Relative Humidity Levels Research Articles

Population dynamics of the main necrophagous Diptera in the sub-Sudanese zone of Côte d’Ivoire

The objective of this work was to identify the population variation of the main necrophagous Diptera in the sub-Sudanese zone of Côte d'Ivoire. Three traps, inspired by Upton's and using pig liver and viscera as bait were placed on the site of the Botanical Garden of Peleforo Gon Coulibaly University and Lataha located 10 km from the Botanical Garden. Weekly captures were taken from October 4, 2018 to October 3, 2019. In total, 194,853 individuals from the Calliphoridae, Sarcophagidae and Muscidae were collected. Calliphoridae represented 48%, Sarcophagidae 24% and Muscidae 28% in the Botanical Garden site and in Lataha, Calliphoridae presented 52%, Sarcophagidae 27% and Muscidae 21%. Chrysomya albiceps, Sarcophaga carnaria and Musca domestica were the majority species. The numbers of these three species were higher at relative humidity levels reaching 70 to 85%. A correlation between relative humidity and the numbers of these three species was observed. Apart from relative humidity, these results show that other climatic parameters have a weak influence on the activity of Chrysomya albiceps, Sarcophaga carnaria and Musca domestica. During this study, temperature and rainfall had little influence on the variation in the numbers of these three main species of necrophagous insects. However, the numbers of the three species were correlated with relative humidity levels.

Investigating the role of temperature and moisture on the degradation of 3D-printed polymethyl methacrylate dental materials through molecular dynamics simulations

This study aimed to comprehensively investigate the degradation behavior of 3D printed polymethyl methacrylate (PMMA) dental materials, with a specific focus on the influential factors of temperature and moisture, by employing molecular dynamics simulations. Owing to their aesthetic properties, 3D-printed PMMA dental materials play a pivotal role in dental applications. However, understanding their degradation mechanisms, particularly in the context of temperature and moisture variations, is crucial for their long-term durability. A Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) was utilized for the molecular dynamics simulations. The simulation setup included temperature variations from 300 to 600 K and relative humidity (RH) levels ranging from 20 to 100%. Various mechanical properties and structural changes were analyzed to determine the degradation behavior. Energetic profiling during equilibration and the subsequent temperature variations were studied. The spatial distribution of the mean squared displacement, non-bond energy, Young’s modulus, bending stress, and volume expansion coefficient of the particles were quantitatively analyzed, revealing temperature- and moisture-dependent trends. The study concluded that temperature and moisture significantly affected the degradation behavior of 3D-printed PMMA dental materials. Higher temperatures and increased humidity levels contribute to reduced mechanical strength and altered structural properties, emphasizing the importance of controlling environmental conditions during fabrication.

Effect of heat stress, determination of temperature-humidity index

Relevance. Increased values of temperature and relative humidity of the external environment lead to negative consequences for the animal body, forcing the thermoregulation processes to be turned on. These mechanisms allow the animal organism to adapt to new environmental conditions at the expense of productivity. In these cases heat stress is observed. It is established that its manifestation is observed after 17 hours and there is a possible decrease in productivity by 35–40%. To identify the effect of heat stress, accurate determination of temperature-humidity index (THI) is necessary.Methods. The materials and methods contain the most common formulas for determining the temperature and humidity index. The equipment and software package used for the research are presented.Results. A graph of the results of South Korean studies is presented to compare the effects of heat stress on productivity. The results and discussions display a modernized formula for determining the heat stress index and figures showing the level of heat stress at different temperature and relative humidity levels.

Study and optimization of the selectivity of an odorant binding protein-based bioelectronic nose

Over the past two decades, the use of odorant-binding proteins (OBPs) for the development of biosensors and bioelectronic noses (bioeNs) aimed at detecting and analyzing volatile organic compounds (VOCs) has been the subject of considerable research. However, there is a lack of fundamental studies for better understanding the interaction between OBPs and VOCs in gas phase. In this work, we investigated the effect of two key factors, namely relative humidity (RH) level and immobilization technique, on the selectivity of two OBP-based biosensors in gas phase. Concerning the effect of RH, the results showed that our active OBP (wild-type rat OBP3) lost its selectivity at 0% RH but retained good selectivity at 30% and 50% RH. To better understand the effect of this parameter, the hydration mechanism of the OBP was studied both experimentally and through molecular dynamics simulations. The effect of a cysteine residue, genetically added to the N-terminus of OBPs to control their orientation after immobilization on the chip, was evaluated. A significant reduction in selectivity was observed in the absence of cysteine. As expected, the introduction of this amino acid enabled to control the orientation of OBPs, making their binding pocket more accessible to VOCs and favoring specific interactions. Furthermore, we demonstrated that combining OBP-based biosensors with different properties can improve the discrimination capability of our bioeN. Finally, the ability of our system to detect essential oil vapors was tested, providing preliminary evidence that our bioeN is capable of detecting VOCs in complex media.

Experimental investigation on the application of cold-mist direct evaporative cooling in data centers

The rapid development of the internet era has driven the construction of numerous data centers worldwide. In hot climate, data centers consume significant energy for cooling. Cold-mist direct evaporative cooling offers a natural cooling solution that can help reduce this energy consumption. This study investigates the temperature and relative humidity changes of natural high-temperature air after being cooled using a cold-mist direct evaporative cooling test bench. The effects of several control factors such as spray angle, spray flow rate, and air speed on the cold-mist direct evaporative cooling performance was systematically examined. The findings revealed that: (1) the optimal spray angle for cold-mist direct evaporative cooling treatment air is 65°; (2) high-temperature air between 27 °C and 37 °C can be cooled to 23.57 °C – 25.58 °C after cold-mist direct evaporative cooling treatment, with relative humidity levels of 67.0 % – 78.8 %, meeting the air supply requirements for data centers; (3) the proposed approach could reduce the data center energy consumption by 14 % – 41 %, while extending the annual natural cooling period by 3.16 % – 20.45 %.

Ultrasensitive and durable borophene-based humidity sensors for advanced human-centric applications

Borophene, a novel two-dimensional (2D) nanomaterials with high surface-to-volume ratio and abundant active sites, show great promise for humidity sensing applications, which are crucial for improving human comfort, public health, and device safety. However, traditional fabrication methods, such as drop-coating, face limitations including uncontrollable sensing layer thickness, poor water-damage resistance, and inherent variability between devices. In this work, we present a high-performance humidity sensor fabricated using borophene glass. The sensor demonstrates an impressive detection range (11–97 % RH), exceptional sensitivity (up to 1.83×105% at 97 % RH), low hysteresis (1.245 %), excellent repeatability, and relatively fast response (28.8 s)/recovery (2.6 s) times. Notably, the sensor exhibits thickness-dependent sensing performance, long-term stability, high selectivity, and water-damage resistance. First-principles calculations show that borophene exhibits an adsorption energy of 0.208 eV for H2O molecules, with the hole doping effect following adsorption driving the sensor’s response to varying relative humidity levels. The sensor’s sustained heightened sensitivity under high humidity conditions is attributed to the Grotthuss mechanism. Additionally, the sensor has been successfully integrated into various human-centric applications, including speech recognition, wireless monitoring of respiratory patterns, and non-contact switches. These advancements pave the way for the integration of borophene humidity sensors into smart devices and non-contact control systems, driving innovation in human–computer interaction and healthcare technologies.

Integrated One-Step Fabrication of Protonic Sensing Devices for Respiratory Monitoring.

The development of direct fabrication routes with seamless integration of both the macro/micropatterning process and nanostructure synthesis is crucial for the commercial realization of cost-effective nanoscale sensor devices. This, if realized, can liberate us from the conventional limitations inherent in nanoscale device manufacturing. Specifically, such fabrication routes can, in principle, address the challenges such as the complexity, multistep nature, and substantial costs associated with existing technologies, which are not suitable for widespread market adoption in everyday-use devices. Herein, we propose a novel yet facile one-step fabrication approach that simultaneously accomplishes both patterning and nanostructure synthesis by employing low-power, cost-effective laser technology with a minimal environmental footprint. Versatile in nature, this approach can enable the incorporation of diverse functionalities spanning a broad spectrum of technologies, encompassing fields such as sensors, catalysts, photonics, energy storage, and biomedical monitoring devices. As a proof of concept, using our approach, we fabricated an ultra responsive, high-speed protonic sensing device for real-time respiratory monitoring. The enhanced temporal characteristics of our as-fabricated device, particularly in the relative humidity levels of interest in breath monitoring (typically over 55%), exhibited a superior response/recovery time in rapid humidity fluctuations. We envisage that the advantages brought by the presented fabrication approach can pave the way to establish a new method for inexpensive large-scale functional-material-based device fabrication.

The impact of relative humidity on the nanoindentation relaxation in calcium silicate hydrates

Despite extensive research efforts, understanding the time-dependent behavior of concrete remains an enigma due to the complex nature of cement microstructure. In this study, the statistical nanoindentation was employed to investigate the influence of relative humidity (RH) on the relaxation behavior of calcium silicate hydrates (C-S-H) in a cement paste. Our experiments, performed at RH levels of 33 % and 86 %, revealed significant enhancements in both the indentation modulus and hardness of the C-S-H as RH increased. Remarkably, the internal water exerted a significant influence on the asymptotic relaxation behavior, displaying a clear power-law fashion. Further analysis identified the presence of short- and long-term viscoelastic behaviors within the C-S-H, distinguished by a transition observed within the initial seconds. These findings advance the understanding of nanoscale mechanisms driving concrete creep under different humidity conditions.

Advancing lettuce physiological state recognition in IoT aeroponic systems: A meta-learning-driven data fusion approach

Automatically identifying key physiological factors in plants, such as leaf relative humidity (LRH), chlorophyll content (Chl), and nitrogen levels (N), is vital for effective aeroponic management and improving growth, yield, quality, and sustainability. Meta-learning (MetaL) solutions utilize data fusion and intelligent processing, ensuring fast and consistent outcomes. This paper aims to develop a novel MetaL framework that leverages multimodal data sources—including spectral, thermal, and IoT environmental data—to enable real-time, non-invasive identification of LRH, Chl, and N content in aeroponically grown lettuce. The research examined various spectral reflectance indices (SRIs) and thermal indicators from plant characteristics. Model-based feature selection was implemented using back-propagation neural networks (BPNN), decision trees (DT), and gradient boosting machines (GBM) to identify key attributes and optimize hyperparameters. The experimental findings indicated that deploying GBM-based top variables as the foundational model, combined with BPNN as the meta-model, significantly improved the accuracy of analyzing the assigned factors. The prediction scores (R²) for LRH, Chl, and N increased to 0.875 (RMSE=0.879), 0.886 (RMSE=0.694), and 0.930 (RMSE=0.184), respectively, compared to applying BPNN-based features alone as a standalone model. Overall, the designed methodology contributes to more accurate predictions of plant physiological states, enabling proactive steps toward sustainable aeroponic agriculture.

Development of smart control system for leakage warning in compact roofs

Smart sensor technologies to monitor temperature and moisture conditions in building components can be used to give automatic warnings for abnormal high levels of moisture. Flat compact roofs are of particular interest in this context, especially due to their vulnerability to rain leakages through the roofing membrane. Installing moisture sensors in such roofs measuring relative humidity (RH) and free water may give an early warning of rain leakages or condensation owing to air leakages from indoors before damage occurs. One challenge is, however, that normal moisture redistribution in the insulation layer over the season or a day may give very high levels of RH in the top or bottom part of the insulation. A sensor system must be able to distinguish between these normal RH levels and leakage events. Together with a sensor technology and control system producer, a semi-quantitative system that defines typical or normal RH levels in the insulation layer of the roof during the year has been developed. To investigate the applicability of such a system, measurements from the compact roofs of two pilot buildings located in Norway have been analysed. The objective has been to identify connections between measured data, occurring climate conditions and seasonal variations. Results may be used to further develop and improve the algorithms of the leakage warning system.

Classroom indoor air quality and noise level assessment of different educational institutions in a university area in Bangladesh

Introduction: The classroom environment is crucial for fostering effective learning and safeguarding teacher-student health. This study assessed the Indoor Air Quality (IAQ) and noise levels in classrooms across three institutions: a university, a secondary and higher secondary school (called a school and college), and a primary school. Materials and methods: Various IAQ parameters such as Particulate Matters (PM2.5 and PM10), Carbon monoxide (CO), Carbon dioxide (CO2), Total Volatile Organic Compound (TVOC), and temperature, Relative Humidity (RH), light, and noise levels were measured using calibrated instruments from February to March 2024. Results: The air pollutants and noise levels varied among the institutions. The mean values of PM 2.5 (76.6 µg/m3) and PM (116.7 µg/m3) were highest The mean values of PM 2.5 (76.6 µg/m3) and PM (116.7 µg/m3) were highest in the primary school, while CO (0.82 ppm), light (92.9 lux), temperature (27.6 °C), and noise levels (77.6 dB) peaked in the school and college. University classrooms showed the maximum concentrations of CO2 (804.9 ppm), TVOC (32.9 ppb), and RH (58.6%). In all institutions, PM2.5, PM10, and noise levels exceeded WHO-recommended limits, whereas CO, CO2, RH, and temperature remained within their respective standards. Light levels were below Occupational Safety and Health Administration (OSHA) guidelines. Correlation analysis showed significant positive correlations between PM2.5 PM10, and CO. Hazard Quotient (HQ) values for PM 2.5 and PM10 exceeded 1.0, indicating potential health risks. Variations in pollutants and noise levels among institutions may be due to classroom facilities, student density, ventilation systems, and student activities. Conclusion: Long-term exposure to IAQ pollutants and noise levels could impair cognitive function, respiratory health, and overall well-being of the students and educators. Implementing proper ventilation (e.g., HEPA filters) systems, soundproofing acoustic panels, and continuous IAQ monitoring is recommended for a safer classroom environment.

γ- WO3 decorated MXene: An advanced nanomaterial for room temperature operable enhanced ammonia sensor

The proliferation of Internet of Things (IoT) applications necessitates the deployment of high-performance ammonia (NH3) sensors. In recent studies, Ti3C2Tx, a novel two-dimensional (2D) material, has been extensively investigated for its potential as a room temperature NH3 sensor. However, pristine MXene-based sensors have exhibited deficiencies in long-term stability and reproducibility. In response, an MXene/γ-WO3 composite has been synthesized using an ultra-sonication method to address these challenges. The resulting composite sensor has demonstrated remarkable performance, attributable to, increased active sites from defects induced by WO3, and the presence of a p-n heterojunction. Notably, electron transfer from WO3 to Ti3C2Tx has been identified as a critical contributing factor to the enhanced characteristics of these nanohybrids, as evidenced by observed alterations in binding energies for the Ti 2p and W 4 f core levels. These findings have expanded our understanding of the electrical interactions in Ti3C2/WO3 and their potential applications in diverse domains. The pristine MXene sensor exhibited a response of 59.39 % at 300 ppm at room temperature, while the composite MXene/γ-WO3 displayed a response of 92.3 %. Additionally, the response recovery time was recorded at 22 seconds and 9 seconds, respectively. The chemiresistive ammonia sensor's performance was evaluated across a range of concentrations (25–300 ppm) and relative humidity levels (11–94 % RH). The composite sensor has demonstrated reproducibility and long-term stability, coupled with high sensitivity to NH3. This manuscript aims to highlight the enhanced ammonia sensing properties and selectivity of MXene/γ-WO3 composite materials.

Visual and Gravimetric CO2 Sensing at High Humidity Levels Enabled by MOF‐804 Cofunctionalized with Ionic Liquid and m‐Cresol Purple

AbstractReal‐time monitoring of carbon dioxide (CO2) is imperative for medical diagnosis and effective environmental preservation. Despite the formidable challenge posed by the inherent chemical inertness of CO₂ molecules, a pioneering CO2 sensor based on MOF‐804 cofunctionalized with ionic liquid (IL) and m‐cresol purple (mCP) is successfully developed. By ingeniously integrating hydrogen bonding, electrostatic interactions, and hydrophobic properties within the sensitive layer, the sensor achieves a state‐of‐the‐art sensitivity (Δf = 384 Hz), an exceptionally vast detection range spanning 400–80 000 ppm, and remarkable stability with minimal sensitivity drift even at relative humidity (RH) levels exceeding 80%. Furthermore, the inherent gasochromic property, stemming from the zwitterionic mechanism, paves the way for innovative self‐sustaining CO2 test strips and groundbreaking applications, including CO2 tracking and CO2‐encrypted security labeling technology. Collectively, the realization of this ultra‐sensitive and robust CO2 monitoring approach, coupled with its CO2‐triggered visual and multifunctional capabilities, opens up novel avenues for dynamic CO2 detection, advanced military encryption strategies, and enhanced health management systems.

Utilizing IoT and Cloud Computing for Weather-Health Monitoring Application

In an era defined by increasing climate changes and an increasing importance of accurate weather information, there is a need for a smart IoT- based weather monitoring system. This paper proposes an innovative system that uses Internet of Things (IoT) technology to advance weather monitoring and global data accessibility using Cloud computing. By seamlessly connecting multiple devices, such as sensors, electronic gadgets, and automotive electronics, to the internet, this system offers a complete solution for monitoring environmental conditions such as temperature, relative humidity, pressure, and rain levels. Specialized sensors collect data, which is then transformed into graphical interface using an app, enabling real-time weather information access worldwide. This technology has the ability to rethink how we convey and analyze environmental data with optimal efficiency and reach in industries including agriculture, urban planning, and environmental research.

Factors Affecting the Adhesion of Flour Particles to Stainless-steel Surfaces and Vacuum Dry-cleaning

Recent outbreaks and recalls linked to flour-based products have highlighted the need for improved cleaning methods in low-moisture environments. The factors affecting adhesion forces of flour particles, and the vacuum cleaning methodologies to overcome these forces, need to be better understood. The objectives of this study were to: (1) Measure electrostatic charge build-up in flour under different environmental conditions (20, 40, 60% relative humidity at room temperature), (2) quantify how powder size (US standard No. 60–80 or 80–100 mesh), electrostatic charge (charged and uncharged), and relative humidity impact the force required to remove the powder from an electropolished 304 stainless steel coupon (8 × 8 × 0.2 cm), and (3) determine the most effective vacuum nozzle angle (0, 45, 90° relative to the surface) for cleaning. Chargeability (nC) of flour samples was assessed using Faraday cup electrometry, while the surface adhesion force of the flour particles was measured using a custom-built impact tester. The surface cleanliness after vacuum treatments was assessed using ATP (adenosine triphosphate) swabs and a luminometer. Charged flour samples at 20% relative humidity (RH) exhibited a significantly higher charge compared to those at 40 and 60% RH. Within the 60–80 mesh range, charged flour showed higher adhesion rates than uncharged samples at both 20 and 40% RH. However, in the 80–100 mesh range, charged flour did not show a significant difference in adhesion when compared to uncharged samples at any RH level. Additionally, at 60% RH, surface residues measured by ATP were significantly lower for a vacuum angle of 90° than for 0° across both 60–80 mesh and 80–100 mesh size ranges of wheat flour. The vacuum cleaning treatment proved capable of overcoming the increase in adhesion from triboelectric forces; however, trace flour residues were still detected on stainless steel surfaces postvacuuming, indicating that vacuuming alone may be insufficient.

Effect of temperature on moisture sorption isotherm characteristics of Thai jasmine paddy (Khao Dawk Mali 105)

Mathematical models of moisture sorption isotherms were evaluated to assess their suitability for long grain paddy (Khao Dawk Mali 105) across various temperature ranges. Paddy samples were placed in sealed containers with relative humidity controlled, ranging from 5.32% to 84.34%, and temperatures maintained from 25 to 70 °C, until equilibrium between the samples and the container's atmosphere was reached. Results showed that for both desorption and adsorption isotherms, equilibrium moisture content (EMC) decreases with an increase in temperature at constant water activity. However, at constant temperature, when water activity increases, EMC also increases. Additionally, the sorption isotherms exhibit a hysteresis effect. At 25 °C, the Henderson model proved to be the most suitable. At 40 °C, the Chung and Pfost model was best suited for adsorption, while the Henderson model was optimal for desorption. At 60 °C, the Peleg model was the most appropriate for adsorption, and the Henderson model remained the most suitable for desorption. At 70 °C, the Peleg model was the most suitable for both adsorption and desorption. The application of mathematical modeling to predict the EMC of jasmine rice at various temperature and relative humidity levels is crucial for efficient storage and processing planning within the rice export industry.

Epiphytic, Attached, and Internal Escherichia coliO157:H7 Subpopulations Associating With Romaine Lettuce Are Strain‐Dependent and Affected by Relative Humidity and Pre‐ and Postharvest Plant State

ABSTRACTRomaine lettuce is susceptible to Escherichia coli O157:H7 contamination. We evaluated strain and pre‐ and postharvest lettuce product differences in E. coli O157:H7 subpopulation distribution on romaine lettuce at two relative humidity (RH) levels. Plants of romaine lettuce cultivar 'Carlsbad' harvested and processed 'Carlsbad' leaves, and store‐bought ready‐to‐eat romaine lettuce were inoculated with E. coli O157:H7 reference strain EDL933 and romaine lettuce outbreak strain 2705C. Using four processing methods, we determined pathogen cell fractions representing All (entire population), Epiphytic (loosely attached cells), Strongly Attached + Internal (excluding loosely attached cells), and Internal (excluding epiphytic cells) subpopulations. Preharvest, 80% RH favored subpopulations in each cell fraction, compared to 40% RH (p < 0.01 for both strains) and yielded 92%–100% internalization incidence of E. coli O157:H7, compared to 50%–57% at 40% RH. Levels of internal EDL933 cells were also 1.1 log higher than 2705C cells from plants kept at 80% RH (p < 0.001). While EDL933 had lower measures of Strongly Attached + Internal cells compared to All and Epiphytic fractions (p < 0.01), 2705C yielded no difference. Taken together, data suggest that the lettuce outbreak strain had a higher propensity for strong attachment to leaves and EDL933 internalized more successfully. Moreover, the Strongly Attached + Internal fractions of both strains were lower on preharvest 'Carlsbad' compared to 'Carlsbad' processed leaves (p < 0.01), suggesting that E. coli O157:H7 attached less strongly to preharvest plants than postharvest cut and stored leaves of the same variety. Our study uncovers important factors influencing cultivar‐ and strain‐specific differences in association and internalization of enteric pathogens on leafy greens.

Fresh water production via atmospheric water harvesting using solar energy for green hydrogen production

Abstract Solar energy is used to drive an atmospheric water harvesting unit to produce fresh water needed for the electrolysis process to produce hydrogen, as well as to drive the electrolyzer. So, the system can be considered as a solar powered hybrid system for fresh water harvesting and green hydrogen production implementing the electrolysis concept. Implementation of the system specially in arid regions with high levels of water scarcity and high relative humidity levels helps in achieving SDGs 3, 7, 9, and 13 progressively, improving health and wellbeing, reducing water scarcity, using clean renewable energy, and limiting climate change. The system is proposed and investigated for the production of both fresh and clean water and green hydrogen gas. To improve the productivity of the overall system, performance enhancement of the atmospheric water harvesting subsystem is experimentally investigated to assure the reliability and continuous operation of the overall green hydrogen hybrid system. It was investigated in summer and winter using different number of porous sheet metals with the silica gel bed. The results show that the productivity of the atmospheric water harvesting system can be increased by a minimum of 6% with one mesh metal sheet and 30% with two meshes, and increases by a maxinmum of 60% with one mech and 260% with two meches.

Inactivation kinetics of dairy phages using photocatalytic paint under diverse environmental conditions and radiation sources

This article investigates the efficacy of a photocatalytic paint for bacteriophages inactivation under various levels of incident radiation flux, relative humidity and radiation sources. Two phages that infect lactic acid bacteria were selected: J-1, infective of Lacticaseibacillus casei ATCC 27139, and M13-G1b, infective of Streptococcus thermophilus G1b. Phage suspensions were deposited on coated and uncoated plates and exposed to radiation typically used for indoor illumination (λ = 360–720 nm). A first-order inactivation kinetics was proposed with respect to the Plaque Forming Units per mL (PFU/mL) that correlates the inactivation constant with the operating conditions. The kinetic constant of this novel model combines a potential function for the incident radiation flux and a logistic function for the relative humidity. The results showed that as these variables increased, phage inactivation turned higher for both uncoated and coated plates. Photonic and quantum efficiencies were also calculated for both phages, when treated with photocatalytic paint under UV-A radiation. The photonic efficiencies were 8.03 × 1012 PFU/Einstein for J-1 and 4.05 × 1012 PFU/Einstein for M13-G1b, while the quantum efficiencies were 1.19 × 1013 PFU/Einstein for J-1 and 6.03 × 1012 PFU/Einstein for M13-G1b. Good agreement was obtained between predictions of the proposed kinetic model and experimental data, with a Root Mean Square Error of 4.43 % for J-1 and 2.98 % for M13-G1b. The developed model would be useful to predict phage inactivation under diverse combinations of operating conditions levels in environments of dairy plants, different from those tested in this work.

A dynamic humidity arena to explore humidity-related behaviours in insects.

Humidity is a critical environmental factor influencing the behaviour of terrestrial organisms. Despite its significance, the neural mechanisms and behavioural algorithms governing humidity sensation remain poorly understood. Here, we introduce a dynamic humidity arena that measures the displacement and walking speed of insects responding to real-time changes in relative humidity (RH). This arena operates in a closed-loop mode, adjusting humidity based on the insect's position with 0.2% RH resolution, allowing the insect to choose its optimal humidity. It can also be set to maintain a specific RH, simulating an open-loop condition to observe insect behaviour at constant humidity levels. Using the dynamic humidity arena, we found that desiccated and starved Drosophila melanogaster search for a RH of around 65-70% at 23°C, whereas sated flies show no unique preference for any RH. If the desiccated and starved flies are rehydrated, their searching behaviour is abolished, suggesting that desiccation has a great impact on the measured response. In contrast, mutant flies with impaired humidity sensing, due to a non-functional ionotropic receptor (Ir)93a, show no preference for any RH level irrespective of being desiccated and starved or sated. These results demonstrate that the dynamic humidity arena is highly sensitive and precise in capturing the nuanced behaviours associated with hydration status and RH preference in D. melanogaster. The dynamic humidity arena is easily adaptable to insects of other sizes and offers a foundation for further research on the mechanisms of hygrosensation, opening new possibilities for understanding how organisms perceive and respond to humidity in their environment.