Article
Infectious Diseases
Hao Lei, Mengya Yang, Zhaomin Dong, Kejia Hu, Tao Chen, Lei Yang, Nan Zhang, Xiaoli Duan, Shigui Yang, Dayan Wang, Yuelong Shu, Yuguo Li
Summary: This study aimed to investigate the impact of indoor and outdoor relative humidity (RH) on influenza transmission in temperate and subtropical climates. The findings showed a U-shaped relationship between indoor RH and the effective reproduction number (Rt) of influenza in both regions, while no correlation was observed between outdoor RH and Rt. These results suggest that indoor RH may play a key role in the seasonality of influenza in temperate and subtropical locations in China.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2023)
Article
Thermodynamics
Alison J. Robey, Laura Fierce
Summary: In temperate climates, the peak in infection rates of enveloped viruses during the winter is likely heightened by seasonal variation in relative humidity within indoor spaces. Relative humidity impacts the seasonal transmission via inactivation rates rather than particle removal.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
(2022)
Article
Chemistry, Physical
Arwa Bazaid, Fengyuan Zhang, Qiancheng Zhang, Sabine Neumayer, Denise Denning, Stefan Habelitz, Ana Marina Ferreira, Brian J. Rodriguez
Summary: Since the discovery of piezoelectricity in bone in 1957, there has been a debate about the functional role of collagen piezoelectricity. The investigation of piezoelectricity in collagen has generated interest in bone remodeling, but there are conflicting reports about its presence in a humid environment. This study used lateral piezoresponse force microscopy to investigate the electromechanical properties of type I collagen from a rat tail tendon at the nanoscale, and found that collagen retains its piezoelectric behavior even in a biologically relevant humidity range.
Article
Thermodynamics
Chao Liu, Yalin Zhang, Limei Sun, Weijun Gao, Xiaotong Jing, Weirui Ye
Summary: The study found that undergraduate students performed best in indoor environments with 40% relative humidity and 24 degrees Celsius, with relative humidity having a greater impact on learning performance than air temperature. Low humidity environments decreased overall learning performance, emphasizing the importance of considering relative humidity when designing learning spaces.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Microbiology
Haoxiang Wu, Jonathan Woon Chung Wong
Summary: Indoor temperature is not as important as relative humidity during dry periods in affecting the resistance of mold to wet-dry cycles.
Article
Environmental Sciences
Yuyan Luo, Hao Wu, Taofeng Gu, Zhenglin Wang, Haiyan Yue, Guangsheng Wu, Langfeng Zhu, Dongyang Pu, Pei Tang, Mengjiao Jiang
Summary: The study compares the performance of four machine learning models (deep learning, gradient boosting machine, extreme gradient boosting, and random forest) in retrieving temperature and relative humidity profiles based on brightness temperature measurements from a ground-based microwave radiometer and radiosonde data. The results show that the deep learning model performs best in temperature retrieval, while the performance of the four machine learning methods in relative humidity retrieval varies with altitude levels. The study also proposes an integrated machine learning method for relative humidity retrieval.
Article
Multidisciplinary Sciences
C. A. Verheyen, L. Bourouiba
Summary: This study found a robust association between indoor relative humidity and COVID-19 outbreaks. Intermediate relative humidity (40-60%) was associated with better outbreak outcomes. This suggests that indoor conditions, particularly indoor relative humidity, can modulate the spread and severity of COVID-19 outbreaks.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2022)
Article
Geochemistry & Geophysics
Ehsan Forootan, Mona Kosary, Saeed Farzaneh, Maike Schumacher
Summary: An accurate estimation of ionospheric variables such as TEC is crucial for space weather, communication, and satellite geodetic applications. Existing empirical and physics-based models fail to capture all ionospheric variability due to their simplified structure, coarse sampling, and calibration dependencies. This study introduces a data assimilation technique called empirical decomposition-based data assimilation (DDA) that significantly reduces computational complexity. Results demonstrate that DDA improves TEC predictions by reducing the root mean squared error (RMSE) by 42.46% and 31.89% compared to final GIM TEC products.
SURVEYS IN GEOPHYSICS
(2023)
Article
Construction & Building Technology
Namhyuck Ahn, Sanghoon Park
Summary: This study evaluated the moisture performance of coated and non-coated timber hybrid window frames through humidity tests. The results showed that the coated frames had significantly improved dimensional stability and reduced surface defects.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
A. Peruzzi, R. Bosma, S. Tabandeh, V Fernicola, E. Georgin
Summary: Three European National Metrology Institutes expanded their relative humidity calibration capabilities, allowing for temperatures up to 170 degrees C, dew-point temperatures up to 150 degrees C, and pressures up to 600 kPa. A comparison of calibration set-ups showed that two institutes agreed within claimed uncertainties, while discrepancies were observed with the third institute.
Article
Agriculture, Dairy & Animal Science
Elanchezhian Arulmozhi, Jayanta Kumar Basak, Thavisack Sihalath, Jaesung Park, Hyeon Tae Kim, Byeong Eun Moon
Summary: This study investigates the use of machine learning models to predict indoor air temperature and relative humidity in barns and their impact on productivity parameters, finding that random forest regression models perform better in this regard.
Article
Environmental Sciences
Khaled Merabet, Salim Heddam
Summary: This paper proposes a hybrid air relative humidity prediction method based on preprocessing signal decomposition. The method combines empirical mode decomposition, variational mode decomposition, and empirical wavelet transform with standalone machine learning models to improve their numerical performances. The results show that the proposed hybrid models outperform the standalone models in predicting daily air relative humidity using various meteorological variables. The signal decomposition technique significantly contributes to the predictive accuracy of the hybrid models.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Construction & Building Technology
Tuomas Raunima, Anssi Laukkarinen, Antti Kauppinen, Mihkel Kiviste, Eero Tuominen, Joonas Ketko, Juha Vinha
Summary: Measurements of indoor air temperature and relative humidity in schools and day-care centers in Finnish municipal buildings with mechanical ventilation showed that the indoor air was too dry, which can have negative effects on the air quality experienced by users.
BUILDING AND ENVIRONMENT
(2023)
Article
Geochemistry & Geophysics
Qian-Yu Liao, Pei Leng, Zhao-Liang Li, Chao Ren, Ya-Yong Sun, Mao-Fang Gao, Si-Bo Duan, Guo-Fei Shang
Summary: A new method for deriving all-sky relative humidity entirely based on MODIS data was proposed in this study, showing reasonable accuracy under different aridity conditions, with stable linear relationships over time.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Construction & Building Technology
Su-Gwang Jeong, Minju Kim, Taemin Lee, Jeonghun Lee
Summary: The study evaluated the impact of installing pre-filter systems in Seoul to reduce PM2.5 levels in newly constructed buildings. Results showed that pre-filters were more effective in reducing outdoor PM2.5 levels and led to a significant decrease in indoor PM2.5 concentrations.
BUILDING AND ENVIRONMENT
(2021)