High Humidity Research Articles

Epidemiology of boxwood blight in western North Carolina and Virginia and evaluation of the boxwood blight infection risk model.

Boxwood blight, caused by Calonectria pseudonaviculata, is a highly invasive emerging disease. Since the first US report in North Carolina and Connecticut in 2011, boxwood blight has spread to over 30 US states, risking more than 90% of boxwood production. Our study investigated the disease field epidemiology and evaluated the boxwood blight infection risk model's prediction by analysing weekly blight monitoring data collected on detector plants exposed to the prevailing environmental conditions at two different locations (western Virginia and North Carolina) from spring through fall of 2014 to 2017. Boxwood blight was recorded in 61 of 86 weeks, with the highest infected leaf counts recorded in late summer or early fall. Rainfall, high relative humidity outside rainy periods and optimal temperatures (13.6-22.7°C) during prolonged leaf wetness (> 65h per week) had a significant positive effect on boxwood blight development. Classification analyses showed that disease predictions from the model using leaf wetness estimated by leaf wetness sensor were more closely aligned with observations from the field than predictions based on algorithms. This study improved our understanding of disease field epidemiology, provided leads to improve the existing model, and generated essential knowledge for formulating effective strategies for blight mitigation.

Impact of Heat on Respiratory Hospitalizations among Older Adults in 120 Large US Urban Areas.

Extreme heat exposure is a well-known cause of mortality among older adults. However, the impacts of exposure on respiratory morbidity across US cities and population subgroups is not well understood. A nationwide study to determine the impact of high heat on respiratory disease hospitalizations among older adults (65+) living in the 120 largest US cities between 2000-2017. Daily rates of inpatient respiratory hospitalizations were examined with respect to variations in ZIP-code-level daily mean temperature and heat index. For each city, we estimated cumulative associations (lag-days 0-6) between warm-season heat (June-September) and cause-specific respiratory hospitalizations using time-stratified conditional quasi-Poisson regression with distributed lag non-linear models. We estimated nationwide associations using multivariate meta-regression and updated city-specific associations via best linear unbiased prediction. With stratified models, we explored effect modification by age, sex, and race (Black/white). Results were reported as percent change in hospitalizations at high temperatures (95th percentile) compared to median temperatures for each outcome, demographic group, and metropolitan area. We identified 3,275,033 respiratory hospitalizations among Medicare beneficiaries across 120 large US cites between 2000 and 2017. Nationwide, 7-day cumulative associations at high temperatures, resulted in a 1.2% (0.4%, 2.0%) increase in hospitalizations for primary diagnoses of all-cause respiratory disease, primarily driven by increases in respiratory tract infections [1.8% (0.6%, 3.0%)], and chronic respiratory diseases/respiratory failure [1.2% (0.0%, 2.4%)]. Stronger associations were observed when exposure was defined using the heat index instead of temperature. Across the 120 cities, we observed considerable geographic variation in the relative risk of heat-related respiratory hospitalizations, and we observed disproportionate burdens of heat-related respiratory hospitalizations among the oldest beneficiaries (85+ years), and among Black beneficiaries living in South Atlantic cities. During the 18-year study period, there were an estimated 11,710 excess respiratory hospitalizations due to heat exposure. Results suggest that high temperature and humidity contribute to exacerbation of respiratory tract infections and chronic lung diseases among older adults. Geographic variation in heat-related hospitalization rates suggests that contextual factors largely account for disproportionate burdens, and area-level influences should be further investigated in multi-city studies.

A seed-specific DNA-binding with One Finger transcription factor, RPBF, positively regulates galactinol synthase to maintain seed vigour in rice.

Seed vigour and longevity are intricate yet indispensable physiological traits for agricultural crops, as they play a crucial role in facilitating the successful emergence of seedlings and exert a substantial influence on crop productivity. Transcriptional regulation plays an important role in seed development, maturation, and desiccation tolerance, which are important attributes for seed vigour and longevity. Here, we have investigated the regulatory role of the seed-specific DNA binding with the One Finger (DOF) transcription factor and the RPBF (Rice P-box Binding Factor) in seed vigour. RPBF modulates the transcription of galactinol synthase and improves seed vigour. The promoter region of Galactinol synthase (GolS)-encoding genes from different species was enriched with DOF binding sites, and the expression levels of both RPBF and OsGolS were found to enhance during seed development. Furthermore, direct interaction of RPBF with OsGolS promoter has been demonstrated through multiple approaches: yeast one-hybrid (Y1H) assays, in planta promoter-GUS assays, dual luciferase assay, and in silico molecular docking. To assess functionality, Agrobacterium-mediated genetic transformation of rice was performed to generate the RNAi lines with reduced RPBF expression. In these RNAi lines, a reduction in both galactinol and raffinose content was observed. Since galactinol and raffinose are known contributors to seed vigour, the T2-transgenic lines were assessed for vigour and viability. For this, RNAi seeds were subjected to accelerated ageing by exposing them to high relative humidity and temperature, followed by scoring the germination and viability potential. Tetrazolium and seed germination assay revealed that the RNAi seeds were more sensitive to ageing compared to their wild-type and vector control counterparts. Collectively, this is the first report demonstrating that the DOF transcription factor RPBF controls the seed vigour through transcriptional regulation of galactinol synthase.

Neutron tomography and image registration methods to study local physical deformations and attenuation variations in treated archaeological iron nail samples

This study presents a preliminary examination of the effects of environment changes post-excavation on heavily corroded archaeological Roman iron nails using neutron tomography and image registration techniques. Roman nails were exposed to either a high relative humidity environment, or fast thermal drying as primary experiments to show the power of this imaging technique to monitor and quantify the structural changes of corroded metal artifacts. This research employed a series of pre- and post-treatment tomography acquisitions (time-series) complemented by advanced image registration methods. Based on mutual information (MI) metrics, we performed rigid body and affine image registrations to meticulously account for sample repositioning challenges and variations in imaging parameters. Using non-affine local registration results, in a second step, we detected localized expansion and shrinkage in the samples attributable to imposed environmental changes. Specifically, we observed local shrinkage on the nail that was dried, mostly in their Transformed Medium (TM), the outer layer where corrosion products are cementing soil and sand particles. Conversely, the sample subjected to high relative humidity environment exhibited localized expansion, with varying degrees of change across different regions. This work highlights the efficacy of our registration techniques in accommodating manual removal or loss of extraneous material (loosely adhering soil and TM layers around the nails) post-initial tomography, successfully capturing local structural changes with high precision. Using differential analysis on the accurately registered samples we could also detect and volumetrically quantify the variation in moisture and detect changes in active corrosion sites (ACS) in the sample. These preliminary experiments allowed us to advance and optimize the application of a neutron tomography and image registration workflow for future, more advanced experiments such as humidity fluctuations, corrosion removal through micro-blasting, dechlorination and other stabilization treatments.

Mechanistic effects of graphitization and oxygen functional groups on benzene competitive adsorption of porous carbon under high humidity conditions

Porous carbon is an ideal adsorbent for the elimination of volatile organic compounds (VOCs) attributed to their price, availability and excellent adsorption capacity. However, there are significant variation in the adsorption capacity and adsorption selectivity of different precursors for VOCs under humid conditions after modification because of the differences in their own structural properties. In this study, graphitized hydrophobic porous carbon with excellent specific surface area was successfully synthesized by selecting bamboo fiber, maize, coconut husk and coal as precursors and potassium hydroxide as an activator. Among them, the dynamic adsorption capacity of benzene in the sample with bamboo fiber as precursor was maintained at 74.7% under the high humidity condition (RH90%) compared with the dry state (RH0%). Grand Canonical Monte Carlo (GCMC) simulations and weak interaction force analyses showed that enhanced dispersion attraction between graphitized carbon surfaces and benzene molecules in comparison to disordered carbon surfaces. The existence of oxygen functional groups enhanced the interaction between porous carbon and water through hydrogen bonding leading to preferential adsorption of water molecules, which resulting in the decrease of their adsorption performance in wet condition. This research provided theoretical and experimental views of the effects of graphitization and oxygen functional groups on the competitive adsorption capture of benzene and water by porous carbon, which further provided a reliable approach to synthesizing porous carbon with high adsorption capture for benzene removal in high humidity environments.

Sustainable commercially-scaled greenhouse building cooling solution: Integrating PCM storage, desiccant wheels, and absorption chillers powered by dual-source solar/biomass energy

This research aims to address the critical need for sustainable cooling systems in greenhouses, particularly relevant in mitigating global warming impacts and enhancing food security worldwide. The urgency becomes more pronounced in locations experiencing high ambient temperature and humidity. The study introduces an innovative cooling system integrating Phase Change Material, a desiccant wheel, and an absorption chiller, powered by solar and biomass energy. This novel system aims to efficiently regulate temperature and humidity in greenhouse environments. The performance of this system is examined in Abu Dhabi, Doha, and Riyadh during the summer months, utilizing TRNSYS software for a medium-scale greenhouse model. Additionally, a comprehensive Life Cycle Assessment is carried out to quantify the environmental impacts of the proposed system. Results indicate that in Abu Dhabi, the system yields a Coefficient of Performance (COP) of 1.108, effectively maintaining indoor climate conditions. Similarly, Doha and Riyadh exhibit COPs of 1.015 and 0.827, respectively. In terms of solar energy utilization, Abu Dhabi demonstrates a solar fraction of 40.4, corresponding to the lowest Global Warming Potential (GWP) at 0.106 kg CO2eq per 1 kW of provided cooling capacity. Conversely, Riyadh records the highest GWP at 0.149 kg CO2eq, followed by Doha at 0.118 kg CO2eq. The Energy Payback Time (EPBT) for the system in Abu Dhabi is calculated to be 3.96 years, the shortest among the examined cities. In comparison, Doha and Riyadh present longer EPBTs of 4.48 and 5.83 years, respectively. These findings suggest that the proposed system offers a viable and environmentally friendly alternative to conventional greenhouse cooling approaches.

Hydrophobic hyper-cross-linked polymer shells encapsulating dispersed nanoscale CuS boosting mercury immobilization

Metal sulfides (MSs) hold significant promise for environmental remediation but are hindered by their low accommodation capacity and poor water resistance. Herein, this work reports a hybrid strategy to address these limitations by assembling highly dispersed CuS nanoparticles within the hyper-cross-linked polymer (HCP). Benefiting from the super-hydrophobicity and well-developed porosity of HCP, alongside the high dispersion and multiple active sites of CuS nanoparticles, the resultant CuS@HCP exhibits exceptional water resistance, enhanced surface area, high mass transfer ability, and substantial Hg0 adsorption capacity. The Hg0 adsorption capacity (Q90) of CuS@HCP3 reaches 1.25 and 1.391 mg/g under N2 and simulated flue gas, respectively. Notably, the normalized Q90 of coated CuS surpasses that of pristine CuS by 25-fold under N2 + 15 % H2O and its durability outstrips most previously reported mineral sulfides even in complex simulated flue gas. Universal research confirms MSs@HCP (M = Zn, Sn, and Fe) equally demonstrate over 15-fold increment in Hg0 retention under high humidity conditions compared to the pristine MSs. Such HCP hybrid strategy universally and effectively optimizes the accommodation capacity and water resistance of MSs, endowing MSs@HCP broad application prospects.

Improving the removal of fine particles in cyclone using heterogeneous vapor condensation enhanced by atomization

Using a heat exchanger to cool high humidity flue gas can create a supersaturated water vapor environment, allowing fine particles to grow into large droplets by heterogeneous vapor condensation, which is conductive to the removal of fine particles by traditional equipment. However, due to the limited condensable vapor obtained by cooling, this technology can only be used in the flue gas with low particle concentration. In this study, atomization droplets were added before the heat exchanger to improve the effect of heterogeneous vapor condensation at high particle concentration, and then coupled with a cyclone separator, which was used for the deep treatment of the flue gas after the wet dedusting system. The particle removal characteristics were investigated through laboratory experiments and bypass experiments in a metallurgical company. The experimental results show that the application of atomization-heterogeneous condensation reduced the particles concentration after cyclone by 74.2 % compared with that of single heterogeneous condensation. Temperature-drop and atomized volume affected the removal of particles with size < 2 μm and > 2 μm, respectively. The industrial flue gas bypass experiment indicated that the system had strong adaptability to fluctuating conditions. When the inlet particle concentration did not exceed 2000 mg/Nm3, the outlet particle concentration can be maintained within 20 mg/Nm3.

Heat Strain in Different Hot Environments Hiking in Wildland Firefighting Garments.

Wildland firefighters can work at high intensity in hot environments for extended periods of time. The resulting heat strain may be modified by the environmental conditions (i.e., ambient temperature and humidity [RH]) even at equal wet-bulb globe temperatures. This investigation assessed if a hot and dry condition would create greater strain than moderate and high humidity at equivalent wet-bulb globe temperature (28°C). Twelve participants (age 24±2 y) walked at 40-50% maximum aerobic capacity for 90 and 40 min separated by a 20 min rest in dry (40°C, 20% RH), moderate-humidity (34°C, 50% RH), and high-humidity (29°C, 90% RH) conditions wearing fire resistant jacket, pants, gloves, and helmet with the neck and face exposed. Peak core temperature was higher in moderate-humidity (38.9±0.2°C, p=0.01) and high-humidity (38.9±0.6°C, p<0.01) than dry condition (38.5±0.3°C). Average net heat gain was less in dry (33±22 W) compared to moderate-humidity (38±23 W, p<0.01) and high-humidity (39±28 W, p<0.01). Peak heart rate (174±14 bpm, p=0.94), Physiological Strain Index (7.7±1.4 score, p=0.99), perceived exertion (8±2 rating, p=0.97), and Perceptual Strain Index (7.3±1.6 score, p=0.99) were not different in high-humidity compared to the dry condition (167±19 bpm, 6.9±1.3 score, 6±2 rating, 7.3±1.7 score, respectively). Whole-body sweat rate (15±6 mL/min, p=0.58) and thermal sensation (7±1 rating, p=0.37) were not different. Hiking in a humid condition while wearing protective garments creates greater exertional heat strain compared to a dry condition of equivalent wet-bulb globe temperature. Wildland firefighters should consider extra strategies to mitigate hyperthermia when humidity is high.

Unraveling the regional environmental ecology dominated baijiu fermentation microbial community succession and associated unique flavor

Chinese baijiu as one of the famous distilled liquor in which fermented in open environments, with various microorganisms (i.e., bacteria, fungi, and yeast) involved in their brewing process, and created corresponding unique flavor. However, the sources of environmentally enriched microbial communities associated with liquor fermentation are still being characterized yet. Given the dependence of microbial growth and reproduction on environmental ecology, it is important to understand the correlation between baijiu fermentation microbial community and surrounding environmental ecology (i.e., temperature, humidity, wind, and precipitation). This study systematically overviewed the sources of microorganisms in the Jiang-flavor-Baijiu fermentation system. The results showed that microorganisms in baijiu brewing (i.e., mold, lactic acid bacteria, and yeast) mainly originated from surrounding environmental matrices, including the air (i.e., Yeast, Streptomyces and Bacillus), soil (i.e., Xanthomonas, Methanococcus and Comamonas) and water (i.e., Flavobacterium, Acinetobacter, and Pseudomonas) via atmospheric transport, raw material transfer and surface runoff. In addition, the unique baijiu fermentation microbial community diversity depends on local geology and meteorological conditions, highlighting that the structural stability and diversity of the microorganisms in the Baijiu brewing process dominated by local environmental ecology. We also explored the regional environmental conditions on the microbial community and found that the unique Jiang-flavor-Baijiu fermentation microbial community diversity depends on local geology and meteorological conditions. The Jiang-flavor-Baijiu workshop is located in the basin of the middle-and low latitude mountainous areas, with sufficient solar irradiation and rainfall, high air humidity, and low wind speed that favor the growth and propagation of Baijiu fermentation microorganisms. Therefore, the obtained conclusions provide new insights unraveling the key factor controlling the unique flavor of Chinese Baijiu, where protecting the ecology of baijiu brewing-regions is fundamental for maintaining the long-term quality of baijiu.

Experimental Study based on Case Analysis for Efficient Management of Smoke Detectors

This paper presents an experimental study aimed at developing effective management strategies for smoke detectors under various environmental conditions. Through surveys and expert consultations, the primary causes of unwanted fire alarms were identified, and scenarios involving humidity, cooking smoke, and dust were selected for re-enactment experiments. The study investigated the operational changes in smoke detectors under varying humidity levels and conducted tests under both normal and humid indoor conditions for cooking smoke. Additional experiments were performed on smoke detectors coated with dust to observe their performance under different humidity and smoke conditions. As a result, it was found that the response time of smoke detectors varied depending on the level of moisture present, the amount of smoke generated, and the accumulation of dust. In conclusion, the study experimentally confirmed that smoke detectors should not be installed in areas exposed to high humidity and highlighted the importance of regular inspection and cleaning to minimize unwanted fire alarms.

Geo-climatic factors co-drive the phenotypic diversity of wild hemp (Cannabis sativa L.) in the Potohar Plateau and Lesser Himalayas

Hemp (Cannabis sativa L.) is an annual, and dioecious herb belonging to the Cannabaceae family. This plant is native to Central and Southeast Asia. The wild races of this species are commonly growing in Khyber Pakhtunkhwa and Punjab provinces, as well as in Islamabad, Pakistan. This study provides crucial insights into how environmental variables influence the wild hemp populations, which can be utilized in for conservation and breeding. The present study was aimed at evaluating the effects of key environmental factors such as altitude, geographical location, precipitation, relative humidity, maximum, minimum, and average temperature on 16 morpho-agronomic traits of a wild population of hemp growing in the Potohar Plateau and Lesser Himalayas. Our findings indicated that high relative humidity (> 64%), low average temperature (< 15 °C), intermediate average temperature (19–22 °C), and high average temperature (> 22 °C) played significant roles in determining the distribution pattern of the wild hemp. Correlation analysis demonstrated that average annual temperature contributed a higher percentage of variation in phenotypic diversity than geographic variables. Additionally, cluster analysis indicated three groups for the selected 35 populations. Clustering and Principal Component Analysis (PCA) of the morpho-agronomic traits indicated that group 1 from the Lesser Himalayas showed high relative humidity (> 64%) and low average temperature (< 15 °C). Conversely, Group 2 populations from the Potohar Plateau demonstrated intermediate average temperature (19–22 °C). There is an existence of Group 3 in the Potohar Plateau with a high average temperature (> 22 °C) compared to Group 1 and Group 2. Our examination highlights the complex interplay between ecological factors, and morphological attributes in native landraces of Cannabis sativa, giving significant insight into knowledge for preservation and breeding initiatives. A study of genetic diversity could complement morpho-agronomic traits in future research to learn more about how genetic variation affects environmental adaptation.

Bioecology of Cinnamomum culitlawan (L.) J.Presl (1825) Endemic Species on Halmahera Island

Cinnamomum culitlawan (L.) J. Presl (1825) is an endemic plant belonging to the Lauraceae family. The plant growth is found in Indonesia, especially in Maluku and Papua. This study aims to: (1) understand the taxonomy of C. culitlawan; (2) find out its habitat, environmental adaptation, and ecological role; and (3) find out its utilization and ethnobotany. This study was conducted by combining the literature review method with the survey method. Efforts to understand the taxonomy, utilization, and ethnobotany of C. culitlawan through a literature review. Each plant specimen found in the documentation was observed for its distribution, habitat, adaptation, and interaction. Taxonomic and ethnobotanical studies were conducted by literature review. The results of the study showed that C. culitlawan has 12 synonyms, namely Benzoin gracile (Nees) Kuntze; C. culiban Raf.; C. culitlawan var. rubrum (Blume) Meisn.; C. rubrum Blume; Daphnidium gracile Nees; Laurus culiban L.; Persea culilawan (L.) Bisch.; Laurus culilawan Nees; Laurus culawang Nees; Laurus culitlaban Roxb.; Laurus culitlawan L.; Laurus glauca Nees; Laurus gracilis Meisn.; and Persea culilawan (L.) Bisch. Some researchers wrote it with the species name Cinnamomum culilawan Blume, a synonym that has not been verified in WFO. Generally lives in low to medium plains, in areas with high rainfall. C. culitlawan has adapted to high humidity and grows in soil with high humus content. C. culitlawan has complex interactions with other species, including pollinating insects and soil organisms. C. culitlawan has important value in ethnobotany aspects, including traditional medicine, culinary, and cultural rituals.

Constructing Long and Stable Ag‐Al2O3 Core–Shell Nanowires for Humidity Sensing and Triboelectric Energy Generation

Silver nanowires (AgNWs) are a promising alternative material to indium tin oxide as flexible transparent electrodes owing to their excellent optoelectrical properties and mechanical performance. However, the main challenge is the poor stability under diverse environments, ranging from high humidity, chemical exposure, and dynamic mechanical deformation. Herein, ultralong AgNWs (≈100 μm) have been synthesized via controlling growth kinetics by a facile acetic acid‐assisted solvothermal method, further decorated with a thin Al2O3 layer by electrodeposition to form a core–shell architecture. The resultant films based on Ag‐Al2O3 core–shell nanowires (NWs) possess a higher conductivity while preserving the optical transparency due to the enhanced NWs contact. More importantly, the constructed films exhibit strong resistance to various conditions, such as exposure to high temperature/humidity and immersion in NaCl, HCl, and Na2S solutions. The laser‐etched interdigital electrodes based on the chemically stable AgNWs are further integrated with graphene oxide layer for humidity sensing and respiration monitoring. Furthermore, the developed NWs with superior mechanical stability are constructed as triboelectric nanogenerators for electricity generation, and reliable output performance has been demonstrated. This work provides a convenient, scalable, and cost‐effective solution that offers great potential for designing robust, transparent electrodes for next‐generation flexible electronics.

High-yield atmospheric water capture via bioinspired material segregation.

Transforming atmospheric water vapor into liquid form can be a way to supply water to arid regions for uses such as drinking water, thermal management, and hydrogen generation. Many current methods rely on solid sorbents that cycle between capture and release at slow rates. We envision a radically different approach where water is transformed and directly captured into a liquid salt solution that is suitable for subsequent distillation or other processing using existing methods. In contrast to other methods utilizing hydrogels as sorbents, we do not store water within hydrogels-we use them as a transport medium. Inspired by nature, we capture atmospheric water through a hydrogel membrane "skin" at an extraordinarily high rate of 5.50 kgm[Formula: see text]d[Formula: see text] at a low humidity of 35%. and up to 16.9 kgm[Formula: see text]d[Formula: see text] at higher humidities. For a drinking-water application, calculated performance of a hypothetical one-square-meter device shows that water could be supplied to two to three people in arid environments. This work is a significant step toward providing new resources and possibilities to water-scarce regions.

Selective Identification of Hazardous Gases Using Flexible, Room-Temperature Operable Sensor Array Based on Reduced Graphene Oxide and Metal Oxide Nanoparticles via Machine Learning.

Selective detection and monitoring of hazardous gases with similar properties are highly desirable to ensure human safety. The development of flexible and room-temperature (RT) operable chemiresistive gas sensors provides an excellent opportunity to create wearable devices for detecting hazardous gases surrounding us. However, chemiresistive gas sensors typically suffer from poor selectivity and zero-cross selectivity toward similar types of gases. Herein, a flexible, RT operable chemiresistive gas sensors array is designed, featuring reduced graphene oxide (rGO) and rGO decorated with zinc oxide (ZnO), titanium dioxide (TiO2), and tin dioxide (SnO2) nanoparticles (NPs) on a flexible polyimide (PI) substrate. The sensor array consists of four different sensing layers capable of the selective identification of various hazardous gases such as NO2, NO, and SO2 using machine learning (ML). The gas sensor array exhibits a stable response even when mechanically deformed or exposed to high humidity (up to 60%). Each gas sensor, due to the different metal oxide NPs, shows unique responses in terms of sensitivity, responsiveness, response time, and recovery time to different gases. Consequently, the sensor array generates distinct response patterns that effectively differentiate between the target gases. By leveraging these distinctive recovery patterns and employing a data fusion approach in ML, specific concentrations of target gases can be distinguished. Using ML with fused array sensing data, the training and test accuracies achieved were 98.20 and 97.70%, respectively. This innovative combination of sensor arrays and ML offers significant potential for selective gas detection in environmental monitoring and personal safety applications.

Unveiling the germination patterns of Alternaria porri (Ellis) by using regression analysis and hydrothermal time modeling

Purple blotch disease is a major fungal disease of Allium cepa L. plants which is caused by the fungus Alternaria porri. The best conditions for the growth of Alternaria porri are temperatures between 22 °C and 25 °C and relatively high humidity. The Hydrotime, Thermal Time, and Hydrothermal Time models were used to measure different parameters of seed germination; therefore, we used them to measure the interactive effects of temperature and water potential on the germination conidia of Alternaria porri. The laboratory experiments were carried out at five constant temperatures, between 5 and 30 °C, and five different water potentials between 0 MPa and − 6 MPa. The germination of Alternaria porri conidia was highest at 25 °C and 0 MPa and lowest at 5 °C and − 6 MPa. The percentage of conidia germination decreased rapidly after 25 oC. Conidia germination was also affected by different water potentials, decreasing at lower water potential. Models based on HTT showed a reasonable fit to the germination and growth rate datasets. The best fitting model for conidia germination (R2 = 0.98491) was based on variable base and maximum temperature as a function of water potential. Based on the TT, HT, and models, the highest and lowest values for θT1 were observed at -6.0 MPa at 30 °C, and 0 MPa at 5 °C and the highest and lowest θT2 values were recorded at -6.0 MPa at 5 °C and 0 MPa at 30 °C while the lowest and highest θH values were recorded at -6.0 MPa at 5 °C and 0 MPa at 25 °C, respectively, for the HTT model, the predicted θHTT average value is 16.32 (MPa°Ch-1). Based on the statistical analysis, the cardinal hydrothermal time constant (θHTT) accurately explains the interactive effect of T and Ψ on the germination of Alternaria porri conidia under different environmental conditions.

Color/Transparent Bi‐Customizable Solar Antifogging Nanofilms

AbstractAlmost all reported solar anti‐/defogging surfaces are black and opaque. However, aesthetics and transparency are preferred to enhance security, privacy, and visual experience without sacrificing antifogging in some practical scenarios, such as automotive windshields, architectural glass facades, and sports goggles. Herein, a color and transparency bi‐customizable solar antifogging heterostructure nanofilms is reported, which only consists of a Ti–TiOx layer for partial visible light transmission and a narrow bandgap Ti2O3 layer for broadband sunlight absorption. By precisely controlling each monolayer thickness, various vibrant structural colors (covering yellow/green/purple/blue) through interference effects, along with tunable visible light transparency (from 0% to 30%), and broadband solar absorption (up to 90%) are obtained, providing personalized options for various applications. Simultaneously, the nanofilms exhibit remarkable photothermal performance (110.3 °C under 1 kW m−2 irradiation) compared to blank samples, demonstrating sustained and superior defogging (3.5‐fold improvement) and antifogging capabilities, even in extremely cold (–20 °C) or high temperature and high humidity (50 °C, 100%) conditions. Importantly, the nanofilms are just 174 nm thick, and can be easily upgraded and scalable fabricated by sputtering on various rigid, flexible and portable substrates, such as glass, metals, textiles, plastics, enabling a wide range of direct applications.

Transfer Learning‐Assisted Porous Polymer Humidity Sensor for Powered Air‐Purifying Mask

Masks protect respiratory health in the coal, oil, and gas industries. However, prolonged exposure to high humidity inside masks can cause discomfort and increase the risk of respiratory diseases. To address the issue, in this work, a porous polymer humidity sensor suitable for monitoring respiratory changes in high humidity environment is prepared and integrated into the power air‐purifying mask. Combined with the transfer learning algorithm, the problem with respiratory resistance caused by delayed air supply due to signal processing in the traditional power air‐purifying mask is overcome, and the respiratory signal is effectively predicted in advance, so as to achieve real‐time on‐demand air supply. The brief process is as follows: A porous polymer humidity sensor with fast response/recovery times (2.94/4.86 s) at 95% relative humidity (RH) is developed for monitoring respiratory rate changes in high humidity environments. By integrating this sensor with a powered air‐purifying system and employing a transfer learning algorithm, the system predicts respiratory signals and adjusts the air supply in real‐time. This reduces mask humidity from 95% RH to 40–50% RH in 1.8 s, ensuring comfortable, low‐resistance breathing for workers.This work will be conductive to the development of comfortable poweredair‐purifying respirators with low resistance and humidity.

A Drosophila-inspired intelligent olfactory biomimetic sensing system for gas recognition in complex environments

The olfactory sensory system of Drosophila has several advantages, including low power consumption, high rapidity and high accuracy. Here, we present a biomimetic intelligent olfactory sensing system based on the integration of an 18-channel microelectromechanical system (MEMS) sensor array (16 gas sensors, 1 humidity sensor and 1 temperature sensor), a complementary metal‒oxide‒semiconductor (CMOS) circuit and an olfactory lightweight machine-learning algorithm inspired by Drosophila. This system is an artificial version of the biological olfactory perception system with the capabilities of environmental sensing, multi-signal processing, and odor recognition. The olfactory data are processed and reconstructed by the combination of a shallow neural network and a residual neural network, with the aim to determine the noxious gas information in challenging environments such as high humidity scenarios and partially damaged sensor units. As a result, our electronic olfactory sensing system is capable of achieving comprehensive gas recognition by qualitatively identifying 7 types of gases with an accuracy of 98.5%, reducing the number of parameters and the difficulty of calculation, and quantitatively predicting each gas of 3–5 concentration gradients with an accuracy of 93.2%; thus, these results show superiority of our system in supporting alarm systems in emergency rescue scenarios.