurement unit containing Hall element arrays. Firstly, the principle is illustrated in detail. Under the excitation of the magnetization unit, a spatially varying magnetized region in the steel wire is utilized as the measurement region. Radial and axial magnetic flux densities at different lift-offs in this region are measured by the measurement unit to calculate the differential permeability curve and magnetization curve. Feature parameters extracted from the curves are used to evaluate the axial stress. Secondly, the special stress sensor for Φ5 and Φ7 steel wires is developed accordingly. At last, the performance of the sensor is tested experimentally. Experimental results show that the sensor can measure the magnetization curve accurately with the error in the range of ±6%. Furthermore, the obtained differential permeability at working points 1200 A/m and 10000 A/m change almost linearly with the stress in steel wires, the goodness of linear fits are all higher than 0.987. Thus, the proposed steel wire stress measuring sensor is feasible.

Development and Validation of a Questionnaire for Preliminary Assessment of Heat Stress at Workplace.

BACKGROUND: Current heat stress indices are not completely suitable for heat strain screening in developing countries due to their inherent and applied limitations. The aim of this study was development of a questionnaire method entitled "Heat Strain Score Index" (HSSI) in order to perform a preliminary assessment of heat stress at work. METHODS: This research included six phases (i) Item generation (ii) Content validity (iii) Reliability analysis (iv)Structure validity (v) Concurrent validity and (vi) Classification of thermal risk level. In item generation phase, 40 items were identified to have impact on the heat strain. Content validity was evaluated by occupational health specialists. RESULTS: In consistency assessment, Cronbach's coefficient (α) of items was 0.91. Exploratory factor analysis on items HSSI draft identified four subscales which explained 71.6% of the variance. Correlation between the HSSI score with aural temperature was 0.73. Cut-off point; sensitivity and specificity for upper no thermal strain zone were 13.5, 91% and 50%, respectively. Whereas Cut-off point, sensitivity and specificity for lower thermal strain zone were 18, 86% and 73%. CONCLUSIONS: The results showed that 18 variables that were measurable through subjective judgment and observation in the HSSI scale covered heat stress key factors. This scale demonstrated reliability and initial validity in scale were suitable. Therefore HSSI scale for primary evaluation heat stress is appropriate.

Stress and multiple sclerosis: A systematic review considering potential moderating and mediating factors and methods of assessing stress.

Research about the effects of stress on multiple sclerosis has yielded contradictory results. This study aims to systematically review the evidence focusing on two possible causes: the role of stress assessment and potential moderating and mediating factors. The Web of Knowledge (MEDLINE and Web of Science), Scopus, and PsycINFO databases were searched for relevant articles published from 1900 through December 2014 using the terms "stress*" AND "multiple sclerosis." Twenty-three articles were included. Studies focused on the effect of stress on multiple sclerosis onset (n = 9) were mostly retrospective, and semi-structured interviews and scales yielded the most consistent associations. Studies focused on multiple sclerosis progression (n = 14) were mostly prospective, and self-reported diaries yielded the most consistent results. The most important modifying factors were stressor duration, severity, and frequency; cardiovascular reactivity and heart rate; and social support and escitalopram intake. Future studies should consider the use of prospective design with self-reported evaluations and the study of moderators and mediators related to amount of stress and autonomic nervous system reactivity to determine the effects of stress on multiple sclerosis.

Noninvasive evaluation of mental stress using by a refined rough set technique based on biomedical signals.

OBJECTIVE: Evaluating and treating of stress can substantially benefits to people with health problems. Currently, mental stress evaluated using medical questionnaires. However, the accuracy of this evaluation method is questionable because of variations caused by factors such as cultural differences and individual subjectivity. Measuring of biomedical signals is an effective method for estimating mental stress that enables this problem to be overcome. However, the relationship between the levels of mental stress and biomedical signals remain poorly understood. METHODS AND MATERIALS: A refined rough set algorithm is proposed to determine the relationship between mental stress and biomedical signals, this algorithm combines rough set theory with a hybrid Taguchi-genetic algorithm, called RS-HTGA. Two parameters were used for evaluating the performance of the proposed RS-HTGA method. A dataset obtained from a practice clinic comprising 362 cases (196 male, 166 female) was adopted to evaluate the performance of the proposed approach. RESULTS: The empirical results indicate that the proposed method can achieve acceptable accuracy in medical practice. Furthermore, the proposed method was successfully used to identify the relationship between mental stress levels and bio-medical signals. In addition, the comparison between the RS-HTGA and a support vector machine (SVM) method indicated that both methods yield good results. The total averages for sensitivity, specificity, and precision were greater than 96%, the results indicated that both algorithms produced highly accurate results, but a substantial difference in discrimination existed among people with Phase 0 stress. The SVM algorithm shows 89% and the RS-HTGA shows 96%. Therefore, the RS-HTGA is superior to the SVM algorithm. The kappa test results for both algorithms were greater than 0.936, indicating high accuracy and consistency. The area under receiver operating characteristic curve for both the RS-HTGA and a SVM method were greater than 0.77, indicating a good discrimination capability. CONCLUSIONS: In this study, crucial attributes in stress evaluation were successfully recognized using biomedical signals, thereby enabling the conservation of medical resources and elucidating the mapping relationship between levels of mental stress and candidate attributes. In addition, we developed a prototype system for mental stress evaluation that can be used to provide benefits in medical practice.

Offshore platforms: comparison of five benthic indicators for assessing the macrozoobenthic stress levels.

Within the European Water Framework Directive, many studies have been conducted to evaluate the sensitivity/robustness of a variety of indices in relation to natural or anthropogenic disturbance events. However, these indices have rarely been applied to verify the impacts of disturbances in offshore environments, though the Marine Strategy Framework Directive recommends their use for assessing benthic community conditions and functionality. The aim of this paper was to determine which biotic indicator performed the best for detecting the impacts of offshore structures on benthic populations in the Adriatic Sea. The impacts of four rigs were investigated six months after their installation, and the H', AMBI, m-AMBI, BENTIX, and BOPA indices were assessed. Although these five indices delivered some contradictory results because of the differences in their structure and discrepancies in their assignment of species sensitivity, the BENTIX, H' and BOPA indices appear to evaluate stress levels better than the AMBI and m-AMBI indices, which tend to provide results that are slightly overly optimistic.