Assessment of monthly runoff simulations based on a physics-informed machine learning framework: The effect of intermediate variables in its construction.

Hydrological forecasting is of great importance for water resources management and planning, especially given the increasing occurrence of extreme events such as floods and droughts. The physics-informed machine learning (PIML) models effectively integrate conceptual hydrologic models with machine learning (ML) models. In this process, the intermediate variables of PIML models serve as bridges between inputs and outputs, while the impact of intermediate variables on the performance of PIML models remains unclear. To fill this knowledge gap, this study aims to encompass the construction of PIML models based on various hydrologic models, conduct comparative analyses of different intermediate variables based on a case study of 205 CAMELS basins, and further explore the relationship between the performance of PIML models and catchment characteristics. The optimal ML model for constructing PIML is first selected among four ML models within the 205 basins. The PIML models are then developed based on five monthly water balance models, namely TM, XM, MEP, SLM, and TVGM. To quantify the potential impact of difference in intermediate variables, two sets of experiments are further designed and performed, namely S1 with actual evapotranspiration as the intermediate variable and S2 with soil moisture as the intermediate variable. Results show that five PIML models generally outperformed the optimal standalone ML models, i.e., the Lasso model. Specifically, regardless of the choice of intermediate variables, the PIML-XM model consistently outperformed the other models within the same basins. Almost all constructed PIML models are affected by the intermediate variables in monthly runoff simulations. Typically, S1 exhibited better performance compared to S2. A greater impact of aridity index, forest fraction, and catchment area on model performance is observed in S2. These findings improve our understanding of constructing PIML models in hydrology by emphasizing their excellent performance in runoff simulations and highlighting the importance of intermediate variables.

Performance assessment of a refrigeration system with an integrated condenser under different environmental conditions.

This paper presents a workable vapour compression system (VCS) for evaluating the performance of a refrigeration system with an integrated condenser that uses a long-term alternative refrigerant to halocarbon as a heat transfer medium (R600a). India's refrigeration system uses halocarbon refrigerants due to their excellent thermophysical and thermodynamic properties. Greenhouse gas emissions from halocarbon refrigerants and fossil fuel combustion contribute to global warming that engenders climate change and the deterioration of the ecosystem. The halocarbon refrigerant was discontinued based on high global warming potential. The system was investigated under various ambient temperatures of 16, 20, 24, and 28 °C (oC). The performance of the VCS was analyzed using the parameters of coefficient performance, compressor work, and pull-down time (PDT). The experimental result shows that the vapour compression system obtained its best PDT, enhanced coefficient of performance, and energy reduction when the ambient temperature was 20 °C.

Environmental controls on the seasonal variations of diatoms and dinoflagellates in the Qingdao coastal region, the Yellow Sea.

Diatoms and dinoflagellates are two typical functional groups of phytoplankton assemblages, which play a crucial role in the structure and functioning of most marine ecosystems. To date, a novel challenge in ecology and biogeochemistry is to address the influences of environmental changes associated with climate change and human activities on the dynamics of diatoms and dinoflagellates. However, the knowledge of the key environmental factors controlling the diatom-dinoflagellate dynamics remains to be improved, particularly in the coastal ecosystems. Therefore, we conducted four cruises along the Qingdao coastline in spring, summer, autumn, and winter 2022 to explore how diatoms and dinoflagellates varied in response to regional environmental changes. The results showed that the phytoplankton communities were dominated by diatoms and dinoflagellates in terms of abundance and species diversity throughout the year in the study region. Yet, there were significant seasonal variability of diatoms and dinoflagellates across the four seasons. For example, diatom species was the most diverse during autumn, and the higher average abundance was observed in the fall and winter. In contrast, the average abundance of dinoflagellates was maximum during the summer and minimum in the autumn season. Moreover, the abundance and species ratios of diatoms/dinoflagellates (dia/dino) also showed significant seasonal variations in the region. The dia/dino abundance ratio was lowest in summer, while the dia/dino species ratio showed an increasing trend from spring to fall and a slight descending trend during winter. Based on the redundancy analysis, we revealed that diatoms and dinoflagellates responded differently to various environmental variables in different seasons, of which temperature and nutrients (especially dissolved inorganic nitrogen, DIN) had highly significant correlations with both the dia/dino abundance and species ratios. Thus, we suggested that temperature and DIN were the key factors controlling the seasonal dynamics of diatoms and dinoflagellates in the Qingdao coastal area.

A scoping review of triatomine control for Chagas disease prevention: current and developing tools in Latin America and the United States.

Chagas disease is an infectious disease of human and animal health concern, with 6-8 million chronic human infections and over 50,000 deaths throughout the Americas annually. Hematophagous insects of the subfamily Triatominae, also called kissing bugs, vector the protozoan parasite, Trypanosoma cruzi Chagas (Trypanosomatida: Trypanosomatidae), that causes Chagas disease. Despite the large human health burden, Chagas disease is a neglected tropical disease with inadequate funding for research and preventive practices. Given the resource-poor environment of most agencies trying to protect public health, it is critical to consider all control options for reducing vector populations and the risk of human exposure to T. cruzi to identify the most appropriate tools for each context. While numerous triatomine control methods exist, the literature lacks a compilation of the strategies used, a critical examination of their efficiency, and a particular focus on triatomine control in the United States compared to elsewhere in the Americas. Here, we present a review of the literature to assess historical intervention strategies of existing and developing triatomine control methods. For each method, we discuss progress in the field, future research to further advance the method, and limitations. While we found that pyrethroid insecticide is still the most commonly used method of triatomine and Chagas disease control, we suggest that complementing these techniques with alternative control methods in development will help to achieve Chagas disease reduction goals.

Risk Factors and Environmental Preventive Actions for Aspergillosis in Patients with Hematological Malignancies.

(1) Background: Aspergillus spp. is a widely distributed filamentous fungus in the environment due to its high sporulation capacity. Currently, invasive aspergillosis (IA) is the most common invasive fungal infection in patients with hematologic malignancies, with high rates of mortality and morbidity. The multifactorial nature of the disease requires appropriate risk stratification to enable the most appropriate preventive measures to be adapted and implemented according to the characteristics of the patient. In this sense, the present research aims to identify recent risk factors and environmental control measures against invasive aspergillosis to establish preventive actions to reduce the incidence of invasive aspergillosis in hospitals. (2) Methods: We conducted a qualitative systematic review of the scientific literature on environmental risk factors and preventive measures for invasive aspergillosis in patients with hematologic malignancies. The Medline, Cochrane, and Scopus databases were consulted, following the PRISMA and STROBE guidelines. (3) Results: Adequate implementation of environmental control measures is presented as the most efficient intervention in terms of prevention to decrease the incidence of invasive aspergillosis in hospitals. Neutropenia, fungal contamination, insufficient environmental control measures in hospital and home settings, length of hospital stay, and anemia, are identified as independent risk factors. We show that HEPA, LAF, and Plasmair® systems are suitable methods to reduce the concentration of airborne fungal spores. Antifungal prophylaxis did not significantly influence IA reduction in our study. (4) Conclusions: Proper professional training and environmental control measures in hospitals are essential for the prevention of invasive aspergillosis. We should optimize risk stratification for patients with hematologic malignancies. Antifungal prophylaxis should be complementary to environmental control measures and should never be substituted for the latter. Studies should also be undertaken to evaluate the efficiency of environmental control measures against IA at patients' homes.

Pervasive soil phosphorus losses in terrestrial ecosystems in China.

Future phosphorus (P) shortages could seriously affect terrestrial productivity and food security. We investigated the changes in topsoil available P (AP) and total P (TP) in China's forests, grasslands, paddy fields, and upland croplands during the 1980s-2010s based on substantial repeated soil P measurements (63,220 samples in the 1980s, 2000s, and 2010s) and machine learning techniques. Between the 1980s and 2010s, total soil AP stock increased with a small but significant rate of 0.13 kg P ha-1 year-1 , but total soil TP stock declined substantially (4.5 kg P ha-1 year-1 ) in the four ecosystems. We quantified the P budgets of soil-plant systems by harmonizing P fluxes from various sources for this period. Matching trends of soil contents over the decades with P budgets and fluxes, we found that the P-surplus in cultivated soils (especially in upland croplands) might be overestimated due to the great soil TP pool compared to fertilization and the substantial soil P losses through plant uptake and water erosion that offset the P additions. Our findings of P-deficit in China raise the alarm on the sustainability of future biomass production (especially in forests), highlight the urgency of P recycling in croplands, and emphasize the critical role of country-level basic data in guiding sound policies to tackle the global P crises.

Environmental management of asthma in clinical practice: Results from the 2012 National Ambulatory Medical Care Survey.

Background: The National Asthma Education and Prevention Program guidelines emphasize environmental control as an integral part of asthma management; however, limited national-level data exist on how clinicians implement environmental control recommendations. Objective: We analyzed data on clinicians' self-reported use of recommended environmental control practices in a nationally representative sample (n = 1645) of primary care physicians, asthma specialists, and advanced practice providers from the National Asthma Survey of Physicians, a supplemental questionnaire to the 2012 National Ambulatory Medical Care Survey. Methods: We examined clinician and practice characteristics as well as clinicians' decisions and strategies regarding environmental trigger assessment and environmental control across provider groups. Regression modeling was used to identify clinician and practice characteristics associated with implementation of guideline recommendations. Results: A higher percentage of specialists assessed asthma triggers at home, school, and/or work than primary care or advanced practice providers (almost always: 53.6% vs 29.4% and 23.7%, respectively, P < .001). Almost all clinicians (>93%) recommended avoidance of secondhand tobacco smoke, whereas recommendations regarding cooking appliances (eg, proper ventilation) were infrequent. Although assessment and recommendation practices differed between clinician groups, modeling results showed that clinicians who reported almost always assessing asthma control were 5- to 6-fold more likely to assess environmental asthma triggers. Use of asthma action plans was also strongly associated with implementation of environmental control recommendations. Conclusions: Environmental assessment and recommendations to patients varied among asthma care providers. High adherence to other key guideline components, such as assessing asthma control, was associated with environmental assessment and recommendation practices on environmental control.

High-Order Neural-Network-Based Multi-Model Nonlinear Adaptive Decoupling Control for Microclimate Environment of Plant Factory.

Plant factory is an important field of practice in smart agriculture which uses highly sophisticated equipment for precision regulation of the environment to ensure crop growth and development efficiently. Environmental factors, such as temperature and humidity, significantly impact crop production in a plant factory. Given the inherent complexities of dynamic models associated with plant factory environments, including strong coupling, strong nonlinearity and multi-disturbances, a nonlinear adaptive decoupling control approach utilizing a high-order neural network is proposed which consists of a linear decoupling controller, a nonlinear decoupling controller and a switching function. In this paper, the parameters of the controller depend on the generalized minimum variance control rate, and an adaptive algorithm is presented to deal with uncertainties in the system. In addition, a high-order neural network is utilized to estimate the unmolded nonlinear terms, consequently mitigating the impact of nonlinearity on the system. The simulation results show that the mean error and standard error of the traditional controller for temperature control are 0.3615 and 0.8425, respectively. In contrast, the proposed control strategy has made significant improvements in both indicators, with results of 0.1655 and 0.6665, respectively. For humidity control, the mean error and standard error of the traditional controller are 0.1475 and 0.441, respectively. In comparison, the proposed control strategy has greatly improved on both indicators, with results of 0.0221 and 0.1541, respectively. The above results indicate that even under complex conditions, the proposed control strategy is capable of enabling the system to quickly track set values and enhance control performance. Overall, precise temperature and humidity control in plant factories and smart agriculture can enhance production efficiency, product quality and resource utilization.

The characteristics of particulate matter in different subway station environmental control systems.

Particulate matter (PM2.5, PM10) in urban subway stations can significantly impact passengers' health. The particle concentration in subway stations is influenced by many factors. However, few existing studies have explored the impact of environmental control systems in-depth, especially under different outdoor pollution conditions. To address this research gap, this study focused on measuring and comparing the characteristics of PM2.5 and PM10 at subway stations with three control systems (open, closed, and screen door) under varying pollution conditions in Beijing. Particle concentrations from platforms, carriages, and outdoors were monitored and analyzed using statistical methods. The results showed that the particle concentration in the closed system was generally 20-40 µg/m3 higher than that in the screen system at the platform, which might be attributed to the piston wind, as the air from the tunnel with a lot of dirt. The pollution in the carriage was more severe for the open system than that of the screen system. The PM2.5/PM10 ratio in the carriage was 91%, 90%, and 83.84% for the closed, open, and screen systems, respectively. This indicates that the screen door could reduce the particle concentration in the platform to 10%-50%. The particle concentration varied among subway stations with different environmental control systems, suggesting that the prevention and control strategies for particulate matter pollution should be different for stations with different systems.

Building blocks of microphysiological system to model physiology and pathophysiology of human heart.

Microphysiological systems (MPS) are drawing increasing interest from academia and from biomedical industry due to their improved capability to capture human physiology. MPS offer an advanced in vitro platform that can be used to study human organ and tissue level functions in health and in diseased states more accurately than traditional single cell cultures or even animal models. Key features in MPS include microenvironmental control and monitoring as well as high biological complexity of the target tissue. To reach these qualities, cross-disciplinary collaboration from multiple fields of science is required to build MPS. Here, we review different areas of expertise and describe essential building blocks of heart MPS including relevant cardiac cell types, supporting matrix, mechanical stimulation, functional measurements, and computational modelling. The review presents current methods in cardiac MPS and provides insights for future MPS development with improved recapitulation of human physiology.

Internet of Things (IoT)-Based Environmental Monitoring and Control System for Home-Based Mushroom Cultivation.

The control and monitoring of the environmental conditions in mushroom cultivation has been a challenge in the mushroom industry. Currently, research has been conducted to implement successful remote environmental monitoring, or, in some cases, remote environmental control, yet there is not yet a combination of both these systems providing live stream images or video. As a result, this research aimed to design and develop an Internet of things (IoT)-based environmental control and monitoring system for mushroom cultivation, whereby the growth conditions of the mushrooms, such as temperature, humidity, light intensity, and soil moisture level, are remotely monitored and controlled through a mobile and web application. Users would be able to visualize the growth of the mushroom remotely by video and images through the Internet. The respective sensors are implemented into the mushroom cultivation process and connected to the NodeMCU microcontroller, which collects and transfers the data to the cloud server, enabling remote access at any time through the end device with internet connection. The control algorithm regulates the equipment within the cultivational chamber autonomously, based on feedback from the sensors, in order to retain the optimum environment for the cultivation of mushrooms. The sensors were tested and compared with manual readings to ensure their accuracy. The implementation of IoT toward mushroom cultivation would greatly contribute to the advancement of the current mushroom industry which still applies the traditional cultivation approach.

SARS-CoV-2 concentration in wastewater consistently predicts trends in COVID-19 case counts by at least two days across multiple WWTP scales.

Wastewater surveillance of SARS-CoV-2 has proven instrumental in mitigating the spread of COVID-19 by providing an economical and equitable approach to disease surveillance. Here, we analyze the correlation of SARS-CoV-2 RNA in influents of seven wastewater plants (WWTPs) across the state of South Carolina with corresponding daily case counts to determine whether underlying characteristics of WWTPs and sewershed populations predict stronger correlations. The populations served by these WWTPs have varying social vulnerability and represent 24% of the South Carolina population. The study spanned 15 months from April 19, 2020, to July 1, 2021, which includes the administration of the first COVID-19 vaccines. SARS-CoV-2 RNA concentrations were measured by either reverse transcription quantitative PCR (RT-qPCR) or droplet digital PCR (RT-ddPCR). Although populations served and average flow rate varied across WWTPs, the strongest correlation was identified for six of the seven WWTPs when daily case counts were lagged two days after the measured SARS-CoV-2 RNA concentration in wastewater. The weakest correlation was found for WWTP 6, which had the lowest ratio of population served to average flow rate, indicating that the SARS-CoV-2 signal was too dilute for a robust correlation. Smoothing daily case counts by a 7-day moving average improved correlation strength between case counts and SARS-CoV-2 RNA concentration in wastewater while dampening the effect of lag-time optimization. Correlation strength between cases and SARS-CoV-2 RNA was compared for cases determined at the ZIP-code and sewershed levels. The strength of correlations using ZIP-code-level versus sewershed-level cases were not statistically different across WWTPs. Results indicate that wastewater surveillance, even without normalization to fecal indicators, is a strong predictor of clinical cases by at least two days, especially when SARS-CoV-2 RNA is measured using RT-ddPCR. Furthermore, the ratio of population served to flow rate may be a useful metric to assess whether a WWTP is suitable for a surveillance program.

The use of speech recognition technology by people living with amyotrophic lateral sclerosis: a scoping review.

BACKGROUND: More than 80% of people living with Amyotrophic Lateral Sclerosis (plwALS) develop difficulties with their speech, affecting communication, self-identity and quality of life. Automatic speech recognition technology (ASR) is becoming a common way to interact with a broad range of devices, to find information and control the environment.ASR can be problematic for people with acquired neurogenic motor speech difficulties (dysarthria). Given that the field is rapidly developing, a scoping review is warranted. AIMS: This study undertakes a scoping review on the use of ASR technology by plwALS and identifies research gaps in the existing literature. MATERIALS AND METHODS: Electronic databases and relevant grey literature were searched from 1990 to 2020. Eleven research papers and articles were identified that included participants living with ALS using ASR technology. Relevant data were extracted from the included sources, and a narrative summary of the findings presented.Outcomes and Results: Eleven publications used recordings of plwALS to assess word recognition rate (WRR) word error rate (WER) or phoneme error rate (PER) and appropriacy of responses by ASR devices. All were found to be linked to severity of dysarthria and the ASR technology used. One article examined how speech modification may improve ASR accuracy. The final article completed thematic analysis of Amazon.com reviews for the Amazon Echo and plwALS were reported to use ASR devices to control the environment and summon assistance. CONCLUSIONS: There are gaps in the evidence base: understanding expectations of plwALS and how they use ASR technology; how WER/PER/WRR relates to usability; how ASR use changes as ALS progresses.Implications for rehabilitationDevices that people can interact with using speech are becoming ubiquitous. As movement and mobility are likely to be affected by ALS and progress over time, speech interaction could be very helpful for accessing information and environmental control.However, many people living with ALS (plwALS) also have impaired speech (dysarthria) and experience trouble using voice interaction technology because it may not understand them.Although advances in automated speech recognition (ASR) technology promise better understanding of dysarthric speech, future research needs to investigate how plwALS use ASR, how accurate it needs to be to be functionally useful, and how useful it may be over time as the disease progresses.

Comprehensive home environmental intervention did not reduce allergen concentrations or controller medication requirements among children in Baltimore.

OBJECTIVE: To determine if the addition of home environmental control strategies (ECSs) to controller medication titration reduces asthma controller medication requirements and in-home allergen concentrations among children with persistent asthma in Baltimore City. METHODS: 155 children ages 5-17 with allergen-sensitized asthma were enrolled in a 6-month randomized clinical trial of multifaceted, individually-tailored ECS plus asthma controller medication titration compared to controller medication titration alone. Participants had to meet criteria for persistent asthma and have had an exacerbation in the previous 18 months. Allergen sensitization (mouse, cockroach, cat, dog, dust mite) was assessed at baseline and home dust allergen concentrations were measured at baseline, 3 and 6 months. ECS was delivered 3-4 times over the trial. Asthma controller medication was titrated using a guidelines-based algorithm at baseline, 2, 4, and 6 months. The primary outcome was controller medication treatment step at 6 months (0-6, as-needed albuterol to high-dose ICS + LABA). RESULTS: The population was predominately Black (90%), on public insurance (93%), and male (61%). The mean age was 10.1 years (SD 3.3). More than 70% were sensitized to a rodent, >50% to cockroach, and 70% were polysensitized. At 6 months, there were no differences in either treatment step (3.8 [SD 1.4] vs. 3.7 [SD 1.5]) or allergen concentrations between groups. CONCLUSION: Among this predominantly low-income, Black pediatric asthma population, the addition of ECS to controller medication titration reduced neither indoor allergen concentrations nor controller medication requirements compared to controller medication titration alone.

Development, validation and application of a questionnaire to qualify the indoor environmental exposure of patients with respiratory allergy.

OBJECTIVE: Environmental control includes measures to prevent exposure to common aeroallergens in an individual's home. Questionnaires are part of the clinical practice of health assessment, and are also widely used in research. Our aim was to develop and validate a questionnaire to identify possible sources of aeroallergens present in the indoor environment. METHODS: This study describes the development, validation and application of a questionnaire. For content validation the Content Validation Index and Ordinal Cronbach's Alpha Index have been used; Polychoric Correlations for the agreement between judges; and an Exploratory Factor Analysis for the structure of the questionnaire, while for reliability assessment, Intraclass Correlation Coefficient has been applied. RESULTS: Twenty-one doctors participated as judges to validate the questionnaire, which 204 patients answered. The Content Validity Index for all the questions on the "Clarity" aspect was 0.846 ± 0.152 and on the "Relevance" aspect, 0.954 ± 0.080. Cronbach's alpha coefficient for the "Clarity" aspect was 0.88 with a 95% confidence intervals (CI) and the "Relevance" aspect, 0.94 with a 95% CI. The average Intraclass Correlation Coefficient was 0.94 and all the F tests were highly significant. CONCLUSIONS: The questionnaire developed by our group was considered valid and reliable, and is capable of portraying the home environment without the need for a personal visit to the patient's home. This questionnaire would be a good tool to use in research or during patient consultations to assess the patient's home environment, as this latter assessment is essential for the management of patients with respiratory allergies.

Model based development of temperature control schemes for fighter aircraft ECS.

The performance of Temperature Control System (TCS), a sub-system of an advanced fighter ECS (Environmental Control System) is studied for its operations both in on-ground and in-air conditions. The standard Bootstrap air cycle system is considered with ACM (Air Cycle Machine) as the main component, which consists of a compressor and a turbine, to produce the cold air. ECS, in particular TCS, is responsible in maintaining the required cockpit or cabin temperature. As the fighter aircraft doesn't require cabin air recirculation, the cabin temperature depends solely on the supply air thermal conditions. The cabin temperature regulation is realized by controlling the supply conditions by maintaining required temperature at ACM outlet and at the entrance duct to the cabin. These temperatures are critical parameters that necessitates appropriate controller to keep the cabin in a good comfortable state. ECS of a fighter aircraft is highly complex and nonlinear than commercial aircraft. The control logics applied, on this system, will drive the actuators or TCVs (Temperature Control Valves) to keep the requisite cabin temperature. The control logics applied on the controller to be simple and appropriate to meet the requirements of fighter aircraft ECS. This shall minimize the control cycle oscillation and subsequent supply air temperature instabilities. This paper explains novel cabin temperature control schemes and their influence on the ECS performance especially during the transient operation. The complete architecture of the control schemes along with system components are modelled in AMESim and the comparison is made for different operating conditions. Finally, a novel variable time-delay based method to control the cabin supply air temperature is proposed.

Development and Validation of an Energy Consumption Model for Animal Houses Achieving Precision Livestock Farming.

Indoor environmental control is usually applied in poultry farming to ensure optimum growth conditions for birds. However, these control methods represent a considerable share of total energy consumption, and the trend of applying new equipment in the future for precision livestock farming would further increase energy demand, resulting in an increase in greenhouse gas emissions and management costs. Therefore, to ensure optimum efficiency of both energy use and livestock productivity, a customized hourly model was developed in the present study to interpret and analyze the electronically collected data. The modules for estimating indoor gas concentrations were incorporated into the present model, as this has not been properly considered in previous studies. A validation test was performed in a manure-belt layer house using sensors and meters to measure the indoor environmental parameters and energy consumption. The predicted results, including indoor temperature, relative humidity, carbon dioxide and ammonia concentrations, showed good agreement with the measured data, indicating a similar overall trend with acceptable discrepancies. Moreover, the corresponding differences between the measured and simulated energy consumption for heating, tunnel ventilation and base ventilation were 13.7, 7.5, and 0.1%, respectively. The total energy demand estimated by the model showed a limited discrepancy of approximately 10.6% compared with that measured in reality. Although human factors, including inspection, cleaning, vaccination, etc., were not included in the model, the validation results still suggested that the customized model was able to accurately predict the indoor environment and overall energy consumption during poultry farming. The validated model provides a tool for poultry producers to optimize production planning and management strategies, increase the production rate of unit energy consumption and achieve precision livestock farming from an energy consumption standpoint.

Environmental control for X-ray nanotomography.

The acquisition speed and spatial resolution of X-ray nanotomography have continuously improved over the last decades. Coherent diffraction-based techniques breach the 10 nm resolution barrier frequently and thus pose stringent demands on sample positioning accuracy and stability. At the same time there is an increasing desire to accommodate in situ or operando measurements. Here, an environmental control system for X-ray nanotomography is introduced to regulate the temperature of a sample from room temperature up to 850°C in a controlled atmospheric composition. The system allows for a 360° sample rotation, permitting tomographic studies in situ or operando free of missing wedge constraints. The system is implemented and available at the flOMNI microscope at the Swiss Light Source. In addition to the environmental control system itself, the related modifications of flOMNI are described. Tomographic measurements of a nanoporous gold sample at 50°C and 600°C at a resolution of sub-20 nm demonstrate the performance of the device.

Post-Global Pandemic Challenges and improvements in advanced detection and removal processes of toxic pollutants: Editorial.

Every two years, the Pollutant Toxic Ions and Molecules Conference, PTIM, meets the environmentalist, biologist, chemists and health researchers in Costa de Caparica, Portugal, to showcase the latest technologies, methodologies and research advances in pollution detection, contamination control, remediation, and related health issues, as well as policy implications.

Environmental Persistence of the World's Most Burdensome Infectious and Parasitic Diseases.

Humans live in complex socio-ecological systems where we interact with parasites and pathogens that spend time in abiotic and biotic environmental reservoirs (e.g., water, air, soil, other vertebrate hosts, vectors, intermediate hosts). Through a synthesis of published literature, we reviewed the life cycles and environmental persistence of 150 parasites and pathogens tracked by the World Health Organization's Global Burden of Disease study. We used those data to derive the time spent in each component of a pathogen's life cycle, including total time spent in humans versus all environmental stages. We found that nearly all infectious organisms were "environmentally mediated" to some degree, meaning that they spend time in reservoirs and can be transmitted from those reservoirs to human hosts. Correspondingly, many infectious diseases were primarily controlled through environmental interventions (e.g., vector control, water sanitation), whereas few (14%) were primarily controlled by integrated methods (i.e., combining medical and environmental interventions). Data on critical life history attributes for most of the 150 parasites and pathogens were difficult to find and often uncertain, potentially hampering efforts to predict disease dynamics and model interactions between life cycle time scales and infection control strategies. We hope that this synthetic review and associated database serve as a resource for understanding both common patterns among parasites and pathogens and important variability and uncertainty regarding particular infectious diseases. These insights can be used to improve systems-based approaches for controlling environmentally mediated diseases of humans in an era where the environment is rapidly changing.