Development Of Control Strategies Research Articles

A novel rule mining method for knowledge discovery of relationships among indoor air quality, HVAC operation and occupants’ activities

This paper presents a novel data mining method to discover the occurrence time, co-occurrence and sequential association rules among indoor air quality (IAQ), Heating, Ventilation and Air Conditioning (HVAC) operation and occupants' activities. The novelty of this work includes a peak detection method to discover the pollutants' peaks and a rule mining method with extended rule selection criteria that considers both the time lags between events and relationships among multiple events. The peak detection method aimed to use moving windows and criteria to find the candidate peaks and the non-maximum suppression to filter the overlapped candidate peaks. The proposed rule mining method is based on the Apriori and Apriori-All with the rule selection criteria extended by labeling the occurrence time to events to find the rules among various occurrence times and multiple events and by limiting the time lags among the occurrences of the events to discover the sequential rules. Two datasets, one from 70 houses and one from a single commercial building, were used to evaluate the performance of this proposed data-driven method. The results showed that 93.19 % of the peak detection results matched the peaks detected from the data records. The CO2 peaked frequently at 12:00, 17:00 and from 19:00 to 24:00. The occurrence of occupants' activities could lead to pollutants’ concentrations and pollutants peaks within 2 hours in the residential buildings. The occurrence of a high Wifi connection number was frequently followed by a CO2 peak within 2 hours in the commercial building. These findings can support the development of control strategies for building HVAC systems to achieve better indoor air quality control.

Sand Fly larvae are capable of positive chemotaxis: a proof of concept study using Phlebotomus papatasi (Diptera: Psychodidae) as a model species.

Phlebotomine sand flies are important vectors of medical and veterinary importance, transmitting pathogens, such as the Leishmania parasites, responsible for 700,000 to 1 million new cases of leishmaniasis every year. The vast majority of the current sand fly surveillance and control tools are tailored against the adult stages, due to the limited knowledge on the ecology of the larval stages. Since vector control is primarily an ecological problem, an in-depth understanding of the behavior of the target insect pests across all the different life stages of their development is required prior to the development of effective control strategies. It is well known that chemical cues play an important role in insect behavior. While there are numerous studies investigating the behavior of adult sand flies in response to chemical sources, there is currently no information available on the response of their larval stages. In this study, novel bioassays were constructed to investigate the effect of chemical cues (gustatory and olfactory) on the behavior of Phlebotomus papatasi (Scopoli) sand fly larvae. The larvae exhibited a clear food preference within a few hours of exposure in a 2-choice bioassay, while, also, demonstrated positive chemotaxis in response to volatile stimuli emitted from their preferred food source. Identification of the specific chemical compounds (or the combination thereof) eliciting attractance response to sand fly immature stages could lead to the development of innovative, and targeted (larval-specific) tools for the surveillance, and management of these important public health pests.

Genome sequencing and comparative genomics reveal insights into pathogenicity and evolution of Fusarium zanthoxyli, the causal agent of stem canker in prickly ash

BackgroundFusarium zanthoxyli is a destructive pathogen causing stem canker in prickly ash, an ecologically and economically important forest tree. However, the genome lack of F. zanthoxyli has hindered research on its interaction with prickly ash and the development of precise control strategies for stem canker.ResultsIn this study, we sequenced and annotated a relatively high-quality genome of F. zanthoxyli with a size of 43.39 Mb, encoding 11,316 putative genes. Pathogenicity-related factors are predicted, comprising 495 CAZymes, 217 effectors, 156 CYP450s, and 202 enzymes associated with secondary metabolism. Besides, a comparative genomics analysis revealed Fusarium and Colletotrichum diverged from a shared ancestor approximately 141.1 ~ 88.4 million years ago (MYA). Additionally, a phylogenomic investigation of 12 different phytopathogens within Fusarium indicated that F. zanthoxyli originated approximately 34.6 ~ 26.9 MYA, and events of gene expansion and contraction within them were also unveiled. Finally, utilizing conserved domain prediction, the results revealed that among the 59 unique genes, the most enriched domains were PnbA and ULP1. Among the 783 expanded genes, the most enriched domains were PKc_like kinases and those belonging to the APH_ChoK_Like family.ConclusionThis study sheds light on the genetic basis of F. zanthoxyli’s pathogenicity and evolution which provides valuable information for future research on its molecular interactions with prickly ash and the development of effective strategies to combat stem canker.

Research and Development of Control Strategies for Fuel Cell Systems

For the self-developed kilowatt level proton exchange membrane fuel cell system, the control algorithm of the fuel cell system is built in MATLAB/Simulink, and the control models of each subsystem, the entire system control process, and steady-state calibration process are discussed. Data analysis through experiments shows that the system has good performance.

A multiplex method for the detection of food microorganisms based on suspension microarrays combined with recombinase-aided amplification

Foodborne diseases caused by foodborne pathogenic microorganisms have long been a severe public health problem. Timely and accurate detection of food-borne microorganisms can minimize their harm and enable the development of efficient control strategies. In this study, we establish a multiplex nucleic acid detection method based on recombinase-aided amplification reaction on a suspension microarray (referred to as SC-RAA) to identify and quantify microorganisms. The experimental results confirmed that this approach has an outstanding sensitivity, with a limit of detection (LOD) of 0.8 fM and a linear range of 0.8 fM–80 pM, spanning five orders of magnitude. Moreover, the prepared method also showed exquisite specificity, which the amplified signal can be detected only when the target nucleic acid is present. The recovery rate of the SC-RAA assay was 82.2%–113.4%, suggesting that the SC-RAA assay is performing well and accurately measuring the concentration of the substance in the sample. In addition, the consistency analysis showed that the results of the SC-RAA detection were also in good agreement with those of traditional qPCR detection (R2 > 0.95). These results highlight the potential of the SC-RAA assay to be applied as a multiplex and sensitive DNA detection platform for identifying and quantifying foodborne pathogenic microorganisms.

Denaturing Gradient Gel Electrophoresis Approach for Microbial Shift Analysis in Thermophilic and Mesophilic Anaerobic Digestions.

To determine the evolution of microbial community and microbial shift under anaerobic processes, this study investigates the use of denaturing gradient gel electrophoresis (DGGE). In the DGGE, short- and medium-sized DNA fragments are separated based on their melting characteristics, and this technique is used in this study to understand the dominant bacterial community in mesophilic and thermophilic anaerobic digestion processes. Dairy manure is known for emitting greenhouse gases (GHGs) such as methane, and GHG emissions from manure is a biological process that is largely dependent on the manure conditions, microbial community presence in manure, and their functions. Additional efforts are needed to understand the GHG emissions from manure and develop control strategies to minimize the biological GHG emissions from manure. To study the microbial shift during anaerobic processes responsible for GHG emission, we conducted a series of manure anaerobic digestion experiments, and these experiments were conducted in lab-scale reactors operated under various temperature conditions (28 °C, 36 °C, 44 °C, and 52 °C). We examined the third variable region (V3) of the 16S rRNA gene fingerprints of bacterial presence in anaerobic environment by PCR amplification and DGGE separation. Results showed that bacterial community was affected by the temperature conditions and anaerobic incubation time of manure. The microbial community structure of the original manure changed over time during anaerobic processes, and the community composition changed substantially with the temperature of the anaerobic process. At Day 0, the sequence similarity confirmed that most of the bacteria were similar (>95%) to Acinetobacter sp. (strain: ATCC 31012), a Gram-negative bacteria, regardless of temperature conditions. At day 7, the sequence similarity of DNA fragments of reactors (28 °C) was similar to Acinetobacter sp.; however, the DNA fragments of effluent of reactors at 44 °C and 52 °C were similar to Coprothermobacter proteolyticus (strain: DSM 5265) (similarity: 97%) and Tepidimicrobium ferriphilum (strain: DSM 16624) (similarity: 100%), respectively. At day 60, the analysis showed that DNA fragments of effluent of 28 °C reactor were similar to Galbibacter mesophilus (strain: NBRC 10162) (similarity: 87%), and DNA fragments of effluent of 36 °C reactors were similar to Syntrophomonas curvata (strain: GB8-1) (similarity: 91%). In reactors with a relatively higher temperature, the DNA fragments of effluent of 44 °C reactor were similar to Dielma fastidiosa (strain: JC13) (similarity: 86%), and the DNA fragments of effluent of 52 °C reactor were similar to Coprothermobacter proteolyticus (strain: DSM 5265) (similarity: 99%). To authors' knowledge, this is one of the few studies where DGGE-based approach is utilized to study and compare microbial shifts under mesophilic and thermophilic anaerobic digestions of manure simultaneously. While there were challenges in identifying the bands during gradient gel electrophoresis, the joint use of DGGE and sequencing tool can be potentially useful for illustrating and comparing the change in microbial community structure under complex anaerobic processes and functionality of microbes for understanding the consequential GHG emissions from manure.

Flip bifurcation analysis and mathematical modeling of cholera disease by taking control measures

To study the dynamical system, it is necessary to formulate the mathematical model to understand the dynamics of various diseases which are spread in the world wide. The objective of the research study is to assess the early diagnosis and treatment of cholera virus by implementing remedial methods with and without the use of drugs. A mathematical model is built with the hypothesis of strengthening the immune system, and a ABC operator is employed to turn the model into a fractional-order model. A newly developed system SEIBR, which is examined both qualitatively and quantitatively to determine its stable position as well as the verification of flip bifurcation has been made for developed system. The local stability of this model has been explored concerning limited observations, a fundamental aspect of epidemic models. We have derived the reproductive number using next generation method, denoted as “R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_{0}$$\\end{document}”, to analyze its impact rate across various sub-compartments, which serves as a critical determinant of its community-wide transmission rate. The sensitivity analysis has been verified according to its each parameters to identify that how much rate of change of parameters are sensitive. Atangana–Toufik scheme is employed to find the solution for the developed system using different fractional values which is advanced tool for reliable bounded solution. Also the error analysis has been made for developed scheme. Simulations have been made to see the real behavior and effects of cholera disease with early detection and treatment by implementing remedial methods without the use of drugs in the community. Also identify the real situation the spread of cholera disease after implementing remedial methods with and without the use of drugs. Such type of investigation will be useful to investigate the spread of virus as well as helpful in developing control strategies from our justified outcomes.

Isolated bidirectional DC-DC Converter: A topological review

Bidirectional DC-DC converters (BDCs) are certainly an important power electronic converter for managing bidirectional power flow in various applications. It offers the ability to flow power in both directions, which is useful in systems with renewable energy sources and energy storage. BDCs are becoming increasingly important in various applications, including renewable energy systems, electric vehicles, and energy storage. The development of new BDC topologies and control strategies is expected to further improve their efficiency and performance. Non-Isolated Bidirectional DC-DC Converters (NBDCs) and Isolated Bidirectional DC-DC Converters (IBDCs) are the two main types of BDCs with different isolation properties and trade-offs in terms of size, cost and performance. Topological classification of BDCs further distinguishes various BDC types based on their configurations and voltage-boosting techniques. IBDCs are preferred over NBDCs due to high-power applications, and wide voltage range with higher efficiency; the performance of IBDCs is improving day by day. To provide a framework for comparison in implementing novel configurations or identifying the best converter for a given application, this study is concentrated on each topology and its usual applications. Soft switching converters are also discussed pointed to Resonant Power Converters (RPCs) for the application into Electric Vehicles (EVs). It is worth noting that the choice of BDC depends on the specific requirements of the application, such as power level, voltage range, efficiency, and cost. A detailed comparison, application, advantage and disadvantage table can be useful in comparing the characteristics of different BDCs and selecting the most suitable one.

Magnetic enhancement of the electrical asymmetry effect in capacitively coupled plasmas

The development of real-time control strategies for key discharge parameters, such as densities, fluxes, and energy distributions, is of fundamental interest to many plasma sources. Over the last decade, multi-harmonic ‘tailored’ voltage waveforms have been successfully employed to achieve enhanced control of key parameters in a wide range of radio-frequency (RF) plasma sources through application of the electrical asymmetry effect (EAE). More recently, the analogous magnetic asymmetry effect (MAE) has been numerically and experimentally demonstrated to achieve a notable degree of control in parallel plate RF plasma sources. The MAE is achieved via selectively magnetising the charged species adjacent to one electrode, altering the charge flux to the surface and enforcing a DC self-bias to maintain quasineutrality. This study addresses the degree of control achieved by the MAE in a non-planar geometry via 2D fluid/kinetic simulations of a magnetised RF capacitively coupled plasma source employing two different magnetic topologies. The simultaneous application of the EAE and MAE is then presented for the same geometry, demonstrating a degree of non-linear behaviour dependant upon the applied magnetic topology. Control of the DC self-bias voltage ηdc is demonstrated for a single 600 Vpp , 13.56 MHz discharge in both ‘convergent’ (maximum on-axis field strength) and ‘divergent’ (minimum on-axis field strength) magnetic topolgies. MAE induced modulations of ηdc = 0.13 Vpp and ηdc = 0.03 Vpp are achieved for each magnetic topology, respectively, for magnetic field strengths between 50 and 1000 G. Simultaneous application of an EAE and MAE is achieved through a multi-harmonic ‘peak’-type tailored voltage waveform employing varying harmonic phase offsets between 0∘ ⩽ θ ⩽ 360∘ . The degree to which the DC self-bias voltage is modulated by the applied EAE is mediated by the orientation and magnitude of the applied magnetic field. The EAE induced DC self-bias modulations exhibit non-linear behaviour in response to a superimposed MAE, such that the resulting DC self-bias differs from an additive combination of the two effects alone Simultaneous application of the electrical and MAEs offers the possibility of further decoupling ion and electron dynamics in RF plasma sources, and represents an improvement over each approach in isolation.

Finite-time resilient control for uncertain periodic piecewise polynomial time-varying systems

This study explores the problem of finite-time resilient control for periodic piecewise polynomial time-varying systems in the face of parameter uncertainties, time-varying state delays and external disturbances. Particularly, the considered system is characterized by dividing the fundamental period of periodic systems into numerous subintervals, each of which can be expressed by using matrix polynomial functions. The foremost intention of this work is to lay out a resilient controller such that the resulting closed-loop system is finite-time bounded and satisfies a mixed [Formula: see text] and passivity performance index. Furthermore, by constructing a periodic piecewise time-varying Lyapunov–Krasovskii functional, a delay-dependent sufficient condition is established in line with Wiritinger’s inequality and matrix polynomial lemma to guarantee the needed outcomes of the system under study. Following this, the gain matrix of the devised controller can be calculated by solving the established constraints. As a final step, we conclude with a numerical example that validates the potential and importance of the theoretical discoveries and the developed control scheme.

Influence of different position modal parameters on milling chatter stability of orthopedic surgery robots

This research is dedicated to exploring the dynamics of milling chatter stability in orthopedic surgery robots, focusing on the impact of position modal parameters on chatter stability. Initially, we develop a dynamic milling force model for the robotic milling process that integrates both modal coupling and regenerative effects. We then employ the zero-order frequency domain method to derive a chatter stability domain model, visually represented through stability lobe diagrams (SLDs). Through conducting hammer test experiments, we ascertain the robot's modal parameters at varying positions, enabling the precise generation of SLDs. This study also includes experimental validation of the chatter SLD analysis method, laying the groundwork for further examination of chatter stability across different positional modal parameters. Finally, our analysis of the variations in modal parameters on the stability of robot milling chatter yields a theoretical framework for optimizing cutting parameters and developing control strategies within the context of orthopedic surgery robots.

Bayesian network analysis of factors influencing type 2 diabetes, coronary heart disease, and their comorbidities

ObjectiveBayesian network (BN) models were developed to explore the specific relationships between influencing factors and type 2 diabetes mellitus (T2DM), coronary heart disease (CAD), and their comorbidities. The aim was to predict disease occurrence and diagnose etiology using these models, thereby informing the development of effective prevention and control strategies for T2DM, CAD, and their comorbidities.MethodEmploying a case-control design, the study compared individuals with T2DM, CAD, and their comorbidities (case group) with healthy counterparts (control group). Univariate and multivariate Logistic regression analyses were conducted to identify disease-influencing factors. The BN structure was learned using the Tabu search algorithm, with parameter estimation achieved through maximum likelihood estimation. The predictive performance of the BN model was assessed using the confusion matrix, and Netica software was utilized for visual prediction and diagnosis.ResultThe study involved 3,824 participants, including 1,175 controls, 1,163 T2DM cases, 982 CAD cases, and 504 comorbidity cases. The BN model unveiled factors directly and indirectly impacting T2DM, such as age, region, education level, and family history (FH). Variables like exercise, LDL-C, TC, fruit, and sweet food intake exhibited direct effects, while smoking, alcohol consumption, occupation, heart rate, HDL-C, meat, and staple food intake had indirect effects. Similarly, for CAD, factors with direct and indirect effects included age, smoking, SBP, exercise, meat, and fruit intake, while sleeping time and heart rate showed direct effects. Regarding T2DM and CAD comorbidities, age, FBG, SBP, fruit, and sweet intake demonstrated both direct and indirect effects, whereas exercise and HDL-C exhibited direct effects, and region, education level, DBP, and TC showed indirect effects.ConclusionThe BN model constructed using the Tabu search algorithm showcased robust predictive performance, reliability, and applicability in forecasting disease probabilities for T2DM, CAD, and their comorbidities. These findings offer valuable insights for enhancing prevention and control strategies and exploring the application of BN in predicting and diagnosing chronic diseases.

Robust Control Based on Adaptative Fuzzy Control of Double-Star Permanent Synchronous Motor Supplied by PWM Inverters for Electric Propulsion of Ships

This study presents the development of an adaptive fuzzy control strategy for double-star PMSM-PWM inverters used in ship electrical propulsion. The approach addresses the current and speed tracking challenges of double-star permanent magnet synchronous motors (DSPMSMs) in the presence of parametric uncertainties. Initially, a modeling technique employing a matrix transformation method is introduced, generating decoupled and independent star windings to eliminate inductive couplings, while maintaining model consistency and torque control. The precise DSPMSM model serves as the foundation for an unknown nonlinear backstepping controller, approximated directly using an adaptive fuzzy controller. Through the Lyapunov direct method, system stability is demonstrated. All signals in the closed-loop system are ensured to be uniformly ultimately bounded (UUB). The proposed control system aims for low tracking errors, while also mitigating the impact of parametric uncertainties. The effectiveness of the adaptive fuzzy nonlinear control system is validated through tests conducted in hardware-in-the-loop (HIL) simulations, utilizing the OPAL-RT platform, OP4510.

A multi-stand work roll bending and shifting approach for profile contour and flatness control of electrical steel in multi-width schedule-free rolling using NSGA-II algorithm

To overcome the severe uneven work roll wear and uneven deformation of the wide-width electrical steel in the SFR (Schedule-Free Rolling) is an effective way to organize production flexibly and maximize production efficiency in hot rolling. In order to meet the increasingly stringent requirements of PCFC (Profile Contour and Flatness Control) of multi-width electrical steel in hot rolling, the collaborative control strategy of multi-stand work roll bending and shifting for profile and flatness of electrical steel in multi-width SFR was developed using NSGA-II approach. The work roll wear prediction model, thermal crown model, and strip crown model were established based on on-site measured data. Combining the work roll wear characteristics with principle, the mathematical model for work roll shifting considering multi-width was established. The main parameters of the multi-width work roll shifting strategy are obtained using the multi-objective NSGA-II algorithm. On this basis, a multi-stand collaborative control strategy, including rolling contour, short stroke roll shifting, and work roll bending, in the downstream stands during multi-width SFR was proposed. The industrial application of the developed control strategy shows that can prominently enhance the PCFC capability of electrical steel, which the uneven wear contour can be reduced.

Sensorless model-based displacement estimator for piezoelectric actuator through a practical three-stage mechanism

Piezoelectric elements (PEMs) are used in a variety of applications. In this paper, we developed a new simple sensorless method for a Piezoelectric Actuator (PEA), which includes piezostack elements and a three-stage amplification mechanism.This research focuses on a piezoelectric actuator that incorporates a three-stage amplification system, where the outcome of one stage serves as the input for the subsequent one. The actuator receives two types of inputs: the voltage applied to the piezoelectric elements and the mechanical load it carries. Its output is defined by the rotation angle observed at the end of the third amplification stage. To indirectly measure the actuator's displacement, a basic external circuit is utilized.The precise movement of these actuators is essential. To circumvent the high costs and limitations associated with highly accurate displacement sensors, there has been a growing interest in sensorless control methods. Certain electrical signals, when measured, can provide an estimation of displacement. However, induced voltage measurements are not effective for piezoelectric stacks. Two more promising measures are the voltage and current of the piezoelectric material.Given that the electrical charge on these actuators closely reflects their displacement with minimal hysteresis across a broad frequency spectrum, it's proposed that displacement can be effectively gauged through current measurements that assess charge.The core contribution of this paper is the introduction and validation, both theoretically and experimentally, of a hybrid algorithm that leverages these two electrical signals to enhance the accuracy of displacement estimates. This was confirmed using a laboratory setup.The primary benefit of this research is the presentation of a straightforward sensorless control algorithm, poised for further exploration within the realm of piezoelectric actuators. The simplicity of both the theoretical model and the sensorless technique facilitates their application across a diverse range of piezoelectric actuators and amplification systems, thereby streamlining the design, modeling, and control strategy development for various actuators.The innovation of this study stems from the application of an uncomplicated sensorless estimation algorithm, coupled with a system-level perspective on piezoelectric actuators. This approach utilizes a simple, adaptable model suitable for a wide array of applications and operational techniques.

Rationalizing artemisinin-based combination therapies use for treatment of uncomplicated malaria: A situation analysis in health facilities and private pharmacies of Douala 5e-Cameroon.

Artemisinin-based combination therapies (ACTs) represent one of the mainstays of malaria control. Despite evidence of the risk of ACTs resistant infections in resource-limited countries, studies on the rational use of ACTs to inform interventions and prevent their emergence and/or spread are limited. The aim of this study was designed to analyze practices toward ACTs use for treating the treatment of uncomplicated malaria (UM) in an urban community. Between November 2015 and April 2016, a cross-sectional and prospective study was conducted in the 6 health facilities and all pharmacies in the Douala 5e subdivision, Cameroon. Anonymous interviews including both open- and closed-ended questions were conducted with selected participants among drug prescribers, patients attending the health facilities, and customers visiting the pharmacies. Data analysis was performed using StataSE11 software (version 11 SE). A total of 41 prescribers were included in the study. All were aware of national treatment guidelines, but 37.7% reported not waiting for test results before prescribing an antimalarial drug, and the main reason being stock-outs at health facilities. Likewise, artemether+lumefantrine/AL (81%) and dihydroartemisinin+piperaquine (63.5%) were the most commonly used first- and second-line drugs respectively. Biological tests were requested in 99.2% (128/129) of patients in health facilities, 60.0% (74) were performed and 6.2% were rationally managed. Overall 266 (35%) of 760 customers purchased antimalarial drugs, of these, 261 (98.1%) agreed to participate and of these, 69.4% purchased antimalarial drugs without a prescription. ACTs accounted for 90.0% of antimalarials purchased from pharmacies, of which AL was the most commonly prescribed antimalarial drug (67.1%), and only 19.5% of patients were appropriately dispensed. The current data suggest a gap between the knowledge and practices of prescribers as well as patients and customers misconceptions regarding the use of ACTs in Douala 5e subdivision. Despite government efforts to increase public awareness regarding the use of ACTs as first-line treatment for UM, our findings point out a critical need for the development, implementation and scaling-up of control strategies and continuing health education for better use of ACTs (prescription and dispensing) in Cameroon.

Fuzzy finite‐time adaptive control of switched nonlinear systems with input nonlinearities

SummaryThis article addresses the fuzzy finite‐time command filtering tracking control problem for switched nonlinear systems with input nonlinearities via using backstepping technique. An equivalent transformation method is proposed for the purpose of handling the impediment problem caused by the nonlinearity of control input. Finite‐time command filtering control technology can solve the “explosion of complexity” issue, which is caused by the multiple derivation of virtual controllers appeared in the classic backstepping control. A filtering compensation scheme is developed to reduce the filtering error. By combining the fuzzy logic system's approximation ability and the finite‐time theory, a new fast convergence adaptive control scheme is proposed so that the output of the system can converge to a small area near the desired signal and the boundedness of all signals of the controlled system can be assured in finite time. Finally, a simulation example successfully verifies the feasibility of the developed control scheme.

A Bioinspired Control Strategy Ensures Maneuverability and Adaptability for Dynamic Environments in an Underactuated Robotic Fish

Bioinspired underwater robots can move efficiently, with agility, even in complex aquatic areas, reducing marine ecosystem disturbance during exploration and inspection. These robots can improve animal farming conditions and preserve wildlife. This study proposes a muscle-like control for an underactuated robot in carangiform swimming mode. The artifact exploits a single DC motor with a non-blocking transmission system to convert the motor’s oscillatory motion into the fishtail’s oscillation. The transmission system combines a magnetic coupling and a wire-driven mechanism. The control strategy was inspired by central pattern generators (CPGs) to control the torque exerted on the fishtail. It integrates proprioceptive sensory feedback to investigate the adaptability to different contexts. A parametrized control law relates the reference target to the fishtail’s angular position. Several tests were carried out to validate the control strategy. The proprioceptive feedback revealed that the controller can adapt to different environments and tail structure changes. The control law parameters variation accesses the robotic fish’s multi-modal swimming. Our solution can vary the swimming speed of 0.08 body lengths per second (BL/s), and change the steering direction and performance by an angular speed and turning curvature radius of 0.08 rad/s and 0.25 m, respectively. Performance can be improved with design changes, while still maintaining the developed control strategy. This approach ensures the robot’s maneuverability despite its underactuated structure. Energy consumption was evaluated under the robotic platform’s control and design. Our bioinspired control system offers an effective, reliable, and sustainable solution for exploring and monitoring aquatic environments, while minimizing human risks and preserving the ecosystem. Additionally, it creates new and innovative opportunities for interacting with marine species. Our findings demonstrate the potential of bioinspired technologies to advance the field of marine science and conservation.

Induction of Salmonella Enteritidis into a Viable but Nonculturable State by Cinnamaldehyde and Its Resuscitation.

Trans-cinnamaldehyde (TC), a typical plant-derived compound, has been widely used in the control of foodborne pathogen contamination. Nevertheless, the risk associated with the occurrence of viable but nonculturable (VBNC) bacteria induced by TC remains unclear. The results of this study showed that Salmonella Enteritidis (S. Enteritidis) entered the VBNC state after being induced by TC at a minimum inhibitory concentration of 312.5 μg/mL and survived for at least 22 days under TC treatment. Enhanced resistance was found against heat treatment (75°C, 30 s), antibiotics (i.e., ampicillin, ceftriaxone sodium, chloramphenicol), and hydrogen peroxide (3%) in VBNC S. Enteritidis. A synergistic effect against VBNC S. Enteritidis occurred when TC was combined with acid treatment, including lactic acid and acetic acid (pH = 3.5). VBNC and resuscitated S. Enteritidis by sodium pyruvate treatment (100 mM) were found to retain the infectious ability to Caco-2 cells. Relative expression levels of the stress-related genes relA, spoT, ppx, lon, katG, sodA, dnaK, and grpE were upregulated in VBNC S. Enteritidis. Accumulation of reactive oxygen species (ROS) and protein aggregates was observed in VBNC cells. Besides, the resuscitation of VBNC cells was accompanied with clearance of ROS and protein aggregates. In summary, this study presents a comprehensive characterization of stress tolerance and resuscitation of VBNC S. Enteritidis induced by cinnamaldehyde, and the results provide useful information for the development of effective control strategy against VBNC pathogenic bacteria in food production.

Digital dermatitis in Swedish dairy herds assessed by ELISA targeting Treponema phagedenis in bulk tank milk

BackgroundDigital dermatitis (DD) is a contagious hoof infection affecting cattle worldwide. The disease causes lameness and a reduction in animal welfare, which ultimately leads to major decreases in milk production in dairy cattle. The disease is most likely of polymicrobial origin with Treponema phagedenis and other Treponema spp. playing a key role; however, the etiology is not fully understood. Diagnosis of the disease is based on visual assessment of the feet by trained hoof-trimmers and veterinarians, as a more reliable diagnostic method is lacking. The aim of this study was to evaluate the use of an enzyme-linked immunosorbent assay (ELISA) on bulk tank milk samples testing for the presence of T. phagedenis antibodies as a proxy to assess herd prevalence of DD in Swedish dairy cattle herds.ResultsBulk tank milk samples were collected in 2013 from 612 dairy herds spread across Sweden. A nationwide DD apparent prevalence of 11.9% (8.1–14.4% CI95%) was found, with the highest proportion of test-positive herds in the South Swedish regions (31.3%; 19.9–42.4% CI95%).ConclusionsThis study reveals an underestimation of DD prevalence based on test results compared to hoof trimming data, highlighting the critical need for a reliable and accurate diagnostic method. Such a method is essential for disease monitoring and the development of effective control strategies. The novelty of ELISA-based diagnostic methods for DD, coupled with the disease’s polymicrobial origin, suggests an avenue for improvement. Developing an expanded ELISA, incorporating antigens from various bacterial species implicated in the disease, could enhance diagnostic accuracy. The significance of this study is underscored by the extensive analysis of a substantial sample size (612). Notably, this investigation stands as the largest assessment to date, evaluating the application of ELISA on bulk tank milk for DD diagnosis at the herd level.