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Objective: To observe the application of the controlled respiratory persistence monitor designed based on the principle of rhythmic temperature variations in artificial airways among different populations and in various artificial airways, and to discuss the feasibility and efficacy of monitoring controlled respiration persistence, and to provide a new method for the clinical respiratory monitoring. Methods: A total of 60 adult patients scheduled for general anesthesia, and 30 pediatric patients aged from 1 to 3 years old, classified as American Society of Anesthesiologists (ASA)Ⅰ-Ⅱ, were selected. A total of 60 adult patients were randomly divided into adult tracheal intubation (ATI) group and adult laryngeal mask(ALM) group, and there were 30 cases in each group. Additionally, 30 pediatric patients aged from 1 to 3 years old were regarded as pediatric tracheal intubation (CTI) group. After induction of general anesthesia, the patients in CTI and ATI groups were underwent tracheal intubation, while the patients in ALM group were given a laryngeal mask inserted and were connected to the anesthesia machine for mechanical ventilation. Whether or not the device could detect the respiratory rate (RR)of the patients in various groups was observed; the RR detected by the device and the frequency set on the anesthesia machine in various groups were compared. All the patients in three groups were simulated three common clinical scenarios of continuous respiration changes before surgery: disconnection of the breathing circuit, failure to switch from manual to mechanical control on the anesthesia machine, and slow air leakage in the breathing circuit. The ways to report the alert and start time of the atarm by the monitors were compared. Results: The controlled respiratory persistence monitor was able to detect the RR of the patients in three groups, and there was no significantly difference between the RR detected by the device and the frequency set on the anesthesia machine (P>0. 05). In the simulated scenarios of common respiratory persistence changes, all the patients in three groups received an artificial voice alarm signaling “Attention, breathing has stopped. ”, which was acknowledged. There was no significant difference in the start time of alarm of the controlled respiratory persistence monitor between ATI group and ALM group (P>0. 05). Compared with the start time of alarm of the patients in the same group across different scenarios, compared with slow air leakage in the breathing circuit, the start time to alarm for circuit disconnection and failure to switch from manual to mechanical control was shorter (P<0. 05). Conclusion: The clinical application of the controlled respiratory persistence monitor device designed based on the principle of detecting rhythmic temperature variations within artificial airways is feasible and effective in different populations and artificial airways. This device offers a new method for monitoring the respiratory continuity and ensuring the respiratory safety during surgery. [ABSTRACT FROM AUTHOR]

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department 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.)

Heat stress has threatened dairy cows during periods of high temperatures. Dairy farms can often assess the respiratory rate (breahts per minute, bpm) of dairy cows, and then implement timely environmental control measures to mitigate the heat stress, thus enhancing the welfare of animals and production performance. However, previous empirical or numerical models cannot accurately predict the respiratory rate of individual dairy cows in real environments. Data-driven machine learning models can be expected to provide a better representation of the relationship between various variables, particularly on the actual respiratory rate. In this study, a random forest-based prediction model was introduced for the cow respiration rate. Five hyperparameters were fine-tuned using genetic algorithm (GA), differential evolution algorithm (DE), particle swarm optimization algorithm (PSO), and Bayesian optimization (BO). These random forest-based models were compared with the artificial neural network (ANN) and extreme gradient boosting (XGBoost) models under grid search (GS). The training data was obtained from a commercial dairy farm in North China. The thermal environment parameters (air temperature, relative humidity, wind speed, and solar radiation) were integrated with the sampling time blocks and cattlerelated variables. The thermal environment variables were utilized as the input features to construct four heat stress indices, namely the temperature-humidity index (THI), adjusted temperature-humidity index (ATHI), equivalent temperature index for cattle (STIC), and skin temperature index (STIC). The dataset was comprised of 3005 records, with 80% allocated for training and 20% for testing. Hyperparameter optimization was conducted on the training set using 5-fold cross-validation. The correlation analysis revealed that there was a highly significant correlation (P<0.01) between all thermal environment variables, heat stress indices, and the respiratory rate of cows. Additionally, significant correlations (P<0.01) were observed between the thermal environment variables and heat stress indices. In feature collinearity, the overall dataset was partitioned into five subdatasets: EP, THI, ATHI, ETIC, and STIC dataset. The differentiation among these subsets was combined with the distinct environmental variables. Specifically, the EP dataset comprised four environmental parameters, while the rest dataset's features were the corresponding indices. Results indicated that the baseline random forest model achieved the highest prediction accuracy, when utilizing the adjusted temperature-humidity index, time block, milk production of the cows, days of lactation, body posture, and the number of calving as inputs. On the test set of the ATHI feature, the performance of the RF-based model was better than those of the GS-ANN and GS-XGBoost under the four intelligent optimizations. The random forest model was optimized by the differential evolution algorithm (DE-RF), indicating the highest accuracy, with a coefficient of determination (R2 ), mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) on the testing set of 0.614, 7.708 bpm, 14.4%, and 9.730 bpm, respectively. After that, the Bayesian-optimized random forest model (BO-RF) was achieved in a coefficient of determination, mean absolute error, mean absolute percentage error, and root mean square error on the testing set of 0.614, 7.723, 14.4%, and 9.737, respectively. Notably, the BO-RF was only required 1/200 of the time taken by the DE-RF. As a result, the BO-RF displayed the most favourable overall performance, in terms of prediction accuracy and computational time. Subsequently, the relative importance (RI) of the input features was determined using the BO-RF. The feature importance analysis revealed that the adjusted temperature-humidity index held the highest importance in the model prediction (RI value = 0.73), followed by time block (RI value = 0.09), milk production of cattle (RI value = 0.07), and days of lactation (RI value = 0.06). The body posture of the cattle (RI value = 0.03) and the number of calving (RI value = 0.02) shared a marginal impact on the model predictions. This finding can offer valuable insights into the precise and intelligent control system in dairy barns. [ABSTRACT FROM AUTHOR]

It is a means of injury assessment to detect respiratory rate using an unmanned aerial camera. However, the existing video- based respiratory rate detection algorithms are only applicable to fixed cameras. On the basis of spatial phase based respiratory signal extraction technology, a non-contact measurement method of human respiratory rate with videos recorded by unmanned aerial vehicle (UAV) is proposed. The complex steerable pyramid is used to extract the spatial phase of each frame image, and the phase sequence is obtained in chronological order. Secondly, the empirical mode decomposition (EMD) is used to decompose multiple modal components from the phase sequence, and the frequency variability analysis model is designed to select the components with stable frequencies, or the target respiratory signal. The peak value detection method is used to detect the human respiratory rate. The experimental results show that the average accuracy of the method can reach more than 98%, which is superior to the existing detection methods. [ABSTRACT FROM AUTHOR]

Respiration is an important metabolic basis for plant growth and development. The objective of this study is to compare the differences of taproot development characteristics, respiratory rate, respiratory key enzyme activity, gene expression, and energy change in different growth stages, and analyze the relationship between various respiratory physiological and sugar accumulation of sugar beet roots. In this study, four different genotypes of sugarbeet varieties were used as the experimental materials. The key enzyme activity and gene expression of respiratory metabolic pathway were determined, and respiratory pathway inhibitors were used at different growth stages. These results indicated the EMP-TCA was the main respiratory metabolic pathway during the growth process in beet taproot. No matter which respiratory pathway was inhibited, the weight and diameter of beet taproot can be reduced. Different respiratory metabolic pathways (EMP, TCA, and PPP) all played the important roles in promoting taproot expansion. In conclusions, this study laid a theoretical foundation for further research on the physiological mechanism of sugarbeet taproot, and provided physiological indicators for the breeding and identifying high-yield sugarbeet. [ABSTRACT FROM AUTHOR]

In order to investigate the correlation between respiratory rate and muscle quality in fresh rainbow trout, the changes of muscle quality corresponding to different respiratory rates were analyzed. The contents of lactic acid, glycogen, malondialdehyde (MDA), nucleotide compounds and pressurized water loss rate were measured. The result showed that with the increase of respiratory rate, the content of glycogen decreased, the content of malondialdehyde and nucleotide compounds, the rate of pressure water loss increased. When the respiratory rate increased from 83 to 95 times/min, the lactic acid content increased significantly from 1.46 to 2.37 mmol/g prot (P

In the manned space flight mission, the ground commanders and medical experts shall timely grasp the physiological conditions of astronauts in the cabin to ensure the safety of them. The heart rate and respiratory rate of astronauts are important physiological indexes to evaluate the health status of astronauts. How to calculate the heart rate and respiratory rate of astronauts quickly and accurately is one of the difficult problems faced by engineering tasks. Comprehensively considering the computing power under the condition of domestic autonomous controllable software and hardware, this paper presents a heart rate calculation R-wave detection algorithm based on self-learning threshold, and the zero-detection algorithm of respiratory rate calculation, and also designs a set of visual display software of heart rate and respiratory rate. It improves the real-time and accuracy of astronauts′ physiological data processing, and provides intuitive and reliable decision-making basis for the commanders and experts. The calculation and analysis of data shows that the algorithm has high accuracy and low computational requirements. It can meet the needs of medical support and medical supervision for astronauts in the waiting and ascending stages.

Objective To establish a machine learning model for driving fatigue recognition based on heart rate variability (HRV) and respiratory rate (RESP), and identify the optimal subsets of features. Methods From June 2021 to December 2021, 20 healthy male volunteers between the ages of 20 and 30 were recruited from the Army Medical University to participate in the fatigue driving experiment. The electrocardiographic (ECG) signals under normal sleep and sleep deprivation during driving tasks were recorded, and 18-dimensional fatigue-related HRV feature values were extracted. The HRV features that differ between awake and fatigue states were selected, which were further combined with RESP as the feature set. Moreover, 5 classic machine learning methods were adopted and compared, including support vector machines (SVM), k-nearest neighbor (KNN), naive Bayes (NB), decision tree (DT) and logistic regression (LR). The optimal feature subset was screened, and then a fatigue recognition model was established. Results The ratio of low frequency power to high frequency power (LF/HF), RESP, mean RR interval (Mean RR), sample entropy (SampEn), and detrended fluctuation analysis short-term slope (DFAα1) constituted the effective feature subsets of fatigue recognition, which achieved the best classification effect in SVM, with an accuracy of 87.03%, a sensitivity of 87.07% and a specificity of 87.13% in fatigue recognition. Among them, LF/HF and RESP were found as the most important indicators of driving fatigue identification, with an accuracy of each model in the above 2 dimensions reaching more than 80%. In addition, SVM and LR showed better overall performance, with an accuracy, sensitivity and specificity of 84.99%, 85.13%, 82.65% for SVM and 84.43%, 86.49%, 82.02% for LR, respectively. Conclusion LF/HF and RESP are the effective features for driving fatigue recognition. In the driving fatigue recognition model based on HRV features and RESP, the overall performance of SVM and LR models is better than the other models.

Objective　To explore the efficacy of high-flow nasal cannula oxygen therapy on oxygenation in populations at altitudes above 2 500 meters. Methods　Participants were recruited from medium-altitude Kunming （about 1891 m above sea level） to quickly enter higher altitude Lhasa （about 3650 m above sea level）. Participants inhaled air using high-flow nasal cannula oxygen therapy in Lhasa. The pulse oxygen saturation （SpO2），respiratory rate， heart rate and blood pressure were compared before and after the use of high-flow nasal cannula oxygen therapy . Results　In high altitude area，the high flow nasal canula oxygen therapy went well and smoothly. After high-flow nasal catheter oxygen therapy，SpO2 improved and respiratory rate decreased with the increase of inhaled gas flow，the difference was statistically significant （P < 0.05）. After using high-flow nasal cannula oxygen therapy equipment for air inhalation，SpO2 improved and respiratory rate decreased with the increase of inhaled gas flow， the difference was statistically significant （P < 0.05） . Conclusion　High-flow nasal cannula oxygen therapy not only improved participants’ oxygenation，it decreased the effort of breathing，and has potential clinical value in the treatment of high-altitude hypoxemia . [ABSTRACT FROM AUTHOR]

Copyright of Packaging & Food Machinery is the property of Packaging & Food Machinery Magazine 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.)

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui 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.)

In order to clarify the effects of different fertilization measures on the soil respiration (autotrophic respiration and heterotrophic respiration) in southern Anhui tobacco growing areas, field experiments with three fertilization treatments of chemical fertilizer (CK), chemical fertilizer + bioorganic fertilizer (T1) and chemical fertilizer + high carbon basal fertilizer (T2) were carried out to evaluate the dynamic changes of soil respiration, temperature, moisture content and active organic carbon content. The results showed that: 1) The total soil respiration rate for all the treatments ranged from 0.99 to 7.39 µmol ⋅ m-2 ⋅ s-1, and presented a trend of increasing first and then decreasing during the tobacco growing period with a peak appearing about 90 days after transplanting. The interaction of soil temperature and moisture content could explain 65.6%-75.3% of the variation of soil respiration rate. 2) Compared with CK, T1 and T2 treatments significantly increased soil respiration rates by 33.17% and 15.14%; wherein T1 significantly increased soil autotrophic and heterotrophic respiration rates by 34.66% and 32.08%, respectively. 3) The application of organic fertilizer significantly increased the contents of labile organic carbon, medium and high active organic carbon in soil. 4) Total soil respiration rate positively correlated with soil temperature, labile organic carbon, medium and high active organic carbon contents, while negatively correlated with soil moisture content. Therefore, the combined application of bioorganic fertilizer and high carbon base fertilizer could increase total soil respiration rate and promoted the accumulation of soil active organic carbon in tobacco fields [ABSTRACT FROM AUTHOR]

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department 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.)

Copyright of Xinjiang Agricultural Sciences is the property of Xinjiang Agricultural Sciences Editorial Department 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.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. 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.)

Objective: To evaluate the predictive value of a risk prediction model guided by the ratio of respiratory rate to diaphragm thickening fraction (RR/DTF) for noninvasive-invasive mechanical ventilation transition timing in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), through ultrasound evaluation of diaphragm movement indicators., Methods: Sixty-four patients diagnosed with AECOPD and undergoing non-invasive ventilation (NIV), who were admitted to the department of critical care medicine of the First Affiliated Hospital of Jinzhou Medical University from January 2022 to July 2023 were enrolled. They were divided into NIV successful group and NIV failure group based on the outcome of NIV within 24 hours. Clinical indicators such as RR/DTF, diaphragmatic excursion (DE), tidal volume (VT), respiratory rate (RR), pH value, partial pressure of carbon dioxide (PaCO 2 ), and sputum excretion disorder were compared between the two groups after 2 hours of NIV. The factors influencing NIV failure were included in binary Logistic regression analysis, and an RR/DTF oriented risk prediction model was established. Receiver operator characteristic curve (ROC curve) analysis was used to assess the predictive value of this model for the timing of noninvasive-invasive mechanical ventilation transition in AECOPD patients., Results: Among 64 patients with AECOPD, with 43 in the NIV successful group and 21 in the NIV failure group. There were no statistically significant differences in baseline data such as age, gender, body mass index (BMI), oxygenation index (P/F), smoking history, and acute physiological and chronic health evaluation II (APACHE II) between the two groups of patients, indicating comparability. Compared to the NIV successful group, the NIV failure group showed a significantly increase in RR/DTF, RR, PaCO 2 , and sputum retention, while VT and DE were significantly decreased [RR/DTF (%): 1.00±0.18 vs. 0.89±0.22, RR (bpm): 21.64±3.13 vs. 19.62±2.98, PaCO 2 (mmHg, 1 mmHg ≈ 0.133 kPa): 70.82±8.82 vs. 65.29±9.47, sputum retention: 57.1% vs. 30.2%, VT (mL): 308.09±14.89 vs. 324.48±23.82, DE (mm): 19.91±2.94 vs. 22.05±3.30, all P < 0.05]. Binary Logistic regression analysis showed that RR/DTF [odds ratio (OR) = 147.989, 95% confidence interval (95%CI) was 3.321-595.412, P = 0.010], RR (OR = 1.296, 95%CI was 1.006-1.670, P = 0.045), VT (OR = 0.966, 95%CI was 0.935-0.999, P = 0.044), PaCO 2 (OR = 1.086, 95%CI was 1.006~1.173, P = 0.035), and sputum retention (OR = 4.533, 95%CI was 1.025-20.049, P = 0.046) were independent risk factors for predicting NIV failure in AECOPD patients. ROC curve analysis showed that the area under the curve (AUC) of 0.713 with a 95%CI of 0.587-0.839 (P = 0.005). The sensitivity was 72.73%, the specificity was 88.10%, the Youden index was 0.394, and the optimal cut-off value was 0.87., Conclusions: The RR/DTF risk prediction model has good predictive value for the timing of noninvasive-invasive mechanical ventilation transition in AECOPD patients.

A pulse and respiration synchronous detection system is designed to explore the changes of physiological signals in different situations. The system obtains the corresponding signal through STM32 control pulse and respiratory acquisition circuit, calculates and displays real-time parameters such as heart rate and respiratory rate, and transmits the data to the upper computer for storage in the database. The experimental test results show that the system can monitor pulse and respiratory waveform in different situations, and the waveform is in good condition. Compared with medical pulse oximeter, the error of measured heart rate and blood oxygen concentration is less than 3%, and the error of respiratory rate is less than 5% compared with the actual value, which verifies the accuracy of system signal acquisition. The system is small in size, low in cost, and comfortable to wear, and can be applied in experimental research related to pulse and respiratory signals.

Copyright of Journal of the Chinese Society of Animal Science is the property of Chinese Society of Animal Science 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.)

Copyright of Journal of the Chinese Society of Animal Science is the property of Chinese Society of Animal Science 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.)

Copyright of Forest Research is the property of Forest Research Editorial Office 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.)

Copyright of South China Fisheries Science is the property of South China Fisheries Science Editorial Department 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.)

Corona virus disease 2019 (COVID-19) is an acute respiratory infectious disease with strong contagiousness, strong variability, and long incubation period. The probability of misdiagnosis and missed diagnosis can be significantly decreased with the use of automatic segmentation of COVID-19 lesions based on computed tomography images, which helps doctors in rapid diagnosis and precise treatment. This paper introduced the level set generalized Dice loss function (LGDL) in conjunction with the level set segmentation method based on COVID-19 lesion segmentation network and proposed a dual-path COVID-19 lesion segmentation network (Dual-SAUNet++) to address the pain points such as the complex symptoms of COVID-19 and the blurred boundaries that are challenging to segment. LGDL is an adaptive weight joint loss obtained by combining the generalized Dice loss of the mask path and the mean square error of the level set path. On the test set, the model achieved Dice similarity coefficient of (87.81 ± 10.86)%, intersection over union of (79.20 ± 14.58)%, sensitivity of (94.18 ± 13.56)%, specificity of (99.83 ± 0.43)% and Hausdorff distance of 18.29 ± 31.48 mm. Studies indicated that Dual-SAUNet++ has a great anti-noise capability and it can segment multi-scale lesions while simultaneously focusing on their area and border information. The method proposed in this paper assists doctors in judging the severity of COVID-19 infection by accurately segmenting the lesion, and provides a reliable basis for subsequent clinical treatment.

Objective: To investigate the effect of different fraction of inspired oxygen (FiO 2 ) baseline levels before endotracheal intubation on the time of expiratory oxygen concentration (EtO 2 ) reaching the standard in emergency patients with the EtO 2 as the monitoring index., Methods: A retrospective observational study was conducted. The clinical data of patients receiving endotracheal intubation in the emergency department of Peking Union Medical College Hospital from January 1 to November 1 in 2021 were enrolled. In order to avoid interference with the final result due to inadequate ventilation caused by non-standard operation or air leakage, the process of the continuous mechanical ventilation after FiO 2 was adjusted to pure oxygen in patients who had been intubated was selected to simulate the process of mask ventilation under pure oxygen before intubation. Combined with the electronic medical record and the ventilator record, the changes of the time required to reach 0.90 of EtO 2 (that was, the time required to reach the standard of EtO 2 ) and the respiratory cycle required to reach the standard after adjusting FiO 2 to pure oxygen under different baseline levels of FiO 2 were analyzed., Results: 113 EtO 2 assay records were collected from 42 patients. Among them, 2 patients had only one EtO 2 record due to the FiO 2 baseline level of 0.80, while the rest had two or more records of EtO 2 reaching time and respiratory cycle corresponding to different FiO 2 baseline level. Among the 42 patients, most of them were male (59.5%), elderly [median age was 62 (40, 70) years old] patients with respiratory diseases (40.5%). There were significant differences in lung function among different patients, but the majority of patients with normal function [oxygenation index (PaO 2 /FiO 2 ) > 300 mmHg (1 mmHg ≈ 0.133 kPa), 38.0%]. In the setting of ventilator parameters, combined with the slightly lower arterial partial pressure of carbon dioxide of patients [33 (28, 37) mmHg], mild hyperventilation phenomenon was considered to be widespread. With the increased in FiO 2 baseline level, the time of EtO 2 reaching standard and the number of respiratory cycles showed a gradually decreasing trend. When the FiO 2 baseline level was 0.35, the time of EtO 2 reaching the standard was the longest [79 (52, 87) s], and the corresponding median respiratory cycle was 22 (16, 26) cycles. When the FiO 2 baseline level was increased from 0.35 to 0.80, the median time of EtO 2 reaching the standard was shortened from 79 (52, 78) s to 30 (21, 44) s, and the median respiratory cycle was also reduced from 22 (16, 26) cycles to 10 (8, 13) cycles, with statistically significant differences (both P < 0.05)., Conclusions: The higher the FiO 2 baseline level of the mask ventilation in front of the endotracheal intubation in emergency patients, the shorter the time for EtO 2 reaching the standard, and the shorter the mask ventilation time.

Agaricus bisporus is highly perishable horticultural product. It does not have a protective skin cover, which consequently leads to high moisture loss and a short shelf life of 1-3 d when held at ambient temperature. And with the improvement of people's living standards, the requirement of the quality of food is also more and more strict. The shelf life of 1-2 d after harvest has not satisfied the market. How to control the quality of the Agaricus bisporus is an urgent problem to be solved. During the storage and transportation of postharvest fruits and vegetables, respiration is the main postharvest physiological and biochemical process of fruits and vegetables. Respiration is the most important cause of physiological tissue changes in fruits and vegetables. The respiration rate of fruits and vegetables is an important indicator of senescence and ethylene production in fruits. A major factor contributing to postharvest losses is the product respiration, which converts the stored sugar or starch to energy in the presence of O2 substrate, thus advancing ripening. Shelf life is directly proportional to the rate of senescence and inversely proportional to the respiration rate. Respiration plays a central role in the overall metabolism of a plant and is therefore often used as a general measure of metabolic rate. Controlling the respiration rate of fruits and vegetables is one of the important means to improve the value of the fruits and vegetables. Changes in respiration rate are influenced by many factors, such as storage time, storage temperature, environmental conditions. Storage temperature plays a major role in the respiration rates of fruits and vegetables, and when storage temperature decreased to lower levels, it causes a reduction in the biochemical reaction rate and consequently increases its shelf life. At present, there are many fresh-keeping methods to inhibit the respiration and keep the quality of fruits and vegetables. And a model of the respiratory rate of fruit and vegetable can provide important theoretical guidance and design basis for the storage and preservation method. Although the storage time is an important factor to affect the respiration rate of fruits and vegetables, there are few models to consider the storage time. A theoretical model of respiration rate of Agaricus bisporus related to storage time, based on the enzyme kinetics equation, was established. The effect of storage time on the respiration rate of Agaricus bisporus was studied at 5℃ and 20% oxygen concentration under the controlled atmosphere storage, and the respiration models of Agaricus bisporus based on this were established, with the coefficients of determination of 0.9766 and 0.9331 respectively. The difference between the model and the measured value was not significant (P>0.05), the absolute error of the respiration rate was less than 5 mL/(kg·h), and the relative error was 0.06%-24.95%. After that, the effects of storage temperature (5, 10, 15 and 20℃) on the respiration rate were studied as well as the established model parameters. Based on the model, the temperature dependence of the model parameters was evaluated using an Arrhenius plot, and the model incorporating temperature and time was established, whose coefficients of determination were 0.9073 and 0.9350 respectively. The difference between the model and the measured value was not significant (P>0.05), the absolute error of the respiration rate was less than 17 mL/(kg·h), and the relative error was 1.00%-25.25%. The verification tests showed that, the respiration of Agaricus bisporus in terms of time and temperature during the storage was well described by the obtained models, and agreed well with the experiment data. The respiration rate model can provide the important theoretical basis for the prediction of respiratory rate and the research of storage quality in the process of storage and transportation of fruits and vegetables. [ABSTRACT FROM AUTHOR]

It is of great significance to clarify the influence of soil temperature and moisture on soil respiration rate and its characteristics in ecologically fragile regions under the background of climate change for the accurate assessment and prediction of carbon budgets in this region. The average CO 2 concentration and soil temperature and moisture at different soil depths (10, 50, and 100 cm) were measured using a CO 2 analyzer and temperature and moisture sensors. The soil respiration rate was calculated using Fick's first diffusion coefficient method. The dynamic characteristics of soil temperature, soil moisture, and soil respiration rate in different soil depths were explored, and the response of soil respiration rate to soil temperature and moisture were further analyzed. The results showed that the diurnal variation in soil respiration rate decreased significantly with the increase in soil depth ( P <0.05), and the peak time lagged behind. Soil respiration rate in adjacent soil depths (10, 50, and 100 cm) lagged 1 h from top to bottom. The monthly variation in soil respiration rate was a multi-peak curve, in which the maximum soil respiration rates of 10, 50, and 100 cm soil depths were on July 25 th , August 6 th , and August 10 th , reaching 13.96, 2.96, and 1.47 μmol·(m 2 ·s) -1 , respectively. The effect of soil temperature on soil respiration rate decreased with the increase in soil depth. Soil temperature at 50 cm and below had no significant effect on soil respiration rate ( P >0.05). The fitting index of 10 cm soil depth was the best ( R 2 =0.96), but the fitting indexes of 50 cm and 100 cm soil depths were poor ( R 2 =0.00 and R 2 =0.01, respectively). The temperature sensitivity coefficient Q 10 decreased with the increase in soil depth. Soil moisture in different soil depths had significant effects on soil respiration rate ( P <0.05), and the quadratic fitting indicated that 50 cm ( R 2 =0.35)>10 cm ( R 2 =0.22)>100 cm ( R 2 =0.31). The combined effects of soil temperature and moisture in different soil depths could explain 96%, 6%-50%, and 22%-24% of soil respiration rate, respectively. In summary, the effects of soil temperature and moisture at different soil depths of the Caragana korshinskii plantation in the loess-hilly region on soil respiration rate differed. The soil respiration rate of the 10 cm soil depth was affected by the comprehensive effect of soil temperature and moisture; however, the relative contribution of soil temperature was higher, and soil moisture at and below a soil depth of 50 cm was the key factor. These results could help improve predictions on the impact of future climate change on the carbon cycle of terrestrial ecosystems in the region and provide a theoretical basis for greenhouse gas regulation in the future.

Breathing is of great significance in the monitoring of patients with obstructive sleep apnea hypopnea syndrome, perioperative monitoring and intensive care. In this study, a respiratory monitoring and verification system based on optical capacitance product pulse wave (PPG) is designed, which can synchronously collect human PPG signals. Through algorithm processing, the characteristic parameters of PPG signal are calculated, and the respiratory signal and respiratory frequency can be extracted in real time. In order to verify the accuracy of extracting respiratory signal and respiratory rate by the algorithm, the system adds the nasal airflow respiratory signal acquisition module to synchronously collect the nasal airflow respiratory signal as the standard signal for comparison and verification. Finally, the root mean square error between the respiratory rate extracted by the algorithm from the pulse wave and the standard respiratory rate is only 1.05 times/min.

Traditional methods of non-contact human respiratory rate measurement usually require complex devices or algorithms. Aiming at this problem, a non-contact respiratory rate measurement method based on only the RGB video information was proposed in this paper. The method consisted of four steps. Firstly, spatial filtering was applied to each frame of the input video. Secondly, a gray compensation algorithm was used to compensate for the gray level change caused by the environmental light. Thirdly, the gray levels of each pixel over time were filtered separately by a low-pass filter. Finally, the region of interest was determined based on the filtering results, and the respiration rate of the human is measured. The physical measurement experiments were designed, and the measurement accuracy was compared with that of the biological radar. The error of the proposed method was between - 5.5% and 3% in different detection directions. The results show that the non-contact respiration rate measurement method can effectively measure the human respiration rate.

Life monitoring technology as the basis of health evaluation, in recent years, its related technology research also has new development, in which cardiopulmonary parameters are the core physiological indicators to measure the basic state of vital signs, the analysis of its monitoring technology is particularly important. In this study, the main means of life monitoring are analyzed, and the monitoring technology of cardiopulmonary parameters is the main focus. What is more, the research status and development of contact and non-contact cardiopulmonary monitoring technology at home and abroad were also considered. Lastly, this study will be combined with the radar wave vital signs monitoring technology, which has been achieved good results in the field of cardiopulmonary monitoring, in order to provide a reference for the long-term development of life monitoring field and the technology integration of intelligent pension, intelligent automobile and other related industries.

Oxygen saturation and respiratory signals are important physiological signals of human body, respiratory monitoring plays an important role in clinical and daily life. A system was established to extract respiratory signals from photoplethysmography in this study. Including the collection of pulse wave signal, the extraction of respiratory signal, and the calculation of respiratory rate and pulse rate transmitted from the slave computer to the host computer in real time.

This paper designs a bluetooth-based low-power multi-parameter monitoring system. The system is mainly composed of ECG signal acquisition, respiratory signal acquisition, body temperature acquisition, bluetooth 4.0 transmission module and Android mobile phone APP display. The system collects the corresponding physiological signals through various collection parts, and can realize the monitoring of three physiological signals of electrocardiogram, respiration and body temperature. The Android mobile APP can display ECG, respiratory waveform and temperature data in real time. The system is small in size and low in power consumption, and has a good application prospect in portable and wearable medical applications.

This paper aims to study the accuracy of cardiopulmonary physiological parameters measurement under different exercise intensity in the accompanying (wearable) physiological parameter monitoring system. SensEcho, an accompanying physiological parameter monitoring system, and CORTEX METALYZER 3B, a cardiopulmonary function testing system, were used to simultaneously collect the cardiopulmonary physiological parameters of 28 healthy volunteers (17 males and 11 females) in various exercise states, such as standing, lying down and Bruce treadmill exercise. Bland-Altman analysis, correlation analysis and other methods, from the perspective of group and individual, were used to contrast and analyze the two types of equipment to measure parameters of heart rate and breathing rate. The results of group analysis showed that the heart rate and respiratory rate data box charts collected by the two devices were highly consistent. The heart rate difference was (-0.407 ± 3.380) times/min, and the respiratory rate difference was (-0.560 ± 7.047) times/min. The difference was very small. The Bland-Altman plot of the heart rate and respiratory rate in each experimental stage showed that the proportion of mean ± 2SD was 96.86% and 95.29%, respectively. The results of individual analysis showed that the correlation coefficients of the whole-process heart rate and respiratory rate data were all greater than 0.9. In conclusion, SensEcho, as an accompanying physiological parameter monitoring system, can accurately measure the human heart rate, respiration rate and other key cardiopulmonary physiological parameters under various sports conditions. It can maintain good stability under various sports conditions and meet the requirements of continuous physiological signal collection and analysis application under sports conditions.

The article aims to discuss the feasibility of using respiratory sounds to monitor respiratory rate. The average power of respiratory sounds was created firstly, the autocorrelation algorithm was used to calculate the respiratory cycle. The respiratory cycle of nasal flow pressure signal was calculated simultaneously, and the result was taken as a reference standard, then, two groups of respiratory cycle data were analyzed by correlation analysis and Bland-Altman analysis. The respiratory rate is relatively stable, using respiratory sounds monitor respiratory rate is feasible, the respiratory rate changes obviously, the existing methods and algorithm using respiratory sounds are temporarily unable to accurately reflect the changes of respiratory rate, further research is needed.

A field mesocosm experiment with Chinese fir (Cunninghamia lanceolata) seedlings was conducted in Chenda State-Owned Forest Farm, Sanming, Fujian Province. The effects of soil warming (ambient +5 ℃) on specific respiration rates and nonstructural carbohydrate (NSC) concentrations in fine roots were measured by the ingrowth core method, to reveal the belowground responses and the adaptability of Chinese fir to global warming. The results showed that soil warming caused significant changes of fine root NSC in the second year. The NSC and starch concentrations in 0-1 mm fine roots, and the NSC and sugar concentrations in 1-2 mm fine roots decreased signifi-cantly in January. The NSC, sugar and starch concentrations in 0-1 mm roots and the starch concentration in 1-2 mm roots increased in July. Soil warming had no significant effect on fine root NSC in the third year. The specific root respiration rate of the 0-1 mm roots significantly increased in July of the second year but significantly decreased in July of the third year in the warmed plots. Compared with the 0-1 mm roots, soil warming had no significant effect on the specific root respiration rate of the 1-2 mm roots. In conclusion, the responses of fine root respiration to soil warming depended on the duration of warming. Fine root respiration partly acclimated to soil warming with increasing duration of soil warming, which kept fine root NSC being relatively stable.

Considering the importance of the human respiratory signal detection and based on the Cole-Cole bio-impedance model,we developed a wearable device for detecting human respiratory signal.The device can be used to analyze the impedance characteristics of human body at different frequencies based on the bio-impedance theory.The device is also based on the method of proportion measurement to design a high signal to noise ratio(SNR)circuit to get human respiratory signal.In order to obtain the waveform of the respiratory signal and the value of the respiration rate,we used the techniques of discrete Fourier transform(DFT)and dynamic difference threshold peak detection.Experiments showed that this system was valid,and we could see that it could accurately detect the waveform of respiration and the detection accuracy rate of respiratory wave peak point detection results was over 98%.So it can meet the needs of the actual breath test.

In order to monitor the physiological condition of the human body in daily life, this study has designed a system of measuring physiological parameters based on cushion, which could detect heart rate and respiration rate when people are sitting. The system can continuously colect signal from cushion with a state of low pressure and without sticking any electrode on people’s bodies. The hardware part mainly includes the signal acquisition circuit of the sensor, microcomputer control module and Bluetooth wireless transmission module. For the two physiological signals have the characteristic of the large noise and low-frequency, we use the Butterworth low-pass filter to process the signal according to an optimized Matlab algorithm. The results show that this system can measure heart rate and respiration rate accurately. Thus, the real-time monitoring on body’s information can be implemented.

In this paper, we designed an oxygen saturation, heart rate, respiration rate monitoring system based on smartphone of android operating system, physiological signal acquired by MSP430 microcontroller and transmitted by Bluetooth module.

To investigate the effect of stepwise paced breathing (PB) on pulse transit time (PTT), we collected physiological signals of electrocardiogram (ECG), respiration and arterial pulse wave during a procedure of stepwise PB, which consists of 6 different breathing rates changing in a protocol of 14.0-12.5-11.0-9.5-8.0-7.0 breath per minute (BPM), with each breathing rate lasting 3 minutes. Twenty two healthy adults involved in this experiment and the change of PTT was analyzed during the stepwise PB procedure. In our study, the PTT was measured by calculating the time interval from the R-spike of the ECG to the peaks of the second derivative of the arterial pulse wave. Ensemble empirical mode decomposition (EEMD) was applied to PTT to decompose the signal into different intrinsic mode function, and respiratory oscillation and trend component (baseline) in PTT were further extracted. It was found that the respiratory oscillations in the PTT increased with decreasing of the PB rate, and many of the subjects (14 out of 22) showed the phenomena of PTT baseline increasing during the stepwise PB procedure. The results indicated that the stepwise PB procedure induced a high level of cardiovascular oscillation and produced an accumulative effect of PTT baseline increase. As PTT is capable of predicting changes in BP over a short period of time, increase of PTT baseline indicates the decrease of blood pressure. The experiments showed that the stepwise PB procedure could reduce blood pressure for most subjects. For future work, it is necessary to develop certain indices differentiating the effectiveness of the stepwise PB procedure on the PTT baseline change, and to test the effectiveness of this stepwise PB procedure on blood pressure reduction for patients with essential hypertension.

Objective: To evaluate the effects of non-invasive ventilation in the treatment of infants with respiratory failure after cardiopulmonary bypass (CPB) and extubation., Method: Sixty-three infants who had undergone successful surgery with CPB, got respiratory failure after extubation. These infants were randomly divided into two groups: non-invasive (NV) group, treated with non-invasive ventilation and invasive (IV) group, treated with tracheal intubation. The alteration of clinical symptoms, heart rate (HR), respiratory rate (RR), pulse oxygen saturation (SpO₂) and blood gas were measured. A comparison was conducted in the incidence of complication and hospital infection, mechanical ventilation time, length of stay in ICU and hospital stay., Result: Among the 32 patients in NV group, 1 patient died of heart failure, the remaining 31 patients recovered. Of these 32, 26 patients had relief of respiratory failure, the HR 181 (19.7) bpm, RR 54 (16.7) bpm and PaCO₂ 55.5(6) mm Hg decreased to 157 (12) bpm, 35 (3.25) bpm, and 42 (10.5) mm Hg, meanwhile SpO₂ 87% (10.5%), pH 7.29 (0.24), PaO₂ 55.5(6) mm Hg increased to 96% (3%), 7.37(0.15), 82.5 (11) mm Hg after treatment with non-invasive ventilation (P < 0.01). Six patients underwent tracheal intubation because their condition was not improved. Tracheal hemorrhage or laryngeal edema did not occur in these patients. Among the 31 patients in IV group, 1 patient died of heart failure, the other patients were cured. Of these 30, one patient had tracheal hemorrhage and four patients had laryngeal edema. The incidence of hospital infection in NV group was lower compared with that in IV group. The mechanical ventilation time in NV group 42 (17.2) h was shorter compared with that in IV group 50 (20) h (P < 0.01). There was no significant difference in the length of ICU and hospital stay between the two groups., Conclusion: Non-invasive ventilation is a safe and effective method to treat infants with respiratory failure after CPB and extubation.

This study is to establish a rat chronic asthma model. Sensitive SD rats were selected through histamine challenge. The asthmatic groups were sensitized by ih and ip with OVA, aluminium hydroxide gel and inactivated bacillus pertussis on day 1 and 14. From day 21, acute asthmatic group was aerosolized 1% OVA for 1 week, chronic asthmatic group was aerosolized 0.1% OVA for 12 weeks. The control groups received saline as the substitution of OVA. Twenty four hours after the last provocation, physiological monitoring equipment was used to detect the pulmonary function, then the rats were sacrificed. Bronchoalveolar lavage fluid (BALF) was collected to calculate the ratio of different inflammatory cells. ELISA was used to detect total IgE and OVA-specific IgE in serum. Microscopy was conducted to observe the histopathology of lung stained with haematoxylin and eosin staining. Collagen fibers were detected using Picric acid-Sirius red staining technique. The optical density at 610 nm of extractive from locus caeruleus was detected by passive cutaneous anaphylaxis (PCA). The results showed that the asthmatic characteristics were significantly developed in model groups, but not in control groups. Chronic asthmatic group had significantly higher indexes than acute asthmatic group, including the thickness of airway smooth muscle and bronchial basement membrane, and goblet cell hyperplasia, the area of collagen in airways, A610 of extractive from locus caeruleus, the concentration of total IgE and OVA-specific IgE in serum. However, inflammatory cell infiltrate in lungs and the percentage of eosinophils of white blood cells in BALF were lower in chronic asthmatic group than those in acute asthmatic group. Respiratory rate and respiratory flow showed no significant difference in both model groups. In conclusion, the rat chronic asthma model is established by the way in this study, which is comparable to the physiopathologic characteristics of human asthma.

Aim: To investigate variation of hydrogen sulfide (H2S) in serum of rats after cardiopulmonary resuscitation (CPR) and explore its pathophysiological role in CPR., Methods: The 30 male SD rats were randomly divided into control group (n=6) and experimental group (n=24), then models of cardiac arrest (CA) were established in rats of experimental group by transcutaneous electrical epicardium stimulation. Blood samples were collected before CA, at 2, 4, 6, 8, 10 and 12 h after restoration of spontaneous circulation (ROSC) for testing the serum levels of H2S, at the same time rectal temperature (Tr), mean arterial pressure (MAP), heart rate (HR) and respiration rate (R) were recorded. Next to analyze the dynamic variation of H2S content in serum of the rats after CPR and its correlation of the above-mentioned signs of life., Results: (1) In experimental group, all of the 24 rats were successfully induced CA and resuscitation; at end points (12 h after ROSC) there were 14 rats alive and their vital signs were stable. There was no death in the control group. (2) The variation trend of H2S content in serum was different between experimental group and the control (F=12.226, P=0.003). In experimental group, H2S content in serum increased dramatically after CPR and reached peak at 6 h after ROSC, then return to the similar level of the control group. (3) H2S content in serum was negatively correlated with Tr (partial r=-0.556, P=0.000) and MAP (partial r=-0.240, P=0.002). But it wasn't correlated with HR and R (P>0.05)., Conclusion: Change of H2S content in serum of rats after CPR may be a manifestation of compensatory response after ROSC and participate in physiological processes such as body temperature and blood pressure regulation. But as for its precisely mechanisms, it still needs to be studied further.

Objective: To investigate the effects of acute hypervolemic hemodilution (AHH) with hydroxyethyl starch (HES) 130/0.4 on the lung in a rabbit model of sepsis and their possible mechanism., Methods: Thirty healthy New Zealand rabbits were randomly divided into three groups (n=10 each): group sham operation (C), group sepsis model (E) and group AHH. Sepsis model was reproduced with modified colon ascendens stent peritonitis (CASP). In group C laparotomy was done but without puncturing the colon. At 4 hours after CASP, AHH was carried out intravenous infusion of 6% HES 130/0.4 20 ml/kg at 20 ml/min. Lactated Ringer solution was infused at 10 ml kg (-1) h (-1) in all three groups during the experiment. The animals breathed spontaneously during the experiment. A catheter was introduced into the right carotid artery for blood sampling, and it was connected to a pressure transducer for continuous mean arterial pressure (MAP) and heart rate (HR) monitoring. At 4 hours and 8 hours after CASP, a median abdominal incision was made and photographic documentation of abdominal situs was made. At the same time arterial blood samples were drawn at 4 hours and 8 hours after CASP for blood gas analysis and determination of hemoglobin (Hb) and hematocrit (Hct). The plasma component was separated and tumor necrosis factor-alpha (TNF-alpha) was measured. Respiratory rate and urinary output were record. The rabbits were sacrificed at 8 hours after CASP. The right lungs were immediately removed for determination of total protein concentration in broncho-alveolar lavage fluid (BALF). The wet/dry (W/D) lung weight rate were calculated. The sections of lung were stained with hematoxylin and eosin for light microscopic examination and the injury score was recorded., Results: (1)MAP declined gradually and HR tended to accelerate during the course of the experiment in group E, but no significant differences were found in both group C and group AHH. (2)After AHH, the Hb and Hct decreased by 20% in group AHH. In group E, arterial oxygen saturation (SaO(2)), arterial partial pressure of oxygen (PaO(2)), arterial partial pressure of carbon dioxide (PaCO(2)) and pH decreased significantly at 8 hours after CASP compared with group C (all P<0.05). (3)TNF-alpha concentration in plasma was higher in group E and group AHH than in group C at 4 hours after CASP (both P<0.05). At 8 hours TNF-alpha concentration was increased in group E compared with group C (P<0.05), but there was no significant difference between group C and group AHH. (4)In group E, score of morphological changes in lung was significantly increased compared with group AHH (6.9+/-1.4 vs. 11.2+/-1.7, P<0.05)., Conclusion: AHH with HES 130/0.4 can protect the lungs from sepsis. Inhibition of proinflammatory cytokines may be involved in the mechanism.

Objective: To evaluate the applicability of electrical impedance equipment in assessing local lung volume during different PEEP ventilation and at different respiratory rate in neonatal piglets., Methods: Electrical impedance measurements (EIM) were performed on 6 healthy newborn piglets (age 4 +/- 1 d, weight 1.66 +/- 0.31 kg) using 8 electrodes distributed to 4 quadrants of the lung (left, right, upper, lower). Tidal impedance and functional residual impedance changes during PEEP levels of 2, 4, 6 and 8 cm H2O and frequencies ranging from 0.5 to 15 Hz were investigated., Results: The sum of regional tidal impedance obtained from four quadrants, significantly reflected tidal volume (VT) measured by a pneumotachograph during both frequency and PEEP changed (r2 = 0.98). A decrease of PEEP 4 to 2 cm H2O caused a significant increase in total tidal impedance (TTI) as well as in VT (P < 0.01 and P < 0.05); whereas an increase in frequency from 0.5 to 15 Hz was associated with a significant decrease in both TTI and VT (P < 0.05 and P < 0.01). Increased frequency had a balancing effect on air distribution, whereas higher PEEP did not result in more homogeneous ventilation. Minimal impedance values (FRI) (surrogate variable for FRC) showed that total FRI significantly decreased with increasing PEEP level., Conclusions: EIM demonstrated good applicability to assess changes in thoracic gas volume. It is highly suggested that this method could be considered and further studied as a non-invasive bedside method to monitor continuously regional lung ventilation of neonates under any mode of mechanical ventilation.