Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places

BackgroundPeople usually spend most of their time indoors, so indoor fine particulate matter (PM2.5) concentrations are crucial for refining individual PM2.5 exposure evaluation. The development of indoor PM2.5 concentration prediction models is essential for the health risk assessment of PM2.5 in epidemiological studies involving large populations.MethodsIn this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM2.5 concentration prediction models. Indoor PM2.5 concentration data, which included 11,712 records from five types of places, were obtained by on-site monitoring. Moreover, the potential predictor variable data were derived from outdoor monitoring stations and meteorological databases. A ten-fold cross-validation was conducted to examine the performance of all proposed models.ResultsThe final predictor variables incorporated in the MLR model were outdoor PM2.5 concentration, type of place, season, wind direction, surface wind speed, hour, precipitation, air pressure, and relative humidity. The ten-fold cross-validation results indicated that both models constructed had good predictive performance, with the determination coefficients (R2) of RFR and MLR were 72.20 and 60.35%, respectively. Generally, the RFR model had better predictive performance than the MLR model (RFR model developed using the same predictor variables as the MLR model, R2 = 71.86%). In terms of predictors, the importance results of predictor variables for both types of models suggested that outdoor PM2.5 concentration, type of place, season, hour, wind direction, and surface wind speed were the most important predictor variables.ConclusionIn this research, hourly average indoor PM2.5 concentration prediction models based on multiple types of places were developed for the first time. Both the MLR and RFR models based on easily accessible indicators displayed promising predictive performance, in which the machine learning domain RFR model outperformed the classical MLR model, and this result suggests the potential application of RFR algorithms for indoor air pollutant concentration prediction

Study of uncontained turbine engine rotor failure airworthiness compliance verification method

AbstractThe safety design is very important to civil aircraft. In order to verify the civil aircraft design whether meet the requirement of airworthiness regulation about the hazards to an airplane in the event of uncontained turbine engine rotor failure, which require the design measures to minimize the hazards in the case of uncontained turbine engine rotor failure. Airworthiness compliance verification method is presented in this paper .Firstly, in the cause of uncontained rotor fragments bursting out, the hazards validation method is proposed based on the results of airplane level functional hazard analysis (FHA) and fault tree analysis (FTA) in this paper. Secondly, airworthiness compliance verification procedure is developed. Thirdly, quantitative assessment model of hazards caused is proposed and calculated. Finally, an example show the whole airworthiness compliance verification procedure include hazards validation, quantitative calculation and airworthiness compliance verdict Results show that the hazard combinations resulting in multiple systems failure can be identified, thus providing more sufficient basis for airplane design improvement to minimize the hazards caused by uncontained engine rotor failure

Anti-apoptotic treatment in mouse models of age-related hearing loss

Age-related hearing loss (AHL), or presbycusis, is the most common neurodegenerative disorder and top communication deficit of the aged population. Genetic predisposition is one of the major factors in the development of AHL. Generally, AHL is associated with an age-dependent loss of sensory hair cells, spiral ganglion neurons and stria vascularis cells in the inner ear. Although the mechanisms leading to genetic hearing loss are not completely understood, caspase-family proteases function as important signals in the inner ear pathology. It is now accepted that mouse models are the best tools to study the mechanism of genetic hearing loss or AHL. Here, we provide a brief review of recent studies on hearing improvement in mouse models of AHL by anti-apoptotic treatment

Subcutaneous adipose tissue is associated with acute kidney injury after abdominal trauma based on the generalized propensity score approach: A retrospective cohort study

Introduction: Obesity is associated with an increased risk of acute kidney injury (AKI) after trauma. However, the associations between different adipose tissue depots and AKI remain unknown. Our study aims to quantify the effect of abdominal adiposity on AKI in trauma patients. Methods: We performed a retrospective cohort study of abdominal trauma patients who were admitted into our hospital from January 2010 to March 2020. Abdominal VAT (visceral adipose tissue) and SAT (subcutaneous adipose tissue) were measured at the level of the third lumbar vertebra using computed tomography. Causal modeling based on the generalized propensity score was used to quantify the effects of BMI (body mass index), VAT and SAT on AKI. Results: Among 324 abdominal trauma patients, 67 (20.68%) patients developed AKI. Patients with AKI had higher BMI (22.46 kg/m2 vs. 22.04 kg/m2, P = 0.014), higher SAT areas (89.06 cm2 vs. 83.39 cm2, P = 0.151) and VAT areas (140.02 cm2 vs. 91.48 cm2, P = 0.001) than those without AKI. By using causal modeling, we found that the risk of developing AKI increased by 8.3% (P = 0.001) and 4.8% (P = 0.022) with one unit increase in BMI (per 1 kg/m2), and ten units increase in SAT (per 10 cm2), respectively. However, VAT did not show a significant association with AKI (P = 0.327). Conclusion: SAT, but not VAT, increased the risk of AKI among abdominal trauma patients. Measurement of SAT might help to identify patients at higher risk of AKI

High Fat-to-Muscle Ratio Was Associated with Increased Clinical Severity in Patients with Abdominal Trauma

Overweight and moderate obesity confer a survival benefit in chronic diseases such as coronary artery disease and chronic kidney disease, which has been termed the “obesity paradox”. However, whether this phenomenon exists in trauma patients remains controversial. We performed a retrospective cohort study in abdominal trauma patients admitted to a Level I trauma center in Nanjing, China between 2010 and 2020. In addition to the traditional body mass index (BMI) based measures, we further examined the association between body composition-based indices with clinical severity in trauma populations. Body composition indices including skeletal muscle index (SMI), fat tissue index (FTI), and total fat-to-muscle ratio (FTI/SMI) were measured using computed tomography. Our study found that overweight was associated with a four-fold risk of mortality (OR, 4.47 [95% CI, 1.40–14.97], p = 0.012) and obesity was associated with a seven-fold risk of mortality (OR, 6.56 [95% CI, 1.07–36.57], p = 0.032) compared to normal weight. Patients with high FTI/SMI had a three-fold risk of mortality (OR, 3.06 [95% CI, 1.08–10.16], p = 0.046) and double the risk of an intensive care unit length of stay ≥ 5 d (OR, 1.75 [95% CI, 1.06–2.91], p = 0.031) compared to patients with low FTI/SMI. The obesity paradox was not observed in abdominal trauma patients, and high FTI/SMI ratio was independently associated with increased clinical severity

In-Fiber Collimator-Based Fabry-Perot Interferometer with Enhanced Vibration Sensitivity

A simple vibration sensor is proposed and demonstrated based on an optical fiber Fabry-Perot interferometer (FPI) with an in-fiber collimator. The device was fabricated by splicing a quarter-pitch graded index fiber (GIF) with a section of a hollow-core fiber (HCF) interposed between single mode fibers (SMFs). The static displacement sensitivity of the FPI with an in-fiber collimator was 5.17 × 10−4 μm−1, whereas the maximum static displacement sensitivity of the device without collimator was 1.73 × 10−4 μm−1. Moreover, the vibration sensitivity of the FPI with the collimator was 60.22 mV/g at 100 Hz, which was significantly higher than the sensitivity of the FPI without collimator (11.09 mV/g at 100 Hz). The proposed FPI with an in-fiber collimator also exhibited a vibration sensitivity nearly one order of magnitude higher than the device without the collimator at frequencies ranging from 40 to 200 Hz. This low-cost FPI sensor is highly-sensitive, robust and easy to fabricate. It could potentially be used for vibration monitoring in remote and harsh environments

Caspase-Mediated Apoptosis in the Cochleae Contributes to the Early Onset of Hearing Loss in A/J Mice

A/J and C57BL/6 J (B6) mice share a mutation in Cdh23 ( ahl allele) and are characterized by age-related hearing loss. However, hearing loss occurs much earlier in A/J mice at about four weeks of age. Recent study has revealed that a mutation in citrate synthase ( Cs ) is one of the main contributors, but the mechanism is largely unknown. In the present study, we showed that A/J mice displayed more severe degeneration of hair cells, spiral ganglion neurons, and stria vascularis in the cochleae compared with B6 mice. Moreover, messenger RNA accumulation levels of c aspase-3 and caspase-9 in the inner ears of A/J mice were significantly higher than those in B6 mice at 2 and 8 weeks of age. Immunohistochemistry localized caspase-3 expression mainly to the hair cells, spiral ganglion neurons, and stria vascularis in cochleae. In vitro transfection with Cs short hairpin RNA (shRNA) alone or cotransfection with Cs shRNA and Cdh23 shRNA significantly increased the levels of caspase-3 in an inner ear cell line (HEI-OC1). Finally, a pan-caspase inhibitor Z-VAD-FMK could preserve the hearing of A/J mice by lowering about 15 decibels of the sound pressure level for the auditory-evoked brainstem response thresholds. In conclusion, our results suggest that caspase-mediated apoptosis in the cochleae, which may be related to a Cs mutation, contributes to the early onset of hearing loss in A/J mice

Highly Sensitive Temperature Sensor Based on Cascaded Polymer-Infiltrated Fiber Mach–Zehnder Interferometers Operating near the Dispersion Turning Point

High-accuracy temperature measurement plays a vital role in biomedical, oceanographic, and photovoltaic industries. Here, a highly sensitive temperature sensor is proposed and demonstrated based on cascaded polymer-infiltrated Mach–Zehnder interferometers (MZIs), operating near the dispersion turning point. The MZI was constructed by splicing a half-pitch graded index fiber (GIF) and two sections of single-mode fiber and creating an inner air cavity based on femtosecond laser micromachining. The UV-curable polymer-infiltrated air cavity functioned as one of the interference arms of MZI, and the residual GIF core functioned as the other. Two MZIs with different cavity lengths and infiltrated with the UV-curable polymers, having the refractive indexes on the different sides of the turning point, were created. Moreover, the effects of the length and the bending way of transmission SMF between the first and the second MZI were studied. As a result, the cascaded MZI temperature sensor exhibits a greatly enhanced temperature sensitivity of −24.86 nm/°C based on wavelength differential detection. The aforementioned result makes it promising for high-accuracy temperature measurements in biomedical, oceanographic, and photovoltaic applications