Poor Environmental Control Research Articles

Tamper Proof Air Quality Management System using Blockchain

One of the most important concerns facing urban regions across the world is air pollution. As a result, it's critical to monitor pollution levels and notify the public on the state of the air. An indicator called the Air Quality Index (AQI) does this by mapping the concentration of different contaminants into a single number. Because the examination of pollutant data is frequently opaque to outsiders, poor environmental control judgments may result. This has led to a need for a tamper-proof pollution management system for use by authorities, like the state and central pollution boards. To address these challenges, a model using machine learning algorithms to predict the air quality and store that information in the blockchain is proposed. Machine learning algorithms are used to categorize the air quality, and blockchain technology guarantees a permanent, tamper-proof record of all air quality data. Such a system might address the persistent issues with data dependability, immutability and trust in pollution control. The execution time of two main operations on blockchain are measured. The execution time of the put block is measured as 10 ms and the get block gets executed in 1 ms that fetches data from the blockchain ledger.

New Insights from the High-Resolution Monitoring of Microalgae-Virus Infection Dynamics.

Investigation of virus-induced microalgal host lysis and the associated infection dynamics typically requires sampling of infected cultures at multiple timepoints, visually monitoring the state of infected cells, or determining virus titration within the culture media. Such approaches require intensive effort and are prone to low sensitivity and high error rates. Furthermore, natural physiological variations can become magnified by poor environmental control, which is often compounded by variability in virus stock efficacy and relatively long infection cycles. We introduce a new method that closely monitors host health and integrity to learn about the infection strategy of Chloroviruses. Our approach combines aspects of spectrometry, plaque assays, and infection dose assessment to monitor algal cells under conditions more representative of the natural environment. Our automated method exploits the continuous monitoring of infected microalgae cultures in highly controlled lab-scale photobioreactors that provide the opportunity for environmental control, technical replication, and intensive culture monitoring without external intervention or culture disruption. This approach has enabled the development of a protocol to investigate molecular signalling impacting the virus life cycle and particle release, accurate determination of virus lysis time under multiple environmental conditions, and assessment of the functional diversity of multiple virus isolates.

Study of tomato growth weight-distribution model based on real-time plant weight in a solar greenhouse

Crop growth modeling is an important aspect of facility horticulture. Due to the imperfect structural and poor environmental control capabilities of most solar greenhouses, tomato growth in solar greenhouses in the winter half-year often occurs under unsuitable environmental conditions that do not facilitate tomato growth. However, existing crop growth models are difficult to apply to crop growth in solar greenhouses in China because suitable environmental factors are used as the main parameters in these models. The real-time tomato measurement system developed was used to measure the real-time growth of tomato plants. Combined with environmental data. A tomato growth model, an aboveground organ allocation model and conversion coefficient model between fresh weight and dry weight of tomato plants based on real-time tomato weight that are able to overcome the influence of environmental stress were established. The results of this study lay the foundation for appropriate management and fertilization in solar greenhouses.

Optimal sensor placement for monitoring and controlling greenhouse internal environments

In large greenhouses with information and communication technology capability, environmental conditions can be measured and communicated to control the internal environment. However, in such greenhouses, it is difficult to control the internal environment uniformly and appropriately. Additionally, there is uncertainty regarding whether the data measured at a particular location accurately represents the entire greenhouse environment. Furthermore, the locations of sensors are usually determined based on the experience of growers and the greenhouse designers. To accurately measure the internal environment of a greenhouse, it is necessary to properly select the installation locations of the sensors. The objective of this study was to determine the optimal sensor placement for monitoring and controlling the internal environment of a greenhouse. The study greenhouse was an eight-span plastic greenhouse growing Irwin mango crops. Air temperature data measured at nine locations in the greenhouse were used. All of the possible combinations of monitoring locations were evaluated, and optimal sensor placements were selected according to the number of sensors. The optimisation was conducted using two methods: error-based sensor placement and entropy-based sensor placement. Using the former approach, sensor locations for which the monitored data were close to the reference value, i.e. the average data of all the measurement locations, were selected. Using the latter approach, sensor locations influenced by the external weather conditions resulting in poor environmental control were selected. Using these methods, optimal sensor locations for representing the entire environment of the facility and for detecting areas with significant air temperature variations were determined.

Toxic Effects of Methanol among Illegally Dispatched Workers at Aluminum CNC Cutting Process in Small-Scale, Third-Tier Subcontractor Factories of Smartphone Manufacturers in the Republic of Korea.

An outbreak of occupational methanol poisoning occurred in small-scale, third-tier factories of large-scale smartphone manufacturers in the Republic of Korea in 2016. To investigate the working environment and the health effects of methanol exposure among co-workers in the methanol poisoning cases, we performed a cross-sectional study on 155 workers at five aluminum Computerized Numerical Control (CNC) cutting factories. Gas chromatography measured air and urinary methanol concentration. In the medical examination, symptom surveys, ophthalmological examinations, and neurobehavioral tests were done. Multiple logistic regression analyses controlling for age and sex were conducted to reveal the association of employment duration with symptoms. Air concentrations of methanol in factory A and E ranged from 228.5 to 2220.0 ppm. Mean urinary methanol concentrations of the workers in each factory were from 3.5 mg/L up to 91.2 mg/L. The odds ratios for symptoms of deteriorating vision and central nervous system (CNS) increased according to the employment duration after adjusting for age and sex. Four cases with an injured optic nerve and two cases with decreased neurobehavioral function were founded among co-workers of the victims. This study showed that the methanol exposure under poor environmental control not only produces eye and CNS symptoms but also affects neurobehavioral function and the optic nerve. The role of subcontracting production and dispatched work under poor environmental control was discussed.

Visualizing Bacterial Colony Morphologies Using Time-Lapse Imaging Chamber MOCHA.

ABSTRACTCapturing microbial growth on a macroscopic scale is of great importance to further our understanding of microbial life. However, methods for imaging microbial life on a scale of millimeters to centimeters are often limited by designs that have poor environmental control, resulting in dehydration of the agar plate within just a few days. Here, we created MOCHA (microbial chamber), a simple but effective chamber that allows users to study microbial growth for extended periods (weeks) in a stable environment. Agar hydration is maintained with a double-decker design, in which two glass petri dishes are connected by a wick, allowing the lower plate to keep the upper plate hydrated. This flexible chamber allows the observation of a variety of microbiological phenomena, such as the growth and development of single bacterial and fungal colonies, interspecies interactions, swarming motility, and pellicle formation.IMPORTANCE Detailed study of microbial life on the colony scale of millimeters to centimeters has been lagging considerably behind microscopic inspection of microbes. One major reason for this is the lack of inexpensive instrumentation that can reproducibly capture images in a controlled environment. In this study, we present the design and use of a unique chamber that was used to produce several time-lapse movies that aimed to capture the diversity of microbial colony phenotypes over long periods.

Camera-based window-opening estimation in a naturally ventilated office

ABSTRACTNaturally ventilated offices enable users to control their environment through the opening of windows. Whilst this level of control is welcomed by users, it creates risk in terms of energy performance, especially during the heating season. In older office buildings, facilities managers usually obtain energy information at the building level. They are often unaware or unable to respond to non-ideal facade interaction by users often as a result of poor environmental control provision. In the summer months, this may mean poor use of free cooling opportunities, whereas in the winter space heating may be wasteful. This paper describes a low-cost, camera-based system to diagnose automatically the status of each window (open or closed) in a facade. The system is shown to achieve a window status prediction accuracy level of 90–97% across both winter and summer test periods in a case study building. A number of limitations are discussed including winter daylight hours, the impact of rain, and the use of fixed camera locations and how these may be addressed. Options to use this window-opening information to engage with office users are explored.

AVERSION OF PIGS AND DOMESTIC FOWL TO ATMOSPHERIC AMMONIA

Housed pigs and domestic fowl are exposed chronically to atmospheric ammonia at concentrations that may exceed 30 ppm in buildings with poor environmental control. While the effects of ammonia on animal performance and health are reasonably well understood, the effects on behavior are not. In a series of experiments, we therefore studied the aversion of weaner pigs, broiler chickens, and adult laying hens to atmospheric ammonia in a choice test. Typically, individual or small groups of animals were kept in a multi-compartment exposure chamber for one or two weeks. The physical environment in all eight compartments of the chamber was identical in all respects but one: the concentration of atmospheric ammonia was set at approximately 0, 10, 20, or 40 ppm. Observations of the animals' location and behavior were used to indicate their aversion to ammonia. Both pigs and domestic fowl (of both strains) significantly preferred fresh air (approximately 0 ppm) to an ammoniated atmosphere. Visit duration and frequency declined with increasing ammonia concentrations, although interestingly, both species showed a delayed avoidance of ammonia, perhaps indicative of a sense of malaise, which was only manifested after about 30 to 60 min. When given a forced choice between thermal comfort and access to fresh air, cold-stressed pigs chose the former over the latter. Overall, pigs and fowl did not always make short-term choices that were necessarily in their long-term interests. Further work is in hand to study the strength of this aversion in fowl. Current recommendations for air quality in pig and poultry houses should be revised to take account of the animal's strong preference for fresh air; our findings indicate limited tolerance of ammonia at concentrations typical of current housing systems.

Management of the seriously ill asthmatic.

An essential objective in the treatment of seriously ill asthmatic patients is control of the environment. This usually means hospitalization in a private room especially prepared to eliminate all usual irritants. Four further objectives are rest, control of cough, liquefaction of sputum, and control of anoxemia. A sixth objective must be considered in asthmatic patients of long standing, namely the management of complications such as emphysema, bronchostenosis, respiratory infections, drug allergies, and intercurrent surgical conditions. Steroids will usually control the symptoms of asthma promptly, but their prolonged use is dangerous. Medication affords only symptomatic relief in asthma and cannot overcome the bad effects of poor environmental control.