Automatic control of water content in a polyurethane foam packed bed used in biotrickling filters for polluted air treatment

Biotrickling filters (BTF) have been applied to treat waste air. Controlling the water content (WC) of BTFs is fundamental to ensure an adequate interfacial mass transfer and the support of the biofilm activity. A sensor system based on electrical conductance measurement was developed for the online assessment of the WC in a bench scale polyurethane foam (PUF) packed bed. ON/OFF and rule-based control algorithms were applied to keep the water content in a biofilm-free PUF-packed bed within the optimal range of 70-90% through the activation of a hydraulic pump. The applied control algorithms activated the pump at various times, which yielded different energy and water savings even under similar WC conditions suitable for biotrickling filtration of waste air. It was estimated that using the ON/OFF and rule-based system control schemes reduced the electrical power consumption by 98% and 99.8%, respectively, compared to systems under continuous water irrigation.

Smart enzyme catalysts capable of self-separation by sensing the reaction extent

A smart biocatalyst should dissolve homogeneously for catalysis and recover spontaneously at the end of the reaction. In this study, we present a strategy for preparing self-precipitating enzyme catalysts by exploiting reaction-induced pH decreases, which connect the reaction extent to the catalyst aggregation state. Using poly(methacrylic acid)-functionalized gold nanoparticles as carriers, we construct smart catalysts with three model systems, including the glucose oxidase (GOx)-catalase (CAT) cascade, the alcohol dehydrogenase (ADH)-glucose dehydrogenase (GDH) cascade, and a combination of two lipases. All smart catalysts can self-separate with a nearly 100% recovery efficiency when a certain conversion threshold is reached. The threshold can be adjusted depending on the reaction demand and buffer capacity. By monitoring the optical signals caused by the dissolution/precipitation of smart catalysts, we propose a prototypic automation system that may enable unsupervised batch/fed-batch bioprocessing.

Influence of pH and dissolved oxygen control strategies on the performance of pilot-scale microalgae raceways using fertilizer or wastewater as the nutrient source

Dissolved oxygen concentration and pH are controllable and cost-effective variables that determine the success of microalgae-related processes. The present study compares different control strategies for pH and dissolved oxygen in pilot-scale microalgae production systems. Two 80 m2 raceway reactors were used, one operated with freshwater plus fertilizer and the other with wastewater as the nutrient source. Both were in semi-continuous mode at a fixed dilution rate of 0.2 day-1. A comparison between the classical On-Off and more advanced pH control strategies, such as PI and Event-based control, was performed, focusing on biomass productivity and the influence of all the process parameters on microalgae growth; "No control" of pH was also assayed. The results show that Event-based control was the best algorithm when using freshwater plus fertilizer. In contrast, no significant differences were observed using the different control strategies when wastewater was the nutrient source. These experiments were performed through selective control strategy, prioritizing pH over dissolved oxygen; however, it was demonstrated that they did not allow to achieve satisfactory dissolved oxygen removal results, especially for the fertilizer system. After modifying the gas diffuser configuration and improving the mass transfer, independent on-off strategies have been developed, permitting effective control of both variables and increasing productivity by up to 20% in both systems. Concluding, a detailed analysis of the energy demand for each strategy implemented in terms of gas consumption and gas flow to biomass ratio is provided.

Developing a special microwave oven: Assessment of its performance for dough fermentation and nutrient soup elaboration

Bread and soup are two of the most important foods in daily life, thus dough fermentation and nutrient soup elaboration are more and more popular, but there is a lack of relevant low-cost and high-reliable household appliances on the market. Therefore, this paper proposes automatic control methods for dough fermentation and nutrient soup elaboration based on a special microwave oven. Fermentation theory, run-up microwave fermentation principle, microwave extraction principle, NTC temperature probe design and scalable fuzzy control algorithm are described in detail. Besides, the experimental platform is set up with a temperature chamber, an optical fiber thermometer and a power meter. Experimental results demonstrate that the relationship between the heating time and flour's mass is linear. For different ambient temperature tests, the volume ratios of the fermented dough to unfermented dough of different cases range from 2.2 to 2.62, and the inside of the dough after fermentation is fluffy, with small and dense cavities. Meanwhile, there is no acid taste and skin dryness, and the power consumption of microwave fermentation is less than half of that induced by grill, convection or steam fermentation. The detection error of the NTC temperature probe with microwave shielded is 0.48 °C, and the control error of the closed loop system is less than 0.5 °C. The temperature-rise slope of water is lower than that of ingredient, and the water's temperature is about 1 °C less than that of the ingredient. The soup after microwave elaboration is amber and clear, the ingredients are intact, the water loss is less than 50 g, and the total power consumption is 684 Wh. In short, microwave-based control methods for dough fermentation and nutrient soup elaboration are effective.

RaspyControl Lab: A fully open-source and real-time remote laboratory for education in automatic control systems using Raspberry Pi and Python

Currently, remote laboratories have gained relevance in engineering education as tools to support active learning, experimentation, and motivation of students. Nonetheless, the costs and issues regarding their implementation and deployment limit the access of the students and educators to their advantages and features such as technical and educational. In this line, this study describes a fully open-source remote laboratory in hardware and software for education in automatic control systems employing Raspberry Pi and Python language with an approximate cost of USD 461. Even, by changing some components, the cost can be reduced to USD 420 or less. To illustrate the functionalities of the laboratory, we proposed a low-cost tank control system with its respective instrumentation, signal conditioning, identification, and control, which are exposed in this document. However, other experiments can be easily scalable and adaptable to the remote laboratory. Concerning the interface of the laboratory, we designed a complete user-friendly web interface with real-time video for the users to perform the different activities in automatic control such as identification or controller implementation through the programming language Python. The instructions to build and replicate the hardware and software are indicated in the open repositories provided for the project as well as in this paper. Our intention with this project is to offer a complete low-cost and open-source remote laboratory that can be adapted and used for the students, educators, and stakeholders to learn, experiment, and teach in the field of automatic control systems.

Improving GAN Learning Dynamics for Thyroid Nodule Segmentation

Thyroid nodules are lesions requiring diagnosis and follow-up. Tools for detecting and segmenting nodules can help physicians with this diagnosis. Besides immediate diagnosis, automated tools can also enable tracking of the probability of malignancy over time. This paper demonstrates a new algorithm for segmenting thyroid nodules in ultrasound images. The algorithm combines traditional supervised semantic segmentation with unsupervised learning using GANs. The hybrid approach has the potential to upgrade the semantic segmentation model's performance, but GANs have the well-known problems of unstable learning and mode collapse. To stabilize the training of the GAN model, we introduce the concept of closed-loop control of the gain on the loss output of the discriminator. We find gain control leads to smoother generator training and avoids the mode collapse that typically occurs when the discriminator learns too quickly relative to the generator. We also find that the combination of the supervised and unsupervised learning styles encourages both low-level accuracy and high-level consistency. As a test of the concept of controlled hybrid supervised and unsupervised semantic segmentation, we introduce a new model named the StableSeg GAN. The model uses DeeplabV3+ as the generator, Resnet18 as the discriminator, and uses PID control to stabilize the GAN learning process. The performance of the new model in terms of IoU is better than DeeplabV3+, with mean IoU of 81.26% on a challenging test set. The results of our thyroid nodule segmentation experiments show that StableSeg GANs have flexibility to segment nodules more accurately than either comparable supervised segmentation models or uncontrolled GANs.

Design of Wearable Electrolarynx with Automatic Control

Objective

The current work aims to design and develop an automatically controlled wearable electrolarynx, a voice substitution device for laryngeal carcinoma survivals.

Methods

The physical activity of mouth opening is sensed, amplified, and made to act as an enable signal to trigger the wearable electrolarynx. The resulting speech is recorded and compared for its voice reaction durations with that of manual electrolarynx and normal speaking methods. Perception evaluations of 5 subjects from 10 speech-language therapists are obtained.

Results

The wearable electrolarynx turn-on in 13 μs once the mouth movement for speech is sensed. The voice initiation time and termination durations are 215.68 m and 231.41 ms, respectively. Results indicate that there is no significant difference (P < 0.05) between the voice reaction durations of wearable electrolarynx and normal speaking methods. The subjective evaluation results show that there is a significant improvement (P < 0.05) in intelligibility and noise reduction when compared to a commercially available electrolarynx with an average intra-class correlation coefficient of 0.68 from analysis of variance two factors without replication.

Conclusions

The assessment of the wearable and automatically controlled electrolarynx provides hands-free speech and easy control over the device.

The influence of the motor command accuracy on the prediction error and the automatic corrective response

The online control system allows for automatic corrective response to unexpected perturbation. This corrective response may involve a prediction error between the sensory prediction by the motor command and the actual feedback signal. Therefore, we attempted to investigate the effect of motor command accuracy on the automatic corrective response. Participants were asked to move a cursor displayed on a monitor and required to reach the center of a Gaussian blob target as accurately as possible for small and large Gaussian blob conditions. The accuracy of the motor command was manipulated by the size of the Gaussian blob. In half of the trials, a perturbation occurred in which the cursor position jumped 10 mm to either the left or right from the actual position, which induced an automatic corrective response. This corrective response was detected by the acceleration signal on the lateral axis. In addition, the prediction error was estimated by the amplitude of the N1 event-related potential (ERP) of the EEG signal. We found that the automatic response and N1 ERP were significantly larger in the small Gaussian blob conditions than in the large one. This result indicates that the automatic corrective response is affected by the certainty of the motor command manipulated by the Gaussian blob. Furthermore, the linear mixed-effect model (LME) indicated that the response is associated with the N1 ERP. Therefore, we suggest that the motor command accuracy affects the prediction error, which in turn modulates the automatic corrective response.

Non-pharmaceutical intervention to reduce COVID-19 impact in Argentina

This work is focused on the multilevel control of the population confinement in the city of Buenos Aires and its surroundings due to the pandemic generated by the COVID-19 outbreak. The model used here is known as SEIRD and two objectives are sought: a time-varying identification of the infection rate and the inclusion of a controller. A control differential equation has been added to regulate the transitions between confinement and normal life, according to five different levels. The plasma treatment from recovered patients has also been considered in the control algorithm. Using the proposed strategy the ICU occupancy is reduced, and as a consequence, the number of deaths is also decreased.

Understanding the Emergence of Social Anxiety in Children With Behavioral Inhibition

Behavioral inhibition (BI) is a temperament characterized in early childhood by distress to novelty and avoidance of unfamiliar people, and it is one of the best-known risk factors for the development of social anxiety. However, nearly 60% of children with BI do not go on to meet criteria for social anxiety disorder. In this review we present an approach to understanding differential developmental trajectories among children with BI. We review research using laboratory-based tasks that isolate specific attention processes that enhance versus mitigate risk for social anxiety among behaviorally inhibited children and studies that suggest that BI is associated with heightened detection of novelty or threat. Moreover, stimulus-driven control processes, which we term "automatic control," increase the probability that behaviorally inhibited children display socially reticent behavior and develop social anxiety. In contrast, goal-driven control processes, which we term "planful control," decrease risk for anxiety. We suggest that these three categories of processes (detection, automatic control, and planful control) function together to determine whether behaviorally inhibited children are able to flexibly regulate their initial reactions to novelty, and in turn, decrease risk for social anxiety. Although laboratory-based tasks have identified these processes underlying risk and resilience, the challenge is linking them to the emotions, thoughts, and behaviors of behaviorally inhibited children in real-world contexts.

An appropriate technique for treating rural wastewater by a flow step feed system driven by wind-solar hybrid power

Most rural wastewater treatment facilities require aeration equipment to ensure sufficient dissolved oxygen (DO) during processing. Operation and maintenance are costly, and cannot be met in many areas with poor economic levels. This has led to further deterioration of the rural water environment and aroused much attention. This work reports a plug-flow step feed system utilizing wind and solar hybrid energy for rural wastewater treatment. Under certain climatic conditions, the wind energy and solar energy provided complimentary power generation, and an automatic control system (without batteries) was constructed. The corresponding control logic for multi-energy level operation was developed. Furthermore, the power generation efficiency of the system, the pollutant removal, and its mechanism on the bioreactor were also analyzed. According to the monitoring of meteorological conditions, wind and solar resources at the test site were abundant, and the electricity generated by the power generation was sufficient to meet the operational needs of the equipment. Energy efficiency can reach 80.0%. The characteristics of pollutant removal in each process section were studied on spatial and temporal dimensions. Results showed that the wastewater treatment process reached mean removal efficiencies of chemical oxygen demand (COD_cr), NH₄⁺-N, total nitrogen (TN) and total phosphorus (TP) were 90.2%, 94.3%, 61.4% and 63.1%, respectively. Analyses of microbial community richness and group changes in each anoxic/aerobic reaction chamber in the biofilm reactor showed that the population structure was relatively stable and that there were abundant functional bacteria capable of degrading pollutants in each aerobic and anoxic unit. This system can thus be a more sustainable treatment process than traditional techniques used for rural wastewater treatment, providing a new design approach for low-energy consumption and unattended rural wastewater treatment.

An optimal interval type-2 fuzzy logic control based closed-loop drug administration to regulate the mean arterial blood pressure

BACKGROUND AND OBJECTIVE

The main aim of this work is to present an optimal and robust controller design in order to improve the drug infusion to the automatic control of mean arterial blood pressure in conditions like critically-ill or post-operative or anaesthesia administration. The physiological systems also have uncertainty issues such as parameter variations with time or external disturbances and noise. Therefore, a controlled drug administration is necessary to regulate the mean arterial blood pressure of a person during surgery/observation. Over the years, the proportional-integral-derivative (PID) controller is the most commonly used controller in industries due to its easy structure and simplicity. However, this controller does not meet the desired performance with the complex and uncertain plants. Therefore, a robust controller is required to regulate the physiological variables that are uncertain in nature and can affect the human life.

METHODS

In this work, a hybrid control scheme consisting of an interval type-2-fuzzy logic controller which acts as pre-compensator to the traditional PID controller is presented, to regulate the mean arterial blood pressure of a patient by administering the drug sodium nitroprusside in a controlled manner. An effective and well-established nature-inspired optimization technique namely cuckoo search algorithm is employed for obtaining the optimal parameters for the presented scheme.

RESULTS

Simulation results are presented to show the effectiveness and robustness of proposed interval type-2-fuzzy logic controller based PID controller scheme, for maintaining the mean arterial pressure to 100 mmHg within considerable limit through SNP infusion. The results are further compared with other two controllers namely type-1 fuzzy logic based PID and traditional PID controllers for the parameter variations and external noise.

CONCLUSION

In this study, the proposed interval type-2-fuzzy logic controller pre-compensator based PID controller provides an effective control than traditional type-1 fuzzy logic based control scheme and PID controller in terms of overshoot, settling-time and error which are the prime performance objectives of the closed-loop controlled drug delivery of human blood pressure. The presented study provides a firm base for initial design considerations for development of a low-cost closed-loop drug delivery system for blood pressure regulation.

Investigating vulnerability of ecological industrial symbiosis network based on automatic control theory

System fluctuations of eco-industrial symbiosis network (EISN) organization due to disturbance are very similar to the controller adjustment in the automatic control theory. Thus, a methodology is proposed in this study to assess the vulnerability of EISN based on the automatic control theory. The results show that the regulator plays a key role to enhance the resilience of the network system to vulnerability. Therefore, it is imperative to strengthen the real-time regulation and control of EISN so that the system stability is improved. In order to further explore the impact of various regulations on the system vulnerability, the influence of system stability is simulated by means of proportional, differential, and integral control. A case study with Guigang eco-industrial park (EIP) was undertaken to test this model. The results showed that when the system was disturbed at different positions, the key nodes which had great influence on system vulnerability could be selected according to the magnitude of simulation curve. By changing the ratio coefficient of proportional, differential, and integral units to adjust the ecological chain network, the system's resilience to vulnerability can be enhanced. Firstly, if basic conditions of EISN organization remain unchanged, the integral control of the policy support and infrastructure sharing should be strengthened. Secondly, the differential regulation should be improved continuously for the technological innovation capability of key node enterprises. Finally, the key chain filling projects should be introduced for proportional control so that the chain network design can be optimized from the source.

Prospects for using a full-scale installation for wet combustion of organic wastes in closed life support systems

The issue of recycling organic wastes in closed life support systems (CLSS) includes both fundamental aspects of environmental safety of the recycled products and their effective involvement in material cycles and technical aspects related to the structure of the system and the crew's demands. This study estimates the effectiveness of wet combustion of different amounts of organic wastes in hydrogen peroxide under application of an alternating current electric field. The study also addresses the possibility of controlling the process automatically. The results show that processing of greater amounts of wastes reduces specific power consumption and shortens the duration of the process, without significantly affecting the level of oxidation of the products. An automatic control system for a semi-commercial installation has been constructed and tested experimentally. The solution of mineralized human wastes prepared in the automatically controlled process in this installation was successfully used to grow radish plants, with the main production parameters being similar to those of the control.

Automatic process control in anaerobic digestion technology: A critical review

Anaerobic digestion (AD) is a mature technology that relies upon a synergistic effort of a diverse group of microbial communities for metabolizing diverse organic substrates. However, AD is highly sensitive to process disturbances, and thus it is advantageous to use online monitoring and process control techniques to efficiently operate AD process. A range of electrochemical, chromatographic and spectroscopic devices can be deployed for on-line monitoring and control of the AD process. While complexity of the control strategy ranges from a feedback control to advanced control systems, there are some debates on implementation of advanced instrumentations or advanced control strategies. Centralized AD plants could be the answer for the applications of progressive automatic control field. This article provides a critical overview of the available automatic control technologies that can be implemented in AD processes at different scales.

Motor automaticity in Parkinson's disease

Bradykinesia is the most important feature contributing to motor difficulties in Parkinson's disease (PD). However, the pathophysiology underlying bradykinesia is not fully understood. One important aspect is that PD patients have difficulty in performing learned motor skills automatically, but this problem has been generally overlooked. Here we review motor automaticity associated motor deficits in PD, such as reduced arm swing, decreased stride length, freezing of gait, micrographia and reduced facial expression. Recent neuroimaging studies have revealed some neural mechanisms underlying impaired motor automaticity in PD, including less efficient neural coding of movement, failure to shift automated motor skills to the sensorimotor striatum, instability of the automatic mode within the striatum, and use of attentional control and/or compensatory efforts to execute movements usually performed automatically in healthy people. PD patients lose previously acquired automatic skills due to their impaired sensorimotor striatum, and have difficulty in acquiring new automatic skills or restoring lost motor skills. More investigations on the pathophysiology of motor automaticity, the effect of L-dopa or surgical treatments on automaticity, and the potential role of using measures of automaticity in early diagnosis of PD would be valuable.