RESUMEN

Creating diverse microparticle patterns on a large scale enhances the performance and efficiency of biochemical analytics. Current techniques exhibit limitations in achieving diverse microparticle patterns on a large scale, primarily focusing on patterning particles of the same type with limited flexibility and accessibility. Moreover, accessibility to patterned particles without a fixed formation poses additional challenges. Herein, in this work, we introduce a novel robotic micropatterning system designed to address these challenges. The system facilitates the selection, batch transferring, patterning, and encapsulation of microparticles using negative dielectrophoresis (nDEP)-tweezers, enabling large-scale microparticle patterning on a hydrogel. A multielectrode chip was mounted on a micromanipulator to serve as the nDEP tweezers, and the microparticles scattering on the substrate could be trapped and displaced to different positions on a substrate with an array of holes for large-scale pattern generation. Photosensitive hydrogel was employed for microparticle pattern encapsulation. The effects of configuring different experimental parameters on the patterning efficiency were evaluated and analyzed. Experiments were conducted to explore the stability and performance of the micropatterns. Various patterns with hydrogel encapsulation were created using different color polystyrene microbeads (orange, blue, and green) with varying sizes (50, 100, and 125 µm) under the adjusted environment. Results demonstrate the successful creation of large-scale microbead patterns in a specified form and their encapsulation into an extractable hydrogel using the proposed nDEP tweezer system. The proposed system can be potentially applied to diverse bioparticles for analysis.

RESUMEN

After injection molding, plastic gears often exhibit surface defects, including those on end faces and tooth surfaces. These defects encompass a wide range of types and possess complex characteristics, which pose challenges for inspection. Current visual inspection systems for plastic gears suffer from limitations such as single-category defect inspection and low accuracy. There is an urgent industry need for a comprehensive and accurate method and system for inspecting defects on plastic gears, with improved inspection capability and higher accuracy. This paper presents an intelligent inspection algorithm network for plastic gear defects (PGD-net), which effectively captures subtle defect features at arbitrary locations on the surface compared to other models. An adaptive sample weighting method is proposed and integrated into an improved Focal-IoU loss function to address the issue of low inspection accuracy caused by imbalanced defect dataset distributions, thus enhancing the regression accuracy for difficult defect categories. CoordConv layers are incorporated into each inspection head to improve the model's generalization capability. Furthermore, a dataset of plastic gear surface defects comprising 16 types of defects is constructed, and our algorithm is trained and tested on this dataset. The PGD-net achieves a comprehensive mean average precision (mAP) value of 95.6% for the 16 defect types. Additionally, an online inspection system is developed based on the PGD-net algorithm, which can be integrated with plastic gear production lines to achieve online full inspection and automatic sorting of plastic gear defects. The entire system has been successfully applied in plastic gear production lines, conducting daily inspections of over 60,000 gears.

RESUMEN

The intensity that people choose for their endurance activities has a major influence on their affective experience. Furthermore, the direction of attention (e.g., internal or external) during endurance activities may significantly influence performance and personal perceptions. Therefore, in the current study, we focus on the interaction between intensity and attentional focus. We aim to address the question of whether adopting an internal (IAF; breathing) or an external attentional focus (EAF; environment), compared to a control condition, leads in differences in speed, heart rate, and affect during running at different intensities in experienced runners. Data from 59 participants were analyzed (Mage: 26.95 (SD = 4.78) years; 34 male; 25 female). Participants ran 9 × 3 min in an outdoor park with three intensity conditions (light, somewhat hard, hard) and three attention conditions (internal, external, control). Intensity, but not attentional focus, impacted affective responses. Results revealed a significant interaction between attentional focus and intensity on heart rate (p < 0.001, ω2p = 0.199): during the somewhat hard intensity, the control focus condition was significantly lower compared the internal and external attentional focus conditions. Additionally, we used exploratory multilevel models (MLM). In the best-fitting MLM of heart rate, 45% of the variance is attributed to differences between athletes, and thus 55% of the variance within athletes. Furthermore, the model indicated that athletes running at a somewhat hard intensity and maintaining an EAF (b = 7.69) or IAF (b = 6.36) had an increase in heart rate compared to the control condition. We speculate that simultaneously monitoring effort and following an attentional instruction was such a difficult task that led to a favorable effect for the control condition. In practice, this could mean that the implementation of an unfamiliar focus of attention, for example, initially requires additional energy expenditure.

Asunto(s)

RESUMEN

Dual-process theories postulate that both reflective and automatic processes regulate health behavior. Further research is required to test the basic postulates of dual-process theories. We investigated the direct associations and moderating effect between automatic processes and multiple indicators of reflective processes on various levels of physical activity and sedentary behavior assessed using accelerometry in adults who were not participating in regular physical exercise programs. This cross-sectional study included 257 adults. Each participant completed a computerized test for automatic associations, a set of questions assessing reflective processes, a seven-day assessment using accelerometers to determine their levels of physical activity and sedentary behavior. The results showed a direct relationship between perceived benefits (B = 15.90, p = 0.043), perceived cons (B = -12.81, p = 0.034), decisional intention (B = -0.07, p = 0.049) with light physical activity, and self-efficacy with daily steps (B = 485.71, p = 0.008). There was a positive association between intention strength and daily steps when implicit associations favored physical activity (b = 623.36, LLCI = 79.09, ULCI = 1167.62, p = 0.025); a negative association between self-efficacy and sedentary behavior when implicit associations favored sedentary behavior (b = -25.73, LLCI = -49.77, ULCI = -1.70, p = 0.035); and a positive association between intention strength and sedentary behavior when implicit associations favored physical activity (b = 34.18, LLCI = 8.81, ULCI = 59.56, p = 0.008). These findings underscore the importance of considering the interplay between reflective and automatic processes in shaping movement behavior.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

RESUMEN

This paper presents a personalized and smart flowerpot for ornamental horticulture, integrating 3D printing and cloud technology to address existing design limitations and enable real-time monitoring of environmental parameters in plant cultivation. While 3D printing and cloud technology have seen widespread adoption across industries, their combined application in agriculture, particularly in ornamental horticulture, remains relatively unexplored. To bridge this gap, we developed a flowerpot that maximizes space utilization, simplicity, personalization, and aesthetic appeal. The shell was fabricated using fused deposition modeling (FDM) in 3D printing, and an Arduino-based control framework with sensors was implemented to monitor critical growth factors such as soil moisture, temperature, humidity, and light intensity. Real-time data are transmitted to the Bamfa Cloud through Wi-Fi, and a mobile application provides users with instant access to data and control over watering and lighting adjustments. Our results demonstrate the effectiveness of the smart flowerpot in enabling automated monitoring of plant growth and environmental control. This innovation holds significant promise for advancing smart device development in ornamental horticulture and other related fields, enhancing efficiency, plant health, and overall user experience. Future research in this area has the potential to revolutionize horticultural practices and contribute to the advancement of smart agriculture.

Asunto(s)

RESUMEN

A multifunctional moxibustion treatment machine is designed and developed to assist the heat-sensitive moxibustion therapy. Through the motion control of the stepping motor by programmable logic controller (PLC), the automatic control is obtained for the acupoint detection of heat-sensitive moxibustion therapy and the manual operation of moxibustion. The skin temperature is monitored in real-time, using infrared non-contact temperature measurement technology. Based on the deviation of the temperature set value and the monitoring one, the distance between the moxibustion device and the exerted region is adjusted automatically by PLC so that the temperature is controlled practically. The multifunctional moxibustion treatment machine based on the heat-sensitive moxibustion therapy is capable of the operation control of mild moxibustion, circling moxibustion, sparrow-pecking moxibustion and along-meridian moxibustion techniques, as well as real-time monitoring of skin temperature. The temperature change curve of this machine is coincident with that obtained by the manual operation of heat-sensitive moxibustion. This multifunctional moxibustion treatment machine assists the delivery of heat-sensitive moxibustion therapy and it is satisfactory in temperature control and precise in operation.

Asunto(s)

RESUMEN

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.

RESUMEN

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.

Asunto(s)

RESUMEN

A multifunctional moxibustion treatment machine is designed and developed to assist the heat-sensitive moxibustion therapy. Through the motion control of the stepping motor by programmable logic controller (PLC), the automatic control is obtained for the acupoint detection of heat-sensitive moxibustion therapy and the manual operation of moxibustion. The skin temperature is monitored in real-time, using infrared non-contact temperature measurement technology. Based on the deviation of the temperature set value and the monitoring one, the distance between the moxibustion device and the exerted region is adjusted automatically by PLC so that the temperature is controlled practically. The multifunctional moxibustion treatment machine based on the heat-sensitive moxibustion therapy is capable of the operation control of mild moxibustion, circling moxibustion, sparrow-pecking moxibustion and along-meridian moxibustion techniques, as well as real-time monitoring of skin temperature. The temperature change curve of this machine is coincident with that obtained by the manual operation of heat-sensitive moxibustion. This multifunctional moxibustion treatment machine assists the delivery of heat-sensitive moxibustion therapy and it is satisfactory in temperature control and precise in operation.

Asunto(s)

RESUMEN

An approach for improving and maintaining a consistent weld quality of the deposited material during the FFF printing process is proposed. The approach is based on the analysis of the printing process thermal cycle and the real-time nozzle temperature control. The mathematical model of the FFF printing process has been developed with the use of real-time control in the algorithm of numerical implementation. The successful solution of the thermal conductivity problem made it possible to determine segment-wise heating settings for use during the printing process, resulting in a high and stable quality of welding. Comparison of the results of modeling with other well-known mathematical models of the FFF printing process and experimental results showed the adequacy of the proposed model. A maximum deviation of 17.7% between the simulation results and the thermography data was observed. The proposed model was verified using rectangular 3D polylactide shapes printed with and without regulation of the power of the heat source according to the previously estimated settings. The overall quality of regulation, stability of the system, and the PI coefficients of the controller were evaluated using a simulated model of the control system. The results of the experiment fully correspond with the modeling results.

RESUMEN

Experiencing negative affect during exercise partially explains high levels of physical inactivity. An important direction for research is to better understand how and why interindividual differences in affective experiences occur while exercising. The dual-mode theory suggests that the interaction of cognitive processes and interoceptive cues influence the affective response. Hence, attentional control in form of adopting an external or internal attentional focus could lead to different affective responses depending on intensity. This study examines possible interactions between self-selected running intensities and attentional focus on affect. Fifty-eight inexperienced runners (30.14 ± 9.19 years; 38% female) ran 9 × 3 min outdoors around a large pond. While running at three intensities, they were instructed to focus on their breathing, on the environment, or did not receive an instruction. Dependent measures were affect, heart rate, and speed. The results revealed a significant interaction between attentional focus and intensity on affect (p = .01, η2p = .08). At subjectively perceived light intensity, participants' affective outcomes benefit from non-focusing attention, whereas during hard intensity the opposite seems helpful: to focus on breathing or to the environment. These findings shed new light on the interaction of focusing attention and running intensity to improve the affective experience.

Asunto(s)

RESUMEN

Bioreactors are important tools for the pre-conditioning of tissue-engineered heart valves. The current state of the art mostly provides for timed, physical and biochemical stimulation in the bioreactor systems according to standard protocols (SOP). However, this does not meet to the individual biological variability of living tissue-engineered constructs. To achieve this, it is necessary to implement (i) sensory systems that detect the actual status of the implant and (ii) controllable bioreactor systems that allow patient-individualized pre-conditioning. During the maturation process, a pulsatile transvalvular flow of culture medium is generated within the bioreactor. For the improvement of this conditioning procedure, the relationship between the mechanical and biochemical stimuli and the corresponding tissue response has to be analyzed by performing reproducible and comparable experiments. In this work, a technological framework for maturation experiments of tissue-engineered heart valves in a pulsating bioreactor is introduced. The aim is the development of a bioreactor system that allows for continuous control and documentation of the conditioning process to increase reproducibility and comparability of experiments. This includes hardware components, a communication structure and software including online user communication and supervision. Preliminary experiments were performed with a tissue-engineered heart valve to evaluate the function of the new system. The results of the experiment proof the adequacy of the setup. Consequently, the concept is an important step for further research towards controlled maturation of tissue-engineered heart valves. The integration of molecular and histological sensor systems will be the next important step towards a fully automated, self-controlled preconditioning system.

Asunto(s)

RESUMEN

In this paper, we address the problem of optimal thyroid hormone replacement strategy development for hypothyroid patients. This is challenging for the following reasons. First, it is difficult to determine the correct dosage leading to normalized serum thyroid hormone concentrations of a patient. Second, it remains unclear whether a levothyroxine L-T4) monotherapy or a liothyronine/levothyroxine (L-T3/L-T4) combined therapy is more suitable to treat hypothyroidism. Third, the optimal intake frequency of L-T3/L-T4 is unclear. We address these issues by extending a mathematical model of the pituitary-thyroid feedback loop to be able to consider an oral intake of L-T3/L-T4. A model predictive controller (MPC) is employed to determine optimal dosages with respect to the thyroid hormone concentrations for each type of therapy. The results indicate that the L-T3/L-T4 combined therapy is slightly better (in terms of the achieved hormone concentrations) to treat hypothyroidism than the L-T4 monotherapy. In case of a specific genetic variant, namely genotype CC in polymorphism rs2235544 of gene DIO1, the simulation results suggest that the L-T4 monotherapy is better to treat hypothyroidism. In turn, when genotype AA is considered, the L-T3/L-T4 combined therapy is better to treat hypothyroidism. Furthermore, when genotype CC of polymorphism rs225014 (also referred to as c.274A>G or p.Thr92Ala) in the DIO2 gene is considered, the outcome of the L-T3/L-T4 combined therapy is better in terms of the steady-state hormone concentrations (for a triiodothyronine setpoint at the upper limit of the reference range of healthy individuals). Finally, the results suggest that two daily intakes of L-T3 could be the best trade-off between stable hormone concentrations and inconveniences for the patient.

Asunto(s)

RESUMEN

An optimal control strategy was tested to regulate the flow rate of the cold stream to maximize the time-averaged water production of a laboratory-scale membrane distillation (MD) process. The MD process is operated under fluctuating inlet hot temperatures at a fixed flow rate for the hot stream. The inlet hot temperature fluctuates due to fluctuation in the supplied renewable energy source, such as solar energy. The simulation revealed the possibility of enhancing the average water production by up to 4.2%, by alternating the flow rate of the cold stream relative to a fixed flow rate of the hot stream. The enhancement was limited because, when using a long membrane, the mass flux degrades when the ratio of the cold stream to the hot stream flow rates is either very high or low. By modifying the control strategy to adapt the membrane length in addition to the flow rate of the cold stream, highly improved performance could be obtained. In fact, up to 40% enhancement in the average water production was observed.

RESUMEN

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.

Asunto(s)

RESUMEN

In order to effectively prevent the damage to the human body caused by abnormal oxygen concentration in the medical hyperbaric oxygen chamber, a ZigBee-based medical hyperbaric oxygen chamber oxygen concentration automatic control system is designed. The data acquisition module uses the microprocessor STM32F103C8T6 to receive the oxygen concentration data of each acquisition point, and the ZigBee of the data processing module transmits the processing results to the MSP430G2553 single-chip microcomputer at the receiving end of the slave. The MSP430G2553 single-chip microcomputer uses a self-organizing TS fuzzy neural network (SOTSFNN) and adds activation. The intensity concept realizes automatic control of the oxygen concentration in the hyperbaric oxygen chamber, and controls the buzzer to give an alarm when the oxygen concentration is lower than 19 mg/L and higher than 23 mg/L, and displays the current real-time oxygen concentration through LCD12864. The experimental results show that as the communication distance increases, the packet loss rate of the system is always lower than 5%, and the signal strength under the same communication distance is better; the system can effectively control the oxygen concentration value within the set range, and the oxygen concentration. The control accuracy is high and the stability is good.

Asunto(s)

RESUMEN

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.

Asunto(s)